W0217 04:25:43.887000 4078901 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:43.887000 4078901 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:43.887000 4078901 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:43.887000 4078901 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:43.887000 262147 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:43.887000 262147 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:43.887000 262147 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:43.887000 262147 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.057000 2598250 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.057000 2598250 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.057000 2598250 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.057000 2598250 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.058000 2621360 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.058000 2621360 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.058000 2621360 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.058000 2621360 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.073000 2598122 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.073000 2598122 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.073000 2598122 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.073000 2598122 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.126000 2608625 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.126000 2608625 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.126000 2608625 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.126000 2608625 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.151000 2614682 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.151000 2614682 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.151000 2614682 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.151000 2614682 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.243000 233265 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.243000 233265 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.243000 233265 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.243000 233265 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.257000 262236 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.257000 262236 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.257000 262236 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.257000 262236 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.283000 2578773 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.283000 2578773 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.283000 2578773 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.283000 2578773 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.512000 1019786 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.512000 1019786 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.512000 1019786 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.512000 1019786 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.526000 2598810 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.526000 2598810 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.526000 2598810 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.526000 2598810 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.720000 1533179 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.720000 1533179 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.720000 1533179 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.720000 1533179 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.801000 2629720 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:44.801000 2629720 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:44.801000 2629720 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:44.801000 2629720 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:45.759000 237666 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:45.759000 237666 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:45.759000 237666 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:45.759000 237666 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:47.149000 2570963 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] 
W0217 04:25:47.149000 2570963 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
W0217 04:25:47.149000 2570963 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0217 04:25:47.149000 2570963 .local/lib/python3.10/site-packages/torch/distributed/run.py:793] *****************************************
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices
PyTorch: setting up devices

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.66it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:01<00:04,  1.18s/it]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.23it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.88it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.35it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.82it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.87it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.42it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:01<00:01,  1.62it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.94it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.38it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.26it/s]
Loading checkp
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.68it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.85it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.07it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.15it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.33it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.04it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.13it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.04it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.62it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.81it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.08it/s]
Loading checkpoint shards:  40%|�loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
�███      | 2/5 [00:00<00:01,  2.92it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.13it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.89it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.63it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.54it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  2.88it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.12it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  2.96it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.16it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.75it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.25it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.16it/s]
Loading checkpoint shards:  60%|██████    | 3/
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.57it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.13it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.70it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.77it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.48it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.21it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.47it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.21it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.82it/s]
L
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}


Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.18it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,

Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.36it/s]Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
oint shards:  20%|██        | 1/5 [00:00<00:01,  3.01it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.73it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.60it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.73it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.21it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  2.07it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.00it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.00it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  2.93it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.04it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.05it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.22it/s]
Loading checkpoint shards:  80%|██Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
oading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.00it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.69it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.61it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.28it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.21it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.69it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.69it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.83it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.93it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.12it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.76it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.52it/s]
Loading checkpoint shards:  60%|�
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.21it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.25it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.70it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.23it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.45it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.36it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.35it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.08it/s]
Loading checkpoinYou are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
loading configuration file config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/config.json
You are using a model of type qwen2_5_vl to instantiate a model of type llava_qwen. This is not supported for all configurations of models and can yield errors.
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Model config LlavaQwenConfig {
  "architectures": [
    "Qwen2_5_VLForConditionalGeneration"
  ],
  "attention_dropout": 0.0,
  "bos_token_id": 151643,
  "eos_token_id": 151645,
  "hidden_act": "silu",
  "hidden_size": 3584,
  "image_token_id": 151655,
  "initializer_range": 0.02,
  "intermediate_size": 18944,
  "max_position_embeddings": 128000,
  "max_window_layers": 28,
  "model_type": "llava_qwen",
  "num_attention_heads": 28,
  "num_hidden_layers": 28,
  "num_key_value_heads": 4,
  "rms_norm_eps": 1e-06,
  "rope_scaling": {
    "mrope_section": [
      16,
      24,
      24
    ],
    "rope_type": "default",
    "type": "default"
  },
  "rope_theta": 1000000.0,
  "sliding_window": 32768,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.49.0.dev0",
  "use_cache": true,
  "use_sliding_window": false,
  "video_token_id": 151656,
  "vision_config": {
    "hidden_size": 1280,
    "in_chans": 3,
    "model_type": "qwen2_5_vl",
    "spatial_patch_size": 14,
    "tokens_per_second": 2
  },
  "vision_end_token_id": 151653,
  "vision_start_token_id": 151652,
  "vision_token_id": 151654,
  "vocab_size": 152064
}

loading weights file model.safetensors from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/model.safetensors.index.json
Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]Instantiating LlavaQwenForCausalLM model under default dtype torch.bfloat16.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
Generate config GenerationConfig {
  "bos_token_id": 151643,
  "eos_token_id": 151645
}

Instantiating Qwen2_5_VisionTransformerPretrainedModel model under default dtype torch.bfloat16.
██████  | 4/5 [00:01<00:00,  3.13it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:02<00:00,  2.37it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.01it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.48it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  2.97it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  2.99it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.03it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.04it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:02<00:00,  2.95it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:02<00:00,  2.23it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.65it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.34it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.56it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.16it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.28it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.15it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.52it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.80it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.38it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.86it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.77it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.53it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.78it/s]
L
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.74it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.36it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.57it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.39it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.05it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.23it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.37it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.36it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.33it/s]
Loading checkpoint shards:  25 [00:00<00:00,  3.69it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.22it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  2.96it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.43it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  2.84it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.09it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.00it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.06it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.59it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.66it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.32it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.07it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.29it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.14it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.30it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.01it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.88it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.15it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.28it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.85it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.61it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.66it/s]
Loading checkpoint shards:  40%|�
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.21it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.36it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.44it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.09it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.07it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.09it/s]
Loading checkpoint shards:  20%|██   loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.35it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  2.95it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.40it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.05it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.46it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.15it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.36it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.00it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.37it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.04it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.69it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.61it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.39it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.23it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.38it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.20it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.42it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.15it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.41it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.21it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.79it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.67it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.89it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.60it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.70it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.30it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.09it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.99it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.21it/s]
Loading checkpoint shardsloading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.91it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.15it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.71it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.16it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.10it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.88it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.64it/s]
Loading checkpoint shards:  2loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.92it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.42it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.04it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.24it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.03it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.97it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.87it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.25it/s]
Loading checkpoinloading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file added_tokens.json from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file special_tokens_map.json from cache at None
loading file added_tokens.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
t shards:  40%|████      | 2/5 [00:00<00:00,  3.18it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.19it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.53it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.37it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.18it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.17it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.97it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.72it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.61it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.61it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.74it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.82it/s]
Loading checkpoint shards:  60%|██████   Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.84it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.83it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.31it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.35it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.31it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.72it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.17it/s]
Loading checkpoint shardsloading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.59it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.81it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.50it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.84it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.71it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.50it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.31it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.95it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.51it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.32it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.25it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.27it/s]
Loading checkpointImage processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.15it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.34it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.45it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.99it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.29it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.14it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.26it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.97it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.3oading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.01it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.66it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.01it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.36it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.24it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.11it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.33it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.17it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.01it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.99it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.51it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.68it/s]
Loading checkpoint shards:  60%|�loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.30it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.41it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.41it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.95it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.14it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.11it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.19it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.18it/s]
Loading checkpoinloading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

��█████    | 3/5 [00:00<00:00,  3.47it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.76it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.67it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.53it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.10it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.00it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.93it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.70it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.62it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.84it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.79it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.00it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.36it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.45it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.21it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.38it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.01it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
�███      | 2/5 [00:00<00:00,  3.72it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.57it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.72it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.10it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.46it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.23it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.98it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.89it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.47it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.59it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.86it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.92it/s]
Loading checkpoint shards:  60%|██████    | 3/Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.30it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.03it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.90it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.61it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.88it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.60it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

0%|██        | 1/5 [00:00<00:01,  2.18it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.26it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.32it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.30it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.29it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.89it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.19it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.00it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.11it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.74it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.63it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.83it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.01it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.86it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.97it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.82it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

t shards:  40%|████      | 2/5 [00:00<00:00,  3.05it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.79it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.13it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.07it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.87it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.78it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.88it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.06it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.50it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.35it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.67it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.48it/s]
Loading checkpoint shards:  60%|██████   Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:02,  1.94it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.51it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.06it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.65it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.32it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.30it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.73it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.32it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  3.01it/s]
LSpecial tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
     | 1/5 [00:00<00:01,  2.03it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.10it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.02it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.15it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.91it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.05it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.86it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.83it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.87it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.90it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.44it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.52it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.55it/s]
Loading Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
:  20%|██        | 1/5 [00:00<00:01,  3.06it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.87it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.34it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.06it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.10it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.98it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.60it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.56it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.56it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.29it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.61it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.46it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:0Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
t shards:  40%|████      | 2/5 [00:00<00:00,  4.08it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.92it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.77it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.89it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.52it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.91it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.66it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.89it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.10it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.25it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.23it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.78it/s]
Loading checkpoint shards:  60%|██████   Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

:  20%|██        | 1/5 [00:00<00:01,  3.23it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:01,  2.99it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.43it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.09it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.11it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.76it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.23it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.62it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.76it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.54it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.69it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.43it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,0%|██        | 1/5 [00:00<00:01,  2.84it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.68it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.80it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.62it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.69it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.99it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.66it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.38it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.02it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.94it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.12it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.86it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
 | 3/5 [00:00<00:00,  3.59it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.47it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.51it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.27it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.88it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.98it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.03it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.65it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.81it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.72it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.75it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.71it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.27it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.78it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.35it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.91it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.38it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.00it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
1it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.17it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.16it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.04it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.50it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.02it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.75it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.52it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.54it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.50it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.42it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.46it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.42it/s]
Loading checkpoint shloading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
��█████    | 3/5 [00:00<00:00,  3.61it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.49it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.65it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.19it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.29it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.89it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.18it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.85it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.85it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.87it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.70it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.54it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.23it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.61it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.34it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.30it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.74it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.51it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.15it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

5 [00:00<00:00,  3.63it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.21it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.57it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.63it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.98it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.21it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.02it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.59it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.78it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.54it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.17it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.17it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.59it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.01it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.49it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.85it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.55it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.02it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.68it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
 shards:  40%|████      | 2/5 [00:00<00:00,  3.24it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.34it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:01,  2.66it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.47it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.77it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.67it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.64it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.65it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.60it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.18it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.65it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.67it/s]
Loading checkpoint shards:  80%|██
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.98it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.56it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.82it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.55it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.54it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.12it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.93it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.61it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

  3.69it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.59it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.34it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.44it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.48it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.83it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.83it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.90it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.74it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.81it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.62it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.65it/s]
Loading checkpoint shards:  80%|█████�loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.03it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.72it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.11it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.81it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.10it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.93it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.02it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.77it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
oading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.91it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.10it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.61it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.07it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.14it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  4.09it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  2.97it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:00<00:00,  3.63it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.43it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.43it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.04it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.51it/s]
Loading checkpoint shards:  60%|�loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.89it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.60it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
ards:  60%|██████    | 3/5 [00:00<00:00,  3.73it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.00it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.73it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.74it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.67it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.63it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.77it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.47it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.39it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.34it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.43it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.33it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.37it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.92it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.75it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.73it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.80it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.66it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.71it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
0<00:00,  4.36it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.29it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.82it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.79it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.77it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.53it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.75it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.65it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.57it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.59it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.26it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.14it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.97it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.01it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.84it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.85it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.71it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.64it/s]loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
 | 3/5 [00:00<00:00,  3.54it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.36it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:01<00:00,  3.29it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.45it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.01it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.96it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.68it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.76it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.79it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.69it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.58it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.68it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.36it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.73it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.38it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.84it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.19it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.12it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.66it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.53it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.95it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.90it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.77it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.47it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.


Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.90it/s]All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.93it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.70it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
�██  | 4/5 [00:01<00:00,  3.69it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.25it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.18it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.84it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.82it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.10it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.70it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.14it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.77it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

  4.46it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.92it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.60it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.00it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.85it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.87it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.83it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.61it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.66it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.00it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.43it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.86it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.13it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.94it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.63it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
██████  | 4/5 [00:01<00:00,  3.88it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.94it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.85it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.86it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.52it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.80it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.81it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.21it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.26it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.82it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.93it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.85it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.55it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.78it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.18it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.76it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.17it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.81it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
:00,  3.62it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.66it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.31it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.71it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.17it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.67it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file added_tokens.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.79it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.47it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.86it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.59it/s]
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None

Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.99it/s]loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.02it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.86it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.54it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.94it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.75it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

  4.17it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.95it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.47it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.73it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.35it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.12it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.27it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.48it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.01it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.07it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.75it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.92it/s]
Loading checkpoint shards:  80%|█████�
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.02it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.67it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.97it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.50it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.98it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.66it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.14it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.59it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.83it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.44it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.84it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.38it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.80it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.32it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.14it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.68it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.97it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.68it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.86it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.51it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.11it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.99it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.04it/s]loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
 | 3/5 [00:00<00:00,  3.20it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.20it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.72it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.87it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.20it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.31it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.07it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.37it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.89it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.47it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.99it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.82it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.49it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.24it/s]
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.97it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.73it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.55it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.29it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.92it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.56it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.88it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.57it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.81it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.52it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.02it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.68it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

�██  | 4/5 [00:01<00:00,  3.59it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.47it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.09it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.59it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.23it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.33it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.16it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.87it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.47it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.75it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.32it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.63it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.33it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.88it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.55it/s]

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.86it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.56it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.86it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.44it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.87it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.48it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.28it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.00it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.19it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.97it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.70it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.38it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.14it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.95it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.22it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.01it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.97it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.78it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.05it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.86it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.99it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.58it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.80it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.78it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.31it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.08it/s]
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.05it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.86it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.03it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.83it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.11it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.82it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

��█████    | 3/5 [00:00<00:00,  3.82it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  4.31it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:00<00:00,  3.89it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.17it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.56it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.63it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.72it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.58it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:00<00:00,  4.10it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  3.95it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:01<00:00,  4.01it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.45it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.10it/s]
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.04it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.80it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.83it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.54it/s]
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file added_tokens.json from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file special_tokens_map.json from cache at None
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file chat_template.jinja from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.36it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.01it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.65it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.44it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.94it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.62it/s]
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
loading file chat_template.jinja from cache at None
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.83it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.56it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.26it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.07it/s]
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading file added_tokens.json from cache at None
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.82it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.56it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.24it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.98it/s]
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.17it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.96it/s]
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}


Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.96it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.89it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file special_tokens_map.json from cache at None
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file added_tokens.json from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file special_tokens_map.json from cache at None
loading file added_tokens.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file special_tokens_map.json from cache at None
loading file chat_template.jinja from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.17it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.94it/s]
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.95it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  3.95it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file added_tokens.json from cache at None
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file chat_template.jinja from cache at None
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
loading file added_tokens.json from cache at None
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.

Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.27it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:01<00:00,  4.01it/s]
All model checkpoint weights were used when initializing LlavaQwenForCausalLM.

All the weights of LlavaQwenForCausalLM were initialized from the model checkpoint at Qwen/Qwen2.5-VL-7B-Instruct.
If your task is similar to the task the model of the checkpoint was trained on, you can already use LlavaQwenForCausalLM for predictions without further training.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
loading file chat_template.jinja from cache at None
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file chat_template.jinja from cache at None
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file generation_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/generation_config.json
Generate config GenerationConfig {
  "attn_implementation": "flash_attention_2",
  "bos_token_id": 151643,
  "do_sample": true,
  "eos_token_id": [
    151645,
    151643
  ],
  "pad_token_id": 151643,
  "repetition_penalty": 1.05,
  "temperature": 0.1,
  "top_k": 1,
  "top_p": 0.001
}

loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
loading configuration file preprocessor_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/preprocessor_config.json
Using a slow image processor as `use_fast` is unset and a slow processor was saved with this model. `use_fast=True` will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with `use_fast=False`.
Image processor Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
loading file vocab.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/vocab.json
loading file merges.txt from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/merges.txt
loading file tokenizer.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer.json
loading file added_tokens.json from cache at None
loading file special_tokens_map.json from cache at None
loading file tokenizer_config.json from cache at /fsx_0/user/zhaojiang/models/hub/models--Qwen--Qwen2.5-VL-7B-Instruct/snapshots/6e6556e8ce728c7b3e438d75ebf04ec93403dc19/tokenizer_config.json
loading file chat_template.jinja from cache at None
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
Processor Qwen2_5_VLProcessor:
- image_processor: Qwen2VLImageProcessor {
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "patch_size": 14,
  "processor_class": "Qwen2_5_VLProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='Qwen/Qwen2.5-VL-7B-Instruct', vocab_size=151643, model_max_length=131072, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|object_ref_start|>', '<|object_ref_end|>', '<|box_start|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_start|>', '<|vision_end|>', '<|vision_pad|>', '<|image_pad|>', '<|video_pad|>']}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|object_ref_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|object_ref_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|box_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|image_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|video_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5_VLProcessor"
}

You are resizing the embedding layer without providing a `pad_to_multiple_of` parameter. This means that the new embedding dimension will be 151668. This might induce some performance reduction as *Tensor Cores* will not be available. For more details about this, or help on choosing the correct value for resizing, refer to this guide: https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/model/multimodal_encoder/eva_clip/eva_vit.py:622: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(checkpoint_path, map_location=map_location)
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Generating dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Downloading and preparing dataset webdataset/default to /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f...
Spawning 128 processes for 128 objects in slices of [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset
Using custom data configuration default-5e4e9de28fd39dca
Loading Dataset Infos from /home/zhaojiang/.local/lib/python3.10/site-packages/datasets/packaged_modules/webdataset








Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]

Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]


Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]



Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]





Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]




Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]






Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]










Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]













Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]















Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]














Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]












Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]



















 ... (more hidden) ...








Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]









Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]











Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]
















Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]

















Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]


















Downloading data:   0%|          | 0/1382 [00:00<?, ?files/s]







Downloading data:   3%|▎         | 42/1382 [00:00<00:03, 407.18files/s]


Downloading data:   3%|▎         | 39/1382 [00:00<00:03, 384.76files/s]

Downloading data:   3%|▎         | 42/1382 [00:00<00:03, 393.97files/s]




Downloading data:   3%|▎         | 36/1382 [00:00<00:03, 359.54files/s]





Downloading data:   3%|▎         | 37/1382 [00:00<00:03, 352.62files/s]



Downloading data:   2%|▏         | 32/1382 [00:00<00:04, 304.13files/s]










Downloading data:   2%|▏         | 32/1382 [00:00<00:04, 316.97files/s]















Downloading data:   2%|▏         | 33/1382 [00:00<00:04, 317.71files/s]













Downloading data:   2%|▏         | 34/1382 [00:00<00:04, 326.21files/s]






Downloading data:   2%|▏         | 34/1382 [00:00<00:04, 320.78files/s]














Downloading data:   2%|▏         | 34/1382 [00:00<00:04, 327.65files/s]











Downloading data:   2%|▏         | 32/1382 [00:00<00:04, 303.66files/s]












Downloading data:   2%|▏         | 32/1382 [00:00<00:04, 300.26files/s]









Downloading data:   2%|▏         | 32/1382 [00:00<00:04, 302.31files/s]








Downloading data:   2%|▏         | 33/1382 [00:00<00:04, 310.94files/s]

















Downloading data:   2%|▏         | 28/1382 [00:00<00:04, 271.93files/s]



















 ... (more hidden) ...
















Downloading data:   2%|▏         | 31/1382 [00:00<00:04, 294.42files/s]


















Downloading data:   2%|▏         | 28/1382 [00:00<00:05, 258.11files/s]
Downloading data: 100%|██████████| 1382/1382 [00:00<00:00, 7902.69files/s]

Downloading data: 100%|██████████| 1284/1284 [00:00<00:00, 7131.11files/s]

Downloading data: 100%|██████████| 1382/1382 [00:00<00:00, 8170.56files/s]

Downloading data: 100%|██████████| 1382/1382 [00:00<00:00, 7557.22files/s]

Downloading data: 100%|██████████| 1382/1382 [00:00<00:00, 7769.57files/s]

Downloading data: 100%|██████████| 1382/1382 [00:00<00:00, 7189.01files/s]

Downloading data: 100%|██████████| 1382/1382 [00:00<00:00, 7334.49files/s]



















Downloading data:   4%|▍         | 54/1382 [00:00<00:08, 156.81files/s]

















Downloading data:   4%|▍         | 56/1382 [00:00<00:08, 151.52files/s]



















 ... (more hidden) ...



Downloading data:   5%|▍         | 63/1382 [00:00<00:08, 158.03files/s]















Downloading data:   5%|▍         | 65/1382 [00:00<00:08, 163.25files/s]
















Downloading data:   4%|▍         | 61/1382 [00:00<00:08, 154.11files/s]










Downloading data:   5%|▍         | 64/1382 [00:00<00:08, 156.81files/s]














Downloading data:   5%|▍         | 67/1382 [00:00<00:07, 164.41files/s]











Downloading data:   5%|▍         | 63/1382 [00:00<00:08, 155.12files/s]






Downloading data:   5%|▍         | 67/1382 [00:00<00:08, 162.63files/s]












Downloading data:   5%|▍         | 63/1382 [00:00<00:08, 153.52files/s]









Downloading data:   5%|▍         | 63/1382 [00:00<00:08, 153.77files/s]













Downloading data:   5%|▍         | 67/1382 [00:00<00:08, 161.07files/s]








Downloading data:   5%|▍         | 65/1382 [00:00<00:08, 155.93files/s]




Downloading data:   5%|▌         | 72/1382 [00:00<00:08, 161.70files/s]





Downloading data:   5%|▌         | 73/1382 [00:00<00:07, 163.87files/s]
Downloading data: 100%|██████████| 1382/1382 [00:00<00:00, 4516.33files/s]



Downloading data:   6%|▌         | 78/1382 [00:00<00:08, 162.71files/s]







Downloading data:   6%|▌         | 83/1382 [00:00<00:07, 168.77files/s]

Downloading data:   6%|▌         | 82/1382 [00:00<00:07, 167.00files/s]


















Downloading data:   5%|▌         | 72/1382 [00:00<00:09, 139.32files/s]

















Downloading data:   5%|▌         | 75/1382 [00:00<00:09, 135.04files/s]



















 ... (more hidden) ...
















Downloading data:   6%|▌         | 80/1382 [00:00<00:09, 139.60files/s]



Downloading data:   6%|▌         | 83/1382 [00:00<00:09, 138.08files/s]











Downloading data:   6%|▌         | 83/1382 [00:00<00:09, 139.95files/s]












Downloading data:   6%|▌         | 83/1382 [00:00<00:09, 139.87files/s]















Downloading data:   6%|▌         | 86/1382 [00:00<00:09, 142.83files/s]










Downloading data:   6%|▌         | 84/1382 [00:00<00:09, 137.52files/s]









Downloading data:   6%|▌         | 83/1382 [00:00<00:09, 137.32files/s]








Downloading data:   6%|▌         | 85/1382 [00:00<00:09, 140.67files/s]






Downloading data:   6%|▋         | 88/1382 [00:00<00:08, 144.14files/s]














Downloading data:   6%|▋         | 88/1382 [00:00<00:09, 141.48files/s]













Downloading data:   6%|▋         | 88/1382 [00:00<00:09, 138.43files/s]




Downloading data:   7%|▋         | 94/1382 [00:00<00:09, 142.32files/s]





Downloading data:   7%|▋         | 95/1382 [00:00<00:09, 141.46files/s]


















Downloading data:   6%|▋         | 87/1382 [00:00<00:10, 129.08files/s]


Downloading data:   7%|▋         | 101/1382 [00:00<00:09, 142.10files/s]

Downloading data:   8%|▊         | 106/1382 [00:00<00:08, 144.43files/s]







Downloading data:   8%|▊         | 107/1382 [00:00<00:08, 145.38files/s]

















Downloading data:   7%|▋         | 90/1382 [00:00<00:10, 127.99files/s]



















 ... (more hidden) ...
















Downloading data:   7%|▋         | 96/1382 [00:00<00:09, 130.55files/s]



Downloading data:   7%|▋         | 99/1382 [00:00<00:09, 129.45files/s]











Downloading data:   7%|▋         | 99/1382 [00:00<00:09, 130.80files/s]












Downloading data:   7%|▋         | 99/1382 [00:00<00:09, 130.24files/s]










Downloading data:   7%|▋         | 100/1382 [00:00<00:09, 130.39files/s]









Downloading data:   7%|▋         | 99/1382 [00:00<00:09, 130.20files/s]















Downloading data:   7%|▋         | 103/1382 [00:00<00:09, 132.71files/s]






Downloading data:   8%|▊         | 105/1382 [00:00<00:09, 133.67files/s]








Downloading data:   7%|▋         | 102/1382 [00:00<00:09, 131.27files/s]














Downloading data:   8%|▊         | 105/1382 [00:00<00:09, 132.08files/s]













Downloading data:   8%|▊         | 105/1382 [00:00<00:09, 129.72files/s]





Downloading data:   8%|▊         | 112/1382 [00:00<00:09, 132.92files/s]




Downloading data:   8%|▊         | 112/1382 [00:00<00:09, 132.53files/s]


















Downloading data:   7%|▋         | 101/1382 [00:00<00:10, 122.94files/s]

















Downloading data:   8%|▊         | 104/1382 [00:00<00:10, 123.20files/s]



















 ... (more hidden) ...


Downloading data:   9%|▊         | 119/1382 [00:00<00:09, 133.12files/s]
















Downloading data:   8%|▊         | 110/1382 [00:00<00:10, 125.26files/s]

Downloading data:   9%|▉         | 124/1382 [00:00<00:09, 134.43files/s]



Downloading data:   8%|▊         | 113/1382 [00:00<00:10, 124.81files/s]












Downloading data:   8%|▊         | 113/1382 [00:00<00:10, 125.74files/s]







Downloading data:   9%|▉         | 126/1382 [00:00<00:09, 134.93files/s]









Downloading data:   8%|▊         | 113/1382 [00:00<00:10, 125.21files/s]











Downloading data:   8%|▊         | 114/1382 [00:00<00:10, 126.12files/s]










Downloading data:   8%|▊         | 115/1382 [00:00<00:10, 125.89files/s]















Downloading data:   9%|▊         | 118/1382 [00:00<00:09, 126.62files/s]








Downloading data:   8%|▊         | 117/1382 [00:00<00:10, 125.37files/s]






Downloading data:   9%|▊         | 120/1382 [00:00<00:10, 125.88files/s]














Downloading data:   9%|▊         | 120/1382 [00:00<00:09, 127.18files/s]













Downloading data:   9%|▊         | 120/1382 [00:00<00:10, 125.67files/s]


















Downloading data:   8%|▊         | 114/1382 [00:00<00:10, 120.03files/s]





Downloading data:   9%|▉         | 127/1382 [00:00<00:09, 127.52files/s]




Downloading data:   9%|▉         | 127/1382 [00:00<00:09, 127.92files/s]

















Downloading data:   8%|▊         | 117/1382 [00:00<00:10, 121.46files/s]



















 ... (more hidden) ...
















Downloading data:   9%|▉         | 123/1382 [00:00<00:10, 122.39files/s]



Downloading data:   9%|▉         | 126/1382 [00:00<00:10, 122.25files/s]


Downloading data:  10%|▉         | 135/1382 [00:00<00:09, 128.49files/s]












Downloading data:   9%|▉         | 127/1382 [00:00<00:10, 121.83files/s]









Downloading data:   9%|▉         | 127/1382 [00:00<00:10, 121.68files/s]











Downloading data:   9%|▉         | 128/1382 [00:00<00:10, 121.61files/s]










Downloading data:   9%|▉         | 129/1382 [00:00<00:10, 122.88files/s]

Downloading data:  10%|█         | 140/1382 [00:00<00:09, 128.52files/s]















Downloading data:  10%|▉         | 132/1382 [00:00<00:10, 122.71files/s]







Downloading data:  10%|█         | 142/1382 [00:00<00:09, 128.77files/s]








Downloading data:   9%|▉         | 131/1382 [00:00<00:10, 121.65files/s]














Downloading data:  10%|▉         | 134/1382 [00:00<00:10, 123.22files/s]






Downloading data:  10%|▉         | 134/1382 [00:00<00:10, 122.22files/s]


















Downloading data:   9%|▉         | 127/1382 [00:00<00:10, 118.48files/s]













Downloading data:  10%|▉         | 134/1382 [00:00<00:10, 121.36files/s]

















Downloading data:   9%|▉         | 130/1382 [00:01<00:10, 117.62files/s]





Downloading data:  10%|█         | 141/1382 [00:01<00:10, 121.33files/s]



















 ... (more hidden) ...




Downloading data:  10%|█         | 141/1382 [00:01<00:10, 121.93files/s]
















Downloading data:  10%|▉         | 136/1382 [00:01<00:10, 118.41files/s]



Downloading data:  10%|█         | 139/1382 [00:01<00:10, 118.30files/s]












Downloading data:  10%|█         | 140/1382 [00:01<00:10, 117.93files/s]


Downloading data:  11%|█         | 149/1382 [00:01<00:10, 123.01files/s]









Downloading data:  10%|█         | 140/1382 [00:01<00:10, 117.03files/s]










Downloading data:  10%|█         | 142/1382 [00:01<00:10, 118.88files/s]











Downloading data:  10%|█         | 141/1382 [00:01<00:10, 117.94files/s]















Downloading data:  10%|█         | 145/1382 [00:01<00:10, 119.00files/s]

Downloading data:  11%|█         | 154/1382 [00:01<00:09, 123.07files/s]








Downloading data:  10%|█         | 144/1382 [00:01<00:10, 116.51files/s]







Downloading data:  11%|█▏        | 156/1382 [00:01<00:10, 122.29files/s]














Downloading data:  11%|█         | 147/1382 [00:01<00:10, 118.51files/s]






Downloading data:  11%|█         | 147/1382 [00:01<00:10, 117.71files/s]


















Downloading data:  10%|█         | 139/1382 [00:01<00:10, 115.91files/s]













Downloading data:  11%|█         | 147/1382 [00:01<00:10, 117.97files/s]

















Downloading data:  10%|█         | 142/1382 [00:01<00:10, 115.81files/s]





Downloading data:  11%|█         | 154/1382 [00:01<00:10, 118.76files/s]



















 ... (more hidden) ...




Downloading data:  11%|█         | 154/1382 [00:01<00:10, 118.41files/s]
















Downloading data:  11%|█         | 148/1382 [00:01<00:10, 115.69files/s]



Downloading data:  11%|█         | 151/1382 [00:01<00:10, 114.34files/s]












Downloading data:  11%|█         | 152/1382 [00:01<00:10, 115.60files/s]









Downloading data:  11%|█         | 152/1382 [00:01<00:10, 115.59files/s]











Downloading data:  11%|█         | 153/1382 [00:01<00:10, 116.25files/s]


Downloading data:  12%|█▏        | 162/1382 [00:01<00:10, 119.30files/s]










Downloading data:  11%|█         | 155/1382 [00:01<00:10, 116.86files/s]















Downloading data:  11%|█▏        | 158/1382 [00:01<00:10, 116.73files/s]

Downloading data:  12%|█▏        | 167/1382 [00:01<00:10, 119.59files/s]


















Downloading data:  11%|█         | 151/1382 [00:01<00:10, 114.69files/s]








Downloading data:  11%|█▏        | 156/1382 [00:01<00:10, 114.56files/s]






Downloading data:  12%|█▏        | 159/1382 [00:01<00:10, 115.66files/s]














Downloading data:  12%|█▏        | 160/1382 [00:01<00:10, 116.62files/s]







Downloading data:  12%|█▏        | 169/1382 [00:01<00:10, 119.53files/s]













Downloading data:  12%|█▏        | 159/1382 [00:01<00:10, 116.01files/s]

















Downloading data:  11%|█         | 154/1382 [00:01<00:10, 114.06files/s]



















 ... (more hidden) ...
















Downloading data:  12%|█▏        | 160/1382 [00:01<00:10, 113.98files/s]




Downloading data:  12%|█▏        | 167/1382 [00:01<00:10, 116.57files/s]





Downloading data:  12%|█▏        | 167/1382 [00:01<00:10, 115.90files/s]



Downloading data:  12%|█▏        | 163/1382 [00:01<00:10, 114.74files/s]












Downloading data:  12%|█▏        | 164/1382 [00:01<00:10, 115.11files/s]









Downloading data:  12%|█▏        | 164/1382 [00:01<00:10, 115.93files/s]











Downloading data:  12%|█▏        | 165/1382 [00:01<00:10, 115.58files/s]










Downloading data:  12%|█▏        | 167/1382 [00:01<00:10, 115.96files/s]


Downloading data:  13%|█▎        | 175/1382 [00:01<00:10, 117.57files/s]















Downloading data:  12%|█▏        | 170/1382 [00:01<00:10, 116.34files/s]


















Downloading data:  12%|█▏        | 163/1382 [00:01<00:10, 114.80files/s]








Downloading data:  12%|█▏        | 168/1382 [00:01<00:10, 114.68files/s]






Downloading data:  12%|█▏        | 171/1382 [00:01<00:10, 115.18files/s]














Downloading data:  12%|█▏        | 172/1382 [00:01<00:10, 116.65files/s]

Downloading data:  13%|█▎        | 180/1382 [00:01<00:10, 118.13files/s]













Downloading data:  12%|█▏        | 171/1382 [00:01<00:10, 116.00files/s]







Downloading data:  13%|█▎        | 182/1382 [00:01<00:10, 117.70files/s]

















Downloading data:  12%|█▏        | 166/1382 [00:01<00:10, 114.06files/s]



















 ... (more hidden) ...




Downloading data:  13%|█▎        | 179/1382 [00:01<00:10, 116.57files/s]





Downloading data:  13%|█▎        | 179/1382 [00:01<00:10, 115.18files/s]
















Downloading data:  12%|█▏        | 172/1382 [00:01<00:10, 113.70files/s]



Downloading data:  13%|█▎        | 175/1382 [00:01<00:10, 114.25files/s]












Downloading data:  13%|█▎        | 176/1382 [00:01<00:10, 115.29files/s]









Downloading data:  13%|█▎        | 176/1382 [00:01<00:10, 115.37files/s]











Downloading data:  13%|█▎        | 177/1382 [00:01<00:10, 115.53files/s]










Downloading data:  13%|█▎        | 179/1382 [00:01<00:10, 115.05files/s]


Downloading data:  14%|█▎        | 187/1382 [00:01<00:10, 117.33files/s]















Downloading data:  13%|█▎        | 182/1382 [00:01<00:10, 115.98files/s]


















Downloading data:  13%|█▎        | 175/1382 [00:01<00:10, 114.66files/s]






Downloading data:  13%|█▎        | 183/1382 [00:01<00:10, 115.60files/s]








Downloading data:  13%|█▎        | 180/1382 [00:01<00:10, 114.85files/s]














Downloading data:  13%|█▎        | 184/1382 [00:01<00:10, 117.27files/s]

Downloading data:  14%|█▍        | 192/1382 [00:01<00:10, 116.98files/s]













Downloading data:  13%|█▎        | 183/1382 [00:01<00:10, 115.37files/s]







Downloading data:  14%|█▍        | 194/1382 [00:01<00:10, 117.19files/s]

















Downloading data:  13%|█▎        | 178/1382 [00:01<00:10, 114.85files/s]



















 ... (more hidden) ...





Downloading data:  14%|█▍        | 191/1382 [00:01<00:10, 115.47files/s]




Downloading data:  14%|█▍        | 191/1382 [00:01<00:10, 114.67files/s]
















Downloading data:  13%|█▎        | 185/1382 [00:01<00:10, 115.65files/s]



Downloading data:  14%|█▎        | 187/1382 [00:01<00:10, 114.02files/s]












Downloading data:  14%|█▎        | 188/1382 [00:01<00:10, 115.16files/s]









Downloading data:  14%|█▎        | 188/1382 [00:01<00:10, 115.95files/s]











Downloading data:  14%|█▎        | 189/1382 [00:01<00:10, 115.40files/s]










Downloading data:  14%|█▍        | 191/1382 [00:01<00:10, 116.24files/s]


Downloading data:  14%|█▍        | 199/1382 [00:01<00:10, 116.95files/s]















Downloading data:  14%|█▍        | 194/1382 [00:01<00:10, 115.63files/s]


















Downloading data:  14%|█▎        | 187/1382 [00:01<00:10, 115.18files/s]








Downloading data:  14%|█▍        | 192/1382 [00:01<00:10, 115.26files/s]






Downloading data:  14%|█▍        | 195/1382 [00:01<00:10, 115.71files/s]














Downloading data:  14%|█▍        | 196/1382 [00:01<00:10, 115.92files/s]

Downloading data:  15%|█▍        | 204/1382 [00:01<00:10, 116.71files/s]













Downloading data:  14%|█▍        | 195/1382 [00:01<00:10, 115.87files/s]







Downloading data:  15%|█▍        | 206/1382 [00:01<00:10, 117.08files/s]

















Downloading data:  14%|█▎        | 190/1382 [00:01<00:10, 115.66files/s]



















 ... (more hidden) ...





Downloading data:  15%|█▍        | 203/1382 [00:01<00:10, 116.24files/s]
















Downloading data:  14%|█▍        | 197/1382 [00:01<00:10, 116.83files/s]




Downloading data:  15%|█▍        | 203/1382 [00:01<00:10, 114.99files/s]



Downloading data:  14%|█▍        | 199/1382 [00:01<00:10, 114.94files/s]












Downloading data:  14%|█▍        | 200/1382 [00:01<00:10, 115.27files/s]









Downloading data:  14%|█▍        | 200/1382 [00:01<00:10, 115.49files/s]











Downloading data:  15%|█▍        | 201/1382 [00:01<00:10, 115.29files/s]










Downloading data:  15%|█▍        | 203/1382 [00:01<00:10, 116.54files/s]


Downloading data:  15%|█▌        | 211/1382 [00:01<00:10, 115.51files/s]















Downloading data:  15%|█▍        | 206/1382 [00:01<00:10, 115.59files/s]


















Downloading data:  14%|█▍        | 199/1382 [00:01<00:10, 115.11files/s]








Downloading data:  15%|█▍        | 204/1382 [00:01<00:10, 115.06files/s]






Downloading data:  15%|█▍        | 207/1382 [00:01<00:10, 115.39files/s]














Downloading data:  15%|█▌        | 208/1382 [00:01<00:10, 115.81files/s]

Downloading data:  16%|█▌        | 216/1382 [00:01<00:10, 116.56files/s]













Downloading data:  15%|█▍        | 207/1382 [00:01<00:10, 115.39files/s]







Downloading data:  16%|█▌        | 218/1382 [00:01<00:10, 116.01files/s]

















Downloading data:  15%|█▍        | 202/1382 [00:01<00:10, 114.44files/s]



















 ... (more hidden) ...





Downloading data:  16%|█▌        | 215/1382 [00:01<00:10, 115.08files/s]
















Downloading data:  15%|█▌        | 209/1382 [00:01<00:10, 115.45files/s]




Downloading data:  16%|█▌        | 215/1382 [00:01<00:10, 111.20files/s]



Downloading data:  15%|█▌        | 211/1382 [00:01<00:10, 111.07files/s]












Downloading data:  15%|█▌        | 212/1382 [00:01<00:10, 111.75files/s]











Downloading data:  15%|█▌        | 213/1382 [00:01<00:10, 113.46files/s]









Downloading data:  15%|█▌        | 212/1382 [00:01<00:10, 111.22files/s]










Downloading data:  16%|█▌        | 215/1382 [00:01<00:10, 112.31files/s]


Downloading data:  16%|█▌        | 223/1382 [00:01<00:10, 112.46files/s]















Downloading data:  16%|█▌        | 218/1382 [00:01<00:10, 111.56files/s]


















Downloading data:  15%|█▌        | 211/1382 [00:01<00:10, 111.78files/s]








Downloading data:  16%|█▌        | 216/1382 [00:01<00:10, 112.05files/s]






Downloading data:  16%|█▌        | 219/1382 [00:01<00:10, 111.31files/s]














Downloading data:  16%|█▌        | 220/1382 [00:01<00:10, 112.46files/s]

Downloading data:  16%|█▋        | 228/1382 [00:01<00:10, 112.72files/s]













Downloading data:  16%|█▌        | 219/1382 [00:01<00:10, 112.01files/s]







Downloading data:  17%|█▋        | 230/1382 [00:01<00:10, 112.51files/s]

















Downloading data:  15%|█▌        | 214/1382 [00:01<00:10, 109.83files/s]



















 ... (more hidden) ...





Downloading data:  16%|█▋        | 227/1382 [00:01<00:10, 111.85files/s]
















Downloading data:  16%|█▌        | 221/1382 [00:01<00:10, 112.87files/s]




Downloading data:  16%|█▋        | 227/1382 [00:01<00:10, 111.92files/s]



Downloading data:  16%|█▌        | 223/1382 [00:01<00:10, 112.56files/s]











Downloading data:  16%|█▋        | 225/1382 [00:01<00:10, 113.42files/s]












Downloading data:  16%|█▌        | 224/1382 [00:01<00:10, 111.75files/s]









Downloading data:  16%|█▌        | 224/1382 [00:01<00:10, 112.11files/s]










Downloading data:  16%|█▋        | 227/1382 [00:01<00:10, 110.44files/s]


Downloading data:  17%|█▋        | 235/1382 [00:01<00:10, 112.75files/s]















Downloading data:  17%|█▋        | 230/1382 [00:01<00:10, 112.69files/s]


















Downloading data:  16%|█▌        | 224/1382 [00:01<00:10, 114.85files/s]














Downloading data:  17%|█▋        | 232/1382 [00:01<00:10, 114.15files/s]








Downloading data:  16%|█▋        | 228/1382 [00:01<00:10, 112.05files/s]

Downloading data:  17%|█▋        | 240/1382 [00:01<00:09, 114.25files/s]






Downloading data:  17%|█▋        | 231/1382 [00:01<00:10, 111.44files/s]













Downloading data:  17%|█▋        | 231/1382 [00:01<00:10, 111.85files/s]







Downloading data:  18%|█▊        | 242/1382 [00:01<00:10, 112.88files/s]

















Downloading data:  16%|█▋        | 226/1382 [00:01<00:10, 110.55files/s]



















 ... (more hidden) ...





Downloading data:  17%|█▋        | 239/1382 [00:01<00:10, 110.83files/s]
















Downloading data:  17%|█▋        | 233/1382 [00:01<00:10, 110.16files/s]




Downloading data:  17%|█▋        | 239/1382 [00:01<00:10, 110.80files/s]



Downloading data:  17%|█▋        | 235/1382 [00:01<00:10, 112.71files/s]











Downloading data:  17%|█▋        | 237/1382 [00:01<00:10, 113.22files/s]












Downloading data:  17%|█▋        | 236/1382 [00:01<00:10, 112.38files/s]









Downloading data:  17%|█▋        | 236/1382 [00:01<00:10, 113.16files/s]










Downloading data:  17%|█▋        | 239/1382 [00:01<00:10, 112.16files/s]


Downloading data:  18%|█▊        | 247/1382 [00:01<00:09, 113.76files/s]















Downloading data:  18%|█▊        | 242/1382 [00:01<00:09, 114.29files/s]


















Downloading data:  17%|█▋        | 236/1382 [00:01<00:09, 115.74files/s]














Downloading data:  18%|█▊        | 244/1382 [00:01<00:09, 115.09files/s]








Downloading data:  17%|█▋        | 240/1382 [00:01<00:10, 113.17files/s]

Downloading data:  18%|█▊        | 252/1382 [00:01<00:09, 114.84files/s]






Downloading data:  18%|█▊        | 243/1382 [00:01<00:10, 112.98files/s]













Downloading data:  18%|█▊        | 243/1382 [00:01<00:10, 113.67files/s]







Downloading data:  18%|█▊        | 254/1382 [00:01<00:09, 113.11files/s]

















Downloading data:  17%|█▋        | 238/1382 [00:01<00:10, 112.48files/s]



















 ... (more hidden) ...





Downloading data:  18%|█▊        | 251/1382 [00:02<00:10, 112.13files/s]




Downloading data:  18%|█▊        | 251/1382 [00:02<00:10, 112.31files/s]



Downloading data:  18%|█▊        | 247/1382 [00:02<00:09, 113.63files/s]
















Downloading data:  18%|█▊        | 246/1382 [00:02<00:10, 113.56files/s]











Downloading data:  18%|█▊        | 249/1382 [00:02<00:10, 113.06files/s]












Downloading data:  18%|█▊        | 248/1382 [00:02<00:10, 112.48files/s]









Downloading data:  18%|█▊        | 248/1382 [00:02<00:10, 113.03files/s]










Downloading data:  18%|█▊        | 251/1382 [00:02<00:10, 112.73files/s]


Downloading data:  19%|█▊        | 259/1382 [00:02<00:09, 113.58files/s]















Downloading data:  18%|█▊        | 254/1382 [00:02<00:09, 114.33files/s]


















Downloading data:  18%|█▊        | 248/1382 [00:02<00:09, 115.52files/s]














Downloading data:  19%|█▊        | 256/1382 [00:02<00:09, 115.22files/s]








Downloading data:  18%|█▊        | 252/1382 [00:02<00:09, 113.66files/s]

Downloading data:  19%|█▉        | 264/1382 [00:02<00:09, 114.34files/s]






Downloading data:  18%|█▊        | 255/1382 [00:02<00:10, 112.62files/s]













Downloading data:  18%|█▊        | 255/1382 [00:02<00:09, 113.70files/s]







Downloading data:  19%|█▉        | 266/1382 [00:02<00:09, 112.78files/s]

















Downloading data:  18%|█▊        | 250/1382 [00:02<00:10, 112.76files/s]



















 ... (more hidden) ...





Downloading data:  19%|█▉        | 263/1382 [00:02<00:09, 112.46files/s]
















Downloading data:  19%|█▊        | 258/1382 [00:02<00:09, 113.89files/s]




Downloading data:  19%|█▉        | 263/1382 [00:02<00:09, 112.12files/s]



Downloading data:  19%|█▊        | 259/1382 [00:02<00:09, 113.19files/s]











Downloading data:  19%|█▉        | 261/1382 [00:02<00:09, 114.00files/s]












Downloading data:  19%|█▉        | 260/1382 [00:02<00:09, 113.60files/s]









Downloading data:  19%|█▉        | 260/1382 [00:02<00:09, 113.57files/s]










Downloading data:  19%|█▉        | 263/1382 [00:02<00:09, 112.80files/s]















Downloading data:  19%|█▉        | 266/1382 [00:02<00:09, 114.32files/s]


Downloading data:  20%|█▉        | 271/1382 [00:02<00:09, 112.34files/s]


















Downloading data:  19%|█▉        | 260/1382 [00:02<00:09, 114.58files/s]














Downloading data:  19%|█▉        | 268/1382 [00:02<00:09, 114.39files/s]








Downloading data:  19%|█▉        | 264/1382 [00:02<00:09, 113.79files/s]

Downloading data:  20%|█▉        | 276/1382 [00:02<00:09, 113.35files/s]






Downloading data:  19%|█▉        | 267/1382 [00:02<00:09, 112.85files/s]













Downloading data:  19%|█▉        | 267/1382 [00:02<00:09, 113.85files/s]







Downloading data:  20%|██        | 278/1382 [00:02<00:09, 113.82files/s]

















Downloading data:  19%|█▉        | 262/1382 [00:02<00:09, 114.77files/s]



















 ... (more hidden) ...





Downloading data:  20%|█▉        | 275/1382 [00:02<00:09, 114.39files/s]




Downloading data:  20%|█▉        | 275/1382 [00:02<00:09, 113.17files/s]
















Downloading data:  20%|█▉        | 271/1382 [00:02<00:09, 115.49files/s]



Downloading data:  20%|█▉        | 271/1382 [00:02<00:09, 112.57files/s]











Downloading data:  20%|█▉        | 273/1382 [00:02<00:09, 115.59files/s]












Downloading data:  20%|█▉        | 272/1382 [00:02<00:09, 115.29files/s]









Downloading data:  20%|█▉        | 273/1382 [00:02<00:09, 115.98files/s]


Downloading data:  20%|██        | 283/1382 [00:02<00:09, 114.26files/s]
Downloading data: 100%|██████████| 1382/1382 [00:02<00:00, 647.56files/s]











Downloading data:  20%|█▉        | 276/1382 [00:02<00:09, 115.75files/s]















Downloading data:  20%|██        | 279/1382 [00:02<00:09, 115.95files/s]














Downloading data:  20%|██        | 281/1382 [00:02<00:09, 116.88files/s]


















Downloading data:  20%|█▉        | 273/1382 [00:02<00:09, 116.97files/s]








Downloading data:  20%|██        | 277/1382 [00:02<00:09, 115.98files/s]

Downloading data:  21%|██        | 289/1382 [00:02<00:09, 116.48files/s]
Downloading data: 100%|██████████| 1382/1382 [00:02<00:00, 641.78files/s]







Downloading data:  20%|██        | 280/1382 [00:02<00:09, 115.35files/s]













Downloading data:  20%|██        | 280/1382 [00:02<00:09, 116.41files/s]







Downloading data:  21%|██        | 291/1382 [00:02<00:09, 117.14files/s]

















Downloading data:  20%|█▉        | 275/1382 [00:02<00:09, 116.95files/s]



















 ... (more hidden) ...





Downloading data:  21%|██        | 288/1382 [00:02<00:09, 116.35files/s]




Downloading data:  21%|██        | 288/1382 [00:02<00:09, 115.99files/s]
















Downloading data:  21%|██        | 284/1382 [00:02<00:09, 117.37files/s]











Downloading data:  21%|██        | 285/1382 [00:02<00:09, 116.60files/s]












Downloading data:  21%|██        | 284/1382 [00:02<00:09, 116.41files/s]



Downloading data:  21%|██        | 284/1382 [00:02<00:09, 115.33files/s]









Downloading data:  21%|██        | 286/1382 [00:02<00:09, 117.14files/s]










Downloading data:  21%|██        | 288/1382 [00:02<00:09, 116.86files/s]


Downloading data:  21%|██▏       | 295/1382 [00:02<00:09, 115.57files/s]


















Downloading data:  21%|██        | 285/1382 [00:02<00:09, 117.55files/s]














Downloading data:  21%|██        | 293/1382 [00:02<00:09, 117.47files/s]















Downloading data:  21%|██        | 292/1382 [00:02<00:09, 117.83files/s]

Downloading data:  22%|██▏       | 301/1382 [00:02<00:09, 116.77files/s]






Downloading data:  21%|██        | 292/1382 [00:02<00:09, 115.64files/s]








Downloading data:  21%|██        | 290/1382 [00:02<00:09, 116.90files/s]







Downloading data:  22%|██▏       | 303/1382 [00:02<00:09, 117.37files/s]













Downloading data:  21%|██        | 293/1382 [00:02<00:09, 117.09files/s]

















Downloading data:  21%|██        | 287/1382 [00:02<00:09, 117.62files/s]



















 ... (more hidden) ...





Downloading data:  22%|██▏       | 300/1382 [00:02<00:09, 116.70files/s]




Downloading data:  22%|██▏       | 300/1382 [00:02<00:09, 115.23files/s]
















Downloading data:  21%|██▏       | 296/1382 [00:02<00:09, 117.47files/s]











Downloading data:  21%|██▏       | 297/1382 [00:02<00:09, 116.93files/s]












Downloading data:  21%|██▏       | 296/1382 [00:02<00:09, 116.20files/s]



Downloading data:  21%|██▏       | 296/1382 [00:02<00:09, 114.88files/s]









Downloading data:  22%|██▏       | 298/1382 [00:02<00:09, 116.35files/s]










Downloading data:  22%|██▏       | 300/1382 [00:02<00:09, 115.70files/s]


Downloading data:  22%|██▏       | 307/1382 [00:02<00:09, 114.81files/s]


















Downloading data:  21%|██▏       | 297/1382 [00:02<00:09, 117.62files/s]














Downloading data:  22%|██▏       | 305/1382 [00:02<00:09, 117.37files/s]















Downloading data:  22%|██▏       | 304/1382 [00:02<00:09, 117.74files/s]

Downloading data:  23%|██▎       | 313/1382 [00:02<00:09, 115.85files/s]








Downloading data:  22%|██▏       | 302/1382 [00:02<00:09, 116.94files/s]






Downloading data:  22%|██▏       | 304/1382 [00:02<00:09, 116.03files/s]













Downloading data:  22%|██▏       | 305/1382 [00:02<00:09, 117.17files/s]







Downloading data:  23%|██▎       | 315/1382 [00:02<00:09, 116.57files/s]

















Downloading data:  22%|██▏       | 299/1382 [00:02<00:09, 118.16files/s]



















 ... (more hidden) ...





Downloading data:  23%|██▎       | 312/1382 [00:02<00:09, 116.11files/s]




Downloading data:  23%|██▎       | 312/1382 [00:02<00:09, 116.29files/s]
















Downloading data:  22%|██▏       | 308/1382 [00:02<00:09, 117.90files/s]











Downloading data:  22%|██▏       | 309/1382 [00:02<00:09, 117.52files/s]












Downloading data:  22%|██▏       | 308/1382 [00:02<00:09, 116.78files/s]



Downloading data:  22%|██▏       | 308/1382 [00:02<00:09, 115.99files/s]









Downloading data:  23%|██▎       | 311/1382 [00:02<00:09, 117.97files/s]


















Downloading data:  22%|██▏       | 309/1382 [00:02<00:09, 118.06files/s]














Downloading data:  23%|██▎       | 317/1382 [00:02<00:09, 118.04files/s]


Downloading data:  23%|██▎       | 320/1382 [00:02<00:09, 117.08files/s]










Downloading data:  23%|██▎       | 313/1382 [00:02<00:09, 117.66files/s]















Downloading data:  23%|██▎       | 316/1382 [00:02<00:09, 118.22files/s]

Downloading data:  24%|██▎       | 325/1382 [00:02<00:09, 116.98files/s]






Downloading data:  23%|██▎       | 316/1382 [00:02<00:09, 116.98files/s]








Downloading data:  23%|██▎       | 315/1382 [00:02<00:09, 117.98files/s]







Downloading data:  24%|██▎       | 327/1382 [00:02<00:09, 116.63files/s]

















Downloading data:  23%|██▎       | 311/1382 [00:02<00:09, 118.00files/s]













Downloading data:  23%|██▎       | 318/1382 [00:02<00:08, 118.33files/s]





Downloading data:  24%|██▎       | 325/1382 [00:02<00:08, 118.66files/s]



















 ... (more hidden) ...











Downloading data:  23%|██▎       | 321/1382 [00:02<00:09, 117.56files/s]
















Downloading data:  23%|██▎       | 321/1382 [00:02<00:08, 119.30files/s]




Downloading data:  24%|██▎       | 325/1382 [00:02<00:08, 117.48files/s]



Downloading data:  23%|██▎       | 320/1382 [00:02<00:09, 116.45files/s]












Downloading data:  23%|██▎       | 321/1382 [00:02<00:08, 117.92files/s]









Downloading data:  23%|██▎       | 323/1382 [00:02<00:08, 118.54files/s]


















Downloading data:  23%|██▎       | 321/1382 [00:02<00:08, 118.57files/s]














Downloading data:  24%|██▍       | 329/1382 [00:02<00:08, 118.52files/s]


Downloading data:  24%|██▍       | 332/1382 [00:02<00:08, 117.68files/s]















Downloading data:  24%|██▎       | 328/1382 [00:02<00:08, 118.52files/s]










Downloading data:  24%|██▎       | 325/1382 [00:02<00:08, 117.94files/s]

Downloading data:  24%|██▍       | 337/1382 [00:02<00:08, 117.11files/s]






Downloading data:  24%|██▎       | 328/1382 [00:02<00:09, 115.27files/s]








Downloading data:  24%|██▎       | 327/1382 [00:02<00:09, 116.68files/s]

















Downloading data:  23%|██▎       | 323/1382 [00:02<00:08, 118.02files/s]







Downloading data:  25%|██▍       | 339/1382 [00:02<00:08, 116.81files/s]













Downloading data:  24%|██▍       | 330/1382 [00:02<00:08, 117.03files/s]



















 ... (more hidden) ...





Downloading data:  24%|██▍       | 337/1382 [00:02<00:08, 116.59files/s]











Downloading data:  24%|██▍       | 333/1382 [00:02<00:09, 114.90files/s]
















Downloading data:  24%|██▍       | 333/1382 [00:02<00:09, 116.25files/s]



Downloading data:  24%|██▍       | 332/1382 [00:02<00:09, 114.16files/s]




Downloading data:  24%|██▍       | 337/1382 [00:02<00:09, 114.65files/s]












Downloading data:  24%|██▍       | 333/1382 [00:02<00:09, 114.66files/s]









Downloading data:  24%|██▍       | 335/1382 [00:02<00:09, 115.40files/s]














Downloading data:  25%|██▍       | 341/1382 [00:02<00:09, 115.09files/s]


















Downloading data:  24%|██▍       | 333/1382 [00:02<00:09, 114.98files/s]















Downloading data:  25%|██▍       | 340/1382 [00:02<00:09, 115.13files/s]


Downloading data:  25%|██▍       | 344/1382 [00:02<00:09, 114.21files/s]










Downloading data:  24%|██▍       | 337/1382 [00:02<00:09, 114.02files/s]

Downloading data:  25%|██▌       | 349/1382 [00:02<00:09, 114.23files/s]






Downloading data:  25%|██▍       | 340/1382 [00:02<00:09, 113.02files/s]








Downloading data:  25%|██▍       | 339/1382 [00:02<00:09, 114.07files/s]

















Downloading data:  24%|██▍       | 335/1382 [00:02<00:09, 115.60files/s]







Downloading data:  25%|██▌       | 351/1382 [00:02<00:09, 114.25files/s]













Downloading data:  25%|██▍       | 342/1382 [00:02<00:09, 115.02files/s]



















 ... (more hidden) ...





Downloading data:  25%|██▌       | 349/1382 [00:02<00:08, 114.92files/s]











Downloading data:  25%|██▍       | 345/1382 [00:02<00:09, 114.41files/s]
















Downloading data:  25%|██▍       | 345/1382 [00:02<00:08, 115.79files/s]



Downloading data:  25%|██▍       | 344/1382 [00:02<00:09, 114.04files/s]




Downloading data:  25%|██▌       | 349/1382 [00:02<00:09, 114.54files/s]












Downloading data:  25%|██▍       | 345/1382 [00:02<00:09, 114.61files/s]









Downloading data:  25%|██▌       | 347/1382 [00:02<00:08, 116.50files/s]















Downloading data:  25%|██▌       | 352/1382 [00:02<00:08, 116.34files/s]


















Downloading data:  25%|██▍       | 345/1382 [00:02<00:08, 116.06files/s]


Downloading data:  26%|██▌       | 356/1382 [00:02<00:08, 114.63files/s]










Downloading data:  25%|██▌       | 349/1382 [00:02<00:08, 115.01files/s]














Downloading data:  26%|██▌       | 354/1382 [00:02<00:08, 117.09files/s]

Downloading data:  26%|██▌       | 361/1382 [00:02<00:08, 115.16files/s]






Downloading data:  26%|██▌       | 353/1382 [00:02<00:08, 115.62files/s]








Downloading data:  25%|██▌       | 352/1382 [00:02<00:08, 116.26files/s]

















Downloading data:  25%|██▌       | 348/1382 [00:02<00:08, 117.52files/s]







Downloading data:  26%|██▋       | 364/1382 [00:02<00:08, 115.19files/s]













Downloading data:  26%|██▌       | 355/1382 [00:02<00:08, 116.69files/s]



















 ... (more hidden) ...





Downloading data:  26%|██▌       | 362/1382 [00:02<00:08, 117.15files/s]




Downloading data:  26%|██▌       | 361/1382 [00:02<00:08, 116.00files/s]
















Downloading data:  26%|██▌       | 358/1382 [00:02<00:08, 118.66files/s]











Downloading data:  26%|██▌       | 358/1382 [00:02<00:08, 116.89files/s]



Downloading data:  26%|██▌       | 356/1382 [00:02<00:08, 114.03files/s]












Downloading data:  26%|██▌       | 358/1382 [00:02<00:08, 117.31files/s]









Downloading data:  26%|██▌       | 360/1382 [00:02<00:08, 118.50files/s]


Downloading data:  27%|██▋       | 368/1382 [00:02<00:08, 115.91files/s]


















Downloading data:  26%|██▌       | 358/1382 [00:02<00:08, 118.16files/s]















Downloading data:  26%|██▋       | 365/1382 [00:02<00:08, 118.30files/s]










Downloading data:  26%|██▌       | 362/1382 [00:02<00:08, 117.12files/s]














Downloading data:  27%|██▋       | 367/1382 [00:02<00:08, 118.98files/s]

Downloading data:  27%|██▋       | 374/1382 [00:03<00:08, 116.86files/s]






Downloading data:  26%|██▋       | 365/1382 [00:02<00:08, 116.65files/s]

















Downloading data:  26%|██▌       | 360/1382 [00:02<00:08, 118.11files/s]








Downloading data:  26%|██▋       | 364/1382 [00:03<00:08, 117.04files/s]







Downloading data:  27%|██▋       | 377/1382 [00:03<00:08, 117.28files/s]













Downloading data:  27%|██▋       | 368/1382 [00:03<00:08, 117.13files/s]



















 ... (more hidden) ...





Downloading data:  27%|██▋       | 374/1382 [00:03<00:08, 116.00files/s]




Downloading data:  27%|██▋       | 373/1382 [00:03<00:08, 116.07files/s]
















Downloading data:  27%|██▋       | 370/1382 [00:03<00:08, 117.62files/s]











Downloading data:  27%|██▋       | 370/1382 [00:03<00:08, 116.35files/s]



Downloading data:  27%|██▋       | 368/1382 [00:03<00:08, 113.67files/s]












Downloading data:  27%|██▋       | 370/1382 [00:03<00:08, 116.35files/s]









Downloading data:  27%|██▋       | 372/1382 [00:03<00:08, 115.57files/s]


Downloading data:  27%|██▋       | 380/1382 [00:03<00:08, 115.95files/s]















Downloading data:  27%|██▋       | 377/1382 [00:03<00:08, 117.88files/s]


















Downloading data:  27%|██▋       | 370/1382 [00:03<00:08, 117.09files/s]










Downloading data:  27%|██▋       | 374/1382 [00:03<00:08, 114.85files/s]














Downloading data:  27%|██▋       | 379/1382 [00:03<00:08, 115.97files/s]

Downloading data:  28%|██▊       | 386/1382 [00:03<00:08, 116.03files/s]






Downloading data:  27%|██▋       | 377/1382 [00:03<00:08, 116.24files/s]








Downloading data:  27%|██▋       | 376/1382 [00:03<00:08, 115.13files/s]

















Downloading data:  27%|██▋       | 372/1382 [00:03<00:08, 115.64files/s]







Downloading data:  28%|██▊       | 389/1382 [00:03<00:08, 116.53files/s]













Downloading data:  27%|██▋       | 380/1382 [00:03<00:08, 117.65files/s]



















 ... (more hidden) ...





Downloading data:  28%|██▊       | 386/1382 [00:03<00:08, 114.08files/s]




Downloading data:  28%|██▊       | 385/1382 [00:03<00:08, 115.15files/s]
















Downloading data:  28%|██▊       | 382/1382 [00:03<00:08, 114.82files/s]



Downloading data:  27%|██▋       | 380/1382 [00:03<00:08, 113.71files/s]











Downloading data:  28%|██▊       | 382/1382 [00:03<00:08, 112.00files/s]












Downloading data:  28%|██▊       | 382/1382 [00:03<00:08, 114.79files/s]















Downloading data:  28%|██▊       | 389/1382 [00:03<00:08, 117.35files/s]









Downloading data:  28%|██▊       | 384/1382 [00:03<00:08, 113.36files/s]


















Downloading data:  28%|██▊       | 382/1382 [00:03<00:08, 115.46files/s]


Downloading data:  28%|██▊       | 392/1382 [00:03<00:08, 112.92files/s]














Downloading data:  28%|██▊       | 391/1382 [00:03<00:08, 116.30files/s]










Downloading data:  28%|██▊       | 386/1382 [00:03<00:08, 114.54files/s]






Downloading data:  28%|██▊       | 389/1382 [00:03<00:08, 115.76files/s]

Downloading data:  29%|██▉       | 398/1382 [00:03<00:08, 114.37files/s]








Downloading data:  28%|██▊       | 388/1382 [00:03<00:08, 114.41files/s]

















Downloading data:  28%|██▊       | 384/1382 [00:03<00:08, 113.89files/s]













Downloading data:  28%|██▊       | 392/1382 [00:03<00:08, 115.73files/s]







Downloading data:  29%|██▉       | 401/1382 [00:03<00:08, 113.70files/s]



















 ... (more hidden) ...





Downloading data:  29%|██▉       | 398/1382 [00:03<00:08, 114.67files/s]




Downloading data:  29%|██▊       | 397/1382 [00:03<00:08, 113.05files/s]



Downloading data:  28%|██▊       | 392/1382 [00:03<00:08, 112.87files/s]
















Downloading data:  29%|██▊       | 394/1382 [00:03<00:08, 113.55files/s]











Downloading data:  29%|██▊       | 394/1382 [00:03<00:08, 111.42files/s]












Downloading data:  29%|██▊       | 394/1382 [00:03<00:08, 113.34files/s]















Downloading data:  29%|██▉       | 401/1382 [00:03<00:08, 115.92files/s]


















Downloading data:  29%|██▊       | 394/1382 [00:03<00:08, 114.71files/s]









Downloading data:  29%|██▊       | 396/1382 [00:03<00:08, 112.56files/s]














Downloading data:  29%|██▉       | 403/1382 [00:03<00:08, 114.05files/s]


Downloading data:  29%|██▉       | 404/1382 [00:03<00:08, 111.06files/s]










Downloading data:  29%|██▉       | 398/1382 [00:03<00:08, 112.79files/s]






Downloading data:  29%|██▉       | 401/1382 [00:03<00:08, 114.53files/s]

Downloading data:  30%|██▉       | 410/1382 [00:03<00:08, 112.86files/s]








Downloading data:  29%|██▉       | 400/1382 [00:03<00:08, 111.75files/s]

















Downloading data:  29%|██▊       | 396/1382 [00:03<00:08, 111.50files/s]













Downloading data:  29%|██▉       | 404/1382 [00:03<00:08, 114.19files/s]







Downloading data:  30%|██▉       | 413/1382 [00:03<00:08, 111.32files/s]



















 ... (more hidden) ...





Downloading data:  30%|██▉       | 410/1382 [00:03<00:08, 114.31files/s]




Downloading data:  30%|██▉       | 409/1382 [00:03<00:08, 114.20files/s]
















Downloading data:  29%|██▉       | 406/1382 [00:03<00:08, 113.75files/s]



Downloading data:  29%|██▉       | 404/1382 [00:03<00:08, 113.25files/s]











Downloading data:  29%|██▉       | 406/1382 [00:03<00:08, 112.89files/s]












Downloading data:  29%|██▉       | 406/1382 [00:03<00:08, 113.02files/s]















Downloading data:  30%|██▉       | 413/1382 [00:03<00:08, 116.15files/s]


















Downloading data:  29%|██▉       | 406/1382 [00:03<00:08, 115.24files/s]









Downloading data:  30%|██▉       | 408/1382 [00:03<00:08, 113.03files/s]


Downloading data:  30%|███       | 416/1382 [00:03<00:08, 113.03files/s]










Downloading data:  30%|██▉       | 410/1382 [00:03<00:08, 114.31files/s]














Downloading data:  30%|███       | 415/1382 [00:03<00:08, 114.15files/s]






Downloading data:  30%|██▉       | 413/1382 [00:03<00:08, 115.18files/s]

Downloading data:  31%|███       | 422/1382 [00:03<00:08, 113.98files/s]








Downloading data:  30%|██▉       | 412/1382 [00:03<00:08, 113.40files/s]

















Downloading data:  30%|██▉       | 409/1382 [00:03<00:08, 114.02files/s]













Downloading data:  30%|███       | 417/1382 [00:03<00:08, 115.95files/s]







Downloading data:  31%|███       | 426/1382 [00:03<00:08, 114.40files/s]




Downloading data:  30%|███       | 421/1382 [00:03<00:08, 114.81files/s]



















 ... (more hidden) ...





Downloading data:  31%|███       | 423/1382 [00:03<00:08, 115.91files/s]
















Downloading data:  30%|███       | 419/1382 [00:03<00:08, 115.76files/s]



Downloading data:  30%|███       | 417/1382 [00:03<00:08, 115.38files/s]











Downloading data:  30%|███       | 419/1382 [00:03<00:08, 114.79files/s]












Downloading data:  30%|███       | 419/1382 [00:03<00:08, 115.66files/s]


















Downloading data:  30%|███       | 418/1382 [00:03<00:08, 116.31files/s]















Downloading data:  31%|███       | 426/1382 [00:03<00:08, 117.49files/s]


Downloading data:  31%|███       | 428/1382 [00:03<00:08, 114.31files/s]










Downloading data:  31%|███       | 422/1382 [00:03<00:08, 115.50files/s]









Downloading data:  30%|███       | 421/1382 [00:03<00:08, 115.30files/s]






Downloading data:  31%|███       | 425/1382 [00:03<00:08, 116.14files/s]














Downloading data:  31%|███       | 428/1382 [00:03<00:08, 116.16files/s]

Downloading data:  31%|███▏      | 434/1382 [00:03<00:08, 115.64files/s]








Downloading data:  31%|███       | 424/1382 [00:03<00:08, 114.33files/s]

















Downloading data:  30%|███       | 421/1382 [00:03<00:08, 115.14files/s]













Downloading data:  31%|███       | 430/1382 [00:03<00:08, 117.13files/s]







Downloading data:  32%|███▏      | 438/1382 [00:03<00:08, 114.93files/s]




Downloading data:  31%|███▏      | 433/1382 [00:03<00:08, 116.15files/s]



















 ... (more hidden) ...





Downloading data:  31%|███▏      | 435/1382 [00:03<00:08, 116.62files/s]
















Downloading data:  31%|███       | 431/1382 [00:03<00:08, 116.49files/s]



Downloading data:  31%|███       | 429/1382 [00:03<00:08, 115.02files/s]












Downloading data:  31%|███       | 431/1382 [00:03<00:08, 116.09files/s]











Downloading data:  31%|███▏      | 432/1382 [00:03<00:08, 115.90files/s]


















Downloading data:  31%|███       | 430/1382 [00:03<00:08, 116.41files/s]















Downloading data:  32%|███▏      | 438/1382 [00:03<00:08, 117.57files/s]










Downloading data:  31%|███▏      | 434/1382 [00:03<00:08, 116.20files/s]









Downloading data:  31%|███▏      | 433/1382 [00:03<00:08, 116.05files/s]


Downloading data:  32%|███▏      | 440/1382 [00:03<00:08, 114.60files/s]














Downloading data:  32%|███▏      | 440/1382 [00:03<00:08, 117.00files/s]






Downloading data:  32%|███▏      | 437/1382 [00:03<00:08, 116.63files/s]

Downloading data:  32%|███▏      | 446/1382 [00:03<00:08, 116.37files/s]








Downloading data:  32%|███▏      | 436/1382 [00:03<00:08, 115.30files/s]

















Downloading data:  31%|███▏      | 433/1382 [00:03<00:08, 115.54files/s]







Downloading data:  33%|███▎      | 450/1382 [00:03<00:08, 115.68files/s]













Downloading data:  32%|███▏      | 443/1382 [00:03<00:07, 118.54files/s]




Downloading data:  32%|███▏      | 445/1382 [00:03<00:08, 116.03files/s]



















 ... (more hidden) ...





Downloading data:  32%|███▏      | 447/1382 [00:03<00:08, 115.50files/s]
















Downloading data:  32%|███▏      | 443/1382 [00:03<00:08, 115.64files/s]



Downloading data:  32%|███▏      | 441/1382 [00:03<00:08, 115.76files/s]












Downloading data:  32%|███▏      | 443/1382 [00:03<00:08, 116.27files/s]











Downloading data:  32%|███▏      | 444/1382 [00:03<00:08, 116.58files/s]















Downloading data:  33%|███▎      | 450/1382 [00:03<00:07, 117.69files/s]


















Downloading data:  32%|███▏      | 443/1382 [00:03<00:07, 117.77files/s]










Downloading data:  32%|███▏      | 446/1382 [00:03<00:08, 115.73files/s]









Downloading data:  32%|███▏      | 445/1382 [00:03<00:08, 115.61files/s]


Downloading data:  33%|███▎      | 452/1382 [00:03<00:08, 114.35files/s]














Downloading data:  33%|███▎      | 452/1382 [00:03<00:07, 117.29files/s]






Downloading data:  32%|███▏      | 449/1382 [00:03<00:08, 115.72files/s]

Downloading data:  33%|███▎      | 458/1382 [00:03<00:07, 115.97files/s]








Downloading data:  32%|███▏      | 448/1382 [00:03<00:08, 116.04files/s]

















Downloading data:  32%|███▏      | 445/1382 [00:03<00:08, 116.14files/s]







Downloading data:  33%|███▎      | 462/1382 [00:03<00:08, 114.10files/s]













Downloading data:  33%|███▎      | 455/1382 [00:03<00:07, 117.09files/s]




Downloading data:  33%|███▎      | 457/1382 [00:03<00:07, 116.54files/s]



















 ... (more hidden) ...





Downloading data:  33%|███▎      | 459/1382 [00:03<00:07, 115.81files/s]
















Downloading data:  33%|███▎      | 455/1382 [00:03<00:08, 115.08files/s]



Downloading data:  33%|███▎      | 453/1382 [00:03<00:08, 115.16files/s]












Downloading data:  33%|███▎      | 455/1382 [00:03<00:07, 116.16files/s]











Downloading data:  33%|███▎      | 456/1382 [00:03<00:07, 115.94files/s]















Downloading data:  33%|███▎      | 462/1382 [00:03<00:07, 116.79files/s]


















Downloading data:  33%|███▎      | 455/1382 [00:03<00:07, 116.86files/s]










Downloading data:  33%|███▎      | 458/1382 [00:03<00:07, 115.90files/s]









Downloading data:  33%|███▎      | 457/1382 [00:03<00:08, 115.36files/s]














Downloading data:  34%|███▎      | 464/1382 [00:03<00:07, 116.78files/s]


Downloading data:  34%|███▎      | 464/1382 [00:03<00:08, 113.90files/s]






Downloading data:  33%|███▎      | 461/1382 [00:03<00:07, 115.49files/s]

Downloading data:  34%|███▍      | 470/1382 [00:03<00:07, 115.03files/s]








Downloading data:  33%|███▎      | 460/1382 [00:03<00:08, 115.04files/s]

















Downloading data:  33%|███▎      | 457/1382 [00:03<00:07, 115.66files/s]







Downloading data:  34%|███▍      | 474/1382 [00:03<00:07, 114.30files/s]













Downloading data:  34%|███▍      | 467/1382 [00:03<00:07, 115.44files/s]




Downloading data:  34%|███▍      | 469/1382 [00:03<00:07, 115.79files/s]



















 ... (more hidden) ...





Downloading data:  34%|███▍      | 471/1382 [00:03<00:07, 114.79files/s]
















Downloading data:  34%|███▍      | 467/1382 [00:03<00:08, 114.20files/s]



Downloading data:  34%|███▎      | 465/1382 [00:03<00:08, 114.27files/s]












Downloading data:  34%|███▍      | 467/1382 [00:03<00:07, 114.43files/s]















Downloading data:  34%|███▍      | 474/1382 [00:03<00:07, 115.82files/s]











Downloading data:  34%|███▍      | 468/1382 [00:03<00:07, 115.13files/s]


















Downloading data:  34%|███▍      | 467/1382 [00:03<00:07, 116.06files/s]










Downloading data:  34%|███▍      | 470/1382 [00:03<00:07, 114.87files/s]














Downloading data:  34%|███▍      | 476/1382 [00:03<00:07, 115.61files/s]









Downloading data:  34%|███▍      | 469/1382 [00:03<00:08, 113.70files/s]


Downloading data:  34%|███▍      | 476/1382 [00:03<00:08, 111.33files/s]






Downloading data:  34%|███▍      | 473/1382 [00:03<00:08, 113.49files/s]

Downloading data:  35%|███▍      | 482/1382 [00:03<00:07, 113.64files/s]








Downloading data:  34%|███▍      | 472/1382 [00:03<00:07, 113.79files/s]

















Downloading data:  34%|███▍      | 469/1382 [00:03<00:08, 114.10files/s]







Downloading data:  35%|███▌      | 486/1382 [00:03<00:07, 113.72files/s]













Downloading data:  35%|███▍      | 479/1382 [00:03<00:07, 115.38files/s]



















 ... (more hidden) ...




Downloading data:  35%|███▍      | 481/1382 [00:04<00:07, 113.92files/s]





Downloading data:  35%|███▍      | 483/1382 [00:04<00:07, 114.37files/s]
















Downloading data:  35%|███▍      | 479/1382 [00:04<00:07, 115.04files/s]



Downloading data:  35%|███▍      | 477/1382 [00:04<00:07, 113.99files/s]












Downloading data:  35%|███▍      | 479/1382 [00:04<00:07, 114.91files/s]















Downloading data:  35%|███▌      | 486/1382 [00:04<00:07, 114.75files/s]











Downloading data:  35%|███▍      | 480/1382 [00:04<00:07, 113.10files/s]


















Downloading data:  35%|███▍      | 479/1382 [00:04<00:07, 114.98files/s]










Downloading data:  35%|███▍      | 482/1382 [00:04<00:07, 114.06files/s]














Downloading data:  35%|███▌      | 488/1382 [00:04<00:07, 114.56files/s]









Downloading data:  35%|███▍      | 481/1382 [00:04<00:07, 112.87files/s]






Downloading data:  35%|███▌      | 485/1382 [00:04<00:07, 113.01files/s]


Downloading data:  35%|███▌      | 488/1382 [00:04<00:08, 111.45files/s]

Downloading data:  36%|███▌      | 494/1382 [00:04<00:07, 112.27files/s]








Downloading data:  35%|███▌      | 484/1382 [00:04<00:07, 112.26files/s]

















Downloading data:  35%|███▍      | 481/1382 [00:04<00:08, 112.39files/s]







Downloading data:  36%|███▌      | 498/1382 [00:04<00:07, 111.70files/s]













Downloading data:  36%|███▌      | 491/1382 [00:04<00:07, 112.85files/s]



















 ... (more hidden) ...




Downloading data:  36%|███▌      | 493/1382 [00:04<00:07, 111.40files/s]





Downloading data:  36%|███▌      | 495/1382 [00:04<00:08, 110.71files/s]
















Downloading data:  36%|███▌      | 491/1382 [00:04<00:08, 111.34files/s]



Downloading data:  35%|███▌      | 489/1382 [00:04<00:08, 111.46files/s]












Downloading data:  36%|███▌      | 491/1382 [00:04<00:07, 112.70files/s]















Downloading data:  36%|███▌      | 498/1382 [00:04<00:07, 111.01files/s]











Downloading data:  36%|███▌      | 492/1382 [00:04<00:08, 111.05files/s]


















Downloading data:  36%|███▌      | 491/1382 [00:04<00:07, 112.48files/s]










Downloading data:  36%|███▌      | 494/1382 [00:04<00:07, 111.73files/s]














Downloading data:  36%|███▌      | 500/1382 [00:04<00:07, 111.73files/s]









Downloading data:  36%|███▌      | 493/1382 [00:04<00:08, 110.58files/s]






Downloading data:  36%|███▌      | 497/1382 [00:04<00:07, 111.02files/s]


Downloading data:  36%|███▌      | 500/1382 [00:04<00:08, 109.38files/s]

Downloading data:  37%|███▋      | 506/1382 [00:04<00:08, 109.40files/s]








Downloading data:  36%|███▌      | 496/1382 [00:04<00:08, 109.92files/s]

















Downloading data:  36%|███▌      | 493/1382 [00:04<00:08, 110.62files/s]













Downloading data:  36%|███▋      | 503/1382 [00:04<00:07, 111.12files/s]







Downloading data:  37%|███▋      | 510/1382 [00:04<00:07, 109.81files/s]



















 ... (more hidden) ...




Downloading data:  37%|███▋      | 505/1382 [00:04<00:07, 109.70files/s]





Downloading data:  37%|███▋      | 507/1382 [00:04<00:07, 110.89files/s]
















Downloading data:  36%|███▋      | 503/1382 [00:04<00:07, 111.71files/s]












Downloading data:  36%|███▋      | 503/1382 [00:04<00:07, 111.48files/s]



Downloading data:  36%|███▋      | 501/1382 [00:04<00:08, 109.53files/s]















Downloading data:  37%|███▋      | 510/1382 [00:04<00:07, 111.42files/s]











Downloading data:  36%|███▋      | 504/1382 [00:04<00:07, 110.58files/s]


















Downloading data:  36%|███▋      | 503/1382 [00:04<00:07, 111.25files/s]










Downloading data:  37%|███▋      | 506/1382 [00:04<00:07, 111.30files/s]














Downloading data:  37%|███▋      | 512/1382 [00:04<00:07, 111.06files/s]


Downloading data:  37%|███▋      | 511/1382 [00:04<00:07, 109.39files/s]









Downloading data:  37%|███▋      | 505/1382 [00:04<00:07, 109.89files/s]






Downloading data:  37%|███▋      | 509/1382 [00:04<00:07, 110.54files/s]

Downloading data:  37%|███▋      | 518/1382 [00:04<00:07, 110.40files/s]








Downloading data:  37%|███▋      | 508/1382 [00:04<00:07, 110.98files/s]

















Downloading data:  37%|███▋      | 505/1382 [00:04<00:07, 110.78files/s]







Downloading data:  38%|███▊      | 521/1382 [00:04<00:07, 109.64files/s]













Downloading data:  37%|███▋      | 515/1382 [00:04<00:07, 111.04files/s]



















 ... (more hidden) ...




Downloading data:  37%|███▋      | 517/1382 [00:04<00:07, 110.36files/s]





Downloading data:  38%|███▊      | 519/1382 [00:04<00:07, 110.11files/s]
















Downloading data:  37%|███▋      | 515/1382 [00:04<00:07, 111.61files/s]



Downloading data:  37%|███▋      | 512/1382 [00:04<00:07, 109.28files/s]












Downloading data:  37%|███▋      | 515/1382 [00:04<00:07, 111.55files/s]















Downloading data:  38%|███▊      | 522/1382 [00:04<00:07, 110.86files/s]


















Downloading data:  37%|███▋      | 515/1382 [00:04<00:07, 111.94files/s]











Downloading data:  37%|███▋      | 516/1382 [00:04<00:07, 110.61files/s]


Downloading data:  38%|███▊      | 522/1382 [00:04<00:07, 109.13files/s]










Downloading data:  37%|███▋      | 518/1382 [00:04<00:07, 111.34files/s]









Downloading data:  37%|███▋      | 516/1382 [00:04<00:07, 109.90files/s]














Downloading data:  38%|███▊      | 524/1382 [00:04<00:07, 110.57files/s]






Downloading data:  38%|███▊      | 521/1382 [00:04<00:07, 110.01files/s]

Downloading data:  38%|███▊      | 530/1382 [00:04<00:07, 110.01files/s]








Downloading data:  38%|███▊      | 520/1382 [00:04<00:07, 110.14files/s]

















Downloading data:  37%|███▋      | 517/1382 [00:04<00:07, 110.69files/s]







Downloading data:  38%|███▊      | 532/1382 [00:04<00:07, 109.73files/s]













Downloading data:  38%|███▊      | 527/1382 [00:04<00:08, 106.47files/s]



Downloading data:  38%|███▊      | 523/1382 [00:04<00:07, 108.26files/s]




Downloading data:  38%|███▊      | 529/1382 [00:04<00:07, 107.65files/s]



















 ... (more hidden) ...





Downloading data:  38%|███▊      | 531/1382 [00:04<00:07, 107.02files/s]
















Downloading data:  38%|███▊      | 527/1382 [00:04<00:07, 108.37files/s]












Downloading data:  38%|███▊      | 527/1382 [00:04<00:07, 108.31files/s]


Downloading data:  39%|███▊      | 533/1382 [00:04<00:07, 106.16files/s]















Downloading data:  39%|███▊      | 534/1382 [00:04<00:07, 107.49files/s]











Downloading data:  38%|███▊      | 528/1382 [00:04<00:07, 107.65files/s]









Downloading data:  38%|███▊      | 527/1382 [00:04<00:08, 106.30files/s]


















Downloading data:  38%|███▊      | 527/1382 [00:04<00:07, 107.85files/s]










Downloading data:  38%|███▊      | 530/1382 [00:04<00:07, 107.99files/s]














Downloading data:  39%|███▉      | 536/1382 [00:04<00:07, 107.01files/s]






Downloading data:  39%|███▊      | 533/1382 [00:04<00:07, 107.34files/s]

Downloading data:  39%|███▉      | 542/1382 [00:04<00:07, 106.18files/s]







Downloading data:  39%|███▉      | 543/1382 [00:04<00:07, 108.34files/s]








Downloading data:  38%|███▊      | 532/1382 [00:04<00:08, 106.15files/s]

















Downloading data:  38%|███▊      | 529/1382 [00:04<00:08, 105.97files/s]













Downloading data:  39%|███▉      | 538/1382 [00:04<00:08, 105.13files/s]



Downloading data:  39%|███▊      | 534/1382 [00:04<00:07, 108.13files/s]





Downloading data:  39%|███▉      | 542/1382 [00:04<00:07, 107.32files/s]




Downloading data:  39%|███▉      | 540/1382 [00:04<00:08, 105.16files/s]



















 ... (more hidden) ...












Downloading data:  39%|███▉      | 538/1382 [00:04<00:07, 108.70files/s]
















Downloading data:  39%|███▉      | 538/1382 [00:04<00:07, 105.91files/s]


Downloading data:  39%|███▉      | 544/1382 [00:04<00:07, 107.09files/s]















Downloading data:  39%|███▉      | 545/1382 [00:04<00:07, 107.74files/s]


















Downloading data:  39%|███▉      | 538/1382 [00:04<00:07, 105.90files/s]











Downloading data:  39%|███▉      | 539/1382 [00:04<00:07, 105.42files/s]










Downloading data:  39%|███▉      | 541/1382 [00:04<00:07, 107.71files/s]









Downloading data:  39%|███▉      | 538/1382 [00:04<00:08, 103.76files/s]














Downloading data:  40%|███▉      | 547/1382 [00:04<00:07, 105.32files/s]






Downloading data:  39%|███▉      | 544/1382 [00:04<00:07, 104.92files/s]

Downloading data:  40%|████      | 553/1382 [00:04<00:07, 105.15files/s]







Downloading data:  40%|████      | 554/1382 [00:04<00:07, 105.53files/s]








Downloading data:  39%|███▉      | 543/1382 [00:04<00:08, 104.55files/s]

















Downloading data:  39%|███▉      | 540/1382 [00:04<00:08, 104.71files/s]













Downloading data:  40%|███▉      | 549/1382 [00:04<00:07, 105.02files/s]



Downloading data:  39%|███▉      | 545/1382 [00:04<00:07, 108.19files/s]




Downloading data:  40%|███▉      | 551/1382 [00:04<00:07, 106.33files/s]





Downloading data:  40%|████      | 554/1382 [00:04<00:07, 109.02files/s]



















 ... (more hidden) ...












Downloading data:  40%|███▉      | 550/1382 [00:04<00:07, 109.61files/s]
















Downloading data:  40%|███▉      | 550/1382 [00:04<00:07, 107.87files/s]















Downloading data:  40%|████      | 557/1382 [00:04<00:07, 109.47files/s]


Downloading data:  40%|████      | 556/1382 [00:04<00:07, 108.09files/s]


















Downloading data:  40%|███▉      | 550/1382 [00:04<00:07, 108.14files/s]










Downloading data:  40%|████      | 553/1382 [00:04<00:07, 109.32files/s]











Downloading data:  40%|███▉      | 551/1382 [00:04<00:07, 107.57files/s]









Downloading data:  40%|███▉      | 550/1382 [00:04<00:07, 106.43files/s]














Downloading data:  40%|████      | 559/1382 [00:04<00:07, 108.17files/s]






Downloading data:  40%|████      | 556/1382 [00:04<00:07, 107.27files/s]

Downloading data:  41%|████      | 565/1382 [00:04<00:07, 107.84files/s]







Downloading data:  41%|████      | 566/1382 [00:04<00:07, 108.62files/s]








Downloading data:  40%|████      | 555/1382 [00:04<00:07, 108.31files/s]

















Downloading data:  40%|███▉      | 552/1382 [00:04<00:07, 107.95files/s]













Downloading data:  41%|████      | 561/1382 [00:04<00:07, 109.16files/s]



Downloading data:  40%|████      | 557/1382 [00:04<00:07, 110.10files/s]




Downloading data:  41%|████      | 563/1382 [00:04<00:07, 110.20files/s]





Downloading data:  41%|████      | 566/1382 [00:04<00:07, 110.86files/s]



















 ... (more hidden) ...












Downloading data:  41%|████      | 562/1382 [00:04<00:07, 112.34files/s]
















Downloading data:  41%|████      | 562/1382 [00:04<00:07, 111.12files/s]















Downloading data:  41%|████      | 569/1382 [00:04<00:07, 112.16files/s]


Downloading data:  41%|████      | 568/1382 [00:04<00:07, 110.36files/s]











Downloading data:  41%|████      | 563/1382 [00:04<00:07, 110.35files/s]










Downloading data:  41%|████      | 565/1382 [00:04<00:07, 111.37files/s]









Downloading data:  41%|████      | 562/1382 [00:04<00:07, 110.05files/s]


















Downloading data:  41%|████      | 563/1382 [00:04<00:07, 112.39files/s]














Downloading data:  41%|████▏     | 571/1382 [00:04<00:07, 111.03files/s]






Downloading data:  41%|████      | 568/1382 [00:04<00:07, 110.62files/s]

Downloading data:  42%|████▏     | 577/1382 [00:04<00:07, 110.57files/s]







Downloading data:  42%|████▏     | 578/1382 [00:04<00:07, 111.65files/s]








Downloading data:  41%|████      | 567/1382 [00:04<00:07, 110.50files/s]

















Downloading data:  41%|████      | 564/1382 [00:04<00:07, 111.17files/s]













Downloading data:  41%|████▏     | 573/1382 [00:04<00:07, 111.36files/s]



Downloading data:  41%|████      | 569/1382 [00:04<00:07, 112.55files/s]




Downloading data:  42%|████▏     | 575/1382 [00:04<00:07, 111.71files/s]





Downloading data:  42%|████▏     | 578/1382 [00:04<00:07, 112.73files/s]



















 ... (more hidden) ...












Downloading data:  42%|████▏     | 574/1382 [00:04<00:07, 114.54files/s]
















Downloading data:  42%|████▏     | 574/1382 [00:04<00:07, 113.19files/s]















Downloading data:  42%|████▏     | 581/1382 [00:04<00:07, 114.24files/s]


Downloading data:  42%|████▏     | 580/1382 [00:04<00:07, 112.32files/s]









Downloading data:  42%|████▏     | 574/1382 [00:04<00:07, 112.31files/s]


















Downloading data:  42%|████▏     | 575/1382 [00:04<00:07, 114.29files/s]











Downloading data:  42%|████▏     | 576/1382 [00:04<00:07, 112.81files/s]










Downloading data:  42%|████▏     | 578/1382 [00:04<00:07, 113.69files/s]














Downloading data:  42%|████▏     | 584/1382 [00:04<00:07, 113.82files/s]






Downloading data:  42%|████▏     | 580/1382 [00:04<00:07, 112.05files/s]

Downloading data:  43%|████▎     | 589/1382 [00:04<00:07, 111.88files/s]







Downloading data:  43%|████▎     | 590/1382 [00:04<00:06, 113.58files/s]








Downloading data:  42%|████▏     | 579/1382 [00:04<00:07, 112.86files/s]
Downloading data: 100%|██████████| 1382/1382 [00:04<00:00, 286.57files/s]


















Downloading data:  42%|████▏     | 576/1382 [00:04<00:07, 113.67files/s]













Downloading data:  42%|████▏     | 585/1382 [00:04<00:07, 113.69files/s]



Downloading data:  42%|████▏     | 581/1382 [00:04<00:07, 113.92files/s]




Downloading data:  42%|████▏     | 587/1382 [00:04<00:07, 113.13files/s]





Downloading data:  43%|████▎     | 590/1382 [00:04<00:06, 114.57files/s]












Downloading data:  42%|████▏     | 586/1382 [00:04<00:06, 114.98files/s]
















Downloading data:  42%|████▏     | 586/1382 [00:04<00:06, 114.79files/s]



















 ... (more hidden) ...















Downloading data:  43%|████▎     | 593/1382 [00:04<00:06, 114.86files/s]


Downloading data:  43%|████▎     | 592/1382 [00:05<00:07, 112.10files/s]









Downloading data:  42%|████▏     | 586/1382 [00:04<00:07, 113.21files/s]


















Downloading data:  42%|████▏     | 587/1382 [00:04<00:06, 114.22files/s]











Downloading data:  43%|████▎     | 588/1382 [00:05<00:07, 113.02files/s]










Downloading data:  43%|████▎     | 590/1382 [00:05<00:06, 113.31files/s]














Downloading data:  43%|████▎     | 596/1382 [00:05<00:06, 113.90files/s]






Downloading data:  43%|████▎     | 592/1382 [00:05<00:06, 113.64files/s]

Downloading data:  43%|████▎     | 601/1382 [00:05<00:06, 113.51files/s]







Downloading data:  44%|████▎     | 602/1382 [00:05<00:06, 113.88files/s]








Downloading data:  43%|████▎     | 591/1382 [00:05<00:06, 113.79files/s]

















Downloading data:  43%|████▎     | 588/1382 [00:05<00:06, 114.35files/s]













Downloading data:  43%|████▎     | 597/1382 [00:05<00:06, 114.25files/s]



Downloading data:  43%|████▎     | 593/1382 [00:05<00:06, 112.95files/s]




Downloading data:  43%|████▎     | 599/1382 [00:05<00:06, 113.33files/s]





Downloading data:  44%|████▎     | 602/1382 [00:05<00:06, 115.04files/s]












Downloading data:  43%|████▎     | 598/1382 [00:05<00:06, 115.28files/s]
















Downloading data:  43%|████▎     | 598/1382 [00:05<00:06, 115.80files/s]



















 ... (more hidden) ...















Downloading data:  44%|████▍     | 605/1382 [00:05<00:06, 115.98files/s]


Downloading data:  44%|████▎     | 604/1382 [00:05<00:06, 113.59files/s]









Downloading data:  43%|████▎     | 598/1382 [00:05<00:06, 115.10files/s]


















Downloading data:  43%|████▎     | 599/1382 [00:05<00:06, 115.03files/s]











Downloading data:  43%|████▎     | 600/1382 [00:05<00:06, 114.53files/s]










Downloading data:  44%|████▎     | 602/1382 [00:05<00:06, 115.13files/s]














Downloading data:  44%|████▍     | 608/1382 [00:05<00:06, 115.08files/s]






Downloading data:  44%|████▎     | 604/1382 [00:05<00:06, 114.56files/s]

Downloading data:  44%|████▍     | 613/1382 [00:05<00:06, 114.84files/s]







Downloading data:  44%|████▍     | 614/1382 [00:05<00:06, 114.89files/s]








Downloading data:  44%|████▎     | 603/1382 [00:05<00:06, 114.08files/s]

















Downloading data:  43%|████▎     | 600/1382 [00:05<00:06, 115.83files/s]













Downloading data:  44%|████▍     | 610/1382 [00:05<00:06, 116.68files/s]



Downloading data:  44%|████▍     | 606/1382 [00:05<00:06, 115.44files/s]












Downloading data:  44%|████▍     | 610/1382 [00:05<00:06, 116.61files/s]




Downloading data:  44%|████▍     | 612/1382 [00:05<00:06, 115.75files/s]





Downloading data:  45%|████▍     | 615/1382 [00:05<00:06, 117.02files/s]
















Downloading data:  44%|████▍     | 610/1382 [00:05<00:06, 116.70files/s]



















 ... (more hidden) ...















Downloading data:  45%|████▍     | 618/1382 [00:05<00:06, 116.75files/s]


Downloading data:  45%|████▍     | 616/1382 [00:05<00:06, 115.07files/s]









Downloading data:  44%|████▍     | 610/1382 [00:05<00:06, 112.31files/s]










Downloading data:  44%|████▍     | 614/1382 [00:05<00:06, 115.24files/s]


















Downloading data:  44%|████▍     | 612/1382 [00:05<00:06, 116.20files/s]











Downloading data:  44%|████▍     | 613/1382 [00:05<00:06, 116.05files/s]














Downloading data:  45%|████▍     | 620/1382 [00:05<00:06, 116.34files/s]






Downloading data:  45%|████▍     | 616/1382 [00:05<00:06, 114.74files/s]

Downloading data:  45%|████▌     | 625/1382 [00:05<00:06, 114.63files/s]







Downloading data:  45%|████▌     | 626/1382 [00:05<00:06, 114.88files/s]








Downloading data:  45%|████▍     | 615/1382 [00:05<00:06, 114.68files/s]

















Downloading data:  44%|████▍     | 612/1382 [00:05<00:06, 114.64files/s]













Downloading data:  45%|████▌     | 622/1382 [00:05<00:06, 114.87files/s]



Downloading data:  45%|████▍     | 618/1382 [00:05<00:06, 112.96files/s]












Downloading data:  45%|████▌     | 622/1382 [00:05<00:06, 113.65files/s]





Downloading data:  45%|████▌     | 627/1382 [00:05<00:06, 113.95files/s]




Downloading data:  45%|████▌     | 624/1382 [00:05<00:06, 113.10files/s]
















Downloading data:  45%|████▌     | 622/1382 [00:05<00:06, 113.99files/s]



















 ... (more hidden) ...















Downloading data:  46%|████▌     | 630/1382 [00:05<00:06, 114.60files/s]


Downloading data:  45%|████▌     | 628/1382 [00:05<00:06, 111.92files/s]









Downloading data:  45%|████▌     | 622/1382 [00:05<00:06, 111.28files/s]










Downloading data:  45%|████▌     | 626/1382 [00:05<00:06, 113.30files/s]


















Downloading data:  45%|████▌     | 624/1382 [00:05<00:06, 113.91files/s]











Downloading data:  45%|████▌     | 625/1382 [00:05<00:06, 112.11files/s]














Downloading data:  46%|████▌     | 632/1382 [00:05<00:06, 112.69files/s]






Downloading data:  45%|████▌     | 628/1382 [00:05<00:06, 112.89files/s]

Downloading data:  46%|████▌     | 637/1382 [00:05<00:06, 112.43files/s]







Downloading data:  46%|████▌     | 638/1382 [00:05<00:06, 113.41files/s]








Downloading data:  45%|████▌     | 627/1382 [00:05<00:06, 112.47files/s]

















Downloading data:  45%|████▌     | 624/1382 [00:05<00:06, 113.70files/s]













Downloading data:  46%|████▌     | 634/1382 [00:05<00:06, 113.75files/s]



Downloading data:  46%|████▌     | 630/1382 [00:05<00:06, 111.65files/s]












Downloading data:  46%|████▌     | 634/1382 [00:05<00:06, 113.80files/s]





Downloading data:  46%|████▌     | 639/1382 [00:05<00:06, 114.06files/s]




Downloading data:  46%|████▌     | 636/1382 [00:05<00:06, 113.33files/s]
















Downloading data:  46%|████▌     | 634/1382 [00:05<00:06, 113.69files/s]



















 ... (more hidden) ...















Downloading data:  46%|████▋     | 642/1382 [00:05<00:06, 114.30files/s]


Downloading data:  46%|████▋     | 640/1382 [00:05<00:06, 113.33files/s]









Downloading data:  46%|████▌     | 634/1382 [00:05<00:06, 112.42files/s]










Downloading data:  46%|████▌     | 638/1382 [00:05<00:06, 113.36files/s]


















Downloading data:  46%|████▌     | 636/1382 [00:05<00:06, 113.56files/s]














Downloading data:  47%|████▋     | 644/1382 [00:05<00:06, 114.19files/s]











Downloading data:  46%|████▌     | 637/1382 [00:05<00:06, 113.54files/s]






Downloading data:  46%|████▋     | 640/1382 [00:05<00:06, 112.72files/s]

Downloading data:  47%|████▋     | 649/1382 [00:05<00:06, 112.87files/s]







Downloading data:  47%|████▋     | 650/1382 [00:05<00:06, 113.20files/s]








Downloading data:  46%|████▌     | 639/1382 [00:05<00:06, 112.96files/s]

















Downloading data:  46%|████▌     | 636/1382 [00:05<00:06, 113.86files/s]













Downloading data:  47%|████▋     | 646/1382 [00:05<00:06, 114.42files/s]



Downloading data:  46%|████▋     | 642/1382 [00:05<00:06, 113.34files/s]












Downloading data:  47%|████▋     | 646/1382 [00:05<00:06, 113.68files/s]





Downloading data:  47%|████▋     | 651/1382 [00:05<00:06, 113.85files/s]




Downloading data:  47%|████▋     | 648/1382 [00:05<00:06, 113.45files/s]



















 ... (more hidden) ...
















Downloading data:  47%|████▋     | 646/1382 [00:05<00:06, 112.13files/s]















Downloading data:  47%|████▋     | 654/1382 [00:05<00:06, 115.44files/s]


Downloading data:  47%|████▋     | 652/1382 [00:05<00:06, 114.22files/s]










Downloading data:  47%|████▋     | 650/1382 [00:05<00:06, 115.08files/s]









Downloading data:  47%|████▋     | 646/1382 [00:05<00:06, 113.27files/s]


















Downloading data:  47%|████▋     | 648/1382 [00:05<00:06, 114.89files/s]














Downloading data:  47%|████▋     | 656/1382 [00:05<00:06, 115.03files/s]











Downloading data:  47%|████▋     | 649/1382 [00:05<00:06, 114.75files/s]






Downloading data:  47%|████▋     | 652/1382 [00:05<00:06, 114.16files/s]

Downloading data:  48%|████▊     | 661/1382 [00:05<00:06, 114.12files/s]







Downloading data:  48%|████▊     | 662/1382 [00:05<00:06, 114.71files/s]

















Downloading data:  47%|████▋     | 648/1382 [00:05<00:06, 115.58files/s]








Downloading data:  47%|████▋     | 651/1382 [00:05<00:06, 114.77files/s]













Downloading data:  48%|████▊     | 658/1382 [00:05<00:06, 115.34files/s]




Downloading data:  48%|████▊     | 660/1382 [00:05<00:06, 114.39files/s]



















 ... (more hidden) ...



Downloading data:  47%|████▋     | 655/1382 [00:05<00:06, 115.01files/s]





Downloading data:  48%|████▊     | 664/1382 [00:05<00:06, 115.04files/s]












Downloading data:  48%|████▊     | 659/1382 [00:05<00:06, 114.91files/s]
















Downloading data:  48%|████▊     | 658/1382 [00:05<00:06, 112.87files/s]















Downloading data:  48%|████▊     | 666/1382 [00:05<00:06, 115.80files/s]


Downloading data:  48%|████▊     | 664/1382 [00:05<00:06, 113.72files/s]










Downloading data:  48%|████▊     | 662/1382 [00:05<00:06, 115.34files/s]


















Downloading data:  48%|████▊     | 660/1382 [00:05<00:06, 115.54files/s]









Downloading data:  48%|████▊     | 658/1382 [00:05<00:06, 113.90files/s]














Downloading data:  48%|████▊     | 668/1382 [00:05<00:06, 116.00files/s]











Downloading data:  48%|████▊     | 661/1382 [00:05<00:06, 115.44files/s]






Downloading data:  48%|████▊     | 664/1382 [00:05<00:06, 113.91files/s]

Downloading data:  49%|████▊     | 673/1382 [00:05<00:06, 114.58files/s]







Downloading data:  49%|████▉     | 674/1382 [00:05<00:06, 113.79files/s]

















Downloading data:  48%|████▊     | 660/1382 [00:05<00:06, 115.60files/s]








Downloading data:  48%|████▊     | 663/1382 [00:05<00:06, 114.81files/s]













Downloading data:  48%|████▊     | 670/1382 [00:05<00:06, 115.85files/s]



















 ... (more hidden) ...




Downloading data:  49%|████▊     | 673/1382 [00:05<00:06, 118.00files/s]



Downloading data:  48%|████▊     | 668/1382 [00:05<00:06, 118.89files/s]
















Downloading data:  49%|████▊     | 671/1382 [00:05<00:06, 117.15files/s]





Downloading data:  49%|████▉     | 678/1382 [00:05<00:05, 121.41files/s]












Downloading data:  49%|████▊     | 673/1382 [00:05<00:05, 121.09files/s]















Downloading data:  49%|████▉     | 680/1382 [00:05<00:05, 120.35files/s]


Downloading data:  49%|████▉     | 678/1382 [00:05<00:05, 119.52files/s]


















Downloading data:  49%|████▉     | 674/1382 [00:05<00:05, 121.59files/s]










Downloading data:  49%|████▉     | 676/1382 [00:05<00:05, 120.29files/s]









Downloading data:  49%|████▊     | 672/1382 [00:05<00:05, 119.56files/s]














Downloading data:  49%|████▉     | 682/1382 [00:05<00:05, 121.74files/s]











Downloading data:  49%|████▉     | 675/1382 [00:05<00:05, 121.40files/s]

Downloading data:  50%|████▉     | 687/1382 [00:05<00:05, 120.50files/s]






Downloading data:  49%|████▉     | 678/1382 [00:05<00:05, 119.23files/s]







Downloading data:  50%|████▉     | 688/1382 [00:05<00:05, 121.27files/s]

















Downloading data:  49%|████▉     | 674/1382 [00:05<00:05, 121.52files/s]








Downloading data:  49%|████▉     | 677/1382 [00:05<00:05, 119.47files/s]













Downloading data:  49%|████▉     | 683/1382 [00:05<00:05, 119.18files/s]



Downloading data:  49%|████▉     | 680/1382 [00:05<00:05, 118.44files/s]




Downloading data:  50%|████▉     | 685/1382 [00:05<00:05, 117.48files/s]



















 ... (more hidden) ...
















Downloading data:  49%|████▉     | 683/1382 [00:05<00:06, 115.64files/s]





Downloading data:  50%|█████     | 691/1382 [00:05<00:05, 120.18files/s]












Downloading data:  50%|████▉     | 686/1382 [00:05<00:05, 118.77files/s]















Downloading data:  50%|█████     | 693/1382 [00:05<00:05, 120.30files/s]


Downloading data:  50%|████▉     | 690/1382 [00:05<00:05, 117.75files/s]









Downloading data:  49%|████▉     | 684/1382 [00:05<00:05, 118.38files/s]


















Downloading data:  50%|████▉     | 687/1382 [00:05<00:05, 119.83files/s]










Downloading data:  50%|████▉     | 689/1382 [00:05<00:05, 119.72files/s]











Downloading data:  50%|████▉     | 688/1382 [00:05<00:05, 120.08files/s]














Downloading data:  50%|█████     | 695/1382 [00:05<00:05, 119.41files/s]






Downloading data:  50%|█████     | 691/1382 [00:05<00:05, 119.39files/s]

Downloading data:  51%|█████     | 700/1382 [00:05<00:05, 118.32files/s]







Downloading data:  51%|█████     | 701/1382 [00:05<00:05, 117.40files/s]








Downloading data:  50%|████▉     | 690/1382 [00:05<00:05, 121.18files/s]

















Downloading data:  50%|████▉     | 687/1382 [00:05<00:05, 119.71files/s]













Downloading data:  50%|█████     | 695/1382 [00:05<00:05, 119.22files/s]



Downloading data:  50%|█████     | 692/1382 [00:05<00:05, 116.51files/s]




Downloading data:  50%|█████     | 697/1382 [00:05<00:05, 115.21files/s]



















 ... (more hidden) ...
















Downloading data:  50%|█████     | 696/1382 [00:05<00:05, 117.62files/s]












Downloading data:  51%|█████     | 698/1382 [00:05<00:05, 118.28files/s]





Downloading data:  51%|█████     | 704/1382 [00:05<00:05, 120.17files/s]















Downloading data:  51%|█████     | 706/1382 [00:05<00:05, 118.95files/s]


Downloading data:  51%|█████     | 702/1382 [00:05<00:05, 116.22files/s]









Downloading data:  50%|█████     | 696/1382 [00:05<00:05, 117.49files/s]


















Downloading data:  51%|█████     | 700/1382 [00:05<00:05, 119.76files/s]














Downloading data:  51%|█████     | 707/1382 [00:05<00:05, 119.13files/s]










Downloading data:  51%|█████     | 701/1382 [00:05<00:05, 116.71files/s]











Downloading data:  51%|█████     | 701/1382 [00:05<00:05, 119.72files/s]






Downloading data:  51%|█████     | 703/1382 [00:05<00:05, 117.62files/s]

Downloading data:  52%|█████▏    | 712/1382 [00:05<00:05, 117.28files/s]

















Downloading data:  51%|█████     | 699/1382 [00:05<00:05, 119.78files/s]







Downloading data:  52%|█████▏    | 714/1382 [00:06<00:05, 117.81files/s]








Downloading data:  51%|█████     | 703/1382 [00:05<00:05, 120.01files/s]













Downloading data:  51%|█████     | 707/1382 [00:05<00:05, 118.81files/s]




Downloading data:  51%|█████▏    | 709/1382 [00:06<00:05, 116.42files/s]



Downloading data:  51%|█████     | 704/1382 [00:06<00:05, 116.67files/s]



















 ... (more hidden) ...
















Downloading data:  51%|█████     | 708/1382 [00:06<00:05, 118.02files/s]












Downloading data:  51%|█████▏    | 710/1382 [00:06<00:05, 115.68files/s]





Downloading data:  52%|█████▏    | 717/1382 [00:06<00:05, 119.41files/s]















Downloading data:  52%|█████▏    | 718/1382 [00:06<00:05, 118.23files/s]


Downloading data:  52%|█████▏    | 714/1382 [00:06<00:05, 116.09files/s]









Downloading data:  51%|█████     | 708/1382 [00:06<00:05, 116.21files/s]














Downloading data:  52%|█████▏    | 719/1382 [00:06<00:05, 119.36files/s]










Downloading data:  52%|█████▏    | 713/1382 [00:06<00:05, 116.81files/s]


















Downloading data:  52%|█████▏    | 713/1382 [00:06<00:05, 120.52files/s]











Downloading data:  52%|█████▏    | 714/1382 [00:06<00:05, 120.04files/s]






Downloading data:  52%|█████▏    | 715/1382 [00:06<00:05, 117.11files/s]

Downloading data:  52%|█████▏    | 724/1382 [00:06<00:05, 117.15files/s]

















Downloading data:  51%|█████▏    | 711/1382 [00:06<00:05, 118.31files/s]













Downloading data:  52%|█████▏    | 719/1382 [00:06<00:05, 118.67files/s]







Downloading data:  53%|█████▎    | 727/1382 [00:06<00:05, 118.41files/s]








Downloading data:  52%|█████▏    | 716/1382 [00:06<00:05, 119.34files/s]




Downloading data:  52%|█████▏    | 721/1382 [00:06<00:05, 117.09files/s]



Downloading data:  52%|█████▏    | 716/1382 [00:06<00:05, 116.80files/s]



















 ... (more hidden) ...
















Downloading data:  52%|█████▏    | 720/1382 [00:06<00:05, 118.01files/s]















Downloading data:  53%|█████▎    | 730/1382 [00:06<00:05, 118.64files/s]












Downloading data:  52%|█████▏    | 722/1382 [00:06<00:05, 114.96files/s]





Downloading data:  53%|█████▎    | 729/1382 [00:06<00:05, 118.39files/s]


Downloading data:  53%|█████▎    | 726/1382 [00:06<00:05, 115.94files/s]









Downloading data:  52%|█████▏    | 720/1382 [00:06<00:05, 115.48files/s]










Downloading data:  52%|█████▏    | 725/1382 [00:06<00:05, 116.95files/s]














Downloading data:  53%|█████▎    | 731/1382 [00:06<00:05, 117.75files/s]


















Downloading data:  53%|█████▎    | 726/1382 [00:06<00:05, 118.85files/s]






Downloading data:  53%|█████▎    | 727/1382 [00:06<00:05, 116.94files/s]

Downloading data:  53%|█████▎    | 736/1382 [00:06<00:05, 117.13files/s]











Downloading data:  53%|█████▎    | 727/1382 [00:06<00:05, 117.80files/s]

















Downloading data:  52%|█████▏    | 723/1382 [00:06<00:05, 117.94files/s]













Downloading data:  53%|█████▎    | 731/1382 [00:06<00:05, 117.51files/s]







Downloading data:  53%|█████▎    | 739/1382 [00:06<00:05, 117.75files/s]








Downloading data:  53%|█████▎    | 728/1382 [00:06<00:05, 118.02files/s]




Downloading data:  53%|█████▎    | 733/1382 [00:06<00:05, 116.84files/s]



Downloading data:  53%|█████▎    | 728/1382 [00:06<00:05, 116.68files/s]



















 ... (more hidden) ...
















Downloading data:  53%|█████▎    | 732/1382 [00:06<00:05, 117.85files/s]















Downloading data:  54%|█████▎    | 742/1382 [00:06<00:05, 118.55files/s]





Downloading data:  54%|█████▎    | 741/1382 [00:06<00:05, 118.37files/s]


Downloading data:  53%|█████▎    | 738/1382 [00:06<00:05, 116.61files/s]












Downloading data:  53%|█████▎    | 735/1382 [00:06<00:05, 117.10files/s]









Downloading data:  53%|█████▎    | 733/1382 [00:06<00:05, 117.87files/s]










Downloading data:  53%|█████▎    | 738/1382 [00:06<00:05, 119.77files/s]














Downloading data:  54%|█████▍    | 744/1382 [00:06<00:05, 119.77files/s]


















Downloading data:  53%|█████▎    | 739/1382 [00:06<00:05, 121.00files/s]






Downloading data:  54%|█████▎    | 740/1382 [00:06<00:05, 119.35files/s]

Downloading data:  54%|█████▍    | 749/1382 [00:06<00:05, 119.74files/s]

















Downloading data:  53%|█████▎    | 736/1382 [00:06<00:05, 120.31files/s]













Downloading data:  54%|█████▍    | 744/1382 [00:06<00:05, 119.21files/s]







Downloading data:  54%|█████▍    | 752/1382 [00:06<00:05, 120.64files/s]








Downloading data:  54%|█████▎    | 741/1382 [00:06<00:05, 119.81files/s]











Downloading data:  53%|█████▎    | 739/1382 [00:06<00:05, 110.64files/s]




Downloading data:  54%|█████▍    | 745/1382 [00:06<00:05, 117.77files/s]



Downloading data:  54%|█████▎    | 741/1382 [00:06<00:05, 117.39files/s]



















 ... (more hidden) ...
















Downloading data:  54%|█████▍    | 745/1382 [00:06<00:05, 118.64files/s]















Downloading data:  55%|█████▍    | 754/1382 [00:06<00:05, 118.20files/s]





Downloading data:  54%|█████▍    | 753/1382 [00:06<00:05, 118.07files/s]


Downloading data:  54%|█████▍    | 750/1382 [00:06<00:05, 117.30files/s]












Downloading data:  54%|█████▍    | 747/1382 [00:06<00:05, 116.42files/s]









Downloading data:  54%|█████▍    | 745/1382 [00:06<00:05, 116.32files/s]










Downloading data:  54%|█████▍    | 750/1382 [00:06<00:05, 117.18files/s]














Downloading data:  55%|█████▍    | 756/1382 [00:06<00:05, 117.51files/s]

Downloading data:  55%|█████▌    | 761/1382 [00:06<00:05, 117.72files/s]






Downloading data:  54%|█████▍    | 752/1382 [00:06<00:05, 116.62files/s]


















Downloading data:  54%|█████▍    | 752/1382 [00:06<00:05, 118.23files/s]

















Downloading data:  54%|█████▍    | 749/1382 [00:06<00:05, 117.84files/s]













Downloading data:  55%|█████▍    | 756/1382 [00:06<00:05, 117.17files/s]








Downloading data:  54%|█████▍    | 753/1382 [00:06<00:05, 118.12files/s]







Downloading data:  55%|█████▌    | 765/1382 [00:06<00:05, 118.48files/s]











Downloading data:  54%|█████▍    | 751/1382 [00:06<00:05, 111.34files/s]




Downloading data:  55%|█████▍    | 757/1382 [00:06<00:05, 117.16files/s]



Downloading data:  54%|█████▍    | 753/1382 [00:06<00:05, 117.28files/s]



















 ... (more hidden) ...
















Downloading data:  55%|█████▍    | 758/1382 [00:06<00:05, 119.21files/s]





Downloading data:  55%|█████▌    | 765/1382 [00:06<00:05, 117.56files/s]


Downloading data:  55%|█████▌    | 762/1382 [00:06<00:05, 117.81files/s]















Downloading data:  55%|█████▌    | 767/1382 [00:06<00:05, 118.99files/s]












Downloading data:  55%|█████▍    | 760/1382 [00:06<00:05, 117.55files/s]









Downloading data:  55%|█████▍    | 757/1382 [00:06<00:05, 117.31files/s]










Downloading data:  55%|█████▌    | 762/1382 [00:06<00:05, 117.57files/s]














Downloading data:  56%|█████▌    | 768/1382 [00:06<00:05, 117.97files/s]

Downloading data:  56%|█████▌    | 774/1382 [00:06<00:05, 118.65files/s]






Downloading data:  55%|█████▌    | 765/1382 [00:06<00:05, 117.86files/s]


















Downloading data:  55%|█████▌    | 765/1382 [00:06<00:05, 119.23files/s]








Downloading data:  55%|█████▌    | 765/1382 [00:06<00:05, 118.35files/s]

















Downloading data:  55%|█████▌    | 762/1382 [00:06<00:05, 118.72files/s]













Downloading data:  56%|█████▌    | 769/1382 [00:06<00:05, 118.15files/s]







Downloading data:  56%|█████▋    | 778/1382 [00:06<00:05, 118.88files/s]











Downloading data:  55%|█████▌    | 764/1382 [00:06<00:05, 115.09files/s]




Downloading data:  56%|█████▌    | 769/1382 [00:06<00:05, 117.55files/s]



Downloading data:  55%|█████▌    | 765/1382 [00:06<00:05, 117.04files/s]



















 ... (more hidden) ...
















Downloading data:  56%|█████▌    | 770/1382 [00:06<00:05, 119.24files/s]





Downloading data:  56%|█████▌    | 777/1382 [00:06<00:05, 118.01files/s]


Downloading data:  56%|█████▌    | 774/1382 [00:06<00:05, 117.25files/s]















Downloading data:  56%|█████▋    | 780/1382 [00:06<00:05, 119.80files/s]












Downloading data:  56%|█████▌    | 773/1382 [00:06<00:05, 119.60files/s]









Downloading data:  56%|█████▌    | 769/1382 [00:06<00:05, 117.72files/s]










Downloading data:  56%|█████▌    | 775/1382 [00:06<00:05, 119.25files/s]














Downloading data:  57%|█████▋    | 781/1382 [00:06<00:05, 119.41files/s]


















Downloading data:  56%|█████▌    | 777/1382 [00:06<00:05, 119.39files/s]

Downloading data:  57%|█████▋    | 787/1382 [00:06<00:04, 119.06files/s]






Downloading data:  56%|█████▋    | 778/1382 [00:06<00:05, 118.43files/s]








Downloading data:  56%|█████▋    | 778/1382 [00:06<00:05, 119.48files/s]













Downloading data:  57%|█████▋    | 782/1382 [00:06<00:05, 119.44files/s]







Downloading data:  57%|█████▋    | 790/1382 [00:06<00:04, 119.15files/s]

















Downloading data:  56%|█████▌    | 774/1382 [00:06<00:05, 115.61files/s]




Downloading data:  57%|█████▋    | 781/1382 [00:06<00:05, 117.46files/s]











Downloading data:  56%|█████▌    | 777/1382 [00:06<00:05, 116.77files/s]



Downloading data:  56%|█████▋    | 778/1382 [00:06<00:05, 118.73files/s]



















 ... (more hidden) ...
















Downloading data:  57%|█████▋    | 783/1382 [00:06<00:04, 120.23files/s]





Downloading data:  57%|█████▋    | 790/1382 [00:06<00:05, 118.02files/s]


Downloading data:  57%|█████▋    | 787/1382 [00:06<00:05, 118.39files/s]















Downloading data:  57%|█████▋    | 792/1382 [00:06<00:04, 119.44files/s]












Downloading data:  57%|█████▋    | 785/1382 [00:06<00:05, 118.45files/s]









Downloading data:  57%|█████▋    | 782/1382 [00:06<00:05, 119.16files/s]










Downloading data:  57%|█████▋    | 787/1382 [00:06<00:05, 118.31files/s]














Downloading data:  57%|█████▋    | 793/1382 [00:06<00:04, 118.01files/s]


















Downloading data:  57%|█████▋    | 789/1382 [00:06<00:05, 118.29files/s]

Downloading data:  58%|█████▊    | 799/1382 [00:06<00:04, 118.41files/s]






Downloading data:  57%|█████▋    | 790/1382 [00:06<00:05, 116.66files/s]













Downloading data:  57%|█████▋    | 794/1382 [00:06<00:05, 117.53files/s]








Downloading data:  57%|█████▋    | 790/1382 [00:06<00:05, 117.28files/s]







Downloading data:  58%|█████▊    | 802/1382 [00:06<00:04, 117.00files/s]

















Downloading data:  57%|█████▋    | 786/1382 [00:06<00:05, 114.11files/s]




Downloading data:  57%|█████▋    | 793/1382 [00:06<00:05, 115.90files/s]











Downloading data:  57%|█████▋    | 789/1382 [00:06<00:05, 115.21files/s]



Downloading data:  57%|█████▋    | 790/1382 [00:06<00:05, 115.22files/s]



















 ... (more hidden) ...





Downloading data:  58%|█████▊    | 802/1382 [00:06<00:05, 115.19files/s]
















Downloading data:  58%|█████▊    | 796/1382 [00:06<00:05, 116.14files/s]


Downloading data:  58%|█████▊    | 799/1382 [00:06<00:05, 114.86files/s]















Downloading data:  58%|█████▊    | 804/1382 [00:06<00:05, 115.38files/s]












Downloading data:  58%|█████▊    | 797/1382 [00:06<00:05, 114.73files/s]









Downloading data:  57%|█████▋    | 794/1382 [00:06<00:05, 114.67files/s]










Downloading data:  58%|█████▊    | 799/1382 [00:06<00:05, 113.95files/s]














Downloading data:  58%|█████▊    | 805/1382 [00:06<00:05, 113.94files/s]


















Downloading data:  58%|█████▊    | 801/1382 [00:06<00:05, 114.89files/s]

Downloading data:  59%|█████▊    | 811/1382 [00:06<00:05, 113.65files/s]






Downloading data:  58%|█████▊    | 802/1382 [00:06<00:05, 113.01files/s]













Downloading data:  58%|█████▊    | 806/1382 [00:06<00:05, 115.07files/s]








Downloading data:  58%|█████▊    | 802/1382 [00:06<00:05, 114.52files/s]







Downloading data:  59%|█████▉    | 814/1382 [00:06<00:04, 114.60files/s]

















Downloading data:  58%|█████▊    | 798/1382 [00:06<00:05, 111.62files/s]




Downloading data:  58%|█████▊    | 805/1382 [00:06<00:05, 113.93files/s]











Downloading data:  58%|█████▊    | 801/1382 [00:06<00:05, 113.84files/s]



Downloading data:  58%|█████▊    | 802/1382 [00:06<00:05, 113.03files/s]



















 ... (more hidden) ...





Downloading data:  59%|█████▉    | 814/1382 [00:06<00:04, 113.74files/s]
















Downloading data:  58%|█████▊    | 808/1382 [00:06<00:05, 114.44files/s]


Downloading data:  59%|█████▊    | 811/1382 [00:06<00:05, 112.81files/s]















Downloading data:  59%|█████▉    | 816/1382 [00:06<00:05, 112.88files/s]












Downloading data:  59%|█████▊    | 809/1382 [00:06<00:05, 112.72files/s]









Downloading data:  58%|█████▊    | 806/1382 [00:06<00:05, 112.92files/s]










Downloading data:  59%|█████▊    | 811/1382 [00:06<00:05, 112.07files/s]














Downloading data:  59%|█████▉    | 817/1382 [00:06<00:05, 112.04files/s]


















Downloading data:  59%|█████▉    | 813/1382 [00:06<00:05, 113.55files/s]

Downloading data:  60%|█████▉    | 823/1382 [00:06<00:05, 111.39files/s]






Downloading data:  59%|█████▉    | 814/1382 [00:06<00:05, 111.30files/s]













Downloading data:  59%|█████▉    | 818/1382 [00:06<00:05, 112.35files/s]








Downloading data:  59%|█████▉    | 814/1382 [00:06<00:05, 111.59files/s]







Downloading data:  60%|█████▉    | 826/1382 [00:06<00:04, 111.61files/s]

















Downloading data:  59%|█████▊    | 810/1382 [00:06<00:05, 109.81files/s]




Downloading data:  59%|█████▉    | 817/1382 [00:06<00:05, 111.55files/s]











Downloading data:  59%|█████▉    | 813/1382 [00:06<00:05, 111.28files/s]



Downloading data:  59%|█████▉    | 814/1382 [00:06<00:05, 110.51files/s]



















 ... (more hidden) ...





Downloading data:  60%|█████▉    | 826/1382 [00:07<00:04, 111.34files/s]
















Downloading data:  59%|█████▉    | 820/1382 [00:06<00:05, 111.92files/s]


Downloading data:  60%|█████▉    | 823/1382 [00:07<00:05, 110.67files/s]















Downloading data:  60%|█████▉    | 828/1382 [00:07<00:05, 110.68files/s]












Downloading data:  59%|█████▉    | 821/1382 [00:07<00:05, 110.73files/s]









Downloading data:  59%|█████▉    | 818/1382 [00:07<00:05, 110.91files/s]










Downloading data:  60%|█████▉    | 823/1382 [00:07<00:05, 110.23files/s]














Downloading data:  60%|█████▉    | 829/1382 [00:07<00:05, 110.24files/s]


















Downloading data:  60%|█████▉    | 825/1382 [00:07<00:05, 111.15files/s]

Downloading data:  60%|██████    | 835/1382 [00:07<00:04, 110.31files/s]






Downloading data:  60%|█████▉    | 826/1382 [00:07<00:05, 110.40files/s]













Downloading data:  60%|██████    | 830/1382 [00:07<00:04, 111.57files/s]








Downloading data:  60%|█████▉    | 826/1382 [00:07<00:05, 110.87files/s]







Downloading data:  61%|██████    | 838/1382 [00:07<00:04, 111.16files/s]

















Downloading data:  59%|█████▉    | 822/1382 [00:07<00:05, 109.94files/s]




Downloading data:  60%|█████▉    | 829/1382 [00:07<00:04, 110.72files/s]











Downloading data:  60%|█████▉    | 825/1382 [00:07<00:05, 110.24files/s]



Downloading data:  60%|█████▉    | 826/1382 [00:07<00:05, 109.52files/s]



















 ... (more hidden) ...
















Downloading data:  60%|██████    | 832/1382 [00:07<00:04, 111.37files/s]





Downloading data:  61%|██████    | 838/1382 [00:07<00:04, 110.84files/s]


Downloading data:  60%|██████    | 835/1382 [00:07<00:04, 110.50files/s]















Downloading data:  61%|██████    | 840/1382 [00:07<00:04, 110.13files/s]












Downloading data:  60%|██████    | 833/1382 [00:07<00:04, 110.44files/s]









Downloading data:  60%|██████    | 830/1382 [00:07<00:04, 110.84files/s]










Downloading data:  60%|██████    | 835/1382 [00:07<00:04, 110.20files/s]














Downloading data:  61%|██████    | 841/1382 [00:07<00:04, 110.08files/s]


















Downloading data:  61%|██████    | 837/1382 [00:07<00:04, 110.91files/s]

Downloading data:  61%|██████▏   | 847/1382 [00:07<00:04, 107.38files/s]






Downloading data:  61%|██████    | 838/1382 [00:07<00:05, 107.61files/s]













Downloading data:  61%|██████    | 842/1382 [00:07<00:04, 109.70files/s]








Downloading data:  61%|██████    | 838/1382 [00:07<00:04, 109.68files/s]

















Downloading data:  60%|██████    | 834/1382 [00:07<00:05, 108.09files/s]







Downloading data:  62%|██████▏   | 850/1382 [00:07<00:04, 107.11files/s]




Downloading data:  61%|██████    | 841/1382 [00:07<00:05, 108.10files/s]











Downloading data:  61%|██████    | 837/1382 [00:07<00:05, 107.61files/s]



Downloading data:  61%|██████    | 837/1382 [00:07<00:05, 105.77files/s]
















Downloading data:  61%|██████    | 844/1382 [00:07<00:04, 109.10files/s]



















 ... (more hidden) ...





Downloading data:  62%|██████▏   | 850/1382 [00:07<00:04, 106.93files/s]


Downloading data:  61%|██████▏   | 847/1382 [00:07<00:05, 105.99files/s]















Downloading data:  62%|██████▏   | 852/1382 [00:07<00:04, 106.46files/s]












Downloading data:  61%|██████    | 845/1382 [00:07<00:05, 107.10files/s]









Downloading data:  61%|██████    | 842/1382 [00:07<00:05, 106.38files/s]










Downloading data:  61%|██████▏   | 847/1382 [00:07<00:05, 106.55files/s]














Downloading data:  62%|██████▏   | 853/1382 [00:07<00:04, 106.45files/s]


















Downloading data:  61%|██████▏   | 849/1382 [00:07<00:04, 108.15files/s]








Downloading data:  61%|██████▏   | 849/1382 [00:07<00:04, 109.65files/s]













Downloading data:  62%|██████▏   | 853/1382 [00:07<00:04, 107.98files/s]






Downloading data:  61%|██████▏   | 849/1382 [00:07<00:05, 105.75files/s]

Downloading data:  62%|██████▏   | 858/1382 [00:07<00:04, 105.47files/s]

















Downloading data:  61%|██████    | 845/1382 [00:07<00:04, 108.31files/s]







Downloading data:  62%|██████▏   | 861/1382 [00:07<00:04, 107.09files/s]




Downloading data:  62%|██████▏   | 852/1382 [00:07<00:04, 106.63files/s]











Downloading data:  61%|██████▏   | 848/1382 [00:07<00:05, 105.35files/s]



Downloading data:  61%|██████▏   | 848/1382 [00:07<00:05, 105.35files/s]
















Downloading data:  62%|██████▏   | 855/1382 [00:07<00:04, 108.76files/s]



















 ... (more hidden) ...





Downloading data:  62%|██████▏   | 861/1382 [00:07<00:04, 106.10files/s]












Downloading data:  62%|██████▏   | 856/1382 [00:07<00:04, 107.88files/s]


Downloading data:  62%|██████▏   | 858/1382 [00:07<00:04, 105.03files/s]















Downloading data:  62%|██████▏   | 863/1382 [00:07<00:04, 104.40files/s]









Downloading data:  62%|██████▏   | 853/1382 [00:07<00:04, 106.18files/s]














Downloading data:  63%|██████▎   | 864/1382 [00:07<00:04, 105.36files/s]










Downloading data:  62%|██████▏   | 858/1382 [00:07<00:05, 104.77files/s]


















Downloading data:  62%|██████▏   | 860/1382 [00:07<00:04, 108.04files/s]








Downloading data:  62%|██████▏   | 860/1382 [00:07<00:04, 109.68files/s]

Downloading data:  63%|██████▎   | 869/1382 [00:07<00:04, 106.39files/s]













Downloading data:  63%|██████▎   | 864/1382 [00:07<00:04, 107.86files/s]






Downloading data:  62%|██████▏   | 860/1382 [00:07<00:04, 104.98files/s]

















Downloading data:  62%|██████▏   | 857/1382 [00:07<00:04, 109.71files/s]




Downloading data:  62%|██████▏   | 863/1382 [00:07<00:04, 107.11files/s]







Downloading data:  63%|██████▎   | 873/1382 [00:07<00:04, 108.41files/s]











Downloading data:  62%|██████▏   | 860/1382 [00:07<00:04, 107.62files/s]



Downloading data:  62%|██████▏   | 859/1382 [00:07<00:04, 106.64files/s]
















Downloading data:  63%|██████▎   | 867/1382 [00:07<00:04, 110.53files/s]



















 ... (more hidden) ...





Downloading data:  63%|██████▎   | 873/1382 [00:07<00:04, 108.01files/s]












Downloading data:  63%|██████▎   | 868/1382 [00:07<00:04, 109.88files/s]


Downloading data:  63%|██████▎   | 870/1382 [00:07<00:04, 107.69files/s]















Downloading data:  63%|██████▎   | 875/1382 [00:07<00:04, 106.69files/s]









Downloading data:  63%|██████▎   | 865/1382 [00:07<00:04, 108.67files/s]














Downloading data:  63%|██████▎   | 876/1382 [00:07<00:04, 108.24files/s]










Downloading data:  63%|██████▎   | 870/1382 [00:07<00:04, 106.93files/s]


















Downloading data:  63%|██████▎   | 872/1382 [00:07<00:04, 109.83files/s]








Downloading data:  63%|██████▎   | 872/1382 [00:07<00:04, 111.04files/s]

Downloading data:  64%|██████▎   | 881/1382 [00:07<00:04, 108.81files/s]













Downloading data:  63%|██████▎   | 876/1382 [00:07<00:04, 109.38files/s]






Downloading data:  63%|██████▎   | 872/1382 [00:07<00:04, 106.67files/s]

















Downloading data:  63%|██████▎   | 869/1382 [00:07<00:04, 110.98files/s]




Downloading data:  63%|██████▎   | 875/1382 [00:07<00:04, 109.18files/s]







Downloading data:  64%|██████▍   | 885/1382 [00:07<00:04, 109.75files/s]











Downloading data:  63%|██████▎   | 872/1382 [00:07<00:04, 109.31files/s]



Downloading data:  63%|██████▎   | 871/1382 [00:07<00:04, 108.88files/s]
















Downloading data:  64%|██████▎   | 879/1382 [00:07<00:04, 110.93files/s]



















 ... (more hidden) ...





Downloading data:  64%|██████▍   | 885/1382 [00:07<00:04, 109.22files/s]












Downloading data:  64%|██████▎   | 880/1382 [00:07<00:04, 110.34files/s]


Downloading data:  64%|██████▍   | 882/1382 [00:07<00:04, 109.30files/s]















Downloading data:  64%|██████▍   | 887/1382 [00:07<00:04, 109.05files/s]









Downloading data:  63%|██████▎   | 877/1382 [00:07<00:04, 110.84files/s]














Downloading data:  64%|██████▍   | 888/1382 [00:07<00:04, 110.11files/s]










Downloading data:  64%|██████▍   | 882/1382 [00:07<00:04, 110.23files/s]


















Downloading data:  64%|██████▍   | 884/1382 [00:07<00:04, 112.10files/s]








Downloading data:  64%|██████▍   | 884/1382 [00:07<00:04, 111.85files/s]

Downloading data:  65%|██████▍   | 893/1382 [00:07<00:04, 110.58files/s]













Downloading data:  64%|██████▍   | 888/1382 [00:07<00:04, 111.59files/s]






Downloading data:  64%|██████▍   | 885/1382 [00:07<00:04, 111.30files/s]







Downloading data:  65%|██████▍   | 897/1382 [00:07<00:04, 112.60files/s]




Downloading data:  64%|██████▍   | 887/1382 [00:07<00:04, 110.30files/s]











Downloading data:  64%|██████▍   | 885/1382 [00:07<00:04, 113.81files/s]



Downloading data:  64%|██████▍   | 882/1382 [00:07<00:04, 107.54files/s]

















Downloading data:  64%|██████▎   | 881/1382 [00:07<00:04, 102.80files/s]
















Downloading data:  65%|██████▍   | 892/1382 [00:07<00:04, 114.60files/s]



















 ... (more hidden) ...





Downloading data:  65%|██████▌   | 899/1382 [00:07<00:04, 116.62files/s]












Downloading data:  65%|██████▍   | 894/1382 [00:07<00:04, 116.31files/s]


Downloading data:  65%|██████▍   | 896/1382 [00:07<00:04, 115.22files/s]









Downloading data:  64%|██████▍   | 890/1382 [00:07<00:04, 115.45files/s]















Downloading data:  65%|██████▌   | 901/1382 [00:07<00:04, 115.71files/s]














Downloading data:  65%|██████▌   | 902/1382 [00:07<00:04, 116.50files/s]










Downloading data:  65%|██████▍   | 896/1382 [00:07<00:04, 116.30files/s]


















Downloading data:  65%|██████▍   | 896/1382 [00:07<00:04, 113.31files/s]








Downloading data:  65%|██████▍   | 897/1382 [00:07<00:04, 114.09files/s]

Downloading data:  66%|██████▌   | 907/1382 [00:07<00:04, 117.07files/s]







Downloading data:  66%|██████▌   | 910/1382 [00:07<00:04, 116.85files/s]






Downloading data:  65%|██████▍   | 898/1382 [00:07<00:04, 115.05files/s]




Downloading data:  65%|██████▌   | 900/1382 [00:07<00:04, 114.52files/s]











Downloading data:  65%|██████▍   | 898/1382 [00:07<00:04, 115.89files/s]



Downloading data:  65%|██████▍   | 894/1382 [00:07<00:04, 110.20files/s]













Downloading data:  65%|██████▌   | 900/1382 [00:07<00:04, 102.65files/s]

















Downloading data:  65%|██████▍   | 893/1382 [00:07<00:04, 106.65files/s]



















 ... (more hidden) ...
















Downloading data:  65%|██████▌   | 904/1382 [00:07<00:04, 113.13files/s]





Downloading data:  66%|██████▌   | 911/1382 [00:07<00:04, 115.26files/s]












Downloading data:  66%|██████▌   | 906/1382 [00:07<00:04, 115.85files/s]


Downloading data:  66%|██████▌   | 908/1382 [00:07<00:04, 114.41files/s]









Downloading data:  65%|██████▌   | 902/1382 [00:07<00:04, 114.85files/s]















Downloading data:  66%|██████▌   | 913/1382 [00:07<00:04, 115.01files/s]














Downloading data:  66%|██████▌   | 914/1382 [00:07<00:04, 116.84files/s]


















Downloading data:  66%|██████▌   | 908/1382 [00:07<00:04, 113.54files/s]










Downloading data:  66%|██████▌   | 908/1382 [00:07<00:04, 115.36files/s]
Downloading data: 100%|██████████| 1382/1382 [00:07<00:00, 179.80files/s]









Downloading data:  66%|██████▌   | 909/1382 [00:07<00:04, 115.15files/s]

Downloading data:  66%|██████▋   | 919/1382 [00:07<00:03, 116.23files/s]







Downloading data:  67%|██████▋   | 922/1382 [00:07<00:03, 116.99files/s]






Downloading data:  66%|██████▌   | 910/1382 [00:07<00:04, 115.76files/s]




Downloading data:  66%|██████▌   | 912/1382 [00:07<00:04, 115.39files/s]











Downloading data:  66%|██████▌   | 910/1382 [00:07<00:04, 117.00files/s]













Downloading data:  66%|██████▌   | 912/1382 [00:07<00:04, 107.23files/s]



Downloading data:  66%|██████▌   | 906/1382 [00:07<00:04, 110.92files/s]

















Downloading data:  65%|██████▌   | 905/1382 [00:07<00:04, 109.02files/s]



















 ... (more hidden) ...
















Downloading data:  66%|██████▋   | 917/1382 [00:07<00:04, 116.07files/s]












Downloading data:  66%|██████▋   | 918/1382 [00:07<00:03, 116.42files/s]





Downloading data:  67%|██████▋   | 924/1382 [00:07<00:03, 116.65files/s]


Downloading data:  67%|██████▋   | 920/1382 [00:07<00:04, 115.04files/s]









Downloading data:  66%|██████▌   | 914/1382 [00:07<00:04, 115.93files/s]















Downloading data:  67%|██████▋   | 925/1382 [00:07<00:03, 114.41files/s]














Downloading data:  67%|██████▋   | 926/1382 [00:07<00:03, 117.74files/s]


















Downloading data:  67%|██████▋   | 921/1382 [00:07<00:03, 115.93files/s]










Downloading data:  67%|██████▋   | 921/1382 [00:07<00:03, 117.00files/s]








Downloading data:  67%|██████▋   | 921/1382 [00:07<00:03, 116.25files/s]

Downloading data:  67%|██████▋   | 931/1382 [00:07<00:03, 116.10files/s]







Downloading data:  68%|██████▊   | 934/1382 [00:07<00:03, 117.50files/s]






Downloading data:  67%|██████▋   | 922/1382 [00:07<00:03, 116.51files/s]




Downloading data:  67%|██████▋   | 924/1382 [00:07<00:03, 116.57files/s]













Downloading data:  67%|██████▋   | 924/1382 [00:07<00:04, 110.19files/s]











Downloading data:  67%|██████▋   | 923/1382 [00:07<00:03, 118.44files/s]



Downloading data:  66%|██████▋   | 919/1382 [00:07<00:04, 114.61files/s]

















Downloading data:  66%|██████▋   | 918/1382 [00:07<00:04, 113.30files/s]



















 ... (more hidden) ...
















Downloading data:  67%|██████▋   | 929/1382 [00:07<00:03, 117.14files/s]












Downloading data:  67%|██████▋   | 931/1382 [00:07<00:03, 118.47files/s]





Downloading data:  68%|██████▊   | 937/1382 [00:07<00:03, 117.14files/s]















Downloading data:  68%|██████▊   | 937/1382 [00:07<00:03, 115.75files/s]









Downloading data:  67%|██████▋   | 927/1382 [00:07<00:03, 117.58files/s]


Downloading data:  68%|██████▊   | 933/1382 [00:07<00:03, 116.82files/s]














Downloading data:  68%|██████▊   | 938/1382 [00:07<00:03, 118.07files/s]


















Downloading data:  68%|██████▊   | 934/1382 [00:07<00:03, 119.27files/s]










Downloading data:  68%|██████▊   | 934/1382 [00:08<00:03, 118.53files/s]








Downloading data:  68%|██████▊   | 934/1382 [00:08<00:03, 117.70files/s]

Downloading data:  68%|██████▊   | 943/1382 [00:08<00:03, 116.71files/s]






Downloading data:  68%|██████▊   | 934/1382 [00:08<00:03, 117.40files/s]







Downloading data:  69%|██████▊   | 947/1382 [00:08<00:03, 118.87files/s]




Downloading data:  68%|██████▊   | 936/1382 [00:08<00:03, 117.39files/s]













Downloading data:  68%|██████▊   | 936/1382 [00:08<00:03, 112.75files/s]











Downloading data:  68%|██████▊   | 935/1382 [00:08<00:03, 118.12files/s]



Downloading data:  67%|██████▋   | 931/1382 [00:08<00:03, 114.22files/s]

















Downloading data:  67%|██████▋   | 931/1382 [00:08<00:03, 115.46files/s]



















 ... (more hidden) ...
















Downloading data:  68%|██████▊   | 941/1382 [00:08<00:03, 117.03files/s]












Downloading data:  68%|██████▊   | 943/1382 [00:08<00:03, 117.71files/s]





Downloading data:  69%|██████▊   | 949/1382 [00:08<00:03, 116.88files/s]















Downloading data:  69%|██████▊   | 949/1382 [00:08<00:03, 116.00files/s]









Downloading data:  68%|██████▊   | 939/1382 [00:08<00:03, 116.95files/s]


Downloading data:  68%|██████▊   | 945/1382 [00:08<00:03, 115.97files/s]














Downloading data:  69%|██████▊   | 950/1382 [00:08<00:03, 117.82files/s]


















Downloading data:  68%|██████▊   | 946/1382 [00:08<00:03, 117.80files/s]










Downloading data:  68%|██████▊   | 946/1382 [00:08<00:03, 117.12files/s]

Downloading data:  69%|██████▉   | 955/1382 [00:08<00:03, 116.19files/s]








Downloading data:  68%|██████▊   | 946/1382 [00:08<00:03, 116.82files/s]






Downloading data:  68%|██████▊   | 946/1382 [00:08<00:03, 116.44files/s]







Downloading data:  69%|██████▉   | 959/1382 [00:08<00:03, 118.20files/s]




Downloading data:  69%|██████▊   | 948/1382 [00:08<00:03, 117.10files/s]













Downloading data:  69%|██████▊   | 948/1382 [00:08<00:03, 114.42files/s]











Downloading data:  69%|██████▊   | 947/1382 [00:08<00:03, 117.73files/s]



Downloading data:  68%|██████▊   | 944/1382 [00:08<00:03, 116.33files/s]

















Downloading data:  68%|██████▊   | 943/1382 [00:08<00:03, 115.46files/s]



















 ... (more hidden) ...
















Downloading data:  69%|██████▉   | 954/1382 [00:08<00:03, 118.23files/s]












Downloading data:  69%|██████▉   | 955/1382 [00:08<00:03, 118.27files/s]















Downloading data:  70%|██████▉   | 961/1382 [00:08<00:03, 115.42files/s]









Downloading data:  69%|██████▉   | 951/1382 [00:08<00:03, 116.68files/s]


Downloading data:  69%|██████▉   | 957/1382 [00:08<00:03, 116.45files/s]














Downloading data:  70%|██████▉   | 962/1382 [00:08<00:03, 117.78files/s]





Downloading data:  70%|██████▉   | 962/1382 [00:08<00:03, 117.69files/s]


















Downloading data:  69%|██████▉   | 958/1382 [00:08<00:03, 118.12files/s]










Downloading data:  69%|██████▉   | 958/1382 [00:08<00:03, 117.54files/s]

Downloading data:  70%|██████▉   | 967/1382 [00:08<00:03, 116.75files/s]








Downloading data:  69%|██████▉   | 958/1382 [00:08<00:03, 117.14files/s]







Downloading data:  70%|███████   | 971/1382 [00:08<00:03, 117.88files/s]






Downloading data:  69%|██████▉   | 959/1382 [00:08<00:03, 117.75files/s]




Downloading data:  69%|██████▉   | 960/1382 [00:08<00:03, 116.09files/s]













Downloading data:  69%|██████▉   | 960/1382 [00:08<00:03, 114.40files/s]











Downloading data:  69%|██████▉   | 959/1382 [00:08<00:03, 117.70files/s]



Downloading data:  69%|██████▉   | 956/1382 [00:08<00:03, 116.29files/s]



















 ... (more hidden) ...

















Downloading data:  69%|██████▉   | 956/1382 [00:08<00:03, 117.14files/s]
















Downloading data:  70%|██████▉   | 967/1382 [00:08<00:03, 118.43files/s]












Downloading data:  70%|██████▉   | 967/1382 [00:08<00:03, 118.18files/s]


Downloading data:  70%|███████   | 969/1382 [00:08<00:03, 116.68files/s]














Downloading data:  70%|███████   | 974/1382 [00:08<00:03, 117.69files/s]









Downloading data:  70%|██████▉   | 963/1382 [00:08<00:03, 116.82files/s]





Downloading data:  70%|███████   | 974/1382 [00:08<00:03, 118.06files/s]















Downloading data:  70%|███████   | 974/1382 [00:08<00:03, 116.65files/s]


















Downloading data:  70%|███████   | 970/1382 [00:08<00:03, 118.55files/s]








Downloading data:  70%|███████   | 970/1382 [00:08<00:03, 117.85files/s]










Downloading data:  70%|███████   | 971/1382 [00:08<00:03, 118.08files/s]

Downloading data:  71%|███████   | 980/1382 [00:08<00:03, 117.58files/s]







Downloading data:  71%|███████   | 983/1382 [00:08<00:03, 117.91files/s]






Downloading data:  70%|███████   | 971/1382 [00:08<00:03, 117.78files/s]




Downloading data:  70%|███████   | 972/1382 [00:08<00:03, 116.25files/s]











Downloading data:  70%|███████   | 972/1382 [00:08<00:03, 118.55files/s]













Downloading data:  70%|███████   | 973/1382 [00:08<00:03, 115.97files/s]



Downloading data:  70%|███████   | 968/1382 [00:08<00:03, 116.70files/s]



















 ... (more hidden) ...

















Downloading data:  70%|███████   | 969/1382 [00:08<00:03, 118.43files/s]
















Downloading data:  71%|███████   | 979/1382 [00:08<00:03, 117.62files/s]












Downloading data:  71%|███████   | 980/1382 [00:08<00:03, 119.04files/s]


Downloading data:  71%|███████   | 981/1382 [00:08<00:03, 117.55files/s]














Downloading data:  71%|███████▏  | 987/1382 [00:08<00:03, 119.35files/s]









Downloading data:  71%|███████   | 976/1382 [00:08<00:03, 117.54files/s]





Downloading data:  71%|███████▏  | 987/1382 [00:08<00:03, 118.65files/s]















Downloading data:  71%|███████▏  | 987/1382 [00:08<00:03, 119.23files/s]


















Downloading data:  71%|███████   | 983/1382 [00:08<00:03, 119.97files/s]








Downloading data:  71%|███████   | 983/1382 [00:08<00:03, 119.25files/s]










Downloading data:  71%|███████   | 984/1382 [00:08<00:03, 119.74files/s]






Downloading data:  71%|███████   | 983/1382 [00:08<00:03, 118.35files/s]

Downloading data:  72%|███████▏  | 993/1382 [00:08<00:03, 118.82files/s]







Downloading data:  72%|███████▏  | 996/1382 [00:08<00:03, 117.63files/s]




Downloading data:  71%|███████▏  | 985/1382 [00:08<00:03, 117.53files/s]











Downloading data:  71%|███████   | 984/1382 [00:08<00:03, 118.32files/s]













Downloading data:  71%|███████▏  | 985/1382 [00:08<00:03, 114.01files/s]



Downloading data:  71%|███████   | 980/1382 [00:08<00:03, 115.85files/s]



















 ... (more hidden) ...

















Downloading data:  71%|███████   | 981/1382 [00:08<00:03, 117.19files/s]
















Downloading data:  72%|███████▏  | 991/1382 [00:08<00:03, 117.89files/s]












Downloading data:  72%|███████▏  | 992/1382 [00:08<00:03, 116.40files/s]


Downloading data:  72%|███████▏  | 993/1382 [00:08<00:03, 116.16files/s]














Downloading data:  72%|███████▏  | 999/1382 [00:08<00:03, 116.95files/s]









Downloading data:  71%|███████▏  | 988/1382 [00:08<00:03, 116.53files/s]















Downloading data:  72%|███████▏  | 999/1382 [00:08<00:03, 117.20files/s]





Downloading data:  72%|███████▏  | 999/1382 [00:08<00:03, 116.77files/s]


















Downloading data:  72%|███████▏  | 995/1382 [00:08<00:03, 117.38files/s]








Downloading data:  72%|███████▏  | 995/1382 [00:08<00:03, 116.32files/s]










Downloading data:  72%|███████▏  | 996/1382 [00:08<00:03, 113.08files/s]






Downloading data:  72%|███████▏  | 995/1382 [00:08<00:03, 113.01files/s]

Downloading data:  73%|███████▎  | 1005/1382 [00:08<00:03, 113.75files/s]







Downloading data:  73%|███████▎  | 1008/1382 [00:08<00:03, 113.36files/s]




Downloading data:  72%|███████▏  | 997/1382 [00:08<00:03, 112.44files/s]











Downloading data:  72%|███████▏  | 996/1382 [00:08<00:03, 113.03files/s]













Downloading data:  72%|███████▏  | 997/1382 [00:08<00:03, 111.71files/s]



Downloading data:  72%|███████▏  | 992/1382 [00:08<00:03, 112.93files/s]



















 ... (more hidden) ...

















Downloading data:  72%|███████▏  | 993/1382 [00:08<00:03, 113.91files/s]
















Downloading data:  73%|███████▎  | 1003/1382 [00:08<00:03, 113.93files/s]












Downloading data:  73%|███████▎  | 1004/1382 [00:08<00:03, 112.84files/s]


Downloading data:  73%|███████▎  | 1005/1382 [00:08<00:03, 112.85files/s]









Downloading data:  72%|███████▏  | 1000/1382 [00:08<00:03, 115.01files/s]














Downloading data:  73%|███████▎  | 1011/1382 [00:08<00:03, 114.29files/s]





Downloading data:  73%|███████▎  | 1011/1382 [00:08<00:03, 115.01files/s]















Downloading data:  73%|███████▎  | 1011/1382 [00:08<00:03, 114.11files/s]


















Downloading data:  73%|███████▎  | 1007/1382 [00:08<00:03, 114.99files/s]








Downloading data:  73%|███████▎  | 1007/1382 [00:08<00:03, 112.80files/s]










Downloading data:  73%|███████▎  | 1008/1382 [00:08<00:03, 114.66files/s]






Downloading data:  73%|███████▎  | 1007/1382 [00:08<00:03, 114.73files/s]

Downloading data:  74%|███████▎  | 1017/1382 [00:08<00:03, 113.70files/s]







Downloading data:  74%|███████▍  | 1020/1382 [00:08<00:03, 114.49files/s]




Downloading data:  73%|███████▎  | 1009/1382 [00:08<00:03, 113.76files/s]











Downloading data:  73%|███████▎  | 1008/1382 [00:08<00:03, 113.73files/s]













Downloading data:  73%|███████▎  | 1009/1382 [00:08<00:03, 113.27files/s]



Downloading data:  73%|███████▎  | 1005/1382 [00:08<00:03, 115.22files/s]



















 ... (more hidden) ...

















Downloading data:  73%|███████▎  | 1005/1382 [00:08<00:03, 112.98files/s]
















Downloading data:  74%|███████▎  | 1016/1382 [00:08<00:03, 116.99files/s]


Downloading data:  74%|███████▎  | 1017/1382 [00:08<00:03, 113.81files/s]












Downloading data:  74%|███████▎  | 1016/1382 [00:08<00:03, 113.68files/s]









Downloading data:  73%|███████▎  | 1012/1382 [00:08<00:03, 114.98files/s]














Downloading data:  74%|███████▍  | 1023/1382 [00:08<00:03, 114.60files/s]















Downloading data:  74%|███████▍  | 1023/1382 [00:08<00:03, 114.61files/s]





Downloading data:  74%|███████▍  | 1023/1382 [00:08<00:03, 112.60files/s]


















Downloading data:  74%|███████▎  | 1019/1382 [00:08<00:03, 113.53files/s]








Downloading data:  74%|███████▎  | 1019/1382 [00:08<00:03, 113.88files/s]










Downloading data:  74%|███████▍  | 1020/1382 [00:08<00:03, 115.27files/s]






Downloading data:  74%|███████▎  | 1019/1382 [00:08<00:03, 115.14files/s]

Downloading data:  74%|███████▍  | 1029/1382 [00:08<00:03, 114.00files/s]







Downloading data:  75%|███████▍  | 1032/1382 [00:08<00:03, 113.75files/s]




Downloading data:  74%|███████▍  | 1021/1382 [00:08<00:03, 112.92files/s]











Downloading data:  74%|███████▍  | 1020/1382 [00:08<00:03, 113.11files/s]













Downloading data:  74%|███████▍  | 1021/1382 [00:08<00:03, 111.69files/s]



Downloading data:  74%|███████▎  | 1017/1382 [00:08<00:03, 113.66files/s]



















 ... (more hidden) ...

















Downloading data:  74%|███████▎  | 1017/1382 [00:08<00:03, 112.26files/s]
















Downloading data:  74%|███████▍  | 1028/1382 [00:08<00:03, 114.96files/s]












Downloading data:  74%|███████▍  | 1028/1382 [00:08<00:03, 112.52files/s]


Downloading data:  74%|███████▍  | 1029/1382 [00:08<00:03, 112.54files/s]









Downloading data:  74%|███████▍  | 1024/1382 [00:08<00:03, 113.40files/s]














Downloading data:  75%|███████▍  | 1035/1382 [00:08<00:03, 113.64files/s]















Downloading data:  75%|███████▍  | 1035/1382 [00:08<00:03, 113.69files/s]





Downloading data:  75%|███████▍  | 1035/1382 [00:08<00:03, 112.70files/s]


















Downloading data:  75%|███████▍  | 1031/1382 [00:08<00:03, 114.05files/s]










Downloading data:  75%|███████▍  | 1032/1382 [00:08<00:03, 114.95files/s]








Downloading data:  75%|███████▍  | 1031/1382 [00:08<00:03, 113.89files/s]






Downloading data:  75%|███████▍  | 1031/1382 [00:08<00:03, 114.93files/s]

Downloading data:  75%|███████▌  | 1041/1382 [00:08<00:03, 113.24files/s]







Downloading data:  76%|███████▌  | 1044/1382 [00:08<00:02, 114.11files/s]




Downloading data:  75%|███████▍  | 1033/1382 [00:08<00:03, 113.94files/s]











Downloading data:  75%|███████▍  | 1032/1382 [00:08<00:03, 114.89files/s]













Downloading data:  75%|███████▍  | 1033/1382 [00:08<00:03, 113.89files/s]



Downloading data:  74%|███████▍  | 1029/1382 [00:08<00:03, 114.94files/s]



















 ... (more hidden) ...
















Downloading data:  75%|███████▌  | 1040/1382 [00:08<00:02, 116.10files/s]

















Downloading data:  75%|███████▍  | 1030/1382 [00:08<00:03, 115.20files/s]


Downloading data:  75%|███████▌  | 1041/1382 [00:08<00:02, 114.45files/s]









Downloading data:  75%|███████▍  | 1036/1382 [00:08<00:03, 113.79files/s]












Downloading data:  75%|███████▌  | 1041/1382 [00:08<00:02, 114.83files/s]















Downloading data:  76%|███████▌  | 1047/1382 [00:08<00:02, 115.05files/s]














Downloading data:  76%|███████▌  | 1048/1382 [00:08<00:02, 115.13files/s]





Downloading data:  76%|███████▌  | 1047/1382 [00:08<00:02, 113.71files/s]


















Downloading data:  76%|███████▌  | 1044/1382 [00:08<00:02, 115.89files/s]








Downloading data:  75%|███████▌  | 1043/1382 [00:08<00:02, 114.95files/s]










Downloading data:  76%|███████▌  | 1044/1382 [00:08<00:02, 115.62files/s]






Downloading data:  75%|███████▌  | 1043/1382 [00:08<00:02, 115.47files/s]

Downloading data:  76%|███████▌  | 1053/1382 [00:08<00:02, 114.80files/s]







Downloading data:  76%|███████▋  | 1056/1382 [00:08<00:02, 114.16files/s]




Downloading data:  76%|███████▌  | 1045/1382 [00:08<00:02, 115.25files/s]











Downloading data:  76%|███████▌  | 1044/1382 [00:08<00:02, 114.59files/s]













Downloading data:  76%|███████▌  | 1045/1382 [00:08<00:02, 114.58files/s]



Downloading data:  75%|███████▌  | 1041/1382 [00:09<00:02, 114.20files/s]



















 ... (more hidden) ...
















Downloading data:  76%|███████▌  | 1052/1382 [00:09<00:02, 116.95files/s]

















Downloading data:  75%|███████▌  | 1042/1382 [00:09<00:02, 116.30files/s]


Downloading data:  76%|███████▌  | 1053/1382 [00:09<00:02, 115.41files/s]















Downloading data:  77%|███████▋  | 1059/1382 [00:09<00:02, 116.17files/s]












Downloading data:  76%|███████▌  | 1053/1382 [00:09<00:02, 115.94files/s]









Downloading data:  76%|███████▌  | 1049/1382 [00:09<00:02, 116.00files/s]





Downloading data:  77%|███████▋  | 1059/1382 [00:09<00:02, 115.01files/s]














Downloading data:  77%|███████▋  | 1061/1382 [00:09<00:02, 118.03files/s]


















Downloading data:  76%|███████▋  | 1057/1382 [00:09<00:02, 118.49files/s]








Downloading data:  76%|███████▋  | 1056/1382 [00:09<00:02, 117.42files/s]










Downloading data:  76%|███████▋  | 1057/1382 [00:09<00:02, 117.89files/s]






Downloading data:  76%|███████▋  | 1056/1382 [00:09<00:02, 117.06files/s]

Downloading data:  77%|███████▋  | 1065/1382 [00:09<00:02, 115.23files/s]







Downloading data:  77%|███████▋  | 1069/1382 [00:09<00:02, 116.55files/s]




Downloading data:  77%|███████▋  | 1058/1382 [00:09<00:02, 117.04files/s]











Downloading data:  76%|███████▋  | 1056/1382 [00:09<00:02, 115.81files/s]













Downloading data:  76%|███████▋  | 1057/1382 [00:09<00:02, 115.93files/s]



Downloading data:  76%|███████▋  | 1054/1382 [00:09<00:02, 116.29files/s]



















 ... (more hidden) ...
















Downloading data:  77%|███████▋  | 1065/1382 [00:09<00:02, 118.67files/s]

















Downloading data:  76%|███████▋  | 1055/1382 [00:09<00:02, 118.36files/s]


Downloading data:  77%|███████▋  | 1066/1382 [00:09<00:02, 117.19files/s]















Downloading data:  78%|███████▊  | 1072/1382 [00:09<00:02, 118.27files/s]












Downloading data:  77%|███████▋  | 1066/1382 [00:09<00:02, 117.97files/s]














Downloading data:  78%|███████▊  | 1073/1382 [00:09<00:02, 117.86files/s]









Downloading data:  77%|███████▋  | 1062/1382 [00:09<00:02, 118.51files/s]





Downloading data:  78%|███████▊  | 1072/1382 [00:09<00:02, 116.09files/s]


















Downloading data:  77%|███████▋  | 1070/1382 [00:09<00:02, 119.13files/s]










Downloading data:  77%|███████▋  | 1069/1382 [00:09<00:02, 118.43files/s]






Downloading data:  77%|███████▋  | 1068/1382 [00:09<00:02, 117.47files/s]








Downloading data:  77%|███████▋  | 1069/1382 [00:09<00:02, 118.42files/s]

Downloading data:  78%|███████▊  | 1078/1382 [00:09<00:02, 116.91files/s]







Downloading data:  78%|███████▊  | 1081/1382 [00:09<00:02, 117.24files/s]




Downloading data:  77%|███████▋  | 1070/1382 [00:09<00:02, 117.83files/s]













Downloading data:  77%|███████▋  | 1069/1382 [00:09<00:02, 116.43files/s]











Downloading data:  77%|███████▋  | 1069/1382 [00:09<00:02, 118.29files/s]



















 ... (more hidden) ...



Downloading data:  77%|███████▋  | 1066/1382 [00:09<00:02, 115.27files/s]
















Downloading data:  78%|███████▊  | 1077/1382 [00:09<00:02, 117.24files/s]

















Downloading data:  77%|███████▋  | 1067/1382 [00:09<00:02, 117.54files/s]















Downloading data:  78%|███████▊  | 1084/1382 [00:09<00:02, 118.45files/s]


Downloading data:  78%|███████▊  | 1078/1382 [00:09<00:02, 116.08files/s]














Downloading data:  79%|███████▊  | 1085/1382 [00:09<00:02, 118.08files/s]












Downloading data:  78%|███████▊  | 1078/1382 [00:09<00:02, 116.89files/s]









Downloading data:  78%|███████▊  | 1074/1382 [00:09<00:02, 117.52files/s]





Downloading data:  79%|███████▊  | 1085/1382 [00:09<00:02, 117.67files/s]


















Downloading data:  78%|███████▊  | 1082/1382 [00:09<00:02, 118.67files/s]










Downloading data:  78%|███████▊  | 1081/1382 [00:09<00:02, 117.86files/s]






Downloading data:  78%|███████▊  | 1080/1382 [00:09<00:02, 116.84files/s]








Downloading data:  78%|███████▊  | 1081/1382 [00:09<00:02, 117.64files/s]

Downloading data:  79%|███████▉  | 1090/1382 [00:09<00:02, 115.91files/s]







Downloading data:  79%|███████▉  | 1093/1382 [00:09<00:02, 116.30files/s]




Downloading data:  78%|███████▊  | 1082/1382 [00:09<00:02, 116.83files/s]











Downloading data:  78%|███████▊  | 1081/1382 [00:09<00:02, 117.89files/s]













Downloading data:  78%|███████▊  | 1081/1382 [00:09<00:02, 115.83files/s]



Downloading data:  78%|███████▊  | 1078/1382 [00:09<00:02, 114.62files/s]



















 ... (more hidden) ...
















Downloading data:  79%|███████▉  | 1089/1382 [00:09<00:02, 116.46files/s]

















Downloading data:  78%|███████▊  | 1079/1382 [00:09<00:02, 117.57files/s]















Downloading data:  79%|███████▉  | 1096/1382 [00:09<00:02, 117.39files/s]


Downloading data:  79%|███████▉  | 1090/1382 [00:09<00:02, 115.68files/s]














Downloading data:  79%|███████▉  | 1097/1382 [00:09<00:02, 118.31files/s]












Downloading data:  79%|███████▉  | 1090/1382 [00:09<00:02, 116.93files/s]









Downloading data:  79%|███████▊  | 1086/1382 [00:09<00:02, 116.43files/s]





Downloading data:  79%|███████▉  | 1097/1382 [00:09<00:02, 116.15files/s]


















Downloading data:  79%|███████▉  | 1094/1382 [00:09<00:02, 117.61files/s]










Downloading data:  79%|███████▉  | 1093/1382 [00:09<00:02, 117.03files/s]






Downloading data:  79%|███████▉  | 1092/1382 [00:09<00:02, 115.78files/s]








Downloading data:  79%|███████▉  | 1093/1382 [00:09<00:02, 117.14files/s]







Downloading data:  80%|███████▉  | 1105/1382 [00:09<00:02, 116.41files/s]

Downloading data:  80%|███████▉  | 1102/1382 [00:09<00:02, 115.74files/s]




Downloading data:  79%|███████▉  | 1094/1382 [00:09<00:02, 115.85files/s]











Downloading data:  79%|███████▉  | 1093/1382 [00:09<00:02, 117.13files/s]













Downloading data:  79%|███████▉  | 1093/1382 [00:09<00:02, 113.63files/s]



















 ... (more hidden) ...



Downloading data:  79%|███████▉  | 1090/1382 [00:09<00:02, 115.17files/s]

















Downloading data:  79%|███████▉  | 1091/1382 [00:09<00:02, 118.02files/s]
















Downloading data:  80%|███████▉  | 1102/1382 [00:09<00:02, 117.69files/s]















Downloading data:  80%|████████  | 1108/1382 [00:09<00:02, 117.63files/s]














Downloading data:  80%|████████  | 1109/1382 [00:09<00:02, 118.58files/s]


Downloading data:  80%|███████▉  | 1102/1382 [00:09<00:02, 115.39files/s]












Downloading data:  80%|███████▉  | 1103/1382 [00:09<00:02, 117.98files/s]









Downloading data:  79%|███████▉  | 1098/1382 [00:09<00:02, 116.87files/s]





Downloading data:  80%|████████  | 1109/1382 [00:09<00:02, 116.40files/s]










Downloading data:  80%|███████▉  | 1105/1382 [00:09<00:02, 116.47files/s]


















Downloading data:  80%|████████  | 1107/1382 [00:09<00:02, 118.72files/s]








Downloading data:  80%|███████▉  | 1105/1382 [00:09<00:02, 116.78files/s]






Downloading data:  80%|███████▉  | 1105/1382 [00:09<00:02, 117.43files/s]







Downloading data:  81%|████████  | 1117/1382 [00:09<00:02, 117.12files/s]

Downloading data:  81%|████████  | 1114/1382 [00:09<00:02, 115.98files/s]




Downloading data:  80%|████████  | 1106/1382 [00:09<00:02, 116.63files/s]











Downloading data:  80%|███████▉  | 1105/1382 [00:09<00:02, 117.32files/s]













Downloading data:  80%|████████  | 1106/1382 [00:09<00:02, 116.06files/s]



















 ... (more hidden) ...



Downloading data:  80%|███████▉  | 1102/1382 [00:09<00:02, 115.42files/s]

















Downloading data:  80%|███████▉  | 1103/1382 [00:09<00:02, 118.05files/s]
















Downloading data:  81%|████████  | 1114/1382 [00:09<00:02, 116.64files/s]














Downloading data:  81%|████████  | 1121/1382 [00:09<00:02, 118.75files/s]















Downloading data:  81%|████████  | 1120/1382 [00:09<00:02, 117.67files/s]












Downloading data:  81%|████████  | 1115/1382 [00:09<00:02, 117.32files/s]


Downloading data:  81%|████████  | 1114/1382 [00:09<00:02, 113.33files/s]









Downloading data:  80%|████████  | 1110/1382 [00:09<00:02, 115.94files/s]





Downloading data:  81%|████████  | 1121/1382 [00:09<00:02, 115.51files/s]


















Downloading data:  81%|████████  | 1119/1382 [00:09<00:02, 118.45files/s]










Downloading data:  81%|████████  | 1118/1382 [00:09<00:02, 118.11files/s]








Downloading data:  81%|████████  | 1117/1382 [00:09<00:02, 117.10files/s]






Downloading data:  81%|████████  | 1117/1382 [00:09<00:02, 117.02files/s]







Downloading data:  82%|████████▏ | 1129/1382 [00:09<00:02, 117.23files/s]

Downloading data:  81%|████████▏ | 1126/1382 [00:09<00:02, 116.22files/s]




Downloading data:  81%|████████  | 1118/1382 [00:09<00:02, 116.64files/s]











Downloading data:  81%|████████  | 1117/1382 [00:09<00:02, 116.41files/s]













Downloading data:  81%|████████  | 1118/1382 [00:09<00:02, 116.43files/s]



Downloading data:  81%|████████  | 1114/1382 [00:09<00:02, 116.73files/s]

















Downloading data:  81%|████████  | 1115/1382 [00:09<00:02, 117.08files/s]



















 ... (more hidden) ...
















Downloading data:  82%|████████▏ | 1127/1382 [00:09<00:02, 118.97files/s]














Downloading data:  82%|████████▏ | 1134/1382 [00:09<00:02, 119.49files/s]















Downloading data:  82%|████████▏ | 1133/1382 [00:09<00:02, 119.06files/s]












Downloading data:  82%|████████▏ | 1128/1382 [00:09<00:02, 119.12files/s]









Downloading data:  81%|████████▏ | 1123/1382 [00:09<00:02, 117.34files/s]


Downloading data:  81%|████████▏ | 1126/1382 [00:09<00:02, 112.31files/s]





Downloading data:  82%|████████▏ | 1133/1382 [00:09<00:02, 116.18files/s]


















Downloading data:  82%|████████▏ | 1132/1382 [00:09<00:02, 119.53files/s]










Downloading data:  82%|████████▏ | 1131/1382 [00:09<00:02, 119.83files/s]







Downloading data:  83%|████████▎ | 1141/1382 [00:09<00:02, 117.82files/s]








Downloading data:  82%|████████▏ | 1130/1382 [00:09<00:02, 117.90files/s]

Downloading data:  82%|████████▏ | 1138/1382 [00:09<00:02, 116.39files/s]




Downloading data:  82%|████████▏ | 1130/1382 [00:09<00:02, 116.79files/s]






Downloading data:  82%|████████▏ | 1130/1382 [00:09<00:02, 117.66files/s]











Downloading data:  82%|████████▏ | 1130/1382 [00:09<00:02, 118.20files/s]













Downloading data:  82%|████████▏ | 1130/1382 [00:09<00:02, 117.36files/s]



Downloading data:  82%|████████▏ | 1127/1382 [00:09<00:02, 119.01files/s]

















Downloading data:  82%|████████▏ | 1128/1382 [00:09<00:02, 119.41files/s]



















 ... (more hidden) ...
















Downloading data:  82%|████████▏ | 1140/1382 [00:09<00:02, 119.18files/s]















Downloading data:  83%|████████▎ | 1145/1382 [00:09<00:01, 119.03files/s]














Downloading data:  83%|████████▎ | 1146/1382 [00:09<00:01, 119.35files/s]












Downloading data:  82%|████████▏ | 1140/1382 [00:09<00:02, 118.98files/s]









Downloading data:  82%|████████▏ | 1136/1382 [00:09<00:02, 118.07files/s]





Downloading data:  83%|████████▎ | 1145/1382 [00:09<00:02, 115.91files/s]


















Downloading data:  83%|████████▎ | 1144/1382 [00:09<00:01, 119.52files/s]


Downloading data:  82%|████████▏ | 1138/1382 [00:09<00:02, 110.05files/s]










Downloading data:  83%|████████▎ | 1143/1382 [00:09<00:02, 119.25files/s]








Downloading data:  83%|████████▎ | 1142/1382 [00:09<00:02, 118.42files/s]







Downloading data:  83%|████████▎ | 1153/1382 [00:09<00:01, 117.96files/s]






Downloading data:  83%|████████▎ | 1142/1382 [00:09<00:02, 116.88files/s]

Downloading data:  83%|████████▎ | 1151/1382 [00:09<00:01, 117.13files/s]




Downloading data:  83%|████████▎ | 1143/1382 [00:09<00:02, 117.36files/s]











Downloading data:  83%|████████▎ | 1142/1382 [00:09<00:02, 117.00files/s]













Downloading data:  83%|████████▎ | 1142/1382 [00:09<00:02, 117.71files/s]



Downloading data:  82%|████████▏ | 1139/1382 [00:09<00:02, 116.97files/s]

















Downloading data:  82%|████████▏ | 1140/1382 [00:09<00:02, 118.66files/s]



















 ... (more hidden) ...














Downloading data:  84%|████████▍ | 1158/1382 [00:09<00:01, 118.82files/s]
















Downloading data:  83%|████████▎ | 1153/1382 [00:09<00:01, 119.63files/s]















Downloading data:  84%|████████▍ | 1158/1382 [00:09<00:01, 119.60files/s]












Downloading data:  83%|████████▎ | 1152/1382 [00:09<00:01, 117.62files/s]









Downloading data:  83%|████████▎ | 1148/1382 [00:09<00:01, 117.62files/s]





Downloading data:  84%|████████▎ | 1157/1382 [00:09<00:01, 114.43files/s]


















Downloading data:  84%|████████▎ | 1156/1382 [00:09<00:01, 118.87files/s]


Downloading data:  83%|████████▎ | 1150/1382 [00:09<00:02, 108.78files/s]










Downloading data:  84%|████████▎ | 1155/1382 [00:09<00:01, 116.13files/s]








Downloading data:  84%|████████▎ | 1154/1382 [00:09<00:01, 115.42files/s]







Downloading data:  84%|████████▍ | 1165/1382 [00:09<00:01, 115.16files/s]




Downloading data:  84%|████████▎ | 1155/1382 [00:09<00:01, 117.14files/s]






Downloading data:  84%|████████▎ | 1154/1382 [00:09<00:01, 114.87files/s]

Downloading data:  84%|████████▍ | 1163/1382 [00:09<00:01, 115.96files/s]













Downloading data:  84%|████████▎ | 1154/1382 [00:09<00:01, 114.96files/s]











Downloading data:  84%|████████▎ | 1154/1382 [00:09<00:01, 114.30files/s]



Downloading data:  83%|████████▎ | 1151/1382 [00:09<00:01, 115.73files/s]

















Downloading data:  83%|████████▎ | 1152/1382 [00:09<00:01, 116.87files/s]



















 ... (more hidden) ...
















Downloading data:  84%|████████▍ | 1165/1382 [00:09<00:01, 119.51files/s]















Downloading data:  85%|████████▍ | 1170/1382 [00:09<00:01, 118.93files/s]














Downloading data:  85%|████████▍ | 1171/1382 [00:09<00:01, 119.07files/s]












Downloading data:  84%|████████▍ | 1164/1382 [00:09<00:01, 116.18files/s]









Downloading data:  84%|████████▍ | 1160/1382 [00:09<00:01, 116.33files/s]





Downloading data:  85%|████████▍ | 1170/1382 [00:09<00:01, 116.25files/s]


















Downloading data:  85%|████████▍ | 1168/1382 [00:09<00:01, 113.61files/s]


Downloading data:  84%|████████▍ | 1163/1382 [00:10<00:01, 112.27files/s]










Downloading data:  85%|████████▍ | 1168/1382 [00:10<00:01, 116.46files/s]







Downloading data:  85%|████████▌ | 1177/1382 [00:10<00:01, 114.34files/s]








Downloading data:  84%|████████▍ | 1166/1382 [00:10<00:01, 114.10files/s]




Downloading data:  85%|████████▍ | 1168/1382 [00:10<00:01, 120.24files/s]

Downloading data:  85%|████████▌ | 1175/1382 [00:10<00:01, 116.20files/s]






Downloading data:  84%|████████▍ | 1166/1382 [00:10<00:01, 114.13files/s]











Downloading data:  84%|████████▍ | 1166/1382 [00:10<00:01, 113.91files/s]













Downloading data:  84%|████████▍ | 1166/1382 [00:10<00:01, 114.07files/s]



Downloading data:  84%|████████▍ | 1163/1382 [00:10<00:01, 116.32files/s]

















Downloading data:  84%|████████▍ | 1164/1382 [00:10<00:01, 115.65files/s]



















 ... (more hidden) ...
















Downloading data:  85%|████████▌ | 1177/1382 [00:10<00:01, 118.80files/s]















Downloading data:  86%|████████▌ | 1182/1382 [00:10<00:01, 116.10files/s]














Downloading data:  86%|████████▌ | 1183/1382 [00:10<00:01, 116.43files/s]












Downloading data:  85%|████████▌ | 1176/1382 [00:10<00:01, 114.68files/s]









Downloading data:  85%|████████▍ | 1172/1382 [00:10<00:01, 117.34files/s]





Downloading data:  86%|████████▌ | 1182/1382 [00:10<00:01, 115.88files/s]


Downloading data:  85%|████████▌ | 1175/1382 [00:10<00:01, 114.37files/s]


















Downloading data:  85%|████████▌ | 1181/1382 [00:10<00:01, 115.88files/s]

Downloading data:  86%|████████▌ | 1187/1382 [00:10<00:01, 117.24files/s]







Downloading data:  86%|████████▌ | 1190/1382 [00:10<00:01, 116.84files/s]










Downloading data:  85%|████████▌ | 1181/1382 [00:10<00:01, 118.15files/s]








Downloading data:  85%|████████▌ | 1179/1382 [00:10<00:01, 115.65files/s]




Downloading data:  85%|████████▌ | 1181/1382 [00:10<00:01, 120.18files/s]






Downloading data:  85%|████████▌ | 1179/1382 [00:10<00:01, 116.40files/s]











Downloading data:  85%|████████▌ | 1179/1382 [00:10<00:01, 117.00files/s]













Downloading data:  85%|████████▌ | 1179/1382 [00:10<00:01, 117.17files/s]



Downloading data:  85%|████████▌ | 1175/1382 [00:10<00:01, 117.16files/s]

















Downloading data:  85%|████████▌ | 1177/1382 [00:10<00:01, 118.55files/s]
















Downloading data:  86%|████████▌ | 1189/1382 [00:10<00:01, 118.28files/s]



















 ... (more hidden) ...














Downloading data:  86%|████████▋ | 1195/1382 [00:10<00:01, 117.38files/s]















Downloading data:  86%|████████▋ | 1194/1382 [00:10<00:01, 117.12files/s]












Downloading data:  86%|████████▌ | 1188/1382 [00:10<00:01, 116.16files/s]









Downloading data:  86%|████████▌ | 1185/1382 [00:10<00:01, 118.10files/s]





Downloading data:  86%|████████▋ | 1194/1382 [00:10<00:01, 116.31files/s]


Downloading data:  86%|████████▌ | 1187/1382 [00:10<00:01, 114.77files/s]


















Downloading data:  86%|████████▋ | 1194/1382 [00:10<00:01, 117.90files/s]








Downloading data:  86%|████████▌ | 1191/1382 [00:10<00:01, 116.75files/s]

Downloading data:  87%|████████▋ | 1200/1382 [00:10<00:01, 119.09files/s]







Downloading data:  87%|████████▋ | 1203/1382 [00:10<00:01, 118.77files/s]










Downloading data:  86%|████████▋ | 1194/1382 [00:10<00:01, 118.88files/s]






Downloading data:  86%|████████▌ | 1191/1382 [00:10<00:01, 117.09files/s]




Downloading data:  86%|████████▋ | 1194/1382 [00:10<00:01, 119.99files/s]











Downloading data:  86%|████████▋ | 1192/1382 [00:10<00:01, 118.40files/s]













Downloading data:  86%|████████▋ | 1192/1382 [00:10<00:01, 118.72files/s]



Downloading data:  86%|████████▌ | 1188/1382 [00:10<00:01, 117.86files/s]

















Downloading data:  86%|████████▌ | 1190/1382 [00:10<00:01, 119.73files/s]
















Downloading data:  87%|████████▋ | 1202/1382 [00:10<00:01, 119.55files/s]



















 ... (more hidden) ...














Downloading data:  87%|████████▋ | 1208/1382 [00:10<00:01, 120.38files/s]















Downloading data:  87%|████████▋ | 1207/1382 [00:10<00:01, 119.70files/s]












Downloading data:  87%|████████▋ | 1201/1382 [00:10<00:01, 117.77files/s]









Downloading data:  87%|████████▋ | 1197/1382 [00:10<00:01, 118.17files/s]





Downloading data:  87%|████████▋ | 1206/1382 [00:10<00:01, 116.38files/s]


















Downloading data:  87%|████████▋ | 1206/1382 [00:10<00:01, 117.61files/s]








Downloading data:  87%|████████▋ | 1203/1382 [00:10<00:01, 116.18files/s]







Downloading data:  88%|████████▊ | 1215/1382 [00:10<00:01, 117.88files/s]


Downloading data:  87%|████████▋ | 1199/1382 [00:10<00:01, 111.12files/s]

Downloading data:  88%|████████▊ | 1212/1382 [00:10<00:01, 117.52files/s]










Downloading data:  87%|████████▋ | 1206/1382 [00:10<00:01, 117.59files/s]






Downloading data:  87%|████████▋ | 1203/1382 [00:10<00:01, 114.99files/s]




Downloading data:  87%|████████▋ | 1207/1382 [00:10<00:01, 118.20files/s]













Downloading data:  87%|████████▋ | 1204/1382 [00:10<00:01, 116.99files/s]











Downloading data:  87%|████████▋ | 1204/1382 [00:10<00:01, 116.50files/s]



Downloading data:  87%|████████▋ | 1200/1382 [00:10<00:01, 116.12files/s]

















Downloading data:  87%|████████▋ | 1202/1382 [00:10<00:01, 117.07files/s]



















 ... (more hidden) ...
















Downloading data:  88%|████████▊ | 1214/1382 [00:10<00:01, 116.62files/s]















Downloading data:  88%|████████▊ | 1219/1382 [00:10<00:01, 117.35files/s]














Downloading data:  88%|████████▊ | 1221/1382 [00:10<00:01, 117.53files/s]












Downloading data:  88%|████████▊ | 1213/1382 [00:10<00:01, 116.00files/s]









Downloading data:  87%|████████▋ | 1209/1382 [00:10<00:01, 116.70files/s]





Downloading data:  88%|████████▊ | 1218/1382 [00:10<00:01, 115.31files/s]


















Downloading data:  88%|████████▊ | 1218/1382 [00:10<00:01, 117.25files/s]







Downloading data:  89%|████████▉ | 1227/1382 [00:10<00:01, 118.42files/s]








Downloading data:  88%|████████▊ | 1215/1382 [00:10<00:01, 115.63files/s]


Downloading data:  88%|████████▊ | 1211/1382 [00:10<00:01, 112.32files/s]

Downloading data:  89%|████████▊ | 1224/1382 [00:10<00:01, 117.08files/s]










Downloading data:  88%|████████▊ | 1218/1382 [00:10<00:01, 117.17files/s]






Downloading data:  88%|████████▊ | 1216/1382 [00:10<00:01, 116.71files/s]




Downloading data:  88%|████████▊ | 1219/1382 [00:10<00:01, 117.33files/s]













Downloading data:  88%|████████▊ | 1216/1382 [00:10<00:01, 117.53files/s]











Downloading data:  88%|████████▊ | 1216/1382 [00:10<00:01, 115.95files/s]



Downloading data:  88%|████████▊ | 1212/1382 [00:10<00:01, 116.24files/s]

















Downloading data:  88%|████████▊ | 1214/1382 [00:10<00:01, 117.66files/s]
















Downloading data:  89%|████████▊ | 1226/1382 [00:10<00:01, 117.49files/s]



















 ... (more hidden) ...















Downloading data:  89%|████████▉ | 1232/1382 [00:10<00:01, 117.96files/s]














Downloading data:  89%|████████▉ | 1233/1382 [00:10<00:01, 117.85files/s]












Downloading data:  89%|████████▊ | 1225/1382 [00:10<00:01, 116.13files/s]









Downloading data:  88%|████████▊ | 1221/1382 [00:10<00:01, 116.91files/s]





Downloading data:  89%|████████▉ | 1230/1382 [00:10<00:01, 115.35files/s]







Downloading data:  90%|████████▉ | 1239/1382 [00:10<00:01, 118.09files/s]


















Downloading data:  89%|████████▉ | 1231/1382 [00:10<00:01, 118.27files/s]








Downloading data:  89%|████████▉ | 1227/1382 [00:10<00:01, 116.59files/s]


Downloading data:  88%|████████▊ | 1223/1382 [00:10<00:01, 113.79files/s]

Downloading data:  89%|████████▉ | 1236/1382 [00:10<00:01, 117.16files/s]










Downloading data:  89%|████████▉ | 1230/1382 [00:10<00:01, 117.56files/s]






Downloading data:  89%|████████▉ | 1228/1382 [00:10<00:01, 116.44files/s]




Downloading data:  89%|████████▉ | 1231/1382 [00:10<00:01, 111.64files/s]











Downloading data:  89%|████████▉ | 1228/1382 [00:10<00:01, 111.65files/s]













Downloading data:  89%|████████▉ | 1228/1382 [00:10<00:01, 109.76files/s]

















Downloading data:  89%|████████▊ | 1226/1382 [00:10<00:01, 111.80files/s]



Downloading data:  89%|████████▊ | 1224/1382 [00:10<00:01, 108.43files/s]
















Downloading data:  90%|████████▉ | 1238/1382 [00:10<00:01, 111.40files/s]



















 ... (more hidden) ...















Downloading data:  90%|█████████ | 1244/1382 [00:10<00:01, 111.88files/s]














Downloading data:  90%|█████████ | 1245/1382 [00:10<00:01, 109.16files/s]












Downloading data:  90%|████████▉ | 1237/1382 [00:10<00:01, 108.75files/s]









Downloading data:  89%|████████▉ | 1233/1382 [00:10<00:01, 108.96files/s]





Downloading data:  90%|████████▉ | 1242/1382 [00:10<00:01, 109.33files/s]


















Downloading data:  90%|████████▉ | 1243/1382 [00:10<00:01, 112.39files/s]








Downloading data:  90%|████████▉ | 1239/1382 [00:10<00:01, 111.18files/s]







Downloading data:  91%|█████████ | 1251/1382 [00:10<00:01, 109.71files/s]


Downloading data:  89%|████████▉ | 1235/1382 [00:10<00:01, 107.50files/s]

Downloading data:  90%|█████████ | 1248/1382 [00:10<00:01, 109.61files/s]










Downloading data:  90%|████████▉ | 1242/1382 [00:10<00:01, 109.79files/s]






Downloading data:  90%|████████▉ | 1240/1382 [00:10<00:01, 111.56files/s]




Downloading data:  90%|████████▉ | 1243/1382 [00:10<00:01, 112.42files/s]











Downloading data:  90%|████████▉ | 1240/1382 [00:10<00:01, 113.62files/s]













Downloading data:  90%|████████▉ | 1240/1382 [00:10<00:01, 112.08files/s]



Downloading data:  89%|████████▉ | 1236/1382 [00:10<00:01, 110.40files/s]

















Downloading data:  90%|████████▉ | 1239/1382 [00:10<00:01, 114.20files/s]
















Downloading data:  91%|█████████ | 1251/1382 [00:10<00:01, 114.10files/s]



















 ... (more hidden) ...















Downloading data:  91%|█████████ | 1257/1382 [00:10<00:01, 114.73files/s]














Downloading data:  91%|█████████ | 1257/1382 [00:10<00:01, 111.91files/s]





Downloading data:  91%|█████████ | 1254/1382 [00:10<00:01, 112.25files/s]









Downloading data:  90%|█████████ | 1245/1382 [00:10<00:01, 110.63files/s]












Downloading data:  90%|█████████ | 1250/1382 [00:10<00:01, 112.23files/s]








Downloading data:  91%|█████████ | 1251/1382 [00:10<00:01, 112.52files/s]







Downloading data:  91%|█████████▏| 1263/1382 [00:10<00:01, 112.57files/s]

Downloading data:  91%|█████████ | 1260/1382 [00:10<00:01, 111.40files/s]


Downloading data:  90%|█████████ | 1247/1382 [00:10<00:01, 109.76files/s]


















Downloading data:  91%|█████████ | 1256/1382 [00:10<00:01, 113.56files/s]










Downloading data:  91%|█████████ | 1254/1382 [00:10<00:01, 111.76files/s]






Downloading data:  91%|█████████ | 1252/1382 [00:10<00:01, 113.40files/s]




Downloading data:  91%|█████████ | 1255/1382 [00:10<00:01, 112.38files/s]











Downloading data:  91%|█████████ | 1252/1382 [00:10<00:01, 114.31files/s]













Downloading data:  91%|█████████ | 1252/1382 [00:10<00:01, 113.11files/s]



Downloading data:  90%|█████████ | 1248/1382 [00:10<00:01, 112.22files/s]

















Downloading data:  91%|█████████ | 1251/1382 [00:10<00:01, 114.39files/s]
















Downloading data:  91%|█████████▏| 1263/1382 [00:10<00:01, 114.23files/s]



















 ... (more hidden) ...















Downloading data:  92%|█████████▏| 1269/1382 [00:10<00:00, 114.00files/s]














Downloading data:  92%|█████████▏| 1269/1382 [00:10<00:01, 112.64files/s]












Downloading data:  91%|█████████▏| 1262/1382 [00:10<00:01, 112.40files/s]





Downloading data:  92%|█████████▏| 1266/1382 [00:10<00:01, 112.31files/s]









Downloading data:  91%|█████████ | 1257/1382 [00:10<00:01, 111.13files/s]








Downloading data:  91%|█████████▏| 1263/1382 [00:10<00:01, 112.43files/s]







Downloading data:  92%|█████████▏| 1275/1382 [00:10<00:00, 111.75files/s]

Downloading data:  92%|█████████▏| 1272/1382 [00:10<00:00, 112.85files/s]


















Downloading data:  92%|█████████▏| 1268/1382 [00:10<00:00, 114.38files/s]


Downloading data:  91%|█████████ | 1259/1382 [00:10<00:01, 111.08files/s]










Downloading data:  92%|█████████▏| 1266/1382 [00:10<00:01, 111.22files/s]






Downloading data:  91%|█████████▏| 1264/1382 [00:10<00:01, 113.03files/s]




Downloading data:  92%|█████████▏| 1267/1382 [00:10<00:01, 113.81files/s]











Downloading data:  91%|█████████▏| 1264/1382 [00:10<00:01, 114.69files/s]













Downloading data:  91%|█████████▏| 1264/1382 [00:10<00:01, 112.55files/s]



Downloading data:  91%|█████████ | 1260/1382 [00:10<00:01, 113.27files/s]

















Downloading data:  91%|█████████▏| 1263/1382 [00:10<00:01, 115.37files/s]
















Downloading data:  92%|█████████▏| 1275/1382 [00:10<00:00, 115.85files/s]



















 ... (more hidden) ...














Downloading data:  93%|█████████▎| 1282/1382 [00:10<00:00, 115.41files/s]















Downloading data:  93%|█████████▎| 1282/1382 [00:10<00:00, 115.70files/s]












Downloading data:  92%|█████████▏| 1274/1382 [00:10<00:00, 114.43files/s]





Downloading data:  92%|█████████▏| 1278/1382 [00:10<00:00, 113.89files/s]









Downloading data:  92%|█████████▏| 1269/1382 [00:10<00:01, 112.78files/s]








Downloading data:  92%|█████████▏| 1275/1382 [00:10<00:00, 113.10files/s]







Downloading data:  93%|█████████▎| 1287/1382 [00:10<00:00, 113.70files/s]


















Downloading data:  93%|█████████▎| 1280/1382 [00:10<00:00, 115.62files/s]

Downloading data:  93%|█████████▎| 1284/1382 [00:10<00:00, 114.53files/s]


Downloading data:  92%|█████████▏| 1271/1382 [00:10<00:00, 112.10files/s]










Downloading data:  92%|█████████▏| 1278/1382 [00:10<00:00, 113.59files/s]






Downloading data:  92%|█████████▏| 1276/1382 [00:10<00:00, 113.94files/s]




Downloading data:  93%|█████████▎| 1279/1382 [00:10<00:00, 114.75files/s]











Downloading data:  92%|█████████▏| 1276/1382 [00:10<00:00, 115.63files/s]













Downloading data:  92%|█████████▏| 1276/1382 [00:10<00:00, 114.48files/s]

















Downloading data:  92%|█████████▏| 1275/1382 [00:11<00:00, 116.17files/s]



Downloading data:  92%|█████████▏| 1272/1382 [00:11<00:00, 114.19files/s]
















Downloading data:  93%|█████████▎| 1287/1382 [00:11<00:00, 115.71files/s]
Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 126.65files/s]




















 ... (more hidden) ...














Downloading data:  94%|█████████▎| 1294/1382 [00:11<00:00, 115.57files/s]
Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 126.49files/s]
















Downloading data:  94%|█████████▎| 1294/1382 [00:11<00:00, 114.80files/s]












Downloading data:  93%|█████████▎| 1286/1382 [00:11<00:00, 114.15files/s]
Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 126.47files/s]










Downloading data:  93%|█████████▎| 1281/1382 [00:11<00:00, 113.62files/s]





Downloading data:  93%|█████████▎| 1290/1382 [00:11<00:00, 112.81files/s]
Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 126.29files/s]



















Downloading data:  93%|█████████▎| 1292/1382 [00:11<00:00, 116.71files/s]







Downloading data:  94%|█████████▍| 1299/1382 [00:11<00:00, 115.20files/s]

Downloading data:  94%|█████████▍| 1296/1382 [00:11<00:00, 115.28files/s]








Downloading data:  93%|█████████▎| 1288/1382 [00:11<00:00, 115.71files/s]










Downloading data:  93%|█████████▎| 1290/1382 [00:11<00:00, 115.14files/s]


Downloading data:  93%|█████████▎| 1283/1382 [00:11<00:00, 114.04files/s]






Downloading data:  93%|█████████▎| 1288/1382 [00:11<00:00, 114.71files/s]




Downloading data:  93%|█████████▎| 1291/1382 [00:11<00:00, 116.04files/s]
Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 126.05files/s]

Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 125.87files/s]

Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 125.94files/s]












Downloading data:  93%|█████████▎| 1289/1382 [00:11<00:00, 117.02files/s]













Downloading data:  93%|█████████▎| 1288/1382 [00:11<00:00, 115.48files/s]
Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 125.79files/s]

Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 125.69files/s]

Downloading data: 100%|██████████| 1382/1382 [00:10<00:00, 125.73files/s]


















Downloading data:  93%|█████████▎| 1288/1382 [00:11<00:00, 118.40files/s]



Downloading data:  93%|█████████▎| 1284/1382 [00:11<00:00, 114.59files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 125.47files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 125.45files/s]

















Downloading data:  94%|█████████▍| 1300/1382 [00:11<00:00, 118.61files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 125.39files/s]















Downloading data:  95%|█████████▍| 1307/1382 [00:11<00:00, 118.81files/s]



















 ... (more hidden) ...
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 125.24files/s]
















Downloading data:  95%|█████████▍| 1307/1382 [00:11<00:00, 118.68files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 125.17files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 125.21files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 125.16files/s]













Downloading data:  94%|█████████▍| 1299/1382 [00:11<00:00, 117.08files/s]





Downloading data:  94%|█████████▍| 1302/1382 [00:11<00:00, 114.84files/s]









Downloading data:  94%|█████████▎| 1294/1382 [00:11<00:00, 116.73files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 124.95files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 125.04files/s]



















Downloading data:  94%|█████████▍| 1305/1382 [00:11<00:00, 119.41files/s]







Downloading data:  95%|█████████▍| 1312/1382 [00:11<00:00, 118.38files/s]

Downloading data:  95%|█████████▍| 1309/1382 [00:11<00:00, 117.59files/s]








Downloading data:  94%|█████████▍| 1301/1382 [00:11<00:00, 118.98files/s]










Downloading data:  94%|█████████▍| 1303/1382 [00:11<00:00, 118.77files/s]


Downloading data:  94%|█████████▍| 1296/1382 [00:11<00:00, 117.90files/s]






Downloading data:  94%|█████████▍| 1302/1382 [00:11<00:00, 120.34files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 124.66files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 124.56files/s]





Downloading data:  94%|█████████▍| 1305/1382 [00:11<00:00, 119.56files/s]











Downloading data:  94%|█████████▍| 1303/1382 [00:11<00:00, 122.36files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 124.64files/s]














Downloading data:  94%|█████████▍| 1302/1382 [00:11<00:00, 120.61files/s]



Downloading data:  94%|█████████▍| 1298/1382 [00:11<00:00, 121.50files/s]

















Downloading data:  94%|█████████▍| 1303/1382 [00:11<00:00, 126.03files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 124.19files/s]

















Downloading data:  95%|█████████▌| 1316/1382 [00:11<00:00, 128.50files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 124.12files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 124.01files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 124.03files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 124.00files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.95files/s]




















 ... (more hidden) ...















Downloading data:  96%|█████████▌| 1322/1382 [00:11<00:00, 127.11files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.97files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.94files/s]















Downloading data:  96%|█████████▌| 1323/1382 [00:11<00:00, 126.03files/s]









Downloading data:  95%|█████████▍| 1309/1382 [00:11<00:00, 125.18files/s]





Downloading data:  95%|█████████▌| 1317/1382 [00:11<00:00, 123.57files/s]












Downloading data:  95%|█████████▌| 1315/1382 [00:11<00:00, 127.25files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.67files/s]



















Downloading data:  96%|█████████▌| 1320/1382 [00:11<00:00, 127.22files/s]

Downloading data:  96%|█████████▌| 1324/1382 [00:11<00:00, 126.84files/s]







Downloading data:  96%|█████████▌| 1327/1382 [00:11<00:00, 125.79files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.50files/s]









Downloading data:  95%|█████████▌| 1316/1382 [00:11<00:00, 126.29files/s]










Downloading data:  95%|█████████▌| 1318/1382 [00:11<00:00, 126.27files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.52files/s]



Downloading data:  95%|█████████▍| 1311/1382 [00:11<00:00, 125.13files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.40files/s]







Downloading data:  95%|█████████▌| 1317/1382 [00:11<00:00, 128.72files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.44files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.25files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.21files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.30files/s]












Downloading data:  95%|█████████▌| 1318/1382 [00:11<00:00, 129.87files/s]




Downloading data:  96%|█████████▌| 1322/1382 [00:11<00:00, 131.37files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.28files/s]














Downloading data:  95%|█████████▌| 1318/1382 [00:11<00:00, 130.96files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.08files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 123.08files/s]




Downloading data:  95%|█████████▌| 1313/1382 [00:11<00:00, 128.92files/s]

















Downloading data:  95%|█████████▌| 1319/1382 [00:11<00:00, 134.65files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.86files/s]

















Downloading data:  96%|█████████▋| 1332/1382 [00:11<00:00, 136.25files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.70files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.68files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.69files/s]




















 ... (more hidden) ...















Downloading data:  97%|█████████▋| 1339/1382 [00:11<00:00, 138.04files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.64files/s]















Downloading data:  97%|█████████▋| 1341/1382 [00:11<00:00, 139.55files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.33files/s]










Downloading data:  96%|█████████▌| 1327/1382 [00:11<00:00, 137.88files/s]












Downloading data:  96%|█████████▋| 1332/1382 [00:11<00:00, 137.19files/s]





Downloading data:  97%|█████████▋| 1334/1382 [00:11<00:00, 134.03files/s]

Downloading data:  97%|█████████▋| 1341/1382 [00:11<00:00, 139.48files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.28files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.21files/s]











Downloading data:  97%|█████████▋| 1336/1382 [00:11<00:00, 141.65files/s]








Downloading data:  96%|█████████▋| 1332/1382 [00:11<00:00, 135.87files/s]


















Downloading data:  97%|█████████▋| 1337/1382 [00:11<00:00, 137.06files/s]







Downloading data:  97%|█████████▋| 1344/1382 [00:11<00:00, 136.86files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.23files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.31files/s]



Downloading data:  96%|█████████▌| 1328/1382 [00:11<00:00, 137.96files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 122.10files/s]







Downloading data:  97%|█████████▋| 1335/1382 [00:11<00:00, 143.44files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.97files/s]












Downloading data:  97%|█████████▋| 1336/1382 [00:11<00:00, 144.46files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.93files/s]





Downloading data:  97%|█████████▋| 1341/1382 [00:11<00:00, 146.94files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.92files/s]














Downloading data:  97%|█████████▋| 1337/1382 [00:11<00:00, 145.95files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.60files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.74files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.81files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.75files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.66files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.66files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.61files/s]




Downloading data:  96%|█████████▋| 1332/1382 [00:11<00:00, 145.57files/s]

















Downloading data:  97%|█████████▋| 1338/1382 [00:11<00:00, 150.74files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.52files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.42files/s]

















Downloading data:  98%|█████████▊| 1352/1382 [00:11<00:00, 153.97files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.26files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.28files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.30files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.11files/s]




















 ... (more hidden) ...















Downloading data:  98%|█████████▊| 1361/1382 [00:11<00:00, 160.98files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.05files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.09files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.08files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 121.15files/s]















Downloading data:  99%|█████████▉| 1365/1382 [00:11<00:00, 167.34files/s]





Downloading data:  98%|█████████▊| 1357/1382 [00:11<00:00, 161.48files/s]









Downloading data:  98%|█████████▊| 1351/1382 [00:11<00:00, 166.69files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.96files/s]













Downloading data:  98%|█████████▊| 1356/1382 [00:11<00:00, 166.16files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.96files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.95files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.95files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.60files/s]


Downloading data:  99%|█████████▉| 1366/1382 [00:11<00:00, 170.68files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.82files/s]









Downloading data:  98%|█████████▊| 1357/1382 [00:11<00:00, 169.14files/s]


















Downloading data:  99%|█████████▊| 1362/1382 [00:11<00:00, 169.73files/s]







Downloading data:  99%|█████████▉| 1369/1382 [00:11<00:00, 169.56files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.82files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.80files/s]



Downloading data:  98%|█████████▊| 1353/1382 [00:11<00:00, 170.56files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.69files/s]











Downloading data:  98%|█████████▊| 1361/1382 [00:11<00:00, 171.96files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.76files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.66files/s]







Downloading data:  98%|█████████▊| 1361/1382 [00:11<00:00, 177.57files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.74files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.43files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.55files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.44files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.45files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.35files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.41files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.36files/s]












Downloading data:  99%|█████████▉| 1366/1382 [00:11<00:00, 189.05files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.29files/s]





Downloading data:  99%|█████████▉| 1374/1382 [00:11<00:00, 199.20files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.18files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.24files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.16files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.02files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.26files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.24files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.18files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 119.98files/s]














Downloading data:  99%|█████████▉| 1374/1382 [00:11<00:00, 210.62files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.12files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.07files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.17files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 119.99files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 119.97files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.04files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.02files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.00files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.12files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.01files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.02files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.01files/s]




Downloading data:  99%|█████████▉| 1373/1382 [00:11<00:00, 223.08files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.00files/s]


















Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 235.67files/s]
Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 120.02files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 119.87files/s]

Downloading data: 100%|██████████| 1382/1382 [00:11<00:00, 119.84files/s]
Finished 128 processes
Unpacked 128 objects
Downloading took 0.0 min

Computing checksums:   4%|▍         | 7775/176798 [00:05<01:48, 1554.93it/s]
Computing checksums:   4%|▍         | 7931/176798 [00:05<01:48, 1552.85it/s]
Computing checksums:   5%|▍         | 8083/176798 [00:05<01:48, 1549.95it/s]
Computing checksums:   5%|▍         | 8304/176798 [00:05<01:46, 1583.73it/s]
Computing checksums:   5%|▍         | 8482/176798 [00:05<01:46, 1575.83it/s]
Computing checksums:   5%|▍         | 8650/176798 [00:05<01:47, 1565.59it/s]
Computing checksums:   5%|▍         | 8811/176798 [00:05<01:48, 1550.57it/s]
Computing checksums:   5%|▌         | 8967/176798 [00:05<01:48, 1543.71it/s]
Computing checksums:   5%|▌         | 9121/176798 [00:05<01:49, 1536.91it/s]
Computing checksums:   5%|▌         | 9274/176798 [00:05<01:49, 1527.10it/s]
Computing checksums:   5%|▌         | 9426/176798 [00:06<01:50, 1518.86it/s]
Computing checksums:   5%|▌         | 9593/176798 [00:06<01:47, 1552.47it/s]
Computing checksums:   6%|▌         | 9785/176798 [00:06<01:41, 1641.68it/s]
Computing checksums:   6%|▌         | 9952/176798 [00:06<01:44, 1598.65it/s]
Computing checksums:   6%|▌         | 10114/176798 [00:06<01:46, 1567.75it/s]
Computing checksums:   6%|▌         | 10272/176798 [00:06<01:47, 1548.18it/s]
Computing checksums:   6%|▌         | 10428/176798 [00:06<01:48, 1532.67it/s]
Computing checksums:   6%|▌         | 10582/176798 [00:06<01:49, 1517.30it/s]
Computing checksums:   6%|▌         | 10734/176798 [00:06<01:50, 1508.18it/s]
Computing checksums:   6%|▌         | 10885/176798 [00:07<01:50, 1502.32it/s]
Computing checksums:   6%|▋         | 11095/176798 [00:07<01:39, 1672.46it/s]
Computing checksums:   6%|▋         | 11263/176798 [00:07<01:42, 1611.46it/s]
Computing checksums:   6%|▋         | 11425/176798 [00:07<01:44, 1575.81it/s]
Computing checksums:   7%|▋         | 11584/176798 [00:07<01:46, 1552.95it/s]
Computing checksums:   7%|▋         | 11740/176798 [00:07<01:47, 1529.68it/s]
Computing checksums:   7%|▋         | 11894/176798 [00:07<01:48, 1526.12it/s]
Computing checksums:   7%|▋         | 12047/176798 [00:07<01:48, 1519.44it/s]
Computing checksums:   7%|▋         | 12200/176798 [00:07<01:48, 1513.82it/s]
Computing checksums:   7%|▋         | 12376/176798 [00:07<01:43, 1584.91it/s]
Computing checksums:   7%|▋         | 12560/176798 [00:08<01:39, 1657.08it/s]
Computing checksums:   7%|▋         | 12726/176798 [00:08<01:41, 1611.35it/s]
Computing checksums:   7%|▋         | 12888/176798 [00:08<01:44, 1561.54it/s]
Computing checksums:   7%|▋         | 13045/176798 [00:08<01:46, 1531.75it/s]
Computing checksums:   7%|▋         | 13199/176798 [00:08<01:48, 1513.52it/s]
Computing checksums:   8%|▊         | 13351/176798 [00:08<01:51, 1471.90it/s]
Computing checksums:   8%|▊         | 13501/176798 [00:08<01:50, 1478.86it/s]
Computing checksums:   8%|▊         | 13652/176798 [00:08<01:49, 1485.77it/s]
Computing checksums:   8%|▊         | 13851/176798 [00:08<01:39, 1632.03it/s]
Computing checksums:   8%|▊         | 14015/176798 [00:08<01:42, 1592.80it/s]
Computing checksums:   8%|▊         | 14175/176798 [00:09<01:46, 1522.81it/s]
Computing checksums:   8%|▊         | 14329/176798 [00:09<01:47, 1514.73it/s]
Computing checksums:   8%|▊         | 14482/176798 [00:09<01:47, 1514.64it/s]
Computing checksums:   8%|▊         | 14634/176798 [00:09<01:47, 1511.98it/s]
Computing checksums:   8%|▊         | 14786/176798 [00:09<01:50, 1461.36it/s]
Computing checksums:   8%|▊         | 14936/176798 [00:09<01:50, 1469.76it/s]
Computing checksums:   9%|▊         | 15086/176798 [00:09<01:49, 1478.45it/s]
Computing checksums:   9%|▊         | 15279/176798 [00:09<01:40, 1609.80it/s]
Computing checksums:   9%|▊         | 15441/176798 [00:09<01:42, 1577.18it/s]
Computing checksums:   9%|▉         | 15600/176798 [00:10<01:43, 1554.71it/s]
Computing checksums:   9%|▉         | 15756/176798 [00:10<01:49, 1474.91it/s]
Computing checksums:   9%|▉         | 15907/176798 [00:10<01:48, 1483.60it/s]
Computing checksums:   9%|▉         | 16061/176798 [00:10<01:47, 1497.90it/s]
Computing checksums:   9%|▉         | 16214/176798 [00:10<01:46, 1506.60it/s]
Computing checksums:   9%|▉         | 16367/176798 [00:10<01:46, 1511.53it/s]
Computing checksums:   9%|▉         | 16522/176798 [00:10<01:45, 1522.05it/s]
Computing checksums:   9%|▉         | 16709/176798 [00:10<01:38, 1622.31it/s]
Computing checksums:  10%|▉         | 16872/176798 [00:10<01:40, 1584.10it/s]
Computing checksums:  10%|▉         | 17031/176798 [00:10<01:42, 1560.44it/s]
Computing checksums:  10%|▉         | 17188/176798 [00:11<01:43, 1544.87it/s]
Computing checksums:  10%|▉         | 17343/176798 [00:11<01:43, 1535.43it/s]
Computing checksums:  10%|▉         | 17497/176798 [00:11<01:44, 1527.84it/s]
Computing checksums:  10%|▉         | 17650/176798 [00:11<01:45, 1514.30it/s]
Computing checksums:  10%|█         | 17804/176798 [00:11<01:44, 1519.14it/s]
Computing checksums:  10%|█         | 17984/176798 [00:11<01:39, 1599.04it/s]
Computing checksums:  10%|█         | 18145/176798 [00:11<01:40, 1574.60it/s]
Computing checksums:  10%|█         | 18303/176798 [00:11<01:41, 1563.29it/s]
Computing checksums:  10%|█         | 18460/176798 [00:11<01:41, 1553.52it/s]
Computing checksums:  11%|█         | 18616/176798 [00:12<01:42, 1543.87it/s]
Computing checksums:  11%|█         | 18771/176798 [00:12<01:42, 1536.33it/s]
Computing checksums:  11%|█         | 18925/176798 [00:12<01:42, 1537.02it/s]
Computing checksums:  11%|█         | 19081/176798 [00:12<01:42, 1542.06it/s]
Computing checksums:  11%|█         | 19237/176798 [00:12<01:41, 1546.78it/s]
Computing checksums:  11%|█         | 19394/176798 [00:12<01:41, 1551.14it/s]
Computing checksums:  11%|█         | 19550/176798 [00:12<01:41, 1546.11it/s]
Computing checksums:  11%|█         | 19705/176798 [00:12<01:41, 1545.11it/s]
Computing checksums:  11%|█         | 19860/176798 [00:12<01:41, 1546.15it/s]
Computing checksums:  11%|█▏        | 20016/176798 [00:12<01:41, 1549.98it/s]
Computing checksums:  11%|█▏        | 20172/176798 [00:13<01:41, 1548.24it/s]
Computing checksums:  11%|█▏        | 20327/176798 [00:13<01:41, 1547.86it/s]
Computing checksums:  12%|█▏        | 20482/176798 [00:13<01:41, 1546.71it/s]
Computing checksums:  12%|█▏        | 20638/176798 [00:13<01:40, 1547.75it/s]
Computing checksums:  12%|█▏        | 20793/176798 [00:13<01:41, 1542.96it/s]
Computing checksums:  12%|█▏        | 20948/176798 [00:13<01:41, 1542.68it/s]
Computing checksums:  12%|█▏        | 21103/176798 [00:13<01:41, 1539.65it/s]
Computing checksums:  12%|█▏        | 21257/176798 [00:13<01:41, 1533.18it/s]
Computing checksums:  12%|█▏        | 21411/176798 [00:13<01:41, 1530.33it/s]
Computing checksums:  12%|█▏        | 21565/176798 [00:13<01:41, 1529.88it/s]
Computing checksums:  12%|█▏        | 21719/176798 [00:14<01:41, 1531.29it/s]
Computing checksums:  12%|█▏        | 21874/176798 [00:14<01:40, 1535.38it/s]
Computing checksums:  12%|█▏        | 22031/176798 [00:14<01:40, 1543.79it/s]
Computing checksums:  13%|█▎        | 22187/176798 [00:14<01:40, 1546.01it/s]
Computing checksums:  13%|█▎        | 22342/176798 [00:14<01:40, 1543.46it/s]
Computing checksums:  13%|█▎        | 22497/176798 [00:14<01:39, 1543.60it/s]
Computing checksums:  13%|█▎        | 22652/176798 [00:14<01:39, 1543.00it/s]
Computing checksums:  13%|█▎        | 22807/176798 [00:14<01:39, 1542.66it/s]
Computing checksums:  13%|█▎        | 22962/176798 [00:14<01:39, 1543.03it/s]
Computing checksums:  13%|█▎        | 23117/176798 [00:14<01:39, 1538.94it/s]
Computing checksums:  13%|█▎        | 23271/176798 [00:15<01:40, 1534.84it/s]
Computing checksums:  13%|█▎        | 23425/176798 [00:15<01:39, 1535.42it/s]
Computing checksums:  13%|█▎        | 23580/176798 [00:15<01:39, 1537.43it/s]
Computing checksums:  13%|█▎        | 23736/176798 [00:15<01:39, 1543.32it/s]
Computing checksums:  14%|█▎        | 23893/176798 [00:15<01:38, 1548.33it/s]
Computing checksums:  14%|█▎        | 24049/176798 [00:15<01:38, 1551.44it/s]
Computing checksums:  14%|█▎        | 24205/176798 [00:15<01:38, 1552.06it/s]
Computing checksums:  14%|█▍        | 24361/176798 [00:15<01:38, 1551.79it/s]
Computing checksums:  14%|█▍        | 24518/176798 [00:15<01:37, 1554.89it/s]
Computing checksums:  14%|█▍        | 24675/176798 [00:15<01:37, 1558.51it/s]
Computing checksums:  14%|█▍        | 24831/176798 [00:16<01:37, 1557.40it/s]
Computing checksums:  14%|█▍        | 24987/176798 [00:16<01:37, 1557.15it/s]
Computing checksums:  14%|█▍        | 25143/176798 [00:16<01:37, 1554.11it/s]
Computing checksums:  14%|█▍        | 25299/176798 [00:16<01:37, 1555.08it/s]
Computing checksums:  14%|█▍        | 25455/176798 [00:16<01:37, 1547.04it/s]
Computing checksums:  14%|█▍        | 25610/176798 [00:16<01:37, 1547.40it/s]
Computing checksums:  15%|█▍        | 25766/176798 [00:16<01:37, 1549.33it/s]
Computing checksums:  15%|█▍        | 25921/176798 [00:16<01:37, 1546.49it/s]
Computing checksums:  15%|█▍        | 26076/176798 [00:16<01:37, 1546.38it/s]
Computing checksums:  15%|█▍        | 26231/176798 [00:16<01:37, 1547.35it/s]
Computing checksums:  15%|█▍        | 26386/176798 [00:17<01:37, 1547.31it/s]
Computing checksums:  15%|█▌        | 26541/176798 [00:17<01:37, 1547.11it/s]
Computing checksums:  15%|█▌        | 26699/176798 [00:17<01:36, 1554.50it/s]
Computing checksums:  15%|█▌        | 26856/176798 [00:17<01:36, 1557.44it/s]
Computing checksums:  15%|█▌        | 27014/176798 [00:17<01:35, 1561.41it/s]
Computing checksums:  15%|█▌        | 27171/176798 [00:17<01:35, 1563.54it/s]
Computing checksums:  15%|█▌        | 27329/176798 [00:17<01:35, 1567.59it/s]
Computing checksums:  16%|█▌        | 27486/176798 [00:17<01:35, 1567.40it/s]
Computing checksums:  16%|█▌        | 27645/176798 [00:17<01:34, 1572.94it/s]
Computing checksums:  16%|█▌        | 27803/176798 [00:17<01:34, 1574.15it/s]
Computing checksums:  16%|█▌        | 27961/176798 [00:18<01:34, 1573.31it/s]
Computing checksums:  16%|█▌        | 28119/176798 [00:18<01:34, 1570.47it/s]
Computing checksums:  16%|█▌        | 28278/176798 [00:18<01:34, 1574.00it/s]
Computing checksums:  16%|█▌        | 28437/176798 [00:18<01:34, 1577.03it/s]
Computing checksums:  16%|█▌        | 28596/176798 [00:18<01:33, 1580.38it/s]
Computing checksums:  16%|█▋        | 28755/176798 [00:18<01:33, 1583.16it/s]
Computing checksums:  16%|█▋        | 28914/176798 [00:18<01:33, 1581.37it/s]
Computing checksums:  16%|█▋        | 29073/176798 [00:18<01:33, 1572.76it/s]
Computing checksums:  17%|█▋        | 29231/176798 [00:18<01:33, 1573.27it/s]
Computing checksums:  17%|█▋        | 29389/176798 [00:18<01:33, 1573.45it/s]
Computing checksums:  17%|█▋        | 29547/176798 [00:19<01:33, 1571.27it/s]
Computing checksums:  17%|█▋        | 29705/176798 [00:19<01:33, 1572.87it/s]
Computing checksums:  17%|█▋        | 29863/176798 [00:19<01:33, 1572.79it/s]
Computing checksums:  17%|█▋        | 30022/176798 [00:19<01:33, 1575.55it/s]
Computing checksums:  17%|█▋        | 30181/176798 [00:19<01:32, 1577.89it/s]
Computing checksums:  17%|█▋        | 30341/176798 [00:19<01:32, 1582.12it/s]
Computing checksums:  17%|█▋        | 30500/176798 [00:19<01:32, 1580.50it/s]
Computing checksums:  17%|█▋        | 30659/176798 [00:19<01:32, 1582.41it/s]
Computing checksums:  17%|█▋        | 30818/176798 [00:19<01:32, 1584.51it/s]
Computing checksums:  18%|█▊        | 30977/176798 [00:19<01:31, 1585.15it/s]
Computing checksums:  18%|█▊        | 31136/176798 [00:20<01:31, 1585.93it/s]
Computing checksums:  18%|█▊        | 31296/176798 [00:20<01:31, 1588.79it/s]
Computing checksums:  18%|█▊        | 31455/176798 [00:20<01:31, 1588.88it/s]
Computing checksums:  18%|█▊        | 31614/176798 [00:20<01:31, 1586.64it/s]
Computing checksums:  18%|█▊        | 31773/176798 [00:20<01:31, 1584.57it/s]
Computing checksums:  18%|█▊        | 31932/176798 [00:20<01:32, 1559.30it/s]
Computing checksums:  18%|█▊        | 32091/176798 [00:20<01:32, 1566.75it/s]
Computing checksums:  18%|█▊        | 32250/176798 [00:20<01:31, 1572.85it/s]
Computing checksums:  18%|█▊        | 32410/176798 [00:20<01:31, 1578.34it/s]
Computing checksums:  18%|█▊        | 32569/176798 [00:20<01:31, 1580.24it/s]
Computing checksums:  19%|█▊        | 32728/176798 [00:21<01:31, 1583.09it/s]
Computing checksums:  19%|█▊        | 32887/176798 [00:21<01:30, 1584.54it/s]
Computing checksums:  19%|█▊        | 33046/176798 [00:21<01:30, 1579.78it/s]
Computing checksums:  19%|█▉        | 33206/176798 [00:21<01:30, 1585.16it/s]
Computing checksums:  19%|█▉        | 33367/176798 [00:21<01:30, 1591.42it/s]
Computing checksums:  19%|█▉        | 33528/176798 [00:21<01:29, 1594.33it/s]
Computing checksums:  19%|█▉        | 33688/176798 [00:21<01:29, 1592.28it/s]
Computing checksums:  19%|█▉        | 33848/176798 [00:21<01:29, 1592.15it/s]
Computing checksums:  19%|█▉        | 34008/176798 [00:21<01:29, 1592.55it/s]
Computing checksums:  19%|█▉        | 34169/176798 [00:21<01:29, 1596.59it/s]
Computing checksums:  19%|█▉        | 34330/176798 [00:22<01:29, 1598.32it/s]
Computing checksums:  20%|█▉        | 34491/176798 [00:22<01:28, 1600.32it/s]
Computing checksums:  20%|█▉        | 34653/176798 [00:22<01:28, 1604.50it/s]
Computing checksums:  20%|█▉        | 34815/176798 [00:22<01:28, 1606.83it/s]
Computing checksums:  20%|█▉        | 34977/176798 [00:22<01:28, 1607.78it/s]
Computing checksums:  20%|█▉        | 35139/176798 [00:22<01:27, 1610.94it/s]
Computing checksums:  20%|█▉        | 35301/176798 [00:22<01:27, 1612.93it/s]
Computing checksums:  20%|██        | 35463/176798 [00:22<01:27, 1612.71it/s]
Computing checksums:  20%|██        | 35625/176798 [00:22<01:28, 1598.47it/s]
Computing checksums:  20%|██        | 35785/176798 [00:22<01:28, 1598.17it/s]
Computing checksums:  20%|██        | 35946/176798 [00:23<01:28, 1599.29it/s]
Computing checksums:  20%|██        | 36107/176798 [00:23<01:27, 1599.88it/s]
Computing checksums:  21%|██        | 36268/176798 [00:23<01:27, 1601.50it/s]
Computing checksums:  21%|██        | 36429/176798 [00:23<01:27, 1602.62it/s]
Computing checksums:  21%|██        | 36590/176798 [00:23<01:27, 1604.13it/s]
Computing checksums:  21%|██        | 36752/176798 [00:23<01:27, 1606.97it/s]
Computing checksums:  21%|██        | 36913/176798 [00:23<01:27, 1600.67it/s]
Computing checksums:  21%|██        | 37076/176798 [00:23<01:26, 1606.56it/s]
Computing checksums:  21%|██        | 37239/176798 [00:23<01:26, 1610.87it/s]
Computing checksums:  21%|██        | 37402/176798 [00:23<01:26, 1616.30it/s]
Computing checksums:  21%|██        | 37564/176798 [00:24<01:26, 1616.85it/s]
Computing checksums:  21%|██▏       | 37728/176798 [00:24<01:25, 1623.36it/s]
Computing checksums:  21%|██▏       | 37892/176798 [00:24<01:25, 1625.61it/s]
Computing checksums:  22%|██▏       | 38055/176798 [00:24<01:25, 1626.42it/s]
Computing checksums:  22%|██▏       | 38218/176798 [00:24<01:25, 1626.65it/s]
Computing checksums:  22%|██▏       | 38381/176798 [00:24<01:25, 1623.13it/s]
Computing checksums:  22%|██▏       | 38544/176798 [00:24<01:25, 1622.06it/s]
Computing checksums:  22%|██▏       | 38707/176798 [00:24<01:25, 1623.30it/s]
Computing checksums:  22%|██▏       | 38870/176798 [00:24<01:25, 1618.06it/s]
Computing checksums:  22%|██▏       | 39032/176798 [00:24<01:25, 1613.67it/s]
Computing checksums:  22%|██▏       | 39194/176798 [00:25<01:25, 1605.80it/s]
Computing checksums:  22%|██▏       | 39355/176798 [00:25<01:25, 1603.00it/s]
Computing checksums:  22%|██▏       | 39516/176798 [00:25<01:25, 1599.89it/s]
Computing checksums:  22%|██▏       | 39677/176798 [00:25<01:25, 1601.83it/s]
Computing checksums:  23%|██▎       | 39840/176798 [00:25<01:25, 1609.73it/s]
Computing checksums:  23%|██▎       | 40003/176798 [00:25<01:24, 1612.95it/s]
Computing checksums:  23%|██▎       | 40165/176798 [00:25<01:24, 1610.74it/s]
Computing checksums:  23%|██▎       | 40328/176798 [00:25<01:24, 1613.51it/s]
Computing checksums:  23%|██▎       | 40490/176798 [00:25<01:24, 1614.01it/s]
Computing checksums:  23%|██▎       | 40653/176798 [00:25<01:24, 1616.31it/s]
Computing checksums:  23%|██▎       | 40815/176798 [00:26<01:24, 1606.99it/s]
Computing checksums:  23%|██▎       | 40976/176798 [00:26<01:26, 1566.91it/s]
Computing checksums:  23%|██▎       | 41133/176798 [00:26<01:31, 1489.83it/s]
Computing checksums:  23%|██▎       | 41283/176798 [00:26<01:33, 1442.10it/s]
Computing checksums:  23%|██▎       | 41428/176798 [00:26<01:35, 1415.47it/s]
Computing checksums:  24%|██▎       | 41571/176798 [00:26<01:36, 1396.64it/s]
Computing checksums:  24%|██▎       | 41711/176798 [00:26<01:37, 1382.26it/s]
Computing checksums:  24%|██▎       | 41850/176798 [00:26<01:38, 1367.57it/s]
Computing checksums:  24%|██▎       | 41987/176798 [00:26<01:39, 1356.39it/s]
Computing checksums:  24%|██▍       | 42123/176798 [00:27<01:40, 1346.57it/s]
Computing checksums:  24%|██▍       | 42258/176798 [00:27<01:40, 1335.24it/s]
Computing checksums:  24%|██▍       | 42392/176798 [00:27<01:40, 1332.60it/s]
Computing checksums:  24%|██▍       | 42526/176798 [00:27<01:40, 1334.16it/s]
Computing checksums:  24%|██▍       | 42661/176798 [00:27<01:40, 1337.78it/s]
Computing checksums:  24%|██▍       | 42796/176798 [00:27<01:40, 1339.56it/s]
Computing checksums:  24%|██▍       | 42931/176798 [00:27<01:39, 1340.04it/s]
Computing checksums:  24%|██▍       | 43066/176798 [00:27<01:39, 1340.21it/s]
Computing checksums:  24%|██▍       | 43201/176798 [00:27<01:39, 1341.51it/s]
Computing checksums:  25%|██▍       | 43336/176798 [00:27<01:39, 1343.76it/s]
Computing checksums:  25%|██▍       | 43472/176798 [00:28<01:39, 1346.28it/s]
Computing checksums:  25%|██▍       | 43608/176798 [00:28<01:38, 1348.99it/s]
Computing checksums:  25%|██▍       | 43744/176798 [00:28<01:38, 1352.04it/s]
Computing checksums:  25%|██▍       | 43882/176798 [00:28<01:37, 1357.82it/s]
Computing checksums:  25%|██▍       | 44030/176798 [00:28<01:35, 1392.03it/s]
Computing checksums:  25%|██▍       | 44198/176798 [00:28<01:29, 1475.58it/s]
Computing checksums:  25%|██▌       | 44365/176798 [00:28<01:26, 1532.80it/s]
Computing checksums:  25%|██▌       | 44532/176798 [00:28<01:24, 1572.10it/s]
Computing checksums:  25%|██▌       | 44699/176798 [00:28<01:22, 1599.87it/s]
Computing checksums:  25%|██▌       | 44866/176798 [00:28<01:21, 1617.88it/s]
Computing checksums:  25%|██▌       | 45034/176798 [00:29<01:20, 1634.16it/s]
Computing checksums:  26%|██▌       | 45202/176798 [00:29<01:19, 1646.68it/s]
Computing checksums:  26%|██▌       | 45370/176798 [00:29<01:19, 1655.05it/s]
Computing checksums:  26%|██▌       | 45536/176798 [00:29<01:19, 1653.97it/s]
Computing checksums:  26%|██▌       | 45704/176798 [00:29<01:19, 1658.08it/s]
Computing checksums:  26%|██▌       | 45873/176798 [00:29<01:18, 1666.56it/s]
Computing checksums:  26%|██▌       | 46040/176798 [00:29<01:18, 1666.63it/s]
Computing checksums:  26%|██▌       | 46209/176798 [00:29<01:18, 1671.63it/s]
Computing checksums:  26%|██▌       | 46379/176798 [00:29<01:17, 1677.19it/s]
Computing checksums:  26%|██▋       | 46548/176798 [00:29<01:17, 1678.41it/s]
Computing checksums:  26%|██▋       | 46716/176798 [00:30<01:17, 1675.95it/s]
Computing checksums:  27%|██▋       | 46886/176798 [00:30<01:17, 1682.25it/s]
Computing checksums:  27%|██▋       | 47055/176798 [00:30<01:17, 1682.87it/s]
Computing checksums:  27%|██▋       | 47224/176798 [00:30<01:17, 1681.54it/s]
Computing checksums:  27%|██▋       | 47393/176798 [00:30<01:16, 1681.52it/s]
Computing checksums:  27%|██▋       | 47562/176798 [00:30<01:16, 1679.76it/s]
Computing checksums:  27%|██▋       | 47730/176798 [00:30<01:16, 1679.33it/s]
Computing checksums:  27%|██▋       | 47899/176798 [00:30<01:16, 1679.79it/s]
Computing checksums:  27%|██▋       | 48067/176798 [00:30<01:16, 1678.17it/s]
Computing checksums:  27%|██▋       | 48238/176798 [00:30<01:16, 1686.43it/s]
Computing checksums:  27%|██▋       | 48407/176798 [00:31<01:16, 1686.12it/s]
Computing checksums:  27%|██▋       | 48576/176798 [00:31<01:16, 1682.14it/s]
Computing checksums:  28%|██▊       | 48745/176798 [00:31<01:16, 1676.15it/s]
Computing checksums:  28%|██▊       | 48913/176798 [00:31<01:16, 1665.22it/s]
Computing checksums:  28%|██▊       | 49080/176798 [00:31<01:16, 1660.99it/s]
Computing checksums:  28%|██▊       | 49247/176798 [00:31<01:16, 1659.01it/s]
Computing checksums:  28%|██▊       | 49413/176798 [00:31<01:16, 1659.25it/s]
Computing checksums:  28%|██▊       | 49580/176798 [00:31<01:16, 1660.36it/s]
Computing checksums:  28%|██▊       | 49749/176798 [00:31<01:16, 1667.37it/s]
Computing checksums:  28%|██▊       | 49919/176798 [00:31<01:15, 1674.35it/s]
Computing checksums:  28%|██▊       | 50088/176798 [00:32<01:15, 1677.85it/s]
Computing checksums:  28%|██▊       | 50257/176798 [00:32<01:15, 1680.76it/s]
Computing checksums:  29%|██▊       | 50426/176798 [00:32<01:15, 1682.85it/s]
Computing checksums:  29%|██▊       | 50595/176798 [00:32<01:14, 1682.76it/s]
Computing checksums:  29%|██▊       | 50764/176798 [00:32<01:14, 1684.72it/s]
Computing checksums:  29%|██▉       | 50933/176798 [00:32<01:14, 1685.95it/s]
Computing checksums:  29%|██▉       | 51102/176798 [00:32<01:14, 1685.26it/s]
Computing checksums:  29%|██▉       | 51272/176798 [00:32<01:14, 1686.87it/s]
Computing checksums:  29%|██▉       | 51441/176798 [00:32<01:14, 1685.99it/s]
Computing checksums:  29%|██▉       | 51610/176798 [00:32<01:14, 1685.11it/s]
Computing checksums:  29%|██▉       | 51779/176798 [00:33<01:14, 1685.17it/s]
Computing checksums:  29%|██▉       | 51948/176798 [00:33<01:14, 1684.50it/s]
Computing checksums:  29%|██▉       | 52117/176798 [00:33<01:14, 1684.47it/s]
Computing checksums:  30%|██▉       | 52286/176798 [00:33<01:13, 1685.74it/s]
Computing checksums:  30%|██▉       | 52456/176798 [00:33<01:13, 1687.46it/s]
Computing checksums:  30%|██▉       | 52625/176798 [00:33<01:13, 1685.74it/s]
Computing checksums:  30%|██▉       | 52794/176798 [00:33<01:14, 1672.74it/s]
Computing checksums:  30%|██▉       | 52963/176798 [00:33<01:13, 1675.45it/s]
Computing checksums:  30%|███       | 53133/176798 [00:33<01:13, 1680.60it/s]
Computing checksums:  30%|███       | 53303/176798 [00:33<01:13, 1684.52it/s]
Computing checksums:  30%|███       | 53473/176798 [00:34<01:13, 1689.12it/s]
Computing checksums:  30%|███       | 53644/176798 [00:34<01:12, 1692.75it/s]
Computing checksums:  30%|███       | 53815/176798 [00:34<01:12, 1697.31it/s]
Computing checksums:  31%|███       | 53986/176798 [00:34<01:12, 1699.56it/s]
Computing checksums:  31%|███       | 54158/176798 [00:34<01:12, 1702.96it/s]
Computing checksums:  31%|███       | 54330/176798 [00:34<01:11, 1706.38it/s]
Computing checksums:  31%|███       | 54502/176798 [00:34<01:11, 1708.79it/s]
Computing checksums:  31%|███       | 54674/176798 [00:34<01:11, 1710.18it/s]
Computing checksums:  31%|███       | 54846/176798 [00:34<01:11, 1707.50it/s]
Computing checksums:  31%|███       | 55017/176798 [00:34<01:11, 1704.17it/s]
Computing checksums:  31%|███       | 55188/176798 [00:35<01:11, 1703.37it/s]
Computing checksums:  31%|███▏      | 55360/176798 [00:35<01:11, 1708.02it/s]
Computing checksums:  31%|███▏      | 55532/176798 [00:35<01:10, 1711.52it/s]
Computing checksums:  32%|███▏      | 55704/176798 [00:35<01:10, 1712.96it/s]
Computing checksums:  32%|███▏      | 55877/176798 [00:35<01:10, 1716.29it/s]
Computing checksums:  32%|███▏      | 56049/176798 [00:35<01:10, 1709.57it/s]
Computing checksums:  32%|███▏      | 56223/176798 [00:35<01:10, 1716.61it/s]
Computing checksums:  32%|███▏      | 56395/176798 [00:35<01:10, 1701.70it/s]
Computing checksums:  32%|███▏      | 56568/176798 [00:35<01:10, 1710.00it/s]
Computing checksums:  32%|███▏      | 56740/176798 [00:36<01:10, 1709.03it/s]
Computing checksums:  32%|███▏      | 56912/176798 [00:36<01:10, 1709.45it/s]
Computing checksums:  32%|███▏      | 57084/176798 [00:36<01:09, 1710.42it/s]
Computing checksums:  32%|███▏      | 57256/176798 [00:36<01:09, 1712.98it/s]
Computing checksums:  32%|███▏      | 57428/176798 [00:36<01:09, 1714.35it/s]
Computing checksums:  33%|███▎      | 57600/176798 [00:36<01:09, 1714.68it/s]
Computing checksums:  33%|███▎      | 57773/176798 [00:36<01:09, 1716.46it/s]
Computing checksums:  33%|███▎      | 57945/176798 [00:36<01:09, 1715.05it/s]
Computing checksums:  33%|███▎      | 58119/176798 [00:36<01:09, 1719.67it/s]
Computing checksums:  33%|███▎      | 58294/176798 [00:36<01:08, 1726.54it/s]
Computing checksums:  33%|███▎      | 58467/176798 [00:37<01:08, 1726.33it/s]
Computing checksums:  33%|███▎      | 58640/176798 [00:37<01:08, 1726.04it/s]
Computing checksums:  33%|███▎      | 58813/176798 [00:37<01:08, 1726.95it/s]
Computing checksums:  33%|███▎      | 58987/176798 [00:37<01:08, 1729.09it/s]
Computing checksums:  33%|███▎      | 59161/176798 [00:37<01:07, 1730.95it/s]
Computing checksums:  34%|███▎      | 59335/176798 [00:37<01:07, 1731.24it/s]
Computing checksums:  34%|███▎      | 59509/176798 [00:37<01:07, 1732.20it/s]
Computing checksums:  34%|███▍      | 59683/176798 [00:37<01:07, 1732.08it/s]
Computing checksums:  34%|███▍      | 59858/176798 [00:37<01:07, 1735.13it/s]
Computing checksums:  34%|███▍      | 60036/176798 [00:37<01:06, 1746.01it/s]
Computing checksums:  34%|███▍      | 60211/176798 [00:38<01:08, 1694.61it/s]
Computing checksums:  34%|███▍      | 60381/176798 [00:38<01:14, 1568.30it/s]
Computing checksums:  34%|███▍      | 60540/176798 [00:38<01:18, 1489.36it/s]
Computing checksums:  34%|███▍      | 60691/176798 [00:38<01:20, 1444.36it/s]
Computing checksums:  34%|███▍      | 60837/176798 [00:38<01:21, 1419.45it/s]
Computing checksums:  34%|███▍      | 60980/176798 [00:38<01:22, 1400.88it/s]
Computing checksums:  35%|███▍      | 61121/176798 [00:38<01:23, 1393.37it/s]
Computing checksums:  35%|███▍      | 61261/176798 [00:38<01:25, 1353.05it/s]
Computing checksums:  35%|███▍      | 61399/176798 [00:38<01:24, 1359.32it/s]
Computing checksums:  35%|███▍      | 61536/176798 [00:39<01:26, 1328.17it/s]
Computing checksums:  35%|███▍      | 61670/176798 [00:39<01:26, 1325.05it/s]
Computing checksums:  35%|███▍      | 61805/176798 [00:39<01:26, 1332.12it/s]
Computing checksums:  35%|███▌      | 61939/176798 [00:39<01:29, 1279.43it/s]
Computing checksums:  35%|███▌      | 62079/176798 [00:39<01:27, 1312.14it/s]
Computing checksums:  35%|███▌      | 62220/176798 [00:39<01:25, 1338.23it/s]
Computing checksums:  35%|███▌      | 62362/176798 [00:39<01:24, 1359.70it/s]
Computing checksums:  35%|███▌      | 62503/176798 [00:39<01:23, 1373.79it/s]
Computing checksums:  35%|███▌      | 62643/176798 [00:39<01:22, 1379.64it/s]
Computing checksums:  36%|███▌      | 62782/176798 [00:39<01:24, 1348.18it/s]
Computing checksums:  36%|███▌      | 62919/176798 [00:40<01:24, 1354.11it/s]
Computing checksums:  36%|███▌      | 63058/176798 [00:40<01:23, 1362.77it/s]
Computing checksums:  36%|███▌      | 63195/176798 [00:40<01:23, 1363.54it/s]
Computing checksums:  36%|███▌      | 63336/176798 [00:40<01:22, 1374.63it/s]
Computing checksums:  36%|███▌      | 63479/176798 [00:40<01:21, 1390.82it/s]
Computing checksums:  36%|███▌      | 63631/176798 [00:40<01:19, 1427.71it/s]
Computing checksums:  36%|███▌      | 63807/176798 [00:40<01:14, 1526.43it/s]
Computing checksums:  36%|███▌      | 63985/176798 [00:40<01:10, 1601.00it/s]
Computing checksums:  36%|███▋      | 64164/176798 [00:40<01:08, 1655.09it/s]
Computing checksums:  36%|███▋      | 64344/176798 [00:40<01:06, 1695.92it/s]
Computing checksums:  36%|███▋      | 64524/176798 [00:41<01:05, 1725.22it/s]
Computing checksums:  37%|███▋      | 64705/176798 [00:41<01:04, 1747.78it/s]
Computing checksums:  37%|███▋      | 64886/176798 [00:41<01:03, 1765.07it/s]
Computing checksums:  37%|███▋      | 65067/176798 [00:41<01:02, 1777.36it/s]
Computing checksums:  37%|███▋      | 65246/176798 [00:41<01:02, 1779.18it/s]
Computing checksums:  37%|███▋      | 65424/176798 [00:41<01:02, 1778.07it/s]
Computing checksums:  37%|███▋      | 65602/176798 [00:41<01:02, 1778.06it/s]
Computing checksums:  37%|███▋      | 65781/176798 [00:41<01:02, 1779.96it/s]
Computing checksums:  37%|███▋      | 65961/176798 [00:41<01:02, 1783.33it/s]
Computing checksums:  37%|███▋      | 66141/176798 [00:41<01:01, 1785.71it/s]
Computing checksums:  38%|███▊      | 66320/176798 [00:42<01:01, 1786.32it/s]
Computing checksums:  38%|███▊      | 66500/176798 [00:42<01:01, 1787.43it/s]
Computing checksums:  38%|███▊      | 66679/176798 [00:42<01:01, 1787.63it/s]
Computing checksums:  38%|███▊      | 66859/176798 [00:42<01:01, 1790.53it/s]
Computing checksums:  38%|███▊      | 67039/176798 [00:42<01:01, 1790.65it/s]
Computing checksums:  38%|███▊      | 67219/176798 [00:42<01:01, 1789.89it/s]
Computing checksums:  38%|███▊      | 67399/176798 [00:42<01:01, 1792.89it/s]
Computing checksums:  38%|███▊      | 67579/176798 [00:42<01:00, 1792.27it/s]
Computing checksums:  38%|███▊      | 67760/176798 [00:42<01:00, 1795.22it/s]
Computing checksums:  38%|███▊      | 67940/176798 [00:42<01:00, 1794.23it/s]
Computing checksums:  39%|███▊      | 68120/176798 [00:43<01:00, 1793.27it/s]
Computing checksums:  39%|███▊      | 68300/176798 [00:43<01:00, 1794.98it/s]
Computing checksums:  39%|███▊      | 68482/176798 [00:43<01:00, 1802.10it/s]
Computing checksums:  39%|███▉      | 68664/176798 [00:43<00:59, 1806.93it/s]
Computing checksums:  39%|███▉      | 68845/176798 [00:43<00:59, 1800.62it/s]
Computing checksums:  39%|███▉      | 69026/176798 [00:43<00:59, 1798.65it/s]
Computing checksums:  39%|███▉      | 69207/176798 [00:43<00:59, 1801.40it/s]
Computing checksums:  39%|███▉      | 69389/176798 [00:43<00:59, 1804.56it/s]
Computing checksums:  39%|███▉      | 69571/176798 [00:43<00:59, 1808.81it/s]
Computing checksums:  39%|███▉      | 69754/176798 [00:43<00:59, 1812.60it/s]
Computing checksums:  40%|███▉      | 69936/176798 [00:44<00:59, 1810.52it/s]
Computing checksums:  40%|███▉      | 70118/176798 [00:44<00:59, 1801.99it/s]
Computing checksums:  40%|███▉      | 70301/176798 [00:44<00:58, 1808.75it/s]
Computing checksums:  40%|███▉      | 70483/176798 [00:44<00:58, 1810.06it/s]
Computing checksums:  40%|███▉      | 70666/176798 [00:44<00:58, 1813.63it/s]
Computing checksums:  40%|████      | 70848/176798 [00:44<00:58, 1815.42it/s]
Computing checksums:  40%|████      | 71031/176798 [00:44<00:58, 1818.31it/s]
Computing checksums:  40%|████      | 71215/176798 [00:44<00:57, 1823.32it/s]
Computing checksums:  40%|████      | 71399/176798 [00:44<00:57, 1828.15it/s]
Computing checksums:  40%|████      | 71583/176798 [00:44<00:57, 1829.54it/s]
Computing checksums:  41%|████      | 71766/176798 [00:45<00:57, 1828.60it/s]
Computing checksums:  41%|████      | 71949/176798 [00:45<00:57, 1825.15it/s]
Computing checksums:  41%|████      | 72134/176798 [00:45<00:57, 1831.21it/s]
Computing checksums:  41%|████      | 72318/176798 [00:45<00:57, 1832.76it/s]
Computing checksums:  41%|████      | 72502/176798 [00:45<01:00, 1720.39it/s]
Computing checksums:  41%|████      | 72684/176798 [00:45<00:59, 1746.78it/s]
Computing checksums:  41%|████      | 72865/176798 [00:45<00:58, 1763.07it/s]
Computing checksums:  41%|████▏     | 73046/176798 [00:45<00:58, 1776.77it/s]
Computing checksums:  41%|████▏     | 73228/176798 [00:45<00:57, 1788.99it/s]
Computing checksums:  42%|████▏     | 73408/176798 [00:45<00:59, 1750.34it/s]
Computing checksums:  42%|████▏     | 73585/176798 [00:46<00:58, 1754.85it/s]
Computing checksums:  42%|████▏     | 73766/176798 [00:46<00:58, 1769.67it/s]
Computing checksums:  42%|████▏     | 73944/176798 [00:46<00:59, 1722.41it/s]
Computing checksums:  42%|████▏     | 74117/176798 [00:46<01:00, 1703.94it/s]
Computing checksums:  42%|████▏     | 74299/176798 [00:46<00:59, 1736.90it/s]
Computing checksums:  42%|████▏     | 74474/176798 [00:46<00:58, 1739.46it/s]
Computing checksums:  42%|████▏     | 74658/176798 [00:46<00:57, 1767.89it/s]
Computing checksums:  42%|████▏     | 74841/176798 [00:46<00:57, 1785.44it/s]
Computing checksums:  42%|████▏     | 75024/176798 [00:46<00:56, 1796.86it/s]
Computing checksums:  43%|████▎     | 75204/176798 [00:47<00:56, 1785.41it/s]
Computing checksums:  43%|████▎     | 75387/176798 [00:47<00:56, 1797.48it/s]
Computing checksums:  43%|████▎     | 75572/176798 [00:47<00:55, 1810.79it/s]
Computing checksums:  43%|████▎     | 75757/176798 [00:47<00:55, 1821.27it/s]
Computing checksums:  43%|████▎     | 75943/176798 [00:47<00:55, 1830.30it/s]
Computing checksums:  43%|████▎     | 76129/176798 [00:47<00:54, 1838.09it/s]
Computing checksums:  43%|████▎     | 76315/176798 [00:47<00:54, 1844.17it/s]
Computing checksums:  43%|████▎     | 76501/176798 [00:47<00:54, 1848.82it/s]
Computing checksums:  43%|████▎     | 76687/176798 [00:47<00:54, 1849.58it/s]
Computing checksums:  43%|████▎     | 76873/176798 [00:47<00:53, 1851.00it/s]
Computing checksums:  44%|████▎     | 77059/176798 [00:48<00:53, 1851.74it/s]
Computing checksums:  44%|████▎     | 77246/176798 [00:48<00:53, 1855.54it/s]
Computing checksums:  44%|████▍     | 77434/176798 [00:48<00:53, 1860.69it/s]
Computing checksums:  44%|████▍     | 77622/176798 [00:48<00:53, 1866.17it/s]
Computing checksums:  44%|████▍     | 77810/176798 [00:48<00:52, 1867.91it/s]
Computing checksums:  44%|████▍     | 77997/176798 [00:48<00:52, 1868.27it/s]
Computing checksums:  44%|████▍     | 78186/176798 [00:48<00:52, 1872.91it/s]
Computing checksums:  44%|████▍     | 78375/176798 [00:48<00:52, 1877.78it/s]
Computing checksums:  44%|████▍     | 78564/176798 [00:48<00:52, 1878.58it/s]
Computing checksums:  45%|████▍     | 78753/176798 [00:48<00:52, 1880.73it/s]
Computing checksums:  45%|████▍     | 78942/176798 [00:49<00:52, 1876.85it/s]
Computing checksums:  45%|████▍     | 79132/176798 [00:49<00:51, 1882.83it/s]
Computing checksums:  45%|████▍     | 79321/176798 [00:49<00:51, 1883.60it/s]
Computing checksums:  45%|████▍     | 79510/176798 [00:49<00:51, 1882.42it/s]
Computing checksums:  45%|████▌     | 79699/176798 [00:49<00:51, 1884.17it/s]
Computing checksums:  45%|████▌     | 79890/176798 [00:49<00:51, 1889.65it/s]
Computing checksums:  45%|████▌     | 80079/176798 [00:49<00:51, 1889.60it/s]
Computing checksums:  45%|████▌     | 80268/176798 [00:49<00:51, 1889.65it/s]
Computing checksums:  46%|████▌     | 80457/176798 [00:49<00:51, 1886.63it/s]
Computing checksums:  46%|████▌     | 80646/176798 [00:49<00:50, 1887.51it/s]
Computing checksums:  46%|████▌     | 80835/176798 [00:50<00:50, 1887.04it/s]
Computing checksums:  46%|████▌     | 81024/176798 [00:50<00:50, 1886.13it/s]
Computing checksums:  46%|████▌     | 81215/176798 [00:50<00:50, 1890.92it/s]
Computing checksums:  46%|████▌     | 81405/176798 [00:50<00:50, 1892.52it/s]
Computing checksums:  46%|████▌     | 81596/176798 [00:50<00:50, 1896.16it/s]
Computing checksums:  46%|████▋     | 81788/176798 [00:50<00:49, 1902.15it/s]
Computing checksums:  46%|████▋     | 81981/176798 [00:50<00:49, 1908.63it/s]
Computing checksums:  46%|████▋     | 82174/176798 [00:50<00:49, 1914.73it/s]
Computing checksums:  47%|████▋     | 82367/176798 [00:50<00:49, 1916.51it/s]
Computing checksums:  47%|████▋     | 82560/176798 [00:50<00:49, 1919.94it/s]
Computing checksums:  47%|████▋     | 82752/176798 [00:51<00:49, 1917.08it/s]
Computing checksums:  47%|████▋     | 82944/176798 [00:51<00:49, 1915.36it/s]
Computing checksums:  47%|████▋     | 83136/176798 [00:51<00:48, 1916.66it/s]
Computing checksums:  47%|████▋     | 83330/176798 [00:51<00:48, 1921.30it/s]
Computing checksums:  47%|████▋     | 83524/176798 [00:51<00:48, 1926.39it/s]
Computing checksums:  47%|████▋     | 83717/176798 [00:51<00:48, 1924.08it/s]
Computing checksums:  47%|████▋     | 83911/176798 [00:51<00:48, 1927.24it/s]
Computing checksums:  48%|████▊     | 84105/176798 [00:51<00:48, 1928.24it/s]
Computing checksums:  48%|████▊     | 84298/176798 [00:51<00:47, 1928.56it/s]
Computing checksums:  48%|████▊     | 84492/176798 [00:51<00:47, 1931.52it/s]
Computing checksums:  48%|████▊     | 84686/176798 [00:52<00:47, 1931.80it/s]
Computing checksums:  48%|████▊     | 84880/176798 [00:52<00:47, 1927.41it/s]
Computing checksums:  48%|████▊     | 85073/176798 [00:52<00:47, 1923.16it/s]
Computing checksums:  48%|████▊     | 85266/176798 [00:52<00:47, 1917.56it/s]
Computing checksums:  48%|████▊     | 85462/176798 [00:52<00:47, 1929.22it/s]
Computing checksums:  48%|████▊     | 85656/176798 [00:52<00:47, 1930.28it/s]
Computing checksums:  49%|████▊     | 85850/176798 [00:52<00:47, 1925.25it/s]
Computing checksums:  49%|████▊     | 86043/176798 [00:52<00:47, 1925.95it/s]
Computing checksums:  49%|████▉     | 86237/176798 [00:52<00:46, 1929.19it/s]
Computing checksums:  49%|████▉     | 86433/176798 [00:52<00:46, 1935.50it/s]
Computing checksums:  49%|████▉     | 86627/176798 [00:53<00:46, 1935.54it/s]
Computing checksums:  49%|████▉     | 86821/176798 [00:53<00:46, 1933.23it/s]
Computing checksums:  49%|████▉     | 87015/176798 [00:53<00:46, 1934.12it/s]
Computing checksums:  49%|████▉     | 87210/176798 [00:53<00:46, 1936.80it/s]
Computing checksums:  49%|████▉     | 87404/176798 [00:53<00:46, 1919.67it/s]
Computing checksums:  50%|████▉     | 87599/176798 [00:53<00:46, 1925.97it/s]
Computing checksums:  50%|████▉     | 87794/176798 [00:53<00:46, 1930.32it/s]
Computing checksums:  50%|████▉     | 87990/176798 [00:53<00:45, 1937.16it/s]
Computing checksums:  50%|████▉     | 88187/176798 [00:53<00:45, 1946.15it/s]
Computing checksums:  50%|████▉     | 88384/176798 [00:53<00:45, 1951.18it/s]
Computing checksums:  50%|█████     | 88580/176798 [00:54<00:45, 1950.06it/s]
Computing checksums:  50%|█████     | 88776/176798 [00:54<00:45, 1947.86it/s]
Computing checksums:  50%|█████     | 88972/176798 [00:54<00:45, 1949.79it/s]
Computing checksums:  50%|█████     | 89171/176798 [00:54<00:44, 1960.01it/s]
Computing checksums:  51%|█████     | 89368/176798 [00:54<00:44, 1957.33it/s]
Computing checksums:  51%|█████     | 89565/176798 [00:54<00:44, 1958.39it/s]
Computing checksums:  51%|█████     | 89761/176798 [00:54<00:44, 1955.75it/s]
Computing checksums:  51%|█████     | 89957/176798 [00:54<00:44, 1947.82it/s]
Computing checksums:  51%|█████     | 90152/176798 [00:54<00:44, 1940.99it/s]
Computing checksums:  51%|█████     | 90347/176798 [00:54<00:45, 1908.33it/s]
Computing checksums:  51%|█████     | 90538/176798 [00:55<00:45, 1890.29it/s]
Computing checksums:  51%|█████▏    | 90729/176798 [00:55<00:45, 1895.96it/s]
Computing checksums:  51%|█████▏    | 90924/176798 [00:55<00:44, 1909.05it/s]
Computing checksums:  52%|█████▏    | 91115/176798 [00:55<00:45, 1890.41it/s]
Computing checksums:  52%|█████▏    | 91310/176798 [00:55<00:44, 1906.40it/s]
Computing checksums:  52%|█████▏    | 91506/176798 [00:55<00:44, 1919.73it/s]
Computing checksums:  52%|█████▏    | 91702/176798 [00:55<00:44, 1930.37it/s]
Computing checksums:  52%|█████▏    | 91899/176798 [00:55<00:43, 1940.52it/s]
Computing checksums:  52%|█████▏    | 92095/176798 [00:55<00:43, 1944.21it/s]
Computing checksums:  52%|█████▏    | 92292/176798 [00:55<00:43, 1951.16it/s]
Computing checksums:  52%|█████▏    | 92489/176798 [00:56<00:43, 1954.02it/s]
Computing checksums:  52%|█████▏    | 92686/176798 [00:56<00:42, 1958.65it/s]
Computing checksums:  53%|█████▎    | 92884/176798 [00:56<00:42, 1963.38it/s]
Computing checksums:  53%|█████▎    | 93081/176798 [00:56<00:42, 1964.70it/s]
Computing checksums:  53%|█████▎    | 93279/176798 [00:56<00:42, 1966.85it/s]
Computing checksums:  53%|█████▎    | 93476/176798 [00:56<00:42, 1967.71it/s]
Computing checksums:  53%|█████▎    | 93675/176798 [00:56<00:42, 1971.94it/s]
Computing checksums:  53%|█████▎    | 93874/176798 [00:56<00:41, 1976.75it/s]
Computing checksums:  53%|█████▎    | 94073/176798 [00:56<00:41, 1978.02it/s]
Computing checksums:  53%|█████▎    | 94271/176798 [00:56<00:41, 1976.35it/s]
Computing checksums:  53%|█████▎    | 94469/176798 [00:57<00:41, 1962.11it/s]
Computing checksums:  54%|█████▎    | 94668/176798 [00:57<00:41, 1969.79it/s]
Computing checksums:  54%|█████▎    | 94868/176798 [00:57<00:41, 1976.42it/s]
Computing checksums:  54%|█████▍    | 95069/176798 [00:57<00:41, 1983.61it/s]
Computing checksums:  54%|█████▍    | 95268/176798 [00:57<00:41, 1973.61it/s]
Computing checksums:  54%|█████▍    | 95466/176798 [00:57<00:41, 1972.07it/s]
Computing checksums:  54%|█████▍    | 95665/176798 [00:57<00:41, 1974.75it/s]
Computing checksums:  54%|█████▍    | 95866/176798 [00:57<00:40, 1982.86it/s]
Computing checksums:  54%|█████▍    | 96066/176798 [00:57<00:40, 1987.80it/s]
Computing checksums:  54%|█████▍    | 96266/176798 [00:57<00:40, 1990.78it/s]
Computing checksums:  55%|█████▍    | 96467/176798 [00:58<00:40, 1994.20it/s]
Computing checksums:  55%|█████▍    | 96667/176798 [00:58<00:44, 1788.95it/s]
Computing checksums:  55%|█████▍    | 96856/176798 [00:58<00:44, 1815.68it/s]
Computing checksums:  55%|█████▍    | 97048/176798 [00:58<00:43, 1844.72it/s]
Computing checksums:  55%|█████▌    | 97244/176798 [00:58<00:42, 1877.89it/s]
Computing checksums:  55%|█████▌    | 97444/176798 [00:58<00:41, 1910.73it/s]
Computing checksums:  55%|█████▌    | 97644/176798 [00:58<00:40, 1934.29it/s]
Computing checksums:  55%|█████▌    | 97842/176798 [00:58<00:40, 1946.51it/s]
Computing checksums:  55%|█████▌    | 98038/176798 [00:58<00:40, 1949.03it/s]
Computing checksums:  56%|█████▌    | 98234/176798 [00:59<00:40, 1951.70it/s]
Computing checksums:  56%|█████▌    | 98432/176798 [00:59<00:39, 1959.67it/s]
Computing checksums:  56%|█████▌    | 98632/176798 [00:59<00:39, 1969.68it/s]
Computing checksums:  56%|█████▌    | 98831/176798 [00:59<00:39, 1974.66it/s]
Computing checksums:  56%|█████▌    | 99030/176798 [00:59<00:39, 1977.40it/s]
Computing checksums:  56%|█████▌    | 99229/176798 [00:59<00:39, 1980.89it/s]
Computing checksums:  56%|█████▌    | 99429/176798 [00:59<00:39, 1983.70it/s]
Computing checksums:  56%|█████▋    | 99628/176798 [00:59<00:38, 1980.29it/s]
Computing checksums:  56%|█████▋    | 99827/176798 [00:59<00:39, 1971.50it/s]
Computing checksums:  57%|█████▋    | 100025/176798 [00:59<00:38, 1971.95it/s]
Computing checksums:  57%|█████▋    | 100223/176798 [01:00<00:38, 1972.83it/s]
Computing checksums:  57%|█████▋    | 100422/176798 [01:00<00:38, 1977.57it/s]
Computing checksums:  57%|█████▋    | 100621/176798 [01:00<00:38, 1978.64it/s]
Computing checksums:  57%|█████▋    | 100820/176798 [01:00<00:38, 1979.79it/s]
Computing checksums:  57%|█████▋    | 101020/176798 [01:00<00:38, 1982.76it/s]
Computing checksums:  57%|█████▋    | 101219/176798 [01:00<00:38, 1983.74it/s]
Computing checksums:  57%|█████▋    | 101418/176798 [01:00<00:38, 1981.11it/s]
Computing checksums:  57%|█████▋    | 101618/176798 [01:00<00:37, 1986.36it/s]
Computing checksums:  58%|█████▊    | 101818/176798 [01:00<00:37, 1990.30it/s]
Computing checksums:  58%|█████▊    | 102019/176798 [01:00<00:37, 1993.42it/s]
Computing checksums:  58%|█████▊    | 102220/176798 [01:01<00:37, 1995.73it/s]
Computing checksums:  58%|█████▊    | 102420/176798 [01:01<00:37, 1996.97it/s]
Computing checksums:  58%|█████▊    | 102620/176798 [01:01<00:37, 1997.49it/s]
Computing checksums:  58%|█████▊    | 102820/176798 [01:01<00:37, 1998.15it/s]
Computing checksums:  58%|█████▊    | 103021/176798 [01:01<00:36, 1999.31it/s]
Computing checksums:  58%|█████▊    | 103221/176798 [01:01<00:36, 1999.44it/s]
Computing checksums:  58%|█████▊    | 103422/176798 [01:01<00:36, 2002.37it/s]
Computing checksums:  59%|█████▊    | 103624/176798 [01:01<00:36, 2005.18it/s]
Computing checksums:  59%|█████▊    | 103825/176798 [01:01<00:36, 2005.05it/s]
Computing checksums:  59%|█████▉    | 104027/176798 [01:01<00:36, 2008.21it/s]
Computing checksums:  59%|█████▉    | 104228/176798 [01:02<00:36, 2007.06it/s]
Computing checksums:  59%|█████▉    | 104430/176798 [01:02<00:36, 2008.78it/s]
Computing checksums:  59%|█████▉    | 104632/176798 [01:02<00:35, 2009.83it/s]
Computing checksums:  59%|█████▉    | 104833/176798 [01:02<00:35, 2009.32it/s]
Computing checksums:  59%|█████▉    | 105036/176798 [01:02<00:35, 2013.02it/s]
Computing checksums:  60%|█████▉    | 105240/176798 [01:02<00:35, 2019.46it/s]
Computing checksums:  60%|█████▉    | 105443/176798 [01:02<00:35, 2020.97it/s]
Computing checksums:  60%|█████▉    | 105647/176798 [01:02<00:35, 2024.08it/s]
Computing checksums:  60%|█████▉    | 105850/176798 [01:02<00:35, 2019.37it/s]
Computing checksums:  60%|█████▉    | 106053/176798 [01:02<00:35, 2020.11it/s]
Computing checksums:  60%|██████    | 106256/176798 [01:03<00:34, 2015.95it/s]
Computing checksums:  60%|██████    | 106458/176798 [01:03<00:34, 2015.94it/s]
Computing checksums:  60%|██████    | 106660/176798 [01:03<00:34, 2015.43it/s]
Computing checksums:  60%|██████    | 106862/176798 [01:03<00:34, 2016.78it/s]
Computing checksums:  61%|██████    | 107064/176798 [01:03<00:34, 2015.84it/s]
Computing checksums:  61%|██████    | 107266/176798 [01:03<00:34, 2016.37it/s]
Computing checksums:  61%|██████    | 107470/176798 [01:03<00:34, 2021.13it/s]
Computing checksums:  61%|██████    | 107673/176798 [01:03<00:34, 2021.33it/s]
Computing checksums:  61%|██████    | 107876/176798 [01:03<00:34, 2023.11it/s]
Computing checksums:  61%|██████    | 108079/176798 [01:03<00:33, 2025.01it/s]
Computing checksums:  61%|██████    | 108282/176798 [01:04<00:33, 2018.38it/s]
Computing checksums:  61%|██████▏   | 108484/176798 [01:04<00:33, 2015.64it/s]
Computing checksums:  61%|██████▏   | 108686/176798 [01:04<00:33, 2012.92it/s]
Computing checksums:  62%|██████▏   | 108889/176798 [01:04<00:33, 2017.95it/s]
Computing checksums:  62%|██████▏   | 109092/176798 [01:04<00:33, 2020.23it/s]
Computing checksums:  62%|██████▏   | 109298/176798 [01:04<00:33, 2030.74it/s]
Computing checksums:  62%|██████▏   | 109503/176798 [01:04<00:33, 2033.61it/s]
Computing checksums:  62%|██████▏   | 109707/176798 [01:04<00:32, 2033.57it/s]
Computing checksums:  62%|██████▏   | 109913/176798 [01:04<00:32, 2040.28it/s]
Computing checksums:  62%|██████▏   | 110118/176798 [01:04<00:32, 2038.72it/s]
Computing checksums:  62%|██████▏   | 110322/176798 [01:05<00:32, 2037.94it/s]
Computing checksums:  63%|██████▎   | 110528/176798 [01:05<00:32, 2044.22it/s]
Computing checksums:  63%|██████▎   | 110733/176798 [01:05<00:32, 2044.72it/s]
Computing checksums:  63%|██████▎   | 110940/176798 [01:05<00:32, 2050.15it/s]
Computing checksums:  63%|██████▎   | 111146/176798 [01:05<00:32, 2051.56it/s]
Computing checksums:  63%|██████▎   | 111353/176798 [01:05<00:31, 2056.82it/s]
Computing checksums:  63%|██████▎   | 111559/176798 [01:05<00:31, 2054.92it/s]
Computing checksums:  63%|██████▎   | 111766/176798 [01:05<00:31, 2057.97it/s]
Computing checksums:  63%|██████▎   | 111972/176798 [01:05<00:31, 2056.22it/s]
Computing checksums:  63%|██████▎   | 112179/176798 [01:05<00:31, 2058.78it/s]
Computing checksums:  64%|██████▎   | 112386/176798 [01:06<00:31, 2060.49it/s]
Computing checksums:  64%|██████▎   | 112595/176798 [01:06<00:31, 2067.33it/s]
Computing checksums:  64%|██████▍   | 112805/176798 [01:06<00:30, 2075.84it/s]
Computing checksums:  64%|██████▍   | 113014/176798 [01:06<00:30, 2078.94it/s]
Computing checksums:  64%|██████▍   | 113222/176798 [01:06<00:30, 2074.76it/s]
Computing checksums:  64%|██████▍   | 113432/176798 [01:06<00:30, 2081.43it/s]
Computing checksums:  64%|██████▍   | 113641/176798 [01:06<00:30, 2076.43it/s]
Computing checksums:  64%|██████▍   | 113851/176798 [01:06<00:30, 2083.43it/s]
Computing checksums:  65%|██████▍   | 114061/176798 [01:06<00:30, 2087.26it/s]
Computing checksums:  65%|██████▍   | 114271/176798 [01:06<00:29, 2090.99it/s]
Computing checksums:  65%|██████▍   | 114482/176798 [01:07<00:29, 2095.47it/s]
Computing checksums:  65%|██████▍   | 114695/176798 [01:07<00:29, 2103.81it/s]
Computing checksums:  65%|██████▍   | 114908/176798 [01:07<00:29, 2109.08it/s]
Computing checksums:  65%|██████▌   | 115120/176798 [01:07<00:29, 2110.51it/s]
Computing checksums:  65%|██████▌   | 115333/176798 [01:07<00:29, 2113.94it/s]
Computing checksums:  65%|██████▌   | 115547/176798 [01:07<00:28, 2119.52it/s]
Computing checksums:  65%|██████▌   | 115761/176798 [01:07<00:28, 2122.86it/s]
Computing checksums:  66%|██████▌   | 115974/176798 [01:07<00:28, 2121.72it/s]
Computing checksums:  66%|██████▌   | 116187/176798 [01:07<00:28, 2115.00it/s]
Computing checksums:  66%|██████▌   | 116399/176798 [01:07<00:28, 2104.69it/s]
Computing checksums:  66%|██████▌   | 116610/176798 [01:08<00:28, 2103.84it/s]
Computing checksums:  66%|██████▌   | 116821/176798 [01:08<00:28, 2099.91it/s]
Computing checksums:  66%|██████▌   | 117033/176798 [01:08<00:28, 2105.35it/s]
Computing checksums:  66%|██████▋   | 117244/176798 [01:08<00:28, 2094.19it/s]
Computing checksums:  66%|██████▋   | 117454/176798 [01:08<00:28, 2084.72it/s]
Computing checksums:  67%|██████▋   | 117663/176798 [01:08<00:28, 2072.83it/s]
Computing checksums:  67%|██████▋   | 117874/176798 [01:08<00:28, 2080.92it/s]
Computing checksums:  67%|██████▋   | 118083/176798 [01:08<00:29, 2012.42it/s]
Computing checksums:  67%|██████▋   | 118291/176798 [01:08<00:28, 2032.02it/s]
Computing checksums:  67%|██████▋   | 118501/176798 [01:08<00:28, 2049.41it/s]
Computing checksums:  67%|██████▋   | 118708/176798 [01:09<00:28, 2054.95it/s]
Computing checksums:  67%|██████▋   | 118920/176798 [01:09<00:27, 2073.19it/s]
Computing checksums:  67%|██████▋   | 119133/176798 [01:09<00:27, 2087.80it/s]
Computing checksums:  68%|██████▊   | 119342/176798 [01:09<00:28, 1985.30it/s]
Computing checksums:  68%|██████▊   | 119552/176798 [01:09<00:28, 2016.57it/s]
Computing checksums:  68%|██████▊   | 119765/176798 [01:09<00:27, 2047.02it/s]
Computing checksums:  68%|██████▊   | 119979/176798 [01:09<00:27, 2072.90it/s]
Computing checksums:  68%|██████▊   | 120194/176798 [01:09<00:27, 2094.93it/s]
Computing checksums:  68%|██████▊   | 120407/176798 [01:09<00:26, 2104.92it/s]
Computing checksums:  68%|██████▊   | 120618/176798 [01:10<00:27, 2032.62it/s]
Computing checksums:  68%|██████▊   | 120827/176798 [01:10<00:27, 2048.14it/s]
Computing checksums:  68%|██████▊   | 121037/176798 [01:10<00:27, 2060.91it/s]
Computing checksums:  69%|██████▊   | 121245/176798 [01:10<00:26, 2065.89it/s]
Computing checksums:  69%|██████▊   | 121452/176798 [01:10<00:26, 2050.50it/s]
Computing checksums:  69%|██████▉   | 121658/176798 [01:10<00:27, 2039.58it/s]
Computing checksums:  69%|██████▉   | 121863/176798 [01:10<00:26, 2037.28it/s]
Computing checksums:  69%|██████▉   | 122067/176798 [01:10<00:26, 2031.79it/s]
Computing checksums:  69%|██████▉   | 122272/176798 [01:10<00:26, 2035.50it/s]
Computing checksums:  69%|██████▉   | 122485/176798 [01:10<00:26, 2061.09it/s]
Computing checksums:  69%|██████▉   | 122700/176798 [01:11<00:25, 2087.18it/s]
Computing checksums:  70%|██████▉   | 122915/176798 [01:11<00:25, 2104.98it/s]
Computing checksums:  70%|██████▉   | 123133/176798 [01:11<00:25, 2124.79it/s]
Computing checksums:  70%|██████▉   | 123350/176798 [01:11<00:25, 2136.33it/s]
Computing checksums:  70%|██████▉   | 123566/176798 [01:11<00:24, 2141.25it/s]
Computing checksums:  70%|███████   | 123781/176798 [01:11<00:24, 2143.76it/s]
Computing checksums:  70%|███████   | 123996/176798 [01:11<00:24, 2141.74it/s]
Computing checksums:  70%|███████   | 124213/176798 [01:11<00:24, 2149.33it/s]
Computing checksums:  70%|███████   | 124429/176798 [01:11<00:24, 2151.52it/s]
Computing checksums:  71%|███████   | 124648/176798 [01:11<00:24, 2160.30it/s]
Computing checksums:  71%|███████   | 124867/176798 [01:12<00:23, 2168.15it/s]
Computing checksums:  71%|███████   | 125085/176798 [01:12<00:23, 2170.87it/s]
Computing checksums:  71%|███████   | 125303/176798 [01:12<00:23, 2165.90it/s]
Computing checksums:  71%|███████   | 125520/176798 [01:12<00:23, 2161.46it/s]
Computing checksums:  71%|███████   | 125737/176798 [01:12<00:23, 2160.00it/s]
Computing checksums:  71%|███████   | 125954/176798 [01:12<00:23, 2162.90it/s]
Computing checksums:  71%|███████▏  | 126174/176798 [01:12<00:23, 2171.64it/s]
Computing checksums:  71%|███████▏  | 126392/176798 [01:12<00:23, 2173.54it/s]
Computing checksums:  72%|███████▏  | 126610/176798 [01:12<00:23, 2171.71it/s]
Computing checksums:  72%|███████▏  | 126828/176798 [01:12<00:22, 2173.88it/s]
Computing checksums:  72%|███████▏  | 127046/176798 [01:13<00:22, 2174.37it/s]
Computing checksums:  72%|███████▏  | 127265/176798 [01:13<00:22, 2177.12it/s]
Computing checksums:  72%|███████▏  | 127483/176798 [01:13<00:22, 2177.38it/s]
Computing checksums:  72%|███████▏  | 127701/176798 [01:13<00:22, 2177.98it/s]
Computing checksums:  72%|███████▏  | 127921/176798 [01:13<00:22, 2182.11it/s]
Computing checksums:  72%|███████▏  | 128140/176798 [01:13<00:22, 2183.17it/s]
Computing checksums:  73%|███████▎  | 128359/176798 [01:13<00:22, 2183.70it/s]
Computing checksums:  73%|███████▎  | 128579/176798 [01:13<00:22, 2187.78it/s]
Computing checksums:  73%|███████▎  | 128799/176798 [01:13<00:21, 2188.08it/s]
Computing checksums:  73%|███████▎  | 129019/176798 [01:13<00:21, 2191.58it/s]
Computing checksums:  73%|███████▎  | 129239/176798 [01:14<00:21, 2190.47it/s]
Computing checksums:  73%|███████▎  | 129460/176798 [01:14<00:21, 2194.27it/s]
Computing checksums:  73%|███████▎  | 129681/176798 [01:14<00:21, 2196.35it/s]
Computing checksums:  73%|███████▎  | 129903/176798 [01:14<00:21, 2201.82it/s]
Computing checksums:  74%|███████▎  | 130125/176798 [01:14<00:21, 2205.05it/s]
Computing checksums:  74%|███████▎  | 130346/176798 [01:14<00:21, 2187.12it/s]
Computing checksums:  74%|███████▍  | 130568/176798 [01:14<00:21, 2195.12it/s]
Computing checksums:  74%|███████▍  | 130792/176798 [01:14<00:20, 2208.43it/s]
Computing checksums:  74%|███████▍  | 131014/176798 [01:14<00:20, 2211.76it/s]
Computing checksums:  74%|███████▍  | 131236/176798 [01:14<00:20, 2210.80it/s]
Computing checksums:  74%|███████▍  | 131458/176798 [01:15<00:20, 2210.57it/s]
Computing checksums:  74%|███████▍  | 131683/176798 [01:15<00:20, 2219.71it/s]
Computing checksums:  75%|███████▍  | 131907/176798 [01:15<00:20, 2224.12it/s]
Computing checksums:  75%|███████▍  | 132130/176798 [01:15<00:20, 2225.32it/s]
Computing checksums:  75%|███████▍  | 132353/176798 [01:15<00:19, 2226.32it/s]
Computing checksums:  75%|███████▍  | 132578/176798 [01:15<00:19, 2231.58it/s]
Computing checksums:  75%|███████▌  | 132802/176798 [01:15<00:19, 2219.21it/s]
Computing checksums:  75%|███████▌  | 133025/176798 [01:15<00:19, 2221.47it/s]
Computing checksums:  75%|███████▌  | 133248/176798 [01:15<00:19, 2223.15it/s]
Computing checksums:  75%|███████▌  | 133471/176798 [01:15<00:19, 2223.27it/s]
Computing checksums:  76%|███████▌  | 133696/176798 [01:16<00:19, 2230.24it/s]
Computing checksums:  76%|███████▌  | 133921/176798 [01:16<00:19, 2233.39it/s]
Computing checksums:  76%|███████▌  | 134145/176798 [01:16<00:19, 2231.22it/s]
Computing checksums:  76%|███████▌  | 134369/176798 [01:16<00:19, 2229.48it/s]
Computing checksums:  76%|███████▌  | 134594/176798 [01:16<00:18, 2235.33it/s]
Computing checksums:  76%|███████▋  | 134818/176798 [01:16<00:18, 2233.35it/s]
Computing checksums:  76%|███████▋  | 135042/176798 [01:16<00:18, 2233.37it/s]
Computing checksums:  77%|███████▋  | 135267/176798 [01:16<00:18, 2235.93it/s]
Computing checksums:  77%|███████▋  | 135493/176798 [01:16<00:18, 2242.65it/s]
Computing checksums:  77%|███████▋  | 135718/176798 [01:16<00:18, 2244.10it/s]
Computing checksums:  77%|███████▋  | 135943/176798 [01:17<00:18, 2238.35it/s]
Computing checksums:  77%|███████▋  | 136167/176798 [01:17<00:18, 2235.10it/s]
Computing checksums:  77%|███████▋  | 136393/176798 [01:17<00:18, 2240.44it/s]
Computing checksums:  77%|███████▋  | 136618/176798 [01:17<00:17, 2242.47it/s]
Computing checksums:  77%|███████▋  | 136843/176798 [01:17<00:17, 2243.28it/s]
Computing checksums:  78%|███████▊  | 137069/176798 [01:17<00:17, 2245.79it/s]
Computing checksums:  78%|███████▊  | 137295/176798 [01:17<00:17, 2249.44it/s]
Computing checksums:  78%|███████▊  | 137521/176798 [01:17<00:17, 2252.30it/s]
Computing checksums:  78%|███████▊  | 137748/176798 [01:17<00:17, 2257.56it/s]
Computing checksums:  78%|███████▊  | 137974/176798 [01:17<00:17, 2257.55it/s]
Computing checksums:  78%|███████▊  | 138200/176798 [01:18<00:17, 2256.74it/s]
Computing checksums:  78%|███████▊  | 138427/176798 [01:18<00:16, 2259.65it/s]
Computing checksums:  78%|███████▊  | 138655/176798 [01:18<00:16, 2262.63it/s]
Computing checksums:  79%|███████▊  | 138882/176798 [01:18<00:16, 2262.97it/s]
Computing checksums:  79%|███████▊  | 139111/176798 [01:18<00:16, 2268.78it/s]
Computing checksums:  79%|███████▉  | 139340/176798 [01:18<00:16, 2273.98it/s]
Computing checksums:  79%|███████▉  | 139568/176798 [01:18<00:16, 2274.40it/s]
Computing checksums:  79%|███████▉  | 139797/176798 [01:18<00:16, 2276.18it/s]
Computing checksums:  79%|███████▉  | 140028/176798 [01:18<00:16, 2284.65it/s]
Computing checksums:  79%|███████▉  | 140257/176798 [01:18<00:16, 2278.92it/s]
Computing checksums:  79%|███████▉  | 140485/176798 [01:19<00:15, 2278.95it/s]
Computing checksums:  80%|███████▉  | 140715/176798 [01:19<00:15, 2282.99it/s]
Computing checksums:  80%|███████▉  | 140944/176798 [01:19<00:15, 2284.33it/s]
Computing checksums:  80%|███████▉  | 141173/176798 [01:19<00:15, 2285.55it/s]
Computing checksums:  80%|███████▉  | 141402/176798 [01:19<00:15, 2275.50it/s]
Computing checksums:  80%|████████  | 141630/176798 [01:19<00:15, 2271.06it/s]
Computing checksums:  80%|████████  | 141859/176798 [01:19<00:15, 2276.07it/s]
Computing checksums:  80%|████████  | 142089/176798 [01:19<00:15, 2281.20it/s]
Computing checksums:  80%|████████  | 142319/176798 [01:19<00:15, 2285.25it/s]
Computing checksums:  81%|████████  | 142550/176798 [01:19<00:14, 2291.04it/s]
Computing checksums:  81%|████████  | 142780/176798 [01:20<00:14, 2290.95it/s]
Computing checksums:  81%|████████  | 143010/176798 [01:20<00:14, 2289.48it/s]
Computing checksums:  81%|████████  | 143239/176798 [01:20<00:14, 2288.66it/s]
Computing checksums:  81%|████████  | 143470/176798 [01:20<00:14, 2294.22it/s]
Computing checksums:  81%|████████▏ | 143701/176798 [01:20<00:14, 2296.64it/s]
Computing checksums:  81%|████████▏ | 143933/176798 [01:20<00:14, 2302.28it/s]
Computing checksums:  82%|████████▏ | 144164/176798 [01:20<00:14, 2303.25it/s]
Computing checksums:  82%|████████▏ | 144395/176798 [01:20<00:14, 2303.71it/s]
Computing checksums:  82%|████████▏ | 144626/176798 [01:20<00:13, 2304.15it/s]
Computing checksums:  82%|████████▏ | 144859/176798 [01:20<00:13, 2308.96it/s]
Computing checksums:  82%|████████▏ | 145090/176798 [01:21<00:13, 2308.70it/s]
Computing checksums:  82%|████████▏ | 145324/176798 [01:21<00:13, 2316.36it/s]
Computing checksums:  82%|████████▏ | 145558/176798 [01:21<00:13, 2320.83it/s]
Computing checksums:  82%|████████▏ | 145791/176798 [01:21<00:13, 2322.12it/s]
Computing checksums:  83%|████████▎ | 146026/176798 [01:21<00:13, 2328.98it/s]
Computing checksums:  83%|████████▎ | 146259/176798 [01:21<00:13, 2323.76it/s]
Computing checksums:  83%|████████▎ | 146492/176798 [01:21<00:13, 2322.28it/s]
Computing checksums:  83%|████████▎ | 146727/176798 [01:21<00:12, 2327.83it/s]
Computing checksums:  83%|████████▎ | 146961/176798 [01:21<00:12, 2329.72it/s]
Computing checksums:  83%|████████▎ | 147196/176798 [01:21<00:12, 2334.39it/s]
Computing checksums:  83%|████████▎ | 147430/176798 [01:22<00:12, 2331.09it/s]
Computing checksums:  84%|████████▎ | 147664/176798 [01:22<00:12, 2331.95it/s]
Computing checksums:  84%|████████▎ | 147898/176798 [01:22<00:12, 2333.53it/s]
Computing checksums:  84%|████████▍ | 148132/176798 [01:22<00:12, 2328.11it/s]
Computing checksums:  84%|████████▍ | 148368/176798 [01:22<00:12, 2337.47it/s]
Computing checksums:  84%|████████▍ | 148602/176798 [01:22<00:12, 2334.39it/s]
Computing checksums:  84%|████████▍ | 148840/176798 [01:22<00:11, 2345.03it/s]
Computing checksums:  84%|████████▍ | 149078/176798 [01:22<00:11, 2352.61it/s]
Computing checksums:  84%|████████▍ | 149314/176798 [01:22<00:11, 2332.29it/s]
Computing checksums:  85%|████████▍ | 149550/176798 [01:22<00:11, 2338.71it/s]
Computing checksums:  85%|████████▍ | 149785/176798 [01:23<00:11, 2341.26it/s]
Computing checksums:  85%|████████▍ | 150021/176798 [01:23<00:11, 2344.33it/s]
Computing checksums:  85%|████████▍ | 150256/176798 [01:23<00:11, 2344.77it/s]
Computing checksums:  85%|████████▌ | 150493/176798 [01:23<00:11, 2351.98it/s]
Computing checksums:  85%|████████▌ | 150730/176798 [01:23<00:11, 2354.65it/s]
Computing checksums:  85%|████████▌ | 150968/176798 [01:23<00:10, 2359.49it/s]
Computing checksums:  86%|████████▌ | 151207/176798 [01:23<00:10, 2367.01it/s]
Computing checksums:  86%|████████▌ | 151445/176798 [01:23<00:10, 2368.00it/s]
Computing checksums:  86%|████████▌ | 151683/176798 [01:23<00:10, 2368.78it/s]
Computing checksums:  86%|████████▌ | 151920/176798 [01:23<00:10, 2354.21it/s]
Computing checksums:  86%|████████▌ | 152158/176798 [01:24<00:10, 2361.28it/s]
Computing checksums:  86%|████████▌ | 152398/176798 [01:24<00:10, 2370.27it/s]
Computing checksums:  86%|████████▋ | 152637/176798 [01:24<00:10, 2375.28it/s]
Computing checksums:  86%|████████▋ | 152875/176798 [01:24<00:10, 2375.14it/s]
Computing checksums:  87%|████████▋ | 153114/176798 [01:24<00:09, 2378.47it/s]
Computing checksums:  87%|████████▋ | 153353/176798 [01:24<00:09, 2380.98it/s]
Computing checksums:  87%|████████▋ | 153592/176798 [01:24<00:09, 2379.23it/s]
Computing checksums:  87%|████████▋ | 153830/176798 [01:24<00:09, 2372.48it/s]
Computing checksums:  87%|████████▋ | 154068/176798 [01:24<00:09, 2369.70it/s]
Computing checksums:  87%|████████▋ | 154307/176798 [01:24<00:09, 2375.27it/s]
Computing checksums:  87%|████████▋ | 154547/176798 [01:25<00:09, 2379.97it/s]
Computing checksums:  88%|████████▊ | 154786/176798 [01:25<00:09, 2379.11it/s]
Computing checksums:  88%|████████▊ | 155027/176798 [01:25<00:09, 2385.69it/s]
Computing checksums:  88%|████████▊ | 155267/176798 [01:25<00:09, 2389.45it/s]
Computing checksums:  88%|████████▊ | 155507/176798 [01:25<00:08, 2390.26it/s]
Computing checksums:  88%|████████▊ | 155747/176798 [01:25<00:08, 2381.96it/s]
Computing checksums:  88%|████████▊ | 155986/176798 [01:25<00:08, 2381.18it/s]
Computing checksums:  88%|████████▊ | 156225/176798 [01:25<00:08, 2382.09it/s]
Computing checksums:  88%|████████▊ | 156465/176798 [01:25<00:08, 2385.71it/s]
Computing checksums:  89%|████████▊ | 156705/176798 [01:25<00:08, 2388.71it/s]
Computing checksums:  89%|████████▉ | 156945/176798 [01:26<00:08, 2391.17it/s]
Computing checksums:  89%|████████▉ | 157185/176798 [01:26<00:08, 2393.17it/s]
Computing checksums:  89%|████████▉ | 157426/176798 [01:26<00:08, 2396.08it/s]
Computing checksums:  89%|████████▉ | 157668/176798 [01:26<00:07, 2401.84it/s]
Computing checksums:  89%|████████▉ | 157910/176798 [01:26<00:07, 2406.29it/s]
Computing checksums:  89%|████████▉ | 158151/176798 [01:26<00:07, 2407.02it/s]
Computing checksums:  90%|████████▉ | 158392/176798 [01:26<00:07, 2405.66it/s]
Computing checksums:  90%|████████▉ | 158634/176798 [01:26<00:07, 2409.05it/s]
Computing checksums:  90%|████████▉ | 158877/176798 [01:26<00:07, 2412.74it/s]
Computing checksums:  90%|█████████ | 159119/176798 [01:26<00:07, 2411.81it/s]
Computing checksums:  90%|█████████ | 159362/176798 [01:27<00:07, 2415.77it/s]
Computing checksums:  90%|█████████ | 159605/176798 [01:27<00:07, 2418.69it/s]
Computing checksums:  90%|█████████ | 159849/176798 [01:27<00:06, 2424.09it/s]
Computing checksums:  91%|█████████ | 160092/176798 [01:27<00:06, 2423.41it/s]
Computing checksums:  91%|█████████ | 160335/176798 [01:27<00:06, 2420.40it/s]
Computing checksums:  91%|█████████ | 160580/176798 [01:27<00:06, 2428.72it/s]
Computing checksums:  91%|█████████ | 160825/176798 [01:27<00:06, 2432.81it/s]
Computing checksums:  91%|█████████ | 161069/176798 [01:27<00:06, 2433.11it/s]
Computing checksums:  91%|█████████ | 161316/176798 [01:27<00:06, 2442.69it/s]
Computing checksums:  91%|█████████▏| 161562/176798 [01:27<00:06, 2445.72it/s]
Computing checksums:  92%|█████████▏| 161807/176798 [01:28<00:06, 2445.92it/s]
Computing checksums:  92%|█████████▏| 162053/176798 [01:28<00:06, 2449.79it/s]
Computing checksums:  92%|█████████▏| 162301/176798 [01:28<00:05, 2456.29it/s]
Computing checksums:  92%|█████████▏| 162547/176798 [01:28<00:05, 2456.21it/s]
Computing checksums:  92%|█████████▏| 162793/176798 [01:28<00:05, 2454.69it/s]
Computing checksums:  92%|█████████▏| 163040/176798 [01:28<00:05, 2456.66it/s]
Computing checksums:  92%|█████████▏| 163288/176798 [01:28<00:05, 2461.59it/s]
Computing checksums:  92%|█████████▏| 163537/176798 [01:28<00:05, 2466.86it/s]
Computing checksums:  93%|█████████▎| 163785/176798 [01:28<00:05, 2469.30it/s]
Computing checksums:  93%|█████████▎| 164032/176798 [01:28<00:05, 2464.64it/s]
Computing checksums:  93%|█████████▎| 164279/176798 [01:29<00:05, 2461.24it/s]
Computing checksums:  93%|█████████▎| 164526/176798 [01:29<00:04, 2456.88it/s]
Computing checksums:  93%|█████████▎| 164775/176798 [01:29<00:04, 2463.99it/s]
Computing checksums:  93%|█████████▎| 165023/176798 [01:29<00:04, 2468.54it/s]
Computing checksums:  93%|█████████▎| 165271/176798 [01:29<00:04, 2470.65it/s]
Computing checksums:  94%|█████████▎| 165520/176798 [01:29<00:04, 2474.78it/s]
Computing checksums:  94%|█████████▍| 165770/176798 [01:29<00:04, 2481.13it/s]
Computing checksums:  94%|█████████▍| 166019/176798 [01:29<00:04, 2483.57it/s]
Computing checksums:  94%|█████████▍| 166269/176798 [01:29<00:04, 2488.32it/s]
Computing checksums:  94%|█████████▍| 166519/176798 [01:29<00:04, 2488.92it/s]
Computing checksums:  94%|█████████▍| 166768/176798 [01:30<00:04, 2480.21it/s]
Computing checksums:  94%|█████████▍| 167017/176798 [01:30<00:03, 2480.67it/s]
Computing checksums:  95%|█████████▍| 167266/176798 [01:30<00:03, 2481.66it/s]
Computing checksums:  95%|█████████▍| 167515/176798 [01:30<00:03, 2481.85it/s]
Computing checksums:  95%|█████████▍| 167764/176798 [01:30<00:03, 2482.73it/s]
Computing checksums:  95%|█████████▌| 168013/176798 [01:30<00:03, 2477.27it/s]
Computing checksums:  95%|█████████▌| 168262/176798 [01:30<00:03, 2479.28it/s]
Computing checksums:  95%|█████████▌| 168513/176798 [01:30<00:03, 2488.26it/s]
Computing checksums:  95%|█████████▌| 168764/176798 [01:30<00:03, 2492.13it/s]
Computing checksums:  96%|█████████▌| 169014/176798 [01:30<00:03, 2491.74it/s]
Computing checksums:  96%|█████████▌| 169266/176798 [01:31<00:03, 2498.98it/s]
Computing checksums:  96%|█████████▌| 169517/176798 [01:31<00:02, 2501.46it/s]
Computing checksums:  96%|█████████▌| 169768/176798 [01:31<00:02, 2501.78it/s]
Computing checksums:  96%|█████████▌| 170019/176798 [01:31<00:02, 2501.54it/s]
Computing checksums:  96%|█████████▋| 170272/176798 [01:31<00:02, 2507.56it/s]
Computing checksums:  96%|█████████▋| 170524/176798 [01:31<00:02, 2511.20it/s]
Computing checksums:  97%|█████████▋| 170776/176798 [01:31<00:02, 2509.61it/s]
Computing checksums:  97%|█████████▋| 171029/176798 [01:31<00:02, 2515.18it/s]
Computing checksums:  97%|█████████▋| 171281/176798 [01:31<00:02, 2487.35it/s]
Computing checksums:  97%|█████████▋| 171535/176798 [01:31<00:02, 2501.87it/s]
Computing checksums:  97%|█████████▋| 171791/176798 [01:32<00:01, 2516.17it/s]
Computing checksums:  97%|█████████▋| 172049/176798 [01:32<00:01, 2532.40it/s]
Computing checksums:  97%|█████████▋| 172303/176798 [01:32<00:01, 2528.26it/s]
Computing checksums:  98%|█████████▊| 172559/176798 [01:32<00:01, 2537.69it/s]
Computing checksums:  98%|█████████▊| 172815/176798 [01:32<00:01, 2541.76it/s]
Computing checksums:  98%|█████████▊| 173070/176798 [01:32<00:01, 2540.50it/s]
Computing checksums:  98%|█████████▊| 173325/176798 [01:32<00:01, 2527.58it/s]
Computing checksums:  98%|█████████▊| 173578/176798 [01:32<00:01, 2521.76it/s]
Computing checksums:  98%|█████████▊| 173833/176798 [01:32<00:01, 2527.62it/s]
Computing checksums:  98%|█████████▊| 174086/176798 [01:32<00:01, 2528.25it/s]
Computing checksums:  99%|█████████▊| 174339/176798 [01:33<00:00, 2528.38it/s]
Computing checksums:  99%|█████████▉| 174592/176798 [01:33<00:00, 2468.06it/s]
Computing checksums:  99%|█████████▉| 174840/176798 [01:33<00:00, 2445.80it/s]
Computing checksums:  99%|█████████▉| 175093/176798 [01:33<00:00, 2467.86it/s]
Computing checksums:  99%|█████████▉| 175345/176798 [01:33<00:00, 2481.11it/s]
Computing checksums:  99%|█████████▉| 175594/176798 [01:33<00:00, 2478.67it/s]
Computing checksums:  99%|█████████▉| 175848/176798 [01:33<00:00, 2495.25it/s]
Computing checksums: 100%|█████████▉| 176102/176798 [01:33<00:00, 2508.42it/s]
Computing checksums: 100%|█████████▉| 176356/176798 [01:33<00:00, 2516.28it/s]
Computing checksums: 100%|█████████▉| 176608/176798 [01:34<00:00, 2501.88it/s]
Computing checksums: 100%|██████████| 176798/176798 [01:34<00:00, 1879.08it/s]
Checksum Computation took 1.0 min
Generating train split

Generating train split: 0 examples [00:00, ? examples/s]
Generating train split: 53 examples [00:30,  1.75 examples/s]
Generating train split: 179 examples [00:30,  7.67 examples/s]
Generating train split: 300 examples [00:30, 15.68 examples/s]
Generating train split: 475 examples [00:30, 31.83 examples/s]
Generating train split: 600 examples [00:30, 47.88 examples/s]
Generating train split: 746 examples [00:30, 74.01 examples/s]
Generating train split: 893 examples [00:30, 109.93 examples/s]
Generating train split: 1082 examples [00:31, 165.96 examples/s]
Generating train split: 1216 examples [00:31, 213.91 examples/s]
Generating train split: 1383 examples [00:31, 292.90 examples/s]
Generating train split: 1522 examples [00:31, 361.89 examples/s]
Generating train split: 1700 examples [00:31, 456.67 examples/s]
Generating train split: 1828 examples [00:31, 548.29 examples/s]
Generating train split: 1987 examples [00:32, 679.20 examples/s]
Generating train split: 2178 examples [00:32, 742.33 examples/s]
Generating train split: 2300 examples [00:32, 792.86 examples/s]
Generating train split: 2423 examples [00:32, 867.54 examples/s]
Generating train split: 2577 examples [00:32, 970.33 examples/s]
Generating train split: 2700 examples [00:32, 992.60 examples/s]
Generating train split: 2843 examples [00:32, 1061.44 examples/s]
Generating train split: 2990 examples [00:32, 1119.97 examples/s]
Generating train split: 3186 examples [00:33, 1046.83 examples/s]
Generating train split: 3300 examples [00:33, 999.54 examples/s] 
Generating train split: 3437 examples [00:33, 1040.21 examples/s]
Generating train split: 3565 examples [00:33, 952.27 examples/s] 
Generating train split: 3736 examples [00:33, 1000.23 examples/s]
Generating train split: 3855 examples [00:33, 1025.86 examples/s]
Generating train split: 3988 examples [00:33, 1079.74 examples/s]
Generating train split: 4110 examples [00:34, 964.74 examples/s] 
Generating train split: 4272 examples [00:34, 972.10 examples/s]
Generating train split: 4378 examples [00:34, 477.16 examples/s]
Generating train split: 4992 examples [00:34, 1179.68 examples/s]
Generating train split: 5188 examples [00:35, 1105.39 examples/s]
Generating train split: 5372 examples [00:35, 1132.73 examples/s]
Generating train split: 5531 examples [00:35, 1075.70 examples/s]
Generating train split: 5700 examples [00:35, 1069.58 examples/s]
Generating train split: 5833 examples [00:35, 1118.12 examples/s]
Generating train split: 6023 examples [00:35, 1161.03 examples/s]
Generating train split: 6195 examples [00:36, 1153.29 examples/s]
Generating train split: 6343 examples [00:36, 989.23 examples/s] 
Generating train split: 6557 examples [00:36, 1213.64 examples/s]
Generating train split: 6797 examples [00:36, 1458.30 examples/s]
Generating train split: 6967 examples [00:36, 1466.37 examples/s]
Generating train split: 7259 examples [00:36, 1791.60 examples/s]
Generating train split: 7562 examples [00:36, 2109.80 examples/s]
Generating train split: 7822 examples [00:36, 1974.15 examples/s]
Generating train split: 8059 examples [00:37, 2052.89 examples/s]
Generating train split: 8319 examples [00:37, 1977.80 examples/s]
Generating train split: 8547 examples [00:37, 1912.00 examples/s]
Generating train split: 8811 examples [00:37, 2074.05 examples/s]
Generating train split: 9092 examples [00:37, 2025.30 examples/s]
Generating train split: 9323 examples [00:37, 2011.18 examples/s]
Generating train split: 9580 examples [00:37, 2122.56 examples/s]
Generating train split: 9804 examples [00:37, 2124.40 examples/s]
Generating train split: 10035 examples [00:38, 2145.13 examples/s]
Generating train split: 10293 examples [00:38, 2195.55 examples/s]
Generating train split: 10559 examples [00:38, 2019.63 examples/s]
Generating train split: 10780 examples [00:38, 1969.73 examples/s]
Generating train split: 11032 examples [00:38, 1892.12 examples/s]
Generating train split: 11258 examples [00:38, 1951.53 examples/s]
Generating train split: 11485 examples [00:38, 2031.13 examples/s]
Generating train split: 11695 examples [00:38, 1928.14 examples/s]
Generating train split: 11925 examples [00:38, 1990.97 examples/s]
Generating train split: 12179 examples [00:39, 2135.16 examples/s]
Generating train split: 12417 examples [00:39, 1971.65 examples/s]
Generating train split: 12698 examples [00:39, 2164.18 examples/s]
Generating train split: 12998 examples [00:39, 2242.47 examples/s]
Generating train split: 13278 examples [00:39, 2100.74 examples/s]
Generating train split: 13500 examples [00:39, 2001.61 examples/s]
Generating train split: 13740 examples [00:39, 2098.45 examples/s]
Generating train split: 14013 examples [00:39, 2199.28 examples/s]
Generating train split: 14293 examples [00:40, 2276.05 examples/s]
Generating train split: 14582 examples [00:40, 2217.54 examples/s]
Generating train split: 14868 examples [00:40, 2160.81 examples/s]
Generating train split: 15094 examples [00:40, 1046.02 examples/s]
Generating train split: 15676 examples [00:40, 1732.83 examples/s]
Generating train split: 16279 examples [00:41, 2450.98 examples/s]
Generating train split: 16700 examples [00:41, 2581.62 examples/s]
Generating train split: 17058 examples [00:41, 2382.02 examples/s]
Generating train split: 17409 examples [00:41, 2231.45 examples/s]
Generating train split: 17707 examples [00:41, 2169.15 examples/s]
Generating train split: 18032 examples [00:41, 2271.77 examples/s]
Generating train split: 18332 examples [00:41, 2193.84 examples/s]
Generating train split: 18601 examples [00:42, 2245.83 examples/s]
Generating train split: 18846 examples [00:42, 2166.65 examples/s]
Generating train split: 19118 examples [00:42, 2174.57 examples/s]
Generating train split: 19374 examples [00:42, 2244.27 examples/s]
Generating train split: 19621 examples [00:42, 2254.35 examples/s]
Generating train split: 19982 examples [00:42, 2588.22 examples/s]
Generating train split: 20300 examples [00:42, 2586.81 examples/s]
Generating train split: 20599 examples [00:42, 2654.69 examples/s]
Generating train split: 21001 examples [00:43, 2968.09 examples/s]
Generating train split: 21349 examples [00:43, 3046.21 examples/s]
Generating train split: 21686 examples [00:43, 3062.47 examples/s]
Generating train split: 22080 examples [00:43, 3128.73 examples/s]
Generating train split: 22458 examples [00:43, 3252.13 examples/s]
Generating train split: 22847 examples [00:43, 3218.96 examples/s]
Generating train split: 23234 examples [00:43, 3139.50 examples/s]
Generating train split: 23646 examples [00:43, 3358.44 examples/s]
Generating train split: 24045 examples [00:43, 3285.60 examples/s]
Generating train split: 24414 examples [00:44, 3169.73 examples/s]
Generating train split: 24817 examples [00:44, 3235.44 examples/s]
Generating train split: 25191 examples [00:44, 3277.60 examples/s]
Generating train split: 25546 examples [00:44, 2785.09 examples/s]
Generating train split: 26013 examples [00:44, 3182.10 examples/s]
Generating train split: 26364 examples [00:44, 2918.42 examples/s]
Generating train split: 26769 examples [00:44, 3187.98 examples/s]
Generating train split: 27112 examples [00:44, 3103.52 examples/s]
Generating train split: 27504 examples [00:45, 3151.04 examples/s]
Generating train split: 27846 examples [00:45, 3218.51 examples/s]
Generating train split: 28220 examples [00:45, 3314.80 examples/s]
Generating train split: 28558 examples [00:45, 3248.28 examples/s]
Generating train split: 28932 examples [00:45, 3071.16 examples/s]
Generating train split: 29319 examples [00:45, 3103.82 examples/s]
Generating train split: 29652 examples [00:45, 3135.76 examples/s]
Generating train split: 30012 examples [00:45, 2928.60 examples/s]
Generating train split: 30396 examples [00:45, 3159.06 examples/s]
Generating train split: 30741 examples [00:46, 3186.95 examples/s]
Generating train split: 31103 examples [00:46, 3293.35 examples/s]
Generating train split: 31454 examples [00:46, 3286.04 examples/s]
Generating train split: 31787 examples [00:46, 1439.69 examples/s]
Generating train split: 32382 examples [00:46, 2100.20 examples/s]
Generating train split: 33261 examples [00:47, 3243.42 examples/s]
Generating train split: 34275 examples [00:47, 4471.05 examples/s]
Generating train split: 34915 examples [00:47, 3896.26 examples/s]
Generating train split: 35464 examples [00:47, 3891.01 examples/s]
Generating train split: 35992 examples [00:47, 3665.29 examples/s]
Generating train split: 36441 examples [00:47, 3463.74 examples/s]
Generating train split: 36861 examples [00:48, 3307.30 examples/s]
Generating train split: 37260 examples [00:48, 3285.10 examples/s]
Generating train split: 37645 examples [00:48, 3319.05 examples/s]
Generating train split: 37993 examples [00:48, 3259.00 examples/s]
Generating train split: 38383 examples [00:48, 3238.84 examples/s]
Generating train split: 38790 examples [00:48, 3151.43 examples/s]
Generating train split: 39160 examples [00:48, 3268.56 examples/s]
Generating train split: 39564 examples [00:48, 3381.18 examples/s]
Generating train split: 40060 examples [00:48, 3798.69 examples/s]
Generating train split: 40532 examples [00:49, 3963.53 examples/s]
Generating train split: 40990 examples [00:49, 4090.50 examples/s]
Generating train split: 41455 examples [00:49, 3904.52 examples/s]
Generating train split: 41931 examples [00:49, 4068.58 examples/s]
Generating train split: 42358 examples [00:49, 4041.51 examples/s]
Generating train split: 42817 examples [00:49, 3962.73 examples/s]
Generating train split: 43316 examples [00:49, 4038.91 examples/s]
Generating train split: 43725 examples [00:49, 3960.60 examples/s]
Generating train split: 44212 examples [00:49, 4029.03 examples/s]
Generating train split: 44693 examples [00:50, 4131.99 examples/s]
Generating train split: 45156 examples [00:50, 3888.07 examples/s]
Generating train split: 45697 examples [00:50, 4204.90 examples/s]
Generating train split: 46188 examples [00:50, 3981.15 examples/s]
Generating train split: 46741 examples [00:50, 4377.65 examples/s]
Generating train split: 47229 examples [00:50, 4340.99 examples/s]
Generating train split: 47712 examples [00:50, 3871.76 examples/s]
Generating train split: 48180 examples [00:50, 4030.70 examples/s]
Generating train split: 48653 examples [00:51, 4195.93 examples/s]
Generating train split: 49100 examples [00:51, 4018.70 examples/s]
Generating train split: 49539 examples [00:51, 3953.57 examples/s]
Generating train split: 50002 examples [00:51, 4031.05 examples/s]
Generating train split: 50418 examples [00:51, 4058.56 examples/s]
Generating train split: 50909 examples [00:51, 4172.44 examples/s]
Generating train split: 51373 examples [00:51, 3894.95 examples/s]
Generating train split: 51800 examples [00:51, 3914.25 examples/s]
Generating train split: 52301 examples [00:51, 4097.29 examples/s]
Generating train split: 52745 examples [00:52, 3926.79 examples/s]
Generating train split: 53174 examples [00:52, 4015.11 examples/s]
Generating train split: 53600 examples [00:52, 4077.06 examples/s]
Generating train split: 54035 examples [00:52, 4013.17 examples/s]
Generating train split: 54509 examples [00:52, 4035.55 examples/s]
Generating train split: 54940 examples [00:53, 1795.76 examples/s]
Generating train split: 55535 examples [00:53, 2390.70 examples/s]
Generating train split: 56340 examples [00:53, 3339.66 examples/s]
Generating train split: 56991 examples [00:53, 3924.01 examples/s]
Generating train split: 57593 examples [00:53, 4333.76 examples/s]
Generating train split: 58242 examples [00:53, 4730.21 examples/s]
Generating train split: 58853 examples [00:53, 4954.16 examples/s]
Generating train split: 59455 examples [00:53, 4798.06 examples/s]
Generating train split: 60292 examples [00:53, 5636.31 examples/s]
Generating train split: 60932 examples [00:54, 4815.25 examples/s]
Generating train split: 61546 examples [00:54, 4606.65 examples/s]
Generating train split: 62109 examples [00:54, 4493.04 examples/s]
Generating train split: 62609 examples [00:54, 4048.43 examples/s]
Generating train split: 63076 examples [00:54, 4030.66 examples/s]
Generating train split: 63573 examples [00:54, 4233.39 examples/s]
Generating train split: 64022 examples [00:54, 4215.03 examples/s]
Generating train split: 64523 examples [00:54, 4315.21 examples/s]
Generating train split: 65039 examples [00:55, 4537.11 examples/s]
Generating train split: 65520 examples [00:55, 4399.33 examples/s]
Generating train split: 66105 examples [00:55, 4785.85 examples/s]
Generating train split: 66676 examples [00:55, 5035.11 examples/s]
Generating train split: 67273 examples [00:55, 5165.29 examples/s]
Generating train split: 67837 examples [00:55, 5202.22 examples/s]
Generating train split: 68362 examples [00:55, 4738.66 examples/s]
Generating train split: 68886 examples [00:55, 4873.83 examples/s]
Generating train split: 69437 examples [00:55, 4781.24 examples/s]
Generating train split: 69945 examples [00:56, 4821.94 examples/s]
Generating train split: 70501 examples [00:56, 5026.33 examples/s]
Generating train split: 71062 examples [00:56, 5118.39 examples/s]
Generating train split: 71590 examples [00:56, 4943.49 examples/s]
Generating train split: 72154 examples [00:56, 5071.43 examples/s]
Generating train split: 72665 examples [00:56, 5059.17 examples/s]
Generating train split: 73204 examples [00:56, 5110.16 examples/s]
Generating train split: 73737 examples [00:56, 4931.48 examples/s]
Generating train split: 74301 examples [00:56, 5109.82 examples/s]
Generating train split: 74856 examples [00:57, 4829.39 examples/s]
Generating train split: 75384 examples [00:57, 4857.81 examples/s]
Generating train split: 75875 examples [00:57, 4791.62 examples/s]
Generating train split: 76451 examples [00:57, 4930.80 examples/s]
Generating train split: 76997 examples [00:57, 4941.61 examples/s]
Generating train split: 77656 examples [00:57, 5364.49 examples/s]
Generating train split: 78244 examples [00:57, 5268.66 examples/s]
Generating train split: 78780 examples [00:57, 5179.36 examples/s]
Generating train split: 79418 examples [00:57, 5473.81 examples/s]
Generating train split: 79971 examples [00:58, 5129.76 examples/s]
Generating train split: 80611 examples [00:58, 5368.18 examples/s]
Generating train split: 81154 examples [00:58, 4990.99 examples/s]
Generating train split: 81685 examples [00:58, 4948.68 examples/s]
Generating train split: 82194 examples [00:58, 4971.15 examples/s]
Generating train split: 82737 examples [00:58, 5024.37 examples/s]
Generating train split: 83300 examples [00:58, 5115.63 examples/s]
Generating train split: 83826 examples [00:58, 4906.52 examples/s]
Generating train split: 84444 examples [00:58, 5145.52 examples/s]
Generating train split: 84982 examples [00:59, 5128.94 examples/s]
Generating train split: 85516 examples [00:59, 5089.02 examples/s]
Generating train split: 86027 examples [00:59, 2012.05 examples/s]
Generating train split: 86543 examples [00:59, 2413.76 examples/s]
Generating train split: 87216 examples [01:00, 3092.09 examples/s]
Generating train split: 87905 examples [01:00, 3765.27 examples/s]
Generating train split: 88589 examples [01:00, 4354.71 examples/s]
Generating train split: 89197 examples [01:00, 4689.95 examples/s]
Generating train split: 89888 examples [01:00, 5223.34 examples/s]
Generating train split: 90619 examples [01:00, 5675.38 examples/s]
Generating train split: 91252 examples [01:00, 5840.51 examples/s]
Generating train split: 91915 examples [01:00, 5871.36 examples/s]
Generating train split: 94272 examples [01:00, 10291.63 examples/s]
Generating train split: 95322 examples [01:01, 8067.66 examples/s] 
Generating train split: 96228 examples [01:01, 6923.52 examples/s]
Generating train split: 97044 examples [01:01, 6244.12 examples/s]
Generating train split: 97734 examples [01:01, 5878.85 examples/s]
Generating train split: 98372 examples [01:01, 5455.91 examples/s]
Generating train split: 99030 examples [01:01, 5633.57 examples/s]
Generating train split: 99662 examples [01:01, 5476.91 examples/s]
Generating train split: 100273 examples [01:02, 5579.66 examples/s]
Generating train split: 100892 examples [01:02, 5562.99 examples/s]
Generating train split: 101558 examples [01:02, 5837.84 examples/s]
Generating train split: 102210 examples [01:02, 5855.86 examples/s]
Generating train split: 102806 examples [01:02, 5718.30 examples/s]
Generating train split: 103430 examples [01:02, 5793.67 examples/s]
Generating train split: 104037 examples [01:02, 5828.71 examples/s]
Generating train split: 104624 examples [01:02, 5574.92 examples/s]
Generating train split: 105516 examples [01:02, 6006.13 examples/s]
Generating train split: 106239 examples [01:03, 6312.47 examples/s]
Generating train split: 106878 examples [01:03, 5946.90 examples/s]
Generating train split: 107510 examples [01:03, 6017.65 examples/s]
Generating train split: 108169 examples [01:03, 5716.71 examples/s]
Generating train split: 108810 examples [01:03, 5583.63 examples/s]
Generating train split: 109390 examples [01:03, 5630.40 examples/s]
Generating train split: 110009 examples [01:03, 5626.44 examples/s]
Generating train split: 110601 examples [01:03, 5706.03 examples/s]
Generating train split: 111196 examples [01:03, 5693.65 examples/s]
Generating train split: 111780 examples [01:04, 5472.60 examples/s]
Generating train split: 112371 examples [01:04, 4826.48 examples/s]
Generating train split: 113066 examples [01:04, 5362.84 examples/s]
Generating train split: 113721 examples [01:04, 5670.38 examples/s]
Generating train split: 114337 examples [01:04, 5717.90 examples/s]
Generating train split: 114950 examples [01:04, 5517.03 examples/s]
Generating train split: 115695 examples [01:04, 5879.79 examples/s]
Generating train split: 116473 examples [01:04, 6306.85 examples/s]
Generating train split: 117161 examples [01:04, 6370.25 examples/s]
Generating train split: 117884 examples [01:05, 6032.94 examples/s]
Generating train split: 118501 examples [01:05, 6054.22 examples/s]
Generating train split: 119323 examples [01:05, 6646.83 examples/s]
Generating train split: 120035 examples [01:05, 6592.37 examples/s]
Generating train split: 120745 examples [01:05, 6629.25 examples/s]
Generating train split: 121442 examples [01:05, 6531.19 examples/s]
Generating train split: 122147 examples [01:05, 6657.12 examples/s]
Generating train split: 122820 examples [01:06, 2473.72 examples/s]
Generating train split: 123578 examples [01:06, 3147.11 examples/s]
Generating train split: 124218 examples [01:06, 3633.20 examples/s]
Generating train split: 124917 examples [01:06, 4208.59 examples/s]
Generating train split: 125531 examples [01:06, 4560.32 examples/s]
Generating train split: 126144 examples [01:06, 4801.76 examples/s]
Generating train split: 126781 examples [01:07, 5052.98 examples/s]
Generating train split: 127545 examples [01:07, 5557.48 examples/s]
Generating train split: 128261 examples [01:07, 5893.00 examples/s]
Generating train split: 128952 examples [01:07, 6082.87 examples/s]
Generating train split: 129674 examples [01:07, 6391.72 examples/s]
Generating train split: 130390 examples [01:07, 5538.56 examples/s]
Generating train split: 134190 examples [01:07, 13617.28 examples/s]
Generating train split: 135756 examples [01:08, 9274.25 examples/s] 
Generating train split: 136985 examples [01:08, 8386.79 examples/s]
Generating train split: 138051 examples [01:08, 7684.26 examples/s]
Generating train split: 138995 examples [01:08, 7378.63 examples/s]
Generating train split: 139912 examples [01:08, 6839.35 examples/s]
Generating train split: 140717 examples [01:08, 6731.97 examples/s]
Generating train split: 141491 examples [01:08, 6645.38 examples/s]
Generating train split: 142204 examples [01:09, 6530.24 examples/s]
Generating train split: 142895 examples [01:09, 6540.47 examples/s]
Generating train split: 143657 examples [01:09, 6730.97 examples/s]
Generating train split: 144420 examples [01:09, 6359.16 examples/s]
Generating train split: 145126 examples [01:09, 6288.60 examples/s]
Generating train split: 145778 examples [01:09, 6340.57 examples/s]
Generating train split: 146449 examples [01:09, 6354.42 examples/s]
Generating train split: 147153 examples [01:09, 6530.63 examples/s]
Generating train split: 147872 examples [01:09, 6513.55 examples/s]
Generating train split: 148669 examples [01:10, 6811.58 examples/s]
Generating train split: 149356 examples [01:10, 6710.27 examples/s]
Generating train split: 150058 examples [01:10, 6419.02 examples/s]
Generating train split: 150712 examples [01:10, 6227.26 examples/s]
Generating train split: 151454 examples [01:10, 6531.97 examples/s]
Generating train split: 152151 examples [01:10, 6548.81 examples/s]
Generating train split: 152877 examples [01:10, 6535.03 examples/s]
Generating train split: 153549 examples [01:10, 6226.05 examples/s]
Generating train split: 154194 examples [01:10, 5951.40 examples/s]
Generating train split: 154914 examples [01:11, 6277.10 examples/s]
Generating train split: 155625 examples [01:11, 6402.23 examples/s]
Generating train split: 156298 examples [01:11, 6005.37 examples/s]
Generating train split: 157114 examples [01:11, 6581.42 examples/s]
Generating train split: 157787 examples [01:11, 6521.33 examples/s]
Generating train split: 158458 examples [01:11, 6034.29 examples/s]
Generating train split: 159273 examples [01:11, 6589.87 examples/s]
Generating train split: 159976 examples [01:11, 5941.67 examples/s]
Generating train split: 160741 examples [01:11, 6360.29 examples/s]
Generating train split: 161408 examples [01:12, 6178.23 examples/s]
Generating train split: 162061 examples [01:12, 6272.42 examples/s]
Generating train split: 162725 examples [01:12, 6368.61 examples/s]
Generating train split: 163417 examples [01:12, 6337.83 examples/s]
Generating train split: 164124 examples [01:13, 2631.20 examples/s]
Generating train split: 164806 examples [01:13, 3171.73 examples/s]
Generating train split: 165452 examples [01:13, 3681.92 examples/s]
Generating train split: 166003 examples [01:13, 3915.38 examples/s]
Generating train split: 166623 examples [01:13, 4346.92 examples/s]
Generating train split: 167429 examples [01:13, 5189.99 examples/s]
Generating train split: 168118 examples [01:13, 5272.27 examples/s]
Generating train split: 168757 examples [01:13, 5410.87 examples/s]
Generating train split: 169600 examples [01:13, 6180.70 examples/s]
Generating train split: 170336 examples [01:14, 6159.44 examples/s]
Generating train split: 171034 examples [01:14, 6319.73 examples/s]
Generating train split: 171750 examples [01:14, 6109.43 examples/s]
Generating train split: 172436 examples [01:14, 5042.44 examples/s]
Generating train split: 180535 examples [01:14, 22543.32 examples/s]
Generating train split: 183270 examples [01:14, 12927.91 examples/s]
Generating train split: 185377 examples [01:15, 10631.41 examples/s]
Generating train split: 187057 examples [01:15, 9053.05 examples/s] 
Generating train split: 188453 examples [01:15, 8872.24 examples/s]
Generating train split: 189689 examples [01:15, 8829.32 examples/s]
Generating train split: 190800 examples [01:16, 8184.74 examples/s]
Generating train split: 191759 examples [01:16, 7647.09 examples/s]
Generating train split: 192615 examples [01:16, 7438.53 examples/s]
Generating train split: 193419 examples [01:16, 7463.06 examples/s]
Generating train split: 194220 examples [01:16, 7332.95 examples/s]
Generating train split: 195013 examples [01:16, 6876.44 examples/s]
Generating train split: 195724 examples [01:16, 6674.62 examples/s]
Generating train split: 196419 examples [01:16, 6728.58 examples/s]
Generating train split: 197168 examples [01:17, 6829.32 examples/s]
Generating train split: 197925 examples [01:17, 6141.20 examples/s]
Generating train split: 198582 examples [01:17, 6172.47 examples/s]
Generating train split: 199253 examples [01:17, 5488.04 examples/s]
Generating train split: 199877 examples [01:17, 5608.53 examples/s]
Generating train split: 200520 examples [01:17, 5741.36 examples/s]
Generating train split: 201220 examples [01:17, 5991.22 examples/s]
Generating train split: 201858 examples [01:17, 5615.16 examples/s]
Generating train split: 202495 examples [01:17, 5661.14 examples/s]
Generating train split: 203085 examples [01:18, 5567.47 examples/s]
Generating train split: 203723 examples [01:18, 5700.83 examples/s]
Generating train split: 204349 examples [01:18, 5689.95 examples/s]
Generating train split: 204978 examples [01:18, 5759.67 examples/s]
Generating train split: 205568 examples [01:18, 5646.56 examples/s]
Generating train split: 206237 examples [01:18, 5853.08 examples/s]
Generating train split: 206951 examples [01:18, 6127.93 examples/s]
Generating train split: 207617 examples [01:19, 2380.78 examples/s]
Generating train split: 208210 examples [01:19, 2852.09 examples/s]
Generating train split: 208784 examples [01:19, 3311.37 examples/s]
Generating train split: 209427 examples [01:19, 3879.15 examples/s]
Generating train split: 210026 examples [01:19, 4258.48 examples/s]
Generating train split: 210717 examples [01:19, 4851.72 examples/s]
Generating train split: 211313 examples [01:20, 4774.07 examples/s]
Generating train split: 211946 examples [01:20, 5087.59 examples/s]
Generating train split: 212541 examples [01:20, 5227.91 examples/s]
Generating train split: 213187 examples [01:20, 5260.50 examples/s]
Generating train split: 213817 examples [01:20, 5462.37 examples/s]
Generating train split: 214406 examples [01:20, 5412.94 examples/s]
Generating train split: 215091 examples [01:20, 5721.91 examples/s]
Generating train split: 215731 examples [01:20, 5903.43 examples/s]
Generating train split: 216372 examples [01:20, 5942.05 examples/s]
Generating train split: 217230 examples [01:21, 6459.45 examples/s]
Generating train split: 217905 examples [01:21, 5172.58 examples/s]
Generating train split: 231621 examples [01:21, 36994.22 examples/s]
Generating train split: 236100 examples [01:22, 14591.93 examples/s]
Generating train split: 239459 examples [01:22, 11219.04 examples/s]
Generating train split: 241979 examples [01:23, 9055.25 examples/s] 
Generating train split: 243953 examples [01:23, 8233.77 examples/s]
Generating train split: 245490 examples [01:23, 7569.98 examples/s]
Generating train split: 246738 examples [01:23, 7248.03 examples/s]
Generating train split: 247793 examples [01:24, 7321.74 examples/s]
Generating train split: 248779 examples [01:24, 6919.52 examples/s]
Generating train split: 249629 examples [01:24, 6441.93 examples/s]
Generating train split: 250367 examples [01:24, 6587.70 examples/s]
Generating train split: 251115 examples [01:24, 6440.61 examples/s]
Generating train split: 251833 examples [01:24, 6399.28 examples/s]
Generating train split: 252551 examples [01:24, 5964.04 examples/s]
Generating train split: 253177 examples [01:25, 5776.62 examples/s]
Generating train split: 253785 examples [01:25, 5720.64 examples/s]
Generating train split: 254524 examples [01:25, 6064.49 examples/s]
Generating train split: 255149 examples [01:25, 5889.51 examples/s]
Generating train split: 255852 examples [01:25, 2613.07 examples/s]
Generating train split: 256649 examples [01:26, 3324.21 examples/s]
Generating train split: 257337 examples [01:26, 3875.00 examples/s]
Generating train split: 258003 examples [01:26, 4363.56 examples/s]
Generating train split: 258664 examples [01:26, 4643.82 examples/s]
Generating train split: 259278 examples [01:26, 4870.85 examples/s]
Generating train split: 259895 examples [01:26, 5131.29 examples/s]
Generating train split: 260604 examples [01:26, 5562.00 examples/s]
Generating train split: 261281 examples [01:26, 5740.50 examples/s]
Generating train split: 261903 examples [01:26, 5806.76 examples/s]
Generating train split: 262547 examples [01:27, 5675.28 examples/s]
Generating train split: 263137 examples [01:27, 5663.81 examples/s]
Generating train split: 263730 examples [01:27, 5518.38 examples/s]
Generating train split: 264299 examples [01:27, 5351.30 examples/s]
Generating train split: 264855 examples [01:27, 5347.50 examples/s]
Generating train split: 265534 examples [01:27, 5602.37 examples/s]
Generating train split: 266329 examples [01:27, 6083.61 examples/s]
Generating train split: 267075 examples [01:27, 6219.13 examples/s]
Generating train split: 267780 examples [01:27, 5686.96 examples/s]
Generating train split: 287939 examples [01:28, 55169.74 examples/s]
Generating train split: 293914 examples [01:29, 16005.68 examples/s]
Generating train split: 298269 examples [01:29, 11781.73 examples/s]
Generating train split: 301554 examples [01:30, 10373.29 examples/s]
Generating train split: 304064 examples [01:30, 9307.62 examples/s] 
Generating train split: 306007 examples [01:31, 8466.23 examples/s]
Generating train split: 307548 examples [01:31, 8033.60 examples/s]
Generating train split: 308821 examples [01:31, 7519.36 examples/s]
Generating train split: 309864 examples [01:31, 7147.99 examples/s]
Generating train split: 310818 examples [01:31, 6651.49 examples/s]
Generating train split: 311635 examples [01:32, 3716.11 examples/s]
Generating train split: 312258 examples [01:32, 3803.43 examples/s]
Generating train split: 313015 examples [01:32, 4242.69 examples/s]
Generating train split: 313675 examples [01:32, 4581.70 examples/s]
Generating train split: 314298 examples [01:33, 4771.17 examples/s]
Generating train split: 315013 examples [01:33, 5221.38 examples/s]
Generating train split: 315661 examples [01:33, 5419.13 examples/s]
Generating train split: 316484 examples [01:33, 5979.48 examples/s]
Generating train split: 317191 examples [01:33, 5525.20 examples/s]
Generating train split: 317831 examples [01:33, 5398.25 examples/s]
Generating train split: 318450 examples [01:33, 5179.18 examples/s]
Generating train split: 319188 examples [01:33, 5642.63 examples/s]
Generating train split: 319842 examples [01:33, 5576.43 examples/s]
Generating train split: 320449 examples [01:34, 5311.63 examples/s]
Generating train split: 321031 examples [01:34, 5440.69 examples/s]
Generating train split: 321623 examples [01:34, 5066.25 examples/s]
Generating train split: 322170 examples [01:34, 5025.91 examples/s]
Generating train split: 322714 examples [01:34, 5131.37 examples/s]
Generating train split: 323351 examples [01:34, 5447.45 examples/s]
Generating train split: 323974 examples [01:34, 5500.48 examples/s]
Generating train split: 324571 examples [01:34, 5462.73 examples/s]
Generating train split: 325144 examples [01:35, 5307.43 examples/s]
Generating train split: 325761 examples [01:35, 4584.88 examples/s]
Generating train split: 354467 examples [01:35, 73072.84 examples/s]
Generating train split: 362957 examples [01:36, 17275.23 examples/s]
Generating train split: 369080 examples [01:37, 11992.70 examples/s]
Generating train split: 373552 examples [01:38, 9943.51 examples/s] 
Generating train split: 376878 examples [01:39, 7055.01 examples/s]
Generating train split: 379288 examples [01:40, 6663.38 examples/s]
Generating train split: 381115 examples [01:40, 6479.12 examples/s]
Generating train split: 382616 examples [01:40, 6520.29 examples/s]
Generating train split: 383838 examples [01:40, 6438.92 examples/s]
Generating train split: 384869 examples [01:41, 6279.79 examples/s]
Generating train split: 385782 examples [01:41, 6077.20 examples/s]
Generating train split: 386620 examples [01:41, 5906.30 examples/s]
Generating train split: 387362 examples [01:41, 5868.38 examples/s]
Generating train split: 388031 examples [01:41, 5710.73 examples/s]
Generating train split: 388778 examples [01:41, 5923.76 examples/s]
Generating train split: 389447 examples [01:41, 6026.23 examples/s]
Generating train split: 390100 examples [01:42, 5749.52 examples/s]
Generating train split: 394307 examples [01:42, 14148.75 examples/s]
Generating train split: 423317 examples [01:42, 81200.06 examples/s]
Generating train split: 432625 examples [01:43, 19168.41 examples/s]
Generating train split: 439334 examples [01:44, 12366.44 examples/s]
Generating train split: 444237 examples [01:46, 8078.05 examples/s] 
Generating train split: 447736 examples [01:47, 7198.68 examples/s]
Generating train split: 450358 examples [01:47, 6885.53 examples/s]
Generating train split: 452355 examples [01:47, 6642.41 examples/s]
Generating train split: 453926 examples [01:48, 6451.07 examples/s]
Generating train split: 455229 examples [01:48, 6308.69 examples/s]
Generating train split: 456282 examples [01:48, 6270.87 examples/s]
Generating train split: 457249 examples [01:48, 6251.15 examples/s]
Generating train split: 458120 examples [01:48, 5980.00 examples/s]
Generating train split: 458842 examples [01:49, 5836.57 examples/s]
Generating train split: 490050 examples [01:49, 54352.58 examples/s]
Generating train split: 501030 examples [01:49, 64306.38 examples/s]
Generating train split: 511129 examples [01:51, 16516.98 examples/s]
Generating train split: 518395 examples [01:52, 9638.97 examples/s] 
Generating train split: 523605 examples [01:53, 8378.60 examples/s]
Generating train split: 527415 examples [01:54, 7857.71 examples/s]
Generating train split: 530279 examples [01:54, 7459.97 examples/s]
Generating train split: 532490 examples [01:55, 7045.72 examples/s]
Generating train split: 534196 examples [01:56, 5079.32 examples/s]
Generating train split: 541039 examples [01:56, 8553.40 examples/s]
Generating train split: 575483 examples [01:56, 32954.50 examples/s]
Generating train split: 587851 examples [01:57, 28016.54 examples/s]
Generating train split: 597131 examples [01:58, 14692.55 examples/s]
Generating train split: 603817 examples [01:59, 10949.51 examples/s]
Generating train split: 608666 examples [02:00, 9317.35 examples/s] 
Generating train split: 612220 examples [02:01, 8595.93 examples/s]
Generating train split: 614902 examples [02:01, 7979.94 examples/s]
Generating train split: 616923 examples [02:02, 6096.54 examples/s]
Generating train split: 618425 examples [02:03, 6069.68 examples/s]
Generating train split: 619648 examples [02:03, 6317.15 examples/s]
Generating train split: 644437 examples [02:03, 26408.83 examples/s]
Generating train split: 655142 examples [02:03, 34910.83 examples/s]
Generating train split: 664052 examples [02:05, 10822.93 examples/s]
Generating train split: 670471 examples [02:07, 8196.07 examples/s] 
Generating train split: 675074 examples [02:08, 7409.24 examples/s]
Generating train split: 678465 examples [02:08, 6853.25 examples/s]
Generating train split: 681016 examples [02:09, 6331.74 examples/s]
Generating train split: 682916 examples [02:10, 4648.65 examples/s]
Generating train split: 684306 examples [02:10, 4543.33 examples/s]
Generating train split: 714330 examples [02:10, 20909.34 examples/s]
Generating train split: 745560 examples [02:10, 42054.28 examples/s]
Generating train split: 761226 examples [02:13, 14815.21 examples/s]
Generating train split: 772322 examples [02:15, 11020.36 examples/s]
Generating train split: 780297 examples [02:17, 8222.77 examples/s] 
Generating train split: 785996 examples [02:18, 8291.54 examples/s]
Generating train split: 814360 examples [02:18, 17076.15 examples/s]
Generating train split: 836567 examples [02:18, 25980.50 examples/s]
Generating train split: 851111 examples [02:21, 13757.08 examples/s]
Generating train split: 861449 examples [02:22, 10678.64 examples/s]
Generating train split: 868858 examples [02:25, 7670.40 examples/s] 
Generating train split: 874163 examples [02:25, 7644.24 examples/s]
Generating train split: 903454 examples [02:25, 16305.48 examples/s]
Generating train split: 927493 examples [02:26, 25556.49 examples/s]
Generating train split: 942363 examples [02:28, 13832.41 examples/s]
Generating train split: 952986 examples [02:30, 10027.83 examples/s]
Generating train split: 960578 examples [02:33, 7364.44 examples/s] 
Generating train split: 965991 examples [02:33, 7477.20 examples/s]
Generating train split: 994055 examples [02:33, 15384.34 examples/s]
Generating train split: 1013030 examples [02:33, 22232.52 examples/s]
Generating train split: 1026128 examples [02:36, 12611.02 examples/s]
Generating train split: 1035519 examples [02:38, 9950.55 examples/s] 
Generating train split: 1042265 examples [02:40, 7375.59 examples/s]
Generating train split: 1047069 examples [02:41, 6581.05 examples/s]
Generating train split: 1050586 examples [02:41, 7173.69 examples/s]
Generating train split: 1077398 examples [02:41, 17070.97 examples/s]
Generating train split: 1102642 examples [02:41, 29135.87 examples/s]
Generating train split: 1117175 examples [02:44, 13623.50 examples/s]
Generating train split: 1127477 examples [02:47, 7919.45 examples/s] 
Generating train split: 1134796 examples [02:49, 7218.15 examples/s]
Generating train split: 1140064 examples [02:49, 8024.34 examples/s]
Generating train split: 1167651 examples [02:49, 16748.09 examples/s]
Generating train split: 1188132 examples [02:49, 25018.97 examples/s]
Generating train split: 1201769 examples [02:52, 11374.58 examples/s]
Generating train split: 1211413 examples [02:55, 7936.70 examples/s] 
Generating train split: 1218303 examples [02:56, 7325.84 examples/s]
Generating train split: 1223292 examples [02:57, 7493.02 examples/s]
Generating train split: 1249937 examples [02:57, 15681.99 examples/s]
Generating train split: 1269467 examples [02:57, 23386.60 examples/s]
Generating train split: 1282422 examples [02:59, 11876.22 examples/s]
Generating train split: 1291678 examples [03:02, 7783.21 examples/s] 
Generating train split: 1298243 examples [03:04, 7009.60 examples/s]
Generating train split: 1302996 examples [03:05, 6566.32 examples/s]
Generating train split: 1325687 examples [03:05, 12966.72 examples/s]
Generating train split: 1344330 examples [03:05, 19846.03 examples/s]
Generating train split: 1356150 examples [03:07, 11375.40 examples/s]
Generating train split: 1364604 examples [03:10, 7297.20 examples/s] 
Generating train split: 1370648 examples [03:11, 6590.01 examples/s]
Generating train split: 1375042 examples [03:12, 6334.62 examples/s]
Generating train split: 1378268 examples [03:12, 6592.93 examples/s]
Generating train split: 1403471 examples [03:13, 16094.25 examples/s]
Generating train split: 1429698 examples [03:13, 28992.23 examples/s]
Generating train split: 1444072 examples [03:15, 12927.21 examples/s]
Generating train split: 1454293 examples [03:18, 8157.44 examples/s] 
Generating train split: 1461554 examples [03:20, 7161.94 examples/s]
Generating train split: 1466833 examples [03:20, 7626.53 examples/s]
Generating train split: 1489643 examples [03:20, 14554.07 examples/s]
Generating train split: 1513741 examples [03:21, 24234.78 examples/s]
Generating train split: 1527424 examples [03:25, 9477.86 examples/s] 
Generating train split: 1537122 examples [03:27, 7903.68 examples/s]
Generating train split: 1544087 examples [03:28, 7504.87 examples/s]
Generating train split: 1549119 examples [03:28, 7501.98 examples/s]
Generating train split: 1570870 examples [03:29, 14122.37 examples/s]
Generating train split: 1589860 examples [03:29, 21614.89 examples/s]
Generating train split: 1601497 examples [03:32, 9419.82 examples/s] 
Generating train split: 1609749 examples [03:34, 7725.75 examples/s]
Generating train split: 1615678 examples [03:35, 6983.77 examples/s]
Generating train split: 1619959 examples [03:36, 6506.68 examples/s]
Generating train split: 1623095 examples [03:38, 4928.29 examples/s]
Generating train split: 1625377 examples [03:38, 5288.29 examples/s]
Generating train split: 1647640 examples [03:38, 13828.40 examples/s]
Generating train split: 1669273 examples [03:38, 24591.51 examples/s]
Generating train split: 1682093 examples [03:38, 31791.10 examples/s]
Generating train split: 1694258 examples [03:41, 11154.53 examples/s]
Generating train split: 1702881 examples [03:43, 8091.75 examples/s] 
Generating train split: 1709071 examples [03:45, 6883.94 examples/s]
Generating train split: 1713516 examples [03:47, 5178.68 examples/s]
Generating train split: 1736895 examples [03:47, 11057.29 examples/s]
Generating train split: 1756921 examples [03:47, 17760.98 examples/s]
Generating train split: 1769397 examples [03:50, 10107.34 examples/s]
Generating train split: 1778304 examples [03:52, 7748.86 examples/s] 
Generating train split: 1784644 examples [03:54, 5632.32 examples/s]
Generating train split: 1789163 examples [03:55, 5823.51 examples/s]
Generating train split: 1814980 examples [03:55, 12713.71 examples/s]
Generating train split: 1842474 examples [03:55, 22557.54 examples/s]
Generating train split: 1857829 examples [03:58, 12269.77 examples/s]
Generating train split: 1868760 examples [04:00, 8819.59 examples/s] 
Generating train split: 1876562 examples [04:03, 6282.07 examples/s]
Generating train split: 1882105 examples [04:04, 6555.52 examples/s]
Generating train split: 1903899 examples [04:04, 11906.77 examples/s]
Generating train split: 1928160 examples [04:04, 19956.79 examples/s]
Generating train split: 1942036 examples [04:08, 10004.76 examples/s]
Generating train split: 1951911 examples [04:11, 6404.61 examples/s] 
Generating train split: 1958887 examples [04:13, 5872.36 examples/s]
Generating train split: 1990327 examples [04:13, 12163.42 examples/s]
Generating train split: 2011023 examples [04:13, 17641.11 examples/s]
Generating train split: 2025856 examples [04:17, 9247.44 examples/s] 
Generating train split: 2036374 examples [04:21, 6097.73 examples/s]
Generating train split: 2043838 examples [04:22, 6152.31 examples/s]
Generating train split: 2065832 examples [04:22, 10384.48 examples/s]
Generating train split: 2087635 examples [04:22, 16094.89 examples/s]
Generating train split: 2101489 examples [04:25, 10544.06 examples/s]
Generating train split: 2111313 examples [04:29, 6313.58 examples/s] 
Generating train split: 2118257 examples [04:31, 5774.85 examples/s]
Generating train split: 2123262 examples [04:31, 5876.77 examples/s]
Generating train split: 2147435 examples [04:31, 11645.21 examples/s]
Generating train split: 2169309 examples [04:32, 18636.40 examples/s]
Generating train split: 2182741 examples [04:34, 11050.87 examples/s]
Generating train split: 2192301 examples [04:38, 6607.67 examples/s] 
Generating train split: 2199100 examples [04:39, 6320.25 examples/s]
Generating train split: 2203996 examples [04:40, 5812.68 examples/s]
Generating train split: 2207563 examples [04:41, 6493.73 examples/s]
Generating train split: 2228900 examples [04:41, 13592.10 examples/s]
Generating train split: 2252441 examples [04:41, 23955.91 examples/s]
Generating train split: 2265560 examples [04:42, 19099.00 examples/s]
Generating train split: 2275121 examples [04:44, 10558.22 examples/s]
Generating train split: 2281944 examples [04:47, 6298.22 examples/s] 
Generating train split: 2286800 examples [04:48, 5801.08 examples/s]
Generating train split: 2290314 examples [04:49, 5669.28 examples/s]
Generating train split: 2292916 examples [04:50, 5400.50 examples/s]
Generating train split: 2294886 examples [04:50, 5334.46 examples/s]
Generating train split: 2316044 examples [04:50, 14605.82 examples/s]
Generating train split: 2332640 examples [04:50, 23735.04 examples/s]
Generating train split: 2342803 examples [04:51, 20918.38 examples/s]
Generating train split: 2350402 examples [04:53, 10257.15 examples/s]
Generating train split: 2355819 examples [04:54, 8092.19 examples/s] 
Generating train split: 2359737 examples [04:57, 5182.16 examples/s]
Generating train split: 2362576 examples [04:57, 4835.00 examples/s]
Generating train split: 2364641 examples [04:58, 4839.99 examples/s]
Generating train split: 2366273 examples [04:58, 4809.95 examples/s]
Generating train split: 2367533 examples [04:58, 4821.58 examples/s]
Generating train split: 2368566 examples [04:59, 4747.73 examples/s]
Generating train split: 2369411 examples [04:59, 4728.73 examples/s]
Generating train split: 2370150 examples [04:59, 4813.36 examples/s]
Generating train split: 2370842 examples [04:59, 4826.64 examples/s]
Generating train split: 2371475 examples [04:59, 4640.90 examples/s]
Generating train split: 2372039 examples [04:59, 4650.68 examples/s]
Generating train split: 2372774 examples [04:59, 5116.28 examples/s]
Generating train split: 2373398 examples [05:00, 4779.47 examples/s]
Generating train split: 2404201 examples [05:00, 66036.12 examples/s]
Generating train split: 2431534 examples [05:00, 112422.82 examples/s]
Generating train split: 2446457 examples [05:05, 9396.18 examples/s]  
Generating train split: 2457011 examples [05:08, 6703.93 examples/s]
Generating train split: 2464547 examples [05:09, 7386.82 examples/s]
Generating train split: 2489139 examples [05:09, 13599.44 examples/s]
Generating train split: 2510898 examples [05:09, 20915.90 examples/s]
Generating train split: 2526146 examples [05:09, 27303.36 examples/s]
Generating train split: 2540773 examples [05:14, 8395.34 examples/s] 
Generating train split: 2551137 examples [05:18, 5572.76 examples/s]
Generating train split: 2558429 examples [05:19, 5885.10 examples/s]
Generating train split: 2578101 examples [05:19, 9723.21 examples/s]
Generating train split: 2593847 examples [05:19, 13849.97 examples/s]
Generating train split: 2607383 examples [05:19, 18502.46 examples/s]
Generating train split: 2619405 examples [05:22, 9599.26 examples/s] 
Generating train split: 2627950 examples [05:24, 7304.73 examples/s]
Generating train split: 2634075 examples [05:26, 6507.09 examples/s]
Generating train split: 2638468 examples [05:28, 4833.46 examples/s]
Generating train split: 2641635 examples [05:28, 5326.64 examples/s]
Generating train split: 2661000 examples [05:28, 11315.06 examples/s]
Generating train split: 2678450 examples [05:28, 18404.73 examples/s]
Generating train split: 2692185 examples [05:28, 25284.59 examples/s]
Generating train split: 2703566 examples [05:32, 9767.42 examples/s] 
Generating train split: 2711632 examples [05:34, 7086.35 examples/s]
Generating train split: 2717409 examples [05:37, 4576.71 examples/s]
Generating train split: 2721492 examples [05:38, 4678.27 examples/s]
Generating train split: 2736183 examples [05:38, 8188.29 examples/s]
Generating train split: 2755113 examples [05:38, 14357.20 examples/s]
Generating train split: 2769295 examples [05:38, 20204.34 examples/s]
Generating train split: 2780457 examples [05:41, 9000.08 examples/s] 
Generating train split: 2788396 examples [05:43, 7186.77 examples/s]
Generating train split: 2794043 examples [05:46, 4686.19 examples/s]
Generating train split: 2798062 examples [05:47, 4597.09 examples/s]
Generating train split: 2800999 examples [05:48, 5037.15 examples/s]
Generating train split: 2820618 examples [05:48, 11293.80 examples/s]
Generating train split: 2836900 examples [05:48, 18062.26 examples/s]
Generating train split: 2847131 examples [05:49, 16192.92 examples/s]
Generating train split: 2854641 examples [05:50, 9704.69 examples/s] 
Generating train split: 2860038 examples [05:52, 8037.66 examples/s]
Generating train split: 2863940 examples [05:53, 6564.85 examples/s]
Generating train split: 2866777 examples [05:53, 6010.78 examples/s]
Generating train split: 2868908 examples [05:55, 4155.82 examples/s]
Generating train split: 2870420 examples [05:55, 4165.09 examples/s]
Generating train split: 2871632 examples [05:56, 3909.51 examples/s]
Generating train split: 2872583 examples [05:56, 3971.13 examples/s]
Generating train split: 2873376 examples [05:56, 3888.67 examples/s]
Generating train split: 2874036 examples [05:56, 3922.58 examples/s]
Generating train split: 2874671 examples [05:57, 4120.50 examples/s]
Generating train split: 2875292 examples [05:57, 4247.07 examples/s]
Generating train split: 2875887 examples [05:57, 4305.57 examples/s]
Generating train split: 2876449 examples [05:57, 4259.11 examples/s]
Generating train split: 2876956 examples [05:57, 4080.96 examples/s]
Generating train split: 2877432 examples [05:57, 3518.44 examples/s]
Generating train split: 2893012 examples [05:57, 32098.97 examples/s]
Generating train split: 2912353 examples [05:58, 66145.62 examples/s]
Generating train split: 2931316 examples [05:58, 94764.58 examples/s]
Generating train split: 2943476 examples [06:01, 11706.92 examples/s]
Generating train split: 2952120 examples [06:03, 7733.01 examples/s] 
Generating train split: 2958267 examples [06:06, 5464.47 examples/s]
Generating train split: 2962646 examples [06:07, 5022.38 examples/s]
Generating train split: 2980777 examples [06:07, 9601.15 examples/s]
Generating train split: 2996321 examples [06:07, 14819.07 examples/s]
Generating train split: 3007094 examples [06:07, 19278.62 examples/s]
Generating train split: 3017204 examples [06:10, 8414.81 examples/s] 
Generating train split: 3024379 examples [06:13, 5458.97 examples/s]
Generating train split: 3029494 examples [06:15, 4958.76 examples/s]
Generating train split: 3033190 examples [06:16, 4773.89 examples/s]
Generating train split: 3035895 examples [06:17, 4466.18 examples/s]
Generating train split: 3049272 examples [06:17, 8589.07 examples/s]
Generating train split: 3066799 examples [06:17, 15850.37 examples/s]
Generating train split: 3076402 examples [06:17, 20524.99 examples/s]
Generating train split: 3085549 examples [06:20, 8330.54 examples/s] 
Generating train split: 3092089 examples [06:23, 5229.37 examples/s]
Generating train split: 3096736 examples [06:24, 5003.53 examples/s]
Generating train split: 3100095 examples [06:25, 4742.05 examples/s]
Generating train split: 3102586 examples [06:25, 4584.93 examples/s]
Generating train split: 3104424 examples [06:26, 4426.82 examples/s]
Generating train split: 3105853 examples [06:26, 4311.32 examples/s]
Generating train split: 3106963 examples [06:26, 4404.19 examples/s]
Generating train split: 3122572 examples [06:27, 14316.69 examples/s]
Generating train split: 3142678 examples [06:27, 30261.35 examples/s]
Generating train split: 3155682 examples [06:27, 40706.58 examples/s]
Generating train split: 3166129 examples [06:29, 11146.02 examples/s]
Generating train split: 3173553 examples [06:33, 6026.39 examples/s] 
Generating train split: 3178837 examples [06:34, 5558.73 examples/s]
Generating train split: 3182640 examples [06:35, 5112.78 examples/s]
Generating train split: 3185427 examples [06:36, 4752.19 examples/s]
Generating train split: 3187512 examples [06:36, 4478.06 examples/s]
Generating train split: 3201556 examples [06:37, 9801.26 examples/s]
Generating train split: 3214738 examples [06:37, 16263.74 examples/s]
Generating train split: 3232160 examples [06:37, 27373.31 examples/s]
Generating train split: 3242747 examples [06:37, 26126.91 examples/s]
Generating train split: 3250863 examples [06:41, 7933.04 examples/s] 
Generating train split: 3256622 examples [06:42, 6455.31 examples/s]
Generating train split: 3260756 examples [06:43, 5699.66 examples/s]
Generating train split: 3263768 examples [06:44, 5316.11 examples/s]
Generating train split: 3265993 examples [06:45, 4928.11 examples/s]
Generating train split: 3267655 examples [06:46, 3338.14 examples/s]
Generating train split: 3268892 examples [06:47, 3286.39 examples/s]
Generating train split: 3288721 examples [06:47, 11591.06 examples/s]
Generating train split: 3301752 examples [06:47, 18380.35 examples/s]
Generating train split: 3317595 examples [06:47, 28973.61 examples/s]
Generating train split: 3328313 examples [06:50, 10142.23 examples/s]
Generating train split: 3335910 examples [06:52, 6919.46 examples/s] 
Generating train split: 3341341 examples [06:54, 5763.09 examples/s]
Generating train split: 3345234 examples [06:56, 4163.39 examples/s]
Generating train split: 3348018 examples [06:57, 4299.04 examples/s]
Generating train split: 3365213 examples [06:57, 9345.75 examples/s]
Generating train split: 3381622 examples [06:57, 15725.85 examples/s]
Generating train split: 3396384 examples [06:57, 23060.86 examples/s]
Generating train split: 3407512 examples [07:00, 8896.99 examples/s] 
Generating train split: 3415395 examples [07:02, 6955.34 examples/s]
Generating train split: 3421038 examples [07:04, 5317.14 examples/s]
Generating train split: 3425088 examples [07:05, 5358.15 examples/s]
Generating train split: 3453656 examples [07:05, 13485.79 examples/s]
Generating train split: 3469831 examples [07:05, 19312.76 examples/s]
Generating train split: 3481740 examples [07:09, 8675.81 examples/s] 
Generating train split: 3490212 examples [07:11, 6557.27 examples/s]
Generating train split: 3496234 examples [07:14, 4707.40 examples/s]
Generating train split: 3500507 examples [07:15, 4541.03 examples/s]
Generating train split: 3517309 examples [07:16, 8188.41 examples/s]
Generating train split: 3531756 examples [07:16, 12397.34 examples/s]
Generating train split: 3543402 examples [07:16, 16748.26 examples/s]
Generating train split: 3553238 examples [07:19, 8321.91 examples/s] 
Generating train split: 3560257 examples [07:20, 6689.06 examples/s]
Generating train split: 3565278 examples [07:22, 5727.07 examples/s]
Generating train split: 3568888 examples [07:23, 5328.78 examples/s]
Generating train split: 3571538 examples [07:25, 3637.56 examples/s]
Generating train split: 3573447 examples [07:25, 3650.04 examples/s]
Generating train split: 3574918 examples [07:26, 3601.11 examples/s]
Generating train split: 3590090 examples [07:26, 9613.40 examples/s]
Generating train split: 3605124 examples [07:26, 17325.18 examples/s]
Generating train split: 3621157 examples [07:26, 27643.85 examples/s]
Generating train split: 3631607 examples [07:29, 9262.70 examples/s] 
Generating train split: 3639017 examples [07:31, 6809.87 examples/s]
Generating train split: 3644323 examples [07:34, 4662.23 examples/s]
Generating train split: 3648117 examples [07:35, 4410.64 examples/s]
Generating train split: 3650880 examples [07:36, 4187.03 examples/s]
Generating train split: 3662869 examples [07:36, 7633.22 examples/s]
Generating train split: 3674265 examples [07:36, 11972.72 examples/s]
Generating train split: 3686870 examples [07:36, 18256.87 examples/s]
Generating train split: 3695530 examples [07:38, 9643.23 examples/s] 
Generating train split: 3701701 examples [07:40, 6746.68 examples/s]
Generating train split: 3706143 examples [07:41, 5877.57 examples/s]
Generating train split: 3709359 examples [07:42, 5260.04 examples/s]
Generating train split: 3711748 examples [07:45, 3361.07 examples/s]
Generating train split: 3713438 examples [07:45, 3344.19 examples/s]
Generating train split: 3714709 examples [07:46, 3403.18 examples/s]
Generating train split: 3715747 examples [07:46, 3456.62 examples/s]
Generating train split: 3716594 examples [07:46, 3359.57 examples/s]
Generating train split: 3717259 examples [07:46, 3345.17 examples/s]
Generating train split: 3717853 examples [07:47, 3135.18 examples/s]
Generating train split: 3744528 examples [07:47, 27637.12 examples/s]
Generating train split: 3765823 examples [07:47, 48804.70 examples/s]
Generating train split: 3777522 examples [07:50, 9992.13 examples/s] 
Generating train split: 3785798 examples [07:53, 6599.35 examples/s]
Generating train split: 3791683 examples [07:56, 4355.39 examples/s]
Generating train split: 3795858 examples [07:57, 4580.92 examples/s]
Generating train split: 3802861 examples [07:57, 6159.67 examples/s]
Generating train split: 3807133 examples [08:01, 3167.92 examples/s]
Generating train split: 3810162 examples [08:07, 1826.21 examples/s]
Generating train split: 3812306 examples [08:08, 1859.31 examples/s]
Generating train split: 3820123 examples [08:08, 3177.07 examples/s]
Generating train split: 3836371 examples [08:08, 7012.31 examples/s]
Generating train split: 3844880 examples [08:08, 9603.75 examples/s]
Generating train split: 3852497 examples [08:08, 12381.87 examples/s]
Generating train split: 3859442 examples [08:10, 6735.21 examples/s] 
Generating train split: 3864405 examples [08:12, 5326.39 examples/s]
Generating train split: 3867978 examples [08:15, 3464.28 examples/s]
Generating train split: 3870528 examples [08:15, 3418.05 examples/s]
Generating train split: 3872416 examples [08:16, 3370.51 examples/s]
Generating train split: 3873829 examples [08:17, 3224.53 examples/s]
Generating train split: 3874885 examples [08:17, 3235.43 examples/s]
Generating train split: 3875745 examples [08:17, 3223.25 examples/s]
Generating train split: 3876446 examples [08:17, 3164.70 examples/s]
Generating train split: 3877024 examples [08:18, 3138.06 examples/s]
Generating train split: 3877517 examples [08:18, 3131.30 examples/s]
Generating train split: 3877956 examples [08:18, 3221.01 examples/s]
Generating train split: 3878406 examples [08:18, 3295.89 examples/s]
Generating train split: 3878840 examples [08:18, 3190.79 examples/s]
Generating train split: 3879208 examples [08:18, 3127.89 examples/s]
Generating train split: 3879581 examples [08:19, 3017.11 examples/s]
Generating train split: 3879912 examples [08:19, 2537.35 examples/s]
Generating train split: 3891290 examples [08:19, 23865.93 examples/s]
Generating train split: 3902582 examples [08:19, 43010.32 examples/s]
Generating train split: 3914047 examples [08:19, 59843.10 examples/s]
Generating train split: 3922963 examples [08:19, 66672.10 examples/s]
Generating train split: 3930866 examples [08:22, 9927.97 examples/s] 
Generating train split: 3936522 examples [08:23, 6878.56 examples/s]
Generating train split: 3940575 examples [08:25, 4565.06 examples/s]
Generating train split: 3943483 examples [08:26, 4302.58 examples/s]
Generating train split: 3945655 examples [08:27, 4399.53 examples/s]
Generating train split: 3947306 examples [08:27, 4432.88 examples/s]
Generating train split: 3948594 examples [08:27, 4256.44 examples/s]
Generating train split: 3949599 examples [08:28, 4118.51 examples/s]
Generating train split: 3950427 examples [08:28, 3923.07 examples/s]
Generating train split: 3951108 examples [08:28, 3798.58 examples/s]
Generating train split: 3951671 examples [08:28, 3583.02 examples/s]
Generating train split: 3952136 examples [08:28, 3652.72 examples/s]
Generating train split: 3952624 examples [08:29, 3772.61 examples/s]
Generating train split: 3953109 examples [08:29, 3289.45 examples/s]
Generating train split: 3963355 examples [08:29, 19212.81 examples/s]
Generating train split: 3979128 examples [08:29, 44953.14 examples/s]
Generating train split: 3989794 examples [08:29, 57775.48 examples/s]
Generating train split: 3997907 examples [08:31, 10201.08 examples/s]
Generating train split: 4003675 examples [08:34, 5073.91 examples/s] 
Generating train split: 4007787 examples [08:36, 4618.43 examples/s]
Generating train split: 4010776 examples [08:37, 4303.28 examples/s]
Generating train split: 4012956 examples [08:37, 4162.60 examples/s]
Generating train split: 4014614 examples [08:38, 3943.51 examples/s]
Generating train split: 4015844 examples [08:38, 3848.08 examples/s]
Generating train split: 4016818 examples [08:38, 3837.52 examples/s]
Generating train split: 4017624 examples [08:39, 3791.25 examples/s]
Generating train split: 4018290 examples [08:39, 3603.65 examples/s]
Generating train split: 4018846 examples [08:39, 3449.46 examples/s]
Generating train split: 4045862 examples [08:39, 32241.69 examples/s]
Generating train split: 4063350 examples [08:39, 51006.71 examples/s]
Generating train split: 4074295 examples [08:44, 7406.56 examples/s] 
Generating train split: 4082061 examples [08:46, 6179.74 examples/s]
Generating train split: 4087589 examples [08:47, 5516.25 examples/s]
Generating train split: 4091625 examples [08:49, 4875.93 examples/s]
Generating train split: 4094528 examples [08:52, 3084.53 examples/s]
Generating train split: 4096572 examples [08:52, 3008.56 examples/s]
Generating train split: 4105332 examples [08:53, 5198.16 examples/s]
Generating train split: 4113557 examples [08:53, 7946.02 examples/s]
Generating train split: 4123823 examples [08:53, 12532.24 examples/s]
Generating train split: 4130416 examples [08:55, 7080.01 examples/s] 
Generating train split: 4135133 examples [08:56, 5354.18 examples/s]
Generating train split: 4138527 examples [08:57, 5027.99 examples/s]
Generating train split: 4141038 examples [08:58, 4527.24 examples/s]
Generating train split: 4142870 examples [08:59, 4099.57 examples/s]
Generating train split: 4144257 examples [08:59, 3906.12 examples/s]
Generating train split: 4145301 examples [09:00, 3802.62 examples/s]
Generating train split: 4146173 examples [09:00, 3845.69 examples/s]
Generating train split: 4146888 examples [09:00, 3806.35 examples/s]
Generating train split: 4147508 examples [09:00, 3663.00 examples/s]
Generating train split: 4148125 examples [09:00, 3910.72 examples/s]
Generating train split: 4148699 examples [09:01, 3676.69 examples/s]
Generating train split: 4149180 examples [09:01, 3439.01 examples/s]
Generating train split: 4149601 examples [09:01, 3486.22 examples/s]
Generating train split: 4150044 examples [09:01, 3150.41 examples/s]
Generating train split: 4150394 examples [09:02, 1028.76 examples/s]
Generating train split: 4150831 examples [09:02, 1281.34 examples/s]
Generating train split: 4151201 examples [09:03, 1495.29 examples/s]
Generating train split: 4151653 examples [09:03, 1853.68 examples/s]
Generating train split: 4152071 examples [09:03, 2182.62 examples/s]
Generating train split: 4152575 examples [09:03, 2639.60 examples/s]
Generating train split: 4152989 examples [09:03, 2844.31 examples/s]
Generating train split: 4153403 examples [09:03, 2653.98 examples/s]
Generating train split: 4168358 examples [09:03, 32864.19 examples/s]
Generating train split: 4177410 examples [09:03, 45944.85 examples/s]
Generating train split: 4189602 examples [09:03, 64545.25 examples/s]
Generating train split: 4199903 examples [09:04, 74320.90 examples/s]
Generating train split: 4208482 examples [09:06, 12647.86 examples/s]
Generating train split: 4214610 examples [09:08, 7253.84 examples/s] 
Generating train split: 4219012 examples [09:09, 5640.22 examples/s]
Generating train split: 4222179 examples [09:10, 4970.74 examples/s]
Generating train split: 4224485 examples [09:11, 4428.32 examples/s]
Generating train split: 4226223 examples [09:13, 2952.42 examples/s]
Generating train split: 4227445 examples [09:13, 3006.94 examples/s]
Generating train split: 4228413 examples [09:14, 2910.29 examples/s]
Generating train split: 4229157 examples [09:14, 2853.23 examples/s]
Generating train split: 4243062 examples [09:14, 11028.15 examples/s]
Generating train split: 4259798 examples [09:14, 23375.26 examples/s]
Generating train split: 4269198 examples [09:14, 30404.69 examples/s]
Generating train split: 4277668 examples [09:17, 9226.31 examples/s] 
Generating train split: 4283697 examples [09:19, 6506.29 examples/s]
Generating train split: 4288036 examples [09:20, 5184.39 examples/s]
Generating train split: 4291138 examples [09:21, 4739.83 examples/s]
Generating train split: 4293452 examples [09:25, 2260.32 examples/s]
Generating train split: 4295092 examples [09:26, 2296.10 examples/s]
Generating train split: 4296308 examples [09:26, 2362.50 examples/s]
Generating train split: 4297271 examples [09:26, 2501.45 examples/s]
Generating train split: 4298106 examples [09:27, 2387.78 examples/s]
Generating train split: 4307522 examples [09:27, 6991.57 examples/s]
Generating train split: 4313536 examples [09:27, 10541.73 examples/s]
Generating train split: 4322089 examples [09:27, 16965.76 examples/s]
Generating train split: 4327332 examples [09:29, 7227.42 examples/s] 
Generating train split: 4331112 examples [09:30, 5497.77 examples/s]
Generating train split: 4333830 examples [09:31, 4871.45 examples/s]
Generating train split: 4335848 examples [09:32, 4336.11 examples/s]
Generating train split: 4337358 examples [09:32, 3963.66 examples/s]
Generating train split: 4338473 examples [09:33, 3723.52 examples/s]
Generating train split: 4339367 examples [09:33, 3503.77 examples/s]
Generating train split: 4340069 examples [09:34, 3261.83 examples/s]
Generating train split: 4340617 examples [09:34, 3202.98 examples/s]
Generating train split: 4341113 examples [09:34, 3327.37 examples/s]
Generating train split: 4341617 examples [09:34, 3310.02 examples/s]
Generating train split: 4342040 examples [09:34, 3365.04 examples/s]
Generating train split: 4342466 examples [09:34, 3176.45 examples/s]
Generating train split: 4342862 examples [09:34, 3046.87 examples/s]
Generating train split: 4343194 examples [09:35, 2766.09 examples/s]
Generating train split: 4343517 examples [09:35, 2643.33 examples/s]
Generating train split: 4343796 examples [09:35, 2577.64 examples/s]
Generating train split: 4344100 examples [09:35, 2672.88 examples/s]
Generating train split: 4344456 examples [09:35, 2864.16 examples/s]
Generating train split: 4344936 examples [09:35, 3327.60 examples/s]
Generating train split: 4345353 examples [09:35, 3461.73 examples/s]
Generating train split: 4345743 examples [09:35, 3486.28 examples/s]
Generating train split: 4346148 examples [09:35, 3499.68 examples/s]
Generating train split: 4346537 examples [09:36, 3071.87 examples/s]
Generating train split: 4346872 examples [09:36, 3096.16 examples/s]
Generating train split: 4347213 examples [09:37, 669.44 examples/s] 
Generating train split: 4347778 examples [09:37, 1021.89 examples/s]
Generating train split: 4348119 examples [09:38, 1230.16 examples/s]
Generating train split: 4348611 examples [09:38, 1646.10 examples/s]
Generating train split: 4349009 examples [09:38, 1963.67 examples/s]
Generating train split: 4349390 examples [09:38, 2115.79 examples/s]
Generating train split: 4349753 examples [09:38, 2382.77 examples/s]
Generating train split: 4350254 examples [09:38, 2870.12 examples/s]
Generating train split: 4350664 examples [09:38, 2745.40 examples/s]
Generating train split: 4351008 examples [09:38, 2873.66 examples/s]
Generating train split: 4351364 examples [09:39, 2746.95 examples/s]
Generating train split: 4351692 examples [09:39, 2665.02 examples/s]
Generating train split: 4352049 examples [09:39, 2852.22 examples/s]
Generating train split: 4352524 examples [09:39, 3266.65 examples/s]
Generating train split: 4352890 examples [09:39, 2684.82 examples/s]
Generating train split: 4361964 examples [09:39, 22805.78 examples/s]
Generating train split: 4371871 examples [09:39, 41561.90 examples/s]
Generating train split: 4381154 examples [09:39, 54875.65 examples/s]
Generating train split: 4392794 examples [09:39, 71494.62 examples/s]
Generating train split: 4400696 examples [09:41, 14076.64 examples/s]
Generating train split: 4406366 examples [09:43, 8085.09 examples/s] 
Generating train split: 4410476 examples [09:44, 6178.96 examples/s]
Generating train split: 4413453 examples [09:45, 5128.93 examples/s]
Generating train split: 4415614 examples [09:46, 4774.14 examples/s]
Generating train split: 4417219 examples [09:46, 4678.65 examples/s]
Generating train split: 4418477 examples [09:49, 1863.42 examples/s]
Generating train split: 4419394 examples [09:50, 1964.40 examples/s]
Generating train split: 4420119 examples [09:50, 2050.35 examples/s]
Generating train split: 4420747 examples [09:50, 2136.24 examples/s]
Generating train split: 4421302 examples [09:50, 2237.35 examples/s]
Generating train split: 4421753 examples [09:51, 2366.27 examples/s]
Generating train split: 4422188 examples [09:51, 2320.10 examples/s]
Generating train split: 4422567 examples [09:51, 2326.13 examples/s]
Generating train split: 4423018 examples [09:51, 2587.19 examples/s]
Generating train split: 4423382 examples [09:51, 2685.79 examples/s]
Generating train split: 4423724 examples [09:51, 2524.44 examples/s]
Generating train split: 4424033 examples [09:51, 2557.03 examples/s]
Generating train split: 4424328 examples [09:51, 2565.04 examples/s]
Generating train split: 4424647 examples [09:52, 2662.76 examples/s]
Generating train split: 4424982 examples [09:52, 1839.93 examples/s]
Generating train split: 4435163 examples [09:52, 19880.60 examples/s]
Generating train split: 4447669 examples [09:52, 41435.04 examples/s]
Generating train split: 4459676 examples [09:52, 59232.86 examples/s]
Generating train split: 4467476 examples [09:55, 9624.93 examples/s] 
Generating train split: 4473068 examples [09:56, 6708.22 examples/s]
Generating train split: 4477071 examples [09:58, 5576.82 examples/s]
Generating train split: 4479962 examples [09:58, 4883.62 examples/s]
Generating train split: 4482116 examples [09:59, 4093.14 examples/s]
Generating train split: 4483678 examples [10:00, 4038.44 examples/s]
Generating train split: 4484879 examples [10:00, 3993.31 examples/s]
Generating train split: 4485843 examples [10:00, 4038.71 examples/s]
Generating train split: 4486641 examples [10:01, 4008.34 examples/s]
Generating train split: 4487323 examples [10:01, 3907.90 examples/s]
Generating train split: 4487940 examples [10:01, 3911.03 examples/s]
Generating train split: 4488459 examples [10:01, 3884.67 examples/s]
Generating train split: 4502709 examples [10:01, 23551.76 examples/s]
Generating train split: 4513851 examples [10:01, 38334.41 examples/s]
Generating train split: 4520408 examples [10:02, 28429.01 examples/s]
Generating train split: 4525563 examples [10:03, 10672.15 examples/s]
Generating train split: 4529258 examples [10:04, 7138.28 examples/s] 
Generating train split: 4531959 examples [10:05, 6039.98 examples/s]
Generating train split: 4533967 examples [10:06, 5160.29 examples/s]
Generating train split: 4535452 examples [10:06, 4404.29 examples/s]
Generating train split: 4536580 examples [10:07, 4312.90 examples/s]
Generating train split: 4537473 examples [10:08, 2674.00 examples/s]
Generating train split: 4538126 examples [10:08, 2730.38 examples/s]
Generating train split: 4538692 examples [10:08, 2713.66 examples/s]
Generating train split: 4539169 examples [10:09, 2730.87 examples/s]
Generating train split: 4539601 examples [10:09, 2792.51 examples/s]
Generating train split: 4540000 examples [10:09, 2848.92 examples/s]
Generating train split: 4540364 examples [10:09, 2939.43 examples/s]
Generating train split: 4540783 examples [10:09, 3127.99 examples/s]
Generating train split: 4541165 examples [10:09, 3105.05 examples/s]
Generating train split: 4541529 examples [10:09, 2886.94 examples/s]
Generating train split: 4541875 examples [10:09, 2964.97 examples/s]
Generating train split: 4542211 examples [10:09, 2836.62 examples/s]
Generating train split: 4542572 examples [10:10, 2942.48 examples/s]
Generating train split: 4542967 examples [10:10, 3145.39 examples/s]
Generating train split: 4543368 examples [10:10, 3263.26 examples/s]
Generating train split: 4543748 examples [10:10, 3324.81 examples/s]
Generating train split: 4544103 examples [10:10, 3375.60 examples/s]
Generating train split: 4544451 examples [10:10, 3140.23 examples/s]
Generating train split: 4544833 examples [10:10, 3246.65 examples/s]
Generating train split: 4545165 examples [10:10, 3059.88 examples/s]
Generating train split: 4545592 examples [10:11, 3270.41 examples/s]
Generating train split: 4545938 examples [10:11, 2912.25 examples/s]
Generating train split: 4546263 examples [10:11, 2583.70 examples/s]
Generating train split: 4546563 examples [10:11, 2634.68 examples/s]
Generating train split: 4546996 examples [10:11, 2519.09 examples/s]
Generating train split: 4557961 examples [10:11, 26818.39 examples/s]
Generating train split: 4565140 examples [10:11, 37810.18 examples/s]
Generating train split: 4575619 examples [10:11, 55112.09 examples/s]
Generating train split: 4581956 examples [10:13, 11117.46 examples/s]
Generating train split: 4586542 examples [10:14, 7540.45 examples/s] 
Generating train split: 4589860 examples [10:15, 5801.36 examples/s]
Generating train split: 4592265 examples [10:16, 4882.06 examples/s]
Generating train split: 4594056 examples [10:18, 3198.31 examples/s]
Generating train split: 4595345 examples [10:18, 3315.67 examples/s]
Generating train split: 4596376 examples [10:19, 3124.82 examples/s]
Generating train split: 4597180 examples [10:19, 3200.72 examples/s]
Generating train split: 4597846 examples [10:19, 3281.44 examples/s]
Generating train split: 4598456 examples [10:19, 3370.07 examples/s]
Generating train split: 4598982 examples [10:19, 3531.05 examples/s]
Generating train split: 4599531 examples [10:20, 3054.04 examples/s]
Generating train split: 4599978 examples [10:20, 2968.00 examples/s]
Generating train split: 4600358 examples [10:20, 3010.81 examples/s]
Generating train split: 4600754 examples [10:20, 2923.26 examples/s]
Generating train split: 4601161 examples [10:20, 3094.57 examples/s]
Generating train split: 4601554 examples [10:20, 3125.33 examples/s]
Generating train split: 4601948 examples [10:20, 3267.58 examples/s]
Generating train split: 4602317 examples [10:20, 3248.89 examples/s]
Generating train split: 4602699 examples [10:21, 3365.29 examples/s]
Generating train split: 4603180 examples [10:21, 3648.56 examples/s]
Generating train split: 4603566 examples [10:21, 2430.94 examples/s]
Generating train split: 4609115 examples [10:21, 12926.10 examples/s]
Generating train split: 4618062 examples [10:21, 29783.29 examples/s]
Generating train split: 4628806 examples [10:21, 48364.44 examples/s]
Generating train split: 4634813 examples [10:21, 43939.46 examples/s]
Generating train split: 4640110 examples [10:23, 8314.99 examples/s] 
Generating train split: 4643928 examples [10:25, 6288.96 examples/s]
Generating train split: 4646693 examples [10:25, 5379.02 examples/s]
Generating train split: 4648727 examples [10:26, 5124.61 examples/s]
Generating train split: 4650288 examples [10:28, 3021.86 examples/s]
Generating train split: 4651393 examples [10:28, 2943.66 examples/s]
Generating train split: 4652242 examples [10:28, 2955.98 examples/s]
Generating train split: 4652968 examples [10:29, 2963.80 examples/s]
Generating train split: 4653566 examples [10:29, 2886.46 examples/s]
Generating train split: 4654051 examples [10:29, 2774.78 examples/s]
Generating train split: 4654463 examples [10:29, 2905.04 examples/s]
Generating train split: 4654874 examples [10:29, 2969.45 examples/s]
Generating train split: 4655274 examples [10:29, 2909.03 examples/s]
Generating train split: 4655633 examples [10:30, 2714.04 examples/s]
Generating train split: 4655963 examples [10:30, 2542.19 examples/s]
Generating train split: 4656327 examples [10:30, 2729.15 examples/s]
Generating train split: 4656664 examples [10:30, 2836.90 examples/s]
Generating train split: 4656997 examples [10:30, 2658.38 examples/s]
Generating train split: 4657286 examples [10:30, 2697.07 examples/s]
Generating train split: 4657703 examples [10:30, 3021.86 examples/s]
Generating train split: 4658160 examples [10:30, 3290.72 examples/s]
Generating train split: 4658507 examples [10:31, 3127.45 examples/s]
Generating train split: 4658879 examples [10:31, 3165.85 examples/s]
Generating train split: 4659232 examples [10:31, 2821.22 examples/s]
Generating train split: 4659549 examples [10:31, 2642.62 examples/s]
Generating train split: 4659870 examples [10:31, 2751.10 examples/s]
Generating train split: 4660180 examples [10:31, 2653.92 examples/s]
Generating train split: 4660484 examples [10:31, 2437.34 examples/s]
Generating train split: 4660783 examples [10:31, 2547.95 examples/s]
Generating train split: 4661121 examples [10:32, 2664.49 examples/s]
Generating train split: 4661393 examples [10:32, 2429.71 examples/s]
Generating train split: 4661740 examples [10:32, 2642.31 examples/s]
Generating train split: 4662052 examples [10:32, 2572.87 examples/s]
Generating train split: 4662516 examples [10:32, 3093.02 examples/s]
Generating train split: 4668753 examples [10:32, 18997.54 examples/s]
Generating train split: 4687067 examples [10:32, 64276.07 examples/s]
Generating train split: 4694840 examples [10:32, 67142.07 examples/s]
Generating train split: 4701921 examples [10:32, 65951.30 examples/s]
Generating train split: 4708797 examples [10:34, 16750.28 examples/s]
Generating train split: 4713767 examples [10:35, 8663.95 examples/s] 
Generating train split: 4717351 examples [10:36, 6620.18 examples/s]
Generating train split: 4719962 examples [10:38, 4480.81 examples/s]
Generating train split: 4721858 examples [10:38, 4031.02 examples/s]
Generating train split: 4723275 examples [10:39, 3622.37 examples/s]
Generating train split: 4724353 examples [10:39, 3738.54 examples/s]
Generating train split: 4725231 examples [10:40, 3623.35 examples/s]
Generating train split: 4725933 examples [10:40, 3552.70 examples/s]
Generating train split: 4726532 examples [10:40, 3734.82 examples/s]
Generating train split: 4727127 examples [10:40, 3931.79 examples/s]
Generating train split: 4727733 examples [10:40, 4059.25 examples/s]
Generating train split: 4728269 examples [10:40, 3958.82 examples/s]
Generating train split: 4728772 examples [10:41, 3834.61 examples/s]
Generating train split: 4729252 examples [10:41, 4011.68 examples/s]
Generating train split: 4729717 examples [10:41, 3931.68 examples/s]
Generating train split: 4730157 examples [10:41, 3396.92 examples/s]
Generating train split: 4730581 examples [10:41, 3442.94 examples/s]
Generating train split: 4730949 examples [10:41, 3359.85 examples/s]
Generating train split: 4731319 examples [10:41, 2992.64 examples/s]
Generating train split: 4731704 examples [10:41, 3149.30 examples/s]
Generating train split: 4732071 examples [10:42, 3228.51 examples/s]
Generating train split: 4732434 examples [10:42, 3312.53 examples/s]
Generating train split: 4732814 examples [10:42, 3121.33 examples/s]
Generating train split: 4733159 examples [10:42, 3151.74 examples/s]
Generating train split: 4733486 examples [10:42, 3121.63 examples/s]
Generating train split: 4733995 examples [10:42, 3565.28 examples/s]
Generating train split: 4734385 examples [10:42, 3194.05 examples/s]
Generating train split: 4734795 examples [10:42, 2882.66 examples/s]
Generating train split: 4753180 examples [10:43, 45175.47 examples/s]
Generating train split: 4766135 examples [10:43, 66280.25 examples/s]
Generating train split: 4781292 examples [10:43, 88428.12 examples/s]
Generating train split: 4791297 examples [10:47, 7453.95 examples/s] 
Generating train split: 4798360 examples [10:49, 5546.86 examples/s]
Generating train split: 4803436 examples [10:51, 5024.99 examples/s]
Generating train split: 4807101 examples [10:52, 4504.07 examples/s]
Generating train split: 4809761 examples [10:54, 3411.66 examples/s]
Generating train split: 4827770 examples [10:54, 8019.01 examples/s]
Generating train split: 4837306 examples [10:54, 11155.07 examples/s]
Generating train split: 4844876 examples [10:54, 12498.74 examples/s]
Generating train split: 4850756 examples [10:56, 7575.52 examples/s] 
Generating train split: 4854955 examples [10:58, 5893.01 examples/s]
Generating train split: 4857998 examples [10:59, 5235.83 examples/s]
Generating train split: 4860223 examples [10:59, 4713.62 examples/s]
Generating train split: 4861871 examples [11:00, 4257.09 examples/s]
Generating train split: 4863124 examples [11:00, 3978.05 examples/s]
Generating train split: 4864086 examples [11:01, 3769.89 examples/s]
Generating train split: 4864838 examples [11:01, 3648.08 examples/s]
Generating train split: 4865464 examples [11:01, 3613.24 examples/s]
Generating train split: 4866029 examples [11:01, 3486.09 examples/s]
Generating train split: 4866495 examples [11:02, 3297.27 examples/s]
Generating train split: 4866973 examples [11:02, 3443.84 examples/s]
Generating train split: 4867406 examples [11:02, 3281.70 examples/s]
Generating train split: 4867829 examples [11:02, 3080.29 examples/s]
Generating train split: 4868168 examples [11:02, 2799.14 examples/s]
Generating train split: 4868640 examples [11:02, 3094.44 examples/s]
Generating train split: 4869024 examples [11:02, 3241.12 examples/s]
Generating train split: 4869404 examples [11:03, 3184.03 examples/s]
Generating train split: 4869756 examples [11:03, 3155.62 examples/s]
Generating train split: 4870087 examples [11:04, 695.29 examples/s] 
Generating train split: 4870423 examples [11:04, 879.73 examples/s]
Generating train split: 4870765 examples [11:05, 1097.01 examples/s]
Generating train split: 4871042 examples [11:05, 1279.39 examples/s]
Generating train split: 4871452 examples [11:05, 1652.31 examples/s]
Generating train split: 4871757 examples [11:05, 1482.88 examples/s]
Generating train split: 4880390 examples [11:05, 14711.94 examples/s]
Generating train split: 4888858 examples [11:05, 27454.06 examples/s]
Generating train split: 4899648 examples [11:05, 44021.58 examples/s]
Generating train split: 4906013 examples [11:06, 15948.59 examples/s]
Generating train split: 4910676 examples [11:08, 8263.53 examples/s] 
Generating train split: 4914052 examples [11:09, 6551.65 examples/s]
Generating train split: 4916501 examples [11:10, 5234.03 examples/s]
Generating train split: 4918301 examples [11:10, 4576.97 examples/s]
Generating train split: 4919666 examples [11:11, 4261.60 examples/s]
Generating train split: 4920711 examples [11:11, 3968.22 examples/s]
Generating train split: 4921541 examples [11:11, 3786.92 examples/s]
Generating train split: 4922198 examples [11:12, 3787.20 examples/s]
Generating train split: 4922780 examples [11:12, 3794.52 examples/s]
Generating train split: 4923313 examples [11:12, 3705.60 examples/s]
Generating train split: 4923792 examples [11:12, 3787.65 examples/s]
Generating train split: 4924264 examples [11:12, 3550.72 examples/s]
Generating train split: 4924694 examples [11:12, 2977.66 examples/s]
Generating train split: 4925032 examples [11:13, 2967.62 examples/s]
Generating train split: 4925429 examples [11:13, 3138.12 examples/s]
Generating train split: 4925776 examples [11:13, 3008.84 examples/s]
Generating train split: 4926106 examples [11:13, 3044.96 examples/s]
Generating train split: 4926609 examples [11:13, 3398.49 examples/s]
Generating train split: 4926969 examples [11:13, 3370.54 examples/s]
Generating train split: 4927337 examples [11:13, 3297.78 examples/s]
Generating train split: 4927678 examples [11:13, 3233.69 examples/s]
Generating train split: 4928086 examples [11:13, 3409.63 examples/s]
Generating train split: 4928438 examples [11:14, 2835.03 examples/s]
Generating train split: 4928758 examples [11:14, 2706.32 examples/s]
Generating train split: 4929071 examples [11:14, 2748.80 examples/s]
Generating train split: 4929512 examples [11:15, 1118.96 examples/s]
Generating train split: 4929835 examples [11:15, 1349.48 examples/s]
Generating train split: 4930141 examples [11:15, 1575.84 examples/s]
Generating train split: 4930551 examples [11:15, 1942.78 examples/s]
Generating train split: 4930840 examples [11:15, 2088.93 examples/s]
Generating train split: 4931249 examples [11:15, 2446.98 examples/s]
Generating train split: 4931558 examples [11:15, 1884.39 examples/s]
Generating train split: 4940005 examples [11:16, 17516.13 examples/s]
Generating train split: 4947005 examples [11:16, 28532.66 examples/s]
Generating train split: 4952924 examples [11:16, 35579.22 examples/s]
Generating train split: 4957470 examples [11:16, 24709.41 examples/s]
Generating train split: 4961070 examples [11:18, 7442.64 examples/s] 
Generating train split: 4963680 examples [11:18, 6128.75 examples/s]
Generating train split: 4965633 examples [11:19, 5145.86 examples/s]
Generating train split: 4967090 examples [11:19, 4723.00 examples/s]
Generating train split: 4968197 examples [11:20, 4274.95 examples/s]
Generating train split: 4969067 examples [11:20, 3977.93 examples/s]
Generating train split: 4969802 examples [11:20, 3802.66 examples/s]
Generating train split: 4970388 examples [11:21, 3695.57 examples/s]
Generating train split: 4970907 examples [11:21, 3552.67 examples/s]
Generating train split: 4971354 examples [11:21, 3511.54 examples/s]
Generating train split: 4971776 examples [11:21, 3175.28 examples/s]
Generating train split: 4972144 examples [11:21, 3064.95 examples/s]
Generating train split: 4972479 examples [11:21, 2844.51 examples/s]
Generating train split: 4972810 examples [11:21, 2882.00 examples/s]
Generating train split: 4973178 examples [11:22, 3018.80 examples/s]
Generating train split: 4973514 examples [11:22, 2983.75 examples/s]
Generating train split: 4973845 examples [11:22, 2976.83 examples/s]
Generating train split: 4974187 examples [11:22, 3053.65 examples/s]
Generating train split: 4974512 examples [11:22, 2703.37 examples/s]
Generating train split: 4974816 examples [11:22, 2422.96 examples/s]
Generating train split: 4975168 examples [11:22, 2635.04 examples/s]
Generating train split: 4975618 examples [11:22, 3088.26 examples/s]
Generating train split: 4976038 examples [11:22, 3342.05 examples/s]
Generating train split: 4976393 examples [11:23, 2958.43 examples/s]
Generating train split: 4976719 examples [11:23, 2937.83 examples/s]
Generating train split: 4977045 examples [11:23, 2906.10 examples/s]
Generating train split: 4977381 examples [11:23, 2953.76 examples/s]
Generating train split: 4977734 examples [11:23, 3059.40 examples/s]
Generating train split: 4978084 examples [11:23, 3023.31 examples/s]
Generating train split: 4978476 examples [11:23, 3208.08 examples/s]
Generating train split: 4978887 examples [11:23, 3371.48 examples/s]
Generating train split: 4979257 examples [11:24, 3307.16 examples/s]
Generating train split: 4979611 examples [11:24, 3324.31 examples/s]
Generating train split: 4980042 examples [11:24, 3577.76 examples/s]
Generating train split: 4980515 examples [11:24, 3802.20 examples/s]
Generating train split: 4980917 examples [11:24, 3333.81 examples/s]
Generating train split: 4981305 examples [11:24, 3044.35 examples/s]
Generating train split: 4981633 examples [11:24, 2957.06 examples/s]
Generating train split: 4981977 examples [11:25, 1165.79 examples/s]
Generating train split: 4982236 examples [11:25, 1313.37 examples/s]
Generating train split: 4982620 examples [11:25, 1654.43 examples/s]
Generating train split: 4982903 examples [11:25, 1800.08 examples/s]
Generating train split: 4983250 examples [11:25, 2103.24 examples/s]
Generating train split: 4983588 examples [11:26, 2321.14 examples/s]
Generating train split: 4983881 examples [11:26, 2386.31 examples/s]
Generating train split: 4984166 examples [11:26, 2268.16 examples/s]
Generating train split: 4984460 examples [11:26, 1761.10 examples/s]
Generating train split: 4989967 examples [11:26, 12295.45 examples/s]
Generating train split: 4995241 examples [11:26, 21176.84 examples/s]
Generating train split: 5014644 examples [11:26, 61342.74 examples/s]
Generating train split: 5022065 examples [11:29, 9053.83 examples/s] 
Generating train split: 5027328 examples [11:31, 6092.76 examples/s]
Generating train split: 5031109 examples [11:32, 4887.16 examples/s]
Generating train split: 5033826 examples [11:33, 4436.96 examples/s]
Generating train split: 5035832 examples [11:34, 4126.54 examples/s]
Generating train split: 5037331 examples [11:34, 3784.67 examples/s]
Generating train split: 5038463 examples [11:35, 3779.00 examples/s]
Generating train split: 5039359 examples [11:36, 2542.50 examples/s]
Generating train split: 5040033 examples [11:36, 2612.88 examples/s]
Generating train split: 5040584 examples [11:36, 2696.87 examples/s]
Generating train split: 5041111 examples [11:36, 2775.23 examples/s]
Generating train split: 5041591 examples [11:37, 2792.97 examples/s]
Generating train split: 5042004 examples [11:37, 2791.59 examples/s]
Generating train split: 5042385 examples [11:37, 2726.44 examples/s]
Generating train split: 5051543 examples [11:37, 16240.96 examples/s]
Generating train split: 5057985 examples [11:37, 24793.59 examples/s]
Generating train split: 5062730 examples [11:37, 29279.58 examples/s]
Generating train split: 5067744 examples [11:37, 33353.52 examples/s]
Generating train split: 5072079 examples [11:39, 7870.84 examples/s] 
Generating train split: 5075202 examples [11:40, 5503.88 examples/s]
Generating train split: 5077493 examples [11:41, 4795.02 examples/s]
Generating train split: 5079202 examples [11:41, 4398.80 examples/s]
Generating train split: 5080513 examples [11:42, 3998.04 examples/s]
Generating train split: 5081506 examples [11:42, 3777.85 examples/s]
Generating train split: 5082305 examples [11:42, 3517.58 examples/s]
Generating train split: 5082939 examples [11:43, 3267.48 examples/s]
Generating train split: 5083469 examples [11:43, 3326.02 examples/s]
Generating train split: 5083958 examples [11:43, 3374.05 examples/s]
Generating train split: 5084409 examples [11:43, 3397.69 examples/s]
Generating train split: 5084817 examples [11:43, 3452.44 examples/s]
Generating train split: 5085234 examples [11:43, 3566.82 examples/s]
Generating train split: 5085655 examples [11:43, 3316.06 examples/s]
Generating train split: 5086024 examples [11:44, 3239.94 examples/s]
Generating train split: 5086367 examples [11:44, 3073.66 examples/s]
Generating train split: 5086710 examples [11:44, 2909.61 examples/s]
Generating train split: 5087018 examples [11:44, 2762.05 examples/s]
Generating train split: 5087363 examples [11:44, 2867.14 examples/s]
Generating train split: 5087663 examples [11:44, 2814.44 examples/s]
Generating train split: 5087970 examples [11:44, 2803.55 examples/s]
Generating train split: 5088371 examples [11:44, 3092.91 examples/s]
Generating train split: 5088700 examples [11:45, 2881.34 examples/s]
Generating train split: 5089021 examples [11:45, 2775.13 examples/s]
Generating train split: 5089395 examples [11:45, 2996.75 examples/s]
Generating train split: 5089703 examples [11:45, 2554.77 examples/s]
Generating train split: 5089991 examples [11:45, 2509.07 examples/s]
Generating train split: 5090278 examples [11:45, 2532.89 examples/s]
Generating train split: 5090684 examples [11:45, 2920.97 examples/s]
Generating train split: 5091030 examples [11:45, 3018.25 examples/s]
Generating train split: 5091353 examples [11:46, 2895.74 examples/s]
Generating train split: 5091777 examples [11:46, 3219.21 examples/s]
Generating train split: 5092146 examples [11:46, 3312.73 examples/s]
Generating train split: 5092508 examples [11:47, 712.85 examples/s] 
Generating train split: 5092772 examples [11:47, 854.36 examples/s]
Generating train split: 5093096 examples [11:47, 1085.62 examples/s]
Generating train split: 5093394 examples [11:48, 1309.42 examples/s]
Generating train split: 5093663 examples [11:48, 1477.26 examples/s]
Generating train split: 5094032 examples [11:48, 1809.72 examples/s]
Generating train split: 5094322 examples [11:48, 2019.06 examples/s]
Generating train split: 5094606 examples [11:48, 2194.79 examples/s]
Generating train split: 5095164 examples [11:48, 2989.40 examples/s]
Generating train split: 5095568 examples [11:48, 3217.17 examples/s]
Generating train split: 5095942 examples [11:48, 3343.17 examples/s]
Generating train split: 5096319 examples [11:48, 2467.66 examples/s]
Generating train split: 5104977 examples [11:49, 20672.69 examples/s]
Generating train split: 5119703 examples [11:49, 50567.48 examples/s]
Generating train split: 5136205 examples [11:49, 79045.59 examples/s]
Generating train split: 5145553 examples [11:52, 9758.43 examples/s] 
Generating train split: 5152187 examples [11:54, 6150.85 examples/s]
Generating train split: 5156920 examples [11:56, 5209.07 examples/s]
Generating train split: 5160338 examples [11:58, 3724.47 examples/s]
Generating train split: 5162793 examples [11:59, 3674.44 examples/s]
Generating train split: 5168363 examples [11:59, 5234.38 examples/s]
Generating train split: 5176380 examples [11:59, 8312.65 examples/s]
Generating train split: 5182431 examples [11:59, 11205.26 examples/s]
Generating train split: 5187384 examples [11:59, 11770.07 examples/s]
Generating train split: 5191261 examples [12:01, 7059.32 examples/s] 
Generating train split: 5194065 examples [12:01, 6158.59 examples/s]
Generating train split: 5196181 examples [12:02, 5421.15 examples/s]
Generating train split: 5197765 examples [12:02, 5079.29 examples/s]
Generating train split: 5198993 examples [12:03, 4612.66 examples/s]
Generating train split: 5199945 examples [12:03, 4183.59 examples/s]
Generating train split: 5200678 examples [12:03, 3946.33 examples/s]
Generating train split: 5201283 examples [12:04, 3804.02 examples/s]
Generating train split: 5201833 examples [12:04, 3713.76 examples/s]
Generating train split: 5202296 examples [12:04, 3232.40 examples/s]
Generating train split: 5202709 examples [12:04, 3105.77 examples/s]
Generating train split: 5203068 examples [12:04, 3092.78 examples/s]
Generating train split: 5203418 examples [12:04, 3058.03 examples/s]
Generating train split: 5203743 examples [12:04, 2882.35 examples/s]
Generating train split: 5204057 examples [12:05, 2776.15 examples/s]
Generating train split: 5204362 examples [12:05, 2739.41 examples/s]
Generating train split: 5204645 examples [12:05, 2741.26 examples/s]
Generating train split: 5204947 examples [12:05, 2764.50 examples/s]
Generating train split: 5205234 examples [12:05, 2692.19 examples/s]
Generating train split: 5205531 examples [12:05, 2637.92 examples/s]
Generating train split: 5205822 examples [12:05, 2479.54 examples/s]
Generating train split: 5206094 examples [12:05, 2479.82 examples/s]
Generating train split: 5206345 examples [12:06, 759.26 examples/s] 
Generating train split: 5206724 examples [12:06, 1069.49 examples/s]
Generating train split: 5207040 examples [12:07, 1328.19 examples/s]
Generating train split: 5207345 examples [12:07, 1573.59 examples/s]
Generating train split: 5207634 examples [12:07, 1775.84 examples/s]
Generating train split: 5208014 examples [12:07, 2117.68 examples/s]
Generating train split: 5208442 examples [12:07, 2553.68 examples/s]
Generating train split: 5208772 examples [12:07, 2677.48 examples/s]
Generating train split: 5209099 examples [12:07, 2624.02 examples/s]
Generating train split: 5209475 examples [12:07, 2896.63 examples/s]
Generating train split: 5209825 examples [12:07, 3033.43 examples/s]
Generating train split: 5210163 examples [12:08, 2859.11 examples/s]
Generating train split: 5210476 examples [12:08, 2874.20 examples/s]
Generating train split: 5210822 examples [12:08, 3028.83 examples/s]
Generating train split: 5211187 examples [12:08, 3079.66 examples/s]
Generating train split: 5211540 examples [12:08, 2993.74 examples/s]
Generating train split: 5211954 examples [12:08, 3258.56 examples/s]
Generating train split: 5212289 examples [12:08, 2585.17 examples/s]
Generating train split: 5217940 examples [12:08, 15267.04 examples/s]
Generating train split: 5225265 examples [12:09, 29817.92 examples/s]
Generating train split: 5239855 examples [12:09, 60476.73 examples/s]
Generating train split: 5246691 examples [12:10, 15331.59 examples/s]
Generating train split: 5251669 examples [12:12, 7864.50 examples/s] 
Generating train split: 5255263 examples [12:13, 5824.38 examples/s]
Generating train split: 5257862 examples [12:14, 5089.75 examples/s]
Generating train split: 5259774 examples [12:14, 4391.13 examples/s]
Generating train split: 5261176 examples [12:15, 4066.34 examples/s]
Generating train split: 5262261 examples [12:15, 3860.36 examples/s]
Generating train split: 5263126 examples [12:16, 3674.68 examples/s]
Generating train split: 5263830 examples [12:16, 3549.40 examples/s]
Generating train split: 5264384 examples [12:16, 3468.85 examples/s]
Generating train split: 5264886 examples [12:17, 1912.21 examples/s]
Generating train split: 5265257 examples [12:17, 2037.13 examples/s]
Generating train split: 5265646 examples [12:17, 2190.33 examples/s]
Generating train split: 5266011 examples [12:17, 2233.49 examples/s]
Generating train split: 5266348 examples [12:17, 2266.13 examples/s]
Generating train split: 5266667 examples [12:18, 2305.73 examples/s]
Generating train split: 5266964 examples [12:18, 2177.57 examples/s]
Generating train split: 5267225 examples [12:18, 2218.44 examples/s]
Generating train split: 5267499 examples [12:18, 2163.83 examples/s]
Generating train split: 5267752 examples [12:18, 2162.35 examples/s]
Generating train split: 5268097 examples [12:18, 2449.60 examples/s]
Generating train split: 5268427 examples [12:18, 2643.56 examples/s]
Generating train split: 5268774 examples [12:18, 2793.96 examples/s]
Generating train split: 5269113 examples [12:19, 2637.25 examples/s]
Generating train split: 5269512 examples [12:19, 2944.26 examples/s]
Generating train split: 5269964 examples [12:19, 3329.04 examples/s]
Generating train split: 5270317 examples [12:19, 3254.20 examples/s]
Generating train split: 5270652 examples [12:19, 2680.78 examples/s]
Generating train split: 5271026 examples [12:19, 2896.28 examples/s]
Generating train split: 5271384 examples [12:19, 2113.43 examples/s]
Generating train split: 5278043 examples [12:20, 14967.67 examples/s]
Generating train split: 5284725 examples [12:20, 26460.76 examples/s]
Generating train split: 5290498 examples [12:20, 33919.80 examples/s]
Generating train split: 5294710 examples [12:20, 20859.14 examples/s]
Generating train split: 5297993 examples [12:21, 7876.29 examples/s] 
Generating train split: 5300364 examples [12:22, 6042.06 examples/s]
Generating train split: 5302137 examples [12:23, 4751.56 examples/s]
Generating train split: 5303472 examples [12:23, 4502.32 examples/s]
Generating train split: 5304507 examples [12:24, 4276.49 examples/s]
Generating train split: 5305347 examples [12:24, 4009.64 examples/s]
Generating train split: 5306020 examples [12:24, 3701.25 examples/s]
Generating train split: 5306570 examples [12:24, 3498.49 examples/s]
Generating train split: 5307045 examples [12:24, 3276.93 examples/s]
Generating train split: 5307459 examples [12:25, 3242.36 examples/s]
Generating train split: 5307845 examples [12:25, 3130.25 examples/s]
Generating train split: 5308186 examples [12:25, 3012.63 examples/s]
Generating train split: 5308522 examples [12:25, 2861.58 examples/s]
Generating train split: 5308892 examples [12:25, 3003.90 examples/s]
Generating train split: 5309236 examples [12:25, 2726.05 examples/s]
Generating train split: 5309534 examples [12:25, 2676.54 examples/s]
Generating train split: 5309818 examples [12:26, 2446.09 examples/s]
Generating train split: 5310090 examples [12:26, 2347.82 examples/s]
Generating train split: 5310344 examples [12:26, 2288.55 examples/s]
Generating train split: 5310591 examples [12:26, 2296.42 examples/s]
Generating train split: 5310836 examples [12:26, 2333.50 examples/s]
Generating train split: 5311084 examples [12:26, 2242.42 examples/s]
Generating train split: 5311384 examples [12:26, 2410.09 examples/s]
Generating train split: 5311795 examples [12:26, 2868.33 examples/s]
Generating train split: 5312143 examples [12:26, 2988.27 examples/s]
Generating train split: 5312453 examples [12:27, 2863.31 examples/s]
Generating train split: 5312745 examples [12:28, 556.54 examples/s] 
Generating train split: 5312984 examples [12:28, 684.65 examples/s]
Generating train split: 5313230 examples [12:28, 825.57 examples/s]
Generating train split: 5313479 examples [12:29, 992.69 examples/s]
Generating train split: 5313715 examples [12:29, 1165.17 examples/s]
Generating train split: 5313990 examples [12:29, 1387.34 examples/s]
Generating train split: 5314277 examples [12:29, 1635.76 examples/s]
Generating train split: 5314553 examples [12:29, 1802.08 examples/s]
Generating train split: 5314818 examples [12:29, 1925.05 examples/s]
Generating train split: 5315058 examples [12:29, 2028.61 examples/s]
Generating train split: 5315430 examples [12:29, 2444.60 examples/s]
Generating train split: 5315737 examples [12:29, 2517.76 examples/s]
Generating train split: 5316031 examples [12:30, 2563.59 examples/s]
Generating train split: 5316319 examples [12:30, 2565.20 examples/s]
Generating train split: 5316627 examples [12:30, 2678.32 examples/s]
Generating train split: 5316932 examples [12:30, 2743.48 examples/s]
Generating train split: 5317241 examples [12:30, 2665.71 examples/s]
Generating train split: 5317517 examples [12:30, 2506.92 examples/s]
Generating train split: 5317779 examples [12:30, 2531.16 examples/s]
Generating train split: 5318061 examples [12:30, 2577.54 examples/s]
Generating train split: 5318455 examples [12:30, 2858.33 examples/s]
Generating train split: 5318781 examples [12:31, 2639.52 examples/s]
Generating train split: 5319138 examples [12:31, 2810.96 examples/s]
Generating train split: 5319426 examples [12:31, 2543.79 examples/s]
Generating train split: 5319736 examples [12:31, 2589.39 examples/s]
Generating train split: 5320035 examples [12:31, 2625.84 examples/s]
Generating train split: 5320311 examples [12:31, 2596.21 examples/s]
Generating train split: 5320585 examples [12:31, 2456.83 examples/s]
Generating train split: 5320848 examples [12:31, 2443.80 examples/s]
Generating train split: 5321791 examples [12:31, 4326.67 examples/s]
Generating train split: 5330112 examples [12:32, 26258.24 examples/s]
Generating train split: 5347518 examples [12:32, 68271.15 examples/s]
Generating train split: 5357047 examples [12:32, 75630.25 examples/s]
Generating train split: 5364908 examples [12:34, 9011.14 examples/s] 
Generating train split: 5370495 examples [12:36, 5944.61 examples/s]
Generating train split: 5374481 examples [12:38, 4814.70 examples/s]
Generating train split: 5377354 examples [12:40, 3378.65 examples/s]
Generating train split: 5379432 examples [12:41, 3409.36 examples/s]
Generating train split: 5381004 examples [12:41, 3221.51 examples/s]
Generating train split: 5382162 examples [12:42, 3235.20 examples/s]
Generating train split: 5383089 examples [12:42, 3011.72 examples/s]
Generating train split: 5383787 examples [12:42, 3008.09 examples/s]
Generating train split: 5384400 examples [12:42, 3185.36 examples/s]
Generating train split: 5384976 examples [12:43, 3103.85 examples/s]
Generating train split: 5385465 examples [12:43, 3077.66 examples/s]
Generating train split: 5385897 examples [12:43, 2962.89 examples/s]
Generating train split: 5386297 examples [12:43, 2996.93 examples/s]
Generating train split: 5408435 examples [12:43, 37578.88 examples/s]
Generating train split: 5426492 examples [12:43, 63657.52 examples/s]
Generating train split: 5436618 examples [12:47, 9142.43 examples/s] 
Generating train split: 5443795 examples [12:50, 4980.85 examples/s]
Generating train split: 5448869 examples [12:52, 4323.91 examples/s]
Generating train split: 5452534 examples [12:54, 3985.09 examples/s]
Generating train split: 5455170 examples [12:54, 3903.96 examples/s]
Generating train split: 5478317 examples [12:54, 10595.65 examples/s]
Generating train split: 5493355 examples [12:54, 16228.36 examples/s]
Generating train split: 5503665 examples [12:58, 7067.79 examples/s] 
Generating train split: 5510973 examples [13:03, 4206.35 examples/s]
Generating train split: 5516133 examples [13:04, 3968.28 examples/s]
Generating train split: 5519840 examples [13:05, 3837.72 examples/s]
Generating train split: 5522534 examples [13:06, 3991.40 examples/s]
Generating train split: 5527129 examples [13:06, 5178.79 examples/s]
Generating train split: 5533213 examples [13:06, 7341.89 examples/s]
Generating train split: 5550485 examples [13:06, 16041.51 examples/s]
Generating train split: 5558311 examples [13:07, 15525.39 examples/s]
Generating train split: 5564224 examples [13:09, 7783.80 examples/s] 
Generating train split: 5568455 examples [13:11, 4643.06 examples/s]
Generating train split: 5571460 examples [13:12, 4152.63 examples/s]
Generating train split: 5573664 examples [13:13, 3826.45 examples/s]
Generating train split: 5575294 examples [13:14, 3723.01 examples/s]
Generating train split: 5576517 examples [13:14, 3541.16 examples/s]
Generating train split: 5577471 examples [13:15, 3446.17 examples/s]
Generating train split: 5578234 examples [13:15, 3456.20 examples/s]
Generating train split: 5578864 examples [13:15, 3374.84 examples/s]
Generating train split: 5579394 examples [13:15, 3153.91 examples/s]
Generating train split: 5579865 examples [13:15, 3107.16 examples/s]
Generating train split: 5580254 examples [13:15, 3170.66 examples/s]
Generating train split: 5580661 examples [13:16, 3127.61 examples/s]
Generating train split: 5581019 examples [13:16, 2745.13 examples/s]
Generating train split: 5581352 examples [13:16, 2621.12 examples/s]
Generating train split: 5581641 examples [13:16, 2471.21 examples/s]
Generating train split: 5581899 examples [13:16, 2447.33 examples/s]
Generating train split: 5582164 examples [13:16, 2367.25 examples/s]
Generating train split: 5582514 examples [13:16, 2570.48 examples/s]
Generating train split: 5582836 examples [13:17, 2629.51 examples/s]
Generating train split: 5583117 examples [13:17, 2451.69 examples/s]
Generating train split: 5583367 examples [13:17, 2398.21 examples/s]
Generating train split: 5583688 examples [13:17, 2568.55 examples/s]
Generating train split: 5584010 examples [13:17, 1999.03 examples/s]
Generating train split: 5591283 examples [13:17, 17185.66 examples/s]
Generating train split: 5595102 examples [13:17, 22116.49 examples/s]
Generating train split: 5601027 examples [13:17, 31374.00 examples/s]
Generating train split: 5606383 examples [13:18, 37211.69 examples/s]
Generating train split: 5610582 examples [13:18, 19459.55 examples/s]
Generating train split: 5613828 examples [13:19, 8184.54 examples/s] 
Generating train split: 5616186 examples [13:20, 5921.09 examples/s]
Generating train split: 5617911 examples [13:22, 2731.70 examples/s]
Generating train split: 5619147 examples [13:23, 2812.27 examples/s]
Generating train split: 5620124 examples [13:23, 2791.30 examples/s]
Generating train split: 5620926 examples [13:23, 2844.10 examples/s]
Generating train split: 5621585 examples [13:23, 2858.17 examples/s]
Generating train split: 5622117 examples [13:24, 2873.30 examples/s]
Generating train split: 5622597 examples [13:24, 2888.48 examples/s]
Generating train split: 5623023 examples [13:24, 2799.72 examples/s]
Generating train split: 5623400 examples [13:24, 2714.20 examples/s]
Generating train split: 5623725 examples [13:24, 2646.45 examples/s]
Generating train split: 5624046 examples [13:24, 2577.17 examples/s]
Generating train split: 5624402 examples [13:24, 2711.58 examples/s]
Generating train split: 5624730 examples [13:25, 2679.04 examples/s]
Generating train split: 5625029 examples [13:25, 2310.23 examples/s]
Generating train split: 5625322 examples [13:25, 2393.74 examples/s]
Generating train split: 5625586 examples [13:25, 2423.47 examples/s]
Generating train split: 5625871 examples [13:25, 2517.79 examples/s]
Generating train split: 5626147 examples [13:25, 2578.68 examples/s]
Generating train split: 5626421 examples [13:25, 2466.88 examples/s]
Generating train split: 5626928 examples [13:25, 3061.68 examples/s]
Generating train split: 5627262 examples [13:26, 2695.65 examples/s]
Generating train split: 5627546 examples [13:26, 2692.79 examples/s]
Generating train split: 5627899 examples [13:26, 2840.68 examples/s]
Generating train split: 5628243 examples [13:26, 2920.00 examples/s]
Generating train split: 5628549 examples [13:26, 2809.20 examples/s]
Generating train split: 5628835 examples [13:26, 2791.61 examples/s]
Generating train split: 5629155 examples [13:26, 2786.77 examples/s]
Generating train split: 5629447 examples [13:26, 2805.85 examples/s]
Generating train split: 5629750 examples [13:26, 2732.54 examples/s]
Generating train split: 5630107 examples [13:27, 2942.05 examples/s]
Generating train split: 5630419 examples [13:27, 2541.68 examples/s]
Generating train split: 5630711 examples [13:27, 2465.86 examples/s]
Generating train split: 5630970 examples [13:27, 2396.44 examples/s]
Generating train split: 5631237 examples [13:27, 2318.80 examples/s]
Generating train split: 5631473 examples [13:27, 2313.88 examples/s]
Generating train split: 5631809 examples [13:27, 2568.41 examples/s]
Generating train split: 5632103 examples [13:27, 2574.90 examples/s]
Generating train split: 5632368 examples [13:28, 2454.82 examples/s]
Generating train split: 5632657 examples [13:28, 2353.46 examples/s]
Generating train split: 5633039 examples [13:28, 2674.38 examples/s]
Generating train split: 5633419 examples [13:28, 2933.17 examples/s]
Generating train split: 5633756 examples [13:28, 2841.26 examples/s]
Generating train split: 5634052 examples [13:28, 2723.58 examples/s]
Generating train split: 5634349 examples [13:28, 2571.77 examples/s]
Generating train split: 5634618 examples [13:28, 2526.86 examples/s]
Generating train split: 5634892 examples [13:28, 2429.90 examples/s]
Generating train split: 5635186 examples [13:29, 2555.63 examples/s]
Generating train split: 5635551 examples [13:29, 2781.23 examples/s]
Generating train split: 5635858 examples [13:31, 428.21 examples/s] 
Generating train split: 5636145 examples [13:31, 561.39 examples/s]
Generating train split: 5636458 examples [13:31, 744.67 examples/s]
Generating train split: 5636727 examples [13:31, 909.60 examples/s]
Generating train split: 5636968 examples [13:31, 1073.70 examples/s]
Generating train split: 5637213 examples [13:31, 1246.84 examples/s]
Generating train split: 5637595 examples [13:32, 1667.69 examples/s]
Generating train split: 5637893 examples [13:32, 1904.94 examples/s]
Generating train split: 5638188 examples [13:32, 2073.80 examples/s]
Generating train split: 5638474 examples [13:32, 2206.55 examples/s]
Generating train split: 5638758 examples [13:32, 1501.64 examples/s]
Generating train split: 5644129 examples [13:32, 10927.33 examples/s]
Generating train split: 5648018 examples [13:32, 16628.44 examples/s]
Generating train split: 5654713 examples [13:32, 27998.76 examples/s]
Generating train split: 5659948 examples [13:33, 33786.66 examples/s]
Generating train split: 5664071 examples [13:34, 8152.93 examples/s] 
Generating train split: 5667081 examples [13:35, 5054.29 examples/s]
Generating train split: 5669237 examples [13:36, 4329.27 examples/s]
Generating train split: 5670825 examples [13:37, 3823.16 examples/s]
Generating train split: 5672026 examples [13:37, 3622.09 examples/s]
Generating train split: 5672942 examples [13:37, 3495.74 examples/s]
Generating train split: 5673686 examples [13:38, 3493.43 examples/s]
Generating train split: 5674300 examples [13:38, 3277.56 examples/s]
Generating train split: 5674813 examples [13:38, 3279.83 examples/s]
Generating train split: 5675286 examples [13:38, 3296.35 examples/s]
Generating train split: 5675746 examples [13:38, 3459.55 examples/s]
Generating train split: 5676204 examples [13:39, 3323.02 examples/s]
Generating train split: 5676601 examples [13:39, 2958.33 examples/s]
Generating train split: 5676980 examples [13:39, 2817.98 examples/s]
Generating train split: 5677285 examples [13:39, 2796.45 examples/s]
Generating train split: 5677607 examples [13:39, 2868.21 examples/s]
Generating train split: 5677956 examples [13:39, 2976.81 examples/s]
Generating train split: 5678292 examples [13:39, 2360.09 examples/s]
Generating train split: 5678622 examples [13:40, 2556.07 examples/s]
Generating train split: 5678949 examples [13:40, 2712.03 examples/s]
Generating train split: 5679255 examples [13:40, 2705.26 examples/s]
Generating train split: 5679544 examples [13:40, 2596.93 examples/s]
Generating train split: 5679839 examples [13:40, 2537.14 examples/s]
Generating train split: 5680125 examples [13:40, 2428.15 examples/s]
Generating train split: 5680395 examples [13:40, 2369.13 examples/s]
Generating train split: 5680644 examples [13:40, 2004.58 examples/s]
Generating train split: 5680860 examples [13:41, 1701.60 examples/s]
Generating train split: 5681069 examples [13:41, 1662.40 examples/s]
Generating train split: 5681320 examples [13:41, 1836.22 examples/s]
Generating train split: 5681739 examples [13:41, 2334.68 examples/s]
Generating train split: 5682050 examples [13:41, 2503.84 examples/s]
Generating train split: 5682325 examples [13:41, 2564.96 examples/s]
Generating train split: 5682597 examples [13:41, 2523.25 examples/s]
Generating train split: 5682877 examples [13:41, 2482.42 examples/s]
Generating train split: 5683186 examples [13:41, 2576.83 examples/s]
Generating train split: 5683459 examples [13:42, 2601.94 examples/s]
Generating train split: 5683749 examples [13:42, 2594.31 examples/s]
Generating train split: 5684073 examples [13:42, 2696.37 examples/s]
Generating train split: 5684366 examples [13:42, 2705.58 examples/s]
Generating train split: 5684881 examples [13:42, 3324.89 examples/s]
Generating train split: 5685249 examples [13:42, 2898.34 examples/s]
Generating train split: 5685570 examples [13:42, 2801.46 examples/s]
Generating train split: 5685906 examples [13:42, 2942.43 examples/s]
Generating train split: 5686276 examples [13:43, 3071.88 examples/s]
Generating train split: 5686599 examples [13:43, 3051.03 examples/s]
Generating train split: 5686914 examples [13:43, 2826.65 examples/s]
Generating train split: 5687213 examples [13:43, 2544.07 examples/s]
Generating train split: 5687524 examples [13:43, 2664.13 examples/s]
Generating train split: 5687895 examples [13:43, 2884.29 examples/s]
Generating train split: 5688218 examples [13:43, 2621.62 examples/s]
Generating train split: 5688527 examples [13:46, 412.93 examples/s] 
Generating train split: 5688797 examples [13:46, 529.05 examples/s]
Generating train split: 5689150 examples [13:46, 731.72 examples/s]
Generating train split: 5689449 examples [13:46, 928.12 examples/s]
Generating train split: 5689713 examples [13:46, 1091.37 examples/s]
Generating train split: 5689959 examples [13:46, 1274.38 examples/s]
Generating train split: 5690204 examples [13:46, 1451.69 examples/s]
Generating train split: 5690506 examples [13:46, 1723.65 examples/s]
Generating train split: 5690845 examples [13:46, 2043.49 examples/s]
Generating train split: 5691138 examples [13:47, 2113.24 examples/s]
Generating train split: 5691409 examples [13:47, 2135.94 examples/s]
Generating train split: 5691679 examples [13:47, 2178.02 examples/s]
Generating train split: 5691922 examples [13:47, 2193.09 examples/s]
Generating train split: 5692198 examples [13:47, 2248.73 examples/s]
Generating train split: 5692447 examples [13:47, 1615.67 examples/s]
Generating train split: 5694675 examples [13:47, 5868.60 examples/s]
Generating train split: 5700676 examples [13:48, 18174.35 examples/s]
Generating train split: 5707839 examples [13:48, 31248.76 examples/s]
Generating train split: 5711627 examples [13:48, 30465.66 examples/s]
Generating train split: 5715179 examples [13:49, 9528.99 examples/s] 
Generating train split: 5717746 examples [13:50, 6576.14 examples/s]
Generating train split: 5719649 examples [13:50, 4997.74 examples/s]
Generating train split: 5721065 examples [13:51, 4384.97 examples/s]
Generating train split: 5722133 examples [13:51, 4273.16 examples/s]
Generating train split: 5722996 examples [13:51, 3826.77 examples/s]
Generating train split: 5723693 examples [13:52, 3537.46 examples/s]
Generating train split: 5724248 examples [13:52, 3692.94 examples/s]
Generating train split: 5724789 examples [13:52, 3409.78 examples/s]
Generating train split: 5725239 examples [13:52, 3402.71 examples/s]
Generating train split: 5725665 examples [13:52, 3354.19 examples/s]
Generating train split: 5726066 examples [13:53, 3195.24 examples/s]
Generating train split: 5726443 examples [13:53, 3102.63 examples/s]
Generating train split: 5726818 examples [13:53, 3210.67 examples/s]
Generating train split: 5727164 examples [13:53, 3072.65 examples/s]
Generating train split: 5727514 examples [13:53, 3162.96 examples/s]
Generating train split: 5727851 examples [13:53, 2992.35 examples/s]
Generating train split: 5728168 examples [13:53, 2814.15 examples/s]
Generating train split: 5728549 examples [13:53, 2977.82 examples/s]
Generating train split: 5728871 examples [13:53, 2944.88 examples/s]
Generating train split: 5729190 examples [13:54, 2781.48 examples/s]
Generating train split: 5729511 examples [13:54, 2742.14 examples/s]
Generating train split: 5729818 examples [13:54, 2640.37 examples/s]
Generating train split: 5730102 examples [13:54, 2479.24 examples/s]
Generating train split: 5730462 examples [13:54, 2671.31 examples/s]
Generating train split: 5730916 examples [13:54, 3089.44 examples/s]
Generating train split: 5731236 examples [13:54, 2491.58 examples/s]
Generating train split: 5731577 examples [13:55, 2613.34 examples/s]
Generating train split: 5731868 examples [13:55, 2637.61 examples/s]
Generating train split: 5732251 examples [13:55, 2897.53 examples/s]
Generating train split: 5732684 examples [13:55, 3191.38 examples/s]
Generating train split: 5733021 examples [13:55, 2847.60 examples/s]
Generating train split: 5733333 examples [13:55, 2772.58 examples/s]
Generating train split: 5733650 examples [13:55, 2480.69 examples/s]
Generating train split: 5733911 examples [13:55, 2457.16 examples/s]
Generating train split: 5734170 examples [13:55, 2421.37 examples/s]
Generating train split: 5734433 examples [13:56, 2385.43 examples/s]
Generating train split: 5734777 examples [13:56, 2626.39 examples/s]
Generating train split: 5735049 examples [13:56, 2644.82 examples/s]
Generating train split: 5735321 examples [13:56, 2495.82 examples/s]
Generating train split: 5735599 examples [13:56, 2362.87 examples/s]
Generating train split: 5735876 examples [13:56, 2399.88 examples/s]
Generating train split: 5736121 examples [13:56, 2368.35 examples/s]
Generating train split: 5736385 examples [13:56, 2394.83 examples/s]
Generating train split: 5736649 examples [13:57, 2350.71 examples/s]
Generating train split: 5736895 examples [13:57, 2342.08 examples/s]
Generating train split: 5737138 examples [13:57, 2297.18 examples/s]
Generating train split: 5737480 examples [13:57, 2576.01 examples/s]
Generating train split: 5737823 examples [13:57, 2784.79 examples/s]
Generating train split: 5738116 examples [13:57, 2775.72 examples/s]
Generating train split: 5738407 examples [13:57, 2493.68 examples/s]
Generating train split: 5738665 examples [13:59, 457.12 examples/s] 
Generating train split: 5738906 examples [13:59, 578.14 examples/s]
Generating train split: 5739200 examples [13:59, 775.36 examples/s]
Generating train split: 5739441 examples [13:59, 929.51 examples/s]
Generating train split: 5739660 examples [13:59, 1089.83 examples/s]
Generating train split: 5739903 examples [14:00, 1282.14 examples/s]
Generating train split: 5740187 examples [14:00, 1546.37 examples/s]
Generating train split: 5740462 examples [14:00, 1776.88 examples/s]
Generating train split: 5740830 examples [14:00, 2181.13 examples/s]
Generating train split: 5741168 examples [14:00, 2394.26 examples/s]
Generating train split: 5741475 examples [14:00, 2228.69 examples/s]
Generating train split: 5741757 examples [14:00, 2179.85 examples/s]
Generating train split: 5742010 examples [14:00, 2255.92 examples/s]
Generating train split: 5742281 examples [14:00, 2194.30 examples/s]
Generating train split: 5765039 examples [14:01, 58621.19 examples/s]
Generating train split: 5780754 examples [14:01, 84315.63 examples/s]
Generating train split: 5790319 examples [14:04, 8092.77 examples/s] 
Generating train split: 5797107 examples [14:07, 5229.49 examples/s]
Generating train split: 5801940 examples [14:09, 4496.76 examples/s]
Generating train split: 5805398 examples [14:11, 3431.14 examples/s]
Generating train split: 5807865 examples [14:12, 3294.07 examples/s]
Generating train split: 5809687 examples [14:13, 3266.43 examples/s]
Generating train split: 5811050 examples [14:13, 3352.67 examples/s]
Generating train split: 5818055 examples [14:13, 6110.32 examples/s]
Generating train split: 5822018 examples [14:13, 7957.96 examples/s]
Generating train split: 5825889 examples [14:13, 10169.85 examples/s]
Generating train split: 5829185 examples [14:14, 8013.85 examples/s] 
Generating train split: 5831628 examples [14:15, 5593.84 examples/s]
Generating train split: 5833451 examples [14:16, 4424.50 examples/s]
Generating train split: 5834800 examples [14:16, 4077.29 examples/s]
Generating train split: 5835843 examples [14:17, 3775.75 examples/s]
Generating train split: 5836646 examples [14:17, 3418.70 examples/s]
Generating train split: 5837268 examples [14:17, 3203.87 examples/s]
Generating train split: 5837791 examples [14:17, 3120.39 examples/s]
Generating train split: 5838249 examples [14:18, 3024.59 examples/s]
Generating train split: 5838639 examples [14:18, 2689.89 examples/s]
Generating train split: 5838967 examples [14:18, 2731.10 examples/s]
Generating train split: 5839445 examples [14:18, 3026.29 examples/s]
Generating train split: 5839801 examples [14:18, 2973.92 examples/s]
Generating train split: 5840158 examples [14:18, 2658.52 examples/s]
Generating train split: 5840468 examples [14:18, 2597.62 examples/s]
Generating train split: 5840745 examples [14:19, 2591.41 examples/s]
Generating train split: 5841041 examples [14:19, 2561.57 examples/s]
Generating train split: 5841334 examples [14:19, 2255.85 examples/s]
Generating train split: 5841576 examples [14:19, 1727.45 examples/s]
Generating train split: 5841843 examples [14:19, 1881.43 examples/s]
Generating train split: 5842062 examples [14:19, 1779.41 examples/s]
Generating train split: 5842297 examples [14:19, 1864.14 examples/s]
Generating train split: 5842588 examples [14:20, 2046.18 examples/s]
Generating train split: 5842835 examples [14:20, 2070.99 examples/s]
Generating train split: 5843069 examples [14:20, 1773.25 examples/s]
Generating train split: 5843276 examples [14:20, 1650.70 examples/s]
Generating train split: 5843461 examples [14:20, 1637.77 examples/s]
Generating train split: 5843658 examples [14:20, 1685.39 examples/s]
Generating train split: 5844058 examples [14:20, 2243.47 examples/s]
Generating train split: 5844297 examples [14:20, 2257.40 examples/s]
Generating train split: 5844544 examples [14:21, 2166.28 examples/s]
Generating train split: 5844781 examples [14:21, 2105.00 examples/s]
Generating train split: 5845039 examples [14:21, 2151.04 examples/s]
Generating train split: 5845261 examples [14:21, 2081.94 examples/s]
Generating train split: 5845509 examples [14:21, 1919.41 examples/s]
Generating train split: 5845716 examples [14:21, 1893.82 examples/s]
Generating train split: 5845996 examples [14:21, 2093.95 examples/s]
Generating train split: 5846338 examples [14:21, 2440.62 examples/s]
Generating train split: 5846611 examples [14:23, 476.20 examples/s] 
Generating train split: 5846969 examples [14:23, 689.66 examples/s]
Generating train split: 5847292 examples [14:23, 914.33 examples/s]
Generating train split: 5847572 examples [14:23, 1123.45 examples/s]
Generating train split: 5847921 examples [14:23, 1441.28 examples/s]
Generating train split: 5848241 examples [14:24, 1664.61 examples/s]
Generating train split: 5848528 examples [14:24, 1878.51 examples/s]
Generating train split: 5848934 examples [14:24, 2310.70 examples/s]
Generating train split: 5849255 examples [14:24, 2305.97 examples/s]
Generating train split: 5849651 examples [14:24, 2673.46 examples/s]
Generating train split: 5849982 examples [14:24, 2505.20 examples/s]
Generating train split: 5850326 examples [14:24, 2683.14 examples/s]
Generating train split: 5850644 examples [14:24, 2624.63 examples/s]
Generating train split: 5850948 examples [14:25, 2723.62 examples/s]
Generating train split: 5851429 examples [14:25, 3239.42 examples/s]
Generating train split: 5851790 examples [14:25, 3219.21 examples/s]
Generating train split: 5852203 examples [14:25, 3394.01 examples/s]
Generating train split: 5852563 examples [14:25, 3134.37 examples/s]
Generating train split: 5852896 examples [14:25, 2971.72 examples/s]
Generating train split: 5853302 examples [14:25, 3213.00 examples/s]
Generating train split: 5853684 examples [14:25, 3263.49 examples/s]
Generating train split: 5854030 examples [14:26, 2597.49 examples/s]
Generating train split: 5858453 examples [14:26, 12240.55 examples/s]
Generating train split: 5863815 examples [14:26, 22522.32 examples/s]
Generating train split: 5869876 examples [14:26, 32444.69 examples/s]
Generating train split: 5873580 examples [14:26, 31751.83 examples/s]
Generating train split: 5877083 examples [14:26, 32263.40 examples/s]
Generating train split: 5880527 examples [14:27, 11452.42 examples/s]
Generating train split: 5883096 examples [14:28, 5818.54 examples/s] 
Generating train split: 5884964 examples [14:29, 4346.21 examples/s]
Generating train split: 5886355 examples [14:29, 4142.42 examples/s]
Generating train split: 5887441 examples [14:30, 3777.87 examples/s]
Generating train split: 5888282 examples [14:30, 3468.79 examples/s]
Generating train split: 5888937 examples [14:30, 3409.63 examples/s]
Generating train split: 5889480 examples [14:31, 3043.99 examples/s]
Generating train split: 5889935 examples [14:31, 3052.94 examples/s]
Generating train split: 5890373 examples [14:31, 3217.75 examples/s]
Generating train split: 5890800 examples [14:31, 3258.58 examples/s]
Generating train split: 5891215 examples [14:31, 3226.63 examples/s]
Generating train split: 5891610 examples [14:31, 3161.33 examples/s]
Generating train split: 5892424 examples [14:31, 4154.11 examples/s]
Generating train split: 5892910 examples [14:32, 2643.54 examples/s]
Generating train split: 5893302 examples [14:32, 2426.94 examples/s]
Generating train split: 5893644 examples [14:32, 2389.90 examples/s]
Generating train split: 5893948 examples [14:32, 2477.70 examples/s]
Generating train split: 5894287 examples [14:32, 2628.34 examples/s]
Generating train split: 5894610 examples [14:32, 2680.48 examples/s]
Generating train split: 5894957 examples [14:32, 2838.73 examples/s]
Generating train split: 5895293 examples [14:33, 2717.65 examples/s]
Generating train split: 5895582 examples [14:33, 2222.56 examples/s]
Generating train split: 5895838 examples [14:33, 2029.82 examples/s]
Generating train split: 5896071 examples [14:33, 1935.99 examples/s]
Generating train split: 5896291 examples [14:34, 529.48 examples/s] 
Generating train split: 5896664 examples [14:35, 776.87 examples/s]
Generating train split: 5897136 examples [14:35, 1153.04 examples/s]
Generating train split: 5897425 examples [14:35, 1352.68 examples/s]
Generating train split: 5897718 examples [14:35, 1557.68 examples/s]
Generating train split: 5897997 examples [14:35, 1634.41 examples/s]
Generating train split: 5898403 examples [14:35, 2078.29 examples/s]
Generating train split: 5898704 examples [14:35, 2169.59 examples/s]
Generating train split: 5899026 examples [14:35, 2342.01 examples/s]
Generating train split: 5899320 examples [14:35, 2400.52 examples/s]
Generating train split: 5899652 examples [14:36, 2594.15 examples/s]
Generating train split: 5899954 examples [14:36, 2590.47 examples/s]
Generating train split: 5900291 examples [14:36, 2721.05 examples/s]
Generating train split: 5900689 examples [14:36, 3055.11 examples/s]
Generating train split: 5901022 examples [14:36, 2767.01 examples/s]
Generating train split: 5901364 examples [14:36, 2852.15 examples/s]
Generating train split: 5901718 examples [14:36, 2944.31 examples/s]
Generating train split: 5902039 examples [14:36, 2576.32 examples/s]
Generating train split: 5902370 examples [14:37, 2718.07 examples/s]
Generating train split: 5902667 examples [14:37, 2712.04 examples/s]
Generating train split: 5903145 examples [14:37, 3176.84 examples/s]
Generating train split: 5903588 examples [14:37, 3468.00 examples/s]
Generating train split: 5903945 examples [14:37, 3186.09 examples/s]
Generating train split: 5904278 examples [14:37, 2453.54 examples/s]
Generating train split: 5912002 examples [14:37, 19100.32 examples/s]
Generating train split: 5916400 examples [14:37, 25062.26 examples/s]
Generating train split: 5922338 examples [14:38, 33829.16 examples/s]
Generating train split: 5930075 examples [14:38, 45445.51 examples/s]
Generating train split: 5935135 examples [14:39, 8222.88 examples/s] 
Generating train split: 5938768 examples [14:41, 5563.70 examples/s]
Generating train split: 5941425 examples [14:42, 4193.74 examples/s]
Generating train split: 5943356 examples [14:43, 4149.89 examples/s]
Generating train split: 5944821 examples [14:43, 3927.35 examples/s]
Generating train split: 5945961 examples [14:45, 2343.81 examples/s]
Generating train split: 5946768 examples [14:45, 2401.57 examples/s]
Generating train split: 5947419 examples [14:45, 2508.00 examples/s]
Generating train split: 5947982 examples [14:45, 2526.27 examples/s]
Generating train split: 5948464 examples [14:46, 2497.19 examples/s]
Generating train split: 5948871 examples [14:46, 2535.93 examples/s]
Generating train split: 5949260 examples [14:46, 2649.64 examples/s]
Generating train split: 5949660 examples [14:46, 2720.03 examples/s]
Generating train split: 5950011 examples [14:46, 2741.40 examples/s]
Generating train split: 5950344 examples [14:46, 2773.50 examples/s]
Generating train split: 5950836 examples [14:46, 3178.25 examples/s]
Generating train split: 5951214 examples [14:46, 3234.66 examples/s]
Generating train split: 5951605 examples [14:47, 2843.92 examples/s]
Generating train split: 5951923 examples [14:47, 2641.79 examples/s]
Generating train split: 5952217 examples [14:47, 2568.49 examples/s]
Generating train split: 5952498 examples [14:47, 2525.10 examples/s]
Generating train split: 5952772 examples [14:47, 2470.94 examples/s]
Generating train split: 5953036 examples [14:47, 2510.49 examples/s]
Generating train split: 5953319 examples [14:47, 2465.15 examples/s]
Generating train split: 5953620 examples [14:47, 2518.33 examples/s]
Generating train split: 5953946 examples [14:47, 2672.40 examples/s]
Generating train split: 5954273 examples [14:48, 2804.13 examples/s]
Generating train split: 5954605 examples [14:48, 2820.91 examples/s]
Generating train split: 5954958 examples [14:48, 2937.24 examples/s]
Generating train split: 5955259 examples [14:48, 2888.82 examples/s]
Generating train split: 5955558 examples [14:48, 2768.45 examples/s]
Generating train split: 5955844 examples [14:48, 2591.31 examples/s]
Generating train split: 5956107 examples [14:48, 1918.23 examples/s]
Generating train split: 5963210 examples [14:49, 17049.51 examples/s]
Generating train split: 5969148 examples [14:49, 27063.31 examples/s]
Generating train split: 5973711 examples [14:49, 31658.53 examples/s]
Generating train split: 5982463 examples [14:49, 46433.26 examples/s]
Generating train split: 5987691 examples [14:51, 8233.51 examples/s] 
Generating train split: 5991421 examples [14:52, 5679.36 examples/s]
Generating train split: 5994128 examples [14:53, 4835.19 examples/s]
Generating train split: 5996120 examples [14:54, 4213.01 examples/s]
Generating train split: 5997593 examples [14:54, 3928.74 examples/s]
Generating train split: 5998714 examples [14:56, 2476.04 examples/s]
Generating train split: 5999519 examples [14:56, 2524.68 examples/s]
Generating train split: 6000189 examples [14:56, 2606.22 examples/s]
Generating train split: 6000759 examples [14:56, 2686.22 examples/s]
Generating train split: 6001273 examples [14:56, 2762.29 examples/s]
Generating train split: 6001730 examples [14:57, 2722.22 examples/s]
Generating train split: 6002117 examples [14:57, 2604.35 examples/s]
Generating train split: 6002459 examples [14:57, 2607.60 examples/s]
Generating train split: 6002778 examples [14:57, 2463.62 examples/s]
Generating train split: 6003057 examples [14:57, 2509.89 examples/s]
Generating train split: 6003365 examples [14:57, 2606.41 examples/s]
Generating train split: 6003652 examples [14:57, 2659.25 examples/s]
Generating train split: 6004010 examples [14:58, 2803.89 examples/s]
Generating train split: 6004322 examples [14:58, 2794.84 examples/s]
Generating train split: 6004753 examples [14:58, 3119.86 examples/s]
Generating train split: 6005105 examples [14:58, 2644.43 examples/s]
Generating train split: 6005400 examples [14:58, 2652.40 examples/s]
Generating train split: 6005708 examples [14:58, 2725.62 examples/s]
Generating train split: 6006116 examples [14:58, 3039.77 examples/s]
Generating train split: 6006438 examples [14:58, 2612.65 examples/s]
Generating train split: 6006761 examples [14:59, 2732.46 examples/s]
Generating train split: 6007074 examples [14:59, 2768.41 examples/s]
Generating train split: 6007544 examples [14:59, 3236.56 examples/s]
Generating train split: 6007973 examples [14:59, 3430.26 examples/s]
Generating train split: 6008337 examples [14:59, 3444.92 examples/s]
Generating train split: 6008749 examples [14:59, 3590.42 examples/s]
Generating train split: 6009220 examples [14:59, 3186.14 examples/s]
Generating train split: 6028257 examples [14:59, 49519.31 examples/s]
Generating train split: 6044686 examples [14:59, 79262.03 examples/s]
Generating train split: 6053721 examples [15:03, 8914.21 examples/s] 
Generating train split: 6060155 examples [15:07, 4324.69 examples/s]
Generating train split: 6064694 examples [15:08, 3961.66 examples/s]
Generating train split: 6067994 examples [15:09, 3729.78 examples/s]
Generating train split: 6070371 examples [15:10, 3626.61 examples/s]
Generating train split: 6087267 examples [15:10, 8687.99 examples/s]
Generating train split: 6093549 examples [15:10, 10607.84 examples/s]
Generating train split: 6099043 examples [15:10, 12662.02 examples/s]
Generating train split: 6103939 examples [15:12, 6676.16 examples/s] 
Generating train split: 6107459 examples [15:14, 5479.89 examples/s]
Generating train split: 6110008 examples [15:14, 4760.19 examples/s]
Generating train split: 6111900 examples [15:16, 3355.13 examples/s]
Generating train split: 6113269 examples [15:17, 3217.81 examples/s]
Generating train split: 6114285 examples [15:17, 3170.94 examples/s]
Generating train split: 6115083 examples [15:17, 2990.00 examples/s]
Generating train split: 6115718 examples [15:17, 2965.98 examples/s]
Generating train split: 6116257 examples [15:18, 2886.33 examples/s]
Generating train split: 6116698 examples [15:18, 2938.58 examples/s]
Generating train split: 6117126 examples [15:18, 2995.50 examples/s]
Generating train split: 6117562 examples [15:18, 3137.92 examples/s]
Generating train split: 6117972 examples [15:18, 2972.95 examples/s]
Generating train split: 6118332 examples [15:18, 2988.46 examples/s]
Generating train split: 6118702 examples [15:18, 3100.37 examples/s]
Generating train split: 6119124 examples [15:19, 3332.49 examples/s]
Generating train split: 6119516 examples [15:19, 2897.29 examples/s]
Generating train split: 6119853 examples [15:19, 2933.25 examples/s]
Generating train split: 6120190 examples [15:19, 2707.90 examples/s]
Generating train split: 6120481 examples [15:19, 2552.07 examples/s]
Generating train split: 6120770 examples [15:19, 2621.86 examples/s]
Generating train split: 6121058 examples [15:19, 2681.06 examples/s]
Generating train split: 6121361 examples [15:19, 2488.91 examples/s]
Generating train split: 6121673 examples [15:20, 2601.82 examples/s]
Generating train split: 6122033 examples [15:20, 2770.40 examples/s]
Generating train split: 6122400 examples [15:20, 2943.17 examples/s]
Generating train split: 6122712 examples [15:20, 2918.80 examples/s]
Generating train split: 6123122 examples [15:20, 3170.31 examples/s]
Generating train split: 6123448 examples [15:20, 3009.40 examples/s]
Generating train split: 6123798 examples [15:20, 2950.42 examples/s]
Generating train split: 6124108 examples [15:20, 2913.47 examples/s]
Generating train split: 6124402 examples [15:21, 2611.90 examples/s]
Generating train split: 6124714 examples [15:21, 2718.09 examples/s]
Generating train split: 6125041 examples [15:21, 2791.73 examples/s]
Generating train split: 6125353 examples [15:21, 2318.17 examples/s]
Generating train split: 6131330 examples [15:21, 15850.62 examples/s]
Generating train split: 6134786 examples [15:21, 20553.95 examples/s]
Generating train split: 6138123 examples [15:21, 23938.84 examples/s]
Generating train split: 6145847 examples [15:21, 38551.82 examples/s]
Generating train split: 6150055 examples [15:23, 7477.76 examples/s] 
Generating train split: 6153067 examples [15:24, 4935.52 examples/s]
Generating train split: 6155258 examples [15:26, 3372.89 examples/s]
Generating train split: 6156853 examples [15:26, 3193.42 examples/s]
Generating train split: 6158026 examples [15:27, 3080.57 examples/s]
Generating train split: 6158937 examples [15:27, 3072.28 examples/s]
Generating train split: 6159658 examples [15:27, 3141.92 examples/s]
Generating train split: 6160278 examples [15:28, 3009.90 examples/s]
Generating train split: 6160781 examples [15:28, 2592.02 examples/s]
Generating train split: 6161207 examples [15:28, 2556.94 examples/s]
Generating train split: 6161561 examples [15:28, 2449.39 examples/s]
Generating train split: 6161884 examples [15:28, 2350.59 examples/s]
Generating train split: 6162158 examples [15:29, 2402.72 examples/s]
Generating train split: 6162451 examples [15:29, 2379.13 examples/s]
Generating train split: 6162735 examples [15:29, 2247.33 examples/s]
Generating train split: 6162994 examples [15:29, 2148.05 examples/s]
Generating train split: 6163229 examples [15:29, 2104.47 examples/s]
Generating train split: 6163521 examples [15:29, 2257.79 examples/s]
Generating train split: 6163773 examples [15:29, 2260.78 examples/s]
Generating train split: 6164143 examples [15:29, 2598.04 examples/s]
Generating train split: 6164493 examples [15:30, 2779.91 examples/s]
Generating train split: 6164816 examples [15:30, 2574.80 examples/s]
Generating train split: 6165108 examples [15:30, 2654.34 examples/s]
Generating train split: 6165392 examples [15:30, 2481.16 examples/s]
Generating train split: 6165656 examples [15:30, 2266.39 examples/s]
Generating train split: 6165916 examples [15:30, 2274.50 examples/s]
Generating train split: 6166151 examples [15:30, 2159.91 examples/s]
Generating train split: 6166413 examples [15:30, 2253.03 examples/s]
Generating train split: 6166652 examples [15:30, 2209.10 examples/s]
Generating train split: 6166929 examples [15:31, 2263.25 examples/s]
Generating train split: 6167192 examples [15:31, 2246.72 examples/s]
Generating train split: 6167507 examples [15:31, 2442.47 examples/s]
Generating train split: 6167818 examples [15:31, 2563.72 examples/s]
Generating train split: 6168121 examples [15:31, 2630.99 examples/s]
Generating train split: 6168424 examples [15:31, 2610.52 examples/s]
Generating train split: 6168719 examples [15:31, 2666.06 examples/s]
Generating train split: 6168987 examples [15:33, 552.11 examples/s] 
Generating train split: 6169180 examples [15:33, 649.82 examples/s]
Generating train split: 6169451 examples [15:33, 846.95 examples/s]
Generating train split: 6169665 examples [15:33, 973.65 examples/s]
Generating train split: 6169868 examples [15:33, 1114.99 examples/s]
Generating train split: 6170197 examples [15:33, 1442.75 examples/s]
Generating train split: 6170453 examples [15:33, 1623.91 examples/s]
Generating train split: 6170779 examples [15:34, 1961.36 examples/s]
Generating train split: 6171066 examples [15:34, 2111.54 examples/s]
Generating train split: 6171406 examples [15:34, 2390.99 examples/s]
Generating train split: 6171683 examples [15:34, 1779.61 examples/s]
Generating train split: 6178599 examples [15:34, 15687.24 examples/s]
Generating train split: 6183441 examples [15:34, 23050.23 examples/s]
Generating train split: 6186542 examples [15:34, 24947.94 examples/s]
Generating train split: 6191495 examples [15:34, 31292.25 examples/s]
Generating train split: 6195092 examples [15:36, 7842.76 examples/s] 
Generating train split: 6197724 examples [15:37, 5454.68 examples/s]
Generating train split: 6199644 examples [15:37, 4442.03 examples/s]
Generating train split: 6201074 examples [15:38, 4107.65 examples/s]
Generating train split: 6202172 examples [15:38, 3605.52 examples/s]
Generating train split: 6203024 examples [15:39, 3467.61 examples/s]
Generating train split: 6203697 examples [15:39, 3379.00 examples/s]
Generating train split: 6204260 examples [15:39, 3192.60 examples/s]
Generating train split: 6204735 examples [15:39, 2979.98 examples/s]
Generating train split: 6205129 examples [15:39, 3012.36 examples/s]
Generating train split: 6205512 examples [15:40, 3057.08 examples/s]
Generating train split: 6205888 examples [15:40, 2546.71 examples/s]
Generating train split: 6206227 examples [15:40, 2594.41 examples/s]
Generating train split: 6206533 examples [15:40, 2570.71 examples/s]
Generating train split: 6206814 examples [15:40, 2531.03 examples/s]
Generating train split: 6207093 examples [15:40, 2553.59 examples/s]
Generating train split: 6207400 examples [15:40, 2487.50 examples/s]
Generating train split: 6207682 examples [15:41, 2529.13 examples/s]
Generating train split: 6207953 examples [15:41, 2493.73 examples/s]
Generating train split: 6208229 examples [15:41, 2530.24 examples/s]
Generating train split: 6208569 examples [15:41, 2717.09 examples/s]
Generating train split: 6208943 examples [15:41, 2957.08 examples/s]
Generating train split: 6209260 examples [15:41, 2771.98 examples/s]
Generating train split: 6209557 examples [15:41, 2543.63 examples/s]
Generating train split: 6209852 examples [15:41, 2512.73 examples/s]
Generating train split: 6210117 examples [15:41, 2403.91 examples/s]
Generating train split: 6210371 examples [15:42, 2262.65 examples/s]
Generating train split: 6210794 examples [15:42, 2759.82 examples/s]
Generating train split: 6211088 examples [15:42, 2530.87 examples/s]
Generating train split: 6211364 examples [15:42, 2551.52 examples/s]
Generating train split: 6211635 examples [15:42, 2413.52 examples/s]
Generating train split: 6211983 examples [15:42, 2663.06 examples/s]
Generating train split: 6212376 examples [15:42, 2942.97 examples/s]
Generating train split: 6212717 examples [15:42, 2788.90 examples/s]
Generating train split: 6213037 examples [15:43, 2757.28 examples/s]
Generating train split: 6213324 examples [15:43, 2676.62 examples/s]
Generating train split: 6213631 examples [15:43, 2739.33 examples/s]
Generating train split: 6213926 examples [15:43, 2375.92 examples/s]
Generating train split: 6214193 examples [15:43, 2325.55 examples/s]
Generating train split: 6214454 examples [15:43, 2261.79 examples/s]
Generating train split: 6214688 examples [15:43, 2152.85 examples/s]
Generating train split: 6214927 examples [15:45, 574.62 examples/s] 
Generating train split: 6215159 examples [15:45, 721.77 examples/s]
Generating train split: 6215472 examples [15:45, 980.92 examples/s]
Generating train split: 6215723 examples [15:45, 1177.05 examples/s]
Generating train split: 6215983 examples [15:45, 1395.54 examples/s]
Generating train split: 6216334 examples [15:45, 1771.15 examples/s]
Generating train split: 6216596 examples [15:45, 1896.45 examples/s]
Generating train split: 6216870 examples [15:45, 1997.14 examples/s]
Generating train split: 6217172 examples [15:45, 2174.40 examples/s]
Generating train split: 6217430 examples [15:46, 2124.10 examples/s]
Generating train split: 6217703 examples [15:46, 2267.34 examples/s]
Generating train split: 6217951 examples [15:46, 2226.91 examples/s]
Generating train split: 6238031 examples [15:46, 54246.82 examples/s]
Generating train split: 6244155 examples [15:46, 43041.63 examples/s]
Generating train split: 6249313 examples [15:53, 2783.61 examples/s] 
Generating train split: 6252947 examples [15:57, 1812.53 examples/s]
Generating train split: 6255513 examples [15:58, 2087.95 examples/s]
Generating train split: 6264153 examples [15:58, 3763.70 examples/s]
Generating train split: 6269626 examples [15:58, 5167.76 examples/s]
Generating train split: 6274043 examples [16:01, 3260.35 examples/s]
Generating train split: 6277196 examples [16:02, 2879.92 examples/s]
Generating train split: 6279459 examples [16:03, 2746.28 examples/s]
Generating train split: 6281116 examples [16:04, 2597.52 examples/s]
Generating train split: 6282352 examples [16:05, 2536.71 examples/s]
Generating train split: 6283291 examples [16:05, 2588.70 examples/s]
Generating train split: 6284023 examples [16:05, 2558.64 examples/s]
Generating train split: 6284612 examples [16:07, 1572.73 examples/s]
Generating train split: 6285043 examples [16:07, 1649.76 examples/s]
Generating train split: 6285424 examples [16:07, 1757.53 examples/s]
Generating train split: 6285780 examples [16:07, 1872.30 examples/s]
Generating train split: 6286129 examples [16:07, 1993.53 examples/s]
Generating train split: 6286463 examples [16:07, 2112.73 examples/s]
Generating train split: 6286803 examples [16:08, 2203.12 examples/s]
Generating train split: 6287120 examples [16:08, 2202.49 examples/s]
Generating train split: 6287402 examples [16:08, 2189.94 examples/s]
Generating train split: 6287672 examples [16:08, 2007.05 examples/s]
Generating train split: 6287937 examples [16:08, 2098.62 examples/s]
Generating train split: 6288174 examples [16:08, 2147.35 examples/s]
Generating train split: 6288462 examples [16:08, 2294.47 examples/s]
Generating train split: 6288871 examples [16:08, 2678.39 examples/s]
Generating train split: 6289161 examples [16:09, 2421.14 examples/s]
Generating train split: 6289423 examples [16:09, 1691.59 examples/s]
Generating train split: 6295234 examples [16:09, 12647.55 examples/s]
Generating train split: 6298111 examples [16:09, 16003.51 examples/s]
Generating train split: 6301966 examples [16:09, 21259.69 examples/s]
Generating train split: 6305828 examples [16:09, 25549.81 examples/s]
Generating train split: 6308849 examples [16:10, 6664.67 examples/s] 
Generating train split: 6311025 examples [16:11, 4752.10 examples/s]
Generating train split: 6312629 examples [16:12, 4182.54 examples/s]
Generating train split: 6313851 examples [16:12, 3712.20 examples/s]
Generating train split: 6314786 examples [16:13, 3541.16 examples/s]
Generating train split: 6315516 examples [16:13, 3134.23 examples/s]
Generating train split: 6316092 examples [16:13, 3138.80 examples/s]
Generating train split: 6316606 examples [16:14, 2921.03 examples/s]
Generating train split: 6317027 examples [16:14, 2826.20 examples/s]
Generating train split: 6317403 examples [16:14, 2679.42 examples/s]
Generating train split: 6317738 examples [16:14, 2608.87 examples/s]
Generating train split: 6318032 examples [16:14, 2532.51 examples/s]
Generating train split: 6318308 examples [16:14, 2551.52 examples/s]
Generating train split: 6318674 examples [16:14, 2752.52 examples/s]
Generating train split: 6319005 examples [16:15, 2707.36 examples/s]
Generating train split: 6319313 examples [16:15, 2634.14 examples/s]
Generating train split: 6319588 examples [16:15, 2435.51 examples/s]
Generating train split: 6319838 examples [16:15, 2449.86 examples/s]
Generating train split: 6320137 examples [16:15, 2535.58 examples/s]
Generating train split: 6320473 examples [16:15, 2720.52 examples/s]
Generating train split: 6320757 examples [16:15, 2432.71 examples/s]
Generating train split: 6321018 examples [16:15, 2369.37 examples/s]
Generating train split: 6321339 examples [16:15, 2521.98 examples/s]
Generating train split: 6321673 examples [16:16, 2674.30 examples/s]
Generating train split: 6322056 examples [16:16, 2953.45 examples/s]
Generating train split: 6322357 examples [16:16, 2528.95 examples/s]
Generating train split: 6322705 examples [16:16, 2712.05 examples/s]
Generating train split: 6323223 examples [16:16, 3343.21 examples/s]
Generating train split: 6323602 examples [16:16, 3097.03 examples/s]
Generating train split: 6323932 examples [16:16, 3077.02 examples/s]
Generating train split: 6324265 examples [16:18, 719.32 examples/s] 
Generating train split: 6324500 examples [16:18, 813.69 examples/s]
Generating train split: 6324744 examples [16:18, 963.42 examples/s]
Generating train split: 6324984 examples [16:18, 1125.84 examples/s]
Generating train split: 6325224 examples [16:18, 1305.34 examples/s]
Generating train split: 6325504 examples [16:18, 1537.37 examples/s]
Generating train split: 6325759 examples [16:18, 1711.81 examples/s]
Generating train split: 6326042 examples [16:19, 1910.83 examples/s]
Generating train split: 6326408 examples [16:19, 2263.59 examples/s]
Generating train split: 6326677 examples [16:19, 2270.64 examples/s]
Generating train split: 6326956 examples [16:19, 2326.21 examples/s]
Generating train split: 6327247 examples [16:19, 2448.87 examples/s]
Generating train split: 6327542 examples [16:19, 2328.61 examples/s]
Generating train split: 6327872 examples [16:19, 2484.31 examples/s]
Generating train split: 6328149 examples [16:19, 2421.55 examples/s]
Generating train split: 6328413 examples [16:19, 2226.79 examples/s]
Generating train split: 6328742 examples [16:20, 2445.11 examples/s]
Generating train split: 6328995 examples [16:20, 2223.17 examples/s]
Generating train split: 6329228 examples [16:20, 2213.58 examples/s]
Generating train split: 6329457 examples [16:20, 1905.91 examples/s]
Generating train split: 6334877 examples [16:20, 14506.30 examples/s]
Generating train split: 6339962 examples [16:20, 23796.06 examples/s]
Generating train split: 6349040 examples [16:20, 41694.78 examples/s]
Generating train split: 6357211 examples [16:20, 52729.76 examples/s]
Generating train split: 6362922 examples [16:22, 12219.19 examples/s]
Generating train split: 6367049 examples [16:23, 6311.02 examples/s] 
Generating train split: 6370009 examples [16:25, 4574.92 examples/s]
Generating train split: 6372157 examples [16:25, 4362.93 examples/s]
Generating train split: 6373776 examples [16:26, 3824.26 examples/s]
Generating train split: 6374973 examples [16:27, 3417.19 examples/s]
Generating train split: 6375871 examples [16:27, 3226.28 examples/s]
Generating train split: 6376592 examples [16:29, 1412.63 examples/s]
Generating train split: 6377100 examples [16:30, 1512.78 examples/s]
Generating train split: 6377554 examples [16:30, 1636.63 examples/s]
Generating train split: 6377994 examples [16:30, 1725.87 examples/s]
Generating train split: 6378386 examples [16:30, 1819.14 examples/s]
Generating train split: 6378743 examples [16:30, 1836.59 examples/s]
Generating train split: 6379055 examples [16:30, 1846.03 examples/s]
Generating train split: 6379318 examples [16:31, 1834.33 examples/s]
Generating train split: 6379562 examples [16:31, 1767.68 examples/s]
Generating train split: 6379799 examples [16:31, 1766.43 examples/s]
Generating train split: 6380027 examples [16:31, 1827.43 examples/s]
Generating train split: 6380294 examples [16:31, 1956.10 examples/s]
Generating train split: 6380555 examples [16:31, 2065.85 examples/s]
Generating train split: 6380787 examples [16:31, 2058.33 examples/s]
Generating train split: 6381056 examples [16:31, 2185.97 examples/s]
Generating train split: 6381376 examples [16:32, 2399.31 examples/s]
Generating train split: 6381648 examples [16:32, 2482.86 examples/s]
Generating train split: 6381913 examples [16:32, 2302.97 examples/s]
Generating train split: 6382202 examples [16:32, 2451.35 examples/s]
Generating train split: 6382482 examples [16:32, 2389.33 examples/s]
Generating train split: 6382806 examples [16:32, 2565.69 examples/s]
Generating train split: 6383099 examples [16:32, 2451.43 examples/s]
Generating train split: 6383366 examples [16:32, 2424.98 examples/s]
Generating train split: 6383636 examples [16:32, 2498.32 examples/s]
Generating train split: 6383959 examples [16:33, 2661.47 examples/s]
Generating train split: 6384245 examples [16:33, 1722.65 examples/s]
Generating train split: 6393553 examples [16:33, 20196.50 examples/s]
Generating train split: 6398163 examples [16:33, 25896.67 examples/s]
Generating train split: 6404030 examples [16:33, 33814.66 examples/s]
Generating train split: 6408211 examples [16:34, 9211.02 examples/s] 
Generating train split: 6411230 examples [16:36, 5351.12 examples/s]
Generating train split: 6413411 examples [16:37, 4402.96 examples/s]
Generating train split: 6415050 examples [16:37, 3796.41 examples/s]
Generating train split: 6416239 examples [16:38, 3553.29 examples/s]
Generating train split: 6417162 examples [16:38, 3476.47 examples/s]
Generating train split: 6417922 examples [16:38, 3277.49 examples/s]
Generating train split: 6418541 examples [16:39, 2950.32 examples/s]
Generating train split: 6419012 examples [16:39, 2623.89 examples/s]
Generating train split: 6419405 examples [16:39, 2603.94 examples/s]
Generating train split: 6419751 examples [16:39, 2492.22 examples/s]
Generating train split: 6420046 examples [16:39, 2351.34 examples/s]
Generating train split: 6420392 examples [16:40, 2491.73 examples/s]
Generating train split: 6420677 examples [16:40, 2525.81 examples/s]
Generating train split: 6421057 examples [16:40, 2724.84 examples/s]
Generating train split: 6421377 examples [16:41, 873.91 examples/s] 
Generating train split: 6421671 examples [16:41, 1050.00 examples/s]
Generating train split: 6422073 examples [16:41, 1375.12 examples/s]
Generating train split: 6422373 examples [16:41, 1586.09 examples/s]
Generating train split: 6422662 examples [16:41, 1704.53 examples/s]
Generating train split: 6422940 examples [16:42, 1817.58 examples/s]
Generating train split: 6423230 examples [16:42, 1874.49 examples/s]
Generating train split: 6423474 examples [16:42, 1904.51 examples/s]
Generating train split: 6423752 examples [16:42, 2093.82 examples/s]
Generating train split: 6424012 examples [16:42, 2150.03 examples/s]
Generating train split: 6424294 examples [16:42, 2264.47 examples/s]
Generating train split: 6424625 examples [16:42, 2450.42 examples/s]
Generating train split: 6424911 examples [16:42, 2545.89 examples/s]
Generating train split: 6425211 examples [16:42, 2648.21 examples/s]
Generating train split: 6425512 examples [16:43, 2709.17 examples/s]
Generating train split: 6425852 examples [16:43, 2803.01 examples/s]
Generating train split: 6426157 examples [16:43, 2532.61 examples/s]
Generating train split: 6426457 examples [16:43, 2513.49 examples/s]
Generating train split: 6426742 examples [16:43, 2524.81 examples/s]
Generating train split: 6427031 examples [16:43, 2227.72 examples/s]
Generating train split: 6427266 examples [16:43, 2081.96 examples/s]
Generating train split: 6427489 examples [16:43, 1906.16 examples/s]
Generating train split: 6427698 examples [16:44, 1918.81 examples/s]
Generating train split: 6427986 examples [16:44, 2122.13 examples/s]
Generating train split: 6428223 examples [16:44, 2184.93 examples/s]
Generating train split: 6428491 examples [16:44, 2258.80 examples/s]
Generating train split: 6428757 examples [16:44, 2277.98 examples/s]
Generating train split: 6429078 examples [16:44, 2521.30 examples/s]
Generating train split: 6429339 examples [16:44, 2403.00 examples/s]
Generating train split: 6429599 examples [16:44, 2361.86 examples/s]
Generating train split: 6429839 examples [16:44, 2345.13 examples/s]
Generating train split: 6430098 examples [16:45, 1424.44 examples/s]
Generating train split: 6433586 examples [16:45, 7785.86 examples/s]
Generating train split: 6437359 examples [16:45, 14172.81 examples/s]
Generating train split: 6440717 examples [16:45, 18665.11 examples/s]
Generating train split: 6447336 examples [16:45, 30472.36 examples/s]
Generating train split: 6454463 examples [16:45, 38068.34 examples/s]
Generating train split: 6458648 examples [16:47, 8475.84 examples/s] 
Generating train split: 6461669 examples [16:48, 5522.55 examples/s]
Generating train split: 6463855 examples [16:49, 4669.12 examples/s]
Generating train split: 6465489 examples [16:49, 4226.70 examples/s]
Generating train split: 6466706 examples [16:50, 4039.14 examples/s]
Generating train split: 6467675 examples [16:50, 3423.24 examples/s]
Generating train split: 6468413 examples [16:52, 1868.84 examples/s]
Generating train split: 6468931 examples [16:52, 1955.88 examples/s]
Generating train split: 6469407 examples [16:52, 2014.58 examples/s]
Generating train split: 6469819 examples [16:52, 2166.61 examples/s]
Generating train split: 6470217 examples [16:52, 2220.69 examples/s]
Generating train split: 6470581 examples [16:53, 2363.07 examples/s]
Generating train split: 6470948 examples [16:53, 2338.76 examples/s]
Generating train split: 6471283 examples [16:53, 2285.09 examples/s]
Generating train split: 6471593 examples [16:53, 2163.71 examples/s]
Generating train split: 6471867 examples [16:53, 2261.82 examples/s]
Generating train split: 6472134 examples [16:53, 2288.07 examples/s]
Generating train split: 6472403 examples [16:53, 2258.95 examples/s]
Generating train split: 6472725 examples [16:54, 2455.92 examples/s]
Generating train split: 6473053 examples [16:54, 2619.76 examples/s]
Generating train split: 6473339 examples [16:54, 2126.83 examples/s]
Generating train split: 6473577 examples [16:54, 2127.83 examples/s]
Generating train split: 6473831 examples [16:54, 2207.18 examples/s]
Generating train split: 6474082 examples [16:54, 2213.20 examples/s]
Generating train split: 6474421 examples [16:54, 2453.50 examples/s]
Generating train split: 6474707 examples [16:54, 2539.45 examples/s]
Generating train split: 6474990 examples [16:54, 2569.38 examples/s]
Generating train split: 6475264 examples [16:55, 2213.22 examples/s]
Generating train split: 6475528 examples [16:55, 2307.57 examples/s]
Generating train split: 6475778 examples [16:55, 2223.58 examples/s]
Generating train split: 6476069 examples [16:55, 2393.15 examples/s]
Generating train split: 6476366 examples [16:55, 2483.58 examples/s]
Generating train split: 6476735 examples [16:55, 2783.76 examples/s]
Generating train split: 6477026 examples [16:55, 2696.84 examples/s]
Generating train split: 6477315 examples [16:55, 2675.46 examples/s]
Generating train split: 6477637 examples [16:56, 2806.85 examples/s]
Generating train split: 6477950 examples [16:56, 2806.59 examples/s]
Generating train split: 6478253 examples [16:56, 1783.48 examples/s]
Generating train split: 6484162 examples [16:56, 13217.32 examples/s]
Generating train split: 6492114 examples [16:56, 27922.14 examples/s]
Generating train split: 6499887 examples [16:56, 39869.25 examples/s]
Generating train split: 6504827 examples [16:57, 19470.78 examples/s]
Generating train split: 6508552 examples [16:58, 6715.78 examples/s] 
Generating train split: 6511259 examples [16:59, 5137.23 examples/s]
Generating train split: 6513235 examples [17:00, 4330.36 examples/s]
Generating train split: 6514681 examples [17:01, 4061.02 examples/s]
Generating train split: 6515806 examples [17:02, 2923.05 examples/s]
Generating train split: 6516613 examples [17:02, 2793.73 examples/s]
Generating train split: 6517264 examples [17:02, 2882.27 examples/s]
Generating train split: 6517838 examples [17:02, 2971.85 examples/s]
Generating train split: 6518335 examples [17:03, 2999.56 examples/s]
Generating train split: 6518789 examples [17:03, 3027.94 examples/s]
Generating train split: 6519203 examples [17:03, 3019.76 examples/s]
Generating train split: 6519580 examples [17:03, 2894.40 examples/s]
Generating train split: 6519932 examples [17:03, 2818.97 examples/s]
Generating train split: 6520246 examples [17:03, 2838.98 examples/s]
Generating train split: 6520567 examples [17:03, 2789.97 examples/s]
Generating train split: 6520872 examples [17:04, 2653.03 examples/s]
Generating train split: 6521164 examples [17:04, 2464.93 examples/s]
Generating train split: 6521419 examples [17:04, 2375.41 examples/s]
Generating train split: 6521703 examples [17:04, 2462.39 examples/s]
Generating train split: 6521991 examples [17:04, 2470.70 examples/s]
Generating train split: 6522289 examples [17:04, 2556.16 examples/s]
Generating train split: 6522578 examples [17:04, 2534.81 examples/s]
Generating train split: 6522854 examples [17:04, 2496.94 examples/s]
Generating train split: 6523121 examples [17:05, 2347.66 examples/s]
Generating train split: 6523491 examples [17:05, 2683.05 examples/s]
Generating train split: 6523775 examples [17:05, 2615.77 examples/s]
Generating train split: 6524044 examples [17:05, 2466.76 examples/s]
Generating train split: 6524398 examples [17:05, 2713.09 examples/s]
Generating train split: 6524680 examples [17:05, 2541.52 examples/s]
Generating train split: 6524957 examples [17:05, 2323.59 examples/s]
Generating train split: 6525234 examples [17:05, 2402.44 examples/s]
Generating train split: 6525495 examples [17:06, 2154.98 examples/s]
Generating train split: 6525804 examples [17:06, 2333.21 examples/s]
Generating train split: 6526051 examples [17:06, 2247.36 examples/s]
Generating train split: 6526312 examples [17:06, 2020.61 examples/s]
Generating train split: 6526555 examples [17:06, 2109.33 examples/s]
Generating train split: 6526801 examples [17:06, 2161.50 examples/s]
Generating train split: 6527053 examples [17:06, 1963.89 examples/s]
Generating train split: 6546739 examples [17:06, 50149.11 examples/s]
Generating train split: 6560798 examples [17:06, 72422.73 examples/s]
Generating train split: 6568984 examples [17:10, 8257.27 examples/s] 
Generating train split: 6574796 examples [17:14, 3916.00 examples/s]
Generating train split: 6578929 examples [17:15, 3539.86 examples/s]
Generating train split: 6581877 examples [17:17, 3317.49 examples/s]
Generating train split: 6584023 examples [17:17, 3237.51 examples/s]
Generating train split: 6585624 examples [17:18, 3180.93 examples/s]
Generating train split: 6603381 examples [17:18, 9510.59 examples/s]
Generating train split: 6614702 examples [17:18, 14622.06 examples/s]
Generating train split: 6622402 examples [17:20, 8401.42 examples/s] 
Generating train split: 6627920 examples [17:24, 3790.58 examples/s]
Generating train split: 6631818 examples [17:26, 3594.53 examples/s]
Generating train split: 6634660 examples [17:26, 3630.76 examples/s]
Generating train split: 6636759 examples [17:27, 3497.71 examples/s]
Generating train split: 6638328 examples [17:28, 3608.57 examples/s]
Generating train split: 6639548 examples [17:28, 3482.83 examples/s]
Generating train split: 6640497 examples [17:30, 1901.74 examples/s]
Generating train split: 6641176 examples [17:30, 1957.44 examples/s]
Generating train split: 6641733 examples [17:31, 1976.00 examples/s]
Generating train split: 6642215 examples [17:31, 1920.79 examples/s]
Generating train split: 6645869 examples [17:31, 4238.97 examples/s]
Generating train split: 6647212 examples [17:31, 4980.87 examples/s]
Generating train split: 6652143 examples [17:31, 9838.12 examples/s]
Generating train split: 6654533 examples [17:32, 6844.98 examples/s]
Generating train split: 6656327 examples [17:33, 4431.42 examples/s]
Generating train split: 6657635 examples [17:33, 3783.90 examples/s]
Generating train split: 6658628 examples [17:34, 3601.07 examples/s]
Generating train split: 6659406 examples [17:34, 3237.18 examples/s]
Generating train split: 6660045 examples [17:34, 3031.30 examples/s]
Generating train split: 6660565 examples [17:34, 3013.78 examples/s]
Generating train split: 6661024 examples [17:35, 2833.18 examples/s]
Generating train split: 6661412 examples [17:35, 2752.50 examples/s]
Generating train split: 6661747 examples [17:35, 2730.77 examples/s]
Generating train split: 6662074 examples [17:35, 2609.18 examples/s]
Generating train split: 6662388 examples [17:35, 2437.93 examples/s]
Generating train split: 6662679 examples [17:35, 2513.96 examples/s]
Generating train split: 6663153 examples [17:35, 2967.78 examples/s]
Generating train split: 6663514 examples [17:36, 2843.35 examples/s]
Generating train split: 6663820 examples [17:36, 2680.53 examples/s]
Generating train split: 6664141 examples [17:36, 2749.36 examples/s]
Generating train split: 6664440 examples [17:36, 2671.81 examples/s]
Generating train split: 6664744 examples [17:36, 2706.66 examples/s]
Generating train split: 6665026 examples [17:36, 2722.19 examples/s]
Generating train split: 6665339 examples [17:36, 2629.45 examples/s]
Generating train split: 6665612 examples [17:36, 2531.72 examples/s]
Generating train split: 6665895 examples [17:37, 2596.84 examples/s]
Generating train split: 6666161 examples [17:37, 2561.49 examples/s]
Generating train split: 6666449 examples [17:37, 2439.65 examples/s]
Generating train split: 6666703 examples [17:37, 2066.66 examples/s]
Generating train split: 6666971 examples [17:37, 2198.83 examples/s]
Generating train split: 6667208 examples [17:37, 2210.54 examples/s]
Generating train split: 6667578 examples [17:37, 2555.51 examples/s]
Generating train split: 6667858 examples [17:37, 2612.04 examples/s]
Generating train split: 6668135 examples [17:38, 2235.34 examples/s]
Generating train split: 6668393 examples [17:38, 2319.14 examples/s]
Generating train split: 6668639 examples [17:38, 2150.48 examples/s]
Generating train split: 6668872 examples [17:38, 1954.89 examples/s]
Generating train split: 6669130 examples [17:38, 2072.76 examples/s]
Generating train split: 6669385 examples [17:38, 1678.90 examples/s]
Generating train split: 6669573 examples [17:38, 1672.76 examples/s]
Generating train split: 6669786 examples [17:38, 1770.89 examples/s]
Generating train split: 6669989 examples [17:39, 1781.10 examples/s]
Generating train split: 6670407 examples [17:39, 2322.75 examples/s]
Generating train split: 6670678 examples [17:39, 2389.36 examples/s]
Generating train split: 6671101 examples [17:39, 2860.78 examples/s]
Generating train split: 6671415 examples [17:39, 2368.96 examples/s]
Generating train split: 6671697 examples [17:39, 2273.65 examples/s]
Generating train split: 6672097 examples [17:39, 2678.99 examples/s]
Generating train split: 6672418 examples [17:39, 2807.15 examples/s]
Generating train split: 6672740 examples [17:40, 2647.69 examples/s]
Generating train split: 6673028 examples [17:40, 2636.63 examples/s]
Generating train split: 6673396 examples [17:40, 2839.34 examples/s]
Generating train split: 6673700 examples [17:40, 2759.52 examples/s]
Generating train split: 6674009 examples [17:40, 2374.09 examples/s]
Generating train split: 6674288 examples [17:40, 2469.46 examples/s]
Generating train split: 6674567 examples [17:40, 2162.33 examples/s]
Generating train split: 6674836 examples [17:40, 2121.75 examples/s]
Generating train split: 6675077 examples [17:41, 1947.87 examples/s]
Generating train split: 6675296 examples [17:41, 1914.40 examples/s]
Generating train split: 6675509 examples [17:41, 1952.49 examples/s]
Generating train split: 6675869 examples [17:41, 2360.12 examples/s]
Generating train split: 6676118 examples [17:41, 2240.10 examples/s]
Generating train split: 6676353 examples [17:41, 2036.50 examples/s]
Generating train split: 6676577 examples [17:41, 1974.76 examples/s]
Generating train split: 6676829 examples [17:41, 2064.31 examples/s]
Generating train split: 6677045 examples [17:42, 2031.17 examples/s]
Generating train split: 6677340 examples [17:42, 2204.22 examples/s]
Generating train split: 6677610 examples [17:42, 2324.43 examples/s]
Generating train split: 6677934 examples [17:42, 2566.46 examples/s]
Generating train split: 6678210 examples [17:42, 2473.47 examples/s]
Generating train split: 6678466 examples [17:42, 2431.29 examples/s]
Generating train split: 6678758 examples [17:42, 2520.74 examples/s]
Generating train split: 6679176 examples [17:42, 2863.08 examples/s]
Generating train split: 6679486 examples [17:42, 2796.76 examples/s]
Generating train split: 6679788 examples [17:43, 848.51 examples/s] 
Generating train split: 6680021 examples [17:43, 1000.50 examples/s]
Generating train split: 6680249 examples [17:44, 1124.61 examples/s]
Generating train split: 6680549 examples [17:44, 1399.38 examples/s]
Generating train split: 6680917 examples [17:44, 1787.25 examples/s]
Generating train split: 6681401 examples [17:44, 2354.96 examples/s]
Generating train split: 6681741 examples [17:44, 2357.13 examples/s]
Generating train split: 6682050 examples [17:44, 2219.21 examples/s]
Generating train split: 6682321 examples [17:44, 1915.21 examples/s]
Generating train split: 6688684 examples [17:45, 14480.25 examples/s]
Generating train split: 6692995 examples [17:45, 20867.15 examples/s]
Generating train split: 6698008 examples [17:45, 27886.53 examples/s]
Generating train split: 6701400 examples [17:45, 15199.72 examples/s]
Generating train split: 6703991 examples [17:46, 6672.18 examples/s] 
Generating train split: 6705896 examples [17:47, 4951.51 examples/s]
Generating train split: 6707303 examples [17:48, 4113.63 examples/s]
Generating train split: 6708346 examples [17:48, 4075.02 examples/s]
Generating train split: 6709202 examples [17:48, 3589.13 examples/s]
Generating train split: 6709869 examples [17:49, 3488.41 examples/s]
Generating train split: 6710430 examples [17:49, 3204.08 examples/s]
Generating train split: 6710888 examples [17:49, 3133.80 examples/s]
Generating train split: 6711304 examples [17:49, 3162.26 examples/s]
Generating train split: 6711690 examples [17:49, 3197.61 examples/s]
Generating train split: 6712066 examples [17:49, 2503.38 examples/s]
Generating train split: 6712389 examples [17:50, 2495.87 examples/s]
Generating train split: 6712682 examples [17:50, 2464.99 examples/s]
Generating train split: 6713011 examples [17:50, 2605.05 examples/s]
Generating train split: 6713304 examples [17:50, 2546.07 examples/s]
Generating train split: 6713581 examples [17:50, 2371.08 examples/s]
Generating train split: 6713844 examples [17:50, 2315.19 examples/s]
Generating train split: 6714097 examples [17:50, 2256.54 examples/s]
Generating train split: 6714341 examples [17:50, 2242.94 examples/s]
Generating train split: 6714608 examples [17:51, 2312.97 examples/s]
Generating train split: 6714855 examples [17:51, 2282.14 examples/s]
Generating train split: 6715086 examples [17:51, 2198.95 examples/s]
Generating train split: 6715321 examples [17:51, 2094.40 examples/s]
Generating train split: 6715609 examples [17:51, 2277.85 examples/s]
Generating train split: 6715909 examples [17:51, 2422.95 examples/s]
Generating train split: 6716269 examples [17:51, 2740.26 examples/s]
Generating train split: 6716601 examples [17:51, 2853.74 examples/s]
Generating train split: 6716897 examples [17:51, 2571.69 examples/s]
Generating train split: 6717275 examples [17:52, 2848.79 examples/s]
Generating train split: 6717605 examples [17:52, 2697.08 examples/s]
Generating train split: 6717887 examples [17:52, 2504.50 examples/s]
Generating train split: 6718154 examples [17:52, 2279.72 examples/s]
Generating train split: 6718481 examples [17:52, 2521.61 examples/s]
Generating train split: 6718761 examples [17:52, 2571.49 examples/s]
Generating train split: 6719030 examples [17:52, 2390.41 examples/s]
Generating train split: 6719281 examples [17:52, 2387.54 examples/s]
Generating train split: 6719574 examples [17:53, 2502.01 examples/s]
Generating train split: 6719842 examples [17:53, 2318.21 examples/s]
Generating train split: 6720086 examples [17:53, 2089.81 examples/s]
Generating train split: 6720330 examples [17:53, 2069.49 examples/s]
Generating train split: 6720617 examples [17:53, 2266.64 examples/s]
Generating train split: 6720858 examples [17:54, 586.90 examples/s] 
Generating train split: 6721254 examples [17:54, 875.92 examples/s]
Generating train split: 6721506 examples [17:54, 1053.71 examples/s]
Generating train split: 6721787 examples [17:55, 1276.70 examples/s]
Generating train split: 6722109 examples [17:55, 1587.91 examples/s]
Generating train split: 6722376 examples [17:55, 1630.41 examples/s]
Generating train split: 6722621 examples [17:55, 1779.53 examples/s]
Generating train split: 6722876 examples [17:55, 1801.25 examples/s]
Generating train split: 6723124 examples [17:55, 1930.87 examples/s]
Generating train split: 6723351 examples [17:55, 1496.14 examples/s]
Generating train split: 6728387 examples [17:56, 11411.45 examples/s]
Generating train split: 6731448 examples [17:56, 15499.29 examples/s]
Generating train split: 6736689 examples [17:56, 24358.27 examples/s]
Generating train split: 6741964 examples [17:56, 30995.50 examples/s]
Generating train split: 6745516 examples [17:57, 7194.35 examples/s] 
Generating train split: 6748085 examples [17:58, 4704.37 examples/s]
Generating train split: 6749971 examples [17:59, 4324.68 examples/s]
Generating train split: 6751391 examples [17:59, 3998.73 examples/s]
Generating train split: 6752461 examples [18:00, 3474.26 examples/s]
Generating train split: 6753275 examples [18:00, 3323.37 examples/s]
Generating train split: 6753937 examples [18:01, 3065.02 examples/s]
Generating train split: 6754479 examples [18:01, 2814.74 examples/s]
Generating train split: 6754915 examples [18:01, 2665.14 examples/s]
Generating train split: 6755276 examples [18:01, 2740.69 examples/s]
Generating train split: 6755634 examples [18:01, 2716.70 examples/s]
Generating train split: 6755956 examples [18:02, 2371.16 examples/s]
Generating train split: 6756241 examples [18:02, 2368.70 examples/s]
Generating train split: 6756578 examples [18:02, 2532.33 examples/s]
Generating train split: 6756943 examples [18:02, 2674.74 examples/s]
Generating train split: 6757267 examples [18:02, 2749.98 examples/s]
Generating train split: 6757570 examples [18:02, 2758.28 examples/s]
Generating train split: 6757872 examples [18:02, 2411.48 examples/s]
Generating train split: 6758129 examples [18:02, 2352.09 examples/s]
Generating train split: 6758379 examples [18:03, 2164.47 examples/s]
Generating train split: 6758642 examples [18:03, 2106.79 examples/s]
Generating train split: 6758944 examples [18:03, 2305.71 examples/s]
Generating train split: 6759238 examples [18:03, 2426.94 examples/s]
Generating train split: 6759512 examples [18:03, 2342.75 examples/s]
Generating train split: 6759871 examples [18:03, 2589.34 examples/s]
Generating train split: 6760144 examples [18:03, 2327.04 examples/s]
Generating train split: 6760594 examples [18:03, 2868.28 examples/s]
Generating train split: 6760933 examples [18:04, 2934.03 examples/s]
Generating train split: 6761238 examples [18:04, 2421.10 examples/s]
Generating train split: 6761548 examples [18:04, 2441.53 examples/s]
Generating train split: 6761886 examples [18:04, 2616.31 examples/s]
Generating train split: 6762169 examples [18:05, 572.51 examples/s] 
Generating train split: 6762463 examples [18:06, 739.96 examples/s]
Generating train split: 6762782 examples [18:06, 964.17 examples/s]
Generating train split: 6763220 examples [18:06, 1356.41 examples/s]
Generating train split: 6763529 examples [18:06, 1525.12 examples/s]
Generating train split: 6763816 examples [18:06, 1599.28 examples/s]
Generating train split: 6764097 examples [18:06, 1746.08 examples/s]
Generating train split: 6764464 examples [18:06, 2093.36 examples/s]
Generating train split: 6764740 examples [18:06, 2230.57 examples/s]
Generating train split: 6765036 examples [18:07, 2202.96 examples/s]
Generating train split: 6765313 examples [18:07, 2258.53 examples/s]
Generating train split: 6765579 examples [18:07, 1789.78 examples/s]
Generating train split: 6765837 examples [18:07, 1954.32 examples/s]
Generating train split: 6766095 examples [18:07, 1538.86 examples/s]
Generating train split: 6773088 examples [18:07, 14531.71 examples/s]
Generating train split: 6778412 examples [18:07, 22591.95 examples/s]
Generating train split: 6781365 examples [18:08, 21702.66 examples/s]
Generating train split: 6784031 examples [18:08, 10503.64 examples/s]
Generating train split: 6786047 examples [18:09, 6062.04 examples/s] 
Generating train split: 6787515 examples [18:10, 4367.05 examples/s]
Generating train split: 6788630 examples [18:10, 3990.37 examples/s]
Generating train split: 6789476 examples [18:10, 3774.60 examples/s]
Generating train split: 6790161 examples [18:11, 3566.17 examples/s]
Generating train split: 6790719 examples [18:11, 3118.95 examples/s]
Generating train split: 6791185 examples [18:11, 2950.64 examples/s]
Generating train split: 6791575 examples [18:11, 2852.88 examples/s]
Generating train split: 6791920 examples [18:12, 2651.92 examples/s]
Generating train split: 6792219 examples [18:12, 2689.37 examples/s]
Generating train split: 6792526 examples [18:12, 2736.94 examples/s]
Generating train split: 6792841 examples [18:12, 2545.98 examples/s]
Generating train split: 6793157 examples [18:12, 2605.53 examples/s]
Generating train split: 6793464 examples [18:12, 2699.86 examples/s]
Generating train split: 6793770 examples [18:12, 2641.84 examples/s]
Generating train split: 6794068 examples [18:12, 2638.50 examples/s]
Generating train split: 6794359 examples [18:13, 2507.63 examples/s]
Generating train split: 6794625 examples [18:13, 2484.07 examples/s]
Generating train split: 6794890 examples [18:13, 2272.52 examples/s]
Generating train split: 6795145 examples [18:13, 2341.47 examples/s]
Generating train split: 6795506 examples [18:13, 2671.46 examples/s]
Generating train split: 6795798 examples [18:13, 2384.22 examples/s]
Generating train split: 6796077 examples [18:13, 2323.35 examples/s]
Generating train split: 6796319 examples [18:13, 2145.03 examples/s]
Generating train split: 6796692 examples [18:14, 2509.68 examples/s]
Generating train split: 6796973 examples [18:14, 2496.41 examples/s]
Generating train split: 6797253 examples [18:14, 2038.50 examples/s]
Generating train split: 6797496 examples [18:14, 2101.25 examples/s]
Generating train split: 6797743 examples [18:14, 2171.91 examples/s]
Generating train split: 6797980 examples [18:14, 2186.82 examples/s]
Generating train split: 6798262 examples [18:14, 2349.54 examples/s]
Generating train split: 6798519 examples [18:14, 2362.83 examples/s]
Generating train split: 6798762 examples [18:14, 2192.25 examples/s]
Generating train split: 6799027 examples [18:15, 2288.18 examples/s]
Generating train split: 6799416 examples [18:15, 2704.02 examples/s]
Generating train split: 6799748 examples [18:15, 2805.95 examples/s]
Generating train split: 6800052 examples [18:15, 2542.82 examples/s]
Generating train split: 6800349 examples [18:15, 2524.27 examples/s]
Generating train split: 6800614 examples [18:15, 2351.81 examples/s]
Generating train split: 6800865 examples [18:15, 2349.40 examples/s]
Generating train split: 6801125 examples [18:15, 2228.57 examples/s]
Generating train split: 6801352 examples [18:16, 2100.79 examples/s]
Generating train split: 6801596 examples [18:17, 449.46 examples/s] 
Generating train split: 6801859 examples [18:17, 599.95 examples/s]
Generating train split: 6802094 examples [18:17, 755.29 examples/s]
Generating train split: 6802463 examples [18:17, 1088.09 examples/s]
Generating train split: 6802734 examples [18:18, 1304.46 examples/s]
Generating train split: 6803032 examples [18:18, 1556.72 examples/s]
Generating train split: 6803461 examples [18:18, 2053.65 examples/s]
Generating train split: 6803776 examples [18:18, 2138.18 examples/s]
Generating train split: 6804070 examples [18:18, 2239.92 examples/s]
Generating train split: 6804370 examples [18:18, 2322.77 examples/s]
Generating train split: 6804654 examples [18:18, 2210.91 examples/s]
Generating train split: 6804906 examples [18:18, 2248.48 examples/s]
Generating train split: 6805155 examples [18:19, 1881.22 examples/s]
Generating train split: 6805385 examples [18:19, 1933.57 examples/s]
Generating train split: 6805607 examples [18:19, 1745.14 examples/s]
Generating train split: 6805811 examples [18:19, 1661.06 examples/s]
Generating train split: 6806197 examples [18:19, 2143.40 examples/s]
Generating train split: 6806462 examples [18:19, 2253.79 examples/s]
Generating train split: 6806736 examples [18:20, 1401.91 examples/s]
Generating train split: 6810943 examples [18:20, 8679.54 examples/s]
Generating train split: 6815995 examples [18:20, 17157.01 examples/s]
Generating train split: 6823208 examples [18:20, 28965.60 examples/s]
Generating train split: 6826952 examples [18:20, 27880.14 examples/s]
Generating train split: 6830344 examples [18:20, 16871.99 examples/s]
Generating train split: 6832966 examples [18:22, 6928.32 examples/s] 
Generating train split: 6834871 examples [18:22, 4939.13 examples/s]
Generating train split: 6836294 examples [18:23, 4297.55 examples/s]
Generating train split: 6837380 examples [18:23, 3882.78 examples/s]
Generating train split: 6838203 examples [18:24, 3337.05 examples/s]
Generating train split: 6838841 examples [18:24, 3228.46 examples/s]
Generating train split: 6839385 examples [18:24, 3134.57 examples/s]
Generating train split: 6839856 examples [18:24, 3102.64 examples/s]
Generating train split: 6840266 examples [18:25, 2841.54 examples/s]
Generating train split: 6840624 examples [18:25, 2781.56 examples/s]
Generating train split: 6840961 examples [18:25, 2807.62 examples/s]
Generating train split: 6841299 examples [18:25, 2635.51 examples/s]
Generating train split: 6841599 examples [18:25, 2563.69 examples/s]
Generating train split: 6841878 examples [18:25, 2547.27 examples/s]
Generating train split: 6842165 examples [18:25, 2319.39 examples/s]
Generating train split: 6842432 examples [18:26, 2233.89 examples/s]
Generating train split: 6842672 examples [18:26, 1717.02 examples/s]
Generating train split: 6842875 examples [18:26, 1604.83 examples/s]
Generating train split: 6843146 examples [18:26, 1780.16 examples/s]
Generating train split: 6843365 examples [18:26, 1851.70 examples/s]
Generating train split: 6843618 examples [18:26, 2009.26 examples/s]
Generating train split: 6843925 examples [18:26, 2192.93 examples/s]
Generating train split: 6844224 examples [18:27, 2358.66 examples/s]
Generating train split: 6844483 examples [18:27, 2058.24 examples/s]
Generating train split: 6844710 examples [18:27, 2040.58 examples/s]
Generating train split: 6844928 examples [18:27, 1882.02 examples/s]
Generating train split: 6845133 examples [18:27, 1884.74 examples/s]
Generating train split: 6845460 examples [18:27, 2153.20 examples/s]
Generating train split: 6845719 examples [18:27, 2255.44 examples/s]
Generating train split: 6846098 examples [18:27, 2632.17 examples/s]
Generating train split: 6846388 examples [18:28, 2264.42 examples/s]
Generating train split: 6846734 examples [18:28, 2515.35 examples/s]
Generating train split: 6847019 examples [18:28, 2560.60 examples/s]
Generating train split: 6847290 examples [18:29, 624.25 examples/s] 
Generating train split: 6847641 examples [18:29, 858.95 examples/s]
Generating train split: 6847952 examples [18:29, 1086.91 examples/s]
Generating train split: 6848232 examples [18:29, 1289.74 examples/s]
Generating train split: 6848493 examples [18:30, 1363.67 examples/s]
Generating train split: 6848815 examples [18:30, 1649.27 examples/s]
Generating train split: 6849123 examples [18:30, 1910.64 examples/s]
Generating train split: 6849528 examples [18:30, 2336.45 examples/s]
Generating train split: 6849830 examples [18:30, 2204.60 examples/s]
Generating train split: 6850130 examples [18:30, 2214.01 examples/s]
Generating train split: 6850428 examples [18:30, 2185.94 examples/s]
Generating train split: 6850832 examples [18:30, 2593.62 examples/s]
Generating train split: 6851138 examples [18:31, 2137.05 examples/s]
Generating train split: 6851441 examples [18:31, 2271.09 examples/s]
Generating train split: 6851751 examples [18:31, 2445.40 examples/s]
Generating train split: 6852052 examples [18:31, 2363.89 examples/s]
Generating train split: 6852306 examples [18:31, 2236.66 examples/s]
Generating train split: 6852556 examples [18:31, 2218.68 examples/s]
Generating train split: 6852801 examples [18:31, 2192.95 examples/s]
Generating train split: 6853113 examples [18:31, 2427.86 examples/s]
Generating train split: 6853391 examples [18:32, 1615.09 examples/s]
Generating train split: 6859243 examples [18:32, 12681.17 examples/s]
Generating train split: 6865039 examples [18:32, 22520.83 examples/s]
Generating train split: 6879293 examples [18:32, 50533.32 examples/s]
Generating train split: 6885531 examples [18:34, 8328.78 examples/s] 
Generating train split: 6889965 examples [18:36, 5302.21 examples/s]
Generating train split: 6893149 examples [18:38, 4085.90 examples/s]
Generating train split: 6895441 examples [18:39, 3728.31 examples/s]
Generating train split: 6897120 examples [18:42, 1813.74 examples/s]
Generating train split: 6898326 examples [18:43, 1906.98 examples/s]
Generating train split: 6899270 examples [18:43, 1953.88 examples/s]
Generating train split: 6900007 examples [18:43, 2002.88 examples/s]
Generating train split: 6900581 examples [18:44, 2005.88 examples/s]
Generating train split: 6901057 examples [18:44, 2065.59 examples/s]
Generating train split: 6901464 examples [18:44, 2073.17 examples/s]
Generating train split: 6901813 examples [18:44, 2022.00 examples/s]
Generating train split: 6902117 examples [18:44, 2096.28 examples/s]
Generating train split: 6902412 examples [18:45, 2177.13 examples/s]
Generating train split: 6902716 examples [18:45, 1945.51 examples/s]
Generating train split: 6906575 examples [18:45, 7624.36 examples/s]
Generating train split: 6911289 examples [18:45, 14765.42 examples/s]
Generating train split: 6918734 examples [18:45, 27022.68 examples/s]
Generating train split: 6922606 examples [18:45, 20678.08 examples/s]
Generating train split: 6925720 examples [18:46, 7962.41 examples/s] 
Generating train split: 6927976 examples [18:47, 5405.64 examples/s]
Generating train split: 6929650 examples [18:48, 4680.00 examples/s]
Generating train split: 6930905 examples [18:48, 4028.11 examples/s]
Generating train split: 6931868 examples [18:49, 3786.76 examples/s]
Generating train split: 6932612 examples [18:49, 3411.01 examples/s]
Generating train split: 6933213 examples [18:49, 3175.21 examples/s]
Generating train split: 6933691 examples [18:50, 3096.02 examples/s]
Generating train split: 6934115 examples [18:50, 3085.28 examples/s]
Generating train split: 6934503 examples [18:50, 2916.64 examples/s]
Generating train split: 6934861 examples [18:50, 2774.63 examples/s]
Generating train split: 6935175 examples [18:50, 2735.74 examples/s]
Generating train split: 6935478 examples [18:50, 2606.72 examples/s]
Generating train split: 6935763 examples [18:50, 2551.19 examples/s]
Generating train split: 6936055 examples [18:51, 2594.78 examples/s]
Generating train split: 6936350 examples [18:51, 2620.64 examples/s]
Generating train split: 6936642 examples [18:51, 2422.99 examples/s]
Generating train split: 6936914 examples [18:51, 2198.48 examples/s]
Generating train split: 6937168 examples [18:54, 274.94 examples/s] 
Generating train split: 6937372 examples [18:54, 341.19 examples/s]
Generating train split: 6937686 examples [18:54, 484.88 examples/s]
Generating train split: 6937939 examples [18:55, 624.56 examples/s]
Generating train split: 6938180 examples [18:55, 778.80 examples/s]
Generating train split: 6938459 examples [18:55, 991.83 examples/s]
Generating train split: 6938736 examples [18:55, 1222.00 examples/s]
Generating train split: 6938987 examples [18:55, 1401.52 examples/s]
Generating train split: 6939222 examples [18:55, 1573.57 examples/s]
Generating train split: 6939465 examples [18:55, 1729.08 examples/s]
Generating train split: 6939759 examples [18:55, 1997.84 examples/s]
Generating train split: 6940092 examples [18:55, 2304.02 examples/s]
Generating train split: 6940386 examples [18:55, 2405.61 examples/s]
Generating train split: 6940672 examples [18:56, 2248.54 examples/s]
Generating train split: 6940935 examples [18:56, 1997.77 examples/s]
Generating train split: 6941204 examples [18:56, 2145.88 examples/s]
Generating train split: 6941465 examples [18:56, 2019.65 examples/s]
Generating train split: 6941776 examples [18:56, 2279.97 examples/s]
Generating train split: 6942086 examples [18:56, 2476.08 examples/s]
Generating train split: 6942355 examples [18:56, 2403.71 examples/s]
Generating train split: 6942677 examples [18:56, 2574.42 examples/s]
Generating train split: 6942946 examples [18:57, 2576.85 examples/s]
Generating train split: 6943241 examples [18:57, 2435.45 examples/s]
Generating train split: 6943512 examples [18:57, 2127.17 examples/s]
Generating train split: 6943750 examples [18:57, 2171.59 examples/s]
Generating train split: 6944016 examples [18:57, 2281.93 examples/s]
Generating train split: 6944356 examples [18:57, 2554.14 examples/s]
Generating train split: 6944641 examples [18:57, 2558.97 examples/s]
Generating train split: 6944925 examples [18:57, 2457.74 examples/s]
Generating train split: 6945253 examples [18:58, 2619.88 examples/s]
Generating train split: 6945521 examples [18:58, 1658.54 examples/s]
Generating train split: 6946946 examples [18:58, 4118.58 examples/s]
Generating train split: 6953072 examples [18:58, 16610.53 examples/s]
Generating train split: 6959893 examples [18:58, 28887.76 examples/s]
Generating train split: 6969088 examples [18:58, 43669.50 examples/s]
Generating train split: 6974102 examples [19:01, 6590.02 examples/s] 
Generating train split: 6977693 examples [19:02, 4866.71 examples/s]
Generating train split: 6980305 examples [19:03, 3733.19 examples/s]
Generating train split: 6982201 examples [19:05, 2618.95 examples/s]
Generating train split: 6983570 examples [19:06, 2588.43 examples/s]
Generating train split: 6984579 examples [19:06, 2579.79 examples/s]
Generating train split: 6985381 examples [19:07, 2560.33 examples/s]
Generating train split: 6986001 examples [19:07, 2482.18 examples/s]
Generating train split: 6986510 examples [19:07, 2444.63 examples/s]
Generating train split: 6986946 examples [19:07, 2365.37 examples/s]
Generating train split: 6987317 examples [19:07, 2248.01 examples/s]
Generating train split: 6987622 examples [19:08, 2197.65 examples/s]
Generating train split: 6987896 examples [19:08, 2184.57 examples/s]
Generating train split: 6988165 examples [19:08, 2258.28 examples/s]
Generating train split: 6988652 examples [19:08, 2671.36 examples/s]
Generating train split: 6988975 examples [19:08, 2721.75 examples/s]
Generating train split: 6989315 examples [19:08, 2593.61 examples/s]
Generating train split: 6989610 examples [19:08, 2402.54 examples/s]
Generating train split: 6989888 examples [19:09, 2320.39 examples/s]
Generating train split: 6990138 examples [19:09, 2311.43 examples/s]
Generating train split: 6990431 examples [19:09, 2417.22 examples/s]
Generating train split: 6990703 examples [19:09, 2456.36 examples/s]
Generating train split: 6990986 examples [19:09, 2479.17 examples/s]
Generating train split: 6991266 examples [19:09, 2434.07 examples/s]
Generating train split: 6991518 examples [19:09, 2260.69 examples/s]
Generating train split: 6991780 examples [19:09, 2349.60 examples/s]
Generating train split: 6992038 examples [19:09, 2031.11 examples/s]
Generating train split: 6992252 examples [19:10, 2051.50 examples/s]
Generating train split: 6992465 examples [19:10, 2024.57 examples/s]
Generating train split: 6992690 examples [19:10, 1427.08 examples/s]
Generating train split: 6996614 examples [19:10, 9166.51 examples/s]
Generating train split: 6999343 examples [19:10, 13198.47 examples/s]
Generating train split: 7003216 examples [19:10, 19404.12 examples/s]
Generating train split: 7005562 examples [19:11, 12383.92 examples/s]
Generating train split: 7007410 examples [19:11, 6761.18 examples/s] 
Generating train split: 7008800 examples [19:12, 4687.11 examples/s]
Generating train split: 7009833 examples [19:12, 4443.99 examples/s]
Generating train split: 7010668 examples [19:13, 3819.61 examples/s]
Generating train split: 7011333 examples [19:13, 3545.37 examples/s]
Generating train split: 7011866 examples [19:13, 3540.73 examples/s]
Generating train split: 7012383 examples [19:13, 3452.77 examples/s]
Generating train split: 7012823 examples [19:13, 3140.41 examples/s]
Generating train split: 7013204 examples [19:14, 2847.53 examples/s]
Generating train split: 7013543 examples [19:14, 2775.05 examples/s]
Generating train split: 7013854 examples [19:14, 2614.63 examples/s]
Generating train split: 7014141 examples [19:14, 2653.71 examples/s]
Generating train split: 7014454 examples [19:14, 2724.88 examples/s]
Generating train split: 7014752 examples [19:14, 2657.78 examples/s]
Generating train split: 7015035 examples [19:14, 2553.82 examples/s]
Generating train split: 7015479 examples [19:14, 3016.61 examples/s]
Generating train split: 7015839 examples [19:14, 3125.37 examples/s]
Generating train split: 7016181 examples [19:15, 2672.31 examples/s]
Generating train split: 7016566 examples [19:15, 2875.99 examples/s]
Generating train split: 7016888 examples [19:15, 2861.01 examples/s]
Generating train split: 7017203 examples [19:16, 781.95 examples/s] 
Generating train split: 7017430 examples [19:16, 901.34 examples/s]
Generating train split: 7017641 examples [19:16, 992.82 examples/s]
Generating train split: 7017858 examples [19:16, 1083.14 examples/s]
Generating train split: 7018094 examples [19:17, 1252.91 examples/s]
Generating train split: 7018306 examples [19:17, 1171.50 examples/s]
Generating train split: 7018596 examples [19:17, 1455.26 examples/s]
Generating train split: 7018826 examples [19:17, 1583.73 examples/s]
Generating train split: 7019025 examples [19:17, 1667.44 examples/s]
Generating train split: 7019374 examples [19:17, 2052.99 examples/s]
Generating train split: 7019677 examples [19:17, 2223.37 examples/s]
Generating train split: 7019965 examples [19:17, 2359.84 examples/s]
Generating train split: 7020296 examples [19:18, 2587.04 examples/s]
Generating train split: 7020580 examples [19:18, 2488.14 examples/s]
Generating train split: 7020840 examples [19:18, 2297.94 examples/s]
Generating train split: 7021107 examples [19:18, 2345.83 examples/s]
Generating train split: 7021370 examples [19:18, 2369.03 examples/s]
Generating train split: 7021626 examples [19:18, 2327.91 examples/s]
Generating train split: 7021886 examples [19:18, 2119.72 examples/s]
Generating train split: 7022138 examples [19:18, 2011.29 examples/s]
Generating train split: 7022387 examples [19:18, 2108.83 examples/s]
Generating train split: 7022624 examples [19:19, 2123.63 examples/s]
Generating train split: 7022862 examples [19:19, 2096.42 examples/s]
Generating train split: 7023094 examples [19:19, 2007.74 examples/s]
Generating train split: 7023323 examples [19:19, 1909.08 examples/s]
Generating train split: 7023620 examples [19:19, 2140.56 examples/s]
Generating train split: 7023839 examples [19:19, 1755.31 examples/s]
Generating train split: 7024070 examples [19:19, 1858.26 examples/s]
Generating train split: 7024476 examples [19:19, 2378.04 examples/s]
Generating train split: 7024844 examples [19:20, 2668.21 examples/s]
Generating train split: 7025134 examples [19:20, 2408.02 examples/s]
Generating train split: 7025392 examples [19:20, 2379.63 examples/s]
Generating train split: 7025763 examples [19:20, 2692.61 examples/s]
Generating train split: 7026053 examples [19:20, 2499.64 examples/s]
Generating train split: 7026425 examples [19:20, 2805.62 examples/s]
Generating train split: 7026717 examples [19:20, 2764.54 examples/s]
Generating train split: 7027073 examples [19:20, 2893.06 examples/s]
Generating train split: 7027376 examples [19:21, 2332.77 examples/s]
Generating train split: 7027657 examples [19:21, 2167.63 examples/s]
Generating train split: 7027921 examples [19:21, 1996.64 examples/s]
Generating train split: 7028166 examples [19:21, 1767.07 examples/s]
Generating train split: 7050300 examples [19:21, 48456.98 examples/s]
Generating train split: 7057084 examples [19:21, 48415.71 examples/s]
Generating train split: 7063278 examples [19:24, 8487.01 examples/s] 
Generating train split: 7067708 examples [19:25, 5501.77 examples/s]
Generating train split: 7070871 examples [19:28, 3455.91 examples/s]
Generating train split: 7073126 examples [19:29, 3185.46 examples/s]
Generating train split: 7074771 examples [19:30, 2929.51 examples/s]
Generating train split: 7076004 examples [19:30, 2894.78 examples/s]
Generating train split: 7076935 examples [19:31, 2808.20 examples/s]
Generating train split: 7077656 examples [19:31, 2620.35 examples/s]
Generating train split: 7078220 examples [19:31, 2419.88 examples/s]
Generating train split: 7078687 examples [19:31, 2436.40 examples/s]
Generating train split: 7079103 examples [19:32, 2450.19 examples/s]
Generating train split: 7079453 examples [19:32, 2359.53 examples/s]
Generating train split: 7079776 examples [19:32, 2356.16 examples/s]
Generating train split: 7080068 examples [19:32, 2309.74 examples/s]
Generating train split: 7080359 examples [19:32, 2325.20 examples/s]
Generating train split: 7080622 examples [19:32, 2208.88 examples/s]
Generating train split: 7080877 examples [19:33, 2100.72 examples/s]
Generating train split: 7081205 examples [19:33, 2320.68 examples/s]
Generating train split: 7081472 examples [19:33, 1463.11 examples/s]
Generating train split: 7085090 examples [19:33, 7085.34 examples/s]
Generating train split: 7086785 examples [19:33, 8908.91 examples/s]
Generating train split: 7089907 examples [19:33, 13077.13 examples/s]
Generating train split: 7091634 examples [19:34, 6367.45 examples/s] 
Generating train split: 7092932 examples [19:35, 4549.61 examples/s]
Generating train split: 7093927 examples [19:35, 3644.54 examples/s]
Generating train split: 7094706 examples [19:35, 3233.32 examples/s]
Generating train split: 7095311 examples [19:36, 3003.22 examples/s]
Generating train split: 7095809 examples [19:36, 3006.72 examples/s]
Generating train split: 7096247 examples [19:36, 3138.69 examples/s]
Generating train split: 7096683 examples [19:36, 2885.14 examples/s]
Generating train split: 7097052 examples [19:36, 2621.06 examples/s]
Generating train split: 7097361 examples [19:38, 664.12 examples/s] 
Generating train split: 7097699 examples [19:38, 811.43 examples/s]
Generating train split: 7098091 examples [19:39, 1019.66 examples/s]
Generating train split: 7098384 examples [19:39, 1113.33 examples/s]
Generating train split: 7098638 examples [19:39, 1245.83 examples/s]
Generating train split: 7098914 examples [19:39, 1439.33 examples/s]
Generating train split: 7099247 examples [19:39, 1727.32 examples/s]
Generating train split: 7099640 examples [19:39, 2097.40 examples/s]
Generating train split: 7099950 examples [19:39, 2134.32 examples/s]
Generating train split: 7100227 examples [19:39, 2110.39 examples/s]
Generating train split: 7100486 examples [19:40, 2194.78 examples/s]
Generating train split: 7101247 examples [19:40, 3412.42 examples/s]
Generating train split: 7101635 examples [19:40, 2754.16 examples/s]
Generating train split: 7101962 examples [19:40, 2662.62 examples/s]
Generating train split: 7102296 examples [19:40, 2780.29 examples/s]
Generating train split: 7102609 examples [19:40, 2511.13 examples/s]
Generating train split: 7102902 examples [19:40, 2273.69 examples/s]
Generating train split: 7103180 examples [19:40, 2360.11 examples/s]
Generating train split: 7103442 examples [19:41, 1926.86 examples/s]
Generating train split: 7103673 examples [19:41, 1624.64 examples/s]
Generating train split: 7103921 examples [19:41, 1794.34 examples/s]
Generating train split: 7104126 examples [19:41, 1834.48 examples/s]
Generating train split: 7104352 examples [19:41, 1919.57 examples/s]
Generating train split: 7104576 examples [19:41, 1800.60 examples/s]
Generating train split: 7104817 examples [19:41, 1945.46 examples/s]
Generating train split: 7105028 examples [19:42, 1842.04 examples/s]
Generating train split: 7105225 examples [19:42, 1806.34 examples/s]
Generating train split: 7105531 examples [19:42, 2122.91 examples/s]
Generating train split: 7105795 examples [19:42, 2210.73 examples/s]
Generating train split: 7106056 examples [19:42, 2133.34 examples/s]
Generating train split: 7106500 examples [19:42, 2700.60 examples/s]
Generating train split: 7107708 examples [19:42, 5003.40 examples/s]
Generating train split: 7108572 examples [19:42, 5961.94 examples/s]
Generating train split: 7109197 examples [19:43, 4687.73 examples/s]
Generating train split: 7109728 examples [19:43, 3934.65 examples/s]
Generating train split: 7110174 examples [19:43, 3227.71 examples/s]
Generating train split: 7110550 examples [19:43, 3151.40 examples/s]
Generating train split: 7110914 examples [19:43, 2761.93 examples/s]
Generating train split: 7111245 examples [19:43, 2863.63 examples/s]
Generating train split: 7111570 examples [19:44, 2881.71 examples/s]
Generating train split: 7111880 examples [19:44, 2874.41 examples/s]
Generating train split: 7112255 examples [19:44, 3050.40 examples/s]
Generating train split: 7112644 examples [19:44, 3240.81 examples/s]
Generating train split: 7112997 examples [19:44, 3154.29 examples/s]
Generating train split: 7113368 examples [19:44, 3250.09 examples/s]
Generating train split: 7113704 examples [19:44, 3274.91 examples/s]
Generating train split: 7114053 examples [19:46, 599.38 examples/s] 
Generating train split: 7114463 examples [19:46, 832.05 examples/s]
Generating train split: 7114773 examples [19:46, 995.39 examples/s]
Generating train split: 7115167 examples [19:46, 1300.29 examples/s]
Generating train split: 7115466 examples [19:46, 1450.38 examples/s]
Generating train split: 7115745 examples [19:47, 1531.45 examples/s]
Generating train split: 7115996 examples [19:47, 1655.35 examples/s]
Generating train split: 7116235 examples [19:47, 1309.78 examples/s]
Generating train split: 7120364 examples [19:47, 7905.71 examples/s]
Generating train split: 7123894 examples [19:47, 12860.98 examples/s]
Generating train split: 7127457 examples [19:47, 17319.11 examples/s]
Generating train split: 7129804 examples [19:48, 7278.44 examples/s] 
Generating train split: 7131522 examples [19:49, 5812.38 examples/s]
Generating train split: 7132828 examples [19:49, 4997.45 examples/s]
Generating train split: 7133839 examples [19:49, 4938.94 examples/s]
Generating train split: 7135027 examples [19:49, 5575.49 examples/s]
Generating train split: 7135921 examples [19:49, 5776.33 examples/s]
Generating train split: 7136778 examples [19:50, 5183.02 examples/s]
Generating train split: 7137501 examples [19:50, 4523.77 examples/s]
Generating train split: 7138096 examples [19:50, 4180.85 examples/s]
Generating train split: 7138614 examples [19:50, 4014.31 examples/s]
Generating train split: 7139077 examples [19:50, 3693.98 examples/s]
Generating train split: 7139499 examples [19:51, 3656.08 examples/s]
Generating train split: 7139903 examples [19:51, 3412.54 examples/s]
Generating train split: 7140267 examples [19:51, 2875.90 examples/s]
Generating train split: 7140606 examples [19:51, 2968.28 examples/s]
Generating train split: 7140942 examples [19:51, 2955.56 examples/s]
Generating train split: 7141278 examples [19:51, 2852.46 examples/s]
Generating train split: 7141595 examples [19:51, 2698.70 examples/s]
Generating train split: 7141914 examples [19:51, 2546.38 examples/s]
Generating train split: 7142195 examples [19:52, 2313.04 examples/s]
Generating train split: 7142437 examples [19:52, 2274.46 examples/s]
Generating train split: 7142681 examples [19:52, 2113.14 examples/s]
Generating train split: 7142942 examples [19:52, 2211.78 examples/s]
Generating train split: 7143171 examples [19:52, 2051.96 examples/s]
Generating train split: 7143392 examples [19:52, 1981.78 examples/s]
Generating train split: 7143624 examples [19:52, 1751.59 examples/s]
Generating train split: 7143807 examples [19:53, 1730.89 examples/s]
Generating train split: 7144036 examples [19:53, 1850.51 examples/s]
Generating train split: 7144248 examples [19:53, 1608.92 examples/s]
Generating train split: 7144447 examples [19:53, 1692.61 examples/s]
Generating train split: 7144755 examples [19:53, 2031.16 examples/s]
Generating train split: 7144983 examples [19:53, 2042.06 examples/s]
Generating train split: 7145205 examples [19:53, 1728.72 examples/s]
Generating train split: 7145553 examples [19:53, 2123.58 examples/s]
Generating train split: 7145875 examples [19:54, 2364.01 examples/s]
Generating train split: 7146341 examples [19:54, 2933.41 examples/s]
Generating train split: 7146674 examples [19:54, 2847.32 examples/s]
Generating train split: 7147004 examples [19:54, 2894.87 examples/s]
Generating train split: 7147317 examples [19:54, 2777.34 examples/s]
Generating train split: 7147629 examples [19:54, 2491.20 examples/s]
Generating train split: 7148654 examples [19:54, 4395.54 examples/s]
Generating train split: 7149147 examples [19:54, 4286.88 examples/s]
Generating train split: 7149625 examples [19:55, 3527.74 examples/s]
Generating train split: 7150044 examples [19:55, 3380.92 examples/s]
Generating train split: 7150424 examples [19:55, 3370.43 examples/s]
Generating train split: 7150800 examples [19:55, 3353.11 examples/s]
Generating train split: 7151172 examples [19:55, 3160.47 examples/s]
Generating train split: 7151522 examples [19:55, 3233.46 examples/s]
Generating train split: 7151866 examples [19:55, 3189.46 examples/s]
Generating train split: 7152193 examples [19:55, 2982.45 examples/s]
Generating train split: 7153219 examples [19:56, 4870.89 examples/s]
Generating train split: 7154039 examples [19:56, 5604.11 examples/s]
Generating train split: 7154635 examples [19:58, 953.63 examples/s] 
Generating train split: 7155075 examples [19:58, 1087.66 examples/s]
Generating train split: 7155452 examples [19:58, 1236.51 examples/s]
Generating train split: 7155800 examples [19:58, 1407.71 examples/s]
Generating train split: 7156161 examples [19:58, 1656.99 examples/s]
Generating train split: 7156496 examples [19:58, 1852.25 examples/s]
Generating train split: 7156813 examples [19:58, 2002.91 examples/s]
Generating train split: 7157110 examples [19:59, 2073.39 examples/s]
Generating train split: 7170953 examples [19:59, 29473.70 examples/s]
Generating train split: 7186347 examples [19:59, 57233.54 examples/s]
Generating train split: 7194019 examples [20:01, 11656.27 examples/s]
Generating train split: 7199515 examples [20:03, 6028.64 examples/s] 
Generating train split: 7203456 examples [20:05, 4685.56 examples/s]
Generating train split: 7206289 examples [20:06, 4110.17 examples/s]
Generating train split: 7208342 examples [20:08, 2671.69 examples/s]
Generating train split: 7209799 examples [20:09, 2645.41 examples/s]
Generating train split: 7210906 examples [20:09, 2543.16 examples/s]
Generating train split: 7228269 examples [20:09, 9187.56 examples/s]
Generating train split: 7234052 examples [20:09, 11489.96 examples/s]
Generating train split: 7239349 examples [20:11, 7336.79 examples/s] 
Generating train split: 7243153 examples [20:13, 4981.38 examples/s]
Generating train split: 7245906 examples [20:14, 4382.13 examples/s]
Generating train split: 7247921 examples [20:14, 3915.50 examples/s]
Generating train split: 7249397 examples [20:15, 3651.66 examples/s]
Generating train split: 7250518 examples [20:15, 3395.99 examples/s]
Generating train split: 7251386 examples [20:16, 3257.10 examples/s]
Generating train split: 7252059 examples [20:16, 3155.89 examples/s]
Generating train split: 7252618 examples [20:16, 3012.16 examples/s]
Generating train split: 7253073 examples [20:17, 2706.69 examples/s]
Generating train split: 7253440 examples [20:17, 2370.65 examples/s]
Generating train split: 7253746 examples [20:17, 2288.34 examples/s]
Generating train split: 7254013 examples [20:17, 2329.40 examples/s]
Generating train split: 7254285 examples [20:17, 2138.75 examples/s]
Generating train split: 7254536 examples [20:17, 1964.98 examples/s]
Generating train split: 7254759 examples [20:18, 1934.96 examples/s]
Generating train split: 7254963 examples [20:18, 1935.54 examples/s]
Generating train split: 7255189 examples [20:21, 236.51 examples/s] 
Generating train split: 7255496 examples [20:21, 333.89 examples/s]
Generating train split: 7255793 examples [20:22, 453.74 examples/s]
Generating train split: 7256157 examples [20:22, 646.11 examples/s]
Generating train split: 7256396 examples [20:22, 770.36 examples/s]
Generating train split: 7256728 examples [20:22, 1025.02 examples/s]
Generating train split: 7257008 examples [20:22, 1226.19 examples/s]
Generating train split: 7257301 examples [20:22, 1413.33 examples/s]
Generating train split: 7257551 examples [20:22, 1595.44 examples/s]
Generating train split: 7257925 examples [20:22, 2005.78 examples/s]
Generating train split: 7258225 examples [20:22, 2019.84 examples/s]
Generating train split: 7258529 examples [20:23, 2239.52 examples/s]
Generating train split: 7259641 examples [20:23, 4359.26 examples/s]
Generating train split: 7260186 examples [20:23, 3959.94 examples/s]
Generating train split: 7260658 examples [20:23, 3734.57 examples/s]
Generating train split: 7263377 examples [20:23, 9216.61 examples/s]
Generating train split: 7273899 examples [20:23, 33238.19 examples/s]
Generating train split: 7285672 examples [20:23, 55484.95 examples/s]
Generating train split: 7292616 examples [20:23, 58407.29 examples/s]
Generating train split: 7299013 examples [20:26, 7757.84 examples/s] 
Generating train split: 7303567 examples [20:28, 5471.87 examples/s]
Generating train split: 7306840 examples [20:29, 4242.81 examples/s]
Generating train split: 7309207 examples [20:30, 3586.58 examples/s]
Generating train split: 7310928 examples [20:31, 3236.76 examples/s]
Generating train split: 7312189 examples [20:32, 2834.94 examples/s]
Generating train split: 7313115 examples [20:32, 2697.62 examples/s]
Generating train split: 7313825 examples [20:36, 1135.39 examples/s]
Generating train split: 7314334 examples [20:36, 1190.07 examples/s]
Generating train split: 7314752 examples [20:36, 1255.97 examples/s]
Generating train split: 7315137 examples [20:36, 1296.51 examples/s]
Generating train split: 7315453 examples [20:37, 1338.24 examples/s]
Generating train split: 7315746 examples [20:37, 1423.00 examples/s]
Generating train split: 7316022 examples [20:37, 1394.18 examples/s]
Generating train split: 7316278 examples [20:37, 1425.55 examples/s]
Generating train split: 7316492 examples [20:37, 1463.60 examples/s]
Generating train split: 7316682 examples [20:37, 1410.53 examples/s]
Generating train split: 7316853 examples [20:38, 1229.06 examples/s]
Generating train split: 7317070 examples [20:38, 1368.82 examples/s]
Generating train split: 7317287 examples [20:38, 1506.28 examples/s]
Generating train split: 7317627 examples [20:38, 1875.12 examples/s]
Generating train split: 7317935 examples [20:38, 1997.00 examples/s]
Generating train split: 7318157 examples [20:38, 1995.30 examples/s]
Generating train split: 7318451 examples [20:38, 2208.68 examples/s]
Generating train split: 7318735 examples [20:38, 2368.12 examples/s]
Generating train split: 7319041 examples [20:38, 2542.46 examples/s]
Generating train split: 7319322 examples [20:39, 1433.35 examples/s]
Generating train split: 7322247 examples [20:39, 6367.21 examples/s]
Generating train split: 7324318 examples [20:39, 8812.86 examples/s]
Generating train split: 7325535 examples [20:39, 8261.43 examples/s]
Generating train split: 7326729 examples [20:39, 8707.15 examples/s]
Generating train split: 7327792 examples [20:40, 4395.26 examples/s]
Generating train split: 7328599 examples [20:41, 2970.88 examples/s]
Generating train split: 7329194 examples [20:41, 2563.73 examples/s]
Generating train split: 7329696 examples [20:41, 2462.64 examples/s]
Generating train split: 7330083 examples [20:41, 2230.37 examples/s]
Generating train split: 7330402 examples [20:42, 2115.22 examples/s]
Generating train split: 7330686 examples [20:42, 2123.77 examples/s]
Generating train split: 7330976 examples [20:42, 2000.84 examples/s]
Generating train split: 7331273 examples [20:42, 2124.22 examples/s]
Generating train split: 7331516 examples [20:42, 2096.60 examples/s]
Generating train split: 7331766 examples [20:42, 2176.68 examples/s]
Generating train split: 7332001 examples [20:42, 1993.79 examples/s]
Generating train split: 7332213 examples [20:43, 1570.22 examples/s]
Generating train split: 7332481 examples [20:43, 1786.18 examples/s]
Generating train split: 7332709 examples [20:43, 1837.21 examples/s]
Generating train split: 7332926 examples [20:43, 1894.52 examples/s]
Generating train split: 7333155 examples [20:43, 1765.94 examples/s]
Generating train split: 7333404 examples [20:43, 1895.78 examples/s]
Generating train split: 7333786 examples [20:43, 2336.34 examples/s]
Generating train split: 7334043 examples [20:43, 2340.76 examples/s]
Generating train split: 7334382 examples [20:43, 2595.62 examples/s]
Generating train split: 7334671 examples [20:44, 2435.72 examples/s]
Generating train split: 7334983 examples [20:44, 2604.18 examples/s]
Generating train split: 7335291 examples [20:44, 2499.12 examples/s]
Generating train split: 7335597 examples [20:44, 2601.77 examples/s]
Generating train split: 7335906 examples [20:44, 2717.38 examples/s]
Generating train split: 7336258 examples [20:44, 2895.95 examples/s]
Generating train split: 7336553 examples [20:44, 2786.72 examples/s]
Generating train split: 7336856 examples [20:44, 2242.44 examples/s]
Generating train split: 7337135 examples [20:45, 2243.96 examples/s]
Generating train split: 7337472 examples [20:45, 2503.80 examples/s]
Generating train split: 7337742 examples [20:45, 2380.79 examples/s]
Generating train split: 7338004 examples [20:45, 2137.17 examples/s]
Generating train split: 7338248 examples [20:45, 2091.90 examples/s]
Generating train split: 7338508 examples [20:45, 2197.14 examples/s]
Generating train split: 7338794 examples [20:45, 2360.24 examples/s]
Generating train split: 7339047 examples [20:46, 1921.78 examples/s]
Generating train split: 7339267 examples [20:46, 1842.66 examples/s]
Generating train split: 7339499 examples [20:46, 1949.60 examples/s]
Generating train split: 7339751 examples [20:46, 2066.81 examples/s]
Generating train split: 7340019 examples [20:46, 2206.16 examples/s]
Generating train split: 7340400 examples [20:46, 2599.83 examples/s]
Generating train split: 7340674 examples [20:46, 2355.08 examples/s]
Generating train split: 7340926 examples [20:46, 2362.75 examples/s]
Generating train split: 7341306 examples [20:46, 2712.56 examples/s]
Generating train split: 7341664 examples [20:47, 2949.54 examples/s]
Generating train split: 7341973 examples [20:47, 2453.18 examples/s]
Generating train split: 7342379 examples [20:47, 2783.54 examples/s]
Generating train split: 7342713 examples [20:47, 2900.85 examples/s]
Generating train split: 7343020 examples [20:47, 2357.47 examples/s]
Generating train split: 7343294 examples [20:49, 507.13 examples/s] 
Generating train split: 7343510 examples [20:49, 613.51 examples/s]
Generating train split: 7343770 examples [20:49, 772.21 examples/s]
Generating train split: 7344003 examples [20:49, 932.08 examples/s]
Generating train split: 7344214 examples [20:49, 1062.22 examples/s]
Generating train split: 7344464 examples [20:49, 1274.46 examples/s]
Generating train split: 7344711 examples [20:49, 1472.72 examples/s]
Generating train split: 7344951 examples [20:50, 1630.46 examples/s]
Generating train split: 7345177 examples [20:50, 1704.82 examples/s]
Generating train split: 7345475 examples [20:50, 1985.73 examples/s]
Generating train split: 7345810 examples [20:50, 2299.57 examples/s]
Generating train split: 7346080 examples [20:50, 2157.03 examples/s]
Generating train split: 7346378 examples [20:50, 2313.89 examples/s]
Generating train split: 7346660 examples [20:50, 2173.75 examples/s]
Generating train split: 7346929 examples [20:50, 2188.91 examples/s]
Generating train split: 7347202 examples [20:51, 2301.48 examples/s]
Generating train split: 7347476 examples [20:51, 2370.64 examples/s]
Generating train split: 7347738 examples [20:51, 2179.82 examples/s]
Generating train split: 7347998 examples [20:51, 2157.34 examples/s]
Generating train split: 7348324 examples [20:51, 2373.70 examples/s]
Generating train split: 7348585 examples [20:51, 2338.54 examples/s]
Generating train split: 7349010 examples [20:51, 2772.46 examples/s]
Generating train split: 7349313 examples [20:51, 2595.48 examples/s]
Generating train split: 7349703 examples [20:52, 1877.02 examples/s]
Generating train split: 7352504 examples [20:52, 6891.24 examples/s]
Generating train split: 7356394 examples [20:52, 13777.48 examples/s]
Generating train split: 7359853 examples [20:52, 18586.37 examples/s]
Generating train split: 7362183 examples [20:52, 18237.71 examples/s]
Generating train split: 7364487 examples [20:52, 19391.70 examples/s]
Generating train split: 7366678 examples [20:53, 8246.52 examples/s] 
Generating train split: 7368320 examples [20:54, 4443.60 examples/s]
Generating train split: 7369551 examples [20:54, 3849.89 examples/s]
Generating train split: 7370488 examples [20:55, 3519.68 examples/s]
Generating train split: 7371208 examples [20:55, 3232.01 examples/s]
Generating train split: 7371782 examples [20:55, 2978.02 examples/s]
Generating train split: 7372245 examples [20:55, 2865.85 examples/s]
Generating train split: 7372647 examples [20:56, 2482.42 examples/s]
Generating train split: 7372984 examples [20:56, 2560.01 examples/s]
Generating train split: 7373304 examples [20:56, 2451.73 examples/s]
Generating train split: 7373597 examples [20:56, 2509.29 examples/s]
Generating train split: 7373880 examples [20:56, 2413.42 examples/s]
Generating train split: 7374158 examples [20:56, 2404.10 examples/s]
Generating train split: 7374428 examples [20:56, 2360.25 examples/s]
Generating train split: 7374739 examples [20:57, 2516.84 examples/s]
Generating train split: 7375026 examples [20:57, 2599.48 examples/s]
Generating train split: 7375361 examples [20:57, 2679.98 examples/s]
Generating train split: 7375641 examples [20:57, 2645.40 examples/s]
Generating train split: 7375940 examples [20:57, 2509.99 examples/s]
Generating train split: 7376200 examples [20:57, 2493.42 examples/s]
Generating train split: 7376457 examples [20:57, 2499.66 examples/s]
Generating train split: 7376732 examples [20:57, 2104.06 examples/s]
Generating train split: 7377039 examples [20:58, 2287.76 examples/s]
Generating train split: 7377303 examples [20:58, 2300.93 examples/s]
Generating train split: 7377561 examples [20:58, 2282.71 examples/s]
Generating train split: 7377804 examples [20:58, 1739.95 examples/s]
Generating train split: 7378186 examples [20:58, 2177.14 examples/s]
Generating train split: 7378492 examples [20:58, 2351.96 examples/s]
Generating train split: 7378780 examples [20:58, 2123.21 examples/s]
Generating train split: 7379019 examples [20:58, 2078.93 examples/s]
Generating train split: 7379242 examples [20:59, 1936.80 examples/s]
Generating train split: 7379466 examples [20:59, 1986.47 examples/s]
Generating train split: 7379717 examples [20:59, 2108.82 examples/s]
Generating train split: 7380006 examples [20:59, 2289.59 examples/s]
Generating train split: 7380253 examples [21:00, 503.58 examples/s] 
Generating train split: 7380462 examples [21:01, 602.76 examples/s]
Generating train split: 7380778 examples [21:01, 847.64 examples/s]
Generating train split: 7381140 examples [21:01, 1172.23 examples/s]
Generating train split: 7381500 examples [21:01, 1517.95 examples/s]
Generating train split: 7381777 examples [21:01, 1630.36 examples/s]
Generating train split: 7382066 examples [21:01, 1479.78 examples/s]
Generating train split: 7382299 examples [21:01, 1448.23 examples/s]
Generating train split: 7382507 examples [21:01, 1557.98 examples/s]
Generating train split: 7382716 examples [21:02, 1509.39 examples/s]
Generating train split: 7382899 examples [21:02, 1425.43 examples/s]
Generating train split: 7383068 examples [21:02, 1406.53 examples/s]
Generating train split: 7383257 examples [21:02, 1497.52 examples/s]
Generating train split: 7383485 examples [21:02, 1649.56 examples/s]
Generating train split: 7383761 examples [21:02, 1910.39 examples/s]
Generating train split: 7383988 examples [21:02, 1974.76 examples/s]
Generating train split: 7384215 examples [21:02, 2035.34 examples/s]
Generating train split: 7384655 examples [21:03, 2666.40 examples/s]
Generating train split: 7384990 examples [21:03, 2784.95 examples/s]
Generating train split: 7385280 examples [21:03, 2768.82 examples/s]
Generating train split: 7385586 examples [21:03, 2560.59 examples/s]
Generating train split: 7385870 examples [21:03, 2604.80 examples/s]
Generating train split: 7386143 examples [21:03, 2578.16 examples/s]
Generating train split: 7386437 examples [21:03, 2404.80 examples/s]
Generating train split: 7386719 examples [21:03, 2363.46 examples/s]
Generating train split: 7386964 examples [21:04, 2109.23 examples/s]
Generating train split: 7387182 examples [21:04, 2120.36 examples/s]
Generating train split: 7387423 examples [21:04, 2010.15 examples/s]
Generating train split: 7387645 examples [21:04, 1295.72 examples/s]
Generating train split: 7388831 examples [21:04, 3246.48 examples/s]
Generating train split: 7389311 examples [21:04, 3072.31 examples/s]
Generating train split: 7391402 examples [21:05, 6387.86 examples/s]
Generating train split: 7392210 examples [21:05, 3156.31 examples/s]
Generating train split: 7392803 examples [21:05, 2682.48 examples/s]
Generating train split: 7393275 examples [21:06, 2482.01 examples/s]
Generating train split: 7393684 examples [21:06, 2258.30 examples/s]
Generating train split: 7394011 examples [21:06, 2301.18 examples/s]
Generating train split: 7394309 examples [21:06, 2397.02 examples/s]
Generating train split: 7394623 examples [21:06, 2253.02 examples/s]
Generating train split: 7394918 examples [21:07, 2294.04 examples/s]
Generating train split: 7395292 examples [21:07, 2397.71 examples/s]
Generating train split: 7395554 examples [21:07, 2343.93 examples/s]
Generating train split: 7395824 examples [21:07, 2280.89 examples/s]
Generating train split: 7396095 examples [21:07, 2362.48 examples/s]
Generating train split: 7396347 examples [21:07, 2287.90 examples/s]
Generating train split: 7396597 examples [21:07, 2152.11 examples/s]
Generating train split: 7396832 examples [21:07, 2043.62 examples/s]
Generating train split: 7397047 examples [21:07, 2065.11 examples/s]
Generating train split: 7397285 examples [21:08, 2051.03 examples/s]
Generating train split: 7397606 examples [21:08, 2288.50 examples/s]
Generating train split: 7397848 examples [21:08, 2248.66 examples/s]
Generating train split: 7398130 examples [21:08, 2390.83 examples/s]
Generating train split: 7398393 examples [21:08, 2108.18 examples/s]
Generating train split: 7398681 examples [21:08, 2283.49 examples/s]
Generating train split: 7398923 examples [21:08, 2263.58 examples/s]
Generating train split: 7399160 examples [21:08, 2026.41 examples/s]
Generating train split: 7399380 examples [21:09, 1896.73 examples/s]
Generating train split: 7399593 examples [21:09, 1843.94 examples/s]
Generating train split: 7399832 examples [21:09, 1940.43 examples/s]
Generating train split: 7400034 examples [21:09, 1738.00 examples/s]
Generating train split: 7400307 examples [21:09, 1982.13 examples/s]
Generating train split: 7400533 examples [21:09, 1960.92 examples/s]
Generating train split: 7400801 examples [21:09, 2119.07 examples/s]
Generating train split: 7401086 examples [21:09, 2057.76 examples/s]
Generating train split: 7401388 examples [21:10, 2283.83 examples/s]
Generating train split: 7401746 examples [21:10, 2539.76 examples/s]
Generating train split: 7402062 examples [21:10, 2665.56 examples/s]
Generating train split: 7402372 examples [21:10, 2775.29 examples/s]
Generating train split: 7402691 examples [21:10, 2675.17 examples/s]
Generating train split: 7403404 examples [21:10, 3839.78 examples/s]
Generating train split: 7403827 examples [21:10, 3445.67 examples/s]
Generating train split: 7404202 examples [21:10, 3070.29 examples/s]
Generating train split: 7404544 examples [21:11, 2941.77 examples/s]
Generating train split: 7404858 examples [21:11, 2480.82 examples/s]
Generating train split: 7405134 examples [21:11, 2028.14 examples/s]
Generating train split: 7405411 examples [21:11, 2129.51 examples/s]
Generating train split: 7405736 examples [21:11, 2345.19 examples/s]
Generating train split: 7406013 examples [21:13, 601.26 examples/s] 
Generating train split: 7406319 examples [21:13, 790.37 examples/s]
Generating train split: 7406560 examples [21:13, 940.65 examples/s]
Generating train split: 7406902 examples [21:13, 1230.81 examples/s]
Generating train split: 7407194 examples [21:13, 1473.49 examples/s]
Generating train split: 7407483 examples [21:13, 1680.77 examples/s]
Generating train split: 7407743 examples [21:13, 1627.33 examples/s]
Generating train split: 7407980 examples [21:13, 1698.73 examples/s]
Generating train split: 7408235 examples [21:13, 1872.42 examples/s]
Generating train split: 7408487 examples [21:14, 1918.64 examples/s]
Generating train split: 7408771 examples [21:14, 2106.73 examples/s]
Generating train split: 7409010 examples [21:14, 1900.12 examples/s]
Generating train split: 7409248 examples [21:14, 1815.77 examples/s]
Generating train split: 7409544 examples [21:14, 2072.42 examples/s]
Generating train split: 7409784 examples [21:14, 1821.69 examples/s]
Generating train split: 7410096 examples [21:14, 2049.55 examples/s]
Generating train split: 7410485 examples [21:14, 2488.09 examples/s]
Generating train split: 7410762 examples [21:15, 2476.14 examples/s]
Generating train split: 7411025 examples [21:15, 2389.38 examples/s]
Generating train split: 7411444 examples [21:15, 2748.53 examples/s]
Generating train split: 7411802 examples [21:15, 2932.87 examples/s]
Generating train split: 7412136 examples [21:15, 2907.71 examples/s]
Generating train split: 7412444 examples [21:15, 2499.02 examples/s]
Generating train split: 7412728 examples [21:15, 2215.88 examples/s]
Generating train split: 7412989 examples [21:16, 2093.75 examples/s]
Generating train split: 7413212 examples [21:16, 1969.75 examples/s]
Generating train split: 7413428 examples [21:16, 1865.78 examples/s]
Generating train split: 7413621 examples [21:16, 1711.36 examples/s]
Generating train split: 7413817 examples [21:16, 1735.49 examples/s]
Generating train split: 7414043 examples [21:16, 1849.51 examples/s]
Generating train split: 7414255 examples [21:16, 1859.08 examples/s]
Generating train split: 7414444 examples [21:17, 1308.84 examples/s]
Generating train split: 7419286 examples [21:17, 11169.99 examples/s]
Generating train split: 7429141 examples [21:17, 31260.44 examples/s]
Generating train split: 7435199 examples [21:17, 37296.89 examples/s]
Generating train split: 7439637 examples [21:19, 6013.31 examples/s] 
Generating train split: 7442813 examples [21:21, 4289.96 examples/s]
Generating train split: 7445105 examples [21:21, 3800.34 examples/s]
Generating train split: 7446811 examples [21:23, 2432.11 examples/s]
Generating train split: 7448012 examples [21:24, 2468.16 examples/s]
Generating train split: 7448953 examples [21:25, 2204.42 examples/s]
Generating train split: 7449816 examples [21:25, 2481.50 examples/s]
Generating train split: 7450568 examples [21:25, 2593.95 examples/s]
Generating train split: 7451182 examples [21:25, 2761.07 examples/s]
Generating train split: 7451745 examples [21:25, 2865.25 examples/s]
Generating train split: 7452253 examples [21:26, 2185.86 examples/s]
Generating train split: 7452650 examples [21:26, 2086.34 examples/s]
Generating train split: 7452970 examples [21:26, 2174.04 examples/s]
Generating train split: 7453338 examples [21:26, 2326.24 examples/s]
Generating train split: 7453663 examples [21:26, 2472.34 examples/s]
Generating train split: 7453992 examples [21:26, 2468.86 examples/s]
Generating train split: 7454318 examples [21:27, 2197.99 examples/s]
Generating train split: 7454577 examples [21:27, 2234.17 examples/s]
Generating train split: 7454830 examples [21:27, 2025.68 examples/s]
Generating train split: 7455085 examples [21:27, 2116.24 examples/s]
Generating train split: 7455333 examples [21:27, 1837.18 examples/s]
Generating train split: 7455557 examples [21:27, 1690.04 examples/s]
Generating train split: 7455751 examples [21:27, 1721.95 examples/s]
Generating train split: 7456043 examples [21:28, 1917.19 examples/s]
Generating train split: 7456298 examples [21:28, 2030.55 examples/s]
Generating train split: 7456567 examples [21:28, 2187.72 examples/s]
Generating train split: 7456829 examples [21:28, 2222.97 examples/s]
Generating train split: 7457063 examples [21:28, 1369.09 examples/s]
Generating train split: 7458884 examples [21:28, 4535.21 examples/s]
Generating train split: 7461496 examples [21:28, 9039.66 examples/s]
Generating train split: 7465811 examples [21:29, 16888.95 examples/s]
Generating train split: 7467957 examples [21:29, 10159.10 examples/s]
Generating train split: 7469621 examples [21:30, 4381.54 examples/s] 
Generating train split: 7470860 examples [21:31, 3589.86 examples/s]
Generating train split: 7471775 examples [21:31, 3280.57 examples/s]
Generating train split: 7472502 examples [21:31, 2996.58 examples/s]
Generating train split: 7473061 examples [21:32, 2790.99 examples/s]
Generating train split: 7473518 examples [21:32, 2752.02 examples/s]
Generating train split: 7473941 examples [21:32, 2741.60 examples/s]
Generating train split: 7474300 examples [21:32, 2548.65 examples/s]
Generating train split: 7474634 examples [21:32, 2594.84 examples/s]
Generating train split: 7474947 examples [21:32, 2330.34 examples/s]
Generating train split: 7475221 examples [21:32, 2359.02 examples/s]
Generating train split: 7475531 examples [21:33, 2484.55 examples/s]
Generating train split: 7475817 examples [21:33, 2273.18 examples/s]
Generating train split: 7476086 examples [21:33, 2338.09 examples/s]
Generating train split: 7476378 examples [21:33, 2427.38 examples/s]
Generating train split: 7476645 examples [21:33, 2259.82 examples/s]
Generating train split: 7476895 examples [21:33, 1974.84 examples/s]
Generating train split: 7477124 examples [21:33, 1948.46 examples/s]
Generating train split: 7477329 examples [21:34, 1725.83 examples/s]
Generating train split: 7477519 examples [21:34, 1375.25 examples/s]
Generating train split: 7477691 examples [21:35, 458.45 examples/s] 
Generating train split: 7477852 examples [21:35, 554.43 examples/s]
Generating train split: 7477999 examples [21:35, 599.61 examples/s]
Generating train split: 7478239 examples [21:35, 818.86 examples/s]
Generating train split: 7478611 examples [21:35, 1243.38 examples/s]
Generating train split: 7478828 examples [21:36, 1401.88 examples/s]
Generating train split: 7479063 examples [21:36, 1531.31 examples/s]
Generating train split: 7479310 examples [21:36, 1452.94 examples/s]
Generating train split: 7479604 examples [21:36, 1725.63 examples/s]
Generating train split: 7479951 examples [21:36, 2065.06 examples/s]
Generating train split: 7480200 examples [21:36, 1950.45 examples/s]
Generating train split: 7480554 examples [21:36, 2115.05 examples/s]
Generating train split: 7480856 examples [21:36, 2286.42 examples/s]
Generating train split: 7481124 examples [21:37, 2221.98 examples/s]
Generating train split: 7481376 examples [21:37, 2276.78 examples/s]
Generating train split: 7481614 examples [21:37, 2213.33 examples/s]
Generating train split: 7481858 examples [21:37, 2075.76 examples/s]
Generating train split: 7482122 examples [21:37, 2191.06 examples/s]
Generating train split: 7482380 examples [21:37, 1929.46 examples/s]
Generating train split: 7482643 examples [21:37, 2083.25 examples/s]
Generating train split: 7482880 examples [21:37, 1956.52 examples/s]
Generating train split: 7483133 examples [21:38, 2062.76 examples/s]
Generating train split: 7483381 examples [21:38, 1891.88 examples/s]
Generating train split: 7483642 examples [21:38, 2059.07 examples/s]
Generating train split: 7483875 examples [21:38, 1966.93 examples/s]
Generating train split: 7484184 examples [21:38, 2213.64 examples/s]
Generating train split: 7484573 examples [21:38, 2621.19 examples/s]
Generating train split: 7484853 examples [21:38, 2642.38 examples/s]
Generating train split: 7485231 examples [21:38, 2927.91 examples/s]
Generating train split: 7485545 examples [21:39, 2633.01 examples/s]
Generating train split: 7485820 examples [21:39, 2662.92 examples/s]
Generating train split: 7486116 examples [21:39, 2671.27 examples/s]
Generating train split: 7486484 examples [21:39, 2917.01 examples/s]
Generating train split: 7486826 examples [21:39, 2975.19 examples/s]
Generating train split: 7487167 examples [21:39, 2935.40 examples/s]
Generating train split: 7487554 examples [21:39, 3156.18 examples/s]
Generating train split: 7487891 examples [21:39, 2804.89 examples/s]
Generating train split: 7488203 examples [21:39, 2773.94 examples/s]
Generating train split: 7488492 examples [21:40, 2421.99 examples/s]
Generating train split: 7488747 examples [21:40, 2411.85 examples/s]
Generating train split: 7489014 examples [21:40, 2263.34 examples/s]
Generating train split: 7489258 examples [21:40, 2262.73 examples/s]
Generating train split: 7489509 examples [21:40, 2278.60 examples/s]
Generating train split: 7489746 examples [21:40, 2172.29 examples/s]
Generating train split: 7490017 examples [21:40, 2242.08 examples/s]
Generating train split: 7490262 examples [21:41, 1488.42 examples/s]
Generating train split: 7492209 examples [21:41, 5047.38 examples/s]
Generating train split: 7497807 examples [21:41, 16277.71 examples/s]
Generating train split: 7499989 examples [21:41, 16009.23 examples/s]
Generating train split: 7502298 examples [21:41, 17454.24 examples/s]
Generating train split: 7504364 examples [21:42, 6098.10 examples/s] 
Generating train split: 7505886 examples [21:43, 4571.32 examples/s]
Generating train split: 7507023 examples [21:43, 3750.82 examples/s]
Generating train split: 7507896 examples [21:43, 3341.90 examples/s]
Generating train split: 7508590 examples [21:44, 2966.12 examples/s]
Generating train split: 7509112 examples [21:44, 3028.37 examples/s]
Generating train split: 7509595 examples [21:44, 3108.76 examples/s]
Generating train split: 7510047 examples [21:44, 2952.90 examples/s]
Generating train split: 7510425 examples [21:44, 2834.98 examples/s]
Generating train split: 7510823 examples [21:45, 2987.08 examples/s]
Generating train split: 7511177 examples [21:46, 1066.62 examples/s]
Generating train split: 7511435 examples [21:46, 1148.28 examples/s]
Generating train split: 7511721 examples [21:46, 1306.82 examples/s]
Generating train split: 7511976 examples [21:46, 1443.99 examples/s]
Generating train split: 7512223 examples [21:46, 1526.69 examples/s]
Generating train split: 7512457 examples [21:46, 1583.02 examples/s]
Generating train split: 7512675 examples [21:46, 1602.13 examples/s]
Generating train split: 7512916 examples [21:47, 1763.02 examples/s]
Generating train split: 7513150 examples [21:47, 1874.42 examples/s]
Generating train split: 7513382 examples [21:47, 1906.21 examples/s]
Generating train split: 7513609 examples [21:47, 1857.86 examples/s]
Generating train split: 7513873 examples [21:47, 2022.53 examples/s]
Generating train split: 7514155 examples [21:47, 2162.01 examples/s]
Generating train split: 7514413 examples [21:47, 2271.94 examples/s]
Generating train split: 7514651 examples [21:47, 2108.92 examples/s]
Generating train split: 7514875 examples [21:48, 1714.29 examples/s]
Generating train split: 7515099 examples [21:48, 1522.39 examples/s]
Generating train split: 7515282 examples [21:48, 1470.04 examples/s]
Generating train split: 7515447 examples [21:48, 1488.08 examples/s]
Generating train split: 7515625 examples [21:48, 1432.41 examples/s]
Generating train split: 7515942 examples [21:48, 1828.52 examples/s]
Generating train split: 7516259 examples [21:48, 2120.34 examples/s]
Generating train split: 7516642 examples [21:48, 2541.27 examples/s]
Generating train split: 7516939 examples [21:49, 2464.47 examples/s]
Generating train split: 7517206 examples [21:49, 2274.67 examples/s]
Generating train split: 7517443 examples [21:49, 2297.84 examples/s]
Generating train split: 7517689 examples [21:49, 1994.32 examples/s]
Generating train split: 7517912 examples [21:49, 1857.33 examples/s]
Generating train split: 7518121 examples [21:49, 1820.08 examples/s]
Generating train split: 7518312 examples [21:49, 1798.46 examples/s]
Generating train split: 7518549 examples [21:49, 1837.80 examples/s]
Generating train split: 7518749 examples [21:50, 1802.31 examples/s]
Generating train split: 7518939 examples [21:50, 1749.74 examples/s]
Generating train split: 7519215 examples [21:50, 1965.83 examples/s]
Generating train split: 7519572 examples [21:50, 2329.13 examples/s]
Generating train split: 7519878 examples [21:50, 2512.42 examples/s]
Generating train split: 7520159 examples [21:50, 2505.50 examples/s]
Generating train split: 7520450 examples [21:50, 2549.56 examples/s]
Generating train split: 7520758 examples [21:50, 2669.54 examples/s]
Generating train split: 7521034 examples [21:51, 2178.98 examples/s]
Generating train split: 7521346 examples [21:51, 2365.27 examples/s]
Generating train split: 7521624 examples [21:51, 2417.19 examples/s]
Generating train split: 7521880 examples [21:51, 2286.03 examples/s]
Generating train split: 7522121 examples [21:51, 1951.07 examples/s]
Generating train split: 7522353 examples [21:51, 1895.75 examples/s]
Generating train split: 7522572 examples [21:51, 1870.32 examples/s]
Generating train split: 7522856 examples [21:51, 2079.15 examples/s]
Generating train split: 7523086 examples [21:52, 2053.51 examples/s]
Generating train split: 7523322 examples [21:52, 2125.11 examples/s]
Generating train split: 7523594 examples [21:52, 2260.69 examples/s]
Generating train split: 7523828 examples [21:52, 1974.86 examples/s]
Generating train split: 7524051 examples [21:52, 1769.32 examples/s]
Generating train split: 7524256 examples [21:52, 1788.80 examples/s]
Generating train split: 7524477 examples [21:52, 1856.97 examples/s]
Generating train split: 7524722 examples [21:52, 1987.85 examples/s]
Generating train split: 7524965 examples [21:52, 2097.58 examples/s]
Generating train split: 7525242 examples [21:53, 2250.04 examples/s]
Generating train split: 7526295 examples [21:53, 4566.93 examples/s]
Generating train split: 7540639 examples [21:53, 44226.41 examples/s]
Generating train split: 7546715 examples [21:53, 48656.33 examples/s]
Generating train split: 7551741 examples [21:54, 15864.47 examples/s]
Generating train split: 7555472 examples [21:56, 4933.92 examples/s] 
Generating train split: 7558129 examples [21:57, 3832.80 examples/s]
Generating train split: 7560055 examples [21:58, 3500.83 examples/s]
Generating train split: 7561487 examples [21:59, 3378.46 examples/s]
Generating train split: 7562590 examples [21:59, 3150.15 examples/s]
Generating train split: 7563417 examples [22:00, 2768.86 examples/s]
Generating train split: 7564053 examples [22:00, 2821.60 examples/s]
Generating train split: 7564586 examples [22:00, 2702.04 examples/s]
Generating train split: 7565025 examples [22:00, 2662.09 examples/s]
Generating train split: 7565404 examples [22:01, 2628.45 examples/s]
Generating train split: 7565756 examples [22:01, 2720.27 examples/s]
Generating train split: 7566114 examples [22:01, 2682.23 examples/s]
Generating train split: 7566528 examples [22:01, 2924.18 examples/s]
Generating train split: 7566881 examples [22:01, 3040.10 examples/s]
Generating train split: 7567304 examples [22:01, 3258.25 examples/s]
Generating train split: 7567700 examples [22:01, 3329.78 examples/s]
Generating train split: 7568080 examples [22:01, 2895.43 examples/s]
Generating train split: 7568415 examples [22:02, 2737.67 examples/s]
Generating train split: 7568726 examples [22:02, 2785.78 examples/s]
Generating train split: 7569035 examples [22:03, 904.57 examples/s] 
Generating train split: 7569344 examples [22:03, 1121.18 examples/s]
Generating train split: 7569692 examples [22:03, 1403.00 examples/s]
Generating train split: 7570031 examples [22:03, 1697.77 examples/s]
Generating train split: 7570453 examples [22:03, 2127.16 examples/s]
Generating train split: 7570896 examples [22:03, 2529.58 examples/s]
Generating train split: 7571244 examples [22:03, 2330.49 examples/s]
Generating train split: 7571553 examples [22:03, 2182.71 examples/s]
Generating train split: 7571837 examples [22:04, 2186.85 examples/s]
Generating train split: 7581511 examples [22:04, 22875.29 examples/s]
Generating train split: 7586661 examples [22:04, 28372.73 examples/s]
Generating train split: 7590122 examples [22:04, 23334.87 examples/s]
Generating train split: 7593040 examples [22:05, 12856.09 examples/s]
Generating train split: 7595272 examples [22:05, 7205.71 examples/s] 
Generating train split: 7596897 examples [22:06, 4840.16 examples/s]
Generating train split: 7598105 examples [22:07, 4114.60 examples/s]
Generating train split: 7599033 examples [22:07, 4010.97 examples/s]
Generating train split: 7599797 examples [22:07, 3796.39 examples/s]
Generating train split: 7600414 examples [22:07, 3837.25 examples/s]
Generating train split: 7600987 examples [22:08, 3240.29 examples/s]
Generating train split: 7602641 examples [22:08, 4770.94 examples/s]
Generating train split: 7603417 examples [22:08, 3897.81 examples/s]
Generating train split: 7604057 examples [22:08, 3455.28 examples/s]
Generating train split: 7604557 examples [22:09, 3412.52 examples/s]
Generating train split: 7605803 examples [22:09, 4734.03 examples/s]
Generating train split: 7606483 examples [22:09, 4195.59 examples/s]
Generating train split: 7607052 examples [22:09, 3270.14 examples/s]
Generating train split: 7608061 examples [22:09, 4247.88 examples/s]
Generating train split: 7608660 examples [22:10, 3292.43 examples/s]
Generating train split: 7609153 examples [22:10, 3254.72 examples/s]
Generating train split: 7609600 examples [22:10, 2992.82 examples/s]
Generating train split: 7610329 examples [22:10, 3719.36 examples/s]
Generating train split: 7610811 examples [22:10, 3439.67 examples/s]
Generating train split: 7611243 examples [22:10, 3265.34 examples/s]
Generating train split: 7611616 examples [22:11, 3016.54 examples/s]
Generating train split: 7611951 examples [22:11, 2464.56 examples/s]
Generating train split: 7612238 examples [22:11, 2422.34 examples/s]
Generating train split: 7612514 examples [22:11, 2251.56 examples/s]
Generating train split: 7612764 examples [22:11, 2264.62 examples/s]
Generating train split: 7613032 examples [22:11, 1998.25 examples/s]
Generating train split: 7613243 examples [22:12, 1785.06 examples/s]
Generating train split: 7613494 examples [22:12, 1898.92 examples/s]
Generating train split: 7613780 examples [22:12, 2087.05 examples/s]
Generating train split: 7614029 examples [22:12, 1836.86 examples/s]
Generating train split: 7614257 examples [22:12, 1870.17 examples/s]
Generating train split: 7614551 examples [22:12, 2100.48 examples/s]
Generating train split: 7614776 examples [22:12, 2032.58 examples/s]
Generating train split: 7615100 examples [22:12, 2333.80 examples/s]
Generating train split: 7615353 examples [22:13, 2194.49 examples/s]
Generating train split: 7615603 examples [22:13, 2129.23 examples/s]
Generating train split: 7615827 examples [22:15, 328.03 examples/s] 
Generating train split: 7616159 examples [22:15, 485.16 examples/s]
Generating train split: 7616574 examples [22:15, 737.70 examples/s]
Generating train split: 7616845 examples [22:15, 903.64 examples/s]
Generating train split: 7617238 examples [22:15, 1234.19 examples/s]
Generating train split: 7617526 examples [22:16, 1190.95 examples/s]
Generating train split: 7617769 examples [22:16, 1331.49 examples/s]
Generating train split: 7618017 examples [22:16, 1462.37 examples/s]
Generating train split: 7618293 examples [22:16, 1688.50 examples/s]
Generating train split: 7618579 examples [22:16, 1895.67 examples/s]
Generating train split: 7618942 examples [22:16, 2264.47 examples/s]
Generating train split: 7619216 examples [22:16, 2169.99 examples/s]
Generating train split: 7628592 examples [22:16, 23979.74 examples/s]
Generating train split: 7631571 examples [22:17, 24098.63 examples/s]
Generating train split: 7638577 examples [22:17, 35826.22 examples/s]
Generating train split: 7645418 examples [22:17, 44364.79 examples/s]
Generating train split: 7651631 examples [22:17, 47019.36 examples/s]
Generating train split: 7656636 examples [22:19, 6904.64 examples/s] 
Generating train split: 7660210 examples [22:21, 4634.63 examples/s]
Generating train split: 7662786 examples [22:22, 3808.92 examples/s]
Generating train split: 7664675 examples [22:23, 3403.60 examples/s]
Generating train split: 7666047 examples [22:23, 3209.31 examples/s]
Generating train split: 7667120 examples [22:24, 3334.02 examples/s]
Generating train split: 7667971 examples [22:24, 3166.69 examples/s]
Generating train split: 7668662 examples [22:24, 3038.63 examples/s]
Generating train split: 7669207 examples [22:24, 2981.73 examples/s]
Generating train split: 7669677 examples [22:25, 2771.55 examples/s]
Generating train split: 7670056 examples [22:25, 2416.26 examples/s]
Generating train split: 7670368 examples [22:26, 1271.48 examples/s]
Generating train split: 7670595 examples [22:26, 1303.15 examples/s]
Generating train split: 7670835 examples [22:26, 1407.01 examples/s]
Generating train split: 7671075 examples [22:26, 1510.15 examples/s]
Generating train split: 7671297 examples [22:26, 1599.26 examples/s]
Generating train split: 7671611 examples [22:26, 1827.39 examples/s]
Generating train split: 7671849 examples [22:27, 1870.36 examples/s]
Generating train split: 7672148 examples [22:27, 2062.03 examples/s]
Generating train split: 7672435 examples [22:27, 2195.27 examples/s]
Generating train split: 7672682 examples [22:27, 2181.03 examples/s]
Generating train split: 7672939 examples [22:27, 2240.07 examples/s]
Generating train split: 7673197 examples [22:27, 2246.75 examples/s]
Generating train split: 7673436 examples [22:27, 2180.51 examples/s]
Generating train split: 7673661 examples [22:27, 2064.91 examples/s]
Generating train split: 7673888 examples [22:28, 1899.07 examples/s]
Generating train split: 7674111 examples [22:28, 1729.76 examples/s]
Generating train split: 7674336 examples [22:28, 1839.94 examples/s]
Generating train split: 7674597 examples [22:28, 1981.22 examples/s]
Generating train split: 7674836 examples [22:28, 1634.72 examples/s]
Generating train split: 7695470 examples [22:28, 47753.97 examples/s]
Generating train split: 7711695 examples [22:28, 75605.05 examples/s]
Generating train split: 7720973 examples [22:29, 53089.18 examples/s]
Generating train split: 7739674 examples [22:29, 79394.16 examples/s]
Generating train split: 7760502 examples [22:29, 107619.40 examples/s]
Generating train split: 7774314 examples [22:29, 73139.74 examples/s] 
Generating train split: 7785205 examples [22:29, 58824.33 examples/s]
Generating train split: 7805316 examples [22:30, 81363.55 examples/s]
Generating train split: 7824379 examples [22:30, 101332.43 examples/s]
Generating train split: 7838535 examples [22:30, 54191.38 examples/s] 
Generating train split: 7849168 examples [22:30, 59760.81 examples/s]
Generating train split: 7864010 examples [22:30, 72880.72 examples/s]
Generating train split: 7875488 examples [22:31, 59309.50 examples/s]
Generating train split: 7884664 examples [22:31, 63650.53 examples/s]
Generating train split: 7893645 examples [22:31, 63114.38 examples/s]
Generating train split: 7901788 examples [22:31, 43872.55 examples/s]
Generating train split: 7908175 examples [22:32, 46766.51 examples/s]
Generating train split: 7916249 examples [22:32, 52808.97 examples/s]
Generating train split: 7923100 examples [22:32, 46989.11 examples/s]
Generating train split: 7928948 examples [22:32, 41053.87 examples/s]
Generating train split: 7944727 examples [22:32, 63193.95 examples/s]
Generating train split: 7960540 examples [22:32, 83409.34 examples/s]
Generating train split: 7971021 examples [22:32, 73840.87 examples/s]
Generating train split: 7980090 examples [22:33, 64247.68 examples/s]
Generating train split: 7999814 examples [22:33, 91513.08 examples/s]
Generating train split: 8013579 examples [22:33, 101755.90 examples/s]
Generating train split: 8025612 examples [22:33, 62285.60 examples/s] 
Generating train split: 8034983 examples [22:33, 54025.78 examples/s]
Generating train split: 8042669 examples [22:34, 45276.78 examples/s]
Generating train split: 8062055 examples [22:34, 68130.95 examples/s]
Generating train split: 8077609 examples [22:34, 83851.39 examples/s]
Generating train split: 8089399 examples [22:34, 60916.00 examples/s]
Generating train split: 8098686 examples [22:35, 44709.08 examples/s]
Generating train split: 8105922 examples [22:35, 36452.13 examples/s]
Generating train split: 8120339 examples [22:35, 50233.37 examples/s]
Generating train split: 8139464 examples [22:35, 72026.08 examples/s]
Generating train split: 8151774 examples [22:35, 79837.26 examples/s]
Generating train split: 8163242 examples [22:35, 73581.00 examples/s]
Generating train split: 8183846 examples [22:36, 99620.43 examples/s]
Generating train split: 8199954 examples [22:36, 113093.31 examples/s]
Generating train split: 8213925 examples [22:36, 56477.41 examples/s] 
Generating train split: 8224459 examples [22:37, 48607.41 examples/s]
Generating train split: 8232824 examples [22:37, 43851.29 examples/s]
Generating train split: 8239649 examples [22:37, 38375.44 examples/s]
Generating train split: 8245183 examples [22:37, 33588.38 examples/s]
Generating train split: 8249954 examples [22:37, 35491.09 examples/s]
Generating train split: 8254565 examples [22:38, 34645.40 examples/s]
Generating train split: 8260626 examples [22:38, 39058.05 examples/s]
Generating train split: 8265304 examples [22:38, 32415.30 examples/s]
Generating train split: 8270016 examples [22:38, 35162.53 examples/s]
Generating train split: 8274179 examples [22:38, 32348.15 examples/s]
Generating train split: 8291990 examples [22:38, 63095.67 examples/s]
Generating train split: 8311101 examples [22:38, 92721.59 examples/s]
Generating train split: 8322370 examples [22:39, 58979.79 examples/s]
Generating train split: 8339225 examples [22:39, 78313.20 examples/s]
Generating train split: 8360823 examples [22:39, 106026.36 examples/s]
Generating train split: 8375165 examples [22:39, 89718.24 examples/s] 
Generating train split: 8387126 examples [22:40, 45364.93 examples/s]
Generating train split: 8396069 examples [22:40, 45936.78 examples/s]
Generating train split: 8403768 examples [22:40, 41748.78 examples/s]
Generating train split: 8421517 examples [22:40, 60421.61 examples/s]
Generating train split: 8436612 examples [22:40, 75281.91 examples/s]
Generating train split: 8447997 examples [22:41, 65041.95 examples/s]
Generating train split: 8459914 examples [22:41, 74574.11 examples/s]
Generating train split: 8471843 examples [22:41, 83292.25 examples/s]
Generating train split: 8482488 examples [22:41, 63654.52 examples/s]
Generating train split: 8500571 examples [22:41, 85471.75 examples/s]
Generating train split: 8519958 examples [22:41, 108244.35 examples/s]
Generating train split: 8533781 examples [22:41, 108282.90 examples/s]
Generating train split: 8546731 examples [22:42, 57316.75 examples/s] 
Generating train split: 8556567 examples [22:42, 54620.38 examples/s]
Generating train split: 8564861 examples [22:43, 35574.47 examples/s]
Generating train split: 8571133 examples [22:43, 27493.17 examples/s]
Generating train split: 8576995 examples [22:43, 30736.32 examples/s]
Generating train split: 8582106 examples [22:43, 32519.05 examples/s]
Generating train split: 8586963 examples [22:44, 28838.80 examples/s]
Generating train split: 8590967 examples [22:44, 30085.92 examples/s]
Generating train split: 8606331 examples [22:44, 52010.35 examples/s]
Generating train split: 8624854 examples [22:44, 78951.77 examples/s]
Generating train split: 8635552 examples [22:44, 50616.15 examples/s]
Generating train split: 8643848 examples [22:45, 48634.30 examples/s]
Generating train split: 8650938 examples [22:45, 47140.87 examples/s]
Generating train split: 8664542 examples [22:45, 62772.84 examples/s]
Generating train split: 8684264 examples [22:45, 89757.24 examples/s]
Generating train split: 8696096 examples [22:45, 82128.79 examples/s]
Generating train split: 8706399 examples [22:45, 65308.39 examples/s]
Generating train split: 8714844 examples [22:46, 44809.83 examples/s]
Generating train split: 8721409 examples [22:46, 43745.55 examples/s]
Generating train split: 8738668 examples [22:46, 64613.85 examples/s]
Generating train split: 8753262 examples [22:46, 79872.49 examples/s]
Generating train split: 8764096 examples [22:47, 47435.86 examples/s]
Generating train split: 8779096 examples [22:47, 62102.91 examples/s]
Generating train split: 8798178 examples [22:47, 83927.15 examples/s]
Generating train split: 8811088 examples [22:47, 57632.72 examples/s]
Generating train split: 8821071 examples [22:48, 48082.31 examples/s]
Generating train split: 8838080 examples [22:48, 64789.19 examples/s]
Generating train split: 8850809 examples [22:48, 75015.55 examples/s]
Generating train split: 8862098 examples [22:48, 61881.91 examples/s]
Generating train split: 8871222 examples [22:48, 46548.55 examples/s]
Generating train split: 8878395 examples [22:49, 35847.53 examples/s]
Generating train split: 8883994 examples [22:49, 32170.46 examples/s]
Generating train split: 8888571 examples [22:49, 31499.03 examples/s]
Generating train split: 8892633 examples [22:49, 27121.25 examples/s]
Generating train split: 8899032 examples [22:49, 32634.62 examples/s]
Generating train split: 8911355 examples [22:50, 48608.33 examples/s]
Generating train split: 8918653 examples [22:50, 53209.30 examples/s]
Generating train split: 8925466 examples [22:50, 34550.30 examples/s]
Generating train split: 8930763 examples [22:50, 37037.66 examples/s]
Generating train split: 8942095 examples [22:50, 51248.15 examples/s]
Generating train split: 8957846 examples [22:50, 73586.11 examples/s]
Generating train split: 8974214 examples [22:50, 94383.69 examples/s]
Generating train split: 8989238 examples [22:51, 108234.10 examples/s]
Generating train split: 9004137 examples [22:51, 118854.97 examples/s]
Generating train split: 9020722 examples [22:51, 131609.45 examples/s]
Generating train split: 9038207 examples [22:51, 143684.63 examples/s]
Generating train split: 9054851 examples [22:51, 150154.56 examples/s]
Generating train split: 9071222 examples [22:51, 154081.37 examples/s]
Generating train split: 9089015 examples [22:51, 161015.79 examples/s]
Generating train split: 9110178 examples [22:51, 175899.34 examples/s]
Generating train split: 9128975 examples [22:51, 179466.87 examples/s]
Generating train split: 9147145 examples [22:52, 168432.70 examples/s]
Generating train split: 9164277 examples [22:52, 165681.41 examples/s]
Generating train split: 9181041 examples [22:52, 106981.32 examples/s]
Generating train split: 9194499 examples [22:52, 85419.11 examples/s] 
Generating train split: 9205508 examples [22:53, 50753.28 examples/s]
Generating train split: 9213859 examples [22:53, 43437.34 examples/s]
Generating train split: 9220517 examples [22:53, 36451.78 examples/s]
Generating train split: 9225808 examples [22:54, 33787.79 examples/s]
Generating train split: 9230271 examples [22:54, 35253.47 examples/s]
Generating train split: 9234749 examples [22:54, 32491.07 examples/s]
Generating train split: 9245689 examples [22:54, 45518.94 examples/s]
Generating train split: 9258365 examples [22:54, 60605.76 examples/s]
Generating train split: 9266147 examples [22:54, 42793.92 examples/s]
Generating train split: 9273857 examples [22:54, 48612.02 examples/s]
Generating train split: 9280462 examples [22:55, 29446.09 examples/s]
Generating train split: 9285508 examples [22:55, 22036.47 examples/s]
Generating train split: 9290671 examples [22:55, 25487.36 examples/s]
Generating train split: 9294933 examples [22:56, 18113.71 examples/s]
Generating train split: 9300823 examples [22:56, 22875.70 examples/s]
Generating train split: 9304875 examples [22:56, 17449.10 examples/s]
Generating train split: 9308189 examples [22:57, 19377.39 examples/s]
Generating train split: 9311367 examples [22:57, 19101.55 examples/s]
Generating train split: 9314153 examples [22:57, 13913.62 examples/s]
Generating train split: 9316318 examples [22:57, 14903.13 examples/s]
Generating train split: 9318451 examples [22:58, 10109.21 examples/s]
Generating train split: 9320190 examples [22:58, 11019.05 examples/s]
Generating train split: 9322008 examples [22:58, 12040.72 examples/s]
Generating train split: 9323719 examples [22:58, 12307.05 examples/s]
Generating train split: 9328261 examples [22:58, 18369.90 examples/s]
Generating train split: 9332579 examples [22:58, 23591.17 examples/s]
Generating train split: 9337468 examples [22:58, 29440.64 examples/s]
Generating train split: 9345572 examples [22:58, 42333.56 examples/s]
Generating train split: 9364754 examples [22:59, 81650.33 examples/s]
Generating train split: 9379102 examples [22:59, 98521.36 examples/s]
Generating train split: 9389827 examples [22:59, 62309.24 examples/s]
Generating train split: 9398334 examples [22:59, 59500.68 examples/s]
Generating train split: 9405872 examples [22:59, 49751.81 examples/s]
Generating train split: 9412142 examples [23:00, 36956.08 examples/s]
Generating train split: 9417119 examples [23:00, 38631.38 examples/s]
Generating train split: 9422010 examples [23:00, 37526.89 examples/s]
Generating train split: 9426464 examples [23:00, 37445.84 examples/s]
Generating train split: 9430925 examples [23:00, 38955.18 examples/s]
Generating train split: 9435238 examples [23:00, 34242.97 examples/s]
Generating train split: 9439570 examples [23:00, 36238.19 examples/s]
Generating train split: 9443526 examples [23:01, 31002.76 examples/s]
Generating train split: 9446935 examples [23:01, 29556.66 examples/s]
Generating train split: 9450177 examples [23:01, 30205.60 examples/s]
Generating train split: 9463668 examples [23:01, 56021.32 examples/s]
Generating train split: 9481006 examples [23:01, 86565.59 examples/s]
Generating train split: 9490855 examples [23:01, 88932.64 examples/s]
Generating train split: 9500431 examples [23:01, 55549.37 examples/s]
Generating train split: 9508009 examples [23:02, 48648.66 examples/s]
Generating train split: 9515975 examples [23:02, 54396.21 examples/s]
Generating train split: 9523781 examples [23:02, 59345.83 examples/s]
Generating train split: 9533828 examples [23:02, 68535.62 examples/s]
Generating train split: 9541794 examples [23:02, 56434.46 examples/s]
Generating train split: 9548545 examples [23:02, 58217.21 examples/s]
Generating train split: 9555192 examples [23:02, 58105.78 examples/s]
Generating train split: 9562319 examples [23:03, 61327.38 examples/s]
Generating train split: 9580412 examples [23:03, 92361.02 examples/s]
Generating train split: 9598805 examples [23:03, 117120.97 examples/s]
Generating train split: 9611378 examples [23:03, 74407.20 examples/s] 
Generating train split: 9621353 examples [23:03, 68301.52 examples/s]
Generating train split: 9629985 examples [23:03, 71742.35 examples/s]
Generating train split: 9638617 examples [23:04, 57444.34 examples/s]
Generating train split: 9645731 examples [23:04, 51548.63 examples/s]
Generating train split: 9651861 examples [23:04, 52461.24 examples/s]
Generating train split: 9658054 examples [23:04, 54458.25 examples/s]
Generating train split: 9670054 examples [23:04, 69664.57 examples/s]
Generating train split: 9677876 examples [23:04, 57840.66 examples/s]
Generating train split: 9687191 examples [23:04, 65616.59 examples/s]
Generating train split: 9694643 examples [23:05, 60182.67 examples/s]
Generating train split: 9701373 examples [23:05, 61845.47 examples/s]
Generating train split: 9708891 examples [23:05, 65172.30 examples/s]
Generating train split: 9715834 examples [23:05, 44813.28 examples/s]
Generating train split: 9721447 examples [23:05, 45461.93 examples/s]
Generating train split: 9731032 examples [23:05, 56397.28 examples/s]
Generating train split: 9738658 examples [23:05, 60985.51 examples/s]
Generating train split: 9749131 examples [23:05, 72044.72 examples/s]
Generating train split: 9766643 examples [23:06, 99394.73 examples/s]
Generating train split: 9783384 examples [23:06, 118043.69 examples/s]
Generating train split: 9795998 examples [23:06, 72501.83 examples/s] 
Generating train split: 9805945 examples [23:06, 72268.21 examples/s]
Generating train split: 9815078 examples [23:06, 74069.81 examples/s]
Generating train split: 9823870 examples [23:07, 49881.42 examples/s]
Generating train split: 9830790 examples [23:07, 45968.08 examples/s]
Generating train split: 9836937 examples [23:07, 48654.89 examples/s]
Generating train split: 9842933 examples [23:07, 42451.20 examples/s]
Generating train split: 9848027 examples [23:07, 35485.87 examples/s]
Generating train split: 9853175 examples [23:07, 38361.87 examples/s]
Generating train split: 9858351 examples [23:07, 41051.22 examples/s]
Generating train split: 9867198 examples [23:08, 51775.39 examples/s]
Generating train split: 9873145 examples [23:09, 14056.27 examples/s]
Generating train split: 9877450 examples [23:09, 13514.98 examples/s]
Generating train split: 9880819 examples [23:09, 14732.72 examples/s]
Generating train split: 9883892 examples [23:09, 15971.36 examples/s]
Generating train split: 9886748 examples [23:10, 17255.72 examples/s]
Generating train split: 9889495 examples [23:10, 16467.49 examples/s]
Generating train split: 9891859 examples [23:10, 16849.85 examples/s]
Generating train split: 9896256 examples [23:10, 21763.47 examples/s]
Generating train split: 9911070 examples [23:10, 47773.32 examples/s]
Generating train split: 9926892 examples [23:10, 71844.67 examples/s]
Generating train split: 9935892 examples [23:10, 56177.88 examples/s]
Generating train split: 9943272 examples [23:11, 49931.18 examples/s]
Generating train split: 9959060 examples [23:11, 71003.56 examples/s]
Generating train split: 9973533 examples [23:11, 87074.21 examples/s]
Generating train split: 9984267 examples [23:11, 57354.26 examples/s]
Generating train split: 9992710 examples [23:11, 47809.56 examples/s]
Generating train split: 10008221 examples [23:12, 65113.27 examples/s]
Generating train split: 10022793 examples [23:12, 80083.69 examples/s]
Generating train split: 10033740 examples [23:12, 49778.29 examples/s]
Generating train split: 10042150 examples [23:12, 53531.37 examples/s]
Generating train split: 10051024 examples [23:12, 59024.86 examples/s]
Generating train split: 10059179 examples [23:13, 45288.81 examples/s]
Generating train split: 10065706 examples [23:13, 46397.80 examples/s]
Generating train split: 10072569 examples [23:13, 50469.52 examples/s]
Generating train split: 10082140 examples [23:13, 59901.08 examples/s]
Generating train split: 10090109 examples [23:13, 64094.80 examples/s]
Generating train split: 10097563 examples [23:13, 50243.82 examples/s]
Generating train split: 10103732 examples [23:13, 50078.09 examples/s]
Generating train split: 10109556 examples [23:14, 49913.62 examples/s]
Generating train split: 10115873 examples [23:14, 52933.60 examples/s]
Generating train split: 10128786 examples [23:14, 71942.50 examples/s]
Generating train split: 10143114 examples [23:14, 90692.66 examples/s]
Generating train split: 10152954 examples [23:14, 53977.74 examples/s]
Generating train split: 10160660 examples [23:14, 55919.06 examples/s]
Generating train split: 10175753 examples [23:14, 75125.05 examples/s]
Generating train split: 10188659 examples [23:15, 86211.79 examples/s]
Generating train split: 10199076 examples [23:15, 76966.79 examples/s]
Generating train split: 10208167 examples [23:15, 65036.20 examples/s]
Generating train split: 10215910 examples [23:15, 56091.23 examples/s]
Generating train split: 10222475 examples [23:15, 56748.92 examples/s]
Generating train split: 10228864 examples [23:15, 56650.50 examples/s]
Generating train split: 10236909 examples [23:15, 58790.92 examples/s]
Generating train split: 10243149 examples [23:16, 34961.12 examples/s]
Generating train split: 10248895 examples [23:16, 38696.41 examples/s]
Generating train split: 10254024 examples [23:16, 32294.28 examples/s]
Generating train split: 10262046 examples [23:16, 40743.61 examples/s]
Generating train split: 10276015 examples [23:16, 60697.12 examples/s]
Generating train split: 10283948 examples [23:17, 46523.36 examples/s]
Generating train split: 10290363 examples [23:17, 40275.26 examples/s]
Generating train split: 10295708 examples [23:17, 29414.06 examples/s]
Generating train split: 10299899 examples [23:17, 28949.89 examples/s]
Generating train split: 10304378 examples [23:18, 31544.06 examples/s]
Generating train split: 10308349 examples [23:18, 24800.68 examples/s]
Generating train split: 10311562 examples [23:18, 22925.17 examples/s]
Generating train split: 10314343 examples [23:18, 16839.18 examples/s]
Generating train split: 10316544 examples [23:18, 16106.47 examples/s]
Generating train split: 10318525 examples [23:19, 16461.68 examples/s]
Generating train split: 10320443 examples [23:19, 13928.59 examples/s]
Generating train split: 10322933 examples [23:19, 15725.03 examples/s]
Generating train split: 10327455 examples [23:19, 21398.99 examples/s]
Generating train split: 10329999 examples [23:19, 19917.93 examples/s]
Generating train split: 10332291 examples [23:19, 17191.35 examples/s]
Generating train split: 10337091 examples [23:19, 23619.07 examples/s]
Generating train split: 10344634 examples [23:20, 35504.16 examples/s]
Generating train split: 10352795 examples [23:20, 46736.70 examples/s]
Generating train split: 10358188 examples [23:20, 34000.44 examples/s]
Generating train split: 10363278 examples [23:20, 37478.98 examples/s]
Generating train split: 10370783 examples [23:20, 46024.74 examples/s]
Generating train split: 10384846 examples [23:20, 69226.02 examples/s]
Generating train split: 10397765 examples [23:20, 84759.07 examples/s]
Generating train split: 10407269 examples [23:21, 69801.26 examples/s]
Generating train split: 10415392 examples [23:21, 55247.96 examples/s]
Generating train split: 10422133 examples [23:21, 52208.46 examples/s]
Generating train split: 10428191 examples [23:21, 52989.60 examples/s]
Generating train split: 10436464 examples [23:21, 59595.35 examples/s]
Generating train split: 10443073 examples [23:21, 48407.50 examples/s]
Generating train split: 10448648 examples [23:22, 35059.25 examples/s]
Generating train split: 10455133 examples [23:22, 40358.25 examples/s]
Generating train split: 10466500 examples [23:22, 55206.48 examples/s]
Generating train split: 10473475 examples [23:22, 36234.62 examples/s]
Generating train split: 10479993 examples [23:22, 40635.56 examples/s]
Generating train split: 10485659 examples [23:22, 42534.93 examples/s]
Generating train split: 10492500 examples [23:23, 46320.45 examples/s]
Generating train split: 10498077 examples [23:23, 37424.50 examples/s]
Generating train split: 10502730 examples [23:23, 38957.38 examples/s]
Generating train split: 10508968 examples [23:23, 44087.25 examples/s]
Generating train split: 10517589 examples [23:23, 54131.92 examples/s]
Generating train split: 10532813 examples [23:23, 79061.98 examples/s]
Generating train split: 10544969 examples [23:23, 90380.63 examples/s]
Generating train split: 10554822 examples [23:24, 47292.63 examples/s]
Generating train split: 10562391 examples [23:24, 45585.98 examples/s]
Generating train split: 10568916 examples [23:24, 35562.45 examples/s]
Generating train split: 10574115 examples [23:24, 37307.54 examples/s]
Generating train split: 10579829 examples [23:24, 40779.74 examples/s]
Generating train split: 10585044 examples [23:25, 37701.38 examples/s]
Generating train split: 10589614 examples [23:25, 27046.96 examples/s]
Generating train split: 10594523 examples [23:25, 30673.12 examples/s]
Generating train split: 10599060 examples [23:25, 33100.81 examples/s]
Generating train split: 10603149 examples [23:25, 29147.61 examples/s]
Generating train split: 10606866 examples [23:25, 30753.17 examples/s]
Generating train split: 10610454 examples [23:26, 29169.55 examples/s]
Generating train split: 10614775 examples [23:26, 32336.96 examples/s]
Generating train split: 10618375 examples [23:26, 23858.04 examples/s]
Generating train split: 10621305 examples [23:26, 24592.14 examples/s]
Generating train split: 10624175 examples [23:26, 24504.00 examples/s]
Generating train split: 10626910 examples [23:26, 23267.77 examples/s]
Generating train split: 10629428 examples [23:26, 22319.63 examples/s]
Generating train split: 10632560 examples [23:26, 24469.34 examples/s]
Generating train split: 10635701 examples [23:27, 26225.75 examples/s]
Generating train split: 10638541 examples [23:27, 26773.87 examples/s]
Generating train split: 10642313 examples [23:27, 29783.55 examples/s]
Generating train split: 10646065 examples [23:27, 31922.48 examples/s]
Generating train split: 10649348 examples [23:27, 18886.96 examples/s]
Generating train split: 10655946 examples [23:27, 28015.33 examples/s]
Generating train split: 10666383 examples [23:27, 44577.30 examples/s]
Generating train split: 10672165 examples [23:28, 42430.85 examples/s]
Generating train split: 10677349 examples [23:28, 37090.35 examples/s]
Generating train split: 10682413 examples [23:28, 40005.23 examples/s]
Generating train split: 10687050 examples [23:28, 40407.05 examples/s]
Generating train split: 10692402 examples [23:28, 43634.56 examples/s]
Generating train split: 10697170 examples [23:28, 25101.00 examples/s]
Generating train split: 10702068 examples [23:29, 29221.57 examples/s]
Generating train split: 10707020 examples [23:29, 33207.88 examples/s]
Generating train split: 10711337 examples [23:29, 20469.04 examples/s]
Generating train split: 10714663 examples [23:29, 22196.48 examples/s]
Generating train split: 10717919 examples [23:29, 19233.71 examples/s]
Generating train split: 10720624 examples [23:30, 19342.22 examples/s]
Generating train split: 10723895 examples [23:30, 21799.49 examples/s]
Generating train split: 10727554 examples [23:30, 24853.84 examples/s]
Generating train split: 10730554 examples [23:30, 16049.22 examples/s]
Generating train split: 10734440 examples [23:30, 19743.77 examples/s]
Generating train split: 10737460 examples [23:30, 21756.75 examples/s]
Generating train split: 10740311 examples [23:31, 19565.75 examples/s]
Generating train split: 10742753 examples [23:31, 19442.71 examples/s]
Generating train split: 10745039 examples [23:31, 18458.45 examples/s]
Generating train split: 10758513 examples [23:31, 44221.28 examples/s]
Generating train split: 10773888 examples [23:31, 70539.07 examples/s]
Generating train split: 10782345 examples [23:31, 52311.18 examples/s]
Generating train split: 10789249 examples [23:32, 34726.48 examples/s]
Generating train split: 10803528 examples [23:32, 51388.94 examples/s]
Generating train split: 10817982 examples [23:32, 67728.72 examples/s]
Generating train split: 10827779 examples [23:32, 41628.51 examples/s]
Generating train split: 10835255 examples [23:32, 46243.89 examples/s]
Generating train split: 10846316 examples [23:33, 57014.93 examples/s]
Generating train split: 10854847 examples [23:33, 48109.56 examples/s]
Generating train split: 10861824 examples [23:33, 49281.64 examples/s]
Generating train split: 10872254 examples [23:33, 59833.09 examples/s]
Generating train split: 10886407 examples [23:33, 77391.69 examples/s]
Generating train split: 10897604 examples [23:33, 85508.54 examples/s]
Generating train split: 10907717 examples [23:34, 61716.20 examples/s]
Generating train split: 10915890 examples [23:34, 45659.90 examples/s]
Generating train split: 10923949 examples [23:34, 51401.98 examples/s]
Generating train split: 10930896 examples [23:34, 44696.01 examples/s]
Generating train split: 10936717 examples [23:34, 34403.80 examples/s]
Generating train split: 10941375 examples [23:35, 36313.71 examples/s]
Generating train split: 10946041 examples [23:35, 25699.33 examples/s]
Generating train split: 10949681 examples [23:35, 27185.18 examples/s]
Generating train split: 10954582 examples [23:35, 31029.55 examples/s]
Generating train split: 10958580 examples [23:35, 26819.89 examples/s]
Generating train split: 10961951 examples [23:36, 26893.78 examples/s]
Generating train split: 10975467 examples [23:36, 49227.44 examples/s]
Generating train split: 10990099 examples [23:36, 71318.09 examples/s]
Generating train split: 10998886 examples [23:36, 42858.60 examples/s]
Generating train split: 11005681 examples [23:36, 35820.13 examples/s]
Generating train split: 11011145 examples [23:37, 37223.75 examples/s]
Generating train split: 11016283 examples [23:37, 22932.59 examples/s]
Generating train split: 11020956 examples [23:37, 25917.12 examples/s]
Generating train split: 11035951 examples [23:37, 44771.24 examples/s]
Generating train split: 11048605 examples [23:37, 59353.30 examples/s]
Generating train split: 11057582 examples [23:38, 37043.52 examples/s]
Generating train split: 11064431 examples [23:38, 26224.40 examples/s]
Generating train split: 11069631 examples [23:39, 21562.16 examples/s]
Generating train split: 11073644 examples [23:39, 23420.63 examples/s]
Generating train split: 11077611 examples [23:39, 24891.69 examples/s]
Generating train split: 11081373 examples [23:39, 21768.18 examples/s]
Generating train split: 11084463 examples [23:40, 17061.04 examples/s]
Generating train split: 11086895 examples [23:40, 13372.11 examples/s]
Generating train split: 11088811 examples [23:40, 9789.28 examples/s] 
Generating train split: 11090295 examples [23:41, 9369.24 examples/s]
Generating train split: 11093813 examples [23:41, 12631.86 examples/s]
Generating train split: 11095759 examples [23:41, 9201.73 examples/s] 
Generating train split: 11100976 examples [23:41, 14695.06 examples/s]
Generating train split: 11103582 examples [23:41, 14055.34 examples/s]
Generating train split: 11105778 examples [23:42, 14808.06 examples/s]
Generating train split: 11107868 examples [23:42, 13409.49 examples/s]
Generating train split: 11110647 examples [23:42, 15567.55 examples/s]
Generating train split: 11112633 examples [23:42, 13858.60 examples/s]
Generating train split: 11114337 examples [23:42, 12879.94 examples/s]
Generating train split: 11115851 examples [23:42, 12249.08 examples/s]
Generating train split: 11117218 examples [23:42, 11278.71 examples/s]
Generating train split: 11118638 examples [23:43, 11868.44 examples/s]
Generating train split: 11119928 examples [23:43, 6853.04 examples/s] 
Generating train split: 11122970 examples [23:43, 10542.02 examples/s]
Generating train split: 11124574 examples [23:43, 9931.71 examples/s] 
Generating train split: 11127388 examples [23:43, 13128.69 examples/s]
Generating train split: 11129150 examples [23:44, 11000.69 examples/s]
Generating train split: 11131977 examples [23:44, 14229.55 examples/s]
Generating train split: 11133858 examples [23:44, 11063.92 examples/s]
Generating train split: 11137033 examples [23:44, 14785.05 examples/s]
Generating train split: 11140179 examples [23:44, 18190.03 examples/s]
Generating train split: 11143090 examples [23:44, 20519.65 examples/s]
Generating train split: 11146001 examples [23:44, 22582.83 examples/s]
Generating train split: 11148617 examples [23:45, 21842.09 examples/s]
Generating train split: 11152164 examples [23:45, 25306.50 examples/s]
Generating train split: 11157024 examples [23:45, 31481.03 examples/s]
Generating train split: 11160432 examples [23:45, 28902.21 examples/s]
Generating train split: 11163545 examples [23:45, 19973.09 examples/s]
Generating train split: 11167467 examples [23:45, 23845.24 examples/s]
Generating train split: 11170407 examples [23:45, 22643.39 examples/s]
Generating train split: 11173677 examples [23:46, 24264.67 examples/s]
Generating train split: 11177527 examples [23:46, 27636.99 examples/s]
Generating train split: 11190846 examples [23:46, 54375.14 examples/s]
Generating train split: 11201840 examples [23:46, 67978.86 examples/s]
Generating train split: 11209249 examples [23:46, 35648.25 examples/s]
Generating train split: 11214926 examples [23:47, 24957.69 examples/s]
Generating train split: 11219286 examples [23:47, 25019.52 examples/s]
Generating train split: 11223119 examples [23:47, 23855.78 examples/s]
Generating train split: 11226412 examples [23:47, 23678.23 examples/s]
Generating train split: 11230064 examples [23:47, 25838.69 examples/s]
Generating train split: 11233234 examples [23:48, 22040.57 examples/s]
Generating train split: 11235897 examples [23:48, 22749.49 examples/s]
Generating train split: 11238538 examples [23:48, 19937.34 examples/s]
Generating train split: 11241228 examples [23:48, 21334.37 examples/s]
Generating train split: 11251167 examples [23:48, 38849.50 examples/s]
Generating train split: 11265040 examples [23:48, 63077.06 examples/s]
Generating train split: 11272478 examples [23:48, 64788.48 examples/s]
Generating train split: 11279761 examples [23:49, 42868.65 examples/s]
Generating train split: 11285586 examples [23:49, 40304.36 examples/s]
Generating train split: 11296770 examples [23:49, 54384.52 examples/s]
Generating train split: 11307021 examples [23:49, 64733.41 examples/s]
Generating train split: 11314892 examples [23:49, 33903.01 examples/s]
Generating train split: 11320874 examples [23:50, 35671.29 examples/s]
Generating train split: 11336283 examples [23:50, 55079.86 examples/s]
Generating train split: 11348432 examples [23:50, 66537.10 examples/s]
Generating train split: 11357688 examples [23:50, 42097.33 examples/s]
Generating train split: 11369733 examples [23:50, 53805.20 examples/s]
Generating train split: 11382171 examples [23:50, 65398.59 examples/s]
Generating train split: 11391685 examples [23:51, 35763.18 examples/s]
Generating train split: 11402143 examples [23:51, 44339.99 examples/s]
Generating train split: 11416330 examples [23:51, 59073.63 examples/s]
Generating train split: 11426275 examples [23:52, 51860.30 examples/s]
Generating train split: 11434397 examples [23:52, 38068.67 examples/s]
Generating train split: 11440718 examples [23:52, 33278.29 examples/s]
Generating train split: 11445804 examples [23:53, 25158.29 examples/s]
Generating train split: 11450318 examples [23:53, 27561.02 examples/s]
Generating train split: 11454436 examples [23:53, 24163.53 examples/s]
Generating train split: 11457812 examples [23:53, 21671.04 examples/s]
Generating train split: 11460636 examples [23:53, 17530.24 examples/s]
Generating train split: 11462915 examples [23:54, 14583.96 examples/s]
Generating train split: 11466783 examples [23:54, 17923.05 examples/s]
Generating train split: 11474918 examples [23:54, 28463.79 examples/s]
Generating train split: 11488823 examples [23:54, 49670.35 examples/s]
Generating train split: 11496489 examples [23:54, 54522.60 examples/s]
Generating train split: 11503571 examples [23:55, 36682.56 examples/s]
Generating train split: 11516933 examples [23:55, 53403.98 examples/s]
Generating train split: 11527831 examples [23:55, 64300.91 examples/s]
Generating train split: 11536605 examples [23:55, 47095.09 examples/s]
Generating train split: 11543583 examples [23:56, 29927.87 examples/s]
Generating train split: 11548881 examples [23:56, 27566.20 examples/s]
Generating train split: 11561563 examples [23:56, 40769.38 examples/s]
Generating train split: 11570896 examples [23:56, 49147.55 examples/s]
Generating train split: 11578492 examples [23:56, 35352.89 examples/s]
Generating train split: 11584401 examples [23:57, 26960.01 examples/s]
Generating train split: 11588996 examples [23:57, 27007.98 examples/s]
Generating train split: 11593371 examples [23:57, 29408.01 examples/s]
Generating train split: 11597496 examples [23:57, 21203.49 examples/s]
Generating train split: 11606167 examples [23:58, 30429.83 examples/s]
Generating train split: 11619730 examples [23:58, 48055.42 examples/s]
Generating train split: 11629369 examples [23:58, 57331.40 examples/s]
Generating train split: 11637493 examples [23:58, 32363.02 examples/s]
Generating train split: 11643628 examples [23:58, 30511.23 examples/s]
Generating train split: 11648705 examples [23:59, 30084.61 examples/s]
Generating train split: 11653408 examples [23:59, 31703.61 examples/s]
Generating train split: 11657678 examples [23:59, 26183.57 examples/s]
Generating train split: 11661147 examples [23:59, 18798.92 examples/s]
Generating train split: 11675849 examples [24:00, 36434.99 examples/s]
Generating train split: 11692172 examples [24:00, 57253.73 examples/s]
Generating train split: 11701503 examples [24:00, 45500.98 examples/s]
Generating train split: 11708921 examples [24:01, 27610.60 examples/s]
Generating train split: 11714484 examples [24:01, 20716.20 examples/s]
Generating train split: 11718699 examples [24:01, 21587.35 examples/s]
Generating train split: 11732902 examples [24:01, 35654.32 examples/s]
Generating train split: 11745815 examples [24:01, 48894.73 examples/s]
Generating train split: 11754435 examples [24:02, 27855.08 examples/s]
Generating train split: 11764385 examples [24:02, 35641.57 examples/s]
Generating train split: 11777579 examples [24:02, 48586.18 examples/s]
Generating train split: 11786786 examples [24:03, 33405.27 examples/s]
Generating train split: 11793777 examples [24:03, 32629.73 examples/s]
Generating train split: 11799576 examples [24:03, 25353.49 examples/s]
Generating train split: 11804526 examples [24:04, 28150.84 examples/s]
Generating train split: 11817756 examples [24:04, 42948.52 examples/s]
Generating train split: 11831245 examples [24:04, 58258.84 examples/s]
Generating train split: 11840267 examples [24:04, 45473.13 examples/s]
Generating train split: 11847446 examples [24:04, 43760.20 examples/s]
Generating train split: 11853638 examples [24:04, 44676.10 examples/s]
Generating train split: 11867160 examples [24:05, 61704.98 examples/s]
Generating train split: 11875713 examples [24:05, 66721.21 examples/s]
Generating train split: 11883941 examples [24:05, 31292.10 examples/s]
Generating train split: 11895308 examples [24:05, 41886.73 examples/s]
Generating train split: 11908168 examples [24:05, 55338.59 examples/s]
Generating train split: 11917420 examples [24:06, 44079.93 examples/s]
Generating train split: 11931265 examples [24:06, 58739.98 examples/s]
Generating train split: 11945454 examples [24:06, 73586.99 examples/s]
Generating train split: 11956131 examples [24:07, 42510.76 examples/s]
Generating train split: 11965285 examples [24:07, 49093.54 examples/s]
Generating train split: 11973683 examples [24:07, 28871.13 examples/s]
Generating train split: 11980078 examples [24:07, 32667.38 examples/s]
Generating train split: 11986382 examples [24:08, 24270.99 examples/s]
Generating train split: 11991191 examples [24:08, 21411.37 examples/s]
Generating train split: 11995000 examples [24:09, 18004.52 examples/s]
Generating train split: 12004715 examples [24:09, 26781.87 examples/s]
Generating train split: 12017330 examples [24:09, 40372.56 examples/s]
Generating train split: 12024616 examples [24:09, 35868.64 examples/s]
Generating train split: 12030559 examples [24:09, 29256.46 examples/s]
Generating train split: 12035270 examples [24:10, 26903.76 examples/s]
Generating train split: 12039173 examples [24:10, 27167.46 examples/s]
Generating train split: 12042763 examples [24:10, 27597.97 examples/s]
Generating train split: 12046153 examples [24:10, 20253.58 examples/s]
Generating train split: 12049232 examples [24:10, 21745.59 examples/s]
Generating train split: 12051995 examples [24:10, 21319.24 examples/s]
Generating train split: 12054533 examples [24:11, 18238.32 examples/s]
Generating train split: 12066491 examples [24:11, 37201.62 examples/s]
Generating train split: 12080290 examples [24:11, 58457.26 examples/s]
Generating train split: 12087992 examples [24:11, 42988.91 examples/s]
Generating train split: 12101152 examples [24:11, 59357.62 examples/s]
Generating train split: 12114370 examples [24:11, 74561.94 examples/s]
Generating train split: 12124128 examples [24:12, 45513.01 examples/s]
Generating train split: 12131638 examples [24:12, 34448.99 examples/s]
Generating train split: 12137483 examples [24:12, 29162.61 examples/s]
Generating train split: 12142124 examples [24:13, 26037.08 examples/s]
Generating train split: 12145918 examples [24:13, 26538.86 examples/s]
Generating train split: 12149453 examples [24:13, 25994.32 examples/s]
Generating train split: 12152636 examples [24:13, 24950.62 examples/s]
Generating train split: 12157294 examples [24:13, 28908.52 examples/s]
Generating train split: 12160707 examples [24:13, 28213.83 examples/s]
Generating train split: 12163891 examples [24:13, 28147.49 examples/s]
Generating train split: 12168601 examples [24:14, 32482.49 examples/s]
Generating train split: 12172157 examples [24:14, 25158.35 examples/s]
Generating train split: 12175391 examples [24:14, 26582.41 examples/s]
Generating train split: 12178416 examples [24:14, 18656.21 examples/s]
Generating train split: 12180828 examples [24:14, 15883.54 examples/s]
Generating train split: 12185869 examples [24:15, 21903.26 examples/s]
Generating train split: 12188794 examples [24:15, 18045.62 examples/s]
Generating train split: 12191197 examples [24:15, 18923.85 examples/s]
Generating train split: 12194196 examples [24:15, 21170.08 examples/s]
Generating train split: 12199428 examples [24:15, 28177.86 examples/s]
Generating train split: 12207859 examples [24:15, 41833.33 examples/s]
Generating train split: 12214772 examples [24:15, 48869.00 examples/s]
Generating train split: 12225130 examples [24:15, 63582.71 examples/s]
Generating train split: 12240091 examples [24:15, 87451.98 examples/s]
Generating train split: 12254831 examples [24:16, 104441.80 examples/s]
Generating train split: 12265790 examples [24:16, 69282.55 examples/s] 
Generating train split: 12274634 examples [24:16, 69403.85 examples/s]
Generating train split: 12282935 examples [24:16, 71869.84 examples/s]
Generating train split: 12291133 examples [24:16, 54205.31 examples/s]
Generating train split: 12297852 examples [24:17, 47803.02 examples/s]
Generating train split: 12303595 examples [24:17, 46557.98 examples/s]
Generating train split: 12310057 examples [24:17, 50269.26 examples/s]
Generating train split: 12317652 examples [24:17, 56107.20 examples/s]
Generating train split: 12326381 examples [24:17, 63745.22 examples/s]
Generating train split: 12334337 examples [24:17, 67802.25 examples/s]
Generating train split: 12341621 examples [24:17, 52108.08 examples/s]
Generating train split: 12351549 examples [24:17, 62722.27 examples/s]
Generating train split: 12358778 examples [24:18, 64745.31 examples/s]
Generating train split: 12365978 examples [24:18, 58281.26 examples/s]
Generating train split: 12372569 examples [24:18, 60126.61 examples/s]
Generating train split: 12379046 examples [24:18, 58639.86 examples/s]
Generating train split: 12392026 examples [24:18, 77168.70 examples/s]
Generating train split: 12402261 examples [24:18, 83990.52 examples/s]
Generating train split: 12411097 examples [24:18, 53912.16 examples/s]
Generating train split: 12418147 examples [24:19, 47908.53 examples/s]
Generating train split: 12425273 examples [24:19, 52349.86 examples/s]
Generating train split: 12434422 examples [24:19, 60814.30 examples/s]
Generating train split: 12444424 examples [24:19, 70068.18 examples/s]
Generating train split: 12456734 examples [24:19, 83441.62 examples/s]
Generating train split: 12469054 examples [24:19, 93954.28 examples/s]
Generating train split: 12479270 examples [24:19, 77716.89 examples/s]
Generating train split: 12488055 examples [24:19, 65651.43 examples/s]
Generating train split: 12497907 examples [24:20, 72826.96 examples/s]
Generating train split: 12506123 examples [24:20, 73274.35 examples/s]
Generating train split: 12514114 examples [24:20, 68405.21 examples/s]
Generating train split: 12521453 examples [24:20, 52937.12 examples/s]
Generating train split: 12527552 examples [24:20, 51361.30 examples/s]
Generating train split: 12537824 examples [24:20, 62669.75 examples/s]
Generating train split: 12548338 examples [24:20, 72764.93 examples/s]
Generating train split: 12556418 examples [24:21, 58133.00 examples/s]
Generating train split: 12563212 examples [24:21, 54561.13 examples/s]
Generating train split: 12569351 examples [24:21, 48546.63 examples/s]
Generating train split: 12578016 examples [24:21, 56735.51 examples/s]
Generating train split: 12592088 examples [24:21, 76476.89 examples/s]
Generating train split: 12602476 examples [24:21, 83324.40 examples/s]
Generating train split: 12611668 examples [24:22, 49301.04 examples/s]
Generating train split: 12618824 examples [24:22, 44324.78 examples/s]
Generating train split: 12631658 examples [24:22, 59028.50 examples/s]
Generating train split: 12646301 examples [24:22, 76498.61 examples/s]
Generating train split: 12656349 examples [24:22, 67598.50 examples/s]
Generating train split: 12664921 examples [24:22, 50571.84 examples/s]
Generating train split: 12674282 examples [24:23, 58046.04 examples/s]
Generating train split: 12682088 examples [24:23, 61368.45 examples/s]
Generating train split: 12689645 examples [24:23, 42885.71 examples/s]
Generating train split: 12695627 examples [24:23, 44305.21 examples/s]
Generating train split: 12701321 examples [24:24, 28391.13 examples/s]
Generating train split: 12706502 examples [24:24, 31723.30 examples/s]
Generating train split: 12715254 examples [24:24, 41189.69 examples/s]
Generating train split: 12728844 examples [24:24, 59658.80 examples/s]
Generating train split: 12737906 examples [24:24, 66387.34 examples/s]
Generating train split: 12746341 examples [24:24, 69386.33 examples/s]
Generating train split: 12754608 examples [24:24, 45348.06 examples/s]
Generating train split: 12761130 examples [24:25, 46492.42 examples/s]
Generating train split: 12767203 examples [24:25, 45003.40 examples/s]
Generating train split: 12774019 examples [24:25, 49741.49 examples/s]
Generating train split: 12785902 examples [24:25, 65400.42 examples/s]
Generating train split: 12799094 examples [24:25, 81540.09 examples/s]
Generating train split: 12808413 examples [24:25, 55836.05 examples/s]
Generating train split: 12815882 examples [24:25, 55144.66 examples/s]
Generating train split: 12822701 examples [24:26, 52955.80 examples/s]
Generating train split: 12836318 examples [24:26, 70609.61 examples/s]
Generating train split: 12851782 examples [24:26, 90154.41 examples/s]
Generating train split: 12862306 examples [24:26, 85527.79 examples/s]
Generating train split: 12875210 examples [24:26, 96172.08 examples/s]
Generating train split: 12885839 examples [24:26, 93617.72 examples/s]
Generating train split: 12895908 examples [24:27, 43423.59 examples/s]
Generating train split: 12903489 examples [24:27, 30348.06 examples/s]
Generating train split: 12913704 examples [24:27, 38614.21 examples/s]
Generating train split: 12927060 examples [24:27, 52024.96 examples/s]
Generating train split: 12936046 examples [24:28, 56630.64 examples/s]
Generating train split: 12944618 examples [24:28, 59393.57 examples/s]
Generating train split: 12952676 examples [24:28, 59933.00 examples/s]
Generating train split: 12962865 examples [24:28, 68972.97 examples/s]
Generating train split: 12971473 examples [24:28, 72958.74 examples/s]
Generating train split: 12982625 examples [24:28, 82647.62 examples/s]
Generating train split: 12991834 examples [24:28, 59168.94 examples/s]
Generating train split: 12999324 examples [24:29, 40428.65 examples/s]
Generating train split: 13005197 examples [24:29, 38814.18 examples/s]
Generating train split: 13013092 examples [24:29, 45656.31 examples/s]
Generating train split: 13020683 examples [24:29, 51586.23 examples/s]
Generating train split: 13029713 examples [24:29, 59364.82 examples/s]
Generating train split: 13036793 examples [24:30, 41564.47 examples/s]
Generating train split: 13042450 examples [24:30, 39651.27 examples/s]
Generating train split: 13047435 examples [24:30, 40742.93 examples/s]
Generating train split: 13052282 examples [24:30, 27876.37 examples/s]
Generating train split: 13056109 examples [24:30, 29181.62 examples/s]
Generating train split: 13066375 examples [24:30, 43046.09 examples/s]
Generating train split: 13078176 examples [24:30, 58631.33 examples/s]
Generating train split: 13085609 examples [24:31, 54346.21 examples/s]
Generating train split: 13092180 examples [24:31, 39375.13 examples/s]
Generating train split: 13097446 examples [24:31, 36589.77 examples/s]
Generating train split: 13103889 examples [24:31, 41732.75 examples/s]
Generating train split: 13109032 examples [24:31, 39482.30 examples/s]
Generating train split: 13113642 examples [24:31, 37608.95 examples/s]
Generating train split: 13117851 examples [24:32, 37832.36 examples/s]
Generating train split: 13123080 examples [24:32, 41209.22 examples/s]
Generating train split: 13127534 examples [24:32, 37383.67 examples/s]
Generating train split: 13131897 examples [24:32, 38226.64 examples/s]
Generating train split: 13135935 examples [24:32, 29831.38 examples/s]
Generating train split: 13139318 examples [24:32, 27367.91 examples/s]
Generating train split: 13142344 examples [24:32, 26416.37 examples/s]
Generating train split: 13145167 examples [24:33, 23976.42 examples/s]
Generating train split: 13147708 examples [24:33, 18824.98 examples/s]
Generating train split: 13149813 examples [24:33, 18285.47 examples/s]
Generating train split: 13151786 examples [24:33, 17248.66 examples/s]
Generating train split: 13153602 examples [24:33, 16817.79 examples/s]
Generating train split: 13155564 examples [24:33, 17174.00 examples/s]
Generating train split: 13157336 examples [24:33, 15622.57 examples/s]
Generating train split: 13158963 examples [24:34, 15387.05 examples/s]
Generating train split: 13160541 examples [24:34, 13353.26 examples/s]
Generating train split: 13163713 examples [24:34, 17681.06 examples/s]
Generating train split: 13165650 examples [24:34, 17192.90 examples/s]
Generating train split: 13167481 examples [24:34, 14880.09 examples/s]
Generating train split: 13169312 examples [24:34, 15675.72 examples/s]
Generating train split: 13171309 examples [24:34, 16751.05 examples/s]
Generating train split: 13173548 examples [24:34, 18238.55 examples/s]
Generating train split: 13175475 examples [24:35, 12822.88 examples/s]
Generating train split: 13177265 examples [24:35, 13823.69 examples/s]
Generating train split: 13178884 examples [24:35, 12718.66 examples/s]
Generating train split: 13181451 examples [24:35, 15656.64 examples/s]
Generating train split: 13183705 examples [24:35, 17250.33 examples/s]
Generating train split: 13185624 examples [24:35, 13168.48 examples/s]
Generating train split: 13188664 examples [24:35, 16395.85 examples/s]
Generating train split: 13191837 examples [24:36, 19912.42 examples/s]
Generating train split: 13194474 examples [24:36, 21464.74 examples/s]
Generating train split: 13196869 examples [24:36, 13599.43 examples/s]
Generating train split: 13198752 examples [24:36, 13733.42 examples/s]
Generating train split: 13202472 examples [24:36, 18432.59 examples/s]
Generating train split: 13204812 examples [24:37, 13728.70 examples/s]
Generating train split: 13206785 examples [24:37, 14823.30 examples/s]
Generating train split: 13211125 examples [24:37, 20734.23 examples/s]
Generating train split: 13224723 examples [24:37, 47013.96 examples/s]
Generating train split: 13236920 examples [24:37, 65423.69 examples/s]
Generating train split: 13244726 examples [24:37, 42734.42 examples/s]
Generating train split: 13250890 examples [24:38, 33864.71 examples/s]
Generating train split: 13255837 examples [24:38, 27395.43 examples/s]
Generating train split: 13259792 examples [24:38, 24954.93 examples/s]
Generating train split: 13263131 examples [24:38, 23834.55 examples/s]
Generating train split: 13266075 examples [24:38, 22545.11 examples/s]
Generating train split: 13268723 examples [24:39, 23205.99 examples/s]
Generating train split: 13271344 examples [24:39, 22108.12 examples/s]
Generating train split: 13278163 examples [24:39, 31867.79 examples/s]
Generating train split: 13291296 examples [24:39, 54945.68 examples/s]
Generating train split: 13301566 examples [24:39, 66737.74 examples/s]
Generating train split: 13309223 examples [24:39, 43617.74 examples/s]
Generating train split: 13315290 examples [24:40, 32100.80 examples/s]
Generating train split: 13320083 examples [24:40, 30125.92 examples/s]
Generating train split: 13324174 examples [24:40, 31874.76 examples/s]
Generating train split: 13328262 examples [24:40, 22131.29 examples/s]
Generating train split: 13331451 examples [24:40, 21817.39 examples/s]
Generating train split: 13334319 examples [24:41, 21130.88 examples/s]
Generating train split: 13336898 examples [24:41, 21366.80 examples/s]
Generating train split: 13339360 examples [24:41, 18110.94 examples/s]
Generating train split: 13342771 examples [24:41, 21148.09 examples/s]
Generating train split: 13356187 examples [24:41, 45273.69 examples/s]
Generating train split: 13369964 examples [24:41, 66889.77 examples/s]
Generating train split: 13378140 examples [24:42, 39608.96 examples/s]
Generating train split: 13384460 examples [24:42, 34555.49 examples/s]
Generating train split: 13389626 examples [24:42, 26280.45 examples/s]
Generating train split: 13403079 examples [24:42, 41237.77 examples/s]
Generating train split: 13417835 examples [24:42, 58758.01 examples/s]
Generating train split: 13427063 examples [24:43, 47508.58 examples/s]
Generating train split: 13434466 examples [24:43, 27369.92 examples/s]
Generating train split: 13439995 examples [24:44, 22914.18 examples/s]
Generating train split: 13444291 examples [24:44, 20069.35 examples/s]
Generating train split: 13447689 examples [24:44, 19326.31 examples/s]
Generating train split: 13450555 examples [24:44, 19589.31 examples/s]
Generating train split: 13453192 examples [24:45, 18016.64 examples/s]
Generating train split: 13465031 examples [24:45, 33253.28 examples/s]
Generating train split: 13479728 examples [24:45, 53520.97 examples/s]
Generating train split: 13487741 examples [24:45, 42105.49 examples/s]
Generating train split: 13494145 examples [24:46, 31096.52 examples/s]
Generating train split: 13499144 examples [24:46, 29523.76 examples/s]
Generating train split: 13503397 examples [24:46, 22267.28 examples/s]
Generating train split: 13506724 examples [24:46, 22085.96 examples/s]
Generating train split: 13509693 examples [24:47, 18190.84 examples/s]
Generating train split: 13512081 examples [24:47, 18517.77 examples/s]
Generating train split: 13514370 examples [24:47, 17240.13 examples/s]
Generating train split: 13516374 examples [24:47, 17147.42 examples/s]
Generating train split: 13518277 examples [24:47, 16373.93 examples/s]
Generating train split: 13520274 examples [24:47, 17097.83 examples/s]
Generating train split: 13522100 examples [24:47, 15553.51 examples/s]
Generating train split: 13525131 examples [24:47, 18883.11 examples/s]
Generating train split: 13527188 examples [24:48, 17689.56 examples/s]
Generating train split: 13529820 examples [24:48, 19751.22 examples/s]
Generating train split: 13531935 examples [24:48, 14128.91 examples/s]
Generating train split: 13533660 examples [24:48, 13667.68 examples/s]
Generating train split: 13535244 examples [24:48, 11943.58 examples/s]
Generating train split: 13536717 examples [24:48, 12172.40 examples/s]
Generating train split: 13538064 examples [24:49, 11337.76 examples/s]
Generating train split: 13541382 examples [24:49, 16014.46 examples/s]
Generating train split: 13543177 examples [24:49, 15290.26 examples/s]
Generating train split: 13544839 examples [24:49, 13202.41 examples/s]
Generating train split: 13546293 examples [24:49, 11472.39 examples/s]
Generating train split: 13548934 examples [24:49, 14241.67 examples/s]
Generating train split: 13550525 examples [24:49, 11770.67 examples/s]
Generating train split: 13553547 examples [24:50, 15614.13 examples/s]
Generating train split: 13556233 examples [24:50, 18098.76 examples/s]
Generating train split: 13558321 examples [24:50, 16195.91 examples/s]
Generating train split: 13560156 examples [24:50, 14806.16 examples/s]
Generating train split: 13563243 examples [24:50, 18460.50 examples/s]
Generating train split: 13565323 examples [24:50, 17186.51 examples/s]
Generating train split: 13567409 examples [24:50, 17669.58 examples/s]
Generating train split: 13569305 examples [24:51, 13229.52 examples/s]
Generating train split: 13572610 examples [24:51, 17358.62 examples/s]
Generating train split: 13574697 examples [24:51, 11141.90 examples/s]
Generating train split: 13577528 examples [24:51, 13988.73 examples/s]
Generating train split: 13579504 examples [24:51, 12601.87 examples/s]
Generating train split: 13581480 examples [24:51, 13575.35 examples/s]
Generating train split: 13583177 examples [24:52, 13704.08 examples/s]
Generating train split: 13587088 examples [24:52, 19303.39 examples/s]
Generating train split: 13589846 examples [24:52, 21285.30 examples/s]
Generating train split: 13592297 examples [24:52, 20515.75 examples/s]
Generating train split: 13594966 examples [24:52, 21506.93 examples/s]
Generating train split: 13597284 examples [24:52, 19447.26 examples/s]
Generating train split: 13599370 examples [24:52, 13116.77 examples/s]
Generating train split: 13601039 examples [24:53, 13421.73 examples/s]
Generating train split: 13603358 examples [24:53, 15458.27 examples/s]
Generating train split: 13606959 examples [24:53, 20172.13 examples/s]
Generating train split: 13610320 examples [24:53, 23469.49 examples/s]
Generating train split: 13615243 examples [24:53, 29738.80 examples/s]
Generating train split: 13618513 examples [24:53, 30362.96 examples/s]
Generating train split: 13623246 examples [24:53, 35034.67 examples/s]
Generating train split: 13632139 examples [24:53, 50269.37 examples/s]
Generating train split: 13642385 examples [24:53, 65255.04 examples/s]
Generating train split: 13649147 examples [24:54, 65928.19 examples/s]
Generating train split: 13655914 examples [24:54, 66160.90 examples/s]
Generating train split: 13663978 examples [24:54, 70235.99 examples/s]
Generating train split: 13671096 examples [24:54, 55568.71 examples/s]
Generating train split: 13677204 examples [24:54, 52318.36 examples/s]
Generating train split: 13683837 examples [24:54, 55757.46 examples/s]
Generating train split: 13689768 examples [24:54, 52154.03 examples/s]
Generating train split: 13698105 examples [24:54, 60119.42 examples/s]
Generating train split: 13705330 examples [24:54, 63331.91 examples/s]
Generating train split: 13711930 examples [24:55, 54836.76 examples/s]
Generating train split: 13717797 examples [24:55, 45668.79 examples/s]
Generating train split: 13722828 examples [24:55, 46538.72 examples/s]
Generating train split: 13727839 examples [24:55, 47278.16 examples/s]
Generating train split: 13740340 examples [24:55, 67358.90 examples/s]
Generating train split: 13753823 examples [24:55, 85549.73 examples/s]
Generating train split: 13762944 examples [24:55, 78134.16 examples/s]
Generating train split: 13772086 examples [24:55, 81598.10 examples/s]
Generating train split: 13780669 examples [24:56, 67824.98 examples/s]
Generating train split: 13788087 examples [24:56, 57466.70 examples/s]
Generating train split: 13794483 examples [24:56, 55346.20 examples/s]
Generating train split: 13800467 examples [24:56, 55380.53 examples/s]
Generating train split: 13806311 examples [24:56, 55581.81 examples/s]
Generating train split: 13812096 examples [24:56, 37882.68 examples/s]
Generating train split: 13817680 examples [24:57, 41430.89 examples/s]
Generating train split: 13822607 examples [24:57, 39938.26 examples/s]
Generating train split: 13836907 examples [24:57, 63213.65 examples/s]
Generating train split: 13851141 examples [24:57, 82506.11 examples/s]
Generating train split: 13860644 examples [24:57, 75045.52 examples/s]
Generating train split: 13869140 examples [24:57, 42603.24 examples/s]
Generating train split: 13875686 examples [24:58, 45568.70 examples/s]
Generating train split: 13882058 examples [24:58, 30603.49 examples/s]
Generating train split: 13888674 examples [24:58, 35619.51 examples/s]
Generating train split: 13898168 examples [24:58, 45594.70 examples/s]
Generating train split: 13909147 examples [24:58, 58017.46 examples/s]
Generating train split: 13919904 examples [24:58, 68744.70 examples/s]
Generating train split: 13930015 examples [24:59, 76371.89 examples/s]
Generating train split: 13939191 examples [24:59, 80227.42 examples/s]
Generating train split: 13950391 examples [24:59, 88633.63 examples/s]
Generating train split: 13960594 examples [24:59, 92294.38 examples/s]
Generating train split: 13972451 examples [24:59, 99670.52 examples/s]
Generating train split: 13983475 examples [24:59, 102672.37 examples/s]
Generating train split: 13995030 examples [24:59, 106335.99 examples/s]
Generating train split: 14005941 examples [24:59, 106051.92 examples/s]
Generating train split: 14016741 examples [24:59, 102795.25 examples/s]
Generating train split: 14027410 examples [24:59, 103879.58 examples/s]
Generating train split: 14037935 examples [25:00, 103101.58 examples/s]
Generating train split: 14048326 examples [25:00, 103138.98 examples/s]
Generating train split: 14059619 examples [25:00, 105979.18 examples/s]
Generating train split: 14070509 examples [25:00, 106824.09 examples/s]
Generating train split: 14081224 examples [25:00, 106782.59 examples/s]
Generating train split: 14092613 examples [25:00, 108888.07 examples/s]
Generating train split: 14103523 examples [25:00, 107507.59 examples/s]
Generating train split: 14114290 examples [25:00, 104647.56 examples/s]
Generating train split: 14124792 examples [25:00, 99353.36 examples/s] 
Generating train split: 14134796 examples [25:01, 85747.66 examples/s]
Generating train split: 14143715 examples [25:01, 81875.73 examples/s]
Generating train split: 14152142 examples [25:01, 77380.58 examples/s]
Generating train split: 14160074 examples [25:01, 69306.22 examples/s]
Generating train split: 14167229 examples [25:01, 68492.40 examples/s]
Generating train split: 14174217 examples [25:01, 42626.11 examples/s]
Generating train split: 14179744 examples [25:02, 39670.71 examples/s]
Generating train split: 14184563 examples [25:02, 38398.23 examples/s]
Generating train split: 14189020 examples [25:02, 39631.15 examples/s]
Generating train split: 14193462 examples [25:02, 27970.35 examples/s]
Generating train split: 14197013 examples [25:02, 27192.00 examples/s]
Generating train split: 14201055 examples [25:02, 29733.58 examples/s]
Generating train split: 14204598 examples [25:02, 30949.49 examples/s]
Generating train split: 14209399 examples [25:03, 34950.72 examples/s]
Generating train split: 14213297 examples [25:03, 25465.73 examples/s]
Generating train split: 14216647 examples [25:03, 27088.56 examples/s]
Generating train split: 14221858 examples [25:03, 32690.01 examples/s]
Generating train split: 14225681 examples [25:03, 31323.20 examples/s]
Generating train split: 14229196 examples [25:03, 25198.75 examples/s]
Generating train split: 14232145 examples [25:03, 23871.30 examples/s]
Generating train split: 14237071 examples [25:04, 29378.08 examples/s]
Generating train split: 14240422 examples [25:04, 24753.68 examples/s]
Generating train split: 14243926 examples [25:04, 26902.70 examples/s]
Generating train split: 14246979 examples [25:04, 22880.13 examples/s]
Generating train split: 14251323 examples [25:04, 27326.44 examples/s]
Generating train split: 14254458 examples [25:05, 18153.27 examples/s]
Generating train split: 14256933 examples [25:05, 17203.85 examples/s]
Generating train split: 14260061 examples [25:05, 19756.93 examples/s]
Generating train split: 14262513 examples [25:05, 11748.93 examples/s]
Generating train split: 14264396 examples [25:06, 8863.49 examples/s] 
Generating train split: 14265979 examples [25:06, 9731.60 examples/s]
Generating train split: 14267480 examples [25:06, 10107.03 examples/s]
Generating train split: 14268877 examples [25:06, 7564.82 examples/s] 
Generating train split: 14269991 examples [25:06, 7055.84 examples/s]
Generating train split: 14270930 examples [25:07, 7347.98 examples/s]
Generating train split: 14271856 examples [25:07, 6139.77 examples/s]
Generating train split: 14274008 examples [25:07, 8749.90 examples/s]
Generating train split: 14275189 examples [25:07, 8310.71 examples/s]
Generating train split: 14278691 examples [25:07, 13610.38 examples/s]
Generating train split: 14280480 examples [25:07, 10470.22 examples/s]
Generating train split: 14282120 examples [25:08, 11546.93 examples/s]
Generating train split: 14283628 examples [25:08, 11940.76 examples/s]
Generating train split: 14285091 examples [25:08, 8507.35 examples/s] 
Generating train split: 14287121 examples [25:08, 10388.64 examples/s]
Generating train split: 14289043 examples [25:08, 11861.78 examples/s]
Generating train split: 14290514 examples [25:09, 6967.48 examples/s] 
Generating train split: 14292768 examples [25:09, 9252.50 examples/s]
Generating train split: 14295574 examples [25:09, 12506.68 examples/s]
Generating train split: 14297421 examples [25:09, 8265.47 examples/s] 
Generating train split: 14299659 examples [25:09, 10239.55 examples/s]
Generating train split: 14301299 examples [25:10, 6846.29 examples/s] 
Generating train split: 14302560 examples [25:10, 7048.04 examples/s]
Generating train split: 14306381 examples [25:10, 11612.70 examples/s]
Generating train split: 14314992 examples [25:10, 24500.06 examples/s]
Generating train split: 14328478 examples [25:10, 46366.39 examples/s]
Generating train split: 14335268 examples [25:10, 45968.77 examples/s]
Generating train split: 14341376 examples [25:11, 32185.64 examples/s]
Generating train split: 14346199 examples [25:11, 32835.84 examples/s]
Generating train split: 14350641 examples [25:11, 28762.81 examples/s]
Generating train split: 14354360 examples [25:12, 20776.76 examples/s]
Generating train split: 14357283 examples [25:12, 20400.55 examples/s]
Generating train split: 14359897 examples [25:12, 18719.35 examples/s]
Generating train split: 14362640 examples [25:12, 20132.18 examples/s]
Generating train split: 14365407 examples [25:12, 21507.50 examples/s]
Generating train split: 14367895 examples [25:12, 19349.21 examples/s]
Generating train split: 14370092 examples [25:12, 15756.81 examples/s]
Generating train split: 14371926 examples [25:13, 15162.43 examples/s]
Generating train split: 14373931 examples [25:13, 15768.47 examples/s]
Generating train split: 14375649 examples [25:13, 15245.96 examples/s]
Generating train split: 14377259 examples [25:13, 11476.37 examples/s]
Generating train split: 14378967 examples [25:13, 12553.80 examples/s]
Generating train split: 14380399 examples [25:13, 10014.93 examples/s]
Generating train split: 14384755 examples [25:14, 16566.12 examples/s]
Generating train split: 14397780 examples [25:14, 41355.99 examples/s]
Generating train split: 14409545 examples [25:14, 58430.00 examples/s]
Generating train split: 14416614 examples [25:14, 36036.97 examples/s]
Generating train split: 14422114 examples [25:14, 27951.67 examples/s]
Generating train split: 14428686 examples [25:15, 33596.90 examples/s]
Generating train split: 14439604 examples [25:15, 46888.27 examples/s]
Generating train split: 14450627 examples [25:15, 59204.61 examples/s]
Generating train split: 14458579 examples [25:15, 33959.57 examples/s]
Generating train split: 14465253 examples [25:15, 38685.28 examples/s]
Generating train split: 14475527 examples [25:15, 49629.23 examples/s]
Generating train split: 14482969 examples [25:16, 42150.30 examples/s]
Generating train split: 14489084 examples [25:16, 41791.91 examples/s]
Generating train split: 14494589 examples [25:16, 38881.14 examples/s]
Generating train split: 14499404 examples [25:16, 32138.03 examples/s]
Generating train split: 14503386 examples [25:16, 27719.74 examples/s]
Generating train split: 14506776 examples [25:17, 28730.02 examples/s]
Generating train split: 14510123 examples [25:17, 26250.34 examples/s]
Generating train split: 14513076 examples [25:17, 21992.78 examples/s]
Generating train split: 14516961 examples [25:17, 24904.15 examples/s]
Generating train split: 14520118 examples [25:17, 26308.52 examples/s]
Generating train split: 14523061 examples [25:17, 21571.16 examples/s]
Generating train split: 14525534 examples [25:17, 20344.84 examples/s]
Generating train split: 14529211 examples [25:18, 23865.67 examples/s]
Generating train split: 14533430 examples [25:18, 28159.11 examples/s]
Generating train split: 14536572 examples [25:18, 22976.82 examples/s]
Generating train split: 14539241 examples [25:18, 22043.49 examples/s]
Generating train split: 14542911 examples [25:18, 25043.69 examples/s]
Generating train split: 14546250 examples [25:18, 27038.58 examples/s]
Generating train split: 14549182 examples [25:18, 23588.80 examples/s]
Generating train split: 14551761 examples [25:19, 19802.75 examples/s]
Generating train split: 14554285 examples [25:19, 20991.24 examples/s]
Generating train split: 14558878 examples [25:19, 26894.97 examples/s]
Generating train split: 14561876 examples [25:19, 27621.29 examples/s]
Generating train split: 14569642 examples [25:19, 40903.09 examples/s]
Generating train split: 14580019 examples [25:19, 58089.91 examples/s]
Generating train split: 14586223 examples [25:19, 37944.66 examples/s]
Generating train split: 14591183 examples [25:20, 39532.53 examples/s]
Generating train split: 14596006 examples [25:20, 41379.75 examples/s]
Generating train split: 14602842 examples [25:20, 47887.09 examples/s]
Generating train split: 14616873 examples [25:20, 71554.15 examples/s]
Generating train split: 14628930 examples [25:20, 83898.59 examples/s]
Generating train split: 14638033 examples [25:20, 48806.15 examples/s]
Generating train split: 14645130 examples [25:20, 50450.17 examples/s]
Generating train split: 14657380 examples [25:21, 64805.92 examples/s]
Generating train split: 14670187 examples [25:21, 78810.42 examples/s]
Generating train split: 14679861 examples [25:21, 60240.38 examples/s]
Generating train split: 14687773 examples [25:21, 46457.49 examples/s]
Generating train split: 14694241 examples [25:21, 49548.46 examples/s]
Generating train split: 14700633 examples [25:22, 39028.05 examples/s]
Generating train split: 14705806 examples [25:22, 32320.48 examples/s]
Generating train split: 14710385 examples [25:22, 34356.35 examples/s]
Generating train split: 14717148 examples [25:22, 40571.41 examples/s]
Generating train split: 14727682 examples [25:22, 54240.05 examples/s]
Generating train split: 14734369 examples [25:22, 38059.28 examples/s]
Generating train split: 14747693 examples [25:23, 55237.76 examples/s]
Generating train split: 14760111 examples [25:23, 69260.03 examples/s]
Generating train split: 14769202 examples [25:23, 61305.95 examples/s]
Generating train split: 14776993 examples [25:23, 43683.07 examples/s]
Generating train split: 14783150 examples [25:23, 40403.19 examples/s]
Generating train split: 14788432 examples [25:24, 30825.98 examples/s]
Generating train split: 14792632 examples [25:24, 30175.41 examples/s]
Generating train split: 14796400 examples [25:24, 30738.46 examples/s]
Generating train split: 14802988 examples [25:24, 37389.81 examples/s]
Generating train split: 14812880 examples [25:24, 50481.73 examples/s]
Generating train split: 14826514 examples [25:24, 70497.05 examples/s]
Generating train split: 14834904 examples [25:25, 46172.19 examples/s]
Generating train split: 14841536 examples [25:25, 36239.67 examples/s]
Generating train split: 14846815 examples [25:25, 24477.49 examples/s]
Generating train split: 14850846 examples [25:26, 20520.36 examples/s]
Generating train split: 14854125 examples [25:26, 22015.56 examples/s]
Generating train split: 14857340 examples [25:26, 18432.75 examples/s]
Generating train split: 14859947 examples [25:26, 16349.27 examples/s]
Generating train split: 14863104 examples [25:26, 18383.79 examples/s]
Generating train split: 14865501 examples [25:27, 14872.88 examples/s]
Generating train split: 14867450 examples [25:27, 14745.59 examples/s]
Generating train split: 14869239 examples [25:27, 15078.63 examples/s]
Generating train split: 14870993 examples [25:27, 13534.41 examples/s]
Generating train split: 14873024 examples [25:27, 14828.05 examples/s]
Generating train split: 14874697 examples [25:27, 11837.34 examples/s]
Generating train split: 14876795 examples [25:28, 13614.54 examples/s]
Generating train split: 14879079 examples [25:28, 15621.44 examples/s]
Generating train split: 14891133 examples [25:28, 40571.78 examples/s]
Generating train split: 14903311 examples [25:28, 60632.06 examples/s]
Generating train split: 14910255 examples [25:28, 40115.09 examples/s]
Generating train split: 14915797 examples [25:29, 27644.47 examples/s]
Generating train split: 14920096 examples [25:29, 23094.45 examples/s]
Generating train split: 14923612 examples [25:29, 24808.25 examples/s]
Generating train split: 14927086 examples [25:29, 17081.62 examples/s]
Generating train split: 14933525 examples [25:29, 23456.73 examples/s]
Generating train split: 14947021 examples [25:30, 41457.52 examples/s]
Generating train split: 14953730 examples [25:30, 44945.58 examples/s]
Generating train split: 14960169 examples [25:30, 24961.23 examples/s]
Generating train split: 14965016 examples [25:31, 20957.85 examples/s]
Generating train split: 14977547 examples [25:31, 33737.70 examples/s]
Generating train split: 14991499 examples [25:31, 49485.73 examples/s]
Generating train split: 15000193 examples [25:31, 37730.99 examples/s]
Generating train split: 15011008 examples [25:31, 47888.16 examples/s]
Generating train split: 15023312 examples [25:31, 60732.56 examples/s]
Generating train split: 15032597 examples [25:32, 37497.99 examples/s]
Generating train split: 15039652 examples [25:32, 24782.90 examples/s]
Generating train split: 15044948 examples [25:33, 18485.32 examples/s]
Generating train split: 15048925 examples [25:34, 13321.52 examples/s]
Generating train split: 15051890 examples [25:34, 12912.94 examples/s]
Generating train split: 15054306 examples [25:34, 12276.66 examples/s]
Generating train split: 15057273 examples [25:34, 13991.18 examples/s]
Generating train split: 15059883 examples [25:34, 15497.46 examples/s]
Generating train split: 15064104 examples [25:35, 19523.84 examples/s]
Generating train split: 15067026 examples [25:35, 20806.85 examples/s]
Generating train split: 15071267 examples [25:35, 25052.13 examples/s]
Generating train split: 15076958 examples [25:35, 32093.97 examples/s]
Generating train split: 15088109 examples [25:35, 51159.97 examples/s]
Generating train split: 15094231 examples [25:35, 47476.29 examples/s]
Generating train split: 15099728 examples [25:35, 36474.74 examples/s]
Generating train split: 15111932 examples [25:35, 53998.18 examples/s]
Generating train split: 15125392 examples [25:36, 72228.01 examples/s]
Generating train split: 15134218 examples [25:36, 37973.49 examples/s]
Generating train split: 15140905 examples [25:36, 33786.19 examples/s]
Generating train split: 15146337 examples [25:37, 21798.73 examples/s]
Generating train split: 15150436 examples [25:37, 22581.88 examples/s]
Generating train split: 15154104 examples [25:38, 16796.44 examples/s]
Generating train split: 15157892 examples [25:38, 19157.86 examples/s]
Generating train split: 15166453 examples [25:38, 28336.45 examples/s]
Generating train split: 15180116 examples [25:38, 46184.06 examples/s]
Generating train split: 15187533 examples [25:38, 45308.23 examples/s]
Generating train split: 15194033 examples [25:39, 24840.61 examples/s]
Generating train split: 15198893 examples [25:39, 24778.08 examples/s]
Generating train split: 15203045 examples [25:39, 23558.85 examples/s]
Generating train split: 15206543 examples [25:39, 18511.30 examples/s]
Generating train split: 15209294 examples [25:40, 17021.51 examples/s]
Generating train split: 15211598 examples [25:40, 17191.80 examples/s]
Generating train split: 15213758 examples [25:40, 16729.89 examples/s]
Generating train split: 15215847 examples [25:40, 17461.33 examples/s]
Generating train split: 15219171 examples [25:40, 20638.52 examples/s]
Generating train split: 15222628 examples [25:40, 23749.85 examples/s]
Generating train split: 15234707 examples [25:40, 47226.27 examples/s]
Generating train split: 15243592 examples [25:40, 57864.32 examples/s]
Generating train split: 15250121 examples [25:41, 54794.72 examples/s]
Generating train split: 15261289 examples [25:41, 69553.95 examples/s]
Generating train split: 15271932 examples [25:41, 79101.50 examples/s]
Generating train split: 15280370 examples [25:41, 46485.47 examples/s]
Generating train split: 15286975 examples [25:41, 47265.43 examples/s]
Generating train split: 15293085 examples [25:41, 39034.00 examples/s]
Generating train split: 15298143 examples [25:42, 31426.93 examples/s]
Generating train split: 15302247 examples [25:42, 32435.23 examples/s]
Generating train split: 15306230 examples [25:42, 27603.81 examples/s]
Generating train split: 15317710 examples [25:42, 43343.20 examples/s]
Generating train split: 15326846 examples [25:42, 52826.61 examples/s]
Generating train split: 15333538 examples [25:43, 39128.05 examples/s]
Generating train split: 15338919 examples [25:43, 27614.15 examples/s]
Generating train split: 15343616 examples [25:43, 30466.99 examples/s]
Generating train split: 15355963 examples [25:43, 46659.14 examples/s]
Generating train split: 15365351 examples [25:43, 56050.41 examples/s]
Generating train split: 15372890 examples [25:44, 39057.14 examples/s]
Generating train split: 15378826 examples [25:44, 36735.21 examples/s]
Generating train split: 15389144 examples [25:44, 48255.80 examples/s]
Generating train split: 15401444 examples [25:44, 63090.96 examples/s]
Generating train split: 15409802 examples [25:44, 34961.29 examples/s]
Generating train split: 15416131 examples [25:45, 28849.25 examples/s]
Generating train split: 15421102 examples [25:45, 23914.53 examples/s]
Generating train split: 15425015 examples [25:46, 19674.99 examples/s]
Generating train split: 15437294 examples [25:46, 31847.93 examples/s]
Generating train split: 15446629 examples [25:46, 40723.54 examples/s]
Generating train split: 15453516 examples [25:46, 35796.90 examples/s]
Generating train split: 15465891 examples [25:46, 49954.95 examples/s]
Generating train split: 15477770 examples [25:46, 62235.31 examples/s]
Generating train split: 15486512 examples [25:47, 41123.60 examples/s]
Generating train split: 15493276 examples [25:47, 45112.11 examples/s]
Generating train split: 15500027 examples [25:47, 38526.20 examples/s]
Generating train split: 15505564 examples [25:47, 37996.15 examples/s]
Generating train split: 15514688 examples [25:47, 47597.05 examples/s]
Generating train split: 15526640 examples [25:47, 62331.56 examples/s]
Generating train split: 15535422 examples [25:47, 68084.99 examples/s]
Generating train split: 15543608 examples [25:48, 57365.42 examples/s]
Generating train split: 15550560 examples [25:48, 35724.68 examples/s]
Generating train split: 15561841 examples [25:48, 47816.83 examples/s]
Generating train split: 15574857 examples [25:48, 62889.22 examples/s]
Generating train split: 15583770 examples [25:48, 62226.86 examples/s]
Generating train split: 15596829 examples [25:48, 76734.76 examples/s]
Generating train split: 15608093 examples [25:49, 84729.67 examples/s]
Generating train split: 15618116 examples [25:49, 42719.57 examples/s]
Generating train split: 15625691 examples [25:49, 39530.93 examples/s]
Generating train split: 15632208 examples [25:49, 43298.92 examples/s]
Generating train split: 15638531 examples [25:50, 39666.60 examples/s]
Generating train split: 15643892 examples [25:50, 41769.29 examples/s]
Generating train split: 15650000 examples [25:50, 45592.14 examples/s]
Generating train split: 15661983 examples [25:50, 61966.16 examples/s]
Generating train split: 15675207 examples [25:50, 78805.52 examples/s]
Generating train split: 15684401 examples [25:51, 43281.62 examples/s]
Generating train split: 15691451 examples [25:51, 46161.30 examples/s]
Generating train split: 15698146 examples [25:51, 29608.92 examples/s]
Generating train split: 15703253 examples [25:51, 31207.59 examples/s]
Generating train split: 15708012 examples [25:51, 33160.01 examples/s]
Generating train split: 15715903 examples [25:51, 41326.18 examples/s]
Generating train split: 15721493 examples [25:53, 14470.57 examples/s]
Generating train split: 15725555 examples [25:54, 9579.46 examples/s] 
Generating train split: 15731571 examples [25:54, 12926.18 examples/s]
Generating train split: 15739997 examples [25:54, 19086.51 examples/s]
Generating train split: 15745249 examples [25:54, 21582.48 examples/s]
Generating train split: 15750288 examples [25:54, 25310.89 examples/s]
Generating train split: 15756964 examples [25:54, 31780.88 examples/s]
Generating train split: 15762846 examples [25:54, 36475.67 examples/s]
Generating train split: 15769094 examples [25:54, 41427.63 examples/s]
Generating train split: 15774729 examples [25:55, 30702.83 examples/s]
Generating train split: 15779220 examples [25:55, 30758.73 examples/s]
Generating train split: 15783301 examples [25:55, 28846.80 examples/s]
Generating train split: 15787831 examples [25:55, 31430.12 examples/s]
Generating train split: 15791567 examples [25:55, 30373.09 examples/s]
Generating train split: 15795013 examples [25:55, 25629.10 examples/s]
Generating train split: 15798171 examples [25:55, 26854.00 examples/s]
Generating train split: 15805389 examples [25:56, 37160.70 examples/s]
Generating train split: 15814869 examples [25:56, 51281.87 examples/s]
Generating train split: 15824305 examples [25:56, 62436.56 examples/s]
Generating train split: 15831223 examples [25:56, 55170.23 examples/s]
Generating train split: 15840888 examples [25:56, 65471.09 examples/s]
Generating train split: 15848071 examples [25:56, 35027.35 examples/s]
Generating train split: 15855602 examples [25:57, 41614.32 examples/s]
Generating train split: 15861734 examples [25:57, 31887.37 examples/s]
Generating train split: 15866592 examples [25:57, 32304.35 examples/s]
Generating train split: 15871010 examples [25:57, 20861.82 examples/s]
Generating train split: 15875145 examples [25:58, 23570.44 examples/s]
Generating train split: 15878747 examples [25:58, 15673.07 examples/s]
Generating train split: 15881486 examples [25:58, 16894.65 examples/s]
Generating train split: 15884160 examples [25:59, 11493.68 examples/s]
Generating train split: 15886247 examples [25:59, 12556.93 examples/s]
Generating train split: 15888286 examples [25:59, 10212.62 examples/s]
Generating train split: 15889889 examples [25:59, 10584.96 examples/s]
Generating train split: 15891404 examples [25:59, 10046.51 examples/s]
Generating train split: 15892712 examples [26:00, 7452.62 examples/s] 
Generating train split: 15894977 examples [26:00, 9584.98 examples/s]
Generating train split: 15896368 examples [26:00, 9368.80 examples/s]
Generating train split: 15902062 examples [26:00, 17883.33 examples/s]
Generating train split: 15911271 examples [26:00, 32984.78 examples/s]
Generating train split: 15915845 examples [26:01, 26995.77 examples/s]
Generating train split: 15920089 examples [26:01, 29986.71 examples/s]
Generating train split: 15923983 examples [26:01, 31845.31 examples/s]
Generating train split: 15928525 examples [26:01, 35030.45 examples/s]
Generating train split: 15932625 examples [26:01, 27389.75 examples/s]
Generating train split: 15936019 examples [26:01, 25850.46 examples/s]
Generating train split: 15940370 examples [26:01, 29633.68 examples/s]
Generating train split: 15946273 examples [26:01, 36221.47 examples/s]
Generating train split: 15950385 examples [26:02, 35524.98 examples/s]
Generating train split: 15954293 examples [26:02, 25569.86 examples/s]
Generating train split: 15957456 examples [26:02, 25905.16 examples/s]
Generating train split: 15966492 examples [26:02, 39969.23 examples/s]
Generating train split: 15979505 examples [26:02, 61394.33 examples/s]
Generating train split: 15988783 examples [26:02, 69002.30 examples/s]
Generating train split: 15996609 examples [26:03, 33388.39 examples/s]
Generating train split: 16002536 examples [26:03, 30792.35 examples/s]
Generating train split: 16007431 examples [26:03, 27431.42 examples/s]
Generating train split: 16011449 examples [26:03, 26162.62 examples/s]
Generating train split: 16014927 examples [26:04, 22318.81 examples/s]
Generating train split: 16017789 examples [26:04, 21546.89 examples/s]
Generating train split: 16020374 examples [26:04, 19400.21 examples/s]
Generating train split: 16022592 examples [26:04, 17162.26 examples/s]
Generating train split: 16025589 examples [26:04, 19381.44 examples/s]
Generating train split: 16027820 examples [26:04, 19206.52 examples/s]
Generating train split: 16029927 examples [26:05, 17599.11 examples/s]
Generating train split: 16031823 examples [26:05, 16216.80 examples/s]
Generating train split: 16033907 examples [26:05, 17144.51 examples/s]
Generating train split: 16036126 examples [26:05, 18342.86 examples/s]
Generating train split: 16038690 examples [26:05, 20155.66 examples/s]
Generating train split: 16042034 examples [26:05, 23674.28 examples/s]
Generating train split: 16049467 examples [26:05, 37581.49 examples/s]
Generating train split: 16057874 examples [26:05, 50689.56 examples/s]
Generating train split: 16063175 examples [26:06, 37396.73 examples/s]
Generating train split: 16067724 examples [26:06, 38672.77 examples/s]
Generating train split: 16072100 examples [26:06, 39416.71 examples/s]
Generating train split: 16076406 examples [26:06, 39922.29 examples/s]
Generating train split: 16080662 examples [26:06, 27358.12 examples/s]
Generating train split: 16084105 examples [26:06, 28617.42 examples/s]
Generating train split: 16087515 examples [26:06, 26798.80 examples/s]
Generating train split: 16090584 examples [26:07, 22896.12 examples/s]
Generating train split: 16094154 examples [26:07, 25563.53 examples/s]
Generating train split: 16098302 examples [26:07, 29213.53 examples/s]
Generating train split: 16101595 examples [26:07, 29651.23 examples/s]
Generating train split: 16105574 examples [26:07, 32263.57 examples/s]
Generating train split: 16109034 examples [26:07, 27038.46 examples/s]
Generating train split: 16112043 examples [26:07, 27078.02 examples/s]
Generating train split: 16114961 examples [26:07, 25354.82 examples/s]
Generating train split: 16119690 examples [26:08, 30779.62 examples/s]
Generating train split: 16130407 examples [26:08, 50711.16 examples/s]
Generating train split: 16139659 examples [26:08, 61563.24 examples/s]
Generating train split: 16146221 examples [26:08, 56916.91 examples/s]
Generating train split: 16152254 examples [26:08, 35342.55 examples/s]
Generating train split: 16157019 examples [26:08, 34217.60 examples/s]
Generating train split: 16162904 examples [26:08, 39046.49 examples/s]
Generating train split: 16173971 examples [26:09, 54715.36 examples/s]
Generating train split: 16184116 examples [26:09, 65351.76 examples/s]
Generating train split: 16191719 examples [26:09, 40854.36 examples/s]
Generating train split: 16197669 examples [26:09, 29853.18 examples/s]
Generating train split: 16202323 examples [26:10, 31333.24 examples/s]
Generating train split: 16206735 examples [26:10, 32305.15 examples/s]
Generating train split: 16210914 examples [26:10, 32678.24 examples/s]
Generating train split: 16214856 examples [26:10, 29339.95 examples/s]
Generating train split: 16218850 examples [26:10, 31470.43 examples/s]
Generating train split: 16222454 examples [26:10, 23918.17 examples/s]
Generating train split: 16225898 examples [26:10, 25916.22 examples/s]
Generating train split: 16228998 examples [26:10, 26998.19 examples/s]
Generating train split: 16232281 examples [26:11, 28359.33 examples/s]
Generating train split: 16236049 examples [26:11, 30692.93 examples/s]
Generating train split: 16239399 examples [26:11, 29487.07 examples/s]
Generating train split: 16243012 examples [26:11, 31115.98 examples/s]
Generating train split: 16246285 examples [26:11, 25826.46 examples/s]
Generating train split: 16249125 examples [26:11, 22821.89 examples/s]
Generating train split: 16252161 examples [26:11, 24537.50 examples/s]
Generating train split: 16254818 examples [26:12, 22392.18 examples/s]
Generating train split: 16257233 examples [26:12, 19428.92 examples/s]
Generating train split: 16259345 examples [26:12, 15673.75 examples/s]
Generating train split: 16261503 examples [26:12, 16859.41 examples/s]
Generating train split: 16264474 examples [26:12, 19688.97 examples/s]
Generating train split: 16266678 examples [26:12, 17298.54 examples/s]
Generating train split: 16268617 examples [26:13, 13803.14 examples/s]
Generating train split: 16270224 examples [26:13, 10716.88 examples/s]
Generating train split: 16271535 examples [26:13, 10952.51 examples/s]
Generating train split: 16272890 examples [26:13, 11465.45 examples/s]
Generating train split: 16275122 examples [26:13, 13746.38 examples/s]
Generating train split: 16278458 examples [26:13, 18167.49 examples/s]
Generating train split: 16280958 examples [26:13, 19879.45 examples/s]
Generating train split: 16283138 examples [26:14, 12659.83 examples/s]
Generating train split: 16284869 examples [26:14, 13477.01 examples/s]
Generating train split: 16286983 examples [26:14, 15106.72 examples/s]
Generating train split: 16297546 examples [26:14, 36193.75 examples/s]
Generating train split: 16307947 examples [26:14, 51204.15 examples/s]
Generating train split: 16313777 examples [26:14, 36174.91 examples/s]
Generating train split: 16318481 examples [26:15, 23631.63 examples/s]
Generating train split: 16322118 examples [26:15, 24991.09 examples/s]
Generating train split: 16325626 examples [26:15, 25871.50 examples/s]
Generating train split: 16328960 examples [26:15, 26517.88 examples/s]
Generating train split: 16339882 examples [26:15, 43961.67 examples/s]
Generating train split: 16348762 examples [26:15, 54309.41 examples/s]
Generating train split: 16355277 examples [26:16, 40129.19 examples/s]
Generating train split: 16360565 examples [26:16, 28091.88 examples/s]
Generating train split: 16364720 examples [26:16, 27370.76 examples/s]
Generating train split: 16368380 examples [26:16, 21459.34 examples/s]
Generating train split: 16371505 examples [26:16, 22945.19 examples/s]
Generating train split: 16374482 examples [26:17, 22706.98 examples/s]
Generating train split: 16377469 examples [26:17, 23963.68 examples/s]
Generating train split: 16380260 examples [26:17, 16281.10 examples/s]
Generating train split: 16382461 examples [26:17, 15823.37 examples/s]
Generating train split: 16385086 examples [26:17, 17505.26 examples/s]
Generating train split: 16387218 examples [26:18, 13917.55 examples/s]
Generating train split: 16389067 examples [26:18, 14691.73 examples/s]
Generating train split: 16392440 examples [26:18, 18586.67 examples/s]
Generating train split: 16394689 examples [26:18, 18441.17 examples/s]
Generating train split: 16396819 examples [26:18, 14217.07 examples/s]
Generating train split: 16398942 examples [26:18, 15584.14 examples/s]
Generating train split: 16402401 examples [26:18, 19553.23 examples/s]
Generating train split: 16405733 examples [26:18, 22827.92 examples/s]
Generating train split: 16408335 examples [26:19, 19740.57 examples/s]
Generating train split: 16411735 examples [26:19, 23038.32 examples/s]
Generating train split: 16418764 examples [26:19, 34805.50 examples/s]
Generating train split: 16429868 examples [26:19, 54797.04 examples/s]
Generating train split: 16436943 examples [26:19, 59066.82 examples/s]
Generating train split: 16443310 examples [26:19, 43895.08 examples/s]
Generating train split: 16454100 examples [26:19, 58310.93 examples/s]
Generating train split: 16462251 examples [26:19, 63869.20 examples/s]
Generating train split: 16469549 examples [26:20, 39257.56 examples/s]
Generating train split: 16475249 examples [26:20, 26644.71 examples/s]
Generating train split: 16486478 examples [26:20, 38503.18 examples/s]
Generating train split: 16496339 examples [26:20, 48047.36 examples/s]
Generating train split: 16503672 examples [26:21, 26658.63 examples/s]
Generating train split: 16509163 examples [26:21, 23999.42 examples/s]
Generating train split: 16513545 examples [26:22, 21371.98 examples/s]
Generating train split: 16517056 examples [26:22, 21307.86 examples/s]
Generating train split: 16520156 examples [26:22, 18371.46 examples/s]
Generating train split: 16522665 examples [26:22, 18851.40 examples/s]
Generating train split: 16530256 examples [26:22, 28105.47 examples/s]
Generating train split: 16541797 examples [26:22, 44530.63 examples/s]
Generating train split: 16548044 examples [26:23, 45887.78 examples/s]
Generating train split: 16553906 examples [26:23, 31218.48 examples/s]
Generating train split: 16558507 examples [26:23, 31250.97 examples/s]
Generating train split: 16569892 examples [26:23, 46385.86 examples/s]
Generating train split: 16580626 examples [26:23, 58797.78 examples/s]
Generating train split: 16588212 examples [26:24, 38717.35 examples/s]
Generating train split: 16600181 examples [26:24, 52270.89 examples/s]
Generating train split: 16607916 examples [26:24, 49021.06 examples/s]
Generating train split: 16614593 examples [26:24, 32470.77 examples/s]
Generating train split: 16625576 examples [26:24, 43674.85 examples/s]
Generating train split: 16636366 examples [26:25, 54681.16 examples/s]
Generating train split: 16644428 examples [26:25, 42142.19 examples/s]
Generating train split: 16654876 examples [26:25, 52445.87 examples/s]
Generating train split: 16663112 examples [26:25, 58160.30 examples/s]
Generating train split: 16670930 examples [26:25, 56674.52 examples/s]
Generating train split: 16683115 examples [26:25, 70844.71 examples/s]
Generating train split: 16691710 examples [26:25, 73677.07 examples/s]
Generating train split: 16700199 examples [26:26, 36129.01 examples/s]
Generating train split: 16706624 examples [26:26, 34494.43 examples/s]
Generating train split: 16718124 examples [26:26, 46632.76 examples/s]
Generating train split: 16725345 examples [26:26, 48803.48 examples/s]
Generating train split: 16732105 examples [26:27, 32960.20 examples/s]
Generating train split: 16737340 examples [26:27, 27628.29 examples/s]
Generating train split: 16742773 examples [26:27, 31380.22 examples/s]
Generating train split: 16747345 examples [26:27, 29489.83 examples/s]
Generating train split: 16751270 examples [26:28, 26547.90 examples/s]
Generating train split: 16754606 examples [26:28, 26895.92 examples/s]
Generating train split: 16758675 examples [26:28, 29493.86 examples/s]
Generating train split: 16763861 examples [26:28, 34287.01 examples/s]
Generating train split: 16771187 examples [26:28, 43478.34 examples/s]
Generating train split: 16776625 examples [26:28, 46106.85 examples/s]
Generating train split: 16781728 examples [26:28, 34561.41 examples/s]
Generating train split: 16786128 examples [26:28, 36573.81 examples/s]
Generating train split: 16790390 examples [26:29, 36891.44 examples/s]
Generating train split: 16794686 examples [26:29, 38307.38 examples/s]
Generating train split: 16804437 examples [26:29, 53686.42 examples/s]
Generating train split: 16813899 examples [26:29, 64754.44 examples/s]
Generating train split: 16820829 examples [26:29, 38993.84 examples/s]
Generating train split: 16826279 examples [26:29, 36773.52 examples/s]
Generating train split: 16831039 examples [26:30, 31721.12 examples/s]
Generating train split: 16835025 examples [26:30, 26303.10 examples/s]
Generating train split: 16838599 examples [26:30, 27924.11 examples/s]
Generating train split: 16842394 examples [26:30, 29899.77 examples/s]
Generating train split: 16845895 examples [26:30, 19359.65 examples/s]
Generating train split: 16849817 examples [26:31, 22611.11 examples/s]
Generating train split: 16853481 examples [26:31, 25253.90 examples/s]
Generating train split: 16856763 examples [26:31, 20314.52 examples/s]
Generating train split: 16859450 examples [26:31, 17396.38 examples/s]
Generating train split: 16864746 examples [26:31, 23705.49 examples/s]
Generating train split: 16876177 examples [26:31, 42020.97 examples/s]
Generating train split: 16885985 examples [26:31, 54573.92 examples/s]
Generating train split: 16892864 examples [26:32, 29816.27 examples/s]
Generating train split: 16898118 examples [26:32, 32148.02 examples/s]
Generating train split: 16904103 examples [26:32, 36925.49 examples/s]
Generating train split: 16911563 examples [26:32, 44295.40 examples/s]
Generating train split: 16917468 examples [26:33, 30079.43 examples/s]
Generating train split: 16927308 examples [26:33, 41405.16 examples/s]
Generating train split: 16938831 examples [26:33, 55538.47 examples/s]
Generating train split: 16946624 examples [26:33, 51947.51 examples/s]
Generating train split: 16953413 examples [26:33, 30970.50 examples/s]
Generating train split: 16958607 examples [26:34, 31408.09 examples/s]
Generating train split: 16963236 examples [26:34, 25779.53 examples/s]
Generating train split: 16966945 examples [26:34, 26813.02 examples/s]
Generating train split: 16975572 examples [26:34, 36975.15 examples/s]
Generating train split: 16986343 examples [26:34, 50849.09 examples/s]
Generating train split: 16994995 examples [26:34, 58638.19 examples/s]
Generating train split: 17002336 examples [26:34, 59656.11 examples/s]
Generating train split: 17012632 examples [26:35, 70307.35 examples/s]
Generating train split: 17020634 examples [26:35, 36820.89 examples/s]
Generating train split: 17026747 examples [26:35, 37589.18 examples/s]
Generating train split: 17032228 examples [26:36, 24666.22 examples/s]
Generating train split: 17036421 examples [26:36, 26424.43 examples/s]
Generating train split: 17041022 examples [26:36, 29443.30 examples/s]
Generating train split: 17045236 examples [26:36, 28493.30 examples/s]
Generating train split: 17048966 examples [26:36, 28439.42 examples/s]
Generating train split: 17054904 examples [26:36, 34700.57 examples/s]
Generating train split: 17064716 examples [26:36, 48918.20 examples/s]
Generating train split: 17073922 examples [26:36, 59362.62 examples/s]
Generating train split: 17080796 examples [26:37, 53292.73 examples/s]
Generating train split: 17086885 examples [26:37, 31708.97 examples/s]
Generating train split: 17092811 examples [26:37, 36253.35 examples/s]
Generating train split: 17103017 examples [26:37, 48812.98 examples/s]
Generating train split: 17110345 examples [26:37, 54001.53 examples/s]
Generating train split: 17117166 examples [26:38, 32335.79 examples/s]
Generating train split: 17122423 examples [26:38, 33636.47 examples/s]
Generating train split: 17132446 examples [26:38, 45400.03 examples/s]
Generating train split: 17141977 examples [26:38, 55433.87 examples/s]
Generating train split: 17149319 examples [26:38, 40657.08 examples/s]
Generating train split: 17155181 examples [26:38, 42946.89 examples/s]
Generating train split: 17160844 examples [26:39, 34807.55 examples/s]
Generating train split: 17165478 examples [26:39, 32470.00 examples/s]
Generating train split: 17170064 examples [26:39, 34926.27 examples/s]
Generating train split: 17174263 examples [26:39, 28308.83 examples/s]
Generating train split: 17177743 examples [26:39, 24472.95 examples/s]
Generating train split: 17184754 examples [26:40, 32767.46 examples/s]
Generating train split: 17196841 examples [26:40, 50926.12 examples/s]
Generating train split: 17203381 examples [26:40, 42051.69 examples/s]
Generating train split: 17208828 examples [26:40, 38053.13 examples/s]
Generating train split: 17213529 examples [26:40, 30676.97 examples/s]
Generating train split: 17217380 examples [26:40, 31886.55 examples/s]
Generating train split: 17221189 examples [26:41, 22616.40 examples/s]
Generating train split: 17226811 examples [26:41, 28146.98 examples/s]
Generating train split: 17232765 examples [26:41, 34094.63 examples/s]
Generating train split: 17237211 examples [26:41, 28350.75 examples/s]
Generating train split: 17240892 examples [26:41, 29535.98 examples/s]
Generating train split: 17244501 examples [26:41, 30200.76 examples/s]
Generating train split: 17250567 examples [26:42, 37171.29 examples/s]
Generating train split: 17259790 examples [26:42, 50747.20 examples/s]
Generating train split: 17270009 examples [26:42, 63299.33 examples/s]
Generating train split: 17276952 examples [26:42, 58282.05 examples/s]
Generating train split: 17283283 examples [26:42, 39345.95 examples/s]
Generating train split: 17288346 examples [26:42, 34828.57 examples/s]
Generating train split: 17292657 examples [26:43, 32460.49 examples/s]
Generating train split: 17300596 examples [26:43, 41567.13 examples/s]
Generating train split: 17309564 examples [26:43, 51993.58 examples/s]
Generating train split: 17319515 examples [26:43, 63236.25 examples/s]
Generating train split: 17326863 examples [26:43, 58800.70 examples/s]
Generating train split: 17333496 examples [26:43, 56793.10 examples/s]
Generating train split: 17343165 examples [26:43, 66601.55 examples/s]
Generating train split: 17353114 examples [26:43, 75137.27 examples/s]
Generating train split: 17361173 examples [26:43, 75111.85 examples/s]
Generating train split: 17369069 examples [26:44, 57010.75 examples/s]
Generating train split: 17375677 examples [26:44, 49553.39 examples/s]
Generating train split: 17384054 examples [26:44, 56875.10 examples/s]
Generating train split: 17394160 examples [26:44, 67214.36 examples/s]
Generating train split: 17401747 examples [26:44, 63278.17 examples/s]
Generating train split: 17408693 examples [26:44, 61916.81 examples/s]
Generating train split: 17415312 examples [26:45, 45629.98 examples/s]
Generating train split: 17420736 examples [26:45, 39824.70 examples/s]
Generating train split: 17425380 examples [26:45, 27777.59 examples/s]
Generating train split: 17429349 examples [26:45, 29687.25 examples/s]
Generating train split: 17433399 examples [26:45, 31696.94 examples/s]
Generating train split: 17437245 examples [26:46, 20207.90 examples/s]
Generating train split: 17440219 examples [26:46, 21234.77 examples/s]
Generating train split: 17443088 examples [26:46, 18115.31 examples/s]
Generating train split: 17445471 examples [26:46, 14341.49 examples/s]
Generating train split: 17448131 examples [26:46, 16225.92 examples/s]
Generating train split: 17450261 examples [26:47, 15201.48 examples/s]
Generating train split: 17452136 examples [26:47, 11900.54 examples/s]
Generating train split: 17455569 examples [26:47, 15583.64 examples/s]
Generating train split: 17459577 examples [26:47, 20153.99 examples/s]
Generating train split: 17462207 examples [26:47, 17056.01 examples/s]
Generating train split: 17466485 examples [26:47, 22064.34 examples/s]
Generating train split: 17471393 examples [26:47, 27932.63 examples/s]
Generating train split: 17475127 examples [26:48, 28076.50 examples/s]
Generating train split: 17478400 examples [26:48, 16240.48 examples/s]
Generating train split: 17480909 examples [26:49, 11284.77 examples/s]
Generating train split: 17482918 examples [26:49, 12407.69 examples/s]
Generating train split: 17484887 examples [26:49, 13519.90 examples/s]
Generating train split: 17486853 examples [26:49, 8643.88 examples/s] 
Generating train split: 17488351 examples [26:50, 6492.20 examples/s]
Generating train split: 17489503 examples [26:50, 6963.26 examples/s]
Generating train split: 17490613 examples [26:50, 6828.59 examples/s]
Generating train split: 17491592 examples [26:50, 5891.29 examples/s]
Generating train split: 17492964 examples [26:50, 7055.85 examples/s]
Generating train split: 17493938 examples [26:50, 7176.42 examples/s]
Generating train split: 17494849 examples [26:51, 5981.41 examples/s]
Generating train split: 17495599 examples [26:51, 5101.96 examples/s]
Generating train split: 17496899 examples [26:51, 6201.85 examples/s]
Generating train split: 17497662 examples [26:51, 5458.49 examples/s]
Generating train split: 17499125 examples [26:51, 7167.34 examples/s]
Generating train split: 17500021 examples [26:52, 4938.89 examples/s]
Generating train split: 17500856 examples [26:52, 5498.65 examples/s]
Generating train split: 17501601 examples [26:52, 5411.84 examples/s]
Generating train split: 17502281 examples [26:52, 4098.04 examples/s]
Generating train split: 17502824 examples [26:52, 4217.92 examples/s]
Generating train split: 17503356 examples [26:52, 4171.14 examples/s]
Generating train split: 17503998 examples [26:53, 4608.41 examples/s]
Generating train split: 17504537 examples [26:53, 3939.55 examples/s]
Generating train split: 17507321 examples [26:53, 8955.79 examples/s]
Generating train split: 17511056 examples [26:53, 15396.63 examples/s]
Generating train split: 17513672 examples [26:53, 18045.13 examples/s]
Generating train split: 17515989 examples [26:53, 19342.28 examples/s]
Generating train split: 17518157 examples [26:53, 17382.50 examples/s]
Generating train split: 17520509 examples [26:53, 18922.39 examples/s]
Generating train split: 17522576 examples [26:54, 15710.96 examples/s]
Generating train split: 17524642 examples [26:54, 16797.71 examples/s]
Generating train split: 17526493 examples [26:54, 16279.81 examples/s]
Generating train split: 17528777 examples [26:54, 17891.14 examples/s]
Generating train split: 17531536 examples [26:54, 20277.64 examples/s]
Generating train split: 17534260 examples [26:54, 22110.32 examples/s]
Generating train split: 17536567 examples [26:54, 14954.10 examples/s]
Generating train split: 17539914 examples [26:54, 18838.85 examples/s]
Generating train split: 17544842 examples [26:55, 25869.59 examples/s]
Generating train split: 17554614 examples [26:55, 43698.81 examples/s]
Generating train split: 17563157 examples [26:55, 53501.69 examples/s]
Generating train split: 17569098 examples [26:55, 29615.96 examples/s]
Generating train split: 17573680 examples [26:55, 28868.60 examples/s]
Generating train split: 17577692 examples [26:56, 26086.96 examples/s]
Generating train split: 17581092 examples [26:56, 22934.98 examples/s]
Generating train split: 17585125 examples [26:56, 25969.41 examples/s]
Generating train split: 17588341 examples [26:56, 22272.68 examples/s]
Generating train split: 17591063 examples [26:56, 18506.79 examples/s]
Generating train split: 17594538 examples [26:56, 21380.21 examples/s]
Generating train split: 17597156 examples [26:57, 20357.92 examples/s]
Generating train split: 17599522 examples [26:57, 18874.92 examples/s]
Generating train split: 17602382 examples [26:57, 20828.97 examples/s]
Generating train split: 17605853 examples [26:57, 23998.18 examples/s]
Generating train split: 17609557 examples [26:57, 27054.29 examples/s]
Generating train split: 17612510 examples [26:57, 21625.67 examples/s]
Generating train split: 17618556 examples [26:57, 30352.93 examples/s]
Generating train split: 17629042 examples [26:57, 48454.28 examples/s]
Generating train split: 17636385 examples [26:58, 52907.57 examples/s]
Generating train split: 17642253 examples [26:58, 38375.60 examples/s]
Generating train split: 17647044 examples [26:58, 25622.16 examples/s]
Generating train split: 17650779 examples [26:58, 22773.32 examples/s]
Generating train split: 17653888 examples [26:59, 16127.89 examples/s]
Generating train split: 17656292 examples [26:59, 16502.10 examples/s]
Generating train split: 17658527 examples [26:59, 11170.43 examples/s]
Generating train split: 17660241 examples [27:00, 11816.87 examples/s]
Generating train split: 17661927 examples [27:00, 8446.75 examples/s] 
Generating train split: 17663336 examples [27:00, 9090.68 examples/s]
Generating train split: 17666105 examples [27:00, 11883.21 examples/s]
Generating train split: 17667853 examples [27:00, 11958.92 examples/s]
Generating train split: 17672793 examples [27:00, 19069.49 examples/s]
Generating train split: 17677281 examples [27:01, 24573.39 examples/s]
Generating train split: 17682468 examples [27:01, 30942.09 examples/s]
Generating train split: 17688317 examples [27:01, 37818.69 examples/s]
Generating train split: 17696452 examples [27:01, 49268.37 examples/s]
Generating train split: 17702933 examples [27:01, 53512.43 examples/s]
Generating train split: 17710133 examples [27:01, 58690.76 examples/s]
Generating train split: 17716362 examples [27:01, 59414.67 examples/s]
Generating train split: 17723520 examples [27:01, 62924.23 examples/s]
Generating train split: 17730003 examples [27:01, 62758.56 examples/s]
Generating train split: 17736412 examples [27:01, 62617.78 examples/s]
Generating train split: 17742859 examples [27:02, 63138.35 examples/s]
Generating train split: 17749531 examples [27:02, 64193.43 examples/s]
Generating train split: 17756314 examples [27:02, 65251.27 examples/s]
Generating train split: 17762877 examples [27:02, 64553.64 examples/s]
Generating train split: 17769373 examples [27:02, 63310.60 examples/s]
Generating train split: 17775730 examples [27:02, 57650.72 examples/s]
Generating train split: 17784466 examples [27:02, 65825.87 examples/s]
Generating train split: 17795422 examples [27:02, 78144.27 examples/s]
Generating train split: 17803424 examples [27:02, 74843.91 examples/s]
Generating train split: 17811062 examples [27:03, 62338.52 examples/s]
Generating train split: 17818744 examples [27:03, 65944.85 examples/s]
Generating train split: 17826464 examples [27:03, 68882.51 examples/s]
Generating train split: 17834602 examples [27:03, 72248.32 examples/s]
Generating train split: 17842338 examples [27:03, 73659.95 examples/s]
Generating train split: 17849897 examples [27:03, 70507.62 examples/s]
Generating train split: 17857456 examples [27:03, 71876.92 examples/s]
Generating train split: 17865932 examples [27:03, 75529.23 examples/s]
Generating train split: 17873592 examples [27:03, 75518.16 examples/s]
Generating train split: 17881215 examples [27:03, 75543.83 examples/s]
Generating train split: 17889959 examples [27:04, 79018.17 examples/s]
Generating train split: 17897911 examples [27:04, 68492.36 examples/s]
Generating train split: 17905042 examples [27:04, 56204.61 examples/s]
Generating train split: 17911176 examples [27:04, 41777.92 examples/s]
Generating train split: 17916191 examples [27:04, 42304.45 examples/s]
Generating train split: 17921030 examples [27:05, 33708.46 examples/s]
Generating train split: 17925029 examples [27:05, 29459.31 examples/s]
Generating train split: 17928441 examples [27:05, 28728.51 examples/s]
Generating train split: 17936677 examples [27:05, 39602.51 examples/s]
Generating train split: 17945403 examples [27:05, 50302.86 examples/s]
Generating train split: 17951304 examples [27:05, 47197.75 examples/s]
Generating train split: 17956656 examples [27:06, 29158.08 examples/s]
Generating train split: 17965338 examples [27:06, 38911.56 examples/s]
Generating train split: 17976228 examples [27:06, 52533.27 examples/s]
Generating train split: 17983366 examples [27:06, 46040.36 examples/s]
Generating train split: 17993176 examples [27:06, 56540.48 examples/s]
Generating train split: 18001305 examples [27:06, 62059.27 examples/s]
Generating train split: 18008765 examples [27:07, 30493.25 examples/s]
Generating train split: 18016136 examples [27:07, 36516.04 examples/s]
Generating train split: 18022274 examples [27:08, 15254.84 examples/s]
Generating train split: 18026740 examples [27:09, 11688.62 examples/s]
Generating train split: 18030050 examples [27:09, 9573.17 examples/s] 
Generating train split: 18032528 examples [27:10, 8517.13 examples/s]
Generating train split: 18034425 examples [27:10, 8143.99 examples/s]
Generating train split: 18035954 examples [27:10, 8460.19 examples/s]
Generating train split: 18038773 examples [27:10, 10514.17 examples/s]
Generating train split: 18043944 examples [27:10, 15848.58 examples/s]
Generating train split: 18049267 examples [27:11, 21684.09 examples/s]
Generating train split: 18052850 examples [27:11, 17040.48 examples/s]
Generating train split: 18055675 examples [27:11, 17899.54 examples/s]
Generating train split: 18058299 examples [27:11, 15328.80 examples/s]
Generating train split: 18060515 examples [27:11, 16188.29 examples/s]
Generating train split: 18062829 examples [27:11, 17491.73 examples/s]
Generating train split: 18072572 examples [27:12, 34399.81 examples/s]
Generating train split: 18082682 examples [27:12, 48345.20 examples/s]
Generating train split: 18088476 examples [27:12, 35646.57 examples/s]
Generating train split: 18099249 examples [27:12, 49793.38 examples/s]
Generating train split: 18109726 examples [27:12, 59207.82 examples/s]
Generating train split: 18116909 examples [27:13, 25425.96 examples/s]
Generating train split: 18122237 examples [27:13, 25389.75 examples/s]
Generating train split: 18132483 examples [27:13, 35432.56 examples/s]
Generating train split: 18143330 examples [27:13, 46897.25 examples/s]
Generating train split: 18150933 examples [27:14, 37164.35 examples/s]
Generating train split: 18156977 examples [27:14, 25188.90 examples/s]
Generating train split: 18162729 examples [27:14, 29116.86 examples/s]
Generating train split: 18173558 examples [27:14, 40826.48 examples/s]
Generating train split: 18183567 examples [27:14, 50834.41 examples/s]
Generating train split: 18191162 examples [27:15, 36161.94 examples/s]
Generating train split: 18201354 examples [27:15, 46363.11 examples/s]
Generating train split: 18208559 examples [27:15, 47798.41 examples/s]
Generating train split: 18216313 examples [27:15, 53597.41 examples/s]
Generating train split: 18225027 examples [27:15, 60899.92 examples/s]
Generating train split: 18232517 examples [27:15, 50468.95 examples/s]
Generating train split: 18243128 examples [27:16, 62183.03 examples/s]
Generating train split: 18250940 examples [27:16, 65848.07 examples/s]
Generating train split: 18258604 examples [27:16, 31923.80 examples/s]
Generating train split: 18264378 examples [27:17, 23434.36 examples/s]
Generating train split: 18268791 examples [27:17, 22938.93 examples/s]
Generating train split: 18272520 examples [27:17, 18598.00 examples/s]
Generating train split: 18275442 examples [27:17, 18224.96 examples/s]
Generating train split: 18277998 examples [27:18, 13979.97 examples/s]
Generating train split: 18279990 examples [27:18, 14242.80 examples/s]
Generating train split: 18282952 examples [27:18, 16505.42 examples/s]
Generating train split: 18285187 examples [27:18, 17521.40 examples/s]
Generating train split: 18287402 examples [27:18, 15807.85 examples/s]
Generating train split: 18289306 examples [27:18, 14411.55 examples/s]
Generating train split: 18292348 examples [27:19, 17563.10 examples/s]
Generating train split: 18294433 examples [27:19, 16649.19 examples/s]
Generating train split: 18296327 examples [27:19, 14368.39 examples/s]
Generating train split: 18297972 examples [27:19, 13486.75 examples/s]
Generating train split: 18300713 examples [27:19, 16473.84 examples/s]
Generating train split: 18303225 examples [27:19, 18172.42 examples/s]
Generating train split: 18305238 examples [27:19, 17985.69 examples/s]
Generating train split: 18307566 examples [27:19, 19324.27 examples/s]
Generating train split: 18309623 examples [27:20, 18427.33 examples/s]
Generating train split: 18311609 examples [27:20, 18796.67 examples/s]
Generating train split: 18313560 examples [27:20, 10968.26 examples/s]
Generating train split: 18315092 examples [27:20, 10646.60 examples/s]
Generating train split: 18318903 examples [27:20, 15730.81 examples/s]
Generating train split: 18320930 examples [27:20, 15104.16 examples/s]
Generating train split: 18322756 examples [27:21, 13636.35 examples/s]
Generating train split: 18324724 examples [27:21, 14886.72 examples/s]
Generating train split: 18326432 examples [27:21, 14824.57 examples/s]
Generating train split: 18328067 examples [27:21, 12725.82 examples/s]
Generating train split: 18330018 examples [27:21, 14241.04 examples/s]
Generating train split: 18332117 examples [27:21, 15655.60 examples/s]
Generating train split: 18337204 examples [27:21, 24610.78 examples/s]
Generating train split: 18348395 examples [27:21, 47878.41 examples/s]
Generating train split: 18356333 examples [27:22, 56543.19 examples/s]
Generating train split: 18362396 examples [27:22, 47654.44 examples/s]
Generating train split: 18372677 examples [27:22, 61440.10 examples/s]
Generating train split: 18380443 examples [27:22, 65651.48 examples/s]
Generating train split: 18387514 examples [27:23, 26623.48 examples/s]
Generating train split: 18392792 examples [27:23, 18990.44 examples/s]
Generating train split: 18396789 examples [27:23, 20662.63 examples/s]
Generating train split: 18407329 examples [27:23, 31689.42 examples/s]
Generating train split: 18413120 examples [27:24, 29533.15 examples/s]
Generating train split: 18417915 examples [27:24, 28520.91 examples/s]
Generating train split: 18422031 examples [27:24, 28017.79 examples/s]
Generating train split: 18431991 examples [27:24, 40655.54 examples/s]
Generating train split: 18442094 examples [27:24, 51572.30 examples/s]
Generating train split: 18448694 examples [27:24, 37865.08 examples/s]
Generating train split: 18453977 examples [27:25, 29211.69 examples/s]
Generating train split: 18458168 examples [27:25, 23267.94 examples/s]
Generating train split: 18461498 examples [27:25, 24164.11 examples/s]
Generating train split: 18464714 examples [27:25, 19975.42 examples/s]
Generating train split: 18471426 examples [27:26, 27340.66 examples/s]
Generating train split: 18487409 examples [27:26, 51514.99 examples/s]
Generating train split: 18495893 examples [27:26, 58387.95 examples/s]
Generating train split: 18503682 examples [27:26, 32489.36 examples/s]
Generating train split: 18509595 examples [27:27, 27075.87 examples/s]
Generating train split: 18514258 examples [27:27, 25787.15 examples/s]
Generating train split: 18518178 examples [27:27, 26084.96 examples/s]
Generating train split: 18528721 examples [27:27, 38789.06 examples/s]
Generating train split: 18539931 examples [27:27, 52064.25 examples/s]
Generating train split: 18547134 examples [27:28, 34325.59 examples/s]
Generating train split: 18552704 examples [27:28, 29643.60 examples/s]
Generating train split: 18557227 examples [27:28, 25357.81 examples/s]
Generating train split: 18560893 examples [27:28, 24608.29 examples/s]
Generating train split: 18564108 examples [27:29, 16609.66 examples/s]
Generating train split: 18566572 examples [27:29, 17529.43 examples/s]
Generating train split: 18569781 examples [27:29, 19555.46 examples/s]
Generating train split: 18572402 examples [27:29, 16329.69 examples/s]
Generating train split: 18574553 examples [27:29, 16619.75 examples/s]
Generating train split: 18576671 examples [27:29, 17064.31 examples/s]
Generating train split: 18578663 examples [27:30, 14152.17 examples/s]
Generating train split: 18580335 examples [27:30, 12019.42 examples/s]
Generating train split: 18584173 examples [27:30, 16834.52 examples/s]
Generating train split: 18588722 examples [27:30, 22769.19 examples/s]
Generating train split: 18595300 examples [27:30, 32580.57 examples/s]
Generating train split: 18599429 examples [27:30, 34713.32 examples/s]
Generating train split: 18604925 examples [27:30, 39970.79 examples/s]
Generating train split: 18609770 examples [27:30, 42183.13 examples/s]
Generating train split: 18618023 examples [27:31, 53258.21 examples/s]
Generating train split: 18624791 examples [27:31, 57272.77 examples/s]
Generating train split: 18632629 examples [27:31, 63303.57 examples/s]
Generating train split: 18639158 examples [27:31, 48830.83 examples/s]
Generating train split: 18644698 examples [27:31, 41157.44 examples/s]
Generating train split: 18649427 examples [27:31, 39736.89 examples/s]
Generating train split: 18654172 examples [27:31, 38866.79 examples/s]
Generating train split: 18658353 examples [27:32, 32335.01 examples/s]
Generating train split: 18661915 examples [27:32, 25922.89 examples/s]
Generating train split: 18664887 examples [27:32, 21762.49 examples/s]
Generating train split: 18667379 examples [27:32, 21470.16 examples/s]
Generating train split: 18669935 examples [27:32, 22253.09 examples/s]
Generating train split: 18672340 examples [27:32, 22085.42 examples/s]
Generating train split: 18674678 examples [27:33, 16047.10 examples/s]
Generating train split: 18677028 examples [27:33, 17433.89 examples/s]
Generating train split: 18679231 examples [27:33, 18368.80 examples/s]
Generating train split: 18682410 examples [27:33, 21506.39 examples/s]
Generating train split: 18684807 examples [27:33, 13032.95 examples/s]
Generating train split: 18686688 examples [27:33, 14030.95 examples/s]
Generating train split: 18688561 examples [27:34, 12643.73 examples/s]
Generating train split: 18690227 examples [27:34, 13420.34 examples/s]
Generating train split: 18691919 examples [27:34, 14176.71 examples/s]
Generating train split: 18696030 examples [27:34, 20550.32 examples/s]
Generating train split: 18702223 examples [27:34, 30999.11 examples/s]
Generating train split: 18713407 examples [27:34, 52421.87 examples/s]
Generating train split: 18719232 examples [27:34, 33017.55 examples/s]
Generating train split: 18725615 examples [27:35, 38970.07 examples/s]
Generating train split: 18739308 examples [27:35, 60171.62 examples/s]
Generating train split: 18748248 examples [27:35, 67067.22 examples/s]
Generating train split: 18756328 examples [27:35, 39908.99 examples/s]
Generating train split: 18762595 examples [27:35, 42164.58 examples/s]
Generating train split: 18774029 examples [27:35, 55797.53 examples/s]
Generating train split: 18784563 examples [27:36, 66226.31 examples/s]
Generating train split: 18793005 examples [27:36, 39013.40 examples/s]
Generating train split: 18799487 examples [27:36, 34516.62 examples/s]
Generating train split: 18804781 examples [27:37, 24680.52 examples/s]
Generating train split: 18808841 examples [27:37, 23794.72 examples/s]
Generating train split: 18812305 examples [27:37, 20629.79 examples/s]
Generating train split: 18815124 examples [27:37, 18781.15 examples/s]
Generating train split: 18817496 examples [27:37, 17627.77 examples/s]
Generating train split: 18820013 examples [27:38, 18815.76 examples/s]
Generating train split: 18822227 examples [27:38, 11219.18 examples/s]
Generating train split: 18823909 examples [27:38, 9337.27 examples/s] 
Generating train split: 18825248 examples [27:39, 9793.85 examples/s]
Generating train split: 18826833 examples [27:39, 10720.06 examples/s]
Generating train split: 18831466 examples [27:39, 17115.20 examples/s]
Generating train split: 18835153 examples [27:39, 21132.82 examples/s]
Generating train split: 18839720 examples [27:39, 26191.41 examples/s]
Generating train split: 18846747 examples [27:39, 36796.46 examples/s]
Generating train split: 18851390 examples [27:39, 39256.77 examples/s]
Generating train split: 18855830 examples [27:39, 26196.92 examples/s]
Generating train split: 18859371 examples [27:40, 25065.14 examples/s]
Generating train split: 18862520 examples [27:40, 25730.27 examples/s]
Generating train split: 18867433 examples [27:40, 30857.22 examples/s]
Generating train split: 18871040 examples [27:40, 31768.96 examples/s]
Generating train split: 18874606 examples [27:40, 24107.37 examples/s]
Generating train split: 18878560 examples [27:40, 27329.88 examples/s]
Generating train split: 18881819 examples [27:40, 28534.22 examples/s]
Generating train split: 18887585 examples [27:40, 35745.12 examples/s]
Generating train split: 18895768 examples [27:41, 47786.25 examples/s]
Generating train split: 18901063 examples [27:41, 49188.13 examples/s]
Generating train split: 18909178 examples [27:41, 58094.76 examples/s]
Generating train split: 18915305 examples [27:41, 40679.01 examples/s]
Generating train split: 18920311 examples [27:41, 38462.74 examples/s]
Generating train split: 18927440 examples [27:41, 45679.61 examples/s]
Generating train split: 18933537 examples [27:41, 49318.65 examples/s]
Generating train split: 18939063 examples [27:41, 48980.32 examples/s]
Generating train split: 18944382 examples [27:42, 48920.51 examples/s]
Generating train split: 18949565 examples [27:42, 47570.04 examples/s]
Generating train split: 18954523 examples [27:42, 44064.66 examples/s]
Generating train split: 18959880 examples [27:42, 46518.39 examples/s]
Generating train split: 18967973 examples [27:42, 55786.54 examples/s]
Generating train split: 18973777 examples [27:42, 55108.94 examples/s]
Generating train split: 18979449 examples [27:42, 54622.01 examples/s]
Generating train split: 18985014 examples [27:42, 52191.80 examples/s]
Generating train split: 18991357 examples [27:42, 55287.40 examples/s]
Generating train split: 18996995 examples [27:43, 47288.67 examples/s]
Generating train split: 19001981 examples [27:43, 43339.17 examples/s]
Generating train split: 19006813 examples [27:43, 44502.98 examples/s]
Generating train split: 19013926 examples [27:43, 51464.96 examples/s]
Generating train split: 19020247 examples [27:43, 54596.89 examples/s]
Generating train split: 19025903 examples [27:43, 32460.27 examples/s]
Generating train split: 19030339 examples [27:44, 31181.68 examples/s]
Generating train split: 19034689 examples [27:44, 33353.88 examples/s]
Generating train split: 19038712 examples [27:44, 20943.37 examples/s]
Generating train split: 19042152 examples [27:44, 23060.02 examples/s]
Generating train split: 19045362 examples [27:44, 19621.16 examples/s]
Generating train split: 19048020 examples [27:45, 20067.08 examples/s]
Generating train split: 19051095 examples [27:45, 21881.95 examples/s]
Generating train split: 19057174 examples [27:45, 30170.33 examples/s]
Generating train split: 19060837 examples [27:45, 29610.65 examples/s]
Generating train split: 19067425 examples [27:45, 38225.54 examples/s]
Generating train split: 19074364 examples [27:45, 45703.51 examples/s]
Generating train split: 19079427 examples [27:45, 34140.67 examples/s]
Generating train split: 19083601 examples [27:45, 35017.23 examples/s]
Generating train split: 19087842 examples [27:46, 36718.11 examples/s]
Generating train split: 19093610 examples [27:46, 41845.15 examples/s]
Generating train split: 19098618 examples [27:46, 43993.69 examples/s]
Generating train split: 19107096 examples [27:46, 55071.06 examples/s]
Generating train split: 19116712 examples [27:46, 66554.28 examples/s]
Generating train split: 19123715 examples [27:46, 65720.38 examples/s]
Generating train split: 19130513 examples [27:46, 65480.81 examples/s]
Generating train split: 19137229 examples [27:46, 54644.73 examples/s]
Generating train split: 19143733 examples [27:46, 57247.88 examples/s]
Generating train split: 19150840 examples [27:47, 60893.70 examples/s]
Generating train split: 19157211 examples [27:47, 56977.13 examples/s]
Generating train split: 19163153 examples [27:47, 46051.95 examples/s]
Generating train split: 19168601 examples [27:47, 47849.48 examples/s]
Generating train split: 19174251 examples [27:47, 49423.83 examples/s]
Generating train split: 19180609 examples [27:47, 53094.45 examples/s]
Generating train split: 19186177 examples [27:47, 48917.63 examples/s]
Generating train split: 19191629 examples [27:47, 50371.80 examples/s]
Generating train split: 19198702 examples [27:47, 55865.08 examples/s]
Generating train split: 19204475 examples [27:48, 54846.73 examples/s]
Generating train split: 19210099 examples [27:48, 35824.32 examples/s]
Generating train split: 19214604 examples [27:48, 34597.22 examples/s]
Generating train split: 19219155 examples [27:48, 36891.23 examples/s]
Generating train split: 19223384 examples [27:49, 22793.63 examples/s]
Generating train split: 19228707 examples [27:49, 27833.14 examples/s]
Generating train split: 19232610 examples [27:49, 28380.74 examples/s]
Generating train split: 19242765 examples [27:49, 43419.79 examples/s]
Generating train split: 19253149 examples [27:49, 57134.76 examples/s]
Generating train split: 19260185 examples [27:49, 39386.83 examples/s]
Generating train split: 19265781 examples [27:49, 37963.03 examples/s]
Generating train split: 19270718 examples [27:50, 37626.53 examples/s]
Generating train split: 19275274 examples [27:50, 36108.39 examples/s]
Generating train split: 19279425 examples [27:50, 33735.78 examples/s]
Generating train split: 19283179 examples [27:50, 24340.18 examples/s]
Generating train split: 19288905 examples [27:50, 30192.08 examples/s]
Generating train split: 19292730 examples [27:50, 31127.84 examples/s]
Generating train split: 19296445 examples [27:50, 31040.23 examples/s]
Generating train split: 19300520 examples [27:51, 33277.38 examples/s]
Generating train split: 19304216 examples [27:51, 27536.91 examples/s]
Generating train split: 19308271 examples [27:51, 29986.06 examples/s]
Generating train split: 19311614 examples [27:51, 27747.27 examples/s]
Generating train split: 19316467 examples [27:51, 32509.41 examples/s]
Generating train split: 19320031 examples [27:51, 29856.95 examples/s]
Generating train split: 19323255 examples [27:51, 27338.00 examples/s]
Generating train split: 19326180 examples [27:52, 24894.71 examples/s]
Generating train split: 19329348 examples [27:52, 26475.56 examples/s]
Generating train split: 19333074 examples [27:52, 29034.69 examples/s]
Generating train split: 19336127 examples [27:52, 27810.86 examples/s]
Generating train split: 19340855 examples [27:52, 32874.25 examples/s]
Generating train split: 19344289 examples [27:52, 19732.93 examples/s]
Generating train split: 19346988 examples [27:53, 15597.68 examples/s]
Generating train split: 19349162 examples [27:53, 16038.12 examples/s]
Generating train split: 19351218 examples [27:53, 11740.22 examples/s]
Generating train split: 19353299 examples [27:53, 13078.02 examples/s]
Generating train split: 19355044 examples [27:53, 11877.58 examples/s]
Generating train split: 19356538 examples [27:54, 10180.37 examples/s]
Generating train split: 19358528 examples [27:54, 11871.20 examples/s]
Generating train split: 19360003 examples [27:54, 10321.90 examples/s]
Generating train split: 19361250 examples [27:54, 9354.56 examples/s] 
Generating train split: 19362333 examples [27:54, 9020.30 examples/s]
Generating train split: 19363333 examples [27:54, 8850.94 examples/s]
Generating train split: 19364390 examples [27:54, 9209.49 examples/s]
Generating train split: 19365387 examples [27:55, 9095.92 examples/s]
Generating train split: 19366554 examples [27:55, 9715.95 examples/s]
Generating train split: 19367600 examples [27:55, 9551.75 examples/s]
Generating train split: 19368596 examples [27:55, 9653.06 examples/s]
Generating train split: 19369889 examples [27:55, 10545.20 examples/s]
Generating train split: 19370976 examples [27:55, 8952.90 examples/s] 
Generating train split: 19371926 examples [27:55, 6754.40 examples/s]
Generating train split: 19372716 examples [27:56, 5552.31 examples/s]
Generating train split: 19373590 examples [27:56, 6114.63 examples/s]
Generating train split: 19374313 examples [27:56, 5464.42 examples/s]
Generating train split: 19375607 examples [27:56, 6865.14 examples/s]
Generating train split: 19376547 examples [27:56, 7421.87 examples/s]
Generating train split: 19377385 examples [27:56, 5640.55 examples/s]
Generating train split: 19378071 examples [27:57, 4104.85 examples/s]
Generating train split: 19378952 examples [27:57, 4876.00 examples/s]
Generating train split: 19379600 examples [27:57, 4394.29 examples/s]
Generating train split: 19380879 examples [27:57, 5982.49 examples/s]
Generating train split: 19383746 examples [27:57, 10817.93 examples/s]
Generating train split: 19388866 examples [27:57, 20241.64 examples/s]
Generating train split: 19392422 examples [27:57, 24021.93 examples/s]
Generating train split: 19395249 examples [27:58, 17299.38 examples/s]
Generating train split: 19398316 examples [27:58, 20035.91 examples/s]
Generating train split: 19405766 examples [27:58, 32381.97 examples/s]
Generating train split: 19415024 examples [27:58, 47102.34 examples/s]
Generating train split: 19421502 examples [27:58, 50126.56 examples/s]
Generating train split: 19427140 examples [27:58, 27958.86 examples/s]
Generating train split: 19431488 examples [27:59, 30227.65 examples/s]
Generating train split: 19435770 examples [27:59, 26069.04 examples/s]
Generating train split: 19439316 examples [27:59, 25296.87 examples/s]
Generating train split: 19442931 examples [27:59, 27352.24 examples/s]
Generating train split: 19453892 examples [27:59, 44902.44 examples/s]
Generating train split: 19460864 examples [27:59, 50699.84 examples/s]
Generating train split: 19466882 examples [28:00, 31669.53 examples/s]
Generating train split: 19471584 examples [28:00, 27395.39 examples/s]
Generating train split: 19481486 examples [28:00, 39341.20 examples/s]
Generating train split: 19492072 examples [28:00, 52139.91 examples/s]
Generating train split: 19499220 examples [28:01, 28946.98 examples/s]
Generating train split: 19508238 examples [28:01, 37313.18 examples/s]
Generating train split: 19519576 examples [28:01, 49729.89 examples/s]
Generating train split: 19528213 examples [28:01, 56650.74 examples/s]
Generating train split: 19536358 examples [28:01, 33404.87 examples/s]
Generating train split: 19542546 examples [28:02, 23367.20 examples/s]
Generating train split: 19547233 examples [28:02, 23336.01 examples/s]
Generating train split: 19551215 examples [28:02, 19738.95 examples/s]
Generating train split: 19555922 examples [28:03, 23074.45 examples/s]
Generating train split: 19566384 examples [28:03, 35178.37 examples/s]
Generating train split: 19576517 examples [28:03, 45820.15 examples/s]
Generating train split: 19583213 examples [28:03, 30400.52 examples/s]
Generating train split: 19588381 examples [28:04, 21325.72 examples/s]
Generating train split: 19592308 examples [28:04, 19986.22 examples/s]
Generating train split: 19599760 examples [28:04, 26801.44 examples/s]
Generating train split: 19611206 examples [28:04, 40077.47 examples/s]
Generating train split: 19617790 examples [28:05, 26561.54 examples/s]
Generating train split: 19622813 examples [28:05, 27197.51 examples/s]
Generating train split: 19633649 examples [28:05, 39100.53 examples/s]
Generating train split: 19642510 examples [28:05, 47554.64 examples/s]
Generating train split: 19649564 examples [28:05, 49667.02 examples/s]
Generating train split: 19660010 examples [28:05, 61297.34 examples/s]
Generating train split: 19668507 examples [28:05, 66803.69 examples/s]
Generating train split: 19676509 examples [28:06, 44827.09 examples/s]
Generating train split: 19687114 examples [28:06, 56190.39 examples/s]
Generating train split: 19694742 examples [28:06, 47516.89 examples/s]
Generating train split: 19701078 examples [28:06, 29468.29 examples/s]
Generating train split: 19705919 examples [28:07, 28172.34 examples/s]
Generating train split: 19710028 examples [28:07, 22684.35 examples/s]
Generating train split: 19713293 examples [28:07, 22581.63 examples/s]
Generating train split: 19716970 examples [28:07, 24768.89 examples/s]
Generating train split: 19720147 examples [28:08, 18398.49 examples/s]
Generating train split: 19722653 examples [28:08, 19324.63 examples/s]
Generating train split: 19726455 examples [28:08, 21262.40 examples/s]
Generating train split: 19729026 examples [28:08, 20239.59 examples/s]
Generating train split: 19731841 examples [28:08, 21831.93 examples/s]
Generating train split: 19736431 examples [28:08, 27185.01 examples/s]
Generating train split: 19740939 examples [28:08, 31504.98 examples/s]
Generating train split: 19744890 examples [28:08, 33560.63 examples/s]
Generating train split: 19748535 examples [28:09, 27504.61 examples/s]
Generating train split: 19751657 examples [28:09, 26997.98 examples/s]
Generating train split: 19754777 examples [28:09, 28013.73 examples/s]
Generating train split: 19759398 examples [28:09, 32689.64 examples/s]
Generating train split: 19769884 examples [28:09, 52069.88 examples/s]
Generating train split: 19780333 examples [28:09, 66594.97 examples/s]
Generating train split: 19787379 examples [28:09, 65582.30 examples/s]
Generating train split: 19794217 examples [28:10, 34413.75 examples/s]
Generating train split: 19799476 examples [28:10, 32704.64 examples/s]
Generating train split: 19804009 examples [28:10, 22699.08 examples/s]
Generating train split: 19808116 examples [28:10, 25269.19 examples/s]
Generating train split: 19815810 examples [28:10, 33926.23 examples/s]
Generating train split: 19825944 examples [28:11, 46942.76 examples/s]
Generating train split: 19832403 examples [28:11, 35843.41 examples/s]
Generating train split: 19837599 examples [28:11, 29902.16 examples/s]
Generating train split: 19841828 examples [28:11, 24066.77 examples/s]
Generating train split: 19845208 examples [28:12, 20538.38 examples/s]
Generating train split: 19847962 examples [28:12, 20212.06 examples/s]
Generating train split: 19850470 examples [28:12, 13931.60 examples/s]
Generating train split: 19852436 examples [28:12, 14660.32 examples/s]
Generating train split: 19856065 examples [28:12, 18119.61 examples/s]
Generating train split: 19858498 examples [28:13, 14657.13 examples/s]
Generating train split: 19860480 examples [28:13, 12964.92 examples/s]
Generating train split: 19862144 examples [28:13, 11893.26 examples/s]
Generating train split: 19863572 examples [28:13, 11501.79 examples/s]
Generating train split: 19866456 examples [28:13, 14756.29 examples/s]
Generating train split: 19876105 examples [28:13, 32051.36 examples/s]
Generating train split: 19884947 examples [28:13, 44797.68 examples/s]
Generating train split: 19890420 examples [28:14, 25362.06 examples/s]
Generating train split: 19894623 examples [28:14, 23163.54 examples/s]
Generating train split: 19898106 examples [28:15, 17540.31 examples/s]
Generating train split: 19900833 examples [28:15, 16923.06 examples/s]
Generating train split: 19903513 examples [28:15, 18345.94 examples/s]
Generating train split: 19905957 examples [28:15, 13151.18 examples/s]
Generating train split: 19907859 examples [28:15, 12762.41 examples/s]
Generating train split: 19909536 examples [28:16, 12523.90 examples/s]
Generating train split: 19911408 examples [28:16, 13573.54 examples/s]
Generating train split: 19913032 examples [28:16, 11248.29 examples/s]
Generating train split: 19915872 examples [28:16, 14425.05 examples/s]
Generating train split: 19917675 examples [28:16, 13118.27 examples/s]
Generating train split: 19919242 examples [28:16, 11228.99 examples/s]
Generating train split: 19920573 examples [28:16, 11567.68 examples/s]
Generating train split: 19923044 examples [28:17, 14365.94 examples/s]
Generating train split: 19924707 examples [28:17, 13062.39 examples/s]
Generating train split: 19927766 examples [28:17, 17055.04 examples/s]
Generating train split: 19929834 examples [28:17, 17839.34 examples/s]
Generating train split: 19931803 examples [28:17, 17734.15 examples/s]
Generating train split: 19937615 examples [28:17, 28364.29 examples/s]
Generating train split: 19943841 examples [28:17, 37497.59 examples/s]
Generating train split: 19947849 examples [28:18, 24080.37 examples/s]
Generating train split: 19951590 examples [28:18, 26762.93 examples/s]
Generating train split: 19955934 examples [28:18, 30475.77 examples/s]
Generating train split: 19959596 examples [28:18, 31643.34 examples/s]
Generating train split: 19969875 examples [28:18, 49769.57 examples/s]
Generating train split: 19979403 examples [28:18, 61887.57 examples/s]
Generating train split: 19986184 examples [28:18, 34210.08 examples/s]
Generating train split: 19991439 examples [28:19, 35023.79 examples/s]
Generating train split: 19996261 examples [28:19, 37525.35 examples/s]
Generating train split: 20007025 examples [28:19, 52465.36 examples/s]
Generating train split: 20017655 examples [28:19, 65030.77 examples/s]
Generating train split: 20025464 examples [28:19, 68155.04 examples/s]
Generating train split: 20033260 examples [28:19, 55164.32 examples/s]
Generating train split: 20039854 examples [28:19, 39860.74 examples/s]
Generating train split: 20045128 examples [28:20, 30038.56 examples/s]
Generating train split: 20049312 examples [28:20, 27308.47 examples/s]
Generating train split: 20052847 examples [28:20, 24495.23 examples/s]
Generating train split: 20056047 examples [28:20, 25654.81 examples/s]
Generating train split: 20059101 examples [28:20, 24037.33 examples/s]
Generating train split: 20061822 examples [28:21, 18978.34 examples/s]
Generating train split: 20064053 examples [28:21, 17563.71 examples/s]
Generating train split: 20066026 examples [28:21, 15826.99 examples/s]
Generating train split: 20067758 examples [28:21, 12350.20 examples/s]
Generating train split: 20069164 examples [28:22, 9451.46 examples/s] 
Generating train split: 20070295 examples [28:22, 9715.35 examples/s]
Generating train split: 20071422 examples [28:22, 9528.73 examples/s]
Generating train split: 20073073 examples [28:22, 10867.67 examples/s]
Generating train split: 20075274 examples [28:22, 13264.34 examples/s]
Generating train split: 20076792 examples [28:22, 11709.75 examples/s]
Generating train split: 20078721 examples [28:22, 13195.72 examples/s]
Generating train split: 20080194 examples [28:23, 10751.87 examples/s]
Generating train split: 20081435 examples [28:23, 9582.66 examples/s] 
Generating train split: 20083169 examples [28:23, 11081.33 examples/s]
Generating train split: 20084422 examples [28:23, 10760.87 examples/s]
Generating train split: 20085604 examples [28:23, 10428.54 examples/s]
Generating train split: 20086711 examples [28:23, 10489.74 examples/s]
Generating train split: 20087807 examples [28:23, 7431.36 examples/s] 
Generating train split: 20088886 examples [28:24, 7953.46 examples/s]
Generating train split: 20089805 examples [28:24, 7812.35 examples/s]
Generating train split: 20090674 examples [28:24, 5874.76 examples/s]
Generating train split: 20091382 examples [28:24, 3372.67 examples/s]
Generating train split: 20091927 examples [28:25, 3387.08 examples/s]
Generating train split: 20093174 examples [28:25, 4736.80 examples/s]
Generating train split: 20093883 examples [28:25, 3149.71 examples/s]
Generating train split: 20094487 examples [28:25, 3533.72 examples/s]
Generating train split: 20095233 examples [28:25, 4154.24 examples/s]
Generating train split: 20095848 examples [28:26, 2846.79 examples/s]
Generating train split: 20097281 examples [28:26, 4486.37 examples/s]
Generating train split: 20098047 examples [28:26, 3720.49 examples/s]
Generating train split: 20100267 examples [28:26, 6520.03 examples/s]
Generating train split: 20102049 examples [28:26, 8460.71 examples/s]
Generating train split: 20103318 examples [28:27, 4982.98 examples/s]
Generating train split: 20104829 examples [28:27, 6329.37 examples/s]
Generating train split: 20105961 examples [28:28, 4431.76 examples/s]
Generating train split: 20106896 examples [28:28, 5042.43 examples/s]
Generating train split: 20113625 examples [28:28, 14436.20 examples/s]
Generating train split: 20123367 examples [28:28, 29149.64 examples/s]
Generating train split: 20128144 examples [28:28, 16430.80 examples/s]
Generating train split: 20131723 examples [28:29, 18140.42 examples/s]
Generating train split: 20135054 examples [28:29, 15808.27 examples/s]
Generating train split: 20138090 examples [28:29, 17850.68 examples/s]
Generating train split: 20145789 examples [28:29, 27734.30 examples/s]
Generating train split: 20155484 examples [28:29, 41067.30 examples/s]
Generating train split: 20161371 examples [28:29, 32421.88 examples/s]
Generating train split: 20166133 examples [28:30, 30839.74 examples/s]
Generating train split: 20176471 examples [28:30, 44303.64 examples/s]
Generating train split: 20185321 examples [28:30, 53163.24 examples/s]
Generating train split: 20192088 examples [28:30, 39916.38 examples/s]
Generating train split: 20197544 examples [28:31, 21160.49 examples/s]
Generating train split: 20201630 examples [28:31, 20003.43 examples/s]
Generating train split: 20204975 examples [28:31, 18685.47 examples/s]
Generating train split: 20215388 examples [28:31, 30084.53 examples/s]
Generating train split: 20225374 examples [28:31, 41254.27 examples/s]
Generating train split: 20231926 examples [28:32, 27609.43 examples/s]
Generating train split: 20236943 examples [28:32, 17664.31 examples/s]
Generating train split: 20240698 examples [28:33, 18528.06 examples/s]
Generating train split: 20244030 examples [28:33, 17765.93 examples/s]
Generating train split: 20246818 examples [28:33, 17057.72 examples/s]
Generating train split: 20249262 examples [28:33, 17994.20 examples/s]
Generating train split: 20251637 examples [28:33, 17541.65 examples/s]
Generating train split: 20253779 examples [28:34, 12904.99 examples/s]
Generating train split: 20255474 examples [28:34, 12295.20 examples/s]
Generating train split: 20257705 examples [28:34, 13971.03 examples/s]
Generating train split: 20259706 examples [28:34, 14871.08 examples/s]
Generating train split: 20261729 examples [28:34, 16012.79 examples/s]
Generating train split: 20266754 examples [28:34, 24006.83 examples/s]
Generating train split: 20273841 examples [28:34, 35723.10 examples/s]
Generating train split: 20277918 examples [28:34, 33997.76 examples/s]
Generating train split: 20281697 examples [28:35, 29899.47 examples/s]
Generating train split: 20285025 examples [28:35, 20553.37 examples/s]
Generating train split: 20288117 examples [28:35, 22475.14 examples/s]
Generating train split: 20290905 examples [28:35, 22833.44 examples/s]
Generating train split: 20293571 examples [28:35, 18000.64 examples/s]
Generating train split: 20295775 examples [28:36, 17492.06 examples/s]
Generating train split: 20298204 examples [28:36, 18890.60 examples/s]
Generating train split: 20300349 examples [28:36, 18001.67 examples/s]
Generating train split: 20303915 examples [28:36, 22078.03 examples/s]
Generating train split: 20310429 examples [28:36, 32770.42 examples/s]
Generating train split: 20317140 examples [28:36, 41650.26 examples/s]
Generating train split: 20321708 examples [28:36, 27049.34 examples/s]
Generating train split: 20325346 examples [28:36, 28335.24 examples/s]
Generating train split: 20332765 examples [28:37, 38258.09 examples/s]
Generating train split: 20344063 examples [28:37, 55902.46 examples/s]
Generating train split: 20352929 examples [28:37, 64103.86 examples/s]
Generating train split: 20360256 examples [28:37, 33379.63 examples/s]
Generating train split: 20365846 examples [28:37, 36586.60 examples/s]
Generating train split: 20375439 examples [28:37, 47502.89 examples/s]
Generating train split: 20385151 examples [28:38, 56780.17 examples/s]
Generating train split: 20392534 examples [28:38, 33646.07 examples/s]
Generating train split: 20398189 examples [28:38, 36486.70 examples/s]
Generating train split: 20405154 examples [28:38, 42306.33 examples/s]
Generating train split: 20411080 examples [28:39, 33799.28 examples/s]
Generating train split: 20415877 examples [28:39, 31755.67 examples/s]
Generating train split: 20421326 examples [28:39, 35828.07 examples/s]
Generating train split: 20430236 examples [28:39, 46686.15 examples/s]
Generating train split: 20439432 examples [28:39, 56895.68 examples/s]
Generating train split: 20446282 examples [28:39, 32144.14 examples/s]
Generating train split: 20451540 examples [28:40, 35251.43 examples/s]
Generating train split: 20456767 examples [28:40, 36807.21 examples/s]
Generating train split: 20462585 examples [28:40, 39120.34 examples/s]
Generating train split: 20467433 examples [28:40, 27813.46 examples/s]
Generating train split: 20471579 examples [28:40, 30145.94 examples/s]
Generating train split: 20475519 examples [28:40, 31918.73 examples/s]
Generating train split: 20479451 examples [28:41, 21720.55 examples/s]
Generating train split: 20482538 examples [28:41, 22253.48 examples/s]
Generating train split: 20485435 examples [28:41, 20306.84 examples/s]
Generating train split: 20487943 examples [28:41, 17777.94 examples/s]
Generating train split: 20491901 examples [28:41, 21770.29 examples/s]
Generating train split: 20499185 examples [28:41, 32372.12 examples/s]
Generating train split: 20506706 examples [28:41, 42162.32 examples/s]
Generating train split: 20512853 examples [28:42, 46912.75 examples/s]
Generating train split: 20518275 examples [28:42, 29821.24 examples/s]
Generating train split: 20522538 examples [28:42, 25679.00 examples/s]
Generating train split: 20526068 examples [28:42, 20656.93 examples/s]
Generating train split: 20534079 examples [28:43, 30056.15 examples/s]
Generating train split: 20542918 examples [28:43, 40348.91 examples/s]
Generating train split: 20548498 examples [28:43, 30269.47 examples/s]
Generating train split: 20552932 examples [28:43, 21134.99 examples/s]
Generating train split: 20556353 examples [28:44, 16783.35 examples/s]
Generating train split: 20559034 examples [28:44, 15193.40 examples/s]
Generating train split: 20561232 examples [28:44, 14480.89 examples/s]
Generating train split: 20565255 examples [28:44, 18176.83 examples/s]
Generating train split: 20574972 examples [28:44, 31618.90 examples/s]
Generating train split: 20581549 examples [28:44, 38288.50 examples/s]
Generating train split: 20588462 examples [28:45, 45009.77 examples/s]
Generating train split: 20597861 examples [28:45, 56647.71 examples/s]
Generating train split: 20604708 examples [28:45, 28053.39 examples/s]
Generating train split: 20609879 examples [28:45, 29596.41 examples/s]
Generating train split: 20614574 examples [28:46, 24710.25 examples/s]
Generating train split: 20618344 examples [28:46, 26493.83 examples/s]
Generating train split: 20626959 examples [28:46, 37019.71 examples/s]
Generating train split: 20635496 examples [28:46, 46337.97 examples/s]
Generating train split: 20641585 examples [28:46, 42336.34 examples/s]
Generating train split: 20646876 examples [28:47, 25157.71 examples/s]
Generating train split: 20650932 examples [28:47, 26336.15 examples/s]
Generating train split: 20654725 examples [28:47, 18202.50 examples/s]
Generating train split: 20663094 examples [28:47, 26938.49 examples/s]
Generating train split: 20672299 examples [28:47, 37361.71 examples/s]
Generating train split: 20678250 examples [28:48, 35388.82 examples/s]
Generating train split: 20683341 examples [28:48, 22745.63 examples/s]
Generating train split: 20690949 examples [28:48, 29981.78 examples/s]
Generating train split: 20700851 examples [28:48, 41191.92 examples/s]
Generating train split: 20707325 examples [28:49, 23749.57 examples/s]
Generating train split: 20715691 examples [28:49, 31106.02 examples/s]
Generating train split: 20723925 examples [28:49, 38748.37 examples/s]
Generating train split: 20730544 examples [28:49, 35029.65 examples/s]
Generating train split: 20736002 examples [28:50, 21616.31 examples/s]
Generating train split: 20740124 examples [28:51, 12333.83 examples/s]
Generating train split: 20743142 examples [28:51, 10959.16 examples/s]
Generating train split: 20745473 examples [28:51, 11592.06 examples/s]
Generating train split: 20747601 examples [28:52, 8740.31 examples/s] 
Generating train split: 20749213 examples [28:53, 4944.13 examples/s]
Generating train split: 20750643 examples [28:53, 5523.04 examples/s]
Generating train split: 20752899 examples [28:53, 6968.49 examples/s]
Generating train split: 20754596 examples [28:53, 8050.16 examples/s]
Generating train split: 20756174 examples [28:53, 8362.18 examples/s]
Generating train split: 20757581 examples [28:54, 8314.32 examples/s]
Generating train split: 20759474 examples [28:54, 10027.37 examples/s]
Generating train split: 20760905 examples [28:54, 10483.74 examples/s]
Generating train split: 20762287 examples [28:54, 11149.63 examples/s]
Generating train split: 20764069 examples [28:54, 12467.99 examples/s]
Generating train split: 20765530 examples [28:54, 11837.97 examples/s]
Generating train split: 20767559 examples [28:54, 13863.16 examples/s]
Generating train split: 20769101 examples [28:54, 13761.23 examples/s]
Generating train split: 20770586 examples [28:54, 13359.30 examples/s]
Generating train split: 20772014 examples [28:55, 10717.72 examples/s]
Generating train split: 20773248 examples [28:55, 11041.98 examples/s]
Generating train split: 20779083 examples [28:55, 22592.39 examples/s]
Generating train split: 20787128 examples [28:55, 37548.28 examples/s]
Generating train split: 20791777 examples [28:55, 38861.16 examples/s]
Generating train split: 20796006 examples [28:55, 21797.83 examples/s]
Generating train split: 20799288 examples [28:56, 23031.74 examples/s]
Generating train split: 20802419 examples [28:56, 21070.06 examples/s]
Generating train split: 20811923 examples [28:56, 35344.78 examples/s]
Generating train split: 20819203 examples [28:56, 43439.69 examples/s]
Generating train split: 20824713 examples [28:56, 28143.90 examples/s]
Generating train split: 20829006 examples [28:57, 22102.36 examples/s]
Generating train split: 20832409 examples [28:57, 20552.89 examples/s]
Generating train split: 20835280 examples [28:57, 16942.75 examples/s]
Generating train split: 20837595 examples [28:57, 16543.79 examples/s]
Generating train split: 20839665 examples [28:57, 17002.02 examples/s]
Generating train split: 20848015 examples [28:57, 29406.21 examples/s]
Generating train split: 20857411 examples [28:58, 42984.03 examples/s]
Generating train split: 20863235 examples [28:58, 46195.92 examples/s]
Generating train split: 20868833 examples [28:58, 20917.67 examples/s]
Generating train split: 20873018 examples [28:59, 15060.41 examples/s]
Generating train split: 20876188 examples [28:59, 16466.71 examples/s]
Generating train split: 20881264 examples [28:59, 20923.66 examples/s]
Generating train split: 20890843 examples [28:59, 32646.64 examples/s]
Generating train split: 20896251 examples [28:59, 32942.87 examples/s]
Generating train split: 20901056 examples [29:00, 20645.68 examples/s]
Generating train split: 20904722 examples [29:00, 17817.43 examples/s]
Generating train split: 20907646 examples [29:00, 15218.17 examples/s]
Generating train split: 20909990 examples [29:01, 12246.12 examples/s]
Generating train split: 20912131 examples [29:01, 13358.51 examples/s]
Generating train split: 20914058 examples [29:01, 9922.05 examples/s] 
Generating train split: 20915707 examples [29:01, 10759.28 examples/s]
Generating train split: 20917255 examples [29:02, 9336.24 examples/s] 
Generating train split: 20919158 examples [29:02, 10813.72 examples/s]
Generating train split: 20920614 examples [29:02, 11121.94 examples/s]
Generating train split: 20922007 examples [29:02, 11551.59 examples/s]
Generating train split: 20923375 examples [29:02, 11812.09 examples/s]
Generating train split: 20924720 examples [29:02, 11934.50 examples/s]
Generating train split: 20933225 examples [29:02, 30014.30 examples/s]
Generating train split: 20942584 examples [29:02, 46605.64 examples/s]
Generating train split: 20947822 examples [29:03, 36213.03 examples/s]
Generating train split: 20956249 examples [29:03, 47056.43 examples/s]
Generating train split: 20965342 examples [29:03, 56907.68 examples/s]
Generating train split: 20971835 examples [29:03, 24127.36 examples/s]
Generating train split: 20976676 examples [29:04, 19908.53 examples/s]
Generating train split: 20980449 examples [29:04, 18245.53 examples/s]
Generating train split: 20983502 examples [29:04, 18213.27 examples/s]
Generating train split: 20986185 examples [29:05, 15993.43 examples/s]
Generating train split: 20988388 examples [29:05, 11743.02 examples/s]
Generating train split: 20990417 examples [29:05, 12790.33 examples/s]
Generating train split: 20992212 examples [29:05, 11460.20 examples/s]
Generating train split: 20993842 examples [29:05, 12193.34 examples/s]
Generating train split: 20995379 examples [29:05, 12681.73 examples/s]
Generating train split: 20997241 examples [29:06, 13882.74 examples/s]
Generating train split: 20998878 examples [29:06, 11797.82 examples/s]
Generating train split: 21001110 examples [29:06, 13983.88 examples/s]
Generating train split: 21002757 examples [29:06, 12249.64 examples/s]
Generating train split: 21007085 examples [29:06, 18945.50 examples/s]
Generating train split: 21009823 examples [29:06, 20853.24 examples/s]
Generating train split: 21012240 examples [29:06, 16833.78 examples/s]
Generating train split: 21014279 examples [29:07, 12399.85 examples/s]
Generating train split: 21019310 examples [29:07, 19212.24 examples/s]
Generating train split: 21028597 examples [29:07, 34251.96 examples/s]
Generating train split: 21034668 examples [29:07, 40215.64 examples/s]
Generating train split: 21039738 examples [29:07, 24618.02 examples/s]
Generating train split: 21043666 examples [29:08, 26623.45 examples/s]
Generating train split: 21053320 examples [29:08, 39906.75 examples/s]
Generating train split: 21061574 examples [29:08, 48998.02 examples/s]
Generating train split: 21067983 examples [29:08, 52499.56 examples/s]
Generating train split: 21074371 examples [29:08, 41300.98 examples/s]
Generating train split: 21079648 examples [29:08, 33274.95 examples/s]
Generating train split: 21083995 examples [29:08, 33920.47 examples/s]
Generating train split: 21088130 examples [29:09, 25595.34 examples/s]
Generating train split: 21091444 examples [29:09, 19945.83 examples/s]
Generating train split: 21094109 examples [29:09, 20010.06 examples/s]
Generating train split: 21096576 examples [29:10, 14413.38 examples/s]
Generating train split: 21099124 examples [29:10, 16042.85 examples/s]
Generating train split: 21101243 examples [29:10, 15545.98 examples/s]
Generating train split: 21103146 examples [29:10, 13341.64 examples/s]
Generating train split: 21112402 examples [29:10, 27548.81 examples/s]
Generating train split: 21121467 examples [29:10, 40415.55 examples/s]
Generating train split: 21126920 examples [29:11, 30893.78 examples/s]
Generating train split: 21131328 examples [29:11, 26865.41 examples/s]
Generating train split: 21134977 examples [29:11, 26898.98 examples/s]
Generating train split: 21144744 examples [29:11, 40460.76 examples/s]
Generating train split: 21154496 examples [29:11, 52717.95 examples/s]
Generating train split: 21161125 examples [29:11, 52823.16 examples/s]
Generating train split: 21167366 examples [29:12, 28363.13 examples/s]
Generating train split: 21173862 examples [29:12, 33860.16 examples/s]
Generating train split: 21179136 examples [29:12, 27109.38 examples/s]
Generating train split: 21183344 examples [29:12, 27497.72 examples/s]
Generating train split: 21187154 examples [29:12, 27085.43 examples/s]
Generating train split: 21190600 examples [29:13, 18205.95 examples/s]
Generating train split: 21193270 examples [29:13, 19204.77 examples/s]
Generating train split: 21196639 examples [29:13, 21610.80 examples/s]
Generating train split: 21199469 examples [29:13, 14720.94 examples/s]
Generating train split: 21201670 examples [29:14, 15227.62 examples/s]
Generating train split: 21208990 examples [29:14, 25220.72 examples/s]
Generating train split: 21219587 examples [29:14, 41174.63 examples/s]
Generating train split: 21226043 examples [29:14, 46308.74 examples/s]
Generating train split: 21231988 examples [29:14, 28339.10 examples/s]
Generating train split: 21241873 examples [29:14, 39883.38 examples/s]
Generating train split: 21250874 examples [29:14, 49368.44 examples/s]
Generating train split: 21257903 examples [29:15, 40261.59 examples/s]
Generating train split: 21263639 examples [29:15, 26862.35 examples/s]
Generating train split: 21268055 examples [29:16, 16542.33 examples/s]
Generating train split: 21271352 examples [29:16, 13427.01 examples/s]
Generating train split: 21273886 examples [29:16, 13012.02 examples/s]
Generating train split: 21277977 examples [29:17, 16073.75 examples/s]
Generating train split: 21280687 examples [29:17, 9840.56 examples/s] 
Generating train split: 21282698 examples [29:18, 7286.95 examples/s]
Generating train split: 21284206 examples [29:18, 6884.93 examples/s]
Generating train split: 21285429 examples [29:19, 5529.78 examples/s]
Generating train split: 21286366 examples [29:19, 4546.01 examples/s]
Generating train split: 21287927 examples [29:19, 5500.48 examples/s]
Generating train split: 21288840 examples [29:19, 4518.50 examples/s]
Generating train split: 21289562 examples [29:20, 4443.50 examples/s]
Generating train split: 21291081 examples [29:20, 5826.13 examples/s]
Generating train split: 21291972 examples [29:20, 4619.74 examples/s]
Generating train split: 21293614 examples [29:20, 6269.05 examples/s]
Generating train split: 21294610 examples [29:20, 6843.20 examples/s]
Generating train split: 21299154 examples [29:20, 14217.29 examples/s]
Generating train split: 21301209 examples [29:20, 15450.71 examples/s]
Generating train split: 21303251 examples [29:21, 16065.28 examples/s]
Generating train split: 21305206 examples [29:21, 15598.74 examples/s]
Generating train split: 21307014 examples [29:21, 14496.65 examples/s]
Generating train split: 21310908 examples [29:21, 20160.42 examples/s]
Generating train split: 21313191 examples [29:21, 17290.74 examples/s]
Generating train split: 21315176 examples [29:21, 16219.48 examples/s]
Generating train split: 21316984 examples [29:21, 14082.81 examples/s]
Generating train split: 21318550 examples [29:22, 13821.42 examples/s]
Generating train split: 21320042 examples [29:22, 13672.48 examples/s]
Generating train split: 21321485 examples [29:22, 12540.95 examples/s]
Generating train split: 21324254 examples [29:22, 16140.58 examples/s]
Generating train split: 21326349 examples [29:22, 17358.65 examples/s]
Generating train split: 21328206 examples [29:22, 15626.73 examples/s]
Generating train split: 21329885 examples [29:22, 12169.87 examples/s]
Generating train split: 21331431 examples [29:23, 12838.52 examples/s]
Generating train split: 21332872 examples [29:23, 12905.03 examples/s]
Generating train split: 21334278 examples [29:23, 12612.29 examples/s]
Generating train split: 21335618 examples [29:23, 8499.09 examples/s] 
Generating train split: 21336688 examples [29:23, 8822.33 examples/s]
Generating train split: 21338221 examples [29:23, 10106.63 examples/s]
Generating train split: 21339406 examples [29:23, 8794.58 examples/s] 
Generating train split: 21341927 examples [29:24, 12357.84 examples/s]
Generating train split: 21344080 examples [29:24, 14513.92 examples/s]
Generating train split: 21345767 examples [29:24, 15074.65 examples/s]
Generating train split: 21348406 examples [29:24, 17956.52 examples/s]
Generating train split: 21350353 examples [29:24, 18317.57 examples/s]
Generating train split: 21353393 examples [29:24, 21610.17 examples/s]
Generating train split: 21355653 examples [29:24, 17849.20 examples/s]
Generating train split: 21357760 examples [29:24, 18442.05 examples/s]
Generating train split: 21359735 examples [29:24, 17508.02 examples/s]
Generating train split: 21362436 examples [29:25, 19924.11 examples/s]
Generating train split: 21364541 examples [29:25, 15560.97 examples/s]
Generating train split: 21367471 examples [29:25, 18662.59 examples/s]
Generating train split: 21369586 examples [29:25, 16360.33 examples/s]
Generating train split: 21372531 examples [29:25, 19358.36 examples/s]
Generating train split: 21381907 examples [29:25, 37706.85 examples/s]
Generating train split: 21390952 examples [29:25, 51447.29 examples/s]
Generating train split: 21396705 examples [29:26, 22887.69 examples/s]
Generating train split: 21401792 examples [29:26, 26888.84 examples/s]
Generating train split: 21407859 examples [29:26, 32618.56 examples/s]
Generating train split: 21412861 examples [29:27, 21205.14 examples/s]
Generating train split: 21416691 examples [29:28, 9340.77 examples/s] 
Generating train split: 21419471 examples [29:29, 5945.41 examples/s]
Generating train split: 21421491 examples [29:30, 5272.27 examples/s]
Generating train split: 21423008 examples [29:30, 5059.94 examples/s]
Generating train split: 21424190 examples [29:30, 4346.69 examples/s]
Generating train split: 21425088 examples [29:31, 4311.45 examples/s]
Generating train split: 21426441 examples [29:31, 5092.23 examples/s]
Generating train split: 21429550 examples [29:31, 7901.77 examples/s]
Generating train split: 21437284 examples [29:31, 17187.96 examples/s]
Generating train split: 21443065 examples [29:31, 23697.11 examples/s]
Generating train split: 21447201 examples [29:32, 15863.46 examples/s]
Generating train split: 21450364 examples [29:32, 14909.93 examples/s]
Generating train split: 21459174 examples [29:32, 25010.19 examples/s]
Generating train split: 21469925 examples [29:32, 38591.01 examples/s]
Generating train split: 21476268 examples [29:32, 27965.82 examples/s]
Generating train split: 21481202 examples [29:32, 31135.78 examples/s]
Generating train split: 21492237 examples [29:33, 45050.71 examples/s]
Generating train split: 21501433 examples [29:33, 54192.53 examples/s]
Generating train split: 21508862 examples [29:33, 27454.04 examples/s]
Generating train split: 21514428 examples [29:34, 21809.84 examples/s]
Generating train split: 21518712 examples [29:34, 21274.51 examples/s]
Generating train split: 21522290 examples [29:34, 16324.28 examples/s]
Generating train split: 21531240 examples [29:34, 24564.70 examples/s]
Generating train split: 21540263 examples [29:35, 33586.96 examples/s]
Generating train split: 21546159 examples [29:35, 26567.36 examples/s]
Generating train split: 21550786 examples [29:35, 19234.37 examples/s]
Generating train split: 21559548 examples [29:36, 27262.13 examples/s]
Generating train split: 21569092 examples [29:36, 37050.76 examples/s]
Generating train split: 21575531 examples [29:36, 23966.96 examples/s]
Generating train split: 21580405 examples [29:36, 23935.89 examples/s]
Generating train split: 21590033 examples [29:36, 33658.81 examples/s]
Generating train split: 21596127 examples [29:37, 37914.70 examples/s]
Generating train split: 21601965 examples [29:37, 27867.21 examples/s]
Generating train split: 21606522 examples [29:37, 21908.55 examples/s]
Generating train split: 21610093 examples [29:38, 19018.26 examples/s]
Generating train split: 21612970 examples [29:38, 17393.09 examples/s]
Generating train split: 21615364 examples [29:38, 13207.28 examples/s]
Generating train split: 21618296 examples [29:38, 15234.33 examples/s]
Generating train split: 21626909 examples [29:38, 26043.77 examples/s]
Generating train split: 21635528 examples [29:38, 36572.10 examples/s]
Generating train split: 21640908 examples [29:39, 23760.28 examples/s]
Generating train split: 21645045 examples [29:39, 21272.46 examples/s]
Generating train split: 21652972 examples [29:39, 29653.86 examples/s]
Generating train split: 21661668 examples [29:39, 39455.35 examples/s]
Generating train split: 21667592 examples [29:40, 21800.71 examples/s]
Generating train split: 21672039 examples [29:40, 19275.35 examples/s]
Generating train split: 21675563 examples [29:41, 16997.69 examples/s]
Generating train split: 21678380 examples [29:41, 13778.76 examples/s]
Generating train split: 21680586 examples [29:41, 13381.42 examples/s]
Generating train split: 21682484 examples [29:41, 13110.64 examples/s]
Generating train split: 21684167 examples [29:41, 13442.68 examples/s]
Generating train split: 21685800 examples [29:42, 12025.80 examples/s]
Generating train split: 21687210 examples [29:42, 11919.10 examples/s]
Generating train split: 21690809 examples [29:42, 16458.73 examples/s]
Generating train split: 21693068 examples [29:42, 17772.11 examples/s]
Generating train split: 21695131 examples [29:42, 16731.26 examples/s]
Generating train split: 21697001 examples [29:42, 14554.55 examples/s]
Generating train split: 21699839 examples [29:42, 17594.71 examples/s]
Generating train split: 21701828 examples [29:42, 17834.54 examples/s]
Generating train split: 21703780 examples [29:43, 17496.10 examples/s]
Generating train split: 21706402 examples [29:43, 19695.34 examples/s]
Generating train split: 21708494 examples [29:43, 16983.41 examples/s]
Generating train split: 21710335 examples [29:43, 14559.20 examples/s]
Generating train split: 21711942 examples [29:43, 14895.55 examples/s]
Generating train split: 21713541 examples [29:43, 13128.83 examples/s]
Generating train split: 21715151 examples [29:43, 13791.75 examples/s]
Generating train split: 21716630 examples [29:44, 12853.95 examples/s]
Generating train split: 21718166 examples [29:44, 13430.60 examples/s]
Generating train split: 21719577 examples [29:44, 11913.50 examples/s]
Generating train split: 21720841 examples [29:44, 11439.44 examples/s]
Generating train split: 21722254 examples [29:44, 12042.18 examples/s]
Generating train split: 21724047 examples [29:44, 13573.16 examples/s]
Generating train split: 21725466 examples [29:44, 13349.86 examples/s]
Generating train split: 21727245 examples [29:44, 14561.04 examples/s]
Generating train split: 21729935 examples [29:44, 18021.08 examples/s]
Generating train split: 21731799 examples [29:45, 14178.65 examples/s]
Generating train split: 21733377 examples [29:45, 12618.37 examples/s]
Generating train split: 21736303 examples [29:45, 16408.37 examples/s]
Generating train split: 21739963 examples [29:45, 21365.21 examples/s]
Generating train split: 21743447 examples [29:45, 24873.98 examples/s]
Generating train split: 21746168 examples [29:45, 21421.42 examples/s]
Generating train split: 21748557 examples [29:45, 20977.33 examples/s]
Generating train split: 21752305 examples [29:45, 25104.43 examples/s]
Generating train split: 21759669 examples [29:46, 37885.80 examples/s]
Generating train split: 21767763 examples [29:46, 49656.48 examples/s]
Generating train split: 21773064 examples [29:46, 28268.40 examples/s]
Generating train split: 21777200 examples [29:46, 29252.25 examples/s]
Generating train split: 21784390 examples [29:46, 37766.54 examples/s]
Generating train split: 21794446 examples [29:46, 51693.48 examples/s]
Generating train split: 21800867 examples [29:47, 50246.90 examples/s]
Generating train split: 21806775 examples [29:47, 28170.21 examples/s]
Generating train split: 21811299 examples [29:47, 20579.49 examples/s]
Generating train split: 21814795 examples [29:48, 22070.71 examples/s]
Generating train split: 21818176 examples [29:48, 19604.39 examples/s]
Generating train split: 21820957 examples [29:48, 20361.41 examples/s]
Generating train split: 21823629 examples [29:48, 19098.86 examples/s]
Generating train split: 21826627 examples [29:48, 21081.05 examples/s]
Generating train split: 21829164 examples [29:48, 19580.69 examples/s]
Generating train split: 21831422 examples [29:48, 19194.27 examples/s]
Generating train split: 21836457 examples [29:49, 25832.64 examples/s]
Generating train split: 21841751 examples [29:49, 32280.11 examples/s]
Generating train split: 21845615 examples [29:49, 33892.81 examples/s]
Generating train split: 21851572 examples [29:49, 40717.85 examples/s]
Generating train split: 21856999 examples [29:49, 44435.20 examples/s]
Generating train split: 21861693 examples [29:49, 38105.48 examples/s]
Generating train split: 21865843 examples [29:49, 36169.84 examples/s]
Generating train split: 21869923 examples [29:49, 37326.85 examples/s]
Generating train split: 21873851 examples [29:49, 34547.79 examples/s]
Generating train split: 21877470 examples [29:50, 30845.25 examples/s]
Generating train split: 21881285 examples [29:50, 32621.32 examples/s]
Generating train split: 21887371 examples [29:50, 39914.15 examples/s]
Generating train split: 21895655 examples [29:50, 50975.60 examples/s]
Generating train split: 21901006 examples [29:50, 29668.65 examples/s]
Generating train split: 21905193 examples [29:50, 30111.76 examples/s]
Generating train split: 21909082 examples [29:51, 30020.17 examples/s]
Generating train split: 21916914 examples [29:51, 40231.21 examples/s]
Generating train split: 21922590 examples [29:51, 44064.82 examples/s]
Generating train split: 21929102 examples [29:51, 49297.16 examples/s]
Generating train split: 21934642 examples [29:51, 49380.20 examples/s]
Generating train split: 21940001 examples [29:51, 40825.21 examples/s]
Generating train split: 21944608 examples [29:51, 38110.44 examples/s]
Generating train split: 21948798 examples [29:51, 34590.34 examples/s]
Generating train split: 21952748 examples [29:52, 35709.75 examples/s]
Generating train split: 21956566 examples [29:52, 24115.51 examples/s]
Generating train split: 21959603 examples [29:52, 17178.93 examples/s]
Generating train split: 21962747 examples [29:52, 19389.60 examples/s]
Generating train split: 21967268 examples [29:52, 24064.70 examples/s]
Generating train split: 21971857 examples [29:53, 27817.51 examples/s]
Generating train split: 21977599 examples [29:53, 34376.69 examples/s]
Generating train split: 21982799 examples [29:53, 38620.71 examples/s]
Generating train split: 21992091 examples [29:53, 52521.01 examples/s]
Generating train split: 22002169 examples [29:53, 65439.87 examples/s]
Generating train split: 22012758 examples [29:53, 76619.01 examples/s]
Generating train split: 22022337 examples [29:53, 82029.52 examples/s]
Generating train split: 22030940 examples [29:53, 49890.93 examples/s]
Generating train split: 22037737 examples [29:54, 43601.17 examples/s]
Generating train split: 22043461 examples [29:54, 45195.98 examples/s]
Generating train split: 22053018 examples [29:54, 55651.58 examples/s]
Generating train split: 22061290 examples [29:54, 60862.64 examples/s]
Generating train split: 22069895 examples [29:54, 66976.02 examples/s]
Generating train split: 22079825 examples [29:54, 75291.58 examples/s]
Generating train split: 22088067 examples [29:54, 57202.88 examples/s]
Generating train split: 22094910 examples [29:55, 35242.04 examples/s]
Generating train split: 22100204 examples [29:55, 28653.68 examples/s]
Generating train split: 22104427 examples [29:55, 30260.01 examples/s]
Generating train split: 22112055 examples [29:55, 38075.56 examples/s]
Generating train split: 22117238 examples [29:56, 31892.85 examples/s]
Generating train split: 22121500 examples [29:56, 30029.59 examples/s]
Generating train split: 22125234 examples [29:56, 28710.94 examples/s]
Generating train split: 22128603 examples [29:56, 18750.74 examples/s]
Generating train split: 22131693 examples [29:56, 20558.50 examples/s]
Generating train split: 22134449 examples [29:57, 17079.51 examples/s]
Generating train split: 22136708 examples [29:57, 14080.58 examples/s]
Generating train split: 22138633 examples [29:57, 14226.14 examples/s]
Generating train split: 22140355 examples [29:57, 14502.85 examples/s]
Generating train split: 22144840 examples [29:57, 20488.10 examples/s]
Generating train split: 22149406 examples [29:57, 26019.28 examples/s]
Generating train split: 22158267 examples [29:57, 40972.09 examples/s]
Generating train split: 22167298 examples [29:58, 53528.93 examples/s]
Generating train split: 22173401 examples [29:58, 35537.96 examples/s]
Generating train split: 22178273 examples [29:58, 29721.91 examples/s]
Generating train split: 22182722 examples [29:58, 32358.08 examples/s]
Generating train split: 22187210 examples [29:58, 34662.39 examples/s]
Generating train split: 22191406 examples [29:59, 22403.85 examples/s]
Generating train split: 22195599 examples [29:59, 25618.83 examples/s]
Generating train split: 22201134 examples [29:59, 31262.76 examples/s]
Generating train split: 22205612 examples [29:59, 34148.94 examples/s]
Generating train split: 22211364 examples [29:59, 39616.45 examples/s]
Generating train split: 22216065 examples [29:59, 40821.99 examples/s]
Generating train split: 22220771 examples [29:59, 42433.45 examples/s]
Generating train split: 22226462 examples [29:59, 46039.77 examples/s]
Generating train split: 22232562 examples [30:00, 50181.79 examples/s]
Generating train split: 22238684 examples [30:00, 53307.29 examples/s]
Generating train split: 22245502 examples [30:00, 57575.84 examples/s]
Generating train split: 22252348 examples [30:00, 60751.03 examples/s]
Generating train split: 22259640 examples [30:00, 64327.49 examples/s]
Generating train split: 22266609 examples [30:00, 65906.41 examples/s]
Generating train split: 22273945 examples [30:00, 68120.34 examples/s]
Generating train split: 22281411 examples [30:00, 70048.29 examples/s]
Generating train split: 22288541 examples [30:00, 70406.63 examples/s]
Generating train split: 22295926 examples [30:00, 71415.37 examples/s]
Generating train split: 22303510 examples [30:01, 72728.52 examples/s]
Generating train split: 22311513 examples [30:01, 74870.37 examples/s]
Generating train split: 22319011 examples [30:01, 74642.95 examples/s]
Generating train split: 22327551 examples [30:01, 77856.78 examples/s]
Generating train split: 22335358 examples [30:01, 74367.75 examples/s]
Generating train split: 22342841 examples [30:01, 72591.22 examples/s]
Generating train split: 22350141 examples [30:01, 71078.77 examples/s]
Generating train split: 22357275 examples [30:01, 63469.31 examples/s]
Generating train split: 22363784 examples [30:01, 53004.28 examples/s]
Generating train split: 22369444 examples [30:02, 51554.31 examples/s]
Generating train split: 22374843 examples [30:02, 48035.21 examples/s]
Generating train split: 22380295 examples [30:02, 49614.75 examples/s]
Generating train split: 22385412 examples [30:02, 47652.72 examples/s]
Generating train split: 22390285 examples [30:02, 46392.08 examples/s]
Generating train split: 22394998 examples [30:02, 40773.40 examples/s]
Generating train split: 22399228 examples [30:03, 26195.44 examples/s]
Generating train split: 22402566 examples [30:03, 18738.35 examples/s]
Generating train split: 22405184 examples [30:03, 17404.79 examples/s]
Generating train split: 22407855 examples [30:03, 18891.91 examples/s]
Generating train split: 22410233 examples [30:03, 19508.99 examples/s]
Generating train split: 22412556 examples [30:04, 16524.89 examples/s]
Generating train split: 22414528 examples [30:04, 14711.82 examples/s]
Generating train split: 22416293 examples [30:04, 15269.19 examples/s]
Generating train split: 22418003 examples [30:04, 12373.19 examples/s]
Generating train split: 22419446 examples [30:04, 10596.85 examples/s]
Generating train split: 22420669 examples [30:04, 8641.66 examples/s] 
Generating train split: 22422104 examples [30:05, 9631.64 examples/s]
Generating train split: 22423232 examples [30:05, 9626.07 examples/s]
Generating train split: 22425268 examples [30:05, 11926.17 examples/s]
Generating train split: 22426634 examples [30:05, 9480.10 examples/s] 
Generating train split: 22427767 examples [30:05, 8014.83 examples/s]
Generating train split: 22428785 examples [30:05, 8422.29 examples/s]
Generating train split: 22429984 examples [30:05, 9175.35 examples/s]
Generating train split: 22431022 examples [30:06, 8653.62 examples/s]
Generating train split: 22433339 examples [30:06, 12053.12 examples/s]
Generating train split: 22434703 examples [30:06, 12068.58 examples/s]
Generating train split: 22436015 examples [30:06, 11939.40 examples/s]
Generating train split: 22437283 examples [30:06, 11944.42 examples/s]
Generating train split: 22439385 examples [30:06, 14391.54 examples/s]
Generating train split: 22440895 examples [30:06, 12916.05 examples/s]
Generating train split: 22445037 examples [30:06, 20327.16 examples/s]
Generating train split: 22453237 examples [30:06, 37029.01 examples/s]
Generating train split: 22457238 examples [30:07, 30727.07 examples/s]
Generating train split: 22461065 examples [30:07, 32383.99 examples/s]
Generating train split: 22464612 examples [30:07, 28488.72 examples/s]
Generating train split: 22468646 examples [30:07, 31328.33 examples/s]
Generating train split: 22475198 examples [30:07, 40055.60 examples/s]
Generating train split: 22485351 examples [30:07, 56476.30 examples/s]
Generating train split: 22491434 examples [30:08, 35612.21 examples/s]
Generating train split: 22496262 examples [30:08, 34470.72 examples/s]
Generating train split: 22505795 examples [30:08, 46763.57 examples/s]
Generating train split: 22514184 examples [30:08, 55053.92 examples/s]
Generating train split: 22520812 examples [30:08, 48949.09 examples/s]
Generating train split: 22526592 examples [30:09, 27546.31 examples/s]
Generating train split: 22531008 examples [30:09, 29518.03 examples/s]
Generating train split: 22539951 examples [30:09, 39886.18 examples/s]
Generating train split: 22547513 examples [30:09, 46936.61 examples/s]
Generating train split: 22553757 examples [30:09, 29084.93 examples/s]
Generating train split: 22563180 examples [30:09, 39109.68 examples/s]
Generating train split: 22569373 examples [30:09, 41928.64 examples/s]
Generating train split: 22575302 examples [30:10, 23994.77 examples/s]
Generating train split: 22579780 examples [30:10, 26339.89 examples/s]
Generating train split: 22588991 examples [30:10, 36590.74 examples/s]
Generating train split: 22596267 examples [30:10, 43173.34 examples/s]
Generating train split: 22602508 examples [30:11, 31049.19 examples/s]
Generating train split: 22612783 examples [30:11, 42708.69 examples/s]
Generating train split: 22619410 examples [30:11, 47145.06 examples/s]
Generating train split: 22626001 examples [30:11, 35717.35 examples/s]
Generating train split: 22631240 examples [30:12, 22026.22 examples/s]
Generating train split: 22635201 examples [30:12, 18241.95 examples/s]
Generating train split: 22638310 examples [30:13, 12843.96 examples/s]
Generating train split: 22640652 examples [30:13, 13748.95 examples/s]
Generating train split: 22642938 examples [30:13, 14777.25 examples/s]
Generating train split: 22645197 examples [30:13, 10618.15 examples/s]
Generating train split: 22646931 examples [30:13, 10292.00 examples/s]
Generating train split: 22651908 examples [30:14, 15700.58 examples/s]
Generating train split: 22656090 examples [30:14, 19799.33 examples/s]
Generating train split: 22659059 examples [30:14, 16638.20 examples/s]
Generating train split: 22662905 examples [30:14, 20373.51 examples/s]
Generating train split: 22672330 examples [30:14, 34881.22 examples/s]
Generating train split: 22683031 examples [30:14, 50686.09 examples/s]
Generating train split: 22689620 examples [30:14, 51657.52 examples/s]
Generating train split: 22699223 examples [30:14, 62498.89 examples/s]
Generating train split: 22706481 examples [30:15, 63954.56 examples/s]
Generating train split: 22713596 examples [30:15, 31612.22 examples/s]
Generating train split: 22718993 examples [30:16, 22563.69 examples/s]
Generating train split: 22723127 examples [30:16, 22812.69 examples/s]
Generating train split: 22726733 examples [30:16, 19175.07 examples/s]
Generating train split: 22729618 examples [30:16, 17271.99 examples/s]
Generating train split: 22732011 examples [30:16, 17805.62 examples/s]
Generating train split: 22734307 examples [30:17, 14481.14 examples/s]
Generating train split: 22736163 examples [30:17, 14634.88 examples/s]
Generating train split: 22741187 examples [30:17, 20839.80 examples/s]
Generating train split: 22746720 examples [30:17, 27669.23 examples/s]
Generating train split: 22750282 examples [30:17, 20247.47 examples/s]
Generating train split: 22753533 examples [30:17, 22425.42 examples/s]
Generating train split: 22758395 examples [30:17, 27732.48 examples/s]
Generating train split: 22764908 examples [30:18, 36139.19 examples/s]
Generating train split: 22774373 examples [30:18, 50356.77 examples/s]
Generating train split: 22780310 examples [30:18, 49415.22 examples/s]
Generating train split: 22789214 examples [30:18, 59577.43 examples/s]
Generating train split: 22795946 examples [30:18, 61654.61 examples/s]
Generating train split: 22802568 examples [30:18, 31435.14 examples/s]
Generating train split: 22811502 examples [30:19, 40995.64 examples/s]
Generating train split: 22821436 examples [30:19, 52121.37 examples/s]
Generating train split: 22828779 examples [30:19, 29560.05 examples/s]
Generating train split: 22834332 examples [30:19, 32004.38 examples/s]
Generating train split: 22839553 examples [30:20, 31773.65 examples/s]
Generating train split: 22844821 examples [30:20, 35330.02 examples/s]
Generating train split: 22852389 examples [30:20, 43141.52 examples/s]
Generating train split: 22857996 examples [30:20, 30883.53 examples/s]
Generating train split: 22862441 examples [30:20, 31088.25 examples/s]
Generating train split: 22866503 examples [30:20, 31171.14 examples/s]
Generating train split: 22873278 examples [30:20, 38592.47 examples/s]
Generating train split: 22880950 examples [30:21, 46818.13 examples/s]
Generating train split: 22886468 examples [30:21, 29284.40 examples/s]
Generating train split: 22890765 examples [30:21, 30792.84 examples/s]
Generating train split: 22896417 examples [30:21, 35743.47 examples/s]
Generating train split: 22905405 examples [30:21, 47422.25 examples/s]
Generating train split: 22911828 examples [30:21, 51364.30 examples/s]
Generating train split: 22917885 examples [30:22, 27639.41 examples/s]
Generating train split: 22923127 examples [30:22, 31504.62 examples/s]
Generating train split: 22927934 examples [30:22, 20205.22 examples/s]
Generating train split: 22931596 examples [30:22, 21598.32 examples/s]
Generating train split: 22935023 examples [30:23, 22698.38 examples/s]
Generating train split: 22945331 examples [30:23, 36774.03 examples/s]
Generating train split: 22950687 examples [30:23, 31317.49 examples/s]
Generating train split: 22955112 examples [30:23, 32196.20 examples/s]
Generating train split: 22963768 examples [30:23, 43029.59 examples/s]
Generating train split: 22971797 examples [30:23, 51036.21 examples/s]
Generating train split: 22978002 examples [30:23, 44505.72 examples/s]
Generating train split: 22983355 examples [30:24, 24949.20 examples/s]
Generating train split: 22987941 examples [30:24, 27914.02 examples/s]
Generating train split: 22992586 examples [30:24, 31085.70 examples/s]
Generating train split: 22996927 examples [30:24, 32824.55 examples/s]
Generating train split: 23001146 examples [30:25, 25978.16 examples/s]
Generating train split: 23004585 examples [30:25, 26889.28 examples/s]
Generating train split: 23008615 examples [30:25, 29658.55 examples/s]
Generating train split: 23012153 examples [30:25, 30346.67 examples/s]
Generating train split: 23015600 examples [30:25, 17263.06 examples/s]
Generating train split: 23018672 examples [30:25, 19395.18 examples/s]
Generating train split: 23025288 examples [30:25, 28082.04 examples/s]
Generating train split: 23033165 examples [30:26, 38707.73 examples/s]
Generating train split: 23038667 examples [30:26, 42461.76 examples/s]
Generating train split: 23043893 examples [30:26, 16526.65 examples/s]
Generating train split: 23047753 examples [30:27, 11313.62 examples/s]
Generating train split: 23050626 examples [30:27, 12251.65 examples/s]
Generating train split: 23053189 examples [30:28, 10130.41 examples/s]
Generating train split: 23055168 examples [30:28, 8529.55 examples/s] 
Generating train split: 23056700 examples [30:28, 8019.29 examples/s]
Generating train split: 23057963 examples [30:29, 7948.96 examples/s]
Generating train split: 23060172 examples [30:29, 9754.48 examples/s]
Generating train split: 23062483 examples [30:29, 11712.11 examples/s]
Generating train split: 23064148 examples [30:29, 10709.43 examples/s]
Generating train split: 23065562 examples [30:29, 8339.85 examples/s] 
Generating train split: 23067159 examples [30:29, 9499.08 examples/s]
Generating train split: 23068436 examples [30:30, 8177.68 examples/s]
Generating train split: 23069483 examples [30:30, 6022.57 examples/s]
Generating train split: 23071142 examples [30:30, 7603.12 examples/s]
Generating train split: 23073867 examples [30:30, 11060.69 examples/s]
Generating train split: 23075444 examples [30:30, 9160.00 examples/s] 
Generating train split: 23076738 examples [30:31, 9550.47 examples/s]
Generating train split: 23078415 examples [30:31, 10988.61 examples/s]
Generating train split: 23079783 examples [30:31, 10003.82 examples/s]
Generating train split: 23080983 examples [30:32, 3147.28 examples/s] 
Generating train split: 23081852 examples [30:32, 2913.40 examples/s]
Generating train split: 23083042 examples [30:32, 3711.45 examples/s]
Generating train split: 23084144 examples [30:33, 4481.31 examples/s]
Generating train split: 23085026 examples [30:33, 3780.01 examples/s]
Generating train split: 23086483 examples [30:33, 5152.44 examples/s]
Generating train split: 23087412 examples [30:33, 4656.28 examples/s]
Generating train split: 23088305 examples [30:33, 5296.70 examples/s]
Generating train split: 23089099 examples [30:34, 4916.71 examples/s]
Generating train split: 23090168 examples [30:34, 5855.56 examples/s]
Generating train split: 23090945 examples [30:34, 4611.60 examples/s]
Generating train split: 23091597 examples [30:34, 4919.95 examples/s]
Generating train split: 23092225 examples [30:34, 4631.96 examples/s]
Generating train split: 23093017 examples [30:34, 5221.11 examples/s]
Generating train split: 23094993 examples [30:34, 8418.11 examples/s]
Generating train split: 23096077 examples [30:35, 8996.12 examples/s]
Generating train split: 23098117 examples [30:35, 11889.56 examples/s]
Generating train split: 23099463 examples [30:35, 11905.87 examples/s]
Generating train split: 23100784 examples [30:35, 12242.09 examples/s]
Generating train split: 23103846 examples [30:35, 17339.93 examples/s]
Generating train split: 23110265 examples [30:35, 30636.94 examples/s]
Generating train split: 23118075 examples [30:35, 44138.00 examples/s]
Generating train split: 23122632 examples [30:35, 27917.70 examples/s]
Generating train split: 23126318 examples [30:36, 29762.08 examples/s]
Generating train split: 23129991 examples [30:36, 30366.65 examples/s]
Generating train split: 23135739 examples [30:36, 36857.56 examples/s]
Generating train split: 23146160 examples [30:36, 54020.84 examples/s]
Generating train split: 23152225 examples [30:36, 35612.62 examples/s]
Generating train split: 23157049 examples [30:36, 33346.82 examples/s]
Generating train split: 23161850 examples [30:36, 36179.08 examples/s]
Generating train split: 23168115 examples [30:37, 41975.12 examples/s]
Generating train split: 23177292 examples [30:37, 53842.90 examples/s]
Generating train split: 23183518 examples [30:37, 37314.16 examples/s]
Generating train split: 23188507 examples [30:37, 32015.75 examples/s]
Generating train split: 23192662 examples [30:37, 25868.54 examples/s]
Generating train split: 23196039 examples [30:38, 25596.11 examples/s]
Generating train split: 23199140 examples [30:38, 25117.51 examples/s]
Generating train split: 23202367 examples [30:38, 26533.24 examples/s]
Generating train split: 23205350 examples [30:38, 20696.99 examples/s]
Generating train split: 23207812 examples [30:38, 17779.17 examples/s]
Generating train split: 23210120 examples [30:38, 18765.08 examples/s]
Generating train split: 23212275 examples [30:39, 17404.08 examples/s]
Generating train split: 23214205 examples [30:39, 16141.93 examples/s]
Generating train split: 23216099 examples [30:39, 16722.17 examples/s]
Generating train split: 23218202 examples [30:39, 17718.75 examples/s]
Generating train split: 23220076 examples [30:39, 16812.37 examples/s]
Generating train split: 23222508 examples [30:39, 18693.80 examples/s]
Generating train split: 23224473 examples [30:39, 15909.38 examples/s]
Generating train split: 23226194 examples [30:39, 15719.08 examples/s]
Generating train split: 23227851 examples [30:39, 15739.46 examples/s]
Generating train split: 23230381 examples [30:40, 18045.06 examples/s]
Generating train split: 23232263 examples [30:40, 15459.09 examples/s]
Generating train split: 23233915 examples [30:40, 14351.84 examples/s]
Generating train split: 23235437 examples [30:40, 12946.74 examples/s]
Generating train split: 23236801 examples [30:40, 10431.36 examples/s]
Generating train split: 23238129 examples [30:40, 10907.02 examples/s]
Generating train split: 23242779 examples [30:40, 19083.27 examples/s]
Generating train split: 23251414 examples [30:41, 35696.11 examples/s]
Generating train split: 23257100 examples [30:41, 41213.22 examples/s]
Generating train split: 23261722 examples [30:41, 17219.33 examples/s]
Generating train split: 23265162 examples [30:42, 14481.86 examples/s]
Generating train split: 23269988 examples [30:42, 18720.03 examples/s]
Generating train split: 23278738 examples [30:42, 29172.89 examples/s]
Generating train split: 23285346 examples [30:42, 35727.73 examples/s]
Generating train split: 23290800 examples [30:42, 23241.43 examples/s]
Generating train split: 23294981 examples [30:42, 25763.52 examples/s]
Generating train split: 23300298 examples [30:43, 30448.20 examples/s]
Generating train split: 23304776 examples [30:43, 24904.72 examples/s]
Generating train split: 23308421 examples [30:43, 26458.59 examples/s]
Generating train split: 23311967 examples [30:43, 27562.63 examples/s]
Generating train split: 23318590 examples [30:43, 35866.42 examples/s]
Generating train split: 23326681 examples [30:43, 46438.39 examples/s]
Generating train split: 23333192 examples [30:43, 51115.44 examples/s]
Generating train split: 23338993 examples [30:44, 28040.38 examples/s]
Generating train split: 23347001 examples [30:44, 36698.73 examples/s]
Generating train split: 23354861 examples [30:44, 44746.58 examples/s]
Generating train split: 23361088 examples [30:44, 42855.52 examples/s]
Generating train split: 23369778 examples [30:44, 52252.83 examples/s]
Generating train split: 23377414 examples [30:44, 56353.33 examples/s]
Generating train split: 23383991 examples [30:45, 36246.43 examples/s]
Generating train split: 23389157 examples [30:45, 32404.00 examples/s]
Generating train split: 23393500 examples [30:45, 32121.38 examples/s]
Generating train split: 23399738 examples [30:45, 37842.20 examples/s]
Generating train split: 23406857 examples [30:45, 44934.03 examples/s]
Generating train split: 23412254 examples [30:46, 37509.67 examples/s]
Generating train split: 23416810 examples [30:46, 33941.66 examples/s]
Generating train split: 23420786 examples [30:46, 33332.72 examples/s]
Generating train split: 23424967 examples [30:46, 35169.24 examples/s]
Generating train split: 23432573 examples [30:46, 44873.64 examples/s]
Generating train split: 23442447 examples [30:46, 58513.86 examples/s]
Generating train split: 23448899 examples [30:46, 40600.96 examples/s]
Generating train split: 23454101 examples [30:47, 34064.73 examples/s]
Generating train split: 23462509 examples [30:47, 43457.26 examples/s]
Generating train split: 23469507 examples [30:47, 49055.07 examples/s]
Generating train split: 23475497 examples [30:47, 42152.21 examples/s]
Generating train split: 23481020 examples [30:47, 44937.70 examples/s]
Generating train split: 23489133 examples [30:47, 53369.83 examples/s]
Generating train split: 23495232 examples [30:48, 32646.88 examples/s]
Generating train split: 23499982 examples [30:48, 33574.04 examples/s]
Generating train split: 23506796 examples [30:48, 40199.66 examples/s]
Generating train split: 23515178 examples [30:48, 49569.98 examples/s]
Generating train split: 23521307 examples [30:48, 37674.73 examples/s]
Generating train split: 23526284 examples [30:48, 28503.29 examples/s]
Generating train split: 23530561 examples [30:49, 30855.33 examples/s]
Generating train split: 23536639 examples [30:49, 36568.86 examples/s]
Generating train split: 23541314 examples [30:49, 25822.38 examples/s]
Generating train split: 23545008 examples [30:49, 24773.55 examples/s]
Generating train split: 23548246 examples [30:49, 25478.31 examples/s]
Generating train split: 23551366 examples [30:50, 17977.86 examples/s]
Generating train split: 23553830 examples [30:50, 18591.81 examples/s]
Generating train split: 23556194 examples [30:50, 13657.82 examples/s]
Generating train split: 23558949 examples [30:50, 15803.35 examples/s]
Generating train split: 23562951 examples [30:50, 20185.21 examples/s]
Generating train split: 23565644 examples [30:51, 17030.24 examples/s]
Generating train split: 23567883 examples [30:51, 17373.30 examples/s]
Generating train split: 23576375 examples [30:51, 31262.67 examples/s]
Generating train split: 23585077 examples [30:51, 43920.91 examples/s]
Generating train split: 23590524 examples [30:51, 42259.88 examples/s]
Generating train split: 23595490 examples [30:51, 37534.87 examples/s]
Generating train split: 23599841 examples [30:51, 26474.82 examples/s]
Generating train split: 23603311 examples [30:52, 27875.13 examples/s]
Generating train split: 23612176 examples [30:52, 40318.62 examples/s]
Generating train split: 23620503 examples [30:52, 50030.08 examples/s]
Generating train split: 23626560 examples [30:52, 50024.41 examples/s]
Generating train split: 23635739 examples [30:52, 60415.20 examples/s]
Generating train split: 23642514 examples [30:52, 62318.22 examples/s]
Generating train split: 23649281 examples [30:53, 25905.33 examples/s]
Generating train split: 23654343 examples [30:53, 20397.85 examples/s]
Generating train split: 23658251 examples [30:54, 17096.44 examples/s]
Generating train split: 23661302 examples [30:54, 13711.56 examples/s]
Generating train split: 23663656 examples [30:54, 13001.45 examples/s]
Generating train split: 23665621 examples [30:55, 9385.38 examples/s] 
Generating train split: 23667422 examples [30:55, 10278.49 examples/s]
Generating train split: 23669008 examples [30:55, 9094.66 examples/s] 
Generating train split: 23670308 examples [30:55, 8288.05 examples/s]
Generating train split: 23671564 examples [30:55, 8860.62 examples/s]
Generating train split: 23672983 examples [30:55, 9684.23 examples/s]
Generating train split: 23674185 examples [30:56, 8141.75 examples/s]
Generating train split: 23675613 examples [30:56, 9234.38 examples/s]
Generating train split: 23676751 examples [30:56, 9509.93 examples/s]
Generating train split: 23677858 examples [30:57, 4320.81 examples/s]
Generating train split: 23678752 examples [30:57, 4879.66 examples/s]
Generating train split: 23679592 examples [30:57, 4396.53 examples/s]
Generating train split: 23680594 examples [30:57, 5225.26 examples/s]
Generating train split: 23682417 examples [30:57, 7484.82 examples/s]
Generating train split: 23683515 examples [30:57, 6673.11 examples/s]
Generating train split: 23686183 examples [30:57, 10315.47 examples/s]
Generating train split: 23687873 examples [30:58, 11697.53 examples/s]
Generating train split: 23689411 examples [30:58, 12534.47 examples/s]
Generating train split: 23690912 examples [30:58, 13134.47 examples/s]
Generating train split: 23700204 examples [30:58, 33962.88 examples/s]
Generating train split: 23707529 examples [30:58, 44281.34 examples/s]
Generating train split: 23712349 examples [30:58, 38495.94 examples/s]
Generating train split: 23717313 examples [30:58, 41304.00 examples/s]
Generating train split: 23721780 examples [30:59, 27618.60 examples/s]
Generating train split: 23725361 examples [30:59, 28673.48 examples/s]
Generating train split: 23728840 examples [30:59, 29866.11 examples/s]
Generating train split: 23732811 examples [30:59, 32181.77 examples/s]
Generating train split: 23736423 examples [30:59, 23590.97 examples/s]
Generating train split: 23739366 examples [30:59, 24569.39 examples/s]
Generating train split: 23742599 examples [30:59, 26305.28 examples/s]
Generating train split: 23746193 examples [30:59, 28632.23 examples/s]
Generating train split: 23751023 examples [30:59, 33677.22 examples/s]
Generating train split: 23758692 examples [31:00, 45218.16 examples/s]
Generating train split: 23764786 examples [31:00, 49561.55 examples/s]
Generating train split: 23770027 examples [31:00, 28283.85 examples/s]
Generating train split: 23774123 examples [31:00, 28185.80 examples/s]
Generating train split: 23777830 examples [31:00, 29920.03 examples/s]
Generating train split: 23786586 examples [31:00, 42513.79 examples/s]
Generating train split: 23792990 examples [31:01, 47073.95 examples/s]
Generating train split: 23798470 examples [31:01, 16205.27 examples/s]
Generating train split: 23802492 examples [31:02, 16346.34 examples/s]
Generating train split: 23806407 examples [31:02, 19006.39 examples/s]
Generating train split: 23809903 examples [31:02, 13681.93 examples/s]
Generating train split: 23812568 examples [31:02, 14442.21 examples/s]
Generating train split: 23817380 examples [31:02, 19026.51 examples/s]
Generating train split: 23820842 examples [31:03, 21545.81 examples/s]
Generating train split: 23824075 examples [31:03, 23433.47 examples/s]
Generating train split: 23831323 examples [31:03, 33782.98 examples/s]
Generating train split: 23840903 examples [31:03, 48137.83 examples/s]
Generating train split: 23846872 examples [31:03, 25629.37 examples/s]
Generating train split: 23851408 examples [31:04, 19732.64 examples/s]
Generating train split: 23854935 examples [31:04, 19983.14 examples/s]
Generating train split: 23863251 examples [31:04, 29178.35 examples/s]
Generating train split: 23870530 examples [31:04, 36443.88 examples/s]
Generating train split: 23875892 examples [31:05, 25348.65 examples/s]
Generating train split: 23883235 examples [31:05, 32630.07 examples/s]
Generating train split: 23894360 examples [31:05, 46614.96 examples/s]
Generating train split: 23901283 examples [31:05, 24420.50 examples/s]
Generating train split: 23906477 examples [31:06, 24986.61 examples/s]
Generating train split: 23910909 examples [31:06, 20796.37 examples/s]
Generating train split: 23914402 examples [31:06, 19947.94 examples/s]
Generating train split: 23917366 examples [31:06, 19114.86 examples/s]
Generating train split: 23921649 examples [31:06, 22675.51 examples/s]
Generating train split: 23932162 examples [31:07, 37253.09 examples/s]
Generating train split: 23937483 examples [31:07, 30692.79 examples/s]
Generating train split: 23945660 examples [31:07, 39843.21 examples/s]
Generating train split: 23954107 examples [31:07, 48925.77 examples/s]
Generating train split: 23960485 examples [31:08, 23290.60 examples/s]
Generating train split: 23965250 examples [31:08, 23890.11 examples/s]
Generating train split: 23969363 examples [31:08, 18988.90 examples/s]
Generating train split: 23972579 examples [31:08, 16580.44 examples/s]
Generating train split: 23975161 examples [31:09, 17629.09 examples/s]
Generating train split: 23977754 examples [31:09, 18864.38 examples/s]
Generating train split: 23980303 examples [31:09, 16863.81 examples/s]
Generating train split: 23982463 examples [31:09, 14628.44 examples/s]
Generating train split: 23984274 examples [31:09, 14359.77 examples/s]
Generating train split: 23985945 examples [31:09, 12953.75 examples/s]
Generating train split: 23987782 examples [31:10, 13852.92 examples/s]
Generating train split: 23989327 examples [31:10, 12968.34 examples/s]
Generating train split: 23992545 examples [31:10, 17139.06 examples/s]
Generating train split: 23994491 examples [31:10, 16768.52 examples/s]
Generating train split: 23996329 examples [31:10, 15084.60 examples/s]
Generating train split: 23997981 examples [31:10, 13124.97 examples/s]
Generating train split: 24000947 examples [31:10, 16737.86 examples/s]
Generating train split: 24002827 examples [31:10, 15102.20 examples/s]
Generating train split: 24009554 examples [31:11, 27136.10 examples/s]
Generating train split: 24018750 examples [31:11, 43206.65 examples/s]
Generating train split: 24023749 examples [31:11, 31506.18 examples/s]
Generating train split: 24027813 examples [31:11, 24150.09 examples/s]
Generating train split: 24033165 examples [31:11, 29327.98 examples/s]
Generating train split: 24040282 examples [31:11, 37749.31 examples/s]
Generating train split: 24045148 examples [31:12, 30429.61 examples/s]
Generating train split: 24049154 examples [31:12, 30153.05 examples/s]
Generating train split: 24053930 examples [31:12, 33767.18 examples/s]
Generating train split: 24057937 examples [31:12, 31601.18 examples/s]
Generating train split: 24064745 examples [31:12, 39834.71 examples/s]
Generating train split: 24071408 examples [31:12, 46353.43 examples/s]
Generating train split: 24076609 examples [31:13, 25341.71 examples/s]
Generating train split: 24080792 examples [31:13, 28027.74 examples/s]
Generating train split: 24084848 examples [31:13, 18998.40 examples/s]
Generating train split: 24087973 examples [31:13, 20540.95 examples/s]
Generating train split: 24091030 examples [31:13, 22119.91 examples/s]
Generating train split: 24094060 examples [31:14, 16655.31 examples/s]
Generating train split: 24097652 examples [31:14, 19796.72 examples/s]
Generating train split: 24103781 examples [31:14, 27582.16 examples/s]
Generating train split: 24108697 examples [31:14, 32045.13 examples/s]
Generating train split: 24112787 examples [31:14, 22617.61 examples/s]
Generating train split: 24116031 examples [31:14, 24132.38 examples/s]
Generating train split: 24124825 examples [31:15, 37080.86 examples/s]
Generating train split: 24133623 examples [31:15, 48518.06 examples/s]
Generating train split: 24139679 examples [31:15, 49178.18 examples/s]
Generating train split: 24149300 examples [31:15, 60890.90 examples/s]
Generating train split: 24156584 examples [31:15, 64025.99 examples/s]
Generating train split: 24163620 examples [31:15, 33631.44 examples/s]
Generating train split: 24170433 examples [31:16, 39357.77 examples/s]
Generating train split: 24180046 examples [31:16, 50237.65 examples/s]
Generating train split: 24187002 examples [31:16, 49947.43 examples/s]
Generating train split: 24193354 examples [31:16, 28926.49 examples/s]
Generating train split: 24199890 examples [31:16, 34262.12 examples/s]
Generating train split: 24207679 examples [31:16, 41806.66 examples/s]
Generating train split: 24213769 examples [31:17, 32875.25 examples/s]
Generating train split: 24218642 examples [31:17, 23946.17 examples/s]
Generating train split: 24222438 examples [31:18, 17471.88 examples/s]
Generating train split: 24225353 examples [31:18, 14868.94 examples/s]
Generating train split: 24227664 examples [31:18, 12315.84 examples/s]
Generating train split: 24229487 examples [31:19, 10124.25 examples/s]
Generating train split: 24230924 examples [31:19, 9018.83 examples/s] 
Generating train split: 24232748 examples [31:19, 10136.39 examples/s]
Generating train split: 24234181 examples [31:19, 10635.50 examples/s]
Generating train split: 24235539 examples [31:19, 8449.92 examples/s] 
Generating train split: 24236640 examples [31:20, 5420.84 examples/s]
Generating train split: 24237471 examples [31:21, 3453.57 examples/s]
Generating train split: 24238097 examples [31:21, 3224.90 examples/s]
Generating train split: 24238854 examples [31:21, 3664.03 examples/s]
Generating train split: 24239431 examples [31:21, 3531.84 examples/s]
Generating train split: 24240154 examples [31:21, 4034.92 examples/s]
Generating train split: 24240708 examples [31:21, 3836.47 examples/s]
Generating train split: 24241414 examples [31:21, 4367.99 examples/s]
Generating train split: 24241961 examples [31:22, 4021.52 examples/s]
Generating train split: 24243293 examples [31:22, 5863.10 examples/s]
Generating train split: 24244022 examples [31:22, 5993.76 examples/s]
Generating train split: 24244888 examples [31:22, 6548.56 examples/s]
Generating train split: 24246994 examples [31:22, 10037.34 examples/s]
Generating train split: 24248122 examples [31:22, 9137.23 examples/s] 
Generating train split: 24249237 examples [31:22, 9614.68 examples/s]
Generating train split: 24250274 examples [31:22, 8780.11 examples/s]
Generating train split: 24251917 examples [31:23, 10687.24 examples/s]
Generating train split: 24253076 examples [31:23, 9091.88 examples/s] 
Generating train split: 24255197 examples [31:23, 11974.02 examples/s]
Generating train split: 24256541 examples [31:23, 11354.90 examples/s]
Generating train split: 24257842 examples [31:23, 11765.10 examples/s]
Generating train split: 24259099 examples [31:23, 9072.05 examples/s] 
Generating train split: 24260151 examples [31:23, 8635.90 examples/s]
Generating train split: 24261263 examples [31:24, 9152.67 examples/s]
Generating train split: 24262286 examples [31:24, 9270.86 examples/s]
Generating train split: 24263745 examples [31:24, 10562.03 examples/s]
Generating train split: 24266051 examples [31:24, 13868.31 examples/s]
Generating train split: 24267536 examples [31:24, 13515.40 examples/s]
Generating train split: 24271975 examples [31:24, 21935.66 examples/s]
Generating train split: 24279548 examples [31:24, 37014.60 examples/s]
Generating train split: 24283451 examples [31:24, 24806.41 examples/s]
Generating train split: 24286598 examples [31:25, 25077.10 examples/s]
Generating train split: 24294406 examples [31:25, 36994.38 examples/s]
Generating train split: 24301698 examples [31:25, 45724.84 examples/s]
Generating train split: 24306990 examples [31:25, 45913.01 examples/s]
Generating train split: 24312097 examples [31:25, 41754.37 examples/s]
Generating train split: 24316696 examples [31:25, 35913.81 examples/s]
Generating train split: 24320684 examples [31:25, 31262.06 examples/s]
Generating train split: 24324158 examples [31:25, 30241.20 examples/s]
Generating train split: 24332798 examples [31:26, 42984.83 examples/s]
Generating train split: 24341594 examples [31:26, 53994.31 examples/s]
Generating train split: 24347635 examples [31:26, 35943.72 examples/s]
Generating train split: 24352445 examples [31:26, 30492.62 examples/s]
Generating train split: 24356438 examples [31:26, 30773.32 examples/s]
Generating train split: 24360185 examples [31:27, 20214.99 examples/s]
Generating train split: 24363096 examples [31:27, 20716.05 examples/s]
Generating train split: 24365826 examples [31:27, 18895.70 examples/s]
Generating train split: 24368163 examples [31:27, 19637.43 examples/s]
Generating train split: 24370609 examples [31:27, 20516.20 examples/s]
Generating train split: 24372962 examples [31:27, 18051.20 examples/s]
Generating train split: 24375003 examples [31:28, 13781.97 examples/s]
Generating train split: 24376772 examples [31:28, 14466.68 examples/s]
Generating train split: 24378694 examples [31:28, 15448.39 examples/s]
Generating train split: 24382064 examples [31:28, 19609.69 examples/s]
Generating train split: 24384313 examples [31:28, 14835.04 examples/s]
Generating train split: 24386151 examples [31:28, 13312.18 examples/s]
Generating train split: 24388508 examples [31:29, 15344.34 examples/s]
Generating train split: 24396324 examples [31:29, 29278.84 examples/s]
Generating train split: 24404007 examples [31:29, 40714.32 examples/s]
Generating train split: 24408849 examples [31:29, 30034.13 examples/s]
Generating train split: 24412787 examples [31:29, 21530.97 examples/s]
Generating train split: 24415898 examples [31:30, 20161.64 examples/s]
Generating train split: 24418565 examples [31:30, 14270.12 examples/s]
Generating train split: 24420644 examples [31:30, 10319.18 examples/s]
Generating train split: 24425426 examples [31:30, 14811.77 examples/s]
Generating train split: 24433893 examples [31:31, 25018.88 examples/s]
Generating train split: 24439933 examples [31:31, 31121.94 examples/s]
Generating train split: 24444784 examples [31:31, 20610.80 examples/s]
Generating train split: 24448506 examples [31:31, 22295.59 examples/s]
Generating train split: 24454741 examples [31:31, 28958.72 examples/s]
Generating train split: 24462624 examples [31:31, 38357.04 examples/s]
Generating train split: 24467964 examples [31:32, 24604.81 examples/s]
Generating train split: 24472092 examples [31:32, 26313.24 examples/s]
Generating train split: 24479087 examples [31:32, 33957.87 examples/s]
Generating train split: 24485793 examples [31:32, 39996.71 examples/s]
Generating train split: 24491064 examples [31:33, 27738.57 examples/s]
Generating train split: 24499191 examples [31:33, 36790.60 examples/s]
Generating train split: 24509156 examples [31:33, 49012.98 examples/s]
Generating train split: 24515891 examples [31:33, 50609.41 examples/s]
Generating train split: 24522263 examples [31:33, 29254.01 examples/s]
Generating train split: 24527137 examples [31:33, 29215.30 examples/s]
Generating train split: 24531418 examples [31:34, 31119.40 examples/s]
Generating train split: 24539002 examples [31:34, 39529.43 examples/s]
Generating train split: 24546285 examples [31:34, 44985.97 examples/s]
Generating train split: 24551814 examples [31:34, 27772.15 examples/s]
Generating train split: 24556087 examples [31:35, 20877.95 examples/s]
Generating train split: 24559423 examples [31:35, 19789.19 examples/s]
Generating train split: 24567182 examples [31:35, 28206.58 examples/s]
Generating train split: 24574757 examples [31:35, 35732.93 examples/s]
Generating train split: 24579828 examples [31:35, 29580.84 examples/s]
Generating train split: 24583962 examples [31:35, 28088.33 examples/s]
Generating train split: 24592488 examples [31:36, 38486.68 examples/s]
Generating train split: 24598032 examples [31:36, 41967.06 examples/s]
Generating train split: 24603252 examples [31:36, 35366.51 examples/s]
Generating train split: 24610858 examples [31:36, 43745.88 examples/s]
Generating train split: 24619205 examples [31:36, 51985.86 examples/s]
Generating train split: 24625308 examples [31:37, 29044.28 examples/s]
Generating train split: 24629981 examples [31:37, 27462.95 examples/s]
Generating train split: 24637620 examples [31:37, 35381.45 examples/s]
Generating train split: 24645549 examples [31:37, 43626.59 examples/s]
Generating train split: 24651475 examples [31:37, 30260.96 examples/s]
Generating train split: 24656131 examples [31:38, 20437.09 examples/s]
Generating train split: 24659676 examples [31:38, 18192.83 examples/s]
Generating train split: 24662551 examples [31:38, 16241.92 examples/s]
Generating train split: 24665368 examples [31:38, 17812.73 examples/s]
Generating train split: 24667856 examples [31:39, 16981.01 examples/s]
Generating train split: 24676581 examples [31:39, 28849.88 examples/s]
Generating train split: 24687104 examples [31:39, 43690.09 examples/s]
Generating train split: 24693153 examples [31:39, 29618.99 examples/s]
Generating train split: 24701371 examples [31:39, 38163.48 examples/s]
Generating train split: 24710221 examples [31:39, 47439.02 examples/s]
Generating train split: 24716859 examples [31:40, 27933.09 examples/s]
Generating train split: 24724041 examples [31:40, 34110.90 examples/s]
Generating train split: 24735131 examples [31:40, 46966.32 examples/s]
Generating train split: 24742446 examples [31:40, 32594.44 examples/s]
Generating train split: 24751149 examples [31:41, 40614.73 examples/s]
Generating train split: 24759369 examples [31:41, 47773.32 examples/s]
Generating train split: 24766408 examples [31:41, 50189.86 examples/s]
Generating train split: 24774991 examples [31:41, 57808.89 examples/s]
Generating train split: 24782254 examples [31:41, 48727.91 examples/s]
Generating train split: 24788363 examples [31:41, 31205.66 examples/s]
Generating train split: 24793100 examples [31:42, 27841.70 examples/s]
Generating train split: 24797014 examples [31:42, 22594.05 examples/s]
Generating train split: 24800156 examples [31:43, 14643.03 examples/s]
Generating train split: 24802531 examples [31:43, 14388.11 examples/s]
Generating train split: 24804596 examples [31:43, 14826.16 examples/s]
Generating train split: 24806556 examples [31:43, 14941.92 examples/s]
Generating train split: 24808395 examples [31:43, 14983.32 examples/s]
Generating train split: 24810134 examples [31:43, 13686.15 examples/s]
Generating train split: 24811676 examples [31:43, 13327.95 examples/s]
Generating train split: 24813873 examples [31:44, 15011.25 examples/s]
Generating train split: 24815520 examples [31:44, 11298.38 examples/s]
Generating train split: 24816868 examples [31:44, 11287.18 examples/s]
Generating train split: 24819287 examples [31:44, 14005.96 examples/s]
Generating train split: 24820916 examples [31:44, 11397.11 examples/s]
Generating train split: 24822275 examples [31:45, 8014.98 examples/s] 
Generating train split: 24824063 examples [31:45, 9649.60 examples/s]
Generating train split: 24825706 examples [31:45, 10906.45 examples/s]
Generating train split: 24827098 examples [31:45, 10911.49 examples/s]
Generating train split: 24828397 examples [31:45, 6959.59 examples/s] 
Generating train split: 24829411 examples [31:45, 6697.81 examples/s]
Generating train split: 24830298 examples [31:46, 6230.34 examples/s]
Generating train split: 24831073 examples [31:46, 5665.73 examples/s]
Generating train split: 24831744 examples [31:46, 3912.84 examples/s]
Generating train split: 24832274 examples [31:46, 4092.99 examples/s]
Generating train split: 24832957 examples [31:46, 4532.79 examples/s]
Generating train split: 24833524 examples [31:47, 3832.09 examples/s]
Generating train split: 24834530 examples [31:47, 4763.87 examples/s]
Generating train split: 24835112 examples [31:47, 4556.89 examples/s]
Generating train split: 24835633 examples [31:47, 4469.84 examples/s]
Generating train split: 24838263 examples [31:47, 9289.59 examples/s]
Generating train split: 24840322 examples [31:47, 11999.56 examples/s]
Generating train split: 24841740 examples [31:47, 12074.02 examples/s]
Generating train split: 24843268 examples [31:47, 12890.45 examples/s]
Generating train split: 24849955 examples [31:47, 27473.95 examples/s]
Generating train split: 24858190 examples [31:48, 42757.73 examples/s]
Generating train split: 24863511 examples [31:48, 44348.93 examples/s]
Generating train split: 24868142 examples [31:48, 25306.74 examples/s]
Generating train split: 24875975 examples [31:48, 35136.53 examples/s]
Generating train split: 24883426 examples [31:48, 43371.52 examples/s]
Generating train split: 24889075 examples [31:48, 44905.38 examples/s]
Generating train split: 24896998 examples [31:48, 53180.82 examples/s]
Generating train split: 24904323 examples [31:49, 58289.25 examples/s]
Generating train split: 24910845 examples [31:49, 27834.30 examples/s]
Generating train split: 24915774 examples [31:50, 19505.44 examples/s]
Generating train split: 24919534 examples [31:50, 16427.19 examples/s]
Generating train split: 24922516 examples [31:50, 17948.34 examples/s]
Generating train split: 24925460 examples [31:50, 16813.47 examples/s]
Generating train split: 24927931 examples [31:51, 14324.99 examples/s]
Generating train split: 24929943 examples [31:51, 14094.65 examples/s]
Generating train split: 24931748 examples [31:51, 14560.04 examples/s]
Generating train split: 24933516 examples [31:51, 14771.01 examples/s]
Generating train split: 24935219 examples [31:51, 15107.93 examples/s]
Generating train split: 24938917 examples [31:51, 20017.44 examples/s]
Generating train split: 24947813 examples [31:51, 36757.84 examples/s]
Generating train split: 24953948 examples [31:51, 42972.56 examples/s]
Generating train split: 24958763 examples [31:52, 23619.92 examples/s]
Generating train split: 24962468 examples [31:52, 21165.82 examples/s]
Generating train split: 24965550 examples [31:52, 17695.40 examples/s]
Generating train split: 24968046 examples [31:52, 17302.74 examples/s]
Generating train split: 24970276 examples [31:53, 16703.59 examples/s]
Generating train split: 24972278 examples [31:53, 16745.29 examples/s]
Generating train split: 24974833 examples [31:53, 18511.01 examples/s]
Generating train split: 24976943 examples [31:53, 18001.84 examples/s]
Generating train split: 24978911 examples [31:53, 11779.07 examples/s]
Generating train split: 24980465 examples [31:53, 10952.59 examples/s]
Generating train split: 24981821 examples [31:54, 11008.89 examples/s]
Generating train split: 24990884 examples [31:54, 26818.83 examples/s]
Generating train split: 24999713 examples [31:54, 40398.46 examples/s]
Generating train split: 25004890 examples [31:54, 19457.09 examples/s]
Generating train split: 25008772 examples [31:55, 16523.85 examples/s]
Generating train split: 25011822 examples [31:55, 16490.85 examples/s]
Generating train split: 25014452 examples [31:55, 15302.76 examples/s]
Generating train split: 25016650 examples [31:55, 12066.16 examples/s]
Generating train split: 25018383 examples [31:56, 11395.97 examples/s]
Generating train split: 25019878 examples [31:56, 10363.10 examples/s]
Generating train split: 25021143 examples [31:56, 10610.77 examples/s]
Generating train split: 25028663 examples [31:56, 22112.97 examples/s]
Generating train split: 25035232 examples [31:56, 30950.77 examples/s]
Generating train split: 25039391 examples [31:56, 31159.93 examples/s]
Generating train split: 25045464 examples [31:56, 37980.81 examples/s]
Generating train split: 25053499 examples [31:57, 48114.95 examples/s]
Generating train split: 25059012 examples [31:57, 29264.26 examples/s]
Generating train split: 25065132 examples [31:57, 34965.74 examples/s]
Generating train split: 25072606 examples [31:57, 43047.40 examples/s]
Generating train split: 25078245 examples [31:57, 32389.19 examples/s]
Generating train split: 25082788 examples [31:58, 27631.50 examples/s]
Generating train split: 25090357 examples [31:58, 35945.09 examples/s]
Generating train split: 25097347 examples [31:58, 42666.22 examples/s]
Generating train split: 25102862 examples [31:58, 20013.24 examples/s]
Generating train split: 25106974 examples [31:59, 19497.21 examples/s]
Generating train split: 25110385 examples [31:59, 16666.40 examples/s]
Generating train split: 25113098 examples [31:59, 15726.45 examples/s]
Generating train split: 25120623 examples [31:59, 23864.76 examples/s]
Generating train split: 25128857 examples [31:59, 33418.42 examples/s]
Generating train split: 25134027 examples [32:00, 26881.91 examples/s]
Generating train split: 25141262 examples [32:00, 34363.95 examples/s]
Generating train split: 25150685 examples [32:00, 45751.87 examples/s]
Generating train split: 25157062 examples [32:00, 36849.53 examples/s]
Generating train split: 25162255 examples [32:00, 31561.35 examples/s]
Generating train split: 25166549 examples [32:01, 30464.64 examples/s]
Generating train split: 25170867 examples [32:01, 32802.03 examples/s]
Generating train split: 25176132 examples [32:01, 36932.01 examples/s]
Generating train split: 25181931 examples [32:01, 41747.62 examples/s]
Generating train split: 25186719 examples [32:01, 42632.19 examples/s]
Generating train split: 25191601 examples [32:01, 44213.53 examples/s]
Generating train split: 25196583 examples [32:01, 45721.03 examples/s]
Generating train split: 25202262 examples [32:01, 48780.86 examples/s]
Generating train split: 25208179 examples [32:01, 51711.96 examples/s]
Generating train split: 25213519 examples [32:02, 51252.13 examples/s]
Generating train split: 25218762 examples [32:02, 51402.12 examples/s]
Generating train split: 25223987 examples [32:02, 49686.15 examples/s]
Generating train split: 25230071 examples [32:02, 52864.67 examples/s]
Generating train split: 25235433 examples [32:02, 51117.83 examples/s]
Generating train split: 25240597 examples [32:02, 49015.31 examples/s]
Generating train split: 25246305 examples [32:02, 51263.42 examples/s]
Generating train split: 25251490 examples [32:02, 45048.69 examples/s]
Generating train split: 25256170 examples [32:02, 42148.52 examples/s]
Generating train split: 25263000 examples [32:03, 48896.52 examples/s]
Generating train split: 25270258 examples [32:03, 55255.71 examples/s]
Generating train split: 25276707 examples [32:03, 57803.69 examples/s]
Generating train split: 25282667 examples [32:03, 55933.33 examples/s]
Generating train split: 25290689 examples [32:03, 62730.63 examples/s]
Generating train split: 25297106 examples [32:03, 61809.40 examples/s]
Generating train split: 25303383 examples [32:03, 61027.54 examples/s]
Generating train split: 25309555 examples [32:03, 49274.65 examples/s]
Generating train split: 25314883 examples [32:04, 45157.81 examples/s]
Generating train split: 25319708 examples [32:04, 37969.36 examples/s]
Generating train split: 25323874 examples [32:04, 31623.49 examples/s]
Generating train split: 25332124 examples [32:04, 42059.81 examples/s]
Generating train split: 25340960 examples [32:04, 52547.53 examples/s]
Generating train split: 25347078 examples [32:05, 29157.98 examples/s]
Generating train split: 25351756 examples [32:05, 26766.97 examples/s]
Generating train split: 25355662 examples [32:05, 20909.36 examples/s]
Generating train split: 25358746 examples [32:05, 18356.64 examples/s]
Generating train split: 25361279 examples [32:06, 17551.69 examples/s]
Generating train split: 25363491 examples [32:06, 16629.47 examples/s]
Generating train split: 25365446 examples [32:06, 16167.11 examples/s]
Generating train split: 25367566 examples [32:06, 17092.40 examples/s]
Generating train split: 25369473 examples [32:06, 14587.96 examples/s]
Generating train split: 25371303 examples [32:06, 15321.97 examples/s]
Generating train split: 25372986 examples [32:06, 15635.72 examples/s]
Generating train split: 25374669 examples [32:06, 15307.28 examples/s]
Generating train split: 25377509 examples [32:07, 18553.85 examples/s]
Generating train split: 25385341 examples [32:07, 34183.09 examples/s]
Generating train split: 25393594 examples [32:07, 46997.74 examples/s]
Generating train split: 25398628 examples [32:07, 36613.21 examples/s]
Generating train split: 25405839 examples [32:07, 44874.00 examples/s]
Generating train split: 25415452 examples [32:07, 57668.99 examples/s]
Generating train split: 25421930 examples [32:08, 26511.32 examples/s]
Generating train split: 25426803 examples [32:08, 29155.57 examples/s]
Generating train split: 25433340 examples [32:08, 35214.33 examples/s]
Generating train split: 25439470 examples [32:08, 40130.78 examples/s]
Generating train split: 25444969 examples [32:08, 25212.07 examples/s]
Generating train split: 25449200 examples [32:09, 26967.13 examples/s]
Generating train split: 25458104 examples [32:09, 37760.37 examples/s]
Generating train split: 25464134 examples [32:09, 42210.69 examples/s]
Generating train split: 25469780 examples [32:09, 41907.11 examples/s]
Generating train split: 25478951 examples [32:09, 53159.77 examples/s]
Generating train split: 25485342 examples [32:09, 54501.87 examples/s]
Generating train split: 25492260 examples [32:09, 58221.84 examples/s]
Generating train split: 25499414 examples [32:09, 61766.64 examples/s]
Generating train split: 25506062 examples [32:10, 32649.25 examples/s]
Generating train split: 25511181 examples [32:10, 28420.59 examples/s]
Generating train split: 25515374 examples [32:10, 22383.23 examples/s]
Generating train split: 25518693 examples [32:11, 14023.91 examples/s]
Generating train split: 25521184 examples [32:11, 12911.58 examples/s]
Generating train split: 25523207 examples [32:11, 12554.31 examples/s]
Generating train split: 25525912 examples [32:12, 14436.85 examples/s]
Generating train split: 25527941 examples [32:12, 15349.31 examples/s]
Generating train split: 25529972 examples [32:12, 13414.74 examples/s]
Generating train split: 25538025 examples [32:12, 25345.90 examples/s]
Generating train split: 25545159 examples [32:12, 34660.88 examples/s]
Generating train split: 25549866 examples [32:12, 37441.78 examples/s]
Generating train split: 25554549 examples [32:12, 27176.68 examples/s]
Generating train split: 25558307 examples [32:13, 22155.79 examples/s]
Generating train split: 25561365 examples [32:13, 22804.46 examples/s]
Generating train split: 25564270 examples [32:13, 23753.25 examples/s]
Generating train split: 25567130 examples [32:13, 20599.57 examples/s]
Generating train split: 25569570 examples [32:13, 19468.94 examples/s]
Generating train split: 25571773 examples [32:13, 16352.75 examples/s]
Generating train split: 25573636 examples [32:14, 14719.16 examples/s]
Generating train split: 25576545 examples [32:14, 17505.92 examples/s]
Generating train split: 25578985 examples [32:14, 19012.07 examples/s]
Generating train split: 25581777 examples [32:14, 20996.79 examples/s]
Generating train split: 25584859 examples [32:14, 23438.65 examples/s]
Generating train split: 25590404 examples [32:14, 31910.32 examples/s]
Generating train split: 25593841 examples [32:14, 30699.29 examples/s]
Generating train split: 25597103 examples [32:14, 30700.75 examples/s]
Generating train split: 25602760 examples [32:14, 37787.82 examples/s]
Generating train split: 25607667 examples [32:15, 40958.01 examples/s]
Generating train split: 25613604 examples [32:15, 46136.29 examples/s]
Generating train split: 25618334 examples [32:15, 39324.01 examples/s]
Generating train split: 25622514 examples [32:15, 38884.94 examples/s]
Generating train split: 25627549 examples [32:15, 41915.52 examples/s]
Generating train split: 25631918 examples [32:15, 31616.89 examples/s]
Generating train split: 25637512 examples [32:15, 37121.63 examples/s]
Generating train split: 25643432 examples [32:16, 37494.64 examples/s]
Generating train split: 25647538 examples [32:16, 37875.71 examples/s]
Generating train split: 25651585 examples [32:16, 37067.97 examples/s]
Generating train split: 25656589 examples [32:16, 40368.84 examples/s]
Generating train split: 25662090 examples [32:16, 44264.20 examples/s]
Generating train split: 25666716 examples [32:16, 38559.29 examples/s]
Generating train split: 25670818 examples [32:16, 38260.17 examples/s]
Generating train split: 25675308 examples [32:16, 39983.00 examples/s]
Generating train split: 25682661 examples [32:16, 49085.11 examples/s]
Generating train split: 25688051 examples [32:17, 49411.72 examples/s]
Generating train split: 25693129 examples [32:17, 28166.90 examples/s]
Generating train split: 25697099 examples [32:17, 30120.32 examples/s]
Generating train split: 25702617 examples [32:17, 35335.86 examples/s]
Generating train split: 25707032 examples [32:17, 37082.43 examples/s]
Generating train split: 25711565 examples [32:17, 39092.76 examples/s]
Generating train split: 25716667 examples [32:17, 42186.78 examples/s]
Generating train split: 25721292 examples [32:18, 41104.18 examples/s]
Generating train split: 25726466 examples [32:18, 43730.06 examples/s]
Generating train split: 25731071 examples [32:18, 31618.32 examples/s]
Generating train split: 25734865 examples [32:18, 32809.79 examples/s]
Generating train split: 25739380 examples [32:18, 35740.05 examples/s]
Generating train split: 25747579 examples [32:18, 47446.85 examples/s]
Generating train split: 25752832 examples [32:18, 39645.47 examples/s]
Generating train split: 25757355 examples [32:19, 29242.63 examples/s]
Generating train split: 25761030 examples [32:19, 25282.27 examples/s]
Generating train split: 25765251 examples [32:19, 28420.11 examples/s]
Generating train split: 25770471 examples [32:19, 33396.29 examples/s]
Generating train split: 25775644 examples [32:19, 37611.23 examples/s]
Generating train split: 25780620 examples [32:19, 40612.89 examples/s]
Generating train split: 25785587 examples [32:19, 42975.87 examples/s]
Generating train split: 25790244 examples [32:19, 39098.38 examples/s]
Generating train split: 25794508 examples [32:20, 39998.66 examples/s]
Generating train split: 25799058 examples [32:20, 41453.83 examples/s]
Generating train split: 25803396 examples [32:20, 36923.25 examples/s]
Generating train split: 25810179 examples [32:20, 44410.88 examples/s]
Generating train split: 25814860 examples [32:20, 32747.20 examples/s]
Generating train split: 25818721 examples [32:20, 32418.26 examples/s]
Generating train split: 25822369 examples [32:20, 27787.27 examples/s]
Generating train split: 25825695 examples [32:21, 28938.51 examples/s]
Generating train split: 25828899 examples [32:21, 27726.05 examples/s]
Generating train split: 25831873 examples [32:21, 25743.67 examples/s]
Generating train split: 25835707 examples [32:21, 28723.98 examples/s]
Generating train split: 25839413 examples [32:21, 30742.08 examples/s]
Generating train split: 25842655 examples [32:21, 19190.91 examples/s]
Generating train split: 25845259 examples [32:21, 20478.20 examples/s]
Generating train split: 25849036 examples [32:22, 23729.40 examples/s]
Generating train split: 25854586 examples [32:22, 31021.72 examples/s]
Generating train split: 25862494 examples [32:22, 42879.36 examples/s]
Generating train split: 25867423 examples [32:22, 43077.55 examples/s]
Generating train split: 25872185 examples [32:22, 31952.68 examples/s]
Generating train split: 25876103 examples [32:22, 24621.17 examples/s]
Generating train split: 25879287 examples [32:23, 22199.24 examples/s]
Generating train split: 25882012 examples [32:23, 17094.18 examples/s]
Generating train split: 25885755 examples [32:23, 20387.93 examples/s]
Generating train split: 25890202 examples [32:23, 24916.61 examples/s]
Generating train split: 25894966 examples [32:23, 29725.68 examples/s]
Generating train split: 25898628 examples [32:23, 24055.77 examples/s]
Generating train split: 25901735 examples [32:24, 25479.71 examples/s]
Generating train split: 25904970 examples [32:24, 27010.60 examples/s]
Generating train split: 25908086 examples [32:24, 26655.56 examples/s]
Generating train split: 25911036 examples [32:24, 22488.53 examples/s]
Generating train split: 25913585 examples [32:24, 22181.48 examples/s]
Generating train split: 25916011 examples [32:24, 22203.60 examples/s]
Generating train split: 25920442 examples [32:24, 27114.29 examples/s]
Generating train split: 25925073 examples [32:24, 31530.04 examples/s]
Generating train split: 25929218 examples [32:24, 34154.03 examples/s]
Generating train split: 25934396 examples [32:25, 38997.48 examples/s]
Generating train split: 25941750 examples [32:25, 48731.85 examples/s]
Generating train split: 25949239 examples [32:25, 56136.40 examples/s]
Generating train split: 25955004 examples [32:25, 35193.99 examples/s]
Generating train split: 25959597 examples [32:25, 29678.45 examples/s]
Generating train split: 25966339 examples [32:25, 36791.45 examples/s]
Generating train split: 25973996 examples [32:26, 45124.54 examples/s]
Generating train split: 25979565 examples [32:26, 40930.16 examples/s]
Generating train split: 25988244 examples [32:26, 51102.85 examples/s]
Generating train split: 25994258 examples [32:26, 49090.24 examples/s]
Generating train split: 26002175 examples [32:26, 56314.65 examples/s]
Generating train split: 26010438 examples [32:26, 63036.81 examples/s]
Generating train split: 26017292 examples [32:27, 36528.25 examples/s]
Generating train split: 26025584 examples [32:27, 44777.33 examples/s]
Generating train split: 26034380 examples [32:27, 53522.97 examples/s]
Generating train split: 26041376 examples [32:27, 29056.98 examples/s]
Generating train split: 26046673 examples [32:28, 25747.85 examples/s]
Generating train split: 26050933 examples [32:28, 17400.20 examples/s]
Generating train split: 26054155 examples [32:28, 15853.00 examples/s]
Generating train split: 26056754 examples [32:29, 13411.92 examples/s]
Generating train split: 26060170 examples [32:29, 15778.07 examples/s]
Generating train split: 26068255 examples [32:29, 24895.59 examples/s]
Generating train split: 26076112 examples [32:29, 33841.79 examples/s]
Generating train split: 26081368 examples [32:29, 27016.48 examples/s]
Generating train split: 26085578 examples [32:30, 23634.29 examples/s]
Generating train split: 26089027 examples [32:30, 25242.01 examples/s]
Generating train split: 26092457 examples [32:30, 22664.09 examples/s]
Generating train split: 26095362 examples [32:30, 22831.52 examples/s]
Generating train split: 26098107 examples [32:30, 18508.29 examples/s]
Generating train split: 26100368 examples [32:30, 19243.96 examples/s]
Generating train split: 26102633 examples [32:30, 18376.97 examples/s]
Generating train split: 26105292 examples [32:31, 20089.99 examples/s]
Generating train split: 26107530 examples [32:31, 20372.71 examples/s]
Generating train split: 26111870 examples [32:31, 26039.44 examples/s]
Generating train split: 26114709 examples [32:31, 24309.39 examples/s]
Generating train split: 26117318 examples [32:31, 24399.57 examples/s]
Generating train split: 26119888 examples [32:31, 21365.33 examples/s]
Generating train split: 26123216 examples [32:31, 24278.90 examples/s]
Generating train split: 26125808 examples [32:31, 21575.82 examples/s]
Generating train split: 26128130 examples [32:32, 21446.57 examples/s]
Generating train split: 26130384 examples [32:32, 20074.77 examples/s]
Generating train split: 26134246 examples [32:32, 24728.36 examples/s]
Generating train split: 26139115 examples [32:32, 31029.57 examples/s]
Generating train split: 26142416 examples [32:32, 23325.67 examples/s]
Generating train split: 26146339 examples [32:32, 26884.68 examples/s]
Generating train split: 26149433 examples [32:33, 15188.62 examples/s]
Generating train split: 26151809 examples [32:33, 13043.61 examples/s]
Generating train split: 26153743 examples [32:33, 11371.34 examples/s]
Generating train split: 26155323 examples [32:33, 10676.49 examples/s]
Generating train split: 26156690 examples [32:34, 10281.99 examples/s]
Generating train split: 26157912 examples [32:34, 9536.27 examples/s] 
Generating train split: 26159023 examples [32:34, 9725.27 examples/s]
Generating train split: 26160096 examples [32:34, 9268.91 examples/s]
Generating train split: 26161463 examples [32:34, 10209.63 examples/s]
Generating train split: 26162763 examples [32:34, 10862.26 examples/s]
Generating train split: 26163932 examples [32:34, 10658.04 examples/s]
Generating train split: 26165057 examples [32:34, 10751.16 examples/s]
Generating train split: 26166570 examples [32:34, 11846.48 examples/s]
Generating train split: 26167792 examples [32:35, 7864.82 examples/s] 
Generating train split: 26168820 examples [32:35, 8328.51 examples/s]
Generating train split: 26169956 examples [32:35, 8890.12 examples/s]
Generating train split: 26170981 examples [32:35, 8870.43 examples/s]
Generating train split: 26171956 examples [32:35, 7341.68 examples/s]
Generating train split: 26172792 examples [32:35, 7297.75 examples/s]
Generating train split: 26175046 examples [32:35, 10852.97 examples/s]
Generating train split: 26176278 examples [32:36, 8565.58 examples/s] 
Generating train split: 26177373 examples [32:36, 9077.91 examples/s]
Generating train split: 26178427 examples [32:36, 8932.10 examples/s]
Generating train split: 26179688 examples [32:36, 9718.29 examples/s]
Generating train split: 26180750 examples [32:36, 8353.86 examples/s]
Generating train split: 26183446 examples [32:36, 12694.49 examples/s]
Generating train split: 26184904 examples [32:36, 12487.93 examples/s]
Generating train split: 26186616 examples [32:37, 13587.83 examples/s]
Generating train split: 26188089 examples [32:37, 12950.02 examples/s]
Generating train split: 26189469 examples [32:37, 10900.76 examples/s]
Generating train split: 26190894 examples [32:37, 11673.16 examples/s]
Generating train split: 26195917 examples [32:37, 21367.86 examples/s]
Generating train split: 26203725 examples [32:37, 36356.54 examples/s]
Generating train split: 26210508 examples [32:37, 44965.82 examples/s]
Generating train split: 26215357 examples [32:38, 21513.94 examples/s]
Generating train split: 26219039 examples [32:38, 16008.17 examples/s]
Generating train split: 26222359 examples [32:38, 18265.01 examples/s]
Generating train split: 26226285 examples [32:38, 21576.86 examples/s]
Generating train split: 26231893 examples [32:38, 27928.27 examples/s]
Generating train split: 26238762 examples [32:39, 36413.03 examples/s]
Generating train split: 26243602 examples [32:39, 26824.45 examples/s]
Generating train split: 26247475 examples [32:39, 26388.20 examples/s]
Generating train split: 26252869 examples [32:39, 31682.23 examples/s]
Generating train split: 26261676 examples [32:39, 43832.04 examples/s]
Generating train split: 26267658 examples [32:39, 46327.95 examples/s]
Generating train split: 26273110 examples [32:40, 28362.45 examples/s]
Generating train split: 26277340 examples [32:40, 26074.65 examples/s]
Generating train split: 26280925 examples [32:40, 21681.50 examples/s]
Generating train split: 26283843 examples [32:40, 19733.54 examples/s]
Generating train split: 26287387 examples [32:40, 22323.21 examples/s]
Generating train split: 26293331 examples [32:41, 29407.22 examples/s]
Generating train split: 26299896 examples [32:41, 37174.25 examples/s]
Generating train split: 26308378 examples [32:41, 47675.78 examples/s]
Generating train split: 26314002 examples [32:41, 31286.49 examples/s]
Generating train split: 26318434 examples [32:41, 31895.69 examples/s]
Generating train split: 26326252 examples [32:41, 41050.51 examples/s]
Generating train split: 26331482 examples [32:42, 25850.59 examples/s]
Generating train split: 26336392 examples [32:42, 29507.31 examples/s]
Generating train split: 26341168 examples [32:42, 32841.24 examples/s]
Generating train split: 26345607 examples [32:42, 24839.86 examples/s]
Generating train split: 26349165 examples [32:42, 26471.11 examples/s]
Generating train split: 26358744 examples [32:42, 40104.31 examples/s]
Generating train split: 26368398 examples [32:43, 52473.79 examples/s]
Generating train split: 26375029 examples [32:43, 50578.34 examples/s]
Generating train split: 26381056 examples [32:43, 49635.23 examples/s]
Generating train split: 26389270 examples [32:43, 57444.13 examples/s]
Generating train split: 26395683 examples [32:43, 56161.58 examples/s]
Generating train split: 26401779 examples [32:43, 30289.87 examples/s]
Generating train split: 26406453 examples [32:44, 31530.90 examples/s]
Generating train split: 26410819 examples [32:44, 21143.25 examples/s]
Generating train split: 26414177 examples [32:44, 22856.72 examples/s]
Generating train split: 26417529 examples [32:44, 23349.32 examples/s]
Generating train split: 26420642 examples [32:45, 19790.03 examples/s]
Generating train split: 26423211 examples [32:45, 18237.69 examples/s]
Generating train split: 26425432 examples [32:45, 18259.21 examples/s]
Generating train split: 26427547 examples [32:45, 15416.34 examples/s]
Generating train split: 26430468 examples [32:45, 17998.58 examples/s]
Generating train split: 26434261 examples [32:45, 22202.64 examples/s]
Generating train split: 26438234 examples [32:45, 25854.36 examples/s]
Generating train split: 26441195 examples [32:45, 24474.72 examples/s]
Generating train split: 26443909 examples [32:46, 20590.21 examples/s]
Generating train split: 26446919 examples [32:46, 22627.00 examples/s]
Generating train split: 26450369 examples [32:46, 25423.65 examples/s]
Generating train split: 26457789 examples [32:46, 37844.95 examples/s]
Generating train split: 26462694 examples [32:46, 40792.98 examples/s]
Generating train split: 26467084 examples [32:46, 26941.11 examples/s]
Generating train split: 26472378 examples [32:46, 32219.71 examples/s]
Generating train split: 26480658 examples [32:47, 43587.56 examples/s]
Generating train split: 26488320 examples [32:47, 51570.96 examples/s]
Generating train split: 26494334 examples [32:47, 28377.05 examples/s]
Generating train split: 26498956 examples [32:47, 25787.90 examples/s]
Generating train split: 26505138 examples [32:47, 31577.85 examples/s]
Generating train split: 26514778 examples [32:48, 43675.74 examples/s]
Generating train split: 26520844 examples [32:48, 29542.05 examples/s]
Generating train split: 26525563 examples [32:48, 31853.16 examples/s]
Generating train split: 26534015 examples [32:48, 41441.24 examples/s]
Generating train split: 26545005 examples [32:48, 55560.61 examples/s]
Generating train split: 26552324 examples [32:49, 41914.84 examples/s]
Generating train split: 26558221 examples [32:49, 33618.03 examples/s]
Generating train split: 26562978 examples [32:49, 33033.04 examples/s]
Generating train split: 26567251 examples [32:49, 33349.72 examples/s]
Generating train split: 26571284 examples [32:49, 31521.05 examples/s]
Generating train split: 26575163 examples [32:49, 32983.35 examples/s]
Generating train split: 26578854 examples [32:50, 20407.01 examples/s]
Generating train split: 26581725 examples [32:50, 21455.48 examples/s]
Generating train split: 26584578 examples [32:50, 22762.86 examples/s]
Generating train split: 26587408 examples [32:50, 15654.95 examples/s]
Generating train split: 26590887 examples [32:50, 18791.12 examples/s]
Generating train split: 26598968 examples [32:50, 30562.69 examples/s]
Generating train split: 26608965 examples [32:51, 45355.37 examples/s]
Generating train split: 26614931 examples [32:51, 26215.20 examples/s]
Generating train split: 26619488 examples [32:51, 28075.55 examples/s]
Generating train split: 26626519 examples [32:51, 35386.39 examples/s]
Generating train split: 26631640 examples [32:52, 26140.30 examples/s]
Generating train split: 26635669 examples [32:52, 28296.02 examples/s]
Generating train split: 26639946 examples [32:52, 30989.62 examples/s]
Generating train split: 26648673 examples [32:52, 42829.15 examples/s]
Generating train split: 26654914 examples [32:52, 47353.32 examples/s]
Generating train split: 26660630 examples [32:53, 25684.54 examples/s]
Generating train split: 26665801 examples [32:53, 29708.28 examples/s]
Generating train split: 26674072 examples [32:53, 39296.00 examples/s]
Generating train split: 26679823 examples [32:53, 43033.31 examples/s]
Generating train split: 26685541 examples [32:53, 43785.96 examples/s]
Generating train split: 26690918 examples [32:53, 24164.60 examples/s]
Generating train split: 26695026 examples [32:54, 19112.11 examples/s]
Generating train split: 26702105 examples [32:54, 25961.02 examples/s]
Generating train split: 26710344 examples [32:54, 34942.83 examples/s]
Generating train split: 26715869 examples [32:54, 30502.13 examples/s]
Generating train split: 26720425 examples [32:55, 19603.97 examples/s]
Generating train split: 26723891 examples [32:55, 19277.60 examples/s]
Generating train split: 26726855 examples [32:55, 18345.50 examples/s]
Generating train split: 26729401 examples [32:55, 17660.28 examples/s]
Generating train split: 26731698 examples [32:55, 18523.38 examples/s]
Generating train split: 26733952 examples [32:56, 13405.55 examples/s]
Generating train split: 26735742 examples [32:56, 13687.62 examples/s]
Generating train split: 26737438 examples [32:56, 12426.35 examples/s]
Generating train split: 26738907 examples [32:56, 10562.75 examples/s]
Generating train split: 26740136 examples [32:56, 10851.11 examples/s]
Generating train split: 26742443 examples [32:56, 13302.95 examples/s]
Generating train split: 26744897 examples [32:57, 15786.01 examples/s]
Generating train split: 26746720 examples [32:57, 16237.49 examples/s]
Generating train split: 26753721 examples [32:57, 29944.04 examples/s]
Generating train split: 26762248 examples [32:57, 44699.99 examples/s]
Generating train split: 26767168 examples [32:57, 25619.86 examples/s]
Generating train split: 26771000 examples [32:57, 24337.95 examples/s]
Generating train split: 26776693 examples [32:57, 30313.57 examples/s]
Generating train split: 26781457 examples [32:58, 33685.50 examples/s]
Generating train split: 26785664 examples [32:58, 26017.16 examples/s]
Generating train split: 26789093 examples [32:58, 25912.63 examples/s]
Generating train split: 26792265 examples [32:58, 26897.30 examples/s]
Generating train split: 26796832 examples [32:58, 31114.43 examples/s]
Generating train split: 26800403 examples [32:59, 20554.36 examples/s]
Generating train split: 26803221 examples [32:59, 21227.38 examples/s]
Generating train split: 26806282 examples [32:59, 23105.69 examples/s]
Generating train split: 26809092 examples [32:59, 14025.82 examples/s]
Generating train split: 26811255 examples [32:59, 14777.84 examples/s]
Generating train split: 26813318 examples [32:59, 15463.40 examples/s]
Generating train split: 26818732 examples [33:00, 23144.71 examples/s]
Generating train split: 26821753 examples [33:00, 21920.34 examples/s]
Generating train split: 26824911 examples [33:00, 22400.03 examples/s]
Generating train split: 26827509 examples [33:00, 20386.04 examples/s]
Generating train split: 26829818 examples [33:00, 20964.30 examples/s]
Generating train split: 26832784 examples [33:00, 23024.83 examples/s]
Generating train split: 26835340 examples [33:00, 23659.58 examples/s]
Generating train split: 26840567 examples [33:00, 31280.72 examples/s]
Generating train split: 26843894 examples [33:00, 29890.11 examples/s]
Generating train split: 26847242 examples [33:01, 30850.91 examples/s]
Generating train split: 26850455 examples [33:01, 21457.18 examples/s]
Generating train split: 26853070 examples [33:01, 21331.73 examples/s]
Generating train split: 26855531 examples [33:01, 21305.06 examples/s]
Generating train split: 26857982 examples [33:01, 20808.81 examples/s]
Generating train split: 26860225 examples [33:01, 18137.14 examples/s]
Generating train split: 26862431 examples [33:01, 19025.48 examples/s]
Generating train split: 26865275 examples [33:02, 21327.08 examples/s]
Generating train split: 26867913 examples [33:02, 22630.83 examples/s]
Generating train split: 26870302 examples [33:02, 18112.49 examples/s]
Generating train split: 26872337 examples [33:02, 18153.28 examples/s]
Generating train split: 26874405 examples [33:02, 18737.81 examples/s]
Generating train split: 26876806 examples [33:02, 20101.76 examples/s]
Generating train split: 26879328 examples [33:02, 21442.01 examples/s]
Generating train split: 26881571 examples [33:03, 16958.96 examples/s]
Generating train split: 26883586 examples [33:03, 17619.28 examples/s]
Generating train split: 26885507 examples [33:03, 16296.78 examples/s]
Generating train split: 26887767 examples [33:03, 17819.93 examples/s]
Generating train split: 26889669 examples [33:03, 12339.66 examples/s]
Generating train split: 26891204 examples [33:03, 12607.99 examples/s]
Generating train split: 26892692 examples [33:03, 12733.90 examples/s]
Generating train split: 26894211 examples [33:03, 13256.03 examples/s]
Generating train split: 26895673 examples [33:04, 10096.30 examples/s]
Generating train split: 26896874 examples [33:04, 10032.89 examples/s]
Generating train split: 26898416 examples [33:04, 11222.10 examples/s]
Generating train split: 26899679 examples [33:04, 7543.63 examples/s] 
Generating train split: 26900682 examples [33:04, 7943.42 examples/s]
Generating train split: 26904126 examples [33:04, 13397.95 examples/s]
Generating train split: 26905849 examples [33:05, 9462.93 examples/s] 
Generating train split: 26907214 examples [33:05, 7894.80 examples/s]
Generating train split: 26908327 examples [33:05, 6389.34 examples/s]
Generating train split: 26910421 examples [33:05, 8571.80 examples/s]
Generating train split: 26911671 examples [33:06, 8840.49 examples/s]
Generating train split: 26912838 examples [33:06, 6700.81 examples/s]
Generating train split: 26914080 examples [33:06, 7644.69 examples/s]
Generating train split: 26916933 examples [33:06, 11605.42 examples/s]
Generating train split: 26919690 examples [33:06, 15001.63 examples/s]
Generating train split: 26922208 examples [33:06, 17250.93 examples/s]
Generating train split: 26924904 examples [33:06, 19664.67 examples/s]
Generating train split: 26927181 examples [33:06, 20160.23 examples/s]
Generating train split: 26929407 examples [33:07, 19551.86 examples/s]
Generating train split: 26931511 examples [33:07, 18775.46 examples/s]
Generating train split: 26933496 examples [33:07, 18189.35 examples/s]
Generating train split: 26935723 examples [33:07, 19257.58 examples/s]
Generating train split: 26937717 examples [33:07, 17798.20 examples/s]
Generating train split: 26940252 examples [33:07, 19775.36 examples/s]
Generating train split: 26942301 examples [33:07, 17432.82 examples/s]
Generating train split: 26944137 examples [33:08, 13198.64 examples/s]
Generating train split: 26945662 examples [33:08, 12242.29 examples/s]
Generating train split: 26948319 examples [33:08, 15320.29 examples/s]
Generating train split: 26950072 examples [33:08, 13780.76 examples/s]
Generating train split: 26953485 examples [33:08, 18373.76 examples/s]
Generating train split: 26956599 examples [33:08, 21485.19 examples/s]
Generating train split: 26959320 examples [33:08, 22964.69 examples/s]
Generating train split: 26961822 examples [33:09, 17407.86 examples/s]
Generating train split: 26963903 examples [33:09, 15542.07 examples/s]
Generating train split: 26966503 examples [33:09, 17703.05 examples/s]
Generating train split: 26969028 examples [33:09, 19395.23 examples/s]
Generating train split: 26971208 examples [33:09, 12509.05 examples/s]
Generating train split: 26973550 examples [33:09, 14494.71 examples/s]
Generating train split: 26975920 examples [33:09, 16382.72 examples/s]
Generating train split: 26977961 examples [33:10, 15505.64 examples/s]
Generating train split: 26986600 examples [33:10, 31497.96 examples/s]
Generating train split: 26995276 examples [33:10, 44957.66 examples/s]
Generating train split: 27000599 examples [33:10, 30237.31 examples/s]
Generating train split: 27009586 examples [33:10, 41655.96 examples/s]
Generating train split: 27017493 examples [33:10, 48663.84 examples/s]
Generating train split: 27023615 examples [33:11, 32085.76 examples/s]
Generating train split: 27028409 examples [33:11, 26437.20 examples/s]
Generating train split: 27032271 examples [33:11, 19297.79 examples/s]
Generating train split: 27035312 examples [33:11, 20749.65 examples/s]
Generating train split: 27038321 examples [33:12, 20366.23 examples/s]
Generating train split: 27041009 examples [33:12, 18636.79 examples/s]
Generating train split: 27043310 examples [33:12, 17970.31 examples/s]
Generating train split: 27045411 examples [33:12, 16817.64 examples/s]
Generating train split: 27047838 examples [33:12, 18275.31 examples/s]
Generating train split: 27049872 examples [33:12, 14887.14 examples/s]
Generating train split: 27051587 examples [33:13, 13198.37 examples/s]
Generating train split: 27055234 examples [33:13, 17770.60 examples/s]
Generating train split: 27057369 examples [33:13, 12296.92 examples/s]
Generating train split: 27060173 examples [33:13, 14883.38 examples/s]
Generating train split: 27062859 examples [33:13, 17178.68 examples/s]
Generating train split: 27065150 examples [33:13, 18400.56 examples/s]
Generating train split: 27067366 examples [33:14, 16526.83 examples/s]
Generating train split: 27069304 examples [33:14, 11189.99 examples/s]
Generating train split: 27070837 examples [33:14, 11893.60 examples/s]
Generating train split: 27077432 examples [33:14, 22604.35 examples/s]
Generating train split: 27085032 examples [33:14, 34379.69 examples/s]
Generating train split: 27089443 examples [33:15, 21270.53 examples/s]
Generating train split: 27092860 examples [33:15, 16464.72 examples/s]
Generating train split: 27095541 examples [33:15, 10646.94 examples/s]
Generating train split: 27097556 examples [33:16, 8387.35 examples/s] 
Generating train split: 27099100 examples [33:16, 8578.53 examples/s]
Generating train split: 27100767 examples [33:16, 9535.77 examples/s]
Generating train split: 27102228 examples [33:16, 9252.07 examples/s]
Generating train split: 27103504 examples [33:17, 8932.31 examples/s]
Generating train split: 27105128 examples [33:17, 10171.37 examples/s]
Generating train split: 27107819 examples [33:17, 13430.67 examples/s]
Generating train split: 27110130 examples [33:17, 15535.35 examples/s]
Generating train split: 27112119 examples [33:17, 16565.49 examples/s]
Generating train split: 27114035 examples [33:17, 16420.71 examples/s]
Generating train split: 27115862 examples [33:17, 15743.13 examples/s]
Generating train split: 27118546 examples [33:17, 18558.53 examples/s]
Generating train split: 27123142 examples [33:17, 25853.29 examples/s]
Generating train split: 27125930 examples [33:18, 25610.10 examples/s]
Generating train split: 27128631 examples [33:18, 18338.53 examples/s]
Generating train split: 27132606 examples [33:18, 22951.40 examples/s]
Generating train split: 27135680 examples [33:18, 24608.28 examples/s]
Generating train split: 27138483 examples [33:18, 20909.77 examples/s]
Generating train split: 27140903 examples [33:18, 16531.90 examples/s]
Generating train split: 27142910 examples [33:19, 14060.25 examples/s]
Generating train split: 27144591 examples [33:19, 12734.92 examples/s]
Generating train split: 27146659 examples [33:19, 14160.04 examples/s]
Generating train split: 27148552 examples [33:19, 15167.55 examples/s]
Generating train split: 27150258 examples [33:19, 12119.68 examples/s]
Generating train split: 27151689 examples [33:19, 11704.57 examples/s]
Generating train split: 27153005 examples [33:20, 9288.85 examples/s] 
Generating train split: 27161352 examples [33:20, 23490.72 examples/s]
Generating train split: 27168346 examples [33:20, 33463.24 examples/s]
Generating train split: 27172726 examples [33:20, 30629.80 examples/s]
Generating train split: 27176564 examples [33:20, 20364.78 examples/s]
Generating train split: 27179560 examples [33:20, 20767.35 examples/s]
Generating train split: 27182326 examples [33:21, 15148.01 examples/s]
Generating train split: 27184501 examples [33:21, 15153.53 examples/s]
Generating train split: 27186484 examples [33:21, 15700.61 examples/s]
Generating train split: 27188417 examples [33:21, 14725.42 examples/s]
Generating train split: 27190823 examples [33:21, 16575.90 examples/s]
Generating train split: 27199903 examples [33:21, 32959.26 examples/s]
Generating train split: 27209333 examples [33:22, 47661.62 examples/s]
Generating train split: 27215008 examples [33:22, 44013.45 examples/s]
Generating train split: 27220105 examples [33:22, 34643.37 examples/s]
Generating train split: 27224325 examples [33:22, 27775.01 examples/s]
Generating train split: 27228029 examples [33:22, 29486.65 examples/s]
Generating train split: 27234667 examples [33:22, 37221.73 examples/s]
Generating train split: 27243317 examples [33:22, 48569.96 examples/s]
Generating train split: 27249259 examples [33:23, 51249.13 examples/s]
Generating train split: 27255057 examples [33:23, 45897.45 examples/s]
Generating train split: 27261778 examples [33:23, 50185.09 examples/s]
Generating train split: 27267261 examples [33:23, 36312.13 examples/s]
Generating train split: 27271733 examples [33:23, 34426.00 examples/s]
Generating train split: 27278343 examples [33:23, 41059.25 examples/s]
Generating train split: 27285560 examples [33:23, 48212.45 examples/s]
Generating train split: 27291337 examples [33:24, 50559.32 examples/s]
Generating train split: 27296941 examples [33:24, 36714.16 examples/s]
Generating train split: 27301509 examples [33:24, 31188.91 examples/s]
Generating train split: 27305357 examples [33:24, 31653.78 examples/s]
Generating train split: 27309210 examples [33:24, 33107.98 examples/s]
Generating train split: 27312947 examples [33:25, 21192.80 examples/s]
Generating train split: 27316109 examples [33:25, 22959.23 examples/s]
Generating train split: 27319100 examples [33:25, 23067.18 examples/s]
Generating train split: 27321902 examples [33:25, 16476.64 examples/s]
Generating train split: 27324126 examples [33:25, 17273.90 examples/s]
Generating train split: 27326673 examples [33:25, 18822.18 examples/s]
Generating train split: 27328966 examples [33:26, 11964.24 examples/s]
Generating train split: 27331810 examples [33:26, 14535.44 examples/s]
Generating train split: 27334252 examples [33:26, 16332.68 examples/s]
Generating train split: 27336441 examples [33:26, 11688.37 examples/s]
Generating train split: 27340608 examples [33:26, 16651.45 examples/s]
Generating train split: 27345517 examples [33:26, 22847.14 examples/s]
Generating train split: 27348715 examples [33:27, 16797.37 examples/s]
Generating train split: 27351254 examples [33:27, 17699.37 examples/s]
Generating train split: 27354877 examples [33:27, 21245.41 examples/s]
Generating train split: 27357652 examples [33:27, 18887.44 examples/s]
Generating train split: 27360037 examples [33:27, 15635.78 examples/s]
Generating train split: 27362101 examples [33:28, 16566.42 examples/s]
Generating train split: 27364732 examples [33:28, 18538.19 examples/s]
Generating train split: 27366911 examples [33:28, 12678.38 examples/s]
Generating train split: 27368987 examples [33:28, 14067.98 examples/s]
Generating train split: 27370817 examples [33:28, 14308.28 examples/s]
Generating train split: 27372549 examples [33:28, 13985.23 examples/s]
Generating train split: 27374154 examples [33:29, 8278.44 examples/s] 
Generating train split: 27375391 examples [33:29, 7602.30 examples/s]
Generating train split: 27376430 examples [33:29, 6812.75 examples/s]
Generating train split: 27377637 examples [33:29, 7613.18 examples/s]
Generating train split: 27378606 examples [33:29, 7883.43 examples/s]
Generating train split: 27379551 examples [33:30, 7439.27 examples/s]
Generating train split: 27380672 examples [33:30, 8237.95 examples/s]
Generating train split: 27381945 examples [33:30, 9222.90 examples/s]
Generating train split: 27382971 examples [33:30, 8514.84 examples/s]
Generating train split: 27385900 examples [33:30, 13527.96 examples/s]
Generating train split: 27392962 examples [33:30, 28159.49 examples/s]
Generating train split: 27396597 examples [33:30, 30047.35 examples/s]
Generating train split: 27399888 examples [33:30, 24289.37 examples/s]
Generating train split: 27402688 examples [33:31, 23807.12 examples/s]
Generating train split: 27405604 examples [33:31, 25098.02 examples/s]
Generating train split: 27409315 examples [33:31, 28167.87 examples/s]
Generating train split: 27415811 examples [33:31, 38035.49 examples/s]
Generating train split: 27424610 examples [33:31, 51811.08 examples/s]
Generating train split: 27430082 examples [33:31, 35803.96 examples/s]
Generating train split: 27434528 examples [33:31, 35846.83 examples/s]
Generating train split: 27440199 examples [33:31, 40564.72 examples/s]
Generating train split: 27448339 examples [33:31, 50555.54 examples/s]
Generating train split: 27456275 examples [33:32, 57297.29 examples/s]
Generating train split: 27462527 examples [33:32, 37293.60 examples/s]
Generating train split: 27467500 examples [33:32, 34080.69 examples/s]
Generating train split: 27471788 examples [33:32, 34682.05 examples/s]
Generating train split: 27475902 examples [33:32, 34997.99 examples/s]
Generating train split: 27479863 examples [33:33, 27912.43 examples/s]
Generating train split: 27483157 examples [33:33, 23947.94 examples/s]
Generating train split: 27485948 examples [33:33, 21297.80 examples/s]
Generating train split: 27488368 examples [33:33, 15918.41 examples/s]
Generating train split: 27491284 examples [33:33, 18105.74 examples/s]
Generating train split: 27494728 examples [33:33, 21224.40 examples/s]
Generating train split: 27498639 examples [33:34, 25058.86 examples/s]
Generating train split: 27501630 examples [33:34, 18320.20 examples/s]
Generating train split: 27504937 examples [33:34, 21117.28 examples/s]
Generating train split: 27508607 examples [33:34, 24430.74 examples/s]
Generating train split: 27511580 examples [33:34, 19855.14 examples/s]
Generating train split: 27514056 examples [33:35, 15734.32 examples/s]
Generating train split: 27516545 examples [33:35, 17362.93 examples/s]
Generating train split: 27518702 examples [33:35, 18097.12 examples/s]
Generating train split: 27520837 examples [33:35, 13620.08 examples/s]
Generating train split: 27522577 examples [33:35, 13061.31 examples/s]
Generating train split: 27524480 examples [33:35, 14238.16 examples/s]
Generating train split: 27526148 examples [33:35, 13467.13 examples/s]
Generating train split: 27527669 examples [33:36, 10040.00 examples/s]
Generating train split: 27529684 examples [33:36, 11916.13 examples/s]
Generating train split: 27531798 examples [33:36, 13749.60 examples/s]
Generating train split: 27533436 examples [33:36, 13825.87 examples/s]
Generating train split: 27535214 examples [33:36, 14752.04 examples/s]
Generating train split: 27536839 examples [33:36, 12281.02 examples/s]
Generating train split: 27538236 examples [33:36, 12542.90 examples/s]
Generating train split: 27543895 examples [33:36, 23294.46 examples/s]
Generating train split: 27551837 examples [33:37, 37742.82 examples/s]
Generating train split: 27556066 examples [33:37, 23347.27 examples/s]
Generating train split: 27559393 examples [33:37, 22484.99 examples/s]
Generating train split: 27562332 examples [33:37, 18466.54 examples/s]
Generating train split: 27564742 examples [33:38, 13698.56 examples/s]
Generating train split: 27566644 examples [33:38, 11251.04 examples/s]
Generating train split: 27568181 examples [33:38, 10947.99 examples/s]
Generating train split: 27573633 examples [33:38, 17864.63 examples/s]
Generating train split: 27579616 examples [33:38, 25621.33 examples/s]
Generating train split: 27583228 examples [33:39, 21180.53 examples/s]
Generating train split: 27586191 examples [33:39, 21063.97 examples/s]
Generating train split: 27589725 examples [33:39, 23860.38 examples/s]
Generating train split: 27593528 examples [33:39, 26901.55 examples/s]
Generating train split: 27599300 examples [33:39, 34233.52 examples/s]
Generating train split: 27607753 examples [33:39, 46993.67 examples/s]
Generating train split: 27614157 examples [33:39, 51513.73 examples/s]
Generating train split: 27619801 examples [33:40, 31363.29 examples/s]
Generating train split: 27624233 examples [33:40, 32074.32 examples/s]
Generating train split: 27631069 examples [33:40, 39468.30 examples/s]
Generating train split: 27637558 examples [33:40, 44591.08 examples/s]
Generating train split: 27642858 examples [33:40, 31329.21 examples/s]
Generating train split: 27647090 examples [33:40, 27273.27 examples/s]
Generating train split: 27651308 examples [33:41, 29953.34 examples/s]
Generating train split: 27655054 examples [33:41, 21206.69 examples/s]
Generating train split: 27662936 examples [33:41, 30672.95 examples/s]
Generating train split: 27671586 examples [33:41, 41285.66 examples/s]
Generating train split: 27677290 examples [33:41, 26014.38 examples/s]
Generating train split: 27681673 examples [33:42, 23594.46 examples/s]
Generating train split: 27685288 examples [33:42, 19558.06 examples/s]
Generating train split: 27688176 examples [33:42, 19665.25 examples/s]
Generating train split: 27690814 examples [33:42, 20458.61 examples/s]
Generating train split: 27694127 examples [33:42, 22788.88 examples/s]
Generating train split: 27696919 examples [33:43, 15030.20 examples/s]
Generating train split: 27699096 examples [33:43, 14818.22 examples/s]
Generating train split: 27701041 examples [33:43, 12732.74 examples/s]
Generating train split: 27702655 examples [33:43, 12073.74 examples/s]
Generating train split: 27704564 examples [33:43, 13321.53 examples/s]
Generating train split: 27706139 examples [33:44, 13315.34 examples/s]
Generating train split: 27707648 examples [33:44, 12970.45 examples/s]
Generating train split: 27709059 examples [33:44, 12063.02 examples/s]
Generating train split: 27710902 examples [33:44, 13452.05 examples/s]
Generating train split: 27712347 examples [33:44, 9873.01 examples/s] 
Generating train split: 27713524 examples [33:44, 10063.97 examples/s]
Generating train split: 27715230 examples [33:44, 11567.59 examples/s]
Generating train split: 27716539 examples [33:44, 11742.06 examples/s]
Generating train split: 27718528 examples [33:45, 13719.51 examples/s]
Generating train split: 27720020 examples [33:45, 9597.11 examples/s] 
Generating train split: 27721224 examples [33:45, 9725.95 examples/s]
Generating train split: 27723266 examples [33:45, 12072.59 examples/s]
Generating train split: 27724811 examples [33:45, 12866.91 examples/s]
Generating train split: 27727672 examples [33:45, 16839.44 examples/s]
Generating train split: 27734055 examples [33:45, 29335.64 examples/s]
Generating train split: 27741353 examples [33:45, 41317.84 examples/s]
Generating train split: 27745802 examples [33:46, 42189.81 examples/s]
Generating train split: 27750250 examples [33:46, 33850.91 examples/s]
Generating train split: 27754050 examples [33:46, 27277.48 examples/s]
Generating train split: 27761555 examples [33:46, 37528.31 examples/s]
Generating train split: 27770250 examples [33:46, 49117.57 examples/s]
Generating train split: 27775998 examples [33:46, 38951.78 examples/s]
Generating train split: 27780788 examples [33:47, 26270.40 examples/s]
Generating train split: 27784546 examples [33:47, 23213.46 examples/s]
Generating train split: 27787675 examples [33:47, 22894.03 examples/s]
Generating train split: 27790523 examples [33:47, 22715.81 examples/s]
Generating train split: 27793186 examples [33:48, 17771.19 examples/s]
Generating train split: 27795346 examples [33:48, 14751.97 examples/s]
Generating train split: 27797428 examples [33:48, 15757.43 examples/s]
Generating train split: 27799301 examples [33:48, 14207.30 examples/s]
Generating train split: 27802776 examples [33:48, 18156.68 examples/s]
Generating train split: 27805561 examples [33:48, 20243.23 examples/s]
Generating train split: 27808298 examples [33:48, 21172.09 examples/s]
Generating train split: 27812439 examples [33:48, 24778.36 examples/s]
Generating train split: 27815116 examples [33:49, 24116.09 examples/s]
Generating train split: 27817667 examples [33:49, 22052.25 examples/s]
Generating train split: 27821583 examples [33:49, 26226.33 examples/s]
Generating train split: 27827000 examples [33:49, 31538.25 examples/s]
Generating train split: 27833095 examples [33:49, 39153.82 examples/s]
Generating train split: 27837720 examples [33:49, 40645.21 examples/s]
Generating train split: 27843644 examples [33:49, 45773.05 examples/s]
Generating train split: 27848375 examples [33:50, 31107.88 examples/s]
Generating train split: 27852220 examples [33:50, 31730.71 examples/s]
Generating train split: 27855915 examples [33:50, 32555.39 examples/s]
Generating train split: 27861600 examples [33:50, 38488.40 examples/s]
Generating train split: 27867188 examples [33:50, 42287.59 examples/s]
Generating train split: 27871744 examples [33:50, 37644.81 examples/s]
Generating train split: 27875815 examples [33:50, 38136.18 examples/s]
Generating train split: 27881334 examples [33:50, 42582.64 examples/s]
Generating train split: 27885820 examples [33:50, 40980.54 examples/s]
Generating train split: 27892204 examples [33:51, 47121.26 examples/s]
Generating train split: 27897102 examples [33:51, 46332.17 examples/s]
Generating train split: 27902092 examples [33:51, 47311.73 examples/s]
Generating train split: 27906920 examples [33:51, 43131.66 examples/s]
Generating train split: 27911368 examples [33:51, 39880.42 examples/s]
Generating train split: 27915482 examples [33:51, 38938.34 examples/s]
Generating train split: 27919468 examples [33:51, 36513.51 examples/s]
Generating train split: 27925326 examples [33:51, 41991.11 examples/s]
Generating train split: 27930834 examples [33:51, 45523.70 examples/s]
Generating train split: 27936275 examples [33:52, 47987.09 examples/s]
Generating train split: 27941186 examples [33:52, 38862.07 examples/s]
Generating train split: 27947127 examples [33:52, 43913.28 examples/s]
Generating train split: 27952511 examples [33:52, 46493.91 examples/s]
Generating train split: 27960318 examples [33:52, 55022.99 examples/s]
Generating train split: 27966121 examples [33:52, 42438.20 examples/s]
Generating train split: 27970996 examples [33:52, 42993.59 examples/s]
Generating train split: 27976465 examples [33:52, 45853.42 examples/s]
Generating train split: 27981432 examples [33:53, 46496.07 examples/s]
Generating train split: 27987152 examples [33:53, 49332.90 examples/s]
Generating train split: 27992320 examples [33:53, 40243.91 examples/s]
Generating train split: 27996759 examples [33:53, 39505.17 examples/s]
Generating train split: 28000996 examples [33:53, 36814.00 examples/s]
Generating train split: 28005957 examples [33:53, 39936.17 examples/s]
Generating train split: 28010171 examples [33:53, 39632.02 examples/s]
Generating train split: 28014287 examples [33:53, 39042.91 examples/s]
Generating train split: 28021578 examples [33:54, 48189.22 examples/s]
Generating train split: 28028123 examples [33:54, 52995.03 examples/s]
Generating train split: 28033600 examples [33:54, 41949.28 examples/s]
Generating train split: 28038254 examples [33:54, 42036.39 examples/s]
Generating train split: 28042787 examples [33:54, 39503.94 examples/s]
Generating train split: 28046980 examples [33:54, 38547.78 examples/s]
Generating train split: 28054257 examples [33:54, 47266.03 examples/s]
Generating train split: 28061890 examples [33:54, 52761.21 examples/s]
Generating train split: 28067358 examples [33:55, 47968.79 examples/s]
Generating train split: 28075598 examples [33:55, 56767.70 examples/s]
Generating train split: 28083738 examples [33:55, 62819.60 examples/s]
Generating train split: 28090283 examples [33:55, 50259.62 examples/s]
Generating train split: 28095995 examples [33:55, 51877.55 examples/s]
Generating train split: 28101622 examples [33:55, 45339.64 examples/s]
Generating train split: 28106569 examples [33:56, 32586.32 examples/s]
Generating train split: 28110571 examples [33:56, 30817.03 examples/s]
Generating train split: 28114150 examples [33:56, 17127.07 examples/s]
Generating train split: 28116856 examples [33:57, 9346.70 examples/s] 
Generating train split: 28118852 examples [33:58, 7234.06 examples/s]
Generating train split: 28120349 examples [33:58, 5899.78 examples/s]
Generating train split: 28122020 examples [33:58, 6730.83 examples/s]
Generating train split: 28123860 examples [33:58, 7913.37 examples/s]
Generating train split: 28125301 examples [33:58, 8239.47 examples/s]
Generating train split: 28126610 examples [33:59, 8394.92 examples/s]
Generating train split: 28128633 examples [33:59, 10328.75 examples/s]
Generating train split: 28130132 examples [33:59, 11210.00 examples/s]
Generating train split: 28134274 examples [33:59, 17645.39 examples/s]
Generating train split: 28140730 examples [33:59, 28587.56 examples/s]
Generating train split: 28144487 examples [33:59, 30302.69 examples/s]
Generating train split: 28148015 examples [33:59, 29734.54 examples/s]
Generating train split: 28152061 examples [33:59, 32494.22 examples/s]
Generating train split: 28155595 examples [33:59, 30991.20 examples/s]
Generating train split: 28164667 examples [34:00, 46761.61 examples/s]
Generating train split: 28173698 examples [34:00, 56708.05 examples/s]
Generating train split: 28179625 examples [34:00, 36979.08 examples/s]
Generating train split: 28184376 examples [34:00, 27663.89 examples/s]
Generating train split: 28188191 examples [34:00, 29073.91 examples/s]
Generating train split: 28193254 examples [34:01, 33216.53 examples/s]
Generating train split: 28198988 examples [34:01, 37980.15 examples/s]
Generating train split: 28203509 examples [34:01, 26645.55 examples/s]
Generating train split: 28207112 examples [34:01, 27771.22 examples/s]
Generating train split: 28212007 examples [34:01, 32033.48 examples/s]
Generating train split: 28215962 examples [34:01, 33722.59 examples/s]
Generating train split: 28219879 examples [34:01, 26806.58 examples/s]
Generating train split: 28223149 examples [34:02, 27662.40 examples/s]
Generating train split: 28226798 examples [34:02, 29545.48 examples/s]
Generating train split: 28230123 examples [34:02, 28863.07 examples/s]
Generating train split: 28233382 examples [34:02, 29791.75 examples/s]
Generating train split: 28236558 examples [34:02, 20242.10 examples/s]
Generating train split: 28239108 examples [34:02, 21072.27 examples/s]
Generating train split: 28242114 examples [34:02, 23009.84 examples/s]
Generating train split: 28245648 examples [34:03, 24465.16 examples/s]
Generating train split: 28248357 examples [34:03, 22764.05 examples/s]
Generating train split: 28250825 examples [34:03, 22711.41 examples/s]
Generating train split: 28254326 examples [34:03, 25709.40 examples/s]
Generating train split: 28257051 examples [34:03, 25382.94 examples/s]
Generating train split: 28260177 examples [34:03, 26945.58 examples/s]
Generating train split: 28267122 examples [34:03, 38696.45 examples/s]
Generating train split: 28276214 examples [34:03, 53477.56 examples/s]
Generating train split: 28281770 examples [34:04, 34398.12 examples/s]
Generating train split: 28286223 examples [34:04, 33479.31 examples/s]
Generating train split: 28290267 examples [34:04, 29535.32 examples/s]
Generating train split: 28293760 examples [34:04, 28095.60 examples/s]
Generating train split: 28296935 examples [34:04, 26049.69 examples/s]
Generating train split: 28299790 examples [34:04, 26176.09 examples/s]
Generating train split: 28302587 examples [34:05, 20882.84 examples/s]
Generating train split: 28304926 examples [34:05, 21107.08 examples/s]
Generating train split: 28307220 examples [34:05, 16690.03 examples/s]
Generating train split: 28314957 examples [34:05, 28803.76 examples/s]
Generating train split: 28323786 examples [34:05, 41996.72 examples/s]
Generating train split: 28328991 examples [34:05, 29641.25 examples/s]
Generating train split: 28333143 examples [34:06, 25655.63 examples/s]
Generating train split: 28336878 examples [34:06, 27717.31 examples/s]
Generating train split: 28340414 examples [34:06, 25122.62 examples/s]
Generating train split: 28343478 examples [34:06, 25826.67 examples/s]
Generating train split: 28346476 examples [34:06, 26518.69 examples/s]
Generating train split: 28349442 examples [34:06, 16849.63 examples/s]
Generating train split: 28351764 examples [34:07, 15935.37 examples/s]
Generating train split: 28353797 examples [34:07, 12892.50 examples/s]
Generating train split: 28355452 examples [34:07, 10997.23 examples/s]
Generating train split: 28356855 examples [34:07, 11485.37 examples/s]
Generating train split: 28358493 examples [34:07, 12374.98 examples/s]
Generating train split: 28359943 examples [34:07, 11552.51 examples/s]
Generating train split: 28361266 examples [34:08, 11886.59 examples/s]
Generating train split: 28363187 examples [34:08, 13566.39 examples/s]
Generating train split: 28364671 examples [34:08, 13614.85 examples/s]
Generating train split: 28366126 examples [34:08, 12628.01 examples/s]
Generating train split: 28367460 examples [34:08, 10691.31 examples/s]
Generating train split: 28368623 examples [34:08, 9872.22 examples/s] 
Generating train split: 28369759 examples [34:08, 10209.63 examples/s]
Generating train split: 28371537 examples [34:08, 12075.68 examples/s]
Generating train split: 28372822 examples [34:09, 8988.48 examples/s] 
Generating train split: 28374000 examples [34:09, 9581.30 examples/s]
Generating train split: 28375095 examples [34:09, 9037.91 examples/s]
Generating train split: 28376587 examples [34:09, 10410.78 examples/s]
Generating train split: 28382028 examples [34:09, 21430.37 examples/s]
Generating train split: 28392326 examples [34:09, 42908.32 examples/s]
Generating train split: 28397120 examples [34:09, 41438.37 examples/s]
Generating train split: 28401636 examples [34:09, 39392.64 examples/s]
Generating train split: 28409209 examples [34:10, 48911.30 examples/s]
Generating train split: 28416208 examples [34:10, 54647.22 examples/s]
Generating train split: 28421965 examples [34:10, 24680.64 examples/s]
Generating train split: 28426306 examples [34:11, 18525.84 examples/s]
Generating train split: 28429667 examples [34:11, 13917.05 examples/s]
Generating train split: 28432236 examples [34:11, 14050.04 examples/s]
Generating train split: 28434745 examples [34:11, 15444.36 examples/s]
Generating train split: 28437065 examples [34:12, 13159.36 examples/s]
Generating train split: 28438964 examples [34:12, 12568.75 examples/s]
Generating train split: 28440617 examples [34:12, 10992.03 examples/s]
Generating train split: 28444064 examples [34:12, 14725.94 examples/s]
Generating train split: 28450552 examples [34:12, 24010.12 examples/s]
Generating train split: 28453893 examples [34:13, 18340.96 examples/s]
Generating train split: 28456982 examples [34:13, 20482.18 examples/s]
Generating train split: 28464162 examples [34:13, 30683.88 examples/s]
Generating train split: 28471530 examples [34:13, 40190.87 examples/s]
Generating train split: 28477697 examples [34:13, 44931.03 examples/s]
Generating train split: 28487267 examples [34:13, 57790.60 examples/s]
Generating train split: 28495939 examples [34:13, 65462.16 examples/s]
Generating train split: 28503165 examples [34:14, 38821.01 examples/s]
Generating train split: 28508824 examples [34:14, 35374.51 examples/s]
Generating train split: 28517950 examples [34:14, 45514.52 examples/s]
Generating train split: 28526117 examples [34:14, 52959.34 examples/s]
Generating train split: 28532840 examples [34:14, 47586.47 examples/s]
Generating train split: 28541599 examples [34:14, 56210.42 examples/s]
Generating train split: 28549612 examples [34:14, 61831.18 examples/s]
Generating train split: 28556713 examples [34:15, 33766.14 examples/s]
Generating train split: 28562156 examples [34:15, 35524.27 examples/s]
Generating train split: 28567248 examples [34:15, 29240.32 examples/s]
Generating train split: 28571375 examples [34:15, 25798.48 examples/s]
Generating train split: 28575237 examples [34:16, 27767.62 examples/s]
Generating train split: 28578773 examples [34:16, 20970.23 examples/s]
Generating train split: 28581592 examples [34:16, 21528.21 examples/s]
Generating train split: 28585403 examples [34:16, 24553.52 examples/s]
Generating train split: 28588430 examples [34:16, 24742.54 examples/s]
Generating train split: 28591313 examples [34:17, 16309.02 examples/s]
Generating train split: 28594027 examples [34:17, 18072.13 examples/s]
Generating train split: 28596418 examples [34:17, 12795.27 examples/s]
Generating train split: 28598295 examples [34:17, 12683.19 examples/s]
Generating train split: 28600064 examples [34:17, 13502.93 examples/s]
Generating train split: 28601766 examples [34:18, 9644.01 examples/s] 
Generating train split: 28604699 examples [34:18, 12776.24 examples/s]
Generating train split: 28614745 examples [34:18, 29018.41 examples/s]
Generating train split: 28620807 examples [34:18, 35630.55 examples/s]
Generating train split: 28625632 examples [34:18, 35304.94 examples/s]
Generating train split: 28630042 examples [34:19, 19517.09 examples/s]
Generating train split: 28633400 examples [34:19, 14389.02 examples/s]
Generating train split: 28635977 examples [34:19, 10754.98 examples/s]
Generating train split: 28638067 examples [34:20, 11838.24 examples/s]
Generating train split: 28643142 examples [34:20, 16993.94 examples/s]
Generating train split: 28651398 examples [34:20, 27425.80 examples/s]
Generating train split: 28657045 examples [34:20, 32797.14 examples/s]
Generating train split: 28661915 examples [34:20, 20526.06 examples/s]
Generating train split: 28665743 examples [34:20, 23102.62 examples/s]
Generating train split: 28673210 examples [34:21, 31956.82 examples/s]
Generating train split: 28679418 examples [34:21, 37886.14 examples/s]
Generating train split: 28684686 examples [34:21, 27486.84 examples/s]
Generating train split: 28688863 examples [34:21, 27902.92 examples/s]
Generating train split: 28696598 examples [34:21, 37158.87 examples/s]
Generating train split: 28701588 examples [34:21, 33159.84 examples/s]
Generating train split: 28710947 examples [34:21, 45278.86 examples/s]
Generating train split: 28716729 examples [34:22, 36783.40 examples/s]
Generating train split: 28721514 examples [34:22, 19579.53 examples/s]
Generating train split: 28728482 examples [34:22, 25752.15 examples/s]
Generating train split: 28737233 examples [34:23, 34998.30 examples/s]
Generating train split: 28743077 examples [34:23, 28023.54 examples/s]
Generating train split: 28747706 examples [34:23, 26104.64 examples/s]
Generating train split: 28754490 examples [34:23, 32614.95 examples/s]
Generating train split: 28759241 examples [34:23, 33303.68 examples/s]
Generating train split: 28763643 examples [34:24, 26748.64 examples/s]
Generating train split: 28767225 examples [34:24, 26974.24 examples/s]
Generating train split: 28770567 examples [34:24, 27951.96 examples/s]
Generating train split: 28774314 examples [34:24, 29948.31 examples/s]
Generating train split: 28777740 examples [34:24, 23067.76 examples/s]
Generating train split: 28780564 examples [34:24, 21128.29 examples/s]
Generating train split: 28783038 examples [34:24, 20745.36 examples/s]
Generating train split: 28785359 examples [34:25, 19601.97 examples/s]
Generating train split: 28789749 examples [34:25, 24927.77 examples/s]
Generating train split: 28797163 examples [34:25, 36655.49 examples/s]
Generating train split: 28801344 examples [34:25, 28066.24 examples/s]
Generating train split: 28804806 examples [34:25, 24690.66 examples/s]
Generating train split: 28807776 examples [34:25, 24843.18 examples/s]
Generating train split: 28813177 examples [34:25, 31198.67 examples/s]
Generating train split: 28820385 examples [34:26, 40909.12 examples/s]
Generating train split: 28825074 examples [34:26, 35280.03 examples/s]
Generating train split: 28829144 examples [34:26, 32502.13 examples/s]
Generating train split: 28832792 examples [34:26, 30237.64 examples/s]
Generating train split: 28841118 examples [34:26, 42273.78 examples/s]
Generating train split: 28850854 examples [34:26, 55758.87 examples/s]
Generating train split: 28857138 examples [34:27, 32596.87 examples/s]
Generating train split: 28862020 examples [34:27, 30790.57 examples/s]
Generating train split: 28868291 examples [34:27, 36440.32 examples/s]
Generating train split: 28877644 examples [34:27, 47958.40 examples/s]
Generating train split: 28883826 examples [34:27, 44743.00 examples/s]
Generating train split: 28889293 examples [34:28, 25710.21 examples/s]
Generating train split: 28893462 examples [34:28, 17725.72 examples/s]
Generating train split: 28896638 examples [34:28, 15582.63 examples/s]
Generating train split: 28899166 examples [34:29, 13712.31 examples/s]
Generating train split: 28901203 examples [34:29, 14198.92 examples/s]
Generating train split: 28903147 examples [34:29, 11207.52 examples/s]
Generating train split: 28904689 examples [34:29, 11293.16 examples/s]
Generating train split: 28906459 examples [34:29, 12263.22 examples/s]
Generating train split: 28907989 examples [34:30, 10311.72 examples/s]
Generating train split: 28913468 examples [34:30, 17985.28 examples/s]
Generating train split: 28916125 examples [34:30, 19682.82 examples/s]
Generating train split: 28918695 examples [34:30, 19278.83 examples/s]
Generating train split: 28922073 examples [34:30, 22524.71 examples/s]
Generating train split: 28927633 examples [34:30, 30540.68 examples/s]
Generating train split: 28931873 examples [34:30, 33461.16 examples/s]
Generating train split: 28935919 examples [34:30, 35330.05 examples/s]
Generating train split: 28939736 examples [34:31, 32594.02 examples/s]
Generating train split: 28943238 examples [34:31, 25748.50 examples/s]
Generating train split: 28946533 examples [34:31, 27358.00 examples/s]
Generating train split: 28951254 examples [34:31, 32181.16 examples/s]
Generating train split: 28955061 examples [34:31, 33464.57 examples/s]
Generating train split: 28958671 examples [34:31, 32979.82 examples/s]
Generating train split: 28962143 examples [34:31, 27895.07 examples/s]
Generating train split: 28967201 examples [34:31, 33409.28 examples/s]
Generating train split: 28970848 examples [34:32, 34152.90 examples/s]
Generating train split: 28977405 examples [34:32, 42564.07 examples/s]
Generating train split: 28981977 examples [34:32, 43434.73 examples/s]
Generating train split: 28989644 examples [34:32, 52855.01 examples/s]
Generating train split: 28995114 examples [34:32, 27495.07 examples/s]
Generating train split: 29000725 examples [34:32, 32442.83 examples/s]
Generating train split: 29005343 examples [34:33, 28257.52 examples/s]
Generating train split: 29009418 examples [34:33, 30510.45 examples/s]
Generating train split: 29013827 examples [34:33, 32973.72 examples/s]
Generating train split: 29017812 examples [34:33, 30690.20 examples/s]
Generating train split: 29024820 examples [34:33, 39533.32 examples/s]
Generating train split: 29029424 examples [34:33, 39921.79 examples/s]
Generating train split: 29033879 examples [34:33, 33883.16 examples/s]
Generating train split: 29037717 examples [34:33, 33969.67 examples/s]
Generating train split: 29041433 examples [34:34, 32684.03 examples/s]
Generating train split: 29046602 examples [34:34, 37082.88 examples/s]
Generating train split: 29050552 examples [34:34, 36661.26 examples/s]
Generating train split: 29055687 examples [34:34, 40524.43 examples/s]
Generating train split: 29062856 examples [34:34, 49035.84 examples/s]
Generating train split: 29072369 examples [34:34, 61964.46 examples/s]
Generating train split: 29078795 examples [34:34, 55660.33 examples/s]
Generating train split: 29084632 examples [34:34, 42213.47 examples/s]
Generating train split: 29089495 examples [34:35, 40986.55 examples/s]
Generating train split: 29094031 examples [34:35, 40663.05 examples/s]
Generating train split: 29098633 examples [34:35, 41952.80 examples/s]
Generating train split: 29103074 examples [34:35, 34180.53 examples/s]
Generating train split: 29106881 examples [34:35, 30620.66 examples/s]
Generating train split: 29110233 examples [34:35, 28057.79 examples/s]
Generating train split: 29114421 examples [34:35, 31091.69 examples/s]
Generating train split: 29117788 examples [34:36, 18815.84 examples/s]
Generating train split: 29120407 examples [34:36, 15660.35 examples/s]
Generating train split: 29122539 examples [34:36, 13142.75 examples/s]
Generating train split: 29124736 examples [34:36, 14482.62 examples/s]
Generating train split: 29126799 examples [34:37, 15557.22 examples/s]
Generating train split: 29128853 examples [34:37, 16548.01 examples/s]
Generating train split: 29130811 examples [34:37, 9688.13 examples/s] 
Generating train split: 29132319 examples [34:37, 10079.59 examples/s]
Generating train split: 29134715 examples [34:37, 12481.03 examples/s]
Generating train split: 29137049 examples [34:37, 14614.97 examples/s]
Generating train split: 29139742 examples [34:37, 17138.23 examples/s]
Generating train split: 29143811 examples [34:38, 22726.52 examples/s]
Generating train split: 29146494 examples [34:38, 22823.35 examples/s]
Generating train split: 29149991 examples [34:38, 25946.90 examples/s]
Generating train split: 29155309 examples [34:38, 33268.59 examples/s]
Generating train split: 29159896 examples [34:38, 36109.21 examples/s]
Generating train split: 29163702 examples [34:38, 26462.52 examples/s]
Generating train split: 29166860 examples [34:38, 22391.39 examples/s]
Generating train split: 29169636 examples [34:39, 23476.04 examples/s]
Generating train split: 29174233 examples [34:39, 28588.21 examples/s]
Generating train split: 29177522 examples [34:39, 29630.54 examples/s]
Generating train split: 29181046 examples [34:39, 31076.97 examples/s]
Generating train split: 29184393 examples [34:39, 27096.14 examples/s]
Generating train split: 29188580 examples [34:39, 30756.72 examples/s]
Generating train split: 29196034 examples [34:39, 42204.88 examples/s]
Generating train split: 29203139 examples [34:39, 50034.17 examples/s]
Generating train split: 29208470 examples [34:40, 35061.47 examples/s]
Generating train split: 29212822 examples [34:40, 35302.95 examples/s]
Generating train split: 29222335 examples [34:40, 48919.92 examples/s]
Generating train split: 29230328 examples [34:40, 56509.98 examples/s]
Generating train split: 29236737 examples [34:40, 57117.82 examples/s]
Generating train split: 29246496 examples [34:40, 67871.62 examples/s]
Generating train split: 29253810 examples [34:40, 65688.89 examples/s]
Generating train split: 29260755 examples [34:40, 59848.17 examples/s]
Generating train split: 29269805 examples [34:40, 67745.86 examples/s]
Generating train split: 29276953 examples [34:41, 65223.23 examples/s]
Generating train split: 29285907 examples [34:41, 71711.38 examples/s]
Generating train split: 29294042 examples [34:41, 72811.49 examples/s]
Generating train split: 29301519 examples [34:41, 39761.77 examples/s]
Generating train split: 29307305 examples [34:42, 31589.43 examples/s]
Generating train split: 29311929 examples [34:42, 26105.96 examples/s]
Generating train split: 29315648 examples [34:42, 25710.67 examples/s]
Generating train split: 29318983 examples [34:42, 19122.64 examples/s]
Generating train split: 29321600 examples [34:42, 19510.06 examples/s]
Generating train split: 29324077 examples [34:43, 19031.98 examples/s]
Generating train split: 29327436 examples [34:43, 21418.55 examples/s]
Generating train split: 29329963 examples [34:43, 19857.01 examples/s]
Generating train split: 29332999 examples [34:43, 22013.88 examples/s]
Generating train split: 29335487 examples [34:43, 21557.11 examples/s]
Generating train split: 29338368 examples [34:43, 23238.74 examples/s]
Generating train split: 29340871 examples [34:43, 23660.66 examples/s]
Generating train split: 29344022 examples [34:43, 25705.54 examples/s]
Generating train split: 29346718 examples [34:44, 17678.42 examples/s]
Generating train split: 29349546 examples [34:44, 19900.22 examples/s]
Generating train split: 29353982 examples [34:44, 25539.33 examples/s]
Generating train split: 29359938 examples [34:44, 33881.34 examples/s]
Generating train split: 29363810 examples [34:44, 32958.33 examples/s]
Generating train split: 29367451 examples [34:44, 31154.60 examples/s]
Generating train split: 29370954 examples [34:44, 31838.87 examples/s]
Generating train split: 29374327 examples [34:44, 29973.05 examples/s]
Generating train split: 29377664 examples [34:45, 30846.35 examples/s]
Generating train split: 29384576 examples [34:45, 41178.75 examples/s]
Generating train split: 29392074 examples [34:45, 50564.95 examples/s]
Generating train split: 29397343 examples [34:45, 30268.05 examples/s]
Generating train split: 29401489 examples [34:45, 30596.72 examples/s]
Generating train split: 29405339 examples [34:45, 31713.77 examples/s]
Generating train split: 29409114 examples [34:46, 24023.28 examples/s]
Generating train split: 29412181 examples [34:46, 16762.59 examples/s]
Generating train split: 29414581 examples [34:46, 14757.46 examples/s]
Generating train split: 29416571 examples [34:46, 15510.07 examples/s]
Generating train split: 29418544 examples [34:47, 12030.36 examples/s]
Generating train split: 29420135 examples [34:47, 8721.35 examples/s] 
Generating train split: 29421381 examples [34:47, 8413.50 examples/s]
Generating train split: 29422465 examples [34:47, 7477.91 examples/s]
Generating train split: 29423378 examples [34:48, 7178.37 examples/s]
Generating train split: 29424936 examples [34:48, 8581.78 examples/s]
Generating train split: 29427947 examples [34:48, 12766.40 examples/s]
Generating train split: 29429580 examples [34:48, 10134.05 examples/s]
Generating train split: 29430911 examples [34:48, 9026.39 examples/s] 
Generating train split: 29432470 examples [34:48, 10238.90 examples/s]
Generating train split: 29433731 examples [34:48, 10483.11 examples/s]
Generating train split: 29434957 examples [34:48, 10408.97 examples/s]
Generating train split: 29436123 examples [34:49, 10209.54 examples/s]
Generating train split: 29437237 examples [34:49, 7609.76 examples/s] 
Generating train split: 29438148 examples [34:49, 6909.81 examples/s]
Generating train split: 29439143 examples [34:49, 7470.93 examples/s]
Generating train split: 29439992 examples [34:49, 7176.01 examples/s]
Generating train split: 29440922 examples [34:49, 7657.80 examples/s]
Generating train split: 29442949 examples [34:49, 10666.73 examples/s]
Generating train split: 29444118 examples [34:50, 10811.43 examples/s]
Generating train split: 29446801 examples [34:50, 15082.46 examples/s]
Generating train split: 29448413 examples [34:50, 13662.49 examples/s]
Generating train split: 29449877 examples [34:50, 8155.81 examples/s] 
Generating train split: 29451035 examples [34:50, 8669.40 examples/s]
Generating train split: 29452160 examples [34:51, 5228.35 examples/s]
Generating train split: 29453027 examples [34:51, 5638.69 examples/s]
Generating train split: 29454015 examples [34:51, 6313.42 examples/s]
Generating train split: 29454897 examples [34:51, 5718.39 examples/s]
Generating train split: 29456429 examples [34:51, 7491.18 examples/s]
Generating train split: 29457414 examples [34:51, 6625.42 examples/s]
Generating train split: 29458257 examples [34:52, 5189.29 examples/s]
Generating train split: 29459529 examples [34:52, 6402.96 examples/s]
Generating train split: 29460358 examples [34:52, 6251.18 examples/s]
Generating train split: 29461314 examples [34:52, 6925.38 examples/s]
Generating train split: 29462128 examples [34:52, 6873.00 examples/s]
Generating train split: 29462903 examples [34:52, 6364.79 examples/s]
Generating train split: 29463605 examples [34:53, 6263.50 examples/s]
Generating train split: 29464781 examples [34:53, 7588.89 examples/s]
Generating train split: 29465604 examples [34:53, 6366.45 examples/s]
Generating train split: 29466311 examples [34:53, 3286.73 examples/s]
Generating train split: 29466849 examples [34:54, 1847.21 examples/s]
Generating train split: 29467247 examples [34:54, 1841.31 examples/s]
Generating train split: 29468157 examples [34:54, 2630.71 examples/s]
Generating train split: 29469224 examples [34:54, 3711.69 examples/s]
Generating train split: 29472322 examples [34:55, 8105.34 examples/s]
Generating train split: 29474722 examples [34:55, 11076.80 examples/s]
Generating train split: 29476426 examples [34:55, 8085.94 examples/s] 
Generating train split: 29477768 examples [34:55, 6820.45 examples/s]
Generating train split: 29478848 examples [34:55, 7299.04 examples/s]
Generating train split: 29479898 examples [34:56, 7705.76 examples/s]
Generating train split: 29480913 examples [34:56, 7722.97 examples/s]
Generating train split: 29482108 examples [34:56, 8611.38 examples/s]
Generating train split: 29483128 examples [34:56, 6139.21 examples/s]
Generating train split: 29483944 examples [34:56, 4739.35 examples/s]
Generating train split: 29484786 examples [34:56, 5325.07 examples/s]
Generating train split: 29486079 examples [34:57, 6736.95 examples/s]
Generating train split: 29486960 examples [34:57, 5232.07 examples/s]
Generating train split: 29487672 examples [34:57, 3666.52 examples/s]
Generating train split: 29488228 examples [34:57, 3446.93 examples/s]
Generating train split: 29489958 examples [34:58, 5566.31 examples/s]
Generating train split: 29493795 examples [34:58, 11168.55 examples/s]
Generating train split: 29495504 examples [34:58, 12268.69 examples/s]
Generating train split: 29497129 examples [34:58, 11323.68 examples/s]
Generating train split: 29500120 examples [34:58, 15292.68 examples/s]
Generating train split: 29504700 examples [34:58, 22422.64 examples/s]
Generating train split: 29510591 examples [34:58, 31547.21 examples/s]
Generating train split: 29516959 examples [34:58, 39998.80 examples/s]
Generating train split: 29523427 examples [34:58, 46742.62 examples/s]
Generating train split: 29529995 examples [34:59, 52049.64 examples/s]
Generating train split: 29537251 examples [34:59, 57899.54 examples/s]
Generating train split: 29544477 examples [34:59, 62056.97 examples/s]
Generating train split: 29550870 examples [34:59, 62091.28 examples/s]
Generating train split: 29557561 examples [34:59, 63488.61 examples/s]
Generating train split: 29566058 examples [34:59, 69785.48 examples/s]
Generating train split: 29573113 examples [34:59, 69894.55 examples/s]
Generating train split: 29580922 examples [34:59, 72316.25 examples/s]
Generating train split: 29588197 examples [34:59, 72370.87 examples/s]
Generating train split: 29595470 examples [34:59, 71455.43 examples/s]
Generating train split: 29603570 examples [35:00, 74236.36 examples/s]
Generating train split: 29611028 examples [35:00, 72939.81 examples/s]
Generating train split: 29618340 examples [35:00, 72061.47 examples/s]
Generating train split: 29625576 examples [35:00, 71795.42 examples/s]
Generating train split: 29632766 examples [35:00, 71451.91 examples/s]
Generating train split: 29640243 examples [35:00, 72428.71 examples/s]
Generating train split: 29647505 examples [35:00, 69344.61 examples/s]
Generating train split: 29654472 examples [35:00, 69335.12 examples/s]
Generating train split: 29661436 examples [35:00, 68013.56 examples/s]
Generating train split: 29668256 examples [35:01, 66497.58 examples/s]
Generating train split: 29674926 examples [35:01, 65845.88 examples/s]
Generating train split: 29681524 examples [35:01, 63508.04 examples/s]
Generating train split: 29687893 examples [35:01, 62762.14 examples/s]
Generating train split: 29694187 examples [35:01, 57473.15 examples/s]
Generating train split: 29700015 examples [35:01, 39559.63 examples/s]
Generating train split: 29704752 examples [35:01, 35139.37 examples/s]
Generating train split: 29708845 examples [35:02, 32068.89 examples/s]
Generating train split: 29712463 examples [35:02, 22320.92 examples/s]
Generating train split: 29721107 examples [35:02, 32934.97 examples/s]
Generating train split: 29728799 examples [35:02, 41317.53 examples/s]
Generating train split: 29734317 examples [35:02, 39116.28 examples/s]
Generating train split: 29740221 examples [35:02, 43349.23 examples/s]
Generating train split: 29745417 examples [35:03, 32415.93 examples/s]
Generating train split: 29749631 examples [35:03, 30754.55 examples/s]
Generating train split: 29758527 examples [35:03, 42256.38 examples/s]
Generating train split: 29766971 examples [35:03, 50094.61 examples/s]
Generating train split: 29772918 examples [35:03, 46827.22 examples/s]
Generating train split: 29780573 examples [35:03, 53666.52 examples/s]
Generating train split: 29788456 examples [35:03, 59532.93 examples/s]
Generating train split: 29794999 examples [35:03, 58533.70 examples/s]
Generating train split: 29803481 examples [35:04, 65420.53 examples/s]
Generating train split: 29810407 examples [35:04, 50547.56 examples/s]
Generating train split: 29816225 examples [35:04, 33552.59 examples/s]
Generating train split: 29820803 examples [35:04, 32788.36 examples/s]
Generating train split: 29824977 examples [35:04, 34440.87 examples/s]
Generating train split: 29829113 examples [35:05, 24794.79 examples/s]
Generating train split: 29832400 examples [35:05, 25547.46 examples/s]
Generating train split: 29840252 examples [35:05, 35752.96 examples/s]
Generating train split: 29847708 examples [35:05, 43879.73 examples/s]
Generating train split: 29853093 examples [35:05, 31766.47 examples/s]
Generating train split: 29857414 examples [35:06, 27339.97 examples/s]
Generating train split: 29864494 examples [35:06, 35048.97 examples/s]
Generating train split: 29871638 examples [35:06, 42404.50 examples/s]
Generating train split: 29877026 examples [35:06, 38937.47 examples/s]
Generating train split: 29884057 examples [35:06, 45734.43 examples/s]
Generating train split: 29890989 examples [35:06, 50694.37 examples/s]
Generating train split: 29896761 examples [35:07, 28878.22 examples/s]
Generating train split: 29901215 examples [35:07, 29914.24 examples/s]
Generating train split: 29905344 examples [35:07, 19621.89 examples/s]
Generating train split: 29908525 examples [35:07, 21075.21 examples/s]
Generating train split: 29912130 examples [35:07, 23517.40 examples/s]
Generating train split: 29915390 examples [35:08, 17209.80 examples/s]
Generating train split: 29917957 examples [35:08, 17765.75 examples/s]
Generating train split: 29920478 examples [35:08, 19068.97 examples/s]
Generating train split: 29922912 examples [35:08, 16316.80 examples/s]
Generating train split: 29924954 examples [35:08, 15794.77 examples/s]
Generating train split: 29926840 examples [35:08, 16401.67 examples/s]
Generating train split: 29933255 examples [35:08, 26973.90 examples/s]
Generating train split: 29941771 examples [35:09, 40959.87 examples/s]
Generating train split: 29946593 examples [35:09, 35616.41 examples/s]
Generating train split: 29950782 examples [35:09, 24436.39 examples/s]
Generating train split: 29954098 examples [35:09, 22765.02 examples/s]
Generating train split: 29956974 examples [35:10, 16692.05 examples/s]
Generating train split: 29959260 examples [35:10, 16382.50 examples/s]
Generating train split: 29961310 examples [35:10, 14207.48 examples/s]
Generating train split: 29963038 examples [35:10, 11450.11 examples/s]
Generating train split: 29969351 examples [35:10, 19596.43 examples/s]
Generating train split: 29978572 examples [35:10, 32937.43 examples/s]
Generating train split: 29983348 examples [35:11, 34418.31 examples/s]
Generating train split: 29987867 examples [35:11, 20317.05 examples/s]
Generating train split: 29991321 examples [35:11, 19466.70 examples/s]
Generating train split: 29994262 examples [35:11, 19390.10 examples/s]
Generating train split: 29996935 examples [35:11, 20598.82 examples/s]
Generating train split: 29999563 examples [35:12, 21489.09 examples/s]
Generating train split: 30009309 examples [35:12, 37920.34 examples/s]
Generating train split: 30016448 examples [35:12, 45654.54 examples/s]
Generating train split: 30021886 examples [35:12, 30231.02 examples/s]
Generating train split: 30026545 examples [35:12, 33255.42 examples/s]
Generating train split: 30037828 examples [35:12, 49882.13 examples/s]
Generating train split: 30046147 examples [35:12, 57013.24 examples/s]
Generating train split: 30053072 examples [35:13, 18563.67 examples/s]
Generating train split: 30058134 examples [35:14, 12485.22 examples/s]
Generating train split: 30061857 examples [35:15, 12206.97 examples/s]
Generating train split: 30067577 examples [35:15, 15944.49 examples/s]
Generating train split: 30075918 examples [35:15, 23101.54 examples/s]
Generating train split: 30081224 examples [35:15, 26950.52 examples/s]
Generating train split: 30086384 examples [35:15, 26119.31 examples/s]
Generating train split: 30090716 examples [35:15, 22453.06 examples/s]
Generating train split: 30094215 examples [35:16, 19068.80 examples/s]
Generating train split: 30097035 examples [35:16, 17271.82 examples/s]
Generating train split: 30100867 examples [35:16, 20406.73 examples/s]
Generating train split: 30103674 examples [35:16, 19210.40 examples/s]
Generating train split: 30106122 examples [35:16, 18254.54 examples/s]
Generating train split: 30108744 examples [35:16, 19761.98 examples/s]
Generating train split: 30111696 examples [35:17, 21833.01 examples/s]
Generating train split: 30114200 examples [35:17, 17450.34 examples/s]
Generating train split: 30116283 examples [35:17, 14728.76 examples/s]
Generating train split: 30119386 examples [35:17, 17855.66 examples/s]
Generating train split: 30121831 examples [35:17, 19246.87 examples/s]
Generating train split: 30124077 examples [35:17, 16198.37 examples/s]
Generating train split: 30125987 examples [35:18, 14791.37 examples/s]
Generating train split: 30130027 examples [35:18, 20199.22 examples/s]
Generating train split: 30134256 examples [35:18, 24900.62 examples/s]
Generating train split: 30137108 examples [35:18, 19619.28 examples/s]
Generating train split: 30139481 examples [35:18, 20332.66 examples/s]
Generating train split: 30141900 examples [35:18, 21214.54 examples/s]
Generating train split: 30145201 examples [35:18, 24132.21 examples/s]
Generating train split: 30147849 examples [35:19, 15868.23 examples/s]
Generating train split: 30150051 examples [35:19, 17049.56 examples/s]
Generating train split: 30156647 examples [35:19, 27616.26 examples/s]
Generating train split: 30166087 examples [35:19, 43360.66 examples/s]
Generating train split: 30172207 examples [35:19, 47684.44 examples/s]
Generating train split: 30177717 examples [35:19, 42526.66 examples/s]
Generating train split: 30184819 examples [35:19, 49475.81 examples/s]
Generating train split: 30190358 examples [35:20, 33027.85 examples/s]
Generating train split: 30195010 examples [35:20, 35626.34 examples/s]
Generating train split: 30199493 examples [35:20, 35783.75 examples/s]
Generating train split: 30203731 examples [35:20, 20696.03 examples/s]
Generating train split: 30208518 examples [35:20, 24838.70 examples/s]
Generating train split: 30215334 examples [35:20, 32583.98 examples/s]
Generating train split: 30226015 examples [35:21, 46932.27 examples/s]
Generating train split: 30232240 examples [35:21, 28612.96 examples/s]
Generating train split: 30237011 examples [35:21, 27578.17 examples/s]
Generating train split: 30241095 examples [35:21, 23828.01 examples/s]
Generating train split: 30244435 examples [35:22, 21006.19 examples/s]
Generating train split: 30247215 examples [35:22, 13350.72 examples/s]
Generating train split: 30249326 examples [35:22, 13639.71 examples/s]
Generating train split: 30252181 examples [35:22, 15713.59 examples/s]
Generating train split: 30260637 examples [35:23, 27132.71 examples/s]
Generating train split: 30267649 examples [35:23, 35243.30 examples/s]
Generating train split: 30272580 examples [35:23, 18969.38 examples/s]
Generating train split: 30278741 examples [35:23, 24586.03 examples/s]
Generating train split: 30285218 examples [35:23, 30951.81 examples/s]
Generating train split: 30290281 examples [35:24, 23657.90 examples/s]
Generating train split: 30294278 examples [35:24, 22453.40 examples/s]
Generating train split: 30301229 examples [35:24, 29875.45 examples/s]
Generating train split: 30309466 examples [35:24, 39523.09 examples/s]
Generating train split: 30315042 examples [35:24, 31797.79 examples/s]
Generating train split: 30319572 examples [35:25, 22850.41 examples/s]
Generating train split: 30323293 examples [35:25, 24952.75 examples/s]
Generating train split: 30327836 examples [35:25, 28198.49 examples/s]
Generating train split: 30331637 examples [35:25, 26133.27 examples/s]
Generating train split: 30335044 examples [35:25, 27687.16 examples/s]
Generating train split: 30340073 examples [35:25, 32622.15 examples/s]
Generating train split: 30343912 examples [35:26, 33059.88 examples/s]
Generating train split: 30347633 examples [35:26, 33829.17 examples/s]
Generating train split: 30355593 examples [35:26, 45742.34 examples/s]
Generating train split: 30360562 examples [35:26, 27997.34 examples/s]
Generating train split: 30364466 examples [35:26, 29482.11 examples/s]
Generating train split: 30372457 examples [35:26, 39996.45 examples/s]
Generating train split: 30379411 examples [35:26, 46763.43 examples/s]
Generating train split: 30385032 examples [35:27, 42143.61 examples/s]
Generating train split: 30389979 examples [35:27, 32318.75 examples/s]
Generating train split: 30394032 examples [35:27, 29695.95 examples/s]
Generating train split: 30397576 examples [35:27, 28942.69 examples/s]
Generating train split: 30401786 examples [35:27, 31686.58 examples/s]
Generating train split: 30405342 examples [35:28, 19623.32 examples/s]
Generating train split: 30408108 examples [35:28, 20895.30 examples/s]
Generating train split: 30412400 examples [35:28, 25057.62 examples/s]
Generating train split: 30415619 examples [35:28, 15833.64 examples/s]
Generating train split: 30418968 examples [35:28, 18549.57 examples/s]
Generating train split: 30428242 examples [35:28, 31916.89 examples/s]
Generating train split: 30437697 examples [35:29, 44733.14 examples/s]
Generating train split: 30443824 examples [35:29, 25374.46 examples/s]
Generating train split: 30452444 examples [35:29, 34174.75 examples/s]
Generating train split: 30462246 examples [35:29, 45102.70 examples/s]
Generating train split: 30469281 examples [35:30, 27014.98 examples/s]
Generating train split: 30474607 examples [35:30, 24313.42 examples/s]
Generating train split: 30478881 examples [35:30, 18660.17 examples/s]
Generating train split: 30482167 examples [35:31, 15616.25 examples/s]
Generating train split: 30484747 examples [35:31, 15475.15 examples/s]
Generating train split: 30487002 examples [35:31, 15542.95 examples/s]
Generating train split: 30489057 examples [35:31, 14943.20 examples/s]
Generating train split: 30490878 examples [35:31, 14332.36 examples/s]
Generating train split: 30492520 examples [35:32, 13775.63 examples/s]
Generating train split: 30494620 examples [35:32, 14708.88 examples/s]
Generating train split: 30496223 examples [35:32, 12953.71 examples/s]
Generating train split: 30498936 examples [35:32, 15816.50 examples/s]
Generating train split: 30500719 examples [35:32, 15475.43 examples/s]
Generating train split: 30503540 examples [35:32, 18463.83 examples/s]
Generating train split: 30505573 examples [35:33, 12346.53 examples/s]
Generating train split: 30507183 examples [35:33, 12463.97 examples/s]
Generating train split: 30509250 examples [35:33, 14038.51 examples/s]
Generating train split: 30510914 examples [35:33, 11160.54 examples/s]
Generating train split: 30512376 examples [35:33, 11746.09 examples/s]
Generating train split: 30513769 examples [35:33, 10269.35 examples/s]
Generating train split: 30514962 examples [35:33, 9775.78 examples/s] 
Generating train split: 30517478 examples [35:34, 12911.26 examples/s]
Generating train split: 30519537 examples [35:34, 14553.76 examples/s]
Generating train split: 30521644 examples [35:34, 16149.93 examples/s]
Generating train split: 30523650 examples [35:34, 17164.30 examples/s]
Generating train split: 30525488 examples [35:34, 16396.76 examples/s]
Generating train split: 30527579 examples [35:34, 17573.09 examples/s]
Generating train split: 30529422 examples [35:34, 14814.95 examples/s]
Generating train split: 30531111 examples [35:34, 15308.97 examples/s]
Generating train split: 30533316 examples [35:34, 17038.21 examples/s]
Generating train split: 30535129 examples [35:35, 9289.79 examples/s] 
Generating train split: 30537209 examples [35:35, 11247.33 examples/s]
Generating train split: 30538801 examples [35:35, 10704.16 examples/s]
Generating train split: 30546940 examples [35:35, 24713.54 examples/s]
Generating train split: 30552739 examples [35:35, 31595.00 examples/s]
Generating train split: 30556766 examples [35:36, 24154.92 examples/s]
Generating train split: 30560951 examples [35:36, 27608.92 examples/s]
Generating train split: 30568851 examples [35:36, 38818.39 examples/s]
Generating train split: 30576432 examples [35:36, 47592.92 examples/s]
Generating train split: 30582109 examples [35:36, 23885.44 examples/s]
Generating train split: 30586407 examples [35:37, 17459.35 examples/s]
Generating train split: 30589695 examples [35:37, 13763.64 examples/s]
Generating train split: 30592230 examples [35:37, 14847.40 examples/s]
Generating train split: 30594687 examples [35:38, 12042.54 examples/s]
Generating train split: 30596614 examples [35:38, 11034.27 examples/s]
Generating train split: 30598305 examples [35:38, 11741.52 examples/s]
Generating train split: 30599908 examples [35:38, 9001.17 examples/s] 
Generating train split: 30601738 examples [35:39, 10296.51 examples/s]
Generating train split: 30603174 examples [35:39, 8385.80 examples/s] 
Generating train split: 30604327 examples [35:39, 8491.43 examples/s]
Generating train split: 30605403 examples [35:39, 7039.77 examples/s]
Generating train split: 30606291 examples [35:39, 7035.42 examples/s]
Generating train split: 30608441 examples [35:39, 9694.89 examples/s]
Generating train split: 30609672 examples [35:40, 10192.33 examples/s]
Generating train split: 30610891 examples [35:40, 4891.86 examples/s] 
Generating train split: 30611806 examples [35:40, 4474.05 examples/s]
Generating train split: 30612712 examples [35:41, 5062.79 examples/s]
Generating train split: 30614137 examples [35:41, 6521.19 examples/s]
Generating train split: 30617240 examples [35:41, 11019.36 examples/s]
Generating train split: 30620751 examples [35:41, 15889.61 examples/s]
Generating train split: 30623214 examples [35:41, 17815.31 examples/s]
Generating train split: 30625431 examples [35:41, 16228.19 examples/s]
Generating train split: 30627382 examples [35:41, 14195.90 examples/s]
Generating train split: 30629080 examples [35:41, 14782.29 examples/s]
Generating train split: 30630764 examples [35:42, 15253.73 examples/s]
Generating train split: 30632447 examples [35:42, 11720.89 examples/s]
Generating train split: 30633846 examples [35:42, 10572.05 examples/s]
Generating train split: 30636553 examples [35:42, 14003.59 examples/s]
Generating train split: 30638221 examples [35:42, 12650.26 examples/s]
Generating train split: 30641088 examples [35:42, 16144.18 examples/s]
Generating train split: 30642965 examples [35:42, 13602.58 examples/s]
Generating train split: 30644563 examples [35:43, 13816.59 examples/s]
Generating train split: 30646126 examples [35:43, 13876.29 examples/s]
Generating train split: 30652869 examples [35:43, 26983.08 examples/s]
Generating train split: 30660204 examples [35:43, 38983.24 examples/s]
Generating train split: 30666064 examples [35:43, 44276.62 examples/s]
Generating train split: 30670870 examples [35:43, 25653.80 examples/s]
Generating train split: 30678923 examples [35:43, 35728.42 examples/s]
Generating train split: 30685817 examples [35:44, 41519.30 examples/s]
Generating train split: 30691182 examples [35:44, 26864.84 examples/s]
Generating train split: 30695361 examples [35:44, 18527.20 examples/s]
Generating train split: 30698560 examples [35:45, 18868.33 examples/s]
Generating train split: 30705869 examples [35:45, 26773.01 examples/s]
Generating train split: 30715123 examples [35:45, 37853.44 examples/s]
Generating train split: 30720731 examples [35:45, 32326.73 examples/s]
Generating train split: 30729205 examples [35:45, 41741.91 examples/s]
Generating train split: 30735089 examples [35:45, 45233.25 examples/s]
Generating train split: 30740897 examples [35:46, 34552.42 examples/s]
Generating train split: 30745597 examples [35:46, 35455.31 examples/s]
Generating train split: 30750047 examples [35:46, 25899.05 examples/s]
Generating train split: 30754220 examples [35:46, 28574.06 examples/s]
Generating train split: 30761876 examples [35:46, 37898.73 examples/s]
Generating train split: 30770273 examples [35:46, 47663.77 examples/s]
Generating train split: 30776170 examples [35:47, 26973.68 examples/s]
Generating train split: 30780679 examples [35:47, 26504.20 examples/s]
Generating train split: 30788590 examples [35:47, 35077.81 examples/s]
Generating train split: 30795482 examples [35:47, 41467.49 examples/s]
Generating train split: 30801122 examples [35:47, 33286.82 examples/s]
Generating train split: 30805728 examples [35:48, 31012.89 examples/s]
Generating train split: 30809714 examples [35:48, 28996.77 examples/s]
Generating train split: 30813216 examples [35:48, 22088.63 examples/s]
Generating train split: 30816029 examples [35:48, 21715.35 examples/s]
Generating train split: 30824235 examples [35:48, 32760.58 examples/s]
Generating train split: 30832864 examples [35:48, 43856.46 examples/s]
Generating train split: 30838450 examples [35:49, 23454.31 examples/s]
Generating train split: 30842681 examples [35:49, 20575.70 examples/s]
Generating train split: 30846081 examples [35:49, 18603.07 examples/s]
Generating train split: 30848865 examples [35:50, 18314.48 examples/s]
Generating train split: 30851340 examples [35:50, 13760.94 examples/s]
Generating train split: 30853281 examples [35:50, 14516.48 examples/s]
Generating train split: 30855217 examples [35:50, 14982.66 examples/s]
Generating train split: 30857091 examples [35:50, 14881.78 examples/s]
Generating train split: 30862911 examples [35:50, 23587.06 examples/s]
Generating train split: 30871415 examples [35:50, 37288.80 examples/s]
Generating train split: 30876045 examples [35:51, 34019.97 examples/s]
Generating train split: 30880117 examples [35:51, 23667.30 examples/s]
Generating train split: 30883358 examples [35:51, 20969.94 examples/s]
Generating train split: 30886083 examples [35:51, 17689.04 examples/s]
Generating train split: 30888329 examples [35:52, 13749.98 examples/s]
Generating train split: 30890133 examples [35:52, 14269.57 examples/s]
Generating train split: 30891899 examples [35:52, 14321.94 examples/s]
Generating train split: 30893572 examples [35:52, 14729.23 examples/s]
Generating train split: 30895414 examples [35:52, 15510.46 examples/s]
Generating train split: 30897788 examples [35:52, 17446.93 examples/s]
Generating train split: 30899710 examples [35:52, 16199.33 examples/s]
Generating train split: 30901760 examples [35:52, 17248.47 examples/s]
Generating train split: 30904105 examples [35:53, 18649.37 examples/s]
Generating train split: 30909253 examples [35:53, 27460.68 examples/s]
Generating train split: 30917822 examples [35:53, 43603.44 examples/s]
Generating train split: 30923428 examples [35:53, 45624.31 examples/s]
Generating train split: 30928178 examples [35:53, 43866.15 examples/s]
Generating train split: 30935368 examples [35:53, 51604.82 examples/s]
Generating train split: 30941607 examples [35:53, 54148.02 examples/s]
Generating train split: 30947142 examples [35:54, 35444.02 examples/s]
Generating train split: 30951599 examples [35:54, 35357.49 examples/s]
Generating train split: 30955773 examples [35:54, 34627.34 examples/s]
Generating train split: 30959671 examples [35:54, 24026.64 examples/s]
Generating train split: 30962778 examples [35:54, 24880.15 examples/s]
Generating train split: 30965809 examples [35:54, 25022.85 examples/s]
Generating train split: 30969927 examples [35:54, 28519.31 examples/s]
Generating train split: 30973188 examples [35:55, 19404.27 examples/s]
Generating train split: 30976094 examples [35:55, 21160.13 examples/s]
Generating train split: 30980186 examples [35:55, 25233.31 examples/s]
Generating train split: 30986009 examples [35:55, 32746.77 examples/s]
Generating train split: 30994351 examples [35:55, 45180.29 examples/s]
Generating train split: 31001773 examples [35:55, 52704.23 examples/s]
Generating train split: 31009588 examples [35:55, 59568.78 examples/s]
Generating train split: 31017058 examples [35:55, 63775.60 examples/s]
Generating train split: 31023829 examples [35:56, 36335.34 examples/s]
Generating train split: 31029110 examples [35:56, 36934.52 examples/s]
Generating train split: 31033973 examples [35:56, 28594.83 examples/s]
Generating train split: 31037889 examples [35:56, 26706.12 examples/s]
Generating train split: 31041282 examples [35:57, 27566.88 examples/s]
Generating train split: 31044595 examples [35:57, 21862.55 examples/s]
Generating train split: 31047305 examples [35:57, 18541.70 examples/s]
Generating train split: 31053869 examples [35:57, 26631.73 examples/s]
Generating train split: 31062728 examples [35:57, 38835.45 examples/s]
Generating train split: 31068367 examples [35:57, 41986.49 examples/s]
Generating train split: 31073541 examples [35:58, 28822.81 examples/s]
Generating train split: 31077651 examples [35:58, 26965.84 examples/s]
Generating train split: 31083884 examples [35:58, 33415.89 examples/s]
Generating train split: 31093627 examples [35:58, 46646.91 examples/s]
Generating train split: 31099589 examples [35:58, 49034.19 examples/s]
Generating train split: 31105465 examples [35:58, 34913.27 examples/s]
Generating train split: 31112819 examples [35:59, 42284.23 examples/s]
Generating train split: 31118333 examples [35:59, 36758.19 examples/s]
Generating train split: 31122996 examples [35:59, 28796.44 examples/s]
Generating train split: 31126771 examples [35:59, 23102.72 examples/s]
Generating train split: 31129823 examples [35:59, 20553.70 examples/s]
Generating train split: 31132400 examples [36:00, 17014.94 examples/s]
Generating train split: 31134494 examples [36:00, 14856.02 examples/s]
Generating train split: 31137045 examples [36:00, 16522.19 examples/s]
Generating train split: 31139039 examples [36:00, 12692.55 examples/s]
Generating train split: 31141006 examples [36:00, 13825.86 examples/s]
Generating train split: 31142721 examples [36:01, 14282.40 examples/s]
Generating train split: 31144407 examples [36:01, 11897.31 examples/s]
Generating train split: 31146632 examples [36:01, 13899.53 examples/s]
Generating train split: 31149403 examples [36:01, 16887.73 examples/s]
Generating train split: 31152423 examples [36:01, 20035.05 examples/s]
Generating train split: 31154726 examples [36:01, 18419.68 examples/s]
Generating train split: 31156801 examples [36:01, 18047.76 examples/s]
Generating train split: 31158793 examples [36:01, 18412.93 examples/s]
Generating train split: 31161921 examples [36:02, 21745.94 examples/s]
Generating train split: 31165240 examples [36:02, 23166.59 examples/s]
Generating train split: 31167643 examples [36:02, 21672.34 examples/s]
Generating train split: 31169878 examples [36:02, 20403.41 examples/s]
Generating train split: 31171972 examples [36:02, 17536.23 examples/s]
Generating train split: 31175125 examples [36:02, 20868.40 examples/s]
Generating train split: 31177370 examples [36:02, 18501.72 examples/s]
Generating train split: 31180483 examples [36:02, 21530.85 examples/s]
Generating train split: 31182807 examples [36:03, 21808.82 examples/s]
Generating train split: 31185125 examples [36:03, 21166.43 examples/s]
Generating train split: 31190621 examples [36:03, 30150.85 examples/s]
Generating train split: 31195591 examples [36:03, 35518.60 examples/s]
Generating train split: 31199322 examples [36:03, 32499.60 examples/s]
Generating train split: 31203301 examples [36:03, 34250.20 examples/s]
Generating train split: 31207837 examples [36:03, 37266.09 examples/s]
Generating train split: 31213547 examples [36:03, 42845.41 examples/s]
Generating train split: 31220568 examples [36:03, 50675.30 examples/s]
Generating train split: 31227111 examples [36:04, 54944.03 examples/s]
Generating train split: 31233427 examples [36:04, 57336.79 examples/s]
Generating train split: 31239234 examples [36:04, 51686.18 examples/s]
Generating train split: 31245665 examples [36:04, 54321.89 examples/s]
Generating train split: 31251221 examples [36:04, 42305.06 examples/s]
Generating train split: 31255929 examples [36:04, 29483.66 examples/s]
Generating train split: 31260836 examples [36:04, 33124.73 examples/s]
Generating train split: 31266760 examples [36:05, 38590.37 examples/s]
Generating train split: 31274781 examples [36:05, 46898.13 examples/s]
Generating train split: 31280186 examples [36:05, 28667.51 examples/s]
Generating train split: 31284390 examples [36:05, 27411.17 examples/s]
Generating train split: 31288048 examples [36:05, 25944.71 examples/s]
Generating train split: 31291265 examples [36:06, 19562.79 examples/s]
Generating train split: 31293834 examples [36:06, 19772.93 examples/s]
Generating train split: 31297642 examples [36:06, 23065.26 examples/s]
Generating train split: 31300474 examples [36:06, 14598.18 examples/s]
Generating train split: 31302666 examples [36:07, 9771.08 examples/s] 
Generating train split: 31304337 examples [36:07, 10206.09 examples/s]
Generating train split: 31305885 examples [36:07, 8686.07 examples/s] 
Generating train split: 31307771 examples [36:07, 10074.23 examples/s]
Generating train split: 31309427 examples [36:07, 11133.08 examples/s]
Generating train split: 31310928 examples [36:08, 11263.79 examples/s]
Generating train split: 31312330 examples [36:08, 7965.77 examples/s] 
Generating train split: 31313447 examples [36:08, 7160.90 examples/s]
Generating train split: 31315740 examples [36:08, 9717.33 examples/s]
Generating train split: 31319318 examples [36:08, 14668.18 examples/s]
Generating train split: 31321321 examples [36:09, 14659.34 examples/s]
Generating train split: 31324189 examples [36:09, 17741.29 examples/s]
Generating train split: 31326338 examples [36:09, 13498.89 examples/s]
Generating train split: 31328097 examples [36:09, 14169.45 examples/s]
Generating train split: 31330540 examples [36:09, 16408.65 examples/s]
Generating train split: 31332480 examples [36:09, 15225.64 examples/s]
Generating train split: 31335125 examples [36:09, 17827.81 examples/s]
Generating train split: 31337499 examples [36:09, 19018.57 examples/s]
Generating train split: 31339592 examples [36:10, 16700.04 examples/s]
Generating train split: 31341444 examples [36:10, 15083.77 examples/s]
Generating train split: 31344012 examples [36:10, 17534.51 examples/s]
Generating train split: 31345936 examples [36:10, 16866.42 examples/s]
Generating train split: 31347988 examples [36:10, 17752.87 examples/s]
Generating train split: 31349862 examples [36:10, 16776.51 examples/s]
Generating train split: 31353275 examples [36:10, 21269.04 examples/s]
Generating train split: 31359958 examples [36:10, 32886.56 examples/s]
Generating train split: 31363395 examples [36:11, 20772.57 examples/s]
Generating train split: 31367025 examples [36:11, 23817.58 examples/s]
Generating train split: 31370936 examples [36:11, 27165.90 examples/s]
Generating train split: 31374211 examples [36:11, 22273.50 examples/s]
Generating train split: 31376959 examples [36:11, 20875.11 examples/s]
Generating train split: 31379944 examples [36:11, 22761.30 examples/s]
Generating train split: 31383261 examples [36:12, 25161.49 examples/s]
Generating train split: 31386089 examples [36:12, 21784.18 examples/s]
Generating train split: 31388548 examples [36:12, 20424.21 examples/s]
Generating train split: 31390785 examples [36:12, 18740.83 examples/s]
Generating train split: 31394013 examples [36:12, 21819.32 examples/s]
Generating train split: 31397332 examples [36:12, 24604.96 examples/s]
Generating train split: 31400000 examples [36:13, 16036.85 examples/s]
Generating train split: 31402371 examples [36:13, 17479.77 examples/s]
Generating train split: 31405770 examples [36:13, 20897.22 examples/s]
Generating train split: 31408435 examples [36:13, 20523.23 examples/s]
Generating train split: 31410801 examples [36:13, 18736.67 examples/s]
Generating train split: 31412902 examples [36:13, 17709.43 examples/s]
Generating train split: 31414840 examples [36:13, 18043.24 examples/s]
Generating train split: 31418286 examples [36:13, 22101.17 examples/s]
Generating train split: 31420903 examples [36:13, 22481.08 examples/s]
Generating train split: 31423285 examples [36:14, 22072.96 examples/s]
Generating train split: 31425584 examples [36:14, 21834.48 examples/s]
Generating train split: 31427825 examples [36:14, 20691.95 examples/s]
Generating train split: 31429942 examples [36:14, 19394.33 examples/s]
Generating train split: 31431929 examples [36:14, 14936.75 examples/s]
Generating train split: 31435455 examples [36:14, 18996.24 examples/s]
Generating train split: 31437781 examples [36:14, 19587.42 examples/s]
Generating train split: 31439903 examples [36:14, 19393.84 examples/s]
Generating train split: 31445476 examples [36:15, 28711.59 examples/s]
Generating train split: 31451003 examples [36:15, 35831.65 examples/s]
Generating train split: 31458229 examples [36:15, 45540.32 examples/s]
Generating train split: 31463023 examples [36:15, 32256.71 examples/s]
Generating train split: 31466943 examples [36:15, 32124.64 examples/s]
Generating train split: 31471131 examples [36:15, 34359.53 examples/s]
Generating train split: 31474973 examples [36:15, 32153.01 examples/s]
Generating train split: 31482623 examples [36:15, 42923.44 examples/s]
Generating train split: 31491120 examples [36:16, 53745.90 examples/s]
Generating train split: 31496994 examples [36:16, 32361.48 examples/s]
Generating train split: 31501597 examples [36:16, 30806.46 examples/s]
Generating train split: 31505633 examples [36:16, 32184.78 examples/s]
Generating train split: 31509596 examples [36:17, 21705.53 examples/s]
Generating train split: 31512692 examples [36:17, 22483.97 examples/s]
Generating train split: 31515633 examples [36:17, 20753.69 examples/s]
Generating train split: 31518191 examples [36:17, 17350.59 examples/s]
Generating train split: 31520361 examples [36:17, 18107.79 examples/s]
Generating train split: 31522973 examples [36:17, 19693.71 examples/s]
Generating train split: 31525247 examples [36:18, 15930.16 examples/s]
Generating train split: 31527157 examples [36:18, 15352.23 examples/s]
Generating train split: 31528902 examples [36:18, 14290.13 examples/s]
Generating train split: 31532017 examples [36:18, 17865.45 examples/s]
Generating train split: 31534837 examples [36:18, 20102.87 examples/s]
Generating train split: 31537238 examples [36:18, 21054.90 examples/s]
Generating train split: 31539951 examples [36:18, 22415.63 examples/s]
Generating train split: 31542336 examples [36:18, 22213.01 examples/s]
Generating train split: 31544660 examples [36:19, 13332.93 examples/s]
Generating train split: 31546898 examples [36:19, 15021.11 examples/s]
Generating train split: 31549244 examples [36:19, 16788.38 examples/s]
Generating train split: 31551310 examples [36:19, 13631.65 examples/s]
Generating train split: 31555239 examples [36:19, 18831.47 examples/s]
Generating train split: 31557857 examples [36:19, 20469.19 examples/s]
Generating train split: 31560303 examples [36:20, 16765.69 examples/s]
Generating train split: 31562475 examples [36:20, 17823.40 examples/s]
Generating train split: 31564566 examples [36:20, 17861.74 examples/s]
Generating train split: 31566573 examples [36:20, 14747.97 examples/s]
Generating train split: 31568283 examples [36:20, 13017.49 examples/s]
Generating train split: 31569766 examples [36:20, 12233.91 examples/s]
Generating train split: 31571108 examples [36:21, 9568.36 examples/s] 
Generating train split: 31572217 examples [36:21, 8923.01 examples/s]
Generating train split: 31575930 examples [36:21, 14490.16 examples/s]
Generating train split: 31577737 examples [36:21, 14571.09 examples/s]
Generating train split: 31579444 examples [36:21, 11098.01 examples/s]
Generating train split: 31580851 examples [36:21, 10198.51 examples/s]
Generating train split: 31585996 examples [36:21, 18251.53 examples/s]
Generating train split: 31594249 examples [36:22, 32263.86 examples/s]
Generating train split: 31599120 examples [36:22, 34890.19 examples/s]
Generating train split: 31603299 examples [36:22, 24998.78 examples/s]
Generating train split: 31610083 examples [36:22, 33303.25 examples/s]
Generating train split: 31617640 examples [36:22, 42152.55 examples/s]
Generating train split: 31622910 examples [36:22, 28757.39 examples/s]
Generating train split: 31627075 examples [36:23, 22171.81 examples/s]
Generating train split: 31630372 examples [36:23, 18780.35 examples/s]
Generating train split: 31635636 examples [36:23, 23770.14 examples/s]
Generating train split: 31644818 examples [36:23, 35605.21 examples/s]
Generating train split: 31650169 examples [36:23, 39109.51 examples/s]
Generating train split: 31655388 examples [36:24, 34865.46 examples/s]
Generating train split: 31662696 examples [36:24, 42801.32 examples/s]
Generating train split: 31669596 examples [36:24, 48791.36 examples/s]
Generating train split: 31675387 examples [36:24, 35324.34 examples/s]
Generating train split: 31680060 examples [36:24, 29530.46 examples/s]
Generating train split: 31683922 examples [36:24, 30048.87 examples/s]
Generating train split: 31692340 examples [36:25, 40808.94 examples/s]
Generating train split: 31699035 examples [36:25, 46574.10 examples/s]
Generating train split: 31704608 examples [36:25, 26672.16 examples/s]
Generating train split: 31713102 examples [36:25, 35869.31 examples/s]
Generating train split: 31721143 examples [36:25, 44065.85 examples/s]
Generating train split: 31727444 examples [36:26, 30320.56 examples/s]
Generating train split: 31732343 examples [36:26, 22899.13 examples/s]
Generating train split: 31736153 examples [36:26, 18366.00 examples/s]
Generating train split: 31739141 examples [36:27, 16161.80 examples/s]
Generating train split: 31741553 examples [36:27, 15445.03 examples/s]
Generating train split: 31743627 examples [36:27, 14244.88 examples/s]
Generating train split: 31745823 examples [36:27, 15346.50 examples/s]
Generating train split: 31747955 examples [36:27, 16215.68 examples/s]
Generating train split: 31750267 examples [36:27, 17585.08 examples/s]
Generating train split: 31758575 examples [36:27, 32057.01 examples/s]
Generating train split: 31766946 examples [36:28, 44445.87 examples/s]
Generating train split: 31772200 examples [36:28, 27439.46 examples/s]
Generating train split: 31776308 examples [36:28, 21689.88 examples/s]
Generating train split: 31779581 examples [36:29, 18784.80 examples/s]
Generating train split: 31782259 examples [36:29, 18621.98 examples/s]
Generating train split: 31784666 examples [36:29, 14934.09 examples/s]
Generating train split: 31786827 examples [36:29, 15895.73 examples/s]
Generating train split: 31788822 examples [36:29, 12822.56 examples/s]
Generating train split: 31790447 examples [36:29, 12919.61 examples/s]
Generating train split: 31791982 examples [36:30, 13338.51 examples/s]
Generating train split: 31799139 examples [36:30, 25531.55 examples/s]
Generating train split: 31806720 examples [36:30, 37105.13 examples/s]
Generating train split: 31811250 examples [36:30, 29967.18 examples/s]
Generating train split: 31815030 examples [36:30, 24478.87 examples/s]
Generating train split: 31823422 examples [36:30, 35809.22 examples/s]
Generating train split: 31831491 examples [36:30, 45250.15 examples/s]
Generating train split: 31837166 examples [36:31, 28674.94 examples/s]
Generating train split: 31841582 examples [36:31, 20510.72 examples/s]
Generating train split: 31844990 examples [36:31, 19116.18 examples/s]
Generating train split: 31847835 examples [36:32, 15442.56 examples/s]
Generating train split: 31850694 examples [36:32, 17143.32 examples/s]
Generating train split: 31853704 examples [36:32, 19198.90 examples/s]
Generating train split: 31859052 examples [36:32, 25481.69 examples/s]
Generating train split: 31862463 examples [36:32, 20217.78 examples/s]
Generating train split: 31865368 examples [36:32, 21811.86 examples/s]
Generating train split: 31872292 examples [36:33, 31542.32 examples/s]
Generating train split: 31880676 examples [36:33, 43390.70 examples/s]
Generating train split: 31886017 examples [36:33, 43301.26 examples/s]
Generating train split: 31891055 examples [36:33, 35922.63 examples/s]
Generating train split: 31897117 examples [36:33, 40769.22 examples/s]
Generating train split: 31901822 examples [36:33, 33439.79 examples/s]
Generating train split: 31905785 examples [36:33, 33576.96 examples/s]
Generating train split: 31909585 examples [36:34, 34562.28 examples/s]
Generating train split: 31914712 examples [36:34, 38619.53 examples/s]
Generating train split: 31918907 examples [36:34, 24089.59 examples/s]
Generating train split: 31922209 examples [36:34, 24577.89 examples/s]
Generating train split: 31926333 examples [36:34, 27813.68 examples/s]
Generating train split: 31929720 examples [36:35, 17447.91 examples/s]
Generating train split: 31932775 examples [36:35, 19524.08 examples/s]
Generating train split: 31937244 examples [36:35, 24187.68 examples/s]
Generating train split: 31940514 examples [36:35, 21859.48 examples/s]
Generating train split: 31943318 examples [36:35, 16930.66 examples/s]
Generating train split: 31946574 examples [36:35, 19641.73 examples/s]
Generating train split: 31949139 examples [36:35, 20737.28 examples/s]
Generating train split: 31951684 examples [36:36, 13871.13 examples/s]
Generating train split: 31953677 examples [36:36, 14431.54 examples/s]
Generating train split: 31956295 examples [36:36, 16639.83 examples/s]
Generating train split: 31962957 examples [36:36, 27220.16 examples/s]
Generating train split: 31966873 examples [36:36, 29982.29 examples/s]
Generating train split: 31973331 examples [36:36, 38544.98 examples/s]
Generating train split: 31977784 examples [36:37, 28314.17 examples/s]
Generating train split: 31981422 examples [36:37, 23668.46 examples/s]
Generating train split: 31984450 examples [36:37, 19938.89 examples/s]
Generating train split: 31987841 examples [36:37, 22318.48 examples/s]
Generating train split: 31990585 examples [36:38, 13344.05 examples/s]
Generating train split: 31992944 examples [36:38, 14792.61 examples/s]
Generating train split: 31995586 examples [36:38, 16747.47 examples/s]
Generating train split: 31998235 examples [36:38, 18634.88 examples/s]
Generating train split: 32000665 examples [36:38, 19862.21 examples/s]
Generating train split: 32003096 examples [36:38, 16738.85 examples/s]
Generating train split: 32005234 examples [36:38, 17724.26 examples/s]
Generating train split: 32009331 examples [36:38, 23134.26 examples/s]
Generating train split: 32012060 examples [36:39, 24168.20 examples/s]
Generating train split: 32014758 examples [36:39, 19234.73 examples/s]
Generating train split: 32017031 examples [36:39, 18714.32 examples/s]
Generating train split: 32019186 examples [36:39, 19333.86 examples/s]
Generating train split: 32022547 examples [36:39, 22868.44 examples/s]
Generating train split: 32025051 examples [36:39, 19940.85 examples/s]
Generating train split: 32027252 examples [36:40, 13713.74 examples/s]
Generating train split: 32030464 examples [36:40, 17167.01 examples/s]
Generating train split: 32032668 examples [36:40, 12010.66 examples/s]
Generating train split: 32034827 examples [36:40, 13593.15 examples/s]
Generating train split: 32036688 examples [36:40, 14359.80 examples/s]
Generating train split: 32039068 examples [36:40, 16141.69 examples/s]
Generating train split: 32041027 examples [36:40, 15087.43 examples/s]
Generating train split: 32042921 examples [36:41, 15754.88 examples/s]
Generating train split: 32044682 examples [36:41, 16052.73 examples/s]
Generating train split: 32049281 examples [36:41, 23691.64 examples/s]
Generating train split: 32058206 examples [36:41, 41205.71 examples/s]
Generating train split: 32064998 examples [36:41, 48586.02 examples/s]
Generating train split: 32070195 examples [36:41, 36653.49 examples/s]
Generating train split: 32074523 examples [36:42, 21985.25 examples/s]
Generating train split: 32077860 examples [36:42, 22404.97 examples/s]
Generating train split: 32080932 examples [36:42, 16696.22 examples/s]
Generating train split: 32083343 examples [36:42, 17796.01 examples/s]
Generating train split: 32088017 examples [36:42, 22892.01 examples/s]
Generating train split: 32093139 examples [36:42, 27615.17 examples/s]
Generating train split: 32096610 examples [36:43, 22845.03 examples/s]
Generating train split: 32099503 examples [36:43, 23297.26 examples/s]
Generating train split: 32102658 examples [36:43, 25050.61 examples/s]
Generating train split: 32105542 examples [36:43, 25774.46 examples/s]
Generating train split: 32108407 examples [36:43, 16925.05 examples/s]
Generating train split: 32110684 examples [36:43, 17243.01 examples/s]
Generating train split: 32119157 examples [36:44, 30875.30 examples/s]
Generating train split: 32127300 examples [36:44, 41141.41 examples/s]
Generating train split: 32132317 examples [36:44, 40025.69 examples/s]
Generating train split: 32136951 examples [36:44, 20963.98 examples/s]
Generating train split: 32145855 examples [36:44, 30966.10 examples/s]
Generating train split: 32153163 examples [36:44, 37991.68 examples/s]
Generating train split: 32158867 examples [36:45, 38772.01 examples/s]
Generating train split: 32164867 examples [36:45, 43173.62 examples/s]
Generating train split: 32170321 examples [36:45, 30737.47 examples/s]
Generating train split: 32174665 examples [36:45, 30411.40 examples/s]
Generating train split: 32178588 examples [36:45, 31249.70 examples/s]
Generating train split: 32182575 examples [36:45, 33047.35 examples/s]
Generating train split: 32189065 examples [36:45, 40398.28 examples/s]
Generating train split: 32197083 examples [36:46, 50254.98 examples/s]
Generating train split: 32202732 examples [36:46, 30622.54 examples/s]
Generating train split: 32207157 examples [36:46, 30557.03 examples/s]
Generating train split: 32212604 examples [36:46, 35148.84 examples/s]
Generating train split: 32219647 examples [36:46, 42744.87 examples/s]
Generating train split: 32226832 examples [36:46, 49591.72 examples/s]
Generating train split: 32232637 examples [36:47, 34409.19 examples/s]
Generating train split: 32237286 examples [36:47, 28767.95 examples/s]
Generating train split: 32241112 examples [36:47, 29106.04 examples/s]
Generating train split: 32248414 examples [36:47, 37668.59 examples/s]
Generating train split: 32255763 examples [36:47, 45468.80 examples/s]
Generating train split: 32261265 examples [36:48, 31729.78 examples/s]
Generating train split: 32265640 examples [36:48, 30450.16 examples/s]
Generating train split: 32273262 examples [36:48, 39181.46 examples/s]
Generating train split: 32281461 examples [36:48, 48345.25 examples/s]
Generating train split: 32287418 examples [36:48, 44301.91 examples/s]
Generating train split: 32292675 examples [36:48, 29280.65 examples/s]
Generating train split: 32296807 examples [36:49, 30275.21 examples/s]
Generating train split: 32300727 examples [36:49, 30194.97 examples/s]
Generating train split: 32304466 examples [36:49, 31657.04 examples/s]
Generating train split: 32311044 examples [36:49, 39348.24 examples/s]
Generating train split: 32317544 examples [36:49, 44965.06 examples/s]
Generating train split: 32322570 examples [36:49, 33417.82 examples/s]
Generating train split: 32326691 examples [36:49, 28863.04 examples/s]
Generating train split: 32330475 examples [36:50, 30631.21 examples/s]
Generating train split: 32334285 examples [36:50, 32232.33 examples/s]
Generating train split: 32337933 examples [36:50, 22324.12 examples/s]
Generating train split: 32340853 examples [36:50, 22759.99 examples/s]
Generating train split: 32344510 examples [36:50, 25522.15 examples/s]
Generating train split: 32347532 examples [36:50, 20669.39 examples/s]
Generating train split: 32350048 examples [36:51, 16844.86 examples/s]
Generating train split: 32352615 examples [36:51, 18454.36 examples/s]
Generating train split: 32355407 examples [36:51, 20243.73 examples/s]
Generating train split: 32357779 examples [36:51, 14587.17 examples/s]
Generating train split: 32360036 examples [36:51, 15918.45 examples/s]
Generating train split: 32362217 examples [36:51, 17107.08 examples/s]
Generating train split: 32364253 examples [36:51, 16706.73 examples/s]
Generating train split: 32366148 examples [36:52, 14164.14 examples/s]
Generating train split: 32367774 examples [36:52, 12850.15 examples/s]
Generating train split: 32374029 examples [36:52, 23412.74 examples/s]
Generating train split: 32381841 examples [36:52, 36152.59 examples/s]
Generating train split: 32387181 examples [36:52, 40441.21 examples/s]
Generating train split: 32391833 examples [36:52, 31254.40 examples/s]
Generating train split: 32395698 examples [36:53, 17259.11 examples/s]
Generating train split: 32398634 examples [36:53, 16989.12 examples/s]
Generating train split: 32403594 examples [36:53, 21960.84 examples/s]
Generating train split: 32407087 examples [36:53, 24277.22 examples/s]
Generating train split: 32410424 examples [36:53, 24625.07 examples/s]
Generating train split: 32413938 examples [36:54, 26878.79 examples/s]
Generating train split: 32418469 examples [36:54, 31208.28 examples/s]
Generating train split: 32423335 examples [36:54, 34459.17 examples/s]
Generating train split: 32427707 examples [36:54, 36019.21 examples/s]
Generating train split: 32433678 examples [36:54, 42268.36 examples/s]
Generating train split: 32438189 examples [36:54, 39519.40 examples/s]
Generating train split: 32442375 examples [36:54, 39426.46 examples/s]
Generating train split: 32446482 examples [36:54, 38808.10 examples/s]
Generating train split: 32450473 examples [36:54, 37077.74 examples/s]
Generating train split: 32455230 examples [36:55, 39780.72 examples/s]
Generating train split: 32460362 examples [36:55, 42947.27 examples/s]
Generating train split: 32465318 examples [36:55, 44810.06 examples/s]
Generating train split: 32470492 examples [36:55, 46559.45 examples/s]
Generating train split: 32475211 examples [36:55, 44641.92 examples/s]
Generating train split: 32480083 examples [36:55, 45791.38 examples/s]
Generating train split: 32484718 examples [36:55, 40640.48 examples/s]
Generating train split: 32490970 examples [36:55, 46482.44 examples/s]
Generating train split: 32499431 examples [36:55, 57009.37 examples/s]
Generating train split: 32506145 examples [36:55, 59862.38 examples/s]
Generating train split: 32512294 examples [36:56, 36455.05 examples/s]
Generating train split: 32517168 examples [36:56, 33722.46 examples/s]
Generating train split: 32522321 examples [36:56, 37243.39 examples/s]
Generating train split: 32526844 examples [36:56, 31312.25 examples/s]
Generating train split: 32531733 examples [36:56, 34746.09 examples/s]
Generating train split: 32535839 examples [36:57, 30016.99 examples/s]
Generating train split: 32539357 examples [36:57, 25729.57 examples/s]
Generating train split: 32542360 examples [36:57, 24008.99 examples/s]
Generating train split: 32545838 examples [36:57, 25971.52 examples/s]
Generating train split: 32548715 examples [36:57, 18508.69 examples/s]
Generating train split: 32551022 examples [36:57, 18903.56 examples/s]
Generating train split: 32553250 examples [36:58, 18516.85 examples/s]
Generating train split: 32555337 examples [36:58, 16950.10 examples/s]
Generating train split: 32558553 examples [36:58, 19931.51 examples/s]
Generating train split: 32560765 examples [36:58, 13721.87 examples/s]
Generating train split: 32562535 examples [36:58, 13007.98 examples/s]
Generating train split: 32564103 examples [36:59, 10873.48 examples/s]
Generating train split: 32566419 examples [36:59, 13070.12 examples/s]
Generating train split: 32568026 examples [36:59, 13175.35 examples/s]
Generating train split: 32569561 examples [36:59, 10484.45 examples/s]
Generating train split: 32571149 examples [36:59, 11516.21 examples/s]
Generating train split: 32572695 examples [36:59, 12331.35 examples/s]
Generating train split: 32574115 examples [36:59, 9970.15 examples/s] 
Generating train split: 32575416 examples [37:00, 10600.17 examples/s]
Generating train split: 32576635 examples [37:00, 6716.48 examples/s] 
Generating train split: 32578651 examples [37:00, 8954.55 examples/s]
Generating train split: 32580290 examples [37:00, 10377.47 examples/s]
Generating train split: 32582532 examples [37:00, 12950.97 examples/s]
Generating train split: 32584954 examples [37:00, 15558.49 examples/s]
Generating train split: 32586822 examples [37:00, 15404.22 examples/s]
Generating train split: 32590181 examples [37:01, 19991.73 examples/s]
Generating train split: 32594875 examples [37:01, 27133.47 examples/s]
Generating train split: 32600722 examples [37:01, 35737.63 examples/s]
Generating train split: 32607362 examples [37:01, 44367.85 examples/s]
Generating train split: 32614038 examples [37:01, 50778.96 examples/s]
Generating train split: 32620959 examples [37:01, 56134.62 examples/s]
Generating train split: 32626730 examples [37:01, 56347.01 examples/s]
Generating train split: 32632478 examples [37:01, 55660.44 examples/s]
Generating train split: 32639016 examples [37:01, 58495.94 examples/s]
Generating train split: 32647159 examples [37:01, 65230.84 examples/s]
Generating train split: 32654342 examples [37:02, 67158.41 examples/s]
Generating train split: 32661880 examples [37:02, 69573.18 examples/s]
Generating train split: 32669953 examples [37:02, 72832.49 examples/s]
Generating train split: 32678157 examples [37:02, 75557.31 examples/s]
Generating train split: 32685737 examples [37:02, 74049.16 examples/s]
Generating train split: 32693162 examples [37:02, 69702.66 examples/s]
Generating train split: 32700208 examples [37:02, 62329.32 examples/s]
Generating train split: 32706617 examples [37:02, 59930.38 examples/s]
Generating train split: 32712728 examples [37:02, 59149.81 examples/s]
Generating train split: 32718728 examples [37:03, 57334.61 examples/s]
Generating train split: 32724521 examples [37:03, 56095.77 examples/s]
Generating train split: 32730168 examples [37:03, 42396.95 examples/s]
Generating train split: 32735051 examples [37:03, 43853.94 examples/s]
Generating train split: 32739824 examples [37:03, 40208.55 examples/s]
Generating train split: 32745984 examples [37:03, 45333.91 examples/s]
Generating train split: 32750861 examples [37:03, 44064.31 examples/s]
Generating train split: 32755510 examples [37:03, 39869.50 examples/s]
Generating train split: 32759713 examples [37:04, 40002.31 examples/s]
Generating train split: 32763870 examples [37:04, 31675.33 examples/s]
Generating train split: 32767382 examples [37:04, 28746.29 examples/s]
Generating train split: 32770518 examples [37:04, 16944.04 examples/s]
Generating train split: 32772928 examples [37:05, 11694.82 examples/s]
Generating train split: 32774784 examples [37:06, 6501.24 examples/s] 
Generating train split: 32776299 examples [37:06, 7176.68 examples/s]
Generating train split: 32777673 examples [37:06, 7729.50 examples/s]
Generating train split: 32781099 examples [37:06, 11194.73 examples/s]
Generating train split: 32783087 examples [37:06, 12556.14 examples/s]
Generating train split: 32785054 examples [37:06, 13796.20 examples/s]
Generating train split: 32787010 examples [37:07, 9161.00 examples/s] 
Generating train split: 32788524 examples [37:07, 10067.14 examples/s]
Generating train split: 32790036 examples [37:07, 10046.61 examples/s]
Generating train split: 32791404 examples [37:07, 9918.14 examples/s] 
Generating train split: 32793570 examples [37:07, 12267.74 examples/s]
Generating train split: 32795086 examples [37:07, 11457.14 examples/s]
Generating train split: 32796437 examples [37:07, 9940.50 examples/s] 
Generating train split: 32803992 examples [37:08, 23572.04 examples/s]
Generating train split: 32813665 examples [37:08, 40312.55 examples/s]
Generating train split: 32818731 examples [37:08, 33387.65 examples/s]
Generating train split: 32822985 examples [37:08, 25270.13 examples/s]
Generating train split: 32826415 examples [37:09, 18353.37 examples/s]
Generating train split: 32829095 examples [37:09, 16708.84 examples/s]
Generating train split: 32831348 examples [37:09, 16853.76 examples/s]
Generating train split: 32833667 examples [37:09, 17948.45 examples/s]
Generating train split: 32835840 examples [37:09, 18267.83 examples/s]
Generating train split: 32837943 examples [37:09, 18450.45 examples/s]
Generating train split: 32840243 examples [37:09, 19496.32 examples/s]
Generating train split: 32842364 examples [37:09, 16060.33 examples/s]
Generating train split: 32844768 examples [37:10, 17840.03 examples/s]
Generating train split: 32847504 examples [37:10, 20109.02 examples/s]
Generating train split: 32849838 examples [37:10, 20926.99 examples/s]
Generating train split: 32852080 examples [37:10, 18484.69 examples/s]
Generating train split: 32854077 examples [37:10, 15915.72 examples/s]
Generating train split: 32856362 examples [37:10, 17445.00 examples/s]
Generating train split: 32859122 examples [37:10, 19948.05 examples/s]
Generating train split: 32861806 examples [37:10, 21611.31 examples/s]
Generating train split: 32864099 examples [37:11, 13532.61 examples/s]
Generating train split: 32865920 examples [37:11, 13891.08 examples/s]
Generating train split: 32867662 examples [37:11, 13745.27 examples/s]
Generating train split: 32869273 examples [37:11, 10845.72 examples/s]
Generating train split: 32870598 examples [37:11, 11105.79 examples/s]
Generating train split: 32873914 examples [37:11, 15788.48 examples/s]
Generating train split: 32875908 examples [37:12, 16753.44 examples/s]
Generating train split: 32877834 examples [37:13, 4796.76 examples/s] 
Generating train split: 32879232 examples [37:13, 5517.60 examples/s]
Generating train split: 32881295 examples [37:13, 7203.84 examples/s]
Generating train split: 32882846 examples [37:13, 7950.80 examples/s]
Generating train split: 32884271 examples [37:13, 7190.07 examples/s]
Generating train split: 32885439 examples [37:14, 6803.45 examples/s]
Generating train split: 32886432 examples [37:14, 7264.35 examples/s]
Generating train split: 32887417 examples [37:14, 5604.70 examples/s]
Generating train split: 32888205 examples [37:14, 5784.46 examples/s]
Generating train split: 32889067 examples [37:14, 6298.18 examples/s]
Generating train split: 32890267 examples [37:14, 7252.18 examples/s]
Generating train split: 32891128 examples [37:14, 5779.86 examples/s]
Generating train split: 32893761 examples [37:15, 9792.31 examples/s]
Generating train split: 32901307 examples [37:15, 24115.14 examples/s]
Generating train split: 32908883 examples [37:15, 36372.32 examples/s]
Generating train split: 32913372 examples [37:15, 19891.56 examples/s]
Generating train split: 32916799 examples [37:15, 21234.68 examples/s]
Generating train split: 32920018 examples [37:16, 16899.81 examples/s]
Generating train split: 32923300 examples [37:16, 19378.18 examples/s]
Generating train split: 32931388 examples [37:16, 30576.72 examples/s]
Generating train split: 32936897 examples [37:16, 35242.49 examples/s]
Generating train split: 32941522 examples [37:16, 37632.11 examples/s]
Generating train split: 32949767 examples [37:16, 48533.48 examples/s]
Generating train split: 32958261 examples [37:16, 57221.95 examples/s]
Generating train split: 32964690 examples [37:17, 26251.22 examples/s]
Generating train split: 32969528 examples [37:17, 27839.94 examples/s]
Generating train split: 32978111 examples [37:17, 37317.59 examples/s]
Generating train split: 32984149 examples [37:17, 41672.65 examples/s]
Generating train split: 32989927 examples [37:18, 27909.53 examples/s]
Generating train split: 32994421 examples [37:18, 23418.66 examples/s]
Generating train split: 32998024 examples [37:18, 20910.00 examples/s]
Generating train split: 33001004 examples [37:18, 21773.87 examples/s]
Generating train split: 33004047 examples [37:18, 23262.75 examples/s]
Generating train split: 33007823 examples [37:18, 26117.87 examples/s]
Generating train split: 33011731 examples [37:19, 28827.10 examples/s]
Generating train split: 33015099 examples [37:19, 27265.20 examples/s]
Generating train split: 33018171 examples [37:19, 23313.02 examples/s]
Generating train split: 33020817 examples [37:19, 20806.62 examples/s]
Generating train split: 33024036 examples [37:19, 22960.71 examples/s]
Generating train split: 33028920 examples [37:19, 28942.75 examples/s]
Generating train split: 33035354 examples [37:19, 37731.61 examples/s]
Generating train split: 33042721 examples [37:19, 47011.15 examples/s]
Generating train split: 33047855 examples [37:20, 25757.02 examples/s]
Generating train split: 33054933 examples [37:20, 33489.97 examples/s]
Generating train split: 33062090 examples [37:20, 40990.88 examples/s]
Generating train split: 33067668 examples [37:20, 39381.83 examples/s]
Generating train split: 33072641 examples [37:21, 23714.04 examples/s]
Generating train split: 33081364 examples [37:21, 33289.88 examples/s]
Generating train split: 33089745 examples [37:21, 41806.09 examples/s]
Generating train split: 33095822 examples [37:21, 23437.74 examples/s]
Generating train split: 33100392 examples [37:22, 23752.81 examples/s]
Generating train split: 33109207 examples [37:22, 32896.11 examples/s]
Generating train split: 33117151 examples [37:22, 40732.35 examples/s]
Generating train split: 33123316 examples [37:22, 40886.28 examples/s]
Generating train split: 33131937 examples [37:22, 50035.79 examples/s]
Generating train split: 33138430 examples [37:22, 53353.15 examples/s]
Generating train split: 33144922 examples [37:23, 29605.09 examples/s]
Generating train split: 33149871 examples [37:23, 25673.51 examples/s]
Generating train split: 33153874 examples [37:23, 17105.29 examples/s]
Generating train split: 33156907 examples [37:24, 16802.80 examples/s]
Generating train split: 33159504 examples [37:24, 17490.78 examples/s]
Generating train split: 33161956 examples [37:24, 13966.63 examples/s]
Generating train split: 33163905 examples [37:24, 14612.10 examples/s]
Generating train split: 33165828 examples [37:24, 14311.04 examples/s]
Generating train split: 33167566 examples [37:25, 12284.44 examples/s]
Generating train split: 33169240 examples [37:25, 13065.39 examples/s]
Generating train split: 33172086 examples [37:25, 16154.42 examples/s]
Generating train split: 33174013 examples [37:25, 15561.47 examples/s]
Generating train split: 33177474 examples [37:25, 19885.00 examples/s]
Generating train split: 33186481 examples [37:25, 37074.26 examples/s]
Generating train split: 33190779 examples [37:25, 34042.00 examples/s]
Generating train split: 33194633 examples [37:26, 24846.52 examples/s]
Generating train split: 33197764 examples [37:26, 24908.11 examples/s]
Generating train split: 33200717 examples [37:26, 18975.19 examples/s]
Generating train split: 33203108 examples [37:26, 17113.49 examples/s]
Generating train split: 33210941 examples [37:26, 28332.23 examples/s]
Generating train split: 33219042 examples [37:26, 39260.83 examples/s]
Generating train split: 33224132 examples [37:26, 37809.88 examples/s]
Generating train split: 33228724 examples [37:27, 21085.35 examples/s]
Generating train split: 33232564 examples [37:27, 23634.31 examples/s]
Generating train split: 33236164 examples [37:27, 25633.68 examples/s]
Generating train split: 33239742 examples [37:28, 17563.33 examples/s]
Generating train split: 33248783 examples [37:28, 28658.46 examples/s]
Generating train split: 33254884 examples [37:28, 34439.98 examples/s]
Generating train split: 33259972 examples [37:28, 35353.55 examples/s]
Generating train split: 33264672 examples [37:29, 17727.73 examples/s]
Generating train split: 33268187 examples [37:29, 11795.20 examples/s]
Generating train split: 33270809 examples [37:30, 9066.56 examples/s] 
Generating train split: 33272783 examples [37:30, 8734.98 examples/s]
Generating train split: 33274407 examples [37:30, 8062.38 examples/s]
Generating train split: 33275711 examples [37:30, 8074.52 examples/s]
Generating train split: 33276873 examples [37:31, 7199.27 examples/s]
Generating train split: 33278758 examples [37:31, 8712.64 examples/s]
Generating train split: 33280392 examples [37:31, 9868.08 examples/s]
Generating train split: 33282916 examples [37:31, 12539.82 examples/s]
Generating train split: 33284575 examples [37:32, 5387.20 examples/s] 
Generating train split: 33285803 examples [37:32, 5637.12 examples/s]
Generating train split: 33286868 examples [37:32, 5555.72 examples/s]
Generating train split: 33287773 examples [37:32, 5397.40 examples/s]
Generating train split: 33288714 examples [37:32, 5972.66 examples/s]
Generating train split: 33289540 examples [37:33, 4695.91 examples/s]
Generating train split: 33290708 examples [37:33, 5768.70 examples/s]
Generating train split: 33291517 examples [37:33, 6159.17 examples/s]
Generating train split: 33293621 examples [37:33, 9186.46 examples/s]
Generating train split: 33295416 examples [37:33, 11072.02 examples/s]
Generating train split: 33300291 examples [37:33, 20089.53 examples/s]
Generating train split: 33308787 examples [37:33, 36689.18 examples/s]
Generating train split: 33313006 examples [37:34, 34799.03 examples/s]
Generating train split: 33316895 examples [37:34, 25386.26 examples/s]
Generating train split: 33325261 examples [37:34, 37467.29 examples/s]
Generating train split: 33330593 examples [37:34, 41080.06 examples/s]
Generating train split: 33335507 examples [37:34, 27728.21 examples/s]
Generating train split: 33339405 examples [37:35, 21741.22 examples/s]
Generating train split: 33343589 examples [37:35, 24943.25 examples/s]
Generating train split: 33348729 examples [37:35, 29885.80 examples/s]
Generating train split: 33356255 examples [37:35, 39165.02 examples/s]
Generating train split: 33361201 examples [37:35, 28512.40 examples/s]
Generating train split: 33365165 examples [37:35, 29593.17 examples/s]
Generating train split: 33369715 examples [37:35, 32764.88 examples/s]
Generating train split: 33373713 examples [37:36, 26833.39 examples/s]
Generating train split: 33377046 examples [37:36, 23998.90 examples/s]
Generating train split: 33380840 examples [37:36, 26725.81 examples/s]
Generating train split: 33384781 examples [37:36, 29491.93 examples/s]
Generating train split: 33388170 examples [37:36, 24315.08 examples/s]
Generating train split: 33391031 examples [37:36, 19657.83 examples/s]
Generating train split: 33395268 examples [37:37, 23779.25 examples/s]
Generating train split: 33398145 examples [37:37, 21588.23 examples/s]
Generating train split: 33400667 examples [37:37, 18766.96 examples/s]
Generating train split: 33402830 examples [37:37, 18011.11 examples/s]
Generating train split: 33408956 examples [37:37, 27121.71 examples/s]
Generating train split: 33417650 examples [37:37, 40959.15 examples/s]
Generating train split: 33425053 examples [37:37, 49171.21 examples/s]
Generating train split: 33430681 examples [37:38, 24470.78 examples/s]
Generating train split: 33434952 examples [37:38, 19666.33 examples/s]
Generating train split: 33442305 examples [37:38, 26968.36 examples/s]
Generating train split: 33450538 examples [37:38, 35492.21 examples/s]
Generating train split: 33456010 examples [37:39, 29581.02 examples/s]
Generating train split: 33460447 examples [37:39, 30361.41 examples/s]
Generating train split: 33467883 examples [37:39, 38495.42 examples/s]
Generating train split: 33474149 examples [37:39, 43218.55 examples/s]
Generating train split: 33479548 examples [37:39, 29199.78 examples/s]
Generating train split: 33486077 examples [37:40, 35425.28 examples/s]
Generating train split: 33495138 examples [37:40, 46340.78 examples/s]
Generating train split: 33501311 examples [37:40, 45809.74 examples/s]
Generating train split: 33506965 examples [37:40, 28977.59 examples/s]
Generating train split: 33511355 examples [37:40, 27220.48 examples/s]
Generating train split: 33519550 examples [37:40, 36354.51 examples/s]
Generating train split: 33527746 examples [37:41, 45130.87 examples/s]
Generating train split: 33533766 examples [37:41, 27352.92 examples/s]
Generating train split: 33538372 examples [37:41, 30050.22 examples/s]
Generating train split: 33542989 examples [37:41, 32858.49 examples/s]
Generating train split: 33548741 examples [37:41, 37760.16 examples/s]
Generating train split: 33553681 examples [37:42, 26429.81 examples/s]
Generating train split: 33557587 examples [37:42, 28281.25 examples/s]
Generating train split: 33561530 examples [37:42, 30450.55 examples/s]
Generating train split: 33568632 examples [37:42, 39293.67 examples/s]
Generating train split: 33576830 examples [37:42, 49421.02 examples/s]
Generating train split: 33582670 examples [37:42, 38886.79 examples/s]
Generating train split: 33587521 examples [37:43, 29008.57 examples/s]
Generating train split: 33595744 examples [37:43, 38481.24 examples/s]
Generating train split: 33603892 examples [37:43, 47194.79 examples/s]
Generating train split: 33609969 examples [37:43, 30088.68 examples/s]
Generating train split: 33614684 examples [37:43, 27000.71 examples/s]
Generating train split: 33622268 examples [37:44, 34768.19 examples/s]
Generating train split: 33630625 examples [37:44, 43802.74 examples/s]
Generating train split: 33636644 examples [37:44, 44411.70 examples/s]
Generating train split: 33642238 examples [37:44, 28868.50 examples/s]
Generating train split: 33650466 examples [37:44, 37498.24 examples/s]
Generating train split: 33659380 examples [37:44, 47175.16 examples/s]
Generating train split: 33665911 examples [37:45, 34844.99 examples/s]
Generating train split: 33671883 examples [37:45, 39092.57 examples/s]
Generating train split: 33677303 examples [37:45, 31116.74 examples/s]
Generating train split: 33681694 examples [37:45, 29641.30 examples/s]
Generating train split: 33685744 examples [37:45, 31427.51 examples/s]
Generating train split: 33689613 examples [37:46, 22422.29 examples/s]
Generating train split: 33692674 examples [37:46, 21065.76 examples/s]
Generating train split: 33695337 examples [37:46, 21586.83 examples/s]
Generating train split: 33698051 examples [37:46, 22481.02 examples/s]
Generating train split: 33700633 examples [37:46, 14091.64 examples/s]
Generating train split: 33704272 examples [37:47, 17609.99 examples/s]
Generating train split: 33709693 examples [37:47, 24313.91 examples/s]
Generating train split: 33713057 examples [37:47, 17642.68 examples/s]
Generating train split: 33715714 examples [37:47, 18124.76 examples/s]
Generating train split: 33719145 examples [37:47, 21093.72 examples/s]
Generating train split: 33726571 examples [37:47, 32149.91 examples/s]
Generating train split: 33735621 examples [37:47, 45513.81 examples/s]
Generating train split: 33741243 examples [37:48, 24659.10 examples/s]
Generating train split: 33745855 examples [37:48, 27910.84 examples/s]
Generating train split: 33751432 examples [37:48, 32894.67 examples/s]
Generating train split: 33756232 examples [37:48, 35136.91 examples/s]
Generating train split: 33760843 examples [37:48, 26411.28 examples/s]
Generating train split: 33764545 examples [37:49, 24014.86 examples/s]
Generating train split: 33767695 examples [37:49, 21168.37 examples/s]
Generating train split: 33770361 examples [37:49, 19577.89 examples/s]
Generating train split: 33779458 examples [37:49, 32623.35 examples/s]
Generating train split: 33787857 examples [37:49, 43244.20 examples/s]
Generating train split: 33793422 examples [37:49, 39801.18 examples/s]
Generating train split: 33798311 examples [37:50, 41156.10 examples/s]
Generating train split: 33803112 examples [37:50, 35646.96 examples/s]
Generating train split: 33807259 examples [37:50, 34241.67 examples/s]
Generating train split: 33811069 examples [37:50, 31901.80 examples/s]
Generating train split: 33814532 examples [37:50, 32464.13 examples/s]
Generating train split: 33823733 examples [37:50, 46986.41 examples/s]
Generating train split: 33831494 examples [37:50, 54826.62 examples/s]
Generating train split: 33837441 examples [37:51, 26056.40 examples/s]
Generating train split: 33841945 examples [37:51, 28504.45 examples/s]
Generating train split: 33846331 examples [37:51, 30800.84 examples/s]
Generating train split: 33853280 examples [37:51, 38221.15 examples/s]
Generating train split: 33858303 examples [37:52, 26560.35 examples/s]
Generating train split: 33862255 examples [37:52, 27712.25 examples/s]
Generating train split: 33865994 examples [37:52, 28929.69 examples/s]
Generating train split: 33869617 examples [37:52, 20339.37 examples/s]
Generating train split: 33872484 examples [37:52, 21092.24 examples/s]
Generating train split: 33875228 examples [37:52, 22271.64 examples/s]
Generating train split: 33877961 examples [37:53, 14994.92 examples/s]
Generating train split: 33880106 examples [37:53, 15795.83 examples/s]
Generating train split: 33882419 examples [37:53, 17092.27 examples/s]
Generating train split: 33884559 examples [37:53, 15039.40 examples/s]
Generating train split: 33886389 examples [37:53, 12149.33 examples/s]
Generating train split: 33893847 examples [37:53, 23448.93 examples/s]
Generating train split: 33902458 examples [37:54, 36321.01 examples/s]
Generating train split: 33907350 examples [37:54, 28212.26 examples/s]
Generating train split: 33911310 examples [37:54, 22123.17 examples/s]
Generating train split: 33914487 examples [37:55, 14819.64 examples/s]
Generating train split: 33916921 examples [37:55, 13752.30 examples/s]
Generating train split: 33918938 examples [37:55, 13243.99 examples/s]
Generating train split: 33920693 examples [37:55, 9003.74 examples/s] 
Generating train split: 33922243 examples [37:56, 9724.77 examples/s]
Generating train split: 33923626 examples [37:56, 7041.95 examples/s]
Generating train split: 33924694 examples [37:57, 4561.95 examples/s]
Generating train split: 33925501 examples [37:57, 4703.37 examples/s]
Generating train split: 33926241 examples [37:57, 4235.34 examples/s]
Generating train split: 33926913 examples [37:57, 4545.17 examples/s]
Generating train split: 33927987 examples [37:57, 5462.96 examples/s]
Generating train split: 33928811 examples [37:57, 5927.40 examples/s]
Generating train split: 33929578 examples [37:57, 6216.26 examples/s]
Generating train split: 33930339 examples [37:58, 4546.77 examples/s]
Generating train split: 33932467 examples [37:58, 7570.14 examples/s]
Generating train split: 33933803 examples [37:58, 8747.58 examples/s]
Generating train split: 33935048 examples [37:58, 9578.10 examples/s]
Generating train split: 33936219 examples [37:58, 9271.19 examples/s]
Generating train split: 33938173 examples [37:58, 11501.96 examples/s]
Generating train split: 33940753 examples [37:58, 15116.13 examples/s]
Generating train split: 33943320 examples [37:58, 17899.49 examples/s]
Generating train split: 33947748 examples [37:59, 25088.62 examples/s]
Generating train split: 33952680 examples [37:59, 31502.04 examples/s]
Generating train split: 33955973 examples [37:59, 20183.64 examples/s]
Generating train split: 33958614 examples [37:59, 19642.02 examples/s]
Generating train split: 33963745 examples [37:59, 26302.72 examples/s]
Generating train split: 33968088 examples [37:59, 30252.29 examples/s]
Generating train split: 33971640 examples [37:59, 26829.30 examples/s]
Generating train split: 33974745 examples [38:00, 25043.58 examples/s]
Generating train split: 33977550 examples [38:00, 23961.94 examples/s]
Generating train split: 33987447 examples [38:00, 41508.13 examples/s]
Generating train split: 33995004 examples [38:00, 50035.53 examples/s]
Generating train split: 34000625 examples [38:00, 48930.45 examples/s]
Generating train split: 34005949 examples [38:01, 23058.09 examples/s]
Generating train split: 34009974 examples [38:01, 25313.78 examples/s]
Generating train split: 34016167 examples [38:01, 31619.65 examples/s]
Generating train split: 34026127 examples [38:01, 45049.93 examples/s]
Generating train split: 34032352 examples [38:01, 28999.53 examples/s]
Generating train split: 34037160 examples [38:01, 29595.18 examples/s]
Generating train split: 34041486 examples [38:02, 26577.69 examples/s]
Generating train split: 34045110 examples [38:02, 24719.81 examples/s]
Generating train split: 34049178 examples [38:02, 27515.07 examples/s]
Generating train split: 34052903 examples [38:02, 29461.66 examples/s]
Generating train split: 34061348 examples [38:02, 41689.57 examples/s]
Generating train split: 34068840 examples [38:02, 49456.11 examples/s]
Generating train split: 34074540 examples [38:03, 26085.22 examples/s]
Generating train split: 34078886 examples [38:03, 26558.55 examples/s]
Generating train split: 34082772 examples [38:03, 25130.27 examples/s]
Generating train split: 34086136 examples [38:03, 24420.23 examples/s]
Generating train split: 34089164 examples [38:03, 23872.97 examples/s]
Generating train split: 34091945 examples [38:03, 23022.25 examples/s]
Generating train split: 34094515 examples [38:04, 16736.07 examples/s]
Generating train split: 34097950 examples [38:04, 19831.57 examples/s]
Generating train split: 34100418 examples [38:04, 19546.16 examples/s]
Generating train split: 34102707 examples [38:04, 13461.68 examples/s]
Generating train split: 34104627 examples [38:04, 14415.70 examples/s]
Generating train split: 34106811 examples [38:05, 15742.71 examples/s]
Generating train split: 34108753 examples [38:05, 16532.15 examples/s]
Generating train split: 34110700 examples [38:05, 13442.87 examples/s]
Generating train split: 34112325 examples [38:05, 13076.31 examples/s]
Generating train split: 34119848 examples [38:05, 26544.07 examples/s]
Generating train split: 34127362 examples [38:05, 38030.95 examples/s]
Generating train split: 34131937 examples [38:05, 35259.69 examples/s]
Generating train split: 34136144 examples [38:05, 36897.49 examples/s]
Generating train split: 34143308 examples [38:06, 45796.50 examples/s]
Generating train split: 34150674 examples [38:06, 53196.49 examples/s]
Generating train split: 34156401 examples [38:06, 27153.05 examples/s]
Generating train split: 34160783 examples [38:06, 24642.02 examples/s]
Generating train split: 34164907 examples [38:06, 27331.21 examples/s]
Generating train split: 34168693 examples [38:07, 24411.60 examples/s]
Generating train split: 34177178 examples [38:07, 35479.14 examples/s]
Generating train split: 34185485 examples [38:07, 44492.39 examples/s]
Generating train split: 34191117 examples [38:07, 40755.95 examples/s]
Generating train split: 34196055 examples [38:07, 39932.73 examples/s]
Generating train split: 34205781 examples [38:07, 52852.60 examples/s]
Generating train split: 34213183 examples [38:07, 57745.48 examples/s]
Generating train split: 34219651 examples [38:08, 38443.49 examples/s]
Generating train split: 34224807 examples [38:08, 37131.09 examples/s]
Generating train split: 34229423 examples [38:08, 38243.32 examples/s]
Generating train split: 34233932 examples [38:08, 22833.93 examples/s]
Generating train split: 34242739 examples [38:08, 32745.86 examples/s]
Generating train split: 34252030 examples [38:09, 43470.13 examples/s]
Generating train split: 34258361 examples [38:09, 42345.33 examples/s]
Generating train split: 34263980 examples [38:09, 26156.02 examples/s]
Generating train split: 34268294 examples [38:09, 25927.46 examples/s]
Generating train split: 34272070 examples [38:10, 18300.51 examples/s]
Generating train split: 34274975 examples [38:10, 17689.56 examples/s]
Generating train split: 34277472 examples [38:10, 18632.84 examples/s]
Generating train split: 34282782 examples [38:10, 24436.53 examples/s]
Generating train split: 34289296 examples [38:10, 32142.67 examples/s]
Generating train split: 34293531 examples [38:11, 23365.18 examples/s]
Generating train split: 34298606 examples [38:11, 28114.23 examples/s]
Generating train split: 34307198 examples [38:11, 39591.66 examples/s]
Generating train split: 34315452 examples [38:11, 48774.08 examples/s]
Generating train split: 34321561 examples [38:11, 47654.08 examples/s]
Generating train split: 34327196 examples [38:12, 27433.27 examples/s]
Generating train split: 34331519 examples [38:12, 24655.39 examples/s]
Generating train split: 34335097 examples [38:12, 19904.80 examples/s]
Generating train split: 34338802 examples [38:12, 22383.72 examples/s]
Generating train split: 34341915 examples [38:12, 17041.50 examples/s]
Generating train split: 34345717 examples [38:13, 20131.96 examples/s]
Generating train split: 34350934 examples [38:13, 25738.32 examples/s]
Generating train split: 34354493 examples [38:13, 19652.39 examples/s]
Generating train split: 34358473 examples [38:13, 22962.85 examples/s]
Generating train split: 34361640 examples [38:13, 23637.94 examples/s]
Generating train split: 34364641 examples [38:13, 21700.72 examples/s]
Generating train split: 34367257 examples [38:14, 18204.51 examples/s]
Generating train split: 34369633 examples [38:14, 19265.15 examples/s]
Generating train split: 34377719 examples [38:14, 32505.17 examples/s]
Generating train split: 34386779 examples [38:14, 46154.63 examples/s]
Generating train split: 34392297 examples [38:14, 47210.95 examples/s]
Generating train split: 34401311 examples [38:14, 58340.47 examples/s]
Generating train split: 34408636 examples [38:14, 62194.96 examples/s]
Generating train split: 34415335 examples [38:15, 26237.58 examples/s]
Generating train split: 34420352 examples [38:15, 20320.01 examples/s]
Generating train split: 34424219 examples [38:16, 16868.48 examples/s]
Generating train split: 34427235 examples [38:16, 17010.42 examples/s]
Generating train split: 34429875 examples [38:16, 17306.03 examples/s]
Generating train split: 34438341 examples [38:16, 27501.77 examples/s]
Generating train split: 34446632 examples [38:16, 37350.27 examples/s]
Generating train split: 34452076 examples [38:16, 27335.39 examples/s]
Generating train split: 34461347 examples [38:17, 37948.29 examples/s]
Generating train split: 34467142 examples [38:17, 38655.85 examples/s]
Generating train split: 34475324 examples [38:17, 47258.54 examples/s]
Generating train split: 34484452 examples [38:17, 57020.82 examples/s]
Generating train split: 34491504 examples [38:17, 34994.77 examples/s]
Generating train split: 34496964 examples [38:18, 21911.65 examples/s]
Generating train split: 34501089 examples [38:18, 21476.85 examples/s]
Generating train split: 34504571 examples [38:18, 19743.58 examples/s]
Generating train split: 34507496 examples [38:18, 21052.01 examples/s]
Generating train split: 34512057 examples [38:19, 24603.98 examples/s]
Generating train split: 34515311 examples [38:19, 21923.89 examples/s]
Generating train split: 34518717 examples [38:19, 24150.06 examples/s]
Generating train split: 34521786 examples [38:19, 25506.62 examples/s]
Generating train split: 34525745 examples [38:19, 28305.90 examples/s]
Generating train split: 34528966 examples [38:19, 16909.78 examples/s]
Generating train split: 34531645 examples [38:20, 18440.86 examples/s]
Generating train split: 34535686 examples [38:20, 22652.72 examples/s]
Generating train split: 34542868 examples [38:20, 33229.02 examples/s]
Generating train split: 34549618 examples [38:20, 40957.09 examples/s]
Generating train split: 34554550 examples [38:20, 24903.04 examples/s]
Generating train split: 34558383 examples [38:21, 17970.42 examples/s]
Generating train split: 34561352 examples [38:21, 17393.08 examples/s]
Generating train split: 34563896 examples [38:21, 17249.95 examples/s]
Generating train split: 34566187 examples [38:21, 17173.68 examples/s]
Generating train split: 34568291 examples [38:22, 10576.46 examples/s]
Generating train split: 34569898 examples [38:22, 9330.68 examples/s] 
Generating train split: 34571210 examples [38:22, 8345.98 examples/s]
Generating train split: 34572695 examples [38:22, 9265.42 examples/s]
Generating train split: 34573901 examples [38:23, 6053.06 examples/s]
Generating train split: 34575282 examples [38:23, 7048.48 examples/s]
Generating train split: 34576369 examples [38:23, 7641.19 examples/s]
Generating train split: 34577440 examples [38:23, 5052.39 examples/s]
Generating train split: 34579811 examples [38:23, 7633.82 examples/s]
Generating train split: 34581105 examples [38:24, 5603.52 examples/s]
Generating train split: 34582100 examples [38:24, 5777.33 examples/s]
Generating train split: 34583738 examples [38:24, 7352.21 examples/s]
Generating train split: 34585667 examples [38:24, 9451.94 examples/s]
Generating train split: 34587009 examples [38:24, 10167.70 examples/s]
Generating train split: 34589933 examples [38:24, 14289.72 examples/s]
Generating train split: 34593890 examples [38:24, 20348.40 examples/s]
Generating train split: 34603162 examples [38:25, 38795.65 examples/s]
Generating train split: 34612512 examples [38:25, 53400.67 examples/s]
Generating train split: 34618455 examples [38:25, 35354.86 examples/s]
Generating train split: 34623211 examples [38:25, 21691.82 examples/s]
Generating train split: 34626849 examples [38:26, 19043.51 examples/s]
Generating train split: 34630155 examples [38:26, 21002.60 examples/s]
Generating train split: 34637269 examples [38:26, 29342.97 examples/s]
Generating train split: 34644744 examples [38:26, 38062.39 examples/s]
Generating train split: 34649977 examples [38:26, 24803.36 examples/s]
Generating train split: 34654023 examples [38:27, 18390.79 examples/s]
Generating train split: 34657369 examples [38:27, 20365.38 examples/s]
Generating train split: 34663093 examples [38:27, 25567.91 examples/s]
Generating train split: 34666822 examples [38:27, 24773.23 examples/s]
Generating train split: 34670118 examples [38:27, 25911.07 examples/s]
Generating train split: 34673345 examples [38:27, 25671.74 examples/s]
Generating train split: 34676975 examples [38:28, 27941.90 examples/s]
Generating train split: 34680160 examples [38:28, 23065.40 examples/s]
Generating train split: 34682859 examples [38:28, 18780.37 examples/s]
Generating train split: 34685101 examples [38:28, 19269.24 examples/s]
Generating train split: 34688259 examples [38:28, 21880.28 examples/s]
Generating train split: 34690754 examples [38:28, 18620.11 examples/s]
Generating train split: 34693241 examples [38:28, 19921.89 examples/s]
Generating train split: 34695577 examples [38:29, 20347.21 examples/s]
Generating train split: 34697790 examples [38:29, 19044.72 examples/s]
Generating train split: 34700529 examples [38:29, 20960.06 examples/s]
Generating train split: 34702765 examples [38:29, 18517.49 examples/s]
Generating train split: 34705419 examples [38:29, 20434.47 examples/s]
Generating train split: 34707706 examples [38:29, 20358.13 examples/s]
Generating train split: 34709842 examples [38:29, 19641.62 examples/s]
Generating train split: 34711879 examples [38:29, 16404.73 examples/s]
Generating train split: 34713644 examples [38:30, 15696.43 examples/s]
Generating train split: 34715457 examples [38:30, 16280.37 examples/s]
Generating train split: 34717159 examples [38:30, 16441.94 examples/s]
Generating train split: 34719899 examples [38:30, 19360.32 examples/s]
Generating train split: 34724789 examples [38:30, 27528.04 examples/s]
Generating train split: 34730254 examples [38:30, 35201.20 examples/s]
Generating train split: 34733904 examples [38:30, 27361.35 examples/s]
Generating train split: 34736998 examples [38:30, 27453.62 examples/s]
Generating train split: 34740163 examples [38:31, 28493.06 examples/s]
Generating train split: 34743258 examples [38:31, 29128.62 examples/s]
Generating train split: 34747065 examples [38:31, 30644.35 examples/s]
Generating train split: 34750239 examples [38:31, 16556.60 examples/s]
Generating train split: 34753039 examples [38:31, 18518.63 examples/s]
Generating train split: 34756231 examples [38:31, 21173.25 examples/s]
Generating train split: 34758982 examples [38:32, 16125.64 examples/s]
Generating train split: 34761199 examples [38:32, 16805.01 examples/s]
Generating train split: 34765728 examples [38:32, 22614.07 examples/s]
Generating train split: 34774546 examples [38:32, 37399.26 examples/s]
Generating train split: 34780494 examples [38:32, 42770.84 examples/s]
Generating train split: 34785537 examples [38:32, 28660.75 examples/s]
Generating train split: 34789541 examples [38:33, 24645.40 examples/s]
Generating train split: 34792862 examples [38:33, 24505.66 examples/s]
Generating train split: 34795918 examples [38:33, 24527.85 examples/s]
Generating train split: 34798898 examples [38:33, 25528.73 examples/s]
Generating train split: 34801788 examples [38:33, 25519.65 examples/s]
Generating train split: 34804578 examples [38:33, 23546.64 examples/s]
Generating train split: 34807113 examples [38:33, 23621.45 examples/s]
Generating train split: 34809608 examples [38:34, 20286.85 examples/s]
Generating train split: 34811796 examples [38:34, 18295.27 examples/s]
Generating train split: 34814062 examples [38:34, 19272.94 examples/s]
Generating train split: 34821573 examples [38:34, 32943.39 examples/s]
Generating train split: 34830963 examples [38:34, 48731.97 examples/s]
Generating train split: 34837935 examples [38:34, 53340.82 examples/s]
Generating train split: 34843660 examples [38:34, 38613.21 examples/s]
Generating train split: 34848367 examples [38:34, 39452.76 examples/s]
Generating train split: 34855660 examples [38:35, 47236.03 examples/s]
Generating train split: 34861044 examples [38:35, 30224.65 examples/s]
Generating train split: 34865272 examples [38:35, 30541.81 examples/s]
Generating train split: 34869185 examples [38:35, 30639.38 examples/s]
Generating train split: 34875386 examples [38:35, 37219.92 examples/s]
Generating train split: 34879818 examples [38:36, 24565.80 examples/s]
Generating train split: 34883295 examples [38:36, 26093.98 examples/s]
Generating train split: 34886731 examples [38:36, 26763.79 examples/s]
Generating train split: 34890005 examples [38:36, 20682.46 examples/s]
Generating train split: 34892663 examples [38:36, 20055.47 examples/s]
Generating train split: 34895077 examples [38:36, 20811.16 examples/s]
Generating train split: 34897862 examples [38:36, 22319.13 examples/s]
Generating train split: 34900380 examples [38:37, 15146.42 examples/s]
Generating train split: 34902382 examples [38:37, 13875.58 examples/s]
Generating train split: 34904111 examples [38:37, 9949.39 examples/s] 
Generating train split: 34905894 examples [38:37, 11143.44 examples/s]
Generating train split: 34907376 examples [38:38, 9783.43 examples/s] 
Generating train split: 34908639 examples [38:38, 8856.38 examples/s]
Generating train split: 34909922 examples [38:38, 9550.31 examples/s]
Generating train split: 34911064 examples [38:38, 9150.01 examples/s]
Generating train split: 34912723 examples [38:38, 10538.05 examples/s]
Generating train split: 34913907 examples [38:38, 10100.90 examples/s]
Generating train split: 34915008 examples [38:38, 10171.61 examples/s]
Generating train split: 34916252 examples [38:38, 10716.85 examples/s]
Generating train split: 34917898 examples [38:39, 12174.43 examples/s]
Generating train split: 34919180 examples [38:39, 12254.46 examples/s]
Generating train split: 34922147 examples [38:39, 16338.69 examples/s]
Generating train split: 34923937 examples [38:39, 16593.39 examples/s]
Generating train split: 34925619 examples [38:39, 13530.19 examples/s]
Generating train split: 34927078 examples [38:39, 11758.47 examples/s]
Generating train split: 34928355 examples [38:39, 10691.61 examples/s]
Generating train split: 34929500 examples [38:40, 9100.33 examples/s] 
Generating train split: 34930493 examples [38:40, 8975.63 examples/s]
Generating train split: 34931448 examples [38:40, 6720.56 examples/s]
Generating train split: 34932230 examples [38:40, 6623.74 examples/s]
Generating train split: 34933530 examples [38:40, 7725.30 examples/s]
Generating train split: 34934392 examples [38:41, 4996.96 examples/s]
Generating train split: 34935972 examples [38:41, 6804.91 examples/s]
Generating train split: 34936917 examples [38:41, 7211.60 examples/s]
Generating train split: 34937845 examples [38:41, 6790.28 examples/s]
Generating train split: 34939455 examples [38:41, 8775.73 examples/s]
Generating train split: 34940697 examples [38:41, 9461.06 examples/s]
Generating train split: 34941945 examples [38:41, 10009.29 examples/s]
Generating train split: 34943060 examples [38:41, 10009.38 examples/s]
Generating train split: 34944136 examples [38:42, 8454.55 examples/s] 
Generating train split: 34945827 examples [38:42, 10100.25 examples/s]
Generating train split: 34946925 examples [38:42, 8482.05 examples/s] 
Generating train split: 34947871 examples [38:42, 8254.93 examples/s]
Generating train split: 34948800 examples [38:42, 8495.53 examples/s]
Generating train split: 34951389 examples [38:42, 12837.07 examples/s]
Generating train split: 34952799 examples [38:42, 12225.77 examples/s]
Generating train split: 34954121 examples [38:43, 9240.10 examples/s] 
Generating train split: 34956431 examples [38:43, 12198.02 examples/s]
Generating train split: 34963883 examples [38:43, 26804.90 examples/s]
Generating train split: 34971225 examples [38:43, 38497.89 examples/s]
Generating train split: 34976436 examples [38:43, 41615.32 examples/s]
Generating train split: 34981756 examples [38:43, 44728.08 examples/s]
Generating train split: 34987942 examples [38:43, 49218.78 examples/s]
Generating train split: 34993151 examples [38:44, 27260.64 examples/s]
Generating train split: 34997193 examples [38:44, 27746.04 examples/s]
Generating train split: 35002416 examples [38:44, 32507.03 examples/s]
Generating train split: 35009325 examples [38:44, 40461.30 examples/s]
Generating train split: 35016894 examples [38:44, 48008.63 examples/s]
Generating train split: 35022507 examples [38:44, 30604.30 examples/s]
Generating train split: 35030851 examples [38:44, 40072.95 examples/s]
Generating train split: 35038326 examples [38:45, 46787.31 examples/s]
Generating train split: 35044407 examples [38:45, 41908.93 examples/s]
Generating train split: 35049645 examples [38:45, 24442.57 examples/s]
Generating train split: 35055723 examples [38:45, 29657.25 examples/s]
Generating train split: 35064580 examples [38:45, 39682.12 examples/s]
Generating train split: 35071250 examples [38:46, 44954.88 examples/s]
Generating train split: 35077374 examples [38:46, 34020.79 examples/s]
Generating train split: 35084419 examples [38:46, 40525.58 examples/s]
Generating train split: 35089958 examples [38:46, 26823.37 examples/s]
Generating train split: 35094370 examples [38:46, 29450.63 examples/s]
Generating train split: 35098696 examples [38:47, 25988.94 examples/s]
Generating train split: 35102293 examples [38:47, 23083.88 examples/s]
Generating train split: 35105969 examples [38:47, 25405.59 examples/s]
Generating train split: 35109297 examples [38:47, 26940.10 examples/s]
Generating train split: 35112555 examples [38:47, 23966.83 examples/s]
Generating train split: 35118345 examples [38:47, 31022.41 examples/s]
Generating train split: 35122039 examples [38:48, 26006.25 examples/s]
Generating train split: 35125164 examples [38:48, 26832.44 examples/s]
Generating train split: 35133123 examples [38:48, 38857.17 examples/s]
Generating train split: 35140033 examples [38:48, 44747.94 examples/s]
Generating train split: 35145036 examples [38:48, 25735.75 examples/s]
Generating train split: 35148906 examples [38:48, 23065.14 examples/s]
Generating train split: 35152131 examples [38:49, 13700.71 examples/s]
Generating train split: 35154552 examples [38:50, 7975.01 examples/s] 
Generating train split: 35156334 examples [38:51, 5808.65 examples/s]
Generating train split: 35157656 examples [38:51, 5719.49 examples/s]
Generating train split: 35158738 examples [38:51, 5077.74 examples/s]
Generating train split: 35159589 examples [38:52, 4179.99 examples/s]
Generating train split: 35160248 examples [38:53, 2609.71 examples/s]
Generating train split: 35160732 examples [38:53, 2522.90 examples/s]
Generating train split: 35161136 examples [38:53, 2632.93 examples/s]
Generating train split: 35161527 examples [38:53, 2713.05 examples/s]
Generating train split: 35162190 examples [38:53, 3226.32 examples/s]
Generating train split: 35163085 examples [38:53, 4123.27 examples/s]
Generating train split: 35163673 examples [38:53, 4378.95 examples/s]
Generating train split: 35164250 examples [38:53, 4579.21 examples/s]
Generating train split: 35164815 examples [38:54, 4150.22 examples/s]
Generating train split: 35165311 examples [38:54, 4312.28 examples/s]
Generating train split: 35165805 examples [38:54, 4216.94 examples/s]
Generating train split: 35166312 examples [38:54, 4361.50 examples/s]
Generating train split: 35167244 examples [38:54, 5617.09 examples/s]
Generating train split: 35167890 examples [38:54, 5799.39 examples/s]
Generating train split: 35168508 examples [38:54, 4611.85 examples/s]
Generating train split: 35169240 examples [38:54, 5240.18 examples/s]
Generating train split: 35169826 examples [38:55, 4919.29 examples/s]
Generating train split: 35170365 examples [38:55, 4781.28 examples/s]
Generating train split: 35170875 examples [38:55, 4319.68 examples/s]
Generating train split: 35171737 examples [38:55, 5351.05 examples/s]
Generating train split: 35172316 examples [38:55, 4257.16 examples/s]
Generating train split: 35172805 examples [38:55, 3684.38 examples/s]
Generating train split: 35173478 examples [38:55, 4316.77 examples/s]
Generating train split: 35174362 examples [38:56, 5344.64 examples/s]
Generating train split: 35174973 examples [38:56, 4094.13 examples/s]
Generating train split: 35175478 examples [38:56, 3857.74 examples/s]
Generating train split: 35176198 examples [38:56, 4547.32 examples/s]
Generating train split: 35176775 examples [38:56, 4825.45 examples/s]
Generating train split: 35177570 examples [38:56, 5594.72 examples/s]
Generating train split: 35178190 examples [38:56, 5723.46 examples/s]
Generating train split: 35184128 examples [38:56, 20239.92 examples/s]
Generating train split: 35190710 examples [38:57, 32937.30 examples/s]
Generating train split: 35194232 examples [38:57, 28192.96 examples/s]
Generating train split: 35197329 examples [38:57, 19758.11 examples/s]
Generating train split: 35199829 examples [38:57, 15103.71 examples/s]
Generating train split: 35201836 examples [38:57, 14185.93 examples/s]
Generating train split: 35203593 examples [38:58, 12745.73 examples/s]
Generating train split: 35205104 examples [38:58, 10946.90 examples/s]
Generating train split: 35206890 examples [38:58, 12103.96 examples/s]
Generating train split: 35208503 examples [38:58, 12908.91 examples/s]
Generating train split: 35209974 examples [38:58, 11550.25 examples/s]
Generating train split: 35212065 examples [38:58, 13572.63 examples/s]
Generating train split: 35219019 examples [38:58, 26772.25 examples/s]
Generating train split: 35227018 examples [38:59, 40177.73 examples/s]
Generating train split: 35231628 examples [38:59, 32307.97 examples/s]
Generating train split: 35235513 examples [38:59, 25442.28 examples/s]
Generating train split: 35238710 examples [38:59, 18748.84 examples/s]
Generating train split: 35241259 examples [38:59, 17708.64 examples/s]
Generating train split: 35243476 examples [39:00, 13598.79 examples/s]
Generating train split: 35245249 examples [39:00, 13893.70 examples/s]
Generating train split: 35246960 examples [39:00, 10623.22 examples/s]
Generating train split: 35248332 examples [39:00, 10932.79 examples/s]
Generating train split: 35249657 examples [39:00, 10672.00 examples/s]
Generating train split: 35251880 examples [39:01, 12924.04 examples/s]
Generating train split: 35253404 examples [39:01, 10512.08 examples/s]
Generating train split: 35254671 examples [39:01, 9862.21 examples/s] 
Generating train split: 35255889 examples [39:01, 10315.60 examples/s]
Generating train split: 35257052 examples [39:01, 8544.58 examples/s] 
Generating train split: 35258041 examples [39:01, 7169.51 examples/s]
Generating train split: 35259590 examples [39:02, 8761.52 examples/s]
Generating train split: 35260632 examples [39:02, 6740.25 examples/s]
Generating train split: 35261503 examples [39:02, 7097.47 examples/s]
Generating train split: 35262365 examples [39:02, 6812.18 examples/s]
Generating train split: 35263245 examples [39:02, 7237.91 examples/s]
Generating train split: 35264063 examples [39:02, 7209.73 examples/s]
Generating train split: 35266480 examples [39:02, 11361.82 examples/s]
Generating train split: 35273875 examples [39:02, 27579.35 examples/s]
Generating train split: 35278653 examples [39:03, 33025.66 examples/s]
Generating train split: 35282266 examples [39:03, 19078.06 examples/s]
Generating train split: 35285084 examples [39:03, 16046.67 examples/s]
Generating train split: 35287387 examples [39:04, 10143.19 examples/s]
Generating train split: 35289136 examples [39:04, 9784.26 examples/s] 
Generating train split: 35290612 examples [39:04, 9553.70 examples/s]
Generating train split: 35292378 examples [39:04, 10723.57 examples/s]
Generating train split: 35294117 examples [39:04, 11890.49 examples/s]
Generating train split: 35296130 examples [39:04, 13490.57 examples/s]
Generating train split: 35297783 examples [39:05, 11770.78 examples/s]
Generating train split: 35299198 examples [39:05, 12160.64 examples/s]
Generating train split: 35300596 examples [39:05, 11277.99 examples/s]
Generating train split: 35303923 examples [39:05, 16250.27 examples/s]
Generating train split: 35306214 examples [39:05, 17303.78 examples/s]
Generating train split: 35308135 examples [39:05, 17296.31 examples/s]
Generating train split: 35310001 examples [39:05, 14033.85 examples/s]
Generating train split: 35311588 examples [39:06, 12700.60 examples/s]
Generating train split: 35319525 examples [39:06, 27522.56 examples/s]
Generating train split: 35327810 examples [39:06, 40847.39 examples/s]
Generating train split: 35332653 examples [39:06, 36703.86 examples/s]
Generating train split: 35336925 examples [39:06, 25685.38 examples/s]
Generating train split: 35340359 examples [39:06, 20126.26 examples/s]
Generating train split: 35343282 examples [39:07, 21620.85 examples/s]
Generating train split: 35352391 examples [39:07, 34827.60 examples/s]
Generating train split: 35362085 examples [39:07, 48095.20 examples/s]
Generating train split: 35368281 examples [39:07, 35502.12 examples/s]
Generating train split: 35373260 examples [39:07, 25588.27 examples/s]
Generating train split: 35377157 examples [39:08, 18465.64 examples/s]
Generating train split: 35380179 examples [39:08, 19781.81 examples/s]
Generating train split: 35384613 examples [39:08, 23521.23 examples/s]
Generating train split: 35393771 examples [39:08, 35685.00 examples/s]
Generating train split: 35402488 examples [39:08, 46143.93 examples/s]
Generating train split: 35408690 examples [39:09, 29998.49 examples/s]
Generating train split: 35413510 examples [39:09, 24276.06 examples/s]
Generating train split: 35417336 examples [39:09, 18777.06 examples/s]
Generating train split: 35420317 examples [39:09, 20039.28 examples/s]
Generating train split: 35423249 examples [39:10, 16627.72 examples/s]
Generating train split: 35425618 examples [39:10, 14222.07 examples/s]
Generating train split: 35427538 examples [39:10, 13900.65 examples/s]
Generating train split: 35430039 examples [39:10, 15479.59 examples/s]
Generating train split: 35431943 examples [39:10, 14006.42 examples/s]
Generating train split: 35436005 examples [39:11, 18954.02 examples/s]
Generating train split: 35442833 examples [39:11, 29318.04 examples/s]
Generating train split: 35452589 examples [39:11, 45067.37 examples/s]
Generating train split: 35458105 examples [39:11, 44468.13 examples/s]
Generating train split: 35463258 examples [39:11, 22945.98 examples/s]
Generating train split: 35467174 examples [39:12, 18328.88 examples/s]
Generating train split: 35470336 examples [39:12, 20106.24 examples/s]
Generating train split: 35473439 examples [39:12, 20363.16 examples/s]
Generating train split: 35477463 examples [39:12, 23156.17 examples/s]
Generating train split: 35483458 examples [39:12, 30373.60 examples/s]
Generating train split: 35493219 examples [39:12, 45082.30 examples/s]
Generating train split: 35499508 examples [39:12, 49305.62 examples/s]
Generating train split: 35505348 examples [39:13, 50418.61 examples/s]
Generating train split: 35513321 examples [39:13, 58078.66 examples/s]
Generating train split: 35519708 examples [39:13, 36029.48 examples/s]
Generating train split: 35524744 examples [39:13, 35813.50 examples/s]
Generating train split: 35529341 examples [39:13, 35922.97 examples/s]
Generating train split: 35533634 examples [39:14, 20666.76 examples/s]
Generating train split: 35537069 examples [39:14, 22641.21 examples/s]
Generating train split: 35540398 examples [39:14, 20340.66 examples/s]
Generating train split: 35543201 examples [39:14, 21367.29 examples/s]
Generating train split: 35545930 examples [39:14, 21768.35 examples/s]
Generating train split: 35548541 examples [39:14, 19465.71 examples/s]
Generating train split: 35551311 examples [39:15, 21089.04 examples/s]
Generating train split: 35553720 examples [39:15, 21419.41 examples/s]
Generating train split: 35558608 examples [39:15, 28033.67 examples/s]
Generating train split: 35561734 examples [39:15, 28651.06 examples/s]
Generating train split: 35564828 examples [39:15, 23878.21 examples/s]
Generating train split: 35567509 examples [39:15, 22806.25 examples/s]
Generating train split: 35569986 examples [39:15, 21049.75 examples/s]
Generating train split: 35574975 examples [39:15, 27853.86 examples/s]
Generating train split: 35580977 examples [39:16, 35952.60 examples/s]
Generating train split: 35587632 examples [39:16, 44039.31 examples/s]
Generating train split: 35592918 examples [39:16, 46434.16 examples/s]
Generating train split: 35597836 examples [39:16, 28925.43 examples/s]
Generating train split: 35601803 examples [39:16, 31036.54 examples/s]
Generating train split: 35605716 examples [39:16, 32549.78 examples/s]
Generating train split: 35610881 examples [39:16, 37087.10 examples/s]
Generating train split: 35616148 examples [39:16, 41024.99 examples/s]
Generating train split: 35620839 examples [39:17, 42587.99 examples/s]
Generating train split: 35627379 examples [39:17, 48851.24 examples/s]
Generating train split: 35635570 examples [39:17, 58154.08 examples/s]
Generating train split: 35641655 examples [39:17, 56318.75 examples/s]
Generating train split: 35647513 examples [39:17, 42032.61 examples/s]
Generating train split: 35652377 examples [39:17, 34642.67 examples/s]
Generating train split: 35662133 examples [39:17, 47634.00 examples/s]
Generating train split: 35671994 examples [39:17, 59243.86 examples/s]
Generating train split: 35679007 examples [39:18, 50378.55 examples/s]
Generating train split: 35687511 examples [39:18, 58073.26 examples/s]
Generating train split: 35694785 examples [39:18, 61586.29 examples/s]
Generating train split: 35701696 examples [39:18, 35539.38 examples/s]
Generating train split: 35707039 examples [39:18, 33446.45 examples/s]
Generating train split: 35711620 examples [39:19, 22119.43 examples/s]
Generating train split: 35715135 examples [39:19, 19795.77 examples/s]
Generating train split: 35718016 examples [39:19, 20295.35 examples/s]
Generating train split: 35720721 examples [39:19, 20916.22 examples/s]
Generating train split: 35726501 examples [39:20, 27603.05 examples/s]
Generating train split: 35730342 examples [39:20, 29825.97 examples/s]
Generating train split: 35735961 examples [39:20, 35815.84 examples/s]
Generating train split: 35741136 examples [39:20, 39711.50 examples/s]
Generating train split: 35746705 examples [39:20, 43845.72 examples/s]
Generating train split: 35751648 examples [39:20, 45336.00 examples/s]
Generating train split: 35760046 examples [39:20, 56079.01 examples/s]
Generating train split: 35765974 examples [39:20, 54763.62 examples/s]
Generating train split: 35771681 examples [39:21, 37535.62 examples/s]
Generating train split: 35776306 examples [39:21, 34926.54 examples/s]
Generating train split: 35781399 examples [39:21, 38214.80 examples/s]
Generating train split: 35787161 examples [39:21, 42721.75 examples/s]
Generating train split: 35798591 examples [39:21, 60561.87 examples/s]
Generating train split: 35805371 examples [39:21, 58443.11 examples/s]
Generating train split: 35811731 examples [39:21, 42276.88 examples/s]
Generating train split: 35816926 examples [39:21, 43192.59 examples/s]
Generating train split: 35821954 examples [39:22, 36867.26 examples/s]
Generating train split: 35826252 examples [39:22, 36127.92 examples/s]
Generating train split: 35830271 examples [39:22, 34639.14 examples/s]
Generating train split: 35836232 examples [39:22, 40321.07 examples/s]
Generating train split: 35846349 examples [39:22, 55236.25 examples/s]
Generating train split: 35852463 examples [39:22, 37166.58 examples/s]
Generating train split: 35857356 examples [39:23, 34071.59 examples/s]
Generating train split: 35861595 examples [39:23, 33746.22 examples/s]
Generating train split: 35865551 examples [39:23, 32196.64 examples/s]
Generating train split: 35869155 examples [39:23, 29417.08 examples/s]
Generating train split: 35872371 examples [39:23, 27732.76 examples/s]
Generating train split: 35881180 examples [39:23, 41052.59 examples/s]
Generating train split: 35890086 examples [39:23, 52561.33 examples/s]
Generating train split: 35896057 examples [39:24, 42738.35 examples/s]
Generating train split: 35901101 examples [39:24, 26987.24 examples/s]
Generating train split: 35905024 examples [39:24, 25445.77 examples/s]
Generating train split: 35908400 examples [39:24, 22529.76 examples/s]
Generating train split: 35911241 examples [39:25, 17858.62 examples/s]
Generating train split: 35916214 examples [39:25, 22777.22 examples/s]
Generating train split: 35919313 examples [39:25, 17155.10 examples/s]
Generating train split: 35921759 examples [39:25, 18180.02 examples/s]
Generating train split: 35925540 examples [39:25, 21707.37 examples/s]
Generating train split: 35929843 examples [39:25, 26062.31 examples/s]
Generating train split: 35933123 examples [39:26, 21786.63 examples/s]
Generating train split: 35935867 examples [39:26, 18801.65 examples/s]
Generating train split: 35942700 examples [39:26, 28316.70 examples/s]
Generating train split: 35951508 examples [39:26, 41181.68 examples/s]
Generating train split: 35957149 examples [39:26, 44412.19 examples/s]
Generating train split: 35962441 examples [39:26, 35328.79 examples/s]
Generating train split: 35966852 examples [39:27, 26675.76 examples/s]
Generating train split: 35970395 examples [39:27, 17664.52 examples/s]
Generating train split: 35973415 examples [39:27, 19394.47 examples/s]
Generating train split: 35976618 examples [39:27, 21457.66 examples/s]
Generating train split: 35979546 examples [39:28, 17924.09 examples/s]
Generating train split: 35983452 examples [39:28, 21621.48 examples/s]
Generating train split: 35986312 examples [39:28, 20663.18 examples/s]
Generating train split: 35988859 examples [39:28, 20951.41 examples/s]
Generating train split: 35992358 examples [39:28, 24032.84 examples/s]
Generating train split: 35998176 examples [39:28, 32188.19 examples/s]
Generating train split: 36003355 examples [39:28, 37171.96 examples/s]
Generating train split: 36008507 examples [39:28, 40974.20 examples/s]
Generating train split: 36012936 examples [39:28, 40162.06 examples/s]
Generating train split: 36017187 examples [39:29, 28322.57 examples/s]
Generating train split: 36023703 examples [39:29, 36180.68 examples/s]
Generating train split: 36031205 examples [39:29, 45261.64 examples/s]
Generating train split: 36039328 examples [39:29, 54264.94 examples/s]
Generating train split: 36045496 examples [39:29, 41137.96 examples/s]
Generating train split: 36050581 examples [39:29, 35582.91 examples/s]
Generating train split: 36054914 examples [39:30, 24703.51 examples/s]
Generating train split: 36058592 examples [39:30, 26496.69 examples/s]
Generating train split: 36062037 examples [39:30, 26211.58 examples/s]
Generating train split: 36065238 examples [39:30, 27346.10 examples/s]
Generating train split: 36068413 examples [39:30, 27830.05 examples/s]
Generating train split: 36073093 examples [39:30, 32330.40 examples/s]
Generating train split: 36076673 examples [39:30, 32027.50 examples/s]
Generating train split: 36080115 examples [39:31, 31865.05 examples/s]
Generating train split: 36083472 examples [39:31, 25135.44 examples/s]
Generating train split: 36087222 examples [39:31, 27936.56 examples/s]
Generating train split: 36090332 examples [39:31, 23120.50 examples/s]
Generating train split: 36092983 examples [39:31, 13288.32 examples/s]
Generating train split: 36095016 examples [39:32, 11074.61 examples/s]
Generating train split: 36096639 examples [39:32, 9941.87 examples/s] 
Generating train split: 36098214 examples [39:32, 10782.65 examples/s]
Generating train split: 36099628 examples [39:32, 11341.59 examples/s]
Generating train split: 36101047 examples [39:32, 11110.16 examples/s]
Generating train split: 36102634 examples [39:32, 12088.04 examples/s]
Generating train split: 36104024 examples [39:33, 12376.59 examples/s]
Generating train split: 36105814 examples [39:33, 13725.13 examples/s]
Generating train split: 36107317 examples [39:33, 13749.12 examples/s]
Generating train split: 36110258 examples [39:33, 17833.31 examples/s]
Generating train split: 36112186 examples [39:33, 17796.21 examples/s]
Generating train split: 36114620 examples [39:33, 19593.94 examples/s]
Generating train split: 36116865 examples [39:33, 20401.53 examples/s]
Generating train split: 36119497 examples [39:33, 21930.85 examples/s]
Generating train split: 36121744 examples [39:34, 13965.72 examples/s]
Generating train split: 36123535 examples [39:34, 13126.03 examples/s]
Generating train split: 36126187 examples [39:34, 15915.47 examples/s]
Generating train split: 36133244 examples [39:34, 28448.46 examples/s]
Generating train split: 36142798 examples [39:34, 44994.38 examples/s]
Generating train split: 36148091 examples [39:34, 29142.60 examples/s]
Generating train split: 36154166 examples [39:34, 35040.42 examples/s]
Generating train split: 36161201 examples [39:35, 42487.82 examples/s]
Generating train split: 36166626 examples [39:35, 27490.91 examples/s]
Generating train split: 36170864 examples [39:35, 27284.87 examples/s]
Generating train split: 36181866 examples [39:35, 42075.89 examples/s]
Generating train split: 36189779 examples [39:35, 49610.87 examples/s]
Generating train split: 36196310 examples [39:36, 29362.29 examples/s]
Generating train split: 36201314 examples [39:36, 30767.64 examples/s]
Generating train split: 36208348 examples [39:36, 37475.18 examples/s]
Generating train split: 36216160 examples [39:36, 45302.82 examples/s]
Generating train split: 36222215 examples [39:36, 42654.59 examples/s]
Generating train split: 36227563 examples [39:37, 30563.38 examples/s]
Generating train split: 36235397 examples [39:37, 38787.13 examples/s]
Generating train split: 36241552 examples [39:37, 43265.86 examples/s]
Generating train split: 36247121 examples [39:37, 27246.65 examples/s]
Generating train split: 36251422 examples [39:37, 24717.38 examples/s]
Generating train split: 36255003 examples [39:38, 23614.26 examples/s]
Generating train split: 36258114 examples [39:38, 18782.50 examples/s]
Generating train split: 36260609 examples [39:38, 16431.25 examples/s]
Generating train split: 36262774 examples [39:38, 17220.91 examples/s]
Generating train split: 36264872 examples [39:38, 16845.35 examples/s]
Generating train split: 36267337 examples [39:38, 18357.36 examples/s]
Generating train split: 36269438 examples [39:39, 15728.93 examples/s]
Generating train split: 36271233 examples [39:39, 12090.53 examples/s]
Generating train split: 36272690 examples [39:39, 12474.07 examples/s]
Generating train split: 36274698 examples [39:39, 14018.44 examples/s]
Generating train split: 36276319 examples [39:39, 14177.16 examples/s]
Generating train split: 36277894 examples [39:39, 13735.19 examples/s]
Generating train split: 36279372 examples [39:40, 12868.34 examples/s]
Generating train split: 36281446 examples [39:40, 14761.34 examples/s]
Generating train split: 36283504 examples [39:40, 16257.32 examples/s]
Generating train split: 36285226 examples [39:40, 15480.88 examples/s]
Generating train split: 36294358 examples [39:40, 35538.79 examples/s]
Generating train split: 36299852 examples [39:40, 38712.56 examples/s]
Generating train split: 36303934 examples [39:40, 27956.96 examples/s]
Generating train split: 36307289 examples [39:41, 21177.45 examples/s]
Generating train split: 36310007 examples [39:41, 18270.68 examples/s]
Generating train split: 36316689 examples [39:41, 26835.35 examples/s]
Generating train split: 36325154 examples [39:41, 38470.13 examples/s]
Generating train split: 36330211 examples [39:42, 19399.47 examples/s]
Generating train split: 36334006 examples [39:42, 15433.66 examples/s]
Generating train split: 36336934 examples [39:42, 16286.28 examples/s]
Generating train split: 36345157 examples [39:42, 25338.58 examples/s]
Generating train split: 36353099 examples [39:42, 34202.70 examples/s]
Generating train split: 36358516 examples [39:43, 23281.29 examples/s]
Generating train split: 36362685 examples [39:43, 21101.29 examples/s]
Generating train split: 36366089 examples [39:43, 19366.73 examples/s]
Generating train split: 36372745 examples [39:43, 26271.13 examples/s]
Generating train split: 36381690 examples [39:43, 37143.07 examples/s]
Generating train split: 36387138 examples [39:44, 21665.83 examples/s]
Generating train split: 36391257 examples [39:44, 18753.00 examples/s]
Generating train split: 36394532 examples [39:45, 12609.91 examples/s]
Generating train split: 36396981 examples [39:45, 12500.31 examples/s]
Generating train split: 36399286 examples [39:45, 13701.93 examples/s]
Generating train split: 36401444 examples [39:46, 11856.03 examples/s]
Generating train split: 36403188 examples [39:46, 12333.62 examples/s]
Generating train split: 36404857 examples [39:46, 12270.61 examples/s]
Generating train split: 36406878 examples [39:46, 13672.91 examples/s]
Generating train split: 36408548 examples [39:46, 13200.02 examples/s]
Generating train split: 36410076 examples [39:46, 11365.60 examples/s]
Generating train split: 36411390 examples [39:46, 10733.68 examples/s]
Generating train split: 36413108 examples [39:46, 12073.93 examples/s]
Generating train split: 36414459 examples [39:47, 9141.32 examples/s] 
Generating train split: 36416028 examples [39:47, 10410.56 examples/s]
Generating train split: 36418419 examples [39:47, 13334.78 examples/s]
Generating train split: 36420312 examples [39:47, 14549.15 examples/s]
Generating train split: 36421979 examples [39:47, 10942.56 examples/s]
Generating train split: 36423343 examples [39:47, 9936.13 examples/s] 
Generating train split: 36424910 examples [39:48, 11042.72 examples/s]
Generating train split: 36426212 examples [39:48, 8277.10 examples/s] 
Generating train split: 36427852 examples [39:48, 9749.34 examples/s]
Generating train split: 36429072 examples [39:48, 9225.16 examples/s]
Generating train split: 36431812 examples [39:48, 13080.15 examples/s]
Generating train split: 36433393 examples [39:48, 12133.33 examples/s]
Generating train split: 36435108 examples [39:48, 13227.20 examples/s]
Generating train split: 36436614 examples [39:49, 13042.54 examples/s]
Generating train split: 36438044 examples [39:49, 11620.63 examples/s]
Generating train split: 36439328 examples [39:49, 11905.63 examples/s]
Generating train split: 36440610 examples [39:49, 11907.36 examples/s]
Generating train split: 36441857 examples [39:49, 10978.81 examples/s]
Generating train split: 36444181 examples [39:49, 13503.08 examples/s]
Generating train split: 36445581 examples [39:49, 12935.81 examples/s]
Generating train split: 36447264 examples [39:49, 13940.56 examples/s]
Generating train split: 36451393 examples [39:50, 21305.36 examples/s]
Generating train split: 36453632 examples [39:50, 16677.97 examples/s]
Generating train split: 36456048 examples [39:50, 18432.28 examples/s]
Generating train split: 36459279 examples [39:50, 21911.97 examples/s]
Generating train split: 36463422 examples [39:50, 27063.61 examples/s]
Generating train split: 36468300 examples [39:50, 32945.10 examples/s]
Generating train split: 36474457 examples [39:50, 40972.00 examples/s]
Generating train split: 36479019 examples [39:50, 42286.17 examples/s]
Generating train split: 36483401 examples [39:50, 35636.74 examples/s]
Generating train split: 36487259 examples [39:51, 33388.89 examples/s]
Generating train split: 36490806 examples [39:51, 27732.05 examples/s]
Generating train split: 36496556 examples [39:51, 34496.66 examples/s]
Generating train split: 36500418 examples [39:51, 32628.56 examples/s]
Generating train split: 36504327 examples [39:51, 34200.97 examples/s]
Generating train split: 36509131 examples [39:51, 37771.40 examples/s]
Generating train split: 36513639 examples [39:51, 36428.37 examples/s]
Generating train split: 36517614 examples [39:51, 37284.05 examples/s]
Generating train split: 36525508 examples [39:52, 48586.48 examples/s]
Generating train split: 36531521 examples [39:52, 51802.37 examples/s]
Generating train split: 36538071 examples [39:52, 55681.73 examples/s]
Generating train split: 36543788 examples [39:52, 37243.42 examples/s]
Generating train split: 36548410 examples [39:52, 38818.01 examples/s]
Generating train split: 36553942 examples [39:52, 42671.65 examples/s]
Generating train split: 36560479 examples [39:52, 48344.45 examples/s]
Generating train split: 36566181 examples [39:52, 50627.03 examples/s]
Generating train split: 36571649 examples [39:53, 39074.35 examples/s]
Generating train split: 36577452 examples [39:53, 43324.07 examples/s]
Generating train split: 36582384 examples [39:53, 37666.11 examples/s]
Generating train split: 36589382 examples [39:53, 44987.48 examples/s]
Generating train split: 36594489 examples [39:53, 46467.79 examples/s]
Generating train split: 36599588 examples [39:54, 27818.44 examples/s]
Generating train split: 36603574 examples [39:54, 27904.52 examples/s]
Generating train split: 36608665 examples [39:54, 32301.77 examples/s]
Generating train split: 36613234 examples [39:54, 35171.29 examples/s]
Generating train split: 36619504 examples [39:54, 41618.49 examples/s]
Generating train split: 36627505 examples [39:54, 51241.55 examples/s]
Generating train split: 36633294 examples [39:54, 52413.79 examples/s]
Generating train split: 36639012 examples [39:54, 50250.06 examples/s]
Generating train split: 36644383 examples [39:54, 43725.69 examples/s]
Generating train split: 36649135 examples [39:55, 44247.94 examples/s]
Generating train split: 36654989 examples [39:55, 47929.75 examples/s]
Generating train split: 36660030 examples [39:55, 41325.22 examples/s]
Generating train split: 36664480 examples [39:55, 39058.07 examples/s]
Generating train split: 36668839 examples [39:55, 39903.92 examples/s]
Generating train split: 36673001 examples [39:55, 38373.52 examples/s]
Generating train split: 36676955 examples [39:55, 37297.17 examples/s]
Generating train split: 36681396 examples [39:55, 39170.79 examples/s]
Generating train split: 36688297 examples [39:56, 47320.91 examples/s]
Generating train split: 36694257 examples [39:56, 50768.83 examples/s]
Generating train split: 36702603 examples [39:56, 60128.98 examples/s]
Generating train split: 36710330 examples [39:56, 65105.58 examples/s]
Generating train split: 36716948 examples [39:56, 45422.42 examples/s]
Generating train split: 36724444 examples [39:56, 52048.39 examples/s]
Generating train split: 36730488 examples [39:56, 34959.24 examples/s]
Generating train split: 36735288 examples [39:57, 35321.06 examples/s]
Generating train split: 36739738 examples [39:57, 36684.91 examples/s]
Generating train split: 36749289 examples [39:57, 49555.04 examples/s]
Generating train split: 36755219 examples [39:57, 29272.15 examples/s]
Generating train split: 36762400 examples [39:57, 36118.28 examples/s]
Generating train split: 36769863 examples [39:57, 43314.31 examples/s]
Generating train split: 36775851 examples [39:58, 44274.60 examples/s]
Generating train split: 36781463 examples [39:58, 40930.41 examples/s]
Generating train split: 36786407 examples [39:58, 33316.63 examples/s]
Generating train split: 36790509 examples [39:58, 31044.04 examples/s]
Generating train split: 36796255 examples [39:58, 36277.22 examples/s]
Generating train split: 36804739 examples [39:58, 46982.99 examples/s]
Generating train split: 36811873 examples [39:58, 52820.67 examples/s]
Generating train split: 36818422 examples [39:59, 56025.53 examples/s]
Generating train split: 36826333 examples [39:59, 62168.64 examples/s]
Generating train split: 36833029 examples [39:59, 63134.39 examples/s]
Generating train split: 36840792 examples [39:59, 67203.90 examples/s]
Generating train split: 36847785 examples [39:59, 65223.82 examples/s]
Generating train split: 36854927 examples [39:59, 66959.87 examples/s]
Generating train split: 36861782 examples [39:59, 67115.70 examples/s]
Generating train split: 36869356 examples [39:59, 69593.66 examples/s]
Generating train split: 36876551 examples [39:59, 70267.28 examples/s]
Generating train split: 36883637 examples [39:59, 67874.74 examples/s]
Generating train split: 36890487 examples [40:00, 67921.90 examples/s]
Generating train split: 36897324 examples [40:00, 67077.68 examples/s]
Generating train split: 36904570 examples [40:00, 68592.89 examples/s]
Generating train split: 36911467 examples [40:00, 68096.27 examples/s]
Generating train split: 36918298 examples [40:00, 68064.65 examples/s]
Generating train split: 36925123 examples [40:00, 64449.12 examples/s]
Generating train split: 36931613 examples [40:00, 64161.12 examples/s]
Generating train split: 36938070 examples [40:00, 59557.87 examples/s]
Generating train split: 36944105 examples [40:01, 33162.57 examples/s]
Generating train split: 36948795 examples [40:01, 35465.02 examples/s]
Generating train split: 36953449 examples [40:01, 36682.86 examples/s]
Generating train split: 36957932 examples [40:01, 38389.21 examples/s]
Generating train split: 36962402 examples [40:01, 39855.46 examples/s]
Generating train split: 36969019 examples [40:01, 46538.33 examples/s]
Generating train split: 36976849 examples [40:01, 54995.97 examples/s]
Generating train split: 36982774 examples [40:02, 28591.65 examples/s]
Generating train split: 36987326 examples [40:02, 25565.84 examples/s]
Generating train split: 36995471 examples [40:02, 34647.07 examples/s]
Generating train split: 37005120 examples [40:02, 46294.34 examples/s]
Generating train split: 37011569 examples [40:03, 30871.65 examples/s]
Generating train split: 37016575 examples [40:03, 25099.58 examples/s]
Generating train split: 37020542 examples [40:03, 20539.45 examples/s]
Generating train split: 37023683 examples [40:03, 20382.50 examples/s]
Generating train split: 37026486 examples [40:04, 20891.15 examples/s]
Generating train split: 37029141 examples [40:04, 17621.98 examples/s]
Generating train split: 37031336 examples [40:04, 15567.54 examples/s]
Generating train split: 37034595 examples [40:04, 18409.73 examples/s]
Generating train split: 37036882 examples [40:04, 15474.77 examples/s]
Generating train split: 37039414 examples [40:04, 17228.04 examples/s]
Generating train split: 37041500 examples [40:05, 14330.13 examples/s]
Generating train split: 37043237 examples [40:05, 11622.61 examples/s]
Generating train split: 37044663 examples [40:05, 8824.81 examples/s] 
Generating train split: 37046478 examples [40:05, 10219.94 examples/s]
Generating train split: 37047803 examples [40:06, 8466.06 examples/s] 
Generating train split: 37049481 examples [40:06, 9800.70 examples/s]
Generating train split: 37050729 examples [40:06, 6946.45 examples/s]
Generating train split: 37051748 examples [40:06, 7453.16 examples/s]
Generating train split: 37053468 examples [40:06, 9199.95 examples/s]
Generating train split: 37054672 examples [40:06, 8276.89 examples/s]
Generating train split: 37055707 examples [40:07, 6198.23 examples/s]
Generating train split: 37056542 examples [40:07, 6237.38 examples/s]
Generating train split: 37058488 examples [40:07, 8703.08 examples/s]
Generating train split: 37059611 examples [40:07, 7998.75 examples/s]
Generating train split: 37060591 examples [40:07, 8345.04 examples/s]
Generating train split: 37061977 examples [40:07, 9597.68 examples/s]
Generating train split: 37063673 examples [40:07, 11370.97 examples/s]
Generating train split: 37064945 examples [40:08, 11194.69 examples/s]
Generating train split: 37066174 examples [40:08, 8210.77 examples/s] 
Generating train split: 37067177 examples [40:08, 6017.50 examples/s]
Generating train split: 37067980 examples [40:08, 6234.53 examples/s]
Generating train split: 37068756 examples [40:08, 5689.54 examples/s]
Generating train split: 37069955 examples [40:08, 6921.34 examples/s]
Generating train split: 37071433 examples [40:09, 8624.69 examples/s]
Generating train split: 37072538 examples [40:09, 9196.52 examples/s]
Generating train split: 37074596 examples [40:09, 12066.37 examples/s]
Generating train split: 37077537 examples [40:09, 16617.40 examples/s]
Generating train split: 37079357 examples [40:09, 16868.37 examples/s]
Generating train split: 37081161 examples [40:09, 16531.00 examples/s]
Generating train split: 37083738 examples [40:09, 19086.02 examples/s]
Generating train split: 37085721 examples [40:09, 16216.75 examples/s]
Generating train split: 37087475 examples [40:10, 13935.60 examples/s]
Generating train split: 37090062 examples [40:10, 16533.39 examples/s]
Generating train split: 37094652 examples [40:10, 23820.29 examples/s]
Generating train split: 37102644 examples [40:10, 38507.29 examples/s]
Generating train split: 37109065 examples [40:10, 45312.87 examples/s]
Generating train split: 37113947 examples [40:10, 27131.49 examples/s]
Generating train split: 37117773 examples [40:11, 22778.67 examples/s]
Generating train split: 37120913 examples [40:11, 18066.63 examples/s]
Generating train split: 37123425 examples [40:11, 16070.65 examples/s]
Generating train split: 37125530 examples [40:11, 11853.21 examples/s]
Generating train split: 37128692 examples [40:12, 14531.96 examples/s]
Generating train split: 37130785 examples [40:12, 11350.43 examples/s]
Generating train split: 37132483 examples [40:12, 12152.17 examples/s]
Generating train split: 37134659 examples [40:12, 13747.92 examples/s]
Generating train split: 37136475 examples [40:13, 8702.89 examples/s] 
Generating train split: 37138911 examples [40:13, 10923.26 examples/s]
Generating train split: 37140616 examples [40:13, 11033.74 examples/s]
Generating train split: 37142141 examples [40:13, 9259.10 examples/s] 
Generating train split: 37143397 examples [40:13, 9784.31 examples/s]
Generating train split: 37145219 examples [40:13, 11402.77 examples/s]
Generating train split: 37147071 examples [40:13, 12910.55 examples/s]
Generating train split: 37148614 examples [40:14, 10437.11 examples/s]
Generating train split: 37151453 examples [40:14, 14144.12 examples/s]
Generating train split: 37158677 examples [40:14, 27385.00 examples/s]
Generating train split: 37169347 examples [40:14, 46865.28 examples/s]
Generating train split: 37174919 examples [40:14, 43084.39 examples/s]
Generating train split: 37180421 examples [40:14, 46006.28 examples/s]
Generating train split: 37191139 examples [40:14, 61869.57 examples/s]
Generating train split: 37197956 examples [40:15, 29532.32 examples/s]
Generating train split: 37203112 examples [40:15, 23320.90 examples/s]
Generating train split: 37207148 examples [40:15, 23235.64 examples/s]
Generating train split: 37216676 examples [40:15, 33866.06 examples/s]
Generating train split: 37222179 examples [40:15, 37526.63 examples/s]
Generating train split: 37227541 examples [40:16, 25779.14 examples/s]
Generating train split: 37231720 examples [40:16, 23874.41 examples/s]
Generating train split: 37235217 examples [40:16, 20934.38 examples/s]
Generating train split: 37238094 examples [40:16, 20197.50 examples/s]
Generating train split: 37240639 examples [40:17, 18518.09 examples/s]
Generating train split: 37242897 examples [40:17, 19210.88 examples/s]
Generating train split: 37245359 examples [40:17, 20135.89 examples/s]
Generating train split: 37247627 examples [40:17, 18723.60 examples/s]
Generating train split: 37250047 examples [40:17, 19867.35 examples/s]
Generating train split: 37252774 examples [40:17, 21603.53 examples/s]
Generating train split: 37255104 examples [40:17, 20750.54 examples/s]
Generating train split: 37257295 examples [40:17, 19654.46 examples/s]
Generating train split: 37259350 examples [40:18, 15459.06 examples/s]
Generating train split: 37261071 examples [40:18, 15253.06 examples/s]
Generating train split: 37262718 examples [40:18, 15082.80 examples/s]
Generating train split: 37264478 examples [40:18, 15682.88 examples/s]
Generating train split: 37266131 examples [40:18, 13414.86 examples/s]
Generating train split: 37275202 examples [40:18, 31744.58 examples/s]
Generating train split: 37284644 examples [40:18, 47600.65 examples/s]
Generating train split: 37290085 examples [40:19, 33587.43 examples/s]
Generating train split: 37294487 examples [40:19, 32233.93 examples/s]
Generating train split: 37298439 examples [40:19, 25123.17 examples/s]
Generating train split: 37301648 examples [40:19, 19308.82 examples/s]
Generating train split: 37308792 examples [40:19, 27630.14 examples/s]
Generating train split: 37319071 examples [40:20, 41581.83 examples/s]
Generating train split: 37324907 examples [40:20, 31429.03 examples/s]
Generating train split: 37329577 examples [40:20, 21018.80 examples/s]
Generating train split: 37333146 examples [40:20, 22856.91 examples/s]
Generating train split: 37340891 examples [40:21, 30401.46 examples/s]
Generating train split: 37345262 examples [40:21, 24921.52 examples/s]
Generating train split: 37348805 examples [40:21, 26461.69 examples/s]
Generating train split: 37352869 examples [40:21, 29119.56 examples/s]
Generating train split: 37360000 examples [40:21, 38033.80 examples/s]
Generating train split: 37366746 examples [40:21, 44858.83 examples/s]
Generating train split: 37372074 examples [40:22, 26729.24 examples/s]
Generating train split: 37376205 examples [40:22, 28846.10 examples/s]
Generating train split: 37383719 examples [40:22, 37728.69 examples/s]
Generating train split: 37391728 examples [40:22, 46839.40 examples/s]
Generating train split: 37397691 examples [40:22, 42548.32 examples/s]
Generating train split: 37402897 examples [40:23, 24716.03 examples/s]
Generating train split: 37406889 examples [40:23, 20035.91 examples/s]
Generating train split: 37410049 examples [40:23, 19918.97 examples/s]
Generating train split: 37412845 examples [40:23, 21105.16 examples/s]
Generating train split: 37415766 examples [40:23, 22553.35 examples/s]
Generating train split: 37420857 examples [40:23, 28318.54 examples/s]
Generating train split: 37425083 examples [40:24, 31269.33 examples/s]
Generating train split: 37428774 examples [40:24, 24421.38 examples/s]
Generating train split: 37432353 examples [40:24, 26753.93 examples/s]
Generating train split: 37441110 examples [40:24, 40565.52 examples/s]
Generating train split: 37450919 examples [40:24, 54654.53 examples/s]
Generating train split: 37458781 examples [40:24, 60856.77 examples/s]
Generating train split: 37465586 examples [40:24, 53642.13 examples/s]
Generating train split: 37474281 examples [40:24, 61887.83 examples/s]
Generating train split: 37481098 examples [40:25, 63327.48 examples/s]
Generating train split: 37487892 examples [40:25, 36702.10 examples/s]
Generating train split: 37493193 examples [40:25, 39342.62 examples/s]
Generating train split: 37502275 examples [40:25, 49822.35 examples/s]
Generating train split: 37509343 examples [40:25, 54521.46 examples/s]
Generating train split: 37515936 examples [40:26, 32210.84 examples/s]
Generating train split: 37521021 examples [40:26, 28716.57 examples/s]
Generating train split: 37527615 examples [40:26, 34668.13 examples/s]
Generating train split: 37536131 examples [40:26, 44054.82 examples/s]
Generating train split: 37542126 examples [40:26, 28323.18 examples/s]
Generating train split: 37546751 examples [40:27, 23969.10 examples/s]
Generating train split: 37555124 examples [40:27, 32544.90 examples/s]
Generating train split: 37562189 examples [40:27, 38699.57 examples/s]
Generating train split: 37567790 examples [40:27, 28822.12 examples/s]
Generating train split: 37578225 examples [40:27, 40882.59 examples/s]
Generating train split: 37586450 examples [40:28, 48560.61 examples/s]
Generating train split: 37593277 examples [40:28, 33143.94 examples/s]
Generating train split: 37598590 examples [40:28, 21699.31 examples/s]
Generating train split: 37602617 examples [40:29, 18776.60 examples/s]
Generating train split: 37605800 examples [40:29, 17472.85 examples/s]
Generating train split: 37608440 examples [40:29, 17541.44 examples/s]
Generating train split: 37618069 examples [40:29, 29008.52 examples/s]
Generating train split: 37623547 examples [40:29, 33438.44 examples/s]
Generating train split: 37628379 examples [40:30, 29056.48 examples/s]
Generating train split: 37632400 examples [40:30, 17852.25 examples/s]
Generating train split: 37635454 examples [40:30, 16465.81 examples/s]
Generating train split: 37637979 examples [40:31, 15460.10 examples/s]
Generating train split: 37640364 examples [40:31, 16559.45 examples/s]
Generating train split: 37642537 examples [40:31, 16139.73 examples/s]
Generating train split: 37644502 examples [40:31, 15090.14 examples/s]
Generating train split: 37646244 examples [40:31, 14118.03 examples/s]
Generating train split: 37647814 examples [40:31, 14241.31 examples/s]
Generating train split: 37649360 examples [40:31, 13861.14 examples/s]
Generating train split: 37651176 examples [40:31, 14713.58 examples/s]
Generating train split: 37653108 examples [40:32, 15813.77 examples/s]
Generating train split: 37654769 examples [40:32, 11339.69 examples/s]
Generating train split: 37656126 examples [40:32, 6448.00 examples/s] 
Generating train split: 37657158 examples [40:32, 6264.03 examples/s]
Generating train split: 37659166 examples [40:33, 8247.82 examples/s]
Generating train split: 37660375 examples [40:33, 8848.07 examples/s]
Generating train split: 37664537 examples [40:33, 15379.28 examples/s]
Generating train split: 37668317 examples [40:33, 20348.15 examples/s]
Generating train split: 37675799 examples [40:33, 33442.18 examples/s]
Generating train split: 37682528 examples [40:33, 42096.90 examples/s]
Generating train split: 37687384 examples [40:33, 27451.87 examples/s]
Generating train split: 37691241 examples [40:34, 23270.30 examples/s]
Generating train split: 37697357 examples [40:34, 30020.86 examples/s]
Generating train split: 37706853 examples [40:34, 43192.24 examples/s]
Generating train split: 37712544 examples [40:34, 38971.21 examples/s]
Generating train split: 37717464 examples [40:34, 34504.19 examples/s]
Generating train split: 37722980 examples [40:34, 38696.02 examples/s]
Generating train split: 37727595 examples [40:35, 26246.39 examples/s]
Generating train split: 37734203 examples [40:35, 33127.48 examples/s]
Generating train split: 37741982 examples [40:35, 41960.54 examples/s]
Generating train split: 37748401 examples [40:35, 46854.50 examples/s]
Generating train split: 37754179 examples [40:35, 40519.56 examples/s]
Generating train split: 37762510 examples [40:35, 49875.09 examples/s]
Generating train split: 37769714 examples [40:35, 55101.64 examples/s]
Generating train split: 37776064 examples [40:36, 33556.41 examples/s]
Generating train split: 37781005 examples [40:36, 34334.02 examples/s]
Generating train split: 37786758 examples [40:36, 38768.51 examples/s]
Generating train split: 37794320 examples [40:36, 46673.48 examples/s]
Generating train split: 37801994 examples [40:36, 53707.82 examples/s]
Generating train split: 37808309 examples [40:36, 36679.64 examples/s]
Generating train split: 37813327 examples [40:37, 35184.16 examples/s]
Generating train split: 37817783 examples [40:37, 36275.51 examples/s]
Generating train split: 37822108 examples [40:37, 29595.96 examples/s]
Generating train split: 37825714 examples [40:37, 25276.48 examples/s]
Generating train split: 37829210 examples [40:37, 27037.65 examples/s]
Generating train split: 37832648 examples [40:37, 28566.18 examples/s]
Generating train split: 37835891 examples [40:38, 17700.49 examples/s]
Generating train split: 37838415 examples [40:38, 18479.75 examples/s]
Generating train split: 37842041 examples [40:38, 21718.79 examples/s]
Generating train split: 37844808 examples [40:38, 14541.75 examples/s]
Generating train split: 37846970 examples [40:38, 15156.33 examples/s]
Generating train split: 37849021 examples [40:39, 13144.18 examples/s]
Generating train split: 37850724 examples [40:39, 12568.45 examples/s]
Generating train split: 37853332 examples [40:39, 15054.87 examples/s]
Generating train split: 37861171 examples [40:39, 28245.11 examples/s]
Generating train split: 37870599 examples [40:39, 43381.03 examples/s]
Generating train split: 37875984 examples [40:39, 29753.07 examples/s]
Generating train split: 37880263 examples [40:40, 21658.55 examples/s]
Generating train split: 37883607 examples [40:40, 20289.78 examples/s]
Generating train split: 37886447 examples [40:40, 20872.94 examples/s]
Generating train split: 37891587 examples [40:40, 26329.64 examples/s]
Generating train split: 37899975 examples [40:40, 38049.76 examples/s]
Generating train split: 37904889 examples [40:41, 28768.09 examples/s]
Generating train split: 37908853 examples [40:41, 29732.12 examples/s]
Generating train split: 37916683 examples [40:41, 39640.84 examples/s]
Generating train split: 37923128 examples [40:41, 45105.94 examples/s]
Generating train split: 37928529 examples [40:41, 37328.82 examples/s]
Generating train split: 37940264 examples [40:41, 54561.23 examples/s]
Generating train split: 37951087 examples [40:41, 67179.29 examples/s]
Generating train split: 37959030 examples [40:42, 37707.61 examples/s]
Generating train split: 37965126 examples [40:42, 39270.87 examples/s]
Generating train split: 37970759 examples [40:42, 23598.23 examples/s]
Generating train split: 37975016 examples [40:43, 25384.15 examples/s]
Generating train split: 37982998 examples [40:43, 33470.82 examples/s]
Generating train split: 37991892 examples [40:43, 43183.41 examples/s]
Generating train split: 37998220 examples [40:43, 29214.63 examples/s]
Generating train split: 38006636 examples [40:43, 37468.17 examples/s]
Generating train split: 38013524 examples [40:43, 43003.18 examples/s]
Generating train split: 38019767 examples [40:44, 42774.62 examples/s]
Generating train split: 38030153 examples [40:44, 55468.75 examples/s]
Generating train split: 38037425 examples [40:44, 57356.24 examples/s]
Generating train split: 38044259 examples [40:44, 30906.91 examples/s]
Generating train split: 38049455 examples [40:45, 19156.95 examples/s]
Generating train split: 38053344 examples [40:45, 15790.34 examples/s]
Generating train split: 38056346 examples [40:45, 15879.62 examples/s]
Generating train split: 38058933 examples [40:46, 11382.12 examples/s]
Generating train split: 38060893 examples [40:46, 11354.25 examples/s]
Generating train split: 38062612 examples [40:46, 11711.51 examples/s]
Generating train split: 38064234 examples [40:46, 11851.54 examples/s]
Generating train split: 38066212 examples [40:47, 13091.89 examples/s]
Generating train split: 38067845 examples [40:47, 12906.20 examples/s]
Generating train split: 38069880 examples [40:47, 14405.22 examples/s]
Generating train split: 38071583 examples [40:47, 14872.14 examples/s]
Generating train split: 38073246 examples [40:47, 14779.74 examples/s]
Generating train split: 38077056 examples [40:47, 20555.72 examples/s]
Generating train split: 38082661 examples [40:47, 29864.00 examples/s]
Generating train split: 38085921 examples [40:47, 26588.82 examples/s]
Generating train split: 38090808 examples [40:47, 32216.72 examples/s]
Generating train split: 38094321 examples [40:48, 25754.53 examples/s]
Generating train split: 38101329 examples [40:48, 35867.74 examples/s]
Generating train split: 38108211 examples [40:48, 43962.33 examples/s]
Generating train split: 38113197 examples [40:48, 41351.58 examples/s]
Generating train split: 38117798 examples [40:48, 35073.08 examples/s]
Generating train split: 38122596 examples [40:48, 37920.46 examples/s]
Generating train split: 38126787 examples [40:48, 36979.75 examples/s]
Generating train split: 38130775 examples [40:49, 26702.10 examples/s]
Generating train split: 38134015 examples [40:49, 22792.16 examples/s]
Generating train split: 38139903 examples [40:49, 29685.49 examples/s]
Generating train split: 38145459 examples [40:49, 35232.07 examples/s]
Generating train split: 38152152 examples [40:49, 42642.23 examples/s]
Generating train split: 38158152 examples [40:49, 46988.26 examples/s]
Generating train split: 38165910 examples [40:49, 55055.13 examples/s]
Generating train split: 38172030 examples [40:49, 56733.49 examples/s]
Generating train split: 38180032 examples [40:50, 63259.42 examples/s]
Generating train split: 38190817 examples [40:50, 76021.32 examples/s]
Generating train split: 38199460 examples [40:50, 79008.87 examples/s]
Generating train split: 38207565 examples [40:50, 43442.55 examples/s]
Generating train split: 38213886 examples [40:50, 46324.71 examples/s]
Generating train split: 38222514 examples [40:50, 54585.05 examples/s]
Generating train split: 38229405 examples [40:51, 53411.73 examples/s]
Generating train split: 38236921 examples [40:51, 58441.91 examples/s]
Generating train split: 38245668 examples [40:51, 65651.03 examples/s]
Generating train split: 38252987 examples [40:51, 60943.41 examples/s]
Generating train split: 38261693 examples [40:51, 67510.94 examples/s]
Generating train split: 38270027 examples [40:51, 69879.87 examples/s]
Generating train split: 38277407 examples [40:51, 70653.98 examples/s]
Generating train split: 38286859 examples [40:51, 77266.03 examples/s]
Generating train split: 38294840 examples [40:51, 72122.17 examples/s]
Generating train split: 38302287 examples [40:52, 45014.34 examples/s]
Generating train split: 38308181 examples [40:52, 41325.00 examples/s]
Generating train split: 38313303 examples [40:52, 38923.78 examples/s]
Generating train split: 38317857 examples [40:52, 27463.86 examples/s]
Generating train split: 38321477 examples [40:52, 28646.45 examples/s]
Generating train split: 38325029 examples [40:53, 28945.68 examples/s]
Generating train split: 38328421 examples [40:53, 29490.02 examples/s]
Generating train split: 38331752 examples [40:53, 18643.90 examples/s]
Generating train split: 38335079 examples [40:53, 21008.57 examples/s]
Generating train split: 38338428 examples [40:53, 23370.00 examples/s]
Generating train split: 38341389 examples [40:54, 14463.44 examples/s]
Generating train split: 38343673 examples [40:54, 11219.22 examples/s]
Generating train split: 38345458 examples [40:54, 11263.69 examples/s]
Generating train split: 38347449 examples [40:54, 12515.83 examples/s]
Generating train split: 38349154 examples [40:54, 12578.11 examples/s]
Generating train split: 38353482 examples [40:55, 18485.79 examples/s]
Generating train split: 38357492 examples [40:55, 23130.73 examples/s]
Generating train split: 38360381 examples [40:55, 18530.54 examples/s]
Generating train split: 38365193 examples [40:55, 24526.94 examples/s]
Generating train split: 38368303 examples [40:55, 24683.53 examples/s]
Generating train split: 38371241 examples [40:55, 23424.54 examples/s]
Generating train split: 38375644 examples [40:55, 27212.92 examples/s]
Generating train split: 38381234 examples [40:56, 34168.53 examples/s]
Generating train split: 38386154 examples [40:56, 38017.77 examples/s]
Generating train split: 38391697 examples [40:56, 42696.48 examples/s]
Generating train split: 38397908 examples [40:56, 47906.29 examples/s]
Generating train split: 38402938 examples [40:56, 45294.21 examples/s]
Generating train split: 38408667 examples [40:56, 48576.45 examples/s]
Generating train split: 38414265 examples [40:56, 50631.63 examples/s]
Generating train split: 38419455 examples [40:56, 34990.75 examples/s]
Generating train split: 38423688 examples [40:57, 12391.67 examples/s]
Generating train split: 38426779 examples [40:58, 8910.42 examples/s] 
Generating train split: 38429074 examples [40:59, 8018.82 examples/s]
Generating train split: 38431187 examples [40:59, 9107.42 examples/s]
Generating train split: 38433129 examples [40:59, 10193.79 examples/s]
Generating train split: 38435024 examples [40:59, 10678.71 examples/s]
Generating train split: 38436739 examples [40:59, 11487.47 examples/s]
Generating train split: 38438406 examples [40:59, 10886.82 examples/s]
Generating train split: 38441115 examples [40:59, 13787.66 examples/s]
Generating train split: 38442938 examples [40:59, 12659.00 examples/s]
Generating train split: 38444525 examples [41:00, 10274.58 examples/s]
Generating train split: 38445902 examples [41:00, 10895.79 examples/s]
Generating train split: 38447231 examples [41:00, 9927.89 examples/s] 
Generating train split: 38449399 examples [41:00, 12320.69 examples/s]
Generating train split: 38450858 examples [41:00, 12398.39 examples/s]
Generating train split: 38453377 examples [41:00, 15420.06 examples/s]
Generating train split: 38455596 examples [41:00, 17066.13 examples/s]
Generating train split: 38457475 examples [41:01, 11038.64 examples/s]
Generating train split: 38458964 examples [41:01, 10571.53 examples/s]
Generating train split: 38460652 examples [41:01, 11807.16 examples/s]
Generating train split: 38463063 examples [41:01, 14497.97 examples/s]
Generating train split: 38464785 examples [41:01, 13221.48 examples/s]
Generating train split: 38466315 examples [41:01, 11454.27 examples/s]
Generating train split: 38467812 examples [41:02, 11994.49 examples/s]
Generating train split: 38470329 examples [41:02, 15050.24 examples/s]
Generating train split: 38480719 examples [41:02, 37159.16 examples/s]
Generating train split: 38486481 examples [41:02, 42498.02 examples/s]
Generating train split: 38491218 examples [41:02, 23411.89 examples/s]
Generating train split: 38494872 examples [41:02, 23403.81 examples/s]
Generating train split: 38504014 examples [41:02, 35851.80 examples/s]
Generating train split: 38509134 examples [41:03, 39031.70 examples/s]
Generating train split: 38514185 examples [41:03, 30459.06 examples/s]
Generating train split: 38518302 examples [41:03, 24107.36 examples/s]
Generating train split: 38524898 examples [41:03, 31194.53 examples/s]
Generating train split: 38533010 examples [41:03, 40920.36 examples/s]
Generating train split: 38538456 examples [41:04, 32515.60 examples/s]
Generating train split: 38542899 examples [41:04, 20941.18 examples/s]
Generating train split: 38546306 examples [41:04, 21413.44 examples/s]
Generating train split: 38549394 examples [41:04, 22539.53 examples/s]
Generating train split: 38552399 examples [41:05, 19801.66 examples/s]
Generating train split: 38554934 examples [41:05, 15699.40 examples/s]
Generating train split: 38556972 examples [41:05, 15292.66 examples/s]
Generating train split: 38558810 examples [41:05, 13386.12 examples/s]
Generating train split: 38560550 examples [41:05, 14086.87 examples/s]
Generating train split: 38562838 examples [41:05, 15773.16 examples/s]
Generating train split: 38564650 examples [41:05, 15825.90 examples/s]
Generating train split: 38567427 examples [41:06, 18546.29 examples/s]
Generating train split: 38569472 examples [41:06, 15278.72 examples/s]
Generating train split: 38572195 examples [41:06, 17944.91 examples/s]
Generating train split: 38574239 examples [41:06, 15055.95 examples/s]
Generating train split: 38575987 examples [41:06, 14262.76 examples/s]
Generating train split: 38577581 examples [41:06, 13838.21 examples/s]
Generating train split: 38579075 examples [41:06, 12550.79 examples/s]
Generating train split: 38580423 examples [41:07, 12526.15 examples/s]
Generating train split: 38581731 examples [41:07, 12523.64 examples/s]
Generating train split: 38583186 examples [41:07, 13026.58 examples/s]
Generating train split: 38584947 examples [41:07, 14177.95 examples/s]
Generating train split: 38586410 examples [41:07, 14246.25 examples/s]
Generating train split: 38589046 examples [41:07, 17645.05 examples/s]
Generating train split: 38597422 examples [41:07, 36571.92 examples/s]
Generating train split: 38605530 examples [41:07, 49359.93 examples/s]
Generating train split: 38610588 examples [41:08, 22382.17 examples/s]
Generating train split: 38615826 examples [41:08, 27130.25 examples/s]
Generating train split: 38622554 examples [41:08, 34535.28 examples/s]
Generating train split: 38628073 examples [41:08, 37939.08 examples/s]
Generating train split: 38633059 examples [41:09, 20661.45 examples/s]
Generating train split: 38641914 examples [41:09, 30213.00 examples/s]
Generating train split: 38649669 examples [41:09, 38135.71 examples/s]
Generating train split: 38655713 examples [41:09, 26339.45 examples/s]
Generating train split: 38660375 examples [41:09, 25037.89 examples/s]
Generating train split: 38667824 examples [41:10, 32519.20 examples/s]
Generating train split: 38672799 examples [41:10, 27475.74 examples/s]
Generating train split: 38676842 examples [41:10, 26722.61 examples/s]
Generating train split: 38680483 examples [41:10, 28412.69 examples/s]
Generating train split: 38684073 examples [41:10, 21471.95 examples/s]
Generating train split: 38686957 examples [41:11, 20931.39 examples/s]
Generating train split: 38692943 examples [41:11, 28042.70 examples/s]
Generating train split: 38703537 examples [41:11, 44157.92 examples/s]
Generating train split: 38710315 examples [41:11, 49541.83 examples/s]
Generating train split: 38716339 examples [41:11, 45571.69 examples/s]
Generating train split: 38721703 examples [41:12, 23688.30 examples/s]
Generating train split: 38725761 examples [41:12, 18587.93 examples/s]
Generating train split: 38729062 examples [41:12, 20422.61 examples/s]
Generating train split: 38732265 examples [41:12, 20925.34 examples/s]
Generating train split: 38735197 examples [41:12, 19518.35 examples/s]
Generating train split: 38737723 examples [41:13, 16251.86 examples/s]
Generating train split: 38740336 examples [41:13, 17832.50 examples/s]
Generating train split: 38743071 examples [41:13, 19649.39 examples/s]
Generating train split: 38751782 examples [41:13, 34104.18 examples/s]
Generating train split: 38757436 examples [41:13, 39356.87 examples/s]
Generating train split: 38762123 examples [41:13, 26544.39 examples/s]
Generating train split: 38765839 examples [41:14, 16857.61 examples/s]
Generating train split: 38768678 examples [41:14, 10816.12 examples/s]
Generating train split: 38770805 examples [41:15, 10725.43 examples/s]
Generating train split: 38772610 examples [41:15, 10281.59 examples/s]
Generating train split: 38774137 examples [41:15, 9919.11 examples/s] 
Generating train split: 38775459 examples [41:15, 9007.25 examples/s]
Generating train split: 38777587 examples [41:15, 10857.58 examples/s]
Generating train split: 38779012 examples [41:16, 9299.32 examples/s] 
Generating train split: 38780192 examples [41:16, 8168.89 examples/s]
Generating train split: 38781300 examples [41:16, 8533.74 examples/s]
Generating train split: 38785608 examples [41:16, 15169.32 examples/s]
Generating train split: 38788705 examples [41:16, 16440.59 examples/s]
Generating train split: 38791280 examples [41:16, 18427.99 examples/s]
Generating train split: 38793920 examples [41:16, 20292.26 examples/s]
Generating train split: 38796387 examples [41:16, 21370.70 examples/s]
Generating train split: 38798761 examples [41:17, 21868.67 examples/s]
Generating train split: 38801099 examples [41:17, 20930.94 examples/s]
Generating train split: 38803312 examples [41:17, 18536.25 examples/s]
Generating train split: 38805289 examples [41:17, 18058.30 examples/s]
Generating train split: 38807924 examples [41:17, 20126.85 examples/s]
Generating train split: 38810038 examples [41:17, 18949.71 examples/s]
Generating train split: 38812014 examples [41:17, 17058.36 examples/s]
Generating train split: 38813987 examples [41:17, 16457.75 examples/s]
Generating train split: 38815694 examples [41:18, 13337.08 examples/s]
Generating train split: 38817212 examples [41:18, 13728.95 examples/s]
Generating train split: 38818678 examples [41:18, 11036.58 examples/s]
Generating train split: 38819927 examples [41:18, 11301.37 examples/s]
Generating train split: 38821179 examples [41:18, 11446.18 examples/s]
Generating train split: 38822400 examples [41:18, 9732.98 examples/s] 
Generating train split: 38823463 examples [41:18, 8974.62 examples/s]
Generating train split: 38826703 examples [41:19, 14242.95 examples/s]
Generating train split: 38828331 examples [41:19, 14171.43 examples/s]
Generating train split: 38829893 examples [41:19, 14118.28 examples/s]
Generating train split: 38831403 examples [41:19, 12521.34 examples/s]
Generating train split: 38832754 examples [41:19, 12603.34 examples/s]
Generating train split: 38834487 examples [41:19, 13809.57 examples/s]
Generating train split: 38836045 examples [41:19, 14151.69 examples/s]
Generating train split: 38837511 examples [41:19, 13753.00 examples/s]
Generating train split: 38838933 examples [41:20, 9317.39 examples/s] 
Generating train split: 38841496 examples [41:20, 12708.66 examples/s]
Generating train split: 38845707 examples [41:20, 19390.41 examples/s]
Generating train split: 38849456 examples [41:20, 23483.52 examples/s]
Generating train split: 38854401 examples [41:20, 30152.49 examples/s]
Generating train split: 38857777 examples [41:20, 29491.82 examples/s]
Generating train split: 38863649 examples [41:20, 37272.25 examples/s]
Generating train split: 38867661 examples [41:20, 36202.61 examples/s]
Generating train split: 38871498 examples [41:21, 34523.84 examples/s]
Generating train split: 38875101 examples [41:21, 31310.62 examples/s]
Generating train split: 38882330 examples [41:21, 41761.77 examples/s]
Generating train split: 38888434 examples [41:21, 46902.14 examples/s]
Generating train split: 38893397 examples [41:21, 46243.75 examples/s]
Generating train split: 38898208 examples [41:21, 44723.46 examples/s]
Generating train split: 38902825 examples [41:21, 39543.07 examples/s]
Generating train split: 38909667 examples [41:21, 46910.60 examples/s]
Generating train split: 38914616 examples [41:22, 42236.32 examples/s]
Generating train split: 38921469 examples [41:22, 48883.72 examples/s]
Generating train split: 38928981 examples [41:22, 55840.77 examples/s]
Generating train split: 38936539 examples [41:22, 61254.89 examples/s]
Generating train split: 38942922 examples [41:22, 33536.79 examples/s]
Generating train split: 38947867 examples [41:22, 35610.66 examples/s]
Generating train split: 38952654 examples [41:22, 33206.73 examples/s]
Generating train split: 38960367 examples [41:23, 41971.49 examples/s]
Generating train split: 38966768 examples [41:23, 45897.16 examples/s]
Generating train split: 38972199 examples [41:23, 43925.61 examples/s]
Generating train split: 38977181 examples [41:23, 31656.62 examples/s]
Generating train split: 38981205 examples [41:23, 26863.24 examples/s]
Generating train split: 38984556 examples [41:23, 27804.82 examples/s]
Generating train split: 38987853 examples [41:24, 28783.28 examples/s]
Generating train split: 38991148 examples [41:24, 29303.52 examples/s]
Generating train split: 38999443 examples [41:24, 42196.13 examples/s]
Generating train split: 39006833 examples [41:24, 50299.91 examples/s]
Generating train split: 39012375 examples [41:24, 28562.07 examples/s]
Generating train split: 39016667 examples [41:24, 28205.83 examples/s]
Generating train split: 39020492 examples [41:25, 29913.92 examples/s]
Generating train split: 39028529 examples [41:25, 40388.45 examples/s]
Generating train split: 39036587 examples [41:25, 48296.31 examples/s]
Generating train split: 39042302 examples [41:25, 30525.61 examples/s]
Generating train split: 39046769 examples [41:25, 29930.31 examples/s]
Generating train split: 39050735 examples [41:25, 29084.96 examples/s]
Generating train split: 39055257 examples [41:26, 32202.86 examples/s]
Generating train split: 39063889 examples [41:26, 43911.54 examples/s]
Generating train split: 39070295 examples [41:26, 48527.81 examples/s]
Generating train split: 39075897 examples [41:26, 27910.34 examples/s]
Generating train split: 39080232 examples [41:26, 27878.84 examples/s]
Generating train split: 39084098 examples [41:26, 28658.01 examples/s]
Generating train split: 39090943 examples [41:27, 36478.81 examples/s]
Generating train split: 39095692 examples [41:27, 38331.70 examples/s]
Generating train split: 39100257 examples [41:27, 29330.34 examples/s]
Generating train split: 39103987 examples [41:27, 28566.03 examples/s]
Generating train split: 39107394 examples [41:27, 29694.25 examples/s]
Generating train split: 39116343 examples [41:27, 43343.08 examples/s]
Generating train split: 39124774 examples [41:27, 53409.19 examples/s]
Generating train split: 39130851 examples [41:27, 51475.98 examples/s]
Generating train split: 39136529 examples [41:28, 27859.97 examples/s]
Generating train split: 39140881 examples [41:28, 27786.13 examples/s]
Generating train split: 39144752 examples [41:28, 19763.51 examples/s]
Generating train split: 39147995 examples [41:29, 21552.55 examples/s]
Generating train split: 39151070 examples [41:29, 17735.50 examples/s]
Generating train split: 39153553 examples [41:29, 18724.55 examples/s]
Generating train split: 39156322 examples [41:29, 20350.99 examples/s]
Generating train split: 39160319 examples [41:29, 24389.44 examples/s]
Generating train split: 39168889 examples [41:29, 38322.07 examples/s]
Generating train split: 39176475 examples [41:29, 47519.93 examples/s]
Generating train split: 39182015 examples [41:30, 25523.61 examples/s]
Generating train split: 39186249 examples [41:30, 24873.59 examples/s]
Generating train split: 39189905 examples [41:30, 17917.66 examples/s]
Generating train split: 39192743 examples [41:31, 15498.81 examples/s]
Generating train split: 39195032 examples [41:31, 14083.29 examples/s]
Generating train split: 39202254 examples [41:31, 22366.81 examples/s]
Generating train split: 39209274 examples [41:31, 30427.19 examples/s]
Generating train split: 39213827 examples [41:31, 31094.00 examples/s]
Generating train split: 39219181 examples [41:31, 35701.27 examples/s]
Generating train split: 39223712 examples [41:31, 33396.84 examples/s]
Generating train split: 39227741 examples [41:32, 25549.16 examples/s]
Generating train split: 39231018 examples [41:32, 26727.13 examples/s]
Generating train split: 39234267 examples [41:32, 26328.06 examples/s]
Generating train split: 39237308 examples [41:32, 21024.84 examples/s]
Generating train split: 39239822 examples [41:32, 21366.66 examples/s]
Generating train split: 39244151 examples [41:32, 26078.08 examples/s]
Generating train split: 39248239 examples [41:33, 29542.46 examples/s]
Generating train split: 39252355 examples [41:33, 32421.12 examples/s]
Generating train split: 39257577 examples [41:33, 37645.90 examples/s]
Generating train split: 39262941 examples [41:33, 41991.44 examples/s]
Generating train split: 39268239 examples [41:33, 45074.26 examples/s]
Generating train split: 39272942 examples [41:33, 44562.86 examples/s]
Generating train split: 39277539 examples [41:33, 40057.69 examples/s]
Generating train split: 39282726 examples [41:33, 43201.39 examples/s]
Generating train split: 39291026 examples [41:33, 54174.42 examples/s]
Generating train split: 39298597 examples [41:33, 60177.30 examples/s]
Generating train split: 39304807 examples [41:34, 41203.40 examples/s]
Generating train split: 39309858 examples [41:34, 31453.75 examples/s]
Generating train split: 39314357 examples [41:34, 33947.96 examples/s]
Generating train split: 39318576 examples [41:34, 35254.06 examples/s]
Generating train split: 39324780 examples [41:34, 41319.48 examples/s]
Generating train split: 39329550 examples [41:34, 38450.25 examples/s]
Generating train split: 39335638 examples [41:35, 43811.26 examples/s]
Generating train split: 39341130 examples [41:35, 46636.48 examples/s]
Generating train split: 39346172 examples [41:35, 47341.27 examples/s]
Generating train split: 39351177 examples [41:35, 47467.31 examples/s]
Generating train split: 39356115 examples [41:35, 36007.35 examples/s]
Generating train split: 39363056 examples [41:35, 43693.29 examples/s]
Generating train split: 39371564 examples [41:35, 53935.29 examples/s]
Generating train split: 39377599 examples [41:36, 37512.49 examples/s]
Generating train split: 39382458 examples [41:36, 34000.14 examples/s]
Generating train split: 39386657 examples [41:36, 23490.47 examples/s]
Generating train split: 39389944 examples [41:36, 22495.09 examples/s]
Generating train split: 39392841 examples [41:36, 21956.32 examples/s]
Generating train split: 39395469 examples [41:37, 15835.91 examples/s]
Generating train split: 39397536 examples [41:37, 16145.75 examples/s]
Generating train split: 39401521 examples [41:37, 20275.29 examples/s]
Generating train split: 39404086 examples [41:37, 12960.48 examples/s]
Generating train split: 39406062 examples [41:38, 13578.71 examples/s]
Generating train split: 39407950 examples [41:38, 9497.44 examples/s] 
Generating train split: 39410465 examples [41:38, 11645.36 examples/s]
Generating train split: 39412569 examples [41:38, 13188.20 examples/s]
Generating train split: 39414451 examples [41:38, 10203.18 examples/s]
Generating train split: 39417866 examples [41:39, 13750.16 examples/s]
Generating train split: 39419798 examples [41:39, 14253.59 examples/s]
Generating train split: 39421634 examples [41:39, 11718.26 examples/s]
Generating train split: 39423147 examples [41:39, 10308.49 examples/s]
Generating train split: 39424536 examples [41:39, 10925.36 examples/s]
Generating train split: 39425848 examples [41:39, 10248.05 examples/s]
Generating train split: 39434270 examples [41:39, 25626.61 examples/s]
Generating train split: 39443508 examples [41:40, 40910.55 examples/s]
Generating train split: 39448618 examples [41:40, 18953.44 examples/s]
Generating train split: 39452450 examples [41:41, 16283.37 examples/s]
Generating train split: 39455467 examples [41:41, 13554.28 examples/s]
Generating train split: 39457828 examples [41:41, 14614.87 examples/s]
Generating train split: 39461305 examples [41:41, 17520.32 examples/s]
Generating train split: 39470650 examples [41:41, 30482.81 examples/s]
Generating train split: 39476520 examples [41:41, 35793.57 examples/s]
Generating train split: 39481498 examples [41:42, 27814.83 examples/s]
Generating train split: 39485509 examples [41:42, 28055.76 examples/s]
Generating train split: 39494107 examples [41:42, 39369.58 examples/s]
Generating train split: 39499263 examples [41:42, 41749.97 examples/s]
Generating train split: 39504370 examples [41:42, 28884.16 examples/s]
Generating train split: 39508421 examples [41:42, 25533.53 examples/s]
Generating train split: 39515336 examples [41:43, 33207.68 examples/s]
Generating train split: 39519784 examples [41:43, 27557.08 examples/s]
Generating train split: 39523448 examples [41:43, 25988.49 examples/s]
Generating train split: 39532741 examples [41:43, 38582.19 examples/s]
Generating train split: 39540954 examples [41:43, 47796.40 examples/s]
Generating train split: 39546945 examples [41:43, 43333.81 examples/s]
Generating train split: 39552184 examples [41:44, 27542.50 examples/s]
Generating train split: 39560968 examples [41:44, 37254.57 examples/s]
Generating train split: 39568882 examples [41:44, 45080.01 examples/s]
Generating train split: 39575093 examples [41:44, 44292.81 examples/s]
Generating train split: 39580721 examples [41:45, 28437.69 examples/s]
Generating train split: 39585078 examples [41:45, 28518.29 examples/s]
Generating train split: 39588992 examples [41:45, 25873.24 examples/s]
Generating train split: 39592323 examples [41:45, 18677.73 examples/s]
Generating train split: 39595435 examples [41:45, 20455.60 examples/s]
Generating train split: 39598187 examples [41:46, 15772.36 examples/s]
Generating train split: 39600747 examples [41:46, 17086.32 examples/s]
Generating train split: 39603355 examples [41:46, 18496.11 examples/s]
Generating train split: 39605675 examples [41:46, 12392.48 examples/s]
Generating train split: 39607825 examples [41:46, 13788.47 examples/s]
Generating train split: 39611719 examples [41:46, 18311.89 examples/s]
Generating train split: 39614218 examples [41:47, 13742.14 examples/s]
Generating train split: 39616220 examples [41:47, 13926.43 examples/s]
Generating train split: 39619738 examples [41:47, 17828.29 examples/s]
Generating train split: 39622062 examples [41:47, 13925.02 examples/s]
Generating train split: 39627535 examples [41:47, 21063.26 examples/s]
Generating train split: 39632241 examples [41:47, 26331.09 examples/s]
Generating train split: 39636862 examples [41:48, 30744.48 examples/s]
Generating train split: 39644453 examples [41:48, 41695.77 examples/s]
Generating train split: 39651867 examples [41:48, 50010.08 examples/s]
Generating train split: 39657539 examples [41:48, 32400.36 examples/s]
Generating train split: 39662034 examples [41:48, 34791.14 examples/s]
Generating train split: 39666519 examples [41:48, 30459.73 examples/s]
Generating train split: 39670335 examples [41:49, 31177.68 examples/s]
Generating train split: 39674018 examples [41:49, 27501.02 examples/s]
Generating train split: 39677214 examples [41:49, 23414.23 examples/s]
Generating train split: 39682644 examples [41:49, 29546.23 examples/s]
Generating train split: 39686331 examples [41:49, 31052.22 examples/s]
Generating train split: 39689885 examples [41:49, 21280.88 examples/s]
Generating train split: 39693439 examples [41:50, 23894.66 examples/s]
Generating train split: 39696588 examples [41:50, 25472.80 examples/s]
Generating train split: 39701250 examples [41:50, 29768.63 examples/s]
Generating train split: 39704885 examples [41:50, 30555.36 examples/s]
Generating train split: 39710138 examples [41:50, 35700.83 examples/s]
Generating train split: 39715388 examples [41:50, 39962.67 examples/s]
Generating train split: 39719663 examples [41:50, 38358.11 examples/s]
Generating train split: 39724956 examples [41:50, 42253.22 examples/s]
Generating train split: 39731871 examples [41:50, 49698.12 examples/s]
Generating train split: 39737037 examples [41:50, 50142.84 examples/s]
Generating train split: 39742198 examples [41:51, 34276.90 examples/s]
Generating train split: 39746390 examples [41:51, 28042.78 examples/s]
Generating train split: 39752233 examples [41:51, 33977.26 examples/s]
Generating train split: 39759958 examples [41:51, 43417.74 examples/s]
Generating train split: 39765213 examples [41:51, 32414.42 examples/s]
Generating train split: 39769469 examples [41:52, 25343.09 examples/s]
Generating train split: 39773229 examples [41:52, 27424.07 examples/s]
Generating train split: 39776768 examples [41:52, 22102.00 examples/s]
Generating train split: 39779667 examples [41:52, 19385.53 examples/s]
Generating train split: 39782678 examples [41:52, 21232.18 examples/s]
Generating train split: 39787180 examples [41:52, 25931.24 examples/s]
Generating train split: 39793749 examples [41:53, 34678.44 examples/s]
Generating train split: 39797947 examples [41:53, 23256.31 examples/s]
Generating train split: 39801255 examples [41:53, 21746.01 examples/s]
Generating train split: 39804110 examples [41:53, 17685.91 examples/s]
Generating train split: 39806555 examples [41:53, 18804.60 examples/s]
Generating train split: 39808915 examples [41:54, 16745.08 examples/s]
Generating train split: 39811826 examples [41:54, 19074.60 examples/s]
Generating train split: 39814113 examples [41:54, 12409.03 examples/s]
Generating train split: 39816466 examples [41:54, 14180.48 examples/s]
Generating train split: 39818782 examples [41:54, 15842.36 examples/s]
Generating train split: 39821485 examples [41:54, 18178.71 examples/s]
Generating train split: 39824477 examples [41:55, 20876.72 examples/s]
Generating train split: 39826955 examples [41:55, 20640.33 examples/s]
Generating train split: 39830450 examples [41:55, 24201.03 examples/s]
Generating train split: 39833614 examples [41:55, 25916.58 examples/s]
Generating train split: 39836415 examples [41:55, 21204.58 examples/s]
Generating train split: 39840306 examples [41:55, 25390.55 examples/s]
Generating train split: 39843152 examples [41:55, 23922.08 examples/s]
Generating train split: 39846098 examples [41:55, 24975.66 examples/s]
Generating train split: 39849013 examples [41:56, 20221.61 examples/s]
Generating train split: 39852971 examples [41:56, 24363.66 examples/s]
Generating train split: 39855718 examples [41:56, 20784.01 examples/s]
Generating train split: 39860983 examples [41:56, 27839.09 examples/s]
Generating train split: 39868508 examples [41:56, 39220.31 examples/s]
Generating train split: 39875728 examples [41:56, 47633.00 examples/s]
Generating train split: 39881059 examples [41:57, 23637.92 examples/s]
Generating train split: 39885107 examples [41:57, 23385.14 examples/s]
Generating train split: 39888620 examples [41:57, 20600.25 examples/s]
Generating train split: 39891535 examples [41:57, 20439.17 examples/s]
Generating train split: 39894175 examples [41:57, 21347.52 examples/s]
Generating train split: 39899160 examples [41:57, 27040.54 examples/s]
Generating train split: 39906390 examples [41:58, 37089.32 examples/s]
Generating train split: 39913414 examples [41:58, 45057.85 examples/s]
Generating train split: 39918667 examples [41:58, 26708.18 examples/s]
Generating train split: 39923344 examples [41:58, 30108.75 examples/s]
Generating train split: 39927595 examples [41:58, 31345.17 examples/s]
Generating train split: 39931630 examples [41:59, 26784.98 examples/s]
Generating train split: 39935036 examples [41:59, 24458.31 examples/s]
Generating train split: 39938934 examples [41:59, 27302.82 examples/s]
Generating train split: 39942857 examples [41:59, 29802.04 examples/s]
Generating train split: 39946279 examples [41:59, 21420.04 examples/s]
Generating train split: 39949106 examples [41:59, 22724.88 examples/s]
Generating train split: 39952752 examples [41:59, 25645.69 examples/s]
Generating train split: 39956249 examples [41:59, 27810.34 examples/s]
Generating train split: 39960011 examples [42:00, 30257.10 examples/s]
Generating train split: 39963362 examples [42:00, 22823.26 examples/s]
Generating train split: 39967330 examples [42:00, 26456.13 examples/s]
Generating train split: 39970462 examples [42:00, 27274.01 examples/s]
Generating train split: 39973544 examples [42:00, 24391.84 examples/s]
Generating train split: 39976276 examples [42:00, 22575.90 examples/s]
Generating train split: 39978966 examples [42:00, 23558.13 examples/s]
Generating train split: 39981504 examples [42:01, 19461.36 examples/s]
Generating train split: 39987213 examples [42:01, 27885.22 examples/s]
Generating train split: 39991215 examples [42:01, 30820.10 examples/s]
Generating train split: 39996697 examples [42:01, 36988.30 examples/s]
Generating train split: 40001648 examples [42:01, 40352.24 examples/s]
Generating train split: 40005984 examples [42:01, 40615.57 examples/s]
Generating train split: 40011158 examples [42:01, 43731.70 examples/s]
Generating train split: 40016741 examples [42:01, 47192.80 examples/s]
Generating train split: 40022167 examples [42:01, 49238.11 examples/s]
Generating train split: 40027807 examples [42:02, 51336.59 examples/s]
Generating train split: 40033024 examples [42:02, 48219.53 examples/s]
Generating train split: 40037940 examples [42:02, 46608.47 examples/s]
Generating train split: 40043510 examples [42:02, 49140.58 examples/s]
Generating train split: 40048655 examples [42:02, 49734.35 examples/s]
Generating train split: 40054374 examples [42:02, 51887.94 examples/s]
Generating train split: 40061662 examples [42:02, 58000.69 examples/s]
Generating train split: 40068174 examples [42:02, 60091.55 examples/s]
Generating train split: 40074538 examples [42:02, 61142.13 examples/s]
Generating train split: 40080692 examples [42:02, 57456.87 examples/s]
Generating train split: 40086510 examples [42:03, 55513.76 examples/s]
Generating train split: 40092115 examples [42:03, 48490.55 examples/s]
Generating train split: 40097408 examples [42:03, 49638.56 examples/s]
Generating train split: 40102555 examples [42:03, 50114.07 examples/s]
Generating train split: 40107680 examples [42:03, 46530.94 examples/s]
Generating train split: 40112448 examples [42:03, 45334.62 examples/s]
Generating train split: 40117064 examples [42:03, 39004.08 examples/s]
Generating train split: 40121145 examples [42:03, 38734.47 examples/s]
Generating train split: 40125150 examples [42:04, 38267.42 examples/s]
Generating train split: 40129059 examples [42:04, 38447.04 examples/s]
Generating train split: 40132965 examples [42:04, 36167.27 examples/s]
Generating train split: 40136638 examples [42:04, 28831.25 examples/s]
Generating train split: 40140408 examples [42:04, 27161.63 examples/s]
Generating train split: 40143312 examples [42:04, 26272.59 examples/s]
Generating train split: 40146061 examples [42:04, 24116.83 examples/s]
Generating train split: 40148568 examples [42:05, 21429.27 examples/s]
Generating train split: 40150862 examples [42:05, 21753.19 examples/s]
Generating train split: 40153106 examples [42:05, 16865.66 examples/s]
Generating train split: 40158264 examples [42:05, 24227.71 examples/s]
Generating train split: 40162619 examples [42:05, 25933.76 examples/s]
Generating train split: 40165518 examples [42:05, 18996.93 examples/s]
Generating train split: 40167874 examples [42:06, 19762.52 examples/s]
Generating train split: 40174788 examples [42:06, 30272.71 examples/s]
Generating train split: 40183830 examples [42:06, 44296.95 examples/s]
Generating train split: 40190123 examples [42:06, 48933.21 examples/s]
Generating train split: 40195723 examples [42:06, 26291.74 examples/s]
Generating train split: 40200015 examples [42:06, 28210.19 examples/s]
Generating train split: 40204120 examples [42:07, 29806.47 examples/s]
Generating train split: 40210266 examples [42:07, 36275.67 examples/s]
Generating train split: 40214880 examples [42:07, 22823.89 examples/s]
Generating train split: 40223531 examples [42:07, 33047.89 examples/s]
Generating train split: 40231251 examples [42:07, 41286.81 examples/s]
Generating train split: 40237132 examples [42:07, 41024.14 examples/s]
Generating train split: 40242458 examples [42:08, 39215.95 examples/s]
Generating train split: 40247242 examples [42:08, 29372.61 examples/s]
Generating train split: 40251093 examples [42:08, 29453.87 examples/s]
Generating train split: 40254681 examples [42:08, 30319.00 examples/s]
Generating train split: 40258294 examples [42:08, 31570.06 examples/s]
Generating train split: 40261839 examples [42:08, 23140.28 examples/s]
Generating train split: 40264716 examples [42:09, 23134.00 examples/s]
Generating train split: 40272620 examples [42:09, 34839.68 examples/s]
Generating train split: 40280034 examples [42:09, 43887.58 examples/s]
Generating train split: 40285256 examples [42:09, 41919.55 examples/s]
Generating train split: 40290040 examples [42:09, 40986.43 examples/s]
Generating train split: 40296573 examples [42:09, 46197.63 examples/s]
Generating train split: 40301562 examples [42:09, 29437.25 examples/s]
Generating train split: 40305507 examples [42:10, 29918.97 examples/s]
Generating train split: 40309212 examples [42:10, 31304.91 examples/s]
Generating train split: 40316923 examples [42:10, 41593.49 examples/s]
Generating train split: 40326313 examples [42:10, 54293.91 examples/s]
Generating train split: 40332555 examples [42:10, 25743.40 examples/s]
Generating train split: 40337264 examples [42:11, 19351.42 examples/s]
Generating train split: 40340883 examples [42:11, 19958.78 examples/s]
Generating train split: 40349064 examples [42:11, 28561.14 examples/s]
Generating train split: 40355171 examples [42:11, 33834.67 examples/s]
Generating train split: 40360255 examples [42:12, 25096.36 examples/s]
Generating train split: 40364255 examples [42:12, 23941.48 examples/s]
Generating train split: 40367677 examples [42:12, 25504.89 examples/s]
Generating train split: 40376571 examples [42:12, 37429.98 examples/s]
Generating train split: 40381983 examples [42:12, 40956.71 examples/s]
Generating train split: 40387142 examples [42:13, 19710.49 examples/s]
Generating train split: 40391005 examples [42:13, 21265.44 examples/s]
Generating train split: 40399039 examples [42:13, 30239.79 examples/s]
Generating train split: 40403954 examples [42:13, 31167.84 examples/s]
Generating train split: 40408421 examples [42:14, 18310.84 examples/s]
Generating train split: 40414936 examples [42:14, 24349.91 examples/s]
Generating train split: 40423550 examples [42:14, 33960.39 examples/s]
Generating train split: 40429157 examples [42:14, 35959.92 examples/s]
Generating train split: 40434368 examples [42:14, 38175.71 examples/s]
Generating train split: 40440267 examples [42:14, 42580.51 examples/s]
Generating train split: 40445546 examples [42:15, 26440.47 examples/s]
Generating train split: 40449647 examples [42:15, 28603.45 examples/s]
Generating train split: 40454405 examples [42:15, 32192.91 examples/s]
Generating train split: 40462852 examples [42:15, 43323.80 examples/s]
Generating train split: 40468368 examples [42:15, 28251.82 examples/s]
Generating train split: 40472684 examples [42:15, 30703.55 examples/s]
Generating train split: 40476984 examples [42:15, 32614.71 examples/s]
Generating train split: 40481197 examples [42:16, 32739.76 examples/s]
Generating train split: 40486080 examples [42:16, 35977.84 examples/s]
Generating train split: 40490233 examples [42:16, 26958.81 examples/s]
Generating train split: 40493621 examples [42:16, 25539.80 examples/s]
Generating train split: 40503742 examples [42:16, 40987.09 examples/s]
Generating train split: 40511476 examples [42:16, 49184.31 examples/s]
Generating train split: 40517412 examples [42:16, 42086.95 examples/s]
Generating train split: 40522483 examples [42:17, 25908.29 examples/s]
Generating train split: 40526405 examples [42:17, 27597.04 examples/s]
Generating train split: 40530224 examples [42:17, 28850.55 examples/s]
Generating train split: 40538105 examples [42:17, 38917.17 examples/s]
Generating train split: 40543054 examples [42:17, 37377.23 examples/s]
Generating train split: 40547532 examples [42:18, 32181.83 examples/s]
Generating train split: 40551365 examples [42:18, 29376.49 examples/s]
Generating train split: 40555829 examples [42:18, 32543.66 examples/s]
Generating train split: 40559527 examples [42:18, 25986.49 examples/s]
Generating train split: 40562609 examples [42:18, 19678.26 examples/s]
Generating train split: 40566159 examples [42:18, 22423.45 examples/s]
Generating train split: 40568968 examples [42:19, 18946.63 examples/s]
Generating train split: 40574925 examples [42:19, 26503.25 examples/s]
Generating train split: 40583346 examples [42:19, 37889.92 examples/s]
Generating train split: 40588060 examples [42:19, 29771.33 examples/s]
Generating train split: 40597023 examples [42:19, 41424.10 examples/s]
Generating train split: 40606611 examples [42:19, 53271.14 examples/s]
Generating train split: 40613271 examples [42:20, 44944.73 examples/s]
Generating train split: 40618889 examples [42:20, 33173.17 examples/s]
Generating train split: 40627022 examples [42:20, 41619.38 examples/s]
Generating train split: 40636764 examples [42:20, 52599.58 examples/s]
Generating train split: 40643552 examples [42:20, 49521.31 examples/s]
Generating train split: 40652007 examples [42:20, 57178.90 examples/s]
Generating train split: 40658765 examples [42:20, 54973.70 examples/s]
Generating train split: 40664987 examples [42:21, 34812.83 examples/s]
Generating train split: 40669865 examples [42:21, 31093.48 examples/s]
Generating train split: 40676214 examples [42:21, 36633.95 examples/s]
Generating train split: 40681386 examples [42:21, 38252.77 examples/s]
Generating train split: 40686039 examples [42:24, 6625.47 examples/s] 
Generating train split: 40689353 examples [42:24, 6393.80 examples/s]
Generating train split: 40691845 examples [42:24, 7166.61 examples/s]
Generating train split: 40694789 examples [42:25, 8681.62 examples/s]
Generating train split: 40697229 examples [42:25, 10027.33 examples/s]
Generating train split: 40701111 examples [42:25, 13249.27 examples/s]
Generating train split: 40707589 examples [42:25, 20351.30 examples/s]
Generating train split: 40711742 examples [42:25, 23829.78 examples/s]
Generating train split: 40717527 examples [42:25, 30300.23 examples/s]
Generating train split: 40722071 examples [42:25, 29156.56 examples/s]
Generating train split: 40726179 examples [42:25, 31651.60 examples/s]
Generating train split: 40730192 examples [42:25, 32130.46 examples/s]
Generating train split: 40734011 examples [42:26, 30933.59 examples/s]
Generating train split: 40742693 examples [42:26, 44322.62 examples/s]
Generating train split: 40750957 examples [42:26, 54087.46 examples/s]
Generating train split: 40756984 examples [42:26, 45367.50 examples/s]
Generating train split: 40762177 examples [42:26, 45544.29 examples/s]
Generating train split: 40770908 examples [42:26, 55857.49 examples/s]
Generating train split: 40777041 examples [42:26, 36061.20 examples/s]
Generating train split: 40781896 examples [42:27, 31224.32 examples/s]
Generating train split: 40785960 examples [42:27, 21997.73 examples/s]
Generating train split: 40789131 examples [42:27, 21122.16 examples/s]
Generating train split: 40795464 examples [42:27, 27842.10 examples/s]
Generating train split: 40804284 examples [42:27, 39024.27 examples/s]
Generating train split: 40809621 examples [42:28, 41204.96 examples/s]
Generating train split: 40818680 examples [42:28, 52392.65 examples/s]
Generating train split: 40827624 examples [42:28, 60771.15 examples/s]
Generating train split: 40834639 examples [42:28, 52430.73 examples/s]
Generating train split: 40843445 examples [42:28, 60744.19 examples/s]
Generating train split: 40850344 examples [42:28, 44153.71 examples/s]
Generating train split: 40855940 examples [42:29, 34833.39 examples/s]
Generating train split: 40860486 examples [42:29, 35677.03 examples/s]
Generating train split: 40864844 examples [42:29, 35978.64 examples/s]
Generating train split: 40869010 examples [42:29, 23525.16 examples/s]
Generating train split: 40872258 examples [42:29, 24023.66 examples/s]
Generating train split: 40876084 examples [42:29, 26608.87 examples/s]
Generating train split: 40884362 examples [42:30, 38189.39 examples/s]
Generating train split: 40891129 examples [42:30, 44540.75 examples/s]
Generating train split: 40896451 examples [42:30, 29241.98 examples/s]
Generating train split: 40900630 examples [42:30, 21072.30 examples/s]
Generating train split: 40903898 examples [42:31, 17412.20 examples/s]
Generating train split: 40906496 examples [42:31, 17644.12 examples/s]
Generating train split: 40909787 examples [42:31, 20044.49 examples/s]
Generating train split: 40915660 examples [42:31, 27141.02 examples/s]
Generating train split: 40919284 examples [42:31, 27419.64 examples/s]
Generating train split: 40922666 examples [42:31, 22929.80 examples/s]
Generating train split: 40926193 examples [42:31, 25191.47 examples/s]
Generating train split: 40929669 examples [42:32, 27298.20 examples/s]
Generating train split: 40937841 examples [42:32, 40319.31 examples/s]
Generating train split: 40946627 examples [42:32, 52416.21 examples/s]
Generating train split: 40952521 examples [42:32, 49937.54 examples/s]
Generating train split: 40961319 examples [42:32, 59824.60 examples/s]
Generating train split: 40969891 examples [42:32, 66828.39 examples/s]
Generating train split: 40976992 examples [42:32, 40864.16 examples/s]
Generating train split: 40982603 examples [42:33, 26981.96 examples/s]
Generating train split: 40986925 examples [42:33, 23769.91 examples/s]
Generating train split: 40990449 examples [42:33, 24371.87 examples/s]
Generating train split: 40995631 examples [42:33, 28890.48 examples/s]
Generating train split: 41001664 examples [42:33, 34868.86 examples/s]
Generating train split: 41007938 examples [42:34, 40409.24 examples/s]
Generating train split: 41012884 examples [42:34, 38498.01 examples/s]
Generating train split: 41017853 examples [42:34, 41073.01 examples/s]
Generating train split: 41024164 examples [42:34, 46529.00 examples/s]
Generating train split: 41029304 examples [42:34, 46146.14 examples/s]
Generating train split: 41034375 examples [42:34, 47342.40 examples/s]
Generating train split: 41039362 examples [42:34, 44762.08 examples/s]
Generating train split: 41044043 examples [42:35, 28202.25 examples/s]
Generating train split: 41047748 examples [42:35, 29628.50 examples/s]
Generating train split: 41054121 examples [42:35, 36897.73 examples/s]
Generating train split: 41058582 examples [42:35, 37762.61 examples/s]
Generating train split: 41062918 examples [42:35, 36590.65 examples/s]
Generating train split: 41066969 examples [42:35, 33454.62 examples/s]
Generating train split: 41073292 examples [42:35, 40578.79 examples/s]
Generating train split: 41080112 examples [42:35, 47610.03 examples/s]
Generating train split: 41086295 examples [42:35, 51402.31 examples/s]
Generating train split: 41091767 examples [42:36, 46580.66 examples/s]
Generating train split: 41096730 examples [42:36, 34451.52 examples/s]
Generating train split: 41102055 examples [42:36, 38437.52 examples/s]
Generating train split: 41108107 examples [42:36, 43566.53 examples/s]
Generating train split: 41113625 examples [42:36, 46459.77 examples/s]
Generating train split: 41118745 examples [42:37, 26900.33 examples/s]
Generating train split: 41122711 examples [42:37, 28372.97 examples/s]
Generating train split: 41128463 examples [42:37, 34068.12 examples/s]
Generating train split: 41134934 examples [42:37, 40435.40 examples/s]
Generating train split: 41142317 examples [42:37, 48326.67 examples/s]
Generating train split: 41147995 examples [42:37, 45868.74 examples/s]
Generating train split: 41153197 examples [42:37, 44277.99 examples/s]
Generating train split: 41158057 examples [42:37, 40172.20 examples/s]
Generating train split: 41166188 examples [42:37, 49985.46 examples/s]
Generating train split: 41171677 examples [42:38, 42934.75 examples/s]
Generating train split: 41176459 examples [42:38, 41208.47 examples/s]
Generating train split: 41180913 examples [42:38, 39168.52 examples/s]
Generating train split: 41185053 examples [42:38, 35586.86 examples/s]
Generating train split: 41188793 examples [42:38, 25944.74 examples/s]
Generating train split: 41191837 examples [42:38, 24291.48 examples/s]
Generating train split: 41194842 examples [42:39, 25448.52 examples/s]
Generating train split: 41198975 examples [42:39, 28986.06 examples/s]
Generating train split: 41205923 examples [42:39, 38770.34 examples/s]
Generating train split: 41211152 examples [42:39, 42233.09 examples/s]
Generating train split: 41215749 examples [42:39, 39033.84 examples/s]
Generating train split: 41220695 examples [42:39, 41703.90 examples/s]
Generating train split: 41225628 examples [42:39, 43645.27 examples/s]
Generating train split: 41230196 examples [42:39, 38541.83 examples/s]
Generating train split: 41234296 examples [42:40, 14541.78 examples/s]
Generating train split: 41237322 examples [42:41, 12110.48 examples/s]
Generating train split: 41239673 examples [42:41, 10351.30 examples/s]
Generating train split: 41241513 examples [42:41, 10697.42 examples/s]
Generating train split: 41243178 examples [42:41, 11115.04 examples/s]
Generating train split: 41244751 examples [42:41, 10659.04 examples/s]
Generating train split: 41246700 examples [42:41, 12107.48 examples/s]
Generating train split: 41248253 examples [42:42, 10063.24 examples/s]
Generating train split: 41249956 examples [42:42, 11289.30 examples/s]
Generating train split: 41253846 examples [42:42, 16844.79 examples/s]
Generating train split: 41262919 examples [42:42, 33341.29 examples/s]
Generating train split: 41270276 examples [42:42, 42982.91 examples/s]
Generating train split: 41275422 examples [42:43, 21846.58 examples/s]
Generating train split: 41279328 examples [42:43, 12970.45 examples/s]
Generating train split: 41282235 examples [42:44, 7667.67 examples/s] 
Generating train split: 41284362 examples [42:44, 8109.21 examples/s]
Generating train split: 41286184 examples [42:45, 6847.37 examples/s]
Generating train split: 41287590 examples [42:45, 7068.73 examples/s]
Generating train split: 41288828 examples [42:45, 6096.23 examples/s]
Generating train split: 41289809 examples [42:46, 5911.22 examples/s]
Generating train split: 41290651 examples [42:46, 5936.36 examples/s]
Generating train split: 41291417 examples [42:46, 5431.78 examples/s]
Generating train split: 41292071 examples [42:46, 5433.30 examples/s]
Generating train split: 41292850 examples [42:46, 5808.12 examples/s]
Generating train split: 41293518 examples [42:46, 5499.20 examples/s]
Generating train split: 41294671 examples [42:46, 6743.01 examples/s]
Generating train split: 41296025 examples [42:46, 8290.25 examples/s]
Generating train split: 41296980 examples [42:47, 8440.44 examples/s]
Generating train split: 41302808 examples [42:47, 21200.93 examples/s]
Generating train split: 41310838 examples [42:47, 37017.02 examples/s]
Generating train split: 41315883 examples [42:47, 40587.98 examples/s]
Generating train split: 41320239 examples [42:48, 15170.79 examples/s]
Generating train split: 41323472 examples [42:48, 12693.05 examples/s]
Generating train split: 41325993 examples [42:48, 12514.24 examples/s]
Generating train split: 41328650 examples [42:48, 14335.25 examples/s]
Generating train split: 41330926 examples [42:49, 12471.13 examples/s]
Generating train split: 41332780 examples [42:49, 13045.12 examples/s]
Generating train split: 41334551 examples [42:49, 13529.24 examples/s]
Generating train split: 41336272 examples [42:49, 13265.98 examples/s]
Generating train split: 41337849 examples [42:49, 12930.33 examples/s]
Generating train split: 41340300 examples [42:49, 15430.15 examples/s]
Generating train split: 41342055 examples [42:49, 13415.97 examples/s]
Generating train split: 41343590 examples [42:50, 12023.91 examples/s]
Generating train split: 41345361 examples [42:50, 13183.35 examples/s]
Generating train split: 41347682 examples [42:50, 15498.22 examples/s]
Generating train split: 41349400 examples [42:50, 12951.05 examples/s]
Generating train split: 41350878 examples [42:50, 13258.08 examples/s]
Generating train split: 41352881 examples [42:50, 14893.36 examples/s]
Generating train split: 41354503 examples [42:50, 12724.31 examples/s]
Generating train split: 41355938 examples [42:50, 13101.34 examples/s]
Generating train split: 41357360 examples [42:51, 11806.54 examples/s]
Generating train split: 41359384 examples [42:51, 13475.56 examples/s]
Generating train split: 41360825 examples [42:51, 13608.64 examples/s]
Generating train split: 41363465 examples [42:51, 16953.32 examples/s]
Generating train split: 41365257 examples [42:51, 16637.10 examples/s]
Generating train split: 41366988 examples [42:51, 14284.72 examples/s]
Generating train split: 41368860 examples [42:51, 15316.07 examples/s]
Generating train split: 41370483 examples [42:51, 12935.66 examples/s]
Generating train split: 41373202 examples [42:52, 16289.50 examples/s]
Generating train split: 41375544 examples [42:52, 17331.86 examples/s]
Generating train split: 41377411 examples [42:52, 10738.64 examples/s]
Generating train split: 41380405 examples [42:52, 14239.72 examples/s]
Generating train split: 41382325 examples [42:52, 11911.11 examples/s]
Generating train split: 41383919 examples [42:52, 11916.06 examples/s]
Generating train split: 41385842 examples [42:53, 13381.43 examples/s]
Generating train split: 41388523 examples [42:53, 16373.77 examples/s]
Generating train split: 41390450 examples [42:53, 12639.09 examples/s]
Generating train split: 41395251 examples [42:53, 19833.05 examples/s]
Generating train split: 41405350 examples [42:53, 38103.33 examples/s]
Generating train split: 41411057 examples [42:53, 40943.54 examples/s]
Generating train split: 41415886 examples [42:53, 29870.09 examples/s]
Generating train split: 41419800 examples [42:54, 23635.16 examples/s]
Generating train split: 41427422 examples [42:54, 32841.95 examples/s]
Generating train split: 41432945 examples [42:54, 37319.45 examples/s]
Generating train split: 41437760 examples [42:54, 30826.57 examples/s]
Generating train split: 41441773 examples [42:54, 25010.10 examples/s]
Generating train split: 41448251 examples [42:55, 32078.73 examples/s]
Generating train split: 41456803 examples [42:55, 42898.53 examples/s]
Generating train split: 41462332 examples [42:55, 37754.40 examples/s]
Generating train split: 41467063 examples [42:55, 25936.65 examples/s]
Generating train split: 41470780 examples [42:56, 16473.16 examples/s]
Generating train split: 41475095 examples [42:56, 19569.58 examples/s]
Generating train split: 41478289 examples [42:56, 19151.44 examples/s]
Generating train split: 41481061 examples [42:56, 18195.85 examples/s]
Generating train split: 41488426 examples [42:56, 27460.67 examples/s]
Generating train split: 41496647 examples [42:56, 38009.88 examples/s]
Generating train split: 41501837 examples [42:57, 24165.38 examples/s]
Generating train split: 41505836 examples [42:57, 20791.09 examples/s]
Generating train split: 41513765 examples [42:57, 29362.65 examples/s]
Generating train split: 41523138 examples [42:57, 40500.53 examples/s]
Generating train split: 41529195 examples [42:58, 26794.72 examples/s]
Generating train split: 41537386 examples [42:58, 34824.30 examples/s]
Generating train split: 41546001 examples [42:58, 43664.36 examples/s]
Generating train split: 41552592 examples [42:58, 26077.71 examples/s]
Generating train split: 41562135 examples [42:59, 35281.01 examples/s]
Generating train split: 41571609 examples [42:59, 44759.59 examples/s]
Generating train split: 41578897 examples [42:59, 37392.23 examples/s]
Generating train split: 41588714 examples [42:59, 47447.22 examples/s]
Generating train split: 41595776 examples [42:59, 36150.41 examples/s]
Generating train split: 41601364 examples [43:00, 28249.20 examples/s]
Generating train split: 41611681 examples [43:00, 38807.55 examples/s]
Generating train split: 41617864 examples [43:00, 39753.75 examples/s]
Generating train split: 41623479 examples [43:00, 25454.66 examples/s]
Generating train split: 41627768 examples [43:01, 20892.80 examples/s]
Generating train split: 41631151 examples [43:01, 17634.94 examples/s]
Generating train split: 41633837 examples [43:01, 16897.66 examples/s]
Generating train split: 41636138 examples [43:01, 15602.12 examples/s]
Generating train split: 41638095 examples [43:02, 12633.28 examples/s]
Generating train split: 41639667 examples [43:02, 12329.49 examples/s]
Generating train split: 41642783 examples [43:02, 15333.22 examples/s]
Generating train split: 41644834 examples [43:02, 16233.56 examples/s]
Generating train split: 41646798 examples [43:02, 13936.78 examples/s]
Generating train split: 41649242 examples [43:02, 15999.00 examples/s]
Generating train split: 41651136 examples [43:03, 16202.39 examples/s]
Generating train split: 41652981 examples [43:03, 15138.99 examples/s]
Generating train split: 41654912 examples [43:03, 16029.19 examples/s]
Generating train split: 41656647 examples [43:03, 15615.32 examples/s]
Generating train split: 41658416 examples [43:03, 16117.93 examples/s]
Generating train split: 41661261 examples [43:03, 19383.08 examples/s]
Generating train split: 41663301 examples [43:03, 11155.15 examples/s]
Generating train split: 41666295 examples [43:04, 14551.84 examples/s]
Generating train split: 41669428 examples [43:04, 17993.65 examples/s]
Generating train split: 41671763 examples [43:04, 15911.14 examples/s]
Generating train split: 41673767 examples [43:04, 13690.69 examples/s]
Generating train split: 41675638 examples [43:04, 14684.77 examples/s]
Generating train split: 41678109 examples [43:04, 16894.85 examples/s]
Generating train split: 41680078 examples [43:05, 13233.04 examples/s]
Generating train split: 41682292 examples [43:05, 14962.29 examples/s]
Generating train split: 41684075 examples [43:05, 15294.37 examples/s]
Generating train split: 41686379 examples [43:05, 17148.59 examples/s]
Generating train split: 41691791 examples [43:05, 26576.26 examples/s]
Generating train split: 41694949 examples [43:05, 27139.64 examples/s]
Generating train split: 41697879 examples [43:05, 22006.01 examples/s]
Generating train split: 41700384 examples [43:05, 21957.26 examples/s]
Generating train split: 41703928 examples [43:05, 25248.53 examples/s]
Generating train split: 41707625 examples [43:06, 27186.12 examples/s]
Generating train split: 41713115 examples [43:06, 34450.05 examples/s]
Generating train split: 41717996 examples [43:06, 38361.96 examples/s]
Generating train split: 41722029 examples [43:06, 30681.14 examples/s]
Generating train split: 41726295 examples [43:06, 33544.79 examples/s]
Generating train split: 41731741 examples [43:06, 38868.19 examples/s]
Generating train split: 41736694 examples [43:06, 35126.92 examples/s]
Generating train split: 41741741 examples [43:06, 37558.59 examples/s]
Generating train split: 41746111 examples [43:07, 38733.84 examples/s]
Generating train split: 41752503 examples [43:07, 45327.36 examples/s]
Generating train split: 41757273 examples [43:07, 45700.80 examples/s]
Generating train split: 41762016 examples [43:07, 45188.77 examples/s]
Generating train split: 41766660 examples [43:07, 40356.22 examples/s]
Generating train split: 41771214 examples [43:07, 41704.19 examples/s]
Generating train split: 41775522 examples [43:07, 29093.67 examples/s]
Generating train split: 41784998 examples [43:07, 43009.41 examples/s]
Generating train split: 41793761 examples [43:08, 53379.30 examples/s]
Generating train split: 41800097 examples [43:08, 30215.75 examples/s]
Generating train split: 41804973 examples [43:08, 28923.68 examples/s]
Generating train split: 41809147 examples [43:08, 31046.07 examples/s]
Generating train split: 41813315 examples [43:08, 30519.66 examples/s]
Generating train split: 41821977 examples [43:09, 41881.00 examples/s]
Generating train split: 41828513 examples [43:09, 47137.39 examples/s]
Generating train split: 41835604 examples [43:09, 52897.03 examples/s]
Generating train split: 41843860 examples [43:09, 60528.23 examples/s]
Generating train split: 41850592 examples [43:09, 36594.44 examples/s]
Generating train split: 41855863 examples [43:09, 29569.39 examples/s]
Generating train split: 41861773 examples [43:10, 34408.22 examples/s]
Generating train split: 41866577 examples [43:10, 36991.31 examples/s]
Generating train split: 41873450 examples [43:10, 43761.67 examples/s]
Generating train split: 41878843 examples [43:10, 41177.34 examples/s]
Generating train split: 41883688 examples [43:10, 41652.28 examples/s]
Generating train split: 41888380 examples [43:10, 33495.45 examples/s]
Generating train split: 41892312 examples [43:10, 31986.06 examples/s]
Generating train split: 41896857 examples [43:11, 34801.24 examples/s]
Generating train split: 41901322 examples [43:11, 37133.12 examples/s]
Generating train split: 41907158 examples [43:11, 42393.17 examples/s]
Generating train split: 41912127 examples [43:11, 44313.47 examples/s]
Generating train split: 41917060 examples [43:11, 45670.34 examples/s]
Generating train split: 41921824 examples [43:11, 45385.31 examples/s]
Generating train split: 41928988 examples [43:11, 52819.07 examples/s]
Generating train split: 41936134 examples [43:11, 56254.44 examples/s]
Generating train split: 41941848 examples [43:12, 30502.89 examples/s]
Generating train split: 41947056 examples [43:12, 33106.97 examples/s]
Generating train split: 41951444 examples [43:12, 31013.33 examples/s]
Generating train split: 41957406 examples [43:12, 36715.52 examples/s]
Generating train split: 41962025 examples [43:12, 38721.24 examples/s]
Generating train split: 41966538 examples [43:12, 38463.41 examples/s]
Generating train split: 41970827 examples [43:12, 36936.01 examples/s]
Generating train split: 41976536 examples [43:12, 41917.86 examples/s]
Generating train split: 41982136 examples [43:13, 45593.70 examples/s]
Generating train split: 41986984 examples [43:13, 46019.76 examples/s]
Generating train split: 41991796 examples [43:13, 37977.21 examples/s]
Generating train split: 41995952 examples [43:13, 24440.41 examples/s]
Generating train split: 41999234 examples [43:13, 22980.13 examples/s]
Generating train split: 42004773 examples [43:13, 28793.75 examples/s]
Generating train split: 42008393 examples [43:14, 28628.05 examples/s]
Generating train split: 42014694 examples [43:14, 36168.79 examples/s]
Generating train split: 42019131 examples [43:14, 38118.80 examples/s]
Generating train split: 42027484 examples [43:14, 49639.95 examples/s]
Generating train split: 42033001 examples [43:14, 45520.30 examples/s]
Generating train split: 42037997 examples [43:14, 37475.14 examples/s]
Generating train split: 42042261 examples [43:15, 27741.17 examples/s]
Generating train split: 42045708 examples [43:15, 24232.74 examples/s]
Generating train split: 42048638 examples [43:15, 24443.31 examples/s]
Generating train split: 42051445 examples [43:15, 23175.21 examples/s]
Generating train split: 42055104 examples [43:15, 25972.45 examples/s]
Generating train split: 42062144 examples [43:15, 36220.68 examples/s]
Generating train split: 42066698 examples [43:15, 38528.75 examples/s]
Generating train split: 42070966 examples [43:16, 27678.80 examples/s]
Generating train split: 42076526 examples [43:16, 33424.18 examples/s]
Generating train split: 42080611 examples [43:16, 33731.83 examples/s]
Generating train split: 42086980 examples [43:16, 40861.38 examples/s]
Generating train split: 42093910 examples [43:16, 48077.15 examples/s]
Generating train split: 42100229 examples [43:16, 52086.63 examples/s]
Generating train split: 42105854 examples [43:16, 38408.03 examples/s]
Generating train split: 42110492 examples [43:16, 38664.76 examples/s]
Generating train split: 42114925 examples [43:17, 34565.71 examples/s]
Generating train split: 42121658 examples [43:17, 41886.13 examples/s]
Generating train split: 42129259 examples [43:17, 50131.02 examples/s]
Generating train split: 42137287 examples [43:17, 56823.31 examples/s]
Generating train split: 42144181 examples [43:17, 59990.15 examples/s]
Generating train split: 42150577 examples [43:17, 35265.74 examples/s]
Generating train split: 42155577 examples [43:17, 37743.95 examples/s]
Generating train split: 42163772 examples [43:18, 46908.54 examples/s]
Generating train split: 42171662 examples [43:18, 54215.88 examples/s]
Generating train split: 42178168 examples [43:18, 45268.27 examples/s]
Generating train split: 42183678 examples [43:18, 36982.53 examples/s]
Generating train split: 42188262 examples [43:18, 34588.73 examples/s]
Generating train split: 42192329 examples [43:18, 35777.13 examples/s]
Generating train split: 42198500 examples [43:18, 41530.20 examples/s]
Generating train split: 42205620 examples [43:19, 48496.84 examples/s]
Generating train split: 42211017 examples [43:19, 39035.94 examples/s]
Generating train split: 42215563 examples [43:19, 35582.67 examples/s]
Generating train split: 42219596 examples [43:19, 34702.52 examples/s]
Generating train split: 42223397 examples [43:19, 33952.15 examples/s]
Generating train split: 42227009 examples [43:20, 20053.04 examples/s]
Generating train split: 42230154 examples [43:20, 21931.92 examples/s]
Generating train split: 42233057 examples [43:20, 23032.23 examples/s]
Generating train split: 42235912 examples [43:20, 19180.30 examples/s]
Generating train split: 42239433 examples [43:20, 22062.82 examples/s]
Generating train split: 42247482 examples [43:20, 34626.91 examples/s]
Generating train split: 42253675 examples [43:20, 41023.91 examples/s]
Generating train split: 42258531 examples [43:21, 32789.92 examples/s]
Generating train split: 42262585 examples [43:21, 25630.25 examples/s]
Generating train split: 42265889 examples [43:21, 26911.84 examples/s]
Generating train split: 42271204 examples [43:21, 32398.07 examples/s]
Generating train split: 42275098 examples [43:21, 33377.90 examples/s]
Generating train split: 42280705 examples [43:21, 38921.96 examples/s]
Generating train split: 42285074 examples [43:21, 28257.13 examples/s]
Generating train split: 42290561 examples [43:22, 33748.07 examples/s]
Generating train split: 42296316 examples [43:22, 37926.31 examples/s]
Generating train split: 42301622 examples [43:22, 41549.53 examples/s]
Generating train split: 42309971 examples [43:22, 52240.78 examples/s]
Generating train split: 42316825 examples [43:22, 56563.81 examples/s]
Generating train split: 42322920 examples [43:22, 33493.07 examples/s]
Generating train split: 42327695 examples [43:23, 26055.03 examples/s]
Generating train split: 42331505 examples [43:23, 24336.19 examples/s]
Generating train split: 42334868 examples [43:23, 25854.48 examples/s]
Generating train split: 42340294 examples [43:23, 31304.42 examples/s]
Generating train split: 42345158 examples [43:23, 35026.64 examples/s]
Generating train split: 42352249 examples [43:23, 43459.99 examples/s]
Generating train split: 42357569 examples [43:23, 45893.18 examples/s]
Generating train split: 42363068 examples [43:23, 48295.07 examples/s]
Generating train split: 42368318 examples [43:24, 48985.20 examples/s]
Generating train split: 42373517 examples [43:24, 42112.72 examples/s]
Generating train split: 42378112 examples [43:24, 32844.32 examples/s]
Generating train split: 42381951 examples [43:24, 27668.91 examples/s]
Generating train split: 42385186 examples [43:24, 27136.10 examples/s]
Generating train split: 42388824 examples [43:24, 29089.78 examples/s]
Generating train split: 42392042 examples [43:24, 29308.85 examples/s]
Generating train split: 42395199 examples [43:25, 27467.16 examples/s]
Generating train split: 42398102 examples [43:25, 22334.84 examples/s]
Generating train split: 42400580 examples [43:25, 20991.49 examples/s]
Generating train split: 42404259 examples [43:25, 24485.87 examples/s]
Generating train split: 42406946 examples [43:25, 19952.23 examples/s]
Generating train split: 42409217 examples [43:26, 14523.31 examples/s]
Generating train split: 42411035 examples [43:26, 11832.98 examples/s]
Generating train split: 42412526 examples [43:26, 12161.06 examples/s]
Generating train split: 42413978 examples [43:26, 11820.25 examples/s]
Generating train split: 42415507 examples [43:26, 11904.91 examples/s]
Generating train split: 42416888 examples [43:26, 12212.11 examples/s]
Generating train split: 42418200 examples [43:26, 10855.07 examples/s]
Generating train split: 42419565 examples [43:27, 11480.15 examples/s]
Generating train split: 42420788 examples [43:27, 9549.62 examples/s] 
Generating train split: 42421835 examples [43:27, 7157.62 examples/s]
Generating train split: 42423533 examples [43:27, 8756.62 examples/s]
Generating train split: 42424573 examples [43:27, 8053.92 examples/s]
Generating train split: 42431430 examples [43:27, 20619.77 examples/s]
Generating train split: 42439594 examples [43:27, 34581.37 examples/s]
Generating train split: 42443936 examples [43:28, 24282.60 examples/s]
Generating train split: 42453724 examples [43:28, 38164.16 examples/s]
Generating train split: 42462920 examples [43:28, 49572.33 examples/s]
Generating train split: 42469432 examples [43:29, 23757.60 examples/s]
Generating train split: 42475402 examples [43:29, 28401.69 examples/s]
Generating train split: 42482804 examples [43:29, 34901.94 examples/s]
Generating train split: 42488448 examples [43:29, 22749.25 examples/s]
Generating train split: 42492744 examples [43:29, 25050.75 examples/s]
Generating train split: 42501072 examples [43:30, 34111.74 examples/s]
Generating train split: 42508593 examples [43:30, 41580.77 examples/s]
Generating train split: 42514649 examples [43:30, 29443.26 examples/s]
Generating train split: 42523184 examples [43:30, 38392.15 examples/s]
Generating train split: 42530367 examples [43:30, 44606.10 examples/s]
Generating train split: 42536640 examples [43:31, 23512.67 examples/s]
Generating train split: 42541349 examples [43:31, 25133.30 examples/s]
Generating train split: 42549635 examples [43:31, 33615.71 examples/s]
Generating train split: 42556806 examples [43:31, 40219.48 examples/s]
Generating train split: 42562794 examples [43:32, 23471.16 examples/s]
Generating train split: 42567314 examples [43:32, 16446.97 examples/s]
Generating train split: 42570740 examples [43:32, 16133.85 examples/s]
Generating train split: 42578075 examples [43:33, 22799.03 examples/s]
Generating train split: 42585527 examples [43:33, 29949.59 examples/s]
Generating train split: 42590583 examples [43:33, 24199.08 examples/s]
Generating train split: 42594588 examples [43:34, 16107.47 examples/s]
Generating train split: 42597619 examples [43:34, 16572.17 examples/s]
Generating train split: 42600306 examples [43:34, 11600.43 examples/s]
Generating train split: 42602341 examples [43:34, 11027.86 examples/s]
Generating train split: 42604037 examples [43:35, 10635.25 examples/s]
Generating train split: 42605500 examples [43:35, 9726.06 examples/s] 
Generating train split: 42606745 examples [43:35, 8917.69 examples/s]
Generating train split: 42607801 examples [43:35, 8728.50 examples/s]
Generating train split: 42608780 examples [43:35, 8768.52 examples/s]
Generating train split: 42611628 examples [43:35, 12531.78 examples/s]
Generating train split: 42613123 examples [43:36, 10765.60 examples/s]
Generating train split: 42614407 examples [43:36, 10380.78 examples/s]
Generating train split: 42617667 examples [43:36, 15079.08 examples/s]
Generating train split: 42621037 examples [43:36, 19403.65 examples/s]
Generating train split: 42630661 examples [43:36, 38551.51 examples/s]
Generating train split: 42639324 examples [43:36, 51170.61 examples/s]
Generating train split: 42645052 examples [43:37, 23860.02 examples/s]
Generating train split: 42649384 examples [43:37, 19509.96 examples/s]
Generating train split: 42652790 examples [43:37, 18664.56 examples/s]
Generating train split: 42655653 examples [43:37, 17450.23 examples/s]
Generating train split: 42662485 examples [43:38, 25128.98 examples/s]
Generating train split: 42672020 examples [43:38, 37580.56 examples/s]
Generating train split: 42677503 examples [43:38, 31274.26 examples/s]
Generating train split: 42681987 examples [43:38, 25986.24 examples/s]
Generating train split: 42685637 examples [43:39, 19150.70 examples/s]
Generating train split: 42688531 examples [43:39, 19819.20 examples/s]
Generating train split: 42691220 examples [43:39, 19199.18 examples/s]
Generating train split: 42693626 examples [43:39, 18700.44 examples/s]
Generating train split: 42696612 examples [43:39, 20764.10 examples/s]
Generating train split: 42699030 examples [43:39, 20935.99 examples/s]
Generating train split: 42701368 examples [43:39, 17263.09 examples/s]
Generating train split: 42703358 examples [43:40, 14968.16 examples/s]
Generating train split: 42706488 examples [43:40, 18222.02 examples/s]
Generating train split: 42709986 examples [43:40, 21929.86 examples/s]
Generating train split: 42712529 examples [43:40, 13425.99 examples/s]
Generating train split: 42715562 examples [43:40, 16242.00 examples/s]
Generating train split: 42717847 examples [43:40, 15851.74 examples/s]
Generating train split: 42719896 examples [43:41, 11911.03 examples/s]
Generating train split: 42721835 examples [43:41, 13121.45 examples/s]
Generating train split: 42723550 examples [43:41, 13852.46 examples/s]
Generating train split: 42728092 examples [43:41, 20671.87 examples/s]
Generating train split: 42733598 examples [43:41, 28778.99 examples/s]
Generating train split: 42741370 examples [43:41, 41108.73 examples/s]
Generating train split: 42748907 examples [43:41, 50166.05 examples/s]
Generating train split: 42754488 examples [43:42, 38056.43 examples/s]
Generating train split: 42759125 examples [43:42, 37884.33 examples/s]
Generating train split: 42763488 examples [43:42, 26909.84 examples/s]
Generating train split: 42766987 examples [43:42, 20002.21 examples/s]
Generating train split: 42769763 examples [43:43, 13052.68 examples/s]
Generating train split: 42771871 examples [43:43, 9964.61 examples/s] 
Generating train split: 42773505 examples [43:43, 10513.82 examples/s]
Generating train split: 42775143 examples [43:43, 11234.22 examples/s]
Generating train split: 42776713 examples [43:44, 10814.46 examples/s]
Generating train split: 42778527 examples [43:44, 12033.18 examples/s]
Generating train split: 42780043 examples [43:44, 9692.20 examples/s] 
Generating train split: 42781282 examples [43:44, 9693.89 examples/s]
Generating train split: 42782440 examples [43:44, 8812.03 examples/s]
Generating train split: 42783991 examples [43:44, 10071.19 examples/s]
Generating train split: 42785164 examples [43:45, 7839.34 examples/s] 
Generating train split: 42786127 examples [43:45, 7996.31 examples/s]
Generating train split: 42788840 examples [43:45, 11961.14 examples/s]
Generating train split: 42790296 examples [43:45, 9313.12 examples/s] 
Generating train split: 42792096 examples [43:45, 10895.64 examples/s]
Generating train split: 42793489 examples [43:45, 11536.60 examples/s]
Generating train split: 42794859 examples [43:45, 12015.47 examples/s]
Generating train split: 42796225 examples [43:46, 8943.26 examples/s] 
Generating train split: 42797575 examples [43:46, 9810.13 examples/s]
Generating train split: 42799494 examples [43:46, 11749.84 examples/s]
Generating train split: 42802731 examples [43:46, 16719.57 examples/s]
Generating train split: 42811511 examples [43:46, 34925.54 examples/s]
Generating train split: 42818693 examples [43:46, 44797.45 examples/s]
Generating train split: 42823636 examples [43:46, 33895.31 examples/s]
Generating train split: 42829291 examples [43:46, 38980.48 examples/s]
Generating train split: 42835844 examples [43:47, 45375.95 examples/s]
Generating train split: 42840994 examples [43:47, 37321.41 examples/s]
Generating train split: 42845378 examples [43:47, 37126.46 examples/s]
Generating train split: 42849543 examples [43:47, 34334.65 examples/s]
Generating train split: 42853306 examples [43:47, 34916.66 examples/s]
Generating train split: 42857051 examples [43:47, 23833.49 examples/s]
Generating train split: 42860045 examples [43:48, 23095.29 examples/s]
Generating train split: 42868386 examples [43:48, 35300.06 examples/s]
Generating train split: 42876519 examples [43:48, 45622.44 examples/s]
Generating train split: 42882054 examples [43:48, 34542.03 examples/s]
Generating train split: 42886560 examples [43:48, 25850.57 examples/s]
Generating train split: 42890310 examples [43:48, 27792.57 examples/s]
Generating train split: 42894166 examples [43:49, 29869.94 examples/s]
Generating train split: 42897882 examples [43:49, 22666.17 examples/s]
Generating train split: 42900886 examples [43:49, 19857.75 examples/s]
Generating train split: 42904061 examples [43:49, 21941.97 examples/s]
Generating train split: 42906780 examples [43:49, 21605.19 examples/s]
Generating train split: 42910092 examples [43:49, 24055.45 examples/s]
Generating train split: 42916465 examples [43:50, 33310.63 examples/s]
Generating train split: 42924517 examples [43:50, 44529.62 examples/s]
Generating train split: 42929503 examples [43:50, 41962.16 examples/s]
Generating train split: 42934093 examples [43:50, 42241.87 examples/s]
Generating train split: 42938602 examples [43:50, 30292.86 examples/s]
Generating train split: 42942276 examples [43:50, 28181.94 examples/s]
Generating train split: 42946366 examples [43:50, 30844.42 examples/s]
Generating train split: 42949882 examples [43:51, 22902.09 examples/s]
Generating train split: 42952738 examples [43:51, 21062.31 examples/s]
Generating train split: 42955936 examples [43:51, 23177.55 examples/s]
Generating train split: 42964638 examples [43:51, 37019.43 examples/s]
Generating train split: 42972919 examples [43:51, 47847.15 examples/s]
Generating train split: 42978558 examples [43:51, 33448.92 examples/s]
Generating train split: 42983084 examples [43:52, 25245.74 examples/s]
Generating train split: 42986684 examples [43:52, 26149.66 examples/s]
Generating train split: 42994642 examples [43:52, 36026.13 examples/s]
Generating train split: 43003577 examples [43:52, 47157.42 examples/s]
Generating train split: 43009602 examples [43:52, 46865.99 examples/s]
Generating train split: 43018106 examples [43:52, 55820.81 examples/s]
Generating train split: 43025721 examples [43:52, 60913.19 examples/s]
Generating train split: 43032536 examples [43:53, 37873.65 examples/s]
Generating train split: 43037896 examples [43:53, 34285.68 examples/s]
Generating train split: 43042446 examples [43:53, 31845.01 examples/s]
Generating train split: 43046402 examples [43:53, 26535.87 examples/s]
Generating train split: 43049669 examples [43:53, 25660.27 examples/s]
Generating train split: 43053527 examples [43:54, 28085.10 examples/s]
Generating train split: 43056776 examples [43:54, 27297.43 examples/s]
Generating train split: 43059806 examples [43:54, 26185.19 examples/s]
Generating train split: 43062616 examples [43:54, 19678.23 examples/s]
Generating train split: 43065619 examples [43:54, 21684.16 examples/s]
Generating train split: 43068126 examples [43:54, 19329.61 examples/s]
Generating train split: 43073183 examples [43:54, 25919.91 examples/s]
Generating train split: 43080132 examples [43:55, 36015.64 examples/s]
Generating train split: 43084351 examples [43:55, 22130.98 examples/s]
Generating train split: 43087640 examples [43:55, 23021.19 examples/s]
Generating train split: 43091691 examples [43:55, 26366.74 examples/s]
Generating train split: 43098474 examples [43:55, 35280.85 examples/s]
Generating train split: 43104684 examples [43:55, 41578.19 examples/s]
Generating train split: 43109637 examples [43:56, 24082.24 examples/s]
Generating train split: 43113833 examples [43:56, 27036.42 examples/s]
Generating train split: 43121666 examples [43:56, 36838.47 examples/s]
Generating train split: 43128047 examples [43:56, 42615.90 examples/s]
Generating train split: 43133526 examples [43:56, 26938.34 examples/s]
Generating train split: 43137788 examples [43:57, 25477.86 examples/s]
Generating train split: 43146486 examples [43:57, 35898.16 examples/s]
Generating train split: 43154538 examples [43:57, 44587.63 examples/s]
Generating train split: 43160562 examples [43:57, 31967.86 examples/s]
Generating train split: 43165323 examples [43:58, 22448.92 examples/s]
Generating train split: 43169006 examples [43:58, 19473.90 examples/s]
Generating train split: 43171971 examples [43:58, 18587.60 examples/s]
Generating train split: 43174702 examples [43:58, 19866.44 examples/s]
Generating train split: 43181266 examples [43:58, 27798.71 examples/s]
Generating train split: 43189336 examples [43:58, 38197.74 examples/s]
Generating train split: 43194387 examples [43:59, 27368.32 examples/s]
Generating train split: 43198389 examples [43:59, 28902.27 examples/s]
Generating train split: 43202250 examples [43:59, 29677.53 examples/s]
Generating train split: 43205932 examples [43:59, 19594.63 examples/s]
Generating train split: 43209853 examples [43:59, 22727.97 examples/s]
Generating train split: 43213844 examples [44:00, 25916.66 examples/s]
Generating train split: 43217280 examples [44:00, 18199.51 examples/s]
Generating train split: 43222300 examples [44:00, 23191.27 examples/s]
Generating train split: 43225592 examples [44:00, 22473.49 examples/s]
Generating train split: 43228521 examples [44:00, 19614.28 examples/s]
Generating train split: 43230985 examples [44:01, 18186.52 examples/s]
Generating train split: 43233148 examples [44:01, 18781.70 examples/s]
Generating train split: 43236137 examples [44:01, 21146.55 examples/s]
Generating train split: 43241986 examples [44:01, 29874.17 examples/s]
Generating train split: 43250825 examples [44:01, 44518.78 examples/s]
Generating train split: 43256373 examples [44:01, 47348.15 examples/s]
Generating train split: 43261580 examples [44:01, 27454.51 examples/s]
Generating train split: 43266090 examples [44:02, 30536.83 examples/s]
Generating train split: 43270258 examples [44:02, 24085.76 examples/s]
Generating train split: 43273628 examples [44:02, 20386.68 examples/s]
Generating train split: 43276387 examples [44:02, 20408.66 examples/s]
Generating train split: 43278940 examples [44:02, 19517.15 examples/s]
Generating train split: 43281231 examples [44:03, 17408.10 examples/s]
Generating train split: 43283212 examples [44:03, 17148.58 examples/s]
Generating train split: 43291496 examples [44:03, 30852.43 examples/s]
Generating train split: 43299759 examples [44:03, 42737.06 examples/s]
Generating train split: 43304898 examples [44:03, 42751.43 examples/s]
Generating train split: 43309784 examples [44:03, 26315.49 examples/s]
Generating train split: 43313613 examples [44:03, 26231.52 examples/s]
Generating train split: 43324523 examples [44:04, 41832.58 examples/s]
Generating train split: 43332529 examples [44:04, 49763.11 examples/s]
Generating train split: 43338870 examples [44:04, 37507.34 examples/s]
Generating train split: 43343995 examples [44:04, 29384.33 examples/s]
Generating train split: 43348109 examples [44:05, 19339.66 examples/s]
Generating train split: 43351261 examples [44:05, 20870.79 examples/s]
Generating train split: 43357223 examples [44:05, 26834.66 examples/s]
Generating train split: 43363468 examples [44:05, 32300.24 examples/s]
Generating train split: 43367876 examples [44:05, 26279.62 examples/s]
Generating train split: 43371470 examples [44:05, 25239.24 examples/s]
Generating train split: 43375757 examples [44:06, 28523.40 examples/s]
Generating train split: 43382299 examples [44:06, 36285.80 examples/s]
Generating train split: 43390696 examples [44:06, 47302.59 examples/s]
Generating train split: 43396461 examples [44:06, 49856.58 examples/s]
Generating train split: 43402122 examples [44:06, 33275.25 examples/s]
Generating train split: 43406642 examples [44:06, 32170.40 examples/s]
Generating train split: 43412292 examples [44:06, 37044.75 examples/s]
Generating train split: 43419715 examples [44:07, 45321.52 examples/s]
Generating train split: 43427783 examples [44:07, 53553.01 examples/s]
Generating train split: 43433927 examples [44:07, 30280.98 examples/s]
Generating train split: 43442496 examples [44:07, 39466.43 examples/s]
Generating train split: 43449704 examples [44:07, 45262.54 examples/s]
Generating train split: 43455886 examples [44:08, 29144.55 examples/s]
Generating train split: 43460657 examples [44:08, 26132.75 examples/s]
Generating train split: 43468528 examples [44:08, 34129.75 examples/s]
Generating train split: 43474634 examples [44:08, 38934.26 examples/s]
Generating train split: 43480045 examples [44:08, 36869.81 examples/s]
Generating train split: 43484792 examples [44:09, 29184.33 examples/s]
Generating train split: 43488656 examples [44:09, 25668.79 examples/s]
Generating train split: 43491910 examples [44:09, 25784.91 examples/s]
Generating train split: 43494974 examples [44:09, 23870.65 examples/s]
Generating train split: 43497690 examples [44:09, 22626.70 examples/s]
Generating train split: 43500159 examples [44:09, 19810.64 examples/s]
Generating train split: 43502320 examples [44:09, 19717.83 examples/s]
Generating train split: 43504410 examples [44:10, 16750.11 examples/s]
Generating train split: 43506203 examples [44:10, 16187.76 examples/s]
Generating train split: 43508869 examples [44:10, 18413.68 examples/s]
Generating train split: 43511219 examples [44:10, 19558.24 examples/s]
Generating train split: 43513295 examples [44:10, 11304.12 examples/s]
Generating train split: 43515350 examples [44:11, 12864.54 examples/s]
Generating train split: 43517089 examples [44:11, 12722.40 examples/s]
Generating train split: 43519206 examples [44:11, 14304.22 examples/s]
Generating train split: 43520926 examples [44:11, 13357.45 examples/s]
Generating train split: 43522462 examples [44:11, 13581.80 examples/s]
Generating train split: 43523980 examples [44:11, 12258.16 examples/s]
Generating train split: 43525322 examples [44:11, 12215.96 examples/s]
Generating train split: 43526688 examples [44:11, 12562.32 examples/s]
Generating train split: 43528680 examples [44:11, 14440.95 examples/s]
Generating train split: 43530201 examples [44:12, 12804.60 examples/s]
Generating train split: 43531839 examples [44:12, 13703.14 examples/s]
Generating train split: 43535308 examples [44:12, 19240.78 examples/s]
Generating train split: 43542857 examples [44:12, 34639.01 examples/s]
Generating train split: 43549396 examples [44:12, 43274.90 examples/s]
Generating train split: 43553948 examples [44:12, 31455.91 examples/s]
Generating train split: 43557714 examples [44:13, 24253.58 examples/s]
Generating train split: 43560791 examples [44:13, 19728.23 examples/s]
Generating train split: 43565326 examples [44:13, 24223.05 examples/s]
Generating train split: 43571336 examples [44:13, 31419.32 examples/s]
Generating train split: 43576064 examples [44:13, 34941.57 examples/s]
Generating train split: 43582181 examples [44:13, 41266.80 examples/s]
Generating train split: 43587505 examples [44:13, 44291.84 examples/s]
Generating train split: 43593719 examples [44:13, 49066.34 examples/s]
Generating train split: 43599044 examples [44:14, 32440.83 examples/s]
Generating train split: 43604901 examples [44:14, 37742.23 examples/s]
Generating train split: 43609637 examples [44:14, 33273.77 examples/s]
Generating train split: 43614036 examples [44:14, 35512.90 examples/s]
Generating train split: 43618202 examples [44:14, 36189.37 examples/s]
Generating train split: 43622607 examples [44:14, 38104.90 examples/s]
Generating train split: 43627750 examples [44:14, 41014.04 examples/s]
Generating train split: 43634017 examples [44:14, 46795.68 examples/s]
Generating train split: 43638975 examples [44:15, 47041.86 examples/s]
Generating train split: 43643868 examples [44:15, 38213.04 examples/s]
Generating train split: 43648086 examples [44:15, 38220.48 examples/s]
Generating train split: 43653496 examples [44:15, 42244.92 examples/s]
Generating train split: 43659674 examples [44:15, 47431.57 examples/s]
Generating train split: 43666161 examples [44:15, 52226.73 examples/s]
Generating train split: 43671604 examples [44:15, 50398.67 examples/s]
Generating train split: 43676815 examples [44:15, 48315.98 examples/s]
Generating train split: 43681771 examples [44:16, 40315.32 examples/s]
Generating train split: 43686088 examples [44:16, 34418.47 examples/s]
Generating train split: 43690944 examples [44:16, 37494.55 examples/s]
Generating train split: 43695640 examples [44:16, 39775.92 examples/s]
Generating train split: 43699935 examples [44:16, 40591.38 examples/s]
Generating train split: 43704463 examples [44:16, 41847.49 examples/s]
Generating train split: 43710024 examples [44:16, 45656.14 examples/s]
Generating train split: 43714730 examples [44:16, 41582.66 examples/s]
Generating train split: 43719058 examples [44:17, 36906.73 examples/s]
Generating train split: 43723602 examples [44:17, 39049.31 examples/s]
Generating train split: 43728481 examples [44:17, 41607.98 examples/s]
Generating train split: 43734414 examples [44:17, 46410.86 examples/s]
Generating train split: 43739211 examples [44:17, 44743.54 examples/s]
Generating train split: 43743807 examples [44:17, 44968.05 examples/s]
Generating train split: 43748662 examples [44:17, 45981.22 examples/s]
Generating train split: 43754412 examples [44:17, 49291.82 examples/s]
Generating train split: 43761038 examples [44:17, 54212.30 examples/s]
Generating train split: 43767383 examples [44:17, 56908.69 examples/s]
Generating train split: 43773118 examples [44:18, 55391.70 examples/s]
Generating train split: 43779501 examples [44:18, 57501.07 examples/s]
Generating train split: 43785288 examples [44:18, 35958.80 examples/s]
Generating train split: 43793032 examples [44:18, 44532.92 examples/s]
Generating train split: 43799432 examples [44:18, 48971.26 examples/s]
Generating train split: 43806111 examples [44:18, 53337.55 examples/s]
Generating train split: 43814799 examples [44:18, 62032.07 examples/s]
Generating train split: 43821658 examples [44:19, 51353.17 examples/s]
Generating train split: 43827544 examples [44:19, 34762.66 examples/s]
Generating train split: 43832211 examples [44:19, 25535.39 examples/s]
Generating train split: 43835896 examples [44:19, 24168.40 examples/s]
Generating train split: 43839072 examples [44:20, 20212.43 examples/s]
Generating train split: 43841870 examples [44:20, 21408.02 examples/s]
Generating train split: 43845870 examples [44:20, 24764.48 examples/s]
Generating train split: 43850742 examples [44:20, 29675.66 examples/s]
Generating train split: 43859535 examples [44:20, 42891.75 examples/s]
Generating train split: 43865834 examples [44:20, 47795.76 examples/s]
Generating train split: 43871330 examples [44:20, 46221.06 examples/s]
Generating train split: 43876467 examples [44:21, 37030.07 examples/s]
Generating train split: 43880790 examples [44:21, 28423.23 examples/s]
Generating train split: 43886228 examples [44:21, 33351.82 examples/s]
Generating train split: 43894791 examples [44:21, 44502.55 examples/s]
Generating train split: 43900231 examples [44:21, 34426.73 examples/s]
Generating train split: 43907103 examples [44:21, 41181.97 examples/s]
Generating train split: 43915462 examples [44:21, 50485.19 examples/s]
Generating train split: 43921593 examples [44:22, 34322.96 examples/s]
Generating train split: 43926465 examples [44:22, 36906.42 examples/s]
Generating train split: 43931326 examples [44:22, 39062.10 examples/s]
Generating train split: 43937001 examples [44:22, 43047.14 examples/s]
Generating train split: 43947840 examples [44:22, 58957.28 examples/s]
Generating train split: 43955897 examples [44:22, 64517.69 examples/s]
Generating train split: 43963070 examples [44:23, 25114.16 examples/s]
Generating train split: 43968394 examples [44:24, 15759.15 examples/s]
Generating train split: 43972336 examples [44:24, 13010.85 examples/s]
Generating train split: 43975325 examples [44:24, 13178.67 examples/s]
Generating train split: 43977839 examples [44:25, 11951.21 examples/s]
Generating train split: 43979848 examples [44:25, 12392.92 examples/s]
Generating train split: 43981716 examples [44:25, 12442.49 examples/s]
Generating train split: 43988920 examples [44:25, 21228.36 examples/s]
Generating train split: 43999197 examples [44:25, 35409.70 examples/s]
Generating train split: 44004613 examples [44:25, 34301.54 examples/s]
Generating train split: 44009356 examples [44:26, 31453.20 examples/s]
Generating train split: 44013437 examples [44:26, 25017.66 examples/s]
Generating train split: 44016756 examples [44:26, 26364.89 examples/s]
Generating train split: 44020064 examples [44:26, 22742.96 examples/s]
Generating train split: 44022862 examples [44:26, 23228.77 examples/s]
Generating train split: 44028766 examples [44:26, 30699.94 examples/s]
Generating train split: 44037908 examples [44:27, 44637.56 examples/s]
Generating train split: 44043215 examples [44:27, 38618.29 examples/s]
Generating train split: 44047789 examples [44:27, 27389.74 examples/s]
Generating train split: 44051437 examples [44:27, 18753.97 examples/s]
Generating train split: 44054477 examples [44:28, 20409.29 examples/s]
Generating train split: 44060376 examples [44:28, 26930.22 examples/s]
Generating train split: 44064180 examples [44:28, 22545.40 examples/s]
Generating train split: 44067294 examples [44:28, 23926.00 examples/s]
Generating train split: 44071150 examples [44:28, 26824.18 examples/s]
Generating train split: 44074455 examples [44:28, 26263.86 examples/s]
Generating train split: 44077517 examples [44:29, 18498.77 examples/s]
Generating train split: 44080107 examples [44:29, 19511.00 examples/s]
Generating train split: 44083743 examples [44:29, 22931.43 examples/s]
Generating train split: 44087355 examples [44:29, 25890.72 examples/s]
Generating train split: 44090394 examples [44:29, 21060.25 examples/s]
Generating train split: 44094923 examples [44:29, 26221.31 examples/s]
Generating train split: 44098971 examples [44:29, 29469.99 examples/s]
Generating train split: 44102369 examples [44:29, 26831.82 examples/s]
Generating train split: 44105663 examples [44:29, 28278.44 examples/s]
Generating train split: 44108778 examples [44:30, 27918.43 examples/s]
Generating train split: 44111771 examples [44:30, 22017.80 examples/s]
Generating train split: 44114290 examples [44:30, 22269.21 examples/s]
Generating train split: 44116747 examples [44:30, 21058.52 examples/s]
Generating train split: 44119024 examples [44:30, 18531.72 examples/s]
Generating train split: 44121021 examples [44:31, 12350.54 examples/s]
Generating train split: 44122811 examples [44:31, 13319.26 examples/s]
Generating train split: 44124461 examples [44:31, 12844.30 examples/s]
Generating train split: 44125955 examples [44:31, 13032.15 examples/s]
Generating train split: 44127413 examples [44:31, 11584.66 examples/s]
Generating train split: 44128694 examples [44:31, 10037.59 examples/s]
Generating train split: 44129804 examples [44:31, 10143.03 examples/s]
Generating train split: 44130894 examples [44:32, 6876.49 examples/s] 
Generating train split: 44132285 examples [44:32, 8124.54 examples/s]
Generating train split: 44133314 examples [44:32, 7638.01 examples/s]
Generating train split: 44134229 examples [44:32, 7431.22 examples/s]
Generating train split: 44135168 examples [44:32, 7717.47 examples/s]
Generating train split: 44136017 examples [44:32, 7665.33 examples/s]
Generating train split: 44137556 examples [44:32, 8972.72 examples/s]
Generating train split: 44138505 examples [44:33, 7142.97 examples/s]
Generating train split: 44144909 examples [44:33, 19458.31 examples/s]
Generating train split: 44152795 examples [44:33, 33482.22 examples/s]
Generating train split: 44156892 examples [44:33, 23334.27 examples/s]
Generating train split: 44160170 examples [44:33, 21924.33 examples/s]
Generating train split: 44163034 examples [44:34, 19311.61 examples/s]
Generating train split: 44165461 examples [44:34, 19988.36 examples/s]
Generating train split: 44173739 examples [44:34, 33064.84 examples/s]
Generating train split: 44181898 examples [44:34, 44193.73 examples/s]
Generating train split: 44187246 examples [44:34, 26539.60 examples/s]
Generating train split: 44191393 examples [44:34, 24457.15 examples/s]
Generating train split: 44194888 examples [44:35, 16705.81 examples/s]
Generating train split: 44197574 examples [44:35, 16359.20 examples/s]
Generating train split: 44199908 examples [44:35, 17213.86 examples/s]
Generating train split: 44202203 examples [44:35, 13367.62 examples/s]
Generating train split: 44207830 examples [44:36, 19912.05 examples/s]
Generating train split: 44216279 examples [44:36, 31463.67 examples/s]
Generating train split: 44220894 examples [44:36, 29950.53 examples/s]
Generating train split: 44224927 examples [44:37, 12901.56 examples/s]
Generating train split: 44227898 examples [44:37, 13816.68 examples/s]
Generating train split: 44230542 examples [44:37, 11372.01 examples/s]
Generating train split: 44232603 examples [44:37, 11090.37 examples/s]
Generating train split: 44234347 examples [44:38, 8656.33 examples/s] 
Generating train split: 44235703 examples [44:38, 9187.72 examples/s]
Generating train split: 44237041 examples [44:38, 9408.83 examples/s]
Generating train split: 44238297 examples [44:38, 9070.18 examples/s]
Generating train split: 44240234 examples [44:38, 10831.34 examples/s]
Generating train split: 44241590 examples [44:39, 9072.62 examples/s] 
Generating train split: 44242891 examples [44:39, 9777.11 examples/s]
Generating train split: 44244065 examples [44:39, 8039.02 examples/s]
Generating train split: 44245786 examples [44:39, 9788.53 examples/s]
Generating train split: 44246991 examples [44:39, 7995.00 examples/s]
Generating train split: 44249618 examples [44:39, 11503.81 examples/s]
Generating train split: 44251488 examples [44:39, 13050.89 examples/s]
Generating train split: 44253087 examples [44:40, 10455.15 examples/s]
Generating train split: 44254669 examples [44:40, 11294.04 examples/s]
Generating train split: 44256024 examples [44:40, 11366.68 examples/s]
Generating train split: 44257333 examples [44:40, 11428.96 examples/s]
Generating train split: 44258593 examples [44:40, 10469.22 examples/s]
Generating train split: 44259795 examples [44:40, 10172.54 examples/s]
Generating train split: 44260878 examples [44:40, 9215.30 examples/s] 
Generating train split: 44262694 examples [44:41, 11312.24 examples/s]
Generating train split: 44263927 examples [44:41, 5360.43 examples/s] 
Generating train split: 44264855 examples [44:41, 5710.20 examples/s]
Generating train split: 44265956 examples [44:41, 6559.67 examples/s]
Generating train split: 44266899 examples [44:42, 3718.74 examples/s]
Generating train split: 44267607 examples [44:42, 2911.58 examples/s]
Generating train split: 44268147 examples [44:43, 2657.31 examples/s]
Generating train split: 44268584 examples [44:43, 2478.40 examples/s]
Generating train split: 44269783 examples [44:43, 3679.81 examples/s]
Generating train split: 44270397 examples [44:43, 2909.70 examples/s]
Generating train split: 44270910 examples [44:43, 3210.51 examples/s]
Generating train split: 44274073 examples [44:43, 7818.44 examples/s]
Generating train split: 44275675 examples [44:44, 9357.06 examples/s]
Generating train split: 44277068 examples [44:44, 9117.70 examples/s]
Generating train split: 44278307 examples [44:44, 9642.56 examples/s]
Generating train split: 44279512 examples [44:44, 9629.41 examples/s]
Generating train split: 44281653 examples [44:44, 12401.74 examples/s]
Generating train split: 44283310 examples [44:44, 13440.85 examples/s]
Generating train split: 44285729 examples [44:44, 16281.41 examples/s]
Generating train split: 44287944 examples [44:44, 17888.05 examples/s]
Generating train split: 44290222 examples [44:44, 19254.89 examples/s]
Generating train split: 44292240 examples [44:45, 15103.95 examples/s]
Generating train split: 44294046 examples [44:45, 15774.00 examples/s]
Generating train split: 44295785 examples [44:45, 14543.99 examples/s]
Generating train split: 44298453 examples [44:45, 17475.62 examples/s]
Generating train split: 44300348 examples [44:45, 17504.55 examples/s]
Generating train split: 44302213 examples [44:45, 17776.41 examples/s]
Generating train split: 44308046 examples [44:45, 28946.75 examples/s]
Generating train split: 44314361 examples [44:46, 30514.30 examples/s]
Generating train split: 44317477 examples [44:46, 27281.46 examples/s]
Generating train split: 44320959 examples [44:46, 29045.32 examples/s]
Generating train split: 44323961 examples [44:46, 28333.18 examples/s]
Generating train split: 44331635 examples [44:46, 40806.63 examples/s]
Generating train split: 44339147 examples [44:46, 50038.37 examples/s]
Generating train split: 44344430 examples [44:46, 45658.44 examples/s]
Generating train split: 44352353 examples [44:46, 54462.20 examples/s]
Generating train split: 44359729 examples [44:46, 59710.18 examples/s]
Generating train split: 44365976 examples [44:47, 30841.28 examples/s]
Generating train split: 44370773 examples [44:47, 27544.26 examples/s]
Generating train split: 44374745 examples [44:47, 21699.31 examples/s]
Generating train split: 44377908 examples [44:48, 18143.95 examples/s]
Generating train split: 44380461 examples [44:48, 16727.05 examples/s]
Generating train split: 44383871 examples [44:48, 19330.84 examples/s]
Generating train split: 44391985 examples [44:48, 30236.94 examples/s]
Generating train split: 44398349 examples [44:48, 36958.88 examples/s]
Generating train split: 44403201 examples [44:48, 29252.29 examples/s]
Generating train split: 44407175 examples [44:49, 21885.62 examples/s]
Generating train split: 44410330 examples [44:49, 18417.64 examples/s]
Generating train split: 44416709 examples [44:49, 25338.95 examples/s]
Generating train split: 44424762 examples [44:49, 35213.81 examples/s]
Generating train split: 44429772 examples [44:49, 31888.84 examples/s]
Generating train split: 44434049 examples [44:50, 32381.03 examples/s]
Generating train split: 44438055 examples [44:50, 27038.32 examples/s]
Generating train split: 44441399 examples [44:50, 21818.02 examples/s]
Generating train split: 44444137 examples [44:50, 22141.19 examples/s]
Generating train split: 44446758 examples [44:50, 21849.04 examples/s]
Generating train split: 44451892 examples [44:50, 28041.64 examples/s]
Generating train split: 44460968 examples [44:51, 42513.77 examples/s]
Generating train split: 44465973 examples [44:51, 31975.00 examples/s]
Generating train split: 44470064 examples [44:51, 31352.08 examples/s]
Generating train split: 44476903 examples [44:51, 39206.27 examples/s]
Generating train split: 44485132 examples [44:51, 48883.77 examples/s]
Generating train split: 44490815 examples [44:52, 28248.57 examples/s]
Generating train split: 44495187 examples [44:52, 24777.44 examples/s]
Generating train split: 44502352 examples [44:52, 32227.43 examples/s]
Generating train split: 44511105 examples [44:52, 42457.65 examples/s]
Generating train split: 44516998 examples [44:53, 23979.53 examples/s]
Generating train split: 44525151 examples [44:53, 31744.29 examples/s]
Generating train split: 44531992 examples [44:53, 37669.23 examples/s]
Generating train split: 44537940 examples [44:53, 40254.95 examples/s]
Generating train split: 44543591 examples [44:53, 40564.20 examples/s]
Generating train split: 44548791 examples [44:53, 30476.58 examples/s]
Generating train split: 44552978 examples [44:53, 28950.19 examples/s]
Generating train split: 44556649 examples [44:54, 29564.00 examples/s]
Generating train split: 44560185 examples [44:54, 24412.30 examples/s]
Generating train split: 44563127 examples [44:54, 22339.00 examples/s]
Generating train split: 44565703 examples [44:54, 22625.65 examples/s]
Generating train split: 44569207 examples [44:54, 25259.05 examples/s]
Generating train split: 44572023 examples [44:54, 22106.85 examples/s]
Generating train split: 44574478 examples [44:55, 18811.72 examples/s]
Generating train split: 44576580 examples [44:55, 18338.62 examples/s]
Generating train split: 44579082 examples [44:55, 19805.54 examples/s]
Generating train split: 44581223 examples [44:55, 17180.32 examples/s]
Generating train split: 44583096 examples [44:55, 13670.61 examples/s]
Generating train split: 44589679 examples [44:55, 24128.53 examples/s]
Generating train split: 44598603 examples [44:55, 38620.47 examples/s]
Generating train split: 44603423 examples [44:55, 39586.00 examples/s]
Generating train split: 44608069 examples [44:56, 19627.10 examples/s]
Generating train split: 44611581 examples [44:56, 17441.36 examples/s]
Generating train split: 44614419 examples [44:57, 16170.17 examples/s]
Generating train split: 44616790 examples [44:57, 17206.21 examples/s]
Generating train split: 44620483 examples [44:57, 20598.18 examples/s]
Generating train split: 44623228 examples [44:57, 15619.52 examples/s]
Generating train split: 44625426 examples [44:57, 15996.64 examples/s]
Generating train split: 44629002 examples [44:57, 19491.55 examples/s]
Generating train split: 44631474 examples [44:57, 20115.86 examples/s]
Generating train split: 44633867 examples [44:58, 16792.82 examples/s]
Generating train split: 44636770 examples [44:58, 19300.93 examples/s]
Generating train split: 44645140 examples [44:58, 33897.13 examples/s]
Generating train split: 44653094 examples [44:58, 44809.38 examples/s]
Generating train split: 44658307 examples [44:58, 45255.16 examples/s]
Generating train split: 44666028 examples [44:58, 53646.86 examples/s]
Generating train split: 44672285 examples [44:58, 56066.36 examples/s]
Generating train split: 44680373 examples [44:58, 63028.30 examples/s]
Generating train split: 44686977 examples [44:58, 63537.78 examples/s]
Generating train split: 44694381 examples [44:58, 66450.98 examples/s]
Generating train split: 44701193 examples [44:59, 65467.96 examples/s]
Generating train split: 44708661 examples [44:59, 68133.90 examples/s]
Generating train split: 44715582 examples [44:59, 67705.75 examples/s]
Generating train split: 44722422 examples [44:59, 65626.54 examples/s]
Generating train split: 44729255 examples [44:59, 66402.22 examples/s]
Generating train split: 44736661 examples [44:59, 68614.94 examples/s]
Generating train split: 44744781 examples [44:59, 72294.08 examples/s]
Generating train split: 44753118 examples [44:59, 75564.27 examples/s]
Generating train split: 44760704 examples [44:59, 71229.79 examples/s]
Generating train split: 44767898 examples [45:00, 68932.33 examples/s]
Generating train split: 44775696 examples [45:00, 71475.81 examples/s]
Generating train split: 44782901 examples [45:00, 69627.68 examples/s]
Generating train split: 44790776 examples [45:00, 72212.44 examples/s]
Generating train split: 44798052 examples [45:00, 70133.57 examples/s]
Generating train split: 44806201 examples [45:00, 73365.59 examples/s]
Generating train split: 44813927 examples [45:00, 74492.62 examples/s]
Generating train split: 44821410 examples [45:00, 74315.33 examples/s]
Generating train split: 44830581 examples [45:00, 79387.29 examples/s]
Generating train split: 44838548 examples [45:00, 76144.72 examples/s]
Generating train split: 44846212 examples [45:01, 73474.05 examples/s]
Generating train split: 44854547 examples [45:01, 76249.12 examples/s]
Generating train split: 44862217 examples [45:01, 73779.60 examples/s]
Generating train split: 44872053 examples [45:01, 80745.99 examples/s]
Generating train split: 44880194 examples [45:01, 73481.56 examples/s]
Generating train split: 44887706 examples [45:01, 67012.47 examples/s]
Generating train split: 44894619 examples [45:01, 56299.62 examples/s]
Generating train split: 44900622 examples [45:02, 53014.07 examples/s]
Generating train split: 44906184 examples [45:02, 48152.80 examples/s]
Generating train split: 44913987 examples [45:02, 55142.47 examples/s]
Generating train split: 44924541 examples [45:02, 67785.81 examples/s]
Generating train split: 44931805 examples [45:02, 32570.24 examples/s]
Generating train split: 44937303 examples [45:03, 30173.57 examples/s]
Generating train split: 44941888 examples [45:03, 23384.55 examples/s]
Generating train split: 44945479 examples [45:03, 23676.01 examples/s]
Generating train split: 44948741 examples [45:03, 20498.70 examples/s]
Generating train split: 44951430 examples [45:03, 20368.77 examples/s]
Generating train split: 44960325 examples [45:04, 32153.13 examples/s]
Generating train split: 44968074 examples [45:04, 41083.14 examples/s]
Generating train split: 44973486 examples [45:04, 35490.04 examples/s]
Generating train split: 44978052 examples [45:04, 22406.09 examples/s]
Generating train split: 44981563 examples [45:05, 18063.65 examples/s]
Generating train split: 44984341 examples [45:05, 13212.70 examples/s]
Generating train split: 44986471 examples [45:06, 9270.66 examples/s] 
Generating train split: 44988088 examples [45:06, 9058.26 examples/s]
Generating train split: 44989464 examples [45:06, 9027.26 examples/s]
Generating train split: 44990688 examples [45:06, 8960.40 examples/s]
Generating train split: 44994444 examples [45:06, 13301.98 examples/s]
Generating train split: 44996745 examples [45:06, 15010.24 examples/s]
Generating train split: 44999849 examples [45:06, 18199.76 examples/s]
Generating train split: 45002199 examples [45:07, 15119.53 examples/s]
Generating train split: 45004150 examples [45:07, 14337.79 examples/s]
Generating train split: 45005890 examples [45:07, 11236.86 examples/s]
Generating train split: 45008804 examples [45:07, 14427.34 examples/s]
Generating train split: 45012670 examples [45:07, 19352.95 examples/s]
Generating train split: 45015127 examples [45:08, 14596.22 examples/s]
Generating train split: 45017113 examples [45:08, 14530.08 examples/s]
Generating train split: 45018936 examples [45:08, 14994.04 examples/s]
Generating train split: 45020717 examples [45:08, 11354.14 examples/s]
Generating train split: 45027736 examples [45:08, 22225.91 examples/s]
Generating train split: 45035717 examples [45:08, 34251.27 examples/s]
Generating train split: 45040290 examples [45:08, 35931.09 examples/s]
Generating train split: 45044726 examples [45:09, 20735.48 examples/s]
Generating train split: 45048141 examples [45:09, 22780.43 examples/s]
Generating train split: 45052453 examples [45:09, 25775.25 examples/s]
Generating train split: 45055947 examples [45:09, 18520.24 examples/s]
Generating train split: 45059113 examples [45:10, 20660.06 examples/s]
Generating train split: 45064955 examples [45:10, 27797.56 examples/s]
Generating train split: 45072335 examples [45:10, 37577.63 examples/s]
Generating train split: 45078386 examples [45:10, 42915.33 examples/s]
Generating train split: 45083598 examples [45:10, 27779.78 examples/s]
Generating train split: 45087689 examples [45:10, 28364.65 examples/s]
Generating train split: 45091470 examples [45:11, 18757.81 examples/s]
Generating train split: 45094948 examples [45:11, 21113.51 examples/s]
Generating train split: 45101629 examples [45:11, 29047.65 examples/s]
Generating train split: 45107427 examples [45:11, 34797.43 examples/s]
Generating train split: 45112081 examples [45:11, 26863.42 examples/s]
Generating train split: 45115852 examples [45:12, 20315.62 examples/s]
Generating train split: 45123830 examples [45:12, 29639.50 examples/s]
Generating train split: 45130251 examples [45:12, 35955.52 examples/s]
Generating train split: 45135313 examples [45:12, 20342.76 examples/s]
Generating train split: 45139143 examples [45:13, 21198.51 examples/s]
Generating train split: 45142563 examples [45:13, 16634.70 examples/s]
Generating train split: 45149504 examples [45:13, 23719.06 examples/s]
Generating train split: 45157680 examples [45:13, 33058.62 examples/s]
Generating train split: 45162905 examples [45:13, 30974.25 examples/s]
Generating train split: 45167354 examples [45:13, 32107.88 examples/s]
Generating train split: 45174435 examples [45:13, 39900.14 examples/s]
Generating train split: 45182290 examples [45:14, 47777.28 examples/s]
Generating train split: 45188033 examples [45:14, 31055.61 examples/s]
Generating train split: 45192542 examples [45:14, 32492.60 examples/s]
Generating train split: 45196850 examples [45:14, 32785.49 examples/s]
Generating train split: 45203363 examples [45:14, 39534.76 examples/s]
Generating train split: 45208137 examples [45:15, 24423.61 examples/s]
Generating train split: 45211841 examples [45:15, 24893.76 examples/s]
Generating train split: 45215463 examples [45:15, 26899.97 examples/s]
Generating train split: 45220996 examples [45:15, 32681.77 examples/s]
Generating train split: 45228522 examples [45:15, 42259.09 examples/s]
Generating train split: 45233635 examples [45:15, 27792.99 examples/s]
Generating train split: 45237655 examples [45:16, 26829.95 examples/s]
Generating train split: 45241194 examples [45:16, 27848.93 examples/s]
Generating train split: 45246400 examples [45:16, 32844.61 examples/s]
Generating train split: 45250365 examples [45:16, 24197.69 examples/s]
Generating train split: 45253779 examples [45:16, 26032.04 examples/s]
Generating train split: 45257037 examples [45:16, 26385.59 examples/s]
Generating train split: 45260671 examples [45:16, 28606.09 examples/s]
Generating train split: 45266021 examples [45:17, 34641.47 examples/s]
Generating train split: 45272670 examples [45:17, 42823.35 examples/s]
Generating train split: 45279588 examples [45:17, 49418.80 examples/s]
Generating train split: 45284897 examples [45:17, 28427.39 examples/s]
Generating train split: 45290150 examples [45:17, 32796.64 examples/s]
Generating train split: 45294624 examples [45:17, 31607.97 examples/s]
Generating train split: 45298624 examples [45:18, 22199.56 examples/s]
Generating train split: 45306485 examples [45:18, 31532.92 examples/s]
Generating train split: 45314747 examples [45:18, 41293.26 examples/s]
Generating train split: 45320416 examples [45:18, 39877.62 examples/s]
Generating train split: 45325484 examples [45:18, 38703.94 examples/s]
Generating train split: 45332993 examples [45:18, 46702.54 examples/s]
Generating train split: 45338476 examples [45:19, 30727.02 examples/s]
Generating train split: 45342796 examples [45:19, 31605.18 examples/s]
Generating train split: 45347268 examples [45:19, 34161.22 examples/s]
Generating train split: 45351458 examples [45:19, 34726.47 examples/s]
Generating train split: 45355486 examples [45:19, 22292.04 examples/s]
Generating train split: 45358637 examples [45:20, 23505.33 examples/s]
Generating train split: 45361712 examples [45:20, 24748.84 examples/s]
Generating train split: 45364759 examples [45:20, 15965.37 examples/s]
Generating train split: 45367131 examples [45:20, 17175.57 examples/s]
Generating train split: 45369498 examples [45:20, 14085.35 examples/s]
Generating train split: 45371419 examples [45:21, 14334.21 examples/s]
Generating train split: 45373227 examples [45:21, 14284.34 examples/s]
Generating train split: 45374915 examples [45:21, 11345.04 examples/s]
Generating train split: 45376312 examples [45:21, 9021.51 examples/s] 
Generating train split: 45377811 examples [45:21, 9993.69 examples/s]
Generating train split: 45379378 examples [45:21, 11073.82 examples/s]
Generating train split: 45381312 examples [45:21, 12697.68 examples/s]
Generating train split: 45383566 examples [45:22, 14711.29 examples/s]
Generating train split: 45385234 examples [45:22, 14846.30 examples/s]
Generating train split: 45388860 examples [45:22, 20313.08 examples/s]
Generating train split: 45396475 examples [45:22, 35227.56 examples/s]
Generating train split: 45403346 examples [45:22, 42880.65 examples/s]
Generating train split: 45407861 examples [45:22, 30297.77 examples/s]
Generating train split: 45413421 examples [45:22, 35737.21 examples/s]
Generating train split: 45422394 examples [45:22, 48423.92 examples/s]
Generating train split: 45428060 examples [45:23, 48840.74 examples/s]
Generating train split: 45433529 examples [45:23, 43480.22 examples/s]
Generating train split: 45438377 examples [45:23, 26157.94 examples/s]
Generating train split: 45447398 examples [45:23, 36903.51 examples/s]
Generating train split: 45454010 examples [45:23, 42554.53 examples/s]
Generating train split: 45459734 examples [45:24, 29361.03 examples/s]
Generating train split: 45464240 examples [45:24, 22456.10 examples/s]
Generating train split: 45467763 examples [45:24, 24219.57 examples/s]
Generating train split: 45471266 examples [45:24, 25598.34 examples/s]
Generating train split: 45477006 examples [45:24, 31689.70 examples/s]
Generating train split: 45481112 examples [45:25, 18568.46 examples/s]
Generating train split: 45484247 examples [45:25, 13449.55 examples/s]
Generating train split: 45487516 examples [45:25, 15753.10 examples/s]
Generating train split: 45490186 examples [45:26, 14896.90 examples/s]
Generating train split: 45492428 examples [45:26, 13097.91 examples/s]
Generating train split: 45494270 examples [45:26, 13653.54 examples/s]
Generating train split: 45496055 examples [45:26, 14292.35 examples/s]
Generating train split: 45497824 examples [45:26, 11811.35 examples/s]
Generating train split: 45499291 examples [45:26, 12160.42 examples/s]
Generating train split: 45500781 examples [45:26, 12702.26 examples/s]
Generating train split: 45502230 examples [45:27, 12918.91 examples/s]
Generating train split: 45503654 examples [45:27, 12695.69 examples/s]
Generating train split: 45505023 examples [45:27, 8231.57 examples/s] 
Generating train split: 45507558 examples [45:27, 11371.76 examples/s]
Generating train split: 45509069 examples [45:28, 7264.06 examples/s] 
Generating train split: 45512384 examples [45:28, 11140.40 examples/s]
Generating train split: 45514202 examples [45:28, 8108.35 examples/s] 
Generating train split: 45515599 examples [45:28, 8198.25 examples/s]
Generating train split: 45516832 examples [45:28, 8445.65 examples/s]
Generating train split: 45517991 examples [45:28, 8851.87 examples/s]
Generating train split: 45519120 examples [45:29, 9285.17 examples/s]
Generating train split: 45521133 examples [45:29, 11660.14 examples/s]
Generating train split: 45523421 examples [45:29, 14339.10 examples/s]
Generating train split: 45525074 examples [45:29, 14737.62 examples/s]
Generating train split: 45526707 examples [45:29, 14972.64 examples/s]
Generating train split: 45534917 examples [45:29, 33207.32 examples/s]
Generating train split: 45541732 examples [45:29, 42965.64 examples/s]
Generating train split: 45546291 examples [45:30, 25940.17 examples/s]
Generating train split: 45549888 examples [45:30, 25811.82 examples/s]
Generating train split: 45553164 examples [45:30, 19589.05 examples/s]
Generating train split: 45555807 examples [45:30, 17608.56 examples/s]
Generating train split: 45558403 examples [45:30, 18727.15 examples/s]
Generating train split: 45560676 examples [45:30, 17890.19 examples/s]
Generating train split: 45564039 examples [45:31, 17115.31 examples/s]
Generating train split: 45565961 examples [45:31, 11948.46 examples/s]
Generating train split: 45567475 examples [45:31, 9322.48 examples/s] 
Generating train split: 45570077 examples [45:31, 11705.70 examples/s]
Generating train split: 45571691 examples [45:32, 11250.57 examples/s]
Generating train split: 45573129 examples [45:32, 9999.37 examples/s] 
Generating train split: 45575721 examples [45:32, 12783.69 examples/s]
Generating train split: 45577326 examples [45:32, 10300.10 examples/s]
Generating train split: 45579488 examples [45:32, 12308.57 examples/s]
Generating train split: 45581047 examples [45:33, 7539.38 examples/s] 
Generating train split: 45582241 examples [45:33, 6750.94 examples/s]
Generating train split: 45583429 examples [45:33, 7392.17 examples/s]
Generating train split: 45584451 examples [45:33, 5953.27 examples/s]
Generating train split: 45585274 examples [45:34, 5388.99 examples/s]
Generating train split: 45586289 examples [45:34, 6045.63 examples/s]
Generating train split: 45587052 examples [45:34, 5665.59 examples/s]
Generating train split: 45587723 examples [45:34, 5303.81 examples/s]
Generating train split: 45589271 examples [45:34, 7285.24 examples/s]
Generating train split: 45591479 examples [45:34, 10477.35 examples/s]
Generating train split: 45592741 examples [45:34, 10891.12 examples/s]
Generating train split: 45594633 examples [45:34, 12889.88 examples/s]
Generating train split: 45597623 examples [45:34, 17378.93 examples/s]
Generating train split: 45599533 examples [45:35, 15850.77 examples/s]
Generating train split: 45607007 examples [45:35, 31029.77 examples/s]
Generating train split: 45615469 examples [45:35, 45440.76 examples/s]
Generating train split: 45620430 examples [45:35, 33470.18 examples/s]
Generating train split: 45624517 examples [45:35, 28849.54 examples/s]
Generating train split: 45627996 examples [45:35, 24267.22 examples/s]
Generating train split: 45630928 examples [45:36, 23583.23 examples/s]
Generating train split: 45637634 examples [45:36, 32457.49 examples/s]
Generating train split: 45646655 examples [45:36, 45491.00 examples/s]
Generating train split: 45652094 examples [45:36, 39896.28 examples/s]
Generating train split: 45656804 examples [45:36, 24314.17 examples/s]
Generating train split: 45665174 examples [45:36, 33746.78 examples/s]
Generating train split: 45672330 examples [45:37, 40731.33 examples/s]
Generating train split: 45678025 examples [45:37, 32803.11 examples/s]
Generating train split: 45682656 examples [45:37, 24850.18 examples/s]
Generating train split: 45686314 examples [45:37, 24868.83 examples/s]
Generating train split: 45689624 examples [45:37, 25898.80 examples/s]
Generating train split: 45692860 examples [45:38, 22076.56 examples/s]
Generating train split: 45695574 examples [45:38, 20337.40 examples/s]
Generating train split: 45699083 examples [45:38, 23099.14 examples/s]
Generating train split: 45701796 examples [45:38, 22327.15 examples/s]
Generating train split: 45704299 examples [45:38, 17435.35 examples/s]
Generating train split: 45706373 examples [45:38, 16984.78 examples/s]
Generating train split: 45708289 examples [45:39, 14546.27 examples/s]
Generating train split: 45710170 examples [45:39, 15379.60 examples/s]
Generating train split: 45711887 examples [45:39, 13818.60 examples/s]
Generating train split: 45713921 examples [45:39, 15196.60 examples/s]
Generating train split: 45716091 examples [45:39, 16713.42 examples/s]
Generating train split: 45718315 examples [45:39, 17980.78 examples/s]
Generating train split: 45720232 examples [45:39, 12424.43 examples/s]
Generating train split: 45722583 examples [45:40, 14672.72 examples/s]
Generating train split: 45727582 examples [45:40, 22610.66 examples/s]
Generating train split: 45732738 examples [45:40, 29631.76 examples/s]
Generating train split: 45736207 examples [45:40, 23842.57 examples/s]
Generating train split: 45740364 examples [45:40, 27747.27 examples/s]
Generating train split: 45743652 examples [45:40, 25025.75 examples/s]
Generating train split: 45747010 examples [45:40, 26972.60 examples/s]
Generating train split: 45754994 examples [45:40, 39972.17 examples/s]
Generating train split: 45762574 examples [45:41, 49270.77 examples/s]
Generating train split: 45768008 examples [45:41, 34671.62 examples/s]
Generating train split: 45772419 examples [45:41, 27056.99 examples/s]
Generating train split: 45776791 examples [45:41, 30060.01 examples/s]
Generating train split: 45780608 examples [45:41, 27671.13 examples/s]
Generating train split: 45784281 examples [45:41, 29481.66 examples/s]
Generating train split: 45788801 examples [45:42, 32967.64 examples/s]
Generating train split: 45792560 examples [45:42, 31207.17 examples/s]
Generating train split: 45796008 examples [45:42, 30646.07 examples/s]
Generating train split: 45799309 examples [45:42, 26791.89 examples/s]
Generating train split: 45802211 examples [45:42, 21528.40 examples/s]
Generating train split: 45804641 examples [45:42, 22069.30 examples/s]
Generating train split: 45807572 examples [45:42, 23724.32 examples/s]
Generating train split: 45810153 examples [45:43, 23795.61 examples/s]
Generating train split: 45812682 examples [45:43, 19798.20 examples/s]
Generating train split: 45814859 examples [45:43, 16550.73 examples/s]
Generating train split: 45817154 examples [45:43, 17907.70 examples/s]
Generating train split: 45819145 examples [45:43, 18115.77 examples/s]
Generating train split: 45821208 examples [45:43, 18566.43 examples/s]
Generating train split: 45823172 examples [45:43, 18815.19 examples/s]
Generating train split: 45825737 examples [45:43, 20642.03 examples/s]
Generating train split: 45827880 examples [45:44, 20546.13 examples/s]
Generating train split: 45831203 examples [45:44, 24091.33 examples/s]
Generating train split: 45833679 examples [45:44, 19289.35 examples/s]
Generating train split: 45836224 examples [45:44, 20683.25 examples/s]
Generating train split: 45838459 examples [45:44, 20803.63 examples/s]
Generating train split: 45840661 examples [45:44, 17263.35 examples/s]
Generating train split: 45842563 examples [45:44, 14562.82 examples/s]
Generating train split: 45844200 examples [45:45, 14240.09 examples/s]
Generating train split: 45846992 examples [45:45, 17367.04 examples/s]
Generating train split: 45850091 examples [45:45, 20696.56 examples/s]
Generating train split: 45852355 examples [45:45, 20058.97 examples/s]
Generating train split: 45854500 examples [45:45, 19504.14 examples/s]
Generating train split: 45856557 examples [45:45, 19531.14 examples/s]
Generating train split: 45860726 examples [45:45, 25505.13 examples/s]
Generating train split: 45866149 examples [45:45, 33488.11 examples/s]
Generating train split: 45869646 examples [45:45, 29522.43 examples/s]
Generating train split: 45872786 examples [45:46, 26125.74 examples/s]
Generating train split: 45875585 examples [45:46, 25862.27 examples/s]
Generating train split: 45878298 examples [45:46, 25908.38 examples/s]
Generating train split: 45880976 examples [45:46, 25692.20 examples/s]
Generating train split: 45883617 examples [45:46, 17524.44 examples/s]
Generating train split: 45885756 examples [45:46, 17146.23 examples/s]
Generating train split: 45887909 examples [45:46, 18093.23 examples/s]
Generating train split: 45890961 examples [45:47, 21032.49 examples/s]
Generating train split: 45893294 examples [45:47, 17955.53 examples/s]
Generating train split: 45895786 examples [45:47, 19558.16 examples/s]
Generating train split: 45899932 examples [45:47, 24981.27 examples/s]
Generating train split: 45903732 examples [45:47, 28381.71 examples/s]
Generating train split: 45906811 examples [45:47, 27585.12 examples/s]
Generating train split: 45909738 examples [45:47, 17509.57 examples/s]
Generating train split: 45912057 examples [45:48, 15503.30 examples/s]
Generating train split: 45914025 examples [45:48, 13405.45 examples/s]
Generating train split: 45915677 examples [45:48, 12560.38 examples/s]
Generating train split: 45917307 examples [45:48, 13110.33 examples/s]
Generating train split: 45918791 examples [45:48, 13292.13 examples/s]
Generating train split: 45920330 examples [45:48, 13717.70 examples/s]
Generating train split: 45921810 examples [45:48, 12299.53 examples/s]
Generating train split: 45924765 examples [45:49, 16354.57 examples/s]
Generating train split: 45927611 examples [45:49, 19393.45 examples/s]
Generating train split: 45932557 examples [45:49, 27332.41 examples/s]
Generating train split: 45938461 examples [45:49, 36019.71 examples/s]
Generating train split: 45944811 examples [45:49, 43750.81 examples/s]
Generating train split: 45949409 examples [45:49, 24251.36 examples/s]
Generating train split: 45952988 examples [45:50, 13085.79 examples/s]
Generating train split: 45955688 examples [45:50, 14680.81 examples/s]
Generating train split: 45965699 examples [45:50, 26714.01 examples/s]
Generating train split: 45970975 examples [45:50, 31070.32 examples/s]
Generating train split: 45975974 examples [45:51, 21650.02 examples/s]
Generating train split: 45979847 examples [45:51, 22007.75 examples/s]
Generating train split: 45985178 examples [45:51, 27025.77 examples/s]
Generating train split: 45994587 examples [45:51, 39520.37 examples/s]
Generating train split: 46000196 examples [45:51, 27395.76 examples/s]
Generating train split: 46004575 examples [45:52, 27143.18 examples/s]
Generating train split: 46008433 examples [45:52, 19523.37 examples/s]
Generating train split: 46016803 examples [45:52, 28589.95 examples/s]
Generating train split: 46025653 examples [45:52, 38649.17 examples/s]
Generating train split: 46031536 examples [45:52, 35643.29 examples/s]
Generating train split: 46037144 examples [45:53, 39475.92 examples/s]
Generating train split: 46043620 examples [45:53, 44474.83 examples/s]
Generating train split: 46049120 examples [45:53, 31037.04 examples/s]
Generating train split: 46053485 examples [45:53, 32795.58 examples/s]
Generating train split: 46061972 examples [45:53, 43267.19 examples/s]
Generating train split: 46067848 examples [45:53, 46716.12 examples/s]
Generating train split: 46073485 examples [45:53, 46550.95 examples/s]
Generating train split: 46078824 examples [45:54, 27415.61 examples/s]
Generating train split: 46082953 examples [45:54, 29279.67 examples/s]
Generating train split: 46088033 examples [45:54, 33370.15 examples/s]
Generating train split: 46097919 examples [45:54, 47348.33 examples/s]
Generating train split: 46103925 examples [45:54, 38227.37 examples/s]
Generating train split: 46108897 examples [45:55, 28605.21 examples/s]
Generating train split: 46112867 examples [45:55, 21364.62 examples/s]
Generating train split: 46115988 examples [45:55, 19831.51 examples/s]
Generating train split: 46124203 examples [45:55, 29345.95 examples/s]
Generating train split: 46132291 examples [45:55, 38566.15 examples/s]
Generating train split: 46137743 examples [45:56, 25553.65 examples/s]
Generating train split: 46141953 examples [45:56, 21865.55 examples/s]
Generating train split: 46145340 examples [45:56, 17429.70 examples/s]
Generating train split: 46148006 examples [45:57, 15754.63 examples/s]
Generating train split: 46150206 examples [45:57, 14494.01 examples/s]
Generating train split: 46152066 examples [45:57, 10539.37 examples/s]
Generating train split: 46153509 examples [45:57, 10530.24 examples/s]
Generating train split: 46154833 examples [45:58, 8294.46 examples/s] 
Generating train split: 46155887 examples [45:58, 8603.23 examples/s]
Generating train split: 46158427 examples [45:58, 11368.59 examples/s]
Generating train split: 46162954 examples [45:58, 17823.24 examples/s]
Generating train split: 46165364 examples [45:58, 18747.91 examples/s]
Generating train split: 46170821 examples [45:58, 26990.71 examples/s]
Generating train split: 46175586 examples [45:58, 32100.27 examples/s]
Generating train split: 46179310 examples [45:59, 17722.54 examples/s]
Generating train split: 46182175 examples [45:59, 17264.08 examples/s]
Generating train split: 46184659 examples [45:59, 11174.79 examples/s]
Generating train split: 46186560 examples [46:00, 11085.17 examples/s]
Generating train split: 46188213 examples [46:00, 11082.63 examples/s]
Generating train split: 46190185 examples [46:00, 12469.92 examples/s]
Generating train split: 46191819 examples [46:00, 11888.42 examples/s]
Generating train split: 46193273 examples [46:00, 11494.35 examples/s]
Generating train split: 46194607 examples [46:00, 8458.49 examples/s] 
Generating train split: 46195671 examples [46:01, 6994.93 examples/s]
Generating train split: 46196648 examples [46:01, 7435.69 examples/s]
Generating train split: 46197551 examples [46:01, 7473.45 examples/s]
Generating train split: 46198760 examples [46:01, 8363.26 examples/s]
Generating train split: 46199721 examples [46:01, 6363.39 examples/s]
Generating train split: 46200998 examples [46:01, 7526.85 examples/s]
Generating train split: 46203127 examples [46:02, 10442.42 examples/s]
Generating train split: 46205315 examples [46:02, 13113.65 examples/s]
Generating train split: 46207679 examples [46:02, 15728.09 examples/s]
Generating train split: 46209473 examples [46:02, 16246.43 examples/s]
Generating train split: 46212034 examples [46:02, 18688.30 examples/s]
Generating train split: 46214043 examples [46:02, 14568.21 examples/s]
Generating train split: 46215866 examples [46:02, 15416.43 examples/s]
Generating train split: 46217592 examples [46:02, 13324.79 examples/s]
Generating train split: 46220252 examples [46:03, 16043.45 examples/s]
Generating train split: 46222041 examples [46:03, 12494.83 examples/s]
Generating train split: 46223522 examples [46:03, 11688.81 examples/s]
Generating train split: 46225323 examples [46:03, 12971.70 examples/s]
Generating train split: 46226790 examples [46:03, 12663.52 examples/s]
Generating train split: 46234503 examples [46:03, 28039.14 examples/s]
Generating train split: 46243767 examples [46:03, 44453.77 examples/s]
Generating train split: 46248838 examples [46:04, 31485.97 examples/s]
Generating train split: 46252942 examples [46:04, 24959.90 examples/s]
Generating train split: 46256287 examples [46:04, 21820.58 examples/s]
Generating train split: 46266051 examples [46:04, 35076.47 examples/s]
Generating train split: 46273889 examples [46:04, 43647.21 examples/s]
Generating train split: 46279638 examples [46:05, 27751.25 examples/s]
Generating train split: 46284087 examples [46:05, 24516.64 examples/s]
Generating train split: 46292679 examples [46:05, 33990.47 examples/s]
Generating train split: 46299158 examples [46:05, 39552.12 examples/s]
Generating train split: 46304691 examples [46:06, 19734.37 examples/s]
Generating train split: 46308816 examples [46:06, 15953.10 examples/s]
Generating train split: 46311994 examples [46:07, 14039.57 examples/s]
Generating train split: 46314505 examples [46:07, 14498.50 examples/s]
Generating train split: 46316775 examples [46:07, 12920.15 examples/s]
Generating train split: 46318714 examples [46:07, 13781.78 examples/s]
Generating train split: 46320594 examples [46:07, 14414.14 examples/s]
Generating train split: 46322448 examples [46:07, 14410.54 examples/s]
Generating train split: 46324176 examples [46:08, 10466.30 examples/s]
Generating train split: 46331097 examples [46:08, 20233.79 examples/s]
Generating train split: 46339712 examples [46:08, 32886.25 examples/s]
Generating train split: 46344424 examples [46:08, 29684.98 examples/s]
Generating train split: 46348436 examples [46:09, 17570.17 examples/s]
Generating train split: 46351486 examples [46:09, 17185.95 examples/s]
Generating train split: 46354107 examples [46:09, 15656.58 examples/s]
Generating train split: 46356288 examples [46:09, 15021.59 examples/s]
Generating train split: 46358390 examples [46:09, 15975.13 examples/s]
Generating train split: 46360426 examples [46:09, 16778.76 examples/s]
Generating train split: 46362411 examples [46:09, 16736.94 examples/s]
Generating train split: 46370296 examples [46:10, 30779.22 examples/s]
Generating train split: 46380145 examples [46:10, 47301.53 examples/s]
Generating train split: 46385679 examples [46:10, 29270.38 examples/s]
Generating train split: 46390006 examples [46:10, 23853.85 examples/s]
Generating train split: 46393493 examples [46:11, 19342.03 examples/s]
Generating train split: 46396279 examples [46:11, 14527.93 examples/s]
Generating train split: 46398459 examples [46:11, 14114.89 examples/s]
Generating train split: 46400365 examples [46:11, 13312.09 examples/s]
Generating train split: 46402013 examples [46:11, 13398.78 examples/s]
Generating train split: 46404250 examples [46:12, 14996.88 examples/s]
Generating train split: 46406981 examples [46:12, 17490.66 examples/s]
Generating train split: 46409073 examples [46:12, 18216.08 examples/s]
Generating train split: 46411132 examples [46:12, 18484.90 examples/s]
Generating train split: 46413155 examples [46:12, 12762.11 examples/s]
Generating train split: 46418257 examples [46:12, 20282.29 examples/s]
Generating train split: 46424931 examples [46:12, 30468.14 examples/s]
Generating train split: 46428798 examples [46:13, 24760.60 examples/s]
Generating train split: 46432024 examples [46:13, 24983.03 examples/s]
Generating train split: 46436244 examples [46:13, 28746.13 examples/s]
Generating train split: 46440146 examples [46:13, 31186.64 examples/s]
Generating train split: 46449275 examples [46:13, 46428.43 examples/s]
Generating train split: 46455503 examples [46:13, 50627.69 examples/s]
Generating train split: 46461027 examples [46:14, 26903.21 examples/s]
Generating train split: 46465271 examples [46:14, 21878.76 examples/s]
Generating train split: 46468656 examples [46:14, 19070.95 examples/s]
Generating train split: 46472320 examples [46:14, 21656.92 examples/s]
Generating train split: 46475343 examples [46:15, 14987.76 examples/s]
Generating train split: 46479212 examples [46:15, 18119.54 examples/s]
Generating train split: 46483370 examples [46:15, 21982.76 examples/s]
Generating train split: 46486526 examples [46:15, 19734.53 examples/s]
Generating train split: 46489196 examples [46:15, 18758.63 examples/s]
Generating train split: 46492352 examples [46:15, 21177.05 examples/s]
Generating train split: 46499147 examples [46:15, 31153.03 examples/s]
Generating train split: 46507791 examples [46:16, 44064.38 examples/s]
Generating train split: 46513078 examples [46:16, 44863.43 examples/s]
Generating train split: 46518197 examples [46:16, 24381.96 examples/s]
Generating train split: 46522117 examples [46:16, 26313.70 examples/s]
Generating train split: 46526037 examples [46:16, 28692.47 examples/s]
Generating train split: 46533318 examples [46:16, 37903.31 examples/s]
Generating train split: 46539783 examples [46:17, 40853.24 examples/s]
Generating train split: 46544641 examples [46:17, 29182.08 examples/s]
Generating train split: 46553686 examples [46:17, 40558.00 examples/s]
Generating train split: 46561664 examples [46:17, 48781.80 examples/s]
Generating train split: 46567861 examples [46:18, 27350.76 examples/s]
Generating train split: 46572584 examples [46:18, 28448.39 examples/s]
Generating train split: 46576882 examples [46:18, 20971.21 examples/s]
Generating train split: 46580226 examples [46:18, 20698.72 examples/s]
Generating train split: 46583168 examples [46:18, 17449.73 examples/s]
Generating train split: 46587954 examples [46:19, 21932.53 examples/s]
Generating train split: 46596664 examples [46:19, 33268.78 examples/s]
Generating train split: 46601446 examples [46:19, 25141.51 examples/s]
Generating train split: 46605931 examples [46:19, 28391.31 examples/s]
Generating train split: 46609940 examples [46:19, 29337.25 examples/s]
Generating train split: 46613731 examples [46:20, 18885.98 examples/s]
Generating train split: 46617122 examples [46:20, 21155.69 examples/s]
Generating train split: 46620181 examples [46:20, 22200.48 examples/s]
Generating train split: 46624420 examples [46:20, 26203.79 examples/s]
Generating train split: 46627747 examples [46:20, 21319.57 examples/s]
Generating train split: 46630505 examples [46:20, 19953.14 examples/s]
Generating train split: 46632933 examples [46:20, 20310.07 examples/s]
Generating train split: 46636172 examples [46:21, 22907.84 examples/s]
Generating train split: 46638920 examples [46:21, 23835.16 examples/s]
Generating train split: 46641550 examples [46:21, 20183.52 examples/s]
Generating train split: 46643822 examples [46:21, 18643.35 examples/s]
Generating train split: 46645881 examples [46:21, 19072.09 examples/s]
Generating train split: 46651675 examples [46:21, 28564.01 examples/s]
Generating train split: 46660327 examples [46:21, 43543.52 examples/s]
Generating train split: 46665152 examples [46:21, 36229.93 examples/s]
Generating train split: 46669294 examples [46:22, 23231.87 examples/s]
Generating train split: 46672539 examples [46:22, 18322.11 examples/s]
Generating train split: 46675142 examples [46:22, 16710.35 examples/s]
Generating train split: 46677442 examples [46:22, 17492.88 examples/s]
Generating train split: 46679619 examples [46:23, 15181.66 examples/s]
Generating train split: 46683898 examples [46:23, 20116.64 examples/s]
Generating train split: 46686466 examples [46:23, 16140.38 examples/s]
Generating train split: 46690461 examples [46:23, 20418.04 examples/s]
Generating train split: 46694386 examples [46:23, 24279.10 examples/s]
Generating train split: 46698079 examples [46:23, 27088.96 examples/s]
Generating train split: 46704827 examples [46:23, 36947.71 examples/s]
Generating train split: 46713500 examples [46:24, 49812.75 examples/s]
Generating train split: 46719101 examples [46:24, 29740.56 examples/s]
Generating train split: 46723486 examples [46:24, 31110.94 examples/s]
Generating train split: 46730341 examples [46:24, 38600.40 examples/s]
Generating train split: 46744522 examples [46:24, 61548.53 examples/s]
Generating train split: 46754445 examples [46:24, 70620.67 examples/s]
Generating train split: 46762829 examples [46:25, 50989.23 examples/s]
Generating train split: 46769609 examples [46:25, 42164.17 examples/s]
Generating train split: 46775187 examples [46:25, 39975.46 examples/s]
Generating train split: 46781986 examples [46:25, 45264.23 examples/s]
Generating train split: 46790214 examples [46:25, 53123.87 examples/s]
Generating train split: 46796532 examples [46:25, 50165.18 examples/s]
Generating train split: 46802254 examples [46:26, 29569.23 examples/s]
Generating train split: 46806661 examples [46:26, 30233.78 examples/s]
Generating train split: 46810743 examples [46:26, 29962.69 examples/s]
Generating train split: 46815416 examples [46:26, 33152.35 examples/s]
Generating train split: 46819902 examples [46:26, 35658.69 examples/s]
Generating train split: 46824054 examples [46:26, 28621.61 examples/s]
Generating train split: 46827515 examples [46:27, 27298.44 examples/s]
Generating train split: 46830830 examples [46:27, 28499.92 examples/s]
Generating train split: 46836436 examples [46:27, 34891.17 examples/s]
Generating train split: 46841593 examples [46:27, 38974.69 examples/s]
Generating train split: 46846690 examples [46:27, 42102.78 examples/s]
Generating train split: 46851213 examples [46:27, 35028.25 examples/s]
Generating train split: 46855117 examples [46:27, 34758.91 examples/s]
Generating train split: 46858876 examples [46:28, 29627.15 examples/s]
Generating train split: 46862136 examples [46:28, 18679.65 examples/s]
Generating train split: 46864681 examples [46:28, 17372.47 examples/s]
Generating train split: 46867020 examples [46:28, 17554.18 examples/s]
Generating train split: 46869413 examples [46:28, 18685.92 examples/s]
Generating train split: 46871575 examples [46:28, 17194.52 examples/s]
Generating train split: 46873504 examples [46:29, 16170.09 examples/s]
Generating train split: 46875257 examples [46:29, 13647.24 examples/s]
Generating train split: 46877051 examples [46:29, 14314.97 examples/s]
Generating train split: 46879949 examples [46:29, 17306.72 examples/s]
Generating train split: 46882916 examples [46:29, 19731.84 examples/s]
Generating train split: 46885047 examples [46:29, 16759.66 examples/s]
Generating train split: 46886897 examples [46:29, 16139.02 examples/s]
Generating train split: 46888624 examples [46:30, 13100.52 examples/s]
Generating train split: 46890089 examples [46:30, 11969.32 examples/s]
Generating train split: 46891392 examples [46:30, 11335.47 examples/s]
Generating train split: 46892590 examples [46:30, 9800.48 examples/s] 
Generating train split: 46893631 examples [46:30, 6747.67 examples/s]
Generating train split: 46894456 examples [46:31, 6081.89 examples/s]
Generating train split: 46895177 examples [46:31, 5708.14 examples/s]
Generating train split: 46896017 examples [46:31, 6177.26 examples/s]
Generating train split: 46896878 examples [46:31, 6652.97 examples/s]
Generating train split: 46898327 examples [46:31, 8360.40 examples/s]
Generating train split: 46899263 examples [46:31, 7942.12 examples/s]
Generating train split: 46901633 examples [46:31, 11674.36 examples/s]
Generating train split: 46902929 examples [46:31, 11806.96 examples/s]
Generating train split: 46905449 examples [46:32, 15245.73 examples/s]
Generating train split: 46907078 examples [46:32, 13755.68 examples/s]
Generating train split: 46908547 examples [46:32, 12676.45 examples/s]
Generating train split: 46910282 examples [46:32, 13786.75 examples/s]
Generating train split: 46911741 examples [46:32, 12228.26 examples/s]
Generating train split: 46920267 examples [46:32, 30218.19 examples/s]
Generating train split: 46929175 examples [46:32, 45531.88 examples/s]
Generating train split: 46934274 examples [46:33, 28661.20 examples/s]
Generating train split: 46938297 examples [46:33, 23050.73 examples/s]
Generating train split: 46941549 examples [46:33, 18439.42 examples/s]
Generating train split: 46944160 examples [46:33, 16275.33 examples/s]
Generating train split: 46947469 examples [46:34, 18857.18 examples/s]
Generating train split: 46949973 examples [46:34, 17645.28 examples/s]
Generating train split: 46952169 examples [46:34, 14819.86 examples/s]
Generating train split: 46953995 examples [46:34, 15366.68 examples/s]
Generating train split: 46956092 examples [46:34, 16434.85 examples/s]
Generating train split: 46958293 examples [46:34, 17657.13 examples/s]
Generating train split: 46960274 examples [46:34, 16399.30 examples/s]
Generating train split: 46962084 examples [46:35, 12574.06 examples/s]
Generating train split: 46963577 examples [46:35, 12896.23 examples/s]
Generating train split: 46965041 examples [46:35, 12584.79 examples/s]
Generating train split: 46966427 examples [46:35, 12303.21 examples/s]
Generating train split: 46967742 examples [46:35, 12315.00 examples/s]
Generating train split: 46969677 examples [46:35, 14000.30 examples/s]
Generating train split: 46971697 examples [46:35, 15630.94 examples/s]
Generating train split: 46973586 examples [46:35, 16479.24 examples/s]
Generating train split: 46976339 examples [46:35, 19308.60 examples/s]
Generating train split: 46978323 examples [46:36, 15778.64 examples/s]
Generating train split: 46980036 examples [46:36, 15914.82 examples/s]
Generating train split: 46982555 examples [46:36, 18244.25 examples/s]
Generating train split: 46985475 examples [46:36, 20836.21 examples/s]
Generating train split: 46987662 examples [46:36, 20942.85 examples/s]
Generating train split: 46989822 examples [46:36, 19075.61 examples/s]
Generating train split: 46991868 examples [46:36, 19438.81 examples/s]
Generating train split: 46993867 examples [46:36, 18600.68 examples/s]
Generating train split: 46995772 examples [46:37, 15812.68 examples/s]
Generating train split: 46997451 examples [46:37, 14364.13 examples/s]
Generating train split: 46999943 examples [46:37, 16582.59 examples/s]
Generating train split: 47001699 examples [46:37, 12395.01 examples/s]
Generating train split: 47003156 examples [46:37, 12764.00 examples/s]
Generating train split: 47004962 examples [46:37, 13883.11 examples/s]
Generating train split: 47006493 examples [46:37, 14054.97 examples/s]
Generating train split: 47008004 examples [46:38, 12162.94 examples/s]
Generating train split: 47015894 examples [46:38, 28016.55 examples/s]
Generating train split: 47023036 examples [46:38, 39012.38 examples/s]
Generating train split: 47027490 examples [46:38, 20216.91 examples/s]
Generating train split: 47030890 examples [46:39, 15535.08 examples/s]
Generating train split: 47033543 examples [46:39, 15492.16 examples/s]
Generating train split: 47041473 examples [46:39, 25089.99 examples/s]
Generating train split: 47047935 examples [46:39, 32078.59 examples/s]
Generating train split: 47052674 examples [46:39, 24792.47 examples/s]
Generating train split: 47059972 examples [46:39, 32926.63 examples/s]
Generating train split: 47067844 examples [46:40, 41728.63 examples/s]
Generating train split: 47073568 examples [46:40, 26268.47 examples/s]
Generating train split: 47077978 examples [46:40, 22826.08 examples/s]
Generating train split: 47081538 examples [46:41, 16077.56 examples/s]
Generating train split: 47084265 examples [46:41, 15643.18 examples/s]
Generating train split: 47086788 examples [46:41, 16917.90 examples/s]
Generating train split: 47094417 examples [46:41, 26419.67 examples/s]
Generating train split: 47099612 examples [46:41, 31166.31 examples/s]
Generating train split: 47103938 examples [46:41, 23843.65 examples/s]
Generating train split: 47107406 examples [46:42, 16434.36 examples/s]
Generating train split: 47110081 examples [46:42, 16900.35 examples/s]
Generating train split: 47112521 examples [46:42, 12098.51 examples/s]
Generating train split: 47114412 examples [46:43, 11967.02 examples/s]
Generating train split: 47116151 examples [46:43, 12739.30 examples/s]
Generating train split: 47117830 examples [46:43, 10446.11 examples/s]
Generating train split: 47119202 examples [46:43, 9601.24 examples/s] 
Generating train split: 47120381 examples [46:43, 9340.62 examples/s]
Generating train split: 47121660 examples [46:43, 9555.32 examples/s]
Generating train split: 47122725 examples [46:44, 9505.90 examples/s]
Generating train split: 47123793 examples [46:44, 9750.80 examples/s]
Generating train split: 47124829 examples [46:44, 9213.96 examples/s]
Generating train split: 47126641 examples [46:44, 11262.09 examples/s]
Generating train split: 47127846 examples [46:44, 7786.37 examples/s] 
Generating train split: 47132084 examples [46:44, 14617.89 examples/s]
Generating train split: 47140177 examples [46:44, 29206.46 examples/s]
Generating train split: 47146019 examples [46:44, 36184.39 examples/s]
Generating train split: 47150435 examples [46:45, 18865.35 examples/s]
Generating train split: 47157407 examples [46:45, 26601.96 examples/s]
Generating train split: 47165191 examples [46:45, 35745.20 examples/s]
Generating train split: 47170637 examples [46:46, 26376.36 examples/s]
Generating train split: 47174921 examples [46:46, 20890.78 examples/s]
Generating train split: 47178294 examples [46:46, 17655.56 examples/s]
Generating train split: 47180996 examples [46:46, 15723.03 examples/s]
Generating train split: 47183222 examples [46:47, 15108.77 examples/s]
Generating train split: 47185159 examples [46:47, 15363.32 examples/s]
Generating train split: 47189673 examples [46:47, 20602.80 examples/s]
Generating train split: 47194963 examples [46:47, 27089.91 examples/s]
Generating train split: 47198413 examples [46:47, 22279.97 examples/s]
Generating train split: 47201284 examples [46:47, 22083.02 examples/s]
Generating train split: 47208796 examples [46:47, 33195.77 examples/s]
Generating train split: 47218389 examples [46:47, 47643.37 examples/s]
Generating train split: 47224138 examples [46:48, 44531.57 examples/s]
Generating train split: 47229319 examples [46:48, 44434.69 examples/s]
Generating train split: 47238029 examples [46:48, 54961.15 examples/s]
Generating train split: 47245022 examples [46:48, 58851.05 examples/s]
Generating train split: 47251383 examples [46:48, 31233.49 examples/s]
Generating train split: 47260420 examples [46:48, 41142.33 examples/s]
Generating train split: 47268075 examples [46:49, 47979.63 examples/s]
Generating train split: 47274666 examples [46:49, 46940.31 examples/s]
Generating train split: 47280605 examples [46:49, 45130.70 examples/s]
Generating train split: 47290026 examples [46:49, 55812.02 examples/s]
Generating train split: 47296581 examples [46:49, 42921.75 examples/s]
Generating train split: 47304407 examples [46:49, 50039.58 examples/s]
Generating train split: 47312619 examples [46:49, 57208.26 examples/s]
Generating train split: 47320244 examples [46:50, 61801.32 examples/s]
Generating train split: 47327252 examples [46:50, 38558.63 examples/s]
Generating train split: 47332748 examples [46:50, 32118.81 examples/s]
Generating train split: 47337224 examples [46:50, 28683.83 examples/s]
Generating train split: 47340985 examples [46:51, 20558.44 examples/s]
Generating train split: 47346166 examples [46:51, 24908.29 examples/s]
Generating train split: 47349764 examples [46:51, 18171.22 examples/s]
Generating train split: 47352565 examples [46:51, 17288.11 examples/s]
Generating train split: 47359396 examples [46:52, 24902.39 examples/s]
Generating train split: 47367832 examples [46:52, 34955.97 examples/s]
Generating train split: 47372819 examples [46:52, 22337.08 examples/s]
Generating train split: 47376641 examples [46:52, 23703.54 examples/s]
Generating train split: 47380229 examples [46:52, 19580.57 examples/s]
Generating train split: 47383107 examples [46:53, 17647.33 examples/s]
Generating train split: 47385609 examples [46:53, 18783.65 examples/s]
Generating train split: 47388044 examples [46:53, 12333.97 examples/s]
Generating train split: 47390505 examples [46:53, 14033.86 examples/s]
Generating train split: 47393428 examples [46:53, 16535.46 examples/s]
Generating train split: 47395738 examples [46:54, 13472.02 examples/s]
Generating train split: 47397621 examples [46:54, 13087.89 examples/s]
Generating train split: 47399913 examples [46:54, 14869.99 examples/s]
Generating train split: 47406569 examples [46:54, 25525.63 examples/s]
Generating train split: 47416474 examples [46:54, 42248.55 examples/s]
Generating train split: 47423736 examples [46:54, 49690.43 examples/s]
Generating train split: 47429619 examples [46:55, 31546.84 examples/s]
Generating train split: 47434242 examples [46:55, 26691.98 examples/s]
Generating train split: 47438022 examples [46:55, 22855.15 examples/s]
Generating train split: 47441126 examples [46:55, 23341.98 examples/s]
Generating train split: 47450535 examples [46:55, 36281.18 examples/s]
Generating train split: 47457101 examples [46:55, 42125.37 examples/s]
Generating train split: 47462435 examples [46:56, 40136.94 examples/s]
Generating train split: 47467724 examples [46:56, 43013.33 examples/s]
Generating train split: 47472682 examples [46:56, 44112.21 examples/s]
Generating train split: 47477565 examples [46:56, 23831.61 examples/s]
Generating train split: 47481313 examples [46:56, 24309.79 examples/s]
Generating train split: 47484725 examples [46:57, 15716.10 examples/s]
Generating train split: 47487324 examples [46:57, 15988.82 examples/s]
Generating train split: 47489669 examples [46:57, 13425.46 examples/s]
Generating train split: 47491561 examples [46:57, 14100.19 examples/s]
Generating train split: 47493804 examples [46:58, 15512.27 examples/s]
Generating train split: 47495775 examples [46:58, 10567.73 examples/s]
Generating train split: 47498201 examples [46:58, 12098.45 examples/s]
Generating train split: 47499840 examples [46:58, 11859.15 examples/s]
Generating train split: 47501322 examples [46:58, 11821.91 examples/s]
Generating train split: 47503100 examples [46:58, 13007.58 examples/s]
Generating train split: 47504600 examples [46:59, 11416.54 examples/s]
Generating train split: 47505901 examples [46:59, 9945.93 examples/s] 
Generating train split: 47507027 examples [46:59, 9219.63 examples/s]
Generating train split: 47508760 examples [46:59, 10904.49 examples/s]
Generating train split: 47510114 examples [46:59, 11419.76 examples/s]
Generating train split: 47511368 examples [46:59, 7306.95 examples/s] 
Generating train split: 47513043 examples [47:00, 9004.55 examples/s]
Generating train split: 47515549 examples [47:00, 12269.11 examples/s]
Generating train split: 47517907 examples [47:00, 14819.01 examples/s]
Generating train split: 47519725 examples [47:00, 13913.11 examples/s]
Generating train split: 47521364 examples [47:00, 12184.67 examples/s]
Generating train split: 47523260 examples [47:00, 13683.03 examples/s]
Generating train split: 47526345 examples [47:00, 17799.34 examples/s]
Generating train split: 47529865 examples [47:00, 22117.73 examples/s]
Generating train split: 47534751 examples [47:01, 29229.37 examples/s]
Generating train split: 47540124 examples [47:01, 35962.44 examples/s]
Generating train split: 47545977 examples [47:01, 41944.78 examples/s]
Generating train split: 47550366 examples [47:01, 35278.69 examples/s]
Generating train split: 47555132 examples [47:01, 38396.55 examples/s]
Generating train split: 47560615 examples [47:01, 42743.94 examples/s]
Generating train split: 47566308 examples [47:01, 46629.85 examples/s]
Generating train split: 47572464 examples [47:01, 50822.21 examples/s]
Generating train split: 47577725 examples [47:01, 50738.75 examples/s]
Generating train split: 47584193 examples [47:01, 54753.65 examples/s]
Generating train split: 47590497 examples [47:02, 57143.05 examples/s]
Generating train split: 47596300 examples [47:02, 54832.28 examples/s]
Generating train split: 47602686 examples [47:02, 57411.05 examples/s]
Generating train split: 47608954 examples [47:02, 58921.25 examples/s]
Generating train split: 47614898 examples [47:02, 57795.37 examples/s]
Generating train split: 47622039 examples [47:02, 61736.71 examples/s]
Generating train split: 47628254 examples [47:02, 61172.49 examples/s]
Generating train split: 47635026 examples [47:02, 63080.04 examples/s]
Generating train split: 47641360 examples [47:02, 62843.32 examples/s]
Generating train split: 47648604 examples [47:03, 65678.22 examples/s]
Generating train split: 47655193 examples [47:03, 62439.30 examples/s]
Generating train split: 47661993 examples [47:03, 64029.87 examples/s]
Generating train split: 47668440 examples [47:03, 61944.89 examples/s]
Generating train split: 47675816 examples [47:03, 65247.33 examples/s]
Generating train split: 47682384 examples [47:03, 59098.53 examples/s]
Generating train split: 47688431 examples [47:03, 55286.86 examples/s]
Generating train split: 47694081 examples [47:03, 55490.44 examples/s]
Generating train split: 47700146 examples [47:03, 56907.24 examples/s]
Generating train split: 47705918 examples [47:04, 40213.27 examples/s]
Generating train split: 47711898 examples [47:04, 44518.62 examples/s]
Generating train split: 47717002 examples [47:04, 44670.46 examples/s]
Generating train split: 47721930 examples [47:04, 41175.84 examples/s]
Generating train split: 47726503 examples [47:04, 42277.12 examples/s]
Generating train split: 47731000 examples [47:04, 28545.14 examples/s]
Generating train split: 47734613 examples [47:05, 27414.82 examples/s]
Generating train split: 47737874 examples [47:05, 20537.20 examples/s]
Generating train split: 47740492 examples [47:05, 17901.95 examples/s]
Generating train split: 47748223 examples [47:05, 28058.51 examples/s]
Generating train split: 47755504 examples [47:05, 36833.60 examples/s]
Generating train split: 47760390 examples [47:06, 27167.96 examples/s]
Generating train split: 47764292 examples [47:06, 22512.65 examples/s]
Generating train split: 47767465 examples [47:06, 21007.42 examples/s]
Generating train split: 47770188 examples [47:06, 21243.09 examples/s]
Generating train split: 47775804 examples [47:06, 27831.68 examples/s]
Generating train split: 47786111 examples [47:06, 43809.71 examples/s]
Generating train split: 47791645 examples [47:07, 33104.28 examples/s]
Generating train split: 47796124 examples [47:07, 33099.90 examples/s]
Generating train split: 47800250 examples [47:07, 33194.45 examples/s]
Generating train split: 47808702 examples [47:07, 44351.99 examples/s]
Generating train split: 47817040 examples [47:07, 53599.68 examples/s]
Generating train split: 47823225 examples [47:07, 46659.30 examples/s]
Generating train split: 47828610 examples [47:07, 39561.48 examples/s]
Generating train split: 47833211 examples [47:08, 36638.80 examples/s]
Generating train split: 47839031 examples [47:08, 41107.00 examples/s]
Generating train split: 47846374 examples [47:08, 48654.02 examples/s]
Generating train split: 47855023 examples [47:08, 58120.24 examples/s]
Generating train split: 47862405 examples [47:08, 62236.78 examples/s]
Generating train split: 47869085 examples [47:08, 55217.24 examples/s]
Generating train split: 47877002 examples [47:08, 61289.57 examples/s]
Generating train split: 47884663 examples [47:08, 65107.26 examples/s]
Generating train split: 47891524 examples [47:09, 38943.58 examples/s]
Generating train split: 47896903 examples [47:09, 37178.83 examples/s]
Generating train split: 47901653 examples [47:09, 27187.53 examples/s]
Generating train split: 47905408 examples [47:09, 24618.91 examples/s]
Generating train split: 47908585 examples [47:10, 21672.53 examples/s]
Generating train split: 47911246 examples [47:10, 18981.85 examples/s]
Generating train split: 47913498 examples [47:10, 18193.63 examples/s]
Generating train split: 47916948 examples [47:10, 20841.55 examples/s]
Generating train split: 47919660 examples [47:10, 22108.61 examples/s]
Generating train split: 47927699 examples [47:10, 35174.96 examples/s]
Generating train split: 47935433 examples [47:10, 44730.01 examples/s]
Generating train split: 47940522 examples [47:11, 29993.35 examples/s]
Generating train split: 47948960 examples [47:11, 40361.35 examples/s]
Generating train split: 47958947 examples [47:11, 53096.21 examples/s]
Generating train split: 47965698 examples [47:11, 33663.88 examples/s]
Generating train split: 47970949 examples [47:12, 30473.41 examples/s]
Generating train split: 47975330 examples [47:12, 25914.08 examples/s]
Generating train split: 47978900 examples [47:12, 19745.68 examples/s]
Generating train split: 47982738 examples [47:12, 22325.26 examples/s]
Generating train split: 47987626 examples [47:12, 26717.38 examples/s]
Generating train split: 47996717 examples [47:12, 38989.86 examples/s]
Generating train split: 48002000 examples [47:13, 38155.45 examples/s]
Generating train split: 48006783 examples [47:13, 35813.77 examples/s]
Generating train split: 48015211 examples [47:13, 46323.64 examples/s]
Generating train split: 48023213 examples [47:13, 53636.00 examples/s]
Generating train split: 48029364 examples [47:13, 41229.61 examples/s]
Generating train split: 48036579 examples [47:13, 47700.57 examples/s]
Generating train split: 48042884 examples [47:13, 51230.69 examples/s]
Generating train split: 48048782 examples [47:14, 33684.90 examples/s]
Generating train split: 48053444 examples [47:14, 30590.43 examples/s]
Generating train split: 48057415 examples [47:14, 20557.56 examples/s]
Generating train split: 48060480 examples [47:15, 19517.00 examples/s]
Generating train split: 48063116 examples [47:15, 18469.87 examples/s]
Generating train split: 48065416 examples [47:15, 19107.29 examples/s]
Generating train split: 48067694 examples [47:15, 17978.48 examples/s]
Generating train split: 48069733 examples [47:15, 18313.11 examples/s]
Generating train split: 48071750 examples [47:15, 15176.33 examples/s]
Generating train split: 48080616 examples [47:15, 29984.38 examples/s]
Generating train split: 48089906 examples [47:15, 42620.09 examples/s]
Generating train split: 48095026 examples [47:16, 35360.26 examples/s]
Generating train split: 48099339 examples [47:16, 32498.93 examples/s]
Generating train split: 48103145 examples [47:16, 30935.83 examples/s]
Generating train split: 48107379 examples [47:16, 32652.90 examples/s]
Generating train split: 48110958 examples [47:16, 26866.88 examples/s]
Generating train split: 48113986 examples [47:16, 26802.05 examples/s]
Generating train split: 48116904 examples [47:17, 26763.93 examples/s]
Generating train split: 48120197 examples [47:17, 28235.06 examples/s]
Generating train split: 48123179 examples [47:17, 20737.64 examples/s]
Generating train split: 48125622 examples [47:17, 19131.35 examples/s]
Generating train split: 48128354 examples [47:17, 20829.83 examples/s]
Generating train split: 48131785 examples [47:17, 23933.53 examples/s]
Generating train split: 48134449 examples [47:17, 21550.13 examples/s]
Generating train split: 48136829 examples [47:18, 18051.44 examples/s]
Generating train split: 48139446 examples [47:18, 19732.41 examples/s]
Generating train split: 48142932 examples [47:18, 23284.79 examples/s]
Generating train split: 48146004 examples [47:18, 25147.94 examples/s]
Generating train split: 48148742 examples [47:18, 15861.41 examples/s]
Generating train split: 48151020 examples [47:18, 17165.15 examples/s]
Generating train split: 48160418 examples [47:18, 33478.60 examples/s]
Generating train split: 48168426 examples [47:19, 44313.96 examples/s]
Generating train split: 48173875 examples [47:19, 44907.96 examples/s]
Generating train split: 48179090 examples [47:19, 42425.61 examples/s]
Generating train split: 48185346 examples [47:19, 47408.74 examples/s]
Generating train split: 48192790 examples [47:19, 53657.68 examples/s]
Generating train split: 48198552 examples [47:19, 30589.30 examples/s]
Generating train split: 48203020 examples [47:20, 25583.73 examples/s]
Generating train split: 48206652 examples [47:20, 20822.77 examples/s]
Generating train split: 48209583 examples [47:20, 16648.27 examples/s]
Generating train split: 48211915 examples [47:20, 16530.01 examples/s]
Generating train split: 48215027 examples [47:21, 18829.71 examples/s]
Generating train split: 48217435 examples [47:21, 17792.90 examples/s]
Generating train split: 48219574 examples [47:21, 9503.64 examples/s] 
Generating train split: 48221339 examples [47:21, 10495.92 examples/s]
Generating train split: 48222986 examples [47:22, 10675.81 examples/s]
Generating train split: 48225274 examples [47:22, 12544.38 examples/s]
Generating train split: 48226955 examples [47:22, 12963.23 examples/s]
Generating train split: 48228575 examples [47:22, 9774.95 examples/s] 
Generating train split: 48230177 examples [47:22, 10857.42 examples/s]
Generating train split: 48231569 examples [47:22, 9926.04 examples/s] 
Generating train split: 48232774 examples [47:22, 9622.86 examples/s]
Generating train split: 48233893 examples [47:23, 8579.41 examples/s]
Generating train split: 48235426 examples [47:23, 9935.01 examples/s]
Generating train split: 48236560 examples [47:23, 8894.73 examples/s]
Generating train split: 48238003 examples [47:23, 10070.45 examples/s]
Generating train split: 48239139 examples [47:23, 8623.56 examples/s] 
Generating train split: 48240116 examples [47:23, 7713.30 examples/s]
Generating train split: 48241098 examples [47:23, 8086.53 examples/s]
Generating train split: 48241977 examples [47:24, 6560.58 examples/s]
Generating train split: 48244346 examples [47:24, 10135.07 examples/s]
Generating train split: 48246755 examples [47:24, 13341.11 examples/s]
Generating train split: 48254331 examples [47:24, 28770.07 examples/s]
Generating train split: 48261787 examples [47:24, 40707.52 examples/s]
Generating train split: 48266391 examples [47:24, 34164.83 examples/s]
Generating train split: 48270358 examples [47:24, 27202.24 examples/s]
Generating train split: 48273670 examples [47:25, 22626.00 examples/s]
Generating train split: 48277388 examples [47:25, 25223.11 examples/s]
Generating train split: 48280403 examples [47:25, 21225.74 examples/s]
Generating train split: 48282932 examples [47:25, 21522.17 examples/s]
Generating train split: 48285386 examples [47:25, 20313.49 examples/s]
Generating train split: 48287618 examples [47:25, 19516.37 examples/s]
Generating train split: 48289709 examples [47:26, 17901.04 examples/s]
Generating train split: 48291598 examples [47:26, 15146.13 examples/s]
Generating train split: 48293398 examples [47:26, 15725.46 examples/s]
Generating train split: 48295074 examples [47:26, 8849.68 examples/s] 
Generating train split: 48296357 examples [47:26, 8775.90 examples/s]
Generating train split: 48297511 examples [47:27, 8703.90 examples/s]
Generating train split: 48300237 examples [47:27, 12063.05 examples/s]
Generating train split: 48301764 examples [47:27, 11168.93 examples/s]
Generating train split: 48303114 examples [47:27, 10183.22 examples/s]
Generating train split: 48304293 examples [47:27, 9735.00 examples/s] 
Generating train split: 48305608 examples [47:27, 10213.13 examples/s]
Generating train split: 48306730 examples [47:28, 6592.27 examples/s] 
Generating train split: 48307621 examples [47:28, 6798.28 examples/s]
Generating train split: 48315496 examples [47:28, 20652.26 examples/s]
Generating train split: 48323369 examples [47:28, 33180.63 examples/s]
Generating train split: 48327795 examples [47:28, 35141.19 examples/s]
Generating train split: 48332134 examples [47:29, 19060.85 examples/s]
Generating train split: 48335443 examples [47:29, 18246.64 examples/s]
Generating train split: 48338238 examples [47:29, 16507.23 examples/s]
Generating train split: 48340574 examples [47:29, 13790.09 examples/s]
Generating train split: 48342465 examples [47:29, 14297.50 examples/s]
Generating train split: 48344290 examples [47:30, 11537.34 examples/s]
Generating train split: 48346101 examples [47:30, 12596.18 examples/s]
Generating train split: 48347683 examples [47:30, 12845.88 examples/s]
Generating train split: 48349903 examples [47:30, 14774.47 examples/s]
Generating train split: 48351645 examples [47:30, 13186.82 examples/s]
Generating train split: 48353300 examples [47:30, 13914.12 examples/s]
Generating train split: 48354857 examples [47:30, 14138.04 examples/s]
Generating train split: 48356390 examples [47:31, 11729.78 examples/s]
Generating train split: 48357712 examples [47:31, 10782.50 examples/s]
Generating train split: 48358894 examples [47:31, 10645.05 examples/s]
Generating train split: 48361051 examples [47:31, 13169.51 examples/s]
Generating train split: 48362481 examples [47:31, 11820.88 examples/s]
Generating train split: 48370287 examples [47:31, 27704.31 examples/s]
Generating train split: 48379255 examples [47:31, 43514.49 examples/s]
Generating train split: 48384212 examples [47:31, 31581.73 examples/s]
Generating train split: 48388251 examples [47:32, 28104.00 examples/s]
Generating train split: 48391726 examples [47:32, 21412.35 examples/s]
Generating train split: 48394525 examples [47:32, 21470.19 examples/s]
Generating train split: 48402769 examples [47:32, 33096.89 examples/s]
Generating train split: 48411736 examples [47:32, 45208.74 examples/s]
Generating train split: 48417437 examples [47:33, 29404.89 examples/s]
Generating train split: 48421896 examples [47:33, 22808.32 examples/s]
Generating train split: 48425408 examples [47:33, 23916.44 examples/s]
Generating train split: 48434852 examples [47:33, 35906.10 examples/s]
Generating train split: 48443867 examples [47:33, 46500.73 examples/s]
Generating train split: 48450205 examples [47:34, 34595.65 examples/s]
Generating train split: 48455258 examples [47:34, 33004.77 examples/s]
Generating train split: 48459657 examples [47:34, 30129.20 examples/s]
Generating train split: 48463440 examples [47:35, 16427.40 examples/s]
Generating train split: 48466518 examples [47:35, 18139.50 examples/s]
Generating train split: 48469419 examples [47:35, 15970.75 examples/s]
Generating train split: 48471790 examples [47:35, 13810.58 examples/s]
Generating train split: 48473715 examples [47:35, 12625.50 examples/s]
Generating train split: 48475341 examples [47:36, 11889.28 examples/s]
Generating train split: 48476769 examples [47:36, 11735.99 examples/s]
Generating train split: 48479467 examples [47:36, 14416.39 examples/s]
Generating train split: 48481184 examples [47:36, 12937.38 examples/s]
Generating train split: 48482676 examples [47:36, 9422.19 examples/s] 
Generating train split: 48483866 examples [47:36, 9757.62 examples/s]
Generating train split: 48485045 examples [47:37, 9301.85 examples/s]
Generating train split: 48493329 examples [47:37, 24152.13 examples/s]
Generating train split: 48502182 examples [47:37, 38556.80 examples/s]
Generating train split: 48507668 examples [47:37, 42499.35 examples/s]
Generating train split: 48512754 examples [47:37, 22783.83 examples/s]
Generating train split: 48517288 examples [47:37, 26074.70 examples/s]
Generating train split: 48521287 examples [47:38, 23037.51 examples/s]
Generating train split: 48524598 examples [47:38, 23703.28 examples/s]
Generating train split: 48527703 examples [47:38, 21489.26 examples/s]
Generating train split: 48530378 examples [47:38, 20535.94 examples/s]
Generating train split: 48532783 examples [47:38, 16567.23 examples/s]
Generating train split: 48534766 examples [47:39, 14781.61 examples/s]
Generating train split: 48536591 examples [47:39, 15411.56 examples/s]
Generating train split: 48538404 examples [47:39, 15069.63 examples/s]
Generating train split: 48540541 examples [47:39, 16405.74 examples/s]
Generating train split: 48542515 examples [47:39, 17090.84 examples/s]
Generating train split: 48544746 examples [47:39, 17891.72 examples/s]
Generating train split: 48546635 examples [47:39, 15193.05 examples/s]
Generating train split: 48548274 examples [47:39, 12480.78 examples/s]
Generating train split: 48549678 examples [47:40, 12297.26 examples/s]
Generating train split: 48554151 examples [47:40, 19367.60 examples/s]
Generating train split: 48556340 examples [47:40, 18467.53 examples/s]
Generating train split: 48558372 examples [47:40, 14432.18 examples/s]
Generating train split: 48561762 examples [47:40, 18496.95 examples/s]
Generating train split: 48566630 examples [47:40, 25407.98 examples/s]
Generating train split: 48570752 examples [47:40, 29309.40 examples/s]
Generating train split: 48575786 examples [47:40, 34782.44 examples/s]
Generating train split: 48579629 examples [47:41, 33167.09 examples/s]
Generating train split: 48583872 examples [47:41, 35609.33 examples/s]
Generating train split: 48587663 examples [47:41, 33279.85 examples/s]
Generating train split: 48592991 examples [47:41, 38548.79 examples/s]
Generating train split: 48598226 examples [47:41, 42330.57 examples/s]
Generating train split: 48606372 examples [47:41, 53326.90 examples/s]
Generating train split: 48612707 examples [47:41, 56167.55 examples/s]
Generating train split: 48618476 examples [47:41, 43929.01 examples/s]
Generating train split: 48623389 examples [47:42, 37243.89 examples/s]
Generating train split: 48627618 examples [47:42, 33216.49 examples/s]
Generating train split: 48631320 examples [47:42, 31046.37 examples/s]
Generating train split: 48636872 examples [47:42, 35201.35 examples/s]
Generating train split: 48640674 examples [47:42, 21623.10 examples/s]
Generating train split: 48644346 examples [47:43, 24138.83 examples/s]
Generating train split: 48648526 examples [47:43, 27535.68 examples/s]
Generating train split: 48652003 examples [47:43, 20991.57 examples/s]
Generating train split: 48655118 examples [47:43, 22833.53 examples/s]
Generating train split: 48659919 examples [47:43, 28020.11 examples/s]
Generating train split: 48669541 examples [47:43, 43537.07 examples/s]
Generating train split: 48676301 examples [47:43, 49420.11 examples/s]
Generating train split: 48682056 examples [47:44, 34243.02 examples/s]
Generating train split: 48686674 examples [47:44, 27080.72 examples/s]
Generating train split: 48690404 examples [47:44, 25167.74 examples/s]
Generating train split: 48693629 examples [47:44, 19192.52 examples/s]
Generating train split: 48696320 examples [47:44, 20389.00 examples/s]
Generating train split: 48699389 examples [47:45, 22181.39 examples/s]
Generating train split: 48702121 examples [47:45, 21680.19 examples/s]
Generating train split: 48704641 examples [47:45, 18292.81 examples/s]
Generating train split: 48706772 examples [47:45, 15830.93 examples/s]
Generating train split: 48710425 examples [47:45, 19827.20 examples/s]
Generating train split: 48718721 examples [47:45, 33483.91 examples/s]
Generating train split: 48726573 examples [47:45, 44107.45 examples/s]
Generating train split: 48731835 examples [47:46, 35152.89 examples/s]
Generating train split: 48736214 examples [47:46, 30202.64 examples/s]
Generating train split: 48739927 examples [47:46, 26645.45 examples/s]
Generating train split: 48743291 examples [47:46, 28001.01 examples/s]
Generating train split: 48748669 examples [47:46, 33593.52 examples/s]
Generating train split: 48752541 examples [47:47, 23621.30 examples/s]
Generating train split: 48755806 examples [47:47, 25265.02 examples/s]
Generating train split: 48760119 examples [47:47, 29022.56 examples/s]
Generating train split: 48764335 examples [47:47, 32038.92 examples/s]
Generating train split: 48768050 examples [47:47, 21959.19 examples/s]
Generating train split: 48771008 examples [47:47, 21981.40 examples/s]
Generating train split: 48773749 examples [47:47, 22923.21 examples/s]
Generating train split: 48776460 examples [47:48, 19224.83 examples/s]
Generating train split: 48781200 examples [47:48, 24862.32 examples/s]
Generating train split: 48784190 examples [47:48, 25525.44 examples/s]
Generating train split: 48787114 examples [47:48, 26222.78 examples/s]
Generating train split: 48790010 examples [47:48, 26018.27 examples/s]
Generating train split: 48794730 examples [47:48, 31509.64 examples/s]
Generating train split: 48798948 examples [47:48, 33873.20 examples/s]
Generating train split: 48802509 examples [47:49, 23579.29 examples/s]
Generating train split: 48807235 examples [47:49, 28603.68 examples/s]
Generating train split: 48813615 examples [47:49, 36804.70 examples/s]
Generating train split: 48819342 examples [47:49, 41898.75 examples/s]
Generating train split: 48824084 examples [47:49, 41177.95 examples/s]
Generating train split: 48828593 examples [47:49, 38075.77 examples/s]
Generating train split: 48833573 examples [47:49, 41041.26 examples/s]
Generating train split: 48837950 examples [47:49, 41182.03 examples/s]
Generating train split: 48842262 examples [47:49, 37662.65 examples/s]
Generating train split: 48846210 examples [47:50, 37690.06 examples/s]
Generating train split: 48850105 examples [47:50, 35283.72 examples/s]
Generating train split: 48855681 examples [47:50, 40653.85 examples/s]
Generating train split: 48859901 examples [47:50, 40864.37 examples/s]
Generating train split: 48864209 examples [47:50, 39289.42 examples/s]
Generating train split: 48868225 examples [47:50, 39452.45 examples/s]
Generating train split: 48872237 examples [47:50, 31484.81 examples/s]
Generating train split: 48875678 examples [47:50, 31894.66 examples/s]
Generating train split: 48880445 examples [47:50, 35909.33 examples/s]
Generating train split: 48884777 examples [47:51, 37885.46 examples/s]
Generating train split: 48888926 examples [47:51, 38789.43 examples/s]
Generating train split: 48893433 examples [47:51, 40535.53 examples/s]
Generating train split: 48897592 examples [47:51, 37770.92 examples/s]
Generating train split: 48901476 examples [47:51, 37903.86 examples/s]
Generating train split: 48907721 examples [47:51, 44795.89 examples/s]
Generating train split: 48913717 examples [47:51, 49131.53 examples/s]
Generating train split: 48918721 examples [47:51, 41434.36 examples/s]
Generating train split: 48923137 examples [47:51, 40971.70 examples/s]
Generating train split: 48927423 examples [47:52, 38994.71 examples/s]
Generating train split: 48931463 examples [47:52, 38409.64 examples/s]
Generating train split: 48940376 examples [47:52, 51955.91 examples/s]
Generating train split: 48949406 examples [47:52, 62547.76 examples/s]
Generating train split: 48955919 examples [47:52, 55331.78 examples/s]
Generating train split: 48961770 examples [47:52, 48468.94 examples/s]
Generating train split: 48969111 examples [47:52, 54524.90 examples/s]
Generating train split: 48976268 examples [47:52, 58908.24 examples/s]
Generating train split: 48982502 examples [47:53, 34258.52 examples/s]
Generating train split: 48987366 examples [47:53, 33099.20 examples/s]
Generating train split: 48991671 examples [47:53, 34074.17 examples/s]
Generating train split: 48995813 examples [47:53, 27969.37 examples/s]
Generating train split: 48999251 examples [47:53, 26559.80 examples/s]
Generating train split: 49002445 examples [47:54, 27571.09 examples/s]
Generating train split: 49005560 examples [47:54, 26158.12 examples/s]
Generating train split: 49010095 examples [47:54, 30433.95 examples/s]
Generating train split: 49015759 examples [47:54, 36789.02 examples/s]
Generating train split: 49025656 examples [47:54, 52783.48 examples/s]
Generating train split: 49031455 examples [47:54, 52393.20 examples/s]
Generating train split: 49039654 examples [47:54, 60396.07 examples/s]
Generating train split: 49047388 examples [47:54, 65110.35 examples/s]
Generating train split: 49054184 examples [47:55, 34544.44 examples/s]
Generating train split: 49059424 examples [47:55, 34474.68 examples/s]
Generating train split: 49064702 examples [47:55, 37886.12 examples/s]
Generating train split: 49073064 examples [47:55, 47516.22 examples/s]
Generating train split: 49080377 examples [47:55, 53313.83 examples/s]
Generating train split: 49087643 examples [47:55, 58105.71 examples/s]
Generating train split: 49095487 examples [47:55, 63404.67 examples/s]
Generating train split: 49102460 examples [47:56, 60405.35 examples/s]
Generating train split: 49108970 examples [47:56, 33546.17 examples/s]
Generating train split: 49113992 examples [47:56, 33119.92 examples/s]
Generating train split: 49118462 examples [47:56, 33441.88 examples/s]
Generating train split: 49122629 examples [47:57, 24523.61 examples/s]
Generating train split: 49125956 examples [47:57, 25926.56 examples/s]
Generating train split: 49130898 examples [47:57, 30394.74 examples/s]
Generating train split: 49134842 examples [47:57, 32317.34 examples/s]
Generating train split: 49138690 examples [47:57, 24151.75 examples/s]
Generating train split: 49141808 examples [47:57, 20405.28 examples/s]
Generating train split: 49144554 examples [47:57, 21678.11 examples/s]
Generating train split: 49154450 examples [47:58, 37527.59 examples/s]
Generating train split: 49162270 examples [47:58, 46739.35 examples/s]
Generating train split: 49167993 examples [47:58, 34717.86 examples/s]
Generating train split: 49172629 examples [47:58, 29599.86 examples/s]
Generating train split: 49176498 examples [47:58, 28471.73 examples/s]
Generating train split: 49179957 examples [47:58, 26454.00 examples/s]
Generating train split: 49183027 examples [47:59, 26125.64 examples/s]
Generating train split: 49185922 examples [47:59, 25826.13 examples/s]
Generating train split: 49188696 examples [47:59, 19931.36 examples/s]
Generating train split: 49190986 examples [47:59, 15170.67 examples/s]
Generating train split: 49192834 examples [47:59, 15326.59 examples/s]
Generating train split: 49194615 examples [48:00, 13145.42 examples/s]
Generating train split: 49196412 examples [48:00, 14045.92 examples/s]
Generating train split: 49198006 examples [48:00, 13651.21 examples/s]
Generating train split: 49199499 examples [48:00, 12133.59 examples/s]
Generating train split: 49200809 examples [48:00, 9920.23 examples/s] 
Generating train split: 49202739 examples [48:00, 11779.18 examples/s]
Generating train split: 49204925 examples [48:00, 14004.96 examples/s]
Generating train split: 49206531 examples [48:01, 11999.63 examples/s]
Generating train split: 49209841 examples [48:01, 16595.92 examples/s]
Generating train split: 49211787 examples [48:01, 16752.20 examples/s]
Generating train split: 49213813 examples [48:01, 17624.70 examples/s]
Generating train split: 49215737 examples [48:01, 14431.62 examples/s]
Generating train split: 49222389 examples [48:01, 26433.71 examples/s]
Generating train split: 49225530 examples [48:02, 16154.34 examples/s]
Generating train split: 49227972 examples [48:02, 8074.71 examples/s] 
Generating train split: 49229775 examples [48:03, 6859.93 examples/s]
Generating train split: 49232924 examples [48:03, 9281.79 examples/s]
Generating train split: 49237394 examples [48:03, 13629.27 examples/s]
Generating train split: 49240253 examples [48:03, 15858.03 examples/s]
Generating train split: 49243595 examples [48:03, 18912.56 examples/s]
Generating train split: 49246508 examples [48:04, 13083.17 examples/s]
Generating train split: 49249428 examples [48:04, 15527.76 examples/s]
Generating train split: 49255927 examples [48:04, 24336.72 examples/s]
Generating train split: 49262968 examples [48:04, 33674.27 examples/s]
Generating train split: 49268043 examples [48:04, 37258.48 examples/s]
Generating train split: 49272794 examples [48:04, 22730.85 examples/s]
Generating train split: 49277238 examples [48:04, 26310.64 examples/s]
Generating train split: 49284705 examples [48:05, 35523.79 examples/s]
Generating train split: 49290147 examples [48:05, 39568.47 examples/s]
Generating train split: 49295261 examples [48:05, 28086.35 examples/s]
Generating train split: 49299333 examples [48:05, 28421.92 examples/s]
Generating train split: 49303067 examples [48:06, 17141.30 examples/s]
Generating train split: 49305909 examples [48:06, 18355.90 examples/s]
Generating train split: 49308660 examples [48:06, 13347.45 examples/s]
Generating train split: 49311971 examples [48:06, 15989.59 examples/s]
Generating train split: 49316943 examples [48:06, 21411.54 examples/s]
Generating train split: 49320235 examples [48:06, 23368.55 examples/s]
Generating train split: 49323442 examples [48:07, 18544.65 examples/s]
Generating train split: 49326719 examples [48:07, 21074.99 examples/s]
Generating train split: 49330023 examples [48:07, 23469.98 examples/s]
Generating train split: 49336511 examples [48:07, 32819.15 examples/s]
Generating train split: 49345446 examples [48:07, 46606.24 examples/s]
Generating train split: 49350938 examples [48:07, 36349.40 examples/s]
Generating train split: 49355489 examples [48:08, 26925.20 examples/s]
Generating train split: 49359142 examples [48:08, 28210.19 examples/s]
Generating train split: 49363328 examples [48:08, 30927.10 examples/s]
Generating train split: 49367083 examples [48:08, 18284.15 examples/s]
Generating train split: 49375256 examples [48:08, 27930.92 examples/s]
Generating train split: 49383746 examples [48:08, 37931.07 examples/s]
Generating train split: 49389366 examples [48:09, 38612.77 examples/s]
Generating train split: 49394815 examples [48:09, 41657.93 examples/s]
Generating train split: 49400007 examples [48:09, 23848.22 examples/s]
Generating train split: 49406263 examples [48:09, 29707.46 examples/s]
Generating train split: 49413865 examples [48:09, 37942.18 examples/s]
Generating train split: 49420672 examples [48:09, 43946.03 examples/s]
Generating train split: 49426564 examples [48:10, 27798.16 examples/s]
Generating train split: 49431123 examples [48:10, 29501.82 examples/s]
Generating train split: 49435421 examples [48:11, 18117.63 examples/s]
Generating train split: 49438676 examples [48:11, 18913.29 examples/s]
Generating train split: 49441648 examples [48:11, 16362.27 examples/s]
Generating train split: 49444059 examples [48:11, 16882.49 examples/s]
Generating train split: 49447479 examples [48:11, 19738.40 examples/s]
Generating train split: 49450095 examples [48:11, 19700.36 examples/s]
Generating train split: 49452864 examples [48:11, 21131.32 examples/s]
Generating train split: 49455348 examples [48:12, 20770.87 examples/s]
Generating train split: 49458321 examples [48:12, 22849.74 examples/s]
Generating train split: 49461012 examples [48:12, 23853.00 examples/s]
Generating train split: 49463594 examples [48:12, 19827.46 examples/s]
Generating train split: 49465812 examples [48:12, 14646.12 examples/s]
Generating train split: 49469032 examples [48:12, 18019.35 examples/s]
Generating train split: 49471269 examples [48:13, 11166.37 examples/s]
Generating train split: 49475806 examples [48:13, 16412.69 examples/s]
Generating train split: 49478898 examples [48:13, 19011.82 examples/s]
Generating train split: 49482723 examples [48:13, 22942.00 examples/s]
Generating train split: 49488858 examples [48:13, 31622.90 examples/s]
Generating train split: 49498180 examples [48:13, 46328.00 examples/s]
Generating train split: 49503684 examples [48:14, 28033.25 examples/s]
Generating train split: 49507963 examples [48:14, 22888.52 examples/s]
Generating train split: 49511406 examples [48:14, 22701.91 examples/s]
Generating train split: 49516924 examples [48:14, 28264.27 examples/s]
Generating train split: 49526664 examples [48:14, 41855.08 examples/s]
Generating train split: 49532421 examples [48:14, 44338.12 examples/s]
Generating train split: 49537907 examples [48:15, 36478.68 examples/s]
Generating train split: 49542488 examples [48:15, 34804.52 examples/s]
Generating train split: 49547362 examples [48:15, 37664.82 examples/s]
Generating train split: 49551695 examples [48:15, 37097.85 examples/s]
Generating train split: 49555795 examples [48:15, 36701.45 examples/s]
Generating train split: 49564486 examples [48:15, 49152.61 examples/s]
Generating train split: 49571583 examples [48:15, 54752.02 examples/s]
Generating train split: 49577454 examples [48:15, 47313.26 examples/s]
Generating train split: 49586026 examples [48:16, 56817.96 examples/s]
Generating train split: 49592219 examples [48:16, 30509.02 examples/s]
Generating train split: 49596974 examples [48:16, 31748.64 examples/s]
Generating train split: 49601396 examples [48:16, 28323.97 examples/s]
Generating train split: 49605123 examples [48:17, 23723.87 examples/s]
Generating train split: 49609127 examples [48:17, 26445.40 examples/s]
Generating train split: 49613879 examples [48:17, 30521.23 examples/s]
Generating train split: 49617642 examples [48:17, 24456.95 examples/s]
Generating train split: 49620753 examples [48:17, 19902.03 examples/s]
Generating train split: 49626930 examples [48:17, 27194.72 examples/s]
Generating train split: 49636331 examples [48:17, 40506.44 examples/s]
Generating train split: 49641694 examples [48:18, 42245.72 examples/s]
Generating train split: 49646882 examples [48:18, 44428.92 examples/s]
Generating train split: 49652056 examples [48:18, 42771.79 examples/s]
Generating train split: 49659765 examples [48:18, 51316.60 examples/s]
Generating train split: 49665443 examples [48:18, 32486.83 examples/s]
Generating train split: 49669922 examples [48:18, 29548.31 examples/s]
Generating train split: 49674049 examples [48:19, 31712.43 examples/s]
Generating train split: 49679769 examples [48:19, 37041.07 examples/s]
Generating train split: 49687753 examples [48:19, 46892.01 examples/s]
Generating train split: 49693798 examples [48:19, 50243.19 examples/s]
Generating train split: 49700065 examples [48:19, 53470.99 examples/s]
Generating train split: 49708339 examples [48:19, 61402.37 examples/s]
Generating train split: 49714920 examples [48:19, 44851.37 examples/s]
Generating train split: 49720344 examples [48:20, 38128.49 examples/s]
Generating train split: 49724938 examples [48:20, 36764.50 examples/s]
Generating train split: 49729146 examples [48:20, 37434.64 examples/s]
Generating train split: 49733284 examples [48:20, 22214.74 examples/s]
Generating train split: 49736922 examples [48:20, 24488.64 examples/s]
Generating train split: 49740253 examples [48:20, 23541.39 examples/s]
Generating train split: 49743218 examples [48:21, 22070.34 examples/s]
Generating train split: 49745843 examples [48:21, 20486.89 examples/s]
Generating train split: 49750718 examples [48:21, 25958.37 examples/s]
Generating train split: 49756195 examples [48:21, 31720.39 examples/s]
Generating train split: 49759833 examples [48:21, 32206.27 examples/s]
Generating train split: 49765254 examples [48:21, 37692.14 examples/s]
Generating train split: 49769364 examples [48:21, 35028.50 examples/s]
Generating train split: 49774759 examples [48:21, 39823.00 examples/s]
Generating train split: 49781818 examples [48:22, 48011.11 examples/s]
Generating train split: 49786911 examples [48:22, 43260.71 examples/s]
Generating train split: 49794271 examples [48:22, 51094.95 examples/s]
Generating train split: 49799704 examples [48:22, 39885.00 examples/s]
Generating train split: 49804287 examples [48:22, 40237.34 examples/s]
Generating train split: 49808729 examples [48:22, 39146.87 examples/s]
Generating train split: 49813949 examples [48:22, 42351.95 examples/s]
Generating train split: 49819100 examples [48:22, 44723.27 examples/s]
Generating train split: 49826377 examples [48:22, 52318.66 examples/s]
Generating train split: 49835331 examples [48:23, 62701.45 examples/s]
Generating train split: 49844585 examples [48:23, 71143.65 examples/s]
Generating train split: 49851918 examples [48:23, 59265.73 examples/s]
Generating train split: 49858332 examples [48:23, 57709.94 examples/s]
Generating train split: 49865338 examples [48:23, 60866.43 examples/s]
Generating train split: 49871710 examples [48:23, 60126.13 examples/s]
Generating train split: 49877923 examples [48:24, 31836.81 examples/s]
Generating train split: 49882707 examples [48:24, 26429.81 examples/s]
Generating train split: 49886561 examples [48:24, 24164.80 examples/s]
Generating train split: 49889816 examples [48:24, 19638.65 examples/s]
Generating train split: 49892632 examples [48:25, 20906.58 examples/s]
Generating train split: 49895364 examples [48:25, 21661.20 examples/s]
Generating train split: 49897991 examples [48:25, 17529.26 examples/s]
Generating train split: 49900152 examples [48:25, 18163.69 examples/s]
Generating train split: 49902303 examples [48:25, 16775.10 examples/s]
Generating train split: 49904211 examples [48:25, 14217.99 examples/s]
Generating train split: 49905835 examples [48:26, 11684.93 examples/s]
Generating train split: 49908308 examples [48:26, 13974.71 examples/s]
Generating train split: 49911663 examples [48:26, 17753.82 examples/s]
Generating train split: 49913773 examples [48:26, 14109.99 examples/s]
Generating train split: 49915522 examples [48:26, 14546.50 examples/s]
Generating train split: 49919219 examples [48:26, 19399.53 examples/s]
Generating train split: 49925429 examples [48:26, 29308.15 examples/s]
Generating train split: 49928865 examples [48:27, 18411.61 examples/s]
Generating train split: 49931990 examples [48:27, 20689.80 examples/s]
Generating train split: 49934811 examples [48:27, 22095.54 examples/s]
Generating train split: 49937610 examples [48:27, 14467.11 examples/s]
Generating train split: 49939794 examples [48:27, 14547.89 examples/s]
Generating train split: 49942609 examples [48:28, 16950.48 examples/s]
Generating train split: 49944826 examples [48:28, 13955.88 examples/s]
Generating train split: 49948147 examples [48:28, 17488.46 examples/s]
Generating train split: 49950418 examples [48:28, 17125.33 examples/s]
Generating train split: 49952579 examples [48:28, 18035.28 examples/s]
Generating train split: 49954675 examples [48:29, 10854.77 examples/s]
Generating train split: 49956301 examples [48:29, 10958.14 examples/s]
Generating train split: 49958923 examples [48:29, 13534.25 examples/s]
Generating train split: 49960697 examples [48:29, 10669.07 examples/s]
Generating train split: 49962141 examples [48:29, 9765.06 examples/s] 
Generating train split: 49963375 examples [48:29, 8155.22 examples/s]
Generating train split: 49964917 examples [48:30, 9368.94 examples/s]
Generating train split: 49966093 examples [48:30, 9296.70 examples/s]
Generating train split: 49967799 examples [48:30, 10902.94 examples/s]
Generating train split: 49969075 examples [48:30, 7853.87 examples/s] 
Generating train split: 49970236 examples [48:30, 8537.01 examples/s]
Generating train split: 49972547 examples [48:30, 11515.25 examples/s]
Generating train split: 49975028 examples [48:30, 14266.17 examples/s]
Generating train split: 49976776 examples [48:31, 14308.63 examples/s]
Generating train split: 49979360 examples [48:31, 16725.25 examples/s]
Generating train split: 49981190 examples [48:31, 16205.72 examples/s]
Generating train split: 49984562 examples [48:31, 20711.22 examples/s]
Generating train split: 49986839 examples [48:31, 21095.01 examples/s]
Generating train split: 49989073 examples [48:31, 17112.05 examples/s]
Generating train split: 49990976 examples [48:31, 15673.34 examples/s]
Generating train split: 49993158 examples [48:31, 16995.84 examples/s]
Generating train split: 49995341 examples [48:31, 18192.35 examples/s]
Generating train split: 49997281 examples [48:32, 17392.01 examples/s]
Generating train split: 49999600 examples [48:32, 18901.15 examples/s]
Generating train split: 50001582 examples [48:32, 19007.76 examples/s]
Generating train split: 50003543 examples [48:32, 17701.12 examples/s]
Generating train split: 50005379 examples [48:32, 13921.55 examples/s]
Generating train split: 50007628 examples [48:32, 15881.04 examples/s]
Generating train split: 50009440 examples [48:32, 16312.02 examples/s]
Generating train split: 50011880 examples [48:32, 18408.67 examples/s]
Generating train split: 50019819 examples [48:33, 34888.36 examples/s]
Generating train split: 50027656 examples [48:33, 46995.18 examples/s]
Generating train split: 50032635 examples [48:33, 33512.56 examples/s]
Generating train split: 50036727 examples [48:33, 20940.69 examples/s]
Generating train split: 50044552 examples [48:33, 30039.29 examples/s]
Generating train split: 50052122 examples [48:34, 37763.71 examples/s]
Generating train split: 50057372 examples [48:34, 25309.80 examples/s]
Generating train split: 50061446 examples [48:34, 18937.59 examples/s]
Generating train split: 50064612 examples [48:35, 18324.35 examples/s]
Generating train split: 50067309 examples [48:35, 14912.50 examples/s]
Generating train split: 50069452 examples [48:35, 15015.78 examples/s]
Generating train split: 50071422 examples [48:35, 15412.98 examples/s]
Generating train split: 50073327 examples [48:35, 12509.15 examples/s]
Generating train split: 50075019 examples [48:35, 13148.36 examples/s]
Generating train split: 50076591 examples [48:36, 13524.02 examples/s]
Generating train split: 50078143 examples [48:36, 11547.73 examples/s]
Generating train split: 50079813 examples [48:36, 12536.13 examples/s]
Generating train split: 50081968 examples [48:36, 14534.35 examples/s]
Generating train split: 50086645 examples [48:36, 22293.75 examples/s]
Generating train split: 50094896 examples [48:36, 37259.95 examples/s]
Generating train split: 50099048 examples [48:36, 26365.16 examples/s]
Generating train split: 50103948 examples [48:37, 31038.43 examples/s]
Generating train split: 50111080 examples [48:37, 40210.27 examples/s]
Generating train split: 50119267 examples [48:37, 50336.77 examples/s]
Generating train split: 50125077 examples [48:37, 39363.97 examples/s]
Generating train split: 50129914 examples [48:37, 22737.50 examples/s]
Generating train split: 50133604 examples [48:38, 24448.07 examples/s]
Generating train split: 50137968 examples [48:38, 27523.98 examples/s]
Generating train split: 50141745 examples [48:38, 21960.90 examples/s]
Generating train split: 50144801 examples [48:38, 22953.13 examples/s]
Generating train split: 50151155 examples [48:38, 30806.56 examples/s]
Generating train split: 50158911 examples [48:38, 40922.02 examples/s]
Generating train split: 50164573 examples [48:38, 43469.17 examples/s]
Generating train split: 50169677 examples [48:39, 28275.64 examples/s]
Generating train split: 50173700 examples [48:39, 27066.22 examples/s]
Generating train split: 50177237 examples [48:39, 28356.74 examples/s]
Generating train split: 50180719 examples [48:39, 19715.44 examples/s]
Generating train split: 50183464 examples [48:40, 18358.07 examples/s]
Generating train split: 50187170 examples [48:40, 21523.01 examples/s]
Generating train split: 50194546 examples [48:40, 31773.06 examples/s]
Generating train split: 50203554 examples [48:40, 44536.66 examples/s]
Generating train split: 50209161 examples [48:40, 38455.37 examples/s]
Generating train split: 50213938 examples [48:40, 30019.97 examples/s]
Generating train split: 50217839 examples [48:40, 29136.72 examples/s]
Generating train split: 50221361 examples [48:41, 26307.72 examples/s]
Generating train split: 50227168 examples [48:41, 32527.66 examples/s]
Generating train split: 50231054 examples [48:41, 29139.73 examples/s]
Generating train split: 50234438 examples [48:41, 25146.94 examples/s]
Generating train split: 50238598 examples [48:41, 28461.84 examples/s]
Generating train split: 50242345 examples [48:41, 30472.87 examples/s]
Generating train split: 50246988 examples [48:41, 34330.85 examples/s]
Generating train split: 50255200 examples [48:41, 46595.07 examples/s]
Generating train split: 50260731 examples [48:42, 48886.01 examples/s]
Generating train split: 50265970 examples [48:42, 25015.79 examples/s]
Generating train split: 50269976 examples [48:42, 27046.96 examples/s]
Generating train split: 50276360 examples [48:42, 33989.42 examples/s]
Generating train split: 50281001 examples [48:42, 27606.84 examples/s]
Generating train split: 50284803 examples [48:43, 26727.34 examples/s]
Generating train split: 50288246 examples [48:43, 28198.59 examples/s]
Generating train split: 50292403 examples [48:43, 31084.36 examples/s]
Generating train split: 50301394 examples [48:43, 44980.90 examples/s]
Generating train split: 50310502 examples [48:43, 56614.66 examples/s]
Generating train split: 50316904 examples [48:43, 32450.11 examples/s]
Generating train split: 50321858 examples [48:44, 30574.12 examples/s]
Generating train split: 50326112 examples [48:44, 31815.40 examples/s]
Generating train split: 50330188 examples [48:44, 21727.80 examples/s]
Generating train split: 50333379 examples [48:44, 23066.99 examples/s]
Generating train split: 50336509 examples [48:44, 19023.12 examples/s]
Generating train split: 50339064 examples [48:45, 18795.92 examples/s]
Generating train split: 50342111 examples [48:45, 20906.70 examples/s]
Generating train split: 50345406 examples [48:45, 23378.11 examples/s]
Generating train split: 50348180 examples [48:45, 19069.18 examples/s]
Generating train split: 50350499 examples [48:45, 13657.10 examples/s]
Generating train split: 50354136 examples [48:45, 17413.80 examples/s]
Generating train split: 50360178 examples [48:46, 25631.72 examples/s]
Generating train split: 50363658 examples [48:46, 20897.11 examples/s]
Generating train split: 50366826 examples [48:46, 22922.19 examples/s]
Generating train split: 50370106 examples [48:46, 25008.70 examples/s]
Generating train split: 50375272 examples [48:46, 31195.01 examples/s]
Generating train split: 50383392 examples [48:46, 43653.48 examples/s]
Generating train split: 50391085 examples [48:46, 52147.35 examples/s]
Generating train split: 50396873 examples [48:47, 43050.46 examples/s]
Generating train split: 50403897 examples [48:47, 49091.30 examples/s]
Generating train split: 50409400 examples [48:47, 44569.91 examples/s]
Generating train split: 50414328 examples [48:47, 37398.35 examples/s]
Generating train split: 50418556 examples [48:47, 35807.17 examples/s]
Generating train split: 50422461 examples [48:47, 22748.59 examples/s]
Generating train split: 50425664 examples [48:48, 24299.03 examples/s]
Generating train split: 50430083 examples [48:48, 28135.78 examples/s]
Generating train split: 50433580 examples [48:48, 27245.31 examples/s]
Generating train split: 50436784 examples [48:48, 19112.56 examples/s]
Generating train split: 50440340 examples [48:48, 21988.86 examples/s]
Generating train split: 50443186 examples [48:48, 20568.64 examples/s]
Generating train split: 50445702 examples [48:49, 16103.46 examples/s]
Generating train split: 50448793 examples [48:49, 18691.29 examples/s]
Generating train split: 50451140 examples [48:49, 16977.55 examples/s]
Generating train split: 50453188 examples [48:49, 12455.26 examples/s]
Generating train split: 50456070 examples [48:49, 15188.56 examples/s]
Generating train split: 50458565 examples [48:49, 17070.85 examples/s]
Generating train split: 50460720 examples [48:50, 12834.50 examples/s]
Generating train split: 50462455 examples [48:50, 12459.01 examples/s]
Generating train split: 50465250 examples [48:50, 15403.31 examples/s]
Generating train split: 50469382 examples [48:50, 20927.28 examples/s]
Generating train split: 50474845 examples [48:50, 28802.46 examples/s]
Generating train split: 50480414 examples [48:50, 33686.65 examples/s]
Generating train split: 50484202 examples [48:51, 22240.13 examples/s]
Generating train split: 50487428 examples [48:51, 24119.17 examples/s]
Generating train split: 50490946 examples [48:51, 26443.41 examples/s]
Generating train split: 50494152 examples [48:51, 17185.48 examples/s]
Generating train split: 50496660 examples [48:51, 17033.51 examples/s]
Generating train split: 50499260 examples [48:51, 18668.48 examples/s]
Generating train split: 50501627 examples [48:52, 14915.79 examples/s]
Generating train split: 50503556 examples [48:52, 14229.49 examples/s]
Generating train split: 50505759 examples [48:52, 15719.32 examples/s]
Generating train split: 50507628 examples [48:52, 9488.23 examples/s] 
Generating train split: 50509136 examples [48:53, 10332.15 examples/s]
Generating train split: 50510986 examples [48:53, 11779.08 examples/s]
Generating train split: 50512565 examples [48:53, 8163.69 examples/s] 
Generating train split: 50514416 examples [48:53, 9719.80 examples/s]
Generating train split: 50515815 examples [48:53, 9972.50 examples/s]
Generating train split: 50517120 examples [48:53, 9043.68 examples/s]
Generating train split: 50518270 examples [48:53, 9488.35 examples/s]
Generating train split: 50520346 examples [48:54, 11933.62 examples/s]
Generating train split: 50522147 examples [48:54, 13371.64 examples/s]
Generating train split: 50523679 examples [48:54, 13479.55 examples/s]
Generating train split: 50527983 examples [48:54, 21159.96 examples/s]
Generating train split: 50536114 examples [48:54, 37441.46 examples/s]
Generating train split: 50540194 examples [48:54, 36032.05 examples/s]
Generating train split: 50544041 examples [48:55, 20081.51 examples/s]
Generating train split: 50547022 examples [48:55, 20744.53 examples/s]
Generating train split: 50549811 examples [48:55, 16140.61 examples/s]
Generating train split: 50552043 examples [48:55, 13488.64 examples/s]
Generating train split: 50553860 examples [48:56, 11039.35 examples/s]
Generating train split: 50561189 examples [48:56, 20315.95 examples/s]
Generating train split: 50568664 examples [48:56, 29869.30 examples/s]
Generating train split: 50573170 examples [48:56, 16994.99 examples/s]
Generating train split: 50576566 examples [48:56, 16934.67 examples/s]
Generating train split: 50579883 examples [48:57, 19191.51 examples/s]
Generating train split: 50585778 examples [48:57, 25802.62 examples/s]
Generating train split: 50590997 examples [48:57, 30850.30 examples/s]
Generating train split: 50595267 examples [48:57, 20957.12 examples/s]
Generating train split: 50598597 examples [48:57, 22857.39 examples/s]
Generating train split: 50605991 examples [48:57, 32407.24 examples/s]
Generating train split: 50613311 examples [48:57, 40994.72 examples/s]
Generating train split: 50618683 examples [48:58, 42422.99 examples/s]
Generating train split: 50623834 examples [48:58, 26319.91 examples/s]
Generating train split: 50627845 examples [48:58, 27605.53 examples/s]
Generating train split: 50631631 examples [48:58, 29078.34 examples/s]
Generating train split: 50635335 examples [48:59, 20906.35 examples/s]
Generating train split: 50642566 examples [48:59, 29612.98 examples/s]
Generating train split: 50649894 examples [48:59, 38111.17 examples/s]
Generating train split: 50655051 examples [48:59, 33505.90 examples/s]
Generating train split: 50659429 examples [48:59, 22620.88 examples/s]
Generating train split: 50666560 examples [48:59, 30177.98 examples/s]
Generating train split: 50675712 examples [49:00, 40871.41 examples/s]
Generating train split: 50681468 examples [49:00, 37476.31 examples/s]
Generating train split: 50686415 examples [49:00, 22086.88 examples/s]
Generating train split: 50690168 examples [49:00, 23779.71 examples/s]
Generating train split: 50697243 examples [49:00, 31157.35 examples/s]
Generating train split: 50701858 examples [49:01, 22487.79 examples/s]
Generating train split: 50705464 examples [49:01, 24217.71 examples/s]
Generating train split: 50713888 examples [49:01, 34661.47 examples/s]
Generating train split: 50721996 examples [49:01, 43650.53 examples/s]
Generating train split: 50727868 examples [49:01, 32109.22 examples/s]
Generating train split: 50732542 examples [49:02, 25637.06 examples/s]
Generating train split: 50736282 examples [49:02, 21897.09 examples/s]
Generating train split: 50739329 examples [49:02, 20231.47 examples/s]
Generating train split: 50742825 examples [49:02, 22554.41 examples/s]
Generating train split: 50745689 examples [49:02, 23583.43 examples/s]
Generating train split: 50748533 examples [49:03, 18888.57 examples/s]
Generating train split: 50754447 examples [49:03, 26379.34 examples/s]
Generating train split: 50758896 examples [49:03, 30176.44 examples/s]
Generating train split: 50762619 examples [49:03, 23709.48 examples/s]
Generating train split: 50766158 examples [49:03, 25615.25 examples/s]
Generating train split: 50769285 examples [49:03, 25107.39 examples/s]
Generating train split: 50772195 examples [49:03, 25989.47 examples/s]
Generating train split: 50776605 examples [49:04, 30383.27 examples/s]
Generating train split: 50779968 examples [49:04, 20290.51 examples/s]
Generating train split: 50782646 examples [49:04, 21369.02 examples/s]
Generating train split: 50785369 examples [49:04, 22626.57 examples/s]
Generating train split: 50792859 examples [49:04, 34892.82 examples/s]
Generating train split: 50801674 examples [49:04, 48261.98 examples/s]
Generating train split: 50807207 examples [49:04, 40166.13 examples/s]
Generating train split: 50811932 examples [49:05, 26220.62 examples/s]
Generating train split: 50815637 examples [49:05, 27637.59 examples/s]
Generating train split: 50819644 examples [49:05, 30026.31 examples/s]
Generating train split: 50823371 examples [49:05, 28814.24 examples/s]
Generating train split: 50830485 examples [49:05, 38149.55 examples/s]
Generating train split: 50834988 examples [49:06, 26372.80 examples/s]
Generating train split: 50838577 examples [49:06, 28129.63 examples/s]
Generating train split: 50846017 examples [49:06, 37795.27 examples/s]
Generating train split: 50855679 examples [49:06, 51315.21 examples/s]
Generating train split: 50861903 examples [49:06, 40382.82 examples/s]
Generating train split: 50867044 examples [49:06, 29657.49 examples/s]
Generating train split: 50871150 examples [49:07, 26858.56 examples/s]
Generating train split: 50875598 examples [49:07, 29897.00 examples/s]
Generating train split: 50879717 examples [49:07, 31753.94 examples/s]
Generating train split: 50883520 examples [49:07, 22010.86 examples/s]
Generating train split: 50887069 examples [49:07, 24252.16 examples/s]
Generating train split: 50894618 examples [49:07, 34312.81 examples/s]
Generating train split: 50902860 examples [49:07, 44844.56 examples/s]
Generating train split: 50908471 examples [49:08, 33252.82 examples/s]
Generating train split: 50913003 examples [49:08, 28885.77 examples/s]
Generating train split: 50916790 examples [49:08, 29045.11 examples/s]
Generating train split: 50920484 examples [49:08, 30597.97 examples/s]
Generating train split: 50924071 examples [49:08, 25555.56 examples/s]
Generating train split: 50927097 examples [49:09, 21285.01 examples/s]
Generating train split: 50930965 examples [49:09, 24552.23 examples/s]
Generating train split: 50934873 examples [49:09, 27625.99 examples/s]
Generating train split: 50938106 examples [49:09, 28506.98 examples/s]
Generating train split: 50941306 examples [49:09, 28939.76 examples/s]
Generating train split: 50944457 examples [49:09, 28430.47 examples/s]
Generating train split: 50947481 examples [49:09, 24561.45 examples/s]
Generating train split: 50950712 examples [49:09, 26416.57 examples/s]
Generating train split: 50953539 examples [49:09, 26788.72 examples/s]
Generating train split: 50956363 examples [49:10, 23316.20 examples/s]
Generating train split: 50958857 examples [49:10, 23334.59 examples/s]
Generating train split: 50962557 examples [49:10, 26622.18 examples/s]
Generating train split: 50969254 examples [49:10, 37394.86 examples/s]
Generating train split: 50977513 examples [49:10, 49870.65 examples/s]
Generating train split: 50982765 examples [49:10, 35509.89 examples/s]
Generating train split: 50987075 examples [49:10, 31921.84 examples/s]
Generating train split: 50990839 examples [49:11, 30953.52 examples/s]
Generating train split: 50994315 examples [49:11, 24053.40 examples/s]
Generating train split: 50997180 examples [49:11, 20020.96 examples/s]
Generating train split: 50999564 examples [49:11, 20305.84 examples/s]
Generating train split: 51003149 examples [49:11, 23418.41 examples/s]
Generating train split: 51005839 examples [49:11, 20848.04 examples/s]
Generating train split: 51008193 examples [49:12, 17389.76 examples/s]
Generating train split: 51010181 examples [49:12, 16882.05 examples/s]
Generating train split: 51013949 examples [49:12, 21276.78 examples/s]
Generating train split: 51017310 examples [49:12, 24137.65 examples/s]
Generating train split: 51023485 examples [49:12, 33509.87 examples/s]
Generating train split: 51028438 examples [49:12, 37703.90 examples/s]
Generating train split: 51032546 examples [49:12, 38292.00 examples/s]
Generating train split: 51037902 examples [49:12, 42535.48 examples/s]
Generating train split: 51043132 examples [49:13, 45313.38 examples/s]
Generating train split: 51051789 examples [49:13, 57232.52 examples/s]
Generating train split: 51057664 examples [49:13, 43440.38 examples/s]
Generating train split: 51062618 examples [49:13, 34214.57 examples/s]
Generating train split: 51066725 examples [49:13, 34006.27 examples/s]
Generating train split: 51070604 examples [49:13, 33865.99 examples/s]
Generating train split: 51078358 examples [49:13, 44022.53 examples/s]
Generating train split: 51087331 examples [49:13, 55422.69 examples/s]
Generating train split: 51094687 examples [49:14, 57888.10 examples/s]
Generating train split: 51100903 examples [49:14, 54970.74 examples/s]
Generating train split: 51106718 examples [49:14, 34837.05 examples/s]
Generating train split: 51111316 examples [49:14, 32873.42 examples/s]
Generating train split: 51116563 examples [49:14, 36664.91 examples/s]
Generating train split: 51121277 examples [49:14, 38930.60 examples/s]
Generating train split: 51125782 examples [49:15, 38567.25 examples/s]
Generating train split: 51130063 examples [49:15, 25725.56 examples/s]
Generating train split: 51133653 examples [49:15, 27583.40 examples/s]
Generating train split: 51137252 examples [49:15, 29327.15 examples/s]
Generating train split: 51140958 examples [49:15, 31093.42 examples/s]
Generating train split: 51144526 examples [49:15, 30534.12 examples/s]
Generating train split: 51150232 examples [49:15, 37169.84 examples/s]
Generating train split: 51157412 examples [49:15, 46288.66 examples/s]
Generating train split: 51162412 examples [49:16, 26946.33 examples/s]
Generating train split: 51166311 examples [49:16, 28109.09 examples/s]
Generating train split: 51171482 examples [49:16, 32839.04 examples/s]
Generating train split: 51175628 examples [49:16, 33314.78 examples/s]
Generating train split: 51182273 examples [49:16, 41054.70 examples/s]
Generating train split: 51190630 examples [49:16, 51690.74 examples/s]
Generating train split: 51198445 examples [49:17, 58644.34 examples/s]
Generating train split: 51204877 examples [49:17, 32517.91 examples/s]
Generating train split: 51209845 examples [49:17, 33094.78 examples/s]
Generating train split: 51214377 examples [49:17, 34812.87 examples/s]
Generating train split: 51218808 examples [49:17, 36137.82 examples/s]
Generating train split: 51223668 examples [49:17, 38959.75 examples/s]
Generating train split: 51228158 examples [49:18, 23618.42 examples/s]
Generating train split: 51231651 examples [49:18, 25066.85 examples/s]
Generating train split: 51236357 examples [49:18, 29293.56 examples/s]
Generating train split: 51240134 examples [49:18, 22686.52 examples/s]
Generating train split: 51243194 examples [49:18, 22688.64 examples/s]
Generating train split: 51246018 examples [49:18, 23532.19 examples/s]
Generating train split: 51248805 examples [49:19, 24388.82 examples/s]
Generating train split: 51251578 examples [49:19, 20533.54 examples/s]
Generating train split: 51253941 examples [49:19, 17985.95 examples/s]
Generating train split: 51257763 examples [49:19, 22119.49 examples/s]
Generating train split: 51261341 examples [49:19, 25230.03 examples/s]
Generating train split: 51264208 examples [49:19, 24603.32 examples/s]
Generating train split: 51266921 examples [49:19, 24767.84 examples/s]
Generating train split: 51269567 examples [49:20, 23248.22 examples/s]
Generating train split: 51272020 examples [49:20, 21067.87 examples/s]
Generating train split: 51274659 examples [49:20, 22336.39 examples/s]
Generating train split: 51278904 examples [49:20, 27425.40 examples/s]
Generating train split: 51283326 examples [49:20, 31919.04 examples/s]
Generating train split: 51286674 examples [49:20, 27193.00 examples/s]
Generating train split: 51289614 examples [49:20, 24853.64 examples/s]
Generating train split: 51292274 examples [49:20, 23074.01 examples/s]
Generating train split: 51299363 examples [49:21, 34549.83 examples/s]
Generating train split: 51308184 examples [49:21, 48243.41 examples/s]
Generating train split: 51314883 examples [49:21, 53228.95 examples/s]
Generating train split: 51320616 examples [49:21, 48654.38 examples/s]
Generating train split: 51329320 examples [49:21, 58671.77 examples/s]
Generating train split: 51336457 examples [49:21, 62115.12 examples/s]
Generating train split: 51342994 examples [49:21, 59846.16 examples/s]
Generating train split: 51352748 examples [49:21, 70208.91 examples/s]
Generating train split: 51360038 examples [49:22, 43434.35 examples/s]
Generating train split: 51365814 examples [49:22, 37593.22 examples/s]
Generating train split: 51370659 examples [49:22, 36608.91 examples/s]
Generating train split: 51378655 examples [49:22, 45175.63 examples/s]
Generating train split: 51384367 examples [49:22, 47699.07 examples/s]
Generating train split: 51389905 examples [49:22, 46404.81 examples/s]
Generating train split: 51395073 examples [49:23, 26426.72 examples/s]
Generating train split: 51399776 examples [49:23, 29739.55 examples/s]
Generating train split: 51403975 examples [49:23, 31991.17 examples/s]
Generating train split: 51408169 examples [49:23, 21602.78 examples/s]
Generating train split: 51412195 examples [49:23, 24584.01 examples/s]
Generating train split: 51416490 examples [49:24, 27999.06 examples/s]
Generating train split: 51420226 examples [49:24, 27319.15 examples/s]
Generating train split: 51423611 examples [49:24, 28175.89 examples/s]
Generating train split: 51426915 examples [49:24, 24574.32 examples/s]
Generating train split: 51429999 examples [49:24, 25899.93 examples/s]
Generating train split: 51432925 examples [49:24, 23612.78 examples/s]
Generating train split: 51437359 examples [49:24, 28063.01 examples/s]
Generating train split: 51440461 examples [49:25, 19136.82 examples/s]
Generating train split: 51442931 examples [49:25, 17717.90 examples/s]
Generating train split: 51446010 examples [49:25, 20175.64 examples/s]
Generating train split: 51448435 examples [49:25, 20446.98 examples/s]
Generating train split: 51450775 examples [49:25, 16488.47 examples/s]
Generating train split: 51452741 examples [49:25, 16993.99 examples/s]
Generating train split: 51456424 examples [49:25, 21433.33 examples/s]
Generating train split: 51458891 examples [49:26, 21778.37 examples/s]
Generating train split: 51461308 examples [49:26, 22259.64 examples/s]
Generating train split: 51463702 examples [49:26, 19896.25 examples/s]
Generating train split: 51465859 examples [49:26, 19460.64 examples/s]
Generating train split: 51468480 examples [49:26, 21172.52 examples/s]
Generating train split: 51474244 examples [49:26, 30873.33 examples/s]
Generating train split: 51477529 examples [49:26, 25444.65 examples/s]
Generating train split: 51480369 examples [49:27, 21224.76 examples/s]
Generating train split: 51483779 examples [49:27, 24040.33 examples/s]
Generating train split: 51487801 examples [49:27, 27888.56 examples/s]
Generating train split: 51491446 examples [49:27, 30026.27 examples/s]
Generating train split: 51494710 examples [49:27, 19233.07 examples/s]
Generating train split: 51498241 examples [49:27, 22307.48 examples/s]
Generating train split: 51501112 examples [49:27, 23309.91 examples/s]
Generating train split: 51506625 examples [49:27, 30696.14 examples/s]
Generating train split: 51513063 examples [49:28, 39077.44 examples/s]
Generating train split: 51519713 examples [49:28, 46264.69 examples/s]
Generating train split: 51524840 examples [49:28, 44795.18 examples/s]
Generating train split: 51529797 examples [49:28, 46057.90 examples/s]
Generating train split: 51536340 examples [49:28, 51413.83 examples/s]
Generating train split: 51541711 examples [49:28, 32493.51 examples/s]
Generating train split: 51545992 examples [49:28, 34301.65 examples/s]
Generating train split: 51550219 examples [49:29, 32548.96 examples/s]
Generating train split: 51554033 examples [49:29, 26078.78 examples/s]
Generating train split: 51557193 examples [49:29, 23474.95 examples/s]
Generating train split: 51559934 examples [49:30, 8724.35 examples/s] 
Generating train split: 51561933 examples [49:30, 9088.18 examples/s]
Generating train split: 51563667 examples [49:30, 9688.37 examples/s]
Generating train split: 51565616 examples [49:30, 10957.05 examples/s]
Generating train split: 51567555 examples [49:30, 12162.22 examples/s]
Generating train split: 51569302 examples [49:31, 9705.01 examples/s] 
Generating train split: 51571722 examples [49:31, 12031.29 examples/s]
Generating train split: 51574553 examples [49:31, 15073.18 examples/s]
Generating train split: 51580875 examples [49:31, 25219.78 examples/s]
Generating train split: 51589586 examples [49:31, 39532.38 examples/s]
Generating train split: 51594533 examples [49:31, 39642.60 examples/s]
Generating train split: 51599191 examples [49:32, 24507.46 examples/s]
Generating train split: 51602825 examples [49:32, 26097.23 examples/s]
Generating train split: 51606928 examples [49:32, 29040.39 examples/s]
Generating train split: 51610634 examples [49:32, 30686.54 examples/s]
Generating train split: 51614321 examples [49:32, 22368.65 examples/s]
Generating train split: 51618746 examples [49:32, 26547.55 examples/s]
Generating train split: 51623460 examples [49:32, 30953.62 examples/s]
Generating train split: 51629943 examples [49:33, 38897.59 examples/s]
Generating train split: 51634679 examples [49:33, 41010.88 examples/s]
Generating train split: 51639324 examples [49:33, 34485.68 examples/s]
Generating train split: 51643318 examples [49:33, 34567.65 examples/s]
Generating train split: 51650932 examples [49:33, 44458.70 examples/s]
Generating train split: 51655850 examples [49:33, 43469.54 examples/s]
Generating train split: 51660528 examples [49:33, 34844.00 examples/s]
Generating train split: 51664681 examples [49:33, 36350.11 examples/s]
Generating train split: 51668696 examples [49:34, 22694.62 examples/s]
Generating train split: 51671849 examples [49:34, 21372.27 examples/s]
Generating train split: 51675801 examples [49:34, 24644.53 examples/s]
Generating train split: 51678908 examples [49:34, 18723.74 examples/s]
Generating train split: 51681401 examples [49:35, 18209.06 examples/s]
Generating train split: 51684094 examples [49:35, 19833.67 examples/s]
Generating train split: 51687392 examples [49:35, 22579.18 examples/s]
Generating train split: 51690046 examples [49:35, 15971.18 examples/s]
Generating train split: 51692163 examples [49:35, 16271.39 examples/s]
Generating train split: 51695110 examples [49:35, 18915.34 examples/s]
Generating train split: 51698088 examples [49:35, 21330.02 examples/s]
Generating train split: 51704419 examples [49:35, 31462.85 examples/s]
Generating train split: 51708063 examples [49:36, 19228.78 examples/s]
Generating train split: 51711708 examples [49:36, 22272.91 examples/s]
Generating train split: 51717546 examples [49:36, 29556.17 examples/s]
Generating train split: 51724723 examples [49:36, 38998.06 examples/s]
Generating train split: 51731764 examples [49:36, 46564.00 examples/s]
Generating train split: 51737289 examples [49:37, 34670.23 examples/s]
Generating train split: 51741798 examples [49:37, 27360.84 examples/s]
Generating train split: 51745463 examples [49:37, 27370.75 examples/s]
Generating train split: 51749416 examples [49:37, 29742.54 examples/s]
Generating train split: 51752982 examples [49:37, 20670.45 examples/s]
Generating train split: 51755802 examples [49:37, 21322.09 examples/s]
Generating train split: 51759238 examples [49:38, 23828.35 examples/s]
Generating train split: 51762546 examples [49:38, 25815.80 examples/s]
Generating train split: 51765576 examples [49:38, 23117.45 examples/s]
Generating train split: 51768237 examples [49:38, 18737.89 examples/s]
Generating train split: 51771502 examples [49:38, 21531.84 examples/s]
Generating train split: 51781363 examples [49:38, 38709.23 examples/s]
Generating train split: 51789365 examples [49:38, 48575.64 examples/s]
Generating train split: 51795056 examples [49:39, 31715.86 examples/s]
Generating train split: 51799556 examples [49:39, 25859.75 examples/s]
Generating train split: 51804866 examples [49:39, 30325.39 examples/s]
Generating train split: 51808986 examples [49:39, 32107.32 examples/s]
Generating train split: 51813046 examples [49:40, 22025.73 examples/s]
Generating train split: 51816233 examples [49:40, 23252.22 examples/s]
Generating train split: 51819328 examples [49:40, 24080.14 examples/s]
Generating train split: 51822321 examples [49:40, 15144.93 examples/s]
Generating train split: 51825249 examples [49:40, 17273.14 examples/s]
Generating train split: 51828415 examples [49:40, 19639.34 examples/s]
Generating train split: 51831063 examples [49:41, 17449.20 examples/s]
Generating train split: 51833306 examples [49:41, 16623.60 examples/s]
Generating train split: 51836490 examples [49:41, 19571.85 examples/s]
Generating train split: 51839936 examples [49:41, 22846.17 examples/s]
Generating train split: 51843770 examples [49:41, 26547.60 examples/s]
Generating train split: 51846791 examples [49:41, 20593.48 examples/s]
Generating train split: 51849304 examples [49:41, 20775.58 examples/s]
Generating train split: 51852242 examples [49:41, 22726.35 examples/s]
Generating train split: 51854802 examples [49:42, 22276.43 examples/s]
Generating train split: 51857460 examples [49:42, 23346.21 examples/s]
Generating train split: 51859960 examples [49:42, 15504.60 examples/s]
Generating train split: 51862060 examples [49:42, 16572.06 examples/s]
Generating train split: 51865561 examples [49:42, 20614.44 examples/s]
Generating train split: 51868035 examples [49:42, 17662.13 examples/s]
Generating train split: 51870155 examples [49:43, 14426.00 examples/s]
Generating train split: 51872179 examples [49:43, 15556.66 examples/s]
Generating train split: 51876463 examples [49:43, 21518.85 examples/s]
Generating train split: 51879041 examples [49:43, 19720.14 examples/s]
Generating train split: 51881324 examples [49:43, 18296.61 examples/s]
Generating train split: 51886348 examples [49:43, 25539.56 examples/s]
Generating train split: 51894370 examples [49:43, 38918.23 examples/s]
Generating train split: 51898926 examples [49:43, 40620.22 examples/s]
Generating train split: 51903430 examples [49:44, 41596.12 examples/s]
Generating train split: 51908767 examples [49:44, 44856.96 examples/s]
Generating train split: 51917480 examples [49:44, 56834.81 examples/s]
Generating train split: 51924279 examples [49:44, 60041.21 examples/s]
Generating train split: 51930464 examples [49:44, 59732.34 examples/s]
Generating train split: 51937153 examples [49:44, 61803.57 examples/s]
Generating train split: 51943883 examples [49:44, 63405.35 examples/s]
Generating train split: 51950297 examples [49:44, 42345.95 examples/s]
Generating train split: 51955505 examples [49:45, 33671.82 examples/s]
Generating train split: 51962707 examples [49:45, 41018.98 examples/s]
Generating train split: 51970406 examples [49:45, 48357.71 examples/s]
Generating train split: 51976244 examples [49:45, 43432.27 examples/s]
Generating train split: 51981357 examples [49:45, 31852.28 examples/s]
Generating train split: 51985473 examples [49:46, 26326.30 examples/s]
Generating train split: 51990095 examples [49:46, 29511.84 examples/s]
Generating train split: 51993792 examples [49:46, 29910.85 examples/s]
Generating train split: 51997317 examples [49:46, 28841.55 examples/s]
Generating train split: 52000564 examples [49:46, 26175.41 examples/s]
Generating train split: 52006228 examples [49:46, 32775.53 examples/s]
Generating train split: 52014955 examples [49:46, 45652.69 examples/s]
Generating train split: 52020207 examples [49:46, 47364.73 examples/s]
Generating train split: 52025433 examples [49:47, 44792.40 examples/s]
Generating train split: 52030272 examples [49:47, 44065.00 examples/s]
Generating train split: 52037076 examples [49:47, 50350.25 examples/s]
Generating train split: 52044588 examples [49:47, 57091.33 examples/s]
Generating train split: 52050549 examples [49:47, 35072.04 examples/s]
Generating train split: 52055271 examples [49:47, 33421.37 examples/s]
Generating train split: 52059454 examples [49:47, 33475.57 examples/s]
Generating train split: 52063392 examples [49:48, 34522.05 examples/s]
Generating train split: 52068248 examples [49:48, 37652.16 examples/s]
Generating train split: 52072418 examples [49:48, 21133.08 examples/s]
Generating train split: 52076967 examples [49:48, 25094.48 examples/s]
Generating train split: 52081135 examples [49:48, 28210.55 examples/s]
Generating train split: 52084916 examples [49:49, 21520.65 examples/s]
Generating train split: 52087959 examples [49:49, 21073.95 examples/s]
Generating train split: 52091525 examples [49:49, 23809.23 examples/s]
Generating train split: 52095284 examples [49:49, 26717.03 examples/s]
Generating train split: 52098836 examples [49:49, 28453.01 examples/s]
Generating train split: 52102107 examples [49:49, 17897.79 examples/s]
Generating train split: 52105691 examples [49:50, 21055.08 examples/s]
Generating train split: 52109620 examples [49:50, 24716.68 examples/s]
Generating train split: 52117997 examples [49:50, 37888.08 examples/s]
Generating train split: 52125608 examples [49:50, 47115.98 examples/s]
Generating train split: 52131211 examples [49:50, 45538.30 examples/s]
Generating train split: 52136394 examples [49:50, 28308.39 examples/s]
Generating train split: 52140454 examples [49:50, 28679.85 examples/s]
Generating train split: 52145502 examples [49:51, 32883.77 examples/s]
Generating train split: 52150296 examples [49:51, 36120.28 examples/s]
Generating train split: 52154680 examples [49:51, 37875.79 examples/s]
Generating train split: 52160638 examples [49:51, 43335.06 examples/s]
Generating train split: 52168744 examples [49:51, 53295.74 examples/s]
Generating train split: 52174558 examples [49:51, 29917.68 examples/s]
Generating train split: 52179055 examples [49:51, 31187.50 examples/s]
Generating train split: 52183281 examples [49:52, 32584.61 examples/s]
Generating train split: 52187804 examples [49:52, 35280.00 examples/s]
Generating train split: 52192028 examples [49:52, 21110.02 examples/s]
Generating train split: 52195306 examples [49:52, 22979.39 examples/s]
Generating train split: 52199015 examples [49:52, 25607.15 examples/s]
Generating train split: 52202417 examples [49:52, 25858.81 examples/s]
Generating train split: 52205595 examples [49:53, 19811.40 examples/s]
Generating train split: 52208182 examples [49:53, 20805.77 examples/s]
Generating train split: 52212923 examples [49:53, 26386.06 examples/s]
Generating train split: 52216137 examples [49:53, 27272.68 examples/s]
Generating train split: 52219287 examples [49:53, 17526.47 examples/s]
Generating train split: 52224240 examples [49:53, 23139.26 examples/s]
Generating train split: 52229541 examples [49:54, 28991.10 examples/s]
Generating train split: 52233380 examples [49:54, 31081.93 examples/s]
Generating train split: 52237183 examples [49:54, 19276.82 examples/s]
Generating train split: 52240137 examples [49:54, 20799.12 examples/s]
Generating train split: 52243726 examples [49:54, 23704.38 examples/s]
Generating train split: 52246839 examples [49:54, 20382.47 examples/s]
Generating train split: 52249456 examples [49:55, 16636.79 examples/s]
Generating train split: 52253085 examples [49:55, 20124.89 examples/s]
Generating train split: 52255675 examples [49:55, 20739.69 examples/s]
Generating train split: 52258176 examples [49:55, 20953.20 examples/s]
Generating train split: 52261108 examples [49:55, 22812.37 examples/s]
Generating train split: 52263995 examples [49:55, 24319.00 examples/s]
Generating train split: 52266643 examples [49:55, 24471.44 examples/s]
Generating train split: 52270157 examples [49:55, 27336.55 examples/s]
Generating train split: 52273028 examples [49:56, 24656.45 examples/s]
Generating train split: 52276741 examples [49:56, 27807.79 examples/s]
Generating train split: 52280568 examples [49:56, 30636.07 examples/s]
Generating train split: 52285436 examples [49:56, 35581.08 examples/s]
Generating train split: 52289122 examples [49:56, 27760.38 examples/s]
Generating train split: 52292257 examples [49:56, 27851.71 examples/s]
Generating train split: 52295285 examples [49:56, 24798.85 examples/s]
Generating train split: 52297975 examples [49:57, 20113.08 examples/s]
Generating train split: 52300246 examples [49:57, 18076.70 examples/s]
Generating train split: 52302246 examples [49:57, 17398.09 examples/s]
Generating train split: 52304108 examples [49:57, 16896.03 examples/s]
Generating train split: 52305884 examples [49:57, 13741.31 examples/s]
Generating train split: 52308916 examples [49:57, 17215.74 examples/s]
Generating train split: 52311018 examples [49:57, 18085.36 examples/s]
Generating train split: 52313207 examples [49:58, 19016.71 examples/s]
Generating train split: 52315264 examples [49:58, 17842.93 examples/s]
Generating train split: 52317171 examples [49:58, 17065.64 examples/s]
Generating train split: 52320519 examples [49:58, 21248.54 examples/s]
Generating train split: 52323121 examples [49:58, 22518.14 examples/s]
Generating train split: 52328526 examples [49:58, 31213.41 examples/s]
Generating train split: 52334669 examples [49:58, 39755.61 examples/s]
Generating train split: 52340892 examples [49:58, 46207.89 examples/s]
Generating train split: 52347051 examples [49:58, 50672.93 examples/s]
Generating train split: 52353272 examples [49:58, 54053.02 examples/s]
Generating train split: 52358762 examples [49:59, 53778.16 examples/s]
Generating train split: 52364204 examples [49:59, 53365.74 examples/s]
Generating train split: 52369637 examples [49:59, 53644.67 examples/s]
Generating train split: 52377940 examples [49:59, 62309.43 examples/s]
Generating train split: 52384388 examples [49:59, 62940.90 examples/s]
Generating train split: 52392321 examples [49:59, 67812.28 examples/s]
Generating train split: 52400397 examples [49:59, 71651.88 examples/s]
Generating train split: 52407584 examples [49:59, 66679.53 examples/s]
Generating train split: 52414337 examples [49:59, 66491.97 examples/s]
Generating train split: 52421051 examples [50:00, 56783.34 examples/s]
Generating train split: 52427020 examples [50:00, 55424.06 examples/s]
Generating train split: 52436636 examples [50:00, 66113.45 examples/s]
Generating train split: 52445147 examples [50:00, 71288.12 examples/s]
Generating train split: 52452533 examples [50:00, 70851.91 examples/s]
Generating train split: 52460927 examples [50:00, 74546.84 examples/s]
Generating train split: 52469056 examples [50:00, 76465.75 examples/s]
Generating train split: 52477157 examples [50:00, 77770.73 examples/s]
Generating train split: 52485025 examples [50:00, 75011.05 examples/s]
Generating train split: 52492607 examples [50:01, 73644.50 examples/s]
Generating train split: 52501413 examples [50:01, 77759.02 examples/s]
Generating train split: 52509248 examples [50:01, 75071.45 examples/s]
Generating train split: 52516809 examples [50:01, 71817.62 examples/s]
Generating train split: 52524048 examples [50:01, 71895.01 examples/s]
Generating train split: 52531280 examples [50:01, 68491.16 examples/s]
Generating train split: 52538181 examples [50:01, 68110.02 examples/s]
Generating train split: 52545040 examples [50:01, 68150.86 examples/s]
Generating train split: 52552747 examples [50:01, 70696.90 examples/s]
Generating train split: 52559846 examples [50:02, 65663.47 examples/s]
Generating train split: 52566495 examples [50:02, 50670.61 examples/s]
Generating train split: 52572116 examples [50:02, 45770.79 examples/s]
Generating train split: 52577116 examples [50:02, 41018.05 examples/s]
Generating train split: 52581546 examples [50:02, 31526.05 examples/s]
Generating train split: 52585187 examples [50:02, 29685.01 examples/s]
Generating train split: 52588473 examples [50:03, 26318.12 examples/s]
Generating train split: 52591339 examples [50:03, 20732.53 examples/s]
Generating train split: 52593697 examples [50:03, 19917.50 examples/s]
Generating train split: 52595860 examples [50:03, 18267.35 examples/s]
Generating train split: 52598674 examples [50:03, 20238.31 examples/s]
Generating train split: 52600871 examples [50:03, 19645.51 examples/s]
Generating train split: 52602945 examples [50:04, 17986.57 examples/s]
Generating train split: 52604826 examples [50:04, 13129.31 examples/s]
Generating train split: 52607341 examples [50:04, 15411.87 examples/s]
Generating train split: 52609159 examples [50:04, 15307.64 examples/s]
Generating train split: 52611370 examples [50:04, 16822.21 examples/s]
Generating train split: 52613240 examples [50:04, 14366.83 examples/s]
Generating train split: 52617186 examples [50:04, 20010.37 examples/s]
Generating train split: 52619506 examples [50:05, 19120.14 examples/s]
Generating train split: 52621638 examples [50:05, 17914.56 examples/s]
Generating train split: 52623592 examples [50:05, 17565.80 examples/s]
Generating train split: 52625458 examples [50:05, 15920.97 examples/s]
Generating train split: 52627766 examples [50:05, 17486.71 examples/s]
Generating train split: 52629616 examples [50:05, 16547.18 examples/s]
Generating train split: 52631340 examples [50:05, 13173.75 examples/s]
Generating train split: 52632797 examples [50:06, 10032.75 examples/s]
Generating train split: 52634148 examples [50:06, 10693.32 examples/s]
Generating train split: 52635856 examples [50:06, 10288.45 examples/s]
Generating train split: 52637013 examples [50:06, 9856.36 examples/s] 
Generating train split: 52639167 examples [50:06, 12379.92 examples/s]
Generating train split: 52640973 examples [50:06, 13679.39 examples/s]
Generating train split: 52642494 examples [50:06, 13204.54 examples/s]
Generating train split: 52644283 examples [50:06, 14382.14 examples/s]
Generating train split: 52645821 examples [50:07, 13615.41 examples/s]
Generating train split: 52648345 examples [50:07, 16637.51 examples/s]
Generating train split: 52650175 examples [50:07, 16856.75 examples/s]
Generating train split: 52651935 examples [50:07, 12743.32 examples/s]
Generating train split: 52653409 examples [50:07, 11773.49 examples/s]
Generating train split: 52654952 examples [50:07, 12588.11 examples/s]
Generating train split: 52657960 examples [50:07, 16731.85 examples/s]
Generating train split: 52660232 examples [50:07, 17927.21 examples/s]
Generating train split: 52662160 examples [50:08, 15083.44 examples/s]
Generating train split: 52663834 examples [50:08, 13616.14 examples/s]
Generating train split: 52665322 examples [50:08, 13521.34 examples/s]
Generating train split: 52667314 examples [50:08, 15021.01 examples/s]
Generating train split: 52668919 examples [50:08, 15091.81 examples/s]
Generating train split: 52670510 examples [50:08, 13083.58 examples/s]
Generating train split: 52672596 examples [50:08, 14985.95 examples/s]
Generating train split: 52678892 examples [50:08, 27416.30 examples/s]
Generating train split: 52689018 examples [50:09, 47364.19 examples/s]
Generating train split: 52694165 examples [50:09, 43894.13 examples/s]
Generating train split: 52698894 examples [50:09, 35553.80 examples/s]
Generating train split: 52702917 examples [50:09, 22065.64 examples/s]
Generating train split: 52706052 examples [50:09, 23397.02 examples/s]
Generating train split: 52713208 examples [50:10, 32543.47 examples/s]
Generating train split: 52719493 examples [50:10, 38999.38 examples/s]
Generating train split: 52725159 examples [50:10, 43117.29 examples/s]
Generating train split: 52730287 examples [50:10, 24960.68 examples/s]
Generating train split: 52737570 examples [50:10, 32852.97 examples/s]
Generating train split: 52745331 examples [50:10, 41378.94 examples/s]
Generating train split: 52751120 examples [50:11, 34669.96 examples/s]
Generating train split: 52755907 examples [50:11, 28667.41 examples/s]
Generating train split: 52761170 examples [50:11, 32825.61 examples/s]
Generating train split: 52765495 examples [50:11, 26549.21 examples/s]
Generating train split: 52769019 examples [50:11, 25634.73 examples/s]
Generating train split: 52773716 examples [50:11, 29635.28 examples/s]
Generating train split: 52777931 examples [50:12, 32272.48 examples/s]
Generating train split: 52782931 examples [50:12, 36212.81 examples/s]
Generating train split: 52787064 examples [50:12, 26489.58 examples/s]
Generating train split: 52790418 examples [50:12, 26438.58 examples/s]
Generating train split: 52799978 examples [50:12, 41191.36 examples/s]
Generating train split: 52805610 examples [50:12, 44717.61 examples/s]
Generating train split: 52810844 examples [50:12, 44808.14 examples/s]
Generating train split: 52815858 examples [50:13, 22479.17 examples/s]
Generating train split: 52823715 examples [50:13, 30942.65 examples/s]
Generating train split: 52831952 examples [50:13, 40057.49 examples/s]
Generating train split: 52837951 examples [50:13, 38723.02 examples/s]
Generating train split: 52843215 examples [50:14, 24051.33 examples/s]
Generating train split: 52847239 examples [50:14, 26006.13 examples/s]
Generating train split: 52851170 examples [50:14, 19813.72 examples/s]
Generating train split: 52854256 examples [50:14, 19398.87 examples/s]
Generating train split: 52857185 examples [50:14, 20909.01 examples/s]
Generating train split: 52859939 examples [50:15, 19393.40 examples/s]
Generating train split: 52862338 examples [50:15, 19033.36 examples/s]
Generating train split: 52865566 examples [50:15, 21683.69 examples/s]
Generating train split: 52868083 examples [50:15, 21809.96 examples/s]
Generating train split: 52872046 examples [50:15, 25984.48 examples/s]
Generating train split: 52874931 examples [50:15, 23114.55 examples/s]
Generating train split: 52877490 examples [50:15, 20624.19 examples/s]
Generating train split: 52884437 examples [50:15, 31752.15 examples/s]
Generating train split: 52893176 examples [50:16, 43933.42 examples/s]
Generating train split: 52898052 examples [50:16, 38509.07 examples/s]
Generating train split: 52902332 examples [50:16, 35576.58 examples/s]
Generating train split: 52906206 examples [50:16, 21934.40 examples/s]
Generating train split: 52909304 examples [50:16, 23439.50 examples/s]
Generating train split: 52915356 examples [50:17, 30587.04 examples/s]
Generating train split: 52920760 examples [50:17, 35638.21 examples/s]
Generating train split: 52927377 examples [50:17, 41984.79 examples/s]
Generating train split: 52932273 examples [50:17, 25293.00 examples/s]
Generating train split: 52937385 examples [50:17, 29678.09 examples/s]
Generating train split: 52941574 examples [50:18, 20973.03 examples/s]
Generating train split: 52947478 examples [50:18, 26817.50 examples/s]
Generating train split: 52951724 examples [50:18, 29633.68 examples/s]
Generating train split: 52956628 examples [50:18, 33259.35 examples/s]
Generating train split: 52960905 examples [50:18, 20454.21 examples/s]
Generating train split: 52964874 examples [50:18, 23463.20 examples/s]
Generating train split: 52968372 examples [50:19, 17836.11 examples/s]
Generating train split: 52971135 examples [50:19, 18437.66 examples/s]
Generating train split: 52977031 examples [50:19, 25459.42 examples/s]
Generating train split: 52986928 examples [50:19, 40041.62 examples/s]
Generating train split: 52992386 examples [50:19, 41716.32 examples/s]
Generating train split: 52997623 examples [50:20, 28380.53 examples/s]
Generating train split: 53001754 examples [50:20, 27581.32 examples/s]
Generating train split: 53010095 examples [50:20, 37885.24 examples/s]
Generating train split: 53018921 examples [50:20, 48035.24 examples/s]
Generating train split: 53025016 examples [50:20, 31331.40 examples/s]
Generating train split: 53030417 examples [50:20, 35108.50 examples/s]
Generating train split: 53037359 examples [50:20, 41715.96 examples/s]
Generating train split: 53044331 examples [50:21, 47755.16 examples/s]
Generating train split: 53050310 examples [50:21, 36529.60 examples/s]
Generating train split: 53055172 examples [50:21, 29429.64 examples/s]
Generating train split: 53059131 examples [50:21, 27103.23 examples/s]
Generating train split: 53062549 examples [50:21, 24984.33 examples/s]
Generating train split: 53065573 examples [50:22, 25912.68 examples/s]
Generating train split: 53068552 examples [50:22, 18304.64 examples/s]
Generating train split: 53070920 examples [50:22, 18677.84 examples/s]
Generating train split: 53073627 examples [50:22, 20264.85 examples/s]
Generating train split: 53076736 examples [50:22, 22565.48 examples/s]
Generating train split: 53079345 examples [50:22, 17115.77 examples/s]
Generating train split: 53082515 examples [50:23, 19946.28 examples/s]
Generating train split: 53084963 examples [50:23, 19932.48 examples/s]
Generating train split: 53088662 examples [50:23, 23834.72 examples/s]
Generating train split: 53094050 examples [50:23, 31238.03 examples/s]
Generating train split: 53100448 examples [50:23, 39761.12 examples/s]
Generating train split: 53104845 examples [50:23, 25189.00 examples/s]
Generating train split: 53108315 examples [50:23, 25898.82 examples/s]
Generating train split: 53111592 examples [50:24, 26836.29 examples/s]
Generating train split: 53114790 examples [50:24, 27236.11 examples/s]
Generating train split: 53119040 examples [50:24, 30882.57 examples/s]
Generating train split: 53126777 examples [50:24, 42714.08 examples/s]
Generating train split: 53133735 examples [50:24, 49652.91 examples/s]
Generating train split: 53139108 examples [50:24, 27112.43 examples/s]
Generating train split: 53146151 examples [50:24, 34624.21 examples/s]
Generating train split: 53153989 examples [50:25, 43308.97 examples/s]
Generating train split: 53159851 examples [50:25, 38476.05 examples/s]
Generating train split: 53164848 examples [50:25, 26341.00 examples/s]
Generating train split: 53168754 examples [50:25, 26415.55 examples/s]
Generating train split: 53172289 examples [50:25, 27600.84 examples/s]
Generating train split: 53175749 examples [50:26, 19773.03 examples/s]
Generating train split: 53178482 examples [50:26, 20461.93 examples/s]
Generating train split: 53182533 examples [50:26, 24146.24 examples/s]
Generating train split: 53185580 examples [50:26, 23290.59 examples/s]
Generating train split: 53188353 examples [50:26, 15932.99 examples/s]
Generating train split: 53191507 examples [50:27, 18534.20 examples/s]
Generating train split: 53194501 examples [50:27, 20627.40 examples/s]
Generating train split: 53197107 examples [50:27, 20750.15 examples/s]
Generating train split: 53202387 examples [50:27, 27989.84 examples/s]
Generating train split: 53207260 examples [50:27, 32996.25 examples/s]
Generating train split: 53211029 examples [50:27, 22657.88 examples/s]
Generating train split: 53214043 examples [50:27, 23887.92 examples/s]
Generating train split: 53217461 examples [50:27, 26122.43 examples/s]
Generating train split: 53222058 examples [50:28, 30823.00 examples/s]
Generating train split: 53226230 examples [50:28, 33571.99 examples/s]
Generating train split: 53229982 examples [50:28, 23079.83 examples/s]
Generating train split: 53232992 examples [50:28, 23542.11 examples/s]
Generating train split: 53237197 examples [50:28, 27552.40 examples/s]
Generating train split: 53240464 examples [50:28, 27126.56 examples/s]
Generating train split: 53244099 examples [50:28, 29333.33 examples/s]
Generating train split: 53247334 examples [50:29, 20040.39 examples/s]
Generating train split: 53250018 examples [50:29, 21352.27 examples/s]
Generating train split: 53252635 examples [50:29, 21665.73 examples/s]
Generating train split: 53255146 examples [50:29, 22377.47 examples/s]
Generating train split: 53261009 examples [50:29, 31345.59 examples/s]
Generating train split: 53266989 examples [50:29, 38781.87 examples/s]
Generating train split: 53274142 examples [50:29, 47369.10 examples/s]
Generating train split: 53279213 examples [50:30, 27297.13 examples/s]
Generating train split: 53283171 examples [50:30, 29523.17 examples/s]
Generating train split: 53287122 examples [50:30, 20385.88 examples/s]
Generating train split: 53290220 examples [50:30, 19979.54 examples/s]
Generating train split: 53293902 examples [50:30, 22872.42 examples/s]
Generating train split: 53296913 examples [50:31, 21096.80 examples/s]
Generating train split: 53299540 examples [50:31, 21918.54 examples/s]
Generating train split: 53304008 examples [50:31, 26777.97 examples/s]
Generating train split: 53307141 examples [50:31, 24951.57 examples/s]
Generating train split: 53310930 examples [50:31, 27937.23 examples/s]
Generating train split: 53314040 examples [50:31, 28034.30 examples/s]
Generating train split: 53317065 examples [50:31, 25679.78 examples/s]
Generating train split: 53322000 examples [50:31, 31556.38 examples/s]
Generating train split: 53331606 examples [50:32, 48451.00 examples/s]
Generating train split: 53337331 examples [50:32, 49418.07 examples/s]
Generating train split: 53342576 examples [50:32, 36769.78 examples/s]
Generating train split: 53346924 examples [50:32, 35919.21 examples/s]
Generating train split: 53353356 examples [50:32, 42449.20 examples/s]
Generating train split: 53358119 examples [50:32, 36634.71 examples/s]
Generating train split: 53362266 examples [50:32, 37516.42 examples/s]
Generating train split: 53366386 examples [50:32, 36930.61 examples/s]
Generating train split: 53370328 examples [50:33, 36716.56 examples/s]
Generating train split: 53374395 examples [50:33, 37732.98 examples/s]
Generating train split: 53378627 examples [50:33, 38971.08 examples/s]
Generating train split: 53382633 examples [50:33, 39234.12 examples/s]
Generating train split: 53386633 examples [50:33, 28497.40 examples/s]
Generating train split: 53389957 examples [50:33, 25857.91 examples/s]
Generating train split: 53394672 examples [50:33, 30534.81 examples/s]
Generating train split: 53398453 examples [50:33, 32241.68 examples/s]
Generating train split: 53402009 examples [50:34, 31795.95 examples/s]
Generating train split: 53405423 examples [50:34, 21027.40 examples/s]
Generating train split: 53408713 examples [50:34, 23317.33 examples/s]
Generating train split: 53413649 examples [50:34, 28953.42 examples/s]
Generating train split: 53417687 examples [50:34, 31641.22 examples/s]
Generating train split: 53421350 examples [50:35, 18364.02 examples/s]
Generating train split: 53424744 examples [50:35, 20968.61 examples/s]
Generating train split: 53428402 examples [50:35, 23712.27 examples/s]
Generating train split: 53431538 examples [50:35, 15562.55 examples/s]
Generating train split: 53433980 examples [50:35, 14311.37 examples/s]
Generating train split: 53436025 examples [50:36, 12707.02 examples/s]
Generating train split: 53439449 examples [50:36, 16145.51 examples/s]
Generating train split: 53441669 examples [50:36, 16835.99 examples/s]
Generating train split: 53445045 examples [50:36, 20312.94 examples/s]
Generating train split: 53449509 examples [50:36, 25830.38 examples/s]
Generating train split: 53454164 examples [50:36, 30011.95 examples/s]
Generating train split: 53457884 examples [50:36, 31830.09 examples/s]
Generating train split: 53462610 examples [50:36, 35648.60 examples/s]
Generating train split: 53466727 examples [50:37, 37151.38 examples/s]
Generating train split: 53472458 examples [50:37, 42811.35 examples/s]
Generating train split: 53481197 examples [50:37, 55562.20 examples/s]
Generating train split: 53488736 examples [50:37, 61301.43 examples/s]
Generating train split: 53495019 examples [50:37, 35925.54 examples/s]
Generating train split: 53499971 examples [50:37, 30216.02 examples/s]
Generating train split: 53504048 examples [50:38, 31740.01 examples/s]
Generating train split: 53508057 examples [50:38, 26151.09 examples/s]
Generating train split: 53511370 examples [50:38, 22876.21 examples/s]
Generating train split: 53514169 examples [50:38, 22744.20 examples/s]
Generating train split: 53518312 examples [50:38, 26429.95 examples/s]
Generating train split: 53522951 examples [50:38, 30355.22 examples/s]
Generating train split: 53526423 examples [50:38, 31375.41 examples/s]
Generating train split: 53531025 examples [50:38, 35055.14 examples/s]
Generating train split: 53537454 examples [50:39, 42789.14 examples/s]
Generating train split: 53543727 examples [50:39, 48243.95 examples/s]
Generating train split: 53548824 examples [50:39, 47495.17 examples/s]
Generating train split: 53554263 examples [50:39, 49424.64 examples/s]
Generating train split: 53559351 examples [50:39, 32144.94 examples/s]
Generating train split: 53564417 examples [50:39, 35997.77 examples/s]
Generating train split: 53568793 examples [50:39, 37615.87 examples/s]
Generating train split: 53573158 examples [50:40, 32952.85 examples/s]
Generating train split: 53578886 examples [50:40, 38470.20 examples/s]
Generating train split: 53583990 examples [50:40, 40136.28 examples/s]
Generating train split: 53588671 examples [50:40, 41750.10 examples/s]
Generating train split: 53593976 examples [50:40, 44739.89 examples/s]
Generating train split: 53598702 examples [50:40, 23612.45 examples/s]
Generating train split: 53602330 examples [50:41, 25405.14 examples/s]
Generating train split: 53605887 examples [50:41, 24757.45 examples/s]
Generating train split: 53609678 examples [50:41, 27375.54 examples/s]
Generating train split: 53615116 examples [50:41, 33347.47 examples/s]
Generating train split: 53620033 examples [50:41, 35791.22 examples/s]
Generating train split: 53624106 examples [50:41, 26742.56 examples/s]
Generating train split: 53629196 examples [50:41, 31670.18 examples/s]
Generating train split: 53633051 examples [50:41, 32906.76 examples/s]
Generating train split: 53636863 examples [50:42, 29614.71 examples/s]
Generating train split: 53640236 examples [50:42, 28248.69 examples/s]
Generating train split: 53644489 examples [50:42, 31565.83 examples/s]
Generating train split: 53647945 examples [50:42, 20754.46 examples/s]
Generating train split: 53651682 examples [50:42, 23833.61 examples/s]
Generating train split: 53654724 examples [50:42, 23249.21 examples/s]
Generating train split: 53659141 examples [50:43, 27751.41 examples/s]
Generating train split: 53662409 examples [50:43, 26832.68 examples/s]
Generating train split: 53665428 examples [50:43, 25256.29 examples/s]
Generating train split: 53670070 examples [50:43, 30270.30 examples/s]
Generating train split: 53674003 examples [50:43, 32561.51 examples/s]
Generating train split: 53678679 examples [50:43, 36277.17 examples/s]
Generating train split: 53682722 examples [50:43, 37414.45 examples/s]
Generating train split: 53689371 examples [50:43, 45594.77 examples/s]
Generating train split: 53697840 examples [50:43, 56805.18 examples/s]
Generating train split: 53703689 examples [50:44, 32060.68 examples/s]
Generating train split: 53708256 examples [50:44, 31729.83 examples/s]
Generating train split: 53712380 examples [50:44, 31977.49 examples/s]
Generating train split: 53716257 examples [50:44, 33011.77 examples/s]
Generating train split: 53720609 examples [50:44, 35417.17 examples/s]
Generating train split: 53724590 examples [50:44, 33169.78 examples/s]
Generating train split: 53729981 examples [50:44, 38209.52 examples/s]
Generating train split: 53734527 examples [50:45, 40068.03 examples/s]
Generating train split: 53739937 examples [50:45, 43843.14 examples/s]
Generating train split: 53745247 examples [50:45, 45439.56 examples/s]
Generating train split: 53749958 examples [50:45, 24751.05 examples/s]
Generating train split: 53754080 examples [50:45, 27668.49 examples/s]
Generating train split: 53758906 examples [50:45, 31793.88 examples/s]
Generating train split: 53765497 examples [50:45, 39421.01 examples/s]
Generating train split: 53773662 examples [50:46, 49634.66 examples/s]
Generating train split: 53779501 examples [50:46, 30544.13 examples/s]
Generating train split: 53784064 examples [50:46, 31496.43 examples/s]
Generating train split: 53788302 examples [50:46, 25853.37 examples/s]
Generating train split: 53791807 examples [50:46, 27458.84 examples/s]
Generating train split: 53795288 examples [50:47, 25378.24 examples/s]
Generating train split: 53798344 examples [50:47, 25230.40 examples/s]
Generating train split: 53801223 examples [50:47, 18344.16 examples/s]
Generating train split: 53805363 examples [50:47, 22443.31 examples/s]
Generating train split: 53810900 examples [50:47, 29113.69 examples/s]
Generating train split: 53814560 examples [50:48, 21111.61 examples/s]
Generating train split: 53817483 examples [50:48, 21914.48 examples/s]
Generating train split: 53821119 examples [50:48, 24802.23 examples/s]
Generating train split: 53824170 examples [50:48, 25715.12 examples/s]
Generating train split: 53831206 examples [50:48, 36361.25 examples/s]
Generating train split: 53838710 examples [50:48, 46175.52 examples/s]
Generating train split: 53843905 examples [50:48, 40789.55 examples/s]
Generating train split: 53848500 examples [50:49, 26449.69 examples/s]
Generating train split: 53855796 examples [50:49, 34848.52 examples/s]
Generating train split: 53862996 examples [50:49, 42468.23 examples/s]
Generating train split: 53868465 examples [50:49, 45149.71 examples/s]
Generating train split: 53874307 examples [50:49, 48384.73 examples/s]
Generating train split: 53881752 examples [50:49, 55107.08 examples/s]
Generating train split: 53887882 examples [50:50, 25858.39 examples/s]
Generating train split: 53892514 examples [50:50, 26865.24 examples/s]
Generating train split: 53896678 examples [50:50, 26091.42 examples/s]
Generating train split: 53900307 examples [50:50, 18703.85 examples/s]
Generating train split: 53903623 examples [50:50, 20765.55 examples/s]
Generating train split: 53906605 examples [50:51, 15430.05 examples/s]
Generating train split: 53908939 examples [50:51, 15298.41 examples/s]
Generating train split: 53912106 examples [50:51, 17899.66 examples/s]
Generating train split: 53914508 examples [50:51, 12711.34 examples/s]
Generating train split: 53916384 examples [50:52, 13160.56 examples/s]
Generating train split: 53919367 examples [50:52, 16006.70 examples/s]
Generating train split: 53921506 examples [50:52, 16533.50 examples/s]
Generating train split: 53923555 examples [50:52, 10690.99 examples/s]
Generating train split: 53926315 examples [50:52, 13354.42 examples/s]
Generating train split: 53929848 examples [50:52, 17353.16 examples/s]
Generating train split: 53932252 examples [50:53, 13133.27 examples/s]
Generating train split: 53937861 examples [50:53, 20532.29 examples/s]
Generating train split: 53944096 examples [50:53, 28766.04 examples/s]
Generating train split: 53948085 examples [50:53, 26795.22 examples/s]
Generating train split: 53951563 examples [50:53, 27654.77 examples/s]
Generating train split: 53954910 examples [50:53, 19939.44 examples/s]
Generating train split: 53957585 examples [50:54, 19404.94 examples/s]
Generating train split: 53959996 examples [50:54, 17816.84 examples/s]
Generating train split: 53962101 examples [50:54, 16815.54 examples/s]
Generating train split: 53963997 examples [50:54, 13866.38 examples/s]
Generating train split: 53965589 examples [50:54, 13228.17 examples/s]
Generating train split: 53968839 examples [50:54, 17081.63 examples/s]
Generating train split: 53974807 examples [50:54, 26540.71 examples/s]
Generating train split: 53981608 examples [50:55, 36141.08 examples/s]
Generating train split: 53985795 examples [50:55, 21913.54 examples/s]
Generating train split: 53989054 examples [50:55, 22038.64 examples/s]
Generating train split: 53992011 examples [50:55, 19976.46 examples/s]
Generating train split: 53994545 examples [50:56, 17226.07 examples/s]
Generating train split: 53996671 examples [50:56, 15477.68 examples/s]
Generating train split: 53998601 examples [50:56, 16166.82 examples/s]
Generating train split: 54000468 examples [50:56, 14397.67 examples/s]
Generating train split: 54002092 examples [50:56, 14126.60 examples/s]
Generating train split: 54008049 examples [50:56, 23949.77 examples/s]
Generating train split: 54015272 examples [50:56, 35340.15 examples/s]
Generating train split: 54019439 examples [50:57, 29471.32 examples/s]
Generating train split: 54022982 examples [50:57, 25145.32 examples/s]
Generating train split: 54026002 examples [50:57, 17211.42 examples/s]
Generating train split: 54028516 examples [50:57, 18495.91 examples/s]
Generating train split: 54030926 examples [50:57, 16915.84 examples/s]
Generating train split: 54033011 examples [50:58, 14450.85 examples/s]
Generating train split: 54034763 examples [50:58, 13935.94 examples/s]
Generating train split: 54036477 examples [50:58, 14532.85 examples/s]
Generating train split: 54038525 examples [50:58, 15424.36 examples/s]
Generating train split: 54040331 examples [50:58, 16031.68 examples/s]
Generating train split: 54042060 examples [50:58, 12920.05 examples/s]
Generating train split: 54043541 examples [50:58, 13306.85 examples/s]
Generating train split: 54045003 examples [50:58, 12739.15 examples/s]
Generating train split: 54046443 examples [50:59, 13012.71 examples/s]
Generating train split: 54047819 examples [50:59, 9689.24 examples/s] 
Generating train split: 54048948 examples [50:59, 9175.73 examples/s]
Generating train split: 54049978 examples [50:59, 8953.03 examples/s]
Generating train split: 54051801 examples [50:59, 11055.59 examples/s]
Generating train split: 54053110 examples [50:59, 11356.75 examples/s]
Generating train split: 54054338 examples [50:59, 10034.81 examples/s]
Generating train split: 54055424 examples [51:00, 8693.99 examples/s] 
Generating train split: 54057728 examples [51:00, 11894.07 examples/s]
Generating train split: 54059223 examples [51:00, 12434.61 examples/s]
Generating train split: 54060591 examples [51:00, 10100.41 examples/s]
Generating train split: 54062104 examples [51:00, 11221.13 examples/s]
Generating train split: 54063659 examples [51:00, 12231.03 examples/s]
Generating train split: 54065665 examples [51:00, 14139.53 examples/s]
Generating train split: 54067314 examples [51:00, 14759.43 examples/s]
Generating train split: 54068888 examples [51:01, 13706.89 examples/s]
Generating train split: 54070342 examples [51:01, 11503.95 examples/s]
Generating train split: 54072048 examples [51:01, 12701.63 examples/s]
Generating train split: 54073429 examples [51:01, 10593.67 examples/s]
Generating train split: 54075653 examples [51:01, 13230.68 examples/s]
Generating train split: 54077151 examples [51:01, 11570.58 examples/s]
Generating train split: 54078652 examples [51:01, 12349.85 examples/s]
Generating train split: 54080161 examples [51:02, 12925.36 examples/s]
Generating train split: 54081564 examples [51:02, 11724.77 examples/s]
Generating train split: 54082827 examples [51:02, 8703.30 examples/s] 
Generating train split: 54083860 examples [51:02, 8153.82 examples/s]
Generating train split: 54085665 examples [51:02, 10023.78 examples/s]
Generating train split: 54086808 examples [51:02, 9330.59 examples/s] 
Generating train split: 54087850 examples [51:03, 7649.18 examples/s]
Generating train split: 54090352 examples [51:03, 11204.23 examples/s]
Generating train split: 54095847 examples [51:03, 21083.35 examples/s]
Generating train split: 54098447 examples [51:03, 21916.76 examples/s]
Generating train split: 54102273 examples [51:03, 26082.49 examples/s]
Generating train split: 54105399 examples [51:03, 27102.25 examples/s]
Generating train split: 54108350 examples [51:03, 21054.39 examples/s]
Generating train split: 54110825 examples [51:04, 16438.68 examples/s]
Generating train split: 54115377 examples [51:04, 22163.09 examples/s]
Generating train split: 54119494 examples [51:04, 26334.18 examples/s]
Generating train split: 54122683 examples [51:04, 22290.59 examples/s]
Generating train split: 54125395 examples [51:04, 19342.18 examples/s]
Generating train split: 54127963 examples [51:04, 20622.84 examples/s]
Generating train split: 54131641 examples [51:04, 24252.87 examples/s]
Generating train split: 54134505 examples [51:04, 25287.71 examples/s]
Generating train split: 54137308 examples [51:05, 19113.10 examples/s]
Generating train split: 54139626 examples [51:05, 19144.28 examples/s]
Generating train split: 54142941 examples [51:05, 22296.86 examples/s]
Generating train split: 54146854 examples [51:05, 26396.84 examples/s]
Generating train split: 54149804 examples [51:05, 25757.18 examples/s]
Generating train split: 54152594 examples [51:05, 17688.15 examples/s]
Generating train split: 54154848 examples [51:05, 17870.03 examples/s]
Generating train split: 54158465 examples [51:06, 21787.56 examples/s]
Generating train split: 54161046 examples [51:06, 20791.01 examples/s]
Generating train split: 54163401 examples [51:06, 17374.76 examples/s]
Generating train split: 54166950 examples [51:06, 21234.90 examples/s]
Generating train split: 54169417 examples [51:06, 21092.64 examples/s]
Generating train split: 54172182 examples [51:06, 22662.46 examples/s]
Generating train split: 54174653 examples [51:06, 23089.74 examples/s]
Generating train split: 54182433 examples [51:06, 37726.05 examples/s]
Generating train split: 54188148 examples [51:07, 43087.03 examples/s]
Generating train split: 54192704 examples [51:07, 28956.13 examples/s]
Generating train split: 54196387 examples [51:07, 27574.64 examples/s]
Generating train split: 54200131 examples [51:07, 29651.43 examples/s]
Generating train split: 54203568 examples [51:07, 28828.57 examples/s]
Generating train split: 54206772 examples [51:07, 23444.90 examples/s]
Generating train split: 54213815 examples [51:08, 33419.93 examples/s]
Generating train split: 54220274 examples [51:08, 40660.57 examples/s]
Generating train split: 54225009 examples [51:08, 30170.10 examples/s]
Generating train split: 54231568 examples [51:08, 37342.47 examples/s]
Generating train split: 54239126 examples [51:08, 45918.87 examples/s]
Generating train split: 54244670 examples [51:08, 31266.73 examples/s]
Generating train split: 54249061 examples [51:09, 28205.02 examples/s]
Generating train split: 54252783 examples [51:09, 27187.92 examples/s]
Generating train split: 54259765 examples [51:09, 35291.55 examples/s]
Generating train split: 54266008 examples [51:09, 41090.16 examples/s]
Generating train split: 54270977 examples [51:09, 33464.68 examples/s]
Generating train split: 54275129 examples [51:09, 32719.76 examples/s]
Generating train split: 54282657 examples [51:09, 41861.79 examples/s]
Generating train split: 54287605 examples [51:10, 43616.80 examples/s]
Generating train split: 54292535 examples [51:10, 34710.78 examples/s]
Generating train split: 54296666 examples [51:10, 31505.63 examples/s]
Generating train split: 54300302 examples [51:10, 24663.06 examples/s]
Generating train split: 54303280 examples [51:10, 25065.91 examples/s]
Generating train split: 54306168 examples [51:10, 21973.90 examples/s]
Generating train split: 54308654 examples [51:11, 19518.09 examples/s]
Generating train split: 54314213 examples [51:11, 26697.55 examples/s]
Generating train split: 54321834 examples [51:11, 37572.81 examples/s]
Generating train split: 54326326 examples [51:11, 29137.65 examples/s]
Generating train split: 54330966 examples [51:11, 32628.14 examples/s]
Generating train split: 54338288 examples [51:11, 41726.04 examples/s]
Generating train split: 54343758 examples [51:11, 44848.10 examples/s]
Generating train split: 54348881 examples [51:12, 23274.44 examples/s]
Generating train split: 54352782 examples [51:12, 21693.43 examples/s]
Generating train split: 54360504 examples [51:12, 30448.06 examples/s]
Generating train split: 54365108 examples [51:12, 31394.70 examples/s]
Generating train split: 54369370 examples [51:13, 23796.10 examples/s]
Generating train split: 54372767 examples [51:13, 19661.95 examples/s]
Generating train split: 54375517 examples [51:13, 17401.65 examples/s]
Generating train split: 54377799 examples [51:13, 13854.55 examples/s]
Generating train split: 54380043 examples [51:14, 15045.56 examples/s]
Generating train split: 54383098 examples [51:14, 17695.54 examples/s]
Generating train split: 54387921 examples [51:14, 23688.28 examples/s]
Generating train split: 54394967 examples [51:14, 33923.05 examples/s]
Generating train split: 54399742 examples [51:14, 37204.62 examples/s]
Generating train split: 54404145 examples [51:14, 21514.16 examples/s]
Generating train split: 54411806 examples [51:14, 30705.88 examples/s]
Generating train split: 54418585 examples [51:15, 37844.59 examples/s]
Generating train split: 54423893 examples [51:15, 23291.49 examples/s]
Generating train split: 54427961 examples [51:15, 22149.87 examples/s]
Generating train split: 54431378 examples [51:15, 22967.96 examples/s]
Generating train split: 54438769 examples [51:15, 31813.60 examples/s]
Generating train split: 54446409 examples [51:16, 39642.16 examples/s]
Generating train split: 54451557 examples [51:16, 22281.60 examples/s]
Generating train split: 54455457 examples [51:16, 20017.85 examples/s]
Generating train split: 54458634 examples [51:17, 17942.55 examples/s]
Generating train split: 54461241 examples [51:17, 15881.00 examples/s]
Generating train split: 54463388 examples [51:17, 11731.35 examples/s]
Generating train split: 54465058 examples [51:17, 11491.08 examples/s]
Generating train split: 54472679 examples [51:17, 20817.00 examples/s]
Generating train split: 54478452 examples [51:18, 26940.41 examples/s]
Generating train split: 54482499 examples [51:18, 29573.69 examples/s]
Generating train split: 54486519 examples [51:18, 31781.10 examples/s]
Generating train split: 54494864 examples [51:18, 44001.43 examples/s]
Generating train split: 54500172 examples [51:18, 27550.24 examples/s]
Generating train split: 54504320 examples [51:18, 29100.09 examples/s]
Generating train split: 54508283 examples [51:18, 30600.40 examples/s]
Generating train split: 54514053 examples [51:19, 36452.24 examples/s]
Generating train split: 54521080 examples [51:19, 44424.69 examples/s]
Generating train split: 54526380 examples [51:19, 46153.32 examples/s]
Generating train split: 54531563 examples [51:19, 24598.22 examples/s]
Generating train split: 54535535 examples [51:19, 26207.13 examples/s]
Generating train split: 54539313 examples [51:20, 18567.08 examples/s]
Generating train split: 54542248 examples [51:20, 18275.10 examples/s]
Generating train split: 54544819 examples [51:20, 18261.98 examples/s]
Generating train split: 54547168 examples [51:20, 15389.41 examples/s]
Generating train split: 54549107 examples [51:20, 16021.18 examples/s]
Generating train split: 54551598 examples [51:21, 17702.58 examples/s]
Generating train split: 54553792 examples [51:21, 18606.96 examples/s]
Generating train split: 54555917 examples [51:21, 19024.34 examples/s]
Generating train split: 54558017 examples [51:21, 18961.34 examples/s]
Generating train split: 54560050 examples [51:21, 18322.98 examples/s]
Generating train split: 54562343 examples [51:21, 19514.49 examples/s]
Generating train split: 54565752 examples [51:21, 23147.31 examples/s]
Generating train split: 54568259 examples [51:21, 23665.03 examples/s]
Generating train split: 54571212 examples [51:21, 25309.64 examples/s]
Generating train split: 54573800 examples [51:22, 17351.88 examples/s]
Generating train split: 54575915 examples [51:22, 18121.87 examples/s]
Generating train split: 54578016 examples [51:22, 18158.08 examples/s]
Generating train split: 54580035 examples [51:22, 17155.28 examples/s]
Generating train split: 54582995 examples [51:22, 20191.89 examples/s]
Generating train split: 54589755 examples [51:22, 32461.00 examples/s]
Generating train split: 54596548 examples [51:22, 42032.01 examples/s]
Generating train split: 54601084 examples [51:23, 29172.60 examples/s]
Generating train split: 54604768 examples [51:23, 27740.67 examples/s]
Generating train split: 54608074 examples [51:23, 26771.61 examples/s]
Generating train split: 54614725 examples [51:23, 35567.81 examples/s]
Generating train split: 54622651 examples [51:23, 46051.86 examples/s]
Generating train split: 54627917 examples [51:23, 41340.23 examples/s]
Generating train split: 54632589 examples [51:24, 26018.75 examples/s]
Generating train split: 54636243 examples [51:24, 21034.28 examples/s]
Generating train split: 54639179 examples [51:24, 13855.66 examples/s]
Generating train split: 54641917 examples [51:24, 15509.54 examples/s]
Generating train split: 54644303 examples [51:25, 12875.96 examples/s]
Generating train split: 54646212 examples [51:25, 11965.10 examples/s]
Generating train split: 54647825 examples [51:25, 10719.02 examples/s]
Generating train split: 54649182 examples [51:25, 9789.87 examples/s] 
Generating train split: 54650713 examples [51:25, 10676.81 examples/s]
Generating train split: 54651987 examples [51:26, 8968.15 examples/s] 
Generating train split: 54653391 examples [51:26, 9847.26 examples/s]
Generating train split: 54654960 examples [51:26, 11028.43 examples/s]
Generating train split: 54656777 examples [51:26, 12598.89 examples/s]
Generating train split: 54659276 examples [51:26, 15594.76 examples/s]
Generating train split: 54666847 examples [51:26, 31036.40 examples/s]
Generating train split: 54672484 examples [51:26, 37831.43 examples/s]
Generating train split: 54676625 examples [51:27, 29125.57 examples/s]
Generating train split: 54680090 examples [51:27, 19701.78 examples/s]
Generating train split: 54682828 examples [51:27, 15969.15 examples/s]
Generating train split: 54685041 examples [51:27, 16826.10 examples/s]
Generating train split: 54687225 examples [51:27, 15107.67 examples/s]
Generating train split: 54689088 examples [51:28, 12157.53 examples/s]
Generating train split: 54690612 examples [51:28, 12496.97 examples/s]
Generating train split: 54692098 examples [51:28, 12177.00 examples/s]
Generating train split: 54693611 examples [51:28, 12777.78 examples/s]
Generating train split: 54695027 examples [51:28, 11470.36 examples/s]
Generating train split: 54697308 examples [51:28, 13921.94 examples/s]
Generating train split: 54698858 examples [51:28, 13240.96 examples/s]
Generating train split: 54700292 examples [51:29, 13211.14 examples/s]
Generating train split: 54701707 examples [51:29, 13433.61 examples/s]
Generating train split: 54703111 examples [51:29, 11293.43 examples/s]
Generating train split: 54705291 examples [51:29, 13796.96 examples/s]
Generating train split: 54709427 examples [51:29, 20796.73 examples/s]
Generating train split: 54712604 examples [51:29, 23637.51 examples/s]
Generating train split: 54716137 examples [51:29, 26823.34 examples/s]
Generating train split: 54720626 examples [51:29, 31905.67 examples/s]
Generating train split: 54727096 examples [51:29, 40948.02 examples/s]
Generating train split: 54731315 examples [51:30, 26256.63 examples/s]
Generating train split: 54734690 examples [51:30, 26222.17 examples/s]
Generating train split: 54737840 examples [51:30, 25622.11 examples/s]
Generating train split: 54740766 examples [51:30, 24443.53 examples/s]
Generating train split: 54744645 examples [51:30, 27717.28 examples/s]
Generating train split: 54747695 examples [51:30, 25876.38 examples/s]
Generating train split: 54752608 examples [51:30, 31526.28 examples/s]
Generating train split: 54757504 examples [51:31, 36016.80 examples/s]
Generating train split: 54761372 examples [51:31, 35669.45 examples/s]
Generating train split: 54765128 examples [51:31, 34259.21 examples/s]
Generating train split: 54768710 examples [51:31, 34673.72 examples/s]
Generating train split: 54774812 examples [51:31, 41972.25 examples/s]
Generating train split: 54781507 examples [51:31, 48857.49 examples/s]
Generating train split: 54787896 examples [51:31, 53164.25 examples/s]
Generating train split: 54793321 examples [51:31, 35275.97 examples/s]
Generating train split: 54797711 examples [51:32, 30419.00 examples/s]
Generating train split: 54802745 examples [51:32, 34420.41 examples/s]
Generating train split: 54807838 examples [51:32, 38092.93 examples/s]
Generating train split: 54812245 examples [51:32, 34555.42 examples/s]
Generating train split: 54816163 examples [51:32, 33097.70 examples/s]
Generating train split: 54819787 examples [51:32, 30723.54 examples/s]
Generating train split: 54823085 examples [51:32, 30127.69 examples/s]
Generating train split: 54828078 examples [51:33, 34239.71 examples/s]
Generating train split: 54834032 examples [51:33, 40470.34 examples/s]
Generating train split: 54838492 examples [51:33, 41561.66 examples/s]
Generating train split: 54847007 examples [51:33, 53543.02 examples/s]
Generating train split: 54852598 examples [51:33, 51021.98 examples/s]
Generating train split: 54857886 examples [51:33, 34242.31 examples/s]
Generating train split: 54862147 examples [51:34, 26523.79 examples/s]
Generating train split: 54865596 examples [51:34, 20534.77 examples/s]
Generating train split: 54868356 examples [51:34, 21568.47 examples/s]
Generating train split: 54871774 examples [51:34, 23826.26 examples/s]
Generating train split: 54874704 examples [51:34, 22177.93 examples/s]
Generating train split: 54877534 examples [51:34, 23449.05 examples/s]
Generating train split: 54883356 examples [51:34, 31412.13 examples/s]
Generating train split: 54888694 examples [51:34, 36791.53 examples/s]
Generating train split: 54892824 examples [51:35, 22114.92 examples/s]
Generating train split: 54898788 examples [51:35, 28795.13 examples/s]
Generating train split: 54902827 examples [51:35, 29125.76 examples/s]
Generating train split: 54909184 examples [51:35, 36464.91 examples/s]
Generating train split: 54915705 examples [51:35, 43163.42 examples/s]
Generating train split: 54920825 examples [51:35, 40251.30 examples/s]
Generating train split: 54925442 examples [51:36, 40290.83 examples/s]
Generating train split: 54932829 examples [51:36, 48681.57 examples/s]
Generating train split: 54938154 examples [51:36, 32658.51 examples/s]
Generating train split: 54942417 examples [51:36, 33350.15 examples/s]
Generating train split: 54947327 examples [51:36, 36713.84 examples/s]
Generating train split: 54951637 examples [51:36, 34654.83 examples/s]
Generating train split: 54960086 examples [51:36, 46234.66 examples/s]
Generating train split: 54965397 examples [51:37, 47927.17 examples/s]
Generating train split: 54970688 examples [51:37, 35305.10 examples/s]
Generating train split: 54975024 examples [51:37, 24902.35 examples/s]
Generating train split: 54978456 examples [51:37, 22320.24 examples/s]
Generating train split: 54982382 examples [51:37, 25047.78 examples/s]
Generating train split: 54985544 examples [51:38, 23766.67 examples/s]
Generating train split: 54988370 examples [51:38, 23021.78 examples/s]
Generating train split: 54991416 examples [51:38, 24582.55 examples/s]
Generating train split: 54997491 examples [51:38, 32936.06 examples/s]
Generating train split: 55002391 examples [51:38, 36918.00 examples/s]
Generating train split: 55007539 examples [51:38, 40729.35 examples/s]
Generating train split: 55011947 examples [51:38, 35369.90 examples/s]
Generating train split: 55015832 examples [51:38, 35843.29 examples/s]
Generating train split: 55019960 examples [51:38, 37158.38 examples/s]
Generating train split: 55025006 examples [51:39, 40741.79 examples/s]
Generating train split: 55029262 examples [51:39, 32787.55 examples/s]
Generating train split: 55033195 examples [51:39, 34347.20 examples/s]
Generating train split: 55036926 examples [51:39, 31909.04 examples/s]
Generating train split: 55040340 examples [51:39, 28751.67 examples/s]
Generating train split: 55046306 examples [51:39, 36154.69 examples/s]
Generating train split: 55051466 examples [51:39, 40088.97 examples/s]
Generating train split: 55056421 examples [51:39, 42063.28 examples/s]
Generating train split: 55060857 examples [51:40, 25207.46 examples/s]
Generating train split: 55064339 examples [51:40, 25865.28 examples/s]
Generating train split: 55069127 examples [51:40, 30355.21 examples/s]
Generating train split: 55074707 examples [51:40, 35302.52 examples/s]
Generating train split: 55080246 examples [51:40, 40114.86 examples/s]
Generating train split: 55086165 examples [51:40, 44973.70 examples/s]
Generating train split: 55093434 examples [51:40, 52359.89 examples/s]
Generating train split: 55099093 examples [51:41, 41521.75 examples/s]
Generating train split: 55103885 examples [51:41, 34926.61 examples/s]
Generating train split: 55107961 examples [51:41, 30800.04 examples/s]
Generating train split: 55111490 examples [51:41, 27565.31 examples/s]
Generating train split: 55114575 examples [51:41, 26965.41 examples/s]
Generating train split: 55117483 examples [51:41, 25185.58 examples/s]
Generating train split: 55120455 examples [51:42, 26053.69 examples/s]
Generating train split: 55123189 examples [51:42, 18211.65 examples/s]
Generating train split: 55125397 examples [51:42, 13581.67 examples/s]
Generating train split: 55127152 examples [51:42, 12779.36 examples/s]
Generating train split: 55128698 examples [51:43, 11301.96 examples/s]
Generating train split: 55130016 examples [51:43, 11490.85 examples/s]
Generating train split: 55132117 examples [51:43, 13304.23 examples/s]
Generating train split: 55133635 examples [51:43, 12438.15 examples/s]
Generating train split: 55135323 examples [51:43, 13409.59 examples/s]
Generating train split: 55138586 examples [51:43, 18017.66 examples/s]
Generating train split: 55144027 examples [51:43, 27300.54 examples/s]
Generating train split: 55149098 examples [51:43, 32778.43 examples/s]
Generating train split: 55152623 examples [51:44, 23650.26 examples/s]
Generating train split: 55155896 examples [51:44, 25595.63 examples/s]
Generating train split: 55158896 examples [51:44, 24242.54 examples/s]
Generating train split: 55161632 examples [51:44, 19407.66 examples/s]
Generating train split: 55164352 examples [51:44, 19922.94 examples/s]
Generating train split: 55166595 examples [51:44, 19282.26 examples/s]
Generating train split: 55169231 examples [51:44, 20874.01 examples/s]
Generating train split: 55171571 examples [51:44, 21490.01 examples/s]
Generating train split: 55173851 examples [51:45, 13162.87 examples/s]
Generating train split: 55177656 examples [51:45, 17703.99 examples/s]
Generating train split: 55183333 examples [51:45, 25781.18 examples/s]
Generating train split: 55186718 examples [51:45, 20227.69 examples/s]
Generating train split: 55189474 examples [51:45, 20726.90 examples/s]
Generating train split: 55196070 examples [51:46, 30159.77 examples/s]
Generating train split: 55202824 examples [51:46, 38732.05 examples/s]
Generating train split: 55207522 examples [51:46, 36995.28 examples/s]
Generating train split: 55211807 examples [51:46, 20413.09 examples/s]
Generating train split: 55215080 examples [51:46, 21123.29 examples/s]
Generating train split: 55218091 examples [51:47, 16653.24 examples/s]
Generating train split: 55220506 examples [51:47, 15602.04 examples/s]
Generating train split: 55222570 examples [51:47, 14860.78 examples/s]
Generating train split: 55224389 examples [51:47, 12720.31 examples/s]
Generating train split: 55230395 examples [51:47, 20724.17 examples/s]
Generating train split: 55235738 examples [51:47, 27073.40 examples/s]
Generating train split: 55239340 examples [51:48, 27055.31 examples/s]
Generating train split: 55242681 examples [51:48, 17412.50 examples/s]
Generating train split: 55245282 examples [51:48, 17777.89 examples/s]
Generating train split: 55250228 examples [51:48, 23511.61 examples/s]
Generating train split: 55258581 examples [51:48, 35838.83 examples/s]
Generating train split: 55263328 examples [51:48, 37266.95 examples/s]
Generating train split: 55267872 examples [51:49, 29080.84 examples/s]
Generating train split: 55276863 examples [51:49, 41362.84 examples/s]
Generating train split: 55283325 examples [51:49, 46566.65 examples/s]
Generating train split: 55288983 examples [51:49, 30202.54 examples/s]
Generating train split: 55296189 examples [51:49, 37556.33 examples/s]
Generating train split: 55306716 examples [51:49, 50218.87 examples/s]
Generating train split: 55313291 examples [51:50, 24870.80 examples/s]
Generating train split: 55318212 examples [51:51, 18773.51 examples/s]
Generating train split: 55325143 examples [51:51, 24261.61 examples/s]
Generating train split: 55331337 examples [51:51, 29321.88 examples/s]
Generating train split: 55336489 examples [51:51, 29260.11 examples/s]
Generating train split: 55340968 examples [51:51, 25773.31 examples/s]
Generating train split: 55347202 examples [51:51, 31765.27 examples/s]
Generating train split: 55351657 examples [51:52, 25266.56 examples/s]
Generating train split: 55355252 examples [51:52, 25225.65 examples/s]
Generating train split: 55358527 examples [51:52, 22560.88 examples/s]
Generating train split: 55361314 examples [51:52, 18191.12 examples/s]
Generating train split: 55363962 examples [51:52, 19566.94 examples/s]
Generating train split: 55367258 examples [51:52, 22123.61 examples/s]
Generating train split: 55370039 examples [51:52, 23339.57 examples/s]
Generating train split: 55372733 examples [51:53, 19268.72 examples/s]
Generating train split: 55375011 examples [51:53, 18235.24 examples/s]
Generating train split: 55377070 examples [51:53, 17180.22 examples/s]
Generating train split: 55379647 examples [51:53, 19070.19 examples/s]
Generating train split: 55381746 examples [51:53, 12073.26 examples/s]
Generating train split: 55384060 examples [51:53, 13947.90 examples/s]
Generating train split: 55386199 examples [51:54, 15425.65 examples/s]
Generating train split: 55388121 examples [51:54, 12084.01 examples/s]
Generating train split: 55389692 examples [51:54, 10648.98 examples/s]
Generating train split: 55391327 examples [51:54, 11697.75 examples/s]
Generating train split: 55393440 examples [51:54, 11284.87 examples/s]
Generating train split: 55394756 examples [51:55, 10022.59 examples/s]
Generating train split: 55395937 examples [51:55, 10367.52 examples/s]
Generating train split: 55398205 examples [51:55, 12981.73 examples/s]
Generating train split: 55400037 examples [51:55, 14141.16 examples/s]
Generating train split: 55401602 examples [51:55, 13609.34 examples/s]
Generating train split: 55404263 examples [51:55, 16873.13 examples/s]
Generating train split: 55406653 examples [51:55, 15318.46 examples/s]
Generating train split: 55408412 examples [51:55, 15853.33 examples/s]
Generating train split: 55410106 examples [51:56, 12368.08 examples/s]
Generating train split: 55411530 examples [51:56, 11900.02 examples/s]
Generating train split: 55412842 examples [51:56, 11341.21 examples/s]
Generating train split: 55414057 examples [51:56, 10102.66 examples/s]
Generating train split: 55415141 examples [51:56, 8585.65 examples/s] 
Generating train split: 55416161 examples [51:56, 8916.95 examples/s]
Generating train split: 55417507 examples [51:56, 9950.75 examples/s]
Generating train split: 55418583 examples [51:57, 7331.95 examples/s]
Generating train split: 55419463 examples [51:57, 7342.69 examples/s]
Generating train split: 55421094 examples [51:57, 9299.67 examples/s]
Generating train split: 55422168 examples [51:57, 8371.93 examples/s]
Generating train split: 55423120 examples [51:57, 8017.89 examples/s]
Generating train split: 55425331 examples [51:57, 11262.00 examples/s]
Generating train split: 55428155 examples [51:57, 15464.46 examples/s]
Generating train split: 55430603 examples [51:57, 17824.10 examples/s]
Generating train split: 55432558 examples [51:58, 12585.44 examples/s]
Generating train split: 55434547 examples [51:58, 14116.98 examples/s]
Generating train split: 55436259 examples [51:58, 14247.57 examples/s]
Generating train split: 55437898 examples [51:58, 10064.63 examples/s]
Generating train split: 55439212 examples [51:58, 9634.09 examples/s] 
Generating train split: 55440383 examples [51:59, 6518.85 examples/s]
Generating train split: 55441300 examples [51:59, 6190.53 examples/s]
Generating train split: 55443196 examples [51:59, 8289.18 examples/s]
Generating train split: 55445010 examples [51:59, 10123.21 examples/s]
Generating train split: 55446644 examples [51:59, 11418.99 examples/s]
Generating train split: 55448918 examples [51:59, 13865.64 examples/s]
Generating train split: 55451042 examples [51:59, 15682.11 examples/s]
Generating train split: 55452820 examples [52:00, 14581.14 examples/s]
Generating train split: 55454543 examples [52:00, 15002.98 examples/s]
Generating train split: 55456164 examples [52:00, 15232.30 examples/s]
Generating train split: 55457780 examples [52:00, 12393.03 examples/s]
Generating train split: 55459502 examples [52:00, 13511.94 examples/s]
Generating train split: 55461045 examples [52:00, 13934.14 examples/s]
Generating train split: 55463552 examples [52:00, 16856.84 examples/s]
Generating train split: 55465358 examples [52:00, 17127.89 examples/s]
Generating train split: 55468422 examples [52:01, 20909.48 examples/s]
Generating train split: 55473922 examples [52:01, 30646.94 examples/s]
Generating train split: 55477092 examples [52:01, 28622.19 examples/s]
Generating train split: 55480056 examples [52:01, 25081.97 examples/s]
Generating train split: 55483902 examples [52:01, 28497.60 examples/s]
Generating train split: 55488717 examples [52:01, 33645.55 examples/s]
Generating train split: 55492609 examples [52:01, 35082.97 examples/s]
Generating train split: 55497226 examples [52:01, 38210.91 examples/s]
Generating train split: 55502747 examples [52:01, 43090.37 examples/s]
Generating train split: 55508217 examples [52:01, 46469.72 examples/s]
Generating train split: 55513995 examples [52:02, 49783.20 examples/s]
Generating train split: 55519493 examples [52:02, 51309.05 examples/s]
Generating train split: 55525685 examples [52:02, 54355.94 examples/s]
Generating train split: 55532346 examples [52:02, 57992.92 examples/s]
Generating train split: 55538643 examples [52:02, 59463.97 examples/s]
Generating train split: 55544614 examples [52:02, 57312.80 examples/s]
Generating train split: 55550379 examples [52:02, 54614.12 examples/s]
Generating train split: 55555896 examples [52:02, 46189.92 examples/s]
Generating train split: 55560752 examples [52:03, 44849.88 examples/s]
Generating train split: 55565968 examples [52:03, 46735.28 examples/s]
Generating train split: 55570819 examples [52:03, 47200.00 examples/s]
Generating train split: 55575915 examples [52:03, 48223.85 examples/s]
Generating train split: 55580827 examples [52:03, 47965.76 examples/s]
Generating train split: 55585681 examples [52:03, 47831.60 examples/s]
Generating train split: 55591400 examples [52:03, 50510.42 examples/s]
Generating train split: 55596642 examples [52:03, 51052.38 examples/s]
Generating train split: 55601893 examples [52:03, 51453.57 examples/s]
Generating train split: 55607696 examples [52:03, 53386.83 examples/s]
Generating train split: 55613060 examples [52:04, 47295.02 examples/s]
Generating train split: 55617927 examples [52:04, 36923.42 examples/s]
Generating train split: 55622047 examples [52:04, 32741.84 examples/s]
Generating train split: 55625662 examples [52:04, 29647.03 examples/s]
Generating train split: 55628883 examples [52:04, 30197.61 examples/s]
Generating train split: 55635530 examples [52:04, 38853.03 examples/s]
Generating train split: 55643255 examples [52:04, 48606.63 examples/s]
Generating train split: 55648551 examples [52:05, 40556.53 examples/s]
Generating train split: 55653111 examples [52:05, 31405.28 examples/s]
Generating train split: 55656879 examples [52:05, 32481.36 examples/s]
Generating train split: 55665007 examples [52:05, 43382.22 examples/s]
Generating train split: 55671171 examples [52:05, 47787.48 examples/s]
Generating train split: 55676558 examples [52:05, 41840.22 examples/s]
Generating train split: 55682365 examples [52:05, 45686.99 examples/s]
Generating train split: 55687412 examples [52:06, 35098.90 examples/s]
Generating train split: 55691598 examples [52:06, 31464.79 examples/s]
Generating train split: 55695420 examples [52:06, 32854.46 examples/s]
Generating train split: 55699116 examples [52:06, 33679.96 examples/s]
Generating train split: 55702862 examples [52:06, 34599.92 examples/s]
Generating train split: 55706563 examples [52:06, 28446.50 examples/s]
Generating train split: 55709738 examples [52:06, 25073.11 examples/s]
Generating train split: 55712519 examples [52:07, 25082.58 examples/s]
Generating train split: 55716057 examples [52:07, 27498.98 examples/s]
Generating train split: 55719006 examples [52:07, 25799.04 examples/s]
Generating train split: 55725356 examples [52:07, 35172.99 examples/s]
Generating train split: 55732692 examples [52:07, 45173.96 examples/s]
Generating train split: 55737567 examples [52:07, 30089.89 examples/s]
Generating train split: 55741479 examples [52:07, 29590.08 examples/s]
Generating train split: 55745062 examples [52:08, 29172.79 examples/s]
Generating train split: 55748406 examples [52:08, 26932.40 examples/s]
Generating train split: 55751409 examples [52:08, 20667.48 examples/s]
Generating train split: 55754142 examples [52:08, 21936.15 examples/s]
Generating train split: 55760912 examples [52:08, 31741.03 examples/s]
Generating train split: 55767743 examples [52:08, 39612.44 examples/s]
Generating train split: 55772321 examples [52:09, 30303.38 examples/s]
Generating train split: 55776085 examples [52:09, 21695.06 examples/s]
Generating train split: 55782376 examples [52:09, 28599.92 examples/s]
Generating train split: 55790103 examples [52:09, 37991.22 examples/s]
Generating train split: 55795201 examples [52:09, 33856.53 examples/s]
Generating train split: 55799555 examples [52:10, 20102.13 examples/s]
Generating train split: 55802880 examples [52:10, 17555.15 examples/s]
Generating train split: 55805570 examples [52:10, 18109.30 examples/s]
Generating train split: 55808070 examples [52:10, 17550.49 examples/s]
Generating train split: 55810293 examples [52:10, 17102.58 examples/s]
Generating train split: 55812327 examples [52:11, 13909.64 examples/s]
Generating train split: 55814436 examples [52:11, 15091.80 examples/s]
Generating train split: 55816252 examples [52:11, 15683.00 examples/s]
Generating train split: 55819830 examples [52:11, 20102.02 examples/s]
Generating train split: 55826980 examples [52:11, 32392.69 examples/s]
Generating train split: 55831653 examples [52:11, 36036.32 examples/s]
Generating train split: 55835699 examples [52:12, 19758.68 examples/s]
Generating train split: 55838814 examples [52:12, 18520.26 examples/s]
Generating train split: 55845144 examples [52:12, 26149.33 examples/s]
Generating train split: 55849999 examples [52:12, 30429.29 examples/s]
Generating train split: 55854061 examples [52:12, 22062.98 examples/s]
Generating train split: 55857285 examples [52:12, 22586.22 examples/s]
Generating train split: 55864664 examples [52:13, 32336.05 examples/s]
Generating train split: 55870194 examples [52:13, 37238.25 examples/s]
Generating train split: 55874873 examples [52:13, 25042.90 examples/s]
Generating train split: 55878549 examples [52:13, 18838.86 examples/s]
Generating train split: 55881447 examples [52:14, 16264.13 examples/s]
Generating train split: 55883794 examples [52:14, 14657.02 examples/s]
Generating train split: 55888160 examples [52:14, 18972.03 examples/s]
Generating train split: 55894553 examples [52:14, 26845.19 examples/s]
Generating train split: 55898347 examples [52:14, 19153.76 examples/s]
Generating train split: 55902754 examples [52:15, 23090.37 examples/s]
Generating train split: 55906152 examples [52:15, 24561.45 examples/s]
Generating train split: 55909448 examples [52:15, 21252.87 examples/s]
Generating train split: 55912211 examples [52:15, 20291.06 examples/s]
Generating train split: 55915326 examples [52:15, 22441.04 examples/s]
Generating train split: 55917997 examples [52:15, 23192.02 examples/s]
Generating train split: 55921551 examples [52:15, 26035.91 examples/s]
Generating train split: 55924449 examples [52:16, 21279.13 examples/s]
Generating train split: 55926920 examples [52:16, 18502.86 examples/s]
Generating train split: 55929153 examples [52:16, 19287.55 examples/s]
Generating train split: 55933573 examples [52:16, 25049.94 examples/s]
Generating train split: 55941375 examples [52:16, 38209.65 examples/s]
Generating train split: 55947900 examples [52:16, 45284.32 examples/s]
Generating train split: 55952885 examples [52:16, 43325.72 examples/s]
Generating train split: 55958811 examples [52:16, 47555.83 examples/s]
Generating train split: 55964314 examples [52:16, 49229.26 examples/s]
Generating train split: 55969456 examples [52:17, 30959.99 examples/s]
Generating train split: 55973536 examples [52:17, 32268.55 examples/s]
Generating train split: 55977515 examples [52:17, 30840.83 examples/s]
Generating train split: 55981116 examples [52:17, 21583.68 examples/s]
Generating train split: 55985309 examples [52:17, 25154.06 examples/s]
Generating train split: 55994486 examples [52:18, 38503.66 examples/s]
Generating train split: 56002443 examples [52:18, 47585.40 examples/s]
Generating train split: 56008339 examples [52:18, 31697.06 examples/s]
Generating train split: 56012981 examples [52:18, 26956.88 examples/s]
Generating train split: 56016790 examples [52:18, 26904.30 examples/s]
Generating train split: 56020261 examples [52:18, 27677.99 examples/s]
Generating train split: 56028113 examples [52:19, 37969.60 examples/s]
Generating train split: 56034237 examples [52:19, 42990.39 examples/s]
Generating train split: 56039325 examples [52:19, 27720.68 examples/s]
Generating train split: 56043322 examples [52:19, 29146.56 examples/s]
Generating train split: 56047174 examples [52:19, 29589.01 examples/s]
Generating train split: 56050797 examples [52:20, 23535.55 examples/s]
Generating train split: 56053772 examples [52:20, 24260.24 examples/s]
Generating train split: 56056670 examples [52:20, 22916.30 examples/s]
Generating train split: 56061370 examples [52:20, 28025.39 examples/s]
Generating train split: 56064607 examples [52:20, 24081.10 examples/s]
Generating train split: 56067455 examples [52:20, 22159.37 examples/s]
Generating train split: 56069937 examples [52:20, 21161.03 examples/s]
Generating train split: 56073778 examples [52:20, 24977.33 examples/s]
Generating train split: 56076542 examples [52:21, 17521.91 examples/s]
Generating train split: 56080082 examples [52:21, 20917.88 examples/s]
Generating train split: 56082691 examples [52:21, 16653.14 examples/s]
Generating train split: 56084832 examples [52:21, 13362.56 examples/s]
Generating train split: 56086979 examples [52:21, 14732.76 examples/s]
Generating train split: 56089027 examples [52:22, 15838.38 examples/s]
Generating train split: 56092963 examples [52:22, 20950.47 examples/s]
Generating train split: 56098347 examples [52:22, 28684.51 examples/s]
Generating train split: 56101715 examples [52:22, 21794.37 examples/s]
Generating train split: 56104487 examples [52:22, 21694.61 examples/s]
Generating train split: 56107063 examples [52:22, 21768.62 examples/s]
Generating train split: 56109526 examples [52:22, 17320.98 examples/s]
Generating train split: 56111584 examples [52:23, 14825.70 examples/s]
Generating train split: 56119577 examples [52:23, 27405.61 examples/s]
Generating train split: 56128668 examples [52:23, 41134.25 examples/s]
Generating train split: 56133923 examples [52:23, 35357.72 examples/s]
Generating train split: 56140370 examples [52:23, 41570.96 examples/s]
Generating train split: 56148183 examples [52:23, 50122.26 examples/s]
Generating train split: 56154066 examples [52:24, 31015.03 examples/s]
Generating train split: 56158668 examples [52:24, 26963.60 examples/s]
Generating train split: 56162462 examples [52:24, 17952.92 examples/s]
Generating train split: 56165359 examples [52:25, 17026.48 examples/s]
Generating train split: 56167814 examples [52:25, 16074.85 examples/s]
Generating train split: 56169918 examples [52:25, 15736.60 examples/s]
Generating train split: 56171827 examples [52:25, 15590.24 examples/s]
Generating train split: 56173619 examples [52:25, 12580.79 examples/s]
Generating train split: 56175098 examples [52:26, 10166.03 examples/s]
Generating train split: 56176332 examples [52:26, 10004.01 examples/s]
Generating train split: 56177550 examples [52:26, 9506.66 examples/s] 
Generating train split: 56178579 examples [52:26, 8733.58 examples/s]
Generating train split: 56179499 examples [52:26, 6045.37 examples/s]
Generating train split: 56180925 examples [52:26, 7287.29 examples/s]
Generating train split: 56181957 examples [52:27, 7850.99 examples/s]
Generating train split: 56183579 examples [52:27, 9571.54 examples/s]
Generating train split: 56184728 examples [52:27, 6810.00 examples/s]
Generating train split: 56185997 examples [52:27, 7867.50 examples/s]
Generating train split: 56192093 examples [52:27, 18837.94 examples/s]
Generating train split: 56200886 examples [52:27, 34580.50 examples/s]
Generating train split: 56205298 examples [52:28, 23583.04 examples/s]
Generating train split: 56208793 examples [52:28, 18911.14 examples/s]
Generating train split: 56211595 examples [52:28, 19619.90 examples/s]
Generating train split: 56220842 examples [52:28, 32857.82 examples/s]
Generating train split: 56226123 examples [52:28, 36969.98 examples/s]
Generating train split: 56230942 examples [52:29, 23030.69 examples/s]
Generating train split: 56234665 examples [52:29, 19447.77 examples/s]
Generating train split: 56240637 examples [52:29, 25438.83 examples/s]
Generating train split: 56247692 examples [52:29, 33333.14 examples/s]
Generating train split: 56252524 examples [52:29, 34289.57 examples/s]
Generating train split: 56257029 examples [52:29, 29477.88 examples/s]
Generating train split: 56260815 examples [52:30, 22737.16 examples/s]
Generating train split: 56263880 examples [52:30, 19558.18 examples/s]
Generating train split: 56267223 examples [52:30, 21655.21 examples/s]
Generating train split: 56269948 examples [52:30, 17535.47 examples/s]
Generating train split: 56272175 examples [52:30, 16643.61 examples/s]
Generating train split: 56274181 examples [52:31, 17263.78 examples/s]
Generating train split: 56281990 examples [52:31, 29858.68 examples/s]
Generating train split: 56287915 examples [52:31, 36562.65 examples/s]
Generating train split: 56292312 examples [52:31, 21997.17 examples/s]
Generating train split: 56295713 examples [52:31, 22597.52 examples/s]
Generating train split: 56298838 examples [52:32, 19058.92 examples/s]
Generating train split: 56301414 examples [52:32, 17960.81 examples/s]
Generating train split: 56304219 examples [52:32, 19761.84 examples/s]
Generating train split: 56307098 examples [52:32, 20220.23 examples/s]
Generating train split: 56309447 examples [52:32, 20805.64 examples/s]
Generating train split: 56313196 examples [52:32, 24549.17 examples/s]
Generating train split: 56316835 examples [52:32, 27089.53 examples/s]
Generating train split: 56319778 examples [52:32, 25888.40 examples/s]
Generating train split: 56322529 examples [52:33, 24476.46 examples/s]
Generating train split: 56325104 examples [52:33, 19464.60 examples/s]
Generating train split: 56327311 examples [52:33, 20040.31 examples/s]
Generating train split: 56330283 examples [52:33, 22316.82 examples/s]
Generating train split: 56333474 examples [52:33, 24762.96 examples/s]
Generating train split: 56336119 examples [52:33, 22356.62 examples/s]
Generating train split: 56339926 examples [52:33, 26329.34 examples/s]
Generating train split: 56342753 examples [52:33, 23137.37 examples/s]
Generating train split: 56345944 examples [52:34, 25279.60 examples/s]
Generating train split: 56349071 examples [52:34, 26833.02 examples/s]
Generating train split: 56351907 examples [52:34, 24946.49 examples/s]
Generating train split: 56354529 examples [52:34, 16817.66 examples/s]
Generating train split: 56357198 examples [52:34, 18775.92 examples/s]
Generating train split: 56364382 examples [52:34, 30521.97 examples/s]
Generating train split: 56374541 examples [52:34, 47588.60 examples/s]
Generating train split: 56380208 examples [52:35, 47531.45 examples/s]
Generating train split: 56385603 examples [52:35, 33657.25 examples/s]
Generating train split: 56389967 examples [52:35, 26490.47 examples/s]
Generating train split: 56393500 examples [52:35, 24616.31 examples/s]
Generating train split: 56400140 examples [52:35, 28899.48 examples/s]
Generating train split: 56403516 examples [52:36, 26271.98 examples/s]
Generating train split: 56408644 examples [52:36, 31053.34 examples/s]
Generating train split: 56412428 examples [52:36, 32505.95 examples/s]
Generating train split: 56416087 examples [52:36, 26543.99 examples/s]
Generating train split: 56419264 examples [52:36, 27635.16 examples/s]
Generating train split: 56422383 examples [52:36, 24408.23 examples/s]
Generating train split: 56425520 examples [52:36, 25843.92 examples/s]
Generating train split: 56429136 examples [52:36, 28299.67 examples/s]
Generating train split: 56432212 examples [52:37, 20288.64 examples/s]
Generating train split: 56434702 examples [52:37, 19654.84 examples/s]
Generating train split: 56437446 examples [52:37, 21294.96 examples/s]
Generating train split: 56441354 examples [52:37, 25331.58 examples/s]
Generating train split: 56445411 examples [52:37, 29108.54 examples/s]
Generating train split: 56448626 examples [52:37, 24336.21 examples/s]
Generating train split: 56451390 examples [52:37, 23914.18 examples/s]
Generating train split: 56454015 examples [52:38, 22970.12 examples/s]
Generating train split: 56457204 examples [52:38, 25122.49 examples/s]
Generating train split: 56459876 examples [52:38, 17412.08 examples/s]
Generating train split: 56462034 examples [52:38, 15819.59 examples/s]
Generating train split: 56465265 examples [52:38, 19103.95 examples/s]
Generating train split: 56472333 examples [52:38, 30533.95 examples/s]
Generating train split: 56480497 examples [52:38, 42824.11 examples/s]
Generating train split: 56485559 examples [52:39, 25056.71 examples/s]
Generating train split: 56489477 examples [52:39, 25748.73 examples/s]
Generating train split: 56494100 examples [52:39, 29459.22 examples/s]
Generating train split: 56498027 examples [52:39, 31503.21 examples/s]
Generating train split: 56502282 examples [52:39, 34034.68 examples/s]
Generating train split: 56508523 examples [52:39, 41038.92 examples/s]
Generating train split: 56517848 examples [52:40, 54654.80 examples/s]
Generating train split: 56527942 examples [52:40, 67198.52 examples/s]
Generating train split: 56535217 examples [52:40, 37591.73 examples/s]
Generating train split: 56540860 examples [52:40, 38289.31 examples/s]
Generating train split: 56546035 examples [52:40, 27389.97 examples/s]
Generating train split: 56550520 examples [52:41, 30108.67 examples/s]
Generating train split: 56554704 examples [52:41, 32002.87 examples/s]
Generating train split: 56558849 examples [52:41, 33569.34 examples/s]
Generating train split: 56562922 examples [52:41, 33511.19 examples/s]
Generating train split: 56567237 examples [52:41, 35755.99 examples/s]
Generating train split: 56571265 examples [52:41, 36812.63 examples/s]
Generating train split: 56575269 examples [52:41, 35515.88 examples/s]
Generating train split: 56579046 examples [52:41, 35220.36 examples/s]
Generating train split: 56582791 examples [52:41, 35800.44 examples/s]
Generating train split: 56587617 examples [52:42, 38814.43 examples/s]
Generating train split: 56591599 examples [52:42, 25831.06 examples/s]
Generating train split: 56594826 examples [52:42, 22979.53 examples/s]
Generating train split: 56597591 examples [52:42, 20321.89 examples/s]
Generating train split: 56599970 examples [52:43, 14313.27 examples/s]
Generating train split: 56601852 examples [52:43, 12322.79 examples/s]
Generating train split: 56604664 examples [52:43, 14782.78 examples/s]
Generating train split: 56611309 examples [52:43, 24294.18 examples/s]
Generating train split: 56614953 examples [52:43, 26793.56 examples/s]
Generating train split: 56618556 examples [52:43, 28897.94 examples/s]
Generating train split: 56622674 examples [52:43, 31915.84 examples/s]
Generating train split: 56626342 examples [52:43, 31517.28 examples/s]
Generating train split: 56631668 examples [52:44, 37184.52 examples/s]
Generating train split: 56636924 examples [52:44, 41354.42 examples/s]
Generating train split: 56644848 examples [52:44, 51931.72 examples/s]
Generating train split: 56651036 examples [52:44, 54769.81 examples/s]
Generating train split: 56658032 examples [52:44, 59164.52 examples/s]
Generating train split: 56664226 examples [52:44, 57342.57 examples/s]
Generating train split: 56670085 examples [52:44, 39297.14 examples/s]
Generating train split: 56675830 examples [52:44, 43241.65 examples/s]
Generating train split: 56680892 examples [52:45, 42214.79 examples/s]
Generating train split: 56685628 examples [52:45, 27697.44 examples/s]
Generating train split: 56690009 examples [52:45, 30433.51 examples/s]
Generating train split: 56695741 examples [52:45, 35901.37 examples/s]
Generating train split: 56703556 examples [52:45, 45410.25 examples/s]
Generating train split: 56710532 examples [52:45, 51321.37 examples/s]
Generating train split: 56716437 examples [52:45, 44530.34 examples/s]
Generating train split: 56721575 examples [52:46, 27269.24 examples/s]
Generating train split: 56725564 examples [52:46, 20198.85 examples/s]
Generating train split: 56728678 examples [52:46, 20706.80 examples/s]
Generating train split: 56731832 examples [52:46, 22440.92 examples/s]
Generating train split: 56734791 examples [52:47, 21608.55 examples/s]
Generating train split: 56739342 examples [52:47, 26258.47 examples/s]
Generating train split: 56745825 examples [52:47, 34650.75 examples/s]
Generating train split: 56750024 examples [52:47, 24447.92 examples/s]
Generating train split: 56753380 examples [52:47, 20230.17 examples/s]
Generating train split: 56756126 examples [52:48, 19336.70 examples/s]
Generating train split: 56758554 examples [52:48, 13893.65 examples/s]
Generating train split: 56760752 examples [52:48, 15103.76 examples/s]
Generating train split: 56762742 examples [52:48, 15528.93 examples/s]
Generating train split: 56765369 examples [52:48, 17640.82 examples/s]
Generating train split: 56767735 examples [52:48, 18959.39 examples/s]
Generating train split: 56769938 examples [52:49, 14952.25 examples/s]
Generating train split: 56771759 examples [52:49, 14659.57 examples/s]
Generating train split: 56773563 examples [52:49, 15369.52 examples/s]
Generating train split: 56775294 examples [52:49, 12297.87 examples/s]
Generating train split: 56776740 examples [52:49, 12031.68 examples/s]
Generating train split: 56778099 examples [52:49, 9758.37 examples/s] 
Generating train split: 56779226 examples [52:50, 8406.27 examples/s]
Generating train split: 56780194 examples [52:50, 8544.41 examples/s]
Generating train split: 56781779 examples [52:50, 9903.56 examples/s]
Generating train split: 56782888 examples [52:50, 9656.96 examples/s]
Generating train split: 56784261 examples [52:50, 10456.45 examples/s]
Generating train split: 56785381 examples [52:50, 9331.14 examples/s] 
Generating train split: 56786377 examples [52:50, 7942.79 examples/s]
Generating train split: 56787744 examples [52:50, 9192.81 examples/s]
Generating train split: 56788757 examples [52:51, 9317.05 examples/s]
Generating train split: 56790037 examples [52:51, 10179.32 examples/s]
Generating train split: 56791125 examples [52:51, 10248.03 examples/s]
Generating train split: 56792598 examples [52:51, 11464.49 examples/s]
Generating train split: 56793847 examples [52:51, 11742.57 examples/s]
Generating train split: 56796410 examples [52:51, 15706.46 examples/s]
Generating train split: 56798111 examples [52:51, 16065.88 examples/s]
Generating train split: 56801407 examples [52:51, 20922.59 examples/s]
Generating train split: 56803531 examples [52:51, 19603.76 examples/s]
Generating train split: 56805528 examples [52:52, 13432.48 examples/s]
Generating train split: 56807154 examples [52:52, 13035.74 examples/s]
Generating train split: 56808650 examples [52:52, 10654.80 examples/s]
Generating train split: 56810096 examples [52:52, 11250.19 examples/s]
Generating train split: 56811383 examples [52:52, 11225.25 examples/s]
Generating train split: 56812621 examples [52:52, 11332.54 examples/s]
Generating train split: 56813834 examples [52:52, 10915.86 examples/s]
Generating train split: 56814987 examples [52:53, 10394.08 examples/s]
Generating train split: 56816067 examples [52:53, 9720.54 examples/s] 
Generating train split: 56817076 examples [52:53, 9407.39 examples/s]
Generating train split: 56818044 examples [52:53, 9308.66 examples/s]
Generating train split: 56818991 examples [52:53, 9296.69 examples/s]
Generating train split: 56819937 examples [52:53, 7698.60 examples/s]
Generating train split: 56820752 examples [52:54, 5067.92 examples/s]
Generating train split: 56822314 examples [52:54, 6994.00 examples/s]
Generating train split: 56824970 examples [52:54, 11054.92 examples/s]
Generating train split: 56829815 examples [52:54, 19605.48 examples/s]
Generating train split: 56837568 examples [52:54, 32436.03 examples/s]
Generating train split: 56841267 examples [52:54, 20403.93 examples/s]
Generating train split: 56844175 examples [52:54, 21188.49 examples/s]
Generating train split: 56847261 examples [52:55, 19189.23 examples/s]
Generating train split: 56849658 examples [52:55, 14953.35 examples/s]
Generating train split: 56854544 examples [52:55, 20658.50 examples/s]
Generating train split: 56862343 examples [52:55, 31771.01 examples/s]
Generating train split: 56868706 examples [52:55, 38666.63 examples/s]
Generating train split: 56873632 examples [52:56, 20022.11 examples/s]
Generating train split: 56877352 examples [52:56, 19257.48 examples/s]
Generating train split: 56880469 examples [52:56, 16355.30 examples/s]
Generating train split: 56882985 examples [52:56, 17568.39 examples/s]
Generating train split: 56885488 examples [52:57, 11376.59 examples/s]
Generating train split: 56887447 examples [52:57, 12381.93 examples/s]
Generating train split: 56889372 examples [52:57, 8912.14 examples/s] 
Generating train split: 56892179 examples [52:57, 11328.72 examples/s]
Generating train split: 56899569 examples [52:58, 20886.72 examples/s]
Generating train split: 56908213 examples [52:58, 32629.13 examples/s]
Generating train split: 56913275 examples [52:58, 31776.95 examples/s]
Generating train split: 56919941 examples [52:58, 38861.67 examples/s]
Generating train split: 56925053 examples [52:58, 41505.19 examples/s]
Generating train split: 56931105 examples [52:58, 46113.59 examples/s]
Generating train split: 56936483 examples [52:59, 24964.40 examples/s]
Generating train split: 56940611 examples [52:59, 19836.13 examples/s]
Generating train split: 56943859 examples [52:59, 15975.23 examples/s]
Generating train split: 56946411 examples [52:59, 17087.38 examples/s]
Generating train split: 56953900 examples [53:00, 26072.82 examples/s]
Generating train split: 56962898 examples [53:00, 37672.20 examples/s]
Generating train split: 56968398 examples [53:00, 25465.44 examples/s]
Generating train split: 56974886 examples [53:00, 31525.94 examples/s]
Generating train split: 56983267 examples [53:00, 40412.46 examples/s]
Generating train split: 56989060 examples [53:01, 19935.37 examples/s]
Generating train split: 56998285 examples [53:01, 28320.66 examples/s]
Generating train split: 57008075 examples [53:01, 37880.31 examples/s]
Generating train split: 57014888 examples [53:01, 37700.61 examples/s]
Generating train split: 57023474 examples [53:01, 46055.78 examples/s]
Generating train split: 57030179 examples [53:02, 46447.46 examples/s]
Generating train split: 57036300 examples [53:02, 20897.36 examples/s]
Generating train split: 57040835 examples [53:03, 18150.65 examples/s]
Generating train split: 57044375 examples [53:03, 14609.06 examples/s]
Generating train split: 57047096 examples [53:03, 13793.17 examples/s]
Generating train split: 57049324 examples [53:04, 12082.73 examples/s]
Generating train split: 57051110 examples [53:04, 12248.24 examples/s]
Generating train split: 57053769 examples [53:04, 14217.43 examples/s]
Generating train split: 57062888 examples [53:04, 26841.40 examples/s]
Generating train split: 57071928 examples [53:04, 38897.87 examples/s]
Generating train split: 57077514 examples [53:04, 28136.55 examples/s]
Generating train split: 57085843 examples [53:05, 37388.34 examples/s]
Generating train split: 57091754 examples [53:05, 41577.36 examples/s]
Generating train split: 57097436 examples [53:05, 42524.06 examples/s]
Generating train split: 57105362 examples [53:05, 50836.73 examples/s]
Generating train split: 57111503 examples [53:05, 53331.46 examples/s]
Generating train split: 57117611 examples [53:05, 29495.95 examples/s]
Generating train split: 57122310 examples [53:06, 26675.68 examples/s]
Generating train split: 57126220 examples [53:06, 25853.55 examples/s]
Generating train split: 57135447 examples [53:06, 37325.34 examples/s]
Generating train split: 57142218 examples [53:06, 43101.33 examples/s]
Generating train split: 57147818 examples [53:06, 36484.46 examples/s]
Generating train split: 57152510 examples [53:07, 25142.31 examples/s]
Generating train split: 57156180 examples [53:07, 23221.33 examples/s]
Generating train split: 57159289 examples [53:07, 19326.23 examples/s]
Generating train split: 57161825 examples [53:07, 16682.81 examples/s]
Generating train split: 57163912 examples [53:07, 16741.16 examples/s]
Generating train split: 57166072 examples [53:08, 17290.79 examples/s]
Generating train split: 57168043 examples [53:08, 12731.23 examples/s]
Generating train split: 57170121 examples [53:08, 14081.26 examples/s]
Generating train split: 57173642 examples [53:08, 18164.37 examples/s]
Generating train split: 57178332 examples [53:08, 24380.56 examples/s]
Generating train split: 57182083 examples [53:08, 27456.61 examples/s]
Generating train split: 57185305 examples [53:08, 25237.40 examples/s]
Generating train split: 57188184 examples [53:09, 24376.75 examples/s]
Generating train split: 57190876 examples [53:09, 24878.60 examples/s]
Generating train split: 57193560 examples [53:09, 25375.64 examples/s]
Generating train split: 57196246 examples [53:09, 14015.78 examples/s]
Generating train split: 57198322 examples [53:09, 14800.53 examples/s]
Generating train split: 57201191 examples [53:09, 17459.89 examples/s]
Generating train split: 57203437 examples [53:10, 13676.35 examples/s]
Generating train split: 57205266 examples [53:10, 12972.63 examples/s]
Generating train split: 57207688 examples [53:10, 15111.47 examples/s]
Generating train split: 57209539 examples [53:10, 10855.43 examples/s]
Generating train split: 57212129 examples [53:10, 13443.21 examples/s]
Generating train split: 57215505 examples [53:10, 17473.61 examples/s]
Generating train split: 57223783 examples [53:10, 31892.32 examples/s]
Generating train split: 57230151 examples [53:11, 39372.83 examples/s]
Generating train split: 57234889 examples [53:11, 33477.05 examples/s]
Generating train split: 57238938 examples [53:11, 21373.16 examples/s]
Generating train split: 57244277 examples [53:11, 26654.99 examples/s]
Generating train split: 57248145 examples [53:11, 28933.30 examples/s]
Generating train split: 57253447 examples [53:11, 34084.36 examples/s]
Generating train split: 57260370 examples [53:12, 42306.76 examples/s]
Generating train split: 57268465 examples [53:12, 51984.68 examples/s]
Generating train split: 57274436 examples [53:12, 50738.07 examples/s]
Generating train split: 57280227 examples [53:12, 52583.76 examples/s]
Generating train split: 57285900 examples [53:12, 31142.47 examples/s]
Generating train split: 57290584 examples [53:12, 34002.84 examples/s]
Generating train split: 57295246 examples [53:12, 36621.11 examples/s]
Generating train split: 57299803 examples [53:13, 36239.41 examples/s]
Generating train split: 57306952 examples [53:13, 44493.66 examples/s]
Generating train split: 57314297 examples [53:13, 51757.31 examples/s]
Generating train split: 57323040 examples [53:13, 61147.71 examples/s]
Generating train split: 57331127 examples [53:13, 66450.82 examples/s]
Generating train split: 57338207 examples [53:13, 40883.40 examples/s]
Generating train split: 57343804 examples [53:13, 38770.37 examples/s]
Generating train split: 57348736 examples [53:14, 39220.79 examples/s]
Generating train split: 57353696 examples [53:14, 41318.45 examples/s]
Generating train split: 57358432 examples [53:14, 33056.00 examples/s]
Generating train split: 57362384 examples [53:14, 29576.77 examples/s]
Generating train split: 57371983 examples [53:14, 42929.80 examples/s]
Generating train split: 57378967 examples [53:14, 48691.49 examples/s]
Generating train split: 57385359 examples [53:14, 52342.44 examples/s]
Generating train split: 57394580 examples [53:15, 62529.58 examples/s]
Generating train split: 57401505 examples [53:15, 59618.01 examples/s]
Generating train split: 57407956 examples [53:15, 44348.62 examples/s]
Generating train split: 57413272 examples [53:15, 28487.77 examples/s]
Generating train split: 57419657 examples [53:15, 34085.13 examples/s]
Generating train split: 57429797 examples [53:15, 46501.64 examples/s]
Generating train split: 57436547 examples [53:16, 50873.33 examples/s]
Generating train split: 57443056 examples [53:16, 35944.69 examples/s]
Generating train split: 57448218 examples [53:16, 32137.52 examples/s]
Generating train split: 57454634 examples [53:16, 37735.84 examples/s]
Generating train split: 57461640 examples [53:16, 44190.17 examples/s]
Generating train split: 57467226 examples [53:17, 37084.50 examples/s]
Generating train split: 57471905 examples [53:17, 31660.05 examples/s]
Generating train split: 57475826 examples [53:17, 28855.86 examples/s]
Generating train split: 57479239 examples [53:17, 28673.37 examples/s]
Generating train split: 57487339 examples [53:17, 39504.40 examples/s]
Generating train split: 57495046 examples [53:17, 48061.89 examples/s]
Generating train split: 57500654 examples [53:18, 31086.39 examples/s]
Generating train split: 57509180 examples [53:18, 40783.08 examples/s]
Generating train split: 57515515 examples [53:18, 44704.06 examples/s]
Generating train split: 57521231 examples [53:18, 26817.10 examples/s]
Generating train split: 57525621 examples [53:19, 23251.73 examples/s]
Generating train split: 57529180 examples [53:19, 23777.92 examples/s]
Generating train split: 57534718 examples [53:19, 29017.52 examples/s]
Generating train split: 57539456 examples [53:19, 32093.87 examples/s]
Generating train split: 57543554 examples [53:19, 28799.38 examples/s]
Generating train split: 57547083 examples [53:19, 28241.98 examples/s]
Generating train split: 57550356 examples [53:19, 27832.33 examples/s]
Generating train split: 57554214 examples [53:19, 30257.04 examples/s]
Generating train split: 57561752 examples [53:20, 41274.29 examples/s]
Generating train split: 57568360 examples [53:20, 47672.47 examples/s]
Generating train split: 57573550 examples [53:20, 40754.63 examples/s]
Generating train split: 57580862 examples [53:20, 48626.98 examples/s]
Generating train split: 57586224 examples [53:20, 37443.16 examples/s]
Generating train split: 57590680 examples [53:20, 32826.14 examples/s]
Generating train split: 57597280 examples [53:20, 39673.25 examples/s]
Generating train split: 57604984 examples [53:20, 48180.29 examples/s]
Generating train split: 57610924 examples [53:21, 50433.97 examples/s]
Generating train split: 57616551 examples [53:21, 35553.54 examples/s]
Generating train split: 57621088 examples [53:21, 32911.91 examples/s]
Generating train split: 57625080 examples [53:21, 30876.55 examples/s]
Generating train split: 57628769 examples [53:21, 32110.53 examples/s]
Generating train split: 57638679 examples [53:21, 47319.85 examples/s]
Generating train split: 57648922 examples [53:22, 60805.68 examples/s]
Generating train split: 57655837 examples [53:22, 40805.26 examples/s]
Generating train split: 57661350 examples [53:22, 30304.85 examples/s]
Generating train split: 57665720 examples [53:22, 32396.71 examples/s]
Generating train split: 57675228 examples [53:22, 44109.76 examples/s]
Generating train split: 57681325 examples [53:22, 47638.62 examples/s]
Generating train split: 57687287 examples [53:23, 37651.24 examples/s]
Generating train split: 57692181 examples [53:23, 38470.57 examples/s]
Generating train split: 57696853 examples [53:23, 35370.03 examples/s]
Generating train split: 57700984 examples [53:23, 27513.72 examples/s]
Generating train split: 57704357 examples [53:23, 27232.27 examples/s]
Generating train split: 57707501 examples [53:24, 24450.18 examples/s]
Generating train split: 57710245 examples [53:24, 22141.45 examples/s]
Generating train split: 57712896 examples [53:24, 23013.86 examples/s]
Generating train split: 57715393 examples [53:24, 23002.08 examples/s]
Generating train split: 57718944 examples [53:24, 25833.76 examples/s]
Generating train split: 57721700 examples [53:24, 21120.75 examples/s]
Generating train split: 57724045 examples [53:24, 21007.45 examples/s]
Generating train split: 57726311 examples [53:25, 13028.19 examples/s]
Generating train split: 57728075 examples [53:25, 10867.50 examples/s]
Generating train split: 57729532 examples [53:25, 11336.11 examples/s]
Generating train split: 57730960 examples [53:25, 11683.70 examples/s]
Generating train split: 57732948 examples [53:25, 13376.58 examples/s]
Generating train split: 57735282 examples [53:25, 15505.26 examples/s]
Generating train split: 57737064 examples [53:25, 15469.48 examples/s]
Generating train split: 57738768 examples [53:26, 14345.06 examples/s]
Generating train split: 57740320 examples [53:26, 12180.63 examples/s]
Generating train split: 57741666 examples [53:26, 11121.41 examples/s]
Generating train split: 57742875 examples [53:26, 11022.94 examples/s]
Generating train split: 57744044 examples [53:26, 10959.87 examples/s]
Generating train split: 57745189 examples [53:26, 10998.77 examples/s]
Generating train split: 57746953 examples [53:26, 12723.10 examples/s]
Generating train split: 57748276 examples [53:27, 12156.74 examples/s]
Generating train split: 57749540 examples [53:27, 9347.59 examples/s] 
Generating train split: 57750721 examples [53:27, 9893.11 examples/s]
Generating train split: 57752121 examples [53:27, 10737.91 examples/s]
Generating train split: 57753280 examples [53:27, 6965.59 examples/s] 
Generating train split: 57755635 examples [53:27, 10087.01 examples/s]
Generating train split: 57759397 examples [53:27, 15919.83 examples/s]
Generating train split: 57768164 examples [53:28, 32588.13 examples/s]
Generating train split: 57774142 examples [53:28, 39361.03 examples/s]
Generating train split: 57778790 examples [53:28, 19688.94 examples/s]
Generating train split: 57782539 examples [53:28, 22388.17 examples/s]
Generating train split: 57788065 examples [53:28, 28238.99 examples/s]
Generating train split: 57793651 examples [53:28, 33575.29 examples/s]
Generating train split: 57798187 examples [53:29, 24236.26 examples/s]
Generating train split: 57805126 examples [53:29, 32181.23 examples/s]
Generating train split: 57813594 examples [53:29, 42717.43 examples/s]
Generating train split: 57819351 examples [53:29, 40027.85 examples/s]
Generating train split: 57824413 examples [53:29, 39543.76 examples/s]
Generating train split: 57829107 examples [53:30, 28166.21 examples/s]
Generating train split: 57832860 examples [53:30, 27403.91 examples/s]
Generating train split: 57839850 examples [53:30, 35507.92 examples/s]
Generating train split: 57849228 examples [53:30, 47978.65 examples/s]
Generating train split: 57855164 examples [53:30, 44245.54 examples/s]
Generating train split: 57860419 examples [53:30, 42509.58 examples/s]
Generating train split: 57865248 examples [53:31, 29243.93 examples/s]
Generating train split: 57869091 examples [53:31, 28816.96 examples/s]
Generating train split: 57878404 examples [53:31, 41227.76 examples/s]
Generating train split: 57887167 examples [53:31, 51244.11 examples/s]
Generating train split: 57893472 examples [53:31, 41769.83 examples/s]
Generating train split: 57902982 examples [53:31, 52777.54 examples/s]
Generating train split: 57909682 examples [53:31, 55456.98 examples/s]
Generating train split: 57916186 examples [53:32, 38008.03 examples/s]
Generating train split: 57921365 examples [53:32, 33071.63 examples/s]
Generating train split: 57925687 examples [53:32, 28754.81 examples/s]
Generating train split: 57929306 examples [53:32, 24492.65 examples/s]
Generating train split: 57932524 examples [53:32, 25782.11 examples/s]
Generating train split: 57935601 examples [53:33, 22948.51 examples/s]
Generating train split: 57938246 examples [53:33, 17630.98 examples/s]
Generating train split: 57942496 examples [53:33, 21848.18 examples/s]
Generating train split: 57951300 examples [53:33, 34764.47 examples/s]
Generating train split: 57961180 examples [53:33, 47712.08 examples/s]
Generating train split: 57967086 examples [53:33, 46495.85 examples/s]
Generating train split: 57972537 examples [53:34, 26110.13 examples/s]
Generating train split: 57982345 examples [53:34, 37166.15 examples/s]
Generating train split: 57992804 examples [53:34, 49298.95 examples/s]
Generating train split: 58000042 examples [53:35, 29308.80 examples/s]
Generating train split: 58005538 examples [53:35, 30494.55 examples/s]
Generating train split: 58013590 examples [53:35, 38182.20 examples/s]
Generating train split: 58019442 examples [53:35, 40648.35 examples/s]
Generating train split: 58025053 examples [53:35, 24967.22 examples/s]
Generating train split: 58029338 examples [53:36, 21959.06 examples/s]
Generating train split: 58032796 examples [53:36, 18509.62 examples/s]
Generating train split: 58041276 examples [53:36, 27350.69 examples/s]
Generating train split: 58048064 examples [53:36, 33832.50 examples/s]
Generating train split: 58053240 examples [53:36, 31666.04 examples/s]
Generating train split: 58057671 examples [53:37, 23501.29 examples/s]
Generating train split: 58061162 examples [53:37, 17128.01 examples/s]
Generating train split: 58063858 examples [53:37, 16819.64 examples/s]
Generating train split: 58066222 examples [53:37, 16363.45 examples/s]
Generating train split: 58068312 examples [53:38, 16253.49 examples/s]
Generating train split: 58075922 examples [53:38, 26933.46 examples/s]
Generating train split: 58083985 examples [53:38, 37838.71 examples/s]
Generating train split: 58090509 examples [53:38, 43848.70 examples/s]
Generating train split: 58095919 examples [53:38, 26183.25 examples/s]
Generating train split: 58100097 examples [53:38, 25996.80 examples/s]
Generating train split: 58103789 examples [53:39, 25268.69 examples/s]
Generating train split: 58107061 examples [53:39, 18486.97 examples/s]
Generating train split: 58109640 examples [53:39, 14324.55 examples/s]
Generating train split: 58111702 examples [53:39, 15196.97 examples/s]
Generating train split: 58113751 examples [53:40, 14222.23 examples/s]
Generating train split: 58115612 examples [53:40, 14789.93 examples/s]
Generating train split: 58117373 examples [53:40, 14238.11 examples/s]
Generating train split: 58118987 examples [53:40, 14585.15 examples/s]
Generating train split: 58120605 examples [53:40, 13113.36 examples/s]
Generating train split: 58127910 examples [53:40, 26389.59 examples/s]
Generating train split: 58132240 examples [53:40, 30451.35 examples/s]
Generating train split: 58138892 examples [53:40, 39664.35 examples/s]
Generating train split: 58144397 examples [53:40, 43774.99 examples/s]
Generating train split: 58149184 examples [53:41, 40056.43 examples/s]
Generating train split: 58155989 examples [53:41, 47336.97 examples/s]
Generating train split: 58161068 examples [53:41, 25689.66 examples/s]
Generating train split: 58166070 examples [53:41, 29846.50 examples/s]
Generating train split: 58170964 examples [53:41, 32827.07 examples/s]
Generating train split: 58175252 examples [53:41, 33943.90 examples/s]
Generating train split: 58180730 examples [53:42, 38710.98 examples/s]
Generating train split: 58185260 examples [53:42, 38379.96 examples/s]
Generating train split: 58192796 examples [53:42, 47661.75 examples/s]
Generating train split: 58200811 examples [53:42, 56234.79 examples/s]
Generating train split: 58206914 examples [53:42, 54276.57 examples/s]
Generating train split: 58212687 examples [53:42, 37347.96 examples/s]
Generating train split: 58217358 examples [53:42, 32885.67 examples/s]
Generating train split: 58221352 examples [53:43, 30681.59 examples/s]
Generating train split: 58224899 examples [53:43, 26775.72 examples/s]
Generating train split: 58229106 examples [53:43, 29772.85 examples/s]
Generating train split: 58232501 examples [53:43, 29007.88 examples/s]
Generating train split: 58236953 examples [53:43, 32539.38 examples/s]
Generating train split: 58241620 examples [53:43, 35263.85 examples/s]
Generating train split: 58245403 examples [53:43, 30776.68 examples/s]
Generating train split: 58248743 examples [53:44, 25485.42 examples/s]
Generating train split: 58257816 examples [53:44, 39617.66 examples/s]
Generating train split: 58266476 examples [53:44, 50707.87 examples/s]
Generating train split: 58272370 examples [53:44, 39924.31 examples/s]
Generating train split: 58277284 examples [53:44, 26659.08 examples/s]
Generating train split: 58281121 examples [53:45, 21579.18 examples/s]
Generating train split: 58284203 examples [53:45, 22268.90 examples/s]
Generating train split: 58287122 examples [53:45, 22440.33 examples/s]
Generating train split: 58289856 examples [53:45, 23014.35 examples/s]
Generating train split: 58292837 examples [53:45, 24431.64 examples/s]
Generating train split: 58295607 examples [53:46, 15980.39 examples/s]
Generating train split: 58298473 examples [53:46, 18173.89 examples/s]
Generating train split: 58300855 examples [53:46, 18169.37 examples/s]
Generating train split: 58303168 examples [53:46, 19135.97 examples/s]
Generating train split: 58305401 examples [53:46, 19180.91 examples/s]
Generating train split: 58307545 examples [53:46, 12488.49 examples/s]
Generating train split: 58310054 examples [53:46, 14742.89 examples/s]
Generating train split: 58311987 examples [53:47, 15559.00 examples/s]
Generating train split: 58314109 examples [53:47, 16428.96 examples/s]
Generating train split: 58316023 examples [53:47, 14908.68 examples/s]
Generating train split: 58317855 examples [53:47, 15486.01 examples/s]
Generating train split: 58319567 examples [53:47, 14360.92 examples/s]
Generating train split: 58321125 examples [53:47, 13931.89 examples/s]
Generating train split: 58322662 examples [53:47, 14284.74 examples/s]
Generating train split: 58324526 examples [53:47, 15217.98 examples/s]
Generating train split: 58326111 examples [53:48, 11611.82 examples/s]
Generating train split: 58327443 examples [53:48, 11974.01 examples/s]
Generating train split: 58328771 examples [53:48, 11733.29 examples/s]
Generating train split: 58330029 examples [53:48, 9053.32 examples/s] 
Generating train split: 58331077 examples [53:48, 8415.26 examples/s]
Generating train split: 58332025 examples [53:48, 8576.50 examples/s]
Generating train split: 58333133 examples [53:48, 9155.97 examples/s]
Generating train split: 58334124 examples [53:49, 7138.11 examples/s]
Generating train split: 58334960 examples [53:49, 7173.12 examples/s]
Generating train split: 58336534 examples [53:49, 9126.08 examples/s]
Generating train split: 58338481 examples [53:49, 11665.17 examples/s]
Generating train split: 58340754 examples [53:49, 14535.08 examples/s]
Generating train split: 58342967 examples [53:49, 16557.64 examples/s]
Generating train split: 58344749 examples [53:49, 13336.59 examples/s]
Generating train split: 58346277 examples [53:49, 13784.47 examples/s]
Generating train split: 58348707 examples [53:50, 16449.75 examples/s]
Generating train split: 58350800 examples [53:50, 17633.54 examples/s]
Generating train split: 58352688 examples [53:50, 17171.98 examples/s]
Generating train split: 58354499 examples [53:50, 13421.64 examples/s]
Generating train split: 58356024 examples [53:50, 12038.91 examples/s]
Generating train split: 58357682 examples [53:50, 13046.08 examples/s]
Generating train split: 58360241 examples [53:50, 16064.82 examples/s]
Generating train split: 58362018 examples [53:51, 12816.83 examples/s]
Generating train split: 58367676 examples [53:51, 22506.07 examples/s]
Generating train split: 58376147 examples [53:51, 37445.00 examples/s]
Generating train split: 58382947 examples [53:51, 45225.15 examples/s]
Generating train split: 58388104 examples [53:51, 25212.05 examples/s]
Generating train split: 58392098 examples [53:51, 27532.44 examples/s]
Generating train split: 58399176 examples [53:51, 35946.49 examples/s]
Generating train split: 58407793 examples [53:52, 46869.96 examples/s]
Generating train split: 58413804 examples [53:52, 24810.20 examples/s]
Generating train split: 58418351 examples [53:52, 20905.51 examples/s]
Generating train split: 58422391 examples [53:53, 23512.72 examples/s]
Generating train split: 58430590 examples [53:53, 32899.14 examples/s]
Generating train split: 58438060 examples [53:53, 40340.66 examples/s]
Generating train split: 58443747 examples [53:53, 20530.62 examples/s]
Generating train split: 58447995 examples [53:54, 20016.96 examples/s]
Generating train split: 58451527 examples [53:54, 15631.37 examples/s]
Generating train split: 58454253 examples [53:54, 16895.88 examples/s]
Generating train split: 58457669 examples [53:54, 19362.99 examples/s]
Generating train split: 58460582 examples [53:54, 18394.01 examples/s]
Generating train split: 58463098 examples [53:55, 14546.99 examples/s]
Generating train split: 58465125 examples [53:55, 15281.38 examples/s]
Generating train split: 58467101 examples [53:55, 16068.69 examples/s]
Generating train split: 58469084 examples [53:55, 13787.77 examples/s]
Generating train split: 58470762 examples [53:55, 13961.03 examples/s]
Generating train split: 58472372 examples [53:55, 14273.21 examples/s]
Generating train split: 58473962 examples [53:56, 11331.65 examples/s]
Generating train split: 58475283 examples [53:56, 10793.18 examples/s]
Generating train split: 58477727 examples [53:56, 13549.54 examples/s]
Generating train split: 58479819 examples [53:56, 15237.51 examples/s]
Generating train split: 58481535 examples [53:56, 13784.17 examples/s]
Generating train split: 58483076 examples [53:56, 13821.05 examples/s]
Generating train split: 58484564 examples [53:56, 11942.17 examples/s]
Generating train split: 58486985 examples [53:56, 14691.92 examples/s]
Generating train split: 58488611 examples [53:57, 7515.69 examples/s] 
Generating train split: 58490131 examples [53:57, 8652.12 examples/s]
Generating train split: 58493386 examples [53:57, 12846.25 examples/s]
Generating train split: 58497015 examples [53:57, 17546.92 examples/s]
Generating train split: 58504230 examples [53:57, 29708.80 examples/s]
Generating train split: 58511452 examples [53:57, 39963.03 examples/s]
Generating train split: 58516316 examples [53:58, 21163.58 examples/s]
Generating train split: 58520032 examples [53:58, 19042.51 examples/s]
Generating train split: 58529588 examples [53:58, 30634.95 examples/s]
Generating train split: 58538796 examples [53:58, 41193.17 examples/s]
Generating train split: 58544918 examples [53:59, 30201.90 examples/s]
Generating train split: 58549738 examples [53:59, 24585.08 examples/s]
Generating train split: 58553570 examples [53:59, 24114.06 examples/s]
Generating train split: 58556930 examples [53:59, 24952.98 examples/s]
Generating train split: 58564998 examples [53:59, 35045.78 examples/s]
Generating train split: 58570627 examples [54:00, 39405.68 examples/s]
Generating train split: 58575592 examples [54:00, 32825.84 examples/s]
Generating train split: 58582531 examples [54:00, 40254.65 examples/s]
Generating train split: 58589033 examples [54:00, 45819.62 examples/s]
Generating train split: 58594480 examples [54:00, 31638.29 examples/s]
Generating train split: 58603306 examples [54:00, 42193.48 examples/s]
Generating train split: 58610006 examples [54:00, 47149.80 examples/s]
Generating train split: 58615938 examples [54:01, 27481.79 examples/s]
Generating train split: 58620489 examples [54:01, 21929.94 examples/s]
Generating train split: 58624076 examples [54:02, 18184.57 examples/s]
Generating train split: 58626910 examples [54:02, 16618.08 examples/s]
Generating train split: 58629262 examples [54:02, 16800.25 examples/s]
Generating train split: 58631442 examples [54:02, 14210.47 examples/s]
Generating train split: 58633230 examples [54:02, 11777.16 examples/s]
Generating train split: 58634757 examples [54:03, 12292.59 examples/s]
Generating train split: 58636601 examples [54:03, 13364.15 examples/s]
Generating train split: 58638184 examples [54:03, 10521.88 examples/s]
Generating train split: 58639475 examples [54:03, 10947.02 examples/s]
Generating train split: 58645406 examples [54:03, 20766.79 examples/s]
Generating train split: 58653619 examples [54:03, 34563.80 examples/s]
Generating train split: 58658269 examples [54:03, 36802.91 examples/s]
Generating train split: 58662612 examples [54:04, 21756.20 examples/s]
Generating train split: 58669063 examples [54:04, 29038.19 examples/s]
Generating train split: 58676974 examples [54:04, 38831.76 examples/s]
Generating train split: 58682354 examples [54:04, 31304.86 examples/s]
Generating train split: 58690233 examples [54:04, 40246.96 examples/s]
Generating train split: 58699169 examples [54:04, 50648.92 examples/s]
Generating train split: 58705658 examples [54:05, 45351.15 examples/s]
Generating train split: 58712097 examples [54:05, 49194.98 examples/s]
Generating train split: 58717913 examples [54:05, 30948.15 examples/s]
Generating train split: 58722439 examples [54:05, 32340.55 examples/s]
Generating train split: 58726749 examples [54:06, 21438.50 examples/s]
Generating train split: 58730080 examples [54:06, 22236.76 examples/s]
Generating train split: 58734524 examples [54:06, 25905.62 examples/s]
Generating train split: 58738042 examples [54:06, 20669.82 examples/s]
Generating train split: 58740877 examples [54:06, 18579.86 examples/s]
Generating train split: 58743556 examples [54:06, 19955.11 examples/s]
Generating train split: 58749204 examples [54:07, 27078.40 examples/s]
Generating train split: 58758637 examples [54:07, 41732.56 examples/s]
Generating train split: 58763865 examples [54:07, 37585.21 examples/s]
Generating train split: 58768422 examples [54:07, 25700.79 examples/s]
Generating train split: 58772017 examples [54:07, 22386.16 examples/s]
Generating train split: 58777686 examples [54:07, 28121.54 examples/s]
Generating train split: 58785064 examples [54:08, 36928.54 examples/s]
Generating train split: 58792378 examples [54:08, 44713.05 examples/s]
Generating train split: 58797971 examples [54:08, 28731.95 examples/s]
Generating train split: 58802334 examples [54:08, 24302.34 examples/s]
Generating train split: 58805874 examples [54:09, 22699.68 examples/s]
Generating train split: 58809302 examples [54:09, 24606.21 examples/s]
Generating train split: 58813402 examples [54:09, 27185.86 examples/s]
Generating train split: 58816725 examples [54:09, 19684.46 examples/s]
Generating train split: 58819371 examples [54:09, 20402.05 examples/s]
Generating train split: 58822454 examples [54:09, 22409.11 examples/s]
Generating train split: 58825169 examples [54:10, 13348.86 examples/s]
Generating train split: 58828018 examples [54:10, 15618.64 examples/s]
Generating train split: 58830345 examples [54:10, 14288.37 examples/s]
Generating train split: 58832303 examples [54:10, 12777.20 examples/s]
Generating train split: 58834694 examples [54:10, 14693.63 examples/s]
Generating train split: 58836566 examples [54:10, 14742.98 examples/s]
Generating train split: 58838328 examples [54:11, 13921.92 examples/s]
Generating train split: 58841035 examples [54:11, 16742.62 examples/s]
Generating train split: 58843456 examples [54:11, 18494.33 examples/s]
Generating train split: 58847803 examples [54:11, 24767.94 examples/s]
Generating train split: 58851638 examples [54:11, 28309.95 examples/s]
Generating train split: 58854716 examples [54:11, 28763.48 examples/s]
Generating train split: 58857767 examples [54:11, 27128.04 examples/s]
Generating train split: 58860621 examples [54:11, 24835.68 examples/s]
Generating train split: 58863239 examples [54:11, 23653.73 examples/s]
Generating train split: 58866210 examples [54:12, 25209.41 examples/s]
Generating train split: 58868827 examples [54:12, 25007.35 examples/s]
Generating train split: 58871388 examples [54:12, 18552.93 examples/s]
Generating train split: 58874596 examples [54:12, 21485.50 examples/s]
Generating train split: 58877033 examples [54:12, 21683.29 examples/s]
Generating train split: 58881069 examples [54:12, 26372.03 examples/s]
Generating train split: 58885996 examples [54:12, 32427.67 examples/s]
Generating train split: 58889677 examples [54:12, 33563.08 examples/s]
Generating train split: 58894840 examples [54:13, 38624.82 examples/s]
Generating train split: 58898861 examples [54:13, 35210.17 examples/s]
Generating train split: 58902552 examples [54:13, 31216.97 examples/s]
Generating train split: 58908105 examples [54:13, 37342.59 examples/s]
Generating train split: 58913614 examples [54:13, 42032.09 examples/s]
Generating train split: 58918063 examples [54:13, 32442.02 examples/s]
Generating train split: 58921802 examples [54:13, 29375.24 examples/s]
Generating train split: 58925749 examples [54:14, 31350.09 examples/s]
Generating train split: 58931059 examples [54:14, 36566.62 examples/s]
Generating train split: 58935123 examples [54:14, 37593.97 examples/s]
Generating train split: 58941042 examples [54:14, 42898.67 examples/s]
Generating train split: 58945573 examples [54:14, 40141.25 examples/s]
Generating train split: 58949794 examples [54:14, 28032.06 examples/s]
Generating train split: 58953214 examples [54:14, 24963.29 examples/s]
Generating train split: 58956166 examples [54:15, 24676.06 examples/s]
Generating train split: 58959974 examples [54:15, 27550.41 examples/s]
Generating train split: 58965302 examples [54:15, 33589.98 examples/s]
Generating train split: 58971285 examples [54:15, 40167.05 examples/s]
Generating train split: 58975841 examples [54:15, 41579.65 examples/s]
Generating train split: 58982826 examples [54:15, 49321.47 examples/s]
Generating train split: 58988057 examples [54:15, 40215.91 examples/s]
Generating train split: 58992559 examples [54:15, 39380.82 examples/s]
Generating train split: 58996818 examples [54:15, 37635.45 examples/s]
Generating train split: 59002028 examples [54:16, 41235.62 examples/s]
Generating train split: 59006381 examples [54:16, 39587.51 examples/s]
Generating train split: 59010502 examples [54:16, 32194.26 examples/s]
Generating train split: 59014038 examples [54:16, 21906.97 examples/s]
Generating train split: 59019244 examples [54:16, 27339.95 examples/s]
Generating train split: 59024962 examples [54:16, 33452.82 examples/s]
Generating train split: 59029188 examples [54:16, 35439.07 examples/s]
Generating train split: 59036042 examples [54:17, 43271.47 examples/s]
Generating train split: 59041356 examples [54:17, 45781.33 examples/s]
Generating train split: 59046416 examples [54:17, 35248.92 examples/s]
Generating train split: 59050635 examples [54:17, 30171.94 examples/s]
Generating train split: 59056566 examples [54:17, 36209.95 examples/s]
Generating train split: 59060872 examples [54:17, 30513.15 examples/s]
Generating train split: 59064510 examples [54:18, 19968.68 examples/s]
Generating train split: 59068112 examples [54:18, 22103.53 examples/s]
Generating train split: 59073802 examples [54:18, 28411.00 examples/s]
Generating train split: 59078015 examples [54:18, 31225.16 examples/s]
Generating train split: 59081924 examples [54:18, 29770.61 examples/s]
Generating train split: 59086481 examples [54:18, 33295.40 examples/s]
Generating train split: 59092730 examples [54:18, 40420.33 examples/s]
Generating train split: 59097440 examples [54:19, 42145.52 examples/s]
Generating train split: 59102044 examples [54:19, 26931.16 examples/s]
Generating train split: 59105695 examples [54:19, 28418.39 examples/s]
Generating train split: 59110543 examples [54:19, 32721.56 examples/s]
Generating train split: 59114795 examples [54:19, 35019.06 examples/s]
Generating train split: 59120858 examples [54:19, 41302.82 examples/s]
Generating train split: 59125511 examples [54:20, 27731.65 examples/s]
Generating train split: 59129233 examples [54:21, 11271.54 examples/s]
Generating train split: 59131944 examples [54:21, 12214.03 examples/s]
Generating train split: 59135598 examples [54:21, 15038.52 examples/s]
Generating train split: 59138401 examples [54:21, 16851.81 examples/s]
Generating train split: 59141199 examples [54:21, 14317.41 examples/s]
Generating train split: 59143452 examples [54:21, 14398.95 examples/s]
Generating train split: 59146815 examples [54:21, 17656.43 examples/s]
Generating train split: 59153008 examples [54:22, 26295.66 examples/s]
Generating train split: 59156556 examples [54:22, 14272.22 examples/s]
Generating train split: 59160508 examples [54:22, 17700.42 examples/s]
Generating train split: 59163564 examples [54:22, 15196.95 examples/s]
Generating train split: 59166030 examples [54:23, 15274.12 examples/s]
Generating train split: 59172435 examples [54:23, 19382.16 examples/s]
Generating train split: 59175188 examples [54:23, 20690.94 examples/s]
Generating train split: 59177682 examples [54:23, 19180.20 examples/s]
Generating train split: 59179890 examples [54:23, 18405.80 examples/s]
Generating train split: 59181927 examples [54:23, 16099.64 examples/s]
Generating train split: 59184044 examples [54:24, 17075.51 examples/s]
Generating train split: 59185904 examples [54:24, 14751.12 examples/s]
Generating train split: 59187513 examples [54:24, 14551.76 examples/s]
Generating train split: 59189211 examples [54:24, 15095.88 examples/s]
Generating train split: 59190848 examples [54:24, 15397.71 examples/s]
Generating train split: 59192454 examples [54:24, 15173.91 examples/s]
Generating train split: 59194017 examples [54:24, 10019.15 examples/s]
Generating train split: 59196032 examples [54:25, 11975.06 examples/s]
Generating train split: 59197635 examples [54:25, 12594.52 examples/s]
Generating train split: 59199569 examples [54:25, 14181.42 examples/s]
Generating train split: 59202275 examples [54:25, 17261.81 examples/s]
Generating train split: 59204183 examples [54:25, 14275.48 examples/s]
Generating train split: 59205968 examples [54:25, 15097.93 examples/s]
Generating train split: 59207645 examples [54:25, 14412.04 examples/s]
Generating train split: 59209774 examples [54:25, 16118.93 examples/s]
Generating train split: 59215751 examples [54:25, 27539.43 examples/s]
Generating train split: 59222815 examples [54:26, 39268.34 examples/s]
Generating train split: 59227215 examples [54:26, 37008.75 examples/s]
Generating train split: 59231153 examples [54:26, 31325.00 examples/s]
Generating train split: 59234592 examples [54:26, 24740.70 examples/s]
Generating train split: 59237455 examples [54:26, 18149.50 examples/s]
Generating train split: 59239765 examples [54:27, 17792.95 examples/s]
Generating train split: 59242660 examples [54:27, 19809.95 examples/s]
Generating train split: 59244986 examples [54:27, 17077.19 examples/s]
Generating train split: 59246968 examples [54:27, 15691.98 examples/s]
Generating train split: 59255071 examples [54:27, 29021.92 examples/s]
Generating train split: 59258732 examples [54:27, 25208.23 examples/s]
Generating train split: 59261859 examples [54:27, 23855.47 examples/s]
Generating train split: 59264661 examples [54:28, 23114.46 examples/s]
Generating train split: 59267253 examples [54:28, 22886.58 examples/s]
Generating train split: 59269982 examples [54:28, 23873.70 examples/s]
Generating train split: 59272534 examples [54:28, 20263.51 examples/s]
Generating train split: 59274745 examples [54:28, 19880.81 examples/s]
Generating train split: 59276863 examples [54:28, 20142.29 examples/s]
Generating train split: 59278984 examples [54:28, 20259.47 examples/s]
Generating train split: 59281088 examples [54:28, 19218.12 examples/s]
Generating train split: 59283063 examples [54:29, 18757.64 examples/s]
Generating train split: 59284976 examples [54:29, 16660.52 examples/s]
Generating train split: 59286704 examples [54:29, 16308.68 examples/s]
Generating train split: 59288744 examples [54:29, 17354.60 examples/s]
Generating train split: 59290520 examples [54:29, 10526.45 examples/s]
Generating train split: 59291920 examples [54:29, 9719.60 examples/s] 
Generating train split: 59293141 examples [54:30, 6861.03 examples/s]
Generating train split: 59294107 examples [54:30, 7217.37 examples/s]
Generating train split: 59295048 examples [54:30, 6834.77 examples/s]
Generating train split: 59296836 examples [54:30, 8800.92 examples/s]
Generating train split: 59298455 examples [54:30, 10341.02 examples/s]
Generating train split: 59300080 examples [54:30, 11689.42 examples/s]
Generating train split: 59302999 examples [54:30, 15984.91 examples/s]
Generating train split: 59304832 examples [54:31, 16417.43 examples/s]
Generating train split: 59313408 examples [54:31, 35065.83 examples/s]
Generating train split: 59322090 examples [54:31, 49413.46 examples/s]
Generating train split: 59327380 examples [54:31, 25825.26 examples/s]
Generating train split: 59331453 examples [54:32, 16198.08 examples/s]
Generating train split: 59337677 examples [54:32, 21857.10 examples/s]
Generating train split: 59345820 examples [54:32, 30756.49 examples/s]
Generating train split: 59351078 examples [54:32, 20684.27 examples/s]
Generating train split: 59355089 examples [54:33, 21265.11 examples/s]
Generating train split: 59360108 examples [54:33, 25486.16 examples/s]
Generating train split: 59364073 examples [54:33, 25769.28 examples/s]
Generating train split: 59369705 examples [54:33, 31346.08 examples/s]
Generating train split: 59373873 examples [54:33, 24290.42 examples/s]
Generating train split: 59377846 examples [54:33, 26924.98 examples/s]
Generating train split: 59381372 examples [54:34, 19287.61 examples/s]
Generating train split: 59384150 examples [54:34, 14623.39 examples/s]
Generating train split: 59386336 examples [54:34, 14863.71 examples/s]
Generating train split: 59388346 examples [54:34, 15659.29 examples/s]
Generating train split: 59394276 examples [54:34, 23792.84 examples/s]
Generating train split: 59397465 examples [54:35, 18927.26 examples/s]
Generating train split: 59400050 examples [54:35, 18425.25 examples/s]
Generating train split: 59404389 examples [54:35, 23215.13 examples/s]
Generating train split: 59408810 examples [54:35, 27731.44 examples/s]
Generating train split: 59414447 examples [54:35, 28984.60 examples/s]
Generating train split: 59417744 examples [54:35, 19650.38 examples/s]
Generating train split: 59420352 examples [54:36, 19753.13 examples/s]
Generating train split: 59422791 examples [54:36, 20627.65 examples/s]
Generating train split: 59425229 examples [54:36, 20055.80 examples/s]
Generating train split: 59427489 examples [54:36, 14229.58 examples/s]
Generating train split: 59430926 examples [54:36, 17836.65 examples/s]
Generating train split: 59436925 examples [54:36, 22100.23 examples/s]
Generating train split: 59439447 examples [54:37, 18018.66 examples/s]
Generating train split: 59441550 examples [54:37, 14271.29 examples/s]
Generating train split: 59443257 examples [54:37, 14120.51 examples/s]
Generating train split: 59444864 examples [54:37, 9579.10 examples/s] 
Generating train split: 59450244 examples [54:38, 16171.18 examples/s]
Generating train split: 59458565 examples [54:38, 27936.60 examples/s]
Generating train split: 59462801 examples [54:38, 26198.25 examples/s]
Generating train split: 59466446 examples [54:38, 17364.04 examples/s]
Generating train split: 59473166 examples [54:38, 21466.45 examples/s]
Generating train split: 59476130 examples [54:39, 16502.78 examples/s]
Generating train split: 59478470 examples [54:39, 13008.95 examples/s]
Generating train split: 59480310 examples [54:39, 11878.06 examples/s]
Generating train split: 59483028 examples [54:39, 13953.59 examples/s]
Generating train split: 59484919 examples [54:40, 13414.46 examples/s]
Generating train split: 59489088 examples [54:40, 18360.74 examples/s]
Generating train split: 59495283 examples [54:40, 27071.69 examples/s]
Generating train split: 59499188 examples [54:40, 29695.40 examples/s]
Generating train split: 59502842 examples [54:40, 23467.01 examples/s]
Generating train split: 59505860 examples [54:40, 17102.84 examples/s]
Generating train split: 59508381 examples [54:41, 18423.39 examples/s]
Generating train split: 59510808 examples [54:41, 12387.46 examples/s]
Generating train split: 59517521 examples [54:41, 20519.16 examples/s]
Generating train split: 59520846 examples [54:41, 18822.74 examples/s]
Generating train split: 59525283 examples [54:41, 23199.88 examples/s]
Generating train split: 59528561 examples [54:42, 15426.11 examples/s]
Generating train split: 59532040 examples [54:42, 18278.77 examples/s]
Generating train split: 59534856 examples [54:42, 19812.76 examples/s]
Generating train split: 59538486 examples [54:42, 22870.40 examples/s]
Generating train split: 59541478 examples [54:43, 12249.53 examples/s]
Generating train split: 59543735 examples [54:43, 10868.37 examples/s]
Generating train split: 59546978 examples [54:43, 13746.81 examples/s]
Generating train split: 59549228 examples [54:43, 15068.43 examples/s]
Generating train split: 59551453 examples [54:43, 13651.80 examples/s]
Generating train split: 59553336 examples [54:44, 12507.01 examples/s]
Generating train split: 59557109 examples [54:44, 16882.31 examples/s]
Generating train split: 59559564 examples [54:44, 14384.59 examples/s]
Generating train split: 59561415 examples [54:44, 13178.00 examples/s]
Generating train split: 59563026 examples [54:44, 10777.14 examples/s]
Generating train split: 59565560 examples [54:44, 13278.54 examples/s]
Generating train split: 59570227 examples [54:45, 19896.22 examples/s]
Generating train split: 59572966 examples [54:45, 18901.52 examples/s]
Generating train split: 59575273 examples [54:45, 18503.51 examples/s]
Generating train split: 59577409 examples [54:45, 13728.43 examples/s]
Generating train split: 59579365 examples [54:45, 14814.02 examples/s]
Generating train split: 59581161 examples [54:45, 11400.47 examples/s]
Generating train split: 59582622 examples [54:46, 9736.33 examples/s] 
Generating train split: 59584104 examples [54:46, 10556.23 examples/s]
Generating train split: 59585392 examples [54:46, 8189.70 examples/s] 
Generating train split: 59586902 examples [54:46, 9297.92 examples/s]
Generating train split: 59588063 examples [54:46, 7483.76 examples/s]
Generating train split: 59589586 examples [54:47, 8856.62 examples/s]
Generating train split: 59590709 examples [54:47, 7892.32 examples/s]
Generating train split: 59591668 examples [54:47, 6592.65 examples/s]
Generating train split: 59593458 examples [54:47, 8544.96 examples/s]
Generating train split: 59594520 examples [54:47, 8620.66 examples/s]
Generating train split: 59595796 examples [54:47, 9527.52 examples/s]
Generating train split: 59597694 examples [54:47, 11730.10 examples/s]
Generating train split: 59599326 examples [54:48, 12787.08 examples/s]
Generating train split: 59600726 examples [54:48, 11176.84 examples/s]
Generating train split: 59602600 examples [54:48, 12991.38 examples/s]
Generating train split: 59604020 examples [54:48, 12293.54 examples/s]
Generating train split: 59605345 examples [54:48, 7187.29 examples/s] 
Generating train split: 59606451 examples [54:48, 7849.80 examples/s]
Generating train split: 59607677 examples [54:48, 8713.66 examples/s]
Generating train split: 59608988 examples [54:49, 9246.61 examples/s]
Generating train split: 59610520 examples [54:49, 10557.29 examples/s]
Generating train split: 59612272 examples [54:49, 12157.97 examples/s]
Generating train split: 59614254 examples [54:49, 14124.05 examples/s]
Generating train split: 59615793 examples [54:49, 11008.89 examples/s]
Generating train split: 59617086 examples [54:49, 10954.03 examples/s]
Generating train split: 59618317 examples [54:49, 10775.77 examples/s]
Generating train split: 59619496 examples [54:49, 10590.92 examples/s]
Generating train split: 59620619 examples [54:50, 9525.43 examples/s] 
Generating train split: 59621632 examples [54:50, 9547.10 examples/s]
Generating train split: 59622647 examples [54:50, 9512.30 examples/s]
Generating train split: 59624021 examples [54:50, 10269.09 examples/s]
Generating train split: 59625079 examples [54:50, 7804.58 examples/s] 
Generating train split: 59625959 examples [54:50, 7630.80 examples/s]
Generating train split: 59626788 examples [54:51, 6330.06 examples/s]
Generating train split: 59627656 examples [54:51, 6825.35 examples/s]
Generating train split: 59628786 examples [54:51, 7737.01 examples/s]
Generating train split: 59630420 examples [54:51, 9769.09 examples/s]
Generating train split: 59631484 examples [54:51, 9293.32 examples/s]
Generating train split: 59633081 examples [54:51, 10998.51 examples/s]
Generating train split: 59634862 examples [54:51, 12808.64 examples/s]
Generating train split: 59636224 examples [54:51, 11315.97 examples/s]
Generating train split: 59637726 examples [54:51, 12240.48 examples/s]
Generating train split: 59639064 examples [54:52, 12299.20 examples/s]
Generating train split: 59641225 examples [54:52, 14831.36 examples/s]
Generating train split: 59644300 examples [54:52, 19283.16 examples/s]
Generating train split: 59650896 examples [54:52, 31283.51 examples/s]
Generating train split: 59654030 examples [54:52, 21628.71 examples/s]
Generating train split: 59656820 examples [54:52, 22988.44 examples/s]
Generating train split: 59659961 examples [54:52, 24971.23 examples/s]
Generating train split: 59663098 examples [54:52, 26585.16 examples/s]
Generating train split: 59666886 examples [54:53, 29251.05 examples/s]
Generating train split: 59670000 examples [54:53, 18630.58 examples/s]
Generating train split: 59672704 examples [54:53, 20275.96 examples/s]
Generating train split: 59675836 examples [54:53, 22683.07 examples/s]
Generating train split: 59679508 examples [54:53, 25742.71 examples/s]
Generating train split: 59682470 examples [54:53, 17725.59 examples/s]
Generating train split: 59684841 examples [54:54, 17969.79 examples/s]
Generating train split: 59689596 examples [54:54, 24103.02 examples/s]
Generating train split: 59698337 examples [54:54, 38575.22 examples/s]
Generating train split: 59706218 examples [54:54, 48479.29 examples/s]
Generating train split: 59711883 examples [54:54, 25047.18 examples/s]
Generating train split: 59716190 examples [54:55, 19168.66 examples/s]
Generating train split: 59719542 examples [54:55, 19550.84 examples/s]
Generating train split: 59727514 examples [54:55, 28539.93 examples/s]
Generating train split: 59736053 examples [54:55, 38407.63 examples/s]
Generating train split: 59741708 examples [54:55, 31778.08 examples/s]
Generating train split: 59750815 examples [54:55, 42318.16 examples/s]
Generating train split: 59759858 examples [54:56, 52059.24 examples/s]
Generating train split: 59766741 examples [54:56, 42400.54 examples/s]
Generating train split: 59772698 examples [54:56, 45759.79 examples/s]
Generating train split: 59778457 examples [54:56, 31381.94 examples/s]
Generating train split: 59782990 examples [54:56, 31338.21 examples/s]
Generating train split: 59790676 examples [54:56, 39651.33 examples/s]
Generating train split: 59797803 examples [54:57, 46192.40 examples/s]
Generating train split: 59803580 examples [54:57, 47847.78 examples/s]
Generating train split: 59812293 examples [54:57, 57350.87 examples/s]
Generating train split: 59818842 examples [54:57, 28079.50 examples/s]
Generating train split: 59823799 examples [54:57, 28694.11 examples/s]
Generating train split: 59828195 examples [54:58, 26445.46 examples/s]
Generating train split: 59831904 examples [54:58, 23211.78 examples/s]
Generating train split: 59834982 examples [54:58, 21701.45 examples/s]
Generating train split: 59837655 examples [54:59, 11451.58 examples/s]
Generating train split: 59839645 examples [55:00, 6771.38 examples/s] 
Generating train split: 59841108 examples [55:00, 6246.95 examples/s]
Generating train split: 59842265 examples [55:00, 6146.89 examples/s]
Generating train split: 59843245 examples [55:00, 5987.36 examples/s]
Generating train split: 59844089 examples [55:00, 6181.74 examples/s]
Generating train split: 59844906 examples [55:01, 6249.11 examples/s]
Generating train split: 59846240 examples [55:01, 7409.62 examples/s]
Generating train split: 59848091 examples [55:01, 9517.01 examples/s]
Generating train split: 59850323 examples [55:01, 12234.45 examples/s]
Generating train split: 59852404 examples [55:01, 14232.93 examples/s]
Generating train split: 59854090 examples [55:01, 14397.77 examples/s]
Generating train split: 59855719 examples [55:01, 14425.18 examples/s]
Generating train split: 59857295 examples [55:01, 12133.48 examples/s]
Generating train split: 59859412 examples [55:02, 14256.34 examples/s]
Generating train split: 59862117 examples [55:02, 17470.24 examples/s]
Generating train split: 59865203 examples [55:02, 21006.51 examples/s]
Generating train split: 59867823 examples [55:02, 17862.69 examples/s]
Generating train split: 59869819 examples [55:02, 15625.56 examples/s]
Generating train split: 59872054 examples [55:02, 17125.40 examples/s]
Generating train split: 59874382 examples [55:02, 18613.79 examples/s]
Generating train split: 59878761 examples [55:02, 25044.82 examples/s]
Generating train split: 59881482 examples [55:03, 14720.53 examples/s]
Generating train split: 59885498 examples [55:03, 16138.54 examples/s]
Generating train split: 59887562 examples [55:03, 16036.79 examples/s]
Generating train split: 59890499 examples [55:03, 18559.98 examples/s]
Generating train split: 59892710 examples [55:04, 12377.67 examples/s]
Generating train split: 59894946 examples [55:04, 14002.41 examples/s]
Generating train split: 59896826 examples [55:04, 10717.60 examples/s]
Generating train split: 59898333 examples [55:04, 9783.81 examples/s] 
Generating train split: 59900505 examples [55:04, 11769.91 examples/s]
Generating train split: 59902152 examples [55:04, 12658.84 examples/s]
Generating train split: 59903734 examples [55:05, 9411.93 examples/s] 
Generating train split: 59908237 examples [55:05, 15758.79 examples/s]
Generating train split: 59917759 examples [55:05, 31881.07 examples/s]
Generating train split: 59923570 examples [55:05, 37759.38 examples/s]
Generating train split: 59928410 examples [55:05, 25807.39 examples/s]
Generating train split: 59932234 examples [55:06, 15911.20 examples/s]
Generating train split: 59935140 examples [55:06, 15415.27 examples/s]
Generating train split: 59937589 examples [55:06, 13715.84 examples/s]
Generating train split: 59939589 examples [55:06, 14463.73 examples/s]
Generating train split: 59941552 examples [55:07, 12887.32 examples/s]
Generating train split: 59943209 examples [55:07, 11099.41 examples/s]
Generating train split: 59944878 examples [55:07, 12008.14 examples/s]
Generating train split: 59946340 examples [55:07, 10603.19 examples/s]
Generating train split: 59949483 examples [55:07, 14472.07 examples/s]
Generating train split: 59951301 examples [55:07, 12522.15 examples/s]
Generating train split: 59952840 examples [55:08, 12699.25 examples/s]
Generating train split: 59954320 examples [55:08, 12692.03 examples/s]
Generating train split: 59955762 examples [55:08, 13078.29 examples/s]
Generating train split: 59960302 examples [55:08, 21027.36 examples/s]
Generating train split: 59968756 examples [55:08, 37535.58 examples/s]
Generating train split: 59973483 examples [55:08, 38304.69 examples/s]
Generating train split: 59977614 examples [55:08, 28813.56 examples/s]
Generating train split: 59981051 examples [55:09, 23924.83 examples/s]
Generating train split: 59983930 examples [55:09, 20085.79 examples/s]
Generating train split: 59986339 examples [55:09, 20500.82 examples/s]
Generating train split: 59989695 examples [55:09, 23176.52 examples/s]
Generating train split: 59992339 examples [55:09, 19994.73 examples/s]
Generating train split: 59994622 examples [55:09, 17122.38 examples/s]
Generating train split: 59996576 examples [55:09, 16025.27 examples/s]
Generating train split: 59998337 examples [55:10, 15061.30 examples/s]
Generating train split: 59999978 examples [55:10, 15348.92 examples/s]
Generating train split: 60001596 examples [55:10, 13239.96 examples/s]
Generating train split: 60003808 examples [55:10, 15193.77 examples/s]
Generating train split: 60005463 examples [55:10, 14242.85 examples/s]
Generating train split: 60007510 examples [55:10, 15546.97 examples/s]
Generating train split: 60009509 examples [55:10, 16599.20 examples/s]
Generating train split: 60011260 examples [55:10, 15062.32 examples/s]
Generating train split: 60014034 examples [55:11, 18251.49 examples/s]
Generating train split: 60015971 examples [55:11, 15834.90 examples/s]
Generating train split: 60018973 examples [55:11, 19288.26 examples/s]
Generating train split: 60021076 examples [55:11, 16841.09 examples/s]
Generating train split: 60023827 examples [55:11, 19397.62 examples/s]
Generating train split: 60027105 examples [55:11, 22797.98 examples/s]
Generating train split: 60029570 examples [55:11, 19057.09 examples/s]
Generating train split: 60031707 examples [55:12, 14504.64 examples/s]
Generating train split: 60035423 examples [55:12, 19050.12 examples/s]
Generating train split: 60039008 examples [55:12, 22773.16 examples/s]
Generating train split: 60043969 examples [55:12, 29243.80 examples/s]
Generating train split: 60048588 examples [55:12, 33196.02 examples/s]
Generating train split: 60052284 examples [55:12, 27042.73 examples/s]
Generating train split: 60055424 examples [55:12, 27399.60 examples/s]
Generating train split: 60058490 examples [55:12, 27547.19 examples/s]
Generating train split: 60061722 examples [55:13, 28748.86 examples/s]
Generating train split: 60066179 examples [55:13, 32769.20 examples/s]
Generating train split: 60069630 examples [55:13, 24522.41 examples/s]
Generating train split: 60073083 examples [55:13, 26741.35 examples/s]
Generating train split: 60076123 examples [55:13, 25439.50 examples/s]
Generating train split: 60078930 examples [55:13, 25397.94 examples/s]
Generating train split: 60081649 examples [55:13, 22626.09 examples/s]
Generating train split: 60084079 examples [55:14, 21502.66 examples/s]
Generating train split: 60086366 examples [55:14, 21796.53 examples/s]
Generating train split: 60088635 examples [55:14, 19747.24 examples/s]
Generating train split: 60092440 examples [55:14, 24186.25 examples/s]
Generating train split: 60100497 examples [55:14, 38867.60 examples/s]
Generating train split: 60105459 examples [55:14, 39992.75 examples/s]
Generating train split: 60109703 examples [55:14, 35035.68 examples/s]
Generating train split: 60113469 examples [55:15, 22287.08 examples/s]
Generating train split: 60116436 examples [55:15, 23010.09 examples/s]
Generating train split: 60119470 examples [55:15, 24291.70 examples/s]
Generating train split: 60122342 examples [55:15, 24296.14 examples/s]
Generating train split: 60125099 examples [55:15, 13287.69 examples/s]
Generating train split: 60127190 examples [55:16, 12389.50 examples/s]
Generating train split: 60129245 examples [55:16, 13169.15 examples/s]
Generating train split: 60130979 examples [55:16, 13207.91 examples/s]
Generating train split: 60132593 examples [55:16, 9386.54 examples/s] 
Generating train split: 60133868 examples [55:16, 9636.92 examples/s]
Generating train split: 60135081 examples [55:16, 9424.17 examples/s]
Generating train split: 60136203 examples [55:17, 8936.09 examples/s]
Generating train split: 60137216 examples [55:17, 7133.81 examples/s]
Generating train split: 60139428 examples [55:17, 9686.71 examples/s]
Generating train split: 60142229 examples [55:17, 13378.79 examples/s]
Generating train split: 60144815 examples [55:17, 16189.62 examples/s]
Generating train split: 60146762 examples [55:18, 10815.37 examples/s]
Generating train split: 60149261 examples [55:18, 13332.03 examples/s]
Generating train split: 60151070 examples [55:18, 8165.21 examples/s] 
Generating train split: 60152965 examples [55:18, 9705.23 examples/s]
Generating train split: 60156316 examples [55:18, 13745.13 examples/s]
Generating train split: 60159716 examples [55:18, 17684.04 examples/s]
Generating train split: 60162187 examples [55:19, 13836.95 examples/s]
Generating train split: 60164185 examples [55:19, 10535.25 examples/s]
Generating train split: 60166797 examples [55:19, 12954.78 examples/s]
Generating train split: 60170082 examples [55:19, 16563.12 examples/s]
Generating train split: 60173434 examples [55:19, 19996.61 examples/s]
Generating train split: 60176041 examples [55:20, 10801.89 examples/s]
Generating train split: 60178013 examples [55:20, 11046.90 examples/s]
Generating train split: 60181005 examples [55:20, 13981.83 examples/s]
Generating train split: 60183125 examples [55:20, 11887.90 examples/s]
Generating train split: 60187170 examples [55:20, 16683.64 examples/s]
Generating train split: 60191108 examples [55:21, 21065.19 examples/s]
Generating train split: 60196782 examples [55:21, 28151.74 examples/s]
Generating train split: 60200337 examples [55:21, 21230.92 examples/s]
Generating train split: 60204098 examples [55:21, 24347.88 examples/s]
Generating train split: 60207248 examples [55:21, 16371.94 examples/s]
Generating train split: 60209706 examples [55:22, 14763.04 examples/s]
Generating train split: 60211755 examples [55:22, 13605.71 examples/s]
Generating train split: 60213824 examples [55:22, 14724.84 examples/s]
Generating train split: 60215663 examples [55:22, 13413.52 examples/s]
Generating train split: 60217270 examples [55:22, 13784.59 examples/s]
Generating train split: 60218850 examples [55:22, 12466.62 examples/s]
Generating train split: 60221428 examples [55:22, 15275.60 examples/s]
Generating train split: 60223326 examples [55:23, 16087.20 examples/s]
Generating train split: 60225115 examples [55:23, 12790.05 examples/s]
Generating train split: 60227257 examples [55:23, 14638.52 examples/s]
Generating train split: 60230765 examples [55:23, 19417.77 examples/s]
Generating train split: 60233551 examples [55:23, 21530.50 examples/s]
Generating train split: 60238654 examples [55:23, 29305.91 examples/s]
Generating train split: 60242238 examples [55:23, 30543.51 examples/s]
Generating train split: 60245493 examples [55:24, 11090.35 examples/s]
Generating train split: 60247903 examples [55:24, 12413.79 examples/s]
Generating train split: 60250204 examples [55:24, 13498.75 examples/s]
Generating train split: 60252367 examples [55:24, 13977.32 examples/s]
Generating train split: 60255757 examples [55:25, 17658.63 examples/s]
Generating train split: 60258810 examples [55:25, 19503.14 examples/s]
Generating train split: 60261268 examples [55:25, 12544.98 examples/s]
Generating train split: 60263173 examples [55:25, 12639.79 examples/s]
Generating train split: 60266790 examples [55:25, 16799.08 examples/s]
Generating train split: 60270667 examples [55:25, 21226.89 examples/s]
Generating train split: 60273442 examples [55:26, 18566.26 examples/s]
Generating train split: 60275808 examples [55:26, 14525.20 examples/s]
Generating train split: 60279904 examples [55:26, 19277.13 examples/s]
Generating train split: 60282476 examples [55:26, 19043.64 examples/s]
Generating train split: 60284839 examples [55:26, 13381.50 examples/s]
Generating train split: 60286695 examples [55:27, 14165.67 examples/s]
Generating train split: 60289002 examples [55:27, 15878.36 examples/s]
Generating train split: 60295387 examples [55:27, 26246.02 examples/s]
Generating train split: 60298696 examples [55:27, 22302.02 examples/s]
Generating train split: 60301500 examples [55:27, 17598.87 examples/s]
Generating train split: 60304461 examples [55:27, 19819.56 examples/s]
Generating train split: 60309351 examples [55:27, 25898.09 examples/s]
Generating train split: 60312556 examples [55:28, 17631.75 examples/s]
Generating train split: 60315481 examples [55:28, 19653.45 examples/s]
Generating train split: 60319437 examples [55:28, 23624.95 examples/s]
Generating train split: 60322482 examples [55:28, 22095.14 examples/s]
Generating train split: 60325179 examples [55:28, 17272.77 examples/s]
Generating train split: 60327382 examples [55:29, 15674.18 examples/s]
Generating train split: 60329282 examples [55:29, 14830.64 examples/s]
Generating train split: 60330996 examples [55:29, 13625.57 examples/s]
Generating train split: 60332507 examples [55:29, 13371.53 examples/s]
Generating train split: 60339605 examples [55:29, 25787.11 examples/s]
Generating train split: 60343106 examples [55:29, 27510.88 examples/s]
Generating train split: 60346280 examples [55:30, 18489.16 examples/s]
Generating train split: 60348811 examples [55:30, 15159.20 examples/s]
Generating train split: 60350875 examples [55:30, 15605.50 examples/s]
Generating train split: 60352839 examples [55:30, 12185.54 examples/s]
Generating train split: 60354430 examples [55:30, 12268.50 examples/s]
Generating train split: 60361898 examples [55:30, 23957.14 examples/s]
Generating train split: 60367878 examples [55:31, 31110.34 examples/s]
Generating train split: 60371867 examples [55:31, 15997.20 examples/s]
Generating train split: 60375766 examples [55:31, 19138.16 examples/s]
Generating train split: 60380741 examples [55:31, 24128.64 examples/s]
Generating train split: 60385677 examples [55:31, 28363.79 examples/s]
Generating train split: 60389677 examples [55:32, 20107.33 examples/s]
Generating train split: 60392814 examples [55:32, 21497.90 examples/s]
Generating train split: 60395981 examples [55:32, 23386.75 examples/s]
Generating train split: 60399056 examples [55:32, 21089.50 examples/s]
Generating train split: 60401708 examples [55:32, 16364.15 examples/s]
Generating train split: 60404705 examples [55:33, 18742.80 examples/s]
Generating train split: 60408245 examples [55:33, 22081.48 examples/s]
Generating train split: 60411639 examples [55:33, 24503.37 examples/s]
Generating train split: 60414537 examples [55:33, 12832.12 examples/s]
Generating train split: 60417514 examples [55:33, 15313.76 examples/s]
Generating train split: 60419953 examples [55:34, 12457.66 examples/s]
Generating train split: 60422840 examples [55:34, 14934.83 examples/s]
Generating train split: 60425047 examples [55:34, 15100.83 examples/s]
Generating train split: 60427071 examples [55:34, 13876.99 examples/s]
Generating train split: 60428833 examples [55:34, 14546.24 examples/s]
Generating train split: 60430572 examples [55:34, 10898.37 examples/s]
Generating train split: 60434023 examples [55:35, 15157.07 examples/s]
Generating train split: 60436039 examples [55:35, 15465.38 examples/s]
Generating train split: 60437943 examples [55:35, 12292.03 examples/s]
Generating train split: 60440527 examples [55:35, 14855.25 examples/s]
Generating train split: 60442648 examples [55:35, 15819.90 examples/s]
Generating train split: 60444530 examples [55:35, 13539.04 examples/s]
Generating train split: 60446849 examples [55:35, 15580.58 examples/s]
Generating train split: 60448992 examples [55:36, 16934.22 examples/s]
Generating train split: 60452393 examples [55:36, 21178.74 examples/s]
Generating train split: 60456321 examples [55:36, 20615.40 examples/s]
Generating train split: 60458730 examples [55:36, 21297.00 examples/s]
Generating train split: 60461016 examples [55:36, 17459.97 examples/s]
Generating train split: 60462961 examples [55:36, 14305.79 examples/s]
Generating train split: 60464731 examples [55:36, 14987.93 examples/s]
Generating train split: 60467364 examples [55:37, 17326.97 examples/s]
Generating train split: 60469287 examples [55:37, 13021.54 examples/s]
Generating train split: 60471072 examples [55:37, 13978.01 examples/s]
Generating train split: 60474445 examples [55:37, 18372.15 examples/s]
Generating train split: 60478291 examples [55:37, 22983.03 examples/s]
Generating train split: 60480908 examples [55:37, 15779.44 examples/s]
Generating train split: 60484523 examples [55:38, 19731.97 examples/s]
Generating train split: 60488040 examples [55:38, 23048.44 examples/s]
Generating train split: 60491220 examples [55:38, 25063.59 examples/s]
Generating train split: 60494150 examples [55:38, 16452.53 examples/s]
Generating train split: 60497027 examples [55:38, 18717.38 examples/s]
Generating train split: 60499514 examples [55:38, 17886.71 examples/s]
Generating train split: 60501741 examples [55:39, 13743.69 examples/s]
Generating train split: 60505365 examples [55:39, 17748.87 examples/s]
Generating train split: 60508493 examples [55:39, 20489.65 examples/s]
Generating train split: 60511059 examples [55:39, 15361.93 examples/s]
Generating train split: 60513237 examples [55:39, 16550.18 examples/s]
Generating train split: 60516841 examples [55:39, 20641.32 examples/s]
Generating train split: 60523614 examples [55:39, 31498.25 examples/s]
Generating train split: 60528286 examples [55:39, 35260.71 examples/s]
Generating train split: 60532359 examples [55:40, 22412.90 examples/s]
Generating train split: 60535565 examples [55:40, 20289.66 examples/s]
Generating train split: 60538285 examples [55:40, 14029.33 examples/s]
Generating train split: 60540394 examples [55:41, 13436.50 examples/s]
Generating train split: 60542220 examples [55:41, 12486.04 examples/s]
Generating train split: 60545040 examples [55:41, 15057.15 examples/s]
Generating train split: 60547004 examples [55:41, 15903.30 examples/s]
Generating train split: 60550539 examples [55:41, 20043.37 examples/s]
Generating train split: 60552969 examples [55:41, 12801.45 examples/s]
Generating train split: 60554874 examples [55:42, 13032.76 examples/s]
Generating train split: 60556613 examples [55:42, 10338.48 examples/s]
Generating train split: 60558016 examples [55:42, 9521.81 examples/s] 
Generating train split: 60560889 examples [55:42, 12778.54 examples/s]
Generating train split: 60563375 examples [55:42, 14606.35 examples/s]
Generating train split: 60565201 examples [55:43, 8201.60 examples/s] 
Generating train split: 60566780 examples [55:43, 9237.09 examples/s]
Generating train split: 60569969 examples [55:43, 12982.44 examples/s]
Generating train split: 60573588 examples [55:43, 17214.04 examples/s]
Generating train split: 60575982 examples [55:43, 13476.36 examples/s]
Generating train split: 60577933 examples [55:44, 9784.16 examples/s] 
Generating train split: 60579679 examples [55:44, 10911.79 examples/s]
Generating train split: 60583079 examples [55:44, 14922.28 examples/s]
Generating train split: 60587381 examples [55:44, 20507.74 examples/s]
Generating train split: 60590169 examples [55:45, 9597.42 examples/s] 
Generating train split: 60592239 examples [55:45, 10658.05 examples/s]
Generating train split: 60595159 examples [55:45, 13320.38 examples/s]
Generating train split: 60598177 examples [55:45, 16189.64 examples/s]
Generating train split: 60600658 examples [55:45, 16720.08 examples/s]
Generating train split: 60602949 examples [55:45, 13952.72 examples/s]
Generating train split: 60604843 examples [55:46, 12582.09 examples/s]
Generating train split: 60606457 examples [55:46, 11918.73 examples/s]
Generating train split: 60609026 examples [55:46, 14550.58 examples/s]
Generating train split: 60610803 examples [55:46, 15098.14 examples/s]
Generating train split: 60612566 examples [55:46, 14511.53 examples/s]
Generating train split: 60614193 examples [55:46, 12980.17 examples/s]
Generating train split: 60615637 examples [55:46, 13076.00 examples/s]
Generating train split: 60617045 examples [55:47, 12967.56 examples/s]
Generating train split: 60619417 examples [55:47, 15596.64 examples/s]
Generating train split: 60621079 examples [55:47, 8915.62 examples/s] 
Generating train split: 60622366 examples [55:47, 9119.50 examples/s]
Generating train split: 60623562 examples [55:47, 8635.27 examples/s]
Generating train split: 60626320 examples [55:47, 12353.17 examples/s]
Generating train split: 60628546 examples [55:48, 14518.38 examples/s]
Generating train split: 60630312 examples [55:48, 12186.43 examples/s]
Generating train split: 60633623 examples [55:48, 16652.91 examples/s]
Generating train split: 60636328 examples [55:48, 19069.48 examples/s]
Generating train split: 60638568 examples [55:48, 17575.27 examples/s]
Generating train split: 60640575 examples [55:48, 16521.36 examples/s]
Generating train split: 60642407 examples [55:48, 12722.06 examples/s]
Generating train split: 60644231 examples [55:49, 13769.66 examples/s]
Generating train split: 60646006 examples [55:49, 14660.85 examples/s]
Generating train split: 60650033 examples [55:49, 20377.34 examples/s]
Generating train split: 60652295 examples [55:49, 13271.03 examples/s]
Generating train split: 60654087 examples [55:49, 11491.70 examples/s]
Generating train split: 60655575 examples [55:50, 8223.46 examples/s] 
Generating train split: 60657268 examples [55:50, 9501.77 examples/s]
Generating train split: 60659613 examples [55:50, 11922.63 examples/s]
Generating train split: 60661241 examples [55:50, 12774.96 examples/s]
Generating train split: 60664021 examples [55:50, 16076.66 examples/s]
Generating train split: 60665994 examples [55:50, 14951.66 examples/s]
Generating train split: 60668556 examples [55:50, 17420.88 examples/s]
Generating train split: 60673081 examples [55:50, 24343.64 examples/s]
Generating train split: 60677818 examples [55:51, 30090.82 examples/s]
Generating train split: 60681131 examples [55:51, 22776.30 examples/s]
Generating train split: 60684292 examples [55:51, 24687.71 examples/s]
Generating train split: 60687149 examples [55:51, 22947.14 examples/s]
Generating train split: 60690576 examples [55:51, 25578.21 examples/s]
Generating train split: 60693414 examples [55:51, 18557.57 examples/s]
Generating train split: 60695715 examples [55:52, 18125.33 examples/s]
Generating train split: 60701785 examples [55:52, 27144.11 examples/s]
Generating train split: 60709442 examples [55:52, 38618.65 examples/s]
Generating train split: 60715095 examples [55:52, 43067.50 examples/s]
Generating train split: 60720016 examples [55:52, 43331.58 examples/s]
Generating train split: 60724778 examples [55:52, 28895.15 examples/s]
Generating train split: 60728597 examples [55:52, 26804.01 examples/s]
Generating train split: 60737187 examples [55:53, 38509.38 examples/s]
Generating train split: 60744152 examples [55:53, 45213.66 examples/s]
Generating train split: 60749646 examples [55:53, 26714.58 examples/s]
Generating train split: 60753875 examples [55:53, 24526.38 examples/s]
Generating train split: 60761871 examples [55:53, 27354.63 examples/s]
Generating train split: 60765353 examples [55:54, 21450.35 examples/s]
Generating train split: 60768147 examples [55:54, 22168.74 examples/s]
Generating train split: 60771389 examples [55:54, 20607.94 examples/s]
Generating train split: 60773801 examples [55:54, 15803.31 examples/s]
Generating train split: 60775732 examples [55:55, 14044.72 examples/s]
Generating train split: 60777943 examples [55:55, 15334.94 examples/s]
Generating train split: 60779749 examples [55:55, 13228.54 examples/s]
Generating train split: 60782629 examples [55:55, 16052.72 examples/s]
Generating train split: 60784560 examples [55:55, 13176.29 examples/s]
Generating train split: 60786273 examples [55:55, 13670.86 examples/s]
Generating train split: 60789260 examples [55:55, 17053.68 examples/s]
Generating train split: 60796817 examples [55:56, 30498.27 examples/s]
Generating train split: 60800489 examples [55:56, 30619.07 examples/s]
Generating train split: 60804574 examples [55:56, 32927.87 examples/s]
Generating train split: 60808215 examples [55:56, 22306.25 examples/s]
Generating train split: 60811135 examples [55:56, 17950.33 examples/s]
Generating train split: 60813516 examples [55:57, 15820.37 examples/s]
Generating train split: 60816071 examples [55:57, 17507.13 examples/s]
Generating train split: 60818241 examples [55:57, 11342.61 examples/s]
Generating train split: 60819921 examples [55:57, 10829.34 examples/s]
Generating train split: 60821370 examples [55:57, 10769.82 examples/s]
Generating train split: 60822702 examples [55:58, 9384.98 examples/s] 
Generating train split: 60824376 examples [55:58, 10364.72 examples/s]
Generating train split: 60825888 examples [55:58, 11264.73 examples/s]
Generating train split: 60827199 examples [55:58, 9981.03 examples/s] 
Generating train split: 60828329 examples [55:58, 9096.99 examples/s]
Generating train split: 60830140 examples [55:58, 10766.90 examples/s]
Generating train split: 60831483 examples [55:58, 11286.01 examples/s]
Generating train split: 60832712 examples [55:58, 10942.12 examples/s]
Generating train split: 60833878 examples [55:59, 10538.02 examples/s]
Generating train split: 60834981 examples [55:59, 9256.99 examples/s] 
Generating train split: 60837592 examples [55:59, 13264.21 examples/s]
Generating train split: 60839064 examples [55:59, 13250.59 examples/s]
Generating train split: 60840495 examples [55:59, 10477.18 examples/s]
Generating train split: 60842664 examples [55:59, 12921.39 examples/s]
Generating train split: 60844325 examples [55:59, 13760.75 examples/s]
Generating train split: 60846214 examples [55:59, 15068.09 examples/s]
Generating train split: 60854429 examples [56:00, 32999.12 examples/s]
Generating train split: 60861950 examples [56:00, 44658.58 examples/s]
Generating train split: 60866729 examples [56:00, 32644.24 examples/s]
Generating train split: 60870681 examples [56:01, 16354.14 examples/s]
Generating train split: 60873651 examples [56:01, 15090.12 examples/s]
Generating train split: 60876086 examples [56:01, 15013.93 examples/s]
Generating train split: 60881015 examples [56:01, 20219.41 examples/s]
Generating train split: 60888789 examples [56:01, 30471.84 examples/s]
Generating train split: 60893217 examples [56:01, 28446.56 examples/s]
Generating train split: 60897033 examples [56:02, 25576.16 examples/s]
Generating train split: 60900301 examples [56:02, 25141.95 examples/s]
Generating train split: 60903306 examples [56:02, 22538.01 examples/s]
Generating train split: 60905913 examples [56:02, 22046.13 examples/s]
Generating train split: 60908351 examples [56:02, 19140.21 examples/s]
Generating train split: 60910460 examples [56:02, 18329.01 examples/s]
Generating train split: 60912425 examples [56:02, 18605.87 examples/s]
Generating train split: 60914394 examples [56:02, 18243.72 examples/s]
Generating train split: 60917736 examples [56:03, 21968.11 examples/s]
Generating train split: 60920061 examples [56:03, 19654.35 examples/s]
Generating train split: 60923181 examples [56:03, 22497.93 examples/s]
Generating train split: 60925641 examples [56:03, 22795.10 examples/s]
Generating train split: 60928030 examples [56:03, 22485.23 examples/s]
Generating train split: 60930358 examples [56:03, 20094.06 examples/s]
Generating train split: 60937932 examples [56:03, 34339.52 examples/s]
Generating train split: 60944833 examples [56:03, 43623.80 examples/s]
Generating train split: 60949534 examples [56:04, 36897.03 examples/s]
Generating train split: 60953624 examples [56:04, 21631.64 examples/s]
Generating train split: 60956789 examples [56:04, 23075.76 examples/s]
Generating train split: 60959905 examples [56:04, 23497.26 examples/s]
Generating train split: 60962833 examples [56:04, 19332.94 examples/s]
Generating train split: 60965259 examples [56:05, 18437.68 examples/s]
Generating train split: 60968458 examples [56:05, 21077.55 examples/s]
Generating train split: 60971258 examples [56:05, 22584.85 examples/s]
Generating train split: 60973834 examples [56:05, 17955.51 examples/s]
Generating train split: 60975983 examples [56:05, 18511.23 examples/s]
Generating train split: 60978100 examples [56:05, 17176.31 examples/s]
Generating train split: 60980591 examples [56:05, 18785.95 examples/s]
Generating train split: 60982652 examples [56:06, 13316.79 examples/s]
Generating train split: 60984422 examples [56:06, 14161.75 examples/s]
Generating train split: 60986196 examples [56:06, 14886.85 examples/s]
Generating train split: 60987910 examples [56:06, 14444.22 examples/s]
Generating train split: 60989831 examples [56:06, 15583.27 examples/s]
Generating train split: 60991900 examples [56:06, 16332.20 examples/s]
Generating train split: 60993638 examples [56:06, 14610.31 examples/s]
Generating train split: 60996461 examples [56:06, 17957.35 examples/s]
Generating train split: 60998396 examples [56:07, 10124.40 examples/s]
Generating train split: 61001151 examples [56:07, 13082.61 examples/s]
Generating train split: 61003229 examples [56:07, 14493.75 examples/s]
Generating train split: 61005152 examples [56:07, 11987.60 examples/s]
Generating train split: 61007440 examples [56:07, 14089.77 examples/s]
Generating train split: 61009236 examples [56:08, 13496.73 examples/s]
Generating train split: 61010856 examples [56:08, 13146.93 examples/s]
Generating train split: 61015084 examples [56:08, 19703.58 examples/s]
Generating train split: 61018211 examples [56:08, 22504.68 examples/s]
Generating train split: 61021867 examples [56:08, 26126.10 examples/s]
Generating train split: 61026642 examples [56:08, 31929.79 examples/s]
Generating train split: 61030098 examples [56:08, 27147.12 examples/s]
Generating train split: 61033119 examples [56:08, 27417.27 examples/s]
Generating train split: 61036077 examples [56:08, 26917.14 examples/s]
Generating train split: 61040362 examples [56:09, 30956.83 examples/s]
Generating train split: 61045655 examples [56:09, 36888.93 examples/s]
Generating train split: 61049518 examples [56:09, 35041.45 examples/s]
Generating train split: 61054812 examples [56:09, 39912.69 examples/s]
Generating train split: 61062405 examples [56:09, 49980.17 examples/s]
Generating train split: 61069238 examples [56:09, 55211.50 examples/s]
Generating train split: 61074908 examples [56:10, 30183.24 examples/s]
Generating train split: 61079314 examples [56:10, 29815.88 examples/s]
Generating train split: 61083260 examples [56:10, 18279.70 examples/s]
Generating train split: 61086280 examples [56:10, 19190.49 examples/s]
Generating train split: 61089104 examples [56:10, 19198.12 examples/s]
Generating train split: 61091659 examples [56:11, 19784.66 examples/s]
Generating train split: 61094111 examples [56:11, 19130.59 examples/s]
Generating train split: 61096346 examples [56:11, 17009.96 examples/s]
Generating train split: 61098293 examples [56:11, 15339.32 examples/s]
Generating train split: 61100203 examples [56:11, 16094.30 examples/s]
Generating train split: 61103042 examples [56:11, 18834.02 examples/s]
Generating train split: 61106724 examples [56:11, 23166.31 examples/s]
Generating train split: 61109288 examples [56:12, 17740.60 examples/s]
Generating train split: 61111813 examples [56:12, 19345.17 examples/s]
Generating train split: 61114056 examples [56:12, 17301.34 examples/s]
Generating train split: 61116033 examples [56:12, 12798.24 examples/s]
Generating train split: 61117739 examples [56:12, 13552.57 examples/s]
Generating train split: 61119383 examples [56:12, 10087.27 examples/s]
Generating train split: 61120702 examples [56:13, 9699.16 examples/s] 
Generating train split: 61121873 examples [56:13, 9450.92 examples/s]
Generating train split: 61122952 examples [56:13, 8085.82 examples/s]
Generating train split: 61124142 examples [56:13, 8791.00 examples/s]
Generating train split: 61125135 examples [56:13, 8555.35 examples/s]
Generating train split: 61126332 examples [56:13, 9323.46 examples/s]
Generating train split: 61127831 examples [56:13, 10494.25 examples/s]
Generating train split: 61128979 examples [56:14, 9288.24 examples/s] 
Generating train split: 61130026 examples [56:14, 8946.73 examples/s]
Generating train split: 61131391 examples [56:14, 10064.55 examples/s]
Generating train split: 61132461 examples [56:14, 7373.92 examples/s] 
Generating train split: 61133337 examples [56:14, 6765.64 examples/s]
Generating train split: 61134110 examples [56:14, 6442.95 examples/s]
Generating train split: 61135384 examples [56:14, 7793.84 examples/s]
Generating train split: 61136266 examples [56:15, 7913.57 examples/s]
Generating train split: 61138500 examples [56:15, 11500.73 examples/s]
Generating train split: 61139773 examples [56:15, 10564.19 examples/s]
Generating train split: 61140935 examples [56:15, 9935.56 examples/s] 
Generating train split: 61143742 examples [56:15, 14405.02 examples/s]
Generating train split: 61145327 examples [56:15, 9630.59 examples/s] 
Generating train split: 61148691 examples [56:15, 14313.37 examples/s]
Generating train split: 61150827 examples [56:16, 15727.44 examples/s]
Generating train split: 61152780 examples [56:16, 13331.98 examples/s]
Generating train split: 61155558 examples [56:16, 16387.84 examples/s]
Generating train split: 61157544 examples [56:16, 9034.17 examples/s] 
Generating train split: 61159261 examples [56:16, 10189.14 examples/s]
Generating train split: 61161616 examples [56:17, 12520.07 examples/s]
Generating train split: 61163418 examples [56:17, 12552.88 examples/s]
Generating train split: 61165060 examples [56:17, 11918.48 examples/s]
Generating train split: 61167276 examples [56:17, 14064.21 examples/s]
Generating train split: 61169269 examples [56:17, 14973.81 examples/s]
Generating train split: 61171002 examples [56:17, 9619.52 examples/s] 
Generating train split: 61173887 examples [56:18, 12999.09 examples/s]
Generating train split: 61175705 examples [56:18, 13268.34 examples/s]
Generating train split: 61177392 examples [56:18, 6951.94 examples/s] 
Generating train split: 61179077 examples [56:18, 8095.93 examples/s]
Generating train split: 61181684 examples [56:18, 10868.11 examples/s]
Generating train split: 61183388 examples [56:19, 9894.07 examples/s] 
Generating train split: 61184821 examples [56:19, 10616.83 examples/s]
Generating train split: 61187032 examples [56:19, 12851.19 examples/s]
Generating train split: 61188678 examples [56:19, 12526.41 examples/s]
Generating train split: 61190549 examples [56:19, 13872.06 examples/s]
Generating train split: 61192423 examples [56:19, 15025.56 examples/s]
Generating train split: 61197819 examples [56:19, 25010.44 examples/s]
Generating train split: 61200627 examples [56:20, 16625.71 examples/s]
Generating train split: 61202874 examples [56:20, 11015.10 examples/s]
Generating train split: 61204618 examples [56:20, 10893.55 examples/s]
Generating train split: 61206146 examples [56:21, 7990.50 examples/s] 
Generating train split: 61207403 examples [56:21, 8616.43 examples/s]
Generating train split: 61210399 examples [56:21, 12118.48 examples/s]
Generating train split: 61213692 examples [56:21, 16070.84 examples/s]
Generating train split: 61216669 examples [56:21, 13695.63 examples/s]
Generating train split: 61218623 examples [56:21, 13686.61 examples/s]
Generating train split: 61220344 examples [56:22, 10138.39 examples/s]
Generating train split: 61224250 examples [56:22, 14841.43 examples/s]
Generating train split: 61227551 examples [56:22, 18264.29 examples/s]
Generating train split: 61230273 examples [56:22, 20139.97 examples/s]
Generating train split: 61232826 examples [56:22, 13573.95 examples/s]
Generating train split: 61235808 examples [56:22, 16398.73 examples/s]
Generating train split: 61239240 examples [56:23, 18102.43 examples/s]
Generating train split: 61241535 examples [56:23, 14191.33 examples/s]
Generating train split: 61243396 examples [56:23, 14465.41 examples/s]
Generating train split: 61245163 examples [56:23, 14303.23 examples/s]
Generating train split: 61246817 examples [56:23, 13926.54 examples/s]
Generating train split: 61248364 examples [56:23, 13929.01 examples/s]
Generating train split: 61250518 examples [56:23, 15662.49 examples/s]
Generating train split: 61253027 examples [56:23, 18017.30 examples/s]
Generating train split: 61255113 examples [56:24, 18766.63 examples/s]
Generating train split: 61257089 examples [56:24, 16523.52 examples/s]
Generating train split: 61259579 examples [56:24, 18643.93 examples/s]
Generating train split: 61261565 examples [56:24, 11337.57 examples/s]
Generating train split: 61263181 examples [56:24, 12201.61 examples/s]
Generating train split: 61265117 examples [56:24, 13207.38 examples/s]
Generating train split: 61266710 examples [56:25, 11949.53 examples/s]
Generating train split: 61268107 examples [56:25, 11016.41 examples/s]
Generating train split: 61269819 examples [56:25, 12255.09 examples/s]
Generating train split: 61271193 examples [56:25, 11951.70 examples/s]
Generating train split: 61274118 examples [56:25, 15731.44 examples/s]
Generating train split: 61275819 examples [56:25, 14417.39 examples/s]
Generating train split: 61278014 examples [56:25, 16185.43 examples/s]
Generating train split: 61282332 examples [56:25, 23134.75 examples/s]
Generating train split: 61286633 examples [56:26, 28474.83 examples/s]
Generating train split: 61289682 examples [56:26, 28925.30 examples/s]
Generating train split: 61292726 examples [56:26, 23775.73 examples/s]
Generating train split: 61295479 examples [56:26, 24701.93 examples/s]
Generating train split: 61298765 examples [56:26, 26828.22 examples/s]
Generating train split: 61301911 examples [56:26, 28045.29 examples/s]
Generating train split: 61304849 examples [56:26, 25584.46 examples/s]
Generating train split: 61307534 examples [56:27, 17471.20 examples/s]
Generating train split: 61309985 examples [56:27, 18888.93 examples/s]
Generating train split: 61312327 examples [56:27, 19683.78 examples/s]
Generating train split: 61314580 examples [56:27, 12973.87 examples/s]
Generating train split: 61318473 examples [56:27, 17612.69 examples/s]
Generating train split: 61321863 examples [56:27, 20649.78 examples/s]
Generating train split: 61324500 examples [56:28, 13294.48 examples/s]
Generating train split: 61329414 examples [56:28, 19096.30 examples/s]
Generating train split: 61332321 examples [56:28, 18062.45 examples/s]
Generating train split: 61334830 examples [56:28, 14449.65 examples/s]
Generating train split: 61337198 examples [56:28, 15970.94 examples/s]
Generating train split: 61339328 examples [56:29, 13948.51 examples/s]
Generating train split: 61341399 examples [56:29, 15189.86 examples/s]
Generating train split: 61343795 examples [56:29, 17011.41 examples/s]
Generating train split: 61347442 examples [56:29, 21466.83 examples/s]
Generating train split: 61349954 examples [56:29, 19956.44 examples/s]
Generating train split: 61353160 examples [56:29, 22798.92 examples/s]
Generating train split: 61355707 examples [56:29, 14591.12 examples/s]
Generating train split: 61357716 examples [56:30, 14279.25 examples/s]
Generating train split: 61359523 examples [56:30, 13205.81 examples/s]
Generating train split: 61361114 examples [56:30, 12413.27 examples/s]
Generating train split: 61362530 examples [56:30, 11626.20 examples/s]
Generating train split: 61363808 examples [56:30, 8459.49 examples/s] 
Generating train split: 61365588 examples [56:30, 10082.07 examples/s]
Generating train split: 61366840 examples [56:31, 9109.31 examples/s] 
Generating train split: 61367929 examples [56:31, 8293.99 examples/s]
Generating train split: 61369096 examples [56:31, 8955.85 examples/s]
Generating train split: 61373418 examples [56:31, 16509.28 examples/s]
Generating train split: 61381007 examples [56:31, 30726.89 examples/s]
Generating train split: 61387069 examples [56:31, 38341.27 examples/s]
Generating train split: 61391476 examples [56:31, 36500.33 examples/s]
Generating train split: 61395538 examples [56:32, 25508.15 examples/s]
Generating train split: 61398809 examples [56:32, 23147.32 examples/s]
Generating train split: 61401646 examples [56:32, 23959.33 examples/s]
Generating train split: 61404445 examples [56:32, 24218.58 examples/s]
Generating train split: 61407162 examples [56:32, 15228.35 examples/s]
Generating train split: 61410327 examples [56:32, 18000.98 examples/s]
Generating train split: 61414730 examples [56:33, 23067.60 examples/s]
Generating train split: 61423795 examples [56:33, 37766.28 examples/s]
Generating train split: 61432146 examples [56:33, 48105.44 examples/s]
Generating train split: 61437935 examples [56:33, 27615.18 examples/s]
Generating train split: 61442400 examples [56:33, 26067.19 examples/s]
Generating train split: 61446180 examples [56:34, 20803.36 examples/s]
Generating train split: 61449203 examples [56:34, 21309.65 examples/s]
Generating train split: 61452019 examples [56:34, 21795.41 examples/s]
Generating train split: 61454704 examples [56:34, 22147.63 examples/s]
Generating train split: 61460371 examples [56:34, 29401.65 examples/s]
Generating train split: 61465755 examples [56:34, 35032.23 examples/s]
Generating train split: 61469826 examples [56:35, 27695.02 examples/s]
Generating train split: 61474411 examples [56:35, 31537.48 examples/s]
Generating train split: 61478159 examples [56:35, 17984.45 examples/s]
Generating train split: 61481031 examples [56:35, 19529.49 examples/s]
Generating train split: 61483874 examples [56:35, 16922.24 examples/s]
Generating train split: 61486222 examples [56:36, 16668.18 examples/s]
Generating train split: 61488340 examples [56:36, 15721.76 examples/s]
Generating train split: 61490230 examples [56:36, 16114.86 examples/s]
Generating train split: 61497149 examples [56:36, 27351.00 examples/s]
Generating train split: 61500781 examples [56:36, 29415.96 examples/s]
Generating train split: 61504226 examples [56:36, 30073.90 examples/s]
Generating train split: 61507596 examples [56:36, 26704.05 examples/s]
Generating train split: 61512058 examples [56:36, 31027.52 examples/s]
Generating train split: 61516011 examples [56:37, 33201.36 examples/s]
Generating train split: 61519598 examples [56:37, 15768.97 examples/s]
Generating train split: 61522941 examples [56:37, 17978.92 examples/s]
Generating train split: 61525698 examples [56:38, 12989.41 examples/s]
Generating train split: 61527844 examples [56:38, 14142.60 examples/s]
Generating train split: 61531536 examples [56:38, 17950.62 examples/s]
Generating train split: 61535314 examples [56:38, 21710.78 examples/s]
Generating train split: 61538261 examples [56:38, 14155.17 examples/s]
Generating train split: 61541256 examples [56:38, 16635.17 examples/s]
Generating train split: 61543745 examples [56:39, 16089.72 examples/s]
Generating train split: 61545928 examples [56:39, 16824.79 examples/s]
Generating train split: 61548052 examples [56:39, 17241.83 examples/s]
Generating train split: 61550690 examples [56:39, 19234.41 examples/s]
Generating train split: 61554499 examples [56:39, 23797.91 examples/s]
Generating train split: 61557188 examples [56:39, 16781.57 examples/s]
Generating train split: 61559475 examples [56:39, 17998.72 examples/s]
Generating train split: 61561690 examples [56:40, 13819.54 examples/s]
Generating train split: 61563495 examples [56:40, 14281.50 examples/s]
Generating train split: 61566038 examples [56:40, 16112.12 examples/s]
Generating train split: 61570072 examples [56:40, 21391.73 examples/s]
Generating train split: 61572566 examples [56:40, 14919.43 examples/s]
Generating train split: 61574564 examples [56:41, 11679.27 examples/s]
Generating train split: 61576167 examples [56:41, 9727.93 examples/s] 
Generating train split: 61578299 examples [56:41, 11533.18 examples/s]
Generating train split: 61580236 examples [56:41, 12704.67 examples/s]
Generating train split: 61581859 examples [56:41, 12896.55 examples/s]
Generating train split: 61584145 examples [56:41, 14860.97 examples/s]
Generating train split: 61585871 examples [56:41, 11290.94 examples/s]
Generating train split: 61587279 examples [56:42, 11777.74 examples/s]
Generating train split: 61589446 examples [56:42, 13916.35 examples/s]
Generating train split: 61592047 examples [56:42, 16792.96 examples/s]
Generating train split: 61594903 examples [56:42, 19710.45 examples/s]
Generating train split: 61597103 examples [56:42, 19768.23 examples/s]
Generating train split: 61599246 examples [56:42, 12640.71 examples/s]
Generating train split: 61600965 examples [56:43, 9910.78 examples/s] 
Generating train split: 61602348 examples [56:43, 8822.26 examples/s]
Generating train split: 61603504 examples [56:43, 8134.33 examples/s]
Generating train split: 61604494 examples [56:43, 7640.64 examples/s]
Generating train split: 61606004 examples [56:43, 7988.06 examples/s]
Generating train split: 61606903 examples [56:44, 6899.50 examples/s]
Generating train split: 61608756 examples [56:44, 8982.84 examples/s]
Generating train split: 61609817 examples [56:44, 9167.28 examples/s]
Generating train split: 61610867 examples [56:44, 9462.11 examples/s]
Generating train split: 61612678 examples [56:44, 11570.36 examples/s]
Generating train split: 61614383 examples [56:44, 12980.10 examples/s]
Generating train split: 61616370 examples [56:44, 14781.72 examples/s]
Generating train split: 61619254 examples [56:44, 18672.73 examples/s]
Generating train split: 61624207 examples [56:44, 27380.43 examples/s]
Generating train split: 61627073 examples [56:45, 18402.91 examples/s]
Generating train split: 61629387 examples [56:45, 15042.99 examples/s]
Generating train split: 61631297 examples [56:45, 11238.12 examples/s]
Generating train split: 61633252 examples [56:45, 12590.07 examples/s]
Generating train split: 61634902 examples [56:46, 10018.44 examples/s]
Generating train split: 61636250 examples [56:46, 9931.60 examples/s] 
Generating train split: 61638108 examples [56:46, 11516.46 examples/s]
Generating train split: 61639521 examples [56:46, 11718.95 examples/s]
Generating train split: 61640882 examples [56:46, 8668.58 examples/s] 
Generating train split: 61642482 examples [56:46, 9965.40 examples/s]
Generating train split: 61643715 examples [56:47, 7070.37 examples/s]
Generating train split: 61644788 examples [56:47, 7662.53 examples/s]
Generating train split: 61646140 examples [56:47, 8789.00 examples/s]
Generating train split: 61651195 examples [56:47, 17806.98 examples/s]
Generating train split: 61653485 examples [56:47, 16004.72 examples/s]
Generating train split: 61655486 examples [56:47, 12796.61 examples/s]
Generating train split: 61657381 examples [56:47, 13941.53 examples/s]
Generating train split: 61659086 examples [56:48, 9065.73 examples/s] 
Generating train split: 61660423 examples [56:48, 9165.51 examples/s]
Generating train split: 61661673 examples [56:48, 9752.15 examples/s]
Generating train split: 61662901 examples [56:48, 7652.03 examples/s]
Generating train split: 61663908 examples [56:48, 7422.53 examples/s]
Generating train split: 61664901 examples [56:49, 7891.57 examples/s]
Generating train split: 61665834 examples [56:49, 6871.05 examples/s]
Generating train split: 61666635 examples [56:49, 3879.76 examples/s]
Generating train split: 61669559 examples [56:49, 7306.66 examples/s]
Generating train split: 61670977 examples [56:50, 8355.03 examples/s]
Generating train split: 61672272 examples [56:50, 8020.80 examples/s]
Generating train split: 61673399 examples [56:50, 7294.32 examples/s]
Generating train split: 61676007 examples [56:50, 10758.59 examples/s]
Generating train split: 61679420 examples [56:50, 15578.48 examples/s]
Generating train split: 61681446 examples [56:50, 15305.49 examples/s]
Generating train split: 61683298 examples [56:50, 15626.79 examples/s]
Generating train split: 61685100 examples [56:50, 14532.62 examples/s]
Generating train split: 61686724 examples [56:51, 13961.67 examples/s]
Generating train split: 61688236 examples [56:51, 11797.16 examples/s]
Generating train split: 61691338 examples [56:51, 15816.26 examples/s]
Generating train split: 61693129 examples [56:51, 15649.35 examples/s]
Generating train split: 61694832 examples [56:51, 14397.75 examples/s]
Generating train split: 61696377 examples [56:51, 14535.77 examples/s]
Generating train split: 61697947 examples [56:51, 14627.17 examples/s]
Generating train split: 61699784 examples [56:51, 15469.16 examples/s]
Generating train split: 61701799 examples [56:52, 16724.13 examples/s]
Generating train split: 61704539 examples [56:52, 19654.19 examples/s]
Generating train split: 61706715 examples [56:52, 20247.66 examples/s]
Generating train split: 61709087 examples [56:52, 21230.53 examples/s]
Generating train split: 61711630 examples [56:52, 22407.20 examples/s]
Generating train split: 61713898 examples [56:52, 22085.58 examples/s]
Generating train split: 61717715 examples [56:52, 26771.20 examples/s]
Generating train split: 61720429 examples [56:52, 26147.61 examples/s]
Generating train split: 61723251 examples [56:52, 26717.61 examples/s]
Generating train split: 61725942 examples [56:53, 21661.31 examples/s]
Generating train split: 61728271 examples [56:53, 20480.69 examples/s]
Generating train split: 61730449 examples [56:53, 16903.77 examples/s]
Generating train split: 61732309 examples [56:53, 12253.90 examples/s]
Generating train split: 61733814 examples [56:53, 11850.90 examples/s]
Generating train split: 61735190 examples [56:53, 12048.19 examples/s]
Generating train split: 61736536 examples [56:54, 11320.08 examples/s]
Generating train split: 61737760 examples [56:54, 10816.75 examples/s]
Generating train split: 61739075 examples [56:54, 11348.43 examples/s]
Generating train split: 61741307 examples [56:54, 14041.13 examples/s]
Generating train split: 61742815 examples [56:54, 13874.20 examples/s]
Generating train split: 61744496 examples [56:54, 14365.38 examples/s]
Generating train split: 61745989 examples [56:55, 8264.77 examples/s] 
Generating train split: 61747148 examples [56:55, 7905.55 examples/s]
Generating train split: 61748177 examples [56:55, 8067.13 examples/s]
Generating train split: 61749445 examples [56:55, 8993.09 examples/s]
Generating train split: 61750528 examples [56:55, 9348.32 examples/s]
Generating train split: 61751809 examples [56:55, 10179.59 examples/s]
Generating train split: 61752938 examples [56:55, 9827.47 examples/s] 
Generating train split: 61754000 examples [56:55, 9126.50 examples/s]
Generating train split: 61754971 examples [56:55, 9127.18 examples/s]
Generating train split: 61755937 examples [56:56, 7021.35 examples/s]
Generating train split: 61757560 examples [56:56, 9027.38 examples/s]
Generating train split: 61758605 examples [56:56, 5332.88 examples/s]
Generating train split: 61760051 examples [56:56, 6807.11 examples/s]
Generating train split: 61761046 examples [56:56, 6625.38 examples/s]
Generating train split: 61761925 examples [56:57, 5588.91 examples/s]
Generating train split: 61762809 examples [56:57, 6174.15 examples/s]
Generating train split: 61763629 examples [56:57, 6550.04 examples/s]
Generating train split: 61764417 examples [56:57, 5849.64 examples/s]
Generating train split: 61771260 examples [56:57, 19337.47 examples/s]
Generating train split: 61778695 examples [56:57, 31958.42 examples/s]
Generating train split: 61782602 examples [56:57, 26850.57 examples/s]
Generating train split: 61790091 examples [56:58, 37471.06 examples/s]
Generating train split: 61798272 examples [56:58, 48111.40 examples/s]
Generating train split: 61803921 examples [56:58, 37283.58 examples/s]
Generating train split: 61808598 examples [56:58, 22889.95 examples/s]
Generating train split: 61812197 examples [56:59, 22154.86 examples/s]
Generating train split: 61820884 examples [56:59, 32556.92 examples/s]
Generating train split: 61827756 examples [56:59, 39307.93 examples/s]
Generating train split: 61833168 examples [56:59, 22391.95 examples/s]
Generating train split: 61837274 examples [57:00, 18852.59 examples/s]
Generating train split: 61840508 examples [57:00, 15380.54 examples/s]
Generating train split: 61843050 examples [57:00, 15075.13 examples/s]
Generating train split: 61846713 examples [57:00, 17995.36 examples/s]
Generating train split: 61849343 examples [57:00, 18436.01 examples/s]
Generating train split: 61854092 examples [57:00, 23683.49 examples/s]
Generating train split: 61858307 examples [57:01, 27455.56 examples/s]
Generating train split: 61863190 examples [57:01, 32269.51 examples/s]
Generating train split: 61868434 examples [57:01, 37196.67 examples/s]
Generating train split: 61874038 examples [57:01, 42061.92 examples/s]
Generating train split: 61879078 examples [57:01, 44309.59 examples/s]
Generating train split: 61884649 examples [57:01, 47463.50 examples/s]
Generating train split: 61890510 examples [57:01, 50592.41 examples/s]
Generating train split: 61897204 examples [57:01, 55294.33 examples/s]
Generating train split: 61902899 examples [57:01, 54609.46 examples/s]
Generating train split: 61908477 examples [57:02, 46372.32 examples/s]
Generating train split: 61913405 examples [57:02, 28556.74 examples/s]
Generating train split: 61917278 examples [57:02, 23043.96 examples/s]
Generating train split: 61920413 examples [57:02, 19873.43 examples/s]
Generating train split: 61923003 examples [57:03, 17624.57 examples/s]
Generating train split: 61925181 examples [57:03, 15748.42 examples/s]
Generating train split: 61927035 examples [57:03, 14890.74 examples/s]
Generating train split: 61928696 examples [57:03, 10468.62 examples/s]
Generating train split: 61930529 examples [57:03, 11647.14 examples/s]
Generating train split: 61931990 examples [57:04, 11867.09 examples/s]
Generating train split: 61933714 examples [57:04, 12907.79 examples/s]
Generating train split: 61935241 examples [57:04, 13418.21 examples/s]
Generating train split: 61937110 examples [57:04, 14677.11 examples/s]
Generating train split: 61938881 examples [57:04, 15443.47 examples/s]
Generating train split: 61940709 examples [57:04, 16180.12 examples/s]
Generating train split: 61942790 examples [57:04, 17423.40 examples/s]
Generating train split: 61944608 examples [57:04, 12201.33 examples/s]
Generating train split: 61946091 examples [57:05, 12601.42 examples/s]
Generating train split: 61953223 examples [57:05, 26393.00 examples/s]
Generating train split: 61956382 examples [57:05, 16320.67 examples/s]
Generating train split: 61958844 examples [57:05, 15526.69 examples/s]
Generating train split: 61964471 examples [57:05, 19025.05 examples/s]
Generating train split: 61966763 examples [57:05, 19618.84 examples/s]
Generating train split: 61969049 examples [57:06, 16236.15 examples/s]
Generating train split: 61970955 examples [57:06, 15637.09 examples/s]
Generating train split: 61973166 examples [57:06, 16923.32 examples/s]
Generating train split: 61976950 examples [57:06, 17627.60 examples/s]
Generating train split: 61978842 examples [57:06, 16507.88 examples/s]
Generating train split: 61981266 examples [57:07, 14225.42 examples/s]
Generating train split: 61982789 examples [57:07, 13165.31 examples/s]
Generating train split: 61984160 examples [57:07, 10049.89 examples/s]
Generating train split: 61985278 examples [57:07, 9926.41 examples/s] 
Generating train split: 61986345 examples [57:07, 9559.56 examples/s]
Generating train split: 61987812 examples [57:07, 10448.36 examples/s]
Generating train split: 61989338 examples [57:07, 11506.76 examples/s]
Generating train split: 61990563 examples [57:08, 10530.41 examples/s]
Generating train split: 61991965 examples [57:08, 11260.24 examples/s]
Generating train split: 61993157 examples [57:08, 8520.59 examples/s] 
Generating train split: 61999842 examples [57:08, 20925.82 examples/s]
Generating train split: 62009023 examples [57:08, 37438.82 examples/s]
Generating train split: 62014368 examples [57:08, 41431.57 examples/s]
Generating train split: 62019223 examples [57:08, 33896.20 examples/s]
Generating train split: 62023326 examples [57:09, 24515.43 examples/s]
Generating train split: 62026622 examples [57:09, 24717.68 examples/s]
Generating train split: 62029813 examples [57:09, 25916.25 examples/s]
Generating train split: 62032877 examples [57:09, 23023.28 examples/s]
Generating train split: 62035537 examples [57:09, 18364.98 examples/s]
Generating train split: 62041004 examples [57:09, 25215.50 examples/s]
Generating train split: 62044187 examples [57:10, 17720.38 examples/s]
Generating train split: 62047317 examples [57:10, 20003.51 examples/s]
Generating train split: 62050023 examples [57:10, 18319.43 examples/s]
Generating train split: 62052352 examples [57:10, 17953.75 examples/s]
Generating train split: 62054483 examples [57:10, 16378.47 examples/s]
Generating train split: 62057595 examples [57:10, 19373.65 examples/s]
Generating train split: 62059844 examples [57:11, 16680.13 examples/s]
Generating train split: 62061784 examples [57:11, 13022.88 examples/s]
Generating train split: 62064213 examples [57:11, 15104.01 examples/s]
Generating train split: 62066049 examples [57:11, 13042.46 examples/s]
Generating train split: 62067606 examples [57:11, 11151.63 examples/s]
Generating train split: 62068922 examples [57:12, 10678.57 examples/s]
Generating train split: 62073364 examples [57:12, 17421.77 examples/s]
Generating train split: 62082077 examples [57:12, 32905.84 examples/s]
Generating train split: 62088191 examples [57:12, 39421.89 examples/s]
Generating train split: 62092869 examples [57:12, 28930.02 examples/s]
Generating train split: 62098129 examples [57:12, 31320.66 examples/s]
Generating train split: 62101933 examples [57:13, 22060.62 examples/s]
Generating train split: 62105146 examples [57:13, 23729.54 examples/s]
Generating train split: 62108219 examples [57:13, 24913.01 examples/s]
Generating train split: 62111251 examples [57:13, 19722.97 examples/s]
Generating train split: 62113748 examples [57:13, 16154.21 examples/s]
Generating train split: 62117365 examples [57:13, 19627.83 examples/s]
Generating train split: 62120305 examples [57:13, 21505.81 examples/s]
Generating train split: 62122933 examples [57:14, 16540.56 examples/s]
Generating train split: 62125081 examples [57:14, 16416.85 examples/s]
Generating train split: 62130141 examples [57:14, 19740.15 examples/s]
Generating train split: 62132330 examples [57:14, 18983.82 examples/s]
Generating train split: 62134363 examples [57:14, 19232.31 examples/s]
Generating train split: 62136397 examples [57:15, 15034.69 examples/s]
Generating train split: 62138092 examples [57:15, 15409.69 examples/s]
Generating train split: 62140433 examples [57:15, 17097.18 examples/s]
Generating train split: 62145760 examples [57:15, 19741.62 examples/s]
Generating train split: 62147768 examples [57:15, 13953.43 examples/s]
Generating train split: 62150936 examples [57:15, 17025.99 examples/s]
Generating train split: 62154317 examples [57:16, 17888.19 examples/s]
Generating train split: 62156373 examples [57:16, 16848.81 examples/s]
Generating train split: 62158235 examples [57:16, 16796.52 examples/s]
Generating train split: 62160041 examples [57:16, 12913.67 examples/s]
Generating train split: 62161880 examples [57:16, 13977.34 examples/s]
Generating train split: 62164995 examples [57:16, 17706.27 examples/s]
Generating train split: 62167041 examples [57:17, 11513.92 examples/s]
Generating train split: 62168801 examples [57:17, 12578.56 examples/s]
Generating train split: 62170462 examples [57:17, 12863.03 examples/s]
Generating train split: 62172041 examples [57:17, 12294.42 examples/s]
Generating train split: 62173467 examples [57:17, 12589.44 examples/s]
Generating train split: 62174879 examples [57:17, 12436.82 examples/s]
Generating train split: 62176541 examples [57:17, 13433.23 examples/s]
Generating train split: 62178595 examples [57:17, 15231.52 examples/s]
Generating train split: 62180232 examples [57:17, 15536.18 examples/s]
Generating train split: 62181864 examples [57:18, 15721.52 examples/s]
Generating train split: 62183487 examples [57:18, 14076.96 examples/s]
Generating train split: 62184958 examples [57:18, 13792.57 examples/s]
Generating train split: 62187257 examples [57:18, 16254.63 examples/s]
Generating train split: 62193493 examples [57:18, 29008.43 examples/s]
Generating train split: 62196543 examples [57:18, 22224.83 examples/s]
Generating train split: 62199724 examples [57:18, 24428.60 examples/s]
Generating train split: 62202470 examples [57:18, 24498.69 examples/s]
Generating train split: 62207409 examples [57:19, 30920.36 examples/s]
Generating train split: 62217772 examples [57:19, 50488.87 examples/s]
Generating train split: 62223222 examples [57:19, 30402.29 examples/s]
Generating train split: 62227508 examples [57:19, 24274.35 examples/s]
Generating train split: 62230958 examples [57:20, 19617.24 examples/s]
Generating train split: 62233782 examples [57:20, 20697.75 examples/s]
Generating train split: 62236519 examples [57:20, 16875.41 examples/s]
Generating train split: 62238739 examples [57:20, 14885.93 examples/s]
Generating train split: 62240612 examples [57:20, 13066.61 examples/s]
Generating train split: 62242180 examples [57:21, 12044.54 examples/s]
Generating train split: 62244067 examples [57:21, 13227.71 examples/s]
Generating train split: 62245599 examples [57:21, 11519.15 examples/s]
Generating train split: 62246969 examples [57:21, 11938.08 examples/s]
Generating train split: 62248868 examples [57:21, 13453.15 examples/s]
Generating train split: 62250637 examples [57:21, 14391.72 examples/s]
Generating train split: 62252259 examples [57:21, 14817.87 examples/s]
Generating train split: 62254807 examples [57:21, 17527.33 examples/s]
Generating train split: 62256661 examples [57:22, 12256.80 examples/s]
Generating train split: 62258925 examples [57:22, 14445.21 examples/s]
Generating train split: 62260670 examples [57:22, 10063.41 examples/s]
Generating train split: 62262494 examples [57:22, 11535.67 examples/s]
Generating train split: 62264420 examples [57:22, 13111.46 examples/s]
Generating train split: 62266065 examples [57:22, 13589.09 examples/s]
Generating train split: 62268604 examples [57:23, 15447.21 examples/s]
Generating train split: 62270325 examples [57:23, 15180.32 examples/s]
Generating train split: 62274522 examples [57:23, 21880.61 examples/s]
Generating train split: 62278821 examples [57:23, 27436.13 examples/s]
Generating train split: 62283497 examples [57:23, 32632.58 examples/s]
Generating train split: 62287967 examples [57:23, 36009.96 examples/s]
Generating train split: 62292480 examples [57:23, 38606.71 examples/s]
Generating train split: 62296472 examples [57:23, 34118.73 examples/s]
Generating train split: 62300070 examples [57:24, 22435.31 examples/s]
Generating train split: 62302952 examples [57:24, 21963.06 examples/s]
Generating train split: 62307674 examples [57:24, 27201.41 examples/s]
Generating train split: 62317515 examples [57:24, 43469.81 examples/s]
Generating train split: 62322745 examples [57:24, 25616.17 examples/s]
Generating train split: 62326785 examples [57:25, 20951.19 examples/s]
Generating train split: 62330016 examples [57:25, 18917.03 examples/s]
Generating train split: 62333974 examples [57:25, 22043.70 examples/s]
Generating train split: 62337317 examples [57:25, 19099.57 examples/s]
Generating train split: 62339877 examples [57:25, 19367.39 examples/s]
Generating train split: 62342286 examples [57:26, 13935.33 examples/s]
Generating train split: 62344178 examples [57:26, 13746.22 examples/s]
Generating train split: 62347449 examples [57:26, 16997.96 examples/s]
Generating train split: 62350520 examples [57:26, 19692.18 examples/s]
Generating train split: 62352971 examples [57:26, 20277.62 examples/s]
Generating train split: 62355357 examples [57:26, 17855.88 examples/s]
Generating train split: 62357430 examples [57:27, 14978.03 examples/s]
Generating train split: 62359181 examples [57:27, 14713.72 examples/s]
Generating train split: 62360824 examples [57:27, 11283.23 examples/s]
Generating train split: 62362169 examples [57:27, 9573.30 examples/s] 
Generating train split: 62364109 examples [57:27, 11151.75 examples/s]
Generating train split: 62365454 examples [57:27, 9788.79 examples/s] 
Generating train split: 62366850 examples [57:28, 10582.21 examples/s]
Generating train split: 62368067 examples [57:28, 9105.22 examples/s] 
Generating train split: 62369107 examples [57:28, 8432.77 examples/s]
Generating train split: 62370217 examples [57:28, 7245.94 examples/s]
Generating train split: 62371030 examples [57:28, 5506.12 examples/s]
Generating train split: 62374365 examples [57:28, 10259.16 examples/s]
Generating train split: 62377842 examples [57:29, 15043.69 examples/s]
Generating train split: 62379900 examples [57:29, 6412.09 examples/s] 
Generating train split: 62381632 examples [57:29, 7607.39 examples/s]
Generating train split: 62384954 examples [57:30, 11074.10 examples/s]
Generating train split: 62389025 examples [57:30, 15871.91 examples/s]
Generating train split: 62392452 examples [57:30, 19284.27 examples/s]
Generating train split: 62395361 examples [57:30, 12519.89 examples/s]
Generating train split: 62397595 examples [57:30, 10860.16 examples/s]
Generating train split: 62400588 examples [57:31, 13580.08 examples/s]
Generating train split: 62402748 examples [57:31, 11634.21 examples/s]
Generating train split: 62404506 examples [57:31, 11402.40 examples/s]
Generating train split: 62406455 examples [57:31, 12695.58 examples/s]
Generating train split: 62408107 examples [57:31, 11474.95 examples/s]
Generating train split: 62411770 examples [57:31, 16281.69 examples/s]
Generating train split: 62415671 examples [57:32, 21166.16 examples/s]
Generating train split: 62418309 examples [57:32, 17403.88 examples/s]
Generating train split: 62420505 examples [57:32, 13890.48 examples/s]
Generating train split: 62423561 examples [57:32, 16931.11 examples/s]
Generating train split: 62426976 examples [57:32, 19263.74 examples/s]
Generating train split: 62429281 examples [57:32, 16095.11 examples/s]
Generating train split: 62431243 examples [57:33, 16795.43 examples/s]
Generating train split: 62433199 examples [57:33, 15804.05 examples/s]
Generating train split: 62437679 examples [57:33, 22273.36 examples/s]
Generating train split: 62442965 examples [57:33, 29665.83 examples/s]
Generating train split: 62446362 examples [57:33, 17388.97 examples/s]
Generating train split: 62448993 examples [57:34, 13722.51 examples/s]
Generating train split: 62452405 examples [57:34, 16795.40 examples/s]
Generating train split: 62456262 examples [57:34, 20652.90 examples/s]
Generating train split: 62459156 examples [57:34, 10806.58 examples/s]
Generating train split: 62461321 examples [57:35, 10355.99 examples/s]
Generating train split: 62463478 examples [57:35, 11812.56 examples/s]
Generating train split: 62466509 examples [57:35, 14704.89 examples/s]
Generating train split: 62468746 examples [57:35, 15515.00 examples/s]
Generating train split: 62470879 examples [57:35, 13527.00 examples/s]
Generating train split: 62472688 examples [57:35, 14345.10 examples/s]
Generating train split: 62474473 examples [57:35, 14192.08 examples/s]
Generating train split: 62477002 examples [57:36, 16594.47 examples/s]
Generating train split: 62478918 examples [57:36, 16608.73 examples/s]
Generating train split: 62481454 examples [57:36, 18431.12 examples/s]
Generating train split: 62483522 examples [57:36, 18978.71 examples/s]
Generating train split: 62485532 examples [57:36, 18963.29 examples/s]
Generating train split: 62487509 examples [57:36, 19061.98 examples/s]
Generating train split: 62489474 examples [57:36, 11834.26 examples/s]
Generating train split: 62491095 examples [57:37, 12696.78 examples/s]
Generating train split: 62493911 examples [57:37, 16091.71 examples/s]
Generating train split: 62495866 examples [57:37, 11087.38 examples/s]
Generating train split: 62498000 examples [57:37, 12958.19 examples/s]
Generating train split: 62501518 examples [57:37, 17559.82 examples/s]
Generating train split: 62507236 examples [57:37, 25204.59 examples/s]
Generating train split: 62510199 examples [57:38, 18187.79 examples/s]
Generating train split: 62512588 examples [57:38, 19191.60 examples/s]
Generating train split: 62517604 examples [57:38, 25758.42 examples/s]
Generating train split: 62520771 examples [57:38, 26440.68 examples/s]
Generating train split: 62530751 examples [57:38, 44386.11 examples/s]
Generating train split: 62535901 examples [57:38, 21961.53 examples/s]
Generating train split: 62539805 examples [57:39, 23442.34 examples/s]
Generating train split: 62543467 examples [57:39, 22699.57 examples/s]
Generating train split: 62546631 examples [57:39, 14467.82 examples/s]
Generating train split: 62549717 examples [57:39, 16604.39 examples/s]
Generating train split: 62552331 examples [57:40, 14033.45 examples/s]
Generating train split: 62554515 examples [57:40, 14956.94 examples/s]
Generating train split: 62556580 examples [57:40, 11655.73 examples/s]
Generating train split: 62558230 examples [57:40, 11671.63 examples/s]
Generating train split: 62561446 examples [57:40, 14476.55 examples/s]
Generating train split: 62563256 examples [57:41, 12268.58 examples/s]
Generating train split: 62565781 examples [57:41, 14588.28 examples/s]
Generating train split: 62568335 examples [57:41, 16792.29 examples/s]
Generating train split: 62570366 examples [57:41, 17169.29 examples/s]
Generating train split: 62572339 examples [57:41, 13116.86 examples/s]
Generating train split: 62573965 examples [57:41, 13625.30 examples/s]
Generating train split: 62578794 examples [57:41, 21307.11 examples/s]
Generating train split: 62587138 examples [57:41, 36242.17 examples/s]
Generating train split: 62591441 examples [57:42, 28426.79 examples/s]
Generating train split: 62595027 examples [57:42, 19259.06 examples/s]
Generating train split: 62597823 examples [57:42, 18677.24 examples/s]
Generating train split: 62601158 examples [57:42, 21242.37 examples/s]
Generating train split: 62604382 examples [57:43, 16314.83 examples/s]
Generating train split: 62606782 examples [57:43, 17586.08 examples/s]
Generating train split: 62609049 examples [57:43, 10353.03 examples/s]
Generating train split: 62610782 examples [57:43, 11109.05 examples/s]
Generating train split: 62613834 examples [57:43, 14153.08 examples/s]
Generating train split: 62617835 examples [57:44, 18889.87 examples/s]
Generating train split: 62620926 examples [57:44, 21366.64 examples/s]
Generating train split: 62623715 examples [57:44, 8783.25 examples/s] 
Generating train split: 62626572 examples [57:45, 10984.81 examples/s]
Generating train split: 62629613 examples [57:45, 13602.00 examples/s]
Generating train split: 62632114 examples [57:45, 13694.15 examples/s]
Generating train split: 62634280 examples [57:45, 13280.47 examples/s]
Generating train split: 62636163 examples [57:45, 13077.25 examples/s]
Generating train split: 62638491 examples [57:45, 14997.80 examples/s]
Generating train split: 62643054 examples [57:45, 21193.29 examples/s]
Generating train split: 62645658 examples [57:46, 15453.04 examples/s]
Generating train split: 62647750 examples [57:46, 16461.01 examples/s]
Generating train split: 62649844 examples [57:46, 17205.43 examples/s]
Generating train split: 62652509 examples [57:46, 19196.33 examples/s]
Generating train split: 62654732 examples [57:46, 13283.24 examples/s]
Generating train split: 62658137 examples [57:46, 17195.13 examples/s]
Generating train split: 62660393 examples [57:47, 11759.43 examples/s]
Generating train split: 62662164 examples [57:47, 11784.01 examples/s]
Generating train split: 62665158 examples [57:47, 14936.69 examples/s]
Generating train split: 62667155 examples [57:47, 11063.63 examples/s]
Generating train split: 62668739 examples [57:47, 11587.48 examples/s]
Generating train split: 62671143 examples [57:48, 13911.50 examples/s]
Generating train split: 62673745 examples [57:48, 16475.46 examples/s]
Generating train split: 62676679 examples [57:48, 19458.93 examples/s]
Generating train split: 62685394 examples [57:48, 36311.34 examples/s]
Generating train split: 62689616 examples [57:48, 35414.05 examples/s]
Generating train split: 62693576 examples [57:48, 23374.84 examples/s]
Generating train split: 62696727 examples [57:49, 18022.67 examples/s]
Generating train split: 62699255 examples [57:49, 17600.63 examples/s]
Generating train split: 62701505 examples [57:49, 16552.64 examples/s]
Generating train split: 62706192 examples [57:49, 22169.74 examples/s]
Generating train split: 62708988 examples [57:49, 22890.68 examples/s]
Generating train split: 62712570 examples [57:49, 25778.75 examples/s]
Generating train split: 62715552 examples [57:49, 23430.43 examples/s]
Generating train split: 62718207 examples [57:49, 22423.44 examples/s]
Generating train split: 62723245 examples [57:50, 29032.02 examples/s]
Generating train split: 62728580 examples [57:50, 35174.47 examples/s]
Generating train split: 62732448 examples [57:50, 15043.15 examples/s]
Generating train split: 62735351 examples [57:50, 15178.03 examples/s]
Generating train split: 62737843 examples [57:51, 12867.79 examples/s]
Generating train split: 62739840 examples [57:51, 12227.90 examples/s]
Generating train split: 62741545 examples [57:51, 10922.27 examples/s]
Generating train split: 62742973 examples [57:51, 11270.81 examples/s]
Generating train split: 62744371 examples [57:51, 11734.12 examples/s]
Generating train split: 62745815 examples [57:52, 12186.68 examples/s]
Generating train split: 62747218 examples [57:52, 9741.36 examples/s] 
Generating train split: 62748621 examples [57:52, 10573.34 examples/s]
Generating train split: 62750170 examples [57:52, 11621.69 examples/s]
Generating train split: 62752700 examples [57:52, 14877.05 examples/s]
Generating train split: 62756313 examples [57:52, 20272.71 examples/s]
Generating train split: 62758782 examples [57:52, 21246.09 examples/s]
Generating train split: 62761085 examples [57:53, 12007.61 examples/s]
Generating train split: 62762923 examples [57:53, 13087.74 examples/s]
Generating train split: 62765433 examples [57:53, 15442.87 examples/s]
Generating train split: 62768635 examples [57:53, 18806.59 examples/s]
Generating train split: 62770919 examples [57:53, 16403.06 examples/s]
Generating train split: 62772897 examples [57:53, 15345.83 examples/s]
Generating train split: 62774668 examples [57:54, 11589.52 examples/s]
Generating train split: 62776116 examples [57:54, 11484.08 examples/s]
Generating train split: 62779281 examples [57:54, 15541.37 examples/s]
Generating train split: 62781264 examples [57:54, 16443.98 examples/s]
Generating train split: 62783185 examples [57:54, 17104.98 examples/s]
Generating train split: 62785100 examples [57:54, 12961.02 examples/s]
Generating train split: 62787949 examples [57:54, 16218.17 examples/s]
Generating train split: 62790189 examples [57:54, 17642.73 examples/s]
Generating train split: 62792231 examples [57:55, 15218.60 examples/s]
Generating train split: 62793998 examples [57:55, 13971.87 examples/s]
Generating train split: 62795575 examples [57:55, 12703.96 examples/s]
Generating train split: 62796978 examples [57:55, 11521.97 examples/s]
Generating train split: 62798223 examples [57:55, 10155.93 examples/s]
Generating train split: 62801575 examples [57:55, 15114.23 examples/s]
Generating train split: 62808270 examples [57:55, 27180.46 examples/s]
Generating train split: 62811529 examples [57:56, 19629.86 examples/s]
Generating train split: 62814481 examples [57:56, 21514.13 examples/s]
Generating train split: 62817198 examples [57:56, 22510.59 examples/s]
Generating train split: 62819874 examples [57:56, 22509.62 examples/s]
Generating train split: 62829804 examples [57:56, 41268.07 examples/s]
Generating train split: 62834803 examples [57:56, 42672.74 examples/s]
Generating train split: 62839531 examples [57:57, 23700.89 examples/s]
Generating train split: 62843176 examples [57:57, 22321.42 examples/s]
Generating train split: 62846310 examples [57:57, 23834.01 examples/s]
Generating train split: 62849490 examples [57:57, 25258.78 examples/s]
Generating train split: 62852598 examples [57:57, 20194.80 examples/s]
Generating train split: 62855165 examples [57:58, 18997.46 examples/s]
Generating train split: 62857874 examples [57:58, 20585.73 examples/s]
Generating train split: 62861038 examples [57:58, 22923.29 examples/s]
Generating train split: 62863891 examples [57:58, 24245.05 examples/s]
Generating train split: 62866581 examples [57:58, 12688.16 examples/s]
Generating train split: 62869734 examples [57:58, 15623.37 examples/s]
Generating train split: 62872247 examples [57:59, 13077.36 examples/s]
Generating train split: 62875137 examples [57:59, 15637.30 examples/s]
Generating train split: 62877348 examples [57:59, 14142.90 examples/s]
Generating train split: 62879234 examples [57:59, 12475.77 examples/s]
Generating train split: 62881927 examples [57:59, 12489.20 examples/s]
Generating train split: 62884349 examples [58:00, 10669.44 examples/s]
Generating train split: 62886756 examples [58:00, 12724.11 examples/s]
Generating train split: 62888420 examples [58:00, 13366.74 examples/s]
Generating train split: 62890042 examples [58:00, 10235.18 examples/s]
Generating train split: 62891344 examples [58:00, 10064.05 examples/s]
Generating train split: 62894369 examples [58:00, 13900.45 examples/s]
Generating train split: 62900360 examples [58:01, 18599.70 examples/s]
Generating train split: 62902359 examples [58:01, 11741.53 examples/s]
Generating train split: 62904124 examples [58:01, 12606.24 examples/s]
Generating train split: 62905735 examples [58:01, 12582.32 examples/s]
Generating train split: 62907237 examples [58:01, 11522.18 examples/s]
Generating train split: 62908557 examples [58:02, 11702.98 examples/s]
Generating train split: 62911096 examples [58:02, 14623.24 examples/s]
Generating train split: 62913317 examples [58:02, 16321.72 examples/s]
Generating train split: 62915137 examples [58:02, 12288.55 examples/s]
Generating train split: 62916633 examples [58:02, 11160.69 examples/s]
Generating train split: 62918340 examples [58:02, 12364.16 examples/s]
Generating train split: 62919777 examples [58:03, 8135.50 examples/s] 
Generating train split: 62921801 examples [58:03, 10193.22 examples/s]
Generating train split: 62924635 examples [58:03, 13683.40 examples/s]
Generating train split: 62926443 examples [58:03, 14412.46 examples/s]
Generating train split: 62928457 examples [58:03, 15713.50 examples/s]
Generating train split: 62930296 examples [58:03, 11902.63 examples/s]
Generating train split: 62938495 examples [58:03, 26354.04 examples/s]
Generating train split: 62945183 examples [58:04, 35350.82 examples/s]
Generating train split: 62949595 examples [58:04, 23542.14 examples/s]
Generating train split: 62953070 examples [58:04, 18240.27 examples/s]
Generating train split: 62955834 examples [58:04, 19078.29 examples/s]
Generating train split: 62963496 examples [58:04, 29229.05 examples/s]
Generating train split: 62970845 examples [58:05, 38116.21 examples/s]
Generating train split: 62975941 examples [58:05, 34143.12 examples/s]
Generating train split: 62981496 examples [58:05, 38632.45 examples/s]
Generating train split: 62986219 examples [58:05, 26377.31 examples/s]
Generating train split: 62989956 examples [58:05, 27085.43 examples/s]
Generating train split: 62993555 examples [58:05, 28808.26 examples/s]
Generating train split: 62997115 examples [58:05, 30135.58 examples/s]
Generating train split: 63000639 examples [58:06, 14040.51 examples/s]
Generating train split: 63005050 examples [58:06, 17980.87 examples/s]
Generating train split: 63008235 examples [58:06, 20147.73 examples/s]
Generating train split: 63011402 examples [58:07, 16065.51 examples/s]
Generating train split: 63013932 examples [58:07, 16117.50 examples/s]
Generating train split: 63018537 examples [58:07, 21288.56 examples/s]
Generating train split: 63021509 examples [58:07, 16434.16 examples/s]
Generating train split: 63023877 examples [58:08, 11978.26 examples/s]
Generating train split: 63025788 examples [58:08, 12973.35 examples/s]
Generating train split: 63029106 examples [58:08, 16345.91 examples/s]
Generating train split: 63031408 examples [58:08, 14140.91 examples/s]
Generating train split: 63033431 examples [58:08, 15236.22 examples/s]
Generating train split: 63035623 examples [58:08, 16606.42 examples/s]
Generating train split: 63037835 examples [58:08, 17848.93 examples/s]
Generating train split: 63041671 examples [58:08, 22857.58 examples/s]
Generating train split: 63048116 examples [58:09, 28500.61 examples/s]
Generating train split: 63051090 examples [58:09, 18775.88 examples/s]
Generating train split: 63054677 examples [58:09, 21879.15 examples/s]
Generating train split: 63058135 examples [58:09, 24480.69 examples/s]
Generating train split: 63061073 examples [58:09, 24642.50 examples/s]
Generating train split: 63063891 examples [58:09, 17131.74 examples/s]
Generating train split: 63066143 examples [58:10, 14251.92 examples/s]
Generating train split: 63068168 examples [58:10, 15278.14 examples/s]
Generating train split: 63070766 examples [58:10, 16969.03 examples/s]
Generating train split: 63073466 examples [58:10, 19117.06 examples/s]
Generating train split: 63075690 examples [58:10, 16120.48 examples/s]
Generating train split: 63077594 examples [58:10, 15791.33 examples/s]
Generating train split: 63081879 examples [58:10, 21645.31 examples/s]
Generating train split: 63086106 examples [58:11, 26606.26 examples/s]
Generating train split: 63089107 examples [58:11, 13024.00 examples/s]
Generating train split: 63092495 examples [58:11, 16101.24 examples/s]
Generating train split: 63096486 examples [58:11, 20249.32 examples/s]
Generating train split: 63099880 examples [58:11, 22947.50 examples/s]
Generating train split: 63103006 examples [58:12, 14823.18 examples/s]
Generating train split: 63106087 examples [58:12, 17361.67 examples/s]
Generating train split: 63110639 examples [58:12, 22570.32 examples/s]
Generating train split: 63113841 examples [58:12, 15803.69 examples/s]
Generating train split: 63116344 examples [58:12, 16842.68 examples/s]
Generating train split: 63119615 examples [58:13, 19741.34 examples/s]
Generating train split: 63122283 examples [58:13, 15225.88 examples/s]
Generating train split: 63124419 examples [58:13, 15832.75 examples/s]
Generating train split: 63126469 examples [58:13, 15079.73 examples/s]
Generating train split: 63128300 examples [58:13, 10936.39 examples/s]
Generating train split: 63137338 examples [58:14, 24170.10 examples/s]
Generating train split: 63141090 examples [58:14, 26674.65 examples/s]
Generating train split: 63144824 examples [58:14, 26283.36 examples/s]
Generating train split: 63148190 examples [58:14, 22158.59 examples/s]
Generating train split: 63151018 examples [58:14, 16100.56 examples/s]
Generating train split: 63153250 examples [58:15, 12907.69 examples/s]
Generating train split: 63155038 examples [58:15, 13513.84 examples/s]
Generating train split: 63156792 examples [58:15, 12359.35 examples/s]
Generating train split: 63158309 examples [58:15, 11924.39 examples/s]
Generating train split: 63159690 examples [58:15, 11989.00 examples/s]
Generating train split: 63162635 examples [58:15, 15658.42 examples/s]
Generating train split: 63167047 examples [58:15, 22227.47 examples/s]
Generating train split: 63172233 examples [58:16, 29517.14 examples/s]
Generating train split: 63175599 examples [58:16, 28084.04 examples/s]
Generating train split: 63178712 examples [58:16, 28149.98 examples/s]
Generating train split: 63182778 examples [58:16, 31413.12 examples/s]
Generating train split: 63186110 examples [58:16, 27568.76 examples/s]
Generating train split: 63189080 examples [58:16, 22908.55 examples/s]
Generating train split: 63191629 examples [58:16, 18804.91 examples/s]
Generating train split: 63193775 examples [58:17, 18635.31 examples/s]
Generating train split: 63196174 examples [58:17, 19788.24 examples/s]
Generating train split: 63198323 examples [58:17, 16709.40 examples/s]
Generating train split: 63201453 examples [58:17, 19923.09 examples/s]
Generating train split: 63206196 examples [58:17, 26505.05 examples/s]
Generating train split: 63210563 examples [58:17, 30861.29 examples/s]
Generating train split: 63213964 examples [58:17, 24111.57 examples/s]
Generating train split: 63217384 examples [58:17, 25537.02 examples/s]
Generating train split: 63220284 examples [58:18, 18188.91 examples/s]
Generating train split: 63222615 examples [58:18, 17468.17 examples/s]
Generating train split: 63225052 examples [58:18, 18821.07 examples/s]
Generating train split: 63227243 examples [58:18, 16672.69 examples/s]
Generating train split: 63229156 examples [58:18, 15422.56 examples/s]
Generating train split: 63230865 examples [58:19, 11554.20 examples/s]
Generating train split: 63232251 examples [58:19, 11550.13 examples/s]
Generating train split: 63233578 examples [58:19, 11523.01 examples/s]
Generating train split: 63234845 examples [58:19, 11614.19 examples/s]
Generating train split: 63236318 examples [58:19, 12343.68 examples/s]
Generating train split: 63238728 examples [58:19, 15221.88 examples/s]
Generating train split: 63240358 examples [58:19, 12106.05 examples/s]
Generating train split: 63242472 examples [58:19, 14007.47 examples/s]
Generating train split: 63244172 examples [58:20, 14729.83 examples/s]
Generating train split: 63245780 examples [58:20, 13213.16 examples/s]
Generating train split: 63247218 examples [58:20, 11624.07 examples/s]
Generating train split: 63248488 examples [58:20, 10180.46 examples/s]
Generating train split: 63249965 examples [58:20, 11177.50 examples/s]
Generating train split: 63251504 examples [58:20, 12178.38 examples/s]
Generating train split: 63253268 examples [58:20, 13564.22 examples/s]
Generating train split: 63254728 examples [58:20, 12345.74 examples/s]
Generating train split: 63256057 examples [58:21, 12167.38 examples/s]
Generating train split: 63257711 examples [58:21, 12791.27 examples/s]
Generating train split: 63259033 examples [58:21, 8898.38 examples/s] 
Generating train split: 63261651 examples [58:21, 12413.19 examples/s]
Generating train split: 63263593 examples [58:21, 13986.38 examples/s]
Generating train split: 63265262 examples [58:22, 9485.26 examples/s] 
Generating train split: 63266575 examples [58:22, 9090.75 examples/s]
Generating train split: 63269466 examples [58:22, 12866.13 examples/s]
Generating train split: 63271215 examples [58:22, 13808.52 examples/s]
Generating train split: 63272917 examples [58:22, 8986.48 examples/s] 
Generating train split: 63274488 examples [58:22, 10133.08 examples/s]
Generating train split: 63276312 examples [58:22, 11719.49 examples/s]
Generating train split: 63277840 examples [58:23, 8758.59 examples/s] 
Generating train split: 63279063 examples [58:23, 8349.20 examples/s]
Generating train split: 63280154 examples [58:23, 6711.45 examples/s]
Generating train split: 63281419 examples [58:23, 7709.14 examples/s]
Generating train split: 63282833 examples [58:23, 8898.38 examples/s]
Generating train split: 63285539 examples [58:23, 12754.23 examples/s]
Generating train split: 63287797 examples [58:24, 14583.41 examples/s]
Generating train split: 63289709 examples [58:24, 15683.39 examples/s]
Generating train split: 63291467 examples [58:24, 14616.35 examples/s]
Generating train split: 63293289 examples [58:24, 15512.08 examples/s]
Generating train split: 63294964 examples [58:24, 15452.14 examples/s]
Generating train split: 63297924 examples [58:24, 17027.60 examples/s]
Generating train split: 63299666 examples [58:24, 15357.26 examples/s]
Generating train split: 63301796 examples [58:24, 16078.65 examples/s]
Generating train split: 63303443 examples [58:25, 14552.53 examples/s]
Generating train split: 63305017 examples [58:25, 14759.72 examples/s]
Generating train split: 63308486 examples [58:25, 13899.24 examples/s]
Generating train split: 63311011 examples [58:25, 16218.64 examples/s]
Generating train split: 63313569 examples [58:25, 18019.91 examples/s]
Generating train split: 63315529 examples [58:25, 13523.01 examples/s]
Generating train split: 63317130 examples [58:26, 11711.12 examples/s]
Generating train split: 63319405 examples [58:26, 13842.58 examples/s]
Generating train split: 63322613 examples [58:26, 17794.66 examples/s]
Generating train split: 63324724 examples [58:26, 16349.97 examples/s]
Generating train split: 63326607 examples [58:26, 15703.06 examples/s]
Generating train split: 63328346 examples [58:26, 14170.71 examples/s]
Generating train split: 63329894 examples [58:26, 14421.12 examples/s]
Generating train split: 63331433 examples [58:26, 14342.28 examples/s]
Generating train split: 63332936 examples [58:27, 9900.77 examples/s] 
Generating train split: 63336306 examples [58:27, 14616.04 examples/s]
Generating train split: 63338375 examples [58:27, 15932.70 examples/s]
Generating train split: 63340310 examples [58:27, 15551.51 examples/s]
Generating train split: 63342303 examples [58:27, 16575.77 examples/s]
Generating train split: 63344152 examples [58:27, 12818.73 examples/s]
Generating train split: 63346048 examples [58:28, 14093.75 examples/s]
Generating train split: 63347692 examples [58:28, 11790.01 examples/s]
Generating train split: 63350041 examples [58:28, 14237.15 examples/s]
Generating train split: 63352744 examples [58:28, 16753.71 examples/s]
Generating train split: 63354636 examples [58:28, 15253.63 examples/s]
Generating train split: 63357450 examples [58:28, 18287.03 examples/s]
Generating train split: 63359483 examples [58:28, 18185.39 examples/s]
Generating train split: 63362081 examples [58:28, 19907.90 examples/s]
Generating train split: 63365629 examples [58:29, 23472.90 examples/s]
Generating train split: 63368081 examples [58:29, 17629.85 examples/s]
Generating train split: 63370118 examples [58:29, 17664.68 examples/s]
Generating train split: 63372089 examples [58:29, 14396.93 examples/s]
Generating train split: 63373747 examples [58:29, 14211.63 examples/s]
Generating train split: 63375555 examples [58:29, 15069.76 examples/s]
Generating train split: 63377396 examples [58:29, 15840.84 examples/s]
Generating train split: 63379641 examples [58:30, 17532.71 examples/s]
Generating train split: 63381508 examples [58:30, 10343.53 examples/s]
Generating train split: 63382962 examples [58:30, 10155.44 examples/s]
Generating train split: 63386859 examples [58:30, 15682.22 examples/s]
Generating train split: 63388946 examples [58:31, 10470.64 examples/s]
Generating train split: 63390611 examples [58:31, 11428.53 examples/s]
Generating train split: 63392241 examples [58:31, 11730.10 examples/s]
Generating train split: 63393769 examples [58:31, 10004.31 examples/s]
Generating train split: 63395043 examples [58:31, 9730.05 examples/s] 
Generating train split: 63398304 examples [58:31, 14278.57 examples/s]
Generating train split: 63400100 examples [58:31, 14034.83 examples/s]
Generating train split: 63403823 examples [58:31, 19122.11 examples/s]
Generating train split: 63406053 examples [58:32, 17601.18 examples/s]
Generating train split: 63408056 examples [58:32, 14523.25 examples/s]
Generating train split: 63410829 examples [58:32, 17309.76 examples/s]
Generating train split: 63412845 examples [58:32, 14802.22 examples/s]
Generating train split: 63414573 examples [58:32, 15316.70 examples/s]
Generating train split: 63416581 examples [58:32, 16406.31 examples/s]
Generating train split: 63418392 examples [58:32, 16000.95 examples/s]
Generating train split: 63420158 examples [58:33, 16405.96 examples/s]
Generating train split: 63421888 examples [58:33, 14514.33 examples/s]
Generating train split: 63423438 examples [58:33, 13415.24 examples/s]
Generating train split: 63424864 examples [58:33, 13242.19 examples/s]
Generating train split: 63427012 examples [58:33, 15020.20 examples/s]
Generating train split: 63432716 examples [58:33, 26014.95 examples/s]
Generating train split: 63441801 examples [58:33, 43646.17 examples/s]
Generating train split: 63446490 examples [58:33, 34982.02 examples/s]
Generating train split: 63450490 examples [58:34, 24030.14 examples/s]
Generating train split: 63453671 examples [58:34, 23202.26 examples/s]
Generating train split: 63456527 examples [58:34, 16753.62 examples/s]
Generating train split: 63458789 examples [58:34, 15892.36 examples/s]
Generating train split: 63460770 examples [58:35, 15183.47 examples/s]
Generating train split: 63462547 examples [58:35, 14833.66 examples/s]
Generating train split: 63464362 examples [58:35, 15486.93 examples/s]
Generating train split: 63466989 examples [58:35, 17866.00 examples/s]
Generating train split: 63468990 examples [58:35, 18338.14 examples/s]
Generating train split: 63470971 examples [58:35, 15874.84 examples/s]
Generating train split: 63472768 examples [58:35, 16323.38 examples/s]
Generating train split: 63474517 examples [58:35, 14491.51 examples/s]
Generating train split: 63476668 examples [58:36, 16137.05 examples/s]
Generating train split: 63478400 examples [58:36, 10616.54 examples/s]
Generating train split: 63480051 examples [58:36, 11714.73 examples/s]
Generating train split: 63481514 examples [58:36, 11661.67 examples/s]
Generating train split: 63483729 examples [58:36, 14002.27 examples/s]
Generating train split: 63485355 examples [58:36, 12331.63 examples/s]
Generating train split: 63487285 examples [58:36, 13907.06 examples/s]
Generating train split: 63489445 examples [58:37, 15786.11 examples/s]
Generating train split: 63491201 examples [58:37, 15055.49 examples/s]
Generating train split: 63493640 examples [58:37, 17394.11 examples/s]
Generating train split: 63495512 examples [58:37, 16428.54 examples/s]
Generating train split: 63497253 examples [58:37, 15490.27 examples/s]
Generating train split: 63498874 examples [58:37, 15358.38 examples/s]
Generating train split: 63500802 examples [58:37, 16168.66 examples/s]
Generating train split: 63502470 examples [58:37, 15869.64 examples/s]
Generating train split: 63504091 examples [58:38, 12818.03 examples/s]
Generating train split: 63505481 examples [58:38, 11972.52 examples/s]
Generating train split: 63506754 examples [58:38, 10530.62 examples/s]
Generating train split: 63509545 examples [58:38, 14487.20 examples/s]
Generating train split: 63512979 examples [58:38, 19330.08 examples/s]
Generating train split: 63515141 examples [58:38, 18312.45 examples/s]
Generating train split: 63517143 examples [58:38, 16937.53 examples/s]
Generating train split: 63519537 examples [58:38, 18663.34 examples/s]
Generating train split: 63522830 examples [58:39, 22381.38 examples/s]
Generating train split: 63528368 examples [58:39, 31327.52 examples/s]
Generating train split: 63533465 examples [58:39, 36804.84 examples/s]
Generating train split: 63537534 examples [58:39, 37895.49 examples/s]
Generating train split: 63542177 examples [58:39, 40359.20 examples/s]
Generating train split: 63546314 examples [58:39, 28664.25 examples/s]
Generating train split: 63551351 examples [58:39, 33592.58 examples/s]
Generating train split: 63555496 examples [58:39, 35511.62 examples/s]
Generating train split: 63563330 examples [58:39, 46621.03 examples/s]
Generating train split: 63571997 examples [58:40, 57429.33 examples/s]
Generating train split: 63578192 examples [58:40, 40525.74 examples/s]
Generating train split: 63583235 examples [58:40, 34031.18 examples/s]
Generating train split: 63587463 examples [58:40, 31195.80 examples/s]
Generating train split: 63591350 examples [58:40, 32458.42 examples/s]
Generating train split: 63595057 examples [58:41, 28818.56 examples/s]
Generating train split: 63598785 examples [58:41, 30607.46 examples/s]
Generating train split: 63603770 examples [58:41, 35069.81 examples/s]
Generating train split: 63607638 examples [58:41, 32253.13 examples/s]
Generating train split: 63613681 examples [58:41, 38509.02 examples/s]
Generating train split: 63617845 examples [58:42, 16846.73 examples/s]
Generating train split: 63620955 examples [58:42, 17711.08 examples/s]
Generating train split: 63624228 examples [58:42, 19971.60 examples/s]
Generating train split: 63627182 examples [58:42, 21247.59 examples/s]
Generating train split: 63630048 examples [58:42, 16348.84 examples/s]
Generating train split: 63632486 examples [58:42, 17677.96 examples/s]
Generating train split: 63634841 examples [58:43, 13181.74 examples/s]
Generating train split: 63636720 examples [58:43, 11778.20 examples/s]
Generating train split: 63638278 examples [58:43, 9878.63 examples/s] 
Generating train split: 63639546 examples [58:43, 9146.43 examples/s]
Generating train split: 63641611 examples [58:43, 10733.57 examples/s]
Generating train split: 63642918 examples [58:44, 8593.12 examples/s] 
Generating train split: 63644299 examples [58:44, 9425.60 examples/s]
Generating train split: 63645662 examples [58:44, 10239.99 examples/s]
Generating train split: 63646871 examples [58:44, 8742.75 examples/s] 
Generating train split: 63647913 examples [58:44, 8487.13 examples/s]
Generating train split: 63648867 examples [58:44, 8081.29 examples/s]
Generating train split: 63649761 examples [58:45, 6891.99 examples/s]
Generating train split: 63650521 examples [58:45, 6785.93 examples/s]
Generating train split: 63653292 examples [58:45, 11418.30 examples/s]
Generating train split: 63654619 examples [58:45, 8477.48 examples/s] 
Generating train split: 63657080 examples [58:45, 11660.98 examples/s]
Generating train split: 63658611 examples [58:45, 12461.71 examples/s]
Generating train split: 63660157 examples [58:45, 13175.68 examples/s]
Generating train split: 63662850 examples [58:45, 16669.24 examples/s]
Generating train split: 63664718 examples [58:46, 13690.01 examples/s]
Generating train split: 63666313 examples [58:46, 12238.14 examples/s]
Generating train split: 63668124 examples [58:46, 13377.42 examples/s]
Generating train split: 63670294 examples [58:46, 14710.02 examples/s]
Generating train split: 63671890 examples [58:46, 13884.02 examples/s]
Generating train split: 63673951 examples [58:46, 15497.76 examples/s]
Generating train split: 63675599 examples [58:47, 9878.08 examples/s] 
Generating train split: 63676904 examples [58:47, 10295.01 examples/s]
Generating train split: 63681458 examples [58:47, 17665.19 examples/s]
Generating train split: 63687777 examples [58:47, 28012.16 examples/s]
Generating train split: 63693353 examples [58:47, 34847.21 examples/s]
Generating train split: 63697442 examples [58:47, 27586.88 examples/s]
Generating train split: 63700851 examples [58:47, 24164.60 examples/s]
Generating train split: 63703775 examples [58:48, 14984.55 examples/s]
Generating train split: 63706024 examples [58:48, 11329.46 examples/s]
Generating train split: 63707775 examples [58:49, 8644.85 examples/s] 
Generating train split: 63709779 examples [58:49, 9928.41 examples/s]
Generating train split: 63711384 examples [58:49, 10672.62 examples/s]
Generating train split: 63712922 examples [58:49, 6141.65 examples/s] 
Generating train split: 63714275 examples [58:50, 6927.23 examples/s]
Generating train split: 63715454 examples [58:50, 6886.35 examples/s]
Generating train split: 63717986 examples [58:50, 9689.90 examples/s]
Generating train split: 63719841 examples [58:50, 11240.99 examples/s]
Generating train split: 63721939 examples [58:50, 13208.01 examples/s]
Generating train split: 63724500 examples [58:50, 15993.41 examples/s]
Generating train split: 63726486 examples [58:50, 15482.72 examples/s]
Generating train split: 63730026 examples [58:50, 20259.06 examples/s]
Generating train split: 63732365 examples [58:51, 17159.22 examples/s]
Generating train split: 63734715 examples [58:51, 18454.41 examples/s]
Generating train split: 63736798 examples [58:51, 16904.59 examples/s]
Generating train split: 63738674 examples [58:51, 16757.89 examples/s]
Generating train split: 63742637 examples [58:51, 22398.33 examples/s]
Generating train split: 63745086 examples [58:51, 14877.16 examples/s]
Generating train split: 63747304 examples [58:51, 16282.82 examples/s]
Generating train split: 63749420 examples [58:52, 17339.43 examples/s]
Generating train split: 63751485 examples [58:52, 12632.05 examples/s]
Generating train split: 63753150 examples [58:52, 12684.01 examples/s]
Generating train split: 63755379 examples [58:52, 14648.30 examples/s]
Generating train split: 63758758 examples [58:52, 18983.29 examples/s]
Generating train split: 63764130 examples [58:52, 26651.59 examples/s]
Generating train split: 63767127 examples [58:52, 23416.93 examples/s]
Generating train split: 63769764 examples [58:53, 19692.03 examples/s]
Generating train split: 63772805 examples [58:53, 21996.21 examples/s]
Generating train split: 63775298 examples [58:53, 15453.20 examples/s]
Generating train split: 63777465 examples [58:53, 16154.61 examples/s]
Generating train split: 63779775 examples [58:53, 17579.12 examples/s]
Generating train split: 63781842 examples [58:53, 14719.99 examples/s]
Generating train split: 63783904 examples [58:54, 15934.95 examples/s]
Generating train split: 63786783 examples [58:54, 18864.65 examples/s]
Generating train split: 63788941 examples [58:54, 17476.37 examples/s]
Generating train split: 63790900 examples [58:54, 15751.41 examples/s]
Generating train split: 63792636 examples [58:54, 15816.67 examples/s]
Generating train split: 63794331 examples [58:54, 14343.71 examples/s]
Generating train split: 63796557 examples [58:54, 15972.38 examples/s]
Generating train split: 63800513 examples [58:54, 21801.96 examples/s]
Generating train split: 63802873 examples [58:55, 21969.92 examples/s]
Generating train split: 63805199 examples [58:55, 20918.70 examples/s]
Generating train split: 63807388 examples [58:55, 17201.80 examples/s]
Generating train split: 63809272 examples [58:55, 11621.78 examples/s]
Generating train split: 63811771 examples [58:55, 14048.96 examples/s]
Generating train split: 63818280 examples [58:55, 24572.36 examples/s]
Generating train split: 63825839 examples [58:56, 32816.16 examples/s]
Generating train split: 63829658 examples [58:56, 22768.64 examples/s]
Generating train split: 63833501 examples [58:56, 25562.93 examples/s]
Generating train split: 63836772 examples [58:56, 18131.65 examples/s]
Generating train split: 63839355 examples [58:57, 13370.83 examples/s]
Generating train split: 63841366 examples [58:57, 13417.89 examples/s]
Generating train split: 63845009 examples [58:57, 17019.07 examples/s]
Generating train split: 63847379 examples [58:57, 12093.20 examples/s]
Generating train split: 63854743 examples [58:57, 21173.19 examples/s]
Generating train split: 63858254 examples [58:58, 18983.46 examples/s]
Generating train split: 63861145 examples [58:58, 15927.93 examples/s]
Generating train split: 63863482 examples [58:58, 13448.45 examples/s]
Generating train split: 63870943 examples [58:58, 19322.39 examples/s]
Generating train split: 63873322 examples [58:59, 16218.75 examples/s]
Generating train split: 63876687 examples [58:59, 16706.68 examples/s]
Generating train split: 63878610 examples [58:59, 15799.62 examples/s]
Generating train split: 63880517 examples [58:59, 16360.98 examples/s]
Generating train split: 63882309 examples [58:59, 15910.43 examples/s]
Generating train split: 63883995 examples [59:00, 10250.29 examples/s]
Generating train split: 63885313 examples [59:00, 10393.57 examples/s]
Generating train split: 63886567 examples [59:00, 9295.26 examples/s] 
Generating train split: 63887646 examples [59:00, 6741.39 examples/s]
Generating train split: 63889203 examples [59:00, 8116.45 examples/s]
Generating train split: 63890269 examples [59:01, 6491.11 examples/s]
Generating train split: 63891457 examples [59:01, 7343.38 examples/s]
Generating train split: 63892412 examples [59:01, 6946.99 examples/s]
Generating train split: 63893256 examples [59:01, 5373.96 examples/s]
Generating train split: 63894074 examples [59:01, 5827.27 examples/s]
Generating train split: 63894793 examples [59:01, 5985.91 examples/s]
Generating train split: 63895496 examples [59:01, 5574.79 examples/s]
Generating train split: 63896135 examples [59:02, 5723.98 examples/s]
Generating train split: 63897848 examples [59:02, 8400.28 examples/s]
Generating train split: 63898810 examples [59:02, 8177.19 examples/s]
Generating train split: 63901028 examples [59:02, 11692.44 examples/s]
Generating train split: 63902319 examples [59:02, 7930.84 examples/s] 
Generating train split: 63903360 examples [59:02, 6747.77 examples/s]
Generating train split: 63904238 examples [59:03, 6093.30 examples/s]
Generating train split: 63905727 examples [59:03, 7716.69 examples/s]
Generating train split: 63906691 examples [59:03, 4157.82 examples/s]
Generating train split: 63907428 examples [59:03, 4520.01 examples/s]
Generating train split: 63909176 examples [59:03, 6555.96 examples/s]
Generating train split: 63910612 examples [59:04, 7970.23 examples/s]
Generating train split: 63911758 examples [59:04, 7142.61 examples/s]
Generating train split: 63913424 examples [59:04, 9004.14 examples/s]
Generating train split: 63915666 examples [59:04, 11934.12 examples/s]
Generating train split: 63917164 examples [59:04, 9549.43 examples/s] 
Generating train split: 63918403 examples [59:04, 7599.59 examples/s]
Generating train split: 63919416 examples [59:05, 7588.04 examples/s]
Generating train split: 63920349 examples [59:05, 7866.79 examples/s]
Generating train split: 63921641 examples [59:05, 8919.14 examples/s]
Generating train split: 63922668 examples [59:05, 6679.97 examples/s]
Generating train split: 63924335 examples [59:05, 8625.13 examples/s]
Generating train split: 63925426 examples [59:05, 8785.12 examples/s]
Generating train split: 63927268 examples [59:05, 10983.90 examples/s]
Generating train split: 63929332 examples [59:06, 13368.34 examples/s]
Generating train split: 63930852 examples [59:06, 12485.67 examples/s]
Generating train split: 63933193 examples [59:06, 15009.18 examples/s]
Generating train split: 63936548 examples [59:06, 19334.44 examples/s]
Generating train split: 63938605 examples [59:06, 18419.73 examples/s]
Generating train split: 63940541 examples [59:06, 18293.79 examples/s]
Generating train split: 63942432 examples [59:07, 8552.91 examples/s] 
Generating train split: 63943866 examples [59:07, 8494.94 examples/s]
Generating train split: 63945256 examples [59:07, 9368.47 examples/s]
Generating train split: 63947525 examples [59:07, 11835.78 examples/s]
Generating train split: 63949176 examples [59:07, 12821.67 examples/s]
Generating train split: 63950777 examples [59:07, 13069.14 examples/s]
Generating train split: 63952320 examples [59:07, 10417.79 examples/s]
Generating train split: 63953637 examples [59:08, 10955.35 examples/s]
Generating train split: 63954923 examples [59:08, 11344.89 examples/s]
Generating train split: 63956805 examples [59:08, 13182.04 examples/s]
Generating train split: 63960880 examples [59:08, 20347.61 examples/s]
Generating train split: 63968292 examples [59:08, 34896.85 examples/s]
Generating train split: 63972087 examples [59:08, 24350.03 examples/s]
Generating train split: 63975424 examples [59:08, 26262.63 examples/s]
Generating train split: 63978578 examples [59:08, 26585.27 examples/s]
Generating train split: 63981612 examples [59:09, 27451.92 examples/s]
Generating train split: 63984639 examples [59:09, 15265.84 examples/s]
Generating train split: 63989201 examples [59:09, 20318.43 examples/s]
Generating train split: 63992210 examples [59:09, 21066.73 examples/s]
Generating train split: 63995019 examples [59:10, 15198.14 examples/s]
Generating train split: 63997870 examples [59:10, 17408.47 examples/s]
Generating train split: 64005338 examples [59:10, 28391.79 examples/s]
Generating train split: 64013389 examples [59:10, 39597.01 examples/s]
Generating train split: 64018551 examples [59:10, 26006.75 examples/s]
Generating train split: 64022588 examples [59:10, 26341.83 examples/s]
Generating train split: 64026728 examples [59:10, 29112.60 examples/s]
Generating train split: 64030536 examples [59:11, 23137.15 examples/s]
Generating train split: 64033634 examples [59:11, 24303.90 examples/s]
Generating train split: 64036679 examples [59:11, 25438.75 examples/s]
Generating train split: 64043181 examples [59:11, 34346.73 examples/s]
Generating train split: 64051843 examples [59:11, 47063.95 examples/s]
Generating train split: 64058318 examples [59:11, 51609.14 examples/s]
Generating train split: 64064073 examples [59:12, 26547.21 examples/s]
Generating train split: 64068467 examples [59:12, 28761.12 examples/s]
Generating train split: 64075776 examples [59:12, 36907.65 examples/s]
Generating train split: 64085772 examples [59:12, 50026.15 examples/s]
Generating train split: 64092387 examples [59:12, 33881.32 examples/s]
Generating train split: 64097578 examples [59:13, 27485.60 examples/s]
Generating train split: 64102789 examples [59:13, 31270.20 examples/s]
Generating train split: 64107255 examples [59:13, 27608.28 examples/s]
Generating train split: 64110986 examples [59:13, 23307.34 examples/s]
Generating train split: 64114639 examples [59:13, 25489.90 examples/s]
Generating train split: 64117881 examples [59:14, 21659.21 examples/s]
Generating train split: 64120588 examples [59:14, 17623.01 examples/s]
Generating train split: 64124778 examples [59:14, 21681.99 examples/s]
Generating train split: 64128435 examples [59:14, 24495.41 examples/s]
Generating train split: 64131503 examples [59:14, 18814.19 examples/s]
Generating train split: 64133987 examples [59:14, 17654.30 examples/s]
Generating train split: 64138835 examples [59:15, 23454.50 examples/s]
Generating train split: 64145768 examples [59:15, 33172.94 examples/s]
Generating train split: 64153000 examples [59:15, 42096.59 examples/s]
Generating train split: 64158049 examples [59:15, 22545.88 examples/s]
Generating train split: 64161895 examples [59:16, 17008.24 examples/s]
Generating train split: 64164875 examples [59:16, 18583.59 examples/s]
Generating train split: 64167838 examples [59:16, 19099.78 examples/s]
Generating train split: 64170545 examples [59:16, 14956.47 examples/s]
Generating train split: 64174893 examples [59:16, 19293.61 examples/s]
Generating train split: 64177692 examples [59:16, 19600.32 examples/s]
Generating train split: 64180290 examples [59:17, 20781.77 examples/s]
Generating train split: 64182863 examples [59:17, 19540.07 examples/s]
Generating train split: 64185169 examples [59:17, 15712.72 examples/s]
Generating train split: 64187076 examples [59:17, 14196.82 examples/s]
Generating train split: 64195092 examples [59:17, 26939.02 examples/s]
Generating train split: 64202978 examples [59:17, 38169.30 examples/s]
Generating train split: 64207843 examples [59:18, 27723.97 examples/s]
Generating train split: 64211737 examples [59:18, 16951.84 examples/s]
Generating train split: 64214698 examples [59:18, 15600.17 examples/s]
Generating train split: 64217136 examples [59:19, 15567.18 examples/s]
Generating train split: 64219309 examples [59:19, 16487.32 examples/s]
Generating train split: 64226445 examples [59:19, 26307.35 examples/s]
Generating train split: 64234571 examples [59:19, 37490.96 examples/s]
Generating train split: 64239572 examples [59:19, 23725.99 examples/s]
Generating train split: 64243862 examples [59:19, 26777.50 examples/s]
Generating train split: 64249165 examples [59:19, 30592.56 examples/s]
Generating train split: 64253307 examples [59:20, 23071.56 examples/s]
Generating train split: 64256612 examples [59:20, 23718.41 examples/s]
Generating train split: 64259712 examples [59:20, 19628.24 examples/s]
Generating train split: 64262257 examples [59:20, 17163.42 examples/s]
Generating train split: 64264964 examples [59:20, 18858.88 examples/s]
Generating train split: 64267562 examples [59:21, 20254.47 examples/s]
Generating train split: 64276469 examples [59:21, 35344.18 examples/s]
Generating train split: 64280824 examples [59:21, 31688.19 examples/s]
Generating train split: 64284621 examples [59:21, 23799.81 examples/s]
Generating train split: 64287699 examples [59:21, 24856.08 examples/s]
Generating train split: 64296561 examples [59:21, 38210.87 examples/s]
Generating train split: 64301345 examples [59:21, 39456.89 examples/s]
Generating train split: 64305984 examples [59:22, 27063.92 examples/s]
Generating train split: 64309682 examples [59:22, 19640.76 examples/s]
Generating train split: 64312588 examples [59:22, 18093.09 examples/s]
Generating train split: 64315046 examples [59:22, 18911.80 examples/s]
Generating train split: 64317460 examples [59:23, 16937.46 examples/s]
Generating train split: 64320441 examples [59:23, 19276.88 examples/s]
Generating train split: 64324053 examples [59:23, 22743.29 examples/s]
Generating train split: 64328809 examples [59:23, 28379.39 examples/s]
Generating train split: 64334133 examples [59:23, 34033.05 examples/s]
Generating train split: 64338767 examples [59:23, 37189.15 examples/s]
Generating train split: 64344471 examples [59:23, 42505.78 examples/s]
Generating train split: 64349522 examples [59:23, 44706.99 examples/s]
Generating train split: 64357525 examples [59:23, 54713.66 examples/s]
Generating train split: 64363230 examples [59:24, 54635.04 examples/s]
Generating train split: 64368851 examples [59:24, 46844.36 examples/s]
Generating train split: 64373842 examples [59:24, 31701.91 examples/s]
Generating train split: 64377853 examples [59:24, 29049.39 examples/s]
Generating train split: 64381357 examples [59:24, 29060.43 examples/s]
Generating train split: 64384681 examples [59:25, 18139.29 examples/s]
Generating train split: 64387252 examples [59:25, 18161.86 examples/s]
Generating train split: 64390361 examples [59:25, 20376.20 examples/s]
Generating train split: 64392937 examples [59:25, 15458.95 examples/s]
Generating train split: 64395000 examples [59:26, 10501.00 examples/s]
Generating train split: 64396602 examples [59:26, 10958.14 examples/s]
Generating train split: 64398122 examples [59:26, 9718.68 examples/s] 
Generating train split: 64400919 examples [59:26, 12608.85 examples/s]
Generating train split: 64404835 examples [59:26, 17510.12 examples/s]
Generating train split: 64407220 examples [59:27, 12217.48 examples/s]
Generating train split: 64409086 examples [59:27, 11869.15 examples/s]
Generating train split: 64410717 examples [59:27, 11530.80 examples/s]
Generating train split: 64413769 examples [59:27, 15003.32 examples/s]
Generating train split: 64416183 examples [59:27, 16625.15 examples/s]
Generating train split: 64418214 examples [59:27, 15671.86 examples/s]
Generating train split: 64420037 examples [59:27, 13795.91 examples/s]
Generating train split: 64421806 examples [59:27, 14626.88 examples/s]
Generating train split: 64424823 examples [59:28, 18260.55 examples/s]
Generating train split: 64429844 examples [59:28, 26114.48 examples/s]
Generating train split: 64432767 examples [59:28, 17638.47 examples/s]
Generating train split: 64435105 examples [59:28, 17492.69 examples/s]
Generating train split: 64438435 examples [59:28, 20722.20 examples/s]
Generating train split: 64441144 examples [59:28, 21993.34 examples/s]
Generating train split: 64443671 examples [59:29, 15664.37 examples/s]
Generating train split: 64445703 examples [59:29, 16192.41 examples/s]
Generating train split: 64448437 examples [59:29, 18562.92 examples/s]
Generating train split: 64451576 examples [59:29, 21544.17 examples/s]
Generating train split: 64456371 examples [59:29, 28025.69 examples/s]
Generating train split: 64459521 examples [59:29, 18177.50 examples/s]
Generating train split: 64462016 examples [59:29, 19392.48 examples/s]
Generating train split: 64465534 examples [59:30, 22739.44 examples/s]
Generating train split: 64468871 examples [59:30, 25214.30 examples/s]
Generating train split: 64471832 examples [59:30, 17072.14 examples/s]
Generating train split: 64474187 examples [59:30, 17874.93 examples/s]
Generating train split: 64477954 examples [59:30, 21870.05 examples/s]
Generating train split: 64481469 examples [59:30, 18456.53 examples/s]
Generating train split: 64483770 examples [59:31, 16057.08 examples/s]
Generating train split: 64485721 examples [59:31, 15285.03 examples/s]
Generating train split: 64489051 examples [59:31, 18827.88 examples/s]
Generating train split: 64491993 examples [59:31, 21150.21 examples/s]
Generating train split: 64494440 examples [59:31, 14997.80 examples/s]
Generating train split: 64496660 examples [59:31, 16358.56 examples/s]
Generating train split: 64498698 examples [59:32, 16528.18 examples/s]
Generating train split: 64500645 examples [59:32, 12313.75 examples/s]
Generating train split: 64502225 examples [59:32, 12115.45 examples/s]
Generating train split: 64505261 examples [59:32, 15765.43 examples/s]
Generating train split: 64507192 examples [59:32, 15762.28 examples/s]
Generating train split: 64509016 examples [59:32, 13533.18 examples/s]
Generating train split: 64510590 examples [59:33, 10984.93 examples/s]
Generating train split: 64511932 examples [59:33, 11457.37 examples/s]
Generating train split: 64513250 examples [59:33, 11509.68 examples/s]
Generating train split: 64515704 examples [59:33, 14533.36 examples/s]
Generating train split: 64517333 examples [59:33, 14291.48 examples/s]
Generating train split: 64518881 examples [59:33, 12244.45 examples/s]
Generating train split: 64520236 examples [59:33, 11323.43 examples/s]
Generating train split: 64521468 examples [59:33, 11553.43 examples/s]
Generating train split: 64522707 examples [59:34, 9507.71 examples/s] 
Generating train split: 64524585 examples [59:34, 11565.54 examples/s]
Generating train split: 64525978 examples [59:34, 11763.86 examples/s]
Generating train split: 64528058 examples [59:34, 14019.64 examples/s]
Generating train split: 64529585 examples [59:34, 13917.71 examples/s]
Generating train split: 64531096 examples [59:34, 14234.52 examples/s]
Generating train split: 64533163 examples [59:34, 15927.54 examples/s]
Generating train split: 64534815 examples [59:34, 15175.55 examples/s]
Generating train split: 64536376 examples [59:35, 11574.40 examples/s]
Generating train split: 64540005 examples [59:35, 17240.19 examples/s]
Generating train split: 64545855 examples [59:35, 26188.96 examples/s]
Generating train split: 64551685 examples [59:35, 34267.52 examples/s]
Generating train split: 64558025 examples [59:35, 41670.05 examples/s]
Generating train split: 64563254 examples [59:35, 44549.56 examples/s]
Generating train split: 64567978 examples [59:35, 26108.29 examples/s]
Generating train split: 64574471 examples [59:36, 33385.11 examples/s]
Generating train split: 64579108 examples [59:36, 35750.96 examples/s]
Generating train split: 64583612 examples [59:36, 15082.75 examples/s]
Generating train split: 64586949 examples [59:37, 11270.42 examples/s]
Generating train split: 64589458 examples [59:37, 10168.53 examples/s]
Generating train split: 64591439 examples [59:37, 10782.77 examples/s]
Generating train split: 64593870 examples [59:38, 12418.00 examples/s]
Generating train split: 64595880 examples [59:38, 10097.72 examples/s]
Generating train split: 64597468 examples [59:38, 10318.29 examples/s]
Generating train split: 64598923 examples [59:38, 10868.31 examples/s]
Generating train split: 64600820 examples [59:38, 12311.76 examples/s]
Generating train split: 64602382 examples [59:39, 8909.52 examples/s] 
Generating train split: 64603626 examples [59:39, 9209.69 examples/s]
Generating train split: 64604815 examples [59:39, 8581.50 examples/s]
Generating train split: 64605858 examples [59:39, 8242.07 examples/s]
Generating train split: 64606806 examples [59:39, 7865.53 examples/s]
Generating train split: 64607674 examples [59:39, 6688.43 examples/s]
Generating train split: 64615392 examples [59:39, 20807.20 examples/s]
Generating train split: 64623772 examples [59:40, 34816.93 examples/s]
Generating train split: 64628277 examples [59:40, 29086.93 examples/s]
Generating train split: 64632046 examples [59:40, 16695.94 examples/s]
Generating train split: 64634918 examples [59:40, 18132.89 examples/s]
Generating train split: 64643433 examples [59:40, 29204.22 examples/s]
Generating train split: 64647945 examples [59:41, 26437.25 examples/s]
Generating train split: 64651744 examples [59:41, 19235.70 examples/s]
Generating train split: 64654711 examples [59:41, 17768.20 examples/s]
Generating train split: 64657201 examples [59:42, 14389.69 examples/s]
Generating train split: 64659195 examples [59:42, 11044.95 examples/s]
Generating train split: 64660768 examples [59:42, 11587.87 examples/s]
Generating train split: 64662319 examples [59:42, 11435.57 examples/s]
Generating train split: 64663731 examples [59:42, 9416.72 examples/s] 
Generating train split: 64666061 examples [59:43, 11662.69 examples/s]
Generating train split: 64668555 examples [59:43, 14137.05 examples/s]
Generating train split: 64670350 examples [59:43, 10323.69 examples/s]
Generating train split: 64673840 examples [59:43, 14577.41 examples/s]
Generating train split: 64678023 examples [59:43, 19980.00 examples/s]
Generating train split: 64682219 examples [59:43, 23510.92 examples/s]
Generating train split: 64685107 examples [59:43, 21844.44 examples/s]
Generating train split: 64688733 examples [59:44, 25075.53 examples/s]
Generating train split: 64692005 examples [59:44, 26914.74 examples/s]
Generating train split: 64695005 examples [59:44, 26050.69 examples/s]
Generating train split: 64697833 examples [59:44, 19506.63 examples/s]
Generating train split: 64700746 examples [59:44, 21542.72 examples/s]
Generating train split: 64704501 examples [59:44, 25258.32 examples/s]
Generating train split: 64707388 examples [59:44, 24795.14 examples/s]
Generating train split: 64710121 examples [59:45, 18468.34 examples/s]
Generating train split: 64713579 examples [59:45, 21796.56 examples/s]
Generating train split: 64717592 examples [59:45, 25925.41 examples/s]
Generating train split: 64720606 examples [59:45, 20457.96 examples/s]
Generating train split: 64724594 examples [59:45, 24538.23 examples/s]
Generating train split: 64730342 examples [59:45, 32144.78 examples/s]
Generating train split: 64734135 examples [59:45, 32188.85 examples/s]
Generating train split: 64739030 examples [59:45, 36437.87 examples/s]
Generating train split: 64745628 examples [59:46, 44286.04 examples/s]
Generating train split: 64750409 examples [59:46, 21165.24 examples/s]
Generating train split: 64754037 examples [59:46, 23027.42 examples/s]
Generating train split: 64757542 examples [59:47, 15139.35 examples/s]
Generating train split: 64760215 examples [59:47, 14139.27 examples/s]
Generating train split: 64764624 examples [59:47, 18283.45 examples/s]
Generating train split: 64768151 examples [59:47, 17208.19 examples/s]
Generating train split: 64770604 examples [59:47, 14831.50 examples/s]
Generating train split: 64772622 examples [59:48, 14047.09 examples/s]
Generating train split: 64775245 examples [59:48, 16083.16 examples/s]
Generating train split: 64777273 examples [59:48, 14533.12 examples/s]
Generating train split: 64779028 examples [59:48, 12725.36 examples/s]
Generating train split: 64781822 examples [59:48, 15571.80 examples/s]
Generating train split: 64783702 examples [59:48, 15399.38 examples/s]
Generating train split: 64785470 examples [59:49, 10480.37 examples/s]
Generating train split: 64787289 examples [59:49, 11798.44 examples/s]
Generating train split: 64790006 examples [59:49, 14834.90 examples/s]
Generating train split: 64791886 examples [59:49, 12521.03 examples/s]
Generating train split: 64793580 examples [59:49, 13196.58 examples/s]
Generating train split: 64795167 examples [59:49, 13365.51 examples/s]
Generating train split: 64796767 examples [59:49, 13944.76 examples/s]
Generating train split: 64798318 examples [59:50, 9591.41 examples/s] 
Generating train split: 64799656 examples [59:50, 10317.50 examples/s]
Generating train split: 64801242 examples [59:50, 11469.36 examples/s]
Generating train split: 64802828 examples [59:50, 12500.67 examples/s]
Generating train split: 64804250 examples [59:50, 11473.97 examples/s]
Generating train split: 64805860 examples [59:50, 12591.14 examples/s]
Generating train split: 64807248 examples [59:50, 9721.89 examples/s] 
Generating train split: 64809466 examples [59:51, 12293.38 examples/s]
Generating train split: 64810914 examples [59:51, 11665.04 examples/s]
Generating train split: 64812229 examples [59:51, 11963.06 examples/s]
Generating train split: 64813539 examples [59:51, 11964.48 examples/s]
Generating train split: 64818843 examples [59:51, 22567.20 examples/s]
Generating train split: 64824345 examples [59:51, 31051.91 examples/s]
Generating train split: 64832269 examples [59:51, 44352.89 examples/s]
Generating train split: 64836988 examples [59:51, 45084.01 examples/s]
Generating train split: 64841702 examples [59:51, 41789.51 examples/s]
Generating train split: 64847681 examples [59:52, 46702.24 examples/s]
Generating train split: 64854439 examples [59:52, 52551.74 examples/s]
Generating train split: 64859868 examples [59:52, 21665.72 examples/s]
Generating train split: 64863938 examples [59:53, 16550.86 examples/s]
Generating train split: 64867065 examples [59:53, 13259.25 examples/s]
Generating train split: 64869485 examples [59:53, 12744.46 examples/s]
Generating train split: 64871505 examples [59:54, 11822.04 examples/s]
Generating train split: 64873242 examples [59:54, 12553.00 examples/s]
Generating train split: 64876406 examples [59:54, 15579.53 examples/s]
Generating train split: 64878900 examples [59:54, 17306.24 examples/s]
Generating train split: 64883062 examples [59:54, 22378.01 examples/s]
Generating train split: 64885882 examples [59:54, 18997.51 examples/s]
Generating train split: 64888274 examples [59:55, 13482.28 examples/s]
Generating train split: 64890165 examples [59:55, 10939.17 examples/s]
Generating train split: 64891679 examples [59:55, 10907.39 examples/s]
Generating train split: 64893211 examples [59:55, 11601.00 examples/s]
Generating train split: 64894626 examples [59:55, 9678.67 examples/s] 
Generating train split: 64898470 examples [59:55, 14912.69 examples/s]
Generating train split: 64902247 examples [59:55, 19627.54 examples/s]
Generating train split: 64906869 examples [59:56, 25378.59 examples/s]
Generating train split: 64909953 examples [59:56, 17282.32 examples/s]
Generating train split: 64912389 examples [59:56, 10890.69 examples/s]
Generating train split: 64914268 examples [59:56, 11941.79 examples/s]
Generating train split: 64916276 examples [59:57, 13017.33 examples/s]
Generating train split: 64918125 examples [59:57, 10377.73 examples/s]
Generating train split: 64921665 examples [59:57, 14441.24 examples/s]
Generating train split: 64924272 examples [59:57, 16626.60 examples/s]
Generating train split: 64927315 examples [59:57, 19440.42 examples/s]
Generating train split: 64929793 examples [59:58, 10248.01 examples/s]
Generating train split: 64931659 examples [59:58, 9628.29 examples/s] 
Generating train split: 64933206 examples [59:58, 8185.83 examples/s]
Generating train split: 64934446 examples [59:59, 4507.52 examples/s]
Generating train split: 64935362 examples [1:00:00, 2898.74 examples/s]
Generating train split: 64936035 examples [1:00:00, 2518.52 examples/s]
Generating train split: 64936550 examples [1:00:01, 2379.27 examples/s]
Generating train split: 64937070 examples [1:00:01, 2613.74 examples/s]
Generating train split: 64938688 examples [1:00:01, 4080.41 examples/s]
Generating train split: 64940514 examples [1:00:01, 5989.89 examples/s]
Generating train split: 64941607 examples [1:00:01, 6786.61 examples/s]
Generating train split: 64943059 examples [1:00:01, 8206.10 examples/s]
Generating train split: 64944252 examples [1:00:01, 8522.73 examples/s]
Generating train split: 64947169 examples [1:00:01, 13071.60 examples/s]
Generating train split: 64948821 examples [1:00:02, 12434.30 examples/s]
Generating train split: 64950309 examples [1:00:02, 12564.34 examples/s]
Generating train split: 64951739 examples [1:00:02, 10922.76 examples/s]
Generating train split: 64953060 examples [1:00:02, 11257.58 examples/s]
Generating train split: 64954306 examples [1:00:02, 11533.23 examples/s]
Generating train split: 64957153 examples [1:00:02, 15880.68 examples/s]
Generating train split: 64961821 examples [1:00:02, 24141.14 examples/s]
Generating train split: 64965311 examples [1:00:02, 23481.07 examples/s]
Generating train split: 64967806 examples [1:00:03, 21261.77 examples/s]
Generating train split: 64970068 examples [1:00:03, 20141.15 examples/s]
Generating train split: 64972171 examples [1:00:03, 17941.16 examples/s]
Generating train split: 64975001 examples [1:00:03, 20387.30 examples/s]
Generating train split: 64977182 examples [1:00:03, 14829.11 examples/s]
Generating train split: 64978957 examples [1:00:03, 12758.43 examples/s]
Generating train split: 64980696 examples [1:00:03, 13653.81 examples/s]
Generating train split: 64982267 examples [1:00:04, 12976.32 examples/s]
Generating train split: 64984048 examples [1:00:04, 14043.55 examples/s]
Generating train split: 64990207 examples [1:00:04, 23862.93 examples/s]
Generating train split: 64992726 examples [1:00:04, 12510.70 examples/s]
Generating train split: 64994654 examples [1:00:04, 12114.87 examples/s]
Generating train split: 65002455 examples [1:00:05, 22862.78 examples/s]
Generating train split: 65005962 examples [1:00:05, 18080.06 examples/s]
Generating train split: 65008759 examples [1:00:05, 17376.75 examples/s]
Generating train split: 65011184 examples [1:00:05, 14608.50 examples/s]
Generating train split: 65013168 examples [1:00:05, 15063.11 examples/s]
Generating train split: 65015073 examples [1:00:06, 10696.69 examples/s]
Generating train split: 65016989 examples [1:00:06, 11962.43 examples/s]
Generating train split: 65018611 examples [1:00:06, 11336.72 examples/s]
Generating train split: 65020041 examples [1:00:06, 11874.57 examples/s]
Generating train split: 65021465 examples [1:00:06, 9847.15 examples/s] 
Generating train split: 65028885 examples [1:00:07, 22145.28 examples/s]
Generating train split: 65035891 examples [1:00:07, 31823.82 examples/s]
Generating train split: 65039967 examples [1:00:07, 22658.94 examples/s]
Generating train split: 65043207 examples [1:00:07, 15731.20 examples/s]
Generating train split: 65045725 examples [1:00:07, 16730.85 examples/s]
Generating train split: 65048141 examples [1:00:08, 12839.86 examples/s]
Generating train split: 65055617 examples [1:00:08, 21831.32 examples/s]
Generating train split: 65063046 examples [1:00:08, 30839.04 examples/s]
Generating train split: 65067787 examples [1:00:09, 16190.28 examples/s]
Generating train split: 65071320 examples [1:00:09, 14254.83 examples/s]
Generating train split: 65074097 examples [1:00:09, 13326.75 examples/s]
Generating train split: 65076359 examples [1:00:10, 11352.44 examples/s]
Generating train split: 65078148 examples [1:00:10, 10689.49 examples/s]
Generating train split: 65079856 examples [1:00:10, 11527.49 examples/s]
Generating train split: 65081426 examples [1:00:10, 11644.12 examples/s]
Generating train split: 65082894 examples [1:00:11, 6627.68 examples/s] 
Generating train split: 65083993 examples [1:00:11, 6025.63 examples/s]
Generating train split: 65084893 examples [1:00:11, 6395.63 examples/s]
Generating train split: 65085798 examples [1:00:11, 5241.05 examples/s]
Generating train split: 65086659 examples [1:00:11, 5723.28 examples/s]
Generating train split: 65095025 examples [1:00:11, 19054.56 examples/s]
Generating train split: 65103743 examples [1:00:12, 32427.60 examples/s]
Generating train split: 65108497 examples [1:00:12, 32527.31 examples/s]
Generating train split: 65116285 examples [1:00:12, 42570.80 examples/s]
Generating train split: 65124743 examples [1:00:12, 51724.09 examples/s]
Generating train split: 65130844 examples [1:00:13, 24101.59 examples/s]
Generating train split: 65135424 examples [1:00:13, 26502.45 examples/s]
Generating train split: 65139810 examples [1:00:13, 19622.69 examples/s]
Generating train split: 65143205 examples [1:00:13, 20233.82 examples/s]
Generating train split: 65146270 examples [1:00:14, 15786.82 examples/s]
Generating train split: 65148683 examples [1:00:14, 16601.90 examples/s]
Generating train split: 65151003 examples [1:00:14, 15325.03 examples/s]
Generating train split: 65152995 examples [1:00:14, 12509.06 examples/s]
Generating train split: 65155185 examples [1:00:14, 13956.78 examples/s]
Generating train split: 65157683 examples [1:00:14, 15306.03 examples/s]
Generating train split: 65159541 examples [1:00:15, 13307.32 examples/s]
Generating train split: 65161138 examples [1:00:15, 13650.79 examples/s]
Generating train split: 65162824 examples [1:00:15, 14333.26 examples/s]
Generating train split: 65164998 examples [1:00:15, 16061.27 examples/s]
Generating train split: 65166778 examples [1:00:15, 15474.66 examples/s]
Generating train split: 65168441 examples [1:00:15, 10662.78 examples/s]
Generating train split: 65169783 examples [1:00:15, 11020.37 examples/s]
Generating train split: 65171095 examples [1:00:15, 11017.18 examples/s]
Generating train split: 65172492 examples [1:00:16, 11545.72 examples/s]
Generating train split: 65174312 examples [1:00:16, 13156.23 examples/s]
Generating train split: 65175754 examples [1:00:16, 11915.62 examples/s]
Generating train split: 65177049 examples [1:00:16, 9980.16 examples/s] 
Generating train split: 65183838 examples [1:00:16, 22914.98 examples/s]
Generating train split: 65192274 examples [1:00:16, 37772.22 examples/s]
Generating train split: 65196937 examples [1:00:16, 39146.62 examples/s]
Generating train split: 65201370 examples [1:00:17, 33771.91 examples/s]
Generating train split: 65205241 examples [1:00:17, 32391.68 examples/s]
Generating train split: 65214485 examples [1:00:17, 46826.05 examples/s]
Generating train split: 65221855 examples [1:00:17, 53142.58 examples/s]
Generating train split: 65227685 examples [1:00:17, 38750.30 examples/s]
Generating train split: 65232828 examples [1:00:17, 41416.49 examples/s]
Generating train split: 65241028 examples [1:00:17, 50843.40 examples/s]
Generating train split: 65246900 examples [1:00:18, 35122.94 examples/s]
Generating train split: 65251599 examples [1:00:18, 32444.12 examples/s]
Generating train split: 65256815 examples [1:00:18, 36213.40 examples/s]
Generating train split: 65261227 examples [1:00:18, 23719.58 examples/s]
Generating train split: 65264675 examples [1:00:18, 24970.52 examples/s]
Generating train split: 65269076 examples [1:00:18, 28344.83 examples/s]
Generating train split: 65272698 examples [1:00:19, 17437.21 examples/s]
Generating train split: 65275478 examples [1:00:19, 18739.12 examples/s]
Generating train split: 65278202 examples [1:00:19, 18614.06 examples/s]
Generating train split: 65282280 examples [1:00:19, 22575.12 examples/s]
Generating train split: 65285189 examples [1:00:20, 17140.78 examples/s]
Generating train split: 65287523 examples [1:00:20, 15979.18 examples/s]
Generating train split: 65289542 examples [1:00:20, 15044.38 examples/s]
Generating train split: 65291335 examples [1:00:20, 13372.67 examples/s]
Generating train split: 65292878 examples [1:00:20, 12350.95 examples/s]
Generating train split: 65294244 examples [1:00:20, 10471.87 examples/s]
Generating train split: 65295408 examples [1:00:21, 10308.30 examples/s]
Generating train split: 65296696 examples [1:00:21, 10830.97 examples/s]
Generating train split: 65297863 examples [1:00:21, 9447.53 examples/s] 
Generating train split: 65299990 examples [1:00:21, 11828.32 examples/s]
Generating train split: 65302652 examples [1:00:21, 15280.15 examples/s]
Generating train split: 65304362 examples [1:00:21, 14673.97 examples/s]
Generating train split: 65306009 examples [1:00:21, 15085.56 examples/s]
Generating train split: 65308335 examples [1:00:21, 16419.03 examples/s]
Generating train split: 65310048 examples [1:00:22, 11424.31 examples/s]
Generating train split: 65314032 examples [1:00:22, 17265.53 examples/s]
Generating train split: 65318591 examples [1:00:22, 23690.64 examples/s]
Generating train split: 65321479 examples [1:00:22, 24682.93 examples/s]
Generating train split: 65327701 examples [1:00:22, 34318.94 examples/s]
Generating train split: 65332924 examples [1:00:22, 39115.77 examples/s]
Generating train split: 65337378 examples [1:00:22, 40613.77 examples/s]
Generating train split: 65341700 examples [1:00:22, 38413.98 examples/s]
Generating train split: 65345748 examples [1:00:23, 32919.88 examples/s]
Generating train split: 65349307 examples [1:00:23, 32729.25 examples/s]
Generating train split: 65352768 examples [1:00:23, 29673.54 examples/s]
Generating train split: 65360768 examples [1:00:23, 42015.72 examples/s]
Generating train split: 65365349 examples [1:00:23, 21082.24 examples/s]
Generating train split: 65368834 examples [1:00:24, 22602.29 examples/s]
Generating train split: 65372160 examples [1:00:24, 20485.00 examples/s]
Generating train split: 65374963 examples [1:00:24, 13819.17 examples/s]
Generating train split: 65377970 examples [1:00:24, 16033.31 examples/s]
Generating train split: 65381733 examples [1:00:24, 19549.17 examples/s]
Generating train split: 65384581 examples [1:00:25, 19446.16 examples/s]
Generating train split: 65387138 examples [1:00:25, 12472.11 examples/s]
Generating train split: 65389795 examples [1:00:25, 14442.15 examples/s]
Generating train split: 65392992 examples [1:00:25, 17446.69 examples/s]
Generating train split: 65396827 examples [1:00:25, 20384.31 examples/s]
Generating train split: 65399438 examples [1:00:26, 13503.27 examples/s]
Generating train split: 65401509 examples [1:00:26, 14635.11 examples/s]
Generating train split: 65403846 examples [1:00:26, 16056.59 examples/s]
Generating train split: 65405940 examples [1:00:26, 13235.32 examples/s]
Generating train split: 65408698 examples [1:00:26, 15879.15 examples/s]
Generating train split: 65411875 examples [1:00:26, 19206.12 examples/s]
Generating train split: 65414254 examples [1:00:27, 16397.18 examples/s]
Generating train split: 65418973 examples [1:00:27, 22862.15 examples/s]
Generating train split: 65422719 examples [1:00:27, 26097.88 examples/s]
Generating train split: 65425801 examples [1:00:27, 15284.68 examples/s]
Generating train split: 65428184 examples [1:00:27, 16507.43 examples/s]
Generating train split: 65430517 examples [1:00:27, 16820.66 examples/s]
Generating train split: 65432683 examples [1:00:28, 11835.86 examples/s]
Generating train split: 65434533 examples [1:00:28, 12865.04 examples/s]
Generating train split: 65436274 examples [1:00:28, 13375.71 examples/s]
Generating train split: 65438332 examples [1:00:28, 14820.56 examples/s]
Generating train split: 65440989 examples [1:00:28, 17489.94 examples/s]
Generating train split: 65443411 examples [1:00:28, 19134.12 examples/s]
Generating train split: 65445604 examples [1:00:29, 13517.45 examples/s]
Generating train split: 65447389 examples [1:00:29, 9295.39 examples/s] 
Generating train split: 65448760 examples [1:00:29, 7861.55 examples/s]
Generating train split: 65451047 examples [1:00:29, 10110.53 examples/s]
Generating train split: 65453374 examples [1:00:29, 12300.42 examples/s]
Generating train split: 65455056 examples [1:00:30, 12858.17 examples/s]
Generating train split: 65456687 examples [1:00:30, 6341.65 examples/s] 
Generating train split: 65458111 examples [1:00:30, 7336.31 examples/s]
Generating train split: 65459394 examples [1:00:30, 8001.58 examples/s]
Generating train split: 65460632 examples [1:00:31, 8251.35 examples/s]
Generating train split: 65461892 examples [1:00:31, 8975.95 examples/s]
Generating train split: 65463044 examples [1:00:31, 8742.41 examples/s]
Generating train split: 65467775 examples [1:00:31, 17155.50 examples/s]
Generating train split: 65470445 examples [1:00:31, 18673.53 examples/s]
Generating train split: 65472638 examples [1:00:31, 17564.23 examples/s]
Generating train split: 65474631 examples [1:00:31, 16012.99 examples/s]
Generating train split: 65476416 examples [1:00:32, 12409.84 examples/s]
Generating train split: 65477891 examples [1:00:32, 11540.73 examples/s]
Generating train split: 65479220 examples [1:00:32, 10590.25 examples/s]
Generating train split: 65480397 examples [1:00:32, 10049.42 examples/s]
Generating train split: 65481481 examples [1:00:32, 10071.41 examples/s]
Generating train split: 65482544 examples [1:00:32, 9762.71 examples/s] 
Generating train split: 65483551 examples [1:00:32, 9350.83 examples/s]
Generating train split: 65484510 examples [1:00:32, 9351.76 examples/s]
Generating train split: 65485816 examples [1:00:33, 10266.91 examples/s]
Generating train split: 65486865 examples [1:00:33, 9030.03 examples/s] 
Generating train split: 65488212 examples [1:00:33, 10130.82 examples/s]
Generating train split: 65489998 examples [1:00:33, 12166.37 examples/s]
Generating train split: 65493397 examples [1:00:33, 18143.21 examples/s]
Generating train split: 65495310 examples [1:00:33, 12776.85 examples/s]
Generating train split: 65496873 examples [1:00:33, 9906.06 examples/s] 
Generating train split: 65498147 examples [1:00:34, 9972.42 examples/s]
Generating train split: 65499998 examples [1:00:34, 11707.41 examples/s]
Generating train split: 65501394 examples [1:00:34, 11841.18 examples/s]
Generating train split: 65504481 examples [1:00:34, 16341.06 examples/s]
Generating train split: 65506342 examples [1:00:34, 7971.24 examples/s] 
Generating train split: 65508000 examples [1:00:35, 9224.54 examples/s]
Generating train split: 65510660 examples [1:00:35, 12169.50 examples/s]
Generating train split: 65513717 examples [1:00:35, 15783.41 examples/s]
Generating train split: 65515910 examples [1:00:35, 16870.61 examples/s]
Generating train split: 65518058 examples [1:00:35, 15225.32 examples/s]
Generating train split: 65519932 examples [1:00:35, 14036.12 examples/s]
Generating train split: 65521953 examples [1:00:35, 15321.46 examples/s]
Generating train split: 65524310 examples [1:00:35, 17215.59 examples/s]
Generating train split: 65527472 examples [1:00:36, 20745.32 examples/s]
Generating train split: 65529761 examples [1:00:36, 14149.88 examples/s]
Generating train split: 65531593 examples [1:00:36, 13964.53 examples/s]
Generating train split: 65533998 examples [1:00:36, 16073.18 examples/s]
Generating train split: 65535901 examples [1:00:36, 15292.18 examples/s]
Generating train split: 65537647 examples [1:00:36, 13600.30 examples/s]
Generating train split: 65539174 examples [1:00:37, 11267.03 examples/s]
Generating train split: 65541220 examples [1:00:37, 13123.97 examples/s]
Generating train split: 65542731 examples [1:00:37, 11365.36 examples/s]
Generating train split: 65544034 examples [1:00:37, 10474.51 examples/s]
Generating train split: 65546845 examples [1:00:37, 14227.36 examples/s]
Generating train split: 65551883 examples [1:00:37, 22658.82 examples/s]
Generating train split: 65555794 examples [1:00:37, 26635.68 examples/s]
Generating train split: 65558818 examples [1:00:38, 18673.16 examples/s]
Generating train split: 65565889 examples [1:00:38, 28956.53 examples/s]
Generating train split: 65569644 examples [1:00:38, 29027.57 examples/s]
Generating train split: 65573144 examples [1:00:38, 17720.68 examples/s]
Generating train split: 65575847 examples [1:00:38, 16457.94 examples/s]
Generating train split: 65578139 examples [1:00:39, 15087.09 examples/s]
Generating train split: 65580089 examples [1:00:39, 14312.95 examples/s]
Generating train split: 65581817 examples [1:00:39, 13069.39 examples/s]
Generating train split: 65584044 examples [1:00:39, 14750.81 examples/s]
Generating train split: 65586186 examples [1:00:39, 16109.21 examples/s]
Generating train split: 65588028 examples [1:00:39, 14443.18 examples/s]
Generating train split: 65589652 examples [1:00:39, 14070.45 examples/s]
Generating train split: 65592368 examples [1:00:40, 17032.62 examples/s]
Generating train split: 65594248 examples [1:00:40, 12402.31 examples/s]
Generating train split: 65595905 examples [1:00:40, 13226.93 examples/s]
Generating train split: 65597474 examples [1:00:40, 11409.68 examples/s]
Generating train split: 65599356 examples [1:00:40, 12829.77 examples/s]
Generating train split: 65600835 examples [1:00:40, 11809.31 examples/s]
Generating train split: 65602329 examples [1:00:41, 12500.78 examples/s]
Generating train split: 65603796 examples [1:00:41, 13016.68 examples/s]
Generating train split: 65605197 examples [1:00:41, 11489.53 examples/s]
Generating train split: 65606439 examples [1:00:41, 11545.66 examples/s]
Generating train split: 65609067 examples [1:00:41, 15200.16 examples/s]
Generating train split: 65610702 examples [1:00:41, 14358.44 examples/s]
Generating train split: 65612223 examples [1:00:41, 13780.73 examples/s]
Generating train split: 65613664 examples [1:00:41, 12514.71 examples/s]
Generating train split: 65618202 examples [1:00:41, 20717.69 examples/s]
Generating train split: 65620478 examples [1:00:42, 20223.05 examples/s]
Generating train split: 65623662 examples [1:00:42, 23262.96 examples/s]
Generating train split: 65626137 examples [1:00:42, 18636.68 examples/s]
Generating train split: 65629403 examples [1:00:42, 21910.82 examples/s]
Generating train split: 65635112 examples [1:00:42, 30740.93 examples/s]
Generating train split: 65639773 examples [1:00:42, 26211.37 examples/s]
Generating train split: 65642791 examples [1:00:43, 20454.97 examples/s]
Generating train split: 65645277 examples [1:00:43, 21147.07 examples/s]
Generating train split: 65647740 examples [1:00:43, 16513.24 examples/s]
Generating train split: 65649753 examples [1:00:43, 15269.15 examples/s]
Generating train split: 65652114 examples [1:00:43, 16865.38 examples/s]
Generating train split: 65654441 examples [1:00:43, 18240.90 examples/s]
Generating train split: 65656500 examples [1:00:43, 15218.42 examples/s]
Generating train split: 65658894 examples [1:00:44, 17074.16 examples/s]
Generating train split: 65660849 examples [1:00:44, 15708.29 examples/s]
Generating train split: 65662601 examples [1:00:44, 14380.83 examples/s]
Generating train split: 65664173 examples [1:00:44, 14625.47 examples/s]
Generating train split: 65667429 examples [1:00:44, 18975.05 examples/s]
Generating train split: 65670088 examples [1:00:44, 20927.16 examples/s]
Generating train split: 65672336 examples [1:00:44, 20326.40 examples/s]
Generating train split: 65674478 examples [1:00:44, 19568.70 examples/s]
Generating train split: 65678434 examples [1:00:45, 23601.49 examples/s]
Generating train split: 65682907 examples [1:00:45, 29199.24 examples/s]
Generating train split: 65685935 examples [1:00:45, 24165.80 examples/s]
Generating train split: 65688568 examples [1:00:45, 10771.46 examples/s]
Generating train split: 65691603 examples [1:00:46, 13346.76 examples/s]
Generating train split: 65694275 examples [1:00:46, 15454.94 examples/s]
Generating train split: 65698156 examples [1:00:46, 19685.22 examples/s]
Generating train split: 65700974 examples [1:00:46, 14316.64 examples/s]
Generating train split: 65703208 examples [1:00:47, 8623.44 examples/s] 
Generating train split: 65705596 examples [1:00:47, 10318.68 examples/s]
Generating train split: 65709397 examples [1:00:47, 14206.99 examples/s]
Generating train split: 65712611 examples [1:00:47, 17074.71 examples/s]
Generating train split: 65715283 examples [1:00:48, 10122.15 examples/s]
Generating train split: 65717272 examples [1:00:48, 10694.57 examples/s]
Generating train split: 65721570 examples [1:00:48, 15420.64 examples/s]
Generating train split: 65725721 examples [1:00:48, 19931.26 examples/s]
Generating train split: 65728742 examples [1:00:48, 13079.50 examples/s]
Generating train split: 65733256 examples [1:00:48, 17699.99 examples/s]
Generating train split: 65736244 examples [1:00:49, 17488.41 examples/s]
Generating train split: 65738841 examples [1:00:49, 12407.09 examples/s]
Generating train split: 65740856 examples [1:00:50, 6948.64 examples/s] 
Generating train split: 65742371 examples [1:00:50, 5936.60 examples/s]
Generating train split: 65743868 examples [1:00:50, 6779.40 examples/s]
Generating train split: 65746197 examples [1:00:50, 8726.93 examples/s]
Generating train split: 65749227 examples [1:00:51, 11840.81 examples/s]
Generating train split: 65751248 examples [1:00:51, 7498.38 examples/s] 
Generating train split: 65753589 examples [1:00:51, 9346.83 examples/s]
Generating train split: 65756277 examples [1:00:51, 11837.94 examples/s]
Generating train split: 65759433 examples [1:00:51, 14766.14 examples/s]
Generating train split: 65761614 examples [1:00:52, 12029.89 examples/s]
Generating train split: 65763387 examples [1:00:52, 10522.03 examples/s]
Generating train split: 65764852 examples [1:00:52, 10520.18 examples/s]
Generating train split: 65766198 examples [1:00:52, 10760.90 examples/s]
Generating train split: 65768437 examples [1:00:52, 12880.93 examples/s]
Generating train split: 65769968 examples [1:00:53, 9334.00 examples/s] 
Generating train split: 65771186 examples [1:00:53, 8816.28 examples/s]
Generating train split: 65773555 examples [1:00:53, 11586.55 examples/s]
Generating train split: 65775551 examples [1:00:53, 12980.06 examples/s]
Generating train split: 65777102 examples [1:00:53, 9067.48 examples/s] 
Generating train split: 65779409 examples [1:00:53, 11355.81 examples/s]
Generating train split: 65781808 examples [1:00:53, 13864.28 examples/s]
Generating train split: 65783575 examples [1:00:54, 11102.16 examples/s]
Generating train split: 65788182 examples [1:00:54, 17850.40 examples/s]
Generating train split: 65792283 examples [1:00:54, 22757.78 examples/s]
Generating train split: 65798056 examples [1:00:54, 30420.58 examples/s]
Generating train split: 65803480 examples [1:00:54, 36317.65 examples/s]
Generating train split: 65807649 examples [1:00:54, 23025.30 examples/s]
Generating train split: 65810929 examples [1:00:55, 20549.92 examples/s]
Generating train split: 65813691 examples [1:00:55, 19404.39 examples/s]
Generating train split: 65816112 examples [1:00:55, 19270.50 examples/s]
Generating train split: 65818374 examples [1:00:55, 19709.28 examples/s]
Generating train split: 65821016 examples [1:00:55, 20975.94 examples/s]
Generating train split: 65823343 examples [1:00:55, 14911.78 examples/s]
Generating train split: 65825215 examples [1:00:56, 15130.90 examples/s]
Generating train split: 65826998 examples [1:00:56, 9283.54 examples/s] 
Generating train split: 65828384 examples [1:00:56, 9835.68 examples/s]
Generating train split: 65829725 examples [1:00:56, 9681.27 examples/s]
Generating train split: 65830940 examples [1:00:57, 7254.84 examples/s]
Generating train split: 65832403 examples [1:00:57, 8438.31 examples/s]
Generating train split: 65834643 examples [1:00:57, 10986.84 examples/s]
Generating train split: 65836100 examples [1:00:57, 7260.96 examples/s] 
Generating train split: 65837225 examples [1:00:57, 7439.65 examples/s]
Generating train split: 65839377 examples [1:00:57, 9387.51 examples/s]
Generating train split: 65840594 examples [1:00:58, 9865.94 examples/s]
Generating train split: 65841802 examples [1:00:58, 10087.50 examples/s]
Generating train split: 65842970 examples [1:00:58, 9944.61 examples/s] 
Generating train split: 65844617 examples [1:00:58, 11438.48 examples/s]
Generating train split: 65845877 examples [1:00:58, 9392.96 examples/s] 
Generating train split: 65847277 examples [1:00:58, 10422.01 examples/s]
Generating train split: 65848452 examples [1:00:58, 9253.61 examples/s] 
Generating train split: 65849495 examples [1:00:58, 9481.86 examples/s]
Generating train split: 65851591 examples [1:00:59, 11769.27 examples/s]
Generating train split: 65852864 examples [1:00:59, 6219.75 examples/s] 
Generating train split: 65853820 examples [1:00:59, 6186.72 examples/s]
Generating train split: 65854731 examples [1:00:59, 6682.13 examples/s]
Generating train split: 65855683 examples [1:00:59, 7236.95 examples/s]
Generating train split: 65856577 examples [1:01:00, 7404.30 examples/s]
Generating train split: 65857822 examples [1:01:00, 8572.05 examples/s]
Generating train split: 65859995 examples [1:01:00, 11842.47 examples/s]
Generating train split: 65861330 examples [1:01:00, 11015.87 examples/s]
Generating train split: 65862770 examples [1:01:00, 11846.67 examples/s]
Generating train split: 65864051 examples [1:01:00, 8734.98 examples/s] 
Generating train split: 65865114 examples [1:01:00, 7558.51 examples/s]
Generating train split: 65866021 examples [1:01:01, 7260.17 examples/s]
Generating train split: 65866851 examples [1:01:01, 7354.53 examples/s]
Generating train split: 65867658 examples [1:01:01, 6386.04 examples/s]
Generating train split: 65868367 examples [1:01:01, 6531.34 examples/s]
Generating train split: 65869270 examples [1:01:01, 7118.58 examples/s]
Generating train split: 65870663 examples [1:01:01, 8653.60 examples/s]
Generating train split: 65871590 examples [1:01:01, 8563.20 examples/s]
Generating train split: 65872739 examples [1:01:01, 9159.34 examples/s]
Generating train split: 65873685 examples [1:01:02, 7907.32 examples/s]
Generating train split: 65874721 examples [1:01:02, 8505.08 examples/s]
Generating train split: 65876397 examples [1:01:02, 10660.18 examples/s]
Generating train split: 65877533 examples [1:01:02, 10044.63 examples/s]
Generating train split: 65878588 examples [1:01:02, 7857.72 examples/s] 
Generating train split: 65879477 examples [1:01:02, 6536.33 examples/s]
Generating train split: 65880228 examples [1:01:02, 6326.66 examples/s]
Generating train split: 65880927 examples [1:01:03, 4600.11 examples/s]
Generating train split: 65881563 examples [1:01:03, 4913.10 examples/s]
Generating train split: 65883995 examples [1:01:03, 8890.28 examples/s]
Generating train split: 65886113 examples [1:01:03, 11663.73 examples/s]
Generating train split: 65889961 examples [1:01:03, 18213.02 examples/s]
Generating train split: 65892122 examples [1:01:03, 16370.76 examples/s]
Generating train split: 65894025 examples [1:01:03, 15059.95 examples/s]
Generating train split: 65895731 examples [1:01:04, 13748.24 examples/s]
Generating train split: 65897258 examples [1:01:04, 13427.60 examples/s]
Generating train split: 65898702 examples [1:01:04, 12059.61 examples/s]
Generating train split: 65899998 examples [1:01:04, 9748.85 examples/s] 
Generating train split: 65901491 examples [1:01:04, 10816.46 examples/s]
Generating train split: 65903298 examples [1:01:04, 12464.78 examples/s]
Generating train split: 65904689 examples [1:01:05, 8151.17 examples/s] 
Generating train split: 65905789 examples [1:01:05, 7445.37 examples/s]
Generating train split: 65908983 examples [1:01:05, 11915.91 examples/s]
Generating train split: 65913476 examples [1:01:05, 18749.49 examples/s]
Generating train split: 65915956 examples [1:01:05, 15102.07 examples/s]
Generating train split: 65918003 examples [1:01:05, 14186.90 examples/s]
Generating train split: 65920508 examples [1:01:06, 16335.22 examples/s]
Generating train split: 65928957 examples [1:01:06, 31345.81 examples/s]
Generating train split: 65934547 examples [1:01:06, 36636.53 examples/s]
Generating train split: 65938873 examples [1:01:06, 31289.43 examples/s]
Generating train split: 65942596 examples [1:01:06, 19046.28 examples/s]
Generating train split: 65946348 examples [1:01:07, 18586.69 examples/s]
Generating train split: 65948884 examples [1:01:07, 19634.82 examples/s]
Generating train split: 65951409 examples [1:01:07, 15317.62 examples/s]
Generating train split: 65953445 examples [1:01:07, 12258.56 examples/s]
Generating train split: 65955083 examples [1:01:08, 9732.20 examples/s] 
Generating train split: 65956786 examples [1:01:08, 10749.39 examples/s]
Generating train split: 65958994 examples [1:01:08, 12638.42 examples/s]
Generating train split: 65960658 examples [1:01:08, 11546.63 examples/s]
Generating train split: 65962089 examples [1:01:08, 11293.71 examples/s]
Generating train split: 65965890 examples [1:01:08, 16739.99 examples/s]
Generating train split: 65971626 examples [1:01:08, 25900.35 examples/s]
Generating train split: 65974794 examples [1:01:09, 19896.97 examples/s]
Generating train split: 65977865 examples [1:01:09, 22007.50 examples/s]
Generating train split: 65980735 examples [1:01:09, 23469.15 examples/s]
Generating train split: 65985645 examples [1:01:09, 29653.13 examples/s]
Generating train split: 65989165 examples [1:01:09, 31069.26 examples/s]
Generating train split: 65996121 examples [1:01:09, 41384.47 examples/s]
Generating train split: 66000615 examples [1:01:10, 18183.03 examples/s]
Generating train split: 66003998 examples [1:01:10, 15461.74 examples/s]
Generating train split: 66006897 examples [1:01:10, 17291.71 examples/s]
Generating train split: 66010026 examples [1:01:10, 19552.27 examples/s]
Generating train split: 66012884 examples [1:01:11, 12590.83 examples/s]
Generating train split: 66015071 examples [1:01:11, 11022.08 examples/s]
Generating train split: 66018095 examples [1:01:11, 13581.98 examples/s]
Generating train split: 66021562 examples [1:01:11, 16975.18 examples/s]
Generating train split: 66024098 examples [1:01:11, 13768.57 examples/s]
Generating train split: 66026136 examples [1:01:12, 12980.39 examples/s]
Generating train split: 66028497 examples [1:01:12, 14797.32 examples/s]
Generating train split: 66033236 examples [1:01:12, 21197.69 examples/s]
Generating train split: 66036018 examples [1:01:12, 14553.57 examples/s]
Generating train split: 66038197 examples [1:01:12, 14852.85 examples/s]
Generating train split: 66040437 examples [1:01:12, 16041.12 examples/s]
Generating train split: 66042477 examples [1:01:13, 13286.54 examples/s]
Generating train split: 66044667 examples [1:01:13, 14343.12 examples/s]
Generating train split: 66046791 examples [1:01:13, 15751.87 examples/s]
Generating train split: 66049769 examples [1:01:13, 18915.60 examples/s]
Generating train split: 66051958 examples [1:01:13, 12905.36 examples/s]
Generating train split: 66053698 examples [1:01:13, 12796.26 examples/s]
Generating train split: 66055482 examples [1:01:13, 13787.93 examples/s]
Generating train split: 66058463 examples [1:01:14, 17328.09 examples/s]
Generating train split: 66060512 examples [1:01:14, 12717.00 examples/s]
Generating train split: 66062643 examples [1:01:14, 14372.60 examples/s]
Generating train split: 66064448 examples [1:01:14, 14711.24 examples/s]
Generating train split: 66066189 examples [1:01:14, 13634.82 examples/s]
Generating train split: 66067748 examples [1:01:14, 11559.36 examples/s]
Generating train split: 66069667 examples [1:01:14, 13111.55 examples/s]
Generating train split: 66071412 examples [1:01:15, 14105.19 examples/s]
Generating train split: 66074640 examples [1:01:15, 18592.92 examples/s]
Generating train split: 66076709 examples [1:01:15, 14024.89 examples/s]
Generating train split: 66078413 examples [1:01:15, 12842.73 examples/s]
Generating train split: 66080729 examples [1:01:15, 15019.10 examples/s]
Generating train split: 66083331 examples [1:01:15, 17517.19 examples/s]
Generating train split: 66085328 examples [1:01:16, 13478.31 examples/s]
Generating train split: 66086978 examples [1:01:16, 13757.66 examples/s]
Generating train split: 66088576 examples [1:01:16, 14221.96 examples/s]
Generating train split: 66090165 examples [1:01:16, 13681.32 examples/s]
Generating train split: 66091655 examples [1:01:16, 13497.03 examples/s]
Generating train split: 66093086 examples [1:01:16, 13663.64 examples/s]
Generating train split: 66095368 examples [1:01:16, 16064.13 examples/s]
Generating train split: 66097297 examples [1:01:16, 16947.23 examples/s]
Generating train split: 66101725 examples [1:01:16, 22921.80 examples/s]
Generating train split: 66106484 examples [1:01:17, 29629.25 examples/s]
Generating train split: 66113062 examples [1:01:17, 39739.34 examples/s]
Generating train split: 66118217 examples [1:01:17, 43105.11 examples/s]
Generating train split: 66123343 examples [1:01:17, 45467.15 examples/s]
Generating train split: 66127983 examples [1:01:17, 42174.22 examples/s]
Generating train split: 66132302 examples [1:01:18, 18460.82 examples/s]
Generating train split: 66136829 examples [1:01:18, 22411.48 examples/s]
Generating train split: 66140467 examples [1:01:18, 23034.10 examples/s]
Generating train split: 66143793 examples [1:01:18, 14202.13 examples/s]
Generating train split: 66146305 examples [1:01:19, 12137.96 examples/s]
Generating train split: 66148295 examples [1:01:19, 10144.50 examples/s]
Generating train split: 66149870 examples [1:01:19, 10527.11 examples/s]
Generating train split: 66151356 examples [1:01:19, 10602.45 examples/s]
Generating train split: 66152727 examples [1:01:19, 10829.33 examples/s]
Generating train split: 66154049 examples [1:01:19, 10962.66 examples/s]
Generating train split: 66155438 examples [1:01:20, 11563.26 examples/s]
Generating train split: 66156741 examples [1:01:20, 10564.80 examples/s]
Generating train split: 66157915 examples [1:01:20, 8715.55 examples/s] 
Generating train split: 66158897 examples [1:01:20, 7058.65 examples/s]
Generating train split: 66161448 examples [1:01:20, 10317.70 examples/s]
Generating train split: 66162713 examples [1:01:20, 7723.43 examples/s] 
Generating train split: 66165636 examples [1:01:21, 10480.70 examples/s]
Generating train split: 66166919 examples [1:01:21, 9371.35 examples/s] 
Generating train split: 66169472 examples [1:01:21, 12181.88 examples/s]
Generating train split: 66171242 examples [1:01:21, 13317.22 examples/s]
Generating train split: 66172818 examples [1:01:21, 10597.61 examples/s]
Generating train split: 66174725 examples [1:01:21, 12268.94 examples/s]
Generating train split: 66179057 examples [1:01:22, 15230.15 examples/s]
Generating train split: 66180699 examples [1:01:22, 14133.99 examples/s]
Generating train split: 66182179 examples [1:01:22, 10506.07 examples/s]
Generating train split: 66183383 examples [1:01:22, 10296.03 examples/s]
Generating train split: 66184513 examples [1:01:22, 9010.70 examples/s] 
Generating train split: 66185491 examples [1:01:23, 7941.50 examples/s]
Generating train split: 66189825 examples [1:01:23, 14806.05 examples/s]
Generating train split: 66196708 examples [1:01:23, 26523.67 examples/s]
Generating train split: 66200227 examples [1:01:23, 28573.92 examples/s]
Generating train split: 66203659 examples [1:01:23, 19174.17 examples/s]
Generating train split: 66206377 examples [1:01:23, 16635.24 examples/s]
Generating train split: 66208639 examples [1:01:24, 15225.22 examples/s]
Generating train split: 66210577 examples [1:01:24, 13483.00 examples/s]
Generating train split: 66213195 examples [1:01:24, 15735.07 examples/s]
Generating train split: 66215244 examples [1:01:24, 16680.83 examples/s]
Generating train split: 66217226 examples [1:01:24, 14167.32 examples/s]
Generating train split: 66218903 examples [1:01:24, 12133.25 examples/s]
Generating train split: 66220335 examples [1:01:24, 11810.77 examples/s]
Generating train split: 66221653 examples [1:01:25, 9983.88 examples/s] 
Generating train split: 66222780 examples [1:01:25, 6949.78 examples/s]
Generating train split: 66223751 examples [1:01:25, 7385.89 examples/s]
Generating train split: 66224659 examples [1:01:25, 5223.77 examples/s]
Generating train split: 66225373 examples [1:01:26, 5398.03 examples/s]
Generating train split: 66226068 examples [1:01:26, 5475.84 examples/s]
Generating train split: 66226725 examples [1:01:26, 4552.69 examples/s]
Generating train split: 66228884 examples [1:01:26, 7651.20 examples/s]
Generating train split: 66229921 examples [1:01:26, 7777.03 examples/s]
Generating train split: 66231342 examples [1:01:26, 9173.32 examples/s]
Generating train split: 66232446 examples [1:01:26, 9566.60 examples/s]
Generating train split: 66233544 examples [1:01:27, 8732.47 examples/s]
Generating train split: 66234797 examples [1:01:27, 9550.39 examples/s]
Generating train split: 66236210 examples [1:01:27, 10615.61 examples/s]
Generating train split: 66237430 examples [1:01:27, 10955.24 examples/s]
Generating train split: 66238589 examples [1:01:27, 10159.48 examples/s]
Generating train split: 66239883 examples [1:01:27, 10883.69 examples/s]
Generating train split: 66241025 examples [1:01:27, 9492.82 examples/s] 
Generating train split: 66242040 examples [1:01:28, 6369.20 examples/s]
Generating train split: 66243457 examples [1:01:28, 7813.27 examples/s]
Generating train split: 66245841 examples [1:01:28, 11129.23 examples/s]
Generating train split: 66247211 examples [1:01:28, 8116.51 examples/s] 
Generating train split: 66248328 examples [1:01:28, 7991.46 examples/s]
Generating train split: 66250859 examples [1:01:28, 11398.67 examples/s]
Generating train split: 66252319 examples [1:01:28, 11669.15 examples/s]
Generating train split: 66253996 examples [1:01:29, 12781.32 examples/s]
Generating train split: 66255470 examples [1:01:29, 12235.90 examples/s]
Generating train split: 66256833 examples [1:01:29, 10448.23 examples/s]
Generating train split: 66258807 examples [1:01:29, 12528.65 examples/s]
Generating train split: 66260340 examples [1:01:29, 13211.73 examples/s]
Generating train split: 66261793 examples [1:01:29, 8300.82 examples/s] 
Generating train split: 66269376 examples [1:01:29, 20751.02 examples/s]
Generating train split: 66278160 examples [1:01:30, 34731.91 examples/s]
Generating train split: 66282952 examples [1:01:30, 27630.54 examples/s]
Generating train split: 66286859 examples [1:01:30, 16629.29 examples/s]
Generating train split: 66289824 examples [1:01:31, 12757.20 examples/s]
Generating train split: 66295098 examples [1:01:31, 17432.32 examples/s]
Generating train split: 66303238 examples [1:01:31, 26585.32 examples/s]
Generating train split: 66307915 examples [1:01:31, 24707.00 examples/s]
Generating train split: 66311806 examples [1:01:32, 17126.24 examples/s]
Generating train split: 66314787 examples [1:01:32, 13712.98 examples/s]
Generating train split: 66317109 examples [1:01:32, 14103.77 examples/s]
Generating train split: 66320079 examples [1:01:32, 16281.84 examples/s]
Generating train split: 66328865 examples [1:01:32, 28202.43 examples/s]
Generating train split: 66336079 examples [1:01:32, 36643.45 examples/s]
Generating train split: 66341253 examples [1:01:33, 28287.05 examples/s]
Generating train split: 66345416 examples [1:01:33, 27644.64 examples/s]
Generating train split: 66349098 examples [1:01:33, 28952.63 examples/s]
Generating train split: 66353431 examples [1:01:33, 31950.45 examples/s]
Generating train split: 66359539 examples [1:01:33, 38638.06 examples/s]
Generating train split: 66367903 examples [1:01:33, 49745.91 examples/s]
Generating train split: 66373572 examples [1:01:34, 32004.27 examples/s]
Generating train split: 66378046 examples [1:01:34, 34291.07 examples/s]
Generating train split: 66382500 examples [1:01:34, 34132.16 examples/s]
Generating train split: 66386637 examples [1:01:34, 25116.74 examples/s]
Generating train split: 66389954 examples [1:01:34, 20657.40 examples/s]
Generating train split: 66393086 examples [1:01:35, 22438.12 examples/s]
Generating train split: 66402878 examples [1:01:35, 36996.09 examples/s]
Generating train split: 66411147 examples [1:01:35, 46861.66 examples/s]
Generating train split: 66417080 examples [1:01:35, 27769.85 examples/s]
Generating train split: 66421645 examples [1:01:36, 16282.53 examples/s]
Generating train split: 66425043 examples [1:01:36, 15735.30 examples/s]
Generating train split: 66427846 examples [1:01:36, 16302.84 examples/s]
Generating train split: 66430452 examples [1:01:36, 17638.78 examples/s]
Generating train split: 66433018 examples [1:01:37, 15465.36 examples/s]
Generating train split: 66435135 examples [1:01:37, 14751.21 examples/s]
Generating train split: 66437634 examples [1:01:37, 16500.37 examples/s]
Generating train split: 66440758 examples [1:01:37, 19385.07 examples/s]
Generating train split: 66443142 examples [1:01:37, 12368.64 examples/s]
Generating train split: 66445173 examples [1:01:37, 13634.97 examples/s]
Generating train split: 66447538 examples [1:01:38, 15069.35 examples/s]
Generating train split: 66449486 examples [1:01:38, 10238.05 examples/s]
Generating train split: 66452557 examples [1:01:38, 13452.25 examples/s]
Generating train split: 66454533 examples [1:01:38, 10715.80 examples/s]
Generating train split: 66456130 examples [1:01:38, 11405.02 examples/s]
Generating train split: 66457678 examples [1:01:39, 12010.01 examples/s]
Generating train split: 66460021 examples [1:01:39, 14376.39 examples/s]
Generating train split: 66461790 examples [1:01:39, 11116.83 examples/s]
Generating train split: 66463240 examples [1:01:39, 10293.89 examples/s]
Generating train split: 66464501 examples [1:01:39, 10560.72 examples/s]
Generating train split: 66465732 examples [1:01:39, 10282.96 examples/s]
Generating train split: 66472202 examples [1:01:39, 22455.98 examples/s]
Generating train split: 66481134 examples [1:01:40, 38646.48 examples/s]
Generating train split: 66487044 examples [1:01:40, 41546.25 examples/s]
Generating train split: 66491727 examples [1:01:40, 28140.47 examples/s]
Generating train split: 66499512 examples [1:01:40, 37802.35 examples/s]
Generating train split: 66504467 examples [1:01:40, 39810.49 examples/s]
Generating train split: 66509330 examples [1:01:40, 30379.54 examples/s]
Generating train split: 66513295 examples [1:01:41, 20278.68 examples/s]
Generating train split: 66516368 examples [1:01:41, 17747.42 examples/s]
Generating train split: 66518890 examples [1:01:41, 18160.42 examples/s]
Generating train split: 66521251 examples [1:01:41, 17804.56 examples/s]
Generating train split: 66528836 examples [1:01:41, 28481.47 examples/s]
Generating train split: 66537260 examples [1:01:42, 39785.64 examples/s]
Generating train split: 66542344 examples [1:01:42, 23818.24 examples/s]
Generating train split: 66546250 examples [1:01:42, 21420.41 examples/s]
Generating train split: 66549470 examples [1:01:43, 15696.74 examples/s]
Generating train split: 66551961 examples [1:01:43, 14372.11 examples/s]
Generating train split: 66554024 examples [1:01:43, 12160.26 examples/s]
Generating train split: 66556121 examples [1:01:43, 13325.33 examples/s]
Generating train split: 66557905 examples [1:01:43, 13949.87 examples/s]
Generating train split: 66559670 examples [1:01:43, 14307.14 examples/s]
Generating train split: 66561381 examples [1:01:44, 11515.42 examples/s]
Generating train split: 66563132 examples [1:01:44, 12625.99 examples/s]
Generating train split: 66564738 examples [1:01:44, 13270.14 examples/s]
Generating train split: 66566269 examples [1:01:44, 11334.06 examples/s]
Generating train split: 66567941 examples [1:01:44, 12474.67 examples/s]
Generating train split: 66569361 examples [1:01:44, 12474.59 examples/s]
Generating train split: 66572049 examples [1:01:44, 15984.10 examples/s]
Generating train split: 66573816 examples [1:01:45, 8890.73 examples/s] 
Generating train split: 66577090 examples [1:01:45, 12860.35 examples/s]
Generating train split: 66580983 examples [1:01:45, 17862.34 examples/s]
Generating train split: 66583865 examples [1:01:45, 20188.66 examples/s]
Generating train split: 66586485 examples [1:01:45, 18847.38 examples/s]
Generating train split: 66590691 examples [1:01:45, 24098.33 examples/s]
Generating train split: 66597581 examples [1:01:46, 35046.56 examples/s]
Generating train split: 66606195 examples [1:01:46, 48258.19 examples/s]
Generating train split: 66612572 examples [1:01:46, 52443.09 examples/s]
Generating train split: 66618301 examples [1:01:46, 36335.54 examples/s]
Generating train split: 66622939 examples [1:01:46, 26994.60 examples/s]
Generating train split: 66626661 examples [1:01:46, 25849.71 examples/s]
Generating train split: 66630957 examples [1:01:47, 28980.82 examples/s]
Generating train split: 66634541 examples [1:01:47, 26767.86 examples/s]
Generating train split: 66637710 examples [1:01:47, 22001.55 examples/s]
Generating train split: 66641268 examples [1:01:47, 24574.09 examples/s]
Generating train split: 66645441 examples [1:01:47, 28217.48 examples/s]
Generating train split: 66652857 examples [1:01:47, 38937.03 examples/s]
Generating train split: 66663809 examples [1:01:47, 56569.38 examples/s]
Generating train split: 66671272 examples [1:01:47, 61309.49 examples/s]
Generating train split: 66678038 examples [1:01:48, 34127.60 examples/s]
Generating train split: 66683261 examples [1:01:48, 27905.16 examples/s]
Generating train split: 66687456 examples [1:01:48, 24974.75 examples/s]
Generating train split: 66693307 examples [1:01:48, 30238.35 examples/s]
Generating train split: 66700322 examples [1:01:49, 37531.83 examples/s]
Generating train split: 66705356 examples [1:01:49, 25535.09 examples/s]
Generating train split: 66709284 examples [1:01:49, 18604.01 examples/s]
Generating train split: 66712319 examples [1:01:50, 18870.25 examples/s]
Generating train split: 66715056 examples [1:01:50, 19370.36 examples/s]
Generating train split: 66717723 examples [1:01:50, 20607.28 examples/s]
Generating train split: 66720313 examples [1:01:50, 14204.48 examples/s]
Generating train split: 66722340 examples [1:01:50, 11685.50 examples/s]
Generating train split: 66724167 examples [1:01:51, 12637.09 examples/s]
Generating train split: 66727681 examples [1:01:51, 16517.51 examples/s]
Generating train split: 66730544 examples [1:01:51, 18911.08 examples/s]
Generating train split: 66732979 examples [1:01:51, 13592.78 examples/s]
Generating train split: 66734910 examples [1:01:51, 13930.62 examples/s]
Generating train split: 66737351 examples [1:01:51, 15944.69 examples/s]
Generating train split: 66739355 examples [1:01:51, 12951.07 examples/s]
Generating train split: 66745186 examples [1:01:52, 21433.35 examples/s]
Generating train split: 66748007 examples [1:01:52, 22297.71 examples/s]
Generating train split: 66750747 examples [1:01:52, 18536.09 examples/s]
Generating train split: 66753036 examples [1:01:52, 9765.91 examples/s] 
Generating train split: 66755131 examples [1:01:53, 10959.90 examples/s]
Generating train split: 66756881 examples [1:01:53, 11524.12 examples/s]
Generating train split: 66758522 examples [1:01:53, 11995.84 examples/s]
Generating train split: 66760726 examples [1:01:53, 13935.08 examples/s]
Generating train split: 66762815 examples [1:01:53, 15421.28 examples/s]
Generating train split: 66764965 examples [1:01:53, 16364.17 examples/s]
Generating train split: 66766843 examples [1:01:54, 8765.14 examples/s] 
Generating train split: 66769664 examples [1:01:54, 11676.77 examples/s]
Generating train split: 66771473 examples [1:01:54, 8162.97 examples/s] 
Generating train split: 66772878 examples [1:01:54, 8856.74 examples/s]
Generating train split: 66775476 examples [1:01:54, 11675.31 examples/s]
Generating train split: 66778905 examples [1:01:54, 15924.91 examples/s]
Generating train split: 66781127 examples [1:01:55, 14364.15 examples/s]
Generating train split: 66783034 examples [1:01:55, 15226.51 examples/s]
Generating train split: 66784918 examples [1:01:55, 14647.49 examples/s]
Generating train split: 66787428 examples [1:01:55, 16905.09 examples/s]
Generating train split: 66789901 examples [1:01:55, 18777.80 examples/s]
Generating train split: 66792177 examples [1:01:55, 19756.22 examples/s]
Generating train split: 66794323 examples [1:01:55, 15948.67 examples/s]
Generating train split: 66796157 examples [1:01:56, 14621.51 examples/s]
Generating train split: 66798565 examples [1:01:56, 16732.16 examples/s]
Generating train split: 66800422 examples [1:01:56, 16593.01 examples/s]
Generating train split: 66802214 examples [1:01:56, 15503.46 examples/s]
Generating train split: 66803859 examples [1:01:56, 15416.26 examples/s]
Generating train split: 66805467 examples [1:01:56, 15011.48 examples/s]
Generating train split: 66808457 examples [1:01:56, 18904.92 examples/s]
Generating train split: 66810444 examples [1:01:56, 15142.99 examples/s]
Generating train split: 66812139 examples [1:01:57, 15466.55 examples/s]
Generating train split: 66813820 examples [1:01:57, 15427.60 examples/s]
Generating train split: 66815456 examples [1:01:57, 13788.04 examples/s]
Generating train split: 66817311 examples [1:01:57, 14937.81 examples/s]
Generating train split: 66818891 examples [1:01:57, 13513.61 examples/s]
Generating train split: 66820680 examples [1:01:57, 14575.01 examples/s]
Generating train split: 66822244 examples [1:01:57, 14705.53 examples/s]
Generating train split: 66823771 examples [1:01:57, 13266.08 examples/s]
Generating train split: 66825862 examples [1:01:58, 14753.34 examples/s]
Generating train split: 66827405 examples [1:01:58, 13350.90 examples/s]
Generating train split: 66829824 examples [1:01:58, 16066.94 examples/s]
Generating train split: 66832530 examples [1:01:58, 18953.47 examples/s]
Generating train split: 66836800 examples [1:01:58, 25391.15 examples/s]
Generating train split: 66840130 examples [1:01:58, 27513.48 examples/s]
Generating train split: 66845770 examples [1:01:58, 35743.28 examples/s]
Generating train split: 66849738 examples [1:01:58, 36845.16 examples/s]
Generating train split: 66854664 examples [1:01:58, 40459.55 examples/s]
Generating train split: 66858788 examples [1:01:59, 22442.14 examples/s]
Generating train split: 66862002 examples [1:01:59, 20558.96 examples/s]
Generating train split: 66864744 examples [1:01:59, 20906.15 examples/s]
Generating train split: 66867895 examples [1:01:59, 22320.28 examples/s]
Generating train split: 66870533 examples [1:02:00, 14324.15 examples/s]
Generating train split: 66872587 examples [1:02:00, 12045.33 examples/s]
Generating train split: 66875569 examples [1:02:00, 14759.56 examples/s]
Generating train split: 66878412 examples [1:02:00, 17208.15 examples/s]
Generating train split: 66880936 examples [1:02:00, 18809.17 examples/s]
Generating train split: 66883293 examples [1:02:00, 12961.76 examples/s]
Generating train split: 66885717 examples [1:02:01, 14916.19 examples/s]
Generating train split: 66887743 examples [1:02:01, 13607.47 examples/s]
Generating train split: 66889484 examples [1:02:01, 10753.51 examples/s]
Generating train split: 66890896 examples [1:02:01, 8335.04 examples/s] 
Generating train split: 66892023 examples [1:02:02, 7558.18 examples/s]
Generating train split: 66892977 examples [1:02:02, 7278.54 examples/s]
Generating train split: 66893965 examples [1:02:02, 7690.27 examples/s]
Generating train split: 66895045 examples [1:02:02, 8302.08 examples/s]
Generating train split: 66896456 examples [1:02:02, 9577.47 examples/s]
Generating train split: 66897541 examples [1:02:02, 8937.85 examples/s]
Generating train split: 66898683 examples [1:02:02, 9509.96 examples/s]
Generating train split: 66899797 examples [1:02:02, 9916.94 examples/s]
Generating train split: 66900943 examples [1:02:02, 10323.81 examples/s]
Generating train split: 66902026 examples [1:02:03, 8968.03 examples/s] 
Generating train split: 66903125 examples [1:02:03, 9448.14 examples/s]
Generating train split: 66904755 examples [1:02:03, 11225.21 examples/s]
Generating train split: 66906185 examples [1:02:03, 12051.62 examples/s]
Generating train split: 66907512 examples [1:02:03, 12388.70 examples/s]
Generating train split: 66908790 examples [1:02:03, 10605.57 examples/s]
Generating train split: 66909920 examples [1:02:03, 9074.89 examples/s] 
Generating train split: 66912416 examples [1:02:03, 12827.09 examples/s]
Generating train split: 66916586 examples [1:02:04, 20085.95 examples/s]
Generating train split: 66918843 examples [1:02:04, 16584.74 examples/s]
Generating train split: 66920771 examples [1:02:04, 12717.02 examples/s]
Generating train split: 66922350 examples [1:02:04, 13264.42 examples/s]
Generating train split: 66925500 examples [1:02:04, 17248.90 examples/s]
Generating train split: 66929128 examples [1:02:04, 21285.33 examples/s]
Generating train split: 66931559 examples [1:02:04, 21634.10 examples/s]
Generating train split: 66933932 examples [1:02:05, 15998.84 examples/s]
Generating train split: 66935885 examples [1:02:05, 15939.98 examples/s]
Generating train split: 66939805 examples [1:02:05, 21095.78 examples/s]
Generating train split: 66942268 examples [1:02:05, 18747.28 examples/s]
Generating train split: 66945522 examples [1:02:05, 21880.04 examples/s]
Generating train split: 66949918 examples [1:02:05, 26606.07 examples/s]
Generating train split: 66952849 examples [1:02:06, 14916.87 examples/s]
Generating train split: 66956702 examples [1:02:06, 18825.37 examples/s]
Generating train split: 66959915 examples [1:02:06, 21320.27 examples/s]
Generating train split: 66962800 examples [1:02:06, 13003.56 examples/s]
Generating train split: 66965003 examples [1:02:07, 12777.95 examples/s]
Generating train split: 66966909 examples [1:02:07, 13754.05 examples/s]
Generating train split: 66969475 examples [1:02:07, 12728.79 examples/s]
Generating train split: 66971577 examples [1:02:07, 14167.88 examples/s]
Generating train split: 66973365 examples [1:02:07, 13991.43 examples/s]
Generating train split: 66976198 examples [1:02:07, 17008.40 examples/s]
Generating train split: 66978215 examples [1:02:07, 12558.27 examples/s]
Generating train split: 66981575 examples [1:02:08, 16544.56 examples/s]
Generating train split: 66984361 examples [1:02:08, 18930.63 examples/s]
Generating train split: 66986695 examples [1:02:08, 15071.06 examples/s]
Generating train split: 66988845 examples [1:02:08, 16360.08 examples/s]
Generating train split: 66990853 examples [1:02:08, 16332.11 examples/s]
Generating train split: 66992851 examples [1:02:08, 17163.44 examples/s]
Generating train split: 66995124 examples [1:02:08, 18545.28 examples/s]
Generating train split: 66999820 examples [1:02:08, 25987.59 examples/s]
Generating train split: 67002651 examples [1:02:09, 13616.99 examples/s]
Generating train split: 67004822 examples [1:02:09, 14804.85 examples/s]
Generating train split: 67006950 examples [1:02:09, 12173.99 examples/s]
Generating train split: 67010686 examples [1:02:09, 16476.43 examples/s]
Generating train split: 67013253 examples [1:02:09, 18272.95 examples/s]
Generating train split: 67015652 examples [1:02:10, 16316.64 examples/s]
Generating train split: 67022283 examples [1:02:10, 24881.07 examples/s]
Generating train split: 67025206 examples [1:02:10, 17188.49 examples/s]
Generating train split: 67027520 examples [1:02:10, 17741.86 examples/s]
Generating train split: 67029740 examples [1:02:10, 16803.30 examples/s]
Generating train split: 67031723 examples [1:02:11, 14277.93 examples/s]
Generating train split: 67033396 examples [1:02:11, 11902.12 examples/s]
Generating train split: 67036546 examples [1:02:11, 15403.61 examples/s]
Generating train split: 67038467 examples [1:02:11, 12389.64 examples/s]
Generating train split: 67040042 examples [1:02:11, 11758.78 examples/s]
Generating train split: 67041452 examples [1:02:12, 10633.85 examples/s]
Generating train split: 67043299 examples [1:02:12, 12034.51 examples/s]
Generating train split: 67044710 examples [1:02:12, 12474.88 examples/s]
Generating train split: 67046103 examples [1:02:12, 9034.46 examples/s] 
Generating train split: 67047364 examples [1:02:12, 9712.78 examples/s]
Generating train split: 67049121 examples [1:02:12, 11379.13 examples/s]
Generating train split: 67050463 examples [1:02:12, 9520.91 examples/s] 
Generating train split: 67051608 examples [1:02:13, 9713.90 examples/s]
Generating train split: 67052726 examples [1:02:13, 9874.67 examples/s]
Generating train split: 67058206 examples [1:02:13, 20766.29 examples/s]
Generating train split: 67062992 examples [1:02:13, 27732.66 examples/s]
Generating train split: 67066784 examples [1:02:13, 30230.19 examples/s]
Generating train split: 67070071 examples [1:02:13, 18889.32 examples/s]
Generating train split: 67076325 examples [1:02:13, 27346.56 examples/s]
Generating train split: 67080027 examples [1:02:13, 29293.13 examples/s]
Generating train split: 67087010 examples [1:02:14, 38828.96 examples/s]
Generating train split: 67091973 examples [1:02:14, 40946.22 examples/s]
Generating train split: 67096645 examples [1:02:14, 25536.63 examples/s]
Generating train split: 67101480 examples [1:02:14, 29716.09 examples/s]
Generating train split: 67105500 examples [1:02:14, 21136.87 examples/s]
Generating train split: 67108670 examples [1:02:15, 19048.09 examples/s]
Generating train split: 67111322 examples [1:02:15, 16011.69 examples/s]
Generating train split: 67113817 examples [1:02:15, 17401.63 examples/s]
Generating train split: 67116071 examples [1:02:15, 16988.58 examples/s]
Generating train split: 67118121 examples [1:02:15, 17592.23 examples/s]
Generating train split: 67120166 examples [1:02:16, 13087.62 examples/s]
Generating train split: 67124113 examples [1:02:16, 14678.92 examples/s]
Generating train split: 67125980 examples [1:02:16, 14800.74 examples/s]
Generating train split: 67128343 examples [1:02:16, 16513.82 examples/s]
Generating train split: 67130200 examples [1:02:16, 13821.37 examples/s]
Generating train split: 67132410 examples [1:02:16, 15485.39 examples/s]
Generating train split: 67134172 examples [1:02:16, 15124.22 examples/s]
Generating train split: 67136262 examples [1:02:17, 16465.88 examples/s]
Generating train split: 67138050 examples [1:02:17, 16476.05 examples/s]
Generating train split: 67139803 examples [1:02:17, 13602.35 examples/s]
Generating train split: 67141650 examples [1:02:17, 14717.63 examples/s]
Generating train split: 67143265 examples [1:02:17, 13592.37 examples/s]
Generating train split: 67144726 examples [1:02:17, 12717.67 examples/s]
Generating train split: 67146070 examples [1:02:17, 11537.43 examples/s]
Generating train split: 67147295 examples [1:02:17, 11631.99 examples/s]
Generating train split: 67149387 examples [1:02:18, 13944.94 examples/s]
Generating train split: 67151975 examples [1:02:18, 17019.97 examples/s]
Generating train split: 67153778 examples [1:02:18, 11427.75 examples/s]
Generating train split: 67155223 examples [1:02:18, 11169.11 examples/s]
Generating train split: 67157766 examples [1:02:18, 14200.95 examples/s]
Generating train split: 67159456 examples [1:02:18, 11248.81 examples/s]
Generating train split: 67163819 examples [1:02:19, 17784.87 examples/s]
Generating train split: 67167978 examples [1:02:19, 23109.61 examples/s]
Generating train split: 67173081 examples [1:02:19, 29864.78 examples/s]
Generating train split: 67179105 examples [1:02:19, 37430.35 examples/s]
Generating train split: 67183334 examples [1:02:19, 35854.83 examples/s]
Generating train split: 67187277 examples [1:02:19, 25305.41 examples/s]
Generating train split: 67190467 examples [1:02:19, 23787.88 examples/s]
Generating train split: 67193303 examples [1:02:20, 24100.23 examples/s]
Generating train split: 67196048 examples [1:02:20, 21256.73 examples/s]
Generating train split: 67198445 examples [1:02:20, 18281.36 examples/s]
Generating train split: 67200492 examples [1:02:20, 11092.72 examples/s]
Generating train split: 67202066 examples [1:02:20, 11249.73 examples/s]
Generating train split: 67203669 examples [1:02:21, 11645.86 examples/s]
Generating train split: 67205106 examples [1:02:21, 12156.29 examples/s]
Generating train split: 67206532 examples [1:02:21, 10915.29 examples/s]
Generating train split: 67209532 examples [1:02:21, 14834.78 examples/s]
Generating train split: 67211308 examples [1:02:21, 10980.42 examples/s]
Generating train split: 67212735 examples [1:02:21, 11393.36 examples/s]
Generating train split: 67214962 examples [1:02:21, 13655.81 examples/s]
Generating train split: 67218284 examples [1:02:22, 18005.16 examples/s]
Generating train split: 67220398 examples [1:02:22, 13281.66 examples/s]
Generating train split: 67223218 examples [1:02:22, 15877.34 examples/s]
Generating train split: 67225179 examples [1:02:22, 9312.75 examples/s] 
Generating train split: 67228049 examples [1:02:23, 12168.64 examples/s]
Generating train split: 67231493 examples [1:02:23, 16039.71 examples/s]
Generating train split: 67235582 examples [1:02:23, 20684.95 examples/s]
Generating train split: 67238387 examples [1:02:23, 13826.17 examples/s]
Generating train split: 67241404 examples [1:02:23, 16479.50 examples/s]
Generating train split: 67243841 examples [1:02:24, 12790.46 examples/s]
Generating train split: 67247364 examples [1:02:24, 16373.60 examples/s]
Generating train split: 67249774 examples [1:02:24, 11032.16 examples/s]
Generating train split: 67251637 examples [1:02:24, 11590.96 examples/s]
Generating train split: 67254987 examples [1:02:24, 15145.38 examples/s]
Generating train split: 67257204 examples [1:02:25, 12191.50 examples/s]
Generating train split: 67258991 examples [1:02:25, 9746.35 examples/s] 
Generating train split: 67261138 examples [1:02:25, 8970.47 examples/s]
Generating train split: 67262354 examples [1:02:25, 8175.45 examples/s]
Generating train split: 67263819 examples [1:02:25, 9140.78 examples/s]
Generating train split: 67266200 examples [1:02:26, 11686.01 examples/s]
Generating train split: 67268096 examples [1:02:26, 10033.86 examples/s]
Generating train split: 67270457 examples [1:02:26, 12424.71 examples/s]
Generating train split: 67272050 examples [1:02:26, 9261.62 examples/s] 
Generating train split: 67273772 examples [1:02:26, 10614.38 examples/s]
Generating train split: 67275187 examples [1:02:26, 10604.51 examples/s]
Generating train split: 67276550 examples [1:02:27, 10996.78 examples/s]
Generating train split: 67277834 examples [1:02:27, 9811.61 examples/s] 
Generating train split: 67279071 examples [1:02:27, 10349.14 examples/s]
Generating train split: 67283423 examples [1:02:27, 17706.21 examples/s]
Generating train split: 67286007 examples [1:02:27, 19700.91 examples/s]
Generating train split: 67288180 examples [1:02:27, 15933.24 examples/s]
Generating train split: 67292050 examples [1:02:27, 21083.62 examples/s]
Generating train split: 67294494 examples [1:02:28, 16032.81 examples/s]
Generating train split: 67303148 examples [1:02:28, 30390.69 examples/s]
Generating train split: 67307161 examples [1:02:28, 25090.80 examples/s]
Generating train split: 67310487 examples [1:02:28, 22683.38 examples/s]
Generating train split: 67313339 examples [1:02:28, 18021.23 examples/s]
Generating train split: 67315658 examples [1:02:29, 16295.38 examples/s]
Generating train split: 67318168 examples [1:02:29, 17830.67 examples/s]
Generating train split: 67320314 examples [1:02:29, 16216.70 examples/s]
Generating train split: 67322187 examples [1:02:29, 14825.62 examples/s]
Generating train split: 67323846 examples [1:02:29, 12035.09 examples/s]
Generating train split: 67328738 examples [1:02:29, 18908.49 examples/s]
Generating train split: 67338395 examples [1:02:29, 35235.83 examples/s]
Generating train split: 67342998 examples [1:02:30, 19306.58 examples/s]
Generating train split: 67346485 examples [1:02:30, 14759.46 examples/s]
Generating train split: 67349180 examples [1:02:31, 14629.51 examples/s]
Generating train split: 67351492 examples [1:02:31, 12772.47 examples/s]
Generating train split: 67353367 examples [1:02:31, 11002.24 examples/s]
Generating train split: 67354883 examples [1:02:31, 10829.31 examples/s]
Generating train split: 67356257 examples [1:02:31, 9716.00 examples/s] 
Generating train split: 67357418 examples [1:02:32, 9861.83 examples/s]
Generating train split: 67358882 examples [1:02:32, 10733.77 examples/s]
Generating train split: 67361015 examples [1:02:32, 12887.98 examples/s]
Generating train split: 67362514 examples [1:02:32, 10808.62 examples/s]
Generating train split: 67365717 examples [1:02:32, 15072.57 examples/s]
Generating train split: 67367516 examples [1:02:32, 14178.08 examples/s]
Generating train split: 67371410 examples [1:02:32, 19785.72 examples/s]
Generating train split: 67379869 examples [1:02:32, 35629.88 examples/s]
Generating train split: 67385492 examples [1:02:33, 40953.78 examples/s]
Generating train split: 67390086 examples [1:02:33, 33585.44 examples/s]
Generating train split: 67394003 examples [1:02:33, 28037.11 examples/s]
Generating train split: 67397329 examples [1:02:33, 18185.14 examples/s]
Generating train split: 67399921 examples [1:02:33, 18820.72 examples/s]
Generating train split: 67402648 examples [1:02:34, 20313.01 examples/s]
Generating train split: 67405914 examples [1:02:34, 22813.65 examples/s]
Generating train split: 67408672 examples [1:02:34, 16832.71 examples/s]
Generating train split: 67410893 examples [1:02:34, 15594.59 examples/s]
Generating train split: 67414705 examples [1:02:34, 19699.61 examples/s]
Generating train split: 67419814 examples [1:02:34, 26304.98 examples/s]
Generating train split: 67428603 examples [1:02:34, 40539.98 examples/s]
Generating train split: 67433520 examples [1:02:35, 41882.98 examples/s]
Generating train split: 67438326 examples [1:02:35, 27638.46 examples/s]
Generating train split: 67442140 examples [1:02:35, 25919.31 examples/s]
Generating train split: 67445467 examples [1:02:35, 23087.77 examples/s]
Generating train split: 67451474 examples [1:02:35, 24460.31 examples/s]
Generating train split: 67454288 examples [1:02:36, 21639.94 examples/s]
Generating train split: 67456692 examples [1:02:36, 19399.41 examples/s]
Generating train split: 67458794 examples [1:02:36, 12027.35 examples/s]
Generating train split: 67460408 examples [1:02:36, 12526.24 examples/s]
Generating train split: 67462340 examples [1:02:36, 13589.33 examples/s]
Generating train split: 67464028 examples [1:02:37, 12196.84 examples/s]
Generating train split: 67465479 examples [1:02:37, 11966.36 examples/s]
Generating train split: 67468582 examples [1:02:37, 15697.61 examples/s]
Generating train split: 67470420 examples [1:02:37, 13119.69 examples/s]
Generating train split: 67471971 examples [1:02:37, 11173.05 examples/s]
Generating train split: 67473285 examples [1:02:37, 9983.19 examples/s] 
Generating train split: 67474424 examples [1:02:38, 10176.06 examples/s]
Generating train split: 67475576 examples [1:02:38, 10447.61 examples/s]
Generating train split: 67476715 examples [1:02:38, 10470.42 examples/s]
Generating train split: 67477929 examples [1:02:38, 10880.89 examples/s]
Generating train split: 67479070 examples [1:02:38, 9407.38 examples/s] 
Generating train split: 67480082 examples [1:02:38, 9574.04 examples/s]
Generating train split: 67481096 examples [1:02:38, 9227.94 examples/s]
Generating train split: 67483321 examples [1:02:38, 12579.43 examples/s]
Generating train split: 67491032 examples [1:02:38, 29946.30 examples/s]
Generating train split: 67498275 examples [1:02:39, 41743.52 examples/s]
Generating train split: 67502978 examples [1:02:39, 41811.06 examples/s]
Generating train split: 67507360 examples [1:02:39, 29521.53 examples/s]
Generating train split: 67510939 examples [1:02:39, 22067.60 examples/s]
Generating train split: 67513822 examples [1:02:39, 18066.43 examples/s]
Generating train split: 67516178 examples [1:02:40, 18160.48 examples/s]
Generating train split: 67518381 examples [1:02:40, 14762.00 examples/s]
Generating train split: 67520193 examples [1:02:40, 14492.15 examples/s]
Generating train split: 67521866 examples [1:02:40, 13793.68 examples/s]
Generating train split: 67523580 examples [1:02:40, 14354.39 examples/s]
Generating train split: 67525152 examples [1:02:40, 13695.99 examples/s]
Generating train split: 67527470 examples [1:02:40, 15854.47 examples/s]
Generating train split: 67529588 examples [1:02:41, 16096.41 examples/s]
Generating train split: 67531288 examples [1:02:41, 14338.98 examples/s]
Generating train split: 67532816 examples [1:02:41, 12951.67 examples/s]
Generating train split: 67534697 examples [1:02:41, 14295.28 examples/s]
Generating train split: 67536221 examples [1:02:41, 11697.39 examples/s]
Generating train split: 67537521 examples [1:02:41, 11860.54 examples/s]
Generating train split: 67540173 examples [1:02:41, 15345.59 examples/s]
Generating train split: 67541861 examples [1:02:42, 11271.34 examples/s]
Generating train split: 67543245 examples [1:02:42, 11539.19 examples/s]
Generating train split: 67544592 examples [1:02:42, 11242.07 examples/s]
Generating train split: 67546802 examples [1:02:42, 13734.31 examples/s]
Generating train split: 67551405 examples [1:02:42, 21732.46 examples/s]
Generating train split: 67557035 examples [1:02:42, 30754.22 examples/s]
Generating train split: 67562184 examples [1:02:42, 36318.92 examples/s]
Generating train split: 67567632 examples [1:02:42, 41367.57 examples/s]
Generating train split: 67576347 examples [1:02:43, 54418.47 examples/s]
Generating train split: 67585164 examples [1:02:43, 64165.37 examples/s]
Generating train split: 67591781 examples [1:02:43, 52504.20 examples/s]
Generating train split: 67597991 examples [1:02:43, 54920.30 examples/s]
Generating train split: 67603867 examples [1:02:43, 37528.60 examples/s]
Generating train split: 67608604 examples [1:02:44, 24655.91 examples/s]
Generating train split: 67612286 examples [1:02:44, 18263.03 examples/s]
Generating train split: 67615145 examples [1:02:44, 18118.86 examples/s]
Generating train split: 67617667 examples [1:02:44, 14575.02 examples/s]
Generating train split: 67621167 examples [1:02:45, 14230.09 examples/s]
Generating train split: 67622983 examples [1:02:45, 13216.18 examples/s]
Generating train split: 67624547 examples [1:02:45, 11793.58 examples/s]
Generating train split: 67626875 examples [1:02:45, 13601.77 examples/s]
Generating train split: 67628509 examples [1:02:45, 12972.22 examples/s]
Generating train split: 67630024 examples [1:02:45, 13391.91 examples/s]
Generating train split: 67631516 examples [1:02:46, 13000.45 examples/s]
Generating train split: 67634094 examples [1:02:46, 15892.48 examples/s]
Generating train split: 67636659 examples [1:02:46, 18266.93 examples/s]
Generating train split: 67638649 examples [1:02:46, 12421.89 examples/s]
Generating train split: 67641277 examples [1:02:46, 15153.56 examples/s]
Generating train split: 67643185 examples [1:02:46, 15522.10 examples/s]
Generating train split: 67645209 examples [1:02:46, 16440.86 examples/s]
Generating train split: 67647075 examples [1:02:47, 13423.79 examples/s]
Generating train split: 67649995 examples [1:02:47, 16725.03 examples/s]
Generating train split: 67652186 examples [1:02:47, 17920.64 examples/s]
Generating train split: 67654207 examples [1:02:47, 14968.94 examples/s]
Generating train split: 67655943 examples [1:02:47, 14274.93 examples/s]
Generating train split: 67661229 examples [1:02:47, 23066.39 examples/s]
Generating train split: 67666374 examples [1:02:47, 30048.86 examples/s]
Generating train split: 67670562 examples [1:02:47, 33109.52 examples/s]
Generating train split: 67674211 examples [1:02:48, 15083.32 examples/s]
Generating train split: 67677268 examples [1:02:48, 17344.63 examples/s]
Generating train split: 67681173 examples [1:02:48, 21028.37 examples/s]
Generating train split: 67684315 examples [1:02:48, 18491.59 examples/s]
Generating train split: 67687602 examples [1:02:49, 21079.39 examples/s]
Generating train split: 67690414 examples [1:02:49, 13735.21 examples/s]
Generating train split: 67692584 examples [1:02:49, 14831.24 examples/s]
Generating train split: 67695703 examples [1:02:49, 17744.50 examples/s]
Generating train split: 67699024 examples [1:02:49, 20830.31 examples/s]
Generating train split: 67701714 examples [1:02:49, 19411.39 examples/s]
Generating train split: 67704100 examples [1:02:50, 16340.40 examples/s]
Generating train split: 67706098 examples [1:02:50, 15069.06 examples/s]
Generating train split: 67707859 examples [1:02:50, 13610.71 examples/s]
Generating train split: 67709397 examples [1:02:50, 10603.18 examples/s]
Generating train split: 67710919 examples [1:02:50, 11273.42 examples/s]
Generating train split: 67712226 examples [1:02:51, 7650.98 examples/s] 
Generating train split: 67713254 examples [1:02:51, 6048.78 examples/s]
Generating train split: 67715467 examples [1:02:51, 8389.09 examples/s]
Generating train split: 67718374 examples [1:02:51, 11938.28 examples/s]
Generating train split: 67721550 examples [1:02:51, 15689.62 examples/s]
Generating train split: 67724960 examples [1:02:51, 19466.82 examples/s]
Generating train split: 67727413 examples [1:02:52, 12047.62 examples/s]
Generating train split: 67729317 examples [1:02:52, 11934.64 examples/s]
Generating train split: 67732660 examples [1:02:52, 15691.54 examples/s]
Generating train split: 67734839 examples [1:02:52, 12626.35 examples/s]
Generating train split: 67736619 examples [1:02:53, 10608.10 examples/s]
Generating train split: 67738070 examples [1:02:53, 10496.56 examples/s]
Generating train split: 67739454 examples [1:02:53, 10763.04 examples/s]
Generating train split: 67740740 examples [1:02:53, 10272.52 examples/s]
Generating train split: 67743638 examples [1:02:53, 14125.63 examples/s]
Generating train split: 67746909 examples [1:02:53, 18366.82 examples/s]
Generating train split: 67749066 examples [1:02:54, 12064.76 examples/s]
Generating train split: 67751171 examples [1:02:54, 13690.11 examples/s]
Generating train split: 67752999 examples [1:02:54, 14467.57 examples/s]
Generating train split: 67754795 examples [1:02:54, 11726.66 examples/s]
Generating train split: 67756292 examples [1:02:54, 10269.05 examples/s]
Generating train split: 67758644 examples [1:02:54, 12783.17 examples/s]
Generating train split: 67761169 examples [1:02:54, 15281.31 examples/s]
Generating train split: 67763012 examples [1:02:55, 12287.18 examples/s]
Generating train split: 67764536 examples [1:02:55, 11562.57 examples/s]
Generating train split: 67767035 examples [1:02:55, 14255.16 examples/s]
Generating train split: 67769247 examples [1:02:55, 15971.38 examples/s]
Generating train split: 67771086 examples [1:02:55, 15959.56 examples/s]
Generating train split: 67772856 examples [1:02:55, 14273.19 examples/s]
Generating train split: 67775054 examples [1:02:55, 16081.31 examples/s]
Generating train split: 67776805 examples [1:02:55, 15253.27 examples/s]
Generating train split: 67778432 examples [1:02:56, 14711.49 examples/s]
Generating train split: 67779982 examples [1:02:56, 14052.45 examples/s]
Generating train split: 67781445 examples [1:02:56, 11503.57 examples/s]
Generating train split: 67786390 examples [1:02:56, 20141.06 examples/s]
Generating train split: 67791068 examples [1:02:56, 26634.33 examples/s]
Generating train split: 67794117 examples [1:02:56, 26900.90 examples/s]
Generating train split: 67798493 examples [1:02:56, 31322.78 examples/s]
Generating train split: 67801878 examples [1:02:56, 28207.64 examples/s]
Generating train split: 67804922 examples [1:02:57, 22881.54 examples/s]
Generating train split: 67809450 examples [1:02:57, 27923.44 examples/s]
Generating train split: 67812625 examples [1:02:57, 17873.24 examples/s]
Generating train split: 67815983 examples [1:02:57, 20592.11 examples/s]
Generating train split: 67818718 examples [1:02:58, 11170.33 examples/s]
Generating train split: 67821533 examples [1:02:58, 13336.78 examples/s]
Generating train split: 67823815 examples [1:02:58, 14402.48 examples/s]
Generating train split: 67827933 examples [1:02:58, 19129.38 examples/s]
Generating train split: 67830697 examples [1:02:59, 11020.86 examples/s]
Generating train split: 67832784 examples [1:02:59, 11714.69 examples/s]
Generating train split: 67835220 examples [1:02:59, 13599.99 examples/s]
Generating train split: 67838836 examples [1:02:59, 17536.92 examples/s]
Generating train split: 67841821 examples [1:02:59, 19728.30 examples/s]
Generating train split: 67844410 examples [1:03:00, 10593.32 examples/s]
Generating train split: 67847810 examples [1:03:00, 13800.86 examples/s]
Generating train split: 67850193 examples [1:03:00, 11880.17 examples/s]
Generating train split: 67852753 examples [1:03:00, 11037.48 examples/s]
Generating train split: 67854801 examples [1:03:00, 12423.52 examples/s]
Generating train split: 67856554 examples [1:03:01, 7267.59 examples/s] 
Generating train split: 67858298 examples [1:03:01, 8478.39 examples/s]
Generating train split: 67862128 examples [1:03:01, 12812.82 examples/s]
Generating train split: 67865701 examples [1:03:01, 16748.14 examples/s]
Generating train split: 67868282 examples [1:03:02, 12356.68 examples/s]
Generating train split: 67870312 examples [1:03:02, 12035.77 examples/s]
Generating train split: 67873025 examples [1:03:02, 14506.69 examples/s]
Generating train split: 67875054 examples [1:03:02, 13243.33 examples/s]
Generating train split: 67876797 examples [1:03:02, 12478.23 examples/s]
Generating train split: 67879518 examples [1:03:02, 15320.52 examples/s]
Generating train split: 67881403 examples [1:03:03, 15754.73 examples/s]
Generating train split: 67883434 examples [1:03:03, 16788.74 examples/s]
Generating train split: 67885325 examples [1:03:03, 12329.50 examples/s]
Generating train split: 67887565 examples [1:03:03, 14345.02 examples/s]
Generating train split: 67889854 examples [1:03:03, 16234.24 examples/s]
Generating train split: 67892899 examples [1:03:03, 19616.13 examples/s]
Generating train split: 67895140 examples [1:03:03, 14749.98 examples/s]
Generating train split: 67896986 examples [1:03:04, 12563.19 examples/s]
Generating train split: 67900628 examples [1:03:04, 17211.16 examples/s]
Generating train split: 67902814 examples [1:03:04, 16862.34 examples/s]
Generating train split: 67904825 examples [1:03:04, 15739.89 examples/s]
Generating train split: 67906626 examples [1:03:04, 14070.84 examples/s]
Generating train split: 67909621 examples [1:03:04, 17398.45 examples/s]
Generating train split: 67911602 examples [1:03:04, 15680.67 examples/s]
Generating train split: 67913546 examples [1:03:05, 16019.86 examples/s]
Generating train split: 67915641 examples [1:03:05, 16663.46 examples/s]
Generating train split: 67920225 examples [1:03:05, 23862.65 examples/s]
Generating train split: 67922844 examples [1:03:05, 23673.48 examples/s]
Generating train split: 67929272 examples [1:03:05, 34444.35 examples/s]
Generating train split: 67935294 examples [1:03:05, 37164.74 examples/s]
Generating train split: 67939152 examples [1:03:05, 24744.23 examples/s]
Generating train split: 67942234 examples [1:03:06, 22252.08 examples/s]
Generating train split: 67944896 examples [1:03:06, 20945.72 examples/s]
Generating train split: 67947783 examples [1:03:06, 22530.47 examples/s]
Generating train split: 67950324 examples [1:03:06, 21031.27 examples/s]
Generating train split: 67952621 examples [1:03:07, 11649.79 examples/s]
Generating train split: 67954378 examples [1:03:07, 11909.01 examples/s]
Generating train split: 67956599 examples [1:03:07, 13630.27 examples/s]
Generating train split: 67958404 examples [1:03:07, 12575.15 examples/s]
Generating train split: 67959977 examples [1:03:07, 11554.48 examples/s]
Generating train split: 67961497 examples [1:03:07, 12262.24 examples/s]
Generating train split: 67963251 examples [1:03:07, 13118.42 examples/s]
Generating train split: 67964728 examples [1:03:07, 12997.38 examples/s]
Generating train split: 67966139 examples [1:03:08, 12900.42 examples/s]
Generating train split: 67969510 examples [1:03:08, 18014.45 examples/s]
Generating train split: 67972520 examples [1:03:08, 14909.21 examples/s]
Generating train split: 67974225 examples [1:03:08, 13310.75 examples/s]
Generating train split: 67975712 examples [1:03:08, 12287.23 examples/s]
Generating train split: 67977732 examples [1:03:08, 11123.98 examples/s]
Generating train split: 67978942 examples [1:03:09, 10692.80 examples/s]
Generating train split: 67981240 examples [1:03:09, 13216.51 examples/s]
Generating train split: 67982713 examples [1:03:09, 10721.12 examples/s]
Generating train split: 67984524 examples [1:03:09, 12129.29 examples/s]
Generating train split: 67985920 examples [1:03:09, 7402.96 examples/s] 
Generating train split: 67987673 examples [1:03:10, 9013.18 examples/s]
Generating train split: 67989200 examples [1:03:10, 10070.96 examples/s]
Generating train split: 67990528 examples [1:03:10, 8120.60 examples/s] 
Generating train split: 67991621 examples [1:03:10, 7654.91 examples/s]
Generating train split: 67993245 examples [1:03:10, 9242.80 examples/s]
Generating train split: 67996870 examples [1:03:10, 14952.58 examples/s]
Generating train split: 68005075 examples [1:03:10, 30517.19 examples/s]
Generating train split: 68012004 examples [1:03:10, 40157.13 examples/s]
Generating train split: 68016729 examples [1:03:11, 30812.27 examples/s]
Generating train split: 68020634 examples [1:03:11, 23115.10 examples/s]
Generating train split: 68023783 examples [1:03:11, 23804.21 examples/s]
Generating train split: 68026771 examples [1:03:11, 18511.07 examples/s]
Generating train split: 68029195 examples [1:03:12, 17972.45 examples/s]
Generating train split: 68031383 examples [1:03:12, 18404.54 examples/s]
Generating train split: 68034573 examples [1:03:12, 20826.73 examples/s]
Generating train split: 68036945 examples [1:03:12, 12356.96 examples/s]
Generating train split: 68039052 examples [1:03:12, 13709.27 examples/s]
Generating train split: 68040971 examples [1:03:12, 13290.66 examples/s]
Generating train split: 68043057 examples [1:03:13, 14651.02 examples/s]
Generating train split: 68044861 examples [1:03:13, 13339.70 examples/s]
Generating train split: 68046860 examples [1:03:13, 14728.32 examples/s]
Generating train split: 68048911 examples [1:03:13, 16042.41 examples/s]
Generating train split: 68054423 examples [1:03:13, 25687.19 examples/s]
Generating train split: 68062912 examples [1:03:13, 41122.52 examples/s]
Generating train split: 68067498 examples [1:03:13, 25137.02 examples/s]
Generating train split: 68071122 examples [1:03:14, 26751.67 examples/s]
Generating train split: 68075431 examples [1:03:14, 23971.27 examples/s]
Generating train split: 68078478 examples [1:03:14, 24514.56 examples/s]
Generating train split: 68081412 examples [1:03:14, 25384.45 examples/s]
Generating train split: 68084511 examples [1:03:14, 26669.63 examples/s]
Generating train split: 68087473 examples [1:03:15, 14789.09 examples/s]
Generating train split: 68090529 examples [1:03:15, 17307.82 examples/s]
Generating train split: 68094153 examples [1:03:15, 20828.42 examples/s]
Generating train split: 68097632 examples [1:03:15, 23047.24 examples/s]
Generating train split: 68100539 examples [1:03:16, 10927.42 examples/s]
Generating train split: 68104165 examples [1:03:16, 14117.86 examples/s]
Generating train split: 68107685 examples [1:03:16, 17328.87 examples/s]
Generating train split: 68110578 examples [1:03:16, 11588.55 examples/s]
Generating train split: 68112779 examples [1:03:16, 11628.90 examples/s]
Generating train split: 68117006 examples [1:03:16, 16072.08 examples/s]
Generating train split: 68119742 examples [1:03:17, 18004.92 examples/s]
Generating train split: 68123490 examples [1:03:17, 21831.58 examples/s]
Generating train split: 68126470 examples [1:03:17, 11288.49 examples/s]
Generating train split: 68130360 examples [1:03:17, 14888.53 examples/s]
Generating train split: 68133600 examples [1:03:17, 17639.31 examples/s]
Generating train split: 68136482 examples [1:03:18, 12847.23 examples/s]
Generating train split: 68138726 examples [1:03:18, 12909.35 examples/s]
Generating train split: 68140690 examples [1:03:18, 12584.99 examples/s]
Generating train split: 68142423 examples [1:03:18, 12385.18 examples/s]
Generating train split: 68147822 examples [1:03:18, 19999.53 examples/s]
Generating train split: 68152061 examples [1:03:19, 24614.95 examples/s]
Generating train split: 68155221 examples [1:03:19, 24264.24 examples/s]
Generating train split: 68158134 examples [1:03:19, 11134.39 examples/s]
Generating train split: 68160322 examples [1:03:19, 12097.10 examples/s]
Generating train split: 68162365 examples [1:03:20, 12279.93 examples/s]
Generating train split: 68164191 examples [1:03:20, 9639.38 examples/s] 
Generating train split: 68165636 examples [1:03:20, 9960.20 examples/s]
Generating train split: 68167477 examples [1:03:20, 11370.04 examples/s]
Generating train split: 68168976 examples [1:03:20, 10401.87 examples/s]
Generating train split: 68170305 examples [1:03:21, 10021.97 examples/s]
Generating train split: 68171490 examples [1:03:21, 10235.45 examples/s]
Generating train split: 68172660 examples [1:03:21, 5348.84 examples/s] 
Generating train split: 68173543 examples [1:03:21, 5666.60 examples/s]
Generating train split: 68174379 examples [1:03:21, 5975.63 examples/s]
Generating train split: 68175183 examples [1:03:21, 6293.25 examples/s]
Generating train split: 68178017 examples [1:03:22, 7296.89 examples/s]
Generating train split: 68178828 examples [1:03:22, 6117.97 examples/s]
Generating train split: 68181603 examples [1:03:22, 9094.11 examples/s]
Generating train split: 68182856 examples [1:03:22, 9695.76 examples/s]
Generating train split: 68184038 examples [1:03:22, 9890.89 examples/s]
Generating train split: 68185374 examples [1:03:23, 10623.23 examples/s]
Generating train split: 68190142 examples [1:03:23, 19511.66 examples/s]
Generating train split: 68192788 examples [1:03:23, 18652.68 examples/s]
Generating train split: 68194876 examples [1:03:23, 11939.75 examples/s]
Generating train split: 68196518 examples [1:03:23, 12653.65 examples/s]
Generating train split: 68199269 examples [1:03:23, 15633.99 examples/s]
Generating train split: 68203384 examples [1:03:23, 21322.54 examples/s]
Generating train split: 68205992 examples [1:03:24, 18039.18 examples/s]
Generating train split: 68208214 examples [1:03:24, 14613.68 examples/s]
Generating train split: 68211379 examples [1:03:24, 17895.33 examples/s]
Generating train split: 68214867 examples [1:03:24, 21537.11 examples/s]
Generating train split: 68217471 examples [1:03:24, 15106.02 examples/s]
Generating train split: 68219549 examples [1:03:25, 15114.69 examples/s]
Generating train split: 68221790 examples [1:03:25, 16547.90 examples/s]
Generating train split: 68225424 examples [1:03:25, 20881.87 examples/s]
Generating train split: 68227914 examples [1:03:25, 17519.28 examples/s]
Generating train split: 68230025 examples [1:03:25, 16661.95 examples/s]
Generating train split: 68231943 examples [1:03:25, 15349.84 examples/s]
Generating train split: 68235671 examples [1:03:25, 19998.58 examples/s]
Generating train split: 68240599 examples [1:03:25, 26869.54 examples/s]
Generating train split: 68243679 examples [1:03:26, 14892.10 examples/s]
Generating train split: 68246834 examples [1:03:26, 17579.47 examples/s]
Generating train split: 68249928 examples [1:03:26, 20076.55 examples/s]
Generating train split: 68253755 examples [1:03:26, 23735.23 examples/s]
Generating train split: 68256784 examples [1:03:27, 11783.88 examples/s]
Generating train split: 68260245 examples [1:03:27, 14821.45 examples/s]
Generating train split: 68263553 examples [1:03:27, 17738.13 examples/s]
Generating train split: 68266392 examples [1:03:27, 17256.72 examples/s]
Generating train split: 68268863 examples [1:03:27, 13629.84 examples/s]
Generating train split: 68271462 examples [1:03:28, 15655.63 examples/s]
Generating train split: 68273636 examples [1:03:28, 11234.87 examples/s]
Generating train split: 68276052 examples [1:03:28, 13216.75 examples/s]
Generating train split: 68279279 examples [1:03:28, 16637.24 examples/s]
Generating train split: 68281583 examples [1:03:28, 11099.31 examples/s]
Generating train split: 68283371 examples [1:03:29, 11416.44 examples/s]
Generating train split: 68285001 examples [1:03:29, 9406.06 examples/s] 
Generating train split: 68286437 examples [1:03:29, 10178.56 examples/s]
Generating train split: 68287800 examples [1:03:29, 10140.93 examples/s]
Generating train split: 68289433 examples [1:03:29, 11244.45 examples/s]
Generating train split: 68290777 examples [1:03:30, 8721.76 examples/s] 
Generating train split: 68291870 examples [1:03:30, 8054.73 examples/s]
Generating train split: 68292829 examples [1:03:30, 7651.94 examples/s]
Generating train split: 68299843 examples [1:03:30, 20180.91 examples/s]
Generating train split: 68306311 examples [1:03:30, 30002.19 examples/s]
Generating train split: 68310129 examples [1:03:30, 26601.25 examples/s]
Generating train split: 68313431 examples [1:03:31, 17943.10 examples/s]
Generating train split: 68316020 examples [1:03:31, 15329.70 examples/s]
Generating train split: 68323340 examples [1:03:31, 24649.55 examples/s]
Generating train split: 68331002 examples [1:03:31, 34362.65 examples/s]
Generating train split: 68335873 examples [1:03:31, 35302.77 examples/s]
Generating train split: 68340425 examples [1:03:32, 21456.30 examples/s]
Generating train split: 68343927 examples [1:03:32, 14428.73 examples/s]
Generating train split: 68346591 examples [1:03:32, 13029.99 examples/s]
Generating train split: 68350799 examples [1:03:32, 16565.39 examples/s]
Generating train split: 68355747 examples [1:03:33, 21440.59 examples/s]
Generating train split: 68359165 examples [1:03:33, 18582.98 examples/s]
Generating train split: 68361957 examples [1:03:33, 19009.83 examples/s]
Generating train split: 68364541 examples [1:03:33, 19283.70 examples/s]
Generating train split: 68370037 examples [1:03:33, 26332.47 examples/s]
Generating train split: 68378634 examples [1:03:33, 39462.93 examples/s]
Generating train split: 68384983 examples [1:03:33, 45154.96 examples/s]
Generating train split: 68390325 examples [1:03:34, 31977.79 examples/s]
Generating train split: 68394615 examples [1:03:34, 27533.19 examples/s]
Generating train split: 68398209 examples [1:03:34, 27213.35 examples/s]
Generating train split: 68401512 examples [1:03:34, 25430.95 examples/s]
Generating train split: 68404458 examples [1:03:34, 23261.46 examples/s]
Generating train split: 68407063 examples [1:03:34, 22888.15 examples/s]
Generating train split: 68410998 examples [1:03:35, 26471.23 examples/s]
Generating train split: 68414017 examples [1:03:35, 27345.19 examples/s]
Generating train split: 68416953 examples [1:03:35, 17871.34 examples/s]
Generating train split: 68419294 examples [1:03:35, 16902.62 examples/s]
Generating train split: 68421729 examples [1:03:35, 18338.75 examples/s]
Generating train split: 68423905 examples [1:03:36, 14959.41 examples/s]
Generating train split: 68425727 examples [1:03:36, 14125.12 examples/s]
Generating train split: 68428610 examples [1:03:36, 17089.50 examples/s]
Generating train split: 68430610 examples [1:03:36, 11597.75 examples/s]
Generating train split: 68432189 examples [1:03:36, 11220.23 examples/s]
Generating train split: 68435434 examples [1:03:36, 15116.78 examples/s]
Generating train split: 68439425 examples [1:03:36, 20267.22 examples/s]
Generating train split: 68445219 examples [1:03:37, 28881.85 examples/s]
Generating train split: 68448762 examples [1:03:37, 22209.18 examples/s]
Generating train split: 68451903 examples [1:03:37, 24085.19 examples/s]
Generating train split: 68455749 examples [1:03:37, 27304.22 examples/s]
Generating train split: 68459917 examples [1:03:37, 30802.70 examples/s]
Generating train split: 68463438 examples [1:03:37, 23289.91 examples/s]
Generating train split: 68466332 examples [1:03:38, 17129.68 examples/s]
Generating train split: 68468642 examples [1:03:38, 12423.24 examples/s]
Generating train split: 68471105 examples [1:03:38, 14202.21 examples/s]
Generating train split: 68473114 examples [1:03:38, 14566.22 examples/s]
Generating train split: 68475890 examples [1:03:38, 17045.76 examples/s]
Generating train split: 68479135 examples [1:03:38, 20293.41 examples/s]
Generating train split: 68481601 examples [1:03:39, 14588.25 examples/s]
Generating train split: 68483580 examples [1:03:39, 13124.03 examples/s]
Generating train split: 68485958 examples [1:03:39, 15071.65 examples/s]
Generating train split: 68487854 examples [1:03:39, 13563.99 examples/s]
Generating train split: 68489494 examples [1:03:39, 13120.99 examples/s]
Generating train split: 68491201 examples [1:03:39, 13952.16 examples/s]
Generating train split: 68493145 examples [1:03:40, 15216.17 examples/s]
Generating train split: 68495427 examples [1:03:40, 17102.30 examples/s]
Generating train split: 68497289 examples [1:03:40, 12287.02 examples/s]
Generating train split: 68498802 examples [1:03:40, 12000.10 examples/s]
Generating train split: 68501450 examples [1:03:40, 15126.88 examples/s]
Generating train split: 68503746 examples [1:03:40, 16839.27 examples/s]
Generating train split: 68505651 examples [1:03:40, 16748.59 examples/s]
Generating train split: 68507480 examples [1:03:41, 14389.70 examples/s]
Generating train split: 68509076 examples [1:03:41, 13624.00 examples/s]
Generating train split: 68510545 examples [1:03:41, 12886.05 examples/s]
Generating train split: 68511918 examples [1:03:41, 11167.66 examples/s]
Generating train split: 68513238 examples [1:03:41, 11362.27 examples/s]
Generating train split: 68515847 examples [1:03:41, 14578.45 examples/s]
Generating train split: 68517403 examples [1:03:41, 14292.73 examples/s]
Generating train split: 68519029 examples [1:03:41, 14698.39 examples/s]
Generating train split: 68520884 examples [1:03:42, 15313.16 examples/s]
Generating train split: 68522683 examples [1:03:42, 16008.92 examples/s]
Generating train split: 68524410 examples [1:03:42, 16238.54 examples/s]
Generating train split: 68526222 examples [1:03:42, 16764.48 examples/s]
Generating train split: 68530476 examples [1:03:42, 24175.24 examples/s]
Generating train split: 68533321 examples [1:03:42, 25199.35 examples/s]
Generating train split: 68535874 examples [1:03:42, 23780.41 examples/s]
Generating train split: 68538762 examples [1:03:42, 25165.08 examples/s]
Generating train split: 68541810 examples [1:03:42, 26643.40 examples/s]
Generating train split: 68544516 examples [1:03:42, 24794.68 examples/s]
Generating train split: 68547123 examples [1:03:43, 25143.95 examples/s]
Generating train split: 68552900 examples [1:03:43, 34357.95 examples/s]
Generating train split: 68557954 examples [1:03:43, 38989.94 examples/s]
Generating train split: 68563517 examples [1:03:43, 43832.77 examples/s]
Generating train split: 68567999 examples [1:03:43, 26611.27 examples/s]
Generating train split: 68571528 examples [1:03:44, 19927.04 examples/s]
Generating train split: 68575008 examples [1:03:44, 22414.64 examples/s]
Generating train split: 68578210 examples [1:03:44, 24080.85 examples/s]
Generating train split: 68581244 examples [1:03:44, 15331.89 examples/s]
Generating train split: 68583590 examples [1:03:44, 15344.00 examples/s]
Generating train split: 68586613 examples [1:03:44, 17891.89 examples/s]
Generating train split: 68590427 examples [1:03:44, 21837.95 examples/s]
Generating train split: 68593240 examples [1:03:45, 12145.44 examples/s]
Generating train split: 68595363 examples [1:03:45, 13289.80 examples/s]
Generating train split: 68599035 examples [1:03:45, 17173.57 examples/s]
Generating train split: 68602322 examples [1:03:45, 20177.82 examples/s]
Generating train split: 68605101 examples [1:03:46, 14886.76 examples/s]
Generating train split: 68607316 examples [1:03:46, 14629.89 examples/s]
Generating train split: 68610150 examples [1:03:46, 17135.42 examples/s]
Generating train split: 68612385 examples [1:03:46, 16006.77 examples/s]
Generating train split: 68614347 examples [1:03:46, 15228.13 examples/s]
Generating train split: 68616125 examples [1:03:46, 14139.50 examples/s]
Generating train split: 68618678 examples [1:03:46, 16534.31 examples/s]
Generating train split: 68620546 examples [1:03:47, 13783.05 examples/s]
Generating train split: 68627819 examples [1:03:47, 26288.80 examples/s]
Generating train split: 68632468 examples [1:03:47, 28767.74 examples/s]
Generating train split: 68635820 examples [1:03:47, 23013.46 examples/s]
Generating train split: 68638617 examples [1:03:47, 18898.74 examples/s]
Generating train split: 68643130 examples [1:03:48, 20011.78 examples/s]
Generating train split: 68645426 examples [1:03:48, 15963.28 examples/s]
Generating train split: 68647300 examples [1:03:48, 15529.76 examples/s]
Generating train split: 68649449 examples [1:03:48, 16487.67 examples/s]
Generating train split: 68651275 examples [1:03:48, 15490.63 examples/s]
Generating train split: 68652946 examples [1:03:48, 15565.96 examples/s]
Generating train split: 68654592 examples [1:03:49, 11843.70 examples/s]
Generating train split: 68657410 examples [1:03:49, 15091.40 examples/s]
Generating train split: 68659211 examples [1:03:49, 11191.36 examples/s]
Generating train split: 68660654 examples [1:03:49, 10026.23 examples/s]
Generating train split: 68664931 examples [1:03:49, 16005.24 examples/s]
Generating train split: 68672343 examples [1:03:49, 28024.16 examples/s]
Generating train split: 68677667 examples [1:03:49, 33762.98 examples/s]
Generating train split: 68681884 examples [1:03:50, 21396.91 examples/s]
Generating train split: 68685175 examples [1:03:50, 17867.83 examples/s]
Generating train split: 68687837 examples [1:03:50, 17696.95 examples/s]
Generating train split: 68690212 examples [1:03:50, 17071.74 examples/s]
Generating train split: 68692327 examples [1:03:51, 16278.98 examples/s]
Generating train split: 68694228 examples [1:03:51, 10247.00 examples/s]
Generating train split: 68699373 examples [1:03:51, 16179.92 examples/s]
Generating train split: 68708223 examples [1:03:51, 28515.22 examples/s]
Generating train split: 68713432 examples [1:03:51, 32584.50 examples/s]
Generating train split: 68718321 examples [1:03:51, 35600.93 examples/s]
Generating train split: 68722887 examples [1:03:52, 15538.54 examples/s]
Generating train split: 68726279 examples [1:03:52, 13824.13 examples/s]
Generating train split: 68728958 examples [1:03:53, 12724.25 examples/s]
Generating train split: 68731131 examples [1:03:53, 11694.61 examples/s]
Generating train split: 68733219 examples [1:03:53, 12846.43 examples/s]
Generating train split: 68735083 examples [1:03:53, 12863.06 examples/s]
Generating train split: 68738542 examples [1:03:53, 16307.58 examples/s]
Generating train split: 68741202 examples [1:03:53, 18303.06 examples/s]
Generating train split: 68743485 examples [1:03:54, 16544.06 examples/s]
Generating train split: 68745472 examples [1:03:54, 15496.79 examples/s]
Generating train split: 68747254 examples [1:03:54, 15307.70 examples/s]
Generating train split: 68749482 examples [1:03:54, 16873.92 examples/s]
Generating train split: 68751728 examples [1:03:54, 18018.69 examples/s]
Generating train split: 68753676 examples [1:03:54, 15943.83 examples/s]
Generating train split: 68755512 examples [1:03:54, 16506.53 examples/s]
Generating train split: 68757268 examples [1:03:54, 16421.40 examples/s]
Generating train split: 68761839 examples [1:03:55, 18402.76 examples/s]
Generating train split: 68764450 examples [1:03:55, 20027.08 examples/s]
Generating train split: 68766498 examples [1:03:55, 19558.04 examples/s]
Generating train split: 68768748 examples [1:03:55, 20244.29 examples/s]
Generating train split: 68771000 examples [1:03:55, 20828.50 examples/s]
Generating train split: 68773132 examples [1:03:55, 13680.31 examples/s]
Generating train split: 68774829 examples [1:03:56, 10411.39 examples/s]
Generating train split: 68777997 examples [1:03:56, 14005.13 examples/s]
Generating train split: 68781771 examples [1:03:56, 18525.90 examples/s]
Generating train split: 68784569 examples [1:03:56, 12482.34 examples/s]
Generating train split: 68786461 examples [1:03:56, 11880.44 examples/s]
Generating train split: 68788985 examples [1:03:57, 14064.20 examples/s]
Generating train split: 68792048 examples [1:03:57, 17187.09 examples/s]
Generating train split: 68795593 examples [1:03:57, 19874.17 examples/s]
Generating train split: 68797978 examples [1:03:57, 13850.85 examples/s]
Generating train split: 68799872 examples [1:03:57, 13947.82 examples/s]
Generating train split: 68803640 examples [1:03:57, 18464.60 examples/s]
Generating train split: 68805986 examples [1:03:58, 13456.00 examples/s]
Generating train split: 68809547 examples [1:03:58, 17318.00 examples/s]
Generating train split: 68811921 examples [1:03:58, 17631.80 examples/s]
Generating train split: 68814144 examples [1:03:58, 15416.61 examples/s]
Generating train split: 68816040 examples [1:03:58, 14627.39 examples/s]
Generating train split: 68818161 examples [1:03:58, 15968.69 examples/s]
Generating train split: 68820401 examples [1:03:58, 17425.60 examples/s]
Generating train split: 68822970 examples [1:03:59, 19446.99 examples/s]
Generating train split: 68826721 examples [1:03:59, 24114.34 examples/s]
Generating train split: 68834865 examples [1:03:59, 36442.32 examples/s]
Generating train split: 68838552 examples [1:03:59, 21746.61 examples/s]
Generating train split: 68842574 examples [1:03:59, 25089.38 examples/s]
Generating train split: 68845800 examples [1:03:59, 23629.47 examples/s]
Generating train split: 68848663 examples [1:04:00, 16442.73 examples/s]
Generating train split: 68850916 examples [1:04:00, 16606.22 examples/s]
Generating train split: 68853014 examples [1:04:00, 13796.49 examples/s]
Generating train split: 68854742 examples [1:04:00, 11521.71 examples/s]
Generating train split: 68857586 examples [1:04:00, 14239.59 examples/s]
Generating train split: 68859417 examples [1:04:01, 14997.32 examples/s]
Generating train split: 68861254 examples [1:04:01, 8979.99 examples/s] 
Generating train split: 68862656 examples [1:04:01, 9124.39 examples/s]
Generating train split: 68866551 examples [1:04:01, 14059.85 examples/s]
Generating train split: 68874476 examples [1:04:01, 26521.30 examples/s]
Generating train split: 68881055 examples [1:04:01, 34629.57 examples/s]
Generating train split: 68885624 examples [1:04:02, 22633.01 examples/s]
Generating train split: 68889197 examples [1:04:02, 22386.00 examples/s]
Generating train split: 68897722 examples [1:04:02, 33581.97 examples/s]
Generating train split: 68902492 examples [1:04:02, 26693.77 examples/s]
Generating train split: 68906333 examples [1:04:03, 17666.05 examples/s]
Generating train split: 68909284 examples [1:04:03, 18453.24 examples/s]
Generating train split: 68912587 examples [1:04:03, 20613.82 examples/s]
Generating train split: 68915897 examples [1:04:03, 22841.00 examples/s]
Generating train split: 68918896 examples [1:04:03, 24047.49 examples/s]
Generating train split: 68921864 examples [1:04:04, 18763.67 examples/s]
Generating train split: 68924330 examples [1:04:04, 14629.72 examples/s]
Generating train split: 68927589 examples [1:04:04, 17591.54 examples/s]
Generating train split: 68929917 examples [1:04:04, 11523.36 examples/s]
Generating train split: 68932644 examples [1:04:04, 13803.52 examples/s]
Generating train split: 68936022 examples [1:04:05, 17227.57 examples/s]
Generating train split: 68938485 examples [1:04:05, 13526.62 examples/s]
Generating train split: 68940460 examples [1:04:05, 12753.88 examples/s]
Generating train split: 68942166 examples [1:04:05, 12150.49 examples/s]
Generating train split: 68943673 examples [1:04:05, 12617.67 examples/s]
Generating train split: 68946886 examples [1:04:05, 16644.45 examples/s]
Generating train split: 68948895 examples [1:04:06, 13059.41 examples/s]
Generating train split: 68951388 examples [1:04:06, 15383.18 examples/s]
Generating train split: 68953301 examples [1:04:06, 13037.17 examples/s]
Generating train split: 68954911 examples [1:04:06, 13264.49 examples/s]
Generating train split: 68956460 examples [1:04:06, 13636.63 examples/s]
Generating train split: 68959555 examples [1:04:06, 17678.01 examples/s]
Generating train split: 68963154 examples [1:04:06, 22023.93 examples/s]
Generating train split: 68965581 examples [1:04:06, 21132.69 examples/s]
Generating train split: 68967856 examples [1:04:07, 15174.11 examples/s]
Generating train split: 68970298 examples [1:04:07, 17080.63 examples/s]
Generating train split: 68972329 examples [1:04:07, 17441.39 examples/s]
Generating train split: 68974308 examples [1:04:07, 13826.37 examples/s]
Generating train split: 68976577 examples [1:04:07, 15682.06 examples/s]
Generating train split: 68979891 examples [1:04:07, 19702.96 examples/s]
Generating train split: 68983673 examples [1:04:08, 20194.30 examples/s]
Generating train split: 68986015 examples [1:04:08, 20927.35 examples/s]
Generating train split: 68988287 examples [1:04:08, 18597.94 examples/s]
Generating train split: 68990293 examples [1:04:08, 16074.00 examples/s]
Generating train split: 68992042 examples [1:04:08, 14697.05 examples/s]
Generating train split: 68993724 examples [1:04:08, 15165.00 examples/s]
Generating train split: 68995447 examples [1:04:08, 15425.87 examples/s]
Generating train split: 68997062 examples [1:04:09, 13487.34 examples/s]
Generating train split: 68999031 examples [1:04:09, 14905.18 examples/s]
Generating train split: 69000614 examples [1:04:09, 13852.07 examples/s]
Generating train split: 69002068 examples [1:04:09, 13675.82 examples/s]
Generating train split: 69003484 examples [1:04:09, 11826.94 examples/s]
Generating train split: 69004740 examples [1:04:09, 11252.58 examples/s]
Generating train split: 69005911 examples [1:04:09, 10264.17 examples/s]
Generating train split: 69007578 examples [1:04:09, 11768.45 examples/s]
Generating train split: 69008821 examples [1:04:10, 11644.01 examples/s]
Generating train split: 69010038 examples [1:04:10, 10994.62 examples/s]
Generating train split: 69011646 examples [1:04:10, 12079.62 examples/s]
Generating train split: 69012890 examples [1:04:10, 9013.40 examples/s] 
Generating train split: 69015470 examples [1:04:10, 12674.26 examples/s]
Generating train split: 69024036 examples [1:04:10, 30064.11 examples/s]
Generating train split: 69032334 examples [1:04:10, 43493.50 examples/s]
Generating train split: 69037353 examples [1:04:11, 31141.65 examples/s]
Generating train split: 69041431 examples [1:04:11, 22493.35 examples/s]
Generating train split: 69044659 examples [1:04:11, 18733.01 examples/s]
Generating train split: 69047579 examples [1:04:11, 20305.48 examples/s]
Generating train split: 69050276 examples [1:04:12, 14428.07 examples/s]
Generating train split: 69055987 examples [1:04:12, 20770.15 examples/s]
Generating train split: 69064454 examples [1:04:12, 31954.44 examples/s]
Generating train split: 69069218 examples [1:04:12, 33982.49 examples/s]
Generating train split: 69073785 examples [1:04:12, 34503.67 examples/s]
Generating train split: 69078472 examples [1:04:12, 36284.40 examples/s]
Generating train split: 69082719 examples [1:04:13, 22013.54 examples/s]
Generating train split: 69086011 examples [1:04:13, 23298.72 examples/s]
Generating train split: 69089231 examples [1:04:13, 24965.38 examples/s]
Generating train split: 69092416 examples [1:04:13, 17649.87 examples/s]
Generating train split: 69094933 examples [1:04:13, 17243.25 examples/s]
Generating train split: 69098214 examples [1:04:13, 20033.12 examples/s]
Generating train split: 69103224 examples [1:04:13, 26144.01 examples/s]
Generating train split: 69106508 examples [1:04:14, 17588.50 examples/s]
Generating train split: 69109290 examples [1:04:14, 19328.24 examples/s]
Generating train split: 69112651 examples [1:04:14, 22116.45 examples/s]
Generating train split: 69115512 examples [1:04:14, 22938.28 examples/s]
Generating train split: 69118276 examples [1:04:15, 14097.97 examples/s]
Generating train split: 69120421 examples [1:04:15, 15129.01 examples/s]
Generating train split: 69123690 examples [1:04:15, 18418.95 examples/s]
Generating train split: 69127942 examples [1:04:15, 23499.20 examples/s]
Generating train split: 69130934 examples [1:04:15, 15769.86 examples/s]
Generating train split: 69133286 examples [1:04:15, 16944.79 examples/s]
Generating train split: 69136885 examples [1:04:15, 20679.27 examples/s]
Generating train split: 69140706 examples [1:04:16, 24396.25 examples/s]
Generating train split: 69143713 examples [1:04:16, 18561.81 examples/s]
Generating train split: 69146170 examples [1:04:16, 12990.85 examples/s]
Generating train split: 69148086 examples [1:04:16, 12273.78 examples/s]
Generating train split: 69149734 examples [1:04:17, 9983.31 examples/s] 
Generating train split: 69151064 examples [1:04:17, 9178.20 examples/s]
Generating train split: 69152212 examples [1:04:17, 9528.23 examples/s]
Generating train split: 69153802 examples [1:04:17, 10676.79 examples/s]
Generating train split: 69155643 examples [1:04:17, 12269.35 examples/s]
Generating train split: 69157088 examples [1:04:17, 9726.23 examples/s] 
Generating train split: 69158287 examples [1:04:17, 9628.78 examples/s]
Generating train split: 69159397 examples [1:04:18, 9593.76 examples/s]
Generating train split: 69160463 examples [1:04:18, 9663.41 examples/s]
Generating train split: 69161840 examples [1:04:18, 10640.84 examples/s]
Generating train split: 69163108 examples [1:04:18, 11156.61 examples/s]
Generating train split: 69164525 examples [1:04:18, 11955.27 examples/s]
Generating train split: 69169533 examples [1:04:18, 22412.84 examples/s]
Generating train split: 69171896 examples [1:04:18, 20763.09 examples/s]
Generating train split: 69174081 examples [1:04:18, 15279.27 examples/s]
Generating train split: 69175886 examples [1:04:19, 14600.29 examples/s]
Generating train split: 69177530 examples [1:04:19, 9569.39 examples/s] 
Generating train split: 69178824 examples [1:04:19, 9236.10 examples/s]
Generating train split: 69179978 examples [1:04:19, 9617.36 examples/s]
Generating train split: 69182537 examples [1:04:19, 10597.98 examples/s]
Generating train split: 69184621 examples [1:04:20, 12479.91 examples/s]
Generating train split: 69186248 examples [1:04:20, 13256.97 examples/s]
Generating train split: 69187728 examples [1:04:20, 13108.21 examples/s]
Generating train split: 69190342 examples [1:04:20, 16280.99 examples/s]
Generating train split: 69192130 examples [1:04:20, 10240.20 examples/s]
Generating train split: 69193801 examples [1:04:20, 11330.68 examples/s]
Generating train split: 69197278 examples [1:04:20, 16181.19 examples/s]
Generating train split: 69200614 examples [1:04:21, 20082.34 examples/s]
Generating train split: 69203056 examples [1:04:21, 17226.02 examples/s]
Generating train split: 69205144 examples [1:04:21, 16750.45 examples/s]
Generating train split: 69207081 examples [1:04:21, 14340.29 examples/s]
Generating train split: 69209892 examples [1:04:21, 17257.10 examples/s]
Generating train split: 69211898 examples [1:04:21, 17273.85 examples/s]
Generating train split: 69214381 examples [1:04:21, 19065.73 examples/s]
Generating train split: 69216466 examples [1:04:22, 11949.06 examples/s]
Generating train split: 69218107 examples [1:04:22, 9036.44 examples/s] 
Generating train split: 69219409 examples [1:04:22, 8739.02 examples/s]
Generating train split: 69220562 examples [1:04:22, 8326.12 examples/s]
Generating train split: 69222997 examples [1:04:22, 11177.68 examples/s]
Generating train split: 69224436 examples [1:04:23, 9676.23 examples/s] 
Generating train split: 69225653 examples [1:04:23, 9878.48 examples/s]
Generating train split: 69227865 examples [1:04:23, 12424.23 examples/s]
Generating train split: 69230067 examples [1:04:23, 14622.29 examples/s]
Generating train split: 69232487 examples [1:04:23, 16979.94 examples/s]
Generating train split: 69234393 examples [1:04:24, 7715.84 examples/s] 
Generating train split: 69235826 examples [1:04:24, 8270.76 examples/s]
Generating train split: 69237750 examples [1:04:24, 9996.71 examples/s]
Generating train split: 69239713 examples [1:04:24, 11746.29 examples/s]
Generating train split: 69241342 examples [1:04:24, 9817.26 examples/s] 
Generating train split: 69245411 examples [1:04:24, 15627.41 examples/s]
Generating train split: 69247576 examples [1:04:25, 6635.31 examples/s] 
Generating train split: 69249170 examples [1:04:25, 7470.65 examples/s]
Generating train split: 69252316 examples [1:04:26, 8214.01 examples/s]
Generating train split: 69254718 examples [1:04:26, 10173.71 examples/s]
Generating train split: 69258117 examples [1:04:26, 13738.62 examples/s]
Generating train split: 69260270 examples [1:04:26, 7910.31 examples/s] 
Generating train split: 69261898 examples [1:04:27, 8787.47 examples/s]
Generating train split: 69264994 examples [1:04:27, 11934.71 examples/s]
Generating train split: 69268110 examples [1:04:27, 15174.43 examples/s]
Generating train split: 69271850 examples [1:04:27, 19424.24 examples/s]
Generating train split: 69274609 examples [1:04:27, 10920.76 examples/s]
Generating train split: 69277071 examples [1:04:28, 10071.51 examples/s]
Generating train split: 69278787 examples [1:04:28, 10535.75 examples/s]
Generating train split: 69282695 examples [1:04:28, 14938.59 examples/s]
Generating train split: 69285219 examples [1:04:28, 14158.19 examples/s]
Generating train split: 69287190 examples [1:04:28, 11299.33 examples/s]
Generating train split: 69290456 examples [1:04:29, 14711.99 examples/s]
Generating train split: 69293787 examples [1:04:29, 18163.37 examples/s]
Generating train split: 69296431 examples [1:04:29, 19877.91 examples/s]
Generating train split: 69298945 examples [1:04:29, 13847.35 examples/s]
Generating train split: 69300940 examples [1:04:29, 14584.43 examples/s]
Generating train split: 69304669 examples [1:04:29, 19086.80 examples/s]
Generating train split: 69308719 examples [1:04:29, 23700.37 examples/s]
Generating train split: 69311635 examples [1:04:30, 18724.35 examples/s]
Generating train split: 69314037 examples [1:04:30, 15763.73 examples/s]
Generating train split: 69317603 examples [1:04:30, 19501.22 examples/s]
Generating train split: 69320085 examples [1:04:30, 18047.08 examples/s]
Generating train split: 69322268 examples [1:04:30, 16982.75 examples/s]
Generating train split: 69324222 examples [1:04:30, 14250.98 examples/s]
Generating train split: 69326424 examples [1:04:31, 15775.70 examples/s]
Generating train split: 69328244 examples [1:04:31, 11916.38 examples/s]
Generating train split: 69330302 examples [1:04:31, 13481.47 examples/s]
Generating train split: 69332141 examples [1:04:31, 14474.40 examples/s]
Generating train split: 69333856 examples [1:04:31, 15089.19 examples/s]
Generating train split: 69335555 examples [1:04:31, 11468.35 examples/s]
Generating train split: 69342461 examples [1:04:31, 23375.65 examples/s]
Generating train split: 69350202 examples [1:04:32, 35165.78 examples/s]
Generating train split: 69354522 examples [1:04:32, 21544.99 examples/s]
Generating train split: 69357874 examples [1:04:32, 18225.17 examples/s]
Generating train split: 69360591 examples [1:04:32, 16286.51 examples/s]
Generating train split: 69362852 examples [1:04:33, 16104.83 examples/s]
Generating train split: 69365231 examples [1:04:33, 17372.04 examples/s]
Generating train split: 69367943 examples [1:04:33, 19286.58 examples/s]
Generating train split: 69370255 examples [1:04:33, 14990.06 examples/s]
Generating train split: 69372152 examples [1:04:33, 13582.84 examples/s]
Generating train split: 69374224 examples [1:04:33, 14870.04 examples/s]
Generating train split: 69375980 examples [1:04:34, 12210.47 examples/s]
Generating train split: 69377440 examples [1:04:34, 11923.67 examples/s]
Generating train split: 69379595 examples [1:04:34, 13883.54 examples/s]
Generating train split: 69382202 examples [1:04:34, 16642.69 examples/s]
Generating train split: 69384119 examples [1:04:34, 17243.25 examples/s]
Generating train split: 69386024 examples [1:04:34, 14508.16 examples/s]
Generating train split: 69390721 examples [1:04:34, 22055.25 examples/s]
Generating train split: 69399358 examples [1:04:34, 38091.59 examples/s]
Generating train split: 69404146 examples [1:04:35, 40652.69 examples/s]
Generating train split: 69408649 examples [1:04:35, 23753.63 examples/s]
Generating train split: 69412165 examples [1:04:35, 21519.23 examples/s]
Generating train split: 69415130 examples [1:04:35, 15784.35 examples/s]
Generating train split: 69417451 examples [1:04:36, 12648.12 examples/s]
Generating train split: 69419295 examples [1:04:36, 12482.17 examples/s]
Generating train split: 69420937 examples [1:04:36, 11674.77 examples/s]
Generating train split: 69422511 examples [1:04:36, 12306.47 examples/s]
Generating train split: 69424056 examples [1:04:36, 12895.95 examples/s]
Generating train split: 69425542 examples [1:04:37, 10491.51 examples/s]
Generating train split: 69427406 examples [1:04:37, 12037.01 examples/s]
Generating train split: 69429177 examples [1:04:37, 13238.29 examples/s]
Generating train split: 69430713 examples [1:04:37, 12197.83 examples/s]
Generating train split: 69432095 examples [1:04:37, 9957.98 examples/s] 
Generating train split: 69433787 examples [1:04:37, 11392.70 examples/s]
Generating train split: 69435186 examples [1:04:37, 11982.58 examples/s]
Generating train split: 69436691 examples [1:04:37, 12656.39 examples/s]
Generating train split: 69438393 examples [1:04:38, 13767.18 examples/s]
Generating train split: 69439875 examples [1:04:38, 12754.71 examples/s]
Generating train split: 69441470 examples [1:04:38, 13543.16 examples/s]
Generating train split: 69443132 examples [1:04:38, 14367.91 examples/s]
Generating train split: 69444626 examples [1:04:38, 10462.59 examples/s]
Generating train split: 69447095 examples [1:04:38, 13624.36 examples/s]
Generating train split: 69448699 examples [1:04:38, 10548.53 examples/s]
Generating train split: 69450026 examples [1:04:39, 9304.22 examples/s] 
Generating train split: 69454077 examples [1:04:39, 15414.36 examples/s]
Generating train split: 69456081 examples [1:04:39, 12259.40 examples/s]
Generating train split: 69458364 examples [1:04:39, 14234.57 examples/s]
Generating train split: 69461839 examples [1:04:39, 18563.09 examples/s]
Generating train split: 69467952 examples [1:04:39, 28453.15 examples/s]
Generating train split: 69475176 examples [1:04:39, 39368.02 examples/s]
Generating train split: 69483581 examples [1:04:39, 50545.40 examples/s]
Generating train split: 69489209 examples [1:04:40, 29952.15 examples/s]
Generating train split: 69493610 examples [1:04:40, 31128.14 examples/s]
Generating train split: 69497752 examples [1:04:40, 30164.70 examples/s]
Generating train split: 69501481 examples [1:04:40, 27208.27 examples/s]
Generating train split: 69510289 examples [1:04:40, 39474.01 examples/s]
Generating train split: 69518504 examples [1:04:41, 49008.86 examples/s]
Generating train split: 69524403 examples [1:04:41, 35637.17 examples/s]
Generating train split: 69529163 examples [1:04:41, 33786.43 examples/s]
Generating train split: 69533361 examples [1:04:41, 21065.50 examples/s]
Generating train split: 69536584 examples [1:04:42, 14664.67 examples/s]
Generating train split: 69539045 examples [1:04:42, 13083.25 examples/s]
Generating train split: 69541803 examples [1:04:42, 14820.46 examples/s]
Generating train split: 69545016 examples [1:04:42, 17308.28 examples/s]
Generating train split: 69547498 examples [1:04:43, 15872.94 examples/s]
Generating train split: 69549611 examples [1:04:43, 13356.83 examples/s]
Generating train split: 69551962 examples [1:04:43, 15028.47 examples/s]
Generating train split: 69553929 examples [1:04:43, 15750.98 examples/s]
Generating train split: 69558388 examples [1:04:43, 21885.43 examples/s]
Generating train split: 69561536 examples [1:04:43, 23487.27 examples/s]
Generating train split: 69564253 examples [1:04:43, 19183.33 examples/s]
Generating train split: 69566553 examples [1:04:44, 19990.08 examples/s]
Generating train split: 69569227 examples [1:04:44, 21573.86 examples/s]
Generating train split: 69571630 examples [1:04:44, 16680.81 examples/s]
Generating train split: 69573627 examples [1:04:44, 12217.05 examples/s]
Generating train split: 69575227 examples [1:04:44, 10476.77 examples/s]
Generating train split: 69576605 examples [1:04:45, 10645.27 examples/s]
Generating train split: 69577994 examples [1:04:45, 11202.55 examples/s]
Generating train split: 69579298 examples [1:04:45, 9714.50 examples/s] 
Generating train split: 69580422 examples [1:04:45, 8952.03 examples/s]
Generating train split: 69581436 examples [1:04:45, 5876.19 examples/s]
Generating train split: 69582792 examples [1:04:45, 7070.70 examples/s]
Generating train split: 69583773 examples [1:04:46, 5942.70 examples/s]
Generating train split: 69585536 examples [1:04:46, 7934.38 examples/s]
Generating train split: 69588614 examples [1:04:46, 12368.56 examples/s]
Generating train split: 69591941 examples [1:04:46, 16921.16 examples/s]
Generating train split: 69594098 examples [1:04:46, 17114.84 examples/s]
Generating train split: 69596790 examples [1:04:46, 19126.45 examples/s]
Generating train split: 69598965 examples [1:04:47, 11572.56 examples/s]
Generating train split: 69601018 examples [1:04:47, 13140.47 examples/s]
Generating train split: 69604288 examples [1:04:47, 17020.54 examples/s]
Generating train split: 69606524 examples [1:04:47, 12978.78 examples/s]
Generating train split: 69608655 examples [1:04:47, 12048.10 examples/s]
Generating train split: 69610225 examples [1:04:48, 10453.99 examples/s]
Generating train split: 69611544 examples [1:04:48, 9121.80 examples/s] 
Generating train split: 69613843 examples [1:04:48, 11501.26 examples/s]
Generating train split: 69616595 examples [1:04:48, 14649.25 examples/s]
Generating train split: 69618495 examples [1:04:48, 14107.71 examples/s]
Generating train split: 69620170 examples [1:04:48, 14465.89 examples/s]
Generating train split: 69621821 examples [1:04:48, 11332.81 examples/s]
Generating train split: 69623951 examples [1:04:49, 13350.24 examples/s]
Generating train split: 69625909 examples [1:04:49, 14746.54 examples/s]
Generating train split: 69627614 examples [1:04:49, 13689.84 examples/s]
Generating train split: 69629986 examples [1:04:49, 15813.09 examples/s]
Generating train split: 69632739 examples [1:04:49, 18636.73 examples/s]
Generating train split: 69634764 examples [1:04:49, 18853.33 examples/s]
Generating train split: 69637402 examples [1:04:49, 20701.14 examples/s]
Generating train split: 69639570 examples [1:04:49, 15808.66 examples/s]
Generating train split: 69641390 examples [1:04:50, 16028.41 examples/s]
Generating train split: 69643661 examples [1:04:50, 17560.82 examples/s]
Generating train split: 69645574 examples [1:04:50, 17224.19 examples/s]
Generating train split: 69647746 examples [1:04:50, 18260.75 examples/s]
Generating train split: 69649662 examples [1:04:50, 13195.61 examples/s]
Generating train split: 69651233 examples [1:04:50, 13728.31 examples/s]
Generating train split: 69660791 examples [1:04:50, 32980.51 examples/s]
Generating train split: 69664757 examples [1:04:50, 32017.18 examples/s]
Generating train split: 69668430 examples [1:04:51, 27925.45 examples/s]
Generating train split: 69671636 examples [1:04:51, 26803.09 examples/s]
Generating train split: 69674805 examples [1:04:51, 27239.17 examples/s]
Generating train split: 69677733 examples [1:04:51, 16112.51 examples/s]
Generating train split: 69680008 examples [1:04:52, 9785.46 examples/s] 
Generating train split: 69682846 examples [1:04:52, 12028.83 examples/s]
Generating train split: 69685827 examples [1:04:52, 14643.21 examples/s]
Generating train split: 69688160 examples [1:04:53, 8913.14 examples/s] 
Generating train split: 69689924 examples [1:04:53, 9941.02 examples/s]
Generating train split: 69693091 examples [1:04:53, 13120.29 examples/s]
Generating train split: 69695980 examples [1:04:53, 15843.93 examples/s]
Generating train split: 69699691 examples [1:04:53, 20051.60 examples/s]
Generating train split: 69702476 examples [1:04:53, 12858.39 examples/s]
Generating train split: 69705757 examples [1:04:53, 15988.51 examples/s]
Generating train split: 69709377 examples [1:04:54, 19678.56 examples/s]
Generating train split: 69712207 examples [1:04:54, 20400.29 examples/s]
Generating train split: 69714863 examples [1:04:54, 12871.97 examples/s]
Generating train split: 69716915 examples [1:04:54, 13881.35 examples/s]
Generating train split: 69721112 examples [1:04:54, 18955.61 examples/s]
Generating train split: 69725018 examples [1:04:54, 22981.14 examples/s]
Generating train split: 69728032 examples [1:04:55, 13532.09 examples/s]
Generating train split: 69730616 examples [1:04:55, 15382.81 examples/s]
Generating train split: 69735653 examples [1:04:55, 21581.61 examples/s]
Generating train split: 69738840 examples [1:04:55, 15532.30 examples/s]
Generating train split: 69741339 examples [1:04:56, 12356.26 examples/s]
Generating train split: 69743995 examples [1:04:56, 14327.13 examples/s]
Generating train split: 69749074 examples [1:04:56, 20447.98 examples/s]
Generating train split: 69752121 examples [1:04:56, 13509.65 examples/s]
Generating train split: 69754455 examples [1:04:57, 14421.46 examples/s]
Generating train split: 69757395 examples [1:04:57, 16889.77 examples/s]
Generating train split: 69760820 examples [1:04:57, 20197.36 examples/s]
Generating train split: 69764447 examples [1:04:57, 20601.76 examples/s]
Generating train split: 69766997 examples [1:04:57, 14223.62 examples/s]
Generating train split: 69770104 examples [1:04:57, 16979.88 examples/s]
Generating train split: 69773804 examples [1:04:57, 20727.57 examples/s]
Generating train split: 69776528 examples [1:04:58, 19082.24 examples/s]
Generating train split: 69778905 examples [1:04:58, 14898.22 examples/s]
Generating train split: 69783201 examples [1:04:58, 19977.05 examples/s]
Generating train split: 69786357 examples [1:04:58, 22350.99 examples/s]
Generating train split: 69789150 examples [1:05:00, 4318.92 examples/s] 
Generating train split: 69791146 examples [1:05:01, 3877.28 examples/s]
Generating train split: 69792629 examples [1:05:01, 4307.29 examples/s]
Generating train split: 69795340 examples [1:05:01, 5939.02 examples/s]
Generating train split: 69797059 examples [1:05:01, 6978.18 examples/s]
Generating train split: 69798869 examples [1:05:01, 8275.11 examples/s]
Generating train split: 69800962 examples [1:05:01, 9930.45 examples/s]
Generating train split: 69802746 examples [1:05:02, 8556.95 examples/s]
Generating train split: 69804181 examples [1:05:02, 9269.24 examples/s]
Generating train split: 69805662 examples [1:05:02, 10199.33 examples/s]
Generating train split: 69807069 examples [1:05:02, 7732.65 examples/s] 
Generating train split: 69809952 examples [1:05:02, 11281.08 examples/s]
Generating train split: 69811607 examples [1:05:03, 7899.28 examples/s] 
Generating train split: 69812893 examples [1:05:03, 7892.93 examples/s]
Generating train split: 69814531 examples [1:05:03, 9258.20 examples/s]
Generating train split: 69815808 examples [1:05:03, 7366.90 examples/s]
Generating train split: 69817081 examples [1:05:03, 8236.71 examples/s]
Generating train split: 69818913 examples [1:05:04, 10162.21 examples/s]
Generating train split: 69821443 examples [1:05:04, 13422.60 examples/s]
Generating train split: 69825451 examples [1:05:04, 19693.88 examples/s]
Generating train split: 69827837 examples [1:05:04, 20274.74 examples/s]
Generating train split: 69830238 examples [1:05:04, 21129.26 examples/s]
Generating train split: 69832576 examples [1:05:04, 21057.88 examples/s]
Generating train split: 69834833 examples [1:05:04, 15358.58 examples/s]
Generating train split: 69836698 examples [1:05:04, 16003.26 examples/s]
Generating train split: 69838567 examples [1:05:05, 16636.03 examples/s]
Generating train split: 69842795 examples [1:05:05, 23094.45 examples/s]
Generating train split: 69846069 examples [1:05:05, 25640.25 examples/s]
Generating train split: 69848850 examples [1:05:05, 19467.37 examples/s]
Generating train split: 69852825 examples [1:05:05, 23996.28 examples/s]
Generating train split: 69855631 examples [1:05:05, 24141.21 examples/s]
Generating train split: 69864028 examples [1:05:05, 39169.77 examples/s]
Generating train split: 69871316 examples [1:05:05, 47729.94 examples/s]
Generating train split: 69876728 examples [1:05:05, 49012.68 examples/s]
Generating train split: 69881950 examples [1:05:06, 29544.89 examples/s]
Generating train split: 69886062 examples [1:05:06, 27972.74 examples/s]
Generating train split: 69892367 examples [1:05:06, 34750.27 examples/s]
Generating train split: 69896777 examples [1:05:06, 28104.36 examples/s]
Generating train split: 69900419 examples [1:05:07, 20558.88 examples/s]
Generating train split: 69903293 examples [1:05:07, 20433.04 examples/s]
Generating train split: 69907012 examples [1:05:07, 19639.55 examples/s]
Generating train split: 69909913 examples [1:05:07, 21004.66 examples/s]
Generating train split: 69912387 examples [1:05:07, 18654.91 examples/s]
Generating train split: 69914523 examples [1:05:07, 16950.46 examples/s]
Generating train split: 69916399 examples [1:05:08, 16008.18 examples/s]
Generating train split: 69919084 examples [1:05:08, 18243.94 examples/s]
Generating train split: 69921094 examples [1:05:08, 17649.45 examples/s]
Generating train split: 69922984 examples [1:05:08, 14995.66 examples/s]
Generating train split: 69924614 examples [1:05:08, 14326.26 examples/s]
Generating train split: 69926135 examples [1:05:08, 14488.72 examples/s]
Generating train split: 69929638 examples [1:05:08, 19501.86 examples/s]
Generating train split: 69937517 examples [1:05:08, 34838.89 examples/s]
Generating train split: 69941365 examples [1:05:09, 22092.30 examples/s]
Generating train split: 69944405 examples [1:05:09, 21653.15 examples/s]
Generating train split: 69948116 examples [1:05:09, 24752.19 examples/s]
Generating train split: 69951157 examples [1:05:09, 16431.28 examples/s]
Generating train split: 69953532 examples [1:05:10, 15371.77 examples/s]
Generating train split: 69955573 examples [1:05:10, 14882.41 examples/s]
Generating train split: 69959351 examples [1:05:10, 19094.92 examples/s]
Generating train split: 69962915 examples [1:05:10, 22509.23 examples/s]
Generating train split: 69965679 examples [1:05:10, 14558.13 examples/s]
Generating train split: 69967835 examples [1:05:10, 13858.36 examples/s]
Generating train split: 69970252 examples [1:05:11, 15646.26 examples/s]
Generating train split: 69973807 examples [1:05:11, 19598.70 examples/s]
Generating train split: 69976302 examples [1:05:11, 19992.69 examples/s]
Generating train split: 69978675 examples [1:05:11, 18426.31 examples/s]
Generating train split: 69980791 examples [1:05:11, 16874.58 examples/s]
Generating train split: 69982678 examples [1:05:11, 16719.05 examples/s]
Generating train split: 69986558 examples [1:05:11, 21919.87 examples/s]
Generating train split: 69988989 examples [1:05:11, 20065.75 examples/s]
Generating train split: 69991186 examples [1:05:12, 18666.73 examples/s]
Generating train split: 69993189 examples [1:05:12, 15153.35 examples/s]
Generating train split: 69996618 examples [1:05:12, 19192.31 examples/s]
Generating train split: 69998825 examples [1:05:12, 19260.79 examples/s]
Generating train split: 70002874 examples [1:05:12, 19491.03 examples/s]
Generating train split: 70004967 examples [1:05:12, 18702.99 examples/s]
Generating train split: 70008305 examples [1:05:12, 21841.22 examples/s]
Generating train split: 70010634 examples [1:05:13, 13425.13 examples/s]
Generating train split: 70012460 examples [1:05:13, 14205.31 examples/s]
Generating train split: 70015706 examples [1:05:13, 17818.45 examples/s]
Generating train split: 70017953 examples [1:05:13, 13643.47 examples/s]
Generating train split: 70021546 examples [1:05:14, 15124.74 examples/s]
Generating train split: 70023375 examples [1:05:14, 14567.80 examples/s]
Generating train split: 70025040 examples [1:05:14, 14202.36 examples/s]
Generating train split: 70026596 examples [1:05:14, 10048.40 examples/s]
Generating train split: 70030565 examples [1:05:14, 15152.05 examples/s]
Generating train split: 70032624 examples [1:05:14, 14785.91 examples/s]
Generating train split: 70034557 examples [1:05:15, 13966.82 examples/s]
Generating train split: 70037159 examples [1:05:15, 16450.72 examples/s]
Generating train split: 70039603 examples [1:05:15, 18258.81 examples/s]
Generating train split: 70042247 examples [1:05:15, 20214.84 examples/s]
Generating train split: 70046364 examples [1:05:15, 25633.69 examples/s]
Generating train split: 70049178 examples [1:05:15, 14307.32 examples/s]
Generating train split: 70051350 examples [1:05:15, 15454.07 examples/s]
Generating train split: 70054385 examples [1:05:16, 18386.06 examples/s]
Generating train split: 70057410 examples [1:05:16, 20988.12 examples/s]
Generating train split: 70060017 examples [1:05:16, 14865.06 examples/s]
Generating train split: 70062088 examples [1:05:16, 11040.08 examples/s]
Generating train split: 70063721 examples [1:05:16, 11801.35 examples/s]
Generating train split: 70066016 examples [1:05:17, 11180.57 examples/s]
Generating train split: 70069092 examples [1:05:17, 14279.41 examples/s]
Generating train split: 70070921 examples [1:05:17, 11441.14 examples/s]
Generating train split: 70073413 examples [1:05:17, 13762.29 examples/s]
Generating train split: 70075201 examples [1:05:17, 9734.17 examples/s] 
Generating train split: 70078861 examples [1:05:18, 14022.18 examples/s]
Generating train split: 70083441 examples [1:05:18, 19922.00 examples/s]
Generating train split: 70086276 examples [1:05:18, 12912.97 examples/s]
Generating train split: 70088457 examples [1:05:18, 11738.57 examples/s]
Generating train split: 70090694 examples [1:05:18, 13340.56 examples/s]
Generating train split: 70094947 examples [1:05:19, 18517.37 examples/s]
Generating train split: 70098039 examples [1:05:19, 19881.68 examples/s]
Generating train split: 70100615 examples [1:05:19, 14660.35 examples/s]
Generating train split: 70105165 examples [1:05:19, 15519.84 examples/s]
Generating train split: 70107929 examples [1:05:19, 17448.77 examples/s]
Generating train split: 70110109 examples [1:05:20, 14377.02 examples/s]
Generating train split: 70111904 examples [1:05:20, 14321.64 examples/s]
Generating train split: 70113632 examples [1:05:20, 14846.56 examples/s]
Generating train split: 70115329 examples [1:05:20, 14679.02 examples/s]
Generating train split: 70116946 examples [1:05:20, 12259.21 examples/s]
Generating train split: 70119151 examples [1:05:20, 14307.90 examples/s]
Generating train split: 70121475 examples [1:05:20, 16363.82 examples/s]
Generating train split: 70123706 examples [1:05:20, 17833.23 examples/s]
Generating train split: 70125656 examples [1:05:21, 13907.49 examples/s]
Generating train split: 70127701 examples [1:05:21, 15303.10 examples/s]
Generating train split: 70129454 examples [1:05:21, 15823.33 examples/s]
Generating train split: 70138006 examples [1:05:21, 33579.09 examples/s]
Generating train split: 70141795 examples [1:05:21, 33143.28 examples/s]
Generating train split: 70145410 examples [1:05:21, 28726.92 examples/s]
Generating train split: 70148589 examples [1:05:22, 17398.21 examples/s]
Generating train split: 70151068 examples [1:05:22, 16975.33 examples/s]
Generating train split: 70153270 examples [1:05:22, 17346.86 examples/s]
Generating train split: 70155531 examples [1:05:22, 18398.04 examples/s]
Generating train split: 70159179 examples [1:05:22, 22427.40 examples/s]
Generating train split: 70162355 examples [1:05:22, 20408.82 examples/s]
Generating train split: 70164688 examples [1:05:22, 16706.49 examples/s]
Generating train split: 70167023 examples [1:05:23, 18039.72 examples/s]
Generating train split: 70170895 examples [1:05:23, 22637.99 examples/s]
Generating train split: 70173697 examples [1:05:23, 20140.83 examples/s]
Generating train split: 70175997 examples [1:05:23, 15478.28 examples/s]
Generating train split: 70177882 examples [1:05:23, 15380.17 examples/s]
Generating train split: 70181423 examples [1:05:23, 19548.22 examples/s]
Generating train split: 70183726 examples [1:05:23, 20007.86 examples/s]
Generating train split: 70185983 examples [1:05:24, 20123.70 examples/s]
Generating train split: 70188178 examples [1:05:24, 19345.91 examples/s]
Generating train split: 70190249 examples [1:05:24, 19663.89 examples/s]
Generating train split: 70192745 examples [1:05:24, 20997.55 examples/s]
Generating train split: 70194927 examples [1:05:24, 17555.52 examples/s]
Generating train split: 70199516 examples [1:05:24, 24488.13 examples/s]
Generating train split: 70202224 examples [1:05:25, 13570.42 examples/s]
Generating train split: 70205626 examples [1:05:25, 16969.17 examples/s]
Generating train split: 70208657 examples [1:05:25, 19512.64 examples/s]
Generating train split: 70212638 examples [1:05:25, 22957.52 examples/s]
Generating train split: 70215498 examples [1:05:25, 15816.70 examples/s]
Generating train split: 70217756 examples [1:05:25, 16563.30 examples/s]
Generating train split: 70223263 examples [1:05:25, 24110.85 examples/s]
Generating train split: 70226455 examples [1:05:26, 18401.77 examples/s]
Generating train split: 70229022 examples [1:05:26, 18323.85 examples/s]
Generating train split: 70232057 examples [1:05:26, 20649.21 examples/s]
Generating train split: 70235683 examples [1:05:26, 24031.13 examples/s]
Generating train split: 70238559 examples [1:05:27, 13180.28 examples/s]
Generating train split: 70240747 examples [1:05:27, 12838.82 examples/s]
Generating train split: 70244275 examples [1:05:27, 16422.75 examples/s]
Generating train split: 70247530 examples [1:05:27, 19418.14 examples/s]
Generating train split: 70250926 examples [1:05:27, 15796.24 examples/s]
Generating train split: 70253112 examples [1:05:27, 13291.14 examples/s]
Generating train split: 70256746 examples [1:05:28, 17069.54 examples/s]
Generating train split: 70261014 examples [1:05:28, 17880.31 examples/s]
Generating train split: 70263236 examples [1:05:28, 13691.12 examples/s]
Generating train split: 70265016 examples [1:05:28, 12361.89 examples/s]
Generating train split: 70267320 examples [1:05:28, 14111.90 examples/s]
Generating train split: 70269077 examples [1:05:29, 12795.05 examples/s]
Generating train split: 70271853 examples [1:05:29, 15634.79 examples/s]
Generating train split: 70273753 examples [1:05:29, 13817.74 examples/s]
Generating train split: 70275888 examples [1:05:29, 15284.83 examples/s]
Generating train split: 70277659 examples [1:05:29, 12693.37 examples/s]
Generating train split: 70279214 examples [1:05:29, 13266.07 examples/s]
Generating train split: 70280874 examples [1:05:29, 14006.72 examples/s]
Generating train split: 70282428 examples [1:05:30, 13605.40 examples/s]
Generating train split: 70283892 examples [1:05:30, 13428.13 examples/s]
Generating train split: 70286169 examples [1:05:30, 15472.89 examples/s]
Generating train split: 70287787 examples [1:05:30, 14981.59 examples/s]
Generating train split: 70289338 examples [1:05:30, 13116.67 examples/s]
Generating train split: 70290718 examples [1:05:30, 12877.90 examples/s]
Generating train split: 70292285 examples [1:05:30, 13544.86 examples/s]
Generating train split: 70294109 examples [1:05:30, 14789.53 examples/s]
Generating train split: 70295635 examples [1:05:30, 14029.55 examples/s]
Generating train split: 70299173 examples [1:05:31, 19788.60 examples/s]
Generating train split: 70303295 examples [1:05:31, 25746.52 examples/s]
Generating train split: 70311095 examples [1:05:31, 40571.75 examples/s]
Generating train split: 70315309 examples [1:05:31, 30793.41 examples/s]
Generating train split: 70318854 examples [1:05:31, 30249.96 examples/s]
Generating train split: 70327058 examples [1:05:31, 33059.21 examples/s]
Generating train split: 70330516 examples [1:05:31, 31050.45 examples/s]
Generating train split: 70333698 examples [1:05:32, 30506.07 examples/s]
Generating train split: 70336788 examples [1:05:32, 25600.60 examples/s]
Generating train split: 70339463 examples [1:05:32, 19871.66 examples/s]
Generating train split: 70342746 examples [1:05:32, 22151.92 examples/s]
Generating train split: 70345461 examples [1:05:32, 22916.08 examples/s]
Generating train split: 70347968 examples [1:05:32, 18777.67 examples/s]
Generating train split: 70350095 examples [1:05:33, 16707.98 examples/s]
Generating train split: 70353230 examples [1:05:33, 16906.86 examples/s]
Generating train split: 70355722 examples [1:05:33, 18495.80 examples/s]
Generating train split: 70358486 examples [1:05:33, 20531.57 examples/s]
Generating train split: 70360739 examples [1:05:33, 19568.37 examples/s]
Generating train split: 70362824 examples [1:05:33, 17224.60 examples/s]
Generating train split: 70364825 examples [1:05:33, 17730.06 examples/s]
Generating train split: 70366932 examples [1:05:33, 18457.48 examples/s]
Generating train split: 70370066 examples [1:05:34, 21553.44 examples/s]
Generating train split: 70372325 examples [1:05:34, 19403.48 examples/s]
Generating train split: 70374373 examples [1:05:34, 18414.94 examples/s]
Generating train split: 70376292 examples [1:05:34, 17400.76 examples/s]
Generating train split: 70378083 examples [1:05:34, 14951.89 examples/s]
Generating train split: 70379667 examples [1:05:34, 13442.92 examples/s]
Generating train split: 70385848 examples [1:05:34, 24556.12 examples/s]
Generating train split: 70388701 examples [1:05:35, 22666.76 examples/s]
Generating train split: 70391254 examples [1:05:35, 16544.69 examples/s]
Generating train split: 70393323 examples [1:05:35, 15382.73 examples/s]
Generating train split: 70398295 examples [1:05:35, 22164.82 examples/s]
Generating train split: 70403208 examples [1:05:35, 26839.58 examples/s]
Generating train split: 70406372 examples [1:05:36, 18344.11 examples/s]
Generating train split: 70408876 examples [1:05:36, 19378.41 examples/s]
Generating train split: 70412015 examples [1:05:36, 21707.52 examples/s]
Generating train split: 70415464 examples [1:05:36, 24497.34 examples/s]
Generating train split: 70418344 examples [1:05:36, 16425.17 examples/s]
Generating train split: 70421787 examples [1:05:36, 19684.60 examples/s]
Generating train split: 70424421 examples [1:05:37, 15072.82 examples/s]
Generating train split: 70426535 examples [1:05:37, 15893.14 examples/s]
Generating train split: 70429230 examples [1:05:37, 18065.08 examples/s]
Generating train split: 70431483 examples [1:05:37, 17411.00 examples/s]
Generating train split: 70433537 examples [1:05:37, 15348.24 examples/s]
Generating train split: 70437543 examples [1:05:37, 20574.63 examples/s]
Generating train split: 70441495 examples [1:05:37, 24890.18 examples/s]
Generating train split: 70444376 examples [1:05:38, 12995.24 examples/s]
Generating train split: 70447944 examples [1:05:38, 16396.96 examples/s]
Generating train split: 70451348 examples [1:05:38, 19527.19 examples/s]
Generating train split: 70454671 examples [1:05:38, 22271.97 examples/s]
Generating train split: 70457660 examples [1:05:39, 13135.85 examples/s]
Generating train split: 70460573 examples [1:05:39, 15520.43 examples/s]
Generating train split: 70464218 examples [1:05:39, 19176.60 examples/s]
Generating train split: 70467030 examples [1:05:39, 17248.96 examples/s]
Generating train split: 70469412 examples [1:05:39, 16313.39 examples/s]
Generating train split: 70471752 examples [1:05:39, 17672.86 examples/s]
Generating train split: 70474524 examples [1:05:39, 19846.59 examples/s]
Generating train split: 70476866 examples [1:05:40, 17787.85 examples/s]
Generating train split: 70478935 examples [1:05:40, 17502.82 examples/s]
Generating train split: 70480879 examples [1:05:40, 17594.28 examples/s]
Generating train split: 70482787 examples [1:05:40, 16557.21 examples/s]
Generating train split: 70485323 examples [1:05:40, 18593.98 examples/s]
Generating train split: 70487304 examples [1:05:40, 18309.64 examples/s]
Generating train split: 70489315 examples [1:05:40, 18775.50 examples/s]
Generating train split: 70491484 examples [1:05:40, 19519.36 examples/s]
Generating train split: 70493493 examples [1:05:40, 18426.68 examples/s]
Generating train split: 70495696 examples [1:05:41, 19347.28 examples/s]
Generating train split: 70497679 examples [1:05:41, 16618.44 examples/s]
Generating train split: 70499436 examples [1:05:41, 15732.32 examples/s]
Generating train split: 70501077 examples [1:05:41, 15374.06 examples/s]
Generating train split: 70504360 examples [1:05:41, 19890.87 examples/s]
Generating train split: 70506455 examples [1:05:41, 14161.20 examples/s]
Generating train split: 70508172 examples [1:05:41, 14252.16 examples/s]
Generating train split: 70510422 examples [1:05:41, 16121.23 examples/s]
Generating train split: 70512694 examples [1:05:42, 17684.76 examples/s]
Generating train split: 70514640 examples [1:05:42, 15774.29 examples/s]
Generating train split: 70516737 examples [1:05:42, 17032.32 examples/s]
Generating train split: 70520147 examples [1:05:42, 21426.73 examples/s]
Generating train split: 70525974 examples [1:05:42, 30883.20 examples/s]
Generating train split: 70529257 examples [1:05:42, 25543.93 examples/s]
Generating train split: 70532099 examples [1:05:42, 25435.22 examples/s]
Generating train split: 70536719 examples [1:05:42, 30643.23 examples/s]
Generating train split: 70540553 examples [1:05:43, 32644.06 examples/s]
Generating train split: 70546305 examples [1:05:43, 27840.16 examples/s]
Generating train split: 70549420 examples [1:05:43, 19721.61 examples/s]
Generating train split: 70551907 examples [1:05:43, 18409.08 examples/s]
Generating train split: 70554992 examples [1:05:43, 20681.19 examples/s]
Generating train split: 70557452 examples [1:05:44, 18913.61 examples/s]
Generating train split: 70559625 examples [1:05:44, 18037.12 examples/s]
Generating train split: 70562897 examples [1:05:44, 20679.51 examples/s]
Generating train split: 70565177 examples [1:05:44, 16255.85 examples/s]
Generating train split: 70568193 examples [1:05:44, 19030.37 examples/s]
Generating train split: 70570732 examples [1:05:44, 20096.14 examples/s]
Generating train split: 70572989 examples [1:05:44, 16888.07 examples/s]
Generating train split: 70574922 examples [1:05:45, 14594.82 examples/s]
Generating train split: 70577099 examples [1:05:45, 16060.51 examples/s]
Generating train split: 70579714 examples [1:05:45, 18283.23 examples/s]
Generating train split: 70581758 examples [1:05:45, 16967.38 examples/s]
Generating train split: 70583622 examples [1:05:45, 14119.56 examples/s]
Generating train split: 70589018 examples [1:05:45, 22797.35 examples/s]
Generating train split: 70591752 examples [1:05:45, 19215.38 examples/s]
Generating train split: 70594066 examples [1:05:46, 18713.31 examples/s]
Generating train split: 70596211 examples [1:05:46, 16360.56 examples/s]
Generating train split: 70598068 examples [1:05:46, 15293.31 examples/s]
Generating train split: 70600058 examples [1:05:46, 16276.13 examples/s]
Generating train split: 70602180 examples [1:05:46, 17349.24 examples/s]
Generating train split: 70604041 examples [1:05:46, 14615.26 examples/s]
Generating train split: 70606155 examples [1:05:46, 16055.69 examples/s]
Generating train split: 70607907 examples [1:05:47, 13181.08 examples/s]
Generating train split: 70610559 examples [1:05:47, 16111.65 examples/s]
Generating train split: 70612403 examples [1:05:47, 15892.36 examples/s]
Generating train split: 70614149 examples [1:05:47, 11837.96 examples/s]
Generating train split: 70615877 examples [1:05:47, 12918.34 examples/s]
Generating train split: 70618557 examples [1:05:47, 16033.30 examples/s]
Generating train split: 70620427 examples [1:05:47, 13844.59 examples/s]
Generating train split: 70622042 examples [1:05:48, 12358.16 examples/s]
Generating train split: 70623949 examples [1:05:48, 13751.65 examples/s]
Generating train split: 70625496 examples [1:05:48, 11407.10 examples/s]
Generating train split: 70627741 examples [1:05:48, 13718.02 examples/s]
Generating train split: 70629801 examples [1:05:48, 15295.10 examples/s]
Generating train split: 70631708 examples [1:05:48, 16219.47 examples/s]
Generating train split: 70634428 examples [1:05:48, 19096.25 examples/s]
Generating train split: 70637234 examples [1:05:48, 21419.25 examples/s]
Generating train split: 70639502 examples [1:05:49, 18008.13 examples/s]
Generating train split: 70642899 examples [1:05:49, 21942.62 examples/s]
Generating train split: 70645303 examples [1:05:49, 21294.64 examples/s]
Generating train split: 70647580 examples [1:05:49, 15229.03 examples/s]
Generating train split: 70649438 examples [1:05:49, 14303.43 examples/s]
Generating train split: 70651096 examples [1:05:49, 13241.35 examples/s]
Generating train split: 70653468 examples [1:05:50, 15459.29 examples/s]
Generating train split: 70659692 examples [1:05:50, 26333.22 examples/s]
Generating train split: 70665258 examples [1:05:50, 33640.57 examples/s]
Generating train split: 70672600 examples [1:05:50, 44086.66 examples/s]
Generating train split: 70679019 examples [1:05:50, 49563.70 examples/s]
Generating train split: 70684369 examples [1:05:50, 29292.65 examples/s]
Generating train split: 70689331 examples [1:05:50, 33068.91 examples/s]
Generating train split: 70693762 examples [1:05:51, 15024.38 examples/s]
Generating train split: 70697028 examples [1:05:51, 14724.19 examples/s]
Generating train split: 70699730 examples [1:05:52, 12201.56 examples/s]
Generating train split: 70701842 examples [1:05:52, 11833.31 examples/s]
Generating train split: 70703638 examples [1:05:52, 11913.76 examples/s]
Generating train split: 70706233 examples [1:05:52, 13999.92 examples/s]
Generating train split: 70710378 examples [1:05:52, 18653.32 examples/s]
Generating train split: 70712907 examples [1:05:52, 17209.39 examples/s]
Generating train split: 70715102 examples [1:05:53, 17449.73 examples/s]
Generating train split: 70717228 examples [1:05:53, 12344.90 examples/s]
Generating train split: 70718887 examples [1:05:53, 8161.14 examples/s] 
Generating train split: 70720888 examples [1:05:53, 9723.78 examples/s]
Generating train split: 70723583 examples [1:05:54, 12451.23 examples/s]
Generating train split: 70725431 examples [1:05:54, 12135.71 examples/s]
Generating train split: 70727075 examples [1:05:54, 8463.99 examples/s] 
Generating train split: 70728924 examples [1:05:54, 9943.10 examples/s]
Generating train split: 70730360 examples [1:05:54, 10217.18 examples/s]
Generating train split: 70731709 examples [1:05:55, 8418.85 examples/s] 
Generating train split: 70732817 examples [1:05:55, 8574.03 examples/s]
Generating train split: 70734006 examples [1:05:55, 9194.90 examples/s]
Generating train split: 70735447 examples [1:05:55, 10092.16 examples/s]
Generating train split: 70736597 examples [1:05:55, 9961.32 examples/s] 
Generating train split: 70737696 examples [1:05:55, 9996.36 examples/s]
Generating train split: 70739087 examples [1:05:55, 10900.25 examples/s]
Generating train split: 70740242 examples [1:05:55, 9299.74 examples/s] 
Generating train split: 70741443 examples [1:05:56, 9918.53 examples/s]
Generating train split: 70742520 examples [1:05:56, 6962.74 examples/s]
Generating train split: 70743387 examples [1:05:56, 7283.85 examples/s]
Generating train split: 70745956 examples [1:05:56, 11365.84 examples/s]
Generating train split: 70747937 examples [1:05:56, 13078.02 examples/s]
Generating train split: 70749512 examples [1:05:56, 13397.38 examples/s]
Generating train split: 70750991 examples [1:05:57, 9417.33 examples/s] 
Generating train split: 70752186 examples [1:05:57, 9543.57 examples/s]
Generating train split: 70753321 examples [1:05:57, 8294.46 examples/s]
Generating train split: 70754302 examples [1:05:57, 8251.97 examples/s]
Generating train split: 70756106 examples [1:05:57, 10223.63 examples/s]
Generating train split: 70757256 examples [1:05:57, 8709.71 examples/s] 
Generating train split: 70758979 examples [1:05:57, 10522.52 examples/s]
Generating train split: 70760186 examples [1:05:57, 10496.89 examples/s]
Generating train split: 70761350 examples [1:05:58, 9540.70 examples/s] 
Generating train split: 70762387 examples [1:05:58, 9148.14 examples/s]
Generating train split: 70764753 examples [1:05:58, 12352.03 examples/s]
Generating train split: 70766087 examples [1:05:58, 12001.29 examples/s]
Generating train split: 70767351 examples [1:05:58, 11374.07 examples/s]
Generating train split: 70768534 examples [1:05:58, 9453.60 examples/s] 
Generating train split: 70769877 examples [1:05:58, 10224.84 examples/s]
Generating train split: 70770970 examples [1:05:59, 9634.38 examples/s] 
Generating train split: 70771997 examples [1:05:59, 7928.23 examples/s]
Generating train split: 70773155 examples [1:05:59, 8725.65 examples/s]
Generating train split: 70774549 examples [1:05:59, 9730.69 examples/s]
Generating train split: 70775605 examples [1:05:59, 8802.17 examples/s]
Generating train split: 70776547 examples [1:05:59, 7407.31 examples/s]
Generating train split: 70777854 examples [1:05:59, 8409.90 examples/s]
Generating train split: 70778768 examples [1:06:00, 5350.40 examples/s]
Generating train split: 70780595 examples [1:06:00, 7324.05 examples/s]
Generating train split: 70781571 examples [1:06:00, 7244.20 examples/s]
Generating train split: 70782450 examples [1:06:00, 7435.63 examples/s]
Generating train split: 70784848 examples [1:06:00, 11113.18 examples/s]
Generating train split: 70786429 examples [1:06:00, 10324.14 examples/s]
Generating train split: 70787622 examples [1:06:01, 10033.35 examples/s]
Generating train split: 70788738 examples [1:06:01, 7692.21 examples/s] 
Generating train split: 70791425 examples [1:06:01, 11491.24 examples/s]
Generating train split: 70793130 examples [1:06:01, 11742.98 examples/s]
Generating train split: 70794520 examples [1:06:01, 8626.25 examples/s] 
Generating train split: 70795636 examples [1:06:01, 8728.32 examples/s]
Generating train split: 70798461 examples [1:06:01, 12669.70 examples/s]
Generating train split: 70801389 examples [1:06:02, 16115.51 examples/s]
Generating train split: 70804537 examples [1:06:02, 19341.96 examples/s]
Generating train split: 70806743 examples [1:06:02, 14967.22 examples/s]
Generating train split: 70809487 examples [1:06:02, 17596.99 examples/s]
Generating train split: 70812975 examples [1:06:02, 21596.50 examples/s]
Generating train split: 70815501 examples [1:06:02, 15162.94 examples/s]
Generating train split: 70817973 examples [1:06:03, 17000.99 examples/s]
Generating train split: 70821197 examples [1:06:03, 20288.40 examples/s]
Generating train split: 70823680 examples [1:06:03, 21346.83 examples/s]
Generating train split: 70826158 examples [1:06:03, 14168.08 examples/s]
Generating train split: 70828613 examples [1:06:03, 16092.57 examples/s]
Generating train split: 70830726 examples [1:06:03, 16584.47 examples/s]
Generating train split: 70835694 examples [1:06:03, 24036.66 examples/s]
Generating train split: 70840167 examples [1:06:04, 27743.10 examples/s]
Generating train split: 70843334 examples [1:06:04, 15847.62 examples/s]
Generating train split: 70846172 examples [1:06:04, 17889.50 examples/s]
Generating train split: 70849564 examples [1:06:04, 20927.82 examples/s]
Generating train split: 70852373 examples [1:06:04, 19276.28 examples/s]
Generating train split: 70854814 examples [1:06:04, 17709.07 examples/s]
Generating train split: 70856949 examples [1:06:05, 18248.91 examples/s]
Generating train split: 70860493 examples [1:06:05, 22107.62 examples/s]
Generating train split: 70863248 examples [1:06:05, 23414.01 examples/s]
Generating train split: 70866508 examples [1:06:05, 25316.20 examples/s]
Generating train split: 70869239 examples [1:06:05, 13306.05 examples/s]
Generating train split: 70871768 examples [1:06:06, 14015.34 examples/s]
Generating train split: 70873726 examples [1:06:06, 9468.84 examples/s] 
Generating train split: 70876605 examples [1:06:06, 12119.30 examples/s]
Generating train split: 70879127 examples [1:06:06, 14142.27 examples/s]
Generating train split: 70881195 examples [1:06:07, 9282.36 examples/s] 
Generating train split: 70884596 examples [1:06:07, 12736.11 examples/s]
Generating train split: 70887501 examples [1:06:07, 15444.10 examples/s]
Generating train split: 70890583 examples [1:06:07, 18338.41 examples/s]
Generating train split: 70893146 examples [1:06:07, 9790.36 examples/s] 
Generating train split: 70895077 examples [1:06:08, 10881.12 examples/s]
Generating train split: 70897980 examples [1:06:08, 13659.44 examples/s]
Generating train split: 70901663 examples [1:06:08, 17860.53 examples/s]
Generating train split: 70904279 examples [1:06:08, 16040.61 examples/s]
Generating train split: 70906493 examples [1:06:08, 13733.06 examples/s]
Generating train split: 70908328 examples [1:06:08, 14061.01 examples/s]
Generating train split: 70911382 examples [1:06:08, 17200.50 examples/s]
Generating train split: 70913482 examples [1:06:09, 12712.72 examples/s]
Generating train split: 70915431 examples [1:06:09, 13939.52 examples/s]
Generating train split: 70918455 examples [1:06:09, 17295.38 examples/s]
Generating train split: 70920602 examples [1:06:09, 12761.23 examples/s]
Generating train split: 70922330 examples [1:06:09, 12512.65 examples/s]
Generating train split: 70925814 examples [1:06:09, 16876.90 examples/s]
Generating train split: 70927950 examples [1:06:10, 15521.34 examples/s]
Generating train split: 70929944 examples [1:06:10, 16461.92 examples/s]
Generating train split: 70931859 examples [1:06:10, 14875.60 examples/s]
Generating train split: 70933751 examples [1:06:10, 15773.45 examples/s]
Generating train split: 70935502 examples [1:06:10, 13742.76 examples/s]
Generating train split: 70937654 examples [1:06:10, 15502.61 examples/s]
Generating train split: 70939373 examples [1:06:10, 14483.67 examples/s]
Generating train split: 70940950 examples [1:06:11, 13907.41 examples/s]
Generating train split: 70942421 examples [1:06:11, 13631.79 examples/s]
Generating train split: 70943842 examples [1:06:11, 11525.85 examples/s]
Generating train split: 70945098 examples [1:06:11, 11763.69 examples/s]
Generating train split: 70946435 examples [1:06:11, 12150.15 examples/s]
Generating train split: 70948657 examples [1:06:11, 14782.18 examples/s]
Generating train split: 70950501 examples [1:06:11, 15753.60 examples/s]
Generating train split: 70952139 examples [1:06:11, 12707.72 examples/s]
Generating train split: 70954728 examples [1:06:12, 15882.07 examples/s]
Generating train split: 70956534 examples [1:06:12, 16390.80 examples/s]
Generating train split: 70958960 examples [1:06:12, 18483.68 examples/s]
Generating train split: 70964612 examples [1:06:12, 28986.45 examples/s]
Generating train split: 70969113 examples [1:06:12, 33519.14 examples/s]
Generating train split: 70973372 examples [1:06:12, 35572.92 examples/s]
Generating train split: 70977039 examples [1:06:12, 27057.94 examples/s]
Generating train split: 70982082 examples [1:06:12, 32585.43 examples/s]
Generating train split: 70985831 examples [1:06:12, 33813.49 examples/s]
Generating train split: 70989814 examples [1:06:13, 35388.50 examples/s]
Generating train split: 70993595 examples [1:06:13, 30838.68 examples/s]
Generating train split: 70998424 examples [1:06:13, 35140.90 examples/s]
Generating train split: 71002205 examples [1:06:13, 26409.68 examples/s]
Generating train split: 71005333 examples [1:06:13, 24715.42 examples/s]
Generating train split: 71009226 examples [1:06:13, 27739.23 examples/s]
Generating train split: 71012357 examples [1:06:13, 28116.95 examples/s]
Generating train split: 71015434 examples [1:06:14, 23143.67 examples/s]
Generating train split: 71018047 examples [1:06:14, 17578.73 examples/s]
Generating train split: 71021716 examples [1:06:14, 21181.18 examples/s]
Generating train split: 71025180 examples [1:06:14, 24054.88 examples/s]
Generating train split: 71028027 examples [1:06:14, 20984.46 examples/s]
Generating train split: 71030493 examples [1:06:15, 15883.14 examples/s]
Generating train split: 71033622 examples [1:06:15, 18716.16 examples/s]
Generating train split: 71037133 examples [1:06:15, 21678.77 examples/s]
Generating train split: 71039725 examples [1:06:15, 22283.18 examples/s]
Generating train split: 71042267 examples [1:06:15, 17143.48 examples/s]
Generating train split: 71044360 examples [1:06:15, 16200.78 examples/s]
Generating train split: 71048678 examples [1:06:15, 17644.57 examples/s]
Generating train split: 71051360 examples [1:06:16, 19223.93 examples/s]
Generating train split: 71053467 examples [1:06:16, 15728.58 examples/s]
Generating train split: 71055867 examples [1:06:16, 17052.82 examples/s]
Generating train split: 71057766 examples [1:06:16, 13316.91 examples/s]
Generating train split: 71059640 examples [1:06:16, 14353.64 examples/s]
Generating train split: 71062983 examples [1:06:16, 18445.67 examples/s]
Generating train split: 71066004 examples [1:06:16, 21180.54 examples/s]
Generating train split: 71068424 examples [1:06:17, 11823.33 examples/s]
Generating train split: 71071777 examples [1:06:17, 15334.88 examples/s]
Generating train split: 71075127 examples [1:06:17, 18739.47 examples/s]
Generating train split: 71077881 examples [1:06:17, 20219.09 examples/s]
Generating train split: 71080483 examples [1:06:17, 17015.83 examples/s]
Generating train split: 71082666 examples [1:06:18, 16445.97 examples/s]
Generating train split: 71085009 examples [1:06:18, 17891.67 examples/s]
Generating train split: 71088285 examples [1:06:18, 21309.13 examples/s]
Generating train split: 71090724 examples [1:06:18, 18909.25 examples/s]
Generating train split: 71092870 examples [1:06:18, 16592.61 examples/s]
Generating train split: 71094736 examples [1:06:18, 13218.01 examples/s]
Generating train split: 71097503 examples [1:06:18, 16045.36 examples/s]
Generating train split: 71100591 examples [1:06:19, 19278.19 examples/s]
Generating train split: 71102858 examples [1:06:19, 19369.05 examples/s]
Generating train split: 71105029 examples [1:06:19, 13837.68 examples/s]
Generating train split: 71107670 examples [1:06:19, 16308.24 examples/s]
Generating train split: 71109701 examples [1:06:19, 16447.70 examples/s]
Generating train split: 71111621 examples [1:06:19, 16342.25 examples/s]
Generating train split: 71113459 examples [1:06:19, 15375.26 examples/s]
Generating train split: 71116364 examples [1:06:19, 18626.52 examples/s]
Generating train split: 71118530 examples [1:06:20, 19169.42 examples/s]
Generating train split: 71120586 examples [1:06:20, 18339.46 examples/s]
Generating train split: 71122532 examples [1:06:20, 14729.18 examples/s]
Generating train split: 71125070 examples [1:06:20, 17087.47 examples/s]
Generating train split: 71126973 examples [1:06:20, 17410.20 examples/s]
Generating train split: 71129769 examples [1:06:20, 20113.38 examples/s]
Generating train split: 71135082 examples [1:06:20, 28980.08 examples/s]
Generating train split: 71138191 examples [1:06:20, 24922.49 examples/s]
Generating train split: 71140925 examples [1:06:21, 21035.48 examples/s]
Generating train split: 71143282 examples [1:06:21, 19982.07 examples/s]
Generating train split: 71145459 examples [1:06:21, 16315.14 examples/s]
Generating train split: 71148403 examples [1:06:21, 19053.08 examples/s]
Generating train split: 71150585 examples [1:06:21, 12350.86 examples/s]
Generating train split: 71152305 examples [1:06:22, 12140.46 examples/s]
Generating train split: 71156000 examples [1:06:22, 16601.84 examples/s]
Generating train split: 71158156 examples [1:06:22, 15788.38 examples/s]
Generating train split: 71161057 examples [1:06:22, 14621.80 examples/s]
Generating train split: 71162783 examples [1:06:22, 13724.72 examples/s]
Generating train split: 71164329 examples [1:06:22, 12551.59 examples/s]
Generating train split: 71165705 examples [1:06:23, 12304.78 examples/s]
Generating train split: 71167917 examples [1:06:23, 14419.50 examples/s]
Generating train split: 71169505 examples [1:06:23, 12967.82 examples/s]
Generating train split: 71170913 examples [1:06:23, 9858.24 examples/s] 
Generating train split: 71172157 examples [1:06:23, 10347.97 examples/s]
Generating train split: 71173398 examples [1:06:23, 10751.18 examples/s]
Generating train split: 71176560 examples [1:06:23, 15694.34 examples/s]
Generating train split: 71184859 examples [1:06:23, 32712.94 examples/s]
Generating train split: 71188795 examples [1:06:24, 34465.54 examples/s]
Generating train split: 71192590 examples [1:06:24, 24521.05 examples/s]
Generating train split: 71195697 examples [1:06:24, 22047.88 examples/s]
Generating train split: 71198375 examples [1:06:24, 21605.64 examples/s]
Generating train split: 71200858 examples [1:06:24, 18151.54 examples/s]
Generating train split: 71202960 examples [1:06:24, 17643.42 examples/s]
Generating train split: 71204922 examples [1:06:25, 17609.33 examples/s]
Generating train split: 71207228 examples [1:06:25, 18847.11 examples/s]
Generating train split: 71211342 examples [1:06:25, 24335.72 examples/s]
Generating train split: 71213994 examples [1:06:25, 15327.32 examples/s]
Generating train split: 71216083 examples [1:06:25, 16214.79 examples/s]
Generating train split: 71218145 examples [1:06:25, 14365.85 examples/s]
Generating train split: 71219917 examples [1:06:26, 14358.86 examples/s]
Generating train split: 71222166 examples [1:06:26, 16096.94 examples/s]
Generating train split: 71224005 examples [1:06:26, 13136.90 examples/s]
Generating train split: 71226105 examples [1:06:26, 14764.83 examples/s]
Generating train split: 71227821 examples [1:06:26, 12345.60 examples/s]
Generating train split: 71229269 examples [1:06:26, 11512.70 examples/s]
Generating train split: 71230939 examples [1:06:26, 12607.92 examples/s]
Generating train split: 71232351 examples [1:06:27, 11628.74 examples/s]
Generating train split: 71234868 examples [1:06:27, 14736.31 examples/s]
Generating train split: 71236524 examples [1:06:27, 12953.65 examples/s]
Generating train split: 71237977 examples [1:06:27, 10905.86 examples/s]
Generating train split: 71239212 examples [1:06:27, 10949.72 examples/s]
Generating train split: 71240575 examples [1:06:27, 11227.62 examples/s]
Generating train split: 71241776 examples [1:06:27, 10021.37 examples/s]
Generating train split: 71243337 examples [1:06:28, 11308.23 examples/s]
Generating train split: 71245285 examples [1:06:28, 13212.99 examples/s]
Generating train split: 71248597 examples [1:06:28, 18395.09 examples/s]
Generating train split: 71256112 examples [1:06:28, 33774.11 examples/s]
Generating train split: 71264505 examples [1:06:28, 46711.22 examples/s]
Generating train split: 71269390 examples [1:06:28, 23714.21 examples/s]
Generating train split: 71273130 examples [1:06:29, 17441.44 examples/s]
Generating train split: 71276034 examples [1:06:29, 13623.89 examples/s]
Generating train split: 71278295 examples [1:06:29, 14010.12 examples/s]
Generating train split: 71280366 examples [1:06:30, 12947.89 examples/s]
Generating train split: 71282417 examples [1:06:30, 14088.76 examples/s]
Generating train split: 71290881 examples [1:06:30, 26598.26 examples/s]
Generating train split: 71299048 examples [1:06:30, 37722.76 examples/s]
Generating train split: 71304176 examples [1:06:30, 38646.30 examples/s]
Generating train split: 71309005 examples [1:06:30, 34040.41 examples/s]
Generating train split: 71313170 examples [1:06:30, 25325.74 examples/s]
Generating train split: 71316759 examples [1:06:31, 27225.84 examples/s]
Generating train split: 71320622 examples [1:06:31, 29555.86 examples/s]
Generating train split: 71327442 examples [1:06:31, 28884.18 examples/s]
Generating train split: 71330768 examples [1:06:31, 20160.53 examples/s]
Generating train split: 71333385 examples [1:06:32, 15602.46 examples/s]
Generating train split: 71335642 examples [1:06:32, 16600.36 examples/s]
Generating train split: 71338480 examples [1:06:32, 18550.57 examples/s]
Generating train split: 71341181 examples [1:06:32, 20197.63 examples/s]
Generating train split: 71343628 examples [1:06:32, 16740.46 examples/s]
Generating train split: 71345671 examples [1:06:32, 16383.77 examples/s]
Generating train split: 71348019 examples [1:06:32, 17869.93 examples/s]
Generating train split: 71351059 examples [1:06:32, 20756.65 examples/s]
Generating train split: 71353390 examples [1:06:33, 19671.93 examples/s]
Generating train split: 71359133 examples [1:06:33, 28782.48 examples/s]
Generating train split: 71362332 examples [1:06:33, 16301.69 examples/s]
Generating train split: 71366544 examples [1:06:33, 20658.25 examples/s]
Generating train split: 71369533 examples [1:06:33, 22422.36 examples/s]
Generating train split: 71372516 examples [1:06:34, 15946.57 examples/s]
Generating train split: 71374881 examples [1:06:34, 14934.15 examples/s]
Generating train split: 71377843 examples [1:06:34, 17458.51 examples/s]
Generating train split: 71381504 examples [1:06:34, 21268.76 examples/s]
Generating train split: 71384212 examples [1:06:34, 18436.51 examples/s]
Generating train split: 71386518 examples [1:06:34, 16134.76 examples/s]
Generating train split: 71388905 examples [1:06:34, 17652.77 examples/s]
Generating train split: 71392016 examples [1:06:35, 20583.62 examples/s]
Generating train split: 71394419 examples [1:06:35, 19200.21 examples/s]
Generating train split: 71396588 examples [1:06:35, 17554.35 examples/s]
Generating train split: 71398528 examples [1:06:35, 16158.55 examples/s]
Generating train split: 71400785 examples [1:06:35, 17608.12 examples/s]
Generating train split: 71404016 examples [1:06:35, 21197.51 examples/s]
Generating train split: 71406323 examples [1:06:35, 21196.39 examples/s]
Generating train split: 71408570 examples [1:06:35, 20608.84 examples/s]
Generating train split: 71410720 examples [1:06:36, 18621.20 examples/s]
Generating train split: 71412674 examples [1:06:36, 16253.65 examples/s]
Generating train split: 71416477 examples [1:06:36, 21352.55 examples/s]
Generating train split: 71418809 examples [1:06:36, 20894.19 examples/s]
Generating train split: 71421048 examples [1:06:36, 19807.07 examples/s]
Generating train split: 71423138 examples [1:06:36, 15003.27 examples/s]
Generating train split: 71424877 examples [1:06:36, 15476.74 examples/s]
Generating train split: 71426953 examples [1:06:37, 16706.44 examples/s]
Generating train split: 71428792 examples [1:06:37, 16682.46 examples/s]
Generating train split: 71435967 examples [1:06:37, 30889.56 examples/s]
Generating train split: 71439366 examples [1:06:37, 22140.81 examples/s]
Generating train split: 71442139 examples [1:06:37, 20490.50 examples/s]
Generating train split: 71444581 examples [1:06:37, 14790.95 examples/s]
Generating train split: 71446530 examples [1:06:38, 11612.69 examples/s]
Generating train split: 71448089 examples [1:06:38, 11691.90 examples/s]
Generating train split: 71449543 examples [1:06:38, 11624.10 examples/s]
Generating train split: 71451724 examples [1:06:38, 13554.56 examples/s]
Generating train split: 71453335 examples [1:06:38, 12902.54 examples/s]
Generating train split: 71454801 examples [1:06:38, 13192.61 examples/s]
Generating train split: 71456792 examples [1:06:38, 14780.92 examples/s]
Generating train split: 71458405 examples [1:06:39, 11236.89 examples/s]
Generating train split: 71459737 examples [1:06:39, 10663.41 examples/s]
Generating train split: 71461655 examples [1:06:39, 12503.10 examples/s]
Generating train split: 71467126 examples [1:06:39, 22468.55 examples/s]
Generating train split: 71474091 examples [1:06:39, 34362.47 examples/s]
Generating train split: 71478023 examples [1:06:39, 28228.37 examples/s]
Generating train split: 71481374 examples [1:06:40, 13975.13 examples/s]
Generating train split: 71483890 examples [1:06:40, 14460.71 examples/s]
Generating train split: 71486148 examples [1:06:40, 12120.30 examples/s]
Generating train split: 71487963 examples [1:06:41, 10739.80 examples/s]
Generating train split: 71489459 examples [1:06:41, 10955.73 examples/s]
Generating train split: 71490871 examples [1:06:41, 11122.97 examples/s]
Generating train split: 71492694 examples [1:06:41, 12289.94 examples/s]
Generating train split: 71495428 examples [1:06:41, 14963.08 examples/s]
Generating train split: 71499297 examples [1:06:41, 20239.14 examples/s]
Generating train split: 71501654 examples [1:06:41, 18626.63 examples/s]
Generating train split: 71504928 examples [1:06:41, 21912.08 examples/s]
Generating train split: 71507632 examples [1:06:42, 22916.89 examples/s]
Generating train split: 71515181 examples [1:06:42, 36656.07 examples/s]
Generating train split: 71523770 examples [1:06:42, 50032.63 examples/s]
Generating train split: 71529158 examples [1:06:42, 45943.91 examples/s]
Generating train split: 71534077 examples [1:06:42, 40130.31 examples/s]
Generating train split: 71538444 examples [1:06:42, 37344.20 examples/s]
Generating train split: 71542440 examples [1:06:42, 26130.90 examples/s]
Generating train split: 71545646 examples [1:06:43, 19623.78 examples/s]
Generating train split: 71548964 examples [1:06:43, 21852.68 examples/s]
Generating train split: 71551751 examples [1:06:43, 18194.83 examples/s]
Generating train split: 71554059 examples [1:06:43, 15343.83 examples/s]
Generating train split: 71556188 examples [1:06:43, 16345.34 examples/s]
Generating train split: 71559739 examples [1:06:44, 20070.52 examples/s]
Generating train split: 71562354 examples [1:06:44, 21023.15 examples/s]
Generating train split: 71564792 examples [1:06:44, 16274.59 examples/s]
Generating train split: 71566800 examples [1:06:44, 15331.50 examples/s]
Generating train split: 71569226 examples [1:06:44, 17147.53 examples/s]
Generating train split: 71571213 examples [1:06:44, 14387.94 examples/s]
Generating train split: 71573291 examples [1:06:44, 15711.98 examples/s]
Generating train split: 71575205 examples [1:06:45, 16487.33 examples/s]
Generating train split: 71577319 examples [1:06:45, 17609.86 examples/s]
Generating train split: 71581727 examples [1:06:45, 24479.50 examples/s]
Generating train split: 71587198 examples [1:06:45, 29107.14 examples/s]
Generating train split: 71590194 examples [1:06:45, 19662.99 examples/s]
Generating train split: 71592598 examples [1:06:45, 16834.17 examples/s]
Generating train split: 71594622 examples [1:06:46, 17362.97 examples/s]
Generating train split: 71596626 examples [1:06:46, 15795.52 examples/s]
Generating train split: 71598402 examples [1:06:46, 15213.33 examples/s]
Generating train split: 71600047 examples [1:06:46, 14381.50 examples/s]
Generating train split: 71602072 examples [1:06:46, 15681.23 examples/s]
Generating train split: 71603765 examples [1:06:46, 15917.50 examples/s]
Generating train split: 71605663 examples [1:06:46, 16697.72 examples/s]
Generating train split: 71607404 examples [1:06:46, 15160.58 examples/s]
Generating train split: 71610952 examples [1:06:47, 20363.20 examples/s]
Generating train split: 71613130 examples [1:06:47, 20320.26 examples/s]
Generating train split: 71615258 examples [1:06:47, 20299.20 examples/s]
Generating train split: 71617369 examples [1:06:47, 18454.30 examples/s]
Generating train split: 71619298 examples [1:06:47, 17048.36 examples/s]
Generating train split: 71621068 examples [1:06:47, 15089.44 examples/s]
Generating train split: 71622658 examples [1:06:47, 14502.20 examples/s]
Generating train split: 71627760 examples [1:06:47, 23522.15 examples/s]
Generating train split: 71630343 examples [1:06:47, 23175.52 examples/s]
Generating train split: 71635445 examples [1:06:48, 30425.33 examples/s]
Generating train split: 71638699 examples [1:06:48, 30955.20 examples/s]
Generating train split: 71641943 examples [1:06:48, 20339.29 examples/s]
Generating train split: 71644560 examples [1:06:48, 16297.09 examples/s]
Generating train split: 71646689 examples [1:06:49, 11186.54 examples/s]
Generating train split: 71648452 examples [1:06:49, 12053.66 examples/s]
Generating train split: 71650536 examples [1:06:49, 13502.01 examples/s]
Generating train split: 71652321 examples [1:06:49, 12027.75 examples/s]
Generating train split: 71654329 examples [1:06:49, 13548.27 examples/s]
Generating train split: 71656371 examples [1:06:49, 14994.23 examples/s]
Generating train split: 71658744 examples [1:06:49, 16990.79 examples/s]
Generating train split: 71660965 examples [1:06:49, 18287.32 examples/s]
Generating train split: 71662995 examples [1:06:50, 15991.53 examples/s]
Generating train split: 71664896 examples [1:06:50, 16552.68 examples/s]
Generating train split: 71666696 examples [1:06:50, 16051.56 examples/s]
Generating train split: 71668402 examples [1:06:50, 11415.83 examples/s]
Generating train split: 71670843 examples [1:06:50, 14062.35 examples/s]
Generating train split: 71673388 examples [1:06:50, 16628.12 examples/s]
Generating train split: 71675391 examples [1:06:50, 17453.15 examples/s]
Generating train split: 71677358 examples [1:06:51, 13190.31 examples/s]
Generating train split: 71679180 examples [1:06:51, 14155.27 examples/s]
Generating train split: 71680849 examples [1:06:51, 13480.85 examples/s]
Generating train split: 71682377 examples [1:06:51, 13799.58 examples/s]
Generating train split: 71684748 examples [1:06:51, 15866.40 examples/s]
Generating train split: 71686456 examples [1:06:51, 15234.01 examples/s]
Generating train split: 71688681 examples [1:06:51, 17027.74 examples/s]
Generating train split: 71690471 examples [1:06:51, 16830.79 examples/s]
Generating train split: 71692218 examples [1:06:52, 16339.71 examples/s]
Generating train split: 71694022 examples [1:06:52, 16504.04 examples/s]
Generating train split: 71695714 examples [1:06:52, 14707.23 examples/s]
Generating train split: 71697474 examples [1:06:52, 14955.14 examples/s]
Generating train split: 71699013 examples [1:06:52, 14978.06 examples/s]
Generating train split: 71700542 examples [1:06:52, 10967.12 examples/s]
Generating train split: 71701824 examples [1:06:52, 11353.36 examples/s]
Generating train split: 71703095 examples [1:06:53, 10464.15 examples/s]
Generating train split: 71704245 examples [1:06:53, 10219.45 examples/s]
Generating train split: 71705346 examples [1:06:53, 9633.68 examples/s] 
Generating train split: 71707180 examples [1:06:53, 11717.51 examples/s]
Generating train split: 71708433 examples [1:06:53, 10905.60 examples/s]
Generating train split: 71709594 examples [1:06:53, 8087.56 examples/s] 
Generating train split: 71713169 examples [1:06:53, 13821.78 examples/s]
Generating train split: 71714907 examples [1:06:54, 10145.05 examples/s]
Generating train split: 71716304 examples [1:06:54, 10069.64 examples/s]
Generating train split: 71718560 examples [1:06:54, 12503.21 examples/s]
Generating train split: 71720123 examples [1:06:54, 13046.59 examples/s]
Generating train split: 71721663 examples [1:06:54, 11630.67 examples/s]
Generating train split: 71723018 examples [1:06:54, 9817.89 examples/s] 
Generating train split: 71724761 examples [1:06:54, 11389.74 examples/s]
Generating train split: 71726097 examples [1:06:55, 11611.66 examples/s]
Generating train split: 71727457 examples [1:06:55, 12077.17 examples/s]
Generating train split: 71729376 examples [1:06:55, 13763.97 examples/s]
Generating train split: 71731318 examples [1:06:55, 15265.70 examples/s]
Generating train split: 71732942 examples [1:06:55, 14012.86 examples/s]
Generating train split: 71734424 examples [1:06:55, 14219.06 examples/s]
Generating train split: 71735907 examples [1:06:55, 12393.42 examples/s]
Generating train split: 71742630 examples [1:06:55, 26149.17 examples/s]
Generating train split: 71750944 examples [1:06:55, 41174.20 examples/s]
Generating train split: 71755506 examples [1:06:56, 33312.55 examples/s]
Generating train split: 71759418 examples [1:06:56, 34653.51 examples/s]
Generating train split: 71763299 examples [1:06:56, 21355.28 examples/s]
Generating train split: 71767712 examples [1:06:56, 25376.59 examples/s]
Generating train split: 71774921 examples [1:06:56, 34785.36 examples/s]
Generating train split: 71779494 examples [1:06:57, 27419.67 examples/s]
Generating train split: 71783228 examples [1:06:57, 26568.79 examples/s]
Generating train split: 71786566 examples [1:06:57, 26834.90 examples/s]
Generating train split: 71789746 examples [1:06:57, 22377.20 examples/s]
Generating train split: 71793681 examples [1:06:57, 25691.11 examples/s]
Generating train split: 71796725 examples [1:06:57, 22157.03 examples/s]
Generating train split: 71801053 examples [1:06:57, 26498.60 examples/s]
Generating train split: 71804309 examples [1:06:58, 27840.34 examples/s]
Generating train split: 71807475 examples [1:06:58, 21760.85 examples/s]
Generating train split: 71810098 examples [1:06:58, 21951.40 examples/s]
Generating train split: 71812614 examples [1:06:58, 22584.48 examples/s]
Generating train split: 71815577 examples [1:06:58, 24281.92 examples/s]
Generating train split: 71818225 examples [1:06:58, 16190.05 examples/s]
Generating train split: 71820340 examples [1:06:59, 15771.09 examples/s]
Generating train split: 71823842 examples [1:06:59, 19661.55 examples/s]
Generating train split: 71829874 examples [1:06:59, 28768.21 examples/s]
Generating train split: 71839377 examples [1:06:59, 44832.20 examples/s]
Generating train split: 71844667 examples [1:06:59, 28636.50 examples/s]
Generating train split: 71848827 examples [1:06:59, 26090.61 examples/s]
Generating train split: 71854250 examples [1:07:00, 31164.47 examples/s]
Generating train split: 71860563 examples [1:07:00, 34993.21 examples/s]
Generating train split: 71864805 examples [1:07:00, 26372.18 examples/s]
Generating train split: 71868226 examples [1:07:00, 24077.80 examples/s]
Generating train split: 71871183 examples [1:07:00, 24346.89 examples/s]
Generating train split: 71874542 examples [1:07:00, 26212.12 examples/s]
Generating train split: 71877532 examples [1:07:01, 22768.84 examples/s]
Generating train split: 71880110 examples [1:07:01, 13694.39 examples/s]
Generating train split: 71882093 examples [1:07:01, 10441.30 examples/s]
Generating train split: 71883652 examples [1:07:02, 9501.66 examples/s] 
Generating train split: 71885848 examples [1:07:02, 11229.51 examples/s]
Generating train split: 71887405 examples [1:07:02, 8477.53 examples/s] 
Generating train split: 71888632 examples [1:07:02, 7790.17 examples/s]
Generating train split: 71889665 examples [1:07:02, 8033.50 examples/s]
Generating train split: 71890670 examples [1:07:02, 8058.46 examples/s]
Generating train split: 71891618 examples [1:07:03, 8054.11 examples/s]
Generating train split: 71892654 examples [1:07:03, 8535.80 examples/s]
Generating train split: 71893906 examples [1:07:03, 9456.92 examples/s]
Generating train split: 71895206 examples [1:07:03, 10300.39 examples/s]
Generating train split: 71896652 examples [1:07:03, 11383.60 examples/s]
Generating train split: 71898108 examples [1:07:03, 12246.51 examples/s]
Generating train split: 71899967 examples [1:07:03, 14015.78 examples/s]
Generating train split: 71901712 examples [1:07:03, 14950.64 examples/s]
Generating train split: 71903251 examples [1:07:03, 14426.83 examples/s]
Generating train split: 71904889 examples [1:07:04, 14912.40 examples/s]
Generating train split: 71906412 examples [1:07:04, 14081.26 examples/s]
Generating train split: 71908800 examples [1:07:04, 16800.70 examples/s]
Generating train split: 71911443 examples [1:07:04, 19510.17 examples/s]
Generating train split: 71913446 examples [1:07:04, 16881.25 examples/s]
Generating train split: 71915328 examples [1:07:04, 17381.33 examples/s]
Generating train split: 71917143 examples [1:07:04, 12377.85 examples/s]
Generating train split: 71919429 examples [1:07:04, 14624.67 examples/s]
Generating train split: 71921245 examples [1:07:05, 15445.65 examples/s]
Generating train split: 71923004 examples [1:07:05, 12235.82 examples/s]
Generating train split: 71925204 examples [1:07:05, 14309.87 examples/s]
Generating train split: 71927769 examples [1:07:05, 16970.61 examples/s]
Generating train split: 71935611 examples [1:07:05, 26669.48 examples/s]
Generating train split: 71938240 examples [1:07:05, 20600.99 examples/s]
Generating train split: 71940435 examples [1:07:06, 17547.78 examples/s]
Generating train split: 71942308 examples [1:07:06, 15782.90 examples/s]
Generating train split: 71944465 examples [1:07:06, 16887.83 examples/s]
Generating train split: 71946267 examples [1:07:06, 12976.98 examples/s]
Generating train split: 71949687 examples [1:07:06, 17057.41 examples/s]
Generating train split: 71954724 examples [1:07:06, 24237.86 examples/s]
Generating train split: 71961119 examples [1:07:06, 33586.21 examples/s]
Generating train split: 71965118 examples [1:07:07, 25999.64 examples/s]
Generating train split: 71968415 examples [1:07:07, 17290.87 examples/s]
Generating train split: 71970977 examples [1:07:07, 15963.74 examples/s]
Generating train split: 71973148 examples [1:07:08, 12612.03 examples/s]
Generating train split: 71974884 examples [1:07:08, 12794.27 examples/s]
Generating train split: 71976504 examples [1:07:08, 11445.77 examples/s]
Generating train split: 71981105 examples [1:07:08, 17358.89 examples/s]
Generating train split: 71988952 examples [1:07:08, 26030.33 examples/s]
Generating train split: 71992018 examples [1:07:08, 24938.65 examples/s]
Generating train split: 71995047 examples [1:07:08, 26050.84 examples/s]
Generating train split: 71997922 examples [1:07:09, 19863.36 examples/s]
Generating train split: 72000286 examples [1:07:09, 19807.21 examples/s]
Generating train split: 72002873 examples [1:07:09, 21085.30 examples/s]
Generating train split: 72006316 examples [1:07:09, 24167.79 examples/s]
Generating train split: 72008983 examples [1:07:09, 17347.68 examples/s]
Generating train split: 72011149 examples [1:07:09, 16439.49 examples/s]
Generating train split: 72013088 examples [1:07:09, 16357.74 examples/s]
Generating train split: 72014931 examples [1:07:10, 15538.23 examples/s]
Generating train split: 72016623 examples [1:07:10, 14327.91 examples/s]
Generating train split: 72018153 examples [1:07:10, 13953.46 examples/s]
Generating train split: 72020508 examples [1:07:10, 16188.82 examples/s]
Generating train split: 72022235 examples [1:07:10, 9511.05 examples/s] 
Generating train split: 72024232 examples [1:07:10, 11306.28 examples/s]
Generating train split: 72025776 examples [1:07:11, 11821.66 examples/s]
Generating train split: 72027274 examples [1:07:11, 9313.00 examples/s] 
Generating train split: 72028814 examples [1:07:11, 10402.37 examples/s]
Generating train split: 72030474 examples [1:07:11, 11700.12 examples/s]
Generating train split: 72033088 examples [1:07:11, 14982.85 examples/s]
Generating train split: 72035229 examples [1:07:11, 16553.11 examples/s]
Generating train split: 72038324 examples [1:07:11, 20292.13 examples/s]
Generating train split: 72040560 examples [1:07:11, 20190.89 examples/s]
Generating train split: 72046044 examples [1:07:12, 29635.14 examples/s]
Generating train split: 72049284 examples [1:07:12, 30406.99 examples/s]
Generating train split: 72052558 examples [1:07:12, 31066.48 examples/s]
Generating train split: 72057358 examples [1:07:12, 35975.36 examples/s]
Generating train split: 72064661 examples [1:07:12, 46426.92 examples/s]
Generating train split: 72069373 examples [1:07:13, 18080.93 examples/s]
Generating train split: 72072901 examples [1:07:13, 16202.50 examples/s]
Generating train split: 72075739 examples [1:07:13, 16187.92 examples/s]
Generating train split: 72080214 examples [1:07:13, 20457.84 examples/s]
Generating train split: 72084987 examples [1:07:13, 25007.71 examples/s]
Generating train split: 72088485 examples [1:07:14, 14723.13 examples/s]
Generating train split: 72091141 examples [1:07:14, 12284.63 examples/s]
Generating train split: 72093231 examples [1:07:14, 11881.91 examples/s]
Generating train split: 72095015 examples [1:07:14, 11457.53 examples/s]
Generating train split: 72097555 examples [1:07:15, 13466.61 examples/s]
Generating train split: 72100622 examples [1:07:15, 16487.61 examples/s]
Generating train split: 72103240 examples [1:07:15, 18231.48 examples/s]
Generating train split: 72105516 examples [1:07:15, 10045.21 examples/s]
Generating train split: 72107243 examples [1:07:15, 10887.32 examples/s]
Generating train split: 72108913 examples [1:07:16, 10623.38 examples/s]
Generating train split: 72110384 examples [1:07:16, 11187.50 examples/s]
Generating train split: 72115451 examples [1:07:16, 14045.60 examples/s]
Generating train split: 72117581 examples [1:07:16, 15277.70 examples/s]
Generating train split: 72119301 examples [1:07:16, 13635.70 examples/s]
Generating train split: 72120805 examples [1:07:16, 12089.89 examples/s]
Generating train split: 72124096 examples [1:07:17, 16188.97 examples/s]
Generating train split: 72125996 examples [1:07:17, 13563.89 examples/s]
Generating train split: 72128660 examples [1:07:17, 15907.13 examples/s]
Generating train split: 72131760 examples [1:07:17, 19229.38 examples/s]
Generating train split: 72133990 examples [1:07:17, 11132.57 examples/s]
Generating train split: 72136689 examples [1:07:18, 13417.43 examples/s]
Generating train split: 72139520 examples [1:07:18, 16118.88 examples/s]
Generating train split: 72142858 examples [1:07:18, 19637.11 examples/s]
Generating train split: 72145382 examples [1:07:18, 12272.04 examples/s]
Generating train split: 72147853 examples [1:07:18, 14259.37 examples/s]
Generating train split: 72149967 examples [1:07:18, 12449.84 examples/s]
Generating train split: 72152459 examples [1:07:19, 14632.81 examples/s]
Generating train split: 72154429 examples [1:07:19, 14687.71 examples/s]
Generating train split: 72157652 examples [1:07:19, 18401.10 examples/s]
Generating train split: 72159893 examples [1:07:19, 13837.00 examples/s]
Generating train split: 72162855 examples [1:07:19, 16862.33 examples/s]
Generating train split: 72168028 examples [1:07:19, 24331.43 examples/s]
Generating train split: 72171089 examples [1:07:19, 24371.37 examples/s]
Generating train split: 72176815 examples [1:07:19, 32250.61 examples/s]
Generating train split: 72180571 examples [1:07:20, 19425.27 examples/s]
Generating train split: 72183482 examples [1:07:21, 10305.35 examples/s]
Generating train split: 72185640 examples [1:07:21, 8036.16 examples/s] 
Generating train split: 72187952 examples [1:07:21, 9504.22 examples/s]
Generating train split: 72190405 examples [1:07:21, 9061.64 examples/s]
Generating train split: 72191942 examples [1:07:22, 9817.93 examples/s]
Generating train split: 72195215 examples [1:07:22, 13051.41 examples/s]
Generating train split: 72197186 examples [1:07:22, 12039.27 examples/s]
Generating train split: 72199102 examples [1:07:22, 13242.94 examples/s]
Generating train split: 72200956 examples [1:07:22, 14211.80 examples/s]
Generating train split: 72202725 examples [1:07:22, 14641.30 examples/s]
Generating train split: 72206899 examples [1:07:22, 15891.62 examples/s]
Generating train split: 72208709 examples [1:07:23, 15337.86 examples/s]
Generating train split: 72210328 examples [1:07:23, 13949.06 examples/s]
Generating train split: 72211782 examples [1:07:23, 12645.11 examples/s]
Generating train split: 72215135 examples [1:07:23, 17161.22 examples/s]
Generating train split: 72217062 examples [1:07:23, 15198.29 examples/s]
Generating train split: 72218747 examples [1:07:23, 13934.08 examples/s]
Generating train split: 72224889 examples [1:07:24, 19637.84 examples/s]
Generating train split: 72226818 examples [1:07:24, 17836.91 examples/s]
Generating train split: 72228574 examples [1:07:24, 17577.40 examples/s]
Generating train split: 72232492 examples [1:07:24, 22345.35 examples/s]
Generating train split: 72234839 examples [1:07:24, 13463.49 examples/s]
Generating train split: 72236667 examples [1:07:24, 13026.54 examples/s]
Generating train split: 72239156 examples [1:07:25, 15188.35 examples/s]
Generating train split: 72242725 examples [1:07:25, 19427.31 examples/s]
Generating train split: 72245402 examples [1:07:25, 20318.62 examples/s]
Generating train split: 72247768 examples [1:07:25, 15748.23 examples/s]
Generating train split: 72249717 examples [1:07:25, 14944.18 examples/s]
Generating train split: 72253937 examples [1:07:25, 20600.35 examples/s]
Generating train split: 72257155 examples [1:07:25, 23210.80 examples/s]
Generating train split: 72259859 examples [1:07:26, 19711.18 examples/s]
Generating train split: 72262174 examples [1:07:26, 16016.17 examples/s]
Generating train split: 72264461 examples [1:07:26, 17348.85 examples/s]
Generating train split: 72268557 examples [1:07:26, 22326.12 examples/s]
Generating train split: 72271518 examples [1:07:26, 23711.90 examples/s]
Generating train split: 72274170 examples [1:07:26, 15336.42 examples/s]
Generating train split: 72276277 examples [1:07:26, 16299.57 examples/s]
Generating train split: 72279656 examples [1:07:27, 19892.72 examples/s]
Generating train split: 72282120 examples [1:07:27, 19921.47 examples/s]
Generating train split: 72284448 examples [1:07:27, 17083.05 examples/s]
Generating train split: 72286448 examples [1:07:27, 15247.16 examples/s]
Generating train split: 72288448 examples [1:07:27, 16211.07 examples/s]
Generating train split: 72290259 examples [1:07:27, 14379.61 examples/s]
Generating train split: 72292006 examples [1:07:27, 15063.39 examples/s]
Generating train split: 72294218 examples [1:07:28, 16088.74 examples/s]
Generating train split: 72295934 examples [1:07:28, 16019.83 examples/s]
Generating train split: 72298270 examples [1:07:28, 17828.04 examples/s]
Generating train split: 72300137 examples [1:07:28, 12707.00 examples/s]
Generating train split: 72301671 examples [1:07:28, 10248.64 examples/s]
Generating train split: 72308084 examples [1:07:28, 20480.59 examples/s]
Generating train split: 72315984 examples [1:07:28, 32963.60 examples/s]
Generating train split: 72320317 examples [1:07:29, 29103.35 examples/s]
Generating train split: 72324026 examples [1:07:29, 13216.14 examples/s]
Generating train split: 72326780 examples [1:07:30, 12344.52 examples/s]
Generating train split: 72329008 examples [1:07:30, 12048.21 examples/s]
Generating train split: 72337678 examples [1:07:30, 22014.18 examples/s]
Generating train split: 72344620 examples [1:07:30, 29250.06 examples/s]
Generating train split: 72349306 examples [1:07:31, 14641.67 examples/s]
Generating train split: 72352766 examples [1:07:31, 11272.44 examples/s]
Generating train split: 72355378 examples [1:07:32, 11193.46 examples/s]
Generating train split: 72357532 examples [1:07:32, 11600.88 examples/s]
Generating train split: 72359467 examples [1:07:32, 12499.71 examples/s]
Generating train split: 72361372 examples [1:07:32, 12301.34 examples/s]
Generating train split: 72363055 examples [1:07:32, 11970.07 examples/s]
Generating train split: 72371247 examples [1:07:32, 24303.49 examples/s]
Generating train split: 72379188 examples [1:07:32, 35388.16 examples/s]
Generating train split: 72384037 examples [1:07:33, 34675.64 examples/s]
Generating train split: 72388420 examples [1:07:33, 23009.40 examples/s]
Generating train split: 72391844 examples [1:07:33, 19582.52 examples/s]
Generating train split: 72398848 examples [1:07:33, 27557.49 examples/s]
Generating train split: 72406952 examples [1:07:33, 37192.05 examples/s]
Generating train split: 72412151 examples [1:07:34, 23419.47 examples/s]
Generating train split: 72419661 examples [1:07:34, 31010.88 examples/s]
Generating train split: 72425420 examples [1:07:34, 35059.29 examples/s]
Generating train split: 72430540 examples [1:07:35, 21287.40 examples/s]
Generating train split: 72434428 examples [1:07:35, 16747.14 examples/s]
Generating train split: 72437436 examples [1:07:35, 13657.09 examples/s]
Generating train split: 72440596 examples [1:07:35, 15683.53 examples/s]
Generating train split: 72443191 examples [1:07:36, 16859.39 examples/s]
Generating train split: 72445707 examples [1:07:36, 16719.04 examples/s]
Generating train split: 72447956 examples [1:07:36, 17284.94 examples/s]
Generating train split: 72450119 examples [1:07:36, 16378.58 examples/s]
Generating train split: 72452051 examples [1:07:36, 16154.42 examples/s]
Generating train split: 72453872 examples [1:07:36, 16488.79 examples/s]
Generating train split: 72461617 examples [1:07:36, 30798.73 examples/s]
Generating train split: 72468977 examples [1:07:36, 41093.58 examples/s]
Generating train split: 72473603 examples [1:07:37, 24607.22 examples/s]
Generating train split: 72477207 examples [1:07:37, 23909.98 examples/s]
Generating train split: 72480953 examples [1:07:37, 26429.94 examples/s]
Generating train split: 72485160 examples [1:07:37, 28661.64 examples/s]
Generating train split: 72488594 examples [1:07:37, 22187.21 examples/s]
Generating train split: 72491403 examples [1:07:38, 21599.72 examples/s]
Generating train split: 72494029 examples [1:07:38, 22472.83 examples/s]
Generating train split: 72496597 examples [1:07:38, 12342.05 examples/s]
Generating train split: 72498558 examples [1:07:38, 12860.40 examples/s]
Generating train split: 72500389 examples [1:07:39, 11203.32 examples/s]
Generating train split: 72502377 examples [1:07:39, 12607.86 examples/s]
Generating train split: 72504627 examples [1:07:39, 14462.85 examples/s]
Generating train split: 72506467 examples [1:07:39, 13468.76 examples/s]
Generating train split: 72509017 examples [1:07:39, 15978.67 examples/s]
Generating train split: 72510920 examples [1:07:39, 13531.18 examples/s]
Generating train split: 72513730 examples [1:07:39, 16563.79 examples/s]
Generating train split: 72515696 examples [1:07:40, 10718.65 examples/s]
Generating train split: 72518114 examples [1:07:40, 13004.27 examples/s]
Generating train split: 72520805 examples [1:07:40, 15263.04 examples/s]
Generating train split: 72522782 examples [1:07:40, 10651.67 examples/s]
Generating train split: 72525101 examples [1:07:40, 12738.58 examples/s]
Generating train split: 72526885 examples [1:07:40, 13220.76 examples/s]
Generating train split: 72530076 examples [1:07:41, 17019.75 examples/s]
Generating train split: 72532204 examples [1:07:41, 11805.29 examples/s]
Generating train split: 72535032 examples [1:07:41, 14715.20 examples/s]
Generating train split: 72539323 examples [1:07:41, 20396.72 examples/s]
Generating train split: 72545140 examples [1:07:41, 28599.28 examples/s]
Generating train split: 72548720 examples [1:07:41, 27081.44 examples/s]
Generating train split: 72551937 examples [1:07:41, 23915.25 examples/s]
Generating train split: 72555094 examples [1:07:42, 25593.29 examples/s]
Generating train split: 72560562 examples [1:07:42, 32558.02 examples/s]
Generating train split: 72564231 examples [1:07:42, 25747.90 examples/s]
Generating train split: 72567306 examples [1:07:42, 21433.93 examples/s]
Generating train split: 72569883 examples [1:07:42, 21944.42 examples/s]
Generating train split: 72572411 examples [1:07:42, 21902.73 examples/s]
Generating train split: 72574833 examples [1:07:43, 16789.88 examples/s]
Generating train split: 72576828 examples [1:07:43, 14362.68 examples/s]
Generating train split: 72580369 examples [1:07:43, 18349.22 examples/s]
Generating train split: 72582619 examples [1:07:43, 19228.85 examples/s]
Generating train split: 72587034 examples [1:07:43, 25037.70 examples/s]
Generating train split: 72594485 examples [1:07:43, 37398.07 examples/s]
Generating train split: 72601182 examples [1:07:43, 43800.30 examples/s]
Generating train split: 72605964 examples [1:07:44, 27482.39 examples/s]
Generating train split: 72609736 examples [1:07:44, 22292.62 examples/s]
Generating train split: 72612805 examples [1:07:44, 14431.19 examples/s]
Generating train split: 72615433 examples [1:07:45, 15931.95 examples/s]
Generating train split: 72617852 examples [1:07:45, 16757.15 examples/s]
Generating train split: 72620158 examples [1:07:45, 17228.87 examples/s]
Generating train split: 72624197 examples [1:07:45, 21765.45 examples/s]
Generating train split: 72626947 examples [1:07:45, 15189.78 examples/s]
Generating train split: 72629111 examples [1:07:45, 12557.64 examples/s]
Generating train split: 72630862 examples [1:07:46, 9692.90 examples/s] 
Generating train split: 72632273 examples [1:07:46, 9539.71 examples/s]
Generating train split: 72633509 examples [1:07:46, 9597.70 examples/s]
Generating train split: 72634681 examples [1:07:46, 9045.77 examples/s]
Generating train split: 72635998 examples [1:07:47, 6619.48 examples/s]
Generating train split: 72637514 examples [1:07:47, 6982.67 examples/s]
Generating train split: 72638342 examples [1:07:47, 6724.11 examples/s]
Generating train split: 72639121 examples [1:07:47, 6896.42 examples/s]
Generating train split: 72640575 examples [1:07:47, 8386.43 examples/s]
Generating train split: 72642598 examples [1:07:47, 11021.97 examples/s]
Generating train split: 72645844 examples [1:07:47, 16169.77 examples/s]
Generating train split: 72649090 examples [1:07:47, 20335.02 examples/s]
Generating train split: 72651379 examples [1:07:48, 11781.83 examples/s]
Generating train split: 72653149 examples [1:07:48, 12490.30 examples/s]
Generating train split: 72655647 examples [1:07:48, 14945.00 examples/s]
Generating train split: 72659957 examples [1:07:48, 21122.77 examples/s]
Generating train split: 72662618 examples [1:07:48, 21350.47 examples/s]
Generating train split: 72665132 examples [1:07:49, 14664.30 examples/s]
Generating train split: 72667338 examples [1:07:49, 16049.22 examples/s]
Generating train split: 72669662 examples [1:07:49, 13750.24 examples/s]
Generating train split: 72672214 examples [1:07:49, 15997.05 examples/s]
Generating train split: 72674205 examples [1:07:49, 15022.12 examples/s]
Generating train split: 72675983 examples [1:07:49, 14313.55 examples/s]
Generating train split: 72677609 examples [1:07:49, 14493.62 examples/s]
Generating train split: 72679388 examples [1:07:50, 15267.02 examples/s]
Generating train split: 72682768 examples [1:07:50, 19908.82 examples/s]
Generating train split: 72684937 examples [1:07:50, 15236.22 examples/s]
Generating train split: 72686734 examples [1:07:50, 13397.93 examples/s]
Generating train split: 72689128 examples [1:07:50, 15612.96 examples/s]
Generating train split: 72690941 examples [1:07:50, 16134.08 examples/s]
Generating train split: 72692748 examples [1:07:50, 16548.34 examples/s]
Generating train split: 72694553 examples [1:07:50, 15267.52 examples/s]
Generating train split: 72696432 examples [1:07:51, 16135.33 examples/s]
Generating train split: 72698147 examples [1:07:51, 16043.84 examples/s]
Generating train split: 72700683 examples [1:07:51, 18550.67 examples/s]
Generating train split: 72702619 examples [1:07:51, 17799.62 examples/s]
Generating train split: 72704456 examples [1:07:51, 10416.68 examples/s]
Generating train split: 72707146 examples [1:07:51, 13446.51 examples/s]
Generating train split: 72708955 examples [1:07:52, 12984.15 examples/s]
Generating train split: 72710853 examples [1:07:52, 13966.97 examples/s]
Generating train split: 72712515 examples [1:07:52, 14370.60 examples/s]
Generating train split: 72714149 examples [1:07:52, 14072.63 examples/s]
Generating train split: 72715690 examples [1:07:52, 10620.43 examples/s]
Generating train split: 72716960 examples [1:07:52, 10272.47 examples/s]
Generating train split: 72718972 examples [1:07:52, 12391.99 examples/s]
Generating train split: 72720392 examples [1:07:52, 12516.05 examples/s]
Generating train split: 72721780 examples [1:07:53, 11766.83 examples/s]
Generating train split: 72726544 examples [1:07:53, 20529.05 examples/s]
Generating train split: 72729227 examples [1:07:53, 22125.47 examples/s]
Generating train split: 72732563 examples [1:07:53, 25143.47 examples/s]
Generating train split: 72735394 examples [1:07:53, 25647.84 examples/s]
Generating train split: 72739407 examples [1:07:53, 29717.21 examples/s]
Generating train split: 72742798 examples [1:07:53, 28785.35 examples/s]
Generating train split: 72746273 examples [1:07:53, 30422.17 examples/s]
Generating train split: 72750591 examples [1:07:53, 34020.12 examples/s]
Generating train split: 72757867 examples [1:07:54, 45162.88 examples/s]
Generating train split: 72762499 examples [1:07:54, 15406.19 examples/s]
Generating train split: 72765915 examples [1:07:54, 16344.69 examples/s]
Generating train split: 72769168 examples [1:07:55, 18389.80 examples/s]
Generating train split: 72772370 examples [1:07:55, 15381.76 examples/s]
Generating train split: 72774796 examples [1:07:55, 16044.21 examples/s]
Generating train split: 72777055 examples [1:07:55, 13629.86 examples/s]
Generating train split: 72778910 examples [1:07:55, 14298.89 examples/s]
Generating train split: 72780733 examples [1:07:56, 10622.49 examples/s]
Generating train split: 72783759 examples [1:07:56, 13729.22 examples/s]
Generating train split: 72786271 examples [1:07:56, 15828.41 examples/s]
Generating train split: 72788375 examples [1:07:56, 14444.47 examples/s]
Generating train split: 72790206 examples [1:07:56, 12087.80 examples/s]
Generating train split: 72791723 examples [1:07:56, 12632.07 examples/s]
Generating train split: 72793238 examples [1:07:57, 11879.78 examples/s]
Generating train split: 72795376 examples [1:07:57, 13791.08 examples/s]
Generating train split: 72796995 examples [1:07:57, 14327.70 examples/s]
Generating train split: 72800074 examples [1:07:57, 18414.30 examples/s]
Generating train split: 72802102 examples [1:07:57, 15724.49 examples/s]
Generating train split: 72803872 examples [1:07:57, 11203.33 examples/s]
Generating train split: 72805399 examples [1:07:57, 11974.54 examples/s]
Generating train split: 72808092 examples [1:07:58, 15162.11 examples/s]
Generating train split: 72809918 examples [1:07:58, 15066.61 examples/s]
Generating train split: 72811648 examples [1:07:58, 15234.25 examples/s]
Generating train split: 72813324 examples [1:07:58, 11377.24 examples/s]
Generating train split: 72814709 examples [1:07:58, 10356.30 examples/s]
Generating train split: 72817394 examples [1:07:58, 13053.23 examples/s]
Generating train split: 72818880 examples [1:07:58, 11319.64 examples/s]
Generating train split: 72820213 examples [1:07:59, 11715.86 examples/s]
Generating train split: 72823240 examples [1:07:59, 15936.42 examples/s]
Generating train split: 72825340 examples [1:07:59, 17158.87 examples/s]
Generating train split: 72827910 examples [1:07:59, 19304.15 examples/s]
Generating train split: 72830011 examples [1:07:59, 19094.00 examples/s]
Generating train split: 72832030 examples [1:07:59, 13404.63 examples/s]
Generating train split: 72833672 examples [1:07:59, 13436.09 examples/s]
Generating train split: 72836206 examples [1:07:59, 15606.73 examples/s]
Generating train split: 72837965 examples [1:08:00, 12240.85 examples/s]
Generating train split: 72839420 examples [1:08:00, 12148.47 examples/s]
Generating train split: 72842683 examples [1:08:00, 16613.87 examples/s]
Generating train split: 72847297 examples [1:08:00, 23625.63 examples/s]
Generating train split: 72850040 examples [1:08:00, 18384.87 examples/s]
Generating train split: 72852577 examples [1:08:00, 19870.05 examples/s]
Generating train split: 72854937 examples [1:08:00, 20251.20 examples/s]
Generating train split: 72858694 examples [1:08:01, 24502.72 examples/s]
Generating train split: 72861667 examples [1:08:01, 25849.76 examples/s]
Generating train split: 72864475 examples [1:08:01, 17992.01 examples/s]
Generating train split: 72867336 examples [1:08:01, 20198.88 examples/s]
Generating train split: 72869782 examples [1:08:01, 20308.01 examples/s]
Generating train split: 72872126 examples [1:08:01, 20898.69 examples/s]
Generating train split: 72882330 examples [1:08:01, 41429.03 examples/s]
Generating train split: 72891287 examples [1:08:01, 54196.27 examples/s]
Generating train split: 72897253 examples [1:08:02, 33995.39 examples/s]
Generating train split: 72901968 examples [1:08:02, 25990.85 examples/s]
Generating train split: 72905723 examples [1:08:02, 23507.74 examples/s]
Generating train split: 72911134 examples [1:08:02, 28559.51 examples/s]
Generating train split: 72916788 examples [1:08:03, 33707.98 examples/s]
Generating train split: 72921123 examples [1:08:03, 22369.97 examples/s]
Generating train split: 72924504 examples [1:08:03, 23668.71 examples/s]
Generating train split: 72927764 examples [1:08:03, 22470.28 examples/s]
Generating train split: 72930631 examples [1:08:03, 18435.46 examples/s]
Generating train split: 72932976 examples [1:08:04, 12300.38 examples/s]
Generating train split: 72935646 examples [1:08:04, 14260.34 examples/s]
Generating train split: 72938331 examples [1:08:04, 16309.63 examples/s]
Generating train split: 72941795 examples [1:08:04, 19684.60 examples/s]
Generating train split: 72944435 examples [1:08:04, 17139.93 examples/s]
Generating train split: 72946633 examples [1:08:05, 12047.80 examples/s]
Generating train split: 72948880 examples [1:08:05, 13691.03 examples/s]
Generating train split: 72950761 examples [1:08:05, 11224.71 examples/s]
Generating train split: 72952784 examples [1:08:05, 12686.85 examples/s]
Generating train split: 72954449 examples [1:08:06, 9749.67 examples/s] 
Generating train split: 72955781 examples [1:08:06, 8200.45 examples/s]
Generating train split: 72957413 examples [1:08:06, 9486.16 examples/s]
Generating train split: 72958668 examples [1:08:06, 9889.56 examples/s]
Generating train split: 72960476 examples [1:08:06, 11567.74 examples/s]
Generating train split: 72961876 examples [1:08:06, 11021.34 examples/s]
Generating train split: 72963152 examples [1:08:06, 10462.81 examples/s]
Generating train split: 72964763 examples [1:08:06, 11732.71 examples/s]
Generating train split: 72966070 examples [1:08:07, 11853.49 examples/s]
Generating train split: 72967342 examples [1:08:07, 7169.36 examples/s] 
Generating train split: 72969500 examples [1:08:07, 9750.29 examples/s]
Generating train split: 72972148 examples [1:08:07, 13155.32 examples/s]
Generating train split: 72974305 examples [1:08:07, 15037.08 examples/s]
Generating train split: 72977946 examples [1:08:07, 20236.02 examples/s]
Generating train split: 72980345 examples [1:08:08, 9938.10 examples/s] 
Generating train split: 72982161 examples [1:08:08, 10582.61 examples/s]
Generating train split: 72984795 examples [1:08:08, 13203.37 examples/s]
Generating train split: 72988366 examples [1:08:08, 12755.07 examples/s]
Generating train split: 72990098 examples [1:08:09, 12324.53 examples/s]
Generating train split: 72991643 examples [1:08:09, 11948.85 examples/s]
Generating train split: 72993053 examples [1:08:09, 11701.30 examples/s]
Generating train split: 72997352 examples [1:08:09, 18120.58 examples/s]
Generating train split: 72999568 examples [1:08:09, 16533.52 examples/s]
Generating train split: 73001511 examples [1:08:09, 13664.90 examples/s]
Generating train split: 73003139 examples [1:08:09, 13612.02 examples/s]
Generating train split: 73005007 examples [1:08:10, 14691.43 examples/s]
Generating train split: 73006652 examples [1:08:10, 15102.76 examples/s]
Generating train split: 73013435 examples [1:08:10, 28345.30 examples/s]
Generating train split: 73016643 examples [1:08:10, 18689.32 examples/s]
Generating train split: 73019177 examples [1:08:10, 16061.48 examples/s]
Generating train split: 73022510 examples [1:08:11, 15230.53 examples/s]
Generating train split: 73024398 examples [1:08:11, 15180.48 examples/s]
Generating train split: 73026978 examples [1:08:11, 17040.45 examples/s]
Generating train split: 73028993 examples [1:08:11, 17366.41 examples/s]
Generating train split: 73030942 examples [1:08:11, 13565.21 examples/s]
Generating train split: 73035499 examples [1:08:11, 15847.07 examples/s]
Generating train split: 73037230 examples [1:08:12, 14207.96 examples/s]
Generating train split: 73038955 examples [1:08:12, 14192.77 examples/s]
Generating train split: 73040437 examples [1:08:12, 12012.78 examples/s]
Generating train split: 73042256 examples [1:08:12, 13155.33 examples/s]
Generating train split: 73043675 examples [1:08:12, 12750.28 examples/s]
Generating train split: 73045017 examples [1:08:12, 11403.30 examples/s]
Generating train split: 73048797 examples [1:08:12, 17335.65 examples/s]
Generating train split: 73057405 examples [1:08:12, 33897.88 examples/s]
Generating train split: 73061321 examples [1:08:13, 19603.60 examples/s]
Generating train split: 73064723 examples [1:08:13, 21982.33 examples/s]
Generating train split: 73067849 examples [1:08:13, 23199.07 examples/s]
Generating train split: 73070869 examples [1:08:13, 16603.29 examples/s]
Generating train split: 73073256 examples [1:08:13, 17069.67 examples/s]
Generating train split: 73076787 examples [1:08:14, 20504.20 examples/s]
Generating train split: 73079420 examples [1:08:14, 15150.16 examples/s]
Generating train split: 73083158 examples [1:08:14, 19018.74 examples/s]
Generating train split: 73085754 examples [1:08:14, 19945.80 examples/s]
Generating train split: 73088274 examples [1:08:14, 15800.21 examples/s]
Generating train split: 73091308 examples [1:08:14, 18536.21 examples/s]
Generating train split: 73093655 examples [1:08:15, 17838.48 examples/s]
Generating train split: 73095805 examples [1:08:15, 18626.43 examples/s]
Generating train split: 73097937 examples [1:08:15, 18195.52 examples/s]
Generating train split: 73099948 examples [1:08:15, 13961.07 examples/s]
Generating train split: 73102159 examples [1:08:15, 15631.67 examples/s]
Generating train split: 73103984 examples [1:08:15, 16064.34 examples/s]
Generating train split: 73105789 examples [1:08:15, 16496.68 examples/s]
Generating train split: 73108668 examples [1:08:15, 19616.60 examples/s]
Generating train split: 73113567 examples [1:08:16, 26944.39 examples/s]
Generating train split: 73116421 examples [1:08:16, 23108.76 examples/s]
Generating train split: 73119953 examples [1:08:16, 25990.27 examples/s]
Generating train split: 73122742 examples [1:08:16, 19329.51 examples/s]
Generating train split: 73125040 examples [1:08:16, 14931.31 examples/s]
Generating train split: 73126918 examples [1:08:16, 14690.66 examples/s]
Generating train split: 73130499 examples [1:08:17, 18878.79 examples/s]
Generating train split: 73138352 examples [1:08:17, 32052.04 examples/s]
Generating train split: 73142317 examples [1:08:17, 28000.09 examples/s]
Generating train split: 73145724 examples [1:08:17, 19668.56 examples/s]
Generating train split: 73148422 examples [1:08:17, 18474.83 examples/s]
Generating train split: 73152365 examples [1:08:18, 18923.68 examples/s]
Generating train split: 73154906 examples [1:08:18, 20003.01 examples/s]
Generating train split: 73158205 examples [1:08:18, 22616.75 examples/s]
Generating train split: 73160829 examples [1:08:18, 13255.70 examples/s]
Generating train split: 73162837 examples [1:08:18, 13912.93 examples/s]
Generating train split: 73166663 examples [1:08:18, 18195.82 examples/s]
Generating train split: 73170417 examples [1:08:19, 22069.63 examples/s]
Generating train split: 73173294 examples [1:08:19, 12292.74 examples/s]
Generating train split: 73175478 examples [1:08:19, 12397.35 examples/s]
Generating train split: 73177651 examples [1:08:19, 13841.51 examples/s]
Generating train split: 73180877 examples [1:08:19, 17170.61 examples/s]
Generating train split: 73183233 examples [1:08:20, 14377.42 examples/s]
Generating train split: 73185172 examples [1:08:20, 14040.74 examples/s]
Generating train split: 73187001 examples [1:08:20, 14784.58 examples/s]
Generating train split: 73190659 examples [1:08:20, 19533.72 examples/s]
Generating train split: 73195052 examples [1:08:20, 20441.93 examples/s]
Generating train split: 73197347 examples [1:08:20, 15831.29 examples/s]
Generating train split: 73199223 examples [1:08:21, 14446.22 examples/s]
Generating train split: 73201514 examples [1:08:21, 16058.88 examples/s]
Generating train split: 73203676 examples [1:08:21, 17253.05 examples/s]
Generating train split: 73205620 examples [1:08:21, 15318.19 examples/s]
Generating train split: 73207320 examples [1:08:21, 13961.75 examples/s]
Generating train split: 73208844 examples [1:08:21, 13946.68 examples/s]
Generating train split: 73210328 examples [1:08:21, 14011.64 examples/s]
Generating train split: 73211800 examples [1:08:22, 10307.49 examples/s]
Generating train split: 73218511 examples [1:08:22, 22030.73 examples/s]
Generating train split: 73225774 examples [1:08:22, 33152.28 examples/s]
Generating train split: 73229848 examples [1:08:22, 17301.49 examples/s]
Generating train split: 73232928 examples [1:08:23, 14048.47 examples/s]
Generating train split: 73235366 examples [1:08:23, 12333.84 examples/s]
Generating train split: 73237319 examples [1:08:23, 8750.15 examples/s] 
Generating train split: 73239214 examples [1:08:24, 9758.02 examples/s]
Generating train split: 73240764 examples [1:08:24, 9154.02 examples/s]
Generating train split: 73242988 examples [1:08:24, 10600.23 examples/s]
Generating train split: 73244423 examples [1:08:24, 9006.26 examples/s] 
Generating train split: 73245614 examples [1:08:25, 7064.64 examples/s]
Generating train split: 73247686 examples [1:08:25, 9037.07 examples/s]
Generating train split: 73248974 examples [1:08:25, 9546.50 examples/s]
Generating train split: 73251110 examples [1:08:25, 9527.10 examples/s]
Generating train split: 73252272 examples [1:08:25, 8758.76 examples/s]
Generating train split: 73253738 examples [1:08:25, 9850.28 examples/s]
Generating train split: 73255727 examples [1:08:25, 11958.88 examples/s]
Generating train split: 73257125 examples [1:08:25, 11657.64 examples/s]
Generating train split: 73258840 examples [1:08:26, 12943.03 examples/s]
Generating train split: 73260269 examples [1:08:26, 12053.69 examples/s]
Generating train split: 73265030 examples [1:08:26, 20818.50 examples/s]
Generating train split: 73267371 examples [1:08:26, 16145.41 examples/s]
Generating train split: 73269327 examples [1:08:26, 16591.66 examples/s]
Generating train split: 73271258 examples [1:08:26, 17177.38 examples/s]
Generating train split: 73273178 examples [1:08:26, 14179.06 examples/s]
Generating train split: 73274803 examples [1:08:27, 14009.23 examples/s]
Generating train split: 73276351 examples [1:08:27, 14306.01 examples/s]
Generating train split: 73278731 examples [1:08:27, 16667.97 examples/s]
Generating train split: 73284570 examples [1:08:27, 20428.74 examples/s]
Generating train split: 73286582 examples [1:08:27, 17622.58 examples/s]
Generating train split: 73288594 examples [1:08:27, 18144.91 examples/s]
Generating train split: 73290438 examples [1:08:27, 16564.89 examples/s]
Generating train split: 73292649 examples [1:08:27, 17806.74 examples/s]
Generating train split: 73294482 examples [1:08:28, 13763.26 examples/s]
Generating train split: 73298715 examples [1:08:28, 19757.82 examples/s]
Generating train split: 73302007 examples [1:08:28, 22807.31 examples/s]
Generating train split: 73305562 examples [1:08:28, 25296.59 examples/s]
Generating train split: 73308342 examples [1:08:28, 17241.35 examples/s]
Generating train split: 73310578 examples [1:08:29, 13955.26 examples/s]
Generating train split: 73313595 examples [1:08:29, 16817.43 examples/s]
Generating train split: 73315780 examples [1:08:29, 13567.04 examples/s]
Generating train split: 73317562 examples [1:08:29, 13367.34 examples/s]
Generating train split: 73319196 examples [1:08:29, 12818.52 examples/s]
Generating train split: 73320678 examples [1:08:29, 12588.76 examples/s]
Generating train split: 73322744 examples [1:08:29, 14328.96 examples/s]
Generating train split: 73326264 examples [1:08:30, 19225.05 examples/s]
Generating train split: 73329039 examples [1:08:30, 18346.47 examples/s]
Generating train split: 73331063 examples [1:08:30, 14101.83 examples/s]
Generating train split: 73332733 examples [1:08:30, 13230.25 examples/s]
Generating train split: 73335260 examples [1:08:30, 15710.31 examples/s]
Generating train split: 73337070 examples [1:08:30, 15938.87 examples/s]
Generating train split: 73338844 examples [1:08:30, 13522.96 examples/s]
Generating train split: 73341893 examples [1:08:31, 17261.56 examples/s]
Generating train split: 73343863 examples [1:08:31, 16962.02 examples/s]
Generating train split: 73346072 examples [1:08:31, 18215.76 examples/s]
Generating train split: 73348039 examples [1:08:31, 13160.30 examples/s]
Generating train split: 73349649 examples [1:08:31, 13313.75 examples/s]
Generating train split: 73352484 examples [1:08:31, 16669.18 examples/s]
Generating train split: 73355505 examples [1:08:31, 19935.30 examples/s]
Generating train split: 73357762 examples [1:08:32, 14867.40 examples/s]
Generating train split: 73363422 examples [1:08:32, 23596.91 examples/s]
Generating train split: 73370414 examples [1:08:32, 32492.67 examples/s]
Generating train split: 73374208 examples [1:08:32, 27834.63 examples/s]
Generating train split: 73377462 examples [1:08:32, 18854.21 examples/s]
Generating train split: 73380031 examples [1:08:33, 14610.17 examples/s]
Generating train split: 73382068 examples [1:08:33, 14533.71 examples/s]
Generating train split: 73385336 examples [1:08:33, 17574.91 examples/s]
Generating train split: 73389746 examples [1:08:33, 19059.76 examples/s]
Generating train split: 73392007 examples [1:08:33, 18865.26 examples/s]
Generating train split: 73394135 examples [1:08:33, 18116.73 examples/s]
Generating train split: 73396110 examples [1:08:34, 16769.92 examples/s]
Generating train split: 73397893 examples [1:08:34, 15054.72 examples/s]
Generating train split: 73400598 examples [1:08:34, 17636.57 examples/s]
Generating train split: 73402526 examples [1:08:34, 16481.89 examples/s]
Generating train split: 73404282 examples [1:08:34, 14413.12 examples/s]
Generating train split: 73405827 examples [1:08:34, 12837.54 examples/s]
Generating train split: 73407656 examples [1:08:34, 14025.29 examples/s]
Generating train split: 73409164 examples [1:08:34, 14253.73 examples/s]
Generating train split: 73410829 examples [1:08:35, 14382.65 examples/s]
Generating train split: 73412327 examples [1:08:35, 14252.08 examples/s]
Generating train split: 73413802 examples [1:08:35, 13575.22 examples/s]
Generating train split: 73415728 examples [1:08:35, 14923.26 examples/s]
Generating train split: 73417266 examples [1:08:35, 11193.34 examples/s]
Generating train split: 73420155 examples [1:08:35, 15162.77 examples/s]
Generating train split: 73425273 examples [1:08:35, 23901.89 examples/s]
Generating train split: 73429912 examples [1:08:35, 29496.72 examples/s]
Generating train split: 73433207 examples [1:08:36, 26412.05 examples/s]
Generating train split: 73436151 examples [1:08:36, 26721.77 examples/s]
Generating train split: 73440993 examples [1:08:36, 32343.06 examples/s]
Generating train split: 73444466 examples [1:08:36, 32155.79 examples/s]
Generating train split: 73448587 examples [1:08:36, 34432.33 examples/s]
Generating train split: 73452177 examples [1:08:36, 29494.11 examples/s]
Generating train split: 73455346 examples [1:08:36, 21964.20 examples/s]
Generating train split: 73457950 examples [1:08:37, 20638.35 examples/s]
Generating train split: 73461284 examples [1:08:37, 23328.33 examples/s]
Generating train split: 73463989 examples [1:08:37, 23897.86 examples/s]
Generating train split: 73466605 examples [1:08:37, 18538.18 examples/s]
Generating train split: 73468791 examples [1:08:37, 17997.71 examples/s]
Generating train split: 73473277 examples [1:08:37, 23902.46 examples/s]
Generating train split: 73476037 examples [1:08:38, 16089.17 examples/s]
Generating train split: 73478223 examples [1:08:38, 16639.40 examples/s]
Generating train split: 73481675 examples [1:08:38, 20189.87 examples/s]
Generating train split: 73484172 examples [1:08:38, 20304.28 examples/s]
Generating train split: 73486540 examples [1:08:38, 17144.58 examples/s]
Generating train split: 73488553 examples [1:08:38, 15825.43 examples/s]
Generating train split: 73490345 examples [1:08:38, 14077.53 examples/s]
Generating train split: 73493165 examples [1:08:39, 16934.13 examples/s]
Generating train split: 73495099 examples [1:08:39, 12332.52 examples/s]
Generating train split: 73497711 examples [1:08:39, 14911.49 examples/s]
Generating train split: 73500480 examples [1:08:39, 17606.83 examples/s]
Generating train split: 73502620 examples [1:08:39, 15433.83 examples/s]
Generating train split: 73504467 examples [1:08:40, 11851.92 examples/s]
Generating train split: 73507956 examples [1:08:40, 16115.27 examples/s]
Generating train split: 73510780 examples [1:08:40, 18648.01 examples/s]
Generating train split: 73513092 examples [1:08:40, 18495.01 examples/s]
Generating train split: 73515256 examples [1:08:40, 16065.07 examples/s]
Generating train split: 73518057 examples [1:08:40, 18685.88 examples/s]
Generating train split: 73523093 examples [1:08:40, 26249.27 examples/s]
Generating train split: 73526109 examples [1:08:40, 19265.21 examples/s]
Generating train split: 73528563 examples [1:08:41, 19642.82 examples/s]
Generating train split: 73532507 examples [1:08:41, 23938.54 examples/s]
Generating train split: 73536453 examples [1:08:41, 27626.96 examples/s]
Generating train split: 73539614 examples [1:08:41, 27745.78 examples/s]
Generating train split: 73542674 examples [1:08:41, 20915.99 examples/s]
Generating train split: 73545192 examples [1:08:41, 20349.43 examples/s]
Generating train split: 73548808 examples [1:08:41, 23845.89 examples/s]
Generating train split: 73552700 examples [1:08:41, 27468.74 examples/s]
Generating train split: 73556565 examples [1:08:42, 20692.48 examples/s]
Generating train split: 73559128 examples [1:08:42, 16859.38 examples/s]
Generating train split: 73561248 examples [1:08:42, 15351.20 examples/s]
Generating train split: 73564021 examples [1:08:42, 17592.70 examples/s]
Generating train split: 73566229 examples [1:08:42, 18481.03 examples/s]
Generating train split: 73568363 examples [1:08:43, 17122.45 examples/s]
Generating train split: 73570278 examples [1:08:43, 17572.48 examples/s]
Generating train split: 73572194 examples [1:08:43, 15263.04 examples/s]
Generating train split: 73575292 examples [1:08:43, 18470.74 examples/s]
Generating train split: 73578379 examples [1:08:43, 21468.89 examples/s]
Generating train split: 73580739 examples [1:08:43, 12752.44 examples/s]
Generating train split: 73583056 examples [1:08:44, 14561.56 examples/s]
Generating train split: 73585649 examples [1:08:44, 16705.57 examples/s]
Generating train split: 73587789 examples [1:08:44, 11611.77 examples/s]
Generating train split: 73590919 examples [1:08:44, 14945.31 examples/s]
Generating train split: 73593023 examples [1:08:44, 14574.94 examples/s]
Generating train split: 73594901 examples [1:08:44, 13232.78 examples/s]
Generating train split: 73596553 examples [1:08:45, 13565.20 examples/s]
Generating train split: 73598154 examples [1:08:45, 8806.61 examples/s] 
Generating train split: 73599395 examples [1:08:45, 8641.85 examples/s]
Generating train split: 73600503 examples [1:08:45, 7338.43 examples/s]
Generating train split: 73602993 examples [1:08:45, 10278.21 examples/s]
Generating train split: 73606523 examples [1:08:45, 15029.08 examples/s]
Generating train split: 73608525 examples [1:08:46, 15627.19 examples/s]
Generating train split: 73611151 examples [1:08:46, 18002.11 examples/s]
Generating train split: 73613270 examples [1:08:46, 12208.18 examples/s]
Generating train split: 73616874 examples [1:08:46, 16539.04 examples/s]
Generating train split: 73619135 examples [1:08:46, 17706.69 examples/s]
Generating train split: 73621360 examples [1:08:46, 15740.66 examples/s]
Generating train split: 73623278 examples [1:08:47, 15003.30 examples/s]
Generating train split: 73625017 examples [1:08:47, 14423.36 examples/s]
Generating train split: 73627371 examples [1:08:47, 16215.69 examples/s]
Generating train split: 73629162 examples [1:08:47, 14790.01 examples/s]
Generating train split: 73630771 examples [1:08:47, 11368.90 examples/s]
Generating train split: 73632880 examples [1:08:47, 13288.42 examples/s]
Generating train split: 73635086 examples [1:08:47, 15114.03 examples/s]
Generating train split: 73637162 examples [1:08:47, 16449.02 examples/s]
Generating train split: 73638998 examples [1:08:48, 12071.56 examples/s]
Generating train split: 73641000 examples [1:08:48, 13682.90 examples/s]
Generating train split: 73643174 examples [1:08:48, 15495.14 examples/s]
Generating train split: 73647848 examples [1:08:48, 23136.49 examples/s]
Generating train split: 73652935 examples [1:08:48, 29664.02 examples/s]
Generating train split: 73656208 examples [1:08:48, 23363.29 examples/s]
Generating train split: 73659263 examples [1:08:48, 24847.57 examples/s]
Generating train split: 73663143 examples [1:08:49, 28065.89 examples/s]
Generating train split: 73666914 examples [1:08:49, 30534.77 examples/s]
Generating train split: 73671182 examples [1:08:49, 33776.09 examples/s]
Generating train split: 73674785 examples [1:08:49, 18901.12 examples/s]
Generating train split: 73678888 examples [1:08:49, 18843.53 examples/s]
Generating train split: 73681617 examples [1:08:49, 20019.49 examples/s]
Generating train split: 73684768 examples [1:08:50, 21816.46 examples/s]
Generating train split: 73687387 examples [1:08:50, 14433.28 examples/s]
Generating train split: 73689547 examples [1:08:50, 15601.67 examples/s]
Generating train split: 73694491 examples [1:08:50, 18568.90 examples/s]
Generating train split: 73696703 examples [1:08:50, 17751.85 examples/s]
Generating train split: 73698705 examples [1:08:51, 16425.21 examples/s]
Generating train split: 73700496 examples [1:08:51, 13412.56 examples/s]
Generating train split: 73701996 examples [1:08:51, 12233.85 examples/s]
Generating train split: 73703926 examples [1:08:51, 13598.01 examples/s]
Generating train split: 73705631 examples [1:08:51, 14204.85 examples/s]
Generating train split: 73707175 examples [1:08:51, 12065.52 examples/s]
Generating train split: 73708681 examples [1:08:51, 12652.64 examples/s]
Generating train split: 73710061 examples [1:08:52, 12778.17 examples/s]
Generating train split: 73711422 examples [1:08:52, 9782.12 examples/s] 
Generating train split: 73712549 examples [1:08:52, 9751.46 examples/s]
Generating train split: 73714476 examples [1:08:52, 11897.07 examples/s]
Generating train split: 73716052 examples [1:08:52, 12838.19 examples/s]
Generating train split: 73717757 examples [1:08:52, 13730.79 examples/s]
Generating train split: 73719237 examples [1:08:52, 10693.76 examples/s]
Generating train split: 73720478 examples [1:08:53, 10646.23 examples/s]
Generating train split: 73722773 examples [1:08:53, 13500.97 examples/s]
Generating train split: 73724279 examples [1:08:53, 10594.27 examples/s]
Generating train split: 73726229 examples [1:08:53, 12509.10 examples/s]
Generating train split: 73727691 examples [1:08:53, 12660.14 examples/s]
Generating train split: 73729419 examples [1:08:53, 13589.75 examples/s]
Generating train split: 73730905 examples [1:08:53, 13345.42 examples/s]
Generating train split: 73732631 examples [1:08:53, 14358.03 examples/s]
Generating train split: 73734145 examples [1:08:54, 11451.36 examples/s]
Generating train split: 73735432 examples [1:08:54, 10939.69 examples/s]
Generating train split: 73743179 examples [1:08:54, 26667.07 examples/s]
Generating train split: 73751233 examples [1:08:54, 38982.00 examples/s]
Generating train split: 73755585 examples [1:08:54, 38324.74 examples/s]
Generating train split: 73759736 examples [1:08:54, 27945.41 examples/s]
Generating train split: 73763138 examples [1:08:55, 21808.57 examples/s]
Generating train split: 73766442 examples [1:08:55, 23861.60 examples/s]
Generating train split: 73769369 examples [1:08:55, 14484.65 examples/s]
Generating train split: 73771615 examples [1:08:55, 13390.97 examples/s]
Generating train split: 73774916 examples [1:08:55, 16146.98 examples/s]
Generating train split: 73777977 examples [1:08:56, 18652.88 examples/s]
Generating train split: 73780454 examples [1:08:56, 15280.57 examples/s]
Generating train split: 73782480 examples [1:08:56, 14150.57 examples/s]
Generating train split: 73784240 examples [1:08:56, 14566.28 examples/s]
Generating train split: 73785990 examples [1:08:56, 15125.02 examples/s]
Generating train split: 73788170 examples [1:08:56, 15802.77 examples/s]
Generating train split: 73789905 examples [1:08:56, 14031.61 examples/s]
Generating train split: 73791441 examples [1:08:57, 10593.83 examples/s]
Generating train split: 73792697 examples [1:08:57, 8885.23 examples/s] 
Generating train split: 73794744 examples [1:08:57, 10989.37 examples/s]
Generating train split: 73796091 examples [1:08:57, 9614.55 examples/s] 
Generating train split: 73797245 examples [1:08:57, 9383.54 examples/s]
Generating train split: 73798314 examples [1:08:58, 9032.75 examples/s]
Generating train split: 73799946 examples [1:08:58, 10583.10 examples/s]
Generating train split: 73801469 examples [1:08:58, 11640.40 examples/s]
Generating train split: 73802749 examples [1:08:58, 8959.90 examples/s] 
Generating train split: 73803808 examples [1:08:58, 8752.53 examples/s]
Generating train split: 73805258 examples [1:08:58, 9833.87 examples/s]
Generating train split: 73808534 examples [1:08:58, 15279.09 examples/s]
Generating train split: 73815719 examples [1:08:58, 29611.37 examples/s]
Generating train split: 73824577 examples [1:08:59, 45272.56 examples/s]
Generating train split: 73830764 examples [1:08:59, 49832.53 examples/s]
Generating train split: 73839825 examples [1:08:59, 61329.42 examples/s]
Generating train split: 73846800 examples [1:08:59, 63705.16 examples/s]
Generating train split: 73853434 examples [1:08:59, 37872.19 examples/s]
Generating train split: 73858657 examples [1:09:00, 24229.37 examples/s]
Generating train split: 73863654 examples [1:09:00, 27910.54 examples/s]
Generating train split: 73870256 examples [1:09:00, 34366.87 examples/s]
Generating train split: 73875248 examples [1:09:00, 22345.38 examples/s]
Generating train split: 73879086 examples [1:09:01, 19351.79 examples/s]
Generating train split: 73882169 examples [1:09:01, 17769.99 examples/s]
Generating train split: 73885242 examples [1:09:01, 19621.08 examples/s]
Generating train split: 73891707 examples [1:09:01, 27272.34 examples/s]
Generating train split: 73895544 examples [1:09:01, 24851.44 examples/s]
Generating train split: 73898826 examples [1:09:01, 25089.60 examples/s]
Generating train split: 73902622 examples [1:09:01, 27736.34 examples/s]
Generating train split: 73906410 examples [1:09:01, 30019.83 examples/s]
Generating train split: 73909848 examples [1:09:02, 24322.30 examples/s]
Generating train split: 73912782 examples [1:09:02, 24838.56 examples/s]
Generating train split: 73915607 examples [1:09:02, 24844.06 examples/s]
Generating train split: 73918336 examples [1:09:02, 23040.37 examples/s]
Generating train split: 73921930 examples [1:09:02, 26101.24 examples/s]
Generating train split: 73924749 examples [1:09:02, 20935.78 examples/s]
Generating train split: 73927129 examples [1:09:03, 16391.17 examples/s]
Generating train split: 73929265 examples [1:09:03, 16863.34 examples/s]
Generating train split: 73931576 examples [1:09:03, 18152.30 examples/s]
Generating train split: 73936306 examples [1:09:03, 24843.15 examples/s]
Generating train split: 73939140 examples [1:09:03, 23394.09 examples/s]
Generating train split: 73942023 examples [1:09:03, 24715.08 examples/s]
Generating train split: 73948644 examples [1:09:03, 34978.98 examples/s]
Generating train split: 73952407 examples [1:09:03, 29473.23 examples/s]
Generating train split: 73955675 examples [1:09:04, 27154.34 examples/s]
Generating train split: 73958625 examples [1:09:04, 18055.90 examples/s]
Generating train split: 73960973 examples [1:09:04, 15884.31 examples/s]
Generating train split: 73962946 examples [1:09:04, 16553.99 examples/s]
Generating train split: 73964918 examples [1:09:04, 13610.16 examples/s]
Generating train split: 73966555 examples [1:09:05, 9232.87 examples/s] 
Generating train split: 73967827 examples [1:09:05, 7961.67 examples/s]
Generating train split: 73969489 examples [1:09:05, 9106.95 examples/s]
Generating train split: 73970678 examples [1:09:05, 9409.60 examples/s]
Generating train split: 73972354 examples [1:09:05, 10833.96 examples/s]
Generating train split: 73975202 examples [1:09:06, 10121.35 examples/s]
Generating train split: 73976407 examples [1:09:06, 10146.60 examples/s]
Generating train split: 73978700 examples [1:09:06, 12582.57 examples/s]
Generating train split: 73980746 examples [1:09:06, 11542.81 examples/s]
Generating train split: 73982068 examples [1:09:06, 9497.21 examples/s] 
Generating train split: 73984022 examples [1:09:06, 11369.73 examples/s]
Generating train split: 73985379 examples [1:09:07, 9145.39 examples/s] 
Generating train split: 73988380 examples [1:09:07, 13075.33 examples/s]
Generating train split: 73991882 examples [1:09:07, 17730.30 examples/s]
Generating train split: 73994126 examples [1:09:07, 9419.10 examples/s] 
Generating train split: 73995817 examples [1:09:08, 9257.16 examples/s]
Generating train split: 73998464 examples [1:09:08, 11878.03 examples/s]
Generating train split: 74003133 examples [1:09:08, 18093.66 examples/s]
Generating train split: 74005796 examples [1:09:08, 16034.52 examples/s]
Generating train split: 74008031 examples [1:09:08, 13402.77 examples/s]
Generating train split: 74009863 examples [1:09:08, 13905.22 examples/s]
Generating train split: 74011745 examples [1:09:09, 14863.35 examples/s]
Generating train split: 74013550 examples [1:09:09, 12762.61 examples/s]
Generating train split: 74018958 examples [1:09:09, 21173.58 examples/s]
Generating train split: 74024966 examples [1:09:09, 29930.66 examples/s]
Generating train split: 74028652 examples [1:09:09, 21427.70 examples/s]
Generating train split: 74031607 examples [1:09:09, 19996.29 examples/s]
Generating train split: 74034180 examples [1:09:10, 16127.49 examples/s]
Generating train split: 74036296 examples [1:09:10, 14257.30 examples/s]
Generating train split: 74038075 examples [1:09:10, 10480.05 examples/s]
Generating train split: 74039507 examples [1:09:10, 10258.84 examples/s]
Generating train split: 74040766 examples [1:09:11, 9603.30 examples/s] 
Generating train split: 74041880 examples [1:09:11, 6626.44 examples/s]
Generating train split: 74043707 examples [1:09:11, 8291.41 examples/s]
Generating train split: 74044883 examples [1:09:11, 7929.32 examples/s]
Generating train split: 74046589 examples [1:09:11, 9552.76 examples/s]
Generating train split: 74048729 examples [1:09:11, 11912.02 examples/s]
Generating train split: 74050600 examples [1:09:11, 13379.49 examples/s]
Generating train split: 74056855 examples [1:09:12, 25182.84 examples/s]
Generating train split: 74059844 examples [1:09:12, 14085.27 examples/s]
Generating train split: 74062135 examples [1:09:12, 14799.42 examples/s]
Generating train split: 74066305 examples [1:09:12, 19691.73 examples/s]
Generating train split: 74069054 examples [1:09:12, 21158.10 examples/s]
Generating train split: 74071770 examples [1:09:13, 13736.31 examples/s]
Generating train split: 74074586 examples [1:09:13, 16064.33 examples/s]
Generating train split: 74076916 examples [1:09:13, 17172.35 examples/s]
Generating train split: 74079188 examples [1:09:13, 12189.38 examples/s]
Generating train split: 74080976 examples [1:09:13, 12865.82 examples/s]
Generating train split: 74083244 examples [1:09:14, 14718.44 examples/s]
Generating train split: 74086854 examples [1:09:14, 19266.16 examples/s]
Generating train split: 74089327 examples [1:09:14, 20468.78 examples/s]
Generating train split: 74091749 examples [1:09:14, 18994.31 examples/s]
Generating train split: 74093925 examples [1:09:14, 15104.74 examples/s]
Generating train split: 74095917 examples [1:09:14, 16104.10 examples/s]
Generating train split: 74099685 examples [1:09:14, 20483.85 examples/s]
Generating train split: 74102008 examples [1:09:14, 20782.67 examples/s]
Generating train split: 74104282 examples [1:09:15, 16747.27 examples/s]
Generating train split: 74106426 examples [1:09:15, 17769.30 examples/s]
Generating train split: 74108679 examples [1:09:15, 17248.64 examples/s]
Generating train split: 74110796 examples [1:09:15, 18120.80 examples/s]
Generating train split: 74112731 examples [1:09:15, 10448.00 examples/s]
Generating train split: 74114238 examples [1:09:15, 10699.47 examples/s]
Generating train split: 74115637 examples [1:09:16, 10871.08 examples/s]
Generating train split: 74116961 examples [1:09:16, 11238.62 examples/s]
Generating train split: 74118279 examples [1:09:16, 9692.10 examples/s] 
Generating train split: 74119406 examples [1:09:16, 9342.39 examples/s]
Generating train split: 74122254 examples [1:09:16, 13524.19 examples/s]
Generating train split: 74123834 examples [1:09:16, 9714.29 examples/s] 
Generating train split: 74125107 examples [1:09:17, 9014.66 examples/s]
Generating train split: 74126852 examples [1:09:17, 10635.68 examples/s]
Generating train split: 74128838 examples [1:09:17, 12614.72 examples/s]
Generating train split: 74131420 examples [1:09:17, 15695.12 examples/s]
Generating train split: 74135090 examples [1:09:17, 20963.58 examples/s]
Generating train split: 74138869 examples [1:09:17, 25310.44 examples/s]
Generating train split: 74141650 examples [1:09:18, 12218.68 examples/s]
Generating train split: 74143760 examples [1:09:18, 12755.53 examples/s]
Generating train split: 74145683 examples [1:09:18, 12007.76 examples/s]
Generating train split: 74147336 examples [1:09:18, 11690.30 examples/s]
Generating train split: 74149639 examples [1:09:18, 13656.28 examples/s]
Generating train split: 74151330 examples [1:09:18, 13048.82 examples/s]
Generating train split: 74152856 examples [1:09:19, 10532.89 examples/s]
Generating train split: 74154126 examples [1:09:19, 10086.98 examples/s]
Generating train split: 74155487 examples [1:09:19, 10665.86 examples/s]
Generating train split: 74157055 examples [1:09:19, 11663.94 examples/s]
Generating train split: 74158341 examples [1:09:19, 7298.47 examples/s] 
Generating train split: 74159578 examples [1:09:19, 8171.91 examples/s]
Generating train split: 74162149 examples [1:09:20, 11631.87 examples/s]
Generating train split: 74164105 examples [1:09:20, 13367.36 examples/s]
Generating train split: 74165758 examples [1:09:20, 11274.41 examples/s]
Generating train split: 74167169 examples [1:09:20, 10757.65 examples/s]
Generating train split: 74168745 examples [1:09:20, 11833.74 examples/s]
Generating train split: 74170561 examples [1:09:20, 13326.08 examples/s]
Generating train split: 74172058 examples [1:09:20, 13505.18 examples/s]
Generating train split: 74174184 examples [1:09:20, 15231.90 examples/s]
Generating train split: 74178795 examples [1:09:20, 23488.72 examples/s]
Generating train split: 74181336 examples [1:09:21, 22420.26 examples/s]
Generating train split: 74183708 examples [1:09:21, 11359.02 examples/s]
Generating train split: 74185524 examples [1:09:21, 11666.22 examples/s]
Generating train split: 74187497 examples [1:09:21, 13090.19 examples/s]
Generating train split: 74190757 examples [1:09:21, 17025.03 examples/s]
Generating train split: 74192961 examples [1:09:22, 15709.31 examples/s]
Generating train split: 74194891 examples [1:09:22, 15427.34 examples/s]
Generating train split: 74196863 examples [1:09:22, 16267.33 examples/s]
Generating train split: 74199083 examples [1:09:22, 17691.16 examples/s]
Generating train split: 74201031 examples [1:09:22, 10969.41 examples/s]
Generating train split: 74202556 examples [1:09:22, 11339.85 examples/s]
Generating train split: 74204007 examples [1:09:23, 9679.00 examples/s] 
Generating train split: 74205222 examples [1:09:23, 8857.10 examples/s]
Generating train split: 74206292 examples [1:09:23, 9163.88 examples/s]
Generating train split: 74208586 examples [1:09:23, 11992.53 examples/s]
Generating train split: 74209991 examples [1:09:23, 11891.28 examples/s]
Generating train split: 74211324 examples [1:09:23, 10001.17 examples/s]
Generating train split: 74212620 examples [1:09:23, 10647.76 examples/s]
Generating train split: 74214272 examples [1:09:24, 12039.28 examples/s]
Generating train split: 74215616 examples [1:09:24, 11861.80 examples/s]
Generating train split: 74219719 examples [1:09:24, 18435.48 examples/s]
Generating train split: 74227085 examples [1:09:24, 32745.97 examples/s]
Generating train split: 74232661 examples [1:09:24, 36859.27 examples/s]
Generating train split: 74236548 examples [1:09:24, 32080.07 examples/s]
Generating train split: 74239979 examples [1:09:25, 16383.02 examples/s]
Generating train split: 74242597 examples [1:09:25, 16718.46 examples/s]
Generating train split: 74245897 examples [1:09:25, 19442.73 examples/s]
Generating train split: 74248988 examples [1:09:25, 21580.54 examples/s]
Generating train split: 74251781 examples [1:09:25, 21543.21 examples/s]
Generating train split: 74254364 examples [1:09:26, 12408.06 examples/s]
Generating train split: 74256343 examples [1:09:26, 10666.78 examples/s]
Generating train split: 74259533 examples [1:09:26, 13736.27 examples/s]
Generating train split: 74262071 examples [1:09:26, 15729.58 examples/s]
Generating train split: 74264439 examples [1:09:26, 17259.39 examples/s]
Generating train split: 74266693 examples [1:09:27, 11921.88 examples/s]
Generating train split: 74268778 examples [1:09:27, 13422.22 examples/s]
Generating train split: 74272605 examples [1:09:27, 18238.73 examples/s]
Generating train split: 74276149 examples [1:09:27, 21685.75 examples/s]
Generating train split: 74278880 examples [1:09:27, 14930.94 examples/s]
Generating train split: 74281293 examples [1:09:27, 16222.18 examples/s]
Generating train split: 74284355 examples [1:09:27, 18818.77 examples/s]
Generating train split: 74288251 examples [1:09:27, 23231.94 examples/s]
Generating train split: 74291082 examples [1:09:28, 13478.50 examples/s]
Generating train split: 74293251 examples [1:09:28, 13552.87 examples/s]
Generating train split: 74296018 examples [1:09:28, 15976.50 examples/s]
Generating train split: 74298848 examples [1:09:28, 18362.55 examples/s]
Generating train split: 74301222 examples [1:09:28, 18316.10 examples/s]
Generating train split: 74303435 examples [1:09:29, 17644.98 examples/s]
Generating train split: 74305457 examples [1:09:29, 15647.50 examples/s]
Generating train split: 74307226 examples [1:09:29, 15567.04 examples/s]
Generating train split: 74310488 examples [1:09:29, 19510.86 examples/s]
Generating train split: 74313119 examples [1:09:29, 15236.76 examples/s]
Generating train split: 74314941 examples [1:09:29, 15399.40 examples/s]
Generating train split: 74316700 examples [1:09:30, 12058.27 examples/s]
Generating train split: 74318379 examples [1:09:30, 12958.07 examples/s]
Generating train split: 74321097 examples [1:09:30, 12462.51 examples/s]
Generating train split: 74323509 examples [1:09:30, 14530.18 examples/s]
Generating train split: 74325180 examples [1:09:30, 11497.37 examples/s]
Generating train split: 74326571 examples [1:09:30, 10281.53 examples/s]
Generating train split: 74328303 examples [1:09:31, 11593.63 examples/s]
Generating train split: 74329650 examples [1:09:31, 11886.69 examples/s]
Generating train split: 74331131 examples [1:09:31, 12217.75 examples/s]
Generating train split: 74333314 examples [1:09:31, 14185.44 examples/s]
Generating train split: 74334842 examples [1:09:31, 13668.72 examples/s]
Generating train split: 74336492 examples [1:09:31, 14359.46 examples/s]
Generating train split: 74338135 examples [1:09:31, 14907.20 examples/s]
Generating train split: 74340916 examples [1:09:31, 18421.16 examples/s]
Generating train split: 74342829 examples [1:09:32, 10541.03 examples/s]
Generating train split: 74344381 examples [1:09:32, 11463.93 examples/s]
Generating train split: 74346004 examples [1:09:32, 12453.99 examples/s]
Generating train split: 74348377 examples [1:09:32, 15037.48 examples/s]
Generating train split: 74350175 examples [1:09:32, 15345.20 examples/s]
Generating train split: 74351919 examples [1:09:32, 14618.33 examples/s]
Generating train split: 74354822 examples [1:09:32, 18244.71 examples/s]
Generating train split: 74360449 examples [1:09:32, 28297.35 examples/s]
Generating train split: 74368067 examples [1:09:32, 41416.07 examples/s]
Generating train split: 74372905 examples [1:09:33, 43353.18 examples/s]
Generating train split: 74377472 examples [1:09:33, 27205.70 examples/s]
Generating train split: 74381100 examples [1:09:33, 16976.13 examples/s]
Generating train split: 74383919 examples [1:09:33, 18589.36 examples/s]
Generating train split: 74386711 examples [1:09:34, 16790.72 examples/s]
Generating train split: 74389052 examples [1:09:34, 15755.76 examples/s]
Generating train split: 74391224 examples [1:09:34, 16799.38 examples/s]
Generating train split: 74393471 examples [1:09:34, 17854.70 examples/s]
Generating train split: 74396347 examples [1:09:34, 20264.91 examples/s]
Generating train split: 74398688 examples [1:09:34, 15128.69 examples/s]
Generating train split: 74400604 examples [1:09:35, 12735.21 examples/s]
Generating train split: 74402195 examples [1:09:35, 11223.17 examples/s]
Generating train split: 74404809 examples [1:09:35, 13934.10 examples/s]
Generating train split: 74406832 examples [1:09:35, 15148.95 examples/s]
Generating train split: 74408637 examples [1:09:35, 13567.58 examples/s]
Generating train split: 74410539 examples [1:09:35, 14644.24 examples/s]
Generating train split: 74412195 examples [1:09:35, 13170.63 examples/s]
Generating train split: 74414265 examples [1:09:36, 14381.06 examples/s]
Generating train split: 74415831 examples [1:09:36, 11540.36 examples/s]
Generating train split: 74417155 examples [1:09:36, 11845.93 examples/s]
Generating train split: 74418466 examples [1:09:36, 7195.77 examples/s] 
Generating train split: 74420778 examples [1:09:36, 9800.56 examples/s]
Generating train split: 74422442 examples [1:09:37, 11095.78 examples/s]
Generating train split: 74423925 examples [1:09:37, 8149.83 examples/s] 
Generating train split: 74425110 examples [1:09:37, 8460.56 examples/s]
Generating train split: 74426226 examples [1:09:37, 5709.85 examples/s]
Generating train split: 74427102 examples [1:09:37, 5866.71 examples/s]
Generating train split: 74428624 examples [1:09:38, 7387.69 examples/s]
Generating train split: 74431471 examples [1:09:38, 11349.75 examples/s]
Generating train split: 74432995 examples [1:09:38, 11912.53 examples/s]
Generating train split: 74434560 examples [1:09:38, 12753.75 examples/s]
Generating train split: 74437163 examples [1:09:38, 16033.19 examples/s]
Generating train split: 74439002 examples [1:09:38, 15435.17 examples/s]
Generating train split: 74441534 examples [1:09:38, 17861.92 examples/s]
Generating train split: 74443471 examples [1:09:38, 16262.20 examples/s]
Generating train split: 74445295 examples [1:09:38, 16610.19 examples/s]
Generating train split: 74448111 examples [1:09:39, 19656.92 examples/s]
Generating train split: 74454119 examples [1:09:39, 30728.24 examples/s]
Generating train split: 74460395 examples [1:09:39, 39709.51 examples/s]
Generating train split: 74464555 examples [1:09:39, 31438.87 examples/s]
Generating train split: 74473170 examples [1:09:39, 44682.19 examples/s]
Generating train split: 74481784 examples [1:09:39, 55334.70 examples/s]
Generating train split: 74487925 examples [1:09:39, 41267.16 examples/s]
Generating train split: 74495838 examples [1:09:40, 49498.45 examples/s]
Generating train split: 74503626 examples [1:09:40, 56209.24 examples/s]
Generating train split: 74510101 examples [1:09:40, 56216.69 examples/s]
Generating train split: 74518862 examples [1:09:40, 64316.78 examples/s]
Generating train split: 74525844 examples [1:09:41, 23464.42 examples/s]
Generating train split: 74531004 examples [1:09:41, 25105.45 examples/s]
Generating train split: 74535611 examples [1:09:41, 25824.12 examples/s]
Generating train split: 74539698 examples [1:09:42, 15358.29 examples/s]
Generating train split: 74542743 examples [1:09:42, 16816.94 examples/s]
Generating train split: 74545713 examples [1:09:42, 14570.31 examples/s]
Generating train split: 74548923 examples [1:09:42, 16471.08 examples/s]
Generating train split: 74551406 examples [1:09:43, 10496.32 examples/s]
Generating train split: 74554595 examples [1:09:43, 12943.05 examples/s]
Generating train split: 74557361 examples [1:09:43, 15006.97 examples/s]
Generating train split: 74560936 examples [1:09:43, 18468.40 examples/s]
Generating train split: 74563701 examples [1:09:43, 14157.24 examples/s]
Generating train split: 74565900 examples [1:09:43, 14104.63 examples/s]
Generating train split: 74567869 examples [1:09:44, 14956.26 examples/s]
Generating train split: 74569806 examples [1:09:44, 11964.55 examples/s]
Generating train split: 74572661 examples [1:09:44, 14884.88 examples/s]
Generating train split: 74574627 examples [1:09:44, 13939.28 examples/s]
Generating train split: 74576351 examples [1:09:44, 12645.21 examples/s]
Generating train split: 74578108 examples [1:09:44, 13627.22 examples/s]
Generating train split: 74582295 examples [1:09:44, 19891.10 examples/s]
Generating train split: 74585769 examples [1:09:45, 19758.79 examples/s]
Generating train split: 74588005 examples [1:09:45, 15363.53 examples/s]
Generating train split: 74589845 examples [1:09:45, 15400.85 examples/s]
Generating train split: 74593346 examples [1:09:45, 19551.20 examples/s]
Generating train split: 74596648 examples [1:09:45, 18404.74 examples/s]
Generating train split: 74598743 examples [1:09:45, 17740.11 examples/s]
Generating train split: 74600684 examples [1:09:46, 13752.53 examples/s]
Generating train split: 74602287 examples [1:09:46, 13120.82 examples/s]
Generating train split: 74604909 examples [1:09:46, 15779.62 examples/s]
Generating train split: 74606796 examples [1:09:46, 15857.61 examples/s]
Generating train split: 74608550 examples [1:09:46, 11914.71 examples/s]
Generating train split: 74612221 examples [1:09:46, 16832.77 examples/s]
Generating train split: 74614478 examples [1:09:46, 17637.13 examples/s]
Generating train split: 74616559 examples [1:09:47, 13471.62 examples/s]
Generating train split: 74619615 examples [1:09:47, 16846.00 examples/s]
Generating train split: 74622146 examples [1:09:47, 18699.50 examples/s]
Generating train split: 74624380 examples [1:09:47, 17357.75 examples/s]
Generating train split: 74626385 examples [1:09:47, 14879.78 examples/s]
Generating train split: 74628104 examples [1:09:48, 11395.71 examples/s]
Generating train split: 74629513 examples [1:09:48, 10977.51 examples/s]
Generating train split: 74630796 examples [1:09:48, 11107.32 examples/s]
Generating train split: 74633257 examples [1:09:48, 14021.54 examples/s]
Generating train split: 74634870 examples [1:09:48, 14340.57 examples/s]
Generating train split: 74637640 examples [1:09:48, 17673.32 examples/s]
Generating train split: 74640293 examples [1:09:48, 19979.01 examples/s]
Generating train split: 74642453 examples [1:09:48, 15622.34 examples/s]
Generating train split: 74646828 examples [1:09:49, 22074.89 examples/s]
Generating train split: 74650556 examples [1:09:49, 25822.75 examples/s]
Generating train split: 74653483 examples [1:09:49, 19409.12 examples/s]
Generating train split: 74657697 examples [1:09:49, 24244.76 examples/s]
Generating train split: 74660815 examples [1:09:49, 25847.77 examples/s]
Generating train split: 74663817 examples [1:09:49, 25544.20 examples/s]
Generating train split: 74668691 examples [1:09:49, 30400.11 examples/s]
Generating train split: 74671971 examples [1:09:50, 23640.27 examples/s]
Generating train split: 74674715 examples [1:09:50, 23309.08 examples/s]
Generating train split: 74678517 examples [1:09:50, 26694.90 examples/s]
Generating train split: 74681485 examples [1:09:50, 27429.07 examples/s]
Generating train split: 74684446 examples [1:09:50, 25950.19 examples/s]
Generating train split: 74687204 examples [1:09:50, 18986.58 examples/s]
Generating train split: 74690516 examples [1:09:50, 21939.51 examples/s]
Generating train split: 74693303 examples [1:09:50, 23299.88 examples/s]
Generating train split: 74695941 examples [1:09:51, 22374.67 examples/s]
Generating train split: 74698395 examples [1:09:51, 15728.16 examples/s]
Generating train split: 74705549 examples [1:09:51, 26604.58 examples/s]
Generating train split: 74709075 examples [1:09:51, 23707.34 examples/s]
Generating train split: 74712094 examples [1:09:52, 15638.24 examples/s]
Generating train split: 74714444 examples [1:09:52, 15164.64 examples/s]
Generating train split: 74716505 examples [1:09:52, 16031.92 examples/s]
Generating train split: 74718557 examples [1:09:52, 15303.27 examples/s]
Generating train split: 74720389 examples [1:09:52, 15298.34 examples/s]
Generating train split: 74723847 examples [1:09:52, 19302.63 examples/s]
Generating train split: 74726080 examples [1:09:52, 14971.22 examples/s]
Generating train split: 74727930 examples [1:09:53, 11493.58 examples/s]
Generating train split: 74729448 examples [1:09:53, 8830.29 examples/s] 
Generating train split: 74730632 examples [1:09:53, 8830.24 examples/s]
Generating train split: 74731753 examples [1:09:53, 9237.03 examples/s]
Generating train split: 74734728 examples [1:09:53, 13260.93 examples/s]
Generating train split: 74737961 examples [1:09:53, 17400.09 examples/s]
Generating train split: 74740733 examples [1:09:54, 19809.84 examples/s]
Generating train split: 74743048 examples [1:09:54, 14342.13 examples/s]
Generating train split: 74744922 examples [1:09:54, 13710.27 examples/s]
Generating train split: 74747927 examples [1:09:54, 17059.72 examples/s]
Generating train split: 74750156 examples [1:09:54, 18236.47 examples/s]
Generating train split: 74752280 examples [1:09:54, 16426.92 examples/s]
Generating train split: 74754152 examples [1:09:54, 16489.80 examples/s]
Generating train split: 74755963 examples [1:09:55, 15835.81 examples/s]
Generating train split: 74757667 examples [1:09:55, 14366.79 examples/s]
Generating train split: 74760085 examples [1:09:55, 16702.77 examples/s]
Generating train split: 74761886 examples [1:09:55, 12101.37 examples/s]
Generating train split: 74763361 examples [1:09:55, 10773.70 examples/s]
Generating train split: 74770862 examples [1:09:55, 23600.24 examples/s]
Generating train split: 74774100 examples [1:09:55, 24898.77 examples/s]
Generating train split: 74777171 examples [1:09:56, 19984.37 examples/s]
Generating train split: 74779714 examples [1:09:56, 18160.38 examples/s]
Generating train split: 74781917 examples [1:09:56, 17557.47 examples/s]
Generating train split: 74784469 examples [1:09:56, 19094.80 examples/s]
Generating train split: 74786631 examples [1:09:56, 18169.57 examples/s]
Generating train split: 74788627 examples [1:09:56, 17840.48 examples/s]
Generating train split: 74790529 examples [1:09:57, 17974.66 examples/s]
Generating train split: 74792416 examples [1:09:57, 17199.97 examples/s]
Generating train split: 74794198 examples [1:09:57, 15176.04 examples/s]
Generating train split: 74795978 examples [1:09:57, 15805.94 examples/s]
Generating train split: 74797621 examples [1:09:57, 14735.17 examples/s]
Generating train split: 74799179 examples [1:09:57, 14867.56 examples/s]
Generating train split: 74801200 examples [1:09:57, 16188.31 examples/s]
Generating train split: 74803110 examples [1:09:57, 16972.44 examples/s]
Generating train split: 74804851 examples [1:09:58, 13481.30 examples/s]
Generating train split: 74806471 examples [1:09:58, 14129.26 examples/s]
Generating train split: 74808438 examples [1:09:58, 15458.92 examples/s]
Generating train split: 74810726 examples [1:09:58, 17424.30 examples/s]
Generating train split: 74813409 examples [1:09:58, 20002.73 examples/s]
Generating train split: 74818625 examples [1:09:58, 29071.45 examples/s]
Generating train split: 74824703 examples [1:09:58, 38171.32 examples/s]
Generating train split: 74828643 examples [1:09:59, 13624.36 examples/s]
Generating train split: 74831567 examples [1:10:01, 4228.25 examples/s] 
Generating train split: 74833652 examples [1:10:01, 4844.11 examples/s]
Generating train split: 74835478 examples [1:10:01, 5645.93 examples/s]
Generating train split: 74837276 examples [1:10:01, 6550.90 examples/s]
Generating train split: 74839000 examples [1:10:02, 7153.57 examples/s]
Generating train split: 74841353 examples [1:10:02, 9111.78 examples/s]
Generating train split: 74843121 examples [1:10:02, 10351.24 examples/s]
Generating train split: 74845616 examples [1:10:02, 12865.27 examples/s]
Generating train split: 74847788 examples [1:10:02, 14351.91 examples/s]
Generating train split: 74849772 examples [1:10:02, 10248.23 examples/s]
Generating train split: 74851654 examples [1:10:02, 11281.06 examples/s]
Generating train split: 74853222 examples [1:10:03, 11111.35 examples/s]
Generating train split: 74855024 examples [1:10:03, 12479.63 examples/s]
Generating train split: 74857379 examples [1:10:03, 14666.33 examples/s]
Generating train split: 74859114 examples [1:10:03, 15187.18 examples/s]
Generating train split: 74860831 examples [1:10:03, 12519.63 examples/s]
Generating train split: 74863043 examples [1:10:03, 14655.27 examples/s]
Generating train split: 74866223 examples [1:10:03, 18784.12 examples/s]
Generating train split: 74869430 examples [1:10:03, 22165.11 examples/s]
Generating train split: 74871881 examples [1:10:04, 18115.54 examples/s]
Generating train split: 74874488 examples [1:10:04, 19969.32 examples/s]
Generating train split: 74877090 examples [1:10:04, 15505.86 examples/s]
Generating train split: 74879724 examples [1:10:04, 17480.39 examples/s]
Generating train split: 74882711 examples [1:10:04, 20122.13 examples/s]
Generating train split: 74885994 examples [1:10:04, 22402.99 examples/s]
Generating train split: 74888470 examples [1:10:05, 11314.37 examples/s]
Generating train split: 74890720 examples [1:10:05, 11255.81 examples/s]
Generating train split: 74893123 examples [1:10:05, 13202.88 examples/s]
Generating train split: 74895887 examples [1:10:05, 15820.87 examples/s]
Generating train split: 74898022 examples [1:10:05, 14712.42 examples/s]
Generating train split: 74899885 examples [1:10:06, 12208.19 examples/s]
Generating train split: 74901428 examples [1:10:06, 12788.29 examples/s]
Generating train split: 74904338 examples [1:10:06, 16186.80 examples/s]
Generating train split: 74906282 examples [1:10:06, 13256.83 examples/s]
Generating train split: 74908273 examples [1:10:06, 13624.44 examples/s]
Generating train split: 74911241 examples [1:10:06, 17059.85 examples/s]
Generating train split: 74913359 examples [1:10:06, 18023.16 examples/s]
Generating train split: 74915852 examples [1:10:07, 19721.17 examples/s]
Generating train split: 74918020 examples [1:10:07, 16002.30 examples/s]
Generating train split: 74919860 examples [1:10:07, 15206.73 examples/s]
Generating train split: 74921899 examples [1:10:07, 16365.19 examples/s]
Generating train split: 74924296 examples [1:10:07, 18205.95 examples/s]
Generating train split: 74926260 examples [1:10:07, 16686.31 examples/s]
Generating train split: 74928044 examples [1:10:07, 15568.81 examples/s]
Generating train split: 74929687 examples [1:10:07, 15494.53 examples/s]
Generating train split: 74932712 examples [1:10:08, 19292.37 examples/s]
Generating train split: 74936268 examples [1:10:08, 23660.77 examples/s]
Generating train split: 74938765 examples [1:10:08, 18293.10 examples/s]
Generating train split: 74940861 examples [1:10:08, 14188.47 examples/s]
Generating train split: 74942596 examples [1:10:08, 14651.79 examples/s]
Generating train split: 74945239 examples [1:10:08, 17222.75 examples/s]
Generating train split: 74947384 examples [1:10:08, 18043.62 examples/s]
Generating train split: 74949397 examples [1:10:09, 14145.65 examples/s]
Generating train split: 74951099 examples [1:10:09, 14722.42 examples/s]
Generating train split: 74952782 examples [1:10:09, 13491.79 examples/s]
Generating train split: 74954283 examples [1:10:09, 11393.15 examples/s]
Generating train split: 74957126 examples [1:10:09, 14592.30 examples/s]
Generating train split: 74959639 examples [1:10:09, 16979.99 examples/s]
Generating train split: 74962488 examples [1:10:09, 19792.62 examples/s]
Generating train split: 74968999 examples [1:10:09, 31543.89 examples/s]
Generating train split: 74977680 examples [1:10:10, 46470.34 examples/s]
Generating train split: 74982728 examples [1:10:10, 43997.93 examples/s]
Generating train split: 74987434 examples [1:10:10, 28568.41 examples/s]
Generating train split: 74991188 examples [1:10:10, 18368.77 examples/s]
Generating train split: 74994074 examples [1:10:11, 17466.95 examples/s]
Generating train split: 74996540 examples [1:10:11, 16662.46 examples/s]
Generating train split: 74998696 examples [1:10:11, 16278.65 examples/s]
Generating train split: 75001292 examples [1:10:11, 18015.25 examples/s]
Generating train split: 75003447 examples [1:10:11, 15231.62 examples/s]
Generating train split: 75005264 examples [1:10:11, 15580.76 examples/s]
Generating train split: 75007038 examples [1:10:12, 14608.84 examples/s]
Generating train split: 75010793 examples [1:10:12, 19569.45 examples/s]
Generating train split: 75013047 examples [1:10:12, 20198.44 examples/s]
Generating train split: 75015285 examples [1:10:12, 17982.75 examples/s]
Generating train split: 75017279 examples [1:10:12, 15108.05 examples/s]
Generating train split: 75020488 examples [1:10:12, 18596.05 examples/s]
Generating train split: 75022599 examples [1:10:12, 18957.93 examples/s]
Generating train split: 75025103 examples [1:10:12, 20240.14 examples/s]
Generating train split: 75027280 examples [1:10:13, 13404.76 examples/s]
Generating train split: 75029013 examples [1:10:13, 13116.75 examples/s]
Generating train split: 75032872 examples [1:10:13, 18228.56 examples/s]
Generating train split: 75038970 examples [1:10:13, 27856.13 examples/s]
Generating train split: 75047795 examples [1:10:13, 42555.70 examples/s]
Generating train split: 75052817 examples [1:10:14, 23709.79 examples/s]
Generating train split: 75056689 examples [1:10:14, 22560.43 examples/s]
Generating train split: 75059989 examples [1:10:14, 22871.36 examples/s]
Generating train split: 75063014 examples [1:10:14, 20161.53 examples/s]
Generating train split: 75065562 examples [1:10:14, 20274.38 examples/s]
Generating train split: 75068245 examples [1:10:14, 21568.35 examples/s]
Generating train split: 75070739 examples [1:10:14, 21349.56 examples/s]
Generating train split: 75073111 examples [1:10:15, 19704.83 examples/s]
Generating train split: 75077172 examples [1:10:15, 24380.32 examples/s]
Generating train split: 75079860 examples [1:10:15, 21564.18 examples/s]
Generating train split: 75082233 examples [1:10:15, 21576.27 examples/s]
Generating train split: 75084542 examples [1:10:15, 16187.42 examples/s]
Generating train split: 75086453 examples [1:10:16, 10466.60 examples/s]
Generating train split: 75087928 examples [1:10:16, 9454.83 examples/s] 
Generating train split: 75089937 examples [1:10:16, 11104.75 examples/s]
Generating train split: 75091979 examples [1:10:16, 12808.55 examples/s]
Generating train split: 75093626 examples [1:10:16, 12105.36 examples/s]
Generating train split: 75095083 examples [1:10:16, 12140.01 examples/s]
Generating train split: 75097773 examples [1:10:16, 15434.86 examples/s]
Generating train split: 75099685 examples [1:10:17, 16315.49 examples/s]
Generating train split: 75101502 examples [1:10:17, 14004.24 examples/s]
Generating train split: 75103085 examples [1:10:17, 13691.28 examples/s]
Generating train split: 75104588 examples [1:10:17, 10940.31 examples/s]
Generating train split: 75107393 examples [1:10:17, 14562.26 examples/s]
Generating train split: 75115534 examples [1:10:17, 30085.50 examples/s]
Generating train split: 75119182 examples [1:10:17, 25656.96 examples/s]
Generating train split: 75123158 examples [1:10:18, 28797.38 examples/s]
Generating train split: 75126538 examples [1:10:18, 12409.24 examples/s]
Generating train split: 75129059 examples [1:10:19, 11254.49 examples/s]
Generating train split: 75131095 examples [1:10:19, 9992.82 examples/s] 
Generating train split: 75133985 examples [1:10:19, 12379.89 examples/s]
Generating train split: 75136531 examples [1:10:19, 14270.64 examples/s]
Generating train split: 75138665 examples [1:10:20, 7618.84 examples/s] 
Generating train split: 75141465 examples [1:10:20, 9861.51 examples/s]
Generating train split: 75145205 examples [1:10:20, 13607.49 examples/s]
Generating train split: 75149192 examples [1:10:20, 17886.35 examples/s]
Generating train split: 75152123 examples [1:10:20, 12118.89 examples/s]
Generating train split: 75154936 examples [1:10:21, 12533.55 examples/s]
Generating train split: 75156922 examples [1:10:21, 12920.22 examples/s]
Generating train split: 75159591 examples [1:10:21, 15228.78 examples/s]
Generating train split: 75161994 examples [1:10:21, 16065.13 examples/s]
Generating train split: 75164015 examples [1:10:22, 9601.58 examples/s] 
Generating train split: 75167079 examples [1:10:22, 12631.43 examples/s]
Generating train split: 75171355 examples [1:10:22, 17768.10 examples/s]
Generating train split: 75174036 examples [1:10:22, 19441.73 examples/s]
Generating train split: 75176708 examples [1:10:22, 13616.84 examples/s]
Generating train split: 75178888 examples [1:10:22, 14986.33 examples/s]
Generating train split: 75182177 examples [1:10:22, 18432.85 examples/s]
Generating train split: 75185620 examples [1:10:22, 21792.88 examples/s]
Generating train split: 75188357 examples [1:10:23, 15263.46 examples/s]
Generating train split: 75190539 examples [1:10:23, 14938.95 examples/s]
Generating train split: 75194643 examples [1:10:23, 16403.15 examples/s]
Generating train split: 75197141 examples [1:10:23, 16909.20 examples/s]
Generating train split: 75199062 examples [1:10:23, 16659.79 examples/s]
Generating train split: 75200885 examples [1:10:24, 12700.73 examples/s]
Generating train split: 75202381 examples [1:10:24, 13073.79 examples/s]
Generating train split: 75203861 examples [1:10:24, 13100.86 examples/s]
Generating train split: 75206021 examples [1:10:24, 15010.67 examples/s]
Generating train split: 75212430 examples [1:10:24, 26706.08 examples/s]
Generating train split: 75215439 examples [1:10:25, 9872.38 examples/s] 
Generating train split: 75217658 examples [1:10:25, 9436.22 examples/s]
Generating train split: 75220653 examples [1:10:25, 11921.67 examples/s]
Generating train split: 75223735 examples [1:10:25, 14699.21 examples/s]
Generating train split: 75226161 examples [1:10:26, 12608.62 examples/s]
Generating train split: 75228129 examples [1:10:26, 11638.86 examples/s]
Generating train split: 75230230 examples [1:10:26, 13161.50 examples/s]
Generating train split: 75233171 examples [1:10:26, 16012.81 examples/s]
Generating train split: 75235258 examples [1:10:26, 13540.77 examples/s]
Generating train split: 75238147 examples [1:10:26, 16463.09 examples/s]
Generating train split: 75240227 examples [1:10:27, 12292.82 examples/s]
Generating train split: 75241900 examples [1:10:27, 13048.46 examples/s]
Generating train split: 75243568 examples [1:10:27, 12693.46 examples/s]
Generating train split: 75245084 examples [1:10:27, 7141.52 examples/s] 
Generating train split: 75246236 examples [1:10:28, 6556.05 examples/s]
Generating train split: 75247192 examples [1:10:28, 6489.84 examples/s]
Generating train split: 75248058 examples [1:10:28, 6289.97 examples/s]
Generating train split: 75249113 examples [1:10:28, 7007.47 examples/s]
Generating train split: 75250220 examples [1:10:28, 7811.70 examples/s]
Generating train split: 75251631 examples [1:10:28, 9062.17 examples/s]
Generating train split: 75252680 examples [1:10:29, 6826.86 examples/s]
Generating train split: 75253858 examples [1:10:29, 7786.96 examples/s]
Generating train split: 75255719 examples [1:10:29, 10151.83 examples/s]
Generating train split: 75257400 examples [1:10:29, 11729.70 examples/s]
Generating train split: 75258767 examples [1:10:29, 11664.35 examples/s]
Generating train split: 75260069 examples [1:10:29, 10169.70 examples/s]
Generating train split: 75261206 examples [1:10:29, 7969.52 examples/s] 
Generating train split: 75263766 examples [1:10:29, 11589.21 examples/s]
Generating train split: 75265201 examples [1:10:30, 10460.06 examples/s]
Generating train split: 75267188 examples [1:10:30, 12489.02 examples/s]
Generating train split: 75268656 examples [1:10:30, 12757.36 examples/s]
Generating train split: 75270095 examples [1:10:30, 12769.76 examples/s]
Generating train split: 75271734 examples [1:10:30, 13493.86 examples/s]
Generating train split: 75273170 examples [1:10:30, 9824.83 examples/s] 
Generating train split: 75280762 examples [1:10:30, 23923.01 examples/s]
Generating train split: 75289054 examples [1:10:30, 37696.96 examples/s]
Generating train split: 75293716 examples [1:10:31, 33797.49 examples/s]
Generating train split: 75297792 examples [1:10:31, 23907.45 examples/s]
Generating train split: 75301047 examples [1:10:31, 25221.93 examples/s]
Generating train split: 75308496 examples [1:10:31, 35341.13 examples/s]
Generating train split: 75315117 examples [1:10:31, 42332.84 examples/s]
Generating train split: 75320236 examples [1:10:32, 28843.78 examples/s]
Generating train split: 75324303 examples [1:10:32, 23597.41 examples/s]
Generating train split: 75331764 examples [1:10:32, 32118.47 examples/s]
Generating train split: 75338554 examples [1:10:32, 38495.03 examples/s]
Generating train split: 75343639 examples [1:10:32, 29244.23 examples/s]
Generating train split: 75347725 examples [1:10:33, 22019.96 examples/s]
Generating train split: 75350953 examples [1:10:33, 17246.54 examples/s]
Generating train split: 75353504 examples [1:10:33, 17289.51 examples/s]
Generating train split: 75357431 examples [1:10:33, 20705.54 examples/s]
Generating train split: 75365700 examples [1:10:33, 31964.48 examples/s]
Generating train split: 75371631 examples [1:10:33, 37593.38 examples/s]
Generating train split: 75376519 examples [1:10:34, 24602.75 examples/s]
Generating train split: 75380327 examples [1:10:34, 21257.54 examples/s]
Generating train split: 75383434 examples [1:10:34, 20391.37 examples/s]
Generating train split: 75389932 examples [1:10:34, 27882.33 examples/s]
Generating train split: 75393777 examples [1:10:35, 21978.47 examples/s]
Generating train split: 75396871 examples [1:10:35, 22463.34 examples/s]
Generating train split: 75400315 examples [1:10:35, 24707.19 examples/s]
Generating train split: 75405077 examples [1:10:35, 29525.04 examples/s]
Generating train split: 75408648 examples [1:10:35, 16952.46 examples/s]
Generating train split: 75411916 examples [1:10:36, 19363.10 examples/s]
Generating train split: 75414818 examples [1:10:36, 16932.88 examples/s]
Generating train split: 75417211 examples [1:10:36, 16699.72 examples/s]
Generating train split: 75419364 examples [1:10:36, 16431.21 examples/s]
Generating train split: 75421339 examples [1:10:36, 15940.33 examples/s]
Generating train split: 75423158 examples [1:10:36, 12385.64 examples/s]
Generating train split: 75424642 examples [1:10:37, 9550.90 examples/s] 
Generating train split: 75426828 examples [1:10:37, 11393.89 examples/s]
Generating train split: 75429711 examples [1:10:37, 14622.88 examples/s]
Generating train split: 75431588 examples [1:10:37, 12118.76 examples/s]
Generating train split: 75434451 examples [1:10:37, 15256.10 examples/s]
Generating train split: 75436397 examples [1:10:38, 11534.68 examples/s]
Generating train split: 75438563 examples [1:10:38, 13261.64 examples/s]
Generating train split: 75440672 examples [1:10:38, 14842.79 examples/s]
Generating train split: 75442521 examples [1:10:38, 14241.08 examples/s]
Generating train split: 75444192 examples [1:10:38, 14333.08 examples/s]
Generating train split: 75445807 examples [1:10:38, 12869.73 examples/s]
Generating train split: 75451338 examples [1:10:38, 22567.60 examples/s]
Generating train split: 75456245 examples [1:10:38, 29089.16 examples/s]
Generating train split: 75461151 examples [1:10:39, 34278.96 examples/s]
Generating train split: 75466153 examples [1:10:39, 38525.58 examples/s]
Generating train split: 75470313 examples [1:10:39, 27256.05 examples/s]
Generating train split: 75474193 examples [1:10:39, 29749.29 examples/s]
Generating train split: 75481347 examples [1:10:39, 39597.74 examples/s]
Generating train split: 75485987 examples [1:10:39, 34199.07 examples/s]
Generating train split: 75491128 examples [1:10:39, 37952.94 examples/s]
Generating train split: 75495452 examples [1:10:40, 20717.92 examples/s]
Generating train split: 75498754 examples [1:10:40, 19841.40 examples/s]
Generating train split: 75501589 examples [1:10:40, 19448.39 examples/s]
Generating train split: 75505342 examples [1:10:40, 22545.78 examples/s]
Generating train split: 75508223 examples [1:10:41, 14320.43 examples/s]
Generating train split: 75510436 examples [1:10:41, 15065.77 examples/s]
Generating train split: 75512545 examples [1:10:41, 12450.17 examples/s]
Generating train split: 75514254 examples [1:10:41, 10400.12 examples/s]
Generating train split: 75515646 examples [1:10:41, 10688.86 examples/s]
Generating train split: 75516979 examples [1:10:42, 8716.46 examples/s] 
Generating train split: 75518067 examples [1:10:42, 8479.41 examples/s]
Generating train split: 75519341 examples [1:10:42, 9209.19 examples/s]
Generating train split: 75521201 examples [1:10:42, 11003.03 examples/s]
Generating train split: 75522490 examples [1:10:42, 11268.01 examples/s]
Generating train split: 75523765 examples [1:10:42, 11467.06 examples/s]
Generating train split: 75525010 examples [1:10:42, 10839.74 examples/s]
Generating train split: 75526176 examples [1:10:43, 5507.57 examples/s] 
Generating train split: 75527659 examples [1:10:43, 6907.42 examples/s]
Generating train split: 75530314 examples [1:10:43, 10388.74 examples/s]
Generating train split: 75534556 examples [1:10:43, 16845.56 examples/s]
Generating train split: 75537786 examples [1:10:43, 20207.27 examples/s]
Generating train split: 75540377 examples [1:10:44, 14345.44 examples/s]
Generating train split: 75542934 examples [1:10:44, 16345.46 examples/s]
Generating train split: 75545147 examples [1:10:44, 10486.66 examples/s]
Generating train split: 75546845 examples [1:10:44, 10499.52 examples/s]
Generating train split: 75549308 examples [1:10:44, 12830.49 examples/s]
Generating train split: 75551094 examples [1:10:45, 10405.34 examples/s]
Generating train split: 75552543 examples [1:10:45, 9795.74 examples/s] 
Generating train split: 75553805 examples [1:10:45, 9289.64 examples/s]
Generating train split: 75554921 examples [1:10:45, 8655.06 examples/s]
Generating train split: 75555912 examples [1:10:45, 8379.14 examples/s]
Generating train split: 75557960 examples [1:10:45, 10860.94 examples/s]
Generating train split: 75559222 examples [1:10:46, 10511.89 examples/s]
Generating train split: 75560392 examples [1:10:46, 9513.87 examples/s] 
Generating train split: 75561442 examples [1:10:46, 6195.63 examples/s]
Generating train split: 75562261 examples [1:10:46, 6255.24 examples/s]
Generating train split: 75564254 examples [1:10:46, 8713.36 examples/s]
Generating train split: 75565346 examples [1:10:47, 7938.46 examples/s]
Generating train split: 75566310 examples [1:10:47, 8205.38 examples/s]
Generating train split: 75567877 examples [1:10:47, 9748.69 examples/s]
Generating train split: 75569011 examples [1:10:47, 6032.97 examples/s]
Generating train split: 75570793 examples [1:10:47, 7993.56 examples/s]
Generating train split: 75573445 examples [1:10:47, 11592.07 examples/s]
Generating train split: 75577494 examples [1:10:47, 17857.50 examples/s]
Generating train split: 75581178 examples [1:10:47, 22343.90 examples/s]
Generating train split: 75583907 examples [1:10:48, 9684.83 examples/s] 
Generating train split: 75586873 examples [1:10:48, 12253.88 examples/s]
Generating train split: 75589180 examples [1:10:48, 13434.51 examples/s]
Generating train split: 75591352 examples [1:10:49, 11098.01 examples/s]
Generating train split: 75594138 examples [1:10:49, 13672.77 examples/s]
Generating train split: 75596168 examples [1:10:49, 7410.21 examples/s] 
Generating train split: 75598714 examples [1:10:50, 9472.66 examples/s]
Generating train split: 75602308 examples [1:10:50, 13209.59 examples/s]
Generating train split: 75606401 examples [1:10:50, 17855.21 examples/s]
Generating train split: 75609266 examples [1:10:50, 11768.54 examples/s]
Generating train split: 75612271 examples [1:10:50, 14329.41 examples/s]
Generating train split: 75616499 examples [1:10:50, 18989.41 examples/s]
Generating train split: 75619619 examples [1:10:51, 20185.55 examples/s]
Generating train split: 75622427 examples [1:10:51, 13683.89 examples/s]
Generating train split: 75625014 examples [1:10:51, 15579.59 examples/s]
Generating train split: 75629565 examples [1:10:51, 21008.85 examples/s]
Generating train split: 75632531 examples [1:10:51, 16161.10 examples/s]
Generating train split: 75634955 examples [1:10:52, 17553.90 examples/s]
Generating train split: 75637352 examples [1:10:52, 16388.02 examples/s]
Generating train split: 75639438 examples [1:10:52, 17180.70 examples/s]
Generating train split: 75641847 examples [1:10:52, 17520.29 examples/s]
Generating train split: 75644047 examples [1:10:52, 18308.52 examples/s]
Generating train split: 75646093 examples [1:10:52, 13343.64 examples/s]
Generating train split: 75647760 examples [1:10:53, 10040.17 examples/s]
Generating train split: 75649350 examples [1:10:53, 10981.29 examples/s]
Generating train split: 75650740 examples [1:10:53, 10426.83 examples/s]
Generating train split: 75651985 examples [1:10:53, 10562.66 examples/s]
Generating train split: 75655785 examples [1:10:53, 16522.29 examples/s]
Generating train split: 75657775 examples [1:10:53, 12379.32 examples/s]
Generating train split: 75660110 examples [1:10:53, 14515.84 examples/s]
Generating train split: 75661941 examples [1:10:54, 9696.16 examples/s] 
Generating train split: 75664667 examples [1:10:54, 12430.71 examples/s]
Generating train split: 75666437 examples [1:10:54, 11600.48 examples/s]
Generating train split: 75667966 examples [1:10:54, 12012.19 examples/s]
Generating train split: 75669444 examples [1:10:54, 12130.43 examples/s]
Generating train split: 75670853 examples [1:10:54, 11540.59 examples/s]
Generating train split: 75672928 examples [1:10:55, 13615.37 examples/s]
Generating train split: 75674450 examples [1:10:55, 13641.81 examples/s]
Generating train split: 75675935 examples [1:10:55, 12667.65 examples/s]
Generating train split: 75677296 examples [1:10:55, 8368.53 examples/s] 
Generating train split: 75679276 examples [1:10:55, 10500.85 examples/s]
Generating train split: 75681487 examples [1:10:55, 12930.44 examples/s]
Generating train split: 75683825 examples [1:10:55, 15124.96 examples/s]
Generating train split: 75685609 examples [1:10:56, 15736.74 examples/s]
Generating train split: 75687396 examples [1:10:56, 16019.40 examples/s]
Generating train split: 75689149 examples [1:10:56, 16056.14 examples/s]
Generating train split: 75691849 examples [1:10:56, 19023.25 examples/s]
Generating train split: 75695288 examples [1:10:56, 23298.96 examples/s]
Generating train split: 75697925 examples [1:10:56, 24169.50 examples/s]
Generating train split: 75700418 examples [1:10:56, 15726.59 examples/s]
Generating train split: 75703824 examples [1:10:56, 19488.73 examples/s]
Generating train split: 75707114 examples [1:10:57, 22510.96 examples/s]
Generating train split: 75709773 examples [1:10:57, 14403.98 examples/s]
Generating train split: 75711856 examples [1:10:57, 15243.48 examples/s]
Generating train split: 75716723 examples [1:10:57, 21840.85 examples/s]
Generating train split: 75723553 examples [1:10:57, 32090.54 examples/s]
Generating train split: 75727595 examples [1:10:57, 31859.71 examples/s]
Generating train split: 75731391 examples [1:10:58, 17848.35 examples/s]
Generating train split: 75734283 examples [1:10:58, 14430.24 examples/s]
Generating train split: 75736569 examples [1:10:58, 14813.01 examples/s]
Generating train split: 75738892 examples [1:10:58, 16075.80 examples/s]
Generating train split: 75741031 examples [1:10:59, 13848.06 examples/s]
Generating train split: 75742817 examples [1:10:59, 10501.10 examples/s]
Generating train split: 75744240 examples [1:10:59, 8623.25 examples/s] 
Generating train split: 75745752 examples [1:10:59, 9570.75 examples/s]
Generating train split: 75747006 examples [1:11:00, 8652.41 examples/s]
Generating train split: 75748632 examples [1:11:00, 9968.30 examples/s]
Generating train split: 75749919 examples [1:11:00, 10508.95 examples/s]
Generating train split: 75751184 examples [1:11:00, 7199.61 examples/s] 
Generating train split: 75753039 examples [1:11:00, 9137.10 examples/s]
Generating train split: 75754283 examples [1:11:00, 9684.18 examples/s]
Generating train split: 75756609 examples [1:11:00, 12167.56 examples/s]
Generating train split: 75758734 examples [1:11:00, 14216.82 examples/s]
Generating train split: 75760592 examples [1:11:01, 14586.52 examples/s]
Generating train split: 75762215 examples [1:11:01, 9734.15 examples/s] 
Generating train split: 75764883 examples [1:11:01, 12916.39 examples/s]
Generating train split: 75767081 examples [1:11:01, 14835.39 examples/s]
Generating train split: 75769660 examples [1:11:01, 17382.60 examples/s]
Generating train split: 75771728 examples [1:11:01, 17492.25 examples/s]
Generating train split: 75773707 examples [1:11:01, 16586.46 examples/s]
Generating train split: 75775533 examples [1:11:02, 16820.20 examples/s]
Generating train split: 75777524 examples [1:11:02, 17624.87 examples/s]
Generating train split: 75780477 examples [1:11:02, 20583.68 examples/s]
Generating train split: 75782628 examples [1:11:02, 18841.83 examples/s]
Generating train split: 75784606 examples [1:11:02, 18532.65 examples/s]
Generating train split: 75786823 examples [1:11:02, 19476.53 examples/s]
Generating train split: 75788830 examples [1:11:02, 16079.97 examples/s]
Generating train split: 75790571 examples [1:11:02, 15556.59 examples/s]
Generating train split: 75792639 examples [1:11:03, 16812.18 examples/s]
Generating train split: 75794820 examples [1:11:03, 18108.81 examples/s]
Generating train split: 75796714 examples [1:11:03, 14866.31 examples/s]
Generating train split: 75798858 examples [1:11:03, 16428.37 examples/s]
Generating train split: 75800642 examples [1:11:03, 12876.02 examples/s]
Generating train split: 75802136 examples [1:11:03, 11538.60 examples/s]
Generating train split: 75803900 examples [1:11:03, 12827.51 examples/s]
Generating train split: 75807056 examples [1:11:03, 17183.67 examples/s]
Generating train split: 75810758 examples [1:11:04, 21406.41 examples/s]
Generating train split: 75813119 examples [1:11:04, 15002.42 examples/s]
Generating train split: 75815658 examples [1:11:04, 16972.17 examples/s]
Generating train split: 75817841 examples [1:11:04, 17919.62 examples/s]
Generating train split: 75822046 examples [1:11:04, 23677.01 examples/s]
Generating train split: 75824767 examples [1:11:04, 24513.57 examples/s]
Generating train split: 75834079 examples [1:11:04, 38930.08 examples/s]
Generating train split: 75838015 examples [1:11:05, 20370.85 examples/s]
Generating train split: 75841084 examples [1:11:05, 22019.79 examples/s]
Generating train split: 75844112 examples [1:11:05, 16938.06 examples/s]
Generating train split: 75847219 examples [1:11:05, 18703.42 examples/s]
Generating train split: 75849716 examples [1:11:06, 12702.33 examples/s]
Generating train split: 75852778 examples [1:11:06, 12159.43 examples/s]
Generating train split: 75855571 examples [1:11:06, 14358.07 examples/s]
Generating train split: 75858535 examples [1:11:06, 16899.23 examples/s]
Generating train split: 75860828 examples [1:11:07, 14074.16 examples/s]
Generating train split: 75862716 examples [1:11:07, 13997.23 examples/s]
Generating train split: 75866199 examples [1:11:07, 17966.35 examples/s]
Generating train split: 75868582 examples [1:11:07, 14703.00 examples/s]
Generating train split: 75870511 examples [1:11:07, 15563.86 examples/s]
Generating train split: 75872704 examples [1:11:07, 16920.24 examples/s]
Generating train split: 75874699 examples [1:11:07, 13556.60 examples/s]
Generating train split: 75876548 examples [1:11:08, 14563.19 examples/s]
Generating train split: 75879573 examples [1:11:08, 18103.73 examples/s]
Generating train split: 75881685 examples [1:11:08, 17201.37 examples/s]
Generating train split: 75883627 examples [1:11:08, 15389.97 examples/s]
Generating train split: 75885701 examples [1:11:08, 16610.82 examples/s]
Generating train split: 75891833 examples [1:11:08, 24349.08 examples/s]
Generating train split: 75894293 examples [1:11:09, 16442.02 examples/s]
Generating train split: 75896256 examples [1:11:09, 14669.36 examples/s]
Generating train split: 75899239 examples [1:11:09, 17429.18 examples/s]
Generating train split: 75901742 examples [1:11:09, 19017.05 examples/s]
Generating train split: 75903936 examples [1:11:09, 16931.65 examples/s]
Generating train split: 75905868 examples [1:11:09, 15468.07 examples/s]
Generating train split: 75907586 examples [1:11:09, 15275.16 examples/s]
Generating train split: 75909231 examples [1:11:10, 10550.71 examples/s]
Generating train split: 75910568 examples [1:11:10, 11060.89 examples/s]
Generating train split: 75911890 examples [1:11:10, 11275.11 examples/s]
Generating train split: 75914517 examples [1:11:10, 14637.29 examples/s]
Generating train split: 75916630 examples [1:11:10, 13960.62 examples/s]
Generating train split: 75919380 examples [1:11:10, 16820.33 examples/s]
Generating train split: 75921735 examples [1:11:10, 18401.39 examples/s]
Generating train split: 75923819 examples [1:11:10, 19021.72 examples/s]
Generating train split: 75925849 examples [1:11:11, 16774.62 examples/s]
Generating train split: 75927657 examples [1:11:11, 14540.88 examples/s]
Generating train split: 75929251 examples [1:11:11, 13438.74 examples/s]
Generating train split: 75930695 examples [1:11:11, 13115.99 examples/s]
Generating train split: 75932074 examples [1:11:11, 12861.37 examples/s]
Generating train split: 75933405 examples [1:11:11, 11277.37 examples/s]
Generating train split: 75935385 examples [1:11:11, 13289.61 examples/s]
Generating train split: 75937440 examples [1:11:12, 15119.37 examples/s]
Generating train split: 75939049 examples [1:11:12, 11850.94 examples/s]
Generating train split: 75940846 examples [1:11:12, 13227.61 examples/s]
Generating train split: 75942334 examples [1:11:12, 13293.34 examples/s]
Generating train split: 75943803 examples [1:11:12, 13645.18 examples/s]
Generating train split: 75945254 examples [1:11:12, 10966.73 examples/s]
Generating train split: 75946492 examples [1:11:12, 10118.92 examples/s]
Generating train split: 75947612 examples [1:11:13, 9464.75 examples/s] 
Generating train split: 75949288 examples [1:11:13, 11128.30 examples/s]
Generating train split: 75951708 examples [1:11:13, 12977.62 examples/s]
Generating train split: 75953503 examples [1:11:13, 14169.37 examples/s]
Generating train split: 75955397 examples [1:11:13, 15392.05 examples/s]
Generating train split: 75957314 examples [1:11:13, 16396.88 examples/s]
Generating train split: 75959037 examples [1:11:13, 16622.67 examples/s]
Generating train split: 75960756 examples [1:11:13, 14362.25 examples/s]
Generating train split: 75963118 examples [1:11:13, 16552.43 examples/s]
Generating train split: 75964865 examples [1:11:14, 16658.75 examples/s]
Generating train split: 75967412 examples [1:11:14, 19065.86 examples/s]
Generating train split: 75969393 examples [1:11:14, 18391.18 examples/s]
Generating train split: 75971401 examples [1:11:14, 18730.44 examples/s]
Generating train split: 75973320 examples [1:11:14, 13024.42 examples/s]
Generating train split: 75974880 examples [1:11:14, 13142.18 examples/s]
Generating train split: 75977534 examples [1:11:14, 16235.52 examples/s]
Generating train split: 75979377 examples [1:11:15, 13977.35 examples/s]
Generating train split: 75980983 examples [1:11:15, 13346.88 examples/s]
Generating train split: 75982503 examples [1:11:15, 13751.78 examples/s]
Generating train split: 75983989 examples [1:11:15, 13788.78 examples/s]
Generating train split: 75985454 examples [1:11:15, 13124.95 examples/s]
Generating train split: 75986829 examples [1:11:15, 11709.45 examples/s]
Generating train split: 75988069 examples [1:11:15, 10929.16 examples/s]
Generating train split: 75990159 examples [1:11:15, 13172.01 examples/s]
Generating train split: 75991546 examples [1:11:16, 10931.22 examples/s]
Generating train split: 75992742 examples [1:11:16, 10818.90 examples/s]
Generating train split: 75993916 examples [1:11:16, 11030.59 examples/s]
Generating train split: 75995074 examples [1:11:16, 8308.21 examples/s] 
Generating train split: 75997920 examples [1:11:16, 12606.85 examples/s]
Generating train split: 76000500 examples [1:11:16, 15688.85 examples/s]
Generating train split: 76002342 examples [1:11:16, 16189.60 examples/s]
Generating train split: 76004161 examples [1:11:17, 9577.40 examples/s] 
Generating train split: 76005590 examples [1:11:17, 8442.93 examples/s]
Generating train split: 76006767 examples [1:11:17, 7439.05 examples/s]
Generating train split: 76012111 examples [1:11:17, 15107.19 examples/s]
Generating train split: 76019182 examples [1:11:17, 25799.49 examples/s]
Generating train split: 76025111 examples [1:11:17, 33015.76 examples/s]
Generating train split: 76029500 examples [1:11:18, 15604.88 examples/s]
Generating train split: 76032777 examples [1:11:18, 16340.88 examples/s]
Generating train split: 76035647 examples [1:11:19, 14971.69 examples/s]
Generating train split: 76038445 examples [1:11:19, 16841.19 examples/s]
Generating train split: 76040933 examples [1:11:19, 16990.24 examples/s]
Generating train split: 76043208 examples [1:11:19, 17875.19 examples/s]
Generating train split: 76048718 examples [1:11:19, 25629.59 examples/s]
Generating train split: 76054967 examples [1:11:19, 34075.85 examples/s]
Generating train split: 76059791 examples [1:11:19, 37569.78 examples/s]
Generating train split: 76066231 examples [1:11:19, 44556.33 examples/s]
Generating train split: 76075287 examples [1:11:19, 57031.30 examples/s]
Generating train split: 76081485 examples [1:11:20, 39778.26 examples/s]
Generating train split: 76086519 examples [1:11:20, 35357.19 examples/s]
Generating train split: 76090845 examples [1:11:20, 35744.56 examples/s]
Generating train split: 76094994 examples [1:11:20, 28559.93 examples/s]
Generating train split: 76098422 examples [1:11:20, 27007.78 examples/s]
Generating train split: 76104828 examples [1:11:20, 34498.80 examples/s]
Generating train split: 76110553 examples [1:11:21, 39600.41 examples/s]
Generating train split: 76117228 examples [1:11:21, 46175.75 examples/s]
Generating train split: 76122430 examples [1:11:21, 47587.73 examples/s]
Generating train split: 76127626 examples [1:11:21, 44848.47 examples/s]
Generating train split: 76132442 examples [1:11:21, 36249.44 examples/s]
Generating train split: 76136531 examples [1:11:21, 28754.00 examples/s]
Generating train split: 76139932 examples [1:11:22, 23812.64 examples/s]
Generating train split: 76142766 examples [1:11:22, 19044.15 examples/s]
Generating train split: 76147035 examples [1:11:22, 23075.75 examples/s]
Generating train split: 76152202 examples [1:11:22, 28670.98 examples/s]
Generating train split: 76157958 examples [1:11:22, 34681.70 examples/s]
Generating train split: 76162132 examples [1:11:23, 15108.33 examples/s]
Generating train split: 76165228 examples [1:11:23, 16320.36 examples/s]
Generating train split: 76168079 examples [1:11:23, 12401.83 examples/s]
Generating train split: 76170284 examples [1:11:24, 12203.44 examples/s]
Generating train split: 76172176 examples [1:11:24, 12429.62 examples/s]
Generating train split: 76173902 examples [1:11:24, 13057.84 examples/s]
Generating train split: 76177132 examples [1:11:24, 16531.54 examples/s]
Generating train split: 76179288 examples [1:11:24, 16988.66 examples/s]
Generating train split: 76181354 examples [1:11:24, 11625.53 examples/s]
Generating train split: 76183166 examples [1:11:24, 11410.96 examples/s]
Generating train split: 76185045 examples [1:11:25, 12727.68 examples/s]
Generating train split: 76186863 examples [1:11:25, 13836.69 examples/s]
Generating train split: 76188520 examples [1:11:25, 10253.38 examples/s]
Generating train split: 76189867 examples [1:11:25, 8174.86 examples/s] 
Generating train split: 76191125 examples [1:11:25, 8853.48 examples/s]
Generating train split: 76193496 examples [1:11:25, 11693.50 examples/s]
Generating train split: 76195005 examples [1:11:26, 11908.72 examples/s]
Generating train split: 76196821 examples [1:11:26, 13236.62 examples/s]
Generating train split: 76198539 examples [1:11:26, 14128.39 examples/s]
Generating train split: 76201688 examples [1:11:26, 18595.86 examples/s]
Generating train split: 76204568 examples [1:11:26, 21331.56 examples/s]
Generating train split: 76206869 examples [1:11:26, 16953.53 examples/s]
Generating train split: 76208818 examples [1:11:26, 13732.13 examples/s]
Generating train split: 76210450 examples [1:11:27, 11588.60 examples/s]
Generating train split: 76211839 examples [1:11:27, 12033.53 examples/s]
Generating train split: 76214086 examples [1:11:27, 13961.72 examples/s]
Generating train split: 76215667 examples [1:11:27, 13886.04 examples/s]
Generating train split: 76217764 examples [1:11:27, 15587.14 examples/s]
Generating train split: 76219450 examples [1:11:27, 12670.79 examples/s]
Generating train split: 76221232 examples [1:11:27, 13829.57 examples/s]
Generating train split: 76224111 examples [1:11:27, 17482.65 examples/s]
Generating train split: 76226054 examples [1:11:28, 12750.87 examples/s]
Generating train split: 76227644 examples [1:11:28, 12523.76 examples/s]
Generating train split: 76229108 examples [1:11:28, 11316.74 examples/s]
Generating train split: 76230395 examples [1:11:28, 11549.41 examples/s]
Generating train split: 76231668 examples [1:11:28, 11409.59 examples/s]
Generating train split: 76232895 examples [1:11:28, 11058.50 examples/s]
Generating train split: 76234730 examples [1:11:28, 12845.24 examples/s]
Generating train split: 76236090 examples [1:11:29, 11549.31 examples/s]
Generating train split: 76237588 examples [1:11:29, 12400.37 examples/s]
Generating train split: 76238897 examples [1:11:29, 8933.82 examples/s] 
Generating train split: 76239977 examples [1:11:29, 9002.80 examples/s]
Generating train split: 76241007 examples [1:11:29, 8765.63 examples/s]
Generating train split: 76242843 examples [1:11:29, 10623.61 examples/s]
Generating train split: 76244003 examples [1:11:29, 10096.72 examples/s]
Generating train split: 76246827 examples [1:11:30, 14393.37 examples/s]
Generating train split: 76248875 examples [1:11:30, 15954.91 examples/s]
Generating train split: 76250588 examples [1:11:30, 13194.64 examples/s]
Generating train split: 76252069 examples [1:11:30, 11565.41 examples/s]
Generating train split: 76253913 examples [1:11:30, 13102.23 examples/s]
Generating train split: 76256140 examples [1:11:30, 15252.05 examples/s]
Generating train split: 76261365 examples [1:11:30, 24729.24 examples/s]
Generating train split: 76266475 examples [1:11:30, 31791.75 examples/s]
Generating train split: 76273159 examples [1:11:31, 41490.08 examples/s]
Generating train split: 76279153 examples [1:11:31, 46703.69 examples/s]
Generating train split: 76284045 examples [1:11:31, 25700.93 examples/s]
Generating train split: 76291083 examples [1:11:31, 33855.29 examples/s]
Generating train split: 76299527 examples [1:11:31, 44312.76 examples/s]
Generating train split: 76305398 examples [1:11:31, 43863.66 examples/s]
Generating train split: 76310794 examples [1:11:32, 30199.71 examples/s]
Generating train split: 76315075 examples [1:11:32, 23707.77 examples/s]
Generating train split: 76318491 examples [1:11:32, 20220.07 examples/s]
Generating train split: 76321265 examples [1:11:32, 18730.20 examples/s]
Generating train split: 76323641 examples [1:11:33, 18587.78 examples/s]
Generating train split: 76327349 examples [1:11:33, 21870.81 examples/s]
Generating train split: 76331384 examples [1:11:33, 24735.47 examples/s]
Generating train split: 76334281 examples [1:11:33, 20238.26 examples/s]
Generating train split: 76336697 examples [1:11:33, 20689.84 examples/s]
Generating train split: 76339847 examples [1:11:33, 23032.81 examples/s]
Generating train split: 76342446 examples [1:11:33, 19567.62 examples/s]
Generating train split: 76345286 examples [1:11:33, 21486.20 examples/s]
Generating train split: 76347701 examples [1:11:34, 18275.77 examples/s]
Generating train split: 76349780 examples [1:11:34, 18141.13 examples/s]
Generating train split: 76351769 examples [1:11:34, 17691.12 examples/s]
Generating train split: 76353939 examples [1:11:34, 18640.20 examples/s]
Generating train split: 76356997 examples [1:11:34, 21635.71 examples/s]
Generating train split: 76359285 examples [1:11:35, 12700.03 examples/s]
Generating train split: 76361531 examples [1:11:35, 14226.13 examples/s]
Generating train split: 76363664 examples [1:11:35, 15644.98 examples/s]
Generating train split: 76367243 examples [1:11:35, 20144.90 examples/s]
Generating train split: 76369676 examples [1:11:35, 16379.70 examples/s]
Generating train split: 76371710 examples [1:11:35, 15194.81 examples/s]
Generating train split: 76374628 examples [1:11:35, 18120.75 examples/s]
Generating train split: 76377019 examples [1:11:35, 19179.06 examples/s]
Generating train split: 76379202 examples [1:11:36, 13983.48 examples/s]
Generating train split: 76380962 examples [1:11:36, 10326.76 examples/s]
Generating train split: 76382363 examples [1:11:36, 9412.74 examples/s] 
Generating train split: 76383567 examples [1:11:37, 6744.13 examples/s]
Generating train split: 76384945 examples [1:11:37, 7741.51 examples/s]
Generating train split: 76386835 examples [1:11:37, 9622.55 examples/s]
Generating train split: 76389836 examples [1:11:37, 13564.38 examples/s]
Generating train split: 76394114 examples [1:11:37, 13933.35 examples/s]
Generating train split: 76395816 examples [1:11:37, 12438.63 examples/s]
Generating train split: 76397587 examples [1:11:37, 13382.98 examples/s]
Generating train split: 76399146 examples [1:11:38, 13147.58 examples/s]
Generating train split: 76400606 examples [1:11:38, 12813.76 examples/s]
Generating train split: 76401985 examples [1:11:38, 12483.49 examples/s]
Generating train split: 76403302 examples [1:11:38, 11792.93 examples/s]
Generating train split: 76404523 examples [1:11:38, 11878.81 examples/s]
Generating train split: 76408609 examples [1:11:38, 19275.30 examples/s]
Generating train split: 76411685 examples [1:11:38, 18834.30 examples/s]
Generating train split: 76413688 examples [1:11:38, 17726.42 examples/s]
Generating train split: 76415786 examples [1:11:39, 17844.18 examples/s]
Generating train split: 76417632 examples [1:11:39, 12099.74 examples/s]
Generating train split: 76420020 examples [1:11:39, 14388.00 examples/s]
Generating train split: 76421775 examples [1:11:39, 13002.34 examples/s]
Generating train split: 76423312 examples [1:11:39, 10572.27 examples/s]
Generating train split: 76424594 examples [1:11:39, 10581.88 examples/s]
Generating train split: 76425963 examples [1:11:40, 11225.66 examples/s]
Generating train split: 76430016 examples [1:11:40, 17911.21 examples/s]
Generating train split: 76432871 examples [1:11:40, 20094.03 examples/s]
Generating train split: 76435123 examples [1:11:40, 12572.75 examples/s]
Generating train split: 76437995 examples [1:11:40, 15501.42 examples/s]
Generating train split: 76441553 examples [1:11:40, 19634.93 examples/s]
Generating train split: 76444347 examples [1:11:40, 21507.02 examples/s]
Generating train split: 76446960 examples [1:11:41, 13713.72 examples/s]
Generating train split: 76449005 examples [1:11:41, 14507.78 examples/s]
Generating train split: 76451995 examples [1:11:41, 17520.86 examples/s]
Generating train split: 76454277 examples [1:11:41, 15033.12 examples/s]
Generating train split: 76456191 examples [1:11:41, 14652.75 examples/s]
Generating train split: 76457941 examples [1:11:41, 15169.85 examples/s]
Generating train split: 76459690 examples [1:11:42, 15660.59 examples/s]
Generating train split: 76462130 examples [1:11:42, 17801.23 examples/s]
Generating train split: 76467149 examples [1:11:42, 26225.47 examples/s]
Generating train split: 76471984 examples [1:11:42, 29143.70 examples/s]
Generating train split: 76475046 examples [1:11:42, 16591.49 examples/s]
Generating train split: 76477417 examples [1:11:43, 13164.61 examples/s]
Generating train split: 76479316 examples [1:11:43, 11074.28 examples/s]
Generating train split: 76481696 examples [1:11:43, 12776.82 examples/s]
Generating train split: 76483528 examples [1:11:43, 13718.05 examples/s]
Generating train split: 76485662 examples [1:11:43, 15210.40 examples/s]
Generating train split: 76487533 examples [1:11:44, 11210.82 examples/s]
Generating train split: 76490936 examples [1:11:44, 15326.27 examples/s]
Generating train split: 76494220 examples [1:11:44, 18907.78 examples/s]
Generating train split: 76496661 examples [1:11:44, 14535.14 examples/s]
Generating train split: 76498634 examples [1:11:44, 15401.21 examples/s]
Generating train split: 76500592 examples [1:11:44, 16248.21 examples/s]
Generating train split: 76504548 examples [1:11:44, 15601.30 examples/s]
Generating train split: 76507414 examples [1:11:45, 18023.46 examples/s]
Generating train split: 76510620 examples [1:11:45, 20429.64 examples/s]
Generating train split: 76512936 examples [1:11:45, 10271.19 examples/s]
Generating train split: 76514717 examples [1:11:45, 11309.51 examples/s]
Generating train split: 76517033 examples [1:11:45, 13179.33 examples/s]
Generating train split: 76520520 examples [1:11:46, 17147.72 examples/s]
Generating train split: 76522868 examples [1:11:46, 10403.91 examples/s]
Generating train split: 76524652 examples [1:11:46, 11224.86 examples/s]
Generating train split: 76526365 examples [1:11:46, 12120.15 examples/s]
Generating train split: 76528059 examples [1:11:46, 10387.03 examples/s]
Generating train split: 76531158 examples [1:11:47, 14092.75 examples/s]
Generating train split: 76533982 examples [1:11:47, 16761.46 examples/s]
Generating train split: 76536121 examples [1:11:47, 11187.93 examples/s]
Generating train split: 76538578 examples [1:11:47, 13424.01 examples/s]
Generating train split: 76540494 examples [1:11:47, 12349.86 examples/s]
Generating train split: 76542131 examples [1:11:48, 9376.31 examples/s] 
Generating train split: 76545668 examples [1:11:48, 13594.53 examples/s]
Generating train split: 76548998 examples [1:11:48, 17287.80 examples/s]
Generating train split: 76552534 examples [1:11:48, 21006.00 examples/s]
Generating train split: 76555241 examples [1:11:48, 19540.72 examples/s]
Generating train split: 76557636 examples [1:11:48, 18234.91 examples/s]
Generating train split: 76562575 examples [1:11:48, 25117.69 examples/s]
Generating train split: 76568351 examples [1:11:48, 32940.79 examples/s]
Generating train split: 76572169 examples [1:11:49, 21817.83 examples/s]
Generating train split: 76575191 examples [1:11:49, 15962.99 examples/s]
Generating train split: 76577572 examples [1:11:49, 15318.61 examples/s]
Generating train split: 76581191 examples [1:11:49, 18696.12 examples/s]
Generating train split: 76583699 examples [1:11:50, 15137.39 examples/s]
Generating train split: 76585949 examples [1:11:50, 15517.31 examples/s]
Generating train split: 76587887 examples [1:11:50, 12802.49 examples/s]
Generating train split: 76589491 examples [1:11:50, 11998.24 examples/s]
Generating train split: 76592008 examples [1:11:50, 14403.80 examples/s]
Generating train split: 76594276 examples [1:11:50, 15301.55 examples/s]
Generating train split: 76596043 examples [1:11:51, 15609.50 examples/s]
Generating train split: 76597776 examples [1:11:51, 13491.54 examples/s]
Generating train split: 76600012 examples [1:11:51, 15371.41 examples/s]
Generating train split: 76601721 examples [1:11:51, 13939.09 examples/s]
Generating train split: 76603247 examples [1:11:51, 12833.98 examples/s]
Generating train split: 76604639 examples [1:11:51, 11297.04 examples/s]
Generating train split: 76607456 examples [1:11:51, 15021.24 examples/s]
Generating train split: 76609471 examples [1:11:51, 16249.50 examples/s]
Generating train split: 76613156 examples [1:11:52, 21459.14 examples/s]
Generating train split: 76615510 examples [1:11:52, 13402.20 examples/s]
Generating train split: 76617747 examples [1:11:52, 15082.65 examples/s]
Generating train split: 76620467 examples [1:11:52, 17641.56 examples/s]
Generating train split: 76623199 examples [1:11:52, 19864.12 examples/s]
Generating train split: 76626104 examples [1:11:52, 22139.92 examples/s]
Generating train split: 76628626 examples [1:11:53, 15887.21 examples/s]
Generating train split: 76630782 examples [1:11:53, 17030.07 examples/s]
Generating train split: 76632864 examples [1:11:53, 16681.42 examples/s]
Generating train split: 76639687 examples [1:11:53, 28649.00 examples/s]
Generating train split: 76646987 examples [1:11:53, 37175.63 examples/s]
Generating train split: 76651101 examples [1:11:53, 23429.72 examples/s]
Generating train split: 76654331 examples [1:11:54, 21526.28 examples/s]
Generating train split: 76657098 examples [1:11:54, 15772.90 examples/s]
Generating train split: 76659276 examples [1:11:54, 15590.27 examples/s]
Generating train split: 76661251 examples [1:11:54, 15806.05 examples/s]
Generating train split: 76663147 examples [1:11:54, 15353.40 examples/s]
Generating train split: 76664893 examples [1:11:55, 13445.06 examples/s]
Generating train split: 76666791 examples [1:11:55, 14450.75 examples/s]
Generating train split: 76668395 examples [1:11:55, 14343.23 examples/s]
Generating train split: 76669939 examples [1:11:55, 13551.56 examples/s]
Generating train split: 76671889 examples [1:11:55, 14950.01 examples/s]
Generating train split: 76673476 examples [1:11:55, 13373.16 examples/s]
Generating train split: 76675291 examples [1:11:55, 13513.54 examples/s]
Generating train split: 76677459 examples [1:11:55, 15489.68 examples/s]
Generating train split: 76679783 examples [1:11:55, 17462.36 examples/s]
Generating train split: 76681633 examples [1:11:56, 16029.81 examples/s]
Generating train split: 76683326 examples [1:11:56, 14032.64 examples/s]
Generating train split: 76685860 examples [1:11:56, 16264.03 examples/s]
Generating train split: 76687587 examples [1:11:56, 15991.60 examples/s]
Generating train split: 76689253 examples [1:11:56, 15162.42 examples/s]
Generating train split: 76692010 examples [1:11:56, 18341.11 examples/s]
Generating train split: 76694444 examples [1:11:56, 19939.92 examples/s]
Generating train split: 76696527 examples [1:11:57, 16178.31 examples/s]
Generating train split: 76700193 examples [1:11:57, 21100.04 examples/s]
Generating train split: 76703851 examples [1:11:57, 25050.55 examples/s]
Generating train split: 76706891 examples [1:11:57, 26473.52 examples/s]
Generating train split: 76713472 examples [1:11:57, 37345.65 examples/s]
Generating train split: 76721611 examples [1:11:57, 49795.04 examples/s]
Generating train split: 76726824 examples [1:11:57, 39381.91 examples/s]
Generating train split: 76731269 examples [1:11:58, 24947.36 examples/s]
Generating train split: 76734751 examples [1:11:58, 23214.32 examples/s]
Generating train split: 76739013 examples [1:11:58, 26684.54 examples/s]
Generating train split: 76742389 examples [1:11:58, 17826.67 examples/s]
Generating train split: 76745557 examples [1:11:58, 19978.04 examples/s]
Generating train split: 76748347 examples [1:11:58, 21143.21 examples/s]
Generating train split: 76751254 examples [1:11:59, 22676.59 examples/s]
Generating train split: 76754023 examples [1:11:59, 17017.49 examples/s]
Generating train split: 76756265 examples [1:11:59, 15369.55 examples/s]
Generating train split: 76759451 examples [1:11:59, 14466.95 examples/s]
Generating train split: 76761807 examples [1:11:59, 16005.07 examples/s]
Generating train split: 76763720 examples [1:11:59, 16396.33 examples/s]
Generating train split: 76765631 examples [1:12:00, 16671.98 examples/s]
Generating train split: 76767480 examples [1:12:00, 14694.21 examples/s]
Generating train split: 76769267 examples [1:12:00, 15394.81 examples/s]
Generating train split: 76771524 examples [1:12:00, 17122.50 examples/s]
Generating train split: 76775562 examples [1:12:00, 23085.29 examples/s]
Generating train split: 76778068 examples [1:12:00, 13759.67 examples/s]
Generating train split: 76780023 examples [1:12:01, 10715.18 examples/s]
Generating train split: 76781585 examples [1:12:01, 9834.52 examples/s] 
Generating train split: 76782905 examples [1:12:01, 8955.00 examples/s]
Generating train split: 76784030 examples [1:12:01, 7996.36 examples/s]
Generating train split: 76784984 examples [1:12:01, 7619.23 examples/s]
Generating train split: 76785844 examples [1:12:02, 7650.74 examples/s]
Generating train split: 76786680 examples [1:12:02, 7292.84 examples/s]
Generating train split: 76787455 examples [1:12:02, 7068.09 examples/s]
Generating train split: 76788267 examples [1:12:02, 7305.33 examples/s]
Generating train split: 76789722 examples [1:12:02, 9070.30 examples/s]
Generating train split: 76790776 examples [1:12:02, 9448.78 examples/s]
Generating train split: 76791768 examples [1:12:02, 7161.96 examples/s]
Generating train split: 76793407 examples [1:12:02, 9216.64 examples/s]
Generating train split: 76794800 examples [1:12:03, 10351.61 examples/s]
Generating train split: 76796125 examples [1:12:03, 11094.47 examples/s]
Generating train split: 76797426 examples [1:12:03, 11597.92 examples/s]
Generating train split: 76799043 examples [1:12:03, 12852.47 examples/s]
Generating train split: 76801041 examples [1:12:03, 14839.78 examples/s]
Generating train split: 76802693 examples [1:12:03, 15321.04 examples/s]
Generating train split: 76804268 examples [1:12:03, 12010.99 examples/s]
Generating train split: 76805612 examples [1:12:03, 11005.32 examples/s]
Generating train split: 76807287 examples [1:12:04, 12335.45 examples/s]
Generating train split: 76809084 examples [1:12:04, 13756.35 examples/s]
Generating train split: 76811057 examples [1:12:04, 15335.59 examples/s]
Generating train split: 76813775 examples [1:12:04, 18572.81 examples/s]
Generating train split: 76815994 examples [1:12:04, 19582.13 examples/s]
Generating train split: 76818028 examples [1:12:04, 14468.07 examples/s]
Generating train split: 76819719 examples [1:12:04, 13475.78 examples/s]
Generating train split: 76821944 examples [1:12:04, 15474.53 examples/s]
Generating train split: 76825402 examples [1:12:05, 20159.60 examples/s]
Generating train split: 76827684 examples [1:12:05, 20823.19 examples/s]
Generating train split: 76829939 examples [1:12:05, 15410.89 examples/s]
Generating train split: 76831806 examples [1:12:05, 14347.32 examples/s]
Generating train split: 76834727 examples [1:12:05, 17543.05 examples/s]
Generating train split: 76838572 examples [1:12:05, 16863.96 examples/s]
Generating train split: 76840490 examples [1:12:06, 14869.16 examples/s]
Generating train split: 76842140 examples [1:12:06, 14720.46 examples/s]
Generating train split: 76843759 examples [1:12:06, 15031.73 examples/s]
Generating train split: 76845352 examples [1:12:06, 13937.69 examples/s]
Generating train split: 76847236 examples [1:12:06, 15016.93 examples/s]
Generating train split: 76851597 examples [1:12:06, 22179.48 examples/s]
Generating train split: 76855143 examples [1:12:06, 21678.76 examples/s]
Generating train split: 76857459 examples [1:12:07, 14350.26 examples/s]
Generating train split: 76860315 examples [1:12:07, 16944.98 examples/s]
Generating train split: 76863826 examples [1:12:07, 20708.25 examples/s]
Generating train split: 76866750 examples [1:12:07, 22654.36 examples/s]
Generating train split: 76869413 examples [1:12:07, 13485.01 examples/s]
Generating train split: 76872624 examples [1:12:07, 16567.46 examples/s]
Generating train split: 76875195 examples [1:12:07, 18210.05 examples/s]
Generating train split: 76878245 examples [1:12:08, 19584.73 examples/s]
Generating train split: 76880652 examples [1:12:08, 14926.10 examples/s]
Generating train split: 76882604 examples [1:12:08, 13680.51 examples/s]
Generating train split: 76884299 examples [1:12:08, 14123.77 examples/s]
Generating train split: 76886544 examples [1:12:08, 15831.44 examples/s]
Generating train split: 76888730 examples [1:12:08, 17205.37 examples/s]
Generating train split: 76891998 examples [1:12:08, 20930.53 examples/s]
Generating train split: 76894314 examples [1:12:09, 17652.28 examples/s]
Generating train split: 76896315 examples [1:12:09, 15650.25 examples/s]
Generating train split: 76898078 examples [1:12:09, 15432.47 examples/s]
Generating train split: 76900526 examples [1:12:09, 17550.32 examples/s]
Generating train split: 76902870 examples [1:12:09, 18943.53 examples/s]
Generating train split: 76905335 examples [1:12:09, 20423.79 examples/s]
Generating train split: 76907491 examples [1:12:09, 16692.47 examples/s]
Generating train split: 76910737 examples [1:12:10, 20455.60 examples/s]
Generating train split: 76913013 examples [1:12:10, 17103.71 examples/s]
Generating train split: 76915731 examples [1:12:10, 19005.08 examples/s]
Generating train split: 76917852 examples [1:12:10, 16281.82 examples/s]
Generating train split: 76921369 examples [1:12:10, 20503.68 examples/s]
Generating train split: 76923705 examples [1:12:10, 14123.40 examples/s]
Generating train split: 76925566 examples [1:12:11, 12901.13 examples/s]
Generating train split: 76927766 examples [1:12:11, 14602.48 examples/s]
Generating train split: 76929548 examples [1:12:11, 13942.51 examples/s]
Generating train split: 76931170 examples [1:12:11, 14176.75 examples/s]
Generating train split: 76932755 examples [1:12:11, 13663.54 examples/s]
Generating train split: 76935309 examples [1:12:11, 16467.54 examples/s]
Generating train split: 76937115 examples [1:12:11, 14969.11 examples/s]
Generating train split: 76939360 examples [1:12:11, 16675.32 examples/s]
Generating train split: 76941315 examples [1:12:12, 17409.78 examples/s]
Generating train split: 76943153 examples [1:12:12, 15769.06 examples/s]
Generating train split: 76946017 examples [1:12:12, 19039.44 examples/s]
Generating train split: 76948793 examples [1:12:12, 21325.86 examples/s]
Generating train split: 76951038 examples [1:12:12, 17667.70 examples/s]
Generating train split: 76952986 examples [1:12:12, 17693.88 examples/s]
Generating train split: 76954883 examples [1:12:12, 15250.75 examples/s]
Generating train split: 76956749 examples [1:12:12, 16039.71 examples/s]
Generating train split: 76958470 examples [1:12:13, 14486.81 examples/s]
Generating train split: 76960586 examples [1:12:13, 15956.01 examples/s]
Generating train split: 76962282 examples [1:12:13, 14154.96 examples/s]
Generating train split: 76963801 examples [1:12:13, 11770.18 examples/s]
Generating train split: 76965095 examples [1:12:13, 10668.00 examples/s]
Generating train split: 76966246 examples [1:12:13, 9334.46 examples/s] 
Generating train split: 76967272 examples [1:12:14, 9522.34 examples/s]
Generating train split: 76968286 examples [1:12:14, 8962.29 examples/s]
Generating train split: 76970320 examples [1:12:14, 11496.70 examples/s]
Generating train split: 76971567 examples [1:12:14, 11616.47 examples/s]
Generating train split: 76974208 examples [1:12:14, 15443.60 examples/s]
Generating train split: 76975852 examples [1:12:14, 15191.61 examples/s]
Generating train split: 76978081 examples [1:12:14, 17098.35 examples/s]
Generating train split: 76979860 examples [1:12:14, 16851.15 examples/s]
Generating train split: 76981604 examples [1:12:14, 16831.23 examples/s]
Generating train split: 76984596 examples [1:12:14, 20539.75 examples/s]
Generating train split: 76988236 examples [1:12:15, 25104.89 examples/s]
Generating train split: 76993406 examples [1:12:15, 32843.33 examples/s]
Generating train split: 76998240 examples [1:12:15, 37386.76 examples/s]
Generating train split: 77002415 examples [1:12:15, 38664.14 examples/s]
Generating train split: 77007556 examples [1:12:15, 42446.38 examples/s]
Generating train split: 77014723 examples [1:12:15, 51137.82 examples/s]
Generating train split: 77019876 examples [1:12:15, 29876.33 examples/s]
Generating train split: 77025785 examples [1:12:16, 35599.57 examples/s]
Generating train split: 77030381 examples [1:12:16, 22871.78 examples/s]
Generating train split: 77033953 examples [1:12:16, 16793.16 examples/s]
Generating train split: 77036718 examples [1:12:17, 15710.76 examples/s]
Generating train split: 77039024 examples [1:12:17, 11873.03 examples/s]
Generating train split: 77040817 examples [1:12:17, 11691.61 examples/s]
Generating train split: 77042596 examples [1:12:17, 12537.28 examples/s]
Generating train split: 77044232 examples [1:12:17, 11066.39 examples/s]
Generating train split: 77045890 examples [1:12:18, 11989.66 examples/s]
Generating train split: 77048151 examples [1:12:18, 13934.34 examples/s]
Generating train split: 77049834 examples [1:12:18, 9902.23 examples/s] 
Generating train split: 77052341 examples [1:12:18, 12492.91 examples/s]
Generating train split: 77054066 examples [1:12:18, 13350.40 examples/s]
Generating train split: 77057693 examples [1:12:18, 18365.22 examples/s]
Generating train split: 77059982 examples [1:12:18, 19095.86 examples/s]
Generating train split: 77062207 examples [1:12:19, 10647.46 examples/s]
Generating train split: 77063911 examples [1:12:19, 11188.43 examples/s]
Generating train split: 77065508 examples [1:12:19, 11926.25 examples/s]
Generating train split: 77067085 examples [1:12:19, 7741.99 examples/s] 
Generating train split: 77068305 examples [1:12:20, 8343.94 examples/s]
Generating train split: 77070680 examples [1:12:20, 11047.06 examples/s]
Generating train split: 77072882 examples [1:12:20, 13247.31 examples/s]
Generating train split: 77074634 examples [1:12:20, 13924.86 examples/s]
Generating train split: 77076570 examples [1:12:20, 15215.78 examples/s]
Generating train split: 77078558 examples [1:12:20, 16077.18 examples/s]
Generating train split: 77080353 examples [1:12:20, 10365.90 examples/s]
Generating train split: 77083375 examples [1:12:20, 14062.69 examples/s]
Generating train split: 77085819 examples [1:12:21, 15067.35 examples/s]
Generating train split: 77087680 examples [1:12:21, 10249.78 examples/s]
Generating train split: 77090026 examples [1:12:21, 12453.13 examples/s]
Generating train split: 77091741 examples [1:12:21, 13147.57 examples/s]
Generating train split: 77093423 examples [1:12:22, 9216.59 examples/s] 
Generating train split: 77096843 examples [1:12:22, 13384.28 examples/s]
Generating train split: 77098785 examples [1:12:22, 8947.80 examples/s] 
Generating train split: 77100529 examples [1:12:22, 10176.69 examples/s]
Generating train split: 77102297 examples [1:12:22, 11446.88 examples/s]
Generating train split: 77105506 examples [1:12:22, 15507.97 examples/s]
Generating train split: 77109555 examples [1:12:22, 20245.00 examples/s]
Generating train split: 77112069 examples [1:12:23, 15129.93 examples/s]
Generating train split: 77114097 examples [1:12:23, 14636.11 examples/s]
Generating train split: 77118739 examples [1:12:23, 20541.88 examples/s]
Generating train split: 77121286 examples [1:12:23, 15298.10 examples/s]
Generating train split: 77123334 examples [1:12:24, 9880.52 examples/s] 
Generating train split: 77124900 examples [1:12:24, 10247.34 examples/s]
Generating train split: 77126365 examples [1:12:24, 8251.39 examples/s] 
Generating train split: 77127530 examples [1:12:24, 8570.18 examples/s]
Generating train split: 77131183 examples [1:12:24, 13263.03 examples/s]
Generating train split: 77133067 examples [1:12:25, 13344.75 examples/s]
Generating train split: 77134787 examples [1:12:25, 13313.94 examples/s]
Generating train split: 77136569 examples [1:12:25, 14197.31 examples/s]
Generating train split: 77138211 examples [1:12:25, 10749.22 examples/s]
Generating train split: 77139868 examples [1:12:25, 11851.42 examples/s]
Generating train split: 77141295 examples [1:12:25, 10464.57 examples/s]
Generating train split: 77142533 examples [1:12:25, 10609.06 examples/s]
Generating train split: 77143733 examples [1:12:26, 10304.68 examples/s]
Generating train split: 77144960 examples [1:12:26, 10758.75 examples/s]
Generating train split: 77147496 examples [1:12:26, 14078.62 examples/s]
Generating train split: 77149008 examples [1:12:26, 13447.00 examples/s]
Generating train split: 77150896 examples [1:12:26, 14829.52 examples/s]
Generating train split: 77152462 examples [1:12:26, 13155.18 examples/s]
Generating train split: 77154747 examples [1:12:26, 15586.00 examples/s]
Generating train split: 77156494 examples [1:12:26, 16060.83 examples/s]
Generating train split: 77158185 examples [1:12:26, 15051.08 examples/s]
Generating train split: 77159763 examples [1:12:27, 12109.17 examples/s]
Generating train split: 77161102 examples [1:12:27, 12112.85 examples/s]
Generating train split: 77162405 examples [1:12:27, 10429.05 examples/s]
Generating train split: 77164323 examples [1:12:27, 12363.44 examples/s]
Generating train split: 77165687 examples [1:12:27, 10243.89 examples/s]
Generating train split: 77173094 examples [1:12:27, 24292.15 examples/s]
Generating train split: 77180080 examples [1:12:27, 34680.02 examples/s]
Generating train split: 77184178 examples [1:12:28, 31543.94 examples/s]
Generating train split: 77187824 examples [1:12:28, 25867.00 examples/s]
Generating train split: 77190892 examples [1:12:28, 19202.80 examples/s]
Generating train split: 77193639 examples [1:12:28, 20667.34 examples/s]
Generating train split: 77196187 examples [1:12:29, 14120.90 examples/s]
Generating train split: 77198191 examples [1:12:29, 12923.83 examples/s]
Generating train split: 77199888 examples [1:12:29, 11739.57 examples/s]
Generating train split: 77201333 examples [1:12:29, 10950.76 examples/s]
Generating train split: 77202621 examples [1:12:29, 11214.37 examples/s]
Generating train split: 77203888 examples [1:12:29, 9021.22 examples/s] 
Generating train split: 77204946 examples [1:12:30, 9095.19 examples/s]
Generating train split: 77206334 examples [1:12:30, 10058.66 examples/s]
Generating train split: 77208201 examples [1:12:30, 11385.22 examples/s]
Generating train split: 77209445 examples [1:12:30, 7993.08 examples/s] 
Generating train split: 77212274 examples [1:12:30, 11447.75 examples/s]
Generating train split: 77213708 examples [1:12:30, 10950.00 examples/s]
Generating train split: 77215003 examples [1:12:31, 10204.02 examples/s]
Generating train split: 77216159 examples [1:12:31, 9124.22 examples/s] 
Generating train split: 77217172 examples [1:12:31, 8642.74 examples/s]
Generating train split: 77218101 examples [1:12:31, 7364.00 examples/s]
Generating train split: 77219152 examples [1:12:31, 7880.96 examples/s]
Generating train split: 77220032 examples [1:12:31, 8061.80 examples/s]
Generating train split: 77221141 examples [1:12:31, 8781.70 examples/s]
Generating train split: 77222072 examples [1:12:31, 8309.24 examples/s]
Generating train split: 77222942 examples [1:12:32, 6803.09 examples/s]
Generating train split: 77225874 examples [1:12:32, 11919.16 examples/s]
Generating train split: 77227279 examples [1:12:32, 12082.18 examples/s]
Generating train split: 77229583 examples [1:12:32, 14853.23 examples/s]
Generating train split: 77231236 examples [1:12:32, 11833.03 examples/s]
Generating train split: 77232619 examples [1:12:32, 11486.37 examples/s]
Generating train split: 77233912 examples [1:12:32, 10568.15 examples/s]
Generating train split: 77235092 examples [1:12:33, 10847.53 examples/s]
Generating train split: 77241267 examples [1:12:33, 23391.89 examples/s]
Generating train split: 77248640 examples [1:12:33, 36493.00 examples/s]
Generating train split: 77252717 examples [1:12:33, 36124.94 examples/s]
Generating train split: 77256630 examples [1:12:33, 20171.69 examples/s]
Generating train split: 77261123 examples [1:12:33, 24485.23 examples/s]
Generating train split: 77269380 examples [1:12:34, 36068.73 examples/s]
Generating train split: 77275431 examples [1:12:34, 41480.27 examples/s]
Generating train split: 77280686 examples [1:12:34, 25446.12 examples/s]
Generating train split: 77284756 examples [1:12:34, 27793.18 examples/s]
Generating train split: 77291783 examples [1:12:34, 35865.02 examples/s]
Generating train split: 77298721 examples [1:12:34, 42647.46 examples/s]
Generating train split: 77304179 examples [1:12:35, 25948.75 examples/s]
Generating train split: 77308377 examples [1:12:35, 22547.24 examples/s]
Generating train split: 77311792 examples [1:12:35, 18145.12 examples/s]
Generating train split: 77314509 examples [1:12:36, 16098.69 examples/s]
Generating train split: 77316734 examples [1:12:36, 15751.51 examples/s]
Generating train split: 77323395 examples [1:12:36, 23816.67 examples/s]
Generating train split: 77331831 examples [1:12:36, 34994.55 examples/s]
Generating train split: 77336737 examples [1:12:36, 26923.09 examples/s]
Generating train split: 77340669 examples [1:12:37, 21746.02 examples/s]
Generating train split: 77343832 examples [1:12:37, 20256.63 examples/s]
Generating train split: 77346525 examples [1:12:37, 21148.06 examples/s]
Generating train split: 77349828 examples [1:12:37, 23368.62 examples/s]
Generating train split: 77352672 examples [1:12:37, 20496.96 examples/s]
Generating train split: 77355115 examples [1:12:37, 16316.26 examples/s]
Generating train split: 77357119 examples [1:12:37, 16588.41 examples/s]
Generating train split: 77365198 examples [1:12:38, 29533.10 examples/s]
Generating train split: 77375089 examples [1:12:38, 45037.31 examples/s]
Generating train split: 77380694 examples [1:12:38, 25482.40 examples/s]
Generating train split: 77384985 examples [1:12:39, 19284.07 examples/s]
Generating train split: 77388316 examples [1:12:39, 16281.96 examples/s]
Generating train split: 77396331 examples [1:12:39, 24392.07 examples/s]
Generating train split: 77404317 examples [1:12:39, 32908.08 examples/s]
Generating train split: 77409688 examples [1:12:39, 24218.95 examples/s]
Generating train split: 77413865 examples [1:12:40, 21780.13 examples/s]
Generating train split: 77417287 examples [1:12:40, 16814.07 examples/s]
Generating train split: 77419946 examples [1:12:40, 15217.22 examples/s]
Generating train split: 77422132 examples [1:12:40, 15171.57 examples/s]
Generating train split: 77424119 examples [1:12:41, 13280.85 examples/s]
Generating train split: 77425771 examples [1:12:41, 13143.55 examples/s]
Generating train split: 77427300 examples [1:12:41, 12173.20 examples/s]
Generating train split: 77429720 examples [1:12:41, 14349.47 examples/s]
Generating train split: 77431399 examples [1:12:41, 13259.06 examples/s]
Generating train split: 77433061 examples [1:12:41, 13952.94 examples/s]
Generating train split: 77435935 examples [1:12:41, 16741.20 examples/s]
Generating train split: 77437756 examples [1:12:42, 14472.90 examples/s]
Generating train split: 77439350 examples [1:12:42, 12516.70 examples/s]
Generating train split: 77440735 examples [1:12:42, 8605.01 examples/s] 
Generating train split: 77442540 examples [1:12:42, 10213.45 examples/s]
Generating train split: 77443933 examples [1:12:42, 10924.30 examples/s]
Generating train split: 77445267 examples [1:12:43, 10464.16 examples/s]
Generating train split: 77446486 examples [1:12:43, 10742.00 examples/s]
Generating train split: 77449238 examples [1:12:43, 14719.04 examples/s]
Generating train split: 77450904 examples [1:12:43, 13227.36 examples/s]
Generating train split: 77453570 examples [1:12:43, 16273.36 examples/s]
Generating train split: 77456285 examples [1:12:43, 19010.62 examples/s]
Generating train split: 77458364 examples [1:12:43, 13689.65 examples/s]
Generating train split: 77460566 examples [1:12:43, 15432.98 examples/s]
Generating train split: 77462750 examples [1:12:44, 16911.61 examples/s]
Generating train split: 77464707 examples [1:12:44, 17023.87 examples/s]
Generating train split: 77469643 examples [1:12:44, 25284.54 examples/s]
Generating train split: 77474136 examples [1:12:44, 30527.52 examples/s]
Generating train split: 77479446 examples [1:12:44, 36765.00 examples/s]
Generating train split: 77484913 examples [1:12:44, 41628.68 examples/s]
Generating train split: 77489261 examples [1:12:44, 39818.48 examples/s]
Generating train split: 77493402 examples [1:12:44, 39571.53 examples/s]
Generating train split: 77499208 examples [1:12:44, 44757.75 examples/s]
Generating train split: 77503802 examples [1:12:45, 24826.81 examples/s]
Generating train split: 77507375 examples [1:12:45, 26814.18 examples/s]
Generating train split: 77510953 examples [1:12:45, 26094.91 examples/s]
Generating train split: 77514179 examples [1:12:45, 15372.60 examples/s]
Generating train split: 77516929 examples [1:12:46, 17072.80 examples/s]
Generating train split: 77519465 examples [1:12:46, 8816.05 examples/s] 
Generating train split: 77521344 examples [1:12:46, 9843.65 examples/s]
Generating train split: 77525022 examples [1:12:47, 13340.72 examples/s]
Generating train split: 77528259 examples [1:12:47, 16315.38 examples/s]
Generating train split: 77531675 examples [1:12:47, 18595.83 examples/s]
Generating train split: 77534339 examples [1:12:47, 10345.75 examples/s]
Generating train split: 77537828 examples [1:12:47, 13459.79 examples/s]
Generating train split: 77541780 examples [1:12:48, 17458.84 examples/s]
Generating train split: 77544676 examples [1:12:48, 11579.06 examples/s]
Generating train split: 77546889 examples [1:12:48, 11681.30 examples/s]
Generating train split: 77549427 examples [1:12:48, 13670.79 examples/s]
Generating train split: 77551893 examples [1:12:48, 15559.67 examples/s]
Generating train split: 77555693 examples [1:12:49, 19551.66 examples/s]
Generating train split: 77558271 examples [1:12:49, 11189.95 examples/s]
Generating train split: 77560231 examples [1:12:49, 11890.44 examples/s]
Generating train split: 77563717 examples [1:12:49, 15630.33 examples/s]
Generating train split: 77566038 examples [1:12:49, 15133.87 examples/s]
Generating train split: 77568079 examples [1:12:50, 14562.85 examples/s]
Generating train split: 77570188 examples [1:12:50, 15844.98 examples/s]
Generating train split: 77572091 examples [1:12:50, 16207.90 examples/s]
Generating train split: 77573945 examples [1:12:50, 16688.12 examples/s]
Generating train split: 77576836 examples [1:12:50, 19743.90 examples/s]
Generating train split: 77578997 examples [1:12:50, 13248.98 examples/s]
Generating train split: 77580818 examples [1:12:50, 14229.75 examples/s]
Generating train split: 77583554 examples [1:12:50, 17111.16 examples/s]
Generating train split: 77585604 examples [1:12:51, 14997.88 examples/s]
Generating train split: 77587801 examples [1:12:51, 16547.37 examples/s]
Generating train split: 77589709 examples [1:12:51, 16459.53 examples/s]
Generating train split: 77592504 examples [1:12:51, 19311.20 examples/s]
Generating train split: 77595329 examples [1:12:51, 21643.39 examples/s]
Generating train split: 77599372 examples [1:12:51, 26433.99 examples/s]
Generating train split: 77602163 examples [1:12:51, 26826.01 examples/s]
Generating train split: 77604949 examples [1:12:51, 20623.13 examples/s]
Generating train split: 77607301 examples [1:12:52, 18388.19 examples/s]
Generating train split: 77609370 examples [1:12:52, 17860.48 examples/s]
Generating train split: 77611310 examples [1:12:52, 18044.94 examples/s]
Generating train split: 77613236 examples [1:12:52, 17964.97 examples/s]
Generating train split: 77615117 examples [1:12:52, 17117.57 examples/s]
Generating train split: 77616884 examples [1:12:53, 9429.13 examples/s] 
Generating train split: 77618247 examples [1:12:53, 7509.74 examples/s]
Generating train split: 77619334 examples [1:12:53, 7419.86 examples/s]
Generating train split: 77620855 examples [1:12:53, 8706.25 examples/s]
Generating train split: 77621991 examples [1:12:53, 8477.20 examples/s]
Generating train split: 77623020 examples [1:12:53, 7542.02 examples/s]
Generating train split: 77624718 examples [1:12:54, 9161.53 examples/s]
Generating train split: 77626366 examples [1:12:54, 10732.49 examples/s]
Generating train split: 77627611 examples [1:12:54, 9286.41 examples/s] 
Generating train split: 77628721 examples [1:12:54, 9324.89 examples/s]
Generating train split: 77629759 examples [1:12:54, 6859.04 examples/s]
Generating train split: 77631005 examples [1:12:54, 7323.35 examples/s]
Generating train split: 77631854 examples [1:12:54, 7287.76 examples/s]
Generating train split: 77632667 examples [1:12:55, 6883.71 examples/s]
Generating train split: 77633409 examples [1:12:55, 5511.67 examples/s]
Generating train split: 77634033 examples [1:12:55, 5431.77 examples/s]
Generating train split: 77634720 examples [1:12:55, 5719.24 examples/s]
Generating train split: 77635879 examples [1:12:55, 7095.80 examples/s]
Generating train split: 77637733 examples [1:12:55, 9823.69 examples/s]
Generating train split: 77638829 examples [1:12:55, 10106.12 examples/s]
Generating train split: 77641074 examples [1:12:55, 13455.47 examples/s]
Generating train split: 77643213 examples [1:12:56, 15671.55 examples/s]
Generating train split: 77644867 examples [1:12:56, 12750.94 examples/s]
Generating train split: 77646282 examples [1:12:56, 9228.93 examples/s] 
Generating train split: 77647441 examples [1:12:56, 6225.29 examples/s]
Generating train split: 77649393 examples [1:12:57, 8271.75 examples/s]
Generating train split: 77650932 examples [1:12:57, 9442.02 examples/s]
Generating train split: 77652988 examples [1:12:57, 11695.69 examples/s]
Generating train split: 77655183 examples [1:12:57, 13997.84 examples/s]
Generating train split: 77656905 examples [1:12:57, 13400.38 examples/s]
Generating train split: 77658475 examples [1:12:57, 12274.03 examples/s]
Generating train split: 77660557 examples [1:12:57, 14196.41 examples/s]
Generating train split: 77662155 examples [1:12:57, 13085.18 examples/s]
Generating train split: 77668562 examples [1:12:57, 25327.98 examples/s]
Generating train split: 77671503 examples [1:12:58, 15846.45 examples/s]
Generating train split: 77673798 examples [1:12:58, 16053.80 examples/s]
Generating train split: 77676823 examples [1:12:58, 16292.76 examples/s]
Generating train split: 77678807 examples [1:12:58, 14534.56 examples/s]
Generating train split: 77681513 examples [1:12:58, 16921.22 examples/s]
Generating train split: 77683534 examples [1:12:59, 13282.72 examples/s]
Generating train split: 77685177 examples [1:12:59, 13059.43 examples/s]
Generating train split: 77686712 examples [1:12:59, 10436.46 examples/s]
Generating train split: 77688087 examples [1:12:59, 11029.08 examples/s]
Generating train split: 77690323 examples [1:12:59, 13362.53 examples/s]
Generating train split: 77692006 examples [1:12:59, 14140.05 examples/s]
Generating train split: 77693612 examples [1:12:59, 14460.38 examples/s]
Generating train split: 77696232 examples [1:13:00, 17376.77 examples/s]
Generating train split: 77698119 examples [1:13:00, 16096.81 examples/s]
Generating train split: 77699843 examples [1:13:00, 15963.99 examples/s]
Generating train split: 77701520 examples [1:13:00, 13251.78 examples/s]
Generating train split: 77702977 examples [1:13:00, 11172.67 examples/s]
Generating train split: 77704221 examples [1:13:00, 11393.58 examples/s]
Generating train split: 77706191 examples [1:13:00, 13340.72 examples/s]
Generating train split: 77707655 examples [1:13:00, 13541.03 examples/s]
Generating train split: 77709096 examples [1:13:01, 13551.39 examples/s]
Generating train split: 77710646 examples [1:13:01, 13265.51 examples/s]
Generating train split: 77712026 examples [1:13:01, 12842.46 examples/s]
Generating train split: 77715004 examples [1:13:01, 17349.11 examples/s]
Generating train split: 77718597 examples [1:13:01, 22477.82 examples/s]
Generating train split: 77725375 examples [1:13:01, 35287.89 examples/s]
Generating train split: 77731762 examples [1:13:01, 40773.09 examples/s]
Generating train split: 77735891 examples [1:13:02, 23924.36 examples/s]
Generating train split: 77739128 examples [1:13:02, 21234.77 examples/s]
Generating train split: 77742431 examples [1:13:02, 23392.10 examples/s]
Generating train split: 77745339 examples [1:13:02, 15208.50 examples/s]
Generating train split: 77747596 examples [1:13:03, 13290.79 examples/s]
Generating train split: 77749451 examples [1:13:03, 13811.81 examples/s]
Generating train split: 77751245 examples [1:13:03, 14340.75 examples/s]
Generating train split: 77753113 examples [1:13:03, 15196.31 examples/s]
Generating train split: 77755071 examples [1:13:03, 16132.82 examples/s]
Generating train split: 77756909 examples [1:13:03, 16359.17 examples/s]
Generating train split: 77758710 examples [1:13:03, 14561.82 examples/s]
Generating train split: 77762664 examples [1:13:03, 20495.38 examples/s]
Generating train split: 77766771 examples [1:13:03, 25693.59 examples/s]
Generating train split: 77769617 examples [1:13:04, 13850.27 examples/s]
Generating train split: 77773146 examples [1:13:04, 17403.48 examples/s]
Generating train split: 77776558 examples [1:13:04, 20542.93 examples/s]
Generating train split: 77779383 examples [1:13:04, 20947.16 examples/s]
Generating train split: 77782018 examples [1:13:05, 14778.39 examples/s]
Generating train split: 77784112 examples [1:13:05, 14698.87 examples/s]
Generating train split: 77787569 examples [1:13:05, 18449.15 examples/s]
Generating train split: 77789934 examples [1:13:05, 16600.02 examples/s]
Generating train split: 77791977 examples [1:13:05, 12844.51 examples/s]
Generating train split: 77796226 examples [1:13:05, 15745.75 examples/s]
Generating train split: 77798851 examples [1:13:06, 17591.86 examples/s]
Generating train split: 77802162 examples [1:13:06, 20769.52 examples/s]
Generating train split: 77804610 examples [1:13:06, 13055.70 examples/s]
Generating train split: 77806510 examples [1:13:06, 10665.22 examples/s]
Generating train split: 77809086 examples [1:13:06, 12939.05 examples/s]
Generating train split: 77811981 examples [1:13:07, 15754.41 examples/s]
Generating train split: 77814138 examples [1:13:07, 13889.98 examples/s]
Generating train split: 77815955 examples [1:13:07, 10684.47 examples/s]
Generating train split: 77818396 examples [1:13:07, 12957.48 examples/s]
Generating train split: 77820149 examples [1:13:08, 7479.83 examples/s] 
Generating train split: 77821471 examples [1:13:08, 7566.74 examples/s]
Generating train split: 77822637 examples [1:13:08, 6498.38 examples/s]
Generating train split: 77824425 examples [1:13:08, 8105.98 examples/s]
Generating train split: 77830626 examples [1:13:08, 17162.51 examples/s]
Generating train split: 77837381 examples [1:13:08, 26915.37 examples/s]
Generating train split: 77843706 examples [1:13:09, 34779.38 examples/s]
Generating train split: 77848342 examples [1:13:09, 17326.75 examples/s]
Generating train split: 77852308 examples [1:13:09, 20334.22 examples/s]
Generating train split: 77857530 examples [1:13:09, 23952.27 examples/s]
Generating train split: 77861193 examples [1:13:10, 20404.57 examples/s]
Generating train split: 77870760 examples [1:13:10, 32846.91 examples/s]
Generating train split: 77875715 examples [1:13:10, 28345.86 examples/s]
Generating train split: 77879798 examples [1:13:10, 28103.08 examples/s]
Generating train split: 77883480 examples [1:13:10, 26200.68 examples/s]
Generating train split: 77886716 examples [1:13:11, 21241.55 examples/s]
Generating train split: 77889363 examples [1:13:11, 16941.81 examples/s]
Generating train split: 77892999 examples [1:13:11, 20057.00 examples/s]
Generating train split: 77895589 examples [1:13:11, 13513.41 examples/s]
Generating train split: 77897598 examples [1:13:12, 12196.60 examples/s]
Generating train split: 77900501 examples [1:13:12, 12987.07 examples/s]
Generating train split: 77902587 examples [1:13:12, 14232.55 examples/s]
Generating train split: 77905175 examples [1:13:12, 16353.76 examples/s]
Generating train split: 77907181 examples [1:13:12, 12978.17 examples/s]
Generating train split: 77908835 examples [1:13:12, 12535.50 examples/s]
Generating train split: 77910326 examples [1:13:12, 11606.02 examples/s]
Generating train split: 77911645 examples [1:13:13, 9895.85 examples/s] 
Generating train split: 77920639 examples [1:13:13, 25172.07 examples/s]
Generating train split: 77924126 examples [1:13:13, 20936.72 examples/s]
Generating train split: 77926998 examples [1:13:13, 18480.91 examples/s]
Generating train split: 77929416 examples [1:13:13, 18814.60 examples/s]
Generating train split: 77931710 examples [1:13:13, 18673.39 examples/s]
Generating train split: 77933866 examples [1:13:14, 16252.77 examples/s]
Generating train split: 77935721 examples [1:13:14, 16454.50 examples/s]
Generating train split: 77937545 examples [1:13:14, 11073.71 examples/s]
Generating train split: 77939327 examples [1:13:14, 11934.37 examples/s]
Generating train split: 77941572 examples [1:13:14, 13910.91 examples/s]
Generating train split: 77943366 examples [1:13:14, 14761.85 examples/s]
Generating train split: 77945091 examples [1:13:15, 14588.11 examples/s]
Generating train split: 77946717 examples [1:13:15, 14197.61 examples/s]
Generating train split: 77948250 examples [1:13:15, 11669.06 examples/s]
Generating train split: 77951713 examples [1:13:15, 16631.16 examples/s]
Generating train split: 77954061 examples [1:13:15, 18243.22 examples/s]
Generating train split: 77956196 examples [1:13:15, 18996.35 examples/s]
Generating train split: 77958269 examples [1:13:15, 16391.25 examples/s]
Generating train split: 77966145 examples [1:13:15, 31511.20 examples/s]
Generating train split: 77974050 examples [1:13:16, 42237.95 examples/s]
Generating train split: 77978674 examples [1:13:16, 26870.47 examples/s]
Generating train split: 77982336 examples [1:13:16, 26481.89 examples/s]
Generating train split: 77988586 examples [1:13:16, 29017.41 examples/s]
Generating train split: 77991948 examples [1:13:16, 23611.26 examples/s]
Generating train split: 77994735 examples [1:13:17, 20997.17 examples/s]
Generating train split: 77997513 examples [1:13:17, 19282.29 examples/s]
Generating train split: 77999640 examples [1:13:17, 18888.51 examples/s]
Generating train split: 78001657 examples [1:13:17, 19093.48 examples/s]
Generating train split: 78003677 examples [1:13:17, 19337.77 examples/s]
Generating train split: 78005694 examples [1:13:17, 13910.01 examples/s]
Generating train split: 78010613 examples [1:13:18, 20874.22 examples/s]
Generating train split: 78014312 examples [1:13:18, 23448.57 examples/s]
Generating train split: 78017078 examples [1:13:18, 15677.24 examples/s]
Generating train split: 78020000 examples [1:13:18, 18008.88 examples/s]
Generating train split: 78023236 examples [1:13:18, 20866.60 examples/s]
Generating train split: 78025880 examples [1:13:18, 21901.31 examples/s]
Generating train split: 78028495 examples [1:13:19, 13830.08 examples/s]
Generating train split: 78030543 examples [1:13:19, 13969.49 examples/s]
Generating train split: 78032403 examples [1:13:19, 10696.55 examples/s]
Generating train split: 78036275 examples [1:13:19, 15188.30 examples/s]
Generating train split: 78038471 examples [1:13:19, 13851.92 examples/s]
Generating train split: 78040339 examples [1:13:20, 12244.39 examples/s]
Generating train split: 78041913 examples [1:13:20, 12351.72 examples/s]
Generating train split: 78044644 examples [1:13:20, 15290.48 examples/s]
Generating train split: 78047652 examples [1:13:20, 17682.39 examples/s]
Generating train split: 78049695 examples [1:13:20, 16159.57 examples/s]
Generating train split: 78051513 examples [1:13:20, 15692.08 examples/s]
Generating train split: 78053983 examples [1:13:20, 17781.21 examples/s]
Generating train split: 78056704 examples [1:13:20, 20120.97 examples/s]
Generating train split: 78058885 examples [1:13:21, 14147.39 examples/s]
Generating train split: 78062195 examples [1:13:21, 18026.93 examples/s]
Generating train split: 78064424 examples [1:13:21, 18518.24 examples/s]
Generating train split: 78071092 examples [1:13:21, 30070.71 examples/s]
Generating train split: 78074601 examples [1:13:21, 23999.78 examples/s]
Generating train split: 78077537 examples [1:13:22, 17723.07 examples/s]
Generating train split: 78079896 examples [1:13:22, 10046.21 examples/s]
Generating train split: 78082199 examples [1:13:22, 11614.71 examples/s]
Generating train split: 78085621 examples [1:13:22, 14931.15 examples/s]
Generating train split: 78090373 examples [1:13:22, 20588.04 examples/s]
Generating train split: 78093464 examples [1:13:23, 11697.94 examples/s]
Generating train split: 78097217 examples [1:13:23, 15000.70 examples/s]
Generating train split: 78099970 examples [1:13:24, 9824.90 examples/s] 
Generating train split: 78102046 examples [1:13:24, 9994.29 examples/s]
Generating train split: 78104400 examples [1:13:24, 11685.82 examples/s]
Generating train split: 78106345 examples [1:13:24, 12806.75 examples/s]
Generating train split: 78109523 examples [1:13:24, 16200.39 examples/s]
Generating train split: 78112816 examples [1:13:24, 16712.67 examples/s]
Generating train split: 78114953 examples [1:13:25, 12163.48 examples/s]
Generating train split: 78116697 examples [1:13:25, 13007.11 examples/s]
Generating train split: 78118574 examples [1:13:25, 14096.39 examples/s]
Generating train split: 78120609 examples [1:13:25, 15420.45 examples/s]
Generating train split: 78123225 examples [1:13:25, 17919.64 examples/s]
Generating train split: 78125482 examples [1:13:25, 18906.23 examples/s]
Generating train split: 78127586 examples [1:13:25, 14218.21 examples/s]
Generating train split: 78129330 examples [1:13:26, 14743.28 examples/s]
Generating train split: 78131830 examples [1:13:26, 17125.18 examples/s]
Generating train split: 78133780 examples [1:13:26, 17314.96 examples/s]
Generating train split: 78136777 examples [1:13:26, 20071.12 examples/s]
Generating train split: 78138992 examples [1:13:26, 20473.43 examples/s]
Generating train split: 78141143 examples [1:13:26, 15025.26 examples/s]
Generating train split: 78143753 examples [1:13:26, 17454.59 examples/s]
Generating train split: 78150711 examples [1:13:26, 29915.99 examples/s]
Generating train split: 78154229 examples [1:13:27, 18012.37 examples/s]
Generating train split: 78158255 examples [1:13:27, 21866.05 examples/s]
Generating train split: 78161382 examples [1:13:27, 23541.17 examples/s]
Generating train split: 78165107 examples [1:13:27, 26542.79 examples/s]
Generating train split: 78168391 examples [1:13:28, 13856.08 examples/s]
Generating train split: 78172067 examples [1:13:28, 17121.65 examples/s]
Generating train split: 78175216 examples [1:13:28, 19556.01 examples/s]
Generating train split: 78178236 examples [1:13:28, 20416.48 examples/s]
Generating train split: 78180975 examples [1:13:28, 14811.79 examples/s]
Generating train split: 78183145 examples [1:13:29, 11919.32 examples/s]
Generating train split: 78186079 examples [1:13:29, 14565.09 examples/s]
Generating train split: 78188952 examples [1:13:29, 15548.41 examples/s]
Generating train split: 78190973 examples [1:13:29, 12176.90 examples/s]
Generating train split: 78192809 examples [1:13:29, 13202.26 examples/s]
Generating train split: 78197285 examples [1:13:29, 19253.29 examples/s]
Generating train split: 78199814 examples [1:13:30, 16547.34 examples/s]
Generating train split: 78203043 examples [1:13:30, 19147.33 examples/s]
Generating train split: 78205391 examples [1:13:30, 10561.02 examples/s]
Generating train split: 78208970 examples [1:13:30, 14084.66 examples/s]
Generating train split: 78212840 examples [1:13:30, 18174.32 examples/s]
Generating train split: 78215892 examples [1:13:30, 20537.78 examples/s]
Generating train split: 78218758 examples [1:13:31, 13446.09 examples/s]
Generating train split: 78222507 examples [1:13:31, 17205.12 examples/s]
Generating train split: 78225707 examples [1:13:31, 14881.74 examples/s]
Generating train split: 78227920 examples [1:13:31, 13665.24 examples/s]
Generating train split: 78230221 examples [1:13:32, 15205.71 examples/s]
Generating train split: 78232221 examples [1:13:32, 15492.25 examples/s]
Generating train split: 78234666 examples [1:13:32, 17344.67 examples/s]
Generating train split: 78238320 examples [1:13:32, 21734.14 examples/s]
Generating train split: 78242047 examples [1:13:32, 22002.83 examples/s]
Generating train split: 78244499 examples [1:13:32, 15932.03 examples/s]
Generating train split: 78247985 examples [1:13:32, 19473.06 examples/s]
Generating train split: 78251829 examples [1:13:33, 23507.48 examples/s]
Generating train split: 78254674 examples [1:13:33, 17678.14 examples/s]
Generating train split: 78256989 examples [1:13:33, 15088.48 examples/s]
Generating train split: 78260644 examples [1:13:33, 18960.62 examples/s]
Generating train split: 78263091 examples [1:13:33, 13131.73 examples/s]
Generating train split: 78265861 examples [1:13:34, 15374.62 examples/s]
Generating train split: 78267998 examples [1:13:34, 13310.67 examples/s]
Generating train split: 78269778 examples [1:13:34, 12945.11 examples/s]
Generating train split: 78271385 examples [1:13:34, 11964.11 examples/s]
Generating train split: 78274088 examples [1:13:34, 14837.71 examples/s]
Generating train split: 78276391 examples [1:13:34, 16452.80 examples/s]
Generating train split: 78279385 examples [1:13:34, 19541.58 examples/s]
Generating train split: 78281613 examples [1:13:35, 14524.84 examples/s]
Generating train split: 78283439 examples [1:13:35, 14899.84 examples/s]
Generating train split: 78286231 examples [1:13:35, 17761.40 examples/s]
Generating train split: 78288299 examples [1:13:35, 15709.21 examples/s]
Generating train split: 78290106 examples [1:13:35, 13005.72 examples/s]
Generating train split: 78292434 examples [1:13:35, 14644.31 examples/s]
Generating train split: 78295385 examples [1:13:36, 17930.40 examples/s]
Generating train split: 78301092 examples [1:13:36, 27319.06 examples/s]
Generating train split: 78308949 examples [1:13:36, 40394.09 examples/s]
Generating train split: 78313517 examples [1:13:36, 34220.19 examples/s]
Generating train split: 78317473 examples [1:13:36, 31972.19 examples/s]
Generating train split: 78321045 examples [1:13:36, 20172.19 examples/s]
Generating train split: 78324821 examples [1:13:37, 23157.31 examples/s]
Generating train split: 78327904 examples [1:13:37, 24030.83 examples/s]
Generating train split: 78330902 examples [1:13:37, 16212.56 examples/s]
Generating train split: 78333238 examples [1:13:37, 12895.28 examples/s]
Generating train split: 78336593 examples [1:13:37, 15949.24 examples/s]
Generating train split: 78340687 examples [1:13:38, 20306.36 examples/s]
Generating train split: 78343527 examples [1:13:38, 11610.48 examples/s]
Generating train split: 78345676 examples [1:13:38, 12539.60 examples/s]
Generating train split: 78348258 examples [1:13:38, 14492.63 examples/s]
Generating train split: 78350799 examples [1:13:38, 16451.06 examples/s]
Generating train split: 78353119 examples [1:13:39, 12996.05 examples/s]
Generating train split: 78355558 examples [1:13:39, 10723.20 examples/s]
Generating train split: 78357078 examples [1:13:39, 9194.95 examples/s] 
Generating train split: 78358323 examples [1:13:39, 9392.68 examples/s]
Generating train split: 78361612 examples [1:13:39, 13405.37 examples/s]
Generating train split: 78363422 examples [1:13:40, 11029.82 examples/s]
Generating train split: 78367139 examples [1:13:40, 15483.44 examples/s]
Generating train split: 78369222 examples [1:13:40, 9151.40 examples/s] 
Generating train split: 78371435 examples [1:13:40, 10923.13 examples/s]
Generating train split: 78374839 examples [1:13:41, 14691.23 examples/s]
Generating train split: 78377943 examples [1:13:41, 17778.80 examples/s]
Generating train split: 78380464 examples [1:13:41, 18456.86 examples/s]
Generating train split: 78382837 examples [1:13:41, 12679.23 examples/s]
Generating train split: 78384711 examples [1:13:41, 13668.35 examples/s]
Generating train split: 78388835 examples [1:13:41, 19061.27 examples/s]
Generating train split: 78392397 examples [1:13:41, 21552.27 examples/s]
Generating train split: 78395034 examples [1:13:42, 12693.32 examples/s]
Generating train split: 78397767 examples [1:13:42, 14951.87 examples/s]
Generating train split: 78400000 examples [1:13:42, 13690.24 examples/s]
Generating train split: 78401898 examples [1:13:42, 13374.39 examples/s]
Generating train split: 78404735 examples [1:13:42, 16207.64 examples/s]
Generating train split: 78407026 examples [1:13:43, 17482.99 examples/s]
Generating train split: 78409115 examples [1:13:43, 17484.15 examples/s]
Generating train split: 78411102 examples [1:13:43, 15194.70 examples/s]
Generating train split: 78412826 examples [1:13:43, 13481.14 examples/s]
Generating train split: 78415358 examples [1:13:43, 15956.27 examples/s]
Generating train split: 78418350 examples [1:13:43, 19231.86 examples/s]
Generating train split: 78420515 examples [1:13:43, 14047.65 examples/s]
Generating train split: 78422272 examples [1:13:44, 13193.62 examples/s]
Generating train split: 78423839 examples [1:13:44, 11437.74 examples/s]
Generating train split: 78425173 examples [1:13:44, 11629.64 examples/s]
Generating train split: 78426480 examples [1:13:44, 10822.98 examples/s]
Generating train split: 78429210 examples [1:13:44, 14434.38 examples/s]
Generating train split: 78430853 examples [1:13:44, 11434.08 examples/s]
Generating train split: 78432294 examples [1:13:45, 12047.88 examples/s]
Generating train split: 78433803 examples [1:13:45, 12732.80 examples/s]
Generating train split: 78435924 examples [1:13:45, 14804.18 examples/s]
Generating train split: 78437624 examples [1:13:45, 15371.88 examples/s]
Generating train split: 78441902 examples [1:13:45, 22698.60 examples/s]
Generating train split: 78445831 examples [1:13:45, 27292.59 examples/s]
Generating train split: 78450479 examples [1:13:45, 32732.05 examples/s]
Generating train split: 78453960 examples [1:13:45, 33196.14 examples/s]
Generating train split: 78457387 examples [1:13:45, 22959.45 examples/s]
Generating train split: 78460947 examples [1:13:46, 25722.13 examples/s]
Generating train split: 78465729 examples [1:13:46, 31027.74 examples/s]
Generating train split: 78469289 examples [1:13:46, 24658.62 examples/s]
Generating train split: 78472255 examples [1:13:46, 17951.20 examples/s]
Generating train split: 78476419 examples [1:13:46, 22181.37 examples/s]
Generating train split: 78479331 examples [1:13:46, 22180.16 examples/s]
Generating train split: 78482657 examples [1:13:47, 24549.47 examples/s]
Generating train split: 78485555 examples [1:13:47, 16612.57 examples/s]
Generating train split: 78487841 examples [1:13:47, 12488.01 examples/s]
Generating train split: 78489657 examples [1:13:47, 13180.25 examples/s]
Generating train split: 78491422 examples [1:13:48, 11321.81 examples/s]
Generating train split: 78492892 examples [1:13:48, 9144.70 examples/s] 
Generating train split: 78494087 examples [1:13:48, 9413.00 examples/s]
Generating train split: 78495731 examples [1:13:48, 10665.79 examples/s]
Generating train split: 78497393 examples [1:13:48, 11844.75 examples/s]
Generating train split: 78500203 examples [1:13:48, 15513.55 examples/s]
Generating train split: 78503364 examples [1:13:48, 18621.29 examples/s]
Generating train split: 78505448 examples [1:13:49, 15549.16 examples/s]
Generating train split: 78507241 examples [1:13:49, 10901.28 examples/s]
Generating train split: 78508667 examples [1:13:49, 10697.50 examples/s]
Generating train split: 78509967 examples [1:13:49, 9588.68 examples/s] 
Generating train split: 78511085 examples [1:13:49, 9118.14 examples/s]
Generating train split: 78513206 examples [1:13:49, 11540.81 examples/s]
Generating train split: 78515715 examples [1:13:50, 14448.90 examples/s]
Generating train split: 78517395 examples [1:13:50, 12313.69 examples/s]
Generating train split: 78519266 examples [1:13:50, 13692.04 examples/s]
Generating train split: 78520826 examples [1:13:50, 13877.01 examples/s]
Generating train split: 78522350 examples [1:13:50, 11721.75 examples/s]
Generating train split: 78523672 examples [1:13:50, 11067.49 examples/s]
Generating train split: 78525262 examples [1:13:50, 12097.87 examples/s]
Generating train split: 78526574 examples [1:13:50, 11208.48 examples/s]
Generating train split: 78527778 examples [1:13:51, 11032.72 examples/s]
Generating train split: 78529215 examples [1:13:51, 11817.03 examples/s]
Generating train split: 78530448 examples [1:13:51, 9637.41 examples/s] 
Generating train split: 78532695 examples [1:13:51, 12605.19 examples/s]
Generating train split: 78534110 examples [1:13:51, 10499.84 examples/s]
Generating train split: 78535465 examples [1:13:51, 10841.56 examples/s]
Generating train split: 78536673 examples [1:13:51, 9056.17 examples/s] 
Generating train split: 78538613 examples [1:13:52, 11278.56 examples/s]
Generating train split: 78540194 examples [1:13:52, 12099.28 examples/s]
Generating train split: 78542930 examples [1:13:52, 15439.79 examples/s]
Generating train split: 78544618 examples [1:13:52, 14185.07 examples/s]
Generating train split: 78546419 examples [1:13:52, 15045.80 examples/s]
Generating train split: 78548018 examples [1:13:52, 14901.40 examples/s]
Generating train split: 78549660 examples [1:13:52, 15139.75 examples/s]
Generating train split: 78551226 examples [1:13:52, 14539.51 examples/s]
Generating train split: 78555601 examples [1:13:52, 22357.42 examples/s]
Generating train split: 78559738 examples [1:13:53, 27638.08 examples/s]
Generating train split: 78563692 examples [1:13:53, 30825.55 examples/s]
Generating train split: 78566868 examples [1:13:53, 26329.75 examples/s]
Generating train split: 78569675 examples [1:13:53, 22220.90 examples/s]
Generating train split: 78572120 examples [1:13:53, 18512.96 examples/s]
Generating train split: 78574199 examples [1:13:53, 16773.41 examples/s]
Generating train split: 78582152 examples [1:13:54, 30110.04 examples/s]
Generating train split: 78590390 examples [1:13:54, 42276.89 examples/s]
Generating train split: 78595442 examples [1:13:54, 23848.41 examples/s]
Generating train split: 78599315 examples [1:13:54, 22910.19 examples/s]
Generating train split: 78602645 examples [1:13:54, 20709.36 examples/s]
Generating train split: 78605436 examples [1:13:55, 18588.95 examples/s]
Generating train split: 78607802 examples [1:13:55, 17908.51 examples/s]
Generating train split: 78609925 examples [1:13:55, 16039.62 examples/s]
Generating train split: 78611758 examples [1:13:55, 14518.15 examples/s]
Generating train split: 78613652 examples [1:13:55, 15346.72 examples/s]
Generating train split: 78616334 examples [1:13:55, 17727.59 examples/s]
Generating train split: 78618317 examples [1:13:56, 13239.96 examples/s]
Generating train split: 78619932 examples [1:13:56, 13288.51 examples/s]
Generating train split: 78621466 examples [1:13:56, 12073.22 examples/s]
Generating train split: 78622824 examples [1:13:56, 11997.63 examples/s]
Generating train split: 78624135 examples [1:13:56, 10578.31 examples/s]
Generating train split: 78627060 examples [1:13:56, 14462.34 examples/s]
Generating train split: 78628798 examples [1:13:56, 15115.62 examples/s]
Generating train split: 78630469 examples [1:13:57, 12668.37 examples/s]
Generating train split: 78631906 examples [1:13:57, 10665.33 examples/s]
Generating train split: 78633607 examples [1:13:57, 11985.55 examples/s]
Generating train split: 78634976 examples [1:13:57, 11896.95 examples/s]
Generating train split: 78636286 examples [1:13:57, 10290.72 examples/s]
Generating train split: 78637428 examples [1:13:57, 7678.23 examples/s] 
Generating train split: 78638356 examples [1:13:58, 7969.60 examples/s]
Generating train split: 78640488 examples [1:13:58, 10806.08 examples/s]
Generating train split: 78641785 examples [1:13:58, 9985.20 examples/s] 
Generating train split: 78642935 examples [1:13:58, 10167.39 examples/s]
Generating train split: 78644724 examples [1:13:58, 12020.37 examples/s]
Generating train split: 78646049 examples [1:13:58, 10455.39 examples/s]
Generating train split: 78647221 examples [1:13:58, 8977.68 examples/s] 
Generating train split: 78649051 examples [1:13:58, 10799.69 examples/s]
Generating train split: 78650263 examples [1:13:59, 10850.51 examples/s]
Generating train split: 78651509 examples [1:13:59, 11244.25 examples/s]
Generating train split: 78653327 examples [1:13:59, 13049.88 examples/s]
Generating train split: 78654712 examples [1:13:59, 11477.81 examples/s]
Generating train split: 78655953 examples [1:13:59, 11368.05 examples/s]
Generating train split: 78657150 examples [1:13:59, 11213.61 examples/s]
Generating train split: 78658312 examples [1:13:59, 10537.40 examples/s]
Generating train split: 78659521 examples [1:13:59, 10894.51 examples/s]
Generating train split: 78660638 examples [1:14:00, 10341.54 examples/s]
Generating train split: 78661695 examples [1:14:00, 8674.38 examples/s] 
Generating train split: 78662621 examples [1:14:00, 8785.29 examples/s]
Generating train split: 78663678 examples [1:14:00, 9217.81 examples/s]
Generating train split: 78664744 examples [1:14:00, 9359.16 examples/s]
Generating train split: 78665875 examples [1:14:00, 9832.40 examples/s]
Generating train split: 78666890 examples [1:14:00, 8860.82 examples/s]
Generating train split: 78670064 examples [1:14:00, 14848.14 examples/s]
Generating train split: 78674120 examples [1:14:00, 21840.24 examples/s]
Generating train split: 78679218 examples [1:14:01, 29783.49 examples/s]
Generating train split: 78682343 examples [1:14:01, 17850.52 examples/s]
Generating train split: 78689255 examples [1:14:01, 27769.89 examples/s]
Generating train split: 78697111 examples [1:14:01, 38763.21 examples/s]
Generating train split: 78702131 examples [1:14:01, 37819.19 examples/s]
Generating train split: 78706710 examples [1:14:01, 33071.28 examples/s]
Generating train split: 78710663 examples [1:14:02, 23146.59 examples/s]
Generating train split: 78713799 examples [1:14:02, 16292.31 examples/s]
Generating train split: 78716234 examples [1:14:02, 15913.72 examples/s]
Generating train split: 78718866 examples [1:14:02, 17527.66 examples/s]
Generating train split: 78724216 examples [1:14:03, 24060.64 examples/s]
Generating train split: 78728375 examples [1:14:03, 27231.14 examples/s]
Generating train split: 78731777 examples [1:14:03, 22829.51 examples/s]
Generating train split: 78734640 examples [1:14:03, 23402.59 examples/s]
Generating train split: 78737462 examples [1:14:03, 24456.49 examples/s]
Generating train split: 78740239 examples [1:14:03, 25024.84 examples/s]
Generating train split: 78742988 examples [1:14:04, 15155.34 examples/s]
Generating train split: 78745134 examples [1:14:04, 15247.94 examples/s]
Generating train split: 78747104 examples [1:14:04, 15153.27 examples/s]
Generating train split: 78748942 examples [1:14:04, 13617.61 examples/s]
Generating train split: 78750540 examples [1:14:04, 13850.47 examples/s]
Generating train split: 78752541 examples [1:14:04, 15194.61 examples/s]
Generating train split: 78754330 examples [1:14:04, 15794.22 examples/s]
Generating train split: 78756045 examples [1:14:04, 13806.45 examples/s]
Generating train split: 78759049 examples [1:14:05, 17366.76 examples/s]
Generating train split: 78761105 examples [1:14:05, 18158.92 examples/s]
Generating train split: 78763062 examples [1:14:05, 18509.86 examples/s]
Generating train split: 78765008 examples [1:14:05, 16643.79 examples/s]
Generating train split: 78766770 examples [1:14:05, 14040.38 examples/s]
Generating train split: 78768299 examples [1:14:05, 12392.18 examples/s]
Generating train split: 78770898 examples [1:14:05, 15435.86 examples/s]
Generating train split: 78772628 examples [1:14:05, 15570.60 examples/s]
Generating train split: 78775406 examples [1:14:06, 18011.61 examples/s]
Generating train split: 78777320 examples [1:14:06, 16078.23 examples/s]
Generating train split: 78779040 examples [1:14:06, 11709.52 examples/s]
Generating train split: 78781691 examples [1:14:06, 14607.93 examples/s]
Generating train split: 78784535 examples [1:14:06, 17588.32 examples/s]
Generating train split: 78786972 examples [1:14:06, 18502.17 examples/s]
Generating train split: 78791306 examples [1:14:06, 24651.25 examples/s]
Generating train split: 78794057 examples [1:14:07, 14362.08 examples/s]
Generating train split: 78796199 examples [1:14:07, 13262.41 examples/s]
Generating train split: 78798728 examples [1:14:07, 15365.13 examples/s]
Generating train split: 78802425 examples [1:14:07, 19675.11 examples/s]
Generating train split: 78804961 examples [1:14:07, 20879.48 examples/s]
Generating train split: 78807486 examples [1:14:08, 17171.63 examples/s]
Generating train split: 78809605 examples [1:14:08, 16912.45 examples/s]
Generating train split: 78811580 examples [1:14:08, 17133.58 examples/s]
Generating train split: 78814322 examples [1:14:08, 19558.86 examples/s]
Generating train split: 78816491 examples [1:14:08, 18461.09 examples/s]
Generating train split: 78819156 examples [1:14:08, 20100.31 examples/s]
Generating train split: 78821910 examples [1:14:08, 22018.42 examples/s]
Generating train split: 78824246 examples [1:14:08, 19011.24 examples/s]
Generating train split: 78826300 examples [1:14:08, 19382.62 examples/s]
Generating train split: 78828417 examples [1:14:09, 19816.12 examples/s]
Generating train split: 78830486 examples [1:14:09, 16683.03 examples/s]
Generating train split: 78832835 examples [1:14:09, 18245.14 examples/s]
Generating train split: 78834834 examples [1:14:09, 18601.36 examples/s]
Generating train split: 78837000 examples [1:14:09, 19399.73 examples/s]
Generating train split: 78840385 examples [1:14:09, 23370.69 examples/s]
Generating train split: 78842815 examples [1:14:09, 19973.54 examples/s]
Generating train split: 78844958 examples [1:14:09, 19679.26 examples/s]
Generating train split: 78847089 examples [1:14:10, 19781.47 examples/s]
Generating train split: 78849148 examples [1:14:10, 19813.37 examples/s]
Generating train split: 78851186 examples [1:14:10, 15149.69 examples/s]
Generating train split: 78853446 examples [1:14:10, 16787.10 examples/s]
Generating train split: 78855315 examples [1:14:10, 16663.90 examples/s]
Generating train split: 78857719 examples [1:14:10, 18474.15 examples/s]
Generating train split: 78859692 examples [1:14:10, 16860.15 examples/s]
Generating train split: 78861485 examples [1:14:10, 15303.34 examples/s]
Generating train split: 78863103 examples [1:14:11, 13715.87 examples/s]
Generating train split: 78864562 examples [1:14:11, 13747.39 examples/s]
Generating train split: 78866052 examples [1:14:11, 14032.61 examples/s]
Generating train split: 78868531 examples [1:14:11, 16840.25 examples/s]
Generating train split: 78870285 examples [1:14:11, 16339.13 examples/s]
Generating train split: 78879276 examples [1:14:11, 36347.76 examples/s]
Generating train split: 78887756 examples [1:14:11, 48093.10 examples/s]
Generating train split: 78892715 examples [1:14:12, 26259.89 examples/s]
Generating train split: 78896554 examples [1:14:12, 25477.22 examples/s]
Generating train split: 78899939 examples [1:14:12, 24761.54 examples/s]
Generating train split: 78902995 examples [1:14:12, 21618.02 examples/s]
Generating train split: 78905589 examples [1:14:12, 17447.32 examples/s]
Generating train split: 78907712 examples [1:14:13, 16625.99 examples/s]
Generating train split: 78909620 examples [1:14:13, 16703.49 examples/s]
Generating train split: 78911944 examples [1:14:13, 18041.07 examples/s]
Generating train split: 78913941 examples [1:14:13, 18329.90 examples/s]
Generating train split: 78915919 examples [1:14:13, 18525.33 examples/s]
Generating train split: 78917884 examples [1:14:13, 16160.65 examples/s]
Generating train split: 78919814 examples [1:14:13, 16903.52 examples/s]
Generating train split: 78921985 examples [1:14:13, 18119.26 examples/s]
Generating train split: 78924210 examples [1:14:13, 19210.34 examples/s]
Generating train split: 78926215 examples [1:14:14, 19417.13 examples/s]
Generating train split: 78928223 examples [1:14:14, 15774.58 examples/s]
Generating train split: 78929950 examples [1:14:14, 12522.49 examples/s]
Generating train split: 78931403 examples [1:14:14, 11753.24 examples/s]
Generating train split: 78934647 examples [1:14:14, 15782.25 examples/s]
Generating train split: 78936433 examples [1:14:14, 15952.16 examples/s]
Generating train split: 78938783 examples [1:14:14, 17799.43 examples/s]
Generating train split: 78941058 examples [1:14:15, 19052.40 examples/s]
Generating train split: 78943085 examples [1:14:15, 12718.54 examples/s]
Generating train split: 78944769 examples [1:14:15, 13548.42 examples/s]
Generating train split: 78946418 examples [1:14:15, 9945.26 examples/s] 
Generating train split: 78949842 examples [1:14:15, 14352.08 examples/s]
Generating train split: 78951780 examples [1:14:16, 11627.46 examples/s]
Generating train split: 78953364 examples [1:14:16, 11399.29 examples/s]
Generating train split: 78954793 examples [1:14:16, 9216.30 examples/s] 
Generating train split: 78955969 examples [1:14:16, 9500.21 examples/s]
Generating train split: 78957224 examples [1:14:16, 10101.58 examples/s]
Generating train split: 78958432 examples [1:14:16, 10531.14 examples/s]
Generating train split: 78959928 examples [1:14:16, 11505.57 examples/s]
Generating train split: 78961648 examples [1:14:16, 12926.92 examples/s]
Generating train split: 78964122 examples [1:14:17, 15972.34 examples/s]
Generating train split: 78966884 examples [1:14:17, 18970.74 examples/s]
Generating train split: 78968885 examples [1:14:17, 15843.64 examples/s]
Generating train split: 78970816 examples [1:14:17, 16631.55 examples/s]
Generating train split: 78972604 examples [1:14:17, 12490.50 examples/s]
Generating train split: 78975220 examples [1:14:17, 15427.20 examples/s]
Generating train split: 78977301 examples [1:14:17, 16679.44 examples/s]
Generating train split: 78979208 examples [1:14:18, 17209.86 examples/s]
Generating train split: 78981098 examples [1:14:18, 15868.25 examples/s]
Generating train split: 78982823 examples [1:14:18, 14209.63 examples/s]
Generating train split: 78986073 examples [1:14:18, 18591.38 examples/s]
Generating train split: 78989877 examples [1:14:18, 23553.64 examples/s]
Generating train split: 78992455 examples [1:14:18, 15213.07 examples/s]
Generating train split: 78995059 examples [1:14:18, 17309.63 examples/s]
Generating train split: 78997795 examples [1:14:19, 19484.33 examples/s]
Generating train split: 79000325 examples [1:14:19, 20778.73 examples/s]
Generating train split: 79003189 examples [1:14:19, 22756.32 examples/s]
Generating train split: 79005741 examples [1:14:19, 17319.97 examples/s]
Generating train split: 79007853 examples [1:14:19, 16711.20 examples/s]
Generating train split: 79009782 examples [1:14:19, 16804.19 examples/s]
Generating train split: 79011651 examples [1:14:19, 15097.36 examples/s]
Generating train split: 79013690 examples [1:14:19, 16217.13 examples/s]
Generating train split: 79016289 examples [1:14:20, 18565.86 examples/s]
Generating train split: 79018297 examples [1:14:20, 16014.14 examples/s]
Generating train split: 79020595 examples [1:14:20, 17666.04 examples/s]
Generating train split: 79022528 examples [1:14:20, 16621.26 examples/s]
Generating train split: 79024311 examples [1:14:20, 14027.52 examples/s]
Generating train split: 79025845 examples [1:14:20, 13095.63 examples/s]
Generating train split: 79027964 examples [1:14:20, 14821.13 examples/s]
Generating train split: 79029565 examples [1:14:21, 13721.61 examples/s]
Generating train split: 79031020 examples [1:14:21, 11933.70 examples/s]
Generating train split: 79032830 examples [1:14:21, 13325.94 examples/s]
Generating train split: 79034266 examples [1:14:21, 12407.58 examples/s]
Generating train split: 79036530 examples [1:14:21, 14885.91 examples/s]
Generating train split: 79038140 examples [1:14:21, 10770.30 examples/s]
Generating train split: 79039456 examples [1:14:21, 11075.55 examples/s]
Generating train split: 79040752 examples [1:14:22, 6926.62 examples/s] 
Generating train split: 79041757 examples [1:14:22, 6439.28 examples/s]
Generating train split: 79042620 examples [1:14:22, 5019.98 examples/s]
Generating train split: 79044657 examples [1:14:22, 7317.31 examples/s]
Generating train split: 79045759 examples [1:14:23, 5897.54 examples/s]
Generating train split: 79046898 examples [1:14:23, 6754.70 examples/s]
Generating train split: 79047919 examples [1:14:23, 7367.22 examples/s]
Generating train split: 79049162 examples [1:14:23, 8406.07 examples/s]
Generating train split: 79050212 examples [1:14:23, 5767.34 examples/s]
Generating train split: 79051039 examples [1:14:24, 5667.03 examples/s]
Generating train split: 79051779 examples [1:14:24, 5352.05 examples/s]
Generating train split: 79052965 examples [1:14:24, 6478.18 examples/s]
Generating train split: 79053755 examples [1:14:24, 5348.85 examples/s]
Generating train split: 79055085 examples [1:14:24, 6867.80 examples/s]
Generating train split: 79056890 examples [1:14:24, 9272.16 examples/s]
Generating train split: 79058030 examples [1:14:24, 8010.28 examples/s]
Generating train split: 79059685 examples [1:14:25, 9681.53 examples/s]
Generating train split: 79060827 examples [1:14:25, 7060.28 examples/s]
Generating train split: 79062068 examples [1:14:25, 8061.91 examples/s]
Generating train split: 79063088 examples [1:14:25, 6696.50 examples/s]
Generating train split: 79063943 examples [1:14:25, 6586.64 examples/s]
Generating train split: 79065800 examples [1:14:25, 8918.71 examples/s]
Generating train split: 79066871 examples [1:14:26, 8149.39 examples/s]
Generating train split: 79067816 examples [1:14:26, 7904.37 examples/s]
Generating train split: 79068714 examples [1:14:26, 7987.78 examples/s]
Generating train split: 79069590 examples [1:14:26, 5466.34 examples/s]
Generating train split: 79071507 examples [1:14:26, 8027.01 examples/s]
Generating train split: 79072576 examples [1:14:26, 7783.18 examples/s]
Generating train split: 79073928 examples [1:14:26, 8998.36 examples/s]
Generating train split: 79075006 examples [1:14:27, 7900.55 examples/s]
Generating train split: 79077628 examples [1:14:27, 11864.28 examples/s]
Generating train split: 79079058 examples [1:14:27, 9632.65 examples/s] 
Generating train split: 79080745 examples [1:14:27, 11120.05 examples/s]
Generating train split: 79082079 examples [1:14:27, 9839.54 examples/s] 
Generating train split: 79083241 examples [1:14:28, 7372.73 examples/s]
Generating train split: 79084176 examples [1:14:28, 6644.77 examples/s]
Generating train split: 79086775 examples [1:14:28, 10182.83 examples/s]
Generating train split: 79088125 examples [1:14:28, 7427.09 examples/s] 
Generating train split: 79089949 examples [1:14:28, 9082.57 examples/s]
Generating train split: 79091196 examples [1:14:28, 9292.34 examples/s]
Generating train split: 79092375 examples [1:14:29, 6660.05 examples/s]
Generating train split: 79093940 examples [1:14:29, 8158.43 examples/s]
Generating train split: 79095140 examples [1:14:29, 8895.43 examples/s]
Generating train split: 79096281 examples [1:14:29, 8324.09 examples/s]
Generating train split: 79098279 examples [1:14:29, 10740.23 examples/s]
Generating train split: 79099578 examples [1:14:29, 10186.92 examples/s]
Generating train split: 79101672 examples [1:14:29, 12561.11 examples/s]
Generating train split: 79104112 examples [1:14:30, 15448.08 examples/s]
Generating train split: 79105844 examples [1:14:30, 9081.49 examples/s] 
Generating train split: 79111537 examples [1:14:30, 17440.32 examples/s]
Generating train split: 79118278 examples [1:14:30, 27416.63 examples/s]
Generating train split: 79123921 examples [1:14:30, 33844.11 examples/s]
Generating train split: 79128331 examples [1:14:31, 24249.02 examples/s]
Generating train split: 79131855 examples [1:14:31, 12713.18 examples/s]
Generating train split: 79134484 examples [1:14:32, 9164.36 examples/s] 
Generating train split: 79136461 examples [1:14:32, 9162.28 examples/s]
Generating train split: 79138112 examples [1:14:32, 8957.18 examples/s]
Generating train split: 79139654 examples [1:14:32, 9739.64 examples/s]
Generating train split: 79141097 examples [1:14:32, 9420.16 examples/s]
Generating train split: 79142358 examples [1:14:33, 8079.16 examples/s]
Generating train split: 79143395 examples [1:14:33, 7868.42 examples/s]
Generating train split: 79144342 examples [1:14:33, 7181.06 examples/s]
Generating train split: 79145230 examples [1:14:33, 7483.80 examples/s]
Generating train split: 79146076 examples [1:14:33, 6567.31 examples/s]
Generating train split: 79147294 examples [1:14:33, 7599.35 examples/s]
Generating train split: 79148149 examples [1:14:34, 7167.62 examples/s]
Generating train split: 79149528 examples [1:14:34, 8648.29 examples/s]
Generating train split: 79150496 examples [1:14:35, 3031.83 examples/s]
Generating train split: 79151645 examples [1:14:35, 3922.51 examples/s]
Generating train split: 79153185 examples [1:14:35, 5419.27 examples/s]
Generating train split: 79154230 examples [1:14:35, 5995.12 examples/s]
Generating train split: 79155271 examples [1:14:35, 6781.87 examples/s]
Generating train split: 79156282 examples [1:14:35, 5428.75 examples/s]
Generating train split: 79157092 examples [1:14:36, 4803.53 examples/s]
Generating train split: 79158350 examples [1:14:36, 6093.03 examples/s]
Generating train split: 79160116 examples [1:14:36, 8325.52 examples/s]
Generating train split: 79161232 examples [1:14:36, 4841.61 examples/s]
Generating train split: 79163485 examples [1:14:36, 7171.85 examples/s]
Generating train split: 79164645 examples [1:14:37, 6640.27 examples/s]
Generating train split: 79165619 examples [1:14:37, 4710.92 examples/s]
Generating train split: 79166375 examples [1:14:37, 4066.24 examples/s]
Generating train split: 79166984 examples [1:14:37, 4143.45 examples/s]
Generating train split: 79167546 examples [1:14:38, 3762.03 examples/s]
Generating train split: 79168352 examples [1:14:38, 4440.16 examples/s]
Generating train split: 79168927 examples [1:14:38, 4484.17 examples/s]
Generating train split: 79169732 examples [1:14:38, 5192.67 examples/s]
Generating train split: 79170352 examples [1:14:38, 4511.80 examples/s]
Generating train split: 79171834 examples [1:14:38, 6649.13 examples/s]
Generating train split: 79172654 examples [1:14:38, 6961.48 examples/s]
Generating train split: 79173469 examples [1:14:38, 6669.79 examples/s]
Generating train split: 79174223 examples [1:14:39, 5228.01 examples/s]
Generating train split: 79174854 examples [1:14:39, 5052.19 examples/s]
Generating train split: 79175432 examples [1:14:39, 3978.92 examples/s]
Generating train split: 79175903 examples [1:14:39, 3599.41 examples/s]
Generating train split: 79177819 examples [1:14:39, 6601.22 examples/s]
Generating train split: 79178689 examples [1:14:40, 5358.14 examples/s]
Generating train split: 79179825 examples [1:14:40, 6432.55 examples/s]
Generating train split: 79180653 examples [1:14:40, 6207.62 examples/s]
Generating train split: 79182683 examples [1:14:40, 9246.87 examples/s]
Generating train split: 79186785 examples [1:14:40, 16730.62 examples/s]
Generating train split: 79194907 examples [1:14:40, 32967.93 examples/s]
Generating train split: 79201971 examples [1:14:40, 42928.73 examples/s]
Generating train split: 79206786 examples [1:14:41, 19936.47 examples/s]
Generating train split: 79210430 examples [1:14:41, 12279.45 examples/s]
Generating train split: 79213146 examples [1:14:42, 12554.79 examples/s]
Generating train split: 79215463 examples [1:14:42, 9370.94 examples/s] 
Generating train split: 79220979 examples [1:14:42, 14124.24 examples/s]
Generating train split: 79229483 examples [1:14:42, 23283.33 examples/s]
Generating train split: 79234054 examples [1:14:42, 23470.12 examples/s]
Generating train split: 79237985 examples [1:14:43, 16636.37 examples/s]
Generating train split: 79240996 examples [1:14:43, 12456.59 examples/s]
Generating train split: 79243294 examples [1:14:44, 13384.29 examples/s]
Generating train split: 79245503 examples [1:14:44, 13965.82 examples/s]
Generating train split: 79247550 examples [1:14:44, 10545.74 examples/s]
Generating train split: 79249149 examples [1:14:44, 11041.96 examples/s]
Generating train split: 79250682 examples [1:14:44, 10622.53 examples/s]
Generating train split: 79252039 examples [1:14:45, 8442.69 examples/s] 
Generating train split: 79253832 examples [1:14:45, 9901.76 examples/s]
Generating train split: 79255127 examples [1:14:45, 8000.08 examples/s]
Generating train split: 79256188 examples [1:14:45, 8046.50 examples/s]
Generating train split: 79257170 examples [1:14:45, 7547.67 examples/s]
Generating train split: 79258277 examples [1:14:45, 7924.53 examples/s]
Generating train split: 79259174 examples [1:14:46, 5924.82 examples/s]
Generating train split: 79261347 examples [1:14:46, 8743.98 examples/s]
Generating train split: 79262504 examples [1:14:46, 9132.91 examples/s]
Generating train split: 79263840 examples [1:14:46, 10053.14 examples/s]
Generating train split: 79265030 examples [1:14:46, 7471.56 examples/s] 
Generating train split: 79265999 examples [1:14:46, 6419.89 examples/s]
Generating train split: 79266814 examples [1:14:47, 5977.72 examples/s]
Generating train split: 79268102 examples [1:14:47, 7288.95 examples/s]
Generating train split: 79268986 examples [1:14:47, 7079.32 examples/s]
Generating train split: 79269806 examples [1:14:47, 7089.88 examples/s]
Generating train split: 79270596 examples [1:14:47, 5462.78 examples/s]
Generating train split: 79271252 examples [1:14:47, 5368.46 examples/s]
Generating train split: 79272832 examples [1:14:47, 7586.18 examples/s]
Generating train split: 79273911 examples [1:14:48, 8331.12 examples/s]
Generating train split: 79274866 examples [1:14:48, 4753.12 examples/s]
Generating train split: 79275609 examples [1:14:48, 4660.44 examples/s]
Generating train split: 79276700 examples [1:14:48, 5660.12 examples/s]
Generating train split: 79277454 examples [1:14:48, 5765.04 examples/s]
Generating train split: 79278167 examples [1:14:49, 4618.35 examples/s]
Generating train split: 79286084 examples [1:14:49, 18588.30 examples/s]
Generating train split: 79294412 examples [1:14:49, 32246.38 examples/s]
Generating train split: 79298856 examples [1:14:49, 23922.62 examples/s]
Generating train split: 79302414 examples [1:14:50, 13704.54 examples/s]
Generating train split: 79305097 examples [1:14:50, 13639.80 examples/s]
Generating train split: 79307371 examples [1:14:50, 10660.96 examples/s]
Generating train split: 79309142 examples [1:14:51, 7624.72 examples/s] 
Generating train split: 79310642 examples [1:14:51, 8380.70 examples/s]
Generating train split: 79312028 examples [1:14:52, 4865.52 examples/s]
Generating train split: 79313053 examples [1:14:52, 5161.72 examples/s]
Generating train split: 79314000 examples [1:14:52, 4940.83 examples/s]
Generating train split: 79314786 examples [1:14:52, 4455.79 examples/s]
Generating train split: 79316212 examples [1:14:52, 5632.34 examples/s]
Generating train split: 79317053 examples [1:14:53, 5884.00 examples/s]
Generating train split: 79317862 examples [1:14:53, 5999.73 examples/s]
Generating train split: 79326618 examples [1:14:53, 21673.44 examples/s]
Generating train split: 79335106 examples [1:14:53, 34173.71 examples/s]
Generating train split: 79339525 examples [1:14:53, 25612.91 examples/s]
Generating train split: 79347337 examples [1:14:53, 35439.88 examples/s]
Generating train split: 79355529 examples [1:14:53, 44521.76 examples/s]
Generating train split: 79361204 examples [1:14:54, 19792.81 examples/s]
Generating train split: 79365414 examples [1:14:55, 12895.69 examples/s]
Generating train split: 79368543 examples [1:14:56, 7988.78 examples/s] 
Generating train split: 79370831 examples [1:14:56, 7375.89 examples/s]
Generating train split: 79372589 examples [1:14:56, 7435.71 examples/s]
Generating train split: 79374057 examples [1:14:57, 8057.91 examples/s]
Generating train split: 79375536 examples [1:14:57, 7841.33 examples/s]
Generating train split: 79376774 examples [1:14:57, 7254.02 examples/s]
Generating train split: 79378284 examples [1:14:57, 8263.24 examples/s]
Generating train split: 79379461 examples [1:14:57, 7667.59 examples/s]
Generating train split: 79380457 examples [1:14:57, 7076.41 examples/s]
Generating train split: 79381321 examples [1:14:58, 7098.14 examples/s]
Generating train split: 79382220 examples [1:14:58, 7413.62 examples/s]
Generating train split: 79383062 examples [1:14:58, 7334.41 examples/s]
Generating train split: 79385397 examples [1:14:58, 10956.24 examples/s]
Generating train split: 79389361 examples [1:14:58, 17950.18 examples/s]
Generating train split: 79395811 examples [1:14:58, 29978.12 examples/s]
Generating train split: 79402852 examples [1:14:58, 40856.14 examples/s]
Generating train split: 79409933 examples [1:14:58, 49171.19 examples/s]
Generating train split: 79416926 examples [1:14:58, 55053.21 examples/s]
Generating train split: 79424184 examples [1:14:59, 60091.08 examples/s]
Generating train split: 79430401 examples [1:14:59, 60379.90 examples/s]
Generating train split: 79437598 examples [1:14:59, 63756.61 examples/s]
Generating train split: 79444788 examples [1:14:59, 66143.90 examples/s]
Generating train split: 79451486 examples [1:14:59, 64046.73 examples/s]
Generating train split: 79458449 examples [1:14:59, 65650.99 examples/s]
Generating train split: 79465079 examples [1:14:59, 65793.99 examples/s]
Generating train split: 79472093 examples [1:14:59, 67048.28 examples/s]
Generating train split: 79478951 examples [1:14:59, 67489.63 examples/s]
Generating train split: 79486749 examples [1:14:59, 70588.63 examples/s]
Generating train split: 79493825 examples [1:15:00, 70604.36 examples/s]
Generating train split: 79500913 examples [1:15:00, 70382.32 examples/s]
Generating train split: 79508707 examples [1:15:00, 72601.54 examples/s]
Generating train split: 79516023 examples [1:15:00, 72709.60 examples/s]
Generating train split: 79523833 examples [1:15:00, 74294.88 examples/s]
Generating train split: 79531271 examples [1:15:00, 71963.76 examples/s]
Generating train split: 79538492 examples [1:15:00, 71389.93 examples/s]
Generating train split: 79545648 examples [1:15:00, 70532.10 examples/s]
Generating train split: 79552718 examples [1:15:00, 68259.50 examples/s]
Generating train split: 79559570 examples [1:15:01, 60843.31 examples/s]
Generating train split: 79565805 examples [1:15:01, 47049.22 examples/s]
Generating train split: 79571061 examples [1:15:01, 31437.89 examples/s]
Generating train split: 79575201 examples [1:15:02, 20831.80 examples/s]
Generating train split: 79578382 examples [1:15:02, 20832.91 examples/s]
Generating train split: 79581245 examples [1:15:02, 14147.68 examples/s]
Generating train split: 79583431 examples [1:15:03, 8313.93 examples/s] 
Generating train split: 79585048 examples [1:15:03, 7891.56 examples/s]
Generating train split: 79586364 examples [1:15:04, 6609.87 examples/s]
Generating train split: 79589674 examples [1:15:04, 9268.98 examples/s]
Generating train split: 79596865 examples [1:15:04, 17124.53 examples/s]
Generating train split: 79604102 examples [1:15:04, 25296.96 examples/s]
Generating train split: 79608509 examples [1:15:04, 21551.99 examples/s]
Generating train split: 79612064 examples [1:15:05, 12390.15 examples/s]
Generating train split: 79614707 examples [1:15:05, 10802.04 examples/s]
Generating train split: 79616770 examples [1:15:05, 10717.33 examples/s]
Generating train split: 79618527 examples [1:15:05, 11403.47 examples/s]
Generating train split: 79626832 examples [1:15:06, 21798.18 examples/s]
Generating train split: 79634539 examples [1:15:06, 30556.49 examples/s]
Generating train split: 79639147 examples [1:15:06, 16496.74 examples/s]
Generating train split: 79642599 examples [1:15:07, 13689.31 examples/s]
Generating train split: 79645272 examples [1:15:07, 10720.31 examples/s]
Generating train split: 79647319 examples [1:15:07, 10108.84 examples/s]
Generating train split: 79648994 examples [1:15:08, 10346.50 examples/s]
Generating train split: 79657402 examples [1:15:08, 20034.10 examples/s]
Generating train split: 79666114 examples [1:15:08, 30630.49 examples/s]
Generating train split: 79671237 examples [1:15:08, 17548.42 examples/s]
Generating train split: 79675080 examples [1:15:09, 15650.24 examples/s]
Generating train split: 79678117 examples [1:15:09, 16889.98 examples/s]
Generating train split: 79680969 examples [1:15:09, 12738.71 examples/s]
Generating train split: 79683166 examples [1:15:10, 11367.58 examples/s]
Generating train split: 79684945 examples [1:15:10, 10052.46 examples/s]
Generating train split: 79686393 examples [1:15:10, 10162.16 examples/s]
Generating train split: 79687736 examples [1:15:10, 7348.95 examples/s] 
Generating train split: 79688777 examples [1:15:11, 7515.72 examples/s]
Generating train split: 79691039 examples [1:15:11, 9766.87 examples/s]
Generating train split: 79692395 examples [1:15:11, 7050.05 examples/s]
Generating train split: 79693460 examples [1:15:11, 7527.45 examples/s]
Generating train split: 79694513 examples [1:15:11, 7176.91 examples/s]
Generating train split: 79695447 examples [1:15:12, 4853.31 examples/s]
Generating train split: 79696456 examples [1:15:12, 5585.02 examples/s]
Generating train split: 79697260 examples [1:15:12, 5603.07 examples/s]
Generating train split: 79698931 examples [1:15:12, 7624.06 examples/s]
Generating train split: 79699947 examples [1:15:12, 7206.20 examples/s]
Generating train split: 79707897 examples [1:15:12, 22179.94 examples/s]
Generating train split: 79716713 examples [1:15:12, 37241.89 examples/s]
Generating train split: 79721469 examples [1:15:13, 27919.24 examples/s]
Generating train split: 79725320 examples [1:15:13, 19941.25 examples/s]
Generating train split: 79728348 examples [1:15:13, 19198.74 examples/s]
Generating train split: 79730976 examples [1:15:14, 12393.63 examples/s]
Generating train split: 79732978 examples [1:15:14, 11259.35 examples/s]
Generating train split: 79734629 examples [1:15:14, 9424.94 examples/s] 
Generating train split: 79735947 examples [1:15:14, 9259.58 examples/s]
Generating train split: 79737139 examples [1:15:15, 7099.11 examples/s]
Generating train split: 79739090 examples [1:15:15, 8577.33 examples/s]
Generating train split: 79740577 examples [1:15:15, 9526.46 examples/s]
Generating train split: 79741823 examples [1:15:15, 7728.36 examples/s]
Generating train split: 79742832 examples [1:15:15, 7496.06 examples/s]
Generating train split: 79750469 examples [1:15:15, 19952.65 examples/s]
Generating train split: 79758992 examples [1:15:16, 33018.01 examples/s]
Generating train split: 79763485 examples [1:15:16, 17152.46 examples/s]
Generating train split: 79766866 examples [1:15:17, 12622.85 examples/s]
Generating train split: 79775679 examples [1:15:17, 20979.42 examples/s]
Generating train split: 79783380 examples [1:15:17, 28444.31 examples/s]
Generating train split: 79788696 examples [1:15:17, 21246.32 examples/s]
Generating train split: 79792789 examples [1:15:18, 19927.59 examples/s]
Generating train split: 79800589 examples [1:15:18, 27820.85 examples/s]
Generating train split: 79809180 examples [1:15:18, 36761.24 examples/s]
Generating train split: 79814848 examples [1:15:18, 20542.55 examples/s]
Generating train split: 79819091 examples [1:15:19, 15463.13 examples/s]
Generating train split: 79822306 examples [1:15:20, 9541.16 examples/s] 
Generating train split: 79824672 examples [1:15:20, 9524.32 examples/s]
Generating train split: 79826619 examples [1:15:20, 9070.43 examples/s]
Generating train split: 79828574 examples [1:15:20, 10093.29 examples/s]
Generating train split: 79830255 examples [1:15:21, 7954.45 examples/s] 
Generating train split: 79831564 examples [1:15:21, 8269.75 examples/s]
Generating train split: 79833117 examples [1:15:21, 9224.63 examples/s]
Generating train split: 79834424 examples [1:15:21, 8194.14 examples/s]
Generating train split: 79835519 examples [1:15:21, 7102.68 examples/s]
Generating train split: 79836427 examples [1:15:22, 6707.82 examples/s]
Generating train split: 79837241 examples [1:15:22, 5974.42 examples/s]
Generating train split: 79838062 examples [1:15:22, 6357.77 examples/s]
Generating train split: 79839264 examples [1:15:22, 7474.31 examples/s]
Generating train split: 79840143 examples [1:15:22, 6396.46 examples/s]
Generating train split: 79840889 examples [1:15:22, 5064.99 examples/s]
Generating train split: 79842323 examples [1:15:23, 6731.48 examples/s]
Generating train split: 79843173 examples [1:15:23, 5316.40 examples/s]
Generating train split: 79844235 examples [1:15:23, 6232.16 examples/s]
Generating train split: 79845304 examples [1:15:23, 7138.84 examples/s]
Generating train split: 79846178 examples [1:15:23, 6870.13 examples/s]
Generating train split: 79846992 examples [1:15:23, 6358.15 examples/s]
Generating train split: 79847730 examples [1:15:23, 6587.24 examples/s]
Generating train split: 79849045 examples [1:15:24, 8078.21 examples/s]
Generating train split: 79849939 examples [1:15:24, 7706.20 examples/s]
Generating train split: 79851765 examples [1:15:24, 10373.80 examples/s]
Generating train split: 79853717 examples [1:15:24, 12780.70 examples/s]
Generating train split: 79855435 examples [1:15:24, 13905.01 examples/s]
Generating train split: 79856907 examples [1:15:24, 12104.87 examples/s]
Generating train split: 79858210 examples [1:15:24, 12002.26 examples/s]
Generating train split: 79859761 examples [1:15:24, 12883.45 examples/s]
Generating train split: 79861109 examples [1:15:25, 6907.64 examples/s] 
Generating train split: 79862149 examples [1:15:25, 7287.26 examples/s]
Generating train split: 79863140 examples [1:15:25, 7231.17 examples/s]
Generating train split: 79864064 examples [1:15:25, 7630.69 examples/s]
Generating train split: 79864983 examples [1:15:25, 5972.21 examples/s]
Generating train split: 79866033 examples [1:15:25, 6806.85 examples/s]
Generating train split: 79867642 examples [1:15:26, 8643.57 examples/s]
Generating train split: 79868672 examples [1:15:26, 7044.58 examples/s]
Generating train split: 79869533 examples [1:15:26, 6478.90 examples/s]
Generating train split: 79870301 examples [1:15:26, 5340.96 examples/s]
Generating train split: 79870940 examples [1:15:26, 4911.82 examples/s]
Generating train split: 79872388 examples [1:15:26, 6754.07 examples/s]
Generating train split: 79873220 examples [1:15:27, 5417.57 examples/s]
Generating train split: 79873901 examples [1:15:27, 4823.02 examples/s]
Generating train split: 79874977 examples [1:15:27, 5918.85 examples/s]
Generating train split: 79875708 examples [1:15:27, 5101.92 examples/s]
Generating train split: 79876844 examples [1:15:27, 6246.17 examples/s]
Generating train split: 79877595 examples [1:15:28, 5233.24 examples/s]
Generating train split: 79878226 examples [1:15:28, 5045.37 examples/s]
Generating train split: 79879636 examples [1:15:28, 6932.37 examples/s]
Generating train split: 79880677 examples [1:15:28, 7696.80 examples/s]
Generating train split: 79881564 examples [1:15:28, 6608.73 examples/s]
Generating train split: 79882577 examples [1:15:28, 7399.26 examples/s]
Generating train split: 79883417 examples [1:15:28, 5429.84 examples/s]
Generating train split: 79884109 examples [1:15:29, 4301.78 examples/s]
Generating train split: 79885050 examples [1:15:29, 5181.35 examples/s]
Generating train split: 79885807 examples [1:15:29, 5596.54 examples/s]
Generating train split: 79886606 examples [1:15:29, 6050.07 examples/s]
Generating train split: 79887315 examples [1:15:29, 5332.16 examples/s]
Generating train split: 79888414 examples [1:15:29, 6588.87 examples/s]
Generating train split: 79889183 examples [1:15:29, 5499.32 examples/s]
Generating train split: 79889828 examples [1:15:30, 4534.65 examples/s]
Generating train split: 79890918 examples [1:15:30, 5784.87 examples/s]
Generating train split: 79891624 examples [1:15:30, 5528.92 examples/s]
Generating train split: 79892274 examples [1:15:30, 5031.35 examples/s]
Generating train split: 79892982 examples [1:15:30, 5477.39 examples/s]
Generating train split: 79894395 examples [1:15:30, 7407.59 examples/s]
Generating train split: 79895224 examples [1:15:30, 7070.40 examples/s]
Generating train split: 79895990 examples [1:15:31, 6250.00 examples/s]
Generating train split: 79896668 examples [1:15:31, 6314.62 examples/s]
Generating train split: 79898276 examples [1:15:31, 8753.23 examples/s]
Generating train split: 79899432 examples [1:15:31, 9491.35 examples/s]
Generating train split: 79900777 examples [1:15:31, 10559.14 examples/s]
Generating train split: 79901891 examples [1:15:31, 7460.53 examples/s] 
Generating train split: 79904217 examples [1:15:31, 10864.39 examples/s]
Generating train split: 79905547 examples [1:15:32, 9614.11 examples/s] 
Generating train split: 79906697 examples [1:15:32, 5994.30 examples/s]
Generating train split: 79908987 examples [1:15:32, 8678.31 examples/s]
Generating train split: 79910732 examples [1:15:32, 10288.34 examples/s]
Generating train split: 79912173 examples [1:15:32, 7717.20 examples/s] 
Generating train split: 79913370 examples [1:15:33, 8443.08 examples/s]
Generating train split: 79915242 examples [1:15:33, 10457.74 examples/s]
Generating train split: 79917403 examples [1:15:33, 12889.77 examples/s]
Generating train split: 79919012 examples [1:15:33, 10329.25 examples/s]
Generating train split: 79920352 examples [1:15:33, 9846.98 examples/s] 
Generating train split: 79922509 examples [1:15:33, 12280.02 examples/s]
Generating train split: 79924214 examples [1:15:33, 13352.19 examples/s]
Generating train split: 79925763 examples [1:15:34, 11406.15 examples/s]
Generating train split: 79927104 examples [1:15:34, 9782.32 examples/s] 
Generating train split: 79928639 examples [1:15:34, 10943.03 examples/s]
Generating train split: 79929905 examples [1:15:34, 8726.34 examples/s] 
Generating train split: 79931732 examples [1:15:34, 10643.13 examples/s]
Generating train split: 79933009 examples [1:15:34, 9346.11 examples/s] 
Generating train split: 79934110 examples [1:15:35, 7178.15 examples/s]
Generating train split: 79935220 examples [1:15:35, 7821.32 examples/s]
Generating train split: 79936172 examples [1:15:35, 7236.53 examples/s]
Generating train split: 79937732 examples [1:15:35, 8956.14 examples/s]
Generating train split: 79938786 examples [1:15:35, 6714.47 examples/s]
Generating train split: 79940365 examples [1:15:35, 8434.97 examples/s]
Generating train split: 79941445 examples [1:15:36, 7741.03 examples/s]
Generating train split: 79942797 examples [1:15:36, 8946.82 examples/s]
Generating train split: 79945337 examples [1:15:36, 12719.50 examples/s]
Generating train split: 79947157 examples [1:15:36, 13786.00 examples/s]
Generating train split: 79949599 examples [1:15:36, 16386.08 examples/s]
Generating train split: 79951413 examples [1:15:36, 12131.69 examples/s]
Generating train split: 79952908 examples [1:15:36, 11016.70 examples/s]
Generating train split: 79954645 examples [1:15:36, 12346.51 examples/s]
Generating train split: 79956483 examples [1:15:37, 13528.05 examples/s]
Generating train split: 79958011 examples [1:15:37, 8599.21 examples/s] 
Generating train split: 79959215 examples [1:15:37, 5849.61 examples/s]
Generating train split: 79960145 examples [1:15:38, 5951.11 examples/s]
Generating train split: 79962041 examples [1:15:38, 7992.31 examples/s]
Generating train split: 79963228 examples [1:15:38, 8660.99 examples/s]
Generating train split: 79964400 examples [1:15:38, 6374.42 examples/s]
Generating train split: 79965986 examples [1:15:38, 7968.79 examples/s]
Generating train split: 79967386 examples [1:15:38, 9131.89 examples/s]
Generating train split: 79968591 examples [1:15:38, 8075.86 examples/s]
Generating train split: 79969622 examples [1:15:39, 7168.09 examples/s]
Generating train split: 79971299 examples [1:15:39, 9035.75 examples/s]
Generating train split: 79972799 examples [1:15:39, 10320.82 examples/s]
Generating train split: 79974026 examples [1:15:39, 8522.73 examples/s] 
Generating train split: 79975069 examples [1:15:39, 8026.66 examples/s]
Generating train split: 79975997 examples [1:15:40, 5208.96 examples/s]
Generating train split: 79976724 examples [1:15:40, 4513.75 examples/s]
Generating train split: 79977323 examples [1:15:40, 4400.74 examples/s]
Generating train split: 79984340 examples [1:15:40, 15764.02 examples/s]
Generating train split: 79993251 examples [1:15:40, 30283.99 examples/s]
Generating train split: 79997670 examples [1:15:41, 19634.51 examples/s]
Generating train split: 80001082 examples [1:15:41, 17150.17 examples/s]
Generating train split: 80003841 examples [1:15:41, 14332.26 examples/s]
Generating train split: 80006043 examples [1:15:42, 7202.20 examples/s] 
Generating train split: 80007655 examples [1:15:43, 4400.24 examples/s]
Generating train split: 80008830 examples [1:15:44, 2940.07 examples/s]
Generating train split: 80009683 examples [1:15:45, 2201.65 examples/s]
Generating train split: 80010307 examples [1:15:46, 1969.31 examples/s]
Generating train split: 80011294 examples [1:15:46, 2390.94 examples/s]
Generating train split: 80012768 examples [1:15:46, 3265.71 examples/s]
Generating train split: 80013651 examples [1:15:46, 3286.68 examples/s]
Generating train split: 80014373 examples [1:15:46, 3579.95 examples/s]
Generating train split: 80015048 examples [1:15:47, 3767.75 examples/s]
Generating train split: 80015990 examples [1:15:47, 4552.83 examples/s]
Generating train split: 80018703 examples [1:15:47, 8387.52 examples/s]
Generating train split: 80026044 examples [1:15:47, 21081.69 examples/s]
Generating train split: 80032086 examples [1:15:47, 29660.21 examples/s]
Generating train split: 80036083 examples [1:15:48, 11695.87 examples/s]
Generating train split: 80039025 examples [1:15:49, 7940.22 examples/s] 
Generating train split: 80041203 examples [1:15:49, 8027.89 examples/s]
Generating train split: 80042983 examples [1:15:49, 7555.43 examples/s]
Generating train split: 80044415 examples [1:15:49, 7809.43 examples/s]
Generating train split: 80045689 examples [1:15:50, 6310.58 examples/s]
Generating train split: 80047119 examples [1:15:50, 7202.47 examples/s]
Generating train split: 80048230 examples [1:15:50, 5934.40 examples/s]
Generating train split: 80049124 examples [1:15:50, 6272.61 examples/s]
Generating train split: 80050480 examples [1:15:50, 7357.98 examples/s]
Generating train split: 80051468 examples [1:15:50, 7591.76 examples/s]
Generating train split: 80052428 examples [1:15:51, 6813.18 examples/s]
Generating train split: 80053574 examples [1:15:51, 7722.56 examples/s]
Generating train split: 80054497 examples [1:15:51, 7787.74 examples/s]
Generating train split: 80055803 examples [1:15:51, 8998.88 examples/s]
Generating train split: 80056817 examples [1:15:51, 6775.38 examples/s]
Generating train split: 80057652 examples [1:15:51, 5097.36 examples/s]
Generating train split: 80059427 examples [1:15:52, 7300.67 examples/s]
Generating train split: 80060430 examples [1:15:52, 6069.18 examples/s]
Generating train split: 80062342 examples [1:15:52, 8388.63 examples/s]
Generating train split: 80063500 examples [1:15:52, 8084.81 examples/s]
Generating train split: 80064517 examples [1:15:52, 6130.12 examples/s]
Generating train split: 80065342 examples [1:15:52, 6490.22 examples/s]
Generating train split: 80066875 examples [1:15:53, 8250.65 examples/s]
Generating train split: 80067903 examples [1:15:53, 6407.40 examples/s]
Generating train split: 80068945 examples [1:15:53, 7082.28 examples/s]
Generating train split: 80070084 examples [1:15:53, 7989.17 examples/s]
Generating train split: 80071066 examples [1:15:53, 8382.57 examples/s]
Generating train split: 80078249 examples [1:15:53, 24104.47 examples/s]
Generating train split: 80085837 examples [1:15:53, 37634.59 examples/s]
Generating train split: 80090104 examples [1:15:54, 24523.63 examples/s]
Generating train split: 80093486 examples [1:15:54, 18641.06 examples/s]
Generating train split: 80096183 examples [1:15:54, 15815.21 examples/s]
Generating train split: 80098395 examples [1:15:54, 13114.15 examples/s]
Generating train split: 80100170 examples [1:15:55, 8746.31 examples/s] 
Generating train split: 80101522 examples [1:15:55, 8484.40 examples/s]
Generating train split: 80102692 examples [1:15:55, 7811.19 examples/s]
Generating train split: 80103682 examples [1:15:56, 6729.76 examples/s]
Generating train split: 80104500 examples [1:15:56, 5868.89 examples/s]
Generating train split: 80105184 examples [1:15:56, 5603.28 examples/s]
Generating train split: 80106482 examples [1:15:56, 6813.26 examples/s]
Generating train split: 80107296 examples [1:15:56, 5991.35 examples/s]
Generating train split: 80108000 examples [1:15:57, 4216.00 examples/s]
Generating train split: 80109014 examples [1:15:57, 5091.38 examples/s]
Generating train split: 80109690 examples [1:15:57, 5212.03 examples/s]
Generating train split: 80110996 examples [1:15:57, 6756.51 examples/s]
Generating train split: 80111844 examples [1:15:57, 4674.89 examples/s]
Generating train split: 80112509 examples [1:15:57, 4455.12 examples/s]
Generating train split: 80113090 examples [1:15:58, 4356.16 examples/s]
Generating train split: 80113618 examples [1:15:58, 3596.27 examples/s]
Generating train split: 80114286 examples [1:15:58, 4119.62 examples/s]
Generating train split: 80115432 examples [1:15:58, 5558.48 examples/s]
Generating train split: 80116274 examples [1:15:58, 6161.21 examples/s]
Generating train split: 80117004 examples [1:15:58, 5112.00 examples/s]
Generating train split: 80117653 examples [1:15:58, 5397.96 examples/s]
Generating train split: 80118281 examples [1:15:59, 4987.13 examples/s]
Generating train split: 80118930 examples [1:15:59, 5318.92 examples/s]
Generating train split: 80119519 examples [1:15:59, 4319.58 examples/s]
Generating train split: 80120094 examples [1:15:59, 4403.22 examples/s]
Generating train split: 80121069 examples [1:15:59, 5622.52 examples/s]
Generating train split: 80121711 examples [1:15:59, 4735.78 examples/s]
Generating train split: 80123318 examples [1:15:59, 7221.85 examples/s]
Generating train split: 80124181 examples [1:16:00, 6447.65 examples/s]
Generating train split: 80124951 examples [1:16:00, 4989.69 examples/s]
Generating train split: 80125574 examples [1:16:00, 5052.96 examples/s]
Generating train split: 80126365 examples [1:16:00, 5609.69 examples/s]
Generating train split: 80127509 examples [1:16:00, 6929.65 examples/s]
Generating train split: 80128307 examples [1:16:00, 6233.57 examples/s]
Generating train split: 80129071 examples [1:16:00, 6547.16 examples/s]
Generating train split: 80129793 examples [1:16:01, 5834.27 examples/s]
Generating train split: 80130993 examples [1:16:01, 7270.70 examples/s]
Generating train split: 80131799 examples [1:16:01, 4967.88 examples/s]
Generating train split: 80133225 examples [1:16:01, 6706.13 examples/s]
Generating train split: 80134086 examples [1:16:01, 5926.78 examples/s]
Generating train split: 80135035 examples [1:16:01, 6621.72 examples/s]
Generating train split: 80135839 examples [1:16:02, 5705.70 examples/s]
Generating train split: 80136525 examples [1:16:02, 4570.63 examples/s]
Generating train split: 80137983 examples [1:16:02, 6240.18 examples/s]
Generating train split: 80138759 examples [1:16:02, 6292.90 examples/s]
Generating train split: 80139985 examples [1:16:02, 7542.72 examples/s]
Generating train split: 80140864 examples [1:16:03, 4645.41 examples/s]
Generating train split: 80142403 examples [1:16:03, 6407.03 examples/s]
Generating train split: 80143327 examples [1:16:03, 6029.41 examples/s]
Generating train split: 80144133 examples [1:16:03, 6017.37 examples/s]
Generating train split: 80144885 examples [1:16:03, 6324.50 examples/s]
Generating train split: 80145633 examples [1:16:03, 5914.39 examples/s]
Generating train split: 80146593 examples [1:16:03, 6742.75 examples/s]
Generating train split: 80148101 examples [1:16:03, 8766.81 examples/s]
Generating train split: 80149093 examples [1:16:04, 8626.99 examples/s]
Generating train split: 80150606 examples [1:16:04, 10293.99 examples/s]
Generating train split: 80151871 examples [1:16:04, 10927.56 examples/s]
Generating train split: 80153194 examples [1:16:04, 11402.66 examples/s]
Generating train split: 80154387 examples [1:16:04, 8299.10 examples/s] 
Generating train split: 80155366 examples [1:16:04, 7638.81 examples/s]
Generating train split: 80157660 examples [1:16:04, 10876.79 examples/s]
Generating train split: 80158927 examples [1:16:05, 6209.55 examples/s] 
Generating train split: 80159897 examples [1:16:05, 5296.75 examples/s]
Generating train split: 80161608 examples [1:16:05, 6852.24 examples/s]
Generating train split: 80162586 examples [1:16:05, 5691.59 examples/s]
Generating train split: 80163382 examples [1:16:06, 4422.83 examples/s]
Generating train split: 80165010 examples [1:16:06, 6115.10 examples/s]
Generating train split: 80165937 examples [1:16:06, 6188.58 examples/s]
Generating train split: 80168230 examples [1:16:06, 9262.34 examples/s]
Generating train split: 80169514 examples [1:16:06, 6473.74 examples/s]
Generating train split: 80170521 examples [1:16:07, 5928.74 examples/s]
Generating train split: 80171864 examples [1:16:07, 7143.04 examples/s]
Generating train split: 80172860 examples [1:16:07, 7608.07 examples/s]
Generating train split: 80173849 examples [1:16:07, 7078.32 examples/s]
Generating train split: 80175201 examples [1:16:07, 8393.84 examples/s]
Generating train split: 80176208 examples [1:16:07, 7488.25 examples/s]
Generating train split: 80178120 examples [1:16:07, 10000.23 examples/s]
Generating train split: 80179306 examples [1:16:08, 6524.70 examples/s] 
Generating train split: 80180246 examples [1:16:08, 6715.40 examples/s]
Generating train split: 80181132 examples [1:16:08, 7086.95 examples/s]
Generating train split: 80182895 examples [1:16:08, 9298.09 examples/s]
Generating train split: 80184018 examples [1:16:09, 5518.08 examples/s]
Generating train split: 80184893 examples [1:16:09, 4497.61 examples/s]
Generating train split: 80185591 examples [1:16:09, 4796.73 examples/s]
Generating train split: 80186402 examples [1:16:09, 5327.80 examples/s]
Generating train split: 80187124 examples [1:16:09, 4670.29 examples/s]
Generating train split: 80193457 examples [1:16:09, 15538.16 examples/s]
Generating train split: 80201899 examples [1:16:10, 29953.34 examples/s]
Generating train split: 80206067 examples [1:16:10, 19242.88 examples/s]
Generating train split: 80209297 examples [1:16:10, 16277.65 examples/s]
Generating train split: 80211884 examples [1:16:11, 11211.25 examples/s]
Generating train split: 80213860 examples [1:16:11, 8098.70 examples/s] 
Generating train split: 80215356 examples [1:16:12, 6627.81 examples/s]
Generating train split: 80216507 examples [1:16:12, 7069.37 examples/s]
Generating train split: 80218985 examples [1:16:12, 9243.41 examples/s]
Generating train split: 80227280 examples [1:16:12, 20240.46 examples/s]
Generating train split: 80234325 examples [1:16:12, 28978.43 examples/s]
Generating train split: 80238899 examples [1:16:12, 19274.11 examples/s]
Generating train split: 80242418 examples [1:16:13, 11058.91 examples/s]
Generating train split: 80245028 examples [1:16:14, 10644.21 examples/s]
Generating train split: 80247130 examples [1:16:14, 10605.24 examples/s]
Generating train split: 80255246 examples [1:16:14, 19015.60 examples/s]
Generating train split: 80262336 examples [1:16:14, 26564.96 examples/s]
Generating train split: 80267049 examples [1:16:14, 21701.99 examples/s]
Generating train split: 80270782 examples [1:16:15, 13739.91 examples/s]
Generating train split: 80273582 examples [1:16:15, 11888.66 examples/s]
Generating train split: 80280851 examples [1:16:15, 18471.04 examples/s]
Generating train split: 80288523 examples [1:16:15, 25971.27 examples/s]
Generating train split: 80293243 examples [1:16:16, 21209.22 examples/s]
Generating train split: 80296968 examples [1:16:16, 17031.95 examples/s]
Generating train split: 80299875 examples [1:16:17, 12695.62 examples/s]
Generating train split: 80302100 examples [1:16:17, 11084.43 examples/s]
Generating train split: 80303866 examples [1:16:17, 10500.12 examples/s]
Generating train split: 80305363 examples [1:16:17, 8514.40 examples/s] 
Generating train split: 80307931 examples [1:16:18, 10571.81 examples/s]
Generating train split: 80309514 examples [1:16:18, 10146.72 examples/s]
Generating train split: 80310970 examples [1:16:18, 10789.26 examples/s]
Generating train split: 80312353 examples [1:16:18, 9794.08 examples/s] 
Generating train split: 80313549 examples [1:16:18, 9915.45 examples/s]
Generating train split: 80315807 examples [1:16:18, 12489.11 examples/s]
Generating train split: 80317283 examples [1:16:19, 8873.76 examples/s] 
Generating train split: 80318465 examples [1:16:19, 6673.23 examples/s]
Generating train split: 80319404 examples [1:16:19, 6025.51 examples/s]
Generating train split: 80320200 examples [1:16:19, 4973.93 examples/s]
Generating train split: 80321119 examples [1:16:19, 5591.67 examples/s]
Generating train split: 80321842 examples [1:16:20, 5604.97 examples/s]
Generating train split: 80322530 examples [1:16:20, 5744.59 examples/s]
Generating train split: 80323788 examples [1:16:20, 7183.80 examples/s]
Generating train split: 80324919 examples [1:16:20, 8117.84 examples/s]
Generating train split: 80325846 examples [1:16:20, 6961.52 examples/s]
Generating train split: 80327078 examples [1:16:20, 8174.57 examples/s]
Generating train split: 80328012 examples [1:16:20, 7212.39 examples/s]
Generating train split: 80328843 examples [1:16:20, 7464.73 examples/s]
Generating train split: 80330433 examples [1:16:21, 9376.11 examples/s]
Generating train split: 80331456 examples [1:16:21, 6168.15 examples/s]
Generating train split: 80332274 examples [1:16:21, 3992.17 examples/s]
Generating train split: 80332999 examples [1:16:21, 4254.06 examples/s]
Generating train split: 80333599 examples [1:16:22, 4483.42 examples/s]
Generating train split: 80334190 examples [1:16:22, 4008.61 examples/s]
Generating train split: 80335242 examples [1:16:22, 5199.20 examples/s]
Generating train split: 80335921 examples [1:16:22, 5390.35 examples/s]
Generating train split: 80343235 examples [1:16:22, 20594.22 examples/s]
Generating train split: 80351745 examples [1:16:22, 36251.53 examples/s]
Generating train split: 80356152 examples [1:16:23, 17571.76 examples/s]
Generating train split: 80359473 examples [1:16:23, 15071.52 examples/s]
Generating train split: 80362334 examples [1:16:23, 16904.30 examples/s]
Generating train split: 80365044 examples [1:16:23, 16034.12 examples/s]
Generating train split: 80367358 examples [1:16:24, 13149.95 examples/s]
Generating train split: 80369215 examples [1:16:24, 12700.47 examples/s]
Generating train split: 80370867 examples [1:16:24, 11564.99 examples/s]
Generating train split: 80372274 examples [1:16:24, 8874.42 examples/s] 
Generating train split: 80373408 examples [1:16:25, 7904.22 examples/s]
Generating train split: 80374522 examples [1:16:25, 8396.79 examples/s]
Generating train split: 80375517 examples [1:16:25, 6929.93 examples/s]
Generating train split: 80376479 examples [1:16:25, 7394.24 examples/s]
Generating train split: 80378305 examples [1:16:25, 9542.38 examples/s]
Generating train split: 80379463 examples [1:16:25, 8050.53 examples/s]
Generating train split: 80380450 examples [1:16:26, 6483.68 examples/s]
Generating train split: 80382238 examples [1:16:26, 8551.10 examples/s]
Generating train split: 80383337 examples [1:16:26, 7948.45 examples/s]
Generating train split: 80384328 examples [1:16:26, 8321.84 examples/s]
Generating train split: 80385307 examples [1:16:26, 6230.24 examples/s]
Generating train split: 80386407 examples [1:16:26, 7075.45 examples/s]
Generating train split: 80387286 examples [1:16:26, 6962.44 examples/s]
Generating train split: 80388097 examples [1:16:27, 4826.94 examples/s]
Generating train split: 80388742 examples [1:16:27, 4813.70 examples/s]
Generating train split: 80389337 examples [1:16:27, 3524.33 examples/s]
Generating train split: 80389808 examples [1:16:27, 3474.03 examples/s]
Generating train split: 80390243 examples [1:16:28, 2909.14 examples/s]
Generating train split: 80390827 examples [1:16:28, 3380.48 examples/s]
Generating train split: 80392634 examples [1:16:28, 6175.05 examples/s]
Generating train split: 80393628 examples [1:16:28, 6982.87 examples/s]
Generating train split: 80394502 examples [1:16:28, 4793.06 examples/s]
Generating train split: 80396112 examples [1:16:28, 6809.23 examples/s]
Generating train split: 80397079 examples [1:16:29, 5719.13 examples/s]
Generating train split: 80397882 examples [1:16:29, 5278.17 examples/s]
Generating train split: 80398911 examples [1:16:29, 6196.11 examples/s]
Generating train split: 80399712 examples [1:16:29, 4735.26 examples/s]
Generating train split: 80400358 examples [1:16:29, 4603.41 examples/s]
Generating train split: 80401434 examples [1:16:29, 5735.88 examples/s]
Generating train split: 80402159 examples [1:16:30, 4256.95 examples/s]
Generating train split: 80402737 examples [1:16:30, 3101.15 examples/s]
Generating train split: 80403196 examples [1:16:30, 3244.48 examples/s]
Generating train split: 80403639 examples [1:16:30, 2658.30 examples/s]
Generating train split: 80404257 examples [1:16:31, 3205.28 examples/s]
Generating train split: 80404688 examples [1:16:31, 3211.11 examples/s]
Generating train split: 80412339 examples [1:16:31, 17706.92 examples/s]
Generating train split: 80420769 examples [1:16:31, 32374.11 examples/s]
Generating train split: 80425104 examples [1:16:32, 10024.99 examples/s]
Generating train split: 80428251 examples [1:16:33, 7620.22 examples/s] 
Generating train split: 80430606 examples [1:16:33, 8811.21 examples/s]
Generating train split: 80432946 examples [1:16:33, 8702.42 examples/s]
Generating train split: 80434836 examples [1:16:33, 8236.77 examples/s]
Generating train split: 80436365 examples [1:16:34, 8591.34 examples/s]
Generating train split: 80437758 examples [1:16:34, 6599.84 examples/s]
Generating train split: 80438831 examples [1:16:34, 5544.30 examples/s]
Generating train split: 80439676 examples [1:16:34, 5160.84 examples/s]
Generating train split: 80440701 examples [1:16:35, 5808.68 examples/s]
Generating train split: 80441505 examples [1:16:35, 6149.55 examples/s]
Generating train split: 80442478 examples [1:16:35, 6739.31 examples/s]
Generating train split: 80443332 examples [1:16:35, 4576.16 examples/s]
Generating train split: 80444753 examples [1:16:35, 6093.06 examples/s]
Generating train split: 80445642 examples [1:16:36, 4918.83 examples/s]
Generating train split: 80446356 examples [1:16:36, 4345.96 examples/s]
Generating train split: 80447550 examples [1:16:36, 5567.60 examples/s]
Generating train split: 80449670 examples [1:16:36, 8448.16 examples/s]
Generating train split: 80450841 examples [1:16:36, 7291.05 examples/s]
Generating train split: 80451812 examples [1:16:36, 5944.92 examples/s]
Generating train split: 80452607 examples [1:16:37, 5046.58 examples/s]
Generating train split: 80453914 examples [1:16:37, 6341.85 examples/s]
Generating train split: 80454760 examples [1:16:37, 5984.39 examples/s]
Generating train split: 80456821 examples [1:16:37, 8815.47 examples/s]
Generating train split: 80457956 examples [1:16:37, 7418.59 examples/s]
Generating train split: 80458901 examples [1:16:38, 6046.80 examples/s]
Generating train split: 80460094 examples [1:16:38, 7065.58 examples/s]
Generating train split: 80460992 examples [1:16:38, 4258.03 examples/s]
Generating train split: 80461674 examples [1:16:38, 3964.82 examples/s]
Generating train split: 80462258 examples [1:16:39, 3552.99 examples/s]
Generating train split: 80464764 examples [1:16:39, 6793.08 examples/s]
Generating train split: 80465853 examples [1:16:39, 7442.48 examples/s]
Generating train split: 80467044 examples [1:16:39, 8249.99 examples/s]
Generating train split: 80468140 examples [1:16:39, 6850.81 examples/s]
Generating train split: 80469053 examples [1:16:39, 5743.52 examples/s]
Generating train split: 80469812 examples [1:16:40, 5385.03 examples/s]
Generating train split: 80471155 examples [1:16:40, 6842.54 examples/s]
Generating train split: 80472009 examples [1:16:40, 7126.04 examples/s]
Generating train split: 80473092 examples [1:16:40, 7829.36 examples/s]
Generating train split: 80474186 examples [1:16:40, 8579.68 examples/s]
Generating train split: 80475229 examples [1:16:40, 9030.99 examples/s]
Generating train split: 80476208 examples [1:16:40, 7177.26 examples/s]
Generating train split: 80483546 examples [1:16:40, 22368.16 examples/s]
Generating train split: 80492657 examples [1:16:40, 39334.95 examples/s]
Generating train split: 80497336 examples [1:16:41, 23530.04 examples/s]
Generating train split: 80500985 examples [1:16:41, 16625.50 examples/s]
Generating train split: 80508803 examples [1:16:41, 25167.89 examples/s]
Generating train split: 80516849 examples [1:16:41, 33905.47 examples/s]
Generating train split: 80522116 examples [1:16:42, 22851.07 examples/s]
Generating train split: 80526165 examples [1:16:43, 12720.57 examples/s]
Generating train split: 80529153 examples [1:16:43, 13942.67 examples/s]
Generating train split: 80531945 examples [1:16:43, 14059.05 examples/s]
Generating train split: 80534335 examples [1:16:43, 11826.62 examples/s]
Generating train split: 80536236 examples [1:16:44, 11183.51 examples/s]
Generating train split: 80537839 examples [1:16:44, 11798.33 examples/s]
Generating train split: 80539424 examples [1:16:44, 8708.66 examples/s] 
Generating train split: 80541128 examples [1:16:44, 9862.04 examples/s]
Generating train split: 80542516 examples [1:16:44, 8858.85 examples/s]
Generating train split: 80543678 examples [1:16:45, 8372.29 examples/s]
Generating train split: 80544698 examples [1:16:45, 8539.20 examples/s]
Generating train split: 80545696 examples [1:16:45, 6911.42 examples/s]
Generating train split: 80546518 examples [1:16:45, 6432.58 examples/s]
Generating train split: 80547249 examples [1:16:45, 6568.57 examples/s]
Generating train split: 80547983 examples [1:16:45, 5946.41 examples/s]
Generating train split: 80549772 examples [1:16:45, 8163.80 examples/s]
Generating train split: 80550681 examples [1:16:46, 6160.60 examples/s]
Generating train split: 80551451 examples [1:16:46, 6312.71 examples/s]
Generating train split: 80552176 examples [1:16:46, 4035.06 examples/s]
Generating train split: 80552806 examples [1:16:46, 3974.70 examples/s]
Generating train split: 80553739 examples [1:16:46, 4878.26 examples/s]
Generating train split: 80555334 examples [1:16:47, 6867.02 examples/s]
Generating train split: 80556217 examples [1:16:47, 6262.76 examples/s]
Generating train split: 80557351 examples [1:16:47, 7208.41 examples/s]
Generating train split: 80558202 examples [1:16:47, 5940.97 examples/s]
Generating train split: 80558918 examples [1:16:47, 5121.80 examples/s]
Generating train split: 80559880 examples [1:16:47, 5944.94 examples/s]
Generating train split: 80560775 examples [1:16:47, 6576.54 examples/s]
Generating train split: 80561540 examples [1:16:48, 5566.35 examples/s]
Generating train split: 80562215 examples [1:16:48, 5816.57 examples/s]
Generating train split: 80563983 examples [1:16:48, 8581.21 examples/s]
Generating train split: 80564973 examples [1:16:48, 6390.65 examples/s]
Generating train split: 80565779 examples [1:16:48, 6298.74 examples/s]
Generating train split: 80567377 examples [1:16:48, 8340.10 examples/s]
Generating train split: 80568450 examples [1:16:48, 8794.10 examples/s]
Generating train split: 80569456 examples [1:16:49, 7537.95 examples/s]
Generating train split: 80570719 examples [1:16:49, 8302.34 examples/s]
Generating train split: 80571644 examples [1:16:49, 7308.78 examples/s]
Generating train split: 80572559 examples [1:16:49, 7698.34 examples/s]
Generating train split: 80573402 examples [1:16:49, 6558.43 examples/s]
Generating train split: 80574687 examples [1:16:49, 7947.54 examples/s]
Generating train split: 80575575 examples [1:16:49, 7472.95 examples/s]
Generating train split: 80576397 examples [1:16:50, 7077.28 examples/s]
Generating train split: 80577158 examples [1:16:50, 5162.38 examples/s]
Generating train split: 80578416 examples [1:16:50, 6622.29 examples/s]
Generating train split: 80579806 examples [1:16:50, 8179.98 examples/s]
Generating train split: 80580788 examples [1:16:50, 7529.60 examples/s]
Generating train split: 80581663 examples [1:16:50, 5465.50 examples/s]
Generating train split: 80583582 examples [1:16:51, 8031.73 examples/s]
Generating train split: 80584694 examples [1:16:51, 8664.37 examples/s]
Generating train split: 80585775 examples [1:16:51, 7794.72 examples/s]
Generating train split: 80586720 examples [1:16:51, 8144.79 examples/s]
Generating train split: 80588426 examples [1:16:51, 10259.89 examples/s]
Generating train split: 80590556 examples [1:16:51, 13046.06 examples/s]
Generating train split: 80592659 examples [1:16:51, 15158.69 examples/s]
Generating train split: 80594312 examples [1:16:51, 14294.33 examples/s]
Generating train split: 80596704 examples [1:16:52, 16642.89 examples/s]
Generating train split: 80598471 examples [1:16:52, 15552.48 examples/s]
Generating train split: 80600108 examples [1:16:52, 15226.89 examples/s]
Generating train split: 80603173 examples [1:16:52, 19319.92 examples/s]
Generating train split: 80605203 examples [1:16:52, 14051.09 examples/s]
Generating train split: 80607131 examples [1:16:52, 14950.64 examples/s]
Generating train split: 80608834 examples [1:16:52, 13629.27 examples/s]
Generating train split: 80610357 examples [1:16:53, 13035.69 examples/s]
Generating train split: 80611772 examples [1:16:53, 11574.71 examples/s]
Generating train split: 80613462 examples [1:16:53, 12041.14 examples/s]
Generating train split: 80614742 examples [1:16:53, 11303.11 examples/s]
Generating train split: 80616652 examples [1:16:53, 13126.55 examples/s]
Generating train split: 80618048 examples [1:16:53, 11744.69 examples/s]
Generating train split: 80619304 examples [1:16:53, 8151.76 examples/s] 
Generating train split: 80621636 examples [1:16:54, 11004.26 examples/s]
Generating train split: 80623031 examples [1:16:54, 6932.61 examples/s] 
Generating train split: 80624281 examples [1:16:54, 7777.40 examples/s]
Generating train split: 80625412 examples [1:16:54, 6609.25 examples/s]
Generating train split: 80626345 examples [1:16:54, 7058.26 examples/s]
Generating train split: 80627923 examples [1:16:55, 8742.38 examples/s]
Generating train split: 80629893 examples [1:16:55, 11100.00 examples/s]
Generating train split: 80632032 examples [1:16:55, 13487.29 examples/s]
Generating train split: 80633638 examples [1:16:55, 9749.45 examples/s] 
Generating train split: 80641895 examples [1:16:55, 24206.37 examples/s]
Generating train split: 80650574 examples [1:16:55, 38028.95 examples/s]
Generating train split: 80655545 examples [1:16:55, 29849.19 examples/s]
Generating train split: 80659618 examples [1:16:56, 18007.67 examples/s]
Generating train split: 80662723 examples [1:16:56, 16799.59 examples/s]
Generating train split: 80665302 examples [1:16:56, 16998.87 examples/s]
Generating train split: 80673784 examples [1:16:56, 27963.52 examples/s]
Generating train split: 80680860 examples [1:16:57, 35595.60 examples/s]
Generating train split: 80685798 examples [1:16:57, 22376.20 examples/s]
Generating train split: 80689582 examples [1:16:57, 20008.83 examples/s]
Generating train split: 80692678 examples [1:16:57, 19947.89 examples/s]
Generating train split: 80695438 examples [1:16:58, 12806.02 examples/s]
Generating train split: 80703009 examples [1:16:58, 20524.16 examples/s]
Generating train split: 80710826 examples [1:16:58, 29118.31 examples/s]
Generating train split: 80715785 examples [1:16:59, 18319.28 examples/s]
Generating train split: 80720618 examples [1:16:59, 22013.60 examples/s]
Generating train split: 80728921 examples [1:16:59, 31139.90 examples/s]
Generating train split: 80735384 examples [1:16:59, 37028.76 examples/s]
Generating train split: 80741067 examples [1:17:00, 21462.88 examples/s]
Generating train split: 80745347 examples [1:17:00, 15278.73 examples/s]
Generating train split: 80748590 examples [1:17:00, 15447.80 examples/s]
Generating train split: 80751344 examples [1:17:00, 16712.92 examples/s]
Generating train split: 80756019 examples [1:17:00, 20997.54 examples/s]
Generating train split: 80759832 examples [1:17:01, 23920.17 examples/s]
Generating train split: 80764789 examples [1:17:01, 28947.46 examples/s]
Generating train split: 80770628 examples [1:17:01, 35386.16 examples/s]
Generating train split: 80775200 examples [1:17:01, 37842.66 examples/s]
Generating train split: 80782591 examples [1:17:01, 46991.62 examples/s]
Generating train split: 80788906 examples [1:17:01, 51287.36 examples/s]
Generating train split: 80795450 examples [1:17:01, 55182.21 examples/s]
Generating train split: 80801380 examples [1:17:01, 55786.45 examples/s]
Generating train split: 80807685 examples [1:17:01, 57844.11 examples/s]
Generating train split: 80813683 examples [1:17:01, 55837.25 examples/s]
Generating train split: 80819434 examples [1:17:02, 55200.63 examples/s]
Generating train split: 80825076 examples [1:17:02, 54677.34 examples/s]
Generating train split: 80831436 examples [1:17:02, 57200.53 examples/s]
Generating train split: 80837230 examples [1:17:02, 55482.30 examples/s]
Generating train split: 80842841 examples [1:17:02, 54974.28 examples/s]
Generating train split: 80848387 examples [1:17:02, 48225.04 examples/s]
Generating train split: 80853384 examples [1:17:02, 46852.52 examples/s]
Generating train split: 80858779 examples [1:17:02, 48723.81 examples/s]
Generating train split: 80863932 examples [1:17:02, 49485.67 examples/s]
Generating train split: 80869627 examples [1:17:03, 51593.76 examples/s]
Generating train split: 80875192 examples [1:17:03, 52751.43 examples/s]
Generating train split: 80880523 examples [1:17:03, 51378.94 examples/s]
Generating train split: 80885703 examples [1:17:03, 46917.35 examples/s]
Generating train split: 80890496 examples [1:17:03, 43912.62 examples/s]
Generating train split: 80894988 examples [1:17:03, 40501.45 examples/s]
Generating train split: 80899135 examples [1:17:03, 33611.17 examples/s]
Generating train split: 80904706 examples [1:17:03, 38760.96 examples/s]
Generating train split: 80908891 examples [1:17:04, 33977.36 examples/s]
Generating train split: 80912574 examples [1:17:04, 30972.37 examples/s]
Generating train split: 80915893 examples [1:17:04, 23775.26 examples/s]
Generating train split: 80918634 examples [1:17:04, 24219.81 examples/s]
Generating train split: 80921330 examples [1:17:04, 24375.92 examples/s]
Generating train split: 80923967 examples [1:17:04, 18884.36 examples/s]
Generating train split: 80926149 examples [1:17:05, 13746.77 examples/s]
Generating train split: 80927899 examples [1:17:05, 13900.61 examples/s]
Generating train split: 80929557 examples [1:17:05, 13585.54 examples/s]
Generating train split: 80931097 examples [1:17:05, 9168.96 examples/s] 
Generating train split: 80932639 examples [1:17:05, 10100.32 examples/s]
Generating train split: 80933929 examples [1:17:06, 7897.75 examples/s] 
Generating train split: 80934978 examples [1:17:06, 8002.29 examples/s]
Generating train split: 80936498 examples [1:17:06, 9000.20 examples/s]
Generating train split: 80937574 examples [1:17:06, 6719.37 examples/s]
Generating train split: 80938447 examples [1:17:06, 7062.26 examples/s]
Generating train split: 80939309 examples [1:17:07, 4228.34 examples/s]
Generating train split: 80939970 examples [1:17:07, 4456.74 examples/s]
Generating train split: 80941360 examples [1:17:07, 5989.96 examples/s]
Generating train split: 80942899 examples [1:17:07, 7757.46 examples/s]
Generating train split: 80943965 examples [1:17:07, 7065.78 examples/s]
Generating train split: 80944880 examples [1:17:08, 5587.38 examples/s]
Generating train split: 80945851 examples [1:17:08, 6297.16 examples/s]
Generating train split: 80946669 examples [1:17:08, 6351.99 examples/s]
Generating train split: 80947492 examples [1:17:08, 6626.06 examples/s]
Generating train split: 80948258 examples [1:17:08, 6843.80 examples/s]
Generating train split: 80951090 examples [1:17:08, 12105.65 examples/s]
Generating train split: 80952450 examples [1:17:08, 10557.69 examples/s]
Generating train split: 80953651 examples [1:17:08, 10571.97 examples/s]
Generating train split: 80955819 examples [1:17:09, 13283.63 examples/s]
Generating train split: 80957274 examples [1:17:09, 10312.30 examples/s]
Generating train split: 80958489 examples [1:17:09, 7812.15 examples/s] 
Generating train split: 80959478 examples [1:17:09, 5581.35 examples/s]
Generating train split: 80960584 examples [1:17:10, 6419.49 examples/s]
Generating train split: 80961564 examples [1:17:10, 7013.30 examples/s]
Generating train split: 80962466 examples [1:17:10, 6835.54 examples/s]
Generating train split: 80963290 examples [1:17:10, 6829.08 examples/s]
Generating train split: 80971055 examples [1:17:10, 22725.71 examples/s]
Generating train split: 80980293 examples [1:17:10, 39630.17 examples/s]
Generating train split: 80985082 examples [1:17:10, 27935.94 examples/s]
Generating train split: 80988930 examples [1:17:11, 15515.39 examples/s]
Generating train split: 80991819 examples [1:17:11, 14990.68 examples/s]
Generating train split: 80999863 examples [1:17:11, 23933.17 examples/s]
Generating train split: 81008245 examples [1:17:11, 33461.80 examples/s]
Generating train split: 81013530 examples [1:17:12, 24031.29 examples/s]
Generating train split: 81017639 examples [1:17:12, 18723.19 examples/s]
Generating train split: 81020833 examples [1:17:13, 14193.75 examples/s]
Generating train split: 81023287 examples [1:17:13, 10595.00 examples/s]
Generating train split: 81025156 examples [1:17:13, 9455.35 examples/s] 
Generating train split: 81026651 examples [1:17:14, 7974.81 examples/s]
Generating train split: 81028770 examples [1:17:14, 9402.28 examples/s]
Generating train split: 81030232 examples [1:17:14, 8355.74 examples/s]
Generating train split: 81031430 examples [1:17:14, 8680.61 examples/s]
Generating train split: 81032835 examples [1:17:14, 9527.40 examples/s]
Generating train split: 81034059 examples [1:17:14, 8766.57 examples/s]
Generating train split: 81035129 examples [1:17:15, 7463.48 examples/s]
Generating train split: 81036020 examples [1:17:15, 7026.46 examples/s]
Generating train split: 81037011 examples [1:17:15, 7521.45 examples/s]
Generating train split: 81038428 examples [1:17:15, 8890.37 examples/s]
Generating train split: 81039437 examples [1:17:15, 6131.37 examples/s]
Generating train split: 81040788 examples [1:17:15, 7466.84 examples/s]
Generating train split: 81041756 examples [1:17:16, 4683.92 examples/s]
Generating train split: 81049220 examples [1:17:16, 15039.16 examples/s]
Generating train split: 81057159 examples [1:17:16, 26269.39 examples/s]
Generating train split: 81061553 examples [1:17:16, 28811.49 examples/s]
Generating train split: 81065699 examples [1:17:17, 23221.49 examples/s]
Generating train split: 81069080 examples [1:17:17, 17710.86 examples/s]
Generating train split: 81077112 examples [1:17:17, 27532.20 examples/s]
Generating train split: 81084139 examples [1:17:17, 35312.72 examples/s]
Generating train split: 81089234 examples [1:17:18, 20041.33 examples/s]
Generating train split: 81093088 examples [1:17:18, 13548.62 examples/s]
Generating train split: 81095971 examples [1:17:19, 9757.92 examples/s] 
Generating train split: 81098132 examples [1:17:19, 9090.59 examples/s]
Generating train split: 81099855 examples [1:17:20, 7792.22 examples/s]
Generating train split: 81101261 examples [1:17:20, 8350.36 examples/s]
Generating train split: 81102607 examples [1:17:20, 8210.99 examples/s]
Generating train split: 81103771 examples [1:17:20, 7162.72 examples/s]
Generating train split: 81104723 examples [1:17:20, 6467.68 examples/s]
Generating train split: 81105564 examples [1:17:20, 6733.73 examples/s]
Generating train split: 81106876 examples [1:17:20, 7829.09 examples/s]
Generating train split: 81107840 examples [1:17:21, 6312.03 examples/s]
Generating train split: 81110429 examples [1:17:21, 9802.95 examples/s]
Generating train split: 81111768 examples [1:17:21, 7164.54 examples/s]
Generating train split: 81112881 examples [1:17:21, 7737.09 examples/s]
Generating train split: 81113937 examples [1:17:21, 7626.87 examples/s]
Generating train split: 81114900 examples [1:17:22, 7904.65 examples/s]
Generating train split: 81115894 examples [1:17:22, 8299.89 examples/s]
Generating train split: 81116850 examples [1:17:22, 7843.79 examples/s]
Generating train split: 81117827 examples [1:17:22, 8271.72 examples/s]
Generating train split: 81119006 examples [1:17:22, 8929.79 examples/s]
Generating train split: 81120012 examples [1:17:22, 9206.78 examples/s]
Generating train split: 81120982 examples [1:17:22, 7308.19 examples/s]
Generating train split: 81121808 examples [1:17:22, 7242.31 examples/s]
Generating train split: 81123640 examples [1:17:22, 9916.21 examples/s]
Generating train split: 81125528 examples [1:17:23, 12212.51 examples/s]
Generating train split: 81126863 examples [1:17:23, 7330.46 examples/s] 
Generating train split: 81129586 examples [1:17:23, 10976.76 examples/s]
Generating train split: 81131136 examples [1:17:23, 11283.02 examples/s]
Generating train split: 81132591 examples [1:17:24, 7238.51 examples/s] 
Generating train split: 81133722 examples [1:17:24, 4938.67 examples/s]
Generating train split: 81134586 examples [1:17:24, 4850.86 examples/s]
Generating train split: 81135324 examples [1:17:25, 4147.53 examples/s]
Generating train split: 81135924 examples [1:17:25, 3875.37 examples/s]
Generating train split: 81136443 examples [1:17:25, 3518.59 examples/s]
Generating train split: 81136877 examples [1:17:25, 3618.26 examples/s]
Generating train split: 81137341 examples [1:17:25, 3784.84 examples/s]
Generating train split: 81137782 examples [1:17:25, 3884.36 examples/s]
Generating train split: 81138650 examples [1:17:25, 4781.77 examples/s]
Generating train split: 81139177 examples [1:17:26, 3690.22 examples/s]
Generating train split: 81139924 examples [1:17:26, 4446.77 examples/s]
Generating train split: 81140453 examples [1:17:26, 3941.06 examples/s]
Generating train split: 81140921 examples [1:17:26, 3888.44 examples/s]
Generating train split: 81141703 examples [1:17:26, 4758.74 examples/s]
Generating train split: 81144396 examples [1:17:26, 10131.05 examples/s]
Generating train split: 81152852 examples [1:17:26, 29263.15 examples/s]
Generating train split: 81158848 examples [1:17:26, 37383.22 examples/s]
Generating train split: 81162980 examples [1:17:27, 13319.72 examples/s]
Generating train split: 81166035 examples [1:17:28, 11714.44 examples/s]
Generating train split: 81168430 examples [1:17:28, 11881.44 examples/s]
Generating train split: 81170490 examples [1:17:28, 11737.53 examples/s]
Generating train split: 81172262 examples [1:17:28, 11018.32 examples/s]
Generating train split: 81173772 examples [1:17:28, 9554.95 examples/s] 
Generating train split: 81176204 examples [1:17:28, 11789.01 examples/s]
Generating train split: 81184095 examples [1:17:29, 23719.39 examples/s]
Generating train split: 81189907 examples [1:17:29, 30685.77 examples/s]
Generating train split: 81194093 examples [1:17:29, 23972.29 examples/s]
Generating train split: 81197489 examples [1:17:29, 16972.53 examples/s]
Generating train split: 81200138 examples [1:17:30, 13778.61 examples/s]
Generating train split: 81202246 examples [1:17:30, 11736.66 examples/s]
Generating train split: 81203933 examples [1:17:30, 11601.51 examples/s]
Generating train split: 81205448 examples [1:17:30, 11316.49 examples/s]
Generating train split: 81206824 examples [1:17:30, 9807.24 examples/s] 
Generating train split: 81208237 examples [1:17:31, 10506.16 examples/s]
Generating train split: 81209459 examples [1:17:31, 8911.26 examples/s] 
Generating train split: 81210492 examples [1:17:31, 8235.49 examples/s]
Generating train split: 81212161 examples [1:17:31, 9854.30 examples/s]
Generating train split: 81213537 examples [1:17:31, 10622.44 examples/s]
Generating train split: 81214737 examples [1:17:31, 6781.83 examples/s] 
Generating train split: 81216467 examples [1:17:32, 8584.65 examples/s]
Generating train split: 81217645 examples [1:17:32, 9204.85 examples/s]
Generating train split: 81218823 examples [1:17:32, 8265.31 examples/s]
Generating train split: 81227339 examples [1:17:32, 24366.08 examples/s]
Generating train split: 81235726 examples [1:17:32, 38057.66 examples/s]
Generating train split: 81240538 examples [1:17:32, 24830.29 examples/s]
Generating train split: 81246699 examples [1:17:33, 31375.84 examples/s]
Generating train split: 81255499 examples [1:17:33, 42853.51 examples/s]
Generating train split: 81261287 examples [1:17:33, 30123.83 examples/s]
Generating train split: 81265848 examples [1:17:33, 31786.80 examples/s]
Generating train split: 81274811 examples [1:17:33, 42956.14 examples/s]
Generating train split: 81281988 examples [1:17:33, 49183.36 examples/s]
Generating train split: 81288153 examples [1:17:34, 38921.28 examples/s]
Generating train split: 81293232 examples [1:17:34, 15539.60 examples/s]
Generating train split: 81296955 examples [1:17:35, 12808.26 examples/s]
Generating train split: 81304396 examples [1:17:35, 18462.97 examples/s]
Generating train split: 81312633 examples [1:17:35, 25870.79 examples/s]
Generating train split: 81318060 examples [1:17:35, 25760.60 examples/s]
Generating train split: 81322623 examples [1:17:36, 17158.46 examples/s]
Generating train split: 81326070 examples [1:17:37, 8534.51 examples/s] 
Generating train split: 81328566 examples [1:17:37, 8366.83 examples/s]
Generating train split: 81330542 examples [1:17:38, 7982.68 examples/s]
Generating train split: 81332167 examples [1:17:38, 8658.41 examples/s]
Generating train split: 81333740 examples [1:17:38, 8457.42 examples/s]
Generating train split: 81335067 examples [1:17:38, 7345.71 examples/s]
Generating train split: 81336143 examples [1:17:39, 6177.41 examples/s]
Generating train split: 81337002 examples [1:17:39, 5786.38 examples/s]
Generating train split: 81338454 examples [1:17:39, 6974.44 examples/s]
Generating train split: 81340780 examples [1:17:39, 9633.85 examples/s]
Generating train split: 81348011 examples [1:17:39, 21489.48 examples/s]
Generating train split: 81356135 examples [1:17:39, 34057.33 examples/s]
Generating train split: 81360710 examples [1:17:40, 18096.22 examples/s]
Generating train split: 81364172 examples [1:17:40, 17188.47 examples/s]
Generating train split: 81367043 examples [1:17:40, 13598.85 examples/s]
Generating train split: 81374893 examples [1:17:40, 22007.82 examples/s]
Generating train split: 81383614 examples [1:17:41, 32188.19 examples/s]
Generating train split: 81388978 examples [1:17:41, 26538.57 examples/s]
Generating train split: 81393279 examples [1:17:42, 13210.73 examples/s]
Generating train split: 81396442 examples [1:17:42, 11432.85 examples/s]
Generating train split: 81398875 examples [1:17:42, 12136.52 examples/s]
Generating train split: 81401100 examples [1:17:42, 12198.11 examples/s]
Generating train split: 81403024 examples [1:17:43, 11040.41 examples/s]
Generating train split: 81404604 examples [1:17:43, 11656.56 examples/s]
Generating train split: 81406179 examples [1:17:43, 8239.66 examples/s] 
Generating train split: 81407883 examples [1:17:43, 9380.88 examples/s]
Generating train split: 81409534 examples [1:17:43, 10418.87 examples/s]
Generating train split: 81410950 examples [1:17:44, 5895.80 examples/s] 
Generating train split: 81412217 examples [1:17:44, 6678.01 examples/s]
Generating train split: 81413329 examples [1:17:44, 6304.06 examples/s]
Generating train split: 81420004 examples [1:17:44, 15604.70 examples/s]
Generating train split: 81427320 examples [1:17:45, 25905.91 examples/s]
Generating train split: 81431346 examples [1:17:45, 19830.22 examples/s]
Generating train split: 81434540 examples [1:17:45, 14693.10 examples/s]
Generating train split: 81442730 examples [1:17:45, 23987.29 examples/s]
Generating train split: 81448431 examples [1:17:45, 29433.39 examples/s]
Generating train split: 81453084 examples [1:17:46, 19601.25 examples/s]
Generating train split: 81456646 examples [1:17:46, 14656.02 examples/s]
Generating train split: 81464332 examples [1:17:46, 22030.09 examples/s]
Generating train split: 81472191 examples [1:17:47, 30203.35 examples/s]
Generating train split: 81477490 examples [1:17:47, 15961.35 examples/s]
Generating train split: 81481415 examples [1:17:48, 9214.77 examples/s] 
Generating train split: 81484274 examples [1:17:49, 7824.89 examples/s]
Generating train split: 81486414 examples [1:17:50, 6017.44 examples/s]
Generating train split: 81487996 examples [1:17:50, 4867.28 examples/s]
Generating train split: 81489181 examples [1:17:51, 4530.61 examples/s]
Generating train split: 81490105 examples [1:17:51, 4339.56 examples/s]
Generating train split: 81490856 examples [1:17:51, 3913.88 examples/s]
Generating train split: 81491460 examples [1:17:52, 4035.67 examples/s]
Generating train split: 81492940 examples [1:17:52, 5249.43 examples/s]
Generating train split: 81501345 examples [1:17:52, 16182.78 examples/s]
Generating train split: 81510282 examples [1:17:52, 28289.25 examples/s]
Generating train split: 81515141 examples [1:17:53, 14750.99 examples/s]
Generating train split: 81518755 examples [1:17:53, 10378.73 examples/s]
Generating train split: 81521443 examples [1:17:54, 9335.97 examples/s] 
Generating train split: 81529105 examples [1:17:54, 15398.58 examples/s]
Generating train split: 81536707 examples [1:17:54, 22148.20 examples/s]
Generating train split: 81541480 examples [1:17:55, 9699.03 examples/s] 
Generating train split: 81544939 examples [1:17:56, 6446.17 examples/s]
Generating train split: 81547440 examples [1:17:57, 5810.24 examples/s]
Generating train split: 81549323 examples [1:17:57, 5726.75 examples/s]
Generating train split: 81550799 examples [1:17:57, 6190.66 examples/s]
Generating train split: 81552164 examples [1:17:58, 6258.11 examples/s]
Generating train split: 81553328 examples [1:17:58, 4312.21 examples/s]
Generating train split: 81554500 examples [1:17:58, 4887.02 examples/s]
Generating train split: 81555436 examples [1:17:59, 3537.52 examples/s]
Generating train split: 81556131 examples [1:17:59, 3774.88 examples/s]
Generating train split: 81558256 examples [1:17:59, 5732.97 examples/s]
Generating train split: 81559356 examples [1:17:59, 5661.01 examples/s]
Generating train split: 81560383 examples [1:18:00, 6315.49 examples/s]
Generating train split: 81561344 examples [1:18:00, 5205.97 examples/s]
Generating train split: 81562116 examples [1:18:00, 4255.02 examples/s]
Generating train split: 81562733 examples [1:18:00, 4117.73 examples/s]
Generating train split: 81563275 examples [1:18:01, 2998.57 examples/s]
Generating train split: 81564392 examples [1:18:01, 4103.41 examples/s]
Generating train split: 81565029 examples [1:18:01, 4178.64 examples/s]
Generating train split: 81566045 examples [1:18:01, 5157.54 examples/s]
Generating train split: 81566730 examples [1:18:01, 3877.07 examples/s]
Generating train split: 81567359 examples [1:18:01, 4280.84 examples/s]
Generating train split: 81568289 examples [1:18:02, 5243.13 examples/s]
Generating train split: 81572490 examples [1:18:02, 13192.54 examples/s]
Generating train split: 81581586 examples [1:18:02, 31539.21 examples/s]
Generating train split: 81586978 examples [1:18:02, 37166.94 examples/s]
Generating train split: 81591370 examples [1:18:02, 19843.02 examples/s]
Generating train split: 81594722 examples [1:18:03, 11110.78 examples/s]
Generating train split: 81597221 examples [1:18:03, 10017.56 examples/s]
Generating train split: 81599179 examples [1:18:04, 9028.75 examples/s] 
Generating train split: 81600755 examples [1:18:05, 5281.16 examples/s]
Generating train split: 81602143 examples [1:18:05, 5940.44 examples/s]
Generating train split: 81603358 examples [1:18:05, 5220.11 examples/s]
Generating train split: 81604304 examples [1:18:05, 5294.07 examples/s]
Generating train split: 81605138 examples [1:18:06, 3658.07 examples/s]
Generating train split: 81605767 examples [1:18:06, 2810.00 examples/s]
Generating train split: 81606848 examples [1:18:06, 3553.14 examples/s]
Generating train split: 81607513 examples [1:18:07, 3333.94 examples/s]
Generating train split: 81608058 examples [1:18:07, 3266.42 examples/s]
Generating train split: 81610102 examples [1:18:07, 5653.72 examples/s]
Generating train split: 81612702 examples [1:18:07, 9027.84 examples/s]
Generating train split: 81614149 examples [1:18:07, 7610.51 examples/s]
Generating train split: 81615330 examples [1:18:07, 8205.99 examples/s]
Generating train split: 81616569 examples [1:18:07, 9017.56 examples/s]
Generating train split: 81625108 examples [1:18:08, 25607.37 examples/s]
Generating train split: 81633935 examples [1:18:08, 40432.76 examples/s]
Generating train split: 81638946 examples [1:18:08, 25755.18 examples/s]
Generating train split: 81642875 examples [1:18:09, 15169.11 examples/s]
Generating train split: 81645833 examples [1:18:09, 15871.02 examples/s]
Generating train split: 81654000 examples [1:18:09, 25029.12 examples/s]
Generating train split: 81662872 examples [1:18:09, 35586.98 examples/s]
Generating train split: 81668552 examples [1:18:09, 25903.88 examples/s]
Generating train split: 81676965 examples [1:18:09, 34729.44 examples/s]
Generating train split: 81682580 examples [1:18:09, 38534.59 examples/s]
Generating train split: 81688202 examples [1:18:11, 14186.74 examples/s]
Generating train split: 81692289 examples [1:18:11, 11113.03 examples/s]
Generating train split: 81695338 examples [1:18:12, 10366.57 examples/s]
Generating train split: 81697717 examples [1:18:12, 8484.17 examples/s] 
Generating train split: 81699518 examples [1:18:13, 7470.26 examples/s]
Generating train split: 81700920 examples [1:18:13, 7672.76 examples/s]
Generating train split: 81702172 examples [1:18:13, 7794.57 examples/s]
Generating train split: 81703314 examples [1:18:13, 6863.76 examples/s]
Generating train split: 81710356 examples [1:18:13, 15084.31 examples/s]
Generating train split: 81718480 examples [1:18:13, 25323.97 examples/s]
Generating train split: 81722810 examples [1:18:14, 17436.29 examples/s]
Generating train split: 81726121 examples [1:18:14, 11441.81 examples/s]
Generating train split: 81734113 examples [1:18:14, 18454.93 examples/s]
Generating train split: 81741717 examples [1:18:15, 25714.05 examples/s]
Generating train split: 81746839 examples [1:18:15, 16873.14 examples/s]
Generating train split: 81750686 examples [1:18:16, 12627.29 examples/s]
Generating train split: 81753579 examples [1:18:16, 9781.63 examples/s] 
Generating train split: 81755754 examples [1:18:16, 10653.17 examples/s]
Generating train split: 81757848 examples [1:18:17, 10640.01 examples/s]
Generating train split: 81759628 examples [1:18:17, 9999.31 examples/s] 
Generating train split: 81761111 examples [1:18:17, 9583.88 examples/s]
Generating train split: 81763440 examples [1:18:17, 11560.95 examples/s]
Generating train split: 81765039 examples [1:18:17, 9497.79 examples/s] 
Generating train split: 81766425 examples [1:18:17, 10189.03 examples/s]
Generating train split: 81767759 examples [1:18:18, 8418.71 examples/s] 
Generating train split: 81769090 examples [1:18:18, 9203.33 examples/s]
Generating train split: 81770250 examples [1:18:18, 8943.27 examples/s]
Generating train split: 81771301 examples [1:18:18, 6757.98 examples/s]
Generating train split: 81772153 examples [1:18:18, 6061.89 examples/s]
Generating train split: 81773080 examples [1:18:19, 6627.79 examples/s]
Generating train split: 81774728 examples [1:18:19, 8491.34 examples/s]
Generating train split: 81775742 examples [1:18:19, 7905.36 examples/s]
Generating train split: 81776655 examples [1:18:19, 6928.59 examples/s]
Generating train split: 81777446 examples [1:18:19, 6052.28 examples/s]
Generating train split: 81778683 examples [1:18:19, 7314.05 examples/s]
Generating train split: 81779609 examples [1:18:19, 7748.32 examples/s]
Generating train split: 81780479 examples [1:18:20, 6703.52 examples/s]
Generating train split: 81783186 examples [1:18:20, 11268.67 examples/s]
Generating train split: 81784517 examples [1:18:20, 10122.22 examples/s]
Generating train split: 81785695 examples [1:18:20, 8404.56 examples/s] 
Generating train split: 81786686 examples [1:18:20, 6323.59 examples/s]
Generating train split: 81788201 examples [1:18:20, 7851.80 examples/s]
Generating train split: 81792181 examples [1:18:21, 14289.09 examples/s]
Generating train split: 81800837 examples [1:18:21, 30437.94 examples/s]
Generating train split: 81804761 examples [1:18:21, 30101.16 examples/s]
Generating train split: 81808385 examples [1:18:22, 10717.18 examples/s]
Generating train split: 81811043 examples [1:18:22, 8856.63 examples/s] 
Generating train split: 81813078 examples [1:18:22, 8423.98 examples/s]
Generating train split: 81814709 examples [1:18:23, 5652.82 examples/s]
Generating train split: 81815921 examples [1:18:23, 5522.80 examples/s]
Generating train split: 81816925 examples [1:18:24, 5806.72 examples/s]
Generating train split: 81821079 examples [1:18:24, 10009.84 examples/s]
Generating train split: 81828865 examples [1:18:24, 19799.41 examples/s]
Generating train split: 81832523 examples [1:18:24, 15645.24 examples/s]
Generating train split: 81839616 examples [1:18:24, 23616.87 examples/s]
Generating train split: 81848533 examples [1:18:24, 34811.53 examples/s]
Generating train split: 81854098 examples [1:18:25, 28477.51 examples/s]
Generating train split: 81862301 examples [1:18:25, 37592.43 examples/s]
Generating train split: 81867907 examples [1:18:25, 40339.52 examples/s]
Generating train split: 81873341 examples [1:18:25, 21526.33 examples/s]
Generating train split: 81880990 examples [1:18:25, 28791.44 examples/s]
Generating train split: 81889755 examples [1:18:26, 38140.12 examples/s]
Generating train split: 81895995 examples [1:18:26, 28511.70 examples/s]
Generating train split: 81900873 examples [1:18:27, 16948.18 examples/s]
Generating train split: 81904512 examples [1:18:27, 13906.24 examples/s]
Generating train split: 81907300 examples [1:18:28, 8292.61 examples/s] 
Generating train split: 81909337 examples [1:18:28, 9078.09 examples/s]
Generating train split: 81911320 examples [1:18:29, 7668.51 examples/s]
Generating train split: 81912846 examples [1:18:29, 8075.80 examples/s]
Generating train split: 81914257 examples [1:18:29, 7423.05 examples/s]
Generating train split: 81922384 examples [1:18:29, 16158.03 examples/s]
Generating train split: 81930173 examples [1:18:29, 25081.60 examples/s]
Generating train split: 81934783 examples [1:18:30, 17245.81 examples/s]
Generating train split: 81938290 examples [1:18:30, 10131.34 examples/s]
Generating train split: 81940876 examples [1:18:31, 8111.21 examples/s] 
Generating train split: 81942828 examples [1:18:32, 4687.12 examples/s]
Generating train split: 81944239 examples [1:18:33, 3305.92 examples/s]
Generating train split: 81945270 examples [1:18:34, 3229.06 examples/s]
Generating train split: 81946070 examples [1:18:34, 3326.12 examples/s]
Generating train split: 81947195 examples [1:18:34, 3881.31 examples/s]
Generating train split: 81948509 examples [1:18:34, 4744.81 examples/s]
Generating train split: 81949472 examples [1:18:35, 3678.35 examples/s]
Generating train split: 81950200 examples [1:18:35, 3900.05 examples/s]
Generating train split: 81951425 examples [1:18:35, 4926.37 examples/s]
Generating train split: 81952257 examples [1:18:35, 4919.32 examples/s]
Generating train split: 81952992 examples [1:18:35, 4691.38 examples/s]
Generating train split: 81954600 examples [1:18:35, 6607.58 examples/s]
Generating train split: 81955923 examples [1:18:35, 7899.84 examples/s]
Generating train split: 81956958 examples [1:18:36, 4927.87 examples/s]
Generating train split: 81957757 examples [1:18:36, 4363.44 examples/s]
Generating train split: 81958409 examples [1:18:36, 4080.85 examples/s]
Generating train split: 81959189 examples [1:18:36, 4664.53 examples/s]
Generating train split: 81959811 examples [1:18:37, 3473.65 examples/s]
Generating train split: 81960310 examples [1:18:37, 3377.98 examples/s]
Generating train split: 81961174 examples [1:18:37, 4201.94 examples/s]
Generating train split: 81961717 examples [1:18:37, 3718.66 examples/s]
Generating train split: 81962180 examples [1:18:37, 3259.88 examples/s]
Generating train split: 81963997 examples [1:18:38, 5957.89 examples/s]
Generating train split: 81964816 examples [1:18:38, 5319.05 examples/s]
Generating train split: 81965517 examples [1:18:38, 4877.46 examples/s]
Generating train split: 81966115 examples [1:18:38, 2929.24 examples/s]
Generating train split: 81966581 examples [1:18:39, 3098.70 examples/s]
Generating train split: 81967283 examples [1:18:39, 3726.27 examples/s]
Generating train split: 81967806 examples [1:18:39, 3300.15 examples/s]
Generating train split: 81969877 examples [1:18:39, 6423.02 examples/s]
Generating train split: 81972783 examples [1:18:39, 10947.48 examples/s]
Generating train split: 81974259 examples [1:18:39, 9686.03 examples/s] 
Generating train split: 81975524 examples [1:18:40, 7040.77 examples/s]
Generating train split: 81977405 examples [1:18:40, 9003.30 examples/s]
Generating train split: 81978668 examples [1:18:40, 8595.94 examples/s]
Generating train split: 81979933 examples [1:18:40, 9334.96 examples/s]
Generating train split: 81981081 examples [1:18:40, 6918.84 examples/s]
Generating train split: 81982001 examples [1:18:40, 6044.33 examples/s]
Generating train split: 81982784 examples [1:18:41, 5971.91 examples/s]
Generating train split: 81984286 examples [1:18:41, 7691.80 examples/s]
Generating train split: 81985707 examples [1:18:41, 9066.30 examples/s]
Generating train split: 81986802 examples [1:18:41, 8984.87 examples/s]
Generating train split: 81988916 examples [1:18:41, 11895.28 examples/s]
Generating train split: 81990271 examples [1:18:42, 6178.04 examples/s] 
Generating train split: 81991307 examples [1:18:42, 6785.93 examples/s]
Generating train split: 81992333 examples [1:18:42, 5028.67 examples/s]
Generating train split: 81993174 examples [1:18:42, 5530.91 examples/s]
Generating train split: 81993985 examples [1:18:42, 4298.32 examples/s]
Generating train split: 81995014 examples [1:18:43, 5185.73 examples/s]
Generating train split: 81996225 examples [1:18:43, 6404.67 examples/s]
Generating train split: 81997362 examples [1:18:43, 7378.51 examples/s]
Generating train split: 81998326 examples [1:18:43, 4371.75 examples/s]
Generating train split: 81999421 examples [1:18:43, 5351.66 examples/s]
Generating train split: 82000261 examples [1:18:44, 3963.61 examples/s]
Generating train split: 82001284 examples [1:18:44, 4870.78 examples/s]
Generating train split: 82002593 examples [1:18:44, 6255.06 examples/s]
Generating train split: 82003510 examples [1:18:44, 4979.32 examples/s]
Generating train split: 82004257 examples [1:18:44, 3843.01 examples/s]
Generating train split: 82004841 examples [1:18:45, 3126.32 examples/s]
Generating train split: 82005316 examples [1:18:45, 3010.28 examples/s]
Generating train split: 82005818 examples [1:18:45, 3293.10 examples/s]
Generating train split: 82006517 examples [1:18:45, 3838.46 examples/s]
Generating train split: 82007363 examples [1:18:45, 4719.00 examples/s]
Generating train split: 82008071 examples [1:18:45, 5096.81 examples/s]
Generating train split: 82008679 examples [1:18:46, 5156.77 examples/s]
Generating train split: 82009326 examples [1:18:46, 5278.94 examples/s]
Generating train split: 82009903 examples [1:18:46, 3580.75 examples/s]
Generating train split: 82010463 examples [1:18:46, 3965.85 examples/s]
Generating train split: 82011876 examples [1:18:46, 6107.75 examples/s]
Generating train split: 82012646 examples [1:18:46, 4564.37 examples/s]
Generating train split: 82013876 examples [1:18:47, 6037.68 examples/s]
Generating train split: 82015240 examples [1:18:47, 7660.61 examples/s]
Generating train split: 82016216 examples [1:18:47, 6631.53 examples/s]
Generating train split: 82017041 examples [1:18:47, 6656.05 examples/s]
Generating train split: 82017824 examples [1:18:47, 6141.62 examples/s]
Generating train split: 82020024 examples [1:18:47, 9663.94 examples/s]
Generating train split: 82021175 examples [1:18:47, 9015.74 examples/s]
Generating train split: 82022219 examples [1:18:48, 8158.96 examples/s]
Generating train split: 82023718 examples [1:18:48, 9605.62 examples/s]
Generating train split: 82025714 examples [1:18:48, 12099.23 examples/s]
Generating train split: 82027062 examples [1:18:48, 9741.47 examples/s] 
Generating train split: 82028211 examples [1:18:48, 8682.39 examples/s]
Generating train split: 82029211 examples [1:18:48, 8469.08 examples/s]
Generating train split: 82030352 examples [1:18:48, 9044.47 examples/s]
Generating train split: 82031462 examples [1:18:48, 9521.83 examples/s]
Generating train split: 82032481 examples [1:18:49, 8335.39 examples/s]
Generating train split: 82035919 examples [1:18:49, 14360.77 examples/s]
Generating train split: 82037535 examples [1:18:49, 7620.99 examples/s] 
Generating train split: 82040173 examples [1:18:49, 10490.23 examples/s]
Generating train split: 82042315 examples [1:18:49, 12448.46 examples/s]
Generating train split: 82044374 examples [1:18:49, 13944.30 examples/s]
Generating train split: 82046196 examples [1:18:50, 10862.17 examples/s]
Generating train split: 82047678 examples [1:18:50, 11204.52 examples/s]
Generating train split: 82049089 examples [1:18:50, 11374.75 examples/s]
Generating train split: 82050498 examples [1:18:50, 11928.96 examples/s]
Generating train split: 82051866 examples [1:18:50, 9100.01 examples/s] 
Generating train split: 82054189 examples [1:18:50, 11856.76 examples/s]
Generating train split: 82055647 examples [1:18:51, 10742.47 examples/s]
Generating train split: 82056925 examples [1:18:51, 8332.32 examples/s] 
Generating train split: 82058473 examples [1:18:51, 9661.02 examples/s]
Generating train split: 82060401 examples [1:18:51, 11658.32 examples/s]
Generating train split: 82062017 examples [1:18:51, 12692.79 examples/s]
Generating train split: 82063504 examples [1:18:51, 9174.41 examples/s] 
Generating train split: 82064705 examples [1:18:52, 9614.88 examples/s]
Generating train split: 82065896 examples [1:18:52, 8011.56 examples/s]
Generating train split: 82067205 examples [1:18:52, 8923.92 examples/s]
Generating train split: 82068273 examples [1:18:52, 7300.52 examples/s]
Generating train split: 82069163 examples [1:18:52, 7072.51 examples/s]
Generating train split: 82070218 examples [1:18:52, 7563.50 examples/s]
Generating train split: 82071137 examples [1:18:52, 7840.04 examples/s]
Generating train split: 82072044 examples [1:18:53, 8133.23 examples/s]
Generating train split: 82073001 examples [1:18:53, 8452.59 examples/s]
Generating train split: 82073893 examples [1:18:53, 5756.84 examples/s]
Generating train split: 82074613 examples [1:18:53, 5632.12 examples/s]
Generating train split: 82076063 examples [1:18:53, 7481.73 examples/s]
Generating train split: 82077328 examples [1:18:53, 8637.14 examples/s]
Generating train split: 82078330 examples [1:18:53, 8403.61 examples/s]
Generating train split: 82086243 examples [1:18:54, 26016.73 examples/s]
Generating train split: 82094904 examples [1:18:54, 41358.56 examples/s]
Generating train split: 82099496 examples [1:18:54, 28515.05 examples/s]
Generating train split: 82103204 examples [1:18:55, 11648.06 examples/s]
Generating train split: 82105932 examples [1:18:55, 8997.32 examples/s] 
Generating train split: 82107993 examples [1:18:56, 9565.99 examples/s]
Generating train split: 82109826 examples [1:18:56, 8517.75 examples/s]
Generating train split: 82111283 examples [1:18:56, 8335.11 examples/s]
Generating train split: 82112537 examples [1:18:56, 8812.51 examples/s]
Generating train split: 82113778 examples [1:18:56, 7010.48 examples/s]
Generating train split: 82115400 examples [1:18:57, 8256.77 examples/s]
Generating train split: 82116554 examples [1:18:57, 7268.51 examples/s]
Generating train split: 82117515 examples [1:18:57, 6254.35 examples/s]
Generating train split: 82118315 examples [1:18:57, 6393.93 examples/s]
Generating train split: 82119083 examples [1:18:57, 4915.04 examples/s]
Generating train split: 82119969 examples [1:18:58, 5555.50 examples/s]
Generating train split: 82122229 examples [1:18:58, 8731.67 examples/s]
Generating train split: 82123572 examples [1:18:58, 9657.81 examples/s]
Generating train split: 82124770 examples [1:18:58, 6807.02 examples/s]
Generating train split: 82126154 examples [1:18:58, 8074.71 examples/s]
Generating train split: 82127467 examples [1:18:58, 9110.41 examples/s]
Generating train split: 82128629 examples [1:18:58, 8323.14 examples/s]
Generating train split: 82130293 examples [1:18:59, 9453.63 examples/s]
Generating train split: 82131520 examples [1:18:59, 10082.39 examples/s]
Generating train split: 82133799 examples [1:18:59, 13161.67 examples/s]
Generating train split: 82135280 examples [1:18:59, 8233.73 examples/s] 
Generating train split: 82136769 examples [1:18:59, 9430.26 examples/s]
Generating train split: 82138350 examples [1:18:59, 10708.81 examples/s]
Generating train split: 82139699 examples [1:18:59, 9620.95 examples/s] 
Generating train split: 82141228 examples [1:19:00, 10612.63 examples/s]
Generating train split: 82142468 examples [1:19:00, 9264.70 examples/s] 
Generating train split: 82144623 examples [1:19:00, 11928.24 examples/s]
Generating train split: 82146029 examples [1:19:00, 10785.13 examples/s]
Generating train split: 82147268 examples [1:19:00, 9614.79 examples/s] 
Generating train split: 82148349 examples [1:19:00, 8695.31 examples/s]
Generating train split: 82149325 examples [1:19:00, 8794.20 examples/s]
Generating train split: 82150594 examples [1:19:01, 9653.80 examples/s]
Generating train split: 82151638 examples [1:19:01, 6572.05 examples/s]
Generating train split: 82153287 examples [1:19:01, 8465.53 examples/s]
Generating train split: 82154366 examples [1:19:01, 8866.42 examples/s]
Generating train split: 82156789 examples [1:19:01, 12441.75 examples/s]
Generating train split: 82158269 examples [1:19:01, 10769.16 examples/s]
Generating train split: 82159549 examples [1:19:01, 10867.77 examples/s]
Generating train split: 82160779 examples [1:19:02, 8041.55 examples/s] 
Generating train split: 82166458 examples [1:19:02, 17639.71 examples/s]
Generating train split: 82174948 examples [1:19:02, 32398.99 examples/s]
Generating train split: 82179183 examples [1:19:02, 22601.77 examples/s]
Generating train split: 82182537 examples [1:19:03, 19483.74 examples/s]
Generating train split: 82185302 examples [1:19:03, 13862.95 examples/s]
Generating train split: 82187445 examples [1:19:03, 11839.09 examples/s]
Generating train split: 82189170 examples [1:19:03, 11850.62 examples/s]
Generating train split: 82190743 examples [1:19:04, 9790.90 examples/s] 
Generating train split: 82192033 examples [1:19:04, 10087.57 examples/s]
Generating train split: 82193279 examples [1:19:04, 10177.55 examples/s]
Generating train split: 82194468 examples [1:19:04, 7959.21 examples/s] 
Generating train split: 82195441 examples [1:19:04, 7606.76 examples/s]
Generating train split: 82196731 examples [1:19:04, 8585.46 examples/s]
Generating train split: 82198834 examples [1:19:04, 11178.82 examples/s]
Generating train split: 82200865 examples [1:19:05, 13204.70 examples/s]
Generating train split: 82202392 examples [1:19:05, 8662.70 examples/s] 
Generating train split: 82203980 examples [1:19:05, 9971.96 examples/s]
Generating train split: 82212093 examples [1:19:05, 24633.98 examples/s]
Generating train split: 82219780 examples [1:19:05, 36416.49 examples/s]
Generating train split: 82224416 examples [1:19:06, 23192.93 examples/s]
Generating train split: 82228038 examples [1:19:06, 13867.00 examples/s]
Generating train split: 82230757 examples [1:19:07, 12126.00 examples/s]
Generating train split: 82232912 examples [1:19:07, 12348.25 examples/s]
Generating train split: 82242203 examples [1:19:07, 23243.63 examples/s]
Generating train split: 82250312 examples [1:19:07, 32381.60 examples/s]
Generating train split: 82255539 examples [1:19:07, 18389.15 examples/s]
Generating train split: 82259452 examples [1:19:08, 17861.92 examples/s]
Generating train split: 82262673 examples [1:19:08, 14421.50 examples/s]
Generating train split: 82265179 examples [1:19:08, 12101.51 examples/s]
Generating train split: 82267151 examples [1:19:09, 12456.79 examples/s]
Generating train split: 82268972 examples [1:19:09, 8897.50 examples/s] 
Generating train split: 82270372 examples [1:19:09, 6929.02 examples/s]
Generating train split: 82271681 examples [1:19:10, 7587.89 examples/s]
Generating train split: 82272834 examples [1:19:10, 6191.35 examples/s]
Generating train split: 82273739 examples [1:19:10, 6201.15 examples/s]
Generating train split: 82274568 examples [1:19:10, 6138.54 examples/s]
Generating train split: 82275439 examples [1:19:10, 6492.91 examples/s]
Generating train split: 82276214 examples [1:19:10, 5944.91 examples/s]
Generating train split: 82283696 examples [1:19:11, 19199.70 examples/s]
Generating train split: 82292490 examples [1:19:11, 34014.63 examples/s]
Generating train split: 82297036 examples [1:19:11, 22438.39 examples/s]
Generating train split: 82300585 examples [1:19:11, 15590.39 examples/s]
Generating train split: 82308623 examples [1:19:12, 24233.87 examples/s]
Generating train split: 82317191 examples [1:19:12, 34067.10 examples/s]
Generating train split: 82322780 examples [1:19:12, 16841.19 examples/s]
Generating train split: 82326914 examples [1:19:13, 13666.42 examples/s]
Generating train split: 82335476 examples [1:19:13, 20541.95 examples/s]
Generating train split: 82340674 examples [1:19:13, 24307.45 examples/s]
Generating train split: 82345572 examples [1:19:14, 14508.12 examples/s]
Generating train split: 82349200 examples [1:19:15, 8526.25 examples/s] 
Generating train split: 82351841 examples [1:19:16, 7168.05 examples/s]
Generating train split: 82353821 examples [1:19:16, 7934.00 examples/s]
Generating train split: 82355730 examples [1:19:16, 7865.16 examples/s]
Generating train split: 82357296 examples [1:19:16, 7531.93 examples/s]
Generating train split: 82358588 examples [1:19:16, 6892.22 examples/s]
Generating train split: 82359636 examples [1:19:17, 6371.73 examples/s]
Generating train split: 82360510 examples [1:19:17, 6540.97 examples/s]
Generating train split: 82361346 examples [1:19:17, 6476.36 examples/s]
Generating train split: 82362123 examples [1:19:17, 5094.23 examples/s]
Generating train split: 82363515 examples [1:19:17, 6454.09 examples/s]
Generating train split: 82364372 examples [1:19:17, 6482.45 examples/s]
Generating train split: 82365285 examples [1:19:18, 6995.09 examples/s]
Generating train split: 82366214 examples [1:19:18, 7357.84 examples/s]
Generating train split: 82367053 examples [1:19:18, 3595.71 examples/s]
Generating train split: 82367801 examples [1:19:18, 4121.13 examples/s]
Generating train split: 82368463 examples [1:19:19, 3734.86 examples/s]
Generating train split: 82369279 examples [1:19:19, 4416.65 examples/s]
Generating train split: 82369899 examples [1:19:19, 3905.36 examples/s]
Generating train split: 82370422 examples [1:19:19, 3329.25 examples/s]
Generating train split: 82371020 examples [1:19:19, 3780.36 examples/s]
Generating train split: 82371509 examples [1:19:19, 3069.39 examples/s]
Generating train split: 82372436 examples [1:19:20, 4166.86 examples/s]
Generating train split: 82372997 examples [1:19:20, 4060.73 examples/s]
Generating train split: 82373499 examples [1:19:20, 2908.68 examples/s]
Generating train split: 82374865 examples [1:19:20, 4684.83 examples/s]
Generating train split: 82377004 examples [1:19:20, 7904.39 examples/s]
Generating train split: 82378123 examples [1:19:21, 5887.33 examples/s]
Generating train split: 82379020 examples [1:19:21, 6363.00 examples/s]
Generating train split: 82380765 examples [1:19:21, 8553.41 examples/s]
Generating train split: 82381914 examples [1:19:22, 3836.70 examples/s]
Generating train split: 82382761 examples [1:19:22, 4294.39 examples/s]
Generating train split: 82383574 examples [1:19:22, 4146.26 examples/s]
Generating train split: 82384254 examples [1:19:22, 3148.01 examples/s]
Generating train split: 82384781 examples [1:19:22, 3058.55 examples/s]
Generating train split: 82387603 examples [1:19:23, 6557.69 examples/s]
Generating train split: 82388759 examples [1:19:23, 6272.58 examples/s]
Generating train split: 82389742 examples [1:19:23, 5491.93 examples/s]
Generating train split: 82390648 examples [1:19:23, 6058.52 examples/s]
Generating train split: 82392109 examples [1:19:23, 7651.00 examples/s]
Generating train split: 82393886 examples [1:19:23, 9565.66 examples/s]
Generating train split: 82395081 examples [1:19:24, 8009.91 examples/s]
Generating train split: 82396088 examples [1:19:24, 6748.70 examples/s]
Generating train split: 82397211 examples [1:19:24, 7589.83 examples/s]
Generating train split: 82398135 examples [1:19:24, 6294.13 examples/s]
Generating train split: 82398905 examples [1:19:24, 5206.27 examples/s]
Generating train split: 82399545 examples [1:19:24, 5257.38 examples/s]
Generating train split: 82400163 examples [1:19:25, 4233.64 examples/s]
Generating train split: 82400929 examples [1:19:25, 4788.38 examples/s]
Generating train split: 82402094 examples [1:19:25, 6180.12 examples/s]
Generating train split: 82403934 examples [1:19:25, 8932.05 examples/s]
Generating train split: 82405006 examples [1:19:25, 7508.92 examples/s]
Generating train split: 82405920 examples [1:19:25, 6190.72 examples/s]
Generating train split: 82407564 examples [1:19:26, 8196.50 examples/s]
Generating train split: 82408590 examples [1:19:26, 6363.96 examples/s]
Generating train split: 82409427 examples [1:19:26, 6275.40 examples/s]
Generating train split: 82410419 examples [1:19:26, 6978.88 examples/s]
Generating train split: 82411260 examples [1:19:26, 6619.10 examples/s]
Generating train split: 82412167 examples [1:19:26, 7159.85 examples/s]
Generating train split: 82413854 examples [1:19:26, 9362.55 examples/s]
Generating train split: 82414979 examples [1:19:26, 9796.16 examples/s]
Generating train split: 82416483 examples [1:19:27, 11184.32 examples/s]
Generating train split: 82417678 examples [1:19:27, 8270.19 examples/s] 
Generating train split: 82418677 examples [1:19:27, 7043.63 examples/s]
Generating train split: 82420339 examples [1:19:27, 9005.75 examples/s]
Generating train split: 82421424 examples [1:19:27, 7057.46 examples/s]
Generating train split: 82422722 examples [1:19:27, 8139.23 examples/s]
Generating train split: 82423728 examples [1:19:28, 8525.89 examples/s]
Generating train split: 82425749 examples [1:19:28, 11265.32 examples/s]
Generating train split: 82427054 examples [1:19:28, 6287.51 examples/s] 
Generating train split: 82428190 examples [1:19:28, 7092.15 examples/s]
Generating train split: 82429256 examples [1:19:28, 7734.59 examples/s]
Generating train split: 82430298 examples [1:19:29, 6199.85 examples/s]
Generating train split: 82431149 examples [1:19:29, 6486.53 examples/s]
Generating train split: 82432519 examples [1:19:29, 7701.98 examples/s]
Generating train split: 82433464 examples [1:19:29, 6511.66 examples/s]
Generating train split: 82434313 examples [1:19:29, 6618.34 examples/s]
Generating train split: 82435086 examples [1:19:29, 6197.72 examples/s]
Generating train split: 82435874 examples [1:19:29, 5587.81 examples/s]
Generating train split: 82436500 examples [1:19:30, 5649.36 examples/s]
Generating train split: 82437117 examples [1:19:30, 4093.16 examples/s]
Generating train split: 82437957 examples [1:19:30, 4883.24 examples/s]
Generating train split: 82438554 examples [1:19:30, 3233.71 examples/s]
Generating train split: 82439016 examples [1:19:31, 2711.30 examples/s]
Generating train split: 82439396 examples [1:19:31, 2582.61 examples/s]
Generating train split: 82441055 examples [1:19:31, 4866.60 examples/s]
Generating train split: 82441786 examples [1:19:31, 3232.65 examples/s]
Generating train split: 82442749 examples [1:19:31, 4113.49 examples/s]
Generating train split: 82443547 examples [1:19:32, 4732.72 examples/s]
Generating train split: 82444259 examples [1:19:32, 5120.44 examples/s]
Generating train split: 82445154 examples [1:19:32, 5848.80 examples/s]
Generating train split: 82445904 examples [1:19:32, 4407.94 examples/s]
Generating train split: 82446837 examples [1:19:32, 4852.11 examples/s]
Generating train split: 82447439 examples [1:19:32, 4391.16 examples/s]
Generating train split: 82448305 examples [1:19:32, 5203.07 examples/s]
Generating train split: 82448928 examples [1:19:33, 4771.30 examples/s]
Generating train split: 82449762 examples [1:19:33, 5529.44 examples/s]
Generating train split: 82450717 examples [1:19:33, 6460.46 examples/s]
Generating train split: 82451453 examples [1:19:33, 5465.97 examples/s]
Generating train split: 82452080 examples [1:19:33, 5278.51 examples/s]
Generating train split: 82453145 examples [1:19:33, 6497.70 examples/s]
Generating train split: 82454217 examples [1:19:33, 7131.74 examples/s]
Generating train split: 82454991 examples [1:19:33, 7191.55 examples/s]
Generating train split: 82456323 examples [1:19:34, 8764.89 examples/s]
Generating train split: 82457249 examples [1:19:34, 6882.09 examples/s]
Generating train split: 82458041 examples [1:19:34, 5995.40 examples/s]
Generating train split: 82459849 examples [1:19:34, 8600.94 examples/s]
Generating train split: 82460875 examples [1:19:34, 8725.01 examples/s]
Generating train split: 82461859 examples [1:19:35, 5586.60 examples/s]
Generating train split: 82463154 examples [1:19:35, 6907.96 examples/s]
Generating train split: 82464084 examples [1:19:35, 6051.55 examples/s]
Generating train split: 82465336 examples [1:19:35, 7234.57 examples/s]
Generating train split: 82466248 examples [1:19:35, 6180.99 examples/s]
Generating train split: 82467020 examples [1:19:35, 5345.09 examples/s]
Generating train split: 82467673 examples [1:19:36, 4904.47 examples/s]
Generating train split: 82468452 examples [1:19:36, 5458.65 examples/s]
Generating train split: 82469278 examples [1:19:36, 6056.49 examples/s]
Generating train split: 82469967 examples [1:19:36, 5917.71 examples/s]
Generating train split: 82472796 examples [1:19:36, 11303.86 examples/s]
Generating train split: 82474105 examples [1:19:36, 9603.88 examples/s] 
Generating train split: 82475392 examples [1:19:36, 10249.99 examples/s]
Generating train split: 82476546 examples [1:19:36, 8126.42 examples/s] 
Generating train split: 82477956 examples [1:19:37, 9307.84 examples/s]
Generating train split: 82479035 examples [1:19:37, 7580.33 examples/s]
Generating train split: 82479939 examples [1:19:37, 5661.79 examples/s]
Generating train split: 82480674 examples [1:19:37, 4610.12 examples/s]
Generating train split: 82481272 examples [1:19:38, 4004.46 examples/s]
Generating train split: 82482606 examples [1:19:38, 5503.12 examples/s]
Generating train split: 82483358 examples [1:19:38, 3947.67 examples/s]
Generating train split: 82484241 examples [1:19:38, 4542.05 examples/s]
Generating train split: 82485567 examples [1:19:38, 6026.53 examples/s]
Generating train split: 82486401 examples [1:19:39, 4796.04 examples/s]
Generating train split: 82487085 examples [1:19:39, 4309.76 examples/s]
Generating train split: 82488619 examples [1:19:39, 6195.74 examples/s]
Generating train split: 82489482 examples [1:19:39, 4401.79 examples/s]
Generating train split: 82491226 examples [1:19:39, 6116.12 examples/s]
Generating train split: 82492092 examples [1:19:40, 5633.20 examples/s]
Generating train split: 82492969 examples [1:19:40, 5928.60 examples/s]
Generating train split: 82493700 examples [1:19:40, 5121.18 examples/s]
Generating train split: 82496150 examples [1:19:40, 8739.80 examples/s]
Generating train split: 82497319 examples [1:19:40, 5743.23 examples/s]
Generating train split: 82498232 examples [1:19:41, 5769.11 examples/s]
Generating train split: 82499047 examples [1:19:41, 3802.68 examples/s]
Generating train split: 82500668 examples [1:19:41, 5406.95 examples/s]
Generating train split: 82502470 examples [1:19:41, 7375.08 examples/s]
Generating train split: 82503653 examples [1:19:42, 5629.19 examples/s]
Generating train split: 82505087 examples [1:19:42, 6907.87 examples/s]
Generating train split: 82506150 examples [1:19:42, 7519.87 examples/s]
Generating train split: 82507201 examples [1:19:42, 5915.88 examples/s]
Generating train split: 82508068 examples [1:19:42, 6383.74 examples/s]
Generating train split: 82508922 examples [1:19:43, 4454.20 examples/s]
Generating train split: 82510331 examples [1:19:43, 5895.85 examples/s]
Generating train split: 82511666 examples [1:19:43, 7226.31 examples/s]
Generating train split: 82512670 examples [1:19:43, 7369.74 examples/s]
Generating train split: 82513607 examples [1:19:43, 5853.73 examples/s]
Generating train split: 82515194 examples [1:19:43, 7738.25 examples/s]
Generating train split: 82516205 examples [1:19:44, 4587.66 examples/s]
Generating train split: 82518134 examples [1:19:44, 6562.62 examples/s]
Generating train split: 82519186 examples [1:19:44, 7017.85 examples/s]
Generating train split: 82520465 examples [1:19:44, 8075.37 examples/s]
Generating train split: 82521539 examples [1:19:44, 5475.25 examples/s]
Generating train split: 82522723 examples [1:19:44, 6398.21 examples/s]
Generating train split: 82523633 examples [1:19:45, 4855.98 examples/s]
Generating train split: 82525755 examples [1:19:45, 7411.02 examples/s]
Generating train split: 82526893 examples [1:19:45, 6667.56 examples/s]
Generating train split: 82527851 examples [1:19:45, 5674.75 examples/s]
Generating train split: 82528876 examples [1:19:45, 6423.24 examples/s]
Generating train split: 82529774 examples [1:19:46, 6716.18 examples/s]
Generating train split: 82530609 examples [1:19:46, 4441.12 examples/s]
Generating train split: 82531260 examples [1:19:46, 4643.26 examples/s]
Generating train split: 82532225 examples [1:19:46, 5352.32 examples/s]
Generating train split: 82532900 examples [1:19:46, 5024.74 examples/s]
Generating train split: 82534545 examples [1:19:46, 7333.08 examples/s]
Generating train split: 82535903 examples [1:19:47, 8656.24 examples/s]
Generating train split: 82537033 examples [1:19:47, 9262.61 examples/s]
Generating train split: 82538090 examples [1:19:47, 8054.63 examples/s]
Generating train split: 82539010 examples [1:19:47, 6187.89 examples/s]
Generating train split: 82539766 examples [1:19:47, 4826.68 examples/s]
Generating train split: 82540384 examples [1:19:48, 4450.98 examples/s]
Generating train split: 82542372 examples [1:19:48, 7201.39 examples/s]
Generating train split: 82543416 examples [1:19:48, 7860.68 examples/s]
Generating train split: 82544397 examples [1:19:48, 5120.99 examples/s]
Generating train split: 82545305 examples [1:19:48, 5739.68 examples/s]
Generating train split: 82546110 examples [1:19:49, 4474.88 examples/s]
Generating train split: 82547058 examples [1:19:49, 5298.32 examples/s]
Generating train split: 82547794 examples [1:19:49, 3836.47 examples/s]
Generating train split: 82548372 examples [1:19:49, 3636.07 examples/s]
Generating train split: 82548876 examples [1:19:49, 3395.67 examples/s]
Generating train split: 82549822 examples [1:19:49, 4421.35 examples/s]
Generating train split: 82550410 examples [1:19:50, 4144.14 examples/s]
Generating train split: 82550924 examples [1:19:50, 4144.56 examples/s]
Generating train split: 82551792 examples [1:19:50, 5023.04 examples/s]
Generating train split: 82552373 examples [1:19:50, 3292.26 examples/s]
Generating train split: 82554132 examples [1:19:50, 5741.39 examples/s]
Generating train split: 82554980 examples [1:19:51, 3519.90 examples/s]
Generating train split: 82556187 examples [1:19:51, 4681.35 examples/s]
Generating train split: 82557031 examples [1:19:51, 5292.20 examples/s]
Generating train split: 82557852 examples [1:19:51, 4739.71 examples/s]
Generating train split: 82558689 examples [1:19:51, 5386.85 examples/s]
Generating train split: 82560416 examples [1:19:51, 7809.16 examples/s]
Generating train split: 82563017 examples [1:19:52, 11844.72 examples/s]
Generating train split: 82564506 examples [1:19:52, 8696.51 examples/s] 
Generating train split: 82565702 examples [1:19:52, 8063.74 examples/s]
Generating train split: 82567218 examples [1:19:52, 9428.17 examples/s]
Generating train split: 82568405 examples [1:19:53, 5284.54 examples/s]
Generating train split: 82569316 examples [1:19:53, 4165.23 examples/s]
Generating train split: 82570029 examples [1:19:53, 4242.31 examples/s]
Generating train split: 82570655 examples [1:19:53, 4311.78 examples/s]
Generating train split: 82571234 examples [1:19:54, 3198.76 examples/s]
Generating train split: 82571693 examples [1:19:54, 2400.46 examples/s]
Generating train split: 82572046 examples [1:19:54, 2199.19 examples/s]
Generating train split: 82572985 examples [1:19:54, 3148.89 examples/s]
Generating train split: 82574160 examples [1:19:54, 4491.57 examples/s]
Generating train split: 82574838 examples [1:19:55, 4657.30 examples/s]
Generating train split: 82576363 examples [1:19:55, 6687.13 examples/s]
Generating train split: 82577233 examples [1:19:55, 6867.47 examples/s]
Generating train split: 82578073 examples [1:19:55, 5275.44 examples/s]
Generating train split: 82578760 examples [1:19:55, 4028.79 examples/s]
Generating train split: 82579702 examples [1:19:56, 4718.38 examples/s]
Generating train split: 82580312 examples [1:19:56, 3745.50 examples/s]
Generating train split: 82580807 examples [1:19:56, 2801.98 examples/s]
Generating train split: 82582453 examples [1:19:56, 4754.34 examples/s]
Generating train split: 82583429 examples [1:19:56, 5523.21 examples/s]
Generating train split: 82584223 examples [1:19:57, 4868.42 examples/s]
Generating train split: 82585048 examples [1:19:57, 5487.70 examples/s]
Generating train split: 82585759 examples [1:19:57, 5713.64 examples/s]
Generating train split: 82586458 examples [1:19:57, 5997.03 examples/s]
Generating train split: 82587159 examples [1:19:57, 3905.41 examples/s]
Generating train split: 82587716 examples [1:19:57, 3797.41 examples/s]
Generating train split: 82588213 examples [1:19:58, 3076.19 examples/s]
Generating train split: 82588622 examples [1:19:58, 3242.23 examples/s]
Generating train split: 82589682 examples [1:19:58, 4673.16 examples/s]
Generating train split: 82592553 examples [1:19:58, 9905.81 examples/s]
Generating train split: 82595953 examples [1:19:58, 15618.22 examples/s]
Generating train split: 82601061 examples [1:19:58, 24586.58 examples/s]
Generating train split: 82606578 examples [1:19:58, 32699.10 examples/s]
Generating train split: 82612838 examples [1:19:58, 40916.95 examples/s]
Generating train split: 82619152 examples [1:19:58, 47180.16 examples/s]
Generating train split: 82624926 examples [1:19:59, 50208.19 examples/s]
Generating train split: 82631960 examples [1:19:59, 56045.40 examples/s]
Generating train split: 82637953 examples [1:19:59, 57164.03 examples/s]
Generating train split: 82644206 examples [1:19:59, 58719.46 examples/s]
Generating train split: 82650172 examples [1:19:59, 57559.74 examples/s]
Generating train split: 82656084 examples [1:19:59, 57994.59 examples/s]
Generating train split: 82662012 examples [1:19:59, 58369.38 examples/s]
Generating train split: 82668703 examples [1:19:59, 60893.08 examples/s]
Generating train split: 82675658 examples [1:19:59, 63449.35 examples/s]
Generating train split: 82682229 examples [1:19:59, 64115.87 examples/s]
Generating train split: 82689357 examples [1:20:00, 66245.61 examples/s]
Generating train split: 82696087 examples [1:20:00, 66549.55 examples/s]
Generating train split: 82703130 examples [1:20:00, 67692.68 examples/s]
Generating train split: 82710207 examples [1:20:00, 68596.64 examples/s]
Generating train split: 82717074 examples [1:20:00, 68018.42 examples/s]
Generating train split: 82723880 examples [1:20:00, 65359.52 examples/s]
Generating train split: 82730445 examples [1:20:00, 59247.14 examples/s]
Generating train split: 82736485 examples [1:20:00, 40144.58 examples/s]
Generating train split: 82741368 examples [1:20:01, 32065.08 examples/s]
Generating train split: 82745377 examples [1:20:01, 29837.96 examples/s]
Generating train split: 82748904 examples [1:20:01, 16683.04 examples/s]
Generating train split: 82751568 examples [1:20:02, 8329.69 examples/s] 
Generating train split: 82753512 examples [1:20:03, 7499.06 examples/s]
Generating train split: 82755027 examples [1:20:03, 5627.67 examples/s]
Generating train split: 82756157 examples [1:20:04, 5996.68 examples/s]
Generating train split: 82757246 examples [1:20:04, 6178.31 examples/s]
Generating train split: 82758235 examples [1:20:04, 4980.35 examples/s]
Generating train split: 82759226 examples [1:20:04, 5514.05 examples/s]
Generating train split: 82760129 examples [1:20:04, 5986.20 examples/s]
Generating train split: 82760976 examples [1:20:05, 3677.43 examples/s]
Generating train split: 82762059 examples [1:20:05, 4425.62 examples/s]
Generating train split: 82763178 examples [1:20:05, 5289.91 examples/s]
Generating train split: 82763980 examples [1:20:06, 3411.12 examples/s]
Generating train split: 82764589 examples [1:20:06, 3553.20 examples/s]
Generating train split: 82765147 examples [1:20:06, 3427.75 examples/s]
Generating train split: 82765625 examples [1:20:06, 2658.59 examples/s]
Generating train split: 82766002 examples [1:20:06, 2803.30 examples/s]
Generating train split: 82766384 examples [1:20:07, 2854.61 examples/s]
Generating train split: 82766993 examples [1:20:07, 3452.65 examples/s]
Generating train split: 82767443 examples [1:20:07, 3628.42 examples/s]
Generating train split: 82767879 examples [1:20:07, 1975.70 examples/s]
Generating train split: 82768206 examples [1:20:07, 2153.31 examples/s]
Generating train split: 82768538 examples [1:20:08, 1701.26 examples/s]
Generating train split: 82768912 examples [1:20:08, 1985.62 examples/s]
Generating train split: 82769200 examples [1:20:08, 1724.78 examples/s]
Generating train split: 82769436 examples [1:20:08, 1475.10 examples/s]
Generating train split: 82769673 examples [1:20:08, 1617.79 examples/s]
Generating train split: 82769889 examples [1:20:08, 1587.23 examples/s]
Generating train split: 82770082 examples [1:20:09, 1360.13 examples/s]
Generating train split: 82770247 examples [1:20:09, 1311.75 examples/s]
Generating train split: 82770486 examples [1:20:09, 1525.88 examples/s]
Generating train split: 82770743 examples [1:20:09, 1757.45 examples/s]
Generating train split: 82770957 examples [1:20:09, 1831.27 examples/s]
Generating train split: 82771160 examples [1:20:09, 1808.51 examples/s]
Generating train split: 82774497 examples [1:20:09, 9968.26 examples/s]
Generating train split: 82782572 examples [1:20:09, 29053.38 examples/s]
Generating train split: 82789284 examples [1:20:10, 39598.35 examples/s]
Generating train split: 82793541 examples [1:20:10, 15254.11 examples/s]
Generating train split: 82796718 examples [1:20:11, 11912.81 examples/s]
Generating train split: 82799159 examples [1:20:11, 8772.39 examples/s] 
Generating train split: 82801005 examples [1:20:12, 6848.45 examples/s]
Generating train split: 82802401 examples [1:20:12, 6272.10 examples/s]
Generating train split: 82803505 examples [1:20:12, 5643.65 examples/s]
Generating train split: 82804397 examples [1:20:12, 5957.30 examples/s]
Generating train split: 82805282 examples [1:20:13, 5378.78 examples/s]
Generating train split: 82806015 examples [1:20:13, 4937.54 examples/s]
Generating train split: 82813947 examples [1:20:13, 15667.41 examples/s]
Generating train split: 82822140 examples [1:20:13, 26986.93 examples/s]
Generating train split: 82826567 examples [1:20:13, 20500.75 examples/s]
Generating train split: 82830055 examples [1:20:14, 13047.30 examples/s]
Generating train split: 82832679 examples [1:20:15, 9911.39 examples/s] 
Generating train split: 82834684 examples [1:20:15, 10242.78 examples/s]
Generating train split: 82836458 examples [1:20:15, 8272.19 examples/s] 
Generating train split: 82842326 examples [1:20:15, 13912.59 examples/s]
Generating train split: 82850799 examples [1:20:15, 23672.79 examples/s]
Generating train split: 82855252 examples [1:20:16, 23787.28 examples/s]
Generating train split: 82859090 examples [1:20:16, 16569.29 examples/s]
Generating train split: 82862041 examples [1:20:16, 16324.86 examples/s]
Generating train split: 82864573 examples [1:20:17, 11922.62 examples/s]
Generating train split: 82866530 examples [1:20:17, 8939.63 examples/s] 
Generating train split: 82868025 examples [1:20:17, 9389.61 examples/s]
Generating train split: 82869452 examples [1:20:17, 9708.40 examples/s]
Generating train split: 82870792 examples [1:20:17, 9166.27 examples/s]
Generating train split: 82872141 examples [1:20:18, 9868.91 examples/s]
Generating train split: 82873355 examples [1:20:18, 9654.20 examples/s]
Generating train split: 82874478 examples [1:20:18, 8296.70 examples/s]
Generating train split: 82875430 examples [1:20:18, 8499.86 examples/s]
Generating train split: 82876377 examples [1:20:18, 7358.60 examples/s]
Generating train split: 82877605 examples [1:20:18, 8370.72 examples/s]
Generating train split: 82878549 examples [1:20:18, 7909.18 examples/s]
Generating train split: 82879418 examples [1:20:19, 7507.37 examples/s]
Generating train split: 82880224 examples [1:20:19, 6827.75 examples/s]
Generating train split: 82881897 examples [1:20:19, 9098.92 examples/s]
Generating train split: 82882905 examples [1:20:19, 9261.30 examples/s]
Generating train split: 82883909 examples [1:20:19, 7680.39 examples/s]
Generating train split: 82884769 examples [1:20:19, 6786.32 examples/s]
Generating train split: 82888016 examples [1:20:19, 12462.40 examples/s]
Generating train split: 82895676 examples [1:20:19, 27855.75 examples/s]
Generating train split: 82901070 examples [1:20:20, 34509.50 examples/s]
Generating train split: 82905040 examples [1:20:20, 20561.64 examples/s]
Generating train split: 82908136 examples [1:20:20, 13712.90 examples/s]
Generating train split: 82910512 examples [1:20:21, 11137.44 examples/s]
Generating train split: 82912374 examples [1:20:21, 11526.20 examples/s]
Generating train split: 82914089 examples [1:20:21, 7725.09 examples/s] 
Generating train split: 82915483 examples [1:20:22, 8411.46 examples/s]
Generating train split: 82916806 examples [1:20:22, 6309.33 examples/s]
Generating train split: 82918152 examples [1:20:22, 7160.84 examples/s]
Generating train split: 82919263 examples [1:20:22, 7183.73 examples/s]
Generating train split: 82920259 examples [1:20:22, 5730.26 examples/s]
Generating train split: 82921051 examples [1:20:23, 5860.52 examples/s]
Generating train split: 82922831 examples [1:20:23, 7903.31 examples/s]
Generating train split: 82923894 examples [1:20:23, 7881.25 examples/s]
Generating train split: 82924876 examples [1:20:23, 5824.46 examples/s]
Generating train split: 82926106 examples [1:20:23, 6869.41 examples/s]
Generating train split: 82927009 examples [1:20:23, 7131.65 examples/s]
Generating train split: 82927990 examples [1:20:23, 7626.44 examples/s]
Generating train split: 82928892 examples [1:20:24, 6150.60 examples/s]
Generating train split: 82929966 examples [1:20:24, 6821.02 examples/s]
Generating train split: 82930767 examples [1:20:24, 6490.35 examples/s]
Generating train split: 82931582 examples [1:20:24, 5850.34 examples/s]
Generating train split: 82932231 examples [1:20:24, 5978.57 examples/s]
Generating train split: 82933148 examples [1:20:24, 6381.98 examples/s]
Generating train split: 82934943 examples [1:20:24, 9085.35 examples/s]
Generating train split: 82935935 examples [1:20:25, 8462.66 examples/s]
Generating train split: 82936845 examples [1:20:25, 6054.55 examples/s]
Generating train split: 82937589 examples [1:20:25, 3989.11 examples/s]
Generating train split: 82938698 examples [1:20:25, 5031.04 examples/s]
Generating train split: 82939422 examples [1:20:26, 4528.32 examples/s]
Generating train split: 82940033 examples [1:20:26, 4542.64 examples/s]
Generating train split: 82941031 examples [1:20:26, 5570.21 examples/s]
Generating train split: 82941733 examples [1:20:26, 5738.13 examples/s]
Generating train split: 82943741 examples [1:20:26, 9032.87 examples/s]
Generating train split: 82944826 examples [1:20:26, 5786.77 examples/s]
Generating train split: 82945843 examples [1:20:26, 6519.20 examples/s]
Generating train split: 82946903 examples [1:20:27, 7310.55 examples/s]
Generating train split: 82947837 examples [1:20:27, 5072.39 examples/s]
Generating train split: 82948575 examples [1:20:27, 4294.75 examples/s]
Generating train split: 82949175 examples [1:20:27, 3679.68 examples/s]
Generating train split: 82950249 examples [1:20:28, 4623.52 examples/s]
Generating train split: 82951020 examples [1:20:28, 5171.85 examples/s]
Generating train split: 82951733 examples [1:20:28, 5509.40 examples/s]
Generating train split: 82952402 examples [1:20:28, 4105.76 examples/s]
Generating train split: 82952942 examples [1:20:28, 3632.85 examples/s]
Generating train split: 82953453 examples [1:20:28, 3819.46 examples/s]
Generating train split: 82953916 examples [1:20:29, 3512.68 examples/s]
Generating train split: 82954655 examples [1:20:29, 3940.03 examples/s]
Generating train split: 82955175 examples [1:20:29, 4155.58 examples/s]
Generating train split: 82955636 examples [1:20:29, 2280.72 examples/s]
Generating train split: 82956385 examples [1:20:29, 3046.91 examples/s]
Generating train split: 82956854 examples [1:20:29, 3168.44 examples/s]
Generating train split: 82957601 examples [1:20:30, 3984.88 examples/s]
Generating train split: 82958133 examples [1:20:30, 3718.23 examples/s]
Generating train split: 82959389 examples [1:20:30, 5562.41 examples/s]
Generating train split: 82960402 examples [1:20:30, 6616.27 examples/s]
Generating train split: 82961290 examples [1:20:30, 7176.80 examples/s]
Generating train split: 82962110 examples [1:20:30, 7414.95 examples/s]
Generating train split: 82962940 examples [1:20:30, 4761.99 examples/s]
Generating train split: 82963590 examples [1:20:31, 5073.62 examples/s]
Generating train split: 82964970 examples [1:20:31, 6953.93 examples/s]
Generating train split: 82966165 examples [1:20:31, 8118.28 examples/s]
Generating train split: 82967702 examples [1:20:31, 9908.36 examples/s]
Generating train split: 82968831 examples [1:20:31, 9325.69 examples/s]
Generating train split: 82969865 examples [1:20:31, 7073.73 examples/s]
Generating train split: 82970730 examples [1:20:32, 5541.88 examples/s]
Generating train split: 82971652 examples [1:20:32, 5982.71 examples/s]
Generating train split: 82972376 examples [1:20:32, 4566.97 examples/s]
Generating train split: 82973496 examples [1:20:32, 5725.05 examples/s]
Generating train split: 82974239 examples [1:20:32, 6000.78 examples/s]
Generating train split: 82974974 examples [1:20:33, 3754.47 examples/s]
Generating train split: 82975713 examples [1:20:33, 4288.58 examples/s]
Generating train split: 82976573 examples [1:20:33, 4997.12 examples/s]
Generating train split: 82978133 examples [1:20:33, 7157.21 examples/s]
Generating train split: 82979265 examples [1:20:33, 8028.40 examples/s]
Generating train split: 82980252 examples [1:20:33, 7576.32 examples/s]
Generating train split: 82981208 examples [1:20:33, 8023.51 examples/s]
Generating train split: 82983302 examples [1:20:33, 11266.28 examples/s]
Generating train split: 82984612 examples [1:20:33, 11503.56 examples/s]
Generating train split: 82985870 examples [1:20:34, 8078.08 examples/s] 
Generating train split: 82986892 examples [1:20:34, 6760.03 examples/s]
Generating train split: 82987780 examples [1:20:34, 7137.50 examples/s]
Generating train split: 82988632 examples [1:20:34, 5232.83 examples/s]
Generating train split: 82989317 examples [1:20:34, 5404.85 examples/s]
Generating train split: 82990130 examples [1:20:35, 5920.65 examples/s]
Generating train split: 82990833 examples [1:20:35, 3920.49 examples/s]
Generating train split: 82992418 examples [1:20:35, 5878.90 examples/s]
Generating train split: 82993271 examples [1:20:35, 6369.61 examples/s]
Generating train split: 82994117 examples [1:20:35, 5732.49 examples/s]
Generating train split: 82994846 examples [1:20:35, 5117.69 examples/s]
Generating train split: 82995524 examples [1:20:36, 5434.27 examples/s]
Generating train split: 82996361 examples [1:20:36, 6034.69 examples/s]
Generating train split: 82997060 examples [1:20:36, 3369.09 examples/s]
Generating train split: 82997668 examples [1:20:36, 3780.83 examples/s]
Generating train split: 82998224 examples [1:20:36, 3561.90 examples/s]
Generating train split: 82998812 examples [1:20:37, 3908.47 examples/s]
Generating train split: 82999762 examples [1:20:37, 5038.48 examples/s]
Generating train split: 83000766 examples [1:20:37, 6117.50 examples/s]
Generating train split: 83001505 examples [1:20:37, 3894.03 examples/s]
Generating train split: 83003405 examples [1:20:37, 6495.54 examples/s]
Generating train split: 83005108 examples [1:20:37, 8576.31 examples/s]
Generating train split: 83006300 examples [1:20:38, 5110.54 examples/s]
Generating train split: 83007852 examples [1:20:38, 6625.74 examples/s]
Generating train split: 83008947 examples [1:20:38, 5095.34 examples/s]
Generating train split: 83010007 examples [1:20:38, 5892.76 examples/s]
Generating train split: 83011419 examples [1:20:38, 7312.09 examples/s]
Generating train split: 83012482 examples [1:20:39, 7584.73 examples/s]
Generating train split: 83013496 examples [1:20:39, 7933.30 examples/s]
Generating train split: 83014484 examples [1:20:39, 6115.88 examples/s]
Generating train split: 83015283 examples [1:20:39, 4657.86 examples/s]
Generating train split: 83016221 examples [1:20:39, 5392.25 examples/s]
Generating train split: 83016940 examples [1:20:40, 4401.01 examples/s]
Generating train split: 83017528 examples [1:20:40, 3348.61 examples/s]
Generating train split: 83018105 examples [1:20:40, 3707.35 examples/s]
Generating train split: 83018732 examples [1:20:40, 4110.78 examples/s]
Generating train split: 83020017 examples [1:20:40, 5828.60 examples/s]
Generating train split: 83020762 examples [1:20:40, 5652.17 examples/s]
Generating train split: 83021881 examples [1:20:40, 6867.83 examples/s]
Generating train split: 83022689 examples [1:20:41, 5073.89 examples/s]
Generating train split: 83024233 examples [1:20:41, 7108.15 examples/s]
Generating train split: 83025155 examples [1:20:41, 7304.79 examples/s]
Generating train split: 83026036 examples [1:20:41, 5098.43 examples/s]
Generating train split: 83027074 examples [1:20:41, 5979.13 examples/s]
Generating train split: 83027861 examples [1:20:42, 5894.78 examples/s]
Generating train split: 83028816 examples [1:20:42, 6666.60 examples/s]
Generating train split: 83029617 examples [1:20:42, 6692.06 examples/s]
Generating train split: 83030376 examples [1:20:42, 5982.42 examples/s]
Generating train split: 83031340 examples [1:20:42, 6823.01 examples/s]
Generating train split: 83032100 examples [1:20:42, 6994.60 examples/s]
Generating train split: 83034309 examples [1:20:42, 10884.82 examples/s]
Generating train split: 83035502 examples [1:20:42, 8604.25 examples/s] 
Generating train split: 83036552 examples [1:20:43, 9035.35 examples/s]
Generating train split: 83037569 examples [1:20:43, 9150.62 examples/s]
Generating train split: 83038870 examples [1:20:43, 10143.18 examples/s]
Generating train split: 83039968 examples [1:20:43, 6978.12 examples/s] 
Generating train split: 83040956 examples [1:20:43, 7546.96 examples/s]
Generating train split: 83041869 examples [1:20:43, 7400.43 examples/s]
Generating train split: 83042719 examples [1:20:44, 5090.91 examples/s]
Generating train split: 83043400 examples [1:20:44, 4729.57 examples/s]
Generating train split: 83044086 examples [1:20:44, 5109.87 examples/s]
Generating train split: 83044858 examples [1:20:44, 5492.37 examples/s]
Generating train split: 83045493 examples [1:20:44, 5509.39 examples/s]
Generating train split: 83046404 examples [1:20:44, 6345.26 examples/s]
Generating train split: 83047474 examples [1:20:44, 7437.13 examples/s]
Generating train split: 83048542 examples [1:20:44, 8252.22 examples/s]
Generating train split: 83049688 examples [1:20:44, 8870.47 examples/s]
Generating train split: 83050628 examples [1:20:45, 7998.54 examples/s]
Generating train split: 83051474 examples [1:20:45, 7462.91 examples/s]
Generating train split: 83052842 examples [1:20:45, 8465.17 examples/s]
Generating train split: 83053712 examples [1:20:45, 5840.52 examples/s]
Generating train split: 83054715 examples [1:20:45, 6669.31 examples/s]
Generating train split: 83055550 examples [1:20:45, 6968.12 examples/s]
Generating train split: 83056344 examples [1:20:46, 4045.79 examples/s]
Generating train split: 83057942 examples [1:20:46, 5953.81 examples/s]
Generating train split: 83058849 examples [1:20:46, 4369.54 examples/s]
Generating train split: 83060525 examples [1:20:46, 6213.46 examples/s]
Generating train split: 83061565 examples [1:20:46, 6908.55 examples/s]
Generating train split: 83062565 examples [1:20:47, 5354.12 examples/s]
Generating train split: 83063365 examples [1:20:47, 5678.61 examples/s]
Generating train split: 83064369 examples [1:20:47, 6441.09 examples/s]
Generating train split: 83065194 examples [1:20:47, 5251.71 examples/s]
Generating train split: 83065881 examples [1:20:47, 4480.76 examples/s]
Generating train split: 83066902 examples [1:20:48, 5506.41 examples/s]
Generating train split: 83067606 examples [1:20:48, 3723.18 examples/s]
Generating train split: 83068159 examples [1:20:48, 3918.62 examples/s]
Generating train split: 83069731 examples [1:20:48, 6039.28 examples/s]
Generating train split: 83071139 examples [1:20:48, 7486.19 examples/s]
Generating train split: 83072103 examples [1:20:48, 6891.78 examples/s]
Generating train split: 83073002 examples [1:20:49, 7329.50 examples/s]
Generating train split: 83074268 examples [1:20:49, 8437.82 examples/s]
Generating train split: 83075234 examples [1:20:49, 5862.68 examples/s]
Generating train split: 83076193 examples [1:20:49, 6574.30 examples/s]
Generating train split: 83077870 examples [1:20:49, 8748.11 examples/s]
Generating train split: 83078960 examples [1:20:49, 6839.39 examples/s]
Generating train split: 83079893 examples [1:20:50, 7282.41 examples/s]
Generating train split: 83080783 examples [1:20:50, 7043.93 examples/s]
Generating train split: 83082700 examples [1:20:50, 9758.13 examples/s]
Generating train split: 83083847 examples [1:20:50, 8780.99 examples/s]
Generating train split: 83084860 examples [1:20:50, 8038.84 examples/s]
Generating train split: 83085769 examples [1:20:50, 7105.47 examples/s]
Generating train split: 83087149 examples [1:20:50, 8529.26 examples/s]
Generating train split: 83088119 examples [1:20:51, 7547.71 examples/s]
Generating train split: 83091675 examples [1:20:51, 13818.76 examples/s]
Generating train split: 83099718 examples [1:20:51, 29956.57 examples/s]
Generating train split: 83107450 examples [1:20:51, 41660.19 examples/s]
Generating train split: 83112184 examples [1:20:52, 16629.32 examples/s]
Generating train split: 83115699 examples [1:20:52, 12251.46 examples/s]
Generating train split: 83118363 examples [1:20:53, 9959.70 examples/s] 
Generating train split: 83120404 examples [1:20:53, 9477.96 examples/s]
Generating train split: 83122063 examples [1:20:53, 8535.75 examples/s]
Generating train split: 83123651 examples [1:20:53, 9300.73 examples/s]
Generating train split: 83125045 examples [1:20:53, 9041.23 examples/s]
Generating train split: 83126258 examples [1:20:54, 8377.18 examples/s]
Generating train split: 83127309 examples [1:20:54, 8092.83 examples/s]
Generating train split: 83128250 examples [1:20:54, 7545.28 examples/s]
Generating train split: 83129999 examples [1:20:54, 9379.99 examples/s]
Generating train split: 83131298 examples [1:20:54, 10133.50 examples/s]
Generating train split: 83132468 examples [1:20:54, 6229.02 examples/s] 
Generating train split: 83134335 examples [1:20:55, 8260.34 examples/s]
Generating train split: 83135527 examples [1:20:55, 7133.86 examples/s]
Generating train split: 83136517 examples [1:20:55, 5613.37 examples/s]
Generating train split: 83138703 examples [1:20:55, 8164.74 examples/s]
Generating train split: 83140848 examples [1:20:55, 10539.31 examples/s]
Generating train split: 83142329 examples [1:20:56, 5488.60 examples/s] 
Generating train split: 83144192 examples [1:20:56, 7107.82 examples/s]
Generating train split: 83145513 examples [1:20:56, 6750.19 examples/s]
Generating train split: 83146623 examples [1:20:56, 6524.53 examples/s]
Generating train split: 83147574 examples [1:20:57, 5399.32 examples/s]
Generating train split: 83148696 examples [1:20:57, 6273.02 examples/s]
Generating train split: 83149571 examples [1:20:57, 5289.07 examples/s]
Generating train split: 83150284 examples [1:20:57, 5437.88 examples/s]
Generating train split: 83150975 examples [1:20:57, 4711.69 examples/s]
Generating train split: 83152115 examples [1:20:57, 5914.92 examples/s]
Generating train split: 83153330 examples [1:20:58, 7194.43 examples/s]
Generating train split: 83154395 examples [1:20:58, 7877.75 examples/s]
Generating train split: 83155329 examples [1:20:58, 6806.09 examples/s]
Generating train split: 83156136 examples [1:20:58, 5640.50 examples/s]
Generating train split: 83156996 examples [1:20:58, 6209.41 examples/s]
Generating train split: 83157732 examples [1:20:58, 5280.16 examples/s]
Generating train split: 83159025 examples [1:20:58, 6842.68 examples/s]
Generating train split: 83159846 examples [1:20:59, 5755.76 examples/s]
Generating train split: 83160726 examples [1:20:59, 6328.60 examples/s]
Generating train split: 83161465 examples [1:20:59, 6545.00 examples/s]
Generating train split: 83163054 examples [1:20:59, 8807.69 examples/s]
Generating train split: 83164043 examples [1:20:59, 7042.43 examples/s]
Generating train split: 83165426 examples [1:20:59, 8524.25 examples/s]
Generating train split: 83166420 examples [1:20:59, 7739.11 examples/s]
Generating train split: 83172855 examples [1:21:00, 20794.98 examples/s]
Generating train split: 83182464 examples [1:21:00, 39454.23 examples/s]
Generating train split: 83187131 examples [1:21:00, 31865.62 examples/s]
Generating train split: 83191051 examples [1:21:00, 17497.38 examples/s]
Generating train split: 83194026 examples [1:21:01, 12834.77 examples/s]
Generating train split: 83196315 examples [1:21:01, 11380.14 examples/s]
Generating train split: 83204679 examples [1:21:01, 20183.97 examples/s]
Generating train split: 83213154 examples [1:21:01, 29756.14 examples/s]
Generating train split: 83218351 examples [1:21:02, 15234.65 examples/s]
Generating train split: 83222187 examples [1:21:03, 7881.71 examples/s] 
Generating train split: 83224972 examples [1:21:04, 7655.77 examples/s]
Generating train split: 83227121 examples [1:21:04, 7678.47 examples/s]
Generating train split: 83228856 examples [1:21:04, 7418.82 examples/s]
Generating train split: 83230260 examples [1:21:05, 7429.71 examples/s]
Generating train split: 83231476 examples [1:21:05, 5394.69 examples/s]
Generating train split: 83232398 examples [1:21:05, 4797.91 examples/s]
Generating train split: 83233136 examples [1:21:06, 4781.57 examples/s]
Generating train split: 83234544 examples [1:21:06, 5898.78 examples/s]
Generating train split: 83235430 examples [1:21:06, 5729.98 examples/s]
Generating train split: 83236869 examples [1:21:06, 7090.28 examples/s]
Generating train split: 83237848 examples [1:21:06, 6356.76 examples/s]
Generating train split: 83238679 examples [1:21:06, 5827.35 examples/s]
Generating train split: 83240846 examples [1:21:06, 8663.90 examples/s]
Generating train split: 83241970 examples [1:21:07, 6818.35 examples/s]
Generating train split: 83242884 examples [1:21:07, 6838.23 examples/s]
Generating train split: 83246127 examples [1:21:07, 11824.24 examples/s]
Generating train split: 83247702 examples [1:21:07, 12624.72 examples/s]
Generating train split: 83249263 examples [1:21:07, 10014.37 examples/s]
Generating train split: 83250548 examples [1:21:08, 8397.94 examples/s] 
Generating train split: 83251619 examples [1:21:08, 6288.63 examples/s]
Generating train split: 83252673 examples [1:21:08, 6778.93 examples/s]
Generating train split: 83253545 examples [1:21:08, 7015.23 examples/s]
Generating train split: 83254391 examples [1:21:08, 5360.10 examples/s]
Generating train split: 83256397 examples [1:21:08, 7933.94 examples/s]
Generating train split: 83257686 examples [1:21:09, 8734.33 examples/s]
Generating train split: 83258798 examples [1:21:09, 9100.09 examples/s]
Generating train split: 83259882 examples [1:21:09, 6366.51 examples/s]
Generating train split: 83260748 examples [1:21:09, 5142.76 examples/s]
Generating train split: 83261453 examples [1:21:09, 4889.29 examples/s]
Generating train split: 83262638 examples [1:21:10, 6098.07 examples/s]
Generating train split: 83263845 examples [1:21:10, 7268.23 examples/s]
Generating train split: 83264752 examples [1:21:10, 5676.22 examples/s]
Generating train split: 83265498 examples [1:21:10, 6000.55 examples/s]
Generating train split: 83266458 examples [1:21:10, 6749.81 examples/s]
Generating train split: 83267763 examples [1:21:10, 8064.68 examples/s]
Generating train split: 83268687 examples [1:21:10, 6948.59 examples/s]
Generating train split: 83269488 examples [1:21:11, 6772.04 examples/s]
Generating train split: 83270779 examples [1:21:11, 8094.54 examples/s]
Generating train split: 83271679 examples [1:21:11, 7952.32 examples/s]
Generating train split: 83272535 examples [1:21:11, 5189.66 examples/s]
Generating train split: 83274077 examples [1:21:11, 7105.37 examples/s]
Generating train split: 83275021 examples [1:21:11, 6111.20 examples/s]
Generating train split: 83276258 examples [1:21:11, 7290.65 examples/s]
Generating train split: 83277177 examples [1:21:12, 4947.42 examples/s]
Generating train split: 83277893 examples [1:21:12, 4751.49 examples/s]
Generating train split: 83279775 examples [1:21:12, 7138.98 examples/s]
Generating train split: 83280755 examples [1:21:12, 6627.33 examples/s]
Generating train split: 83281607 examples [1:21:12, 6019.75 examples/s]
Generating train split: 83282339 examples [1:21:13, 6258.15 examples/s]
Generating train split: 83283562 examples [1:21:13, 7499.16 examples/s]
Generating train split: 83285166 examples [1:21:13, 9505.19 examples/s]
Generating train split: 83286372 examples [1:21:13, 10066.14 examples/s]
Generating train split: 83287495 examples [1:21:13, 9379.20 examples/s] 
Generating train split: 83288930 examples [1:21:13, 10611.79 examples/s]
Generating train split: 83290076 examples [1:21:13, 10700.96 examples/s]
Generating train split: 83291201 examples [1:21:13, 8950.84 examples/s] 
Generating train split: 83292179 examples [1:21:14, 6718.30 examples/s]
Generating train split: 83293649 examples [1:21:14, 8326.95 examples/s]
Generating train split: 83294657 examples [1:21:14, 6076.65 examples/s]
Generating train split: 83295461 examples [1:21:14, 5626.17 examples/s]
Generating train split: 83297418 examples [1:21:14, 8188.85 examples/s]
Generating train split: 83298497 examples [1:21:15, 7186.40 examples/s]
Generating train split: 83299410 examples [1:21:15, 7027.99 examples/s]
Generating train split: 83300251 examples [1:21:15, 7086.50 examples/s]
Generating train split: 83301979 examples [1:21:15, 9302.41 examples/s]
Generating train split: 83303052 examples [1:21:15, 8072.28 examples/s]
Generating train split: 83303977 examples [1:21:15, 7466.83 examples/s]
Generating train split: 83304865 examples [1:21:15, 7517.11 examples/s]
Generating train split: 83306275 examples [1:21:15, 9050.60 examples/s]
Generating train split: 83307268 examples [1:21:16, 7514.02 examples/s]
Generating train split: 83308122 examples [1:21:16, 7250.35 examples/s]
Generating train split: 83308915 examples [1:21:16, 6933.13 examples/s]
Generating train split: 83315543 examples [1:21:16, 20954.32 examples/s]
Generating train split: 83324578 examples [1:21:16, 38455.16 examples/s]
Generating train split: 83329051 examples [1:21:16, 28742.16 examples/s]
Generating train split: 83332714 examples [1:21:17, 20641.05 examples/s]
Generating train split: 83335629 examples [1:21:17, 15125.49 examples/s]
Generating train split: 83337899 examples [1:21:17, 11257.01 examples/s]
Generating train split: 83339657 examples [1:21:18, 11239.89 examples/s]
Generating train split: 83341224 examples [1:21:18, 10864.83 examples/s]
Generating train split: 83342613 examples [1:21:18, 9790.59 examples/s] 
Generating train split: 83343788 examples [1:21:18, 9082.75 examples/s]
Generating train split: 83344827 examples [1:21:18, 8533.68 examples/s]
Generating train split: 83345758 examples [1:21:18, 7971.00 examples/s]
Generating train split: 83346608 examples [1:21:19, 7697.38 examples/s]
Generating train split: 83347398 examples [1:21:19, 7416.52 examples/s]
Generating train split: 83348155 examples [1:21:19, 6432.60 examples/s]
Generating train split: 83348823 examples [1:21:19, 5520.98 examples/s]
Generating train split: 83349976 examples [1:21:19, 6765.44 examples/s]
Generating train split: 83350727 examples [1:21:19, 5820.83 examples/s]
Generating train split: 83351815 examples [1:21:19, 6802.87 examples/s]
Generating train split: 83352571 examples [1:21:20, 4755.81 examples/s]
Generating train split: 83360908 examples [1:21:20, 19257.44 examples/s]
Generating train split: 83368973 examples [1:21:20, 32060.75 examples/s]
Generating train split: 83373439 examples [1:21:20, 25459.44 examples/s]
Generating train split: 83377080 examples [1:21:21, 16419.99 examples/s]
Generating train split: 83385323 examples [1:21:21, 25717.43 examples/s]
Generating train split: 83391496 examples [1:21:21, 31747.26 examples/s]
Generating train split: 83396450 examples [1:21:21, 22238.42 examples/s]
Generating train split: 83400290 examples [1:21:22, 18238.34 examples/s]
Generating train split: 83403322 examples [1:21:22, 9987.30 examples/s] 
Generating train split: 83405559 examples [1:21:23, 9682.42 examples/s]
Generating train split: 83407382 examples [1:21:23, 10132.38 examples/s]
Generating train split: 83411029 examples [1:21:23, 13305.02 examples/s]
Generating train split: 83413299 examples [1:21:23, 12298.67 examples/s]
Generating train split: 83415173 examples [1:21:23, 10846.04 examples/s]
Generating train split: 83416721 examples [1:21:24, 11426.83 examples/s]
Generating train split: 83418235 examples [1:21:24, 9299.30 examples/s] 
Generating train split: 83419471 examples [1:21:24, 7146.53 examples/s]
Generating train split: 83420450 examples [1:21:24, 6712.74 examples/s]
Generating train split: 83421292 examples [1:21:24, 6975.80 examples/s]
Generating train split: 83423448 examples [1:21:24, 9574.45 examples/s]
Generating train split: 83424685 examples [1:21:25, 9709.68 examples/s]
Generating train split: 83426027 examples [1:21:25, 10507.84 examples/s]
Generating train split: 83427245 examples [1:21:25, 8463.77 examples/s] 
Generating train split: 83428266 examples [1:21:25, 6830.13 examples/s]
Generating train split: 83429899 examples [1:21:25, 8598.73 examples/s]
Generating train split: 83430982 examples [1:21:25, 7749.39 examples/s]
Generating train split: 83431925 examples [1:21:26, 4621.43 examples/s]
Generating train split: 83432640 examples [1:21:26, 4719.17 examples/s]
Generating train split: 83433449 examples [1:21:26, 5263.88 examples/s]
Generating train split: 83434150 examples [1:21:26, 3893.27 examples/s]
Generating train split: 83434934 examples [1:21:27, 4506.25 examples/s]
Generating train split: 83435563 examples [1:21:27, 4710.82 examples/s]
Generating train split: 83436173 examples [1:21:27, 4737.66 examples/s]
Generating train split: 83436742 examples [1:21:27, 4761.89 examples/s]
Generating train split: 83437291 examples [1:21:27, 4208.57 examples/s]
Generating train split: 83439687 examples [1:21:27, 8515.69 examples/s]
Generating train split: 83440736 examples [1:21:28, 5044.01 examples/s]
Generating train split: 83441887 examples [1:21:28, 6066.63 examples/s]
Generating train split: 83442803 examples [1:21:28, 5864.05 examples/s]
Generating train split: 83443603 examples [1:21:28, 6061.51 examples/s]
Generating train split: 83444376 examples [1:21:28, 5992.50 examples/s]
Generating train split: 83445085 examples [1:21:28, 5586.73 examples/s]
Generating train split: 83446253 examples [1:21:28, 6888.80 examples/s]
Generating train split: 83447043 examples [1:21:29, 6700.87 examples/s]
Generating train split: 83447781 examples [1:21:29, 4890.58 examples/s]
Generating train split: 83448698 examples [1:21:29, 5717.05 examples/s]
Generating train split: 83449392 examples [1:21:29, 4899.40 examples/s]
Generating train split: 83449986 examples [1:21:29, 3621.39 examples/s]
Generating train split: 83451044 examples [1:21:30, 4774.02 examples/s]
Generating train split: 83452154 examples [1:21:30, 6008.32 examples/s]
Generating train split: 83453556 examples [1:21:30, 7752.80 examples/s]
Generating train split: 83454523 examples [1:21:30, 5165.52 examples/s]
Generating train split: 83455281 examples [1:21:30, 4487.12 examples/s]
Generating train split: 83456317 examples [1:21:30, 5391.75 examples/s]
Generating train split: 83457045 examples [1:21:31, 4473.46 examples/s]
Generating train split: 83458105 examples [1:21:31, 5222.36 examples/s]
Generating train split: 83458762 examples [1:21:31, 3592.55 examples/s]
Generating train split: 83459280 examples [1:21:32, 2676.91 examples/s]
Generating train split: 83459688 examples [1:21:32, 2114.65 examples/s]
Generating train split: 83462061 examples [1:21:32, 4745.44 examples/s]
Generating train split: 83463140 examples [1:21:32, 5640.73 examples/s]
Generating train split: 83464122 examples [1:21:32, 6142.72 examples/s]
Generating train split: 83465048 examples [1:21:32, 6658.60 examples/s]
Generating train split: 83465959 examples [1:21:33, 6318.17 examples/s]
Generating train split: 83467900 examples [1:21:33, 9094.90 examples/s]
Generating train split: 83469049 examples [1:21:33, 7056.01 examples/s]
Generating train split: 83470089 examples [1:21:33, 7679.79 examples/s]
Generating train split: 83471393 examples [1:21:33, 8844.56 examples/s]
Generating train split: 83472752 examples [1:21:33, 9968.36 examples/s]
Generating train split: 83473907 examples [1:21:33, 8569.70 examples/s]
Generating train split: 83476060 examples [1:21:33, 11546.43 examples/s]
Generating train split: 83478097 examples [1:21:34, 13687.22 examples/s]
Generating train split: 83479640 examples [1:21:34, 8877.00 examples/s] 
Generating train split: 83481260 examples [1:21:34, 9887.97 examples/s]
Generating train split: 83483455 examples [1:21:34, 12380.19 examples/s]
Generating train split: 83484995 examples [1:21:34, 12025.85 examples/s]
Generating train split: 83486411 examples [1:21:35, 7364.76 examples/s] 
Generating train split: 83488958 examples [1:21:35, 10300.40 examples/s]
Generating train split: 83490519 examples [1:21:35, 11281.59 examples/s]
Generating train split: 83492059 examples [1:21:35, 7323.01 examples/s] 
Generating train split: 83493258 examples [1:21:35, 7829.08 examples/s]
Generating train split: 83494397 examples [1:21:36, 7993.63 examples/s]
Generating train split: 83495452 examples [1:21:36, 6575.71 examples/s]
Generating train split: 83496322 examples [1:21:36, 6232.74 examples/s]
Generating train split: 83497094 examples [1:21:36, 5713.47 examples/s]
Generating train split: 83497775 examples [1:21:36, 5888.13 examples/s]
Generating train split: 83498447 examples [1:21:36, 5554.87 examples/s]
Generating train split: 83499804 examples [1:21:36, 7273.93 examples/s]
Generating train split: 83500635 examples [1:21:37, 4935.30 examples/s]
Generating train split: 83501483 examples [1:21:37, 5575.97 examples/s]
Generating train split: 83503293 examples [1:21:37, 8135.37 examples/s]
Generating train split: 83505131 examples [1:21:37, 10453.74 examples/s]
Generating train split: 83512942 examples [1:21:37, 26991.32 examples/s]
Generating train split: 83519230 examples [1:21:37, 36244.31 examples/s]
Generating train split: 83523379 examples [1:21:38, 13647.96 examples/s]
Generating train split: 83526447 examples [1:21:39, 7893.73 examples/s] 
Generating train split: 83528710 examples [1:21:39, 7731.47 examples/s]
Generating train split: 83531053 examples [1:21:39, 9134.59 examples/s]
Generating train split: 83533010 examples [1:21:40, 9466.22 examples/s]
Generating train split: 83534711 examples [1:21:40, 7367.37 examples/s]
Generating train split: 83536025 examples [1:21:40, 7971.27 examples/s]
Generating train split: 83537314 examples [1:21:40, 7455.70 examples/s]
Generating train split: 83539022 examples [1:21:40, 8866.12 examples/s]
Generating train split: 83540300 examples [1:21:41, 8123.44 examples/s]
Generating train split: 83541377 examples [1:21:41, 7711.67 examples/s]
Generating train split: 83542332 examples [1:21:41, 7795.45 examples/s]
Generating train split: 83543816 examples [1:21:41, 9195.67 examples/s]
Generating train split: 83544903 examples [1:21:41, 7289.01 examples/s]
Generating train split: 83551111 examples [1:21:41, 18000.93 examples/s]
Generating train split: 83559318 examples [1:21:41, 31922.09 examples/s]
Generating train split: 83563506 examples [1:21:42, 16097.17 examples/s]
Generating train split: 83566655 examples [1:21:43, 11394.33 examples/s]
Generating train split: 83569043 examples [1:21:43, 10683.03 examples/s]
Generating train split: 83570965 examples [1:21:43, 7033.60 examples/s] 
Generating train split: 83572408 examples [1:21:44, 7134.77 examples/s]
Generating train split: 83573643 examples [1:21:44, 5969.41 examples/s]
Generating train split: 83574607 examples [1:21:45, 4529.00 examples/s]
Generating train split: 83575341 examples [1:21:45, 4438.86 examples/s]
Generating train split: 83576280 examples [1:21:45, 4962.53 examples/s]
Generating train split: 83576995 examples [1:21:45, 3864.86 examples/s]
Generating train split: 83579071 examples [1:21:45, 6013.17 examples/s]
Generating train split: 83580561 examples [1:21:45, 7309.09 examples/s]
Generating train split: 83581703 examples [1:21:46, 7956.36 examples/s]
Generating train split: 83582816 examples [1:21:46, 6060.47 examples/s]
Generating train split: 83583833 examples [1:21:46, 6745.71 examples/s]
Generating train split: 83584759 examples [1:21:46, 6771.33 examples/s]
Generating train split: 83592779 examples [1:21:46, 21896.30 examples/s]
Generating train split: 83601198 examples [1:21:46, 35605.47 examples/s]
Generating train split: 83605702 examples [1:21:47, 14771.54 examples/s]
Generating train split: 83609034 examples [1:21:47, 15550.82 examples/s]
Generating train split: 83611931 examples [1:21:48, 11422.23 examples/s]
Generating train split: 83614140 examples [1:21:48, 10733.38 examples/s]
Generating train split: 83615948 examples [1:21:48, 10007.42 examples/s]
Generating train split: 83617572 examples [1:21:48, 10702.80 examples/s]
Generating train split: 83619073 examples [1:21:48, 9379.29 examples/s] 
Generating train split: 83620323 examples [1:21:49, 9121.50 examples/s]
Generating train split: 83622412 examples [1:21:49, 11106.11 examples/s]
Generating train split: 83623824 examples [1:21:49, 8885.76 examples/s] 
Generating train split: 83624971 examples [1:21:49, 9112.11 examples/s]
Generating train split: 83626081 examples [1:21:49, 8976.08 examples/s]
Generating train split: 83627161 examples [1:21:49, 9345.77 examples/s]
Generating train split: 83628215 examples [1:21:50, 5993.46 examples/s]
Generating train split: 83630681 examples [1:21:50, 9129.77 examples/s]
Generating train split: 83634631 examples [1:21:50, 15034.35 examples/s]
Generating train split: 83641562 examples [1:21:50, 26833.70 examples/s]
Generating train split: 83648106 examples [1:21:50, 35966.92 examples/s]
Generating train split: 83652557 examples [1:21:51, 20490.70 examples/s]
Generating train split: 83655969 examples [1:21:51, 15264.78 examples/s]
Generating train split: 83658626 examples [1:21:51, 13023.02 examples/s]
Generating train split: 83660732 examples [1:21:52, 8308.05 examples/s] 
Generating train split: 83662319 examples [1:21:52, 7816.96 examples/s]
Generating train split: 83663612 examples [1:21:52, 8103.90 examples/s]
Generating train split: 83664819 examples [1:21:53, 6041.13 examples/s]
Generating train split: 83665745 examples [1:21:53, 6029.50 examples/s]
Generating train split: 83666579 examples [1:21:53, 5927.43 examples/s]
Generating train split: 83667338 examples [1:21:53, 5995.05 examples/s]
Generating train split: 83669572 examples [1:21:53, 8798.10 examples/s]
Generating train split: 83670726 examples [1:21:53, 8538.61 examples/s]
Generating train split: 83671766 examples [1:21:54, 8626.24 examples/s]
Generating train split: 83674248 examples [1:21:54, 12203.17 examples/s]
Generating train split: 83675693 examples [1:21:54, 10921.56 examples/s]
Generating train split: 83676957 examples [1:21:54, 8050.34 examples/s] 
Generating train split: 83678479 examples [1:21:54, 9382.63 examples/s]
Generating train split: 83679806 examples [1:21:54, 10200.13 examples/s]
Generating train split: 83681025 examples [1:21:54, 10392.88 examples/s]
Generating train split: 83682661 examples [1:21:54, 11266.63 examples/s]
Generating train split: 83683892 examples [1:21:55, 8071.79 examples/s] 
Generating train split: 83685965 examples [1:21:55, 10590.42 examples/s]
Generating train split: 83687817 examples [1:21:55, 12319.94 examples/s]
Generating train split: 83689302 examples [1:21:55, 9021.53 examples/s] 
Generating train split: 83691057 examples [1:21:55, 10667.31 examples/s]
Generating train split: 83692418 examples [1:21:55, 11186.45 examples/s]
Generating train split: 83694089 examples [1:21:56, 12438.54 examples/s]
Generating train split: 83695524 examples [1:21:56, 8672.98 examples/s] 
Generating train split: 83696764 examples [1:21:56, 9365.52 examples/s]
Generating train split: 83698139 examples [1:21:56, 10311.97 examples/s]
Generating train split: 83699594 examples [1:21:56, 11298.36 examples/s]
Generating train split: 83700901 examples [1:21:56, 8150.29 examples/s] 
Generating train split: 83702433 examples [1:21:57, 9580.79 examples/s]
Generating train split: 83704135 examples [1:21:57, 11226.09 examples/s]
Generating train split: 83705486 examples [1:21:57, 7906.09 examples/s] 
Generating train split: 83707305 examples [1:21:57, 9832.12 examples/s]
Generating train split: 83709272 examples [1:21:57, 11904.97 examples/s]
Generating train split: 83710770 examples [1:21:57, 9284.78 examples/s] 
Generating train split: 83712008 examples [1:21:58, 8837.64 examples/s]
Generating train split: 83713147 examples [1:21:58, 9340.13 examples/s]
Generating train split: 83714258 examples [1:21:58, 8939.65 examples/s]
Generating train split: 83715275 examples [1:21:58, 7792.69 examples/s]
Generating train split: 83716153 examples [1:21:58, 7821.24 examples/s]
Generating train split: 83717199 examples [1:21:58, 8394.26 examples/s]
Generating train split: 83720663 examples [1:21:58, 14866.44 examples/s]
Generating train split: 83729578 examples [1:21:58, 34215.05 examples/s]
Generating train split: 83736070 examples [1:21:58, 42520.22 examples/s]
Generating train split: 83740709 examples [1:21:59, 20996.60 examples/s]
Generating train split: 83744246 examples [1:21:59, 16393.57 examples/s]
Generating train split: 83747018 examples [1:21:59, 17403.54 examples/s]
Generating train split: 83750297 examples [1:22:00, 19888.75 examples/s]
Generating train split: 83753115 examples [1:22:00, 13876.16 examples/s]
Generating train split: 83755436 examples [1:22:00, 15252.67 examples/s]
Generating train split: 83758637 examples [1:22:00, 18164.01 examples/s]
Generating train split: 83761406 examples [1:22:00, 20053.10 examples/s]
Generating train split: 83763995 examples [1:22:00, 16096.44 examples/s]
Generating train split: 83768272 examples [1:22:01, 21233.03 examples/s]
Generating train split: 83773792 examples [1:22:01, 28556.57 examples/s]
Generating train split: 83780020 examples [1:22:01, 36500.59 examples/s]
Generating train split: 83786712 examples [1:22:01, 44150.06 examples/s]
Generating train split: 83793111 examples [1:22:01, 49397.35 examples/s]
Generating train split: 83800141 examples [1:22:01, 55083.24 examples/s]
Generating train split: 83806529 examples [1:22:01, 57525.22 examples/s]
Generating train split: 83812823 examples [1:22:01, 59064.27 examples/s]
Generating train split: 83818962 examples [1:22:01, 59439.12 examples/s]
Generating train split: 83825075 examples [1:22:02, 59268.08 examples/s]
Generating train split: 83831115 examples [1:22:02, 57935.52 examples/s]
Generating train split: 83837001 examples [1:22:02, 56547.73 examples/s]
Generating train split: 83842733 examples [1:22:02, 54384.19 examples/s]
Generating train split: 83848227 examples [1:22:02, 45368.92 examples/s]
Generating train split: 83854207 examples [1:22:02, 48984.21 examples/s]
Generating train split: 83860941 examples [1:22:02, 53796.25 examples/s]
Generating train split: 83867743 examples [1:22:02, 57669.98 examples/s]
Generating train split: 83873725 examples [1:22:02, 55487.65 examples/s]
Generating train split: 83879435 examples [1:22:03, 55507.29 examples/s]
Generating train split: 83885567 examples [1:22:03, 57139.78 examples/s]
Generating train split: 83891381 examples [1:22:03, 52506.39 examples/s]
Generating train split: 83896774 examples [1:22:03, 49676.58 examples/s]
Generating train split: 83901846 examples [1:22:03, 49361.51 examples/s]
Generating train split: 83906855 examples [1:22:03, 40081.95 examples/s]
Generating train split: 83912820 examples [1:22:03, 44778.95 examples/s]
Generating train split: 83917639 examples [1:22:03, 43854.32 examples/s]
Generating train split: 83922631 examples [1:22:03, 45426.75 examples/s]
Generating train split: 83927372 examples [1:22:04, 37463.23 examples/s]
Generating train split: 83931464 examples [1:22:04, 26145.59 examples/s]
Generating train split: 83934742 examples [1:22:04, 26495.49 examples/s]
Generating train split: 83937868 examples [1:22:04, 20980.72 examples/s]
Generating train split: 83940445 examples [1:22:05, 15815.15 examples/s]
Generating train split: 83942492 examples [1:22:05, 12257.87 examples/s]
Generating train split: 83944128 examples [1:22:05, 10918.58 examples/s]
Generating train split: 83945804 examples [1:22:05, 11783.05 examples/s]
Generating train split: 83947260 examples [1:22:06, 8344.46 examples/s] 
Generating train split: 83949865 examples [1:22:06, 10925.44 examples/s]
Generating train split: 83951446 examples [1:22:06, 10905.29 examples/s]
Generating train split: 83952880 examples [1:22:06, 9592.58 examples/s] 
Generating train split: 83954559 examples [1:22:06, 10825.74 examples/s]
Generating train split: 83956857 examples [1:22:06, 13306.69 examples/s]
Generating train split: 83959178 examples [1:22:06, 15304.69 examples/s]
Generating train split: 83960973 examples [1:22:07, 10183.09 examples/s]
Generating train split: 83962394 examples [1:22:07, 10625.22 examples/s]
Generating train split: 83963753 examples [1:22:07, 9951.79 examples/s] 
Generating train split: 83964958 examples [1:22:07, 8417.00 examples/s]
Generating train split: 83967319 examples [1:22:07, 11299.96 examples/s]
Generating train split: 83968734 examples [1:22:07, 10952.03 examples/s]
Generating train split: 83970027 examples [1:22:08, 7769.63 examples/s] 
Generating train split: 83971063 examples [1:22:08, 7286.32 examples/s]
Generating train split: 83971967 examples [1:22:08, 5383.69 examples/s]
Generating train split: 83972689 examples [1:22:08, 5237.19 examples/s]
Generating train split: 83973338 examples [1:22:09, 5251.78 examples/s]
Generating train split: 83974068 examples [1:22:09, 5607.91 examples/s]
Generating train split: 83974713 examples [1:22:09, 4464.51 examples/s]
Generating train split: 83975468 examples [1:22:09, 5045.69 examples/s]
Generating train split: 83977497 examples [1:22:09, 8281.69 examples/s]
Generating train split: 83978525 examples [1:22:10, 4977.55 examples/s]
Generating train split: 83979474 examples [1:22:10, 5692.17 examples/s]
Generating train split: 83981067 examples [1:22:10, 7557.26 examples/s]
Generating train split: 83982126 examples [1:22:10, 5162.53 examples/s]
Generating train split: 83984352 examples [1:22:10, 7821.48 examples/s]
Generating train split: 83985654 examples [1:22:10, 8766.86 examples/s]
Generating train split: 83986900 examples [1:22:11, 6125.22 examples/s]
Generating train split: 83989548 examples [1:22:11, 9370.04 examples/s]
Generating train split: 83991724 examples [1:22:11, 11626.92 examples/s]
Generating train split: 83993396 examples [1:22:11, 11109.30 examples/s]
Generating train split: 83994865 examples [1:22:11, 8914.80 examples/s] 
Generating train split: 83996926 examples [1:22:11, 11034.77 examples/s]
Generating train split: 83998384 examples [1:22:12, 10808.12 examples/s]
Generating train split: 83999716 examples [1:22:12, 7279.62 examples/s] 
Generating train split: 84000954 examples [1:22:12, 8106.96 examples/s]
Generating train split: 84002159 examples [1:22:12, 8833.58 examples/s]
Generating train split: 84003288 examples [1:22:12, 8241.17 examples/s]
Generating train split: 84004313 examples [1:22:12, 8611.58 examples/s]
Generating train split: 84005320 examples [1:22:13, 8614.54 examples/s]
Generating train split: 84006282 examples [1:22:13, 8069.98 examples/s]
Generating train split: 84007159 examples [1:22:13, 8101.10 examples/s]
Generating train split: 84008026 examples [1:22:13, 5582.13 examples/s]
Generating train split: 84009472 examples [1:22:13, 7315.57 examples/s]
Generating train split: 84010788 examples [1:22:13, 8264.68 examples/s]
Generating train split: 84011765 examples [1:22:14, 5028.98 examples/s]
Generating train split: 84012521 examples [1:22:14, 4931.54 examples/s]
Generating train split: 84014706 examples [1:22:14, 7856.95 examples/s]
Generating train split: 84015838 examples [1:22:14, 8469.58 examples/s]
Generating train split: 84016956 examples [1:22:15, 5100.20 examples/s]
Generating train split: 84017814 examples [1:22:15, 5509.82 examples/s]
Generating train split: 84019065 examples [1:22:15, 6705.09 examples/s]
Generating train split: 84020023 examples [1:22:15, 6070.23 examples/s]
Generating train split: 84020838 examples [1:22:15, 5720.24 examples/s]
Generating train split: 84022574 examples [1:22:15, 7976.17 examples/s]
Generating train split: 84023596 examples [1:22:16, 4746.85 examples/s]
Generating train split: 84024375 examples [1:22:16, 5083.26 examples/s]
Generating train split: 84025130 examples [1:22:16, 4672.70 examples/s]
Generating train split: 84025768 examples [1:22:16, 4125.78 examples/s]
Generating train split: 84026976 examples [1:22:16, 5467.77 examples/s]
Generating train split: 84027720 examples [1:22:17, 4452.18 examples/s]
Generating train split: 84029058 examples [1:22:17, 6009.61 examples/s]
Generating train split: 84030952 examples [1:22:17, 8587.70 examples/s]
Generating train split: 84032555 examples [1:22:17, 10208.97 examples/s]
Generating train split: 84033831 examples [1:22:17, 6071.31 examples/s] 
Generating train split: 84034815 examples [1:22:17, 6613.22 examples/s]
Generating train split: 84035783 examples [1:22:17, 7172.89 examples/s]
Generating train split: 84036752 examples [1:22:18, 4289.85 examples/s]
Generating train split: 84037493 examples [1:22:18, 4692.39 examples/s]
Generating train split: 84038221 examples [1:22:19, 3096.02 examples/s]
Generating train split: 84039936 examples [1:22:19, 4854.93 examples/s]
Generating train split: 84041317 examples [1:22:19, 6216.67 examples/s]
Generating train split: 84042721 examples [1:22:19, 7572.06 examples/s]
Generating train split: 84043854 examples [1:22:19, 5951.96 examples/s]
Generating train split: 84044774 examples [1:22:19, 6347.65 examples/s]
Generating train split: 84045655 examples [1:22:19, 6713.59 examples/s]
Generating train split: 84048054 examples [1:22:19, 10395.81 examples/s]
Generating train split: 84056358 examples [1:22:20, 27345.12 examples/s]
Generating train split: 84062204 examples [1:22:20, 35069.34 examples/s]
Generating train split: 84066336 examples [1:22:20, 15989.62 examples/s]
Generating train split: 84069446 examples [1:22:21, 15041.47 examples/s]
Generating train split: 84072003 examples [1:22:21, 12661.50 examples/s]
Generating train split: 84074039 examples [1:22:21, 12042.59 examples/s]
Generating train split: 84076617 examples [1:22:21, 13893.56 examples/s]
Generating train split: 84078558 examples [1:22:22, 7203.60 examples/s] 
Generating train split: 84080354 examples [1:22:22, 8248.12 examples/s]
Generating train split: 84081847 examples [1:22:22, 8312.84 examples/s]
Generating train split: 84083159 examples [1:22:22, 7211.20 examples/s]
Generating train split: 84084473 examples [1:22:23, 7891.98 examples/s]
Generating train split: 84085569 examples [1:22:23, 6811.02 examples/s]
Generating train split: 84086469 examples [1:22:23, 4774.31 examples/s]
Generating train split: 84088086 examples [1:22:23, 6288.20 examples/s]
Generating train split: 84089066 examples [1:22:24, 5689.46 examples/s]
Generating train split: 84089887 examples [1:22:24, 5688.30 examples/s]
Generating train split: 84090670 examples [1:22:24, 6056.77 examples/s]
Generating train split: 84091624 examples [1:22:24, 6714.84 examples/s]
Generating train split: 84092430 examples [1:22:24, 5645.84 examples/s]
Generating train split: 84093108 examples [1:22:24, 4810.63 examples/s]
Generating train split: 84093797 examples [1:22:24, 5171.70 examples/s]
Generating train split: 84094407 examples [1:22:25, 3594.96 examples/s]
Generating train split: 84095106 examples [1:22:25, 4168.83 examples/s]
Generating train split: 84095651 examples [1:22:25, 3543.97 examples/s]
Generating train split: 84096111 examples [1:22:25, 3053.43 examples/s]
Generating train split: 84096520 examples [1:22:25, 3231.12 examples/s]
Generating train split: 84096911 examples [1:22:26, 2921.17 examples/s]
Generating train split: 84097252 examples [1:22:26, 3015.80 examples/s]
Generating train split: 84097604 examples [1:22:26, 2420.18 examples/s]
Generating train split: 84098077 examples [1:22:26, 2858.06 examples/s]
Generating train split: 84098420 examples [1:22:26, 2848.74 examples/s]
Generating train split: 84099048 examples [1:22:26, 3619.82 examples/s]
Generating train split: 84099468 examples [1:22:27, 1607.95 examples/s]
Generating train split: 84099781 examples [1:22:27, 1349.58 examples/s]
Generating train split: 84100031 examples [1:22:27, 1443.76 examples/s]
Generating train split: 84100261 examples [1:22:28, 1109.77 examples/s]
Generating train split: 84100441 examples [1:22:28, 1094.16 examples/s]
Generating train split: 84100602 examples [1:22:28, 950.83 examples/s] 
Generating train split: 84100761 examples [1:22:28, 1032.43 examples/s]
Generating train split: 84100902 examples [1:22:28, 987.19 examples/s] 
Generating train split: 84101115 examples [1:22:29, 1122.81 examples/s]
Generating train split: 84101251 examples [1:22:29, 914.35 examples/s] 
Generating train split: 84101406 examples [1:22:29, 1011.14 examples/s]
Generating train split: 84101533 examples [1:22:29, 1022.34 examples/s]
Generating train split: 84101989 examples [1:22:29, 1774.12 examples/s]
Generating train split: 84102205 examples [1:22:29, 1633.49 examples/s]
Generating train split: 84102581 examples [1:22:29, 2070.48 examples/s]
Generating train split: 84102829 examples [1:22:30, 2109.64 examples/s]
Generating train split: 84103781 examples [1:22:30, 3840.18 examples/s]
Generating train split: 84104210 examples [1:22:30, 2919.20 examples/s]
Generating train split: 84104559 examples [1:22:30, 2986.58 examples/s]
Generating train split: 84105525 examples [1:22:30, 4520.50 examples/s]
Generating train split: 84107060 examples [1:22:30, 7181.42 examples/s]
Generating train split: 84107899 examples [1:22:30, 6468.74 examples/s]
Generating train split: 84108919 examples [1:22:30, 7320.73 examples/s]
Generating train split: 84109730 examples [1:22:31, 6354.58 examples/s]
Generating train split: 84110448 examples [1:22:31, 3908.50 examples/s]
Generating train split: 84111002 examples [1:22:31, 3923.11 examples/s]
Generating train split: 84111511 examples [1:22:31, 3233.38 examples/s]
Generating train split: 84111955 examples [1:22:32, 3142.27 examples/s]
Generating train split: 84112345 examples [1:22:32, 2417.28 examples/s]
Generating train split: 84112688 examples [1:22:32, 2570.28 examples/s]
Generating train split: 84113003 examples [1:22:32, 2279.41 examples/s]
Generating train split: 84113289 examples [1:22:32, 2385.12 examples/s]
Generating train split: 84113705 examples [1:22:32, 2665.90 examples/s]
Generating train split: 84114005 examples [1:22:33, 2452.95 examples/s]
Generating train split: 84114412 examples [1:22:33, 2811.89 examples/s]
Generating train split: 84122768 examples [1:22:33, 22270.22 examples/s]
Generating train split: 84131612 examples [1:22:33, 39208.13 examples/s]
Generating train split: 84136172 examples [1:22:33, 23169.93 examples/s]
Generating train split: 84139718 examples [1:22:34, 9605.43 examples/s] 
Generating train split: 84147307 examples [1:22:34, 15429.65 examples/s]
Generating train split: 84156453 examples [1:22:34, 23907.59 examples/s]
Generating train split: 84162053 examples [1:22:35, 15245.01 examples/s]
Generating train split: 84166212 examples [1:22:36, 9607.17 examples/s] 
Generating train split: 84169253 examples [1:22:37, 7803.72 examples/s]
Generating train split: 84171514 examples [1:22:37, 6957.27 examples/s]
Generating train split: 84173294 examples [1:22:37, 7699.19 examples/s]
Generating train split: 84175035 examples [1:22:38, 6136.85 examples/s]
Generating train split: 84176538 examples [1:22:38, 6873.76 examples/s]
Generating train split: 84177907 examples [1:22:39, 5154.42 examples/s]
Generating train split: 84186471 examples [1:22:39, 12692.09 examples/s]
Generating train split: 84194826 examples [1:22:39, 21053.23 examples/s]
Generating train split: 84199639 examples [1:22:39, 17550.36 examples/s]
Generating train split: 84207503 examples [1:22:39, 25278.98 examples/s]
Generating train split: 84215614 examples [1:22:39, 33761.36 examples/s]
Generating train split: 84221499 examples [1:22:40, 22595.92 examples/s]
Generating train split: 84225990 examples [1:22:40, 19817.56 examples/s]
Generating train split: 84229556 examples [1:22:41, 15281.37 examples/s]
Generating train split: 84232294 examples [1:22:41, 10970.79 examples/s]
Generating train split: 84234882 examples [1:22:41, 12336.09 examples/s]
Generating train split: 84237172 examples [1:22:41, 13589.89 examples/s]
Generating train split: 84239383 examples [1:22:42, 13516.69 examples/s]
Generating train split: 84241332 examples [1:22:42, 10498.65 examples/s]
Generating train split: 84242870 examples [1:22:42, 11072.20 examples/s]
Generating train split: 84244378 examples [1:22:43, 6600.45 examples/s] 
Generating train split: 84246014 examples [1:22:43, 7701.41 examples/s]
Generating train split: 84247280 examples [1:22:43, 8164.21 examples/s]
Generating train split: 84249893 examples [1:22:43, 11126.93 examples/s]
Generating train split: 84251516 examples [1:22:43, 9217.78 examples/s] 
Generating train split: 84252831 examples [1:22:44, 7027.37 examples/s]
Generating train split: 84254682 examples [1:22:44, 8736.90 examples/s]
Generating train split: 84255963 examples [1:22:44, 6185.41 examples/s]
Generating train split: 84256963 examples [1:22:44, 5504.91 examples/s]
Generating train split: 84257941 examples [1:22:44, 6106.45 examples/s]
Generating train split: 84258805 examples [1:22:45, 4373.25 examples/s]
Generating train split: 84259480 examples [1:22:45, 3968.49 examples/s]
Generating train split: 84260041 examples [1:22:45, 4079.00 examples/s]
Generating train split: 84260758 examples [1:22:45, 4578.51 examples/s]
Generating train split: 84262467 examples [1:22:45, 6963.48 examples/s]
Generating train split: 84263388 examples [1:22:46, 4937.82 examples/s]
Generating train split: 84264197 examples [1:22:46, 5469.44 examples/s]
Generating train split: 84264951 examples [1:22:46, 3805.16 examples/s]
Generating train split: 84271983 examples [1:22:46, 13940.65 examples/s]
Generating train split: 84280765 examples [1:22:46, 27147.51 examples/s]
Generating train split: 84285163 examples [1:22:47, 15162.16 examples/s]
Generating train split: 84288763 examples [1:22:47, 17783.98 examples/s]
Generating train split: 84297205 examples [1:22:47, 27942.20 examples/s]
Generating train split: 84304356 examples [1:22:47, 35734.10 examples/s]
Generating train split: 84309950 examples [1:22:48, 20947.18 examples/s]
Generating train split: 84314164 examples [1:22:48, 14943.94 examples/s]
Generating train split: 84317363 examples [1:22:49, 11428.19 examples/s]
Generating train split: 84319769 examples [1:22:49, 11352.84 examples/s]
Generating train split: 84321787 examples [1:22:49, 10041.52 examples/s]
Generating train split: 84323404 examples [1:22:50, 8582.37 examples/s] 
Generating train split: 84324688 examples [1:22:50, 7122.73 examples/s]
Generating train split: 84325952 examples [1:22:50, 7655.48 examples/s]
Generating train split: 84327007 examples [1:22:50, 7364.26 examples/s]
Generating train split: 84328024 examples [1:22:50, 7788.60 examples/s]
Generating train split: 84328975 examples [1:22:51, 7864.28 examples/s]
Generating train split: 84329889 examples [1:22:51, 5150.40 examples/s]
Generating train split: 84330603 examples [1:22:51, 5181.63 examples/s]
Generating train split: 84331261 examples [1:22:51, 4086.34 examples/s]
Generating train split: 84331793 examples [1:22:52, 3435.71 examples/s]
Generating train split: 84332228 examples [1:22:52, 3436.54 examples/s]
Generating train split: 84333667 examples [1:22:52, 5316.33 examples/s]
Generating train split: 84335233 examples [1:22:52, 7352.04 examples/s]
Generating train split: 84336212 examples [1:22:52, 5502.31 examples/s]
Generating train split: 84336993 examples [1:22:52, 4923.78 examples/s]
Generating train split: 84338601 examples [1:22:53, 6884.82 examples/s]
Generating train split: 84339544 examples [1:22:53, 6633.17 examples/s]
Generating train split: 84340389 examples [1:22:53, 5050.20 examples/s]
Generating train split: 84341063 examples [1:22:53, 4823.47 examples/s]
Generating train split: 84342348 examples [1:22:53, 6274.84 examples/s]
Generating train split: 84343160 examples [1:22:53, 5915.52 examples/s]
Generating train split: 84343879 examples [1:22:54, 5439.42 examples/s]
Generating train split: 84344516 examples [1:22:54, 5539.08 examples/s]
Generating train split: 84345140 examples [1:22:54, 4236.50 examples/s]
Generating train split: 84346536 examples [1:22:54, 6111.79 examples/s]
Generating train split: 84347317 examples [1:22:54, 6460.58 examples/s]
Generating train split: 84348100 examples [1:22:54, 6174.44 examples/s]
Generating train split: 84350032 examples [1:22:54, 9177.51 examples/s]
Generating train split: 84351096 examples [1:22:55, 7508.82 examples/s]
Generating train split: 84352062 examples [1:22:55, 7914.50 examples/s]
Generating train split: 84352970 examples [1:22:55, 3819.74 examples/s]
Generating train split: 84353652 examples [1:22:55, 3996.35 examples/s]
Generating train split: 84354613 examples [1:22:56, 4768.20 examples/s]
Generating train split: 84355304 examples [1:22:56, 5011.28 examples/s]
Generating train split: 84355969 examples [1:22:56, 3987.19 examples/s]
Generating train split: 84357488 examples [1:22:56, 5942.64 examples/s]
Generating train split: 84358323 examples [1:22:56, 5756.46 examples/s]
Generating train split: 84360048 examples [1:22:56, 8066.04 examples/s]
Generating train split: 84361077 examples [1:22:56, 8136.88 examples/s]
Generating train split: 84362091 examples [1:22:57, 8598.07 examples/s]
Generating train split: 84363178 examples [1:22:57, 9163.36 examples/s]
Generating train split: 84364198 examples [1:22:57, 7258.48 examples/s]
Generating train split: 84365056 examples [1:22:57, 6684.09 examples/s]
Generating train split: 84366406 examples [1:22:57, 8164.67 examples/s]
Generating train split: 84367347 examples [1:22:57, 7904.44 examples/s]
Generating train split: 84368339 examples [1:22:57, 8306.51 examples/s]
Generating train split: 84372132 examples [1:22:57, 15856.98 examples/s]
Generating train split: 84379756 examples [1:22:58, 31971.37 examples/s]
Generating train split: 84385276 examples [1:22:58, 38381.60 examples/s]
Generating train split: 84389401 examples [1:22:58, 18021.92 examples/s]
Generating train split: 84392533 examples [1:22:59, 11942.89 examples/s]
Generating train split: 84394898 examples [1:22:59, 9970.37 examples/s] 
Generating train split: 84396746 examples [1:22:59, 9248.04 examples/s]
Generating train split: 84398250 examples [1:23:00, 7733.66 examples/s]
Generating train split: 84399440 examples [1:23:00, 6744.46 examples/s]
Generating train split: 84400406 examples [1:23:00, 6199.33 examples/s]
Generating train split: 84406807 examples [1:23:00, 13748.80 examples/s]
Generating train split: 84415609 examples [1:23:00, 25422.65 examples/s]
Generating train split: 84419984 examples [1:23:01, 19062.93 examples/s]
Generating train split: 84423407 examples [1:23:02, 10480.48 examples/s]
Generating train split: 84431430 examples [1:23:02, 17043.84 examples/s]
Generating train split: 84440423 examples [1:23:02, 25678.54 examples/s]
Generating train split: 84446037 examples [1:23:02, 17521.10 examples/s]
Generating train split: 84450263 examples [1:23:03, 13125.75 examples/s]
Generating train split: 84453424 examples [1:23:03, 10831.09 examples/s]
Generating train split: 84455827 examples [1:23:04, 10743.68 examples/s]
Generating train split: 84457821 examples [1:23:04, 9425.20 examples/s] 
Generating train split: 84459395 examples [1:23:04, 8259.65 examples/s]
Generating train split: 84460654 examples [1:23:05, 7366.35 examples/s]
Generating train split: 84462065 examples [1:23:05, 8096.31 examples/s]
Generating train split: 84463178 examples [1:23:05, 6927.80 examples/s]
Generating train split: 84464262 examples [1:23:05, 7425.14 examples/s]
Generating train split: 84465467 examples [1:23:05, 8132.44 examples/s]
Generating train split: 84466480 examples [1:23:05, 8481.70 examples/s]
Generating train split: 84467486 examples [1:23:06, 6823.66 examples/s]
Generating train split: 84468325 examples [1:23:06, 3959.70 examples/s]
Generating train split: 84468963 examples [1:23:06, 4011.66 examples/s]
Generating train split: 84477221 examples [1:23:06, 15786.98 examples/s]
Generating train split: 84485846 examples [1:23:06, 28208.83 examples/s]
Generating train split: 84490445 examples [1:23:07, 19380.72 examples/s]
Generating train split: 84494011 examples [1:23:07, 16849.07 examples/s]
Generating train split: 84501798 examples [1:23:07, 25471.02 examples/s]
Generating train split: 84509431 examples [1:23:07, 34006.44 examples/s]
Generating train split: 84514756 examples [1:23:08, 19546.49 examples/s]
Generating train split: 84518760 examples [1:23:09, 11888.32 examples/s]
Generating train split: 84521715 examples [1:23:09, 9901.84 examples/s] 
Generating train split: 84523956 examples [1:23:10, 6211.92 examples/s]
Generating train split: 84525595 examples [1:23:11, 6146.42 examples/s]
Generating train split: 84526916 examples [1:23:11, 5819.26 examples/s]
Generating train split: 84527973 examples [1:23:11, 5929.90 examples/s]
Generating train split: 84530279 examples [1:23:11, 7721.68 examples/s]
Generating train split: 84533213 examples [1:23:11, 10534.61 examples/s]
Generating train split: 84540801 examples [1:23:11, 20781.72 examples/s]
Generating train split: 84546112 examples [1:23:11, 26476.67 examples/s]
Generating train split: 84550125 examples [1:23:12, 10027.13 examples/s]
Generating train split: 84553061 examples [1:23:13, 9795.71 examples/s] 
Generating train split: 84555386 examples [1:23:13, 7193.90 examples/s]
Generating train split: 84557122 examples [1:23:14, 6955.95 examples/s]
Generating train split: 84558526 examples [1:23:14, 7243.10 examples/s]
Generating train split: 84559780 examples [1:23:14, 6629.66 examples/s]
Generating train split: 84560797 examples [1:23:14, 5576.37 examples/s]
Generating train split: 84561607 examples [1:23:15, 5405.19 examples/s]
Generating train split: 84562317 examples [1:23:15, 5026.98 examples/s]
Generating train split: 84563801 examples [1:23:15, 6453.71 examples/s]
Generating train split: 84564671 examples [1:23:15, 3761.41 examples/s]
Generating train split: 84565324 examples [1:23:16, 3203.56 examples/s]
Generating train split: 84565838 examples [1:23:16, 3275.02 examples/s]
Generating train split: 84566722 examples [1:23:16, 4046.31 examples/s]
Generating train split: 84573700 examples [1:23:16, 14909.23 examples/s]
Generating train split: 84581015 examples [1:23:16, 26030.05 examples/s]
Generating train split: 84584972 examples [1:23:17, 19376.27 examples/s]
Generating train split: 84591868 examples [1:23:17, 27811.08 examples/s]
Generating train split: 84599679 examples [1:23:17, 37039.84 examples/s]
Generating train split: 84604823 examples [1:23:18, 11730.39 examples/s]
Generating train split: 84608553 examples [1:23:18, 11186.26 examples/s]
Generating train split: 84611453 examples [1:23:19, 9627.43 examples/s] 
Generating train split: 84613676 examples [1:23:19, 8137.09 examples/s]
Generating train split: 84621902 examples [1:23:19, 14458.68 examples/s]
Generating train split: 84630187 examples [1:23:20, 21884.83 examples/s]
Generating train split: 84635233 examples [1:23:20, 20136.72 examples/s]
Generating train split: 84639263 examples [1:23:20, 14087.15 examples/s]
Generating train split: 84642290 examples [1:23:21, 11118.10 examples/s]
Generating train split: 84644595 examples [1:23:21, 9798.34 examples/s] 
Generating train split: 84646895 examples [1:23:21, 11082.73 examples/s]
Generating train split: 84654386 examples [1:23:21, 18877.25 examples/s]
Generating train split: 84663277 examples [1:23:22, 29098.66 examples/s]
Generating train split: 84668366 examples [1:23:22, 16766.71 examples/s]
Generating train split: 84672167 examples [1:23:23, 15202.29 examples/s]
Generating train split: 84675175 examples [1:23:23, 11692.75 examples/s]
Generating train split: 84677465 examples [1:23:23, 11538.37 examples/s]
Generating train split: 84679391 examples [1:23:23, 11248.40 examples/s]
Generating train split: 84681837 examples [1:23:24, 12945.45 examples/s]
Generating train split: 84683727 examples [1:23:24, 11937.94 examples/s]
Generating train split: 84685954 examples [1:23:24, 13507.97 examples/s]
Generating train split: 84687717 examples [1:23:24, 13281.75 examples/s]
Generating train split: 84689339 examples [1:23:24, 10313.70 examples/s]
Generating train split: 84690643 examples [1:23:24, 10209.01 examples/s]
Generating train split: 84692082 examples [1:23:25, 10166.20 examples/s]
Generating train split: 84693240 examples [1:23:25, 10371.96 examples/s]
Generating train split: 84694381 examples [1:23:25, 9612.11 examples/s] 
Generating train split: 84695414 examples [1:23:25, 8764.13 examples/s]
Generating train split: 84698139 examples [1:23:25, 12798.95 examples/s]
Generating train split: 84699585 examples [1:23:25, 8256.12 examples/s] 
Generating train split: 84701731 examples [1:23:25, 10547.18 examples/s]
Generating train split: 84703157 examples [1:23:26, 10733.27 examples/s]
Generating train split: 84710669 examples [1:23:26, 24519.35 examples/s]
Generating train split: 84718023 examples [1:23:26, 35995.51 examples/s]
Generating train split: 84722466 examples [1:23:26, 23894.83 examples/s]
Generating train split: 84725966 examples [1:23:27, 17497.06 examples/s]
Generating train split: 84728705 examples [1:23:27, 9000.97 examples/s] 
Generating train split: 84730726 examples [1:23:28, 6264.29 examples/s]
Generating train split: 84732224 examples [1:23:28, 5830.77 examples/s]
Generating train split: 84733787 examples [1:23:29, 6648.57 examples/s]
Generating train split: 84735075 examples [1:23:29, 6867.24 examples/s]
Generating train split: 84736228 examples [1:23:29, 7216.82 examples/s]
Generating train split: 84737307 examples [1:23:29, 6552.04 examples/s]
Generating train split: 84738212 examples [1:23:29, 5734.77 examples/s]
Generating train split: 84738956 examples [1:23:29, 5752.36 examples/s]
Generating train split: 84739652 examples [1:23:30, 5287.02 examples/s]
Generating train split: 84740275 examples [1:23:30, 4179.83 examples/s]
Generating train split: 84740778 examples [1:23:30, 4309.47 examples/s]
Generating train split: 84741274 examples [1:23:30, 4225.23 examples/s]
Generating train split: 84741874 examples [1:23:30, 4569.54 examples/s]
Generating train split: 84742880 examples [1:23:30, 5795.50 examples/s]
Generating train split: 84743539 examples [1:23:30, 5431.47 examples/s]
Generating train split: 84745151 examples [1:23:31, 7939.24 examples/s]
Generating train split: 84746050 examples [1:23:31, 5569.90 examples/s]
Generating train split: 84746765 examples [1:23:31, 5418.83 examples/s]
Generating train split: 84747744 examples [1:23:31, 6273.76 examples/s]
Generating train split: 84749329 examples [1:23:31, 8438.67 examples/s]
Generating train split: 84750324 examples [1:23:32, 5678.71 examples/s]
Generating train split: 84751607 examples [1:23:32, 6950.39 examples/s]
Generating train split: 84752546 examples [1:23:32, 7236.59 examples/s]
Generating train split: 84753440 examples [1:23:32, 7583.77 examples/s]
Generating train split: 84754334 examples [1:23:32, 6813.39 examples/s]
Generating train split: 84755127 examples [1:23:32, 5353.89 examples/s]
Generating train split: 84756436 examples [1:23:32, 6887.19 examples/s]
Generating train split: 84757295 examples [1:23:32, 6956.08 examples/s]
Generating train split: 84759024 examples [1:23:33, 9242.94 examples/s]
Generating train split: 84760096 examples [1:23:33, 5908.86 examples/s]
Generating train split: 84760934 examples [1:23:33, 5483.53 examples/s]
Generating train split: 84762363 examples [1:23:33, 7023.00 examples/s]
Generating train split: 84763282 examples [1:23:33, 6907.42 examples/s]
Generating train split: 84764556 examples [1:23:33, 7812.58 examples/s]
Generating train split: 84765469 examples [1:23:34, 6857.44 examples/s]
Generating train split: 84766314 examples [1:23:34, 7126.97 examples/s]
Generating train split: 84767116 examples [1:23:34, 7042.39 examples/s]
Generating train split: 84768366 examples [1:23:34, 8236.45 examples/s]
Generating train split: 84769250 examples [1:23:34, 6785.42 examples/s]
Generating train split: 84770766 examples [1:23:34, 8635.55 examples/s]
Generating train split: 84771741 examples [1:23:34, 7125.15 examples/s]
Generating train split: 84772574 examples [1:23:35, 5238.32 examples/s]
Generating train split: 84773486 examples [1:23:35, 5918.17 examples/s]
Generating train split: 84775338 examples [1:23:35, 8487.82 examples/s]
Generating train split: 84777006 examples [1:23:35, 10329.83 examples/s]
Generating train split: 84778255 examples [1:23:35, 6386.48 examples/s] 
Generating train split: 84780209 examples [1:23:36, 8594.17 examples/s]
Generating train split: 84781504 examples [1:23:36, 9439.55 examples/s]
Generating train split: 84782781 examples [1:23:36, 7108.88 examples/s]
Generating train split: 84783799 examples [1:23:36, 7621.63 examples/s]
Generating train split: 84784817 examples [1:23:36, 7998.02 examples/s]
Generating train split: 84786647 examples [1:23:36, 10178.04 examples/s]
Generating train split: 84787870 examples [1:23:36, 10541.52 examples/s]
Generating train split: 84789081 examples [1:23:37, 8490.84 examples/s] 
Generating train split: 84790804 examples [1:23:37, 10397.59 examples/s]
Generating train split: 84792273 examples [1:23:37, 11364.36 examples/s]
Generating train split: 84793570 examples [1:23:37, 7291.07 examples/s] 
Generating train split: 84795446 examples [1:23:37, 9349.35 examples/s]
Generating train split: 84796715 examples [1:23:37, 9367.73 examples/s]
Generating train split: 84797891 examples [1:23:38, 8327.08 examples/s]
Generating train split: 84798900 examples [1:23:38, 7553.06 examples/s]
Generating train split: 84807562 examples [1:23:38, 23658.80 examples/s]
Generating train split: 84816814 examples [1:23:38, 39177.45 examples/s]
Generating train split: 84821836 examples [1:23:39, 18560.78 examples/s]
Generating train split: 84825601 examples [1:23:39, 17683.39 examples/s]
Generating train split: 84828702 examples [1:23:39, 11741.21 examples/s]
Generating train split: 84835601 examples [1:23:39, 17802.33 examples/s]
Generating train split: 84844775 examples [1:23:40, 27517.44 examples/s]
Generating train split: 84850121 examples [1:23:40, 20309.70 examples/s]
Generating train split: 84854216 examples [1:23:41, 13176.83 examples/s]
Generating train split: 84857261 examples [1:23:41, 12193.41 examples/s]
Generating train split: 84859673 examples [1:23:42, 6846.41 examples/s] 
Generating train split: 84861432 examples [1:23:42, 7015.87 examples/s]
Generating train split: 84862907 examples [1:23:42, 7290.40 examples/s]
Generating train split: 84864225 examples [1:23:43, 6265.89 examples/s]
Generating train split: 84866641 examples [1:23:43, 8103.97 examples/s]
Generating train split: 84868083 examples [1:23:43, 5750.36 examples/s]
Generating train split: 84869178 examples [1:23:44, 6290.93 examples/s]
Generating train split: 84871047 examples [1:23:44, 7905.17 examples/s]
Generating train split: 84872365 examples [1:23:44, 5856.25 examples/s]
Generating train split: 84878040 examples [1:23:44, 12520.53 examples/s]
Generating train split: 84885836 examples [1:23:44, 22832.60 examples/s]
Generating train split: 84891865 examples [1:23:44, 29701.47 examples/s]
Generating train split: 84896490 examples [1:23:45, 13650.87 examples/s]
Generating train split: 84899907 examples [1:23:46, 12191.30 examples/s]
Generating train split: 84902567 examples [1:23:46, 8996.11 examples/s] 
Generating train split: 84904578 examples [1:23:46, 9980.07 examples/s]
Generating train split: 84906567 examples [1:23:46, 10455.88 examples/s]
Generating train split: 84915341 examples [1:23:46, 20768.15 examples/s]
Generating train split: 84922954 examples [1:23:47, 29594.77 examples/s]
Generating train split: 84927932 examples [1:23:47, 21797.11 examples/s]
Generating train split: 84931814 examples [1:23:47, 16696.34 examples/s]
Generating train split: 84934815 examples [1:23:48, 16093.89 examples/s]
Generating train split: 84937348 examples [1:23:48, 12898.45 examples/s]
Generating train split: 84939338 examples [1:23:48, 8901.12 examples/s] 
Generating train split: 84941763 examples [1:23:49, 10506.07 examples/s]
Generating train split: 84943551 examples [1:23:49, 7795.13 examples/s] 
Generating train split: 84944917 examples [1:23:49, 6253.24 examples/s]
Generating train split: 84945978 examples [1:23:50, 6365.54 examples/s]
Generating train split: 84946927 examples [1:23:50, 4613.95 examples/s]
Generating train split: 84948291 examples [1:23:50, 5576.49 examples/s]
Generating train split: 84949198 examples [1:23:51, 4055.13 examples/s]
Generating train split: 84949896 examples [1:23:51, 4326.37 examples/s]
Generating train split: 84950572 examples [1:23:51, 3358.54 examples/s]
Generating train split: 84951478 examples [1:23:51, 4008.25 examples/s]
Generating train split: 84952095 examples [1:23:51, 4135.21 examples/s]
Generating train split: 84952955 examples [1:23:51, 4883.71 examples/s]
Generating train split: 84953740 examples [1:23:52, 5421.67 examples/s]
Generating train split: 84954435 examples [1:23:52, 4014.96 examples/s]
Generating train split: 84954994 examples [1:23:52, 3924.21 examples/s]
Generating train split: 84956455 examples [1:23:52, 5932.12 examples/s]
Generating train split: 84957244 examples [1:23:52, 4544.46 examples/s]
Generating train split: 84957877 examples [1:23:53, 4759.93 examples/s]
Generating train split: 84958503 examples [1:23:53, 4117.52 examples/s]
Generating train split: 84959023 examples [1:23:53, 3611.04 examples/s]
Generating train split: 84959466 examples [1:23:53, 3737.48 examples/s]
Generating train split: 84960611 examples [1:23:53, 5330.23 examples/s]
Generating train split: 84961852 examples [1:23:53, 6939.51 examples/s]
Generating train split: 84962684 examples [1:23:53, 6171.06 examples/s]
Generating train split: 84963961 examples [1:23:54, 7674.40 examples/s]
Generating train split: 84964862 examples [1:23:54, 5731.02 examples/s]
Generating train split: 84965663 examples [1:23:54, 5887.48 examples/s]
Generating train split: 84966370 examples [1:23:54, 5037.08 examples/s]
Generating train split: 84966972 examples [1:23:54, 4798.06 examples/s]
Generating train split: 84968895 examples [1:23:54, 7697.37 examples/s]
Generating train split: 84969815 examples [1:23:55, 6612.78 examples/s]
Generating train split: 84970662 examples [1:23:55, 6914.58 examples/s]
Generating train split: 84971453 examples [1:23:55, 4918.20 examples/s]
Generating train split: 84972098 examples [1:23:55, 4229.47 examples/s]
Generating train split: 84972633 examples [1:23:56, 2546.22 examples/s]
Generating train split: 84973036 examples [1:23:56, 2365.96 examples/s]
Generating train split: 84973664 examples [1:23:56, 2857.85 examples/s]
Generating train split: 84974075 examples [1:23:56, 2676.30 examples/s]
Generating train split: 84974428 examples [1:23:56, 2287.07 examples/s]
Generating train split: 84975142 examples [1:23:57, 2998.13 examples/s]
Generating train split: 84975534 examples [1:23:57, 2668.99 examples/s]
Generating train split: 84975870 examples [1:23:57, 2395.36 examples/s]
Generating train split: 84976161 examples [1:23:57, 1897.34 examples/s]
Generating train split: 84976548 examples [1:23:57, 2150.07 examples/s]
Generating train split: 84976815 examples [1:23:57, 2238.43 examples/s]
Generating train split: 84977080 examples [1:23:58, 2193.30 examples/s]
Generating train split: 84980896 examples [1:23:58, 10104.22 examples/s]
Generating train split: 84989249 examples [1:23:58, 27652.52 examples/s]
Generating train split: 84994710 examples [1:23:58, 33083.86 examples/s]
Generating train split: 84998508 examples [1:23:59, 10847.52 examples/s]
Generating train split: 85001294 examples [1:24:00, 7903.04 examples/s] 
Generating train split: 85003364 examples [1:24:00, 8756.75 examples/s]
Generating train split: 85005342 examples [1:24:00, 9814.21 examples/s]
Generating train split: 85007229 examples [1:24:00, 8750.12 examples/s]
Generating train split: 85009419 examples [1:24:00, 10444.69 examples/s]
Generating train split: 85011862 examples [1:24:00, 12618.11 examples/s]
Generating train split: 85013795 examples [1:24:01, 9512.68 examples/s] 
Generating train split: 85015320 examples [1:24:01, 10025.19 examples/s]
Generating train split: 85017975 examples [1:24:01, 12875.55 examples/s]
Generating train split: 85019921 examples [1:24:01, 14171.48 examples/s]
Generating train split: 85021772 examples [1:24:01, 12225.60 examples/s]
Generating train split: 85023334 examples [1:24:01, 11354.61 examples/s]
Generating train split: 85024827 examples [1:24:01, 12020.86 examples/s]
Generating train split: 85026228 examples [1:24:02, 8944.97 examples/s] 
Generating train split: 85027606 examples [1:24:02, 9777.13 examples/s]
Generating train split: 85029530 examples [1:24:02, 11737.67 examples/s]
Generating train split: 85031760 examples [1:24:02, 14155.22 examples/s]
Generating train split: 85033410 examples [1:24:02, 8190.07 examples/s] 
Generating train split: 85036079 examples [1:24:03, 11205.46 examples/s]
Generating train split: 85037767 examples [1:24:03, 8723.41 examples/s] 
Generating train split: 85039139 examples [1:24:03, 9526.45 examples/s]
Generating train split: 85040615 examples [1:24:03, 10498.29 examples/s]
Generating train split: 85042849 examples [1:24:03, 12982.21 examples/s]
Generating train split: 85044486 examples [1:24:03, 9389.13 examples/s] 
Generating train split: 85045795 examples [1:24:04, 9237.03 examples/s]
Generating train split: 85047941 examples [1:24:04, 11600.24 examples/s]
Generating train split: 85049409 examples [1:24:04, 6526.47 examples/s] 
Generating train split: 85050525 examples [1:24:04, 5952.70 examples/s]
Generating train split: 85051627 examples [1:24:05, 6679.27 examples/s]
Generating train split: 85052612 examples [1:24:05, 6701.22 examples/s]
Generating train split: 85055040 examples [1:24:05, 9935.60 examples/s]
Generating train split: 85056393 examples [1:24:05, 9738.30 examples/s]
Generating train split: 85057619 examples [1:24:06, 4047.68 examples/s]
Generating train split: 85058519 examples [1:24:06, 4179.06 examples/s]
Generating train split: 85060595 examples [1:24:06, 6196.33 examples/s]
Generating train split: 85061751 examples [1:24:06, 5871.77 examples/s]
Generating train split: 85062709 examples [1:24:07, 5110.58 examples/s]
Generating train split: 85063485 examples [1:24:07, 4783.09 examples/s]
Generating train split: 85069365 examples [1:24:07, 13104.33 examples/s]
Generating train split: 85077134 examples [1:24:07, 24752.04 examples/s]
Generating train split: 85082272 examples [1:24:07, 29640.45 examples/s]
Generating train split: 85086412 examples [1:24:08, 14601.79 examples/s]
Generating train split: 85093930 examples [1:24:08, 22235.06 examples/s]
Generating train split: 85101803 examples [1:24:08, 30850.26 examples/s]
Generating train split: 85107259 examples [1:24:09, 18110.40 examples/s]
Generating train split: 85111337 examples [1:24:10, 8539.58 examples/s] 
Generating train split: 85114283 examples [1:24:11, 6913.26 examples/s]
Generating train split: 85116468 examples [1:24:11, 6967.77 examples/s]
Generating train split: 85118209 examples [1:24:11, 6889.93 examples/s]
Generating train split: 85119638 examples [1:24:11, 6477.21 examples/s]
Generating train split: 85120782 examples [1:24:12, 5694.25 examples/s]
Generating train split: 85121988 examples [1:24:12, 6304.35 examples/s]
Generating train split: 85122973 examples [1:24:12, 6638.70 examples/s]
Generating train split: 85124030 examples [1:24:12, 7001.09 examples/s]
Generating train split: 85124963 examples [1:24:12, 6695.43 examples/s]
Generating train split: 85126542 examples [1:24:12, 8319.10 examples/s]
Generating train split: 85127597 examples [1:24:13, 6372.47 examples/s]
Generating train split: 85128442 examples [1:24:13, 4636.46 examples/s]
Generating train split: 85129104 examples [1:24:13, 3953.40 examples/s]
Generating train split: 85129651 examples [1:24:13, 4037.75 examples/s]
Generating train split: 85130168 examples [1:24:14, 3927.88 examples/s]
Generating train split: 85130642 examples [1:24:14, 4029.30 examples/s]
Generating train split: 85132084 examples [1:24:14, 6139.79 examples/s]
Generating train split: 85133292 examples [1:24:14, 7435.42 examples/s]
Generating train split: 85134972 examples [1:24:14, 9697.99 examples/s]
Generating train split: 85136093 examples [1:24:14, 5914.67 examples/s]
Generating train split: 85137439 examples [1:24:14, 7223.01 examples/s]
Generating train split: 85138458 examples [1:24:15, 7187.68 examples/s]
Generating train split: 85139591 examples [1:24:15, 8021.58 examples/s]
Generating train split: 85140570 examples [1:24:15, 5850.67 examples/s]
Generating train split: 85141354 examples [1:24:15, 4991.51 examples/s]
Generating train split: 85142601 examples [1:24:15, 6291.19 examples/s]
Generating train split: 85143434 examples [1:24:16, 5600.10 examples/s]
Generating train split: 85144145 examples [1:24:16, 5212.03 examples/s]
Generating train split: 85144907 examples [1:24:16, 5600.63 examples/s]
Generating train split: 85145738 examples [1:24:16, 6180.88 examples/s]
Generating train split: 85146442 examples [1:24:16, 4852.27 examples/s]
Generating train split: 85147029 examples [1:24:16, 4992.72 examples/s]
Generating train split: 85147602 examples [1:24:16, 4975.51 examples/s]
Generating train split: 85148709 examples [1:24:17, 6175.01 examples/s]
Generating train split: 85149388 examples [1:24:17, 5202.96 examples/s]
Generating train split: 85150293 examples [1:24:17, 6031.37 examples/s]
Generating train split: 85150968 examples [1:24:17, 5270.07 examples/s]
Generating train split: 85151565 examples [1:24:17, 3630.26 examples/s]
Generating train split: 85152421 examples [1:24:17, 4476.94 examples/s]
Generating train split: 85153134 examples [1:24:17, 5009.29 examples/s]
Generating train split: 85154026 examples [1:24:18, 5877.48 examples/s]
Generating train split: 85154729 examples [1:24:18, 6045.09 examples/s]
Generating train split: 85156206 examples [1:24:18, 8253.25 examples/s]
Generating train split: 85157471 examples [1:24:18, 9418.23 examples/s]
Generating train split: 85158496 examples [1:24:18, 8475.57 examples/s]
Generating train split: 85159428 examples [1:24:18, 7154.18 examples/s]
Generating train split: 85160231 examples [1:24:18, 6543.17 examples/s]
Generating train split: 85162488 examples [1:24:18, 10188.06 examples/s]
Generating train split: 85163674 examples [1:24:19, 9140.66 examples/s] 
Generating train split: 85171433 examples [1:24:19, 25024.16 examples/s]
Generating train split: 85179556 examples [1:24:19, 38930.36 examples/s]
Generating train split: 85184111 examples [1:24:19, 18905.01 examples/s]
Generating train split: 85187552 examples [1:24:20, 15719.06 examples/s]
Generating train split: 85190274 examples [1:24:21, 7843.07 examples/s] 
Generating train split: 85192266 examples [1:24:21, 7662.33 examples/s]
Generating train split: 85193867 examples [1:24:22, 5242.91 examples/s]
Generating train split: 85195059 examples [1:24:22, 5058.02 examples/s]
Generating train split: 85202704 examples [1:24:22, 11212.27 examples/s]
Generating train split: 85211153 examples [1:24:22, 19200.02 examples/s]
Generating train split: 85215707 examples [1:24:23, 11814.56 examples/s]
Generating train split: 85219071 examples [1:24:24, 9938.31 examples/s] 
Generating train split: 85221616 examples [1:24:24, 10378.75 examples/s]
Generating train split: 85223787 examples [1:24:25, 5298.20 examples/s] 
Generating train split: 85225363 examples [1:24:25, 5160.63 examples/s]
Generating train split: 85226604 examples [1:24:26, 4806.10 examples/s]
Generating train split: 85227576 examples [1:24:26, 4615.09 examples/s]
Generating train split: 85228375 examples [1:24:26, 3668.13 examples/s]
Generating train split: 85228987 examples [1:24:27, 3816.57 examples/s]
Generating train split: 85229945 examples [1:24:27, 4379.02 examples/s]
Generating train split: 85230607 examples [1:24:27, 3043.81 examples/s]
Generating train split: 85231348 examples [1:24:27, 3510.04 examples/s]
Generating train split: 85231915 examples [1:24:27, 3625.21 examples/s]
Generating train split: 85233606 examples [1:24:28, 5699.89 examples/s]
Generating train split: 85234472 examples [1:24:28, 5529.93 examples/s]
Generating train split: 85235239 examples [1:24:28, 5359.75 examples/s]
Generating train split: 85235928 examples [1:24:28, 4417.29 examples/s]
Generating train split: 85236496 examples [1:24:28, 3544.37 examples/s]
Generating train split: 85236963 examples [1:24:28, 3674.19 examples/s]
Generating train split: 85237768 examples [1:24:29, 4396.65 examples/s]
Generating train split: 85238309 examples [1:24:29, 3971.36 examples/s]
Generating train split: 85238835 examples [1:24:29, 4209.94 examples/s]
Generating train split: 85239315 examples [1:24:29, 3219.20 examples/s]
Generating train split: 85239715 examples [1:24:30, 1873.10 examples/s]
Generating train split: 85240016 examples [1:24:30, 1902.69 examples/s]
Generating train split: 85240285 examples [1:24:30, 1941.50 examples/s]
Generating train split: 85240542 examples [1:24:30, 1592.57 examples/s]
Generating train split: 85246772 examples [1:24:30, 11297.17 examples/s]
Generating train split: 85255913 examples [1:24:30, 26186.46 examples/s]
Generating train split: 85260108 examples [1:24:30, 29388.71 examples/s]
Generating train split: 85264261 examples [1:24:31, 15480.05 examples/s]
Generating train split: 85273438 examples [1:24:31, 25889.01 examples/s]
Generating train split: 85279243 examples [1:24:31, 31134.74 examples/s]
Generating train split: 85284442 examples [1:24:32, 17454.01 examples/s]
Generating train split: 85288336 examples [1:24:32, 12705.95 examples/s]
Generating train split: 85291262 examples [1:24:33, 10825.00 examples/s]
Generating train split: 85293512 examples [1:24:33, 8362.11 examples/s] 
Generating train split: 85295218 examples [1:24:34, 5824.82 examples/s]
Generating train split: 85296478 examples [1:24:34, 5742.28 examples/s]
Generating train split: 85297523 examples [1:24:35, 4251.02 examples/s]
Generating train split: 85298308 examples [1:24:35, 4050.64 examples/s]
Generating train split: 85298951 examples [1:24:36, 2880.05 examples/s]
Generating train split: 85299436 examples [1:24:36, 2974.64 examples/s]
Generating train split: 85299901 examples [1:24:36, 2859.68 examples/s]
Generating train split: 85300286 examples [1:24:36, 2834.38 examples/s]
Generating train split: 85300640 examples [1:24:37, 2500.62 examples/s]
Generating train split: 85300948 examples [1:24:37, 2172.13 examples/s]
Generating train split: 85301196 examples [1:24:37, 2077.82 examples/s]
Generating train split: 85301591 examples [1:24:37, 2318.24 examples/s]
Generating train split: 85301860 examples [1:24:37, 1861.67 examples/s]
Generating train split: 85302093 examples [1:24:37, 1937.68 examples/s]
Generating train split: 85302321 examples [1:24:38, 1824.51 examples/s]
Generating train split: 85302529 examples [1:24:38, 1687.09 examples/s]
Generating train split: 85303330 examples [1:24:38, 2971.80 examples/s]
Generating train split: 85303686 examples [1:24:38, 2937.04 examples/s]
Generating train split: 85305356 examples [1:24:38, 6165.13 examples/s]
Generating train split: 85306102 examples [1:24:39, 3776.56 examples/s]
Generating train split: 85306683 examples [1:24:39, 2915.10 examples/s]
Generating train split: 85307304 examples [1:24:39, 3399.83 examples/s]
Generating train split: 85307816 examples [1:24:39, 3234.69 examples/s]
Generating train split: 85308253 examples [1:24:39, 3421.20 examples/s]
Generating train split: 85311869 examples [1:24:39, 10062.24 examples/s]
Generating train split: 85313523 examples [1:24:39, 11279.63 examples/s]
Generating train split: 85314947 examples [1:24:40, 9658.98 examples/s] 
Generating train split: 85318415 examples [1:24:40, 15059.83 examples/s]
Generating train split: 85320310 examples [1:24:40, 15902.65 examples/s]
Generating train split: 85323169 examples [1:24:40, 19005.43 examples/s]
Generating train split: 85325329 examples [1:24:40, 11109.34 examples/s]
Generating train split: 85327270 examples [1:24:40, 12560.71 examples/s]
Generating train split: 85329209 examples [1:24:41, 13918.39 examples/s]
Generating train split: 85331030 examples [1:24:41, 10176.00 examples/s]
Generating train split: 85332477 examples [1:24:41, 10705.95 examples/s]
Generating train split: 85333934 examples [1:24:41, 11475.39 examples/s]
Generating train split: 85335351 examples [1:24:42, 6349.56 examples/s] 
Generating train split: 85336426 examples [1:24:42, 4571.44 examples/s]
Generating train split: 85340622 examples [1:24:42, 8979.76 examples/s]
Generating train split: 85349410 examples [1:24:42, 20353.51 examples/s]
Generating train split: 85354262 examples [1:24:42, 25157.87 examples/s]
Generating train split: 85358472 examples [1:24:43, 11675.48 examples/s]
Generating train split: 85361565 examples [1:24:44, 9082.39 examples/s] 
Generating train split: 85363891 examples [1:24:44, 7426.47 examples/s]
Generating train split: 85365656 examples [1:24:44, 8033.59 examples/s]
Generating train split: 85367276 examples [1:24:45, 6637.58 examples/s]
Generating train split: 85368548 examples [1:24:45, 7243.91 examples/s]
Generating train split: 85369897 examples [1:24:45, 8012.80 examples/s]
Generating train split: 85371718 examples [1:24:45, 9523.56 examples/s]
Generating train split: 85373157 examples [1:24:46, 6854.04 examples/s]
Generating train split: 85374277 examples [1:24:46, 7159.31 examples/s]
Generating train split: 85375318 examples [1:24:46, 5194.36 examples/s]
Generating train split: 85376337 examples [1:24:46, 5872.50 examples/s]
Generating train split: 85377220 examples [1:24:46, 5061.27 examples/s]
Generating train split: 85378386 examples [1:24:47, 5978.77 examples/s]
Generating train split: 85379198 examples [1:24:47, 5573.54 examples/s]
Generating train split: 85379901 examples [1:24:47, 4897.65 examples/s]
Generating train split: 85381351 examples [1:24:47, 6626.30 examples/s]
Generating train split: 85389202 examples [1:24:47, 21344.17 examples/s]
Generating train split: 85395796 examples [1:24:47, 31434.12 examples/s]
Generating train split: 85399847 examples [1:24:47, 25869.92 examples/s]
Generating train split: 85403222 examples [1:24:48, 11649.52 examples/s]
Generating train split: 85405725 examples [1:24:49, 6218.89 examples/s] 
Generating train split: 85407554 examples [1:24:50, 4654.78 examples/s]
Generating train split: 85408894 examples [1:24:51, 3760.01 examples/s]
Generating train split: 85409892 examples [1:24:51, 3182.29 examples/s]
Generating train split: 85410650 examples [1:24:52, 2780.21 examples/s]
Generating train split: 85412549 examples [1:24:52, 3863.14 examples/s]
Generating train split: 85413511 examples [1:24:52, 3669.99 examples/s]
Generating train split: 85414278 examples [1:24:53, 3452.84 examples/s]
Generating train split: 85414964 examples [1:24:53, 3619.50 examples/s]
Generating train split: 85415541 examples [1:24:53, 3249.67 examples/s]
Generating train split: 85416008 examples [1:24:53, 3308.93 examples/s]
Generating train split: 85416451 examples [1:24:53, 3162.38 examples/s]
Generating train split: 85417063 examples [1:24:53, 3644.24 examples/s]
Generating train split: 85417522 examples [1:24:54, 3188.94 examples/s]
Generating train split: 85419278 examples [1:24:54, 5725.33 examples/s]
Generating train split: 85420776 examples [1:24:54, 7395.69 examples/s]
Generating train split: 85421693 examples [1:24:54, 7116.81 examples/s]
Generating train split: 85422529 examples [1:24:54, 6806.10 examples/s]
Generating train split: 85423299 examples [1:24:54, 6220.05 examples/s]
Generating train split: 85423983 examples [1:24:55, 4555.47 examples/s]
Generating train split: 85424599 examples [1:24:55, 4852.30 examples/s]
Generating train split: 85425171 examples [1:24:55, 4907.28 examples/s]
Generating train split: 85426416 examples [1:24:55, 6589.40 examples/s]
Generating train split: 85427174 examples [1:24:55, 3695.00 examples/s]
Generating train split: 85427754 examples [1:24:55, 3927.50 examples/s]
Generating train split: 85428645 examples [1:24:56, 4827.15 examples/s]
Generating train split: 85429306 examples [1:24:56, 4885.96 examples/s]
Generating train split: 85430322 examples [1:24:56, 6023.12 examples/s]
Generating train split: 85431059 examples [1:24:56, 5476.03 examples/s]
Generating train split: 85431713 examples [1:24:56, 5496.58 examples/s]
Generating train split: 85432342 examples [1:24:56, 4326.22 examples/s]
Generating train split: 85433792 examples [1:24:56, 6393.69 examples/s]
Generating train split: 85434586 examples [1:24:57, 6250.55 examples/s]
Generating train split: 85435323 examples [1:24:57, 4359.17 examples/s]
Generating train split: 85435907 examples [1:24:57, 4065.78 examples/s]
Generating train split: 85437067 examples [1:24:57, 5339.02 examples/s]
Generating train split: 85438461 examples [1:24:57, 7103.52 examples/s]
Generating train split: 85440620 examples [1:24:57, 10380.83 examples/s]
Generating train split: 85442660 examples [1:24:57, 12806.46 examples/s]
Generating train split: 85444165 examples [1:24:58, 7930.79 examples/s] 
Generating train split: 85446294 examples [1:24:58, 10252.48 examples/s]
Generating train split: 85449916 examples [1:24:58, 15510.22 examples/s]
Generating train split: 85455206 examples [1:24:58, 23902.09 examples/s]
Generating train split: 85461727 examples [1:24:58, 33934.43 examples/s]
Generating train split: 85468235 examples [1:24:58, 41953.84 examples/s]
Generating train split: 85474932 examples [1:24:58, 48679.55 examples/s]
Generating train split: 85481868 examples [1:24:59, 54391.01 examples/s]
Generating train split: 85487718 examples [1:24:59, 53826.41 examples/s]
Generating train split: 85495139 examples [1:24:59, 59559.44 examples/s]
Generating train split: 85502874 examples [1:24:59, 64664.69 examples/s]
Generating train split: 85510233 examples [1:24:59, 67240.25 examples/s]
Generating train split: 85518199 examples [1:24:59, 70883.67 examples/s]
Generating train split: 85525908 examples [1:24:59, 72713.56 examples/s]
Generating train split: 85533258 examples [1:24:59, 72255.67 examples/s]
Generating train split: 85540595 examples [1:24:59, 72556.54 examples/s]
Generating train split: 85547899 examples [1:24:59, 72000.59 examples/s]
Generating train split: 85555128 examples [1:25:00, 70386.99 examples/s]
Generating train split: 85563106 examples [1:25:00, 73099.24 examples/s]
Generating train split: 85570733 examples [1:25:00, 74031.04 examples/s]
Generating train split: 85578400 examples [1:25:00, 74806.89 examples/s]
Generating train split: 85586645 examples [1:25:00, 77070.77 examples/s]
Generating train split: 85594374 examples [1:25:00, 75878.54 examples/s]
Generating train split: 85602364 examples [1:25:00, 77042.52 examples/s]
Generating train split: 85610084 examples [1:25:00, 70037.61 examples/s]
Generating train split: 85617214 examples [1:25:00, 66496.44 examples/s]
Generating train split: 85624444 examples [1:25:00, 68053.07 examples/s]
Generating train split: 85631347 examples [1:25:01, 66749.62 examples/s]
Generating train split: 85638090 examples [1:25:01, 64916.25 examples/s]
Generating train split: 85644637 examples [1:25:01, 54262.14 examples/s]
Generating train split: 85650374 examples [1:25:01, 43093.93 examples/s]
Generating train split: 85655201 examples [1:25:02, 20724.02 examples/s]
Generating train split: 85658812 examples [1:25:02, 18384.19 examples/s]
Generating train split: 85661722 examples [1:25:02, 15403.45 examples/s]
Generating train split: 85664049 examples [1:25:03, 9549.80 examples/s] 
Generating train split: 85665784 examples [1:25:04, 7243.35 examples/s]
Generating train split: 85667087 examples [1:25:04, 7534.89 examples/s]
Generating train split: 85668384 examples [1:25:04, 8117.28 examples/s]
Generating train split: 85669616 examples [1:25:04, 6574.36 examples/s]
Generating train split: 85670598 examples [1:25:04, 6796.96 examples/s]
Generating train split: 85671722 examples [1:25:04, 7445.96 examples/s]
Generating train split: 85672706 examples [1:25:05, 6311.15 examples/s]
Generating train split: 85674663 examples [1:25:05, 8528.61 examples/s]
Generating train split: 85677149 examples [1:25:05, 11677.36 examples/s]
Generating train split: 85678709 examples [1:25:05, 10557.49 examples/s]
Generating train split: 85680062 examples [1:25:05, 11063.43 examples/s]
Generating train split: 85681403 examples [1:25:05, 9944.99 examples/s] 
Generating train split: 85683616 examples [1:25:05, 12434.25 examples/s]
Generating train split: 85685070 examples [1:25:06, 9240.19 examples/s] 
Generating train split: 85686251 examples [1:25:06, 9721.10 examples/s]
Generating train split: 85687424 examples [1:25:06, 9449.71 examples/s]
Generating train split: 85688870 examples [1:25:06, 10565.90 examples/s]
Generating train split: 85690066 examples [1:25:06, 5508.61 examples/s] 
Generating train split: 85690984 examples [1:25:07, 5528.80 examples/s]
Generating train split: 85693040 examples [1:25:07, 7894.51 examples/s]
Generating train split: 85694192 examples [1:25:07, 7008.56 examples/s]
Generating train split: 85695999 examples [1:25:07, 8978.09 examples/s]
Generating train split: 85697563 examples [1:25:07, 10329.24 examples/s]
Generating train split: 85699164 examples [1:25:07, 11607.38 examples/s]
Generating train split: 85700570 examples [1:25:08, 8372.22 examples/s] 
Generating train split: 85703379 examples [1:25:08, 12161.83 examples/s]
Generating train split: 85705259 examples [1:25:08, 13591.90 examples/s]
Generating train split: 85706974 examples [1:25:08, 7628.92 examples/s] 
Generating train split: 85708285 examples [1:25:08, 8129.42 examples/s]
Generating train split: 85709509 examples [1:25:09, 7395.85 examples/s]
Generating train split: 85710537 examples [1:25:09, 5497.80 examples/s]
Generating train split: 85711347 examples [1:25:09, 3730.09 examples/s]
Generating train split: 85711970 examples [1:25:10, 3973.26 examples/s]
Generating train split: 85713345 examples [1:25:10, 5339.35 examples/s]
Generating train split: 85714176 examples [1:25:10, 5216.07 examples/s]
Generating train split: 85714903 examples [1:25:10, 4349.58 examples/s]
Generating train split: 85715505 examples [1:25:10, 4611.89 examples/s]
Generating train split: 85716742 examples [1:25:10, 6072.27 examples/s]
Generating train split: 85717729 examples [1:25:10, 6861.11 examples/s]
Generating train split: 85718574 examples [1:25:11, 4509.31 examples/s]
Generating train split: 85720427 examples [1:25:11, 6884.10 examples/s]
Generating train split: 85722707 examples [1:25:11, 9979.75 examples/s]
Generating train split: 85724089 examples [1:25:11, 10591.57 examples/s]
Generating train split: 85725441 examples [1:25:11, 6073.32 examples/s] 
Generating train split: 85733461 examples [1:25:12, 17382.67 examples/s]
Generating train split: 85741851 examples [1:25:12, 29285.24 examples/s]
Generating train split: 85746556 examples [1:25:12, 19695.09 examples/s]
Generating train split: 85750184 examples [1:25:13, 9929.40 examples/s] 
Generating train split: 85752836 examples [1:25:14, 7631.45 examples/s]
Generating train split: 85754819 examples [1:25:14, 7346.66 examples/s]
Generating train split: 85756390 examples [1:25:14, 7756.86 examples/s]
Generating train split: 85757817 examples [1:25:15, 6787.86 examples/s]
Generating train split: 85758950 examples [1:25:15, 5747.21 examples/s]
Generating train split: 85759843 examples [1:25:15, 5278.11 examples/s]
Generating train split: 85761588 examples [1:25:15, 6675.58 examples/s]
Generating train split: 85762607 examples [1:25:16, 4190.67 examples/s]
Generating train split: 85763372 examples [1:25:16, 4297.01 examples/s]
Generating train split: 85764054 examples [1:25:16, 3919.93 examples/s]
Generating train split: 85764628 examples [1:25:16, 3671.23 examples/s]
Generating train split: 85765977 examples [1:25:16, 5071.24 examples/s]
Generating train split: 85766970 examples [1:25:17, 5820.47 examples/s]
Generating train split: 85767941 examples [1:25:17, 6557.74 examples/s]
Generating train split: 85770209 examples [1:25:17, 10007.79 examples/s]
Generating train split: 85771471 examples [1:25:17, 9298.55 examples/s] 
Generating train split: 85775001 examples [1:25:17, 15203.04 examples/s]
Generating train split: 85783521 examples [1:25:17, 32351.61 examples/s]
Generating train split: 85789701 examples [1:25:17, 39971.33 examples/s]
Generating train split: 85794250 examples [1:25:18, 14993.71 examples/s]
Generating train split: 85797617 examples [1:25:18, 13893.98 examples/s]
Generating train split: 85800322 examples [1:25:19, 13728.51 examples/s]
Generating train split: 85803017 examples [1:25:19, 15509.30 examples/s]
Generating train split: 85805430 examples [1:25:19, 15059.80 examples/s]
Generating train split: 85807525 examples [1:25:19, 13594.36 examples/s]
Generating train split: 85809296 examples [1:25:19, 12459.21 examples/s]
Generating train split: 85810833 examples [1:25:19, 11009.56 examples/s]
Generating train split: 85813111 examples [1:25:19, 13008.63 examples/s]
Generating train split: 85814691 examples [1:25:20, 10024.92 examples/s]
Generating train split: 85815968 examples [1:25:20, 9693.00 examples/s] 
Generating train split: 85817976 examples [1:25:20, 11629.59 examples/s]
Generating train split: 85826630 examples [1:25:20, 27395.28 examples/s]
Generating train split: 85835512 examples [1:25:20, 40722.60 examples/s]
Generating train split: 85840465 examples [1:25:21, 25830.08 examples/s]
Generating train split: 85844331 examples [1:25:21, 21780.12 examples/s]
Generating train split: 85847583 examples [1:25:21, 23339.73 examples/s]
Generating train split: 85850717 examples [1:25:22, 13717.29 examples/s]
Generating train split: 85853091 examples [1:25:22, 10325.75 examples/s]
Generating train split: 85854912 examples [1:25:22, 9576.34 examples/s] 
Generating train split: 85856766 examples [1:25:22, 10644.77 examples/s]
Generating train split: 85858361 examples [1:25:23, 8927.23 examples/s] 
Generating train split: 85859643 examples [1:25:23, 8095.73 examples/s]
Generating train split: 85865008 examples [1:25:23, 14764.61 examples/s]
Generating train split: 85873383 examples [1:25:23, 26693.40 examples/s]
Generating train split: 85880296 examples [1:25:23, 35095.95 examples/s]
Generating train split: 85885289 examples [1:25:24, 15334.57 examples/s]
Generating train split: 85888980 examples [1:25:24, 11617.01 examples/s]
Generating train split: 85891759 examples [1:25:25, 10828.07 examples/s]
Generating train split: 85893961 examples [1:25:25, 11294.46 examples/s]
Generating train split: 85902996 examples [1:25:25, 20714.84 examples/s]
Generating train split: 85910615 examples [1:25:25, 28305.52 examples/s]
Generating train split: 85915520 examples [1:25:26, 21534.52 examples/s]
Generating train split: 85919345 examples [1:25:26, 17099.61 examples/s]
Generating train split: 85922326 examples [1:25:26, 13423.54 examples/s]
Generating train split: 85924628 examples [1:25:26, 13965.89 examples/s]
Generating train split: 85926750 examples [1:25:27, 13904.38 examples/s]
Generating train split: 85928648 examples [1:25:27, 11271.52 examples/s]
Generating train split: 85930319 examples [1:25:27, 12042.43 examples/s]
Generating train split: 85931890 examples [1:25:27, 9307.32 examples/s] 
Generating train split: 85938951 examples [1:25:27, 18594.12 examples/s]
Generating train split: 85946446 examples [1:25:28, 28615.22 examples/s]
Generating train split: 85950788 examples [1:25:28, 21088.98 examples/s]
Generating train split: 85954207 examples [1:25:28, 12873.16 examples/s]
Generating train split: 85956776 examples [1:25:29, 9982.29 examples/s] 
Generating train split: 85958734 examples [1:25:30, 7327.62 examples/s]
Generating train split: 85960211 examples [1:25:30, 7740.69 examples/s]
Generating train split: 85961564 examples [1:25:30, 6998.03 examples/s]
Generating train split: 85962657 examples [1:25:30, 6260.25 examples/s]
Generating train split: 85963956 examples [1:25:30, 7057.86 examples/s]
Generating train split: 85964967 examples [1:25:31, 6455.00 examples/s]
Generating train split: 85965815 examples [1:25:31, 5597.56 examples/s]
Generating train split: 85967539 examples [1:25:31, 7382.50 examples/s]
Generating train split: 85968548 examples [1:25:31, 4380.02 examples/s]
Generating train split: 85969309 examples [1:25:32, 3369.52 examples/s]
Generating train split: 85969910 examples [1:25:32, 3608.30 examples/s]
Generating train split: 85970487 examples [1:25:32, 3007.34 examples/s]
Generating train split: 85970948 examples [1:25:32, 3215.22 examples/s]
Generating train split: 85971405 examples [1:25:33, 3369.48 examples/s]
Generating train split: 85972213 examples [1:25:33, 4187.78 examples/s]
Generating train split: 85972756 examples [1:25:33, 3197.56 examples/s]
Generating train split: 85973373 examples [1:25:33, 3686.60 examples/s]
Generating train split: 85974007 examples [1:25:33, 4201.85 examples/s]
Generating train split: 85975084 examples [1:25:33, 5456.51 examples/s]
Generating train split: 85975735 examples [1:25:33, 4353.82 examples/s]
Generating train split: 85984024 examples [1:25:34, 20251.27 examples/s]
Generating train split: 85991268 examples [1:25:34, 31842.69 examples/s]
Generating train split: 85995415 examples [1:25:34, 22069.14 examples/s]
Generating train split: 85998715 examples [1:25:34, 14947.64 examples/s]
Generating train split: 86006471 examples [1:25:35, 23674.16 examples/s]
Generating train split: 86014834 examples [1:25:35, 33629.58 examples/s]
Generating train split: 86020215 examples [1:25:35, 18491.30 examples/s]
Generating train split: 86024243 examples [1:25:36, 10118.78 examples/s]
Generating train split: 86027175 examples [1:25:37, 6867.77 examples/s] 
Generating train split: 86029323 examples [1:25:38, 6323.91 examples/s]
Generating train split: 86030968 examples [1:25:38, 5864.40 examples/s]
Generating train split: 86032245 examples [1:25:38, 6052.22 examples/s]
Generating train split: 86033359 examples [1:25:38, 6092.27 examples/s]
Generating train split: 86034329 examples [1:25:39, 5788.93 examples/s]
Generating train split: 86035150 examples [1:25:39, 5522.00 examples/s]
Generating train split: 86035955 examples [1:25:39, 5857.15 examples/s]
Generating train split: 86036703 examples [1:25:39, 5742.27 examples/s]
Generating train split: 86038784 examples [1:25:39, 8423.32 examples/s]
Generating train split: 86039884 examples [1:25:39, 7799.14 examples/s]
Generating train split: 86040846 examples [1:25:40, 6070.12 examples/s]
Generating train split: 86042054 examples [1:25:40, 7069.86 examples/s]
Generating train split: 86042944 examples [1:25:40, 6376.76 examples/s]
Generating train split: 86043720 examples [1:25:40, 4667.11 examples/s]
Generating train split: 86044333 examples [1:25:40, 4150.47 examples/s]
Generating train split: 86046498 examples [1:25:41, 7052.62 examples/s]
Generating train split: 86047512 examples [1:25:41, 6217.03 examples/s]
Generating train split: 86051397 examples [1:25:41, 12157.48 examples/s]
Generating train split: 86059760 examples [1:25:41, 26907.05 examples/s]
Generating train split: 86067104 examples [1:25:41, 37124.57 examples/s]
Generating train split: 86071831 examples [1:25:41, 27467.04 examples/s]
Generating train split: 86075650 examples [1:25:42, 14965.72 examples/s]
Generating train split: 86078512 examples [1:25:43, 10898.99 examples/s]
Generating train split: 86080681 examples [1:25:43, 10121.64 examples/s]
Generating train split: 86089010 examples [1:25:43, 18218.03 examples/s]
Generating train split: 86097850 examples [1:25:43, 27792.45 examples/s]
Generating train split: 86103115 examples [1:25:44, 15436.68 examples/s]
Generating train split: 86107007 examples [1:25:44, 12070.18 examples/s]
Generating train split: 86109933 examples [1:25:45, 7375.94 examples/s] 
Generating train split: 86112068 examples [1:25:46, 7227.64 examples/s]
Generating train split: 86113772 examples [1:25:46, 6230.51 examples/s]
Generating train split: 86115182 examples [1:25:46, 6836.82 examples/s]
Generating train split: 86116521 examples [1:25:47, 5874.74 examples/s]
Generating train split: 86117688 examples [1:25:47, 6453.62 examples/s]
Generating train split: 86118778 examples [1:25:47, 6844.72 examples/s]
Generating train split: 86119817 examples [1:25:47, 5357.15 examples/s]
Generating train split: 86121673 examples [1:25:47, 7114.87 examples/s]
Generating train split: 86123911 examples [1:25:47, 9549.80 examples/s]
Generating train split: 86125371 examples [1:25:48, 6642.84 examples/s]
Generating train split: 86126809 examples [1:25:48, 7757.46 examples/s]
Generating train split: 86134267 examples [1:25:48, 19157.80 examples/s]
Generating train split: 86141688 examples [1:25:48, 29487.93 examples/s]
Generating train split: 86145925 examples [1:25:48, 26983.70 examples/s]
Generating train split: 86149549 examples [1:25:49, 14597.96 examples/s]
Generating train split: 86152276 examples [1:25:49, 10795.14 examples/s]
Generating train split: 86154355 examples [1:25:50, 9633.19 examples/s] 
Generating train split: 86156019 examples [1:25:50, 9879.52 examples/s]
Generating train split: 86157695 examples [1:25:50, 10753.27 examples/s]
Generating train split: 86159337 examples [1:25:50, 11468.87 examples/s]
Generating train split: 86160864 examples [1:25:50, 10352.69 examples/s]
Generating train split: 86162165 examples [1:25:51, 8097.94 examples/s] 
Generating train split: 86164272 examples [1:25:51, 10184.70 examples/s]
Generating train split: 86165637 examples [1:25:51, 10308.33 examples/s]
Generating train split: 86167436 examples [1:25:51, 11832.12 examples/s]
Generating train split: 86168859 examples [1:25:51, 11475.11 examples/s]
Generating train split: 86170174 examples [1:25:51, 10752.35 examples/s]
Generating train split: 86171671 examples [1:25:51, 11690.43 examples/s]
Generating train split: 86174100 examples [1:25:51, 14785.88 examples/s]
Generating train split: 86182090 examples [1:25:51, 31711.46 examples/s]
Generating train split: 86188255 examples [1:25:52, 39799.30 examples/s]
Generating train split: 86192579 examples [1:25:52, 19684.51 examples/s]
Generating train split: 86195871 examples [1:25:53, 12504.50 examples/s]
Generating train split: 86198356 examples [1:25:53, 11226.21 examples/s]
Generating train split: 86200339 examples [1:25:53, 10537.60 examples/s]
Generating train split: 86201983 examples [1:25:53, 10743.85 examples/s]
Generating train split: 86203484 examples [1:25:53, 10799.23 examples/s]
Generating train split: 86204870 examples [1:25:54, 11090.96 examples/s]
Generating train split: 86206209 examples [1:25:54, 11265.73 examples/s]
Generating train split: 86207518 examples [1:25:54, 9834.17 examples/s] 
Generating train split: 86209322 examples [1:25:54, 11100.35 examples/s]
Generating train split: 86210566 examples [1:25:54, 10959.11 examples/s]
Generating train split: 86218763 examples [1:25:54, 27297.12 examples/s]
Generating train split: 86227979 examples [1:25:54, 43332.28 examples/s]
Generating train split: 86233050 examples [1:25:55, 24592.67 examples/s]
Generating train split: 86236965 examples [1:25:55, 17552.87 examples/s]
Generating train split: 86239980 examples [1:25:55, 14873.39 examples/s]
Generating train split: 86242376 examples [1:25:56, 10680.60 examples/s]
Generating train split: 86244209 examples [1:25:56, 10344.77 examples/s]
Generating train split: 86245760 examples [1:25:56, 10582.56 examples/s]
Generating train split: 86247200 examples [1:25:56, 10025.94 examples/s]
Generating train split: 86254277 examples [1:25:57, 19583.57 examples/s]
Generating train split: 86263121 examples [1:25:57, 32215.73 examples/s]
Generating train split: 86267877 examples [1:25:57, 16877.58 examples/s]
Generating train split: 86271433 examples [1:25:58, 9613.79 examples/s] 
Generating train split: 86274043 examples [1:25:59, 7681.28 examples/s]
Generating train split: 86275992 examples [1:25:59, 6430.32 examples/s]
Generating train split: 86278499 examples [1:25:59, 7814.55 examples/s]
Generating train split: 86280276 examples [1:26:00, 8573.20 examples/s]
Generating train split: 86281945 examples [1:26:00, 9461.39 examples/s]
Generating train split: 86283594 examples [1:26:00, 8011.11 examples/s]
Generating train split: 86284905 examples [1:26:00, 8067.97 examples/s]
Generating train split: 86286072 examples [1:26:00, 8531.03 examples/s]
Generating train split: 86287222 examples [1:26:00, 7835.48 examples/s]
Generating train split: 86294510 examples [1:26:01, 19531.19 examples/s]
Generating train split: 86303159 examples [1:26:01, 33209.18 examples/s]
Generating train split: 86307766 examples [1:26:01, 22971.72 examples/s]
Generating train split: 86311390 examples [1:26:01, 21526.33 examples/s]
Generating train split: 86320570 examples [1:26:01, 33601.48 examples/s]
Generating train split: 86325474 examples [1:26:01, 34252.34 examples/s]
Generating train split: 86330006 examples [1:26:02, 15740.68 examples/s]
Generating train split: 86333356 examples [1:26:03, 10128.38 examples/s]
Generating train split: 86335846 examples [1:26:03, 10349.77 examples/s]
Generating train split: 86337925 examples [1:26:03, 10949.18 examples/s]
Generating train split: 86339826 examples [1:26:04, 8528.82 examples/s] 
Generating train split: 86341296 examples [1:26:04, 8803.52 examples/s]
Generating train split: 86342633 examples [1:26:04, 6926.32 examples/s]
Generating train split: 86343675 examples [1:26:04, 7078.32 examples/s]
Generating train split: 86344652 examples [1:26:04, 7296.76 examples/s]
Generating train split: 86346086 examples [1:26:05, 8406.42 examples/s]
Generating train split: 86347157 examples [1:26:05, 6167.03 examples/s]
Generating train split: 86349797 examples [1:26:05, 9388.15 examples/s]
Generating train split: 86351615 examples [1:26:05, 10894.41 examples/s]
Generating train split: 86353096 examples [1:26:06, 5913.09 examples/s] 
Generating train split: 86354220 examples [1:26:06, 6249.89 examples/s]
Generating train split: 86356135 examples [1:26:06, 8173.80 examples/s]
Generating train split: 86357434 examples [1:26:06, 6331.58 examples/s]
Generating train split: 86358466 examples [1:26:07, 5279.79 examples/s]
Generating train split: 86359280 examples [1:26:07, 4880.84 examples/s]
Generating train split: 86360157 examples [1:26:07, 5382.26 examples/s]
Generating train split: 86360874 examples [1:26:07, 4245.00 examples/s]
Generating train split: 86361448 examples [1:26:07, 4237.97 examples/s]
Generating train split: 86361986 examples [1:26:08, 2998.06 examples/s]
Generating train split: 86362837 examples [1:26:08, 3785.84 examples/s]
Generating train split: 86365000 examples [1:26:08, 6812.63 examples/s]
Generating train split: 86366040 examples [1:26:08, 4716.84 examples/s]
Generating train split: 86366841 examples [1:26:08, 4757.00 examples/s]
Generating train split: 86367556 examples [1:26:09, 4234.73 examples/s]
Generating train split: 86368160 examples [1:26:09, 4477.35 examples/s]
Generating train split: 86368752 examples [1:26:09, 4610.56 examples/s]
Generating train split: 86369316 examples [1:26:09, 4708.19 examples/s]
Generating train split: 86371587 examples [1:26:09, 8699.34 examples/s]
Generating train split: 86372656 examples [1:26:09, 7941.97 examples/s]
Generating train split: 86373599 examples [1:26:10, 4437.53 examples/s]
Generating train split: 86374327 examples [1:26:10, 3998.94 examples/s]
Generating train split: 86375059 examples [1:26:10, 4429.93 examples/s]
Generating train split: 86375682 examples [1:26:10, 4064.27 examples/s]
Generating train split: 86384006 examples [1:26:10, 17940.52 examples/s]
Generating train split: 86391948 examples [1:26:11, 30245.47 examples/s]
Generating train split: 86396334 examples [1:26:11, 19495.94 examples/s]
Generating train split: 86399732 examples [1:26:12, 12043.29 examples/s]
Generating train split: 86402267 examples [1:26:12, 11630.28 examples/s]
Generating train split: 86404358 examples [1:26:12, 9552.27 examples/s] 
Generating train split: 86405986 examples [1:26:12, 10075.35 examples/s]
Generating train split: 86408420 examples [1:26:12, 12000.17 examples/s]
Generating train split: 86410230 examples [1:26:13, 9787.27 examples/s] 
Generating train split: 86411669 examples [1:26:13, 9272.85 examples/s]
Generating train split: 86413765 examples [1:26:13, 11115.10 examples/s]
Generating train split: 86415268 examples [1:26:14, 6389.53 examples/s] 
Generating train split: 86416394 examples [1:26:14, 4963.11 examples/s]
Generating train split: 86417662 examples [1:26:14, 5827.72 examples/s]
Generating train split: 86418653 examples [1:26:15, 4397.08 examples/s]
Generating train split: 86420455 examples [1:26:15, 6004.17 examples/s]
Generating train split: 86423288 examples [1:26:15, 9249.46 examples/s]
Generating train split: 86431780 examples [1:26:15, 22258.83 examples/s]
Generating train split: 86440838 examples [1:26:15, 35728.32 examples/s]
Generating train split: 86446122 examples [1:26:16, 13136.08 examples/s]
Generating train split: 86449978 examples [1:26:16, 11846.12 examples/s]
Generating train split: 86458611 examples [1:26:16, 18798.44 examples/s]
Generating train split: 86466387 examples [1:26:17, 25696.20 examples/s]
Generating train split: 86471961 examples [1:26:17, 13798.56 examples/s]
Generating train split: 86476042 examples [1:26:18, 12178.64 examples/s]
Generating train split: 86479168 examples [1:26:19, 9216.53 examples/s] 
Generating train split: 86481490 examples [1:26:19, 7698.01 examples/s]
Generating train split: 86483250 examples [1:26:19, 8396.79 examples/s]
Generating train split: 86484974 examples [1:26:20, 6751.40 examples/s]
Generating train split: 86486297 examples [1:26:20, 6567.74 examples/s]
Generating train split: 86487389 examples [1:26:20, 6571.53 examples/s]
Generating train split: 86488351 examples [1:26:20, 6443.53 examples/s]
Generating train split: 86490505 examples [1:26:20, 8520.60 examples/s]
Generating train split: 86491747 examples [1:26:21, 8669.28 examples/s]
Generating train split: 86492887 examples [1:26:21, 8839.86 examples/s]
Generating train split: 86493970 examples [1:26:21, 9192.07 examples/s]
Generating train split: 86495304 examples [1:26:21, 9996.55 examples/s]
Generating train split: 86496441 examples [1:26:21, 5434.06 examples/s]
Generating train split: 86498240 examples [1:26:21, 7328.03 examples/s]
Generating train split: 86499426 examples [1:26:22, 8123.87 examples/s]
Generating train split: 86500588 examples [1:26:22, 8213.18 examples/s]
Generating train split: 86501653 examples [1:26:22, 5860.85 examples/s]
Generating train split: 86502495 examples [1:26:22, 4464.23 examples/s]
Generating train split: 86503166 examples [1:26:23, 4531.87 examples/s]
Generating train split: 86510435 examples [1:26:23, 15775.84 examples/s]
Generating train split: 86519161 examples [1:26:23, 29217.36 examples/s]
Generating train split: 86523515 examples [1:26:23, 22505.43 examples/s]
Generating train split: 86527004 examples [1:26:23, 23381.96 examples/s]
Generating train split: 86530237 examples [1:26:24, 14462.04 examples/s]
Generating train split: 86532903 examples [1:26:24, 16111.04 examples/s]
Generating train split: 86535424 examples [1:26:24, 14903.11 examples/s]
Generating train split: 86537823 examples [1:26:24, 16397.55 examples/s]
Generating train split: 86546554 examples [1:26:24, 29895.64 examples/s]
Generating train split: 86553612 examples [1:26:24, 38584.37 examples/s]
Generating train split: 86558657 examples [1:26:25, 20491.38 examples/s]
Generating train split: 86562464 examples [1:26:25, 13471.97 examples/s]
Generating train split: 86565318 examples [1:26:26, 13502.67 examples/s]
Generating train split: 86567734 examples [1:26:26, 11138.61 examples/s]
Generating train split: 86569617 examples [1:26:26, 10202.33 examples/s]
Generating train split: 86571163 examples [1:26:26, 10227.86 examples/s]
Generating train split: 86572549 examples [1:26:27, 6367.10 examples/s] 
Generating train split: 86573593 examples [1:26:27, 5522.19 examples/s]
Generating train split: 86574421 examples [1:26:27, 5374.68 examples/s]
Generating train split: 86575299 examples [1:26:28, 5745.00 examples/s]
Generating train split: 86576056 examples [1:26:28, 4787.52 examples/s]
Generating train split: 86577014 examples [1:26:28, 5474.32 examples/s]
Generating train split: 86577726 examples [1:26:28, 3311.73 examples/s]
Generating train split: 86578306 examples [1:26:29, 3617.01 examples/s]
Generating train split: 86578864 examples [1:26:29, 3341.48 examples/s]
Generating train split: 86580188 examples [1:26:29, 4879.01 examples/s]
Generating train split: 86580957 examples [1:26:29, 5374.80 examples/s]
Generating train split: 86581690 examples [1:26:29, 5593.74 examples/s]
Generating train split: 86582394 examples [1:26:29, 3801.31 examples/s]
Generating train split: 86583080 examples [1:26:30, 4301.09 examples/s]
Generating train split: 86583669 examples [1:26:30, 3880.33 examples/s]
Generating train split: 86584171 examples [1:26:30, 3122.73 examples/s]
Generating train split: 86585384 examples [1:26:30, 4652.62 examples/s]
Generating train split: 86586040 examples [1:26:30, 4969.63 examples/s]
Generating train split: 86587053 examples [1:26:30, 6084.01 examples/s]
Generating train split: 86587817 examples [1:26:30, 5899.72 examples/s]
Generating train split: 86588508 examples [1:26:31, 5839.68 examples/s]
Generating train split: 86589425 examples [1:26:31, 6610.43 examples/s]
Generating train split: 86590244 examples [1:26:31, 6974.99 examples/s]
Generating train split: 86591004 examples [1:26:31, 4602.99 examples/s]
Generating train split: 86592708 examples [1:26:31, 7050.63 examples/s]
Generating train split: 86594101 examples [1:26:31, 8548.83 examples/s]
Generating train split: 86595463 examples [1:26:31, 9669.16 examples/s]
Generating train split: 86596611 examples [1:26:32, 9510.83 examples/s]
Generating train split: 86598478 examples [1:26:32, 11792.23 examples/s]
Generating train split: 86599789 examples [1:26:32, 11055.60 examples/s]
Generating train split: 86602100 examples [1:26:32, 14144.08 examples/s]
Generating train split: 86603640 examples [1:26:32, 14439.53 examples/s]
Generating train split: 86605848 examples [1:26:32, 16251.99 examples/s]
Generating train split: 86607552 examples [1:26:32, 13575.66 examples/s]
Generating train split: 86609037 examples [1:26:32, 13749.95 examples/s]
Generating train split: 86610512 examples [1:26:32, 13878.79 examples/s]
Generating train split: 86611966 examples [1:26:33, 8859.71 examples/s] 
Generating train split: 86614174 examples [1:26:33, 11418.88 examples/s]
Generating train split: 86616290 examples [1:26:33, 13499.50 examples/s]
Generating train split: 86617958 examples [1:26:33, 13369.44 examples/s]
Generating train split: 86619515 examples [1:26:33, 13586.24 examples/s]
Generating train split: 86621028 examples [1:26:33, 12240.64 examples/s]
Generating train split: 86622380 examples [1:26:34, 12104.32 examples/s]
Generating train split: 86623958 examples [1:26:34, 12944.08 examples/s]
Generating train split: 86625342 examples [1:26:34, 6963.10 examples/s] 
Generating train split: 86627016 examples [1:26:34, 8544.75 examples/s]
Generating train split: 86628257 examples [1:26:34, 7033.65 examples/s]
Generating train split: 86629845 examples [1:26:35, 8540.58 examples/s]
Generating train split: 86631027 examples [1:26:35, 8288.81 examples/s]
Generating train split: 86632616 examples [1:26:35, 9812.54 examples/s]
Generating train split: 86633841 examples [1:26:35, 8176.27 examples/s]
Generating train split: 86634868 examples [1:26:35, 8182.95 examples/s]
Generating train split: 86635920 examples [1:26:35, 8685.08 examples/s]
Generating train split: 86638584 examples [1:26:35, 12701.11 examples/s]
Generating train split: 86640038 examples [1:26:36, 8857.95 examples/s] 
Generating train split: 86641194 examples [1:26:36, 8771.90 examples/s]
Generating train split: 86642260 examples [1:26:36, 8586.51 examples/s]
Generating train split: 86643246 examples [1:26:36, 6335.57 examples/s]
Generating train split: 86644570 examples [1:26:36, 7578.20 examples/s]
Generating train split: 86646069 examples [1:26:36, 9058.02 examples/s]
Generating train split: 86647182 examples [1:26:37, 6901.89 examples/s]
Generating train split: 86648351 examples [1:26:37, 7798.82 examples/s]
Generating train split: 86649335 examples [1:26:37, 7785.97 examples/s]
Generating train split: 86650264 examples [1:26:37, 4785.48 examples/s]
Generating train split: 86651449 examples [1:26:37, 5871.72 examples/s]
Generating train split: 86652290 examples [1:26:38, 5994.50 examples/s]
Generating train split: 86653581 examples [1:26:38, 7368.23 examples/s]
Generating train split: 86654623 examples [1:26:38, 8026.21 examples/s]
Generating train split: 86655599 examples [1:26:38, 7442.51 examples/s]
Generating train split: 86656594 examples [1:26:38, 8016.07 examples/s]
Generating train split: 86657496 examples [1:26:38, 7946.28 examples/s]
Generating train split: 86658366 examples [1:26:38, 5716.95 examples/s]
Generating train split: 86659069 examples [1:26:38, 5773.26 examples/s]
Generating train split: 86660194 examples [1:26:39, 6841.53 examples/s]
Generating train split: 86660978 examples [1:26:39, 6693.90 examples/s]
Generating train split: 86661723 examples [1:26:39, 4942.14 examples/s]
Generating train split: 86664476 examples [1:26:39, 9416.66 examples/s]
Generating train split: 86665722 examples [1:26:39, 8924.68 examples/s]
Generating train split: 86666837 examples [1:26:40, 6344.15 examples/s]
Generating train split: 86668177 examples [1:26:40, 7449.62 examples/s]
Generating train split: 86669164 examples [1:26:40, 5503.49 examples/s]
Generating train split: 86670220 examples [1:26:40, 6313.50 examples/s]
Generating train split: 86672437 examples [1:26:40, 9299.52 examples/s]
Generating train split: 86680529 examples [1:26:40, 24483.32 examples/s]
Generating train split: 86688851 examples [1:26:40, 38102.80 examples/s]
Generating train split: 86693657 examples [1:26:41, 24488.42 examples/s]
Generating train split: 86697416 examples [1:26:41, 20051.33 examples/s]
Generating train split: 86700445 examples [1:26:41, 15337.77 examples/s]
Generating train split: 86702819 examples [1:26:42, 11291.53 examples/s]
Generating train split: 86704648 examples [1:26:42, 10882.98 examples/s]
Generating train split: 86706216 examples [1:26:42, 8980.53 examples/s] 
Generating train split: 86707883 examples [1:26:42, 9968.80 examples/s]
Generating train split: 86709251 examples [1:26:43, 10484.82 examples/s]
Generating train split: 86710617 examples [1:26:43, 9620.83 examples/s] 
Generating train split: 86711807 examples [1:26:43, 9043.09 examples/s]
Generating train split: 86712852 examples [1:26:43, 8594.80 examples/s]
Generating train split: 86713801 examples [1:26:43, 7164.33 examples/s]
Generating train split: 86714602 examples [1:26:43, 6612.17 examples/s]
Generating train split: 86716048 examples [1:26:44, 8140.78 examples/s]
Generating train split: 86717454 examples [1:26:44, 9435.72 examples/s]
Generating train split: 86718531 examples [1:26:44, 8555.68 examples/s]
Generating train split: 86719486 examples [1:26:44, 7269.56 examples/s]
Generating train split: 86720882 examples [1:26:44, 8694.43 examples/s]
Generating train split: 86721935 examples [1:26:44, 9109.11 examples/s]
Generating train split: 86722975 examples [1:26:44, 9241.81 examples/s]
Generating train split: 86723976 examples [1:26:45, 6570.06 examples/s]
Generating train split: 86724788 examples [1:26:45, 6775.17 examples/s]
Generating train split: 86725583 examples [1:26:45, 4910.52 examples/s]
Generating train split: 86726900 examples [1:26:45, 6415.82 examples/s]
Generating train split: 86728830 examples [1:26:45, 9075.93 examples/s]
Generating train split: 86729999 examples [1:26:45, 7170.81 examples/s]
Generating train split: 86730956 examples [1:26:46, 6057.84 examples/s]
Generating train split: 86732316 examples [1:26:46, 7402.89 examples/s]
Generating train split: 86733282 examples [1:26:46, 7398.13 examples/s]
Generating train split: 86734181 examples [1:26:46, 5289.47 examples/s]
Generating train split: 86735285 examples [1:26:46, 6286.17 examples/s]
Generating train split: 86736112 examples [1:26:47, 4244.09 examples/s]
Generating train split: 86736756 examples [1:26:47, 4350.57 examples/s]
Generating train split: 86737352 examples [1:26:47, 4417.08 examples/s]
Generating train split: 86737909 examples [1:26:48, 2238.96 examples/s]
Generating train split: 86738324 examples [1:26:49, 1024.84 examples/s]
Generating train split: 86738624 examples [1:26:49, 983.94 examples/s] 
Generating train split: 86738859 examples [1:26:50, 980.27 examples/s]
Generating train split: 86739052 examples [1:26:50, 1027.25 examples/s]
Generating train split: 86739229 examples [1:26:50, 867.99 examples/s] 
Generating train split: 86739369 examples [1:26:50, 883.84 examples/s]
Generating train split: 86739574 examples [1:26:50, 1031.81 examples/s]
Generating train split: 86739724 examples [1:26:51, 777.53 examples/s] 
Generating train split: 86739841 examples [1:26:51, 783.81 examples/s]
Generating train split: 86739948 examples [1:26:51, 790.51 examples/s]
Generating train split: 86740048 examples [1:26:51, 790.21 examples/s]
Generating train split: 86740143 examples [1:26:51, 737.07 examples/s]
Generating train split: 86740257 examples [1:26:51, 798.50 examples/s]
Generating train split: 86740350 examples [1:26:51, 826.80 examples/s]
Generating train split: 86740441 examples [1:26:52, 516.38 examples/s]
Generating train split: 86740553 examples [1:26:52, 619.12 examples/s]
Generating train split: 86740970 examples [1:26:52, 1313.24 examples/s]
Generating train split: 86741401 examples [1:26:52, 1967.32 examples/s]
Generating train split: 86741659 examples [1:26:52, 1841.15 examples/s]
Generating train split: 86741888 examples [1:26:52, 1492.21 examples/s]
Generating train split: 86742077 examples [1:26:53, 1422.37 examples/s]
Generating train split: 86742248 examples [1:26:53, 1345.73 examples/s]
Generating train split: 86742405 examples [1:26:53, 1381.03 examples/s]
Generating train split: 86742559 examples [1:26:53, 1361.98 examples/s]
Generating train split: 86742752 examples [1:26:53, 1490.89 examples/s]
Generating train split: 86743030 examples [1:26:53, 1760.03 examples/s]
Generating train split: 86743217 examples [1:26:53, 1220.93 examples/s]
Generating train split: 86743400 examples [1:26:54, 1332.71 examples/s]
Generating train split: 86743732 examples [1:26:54, 1774.59 examples/s]
Generating train split: 86747804 examples [1:26:54, 11169.22 examples/s]
Generating train split: 86754952 examples [1:26:54, 25836.69 examples/s]
Generating train split: 86757835 examples [1:26:54, 21590.47 examples/s]
Generating train split: 86760307 examples [1:26:54, 15590.24 examples/s]
Generating train split: 86762302 examples [1:26:55, 12973.82 examples/s]
Generating train split: 86763943 examples [1:26:55, 9302.75 examples/s] 
Generating train split: 86765232 examples [1:26:55, 9127.87 examples/s]
Generating train split: 86766385 examples [1:26:55, 9185.04 examples/s]
Generating train split: 86768034 examples [1:26:55, 10522.02 examples/s]
Generating train split: 86769380 examples [1:26:55, 11070.57 examples/s]
Generating train split: 86770667 examples [1:26:56, 8267.63 examples/s] 
Generating train split: 86771709 examples [1:26:56, 5300.09 examples/s]
Generating train split: 86772508 examples [1:26:56, 5363.07 examples/s]
Generating train split: 86774652 examples [1:26:56, 7945.23 examples/s]
Generating train split: 86775807 examples [1:26:57, 6080.24 examples/s]
Generating train split: 86776780 examples [1:26:57, 6534.17 examples/s]
Generating train split: 86777682 examples [1:26:57, 5599.76 examples/s]
Generating train split: 86778933 examples [1:26:57, 6773.08 examples/s]
Generating train split: 86779827 examples [1:26:57, 6451.76 examples/s]
Generating train split: 86780623 examples [1:26:57, 6221.14 examples/s]
Generating train split: 86781350 examples [1:26:58, 6249.91 examples/s]
Generating train split: 86782050 examples [1:26:58, 6016.35 examples/s]
Generating train split: 86782705 examples [1:26:58, 5297.86 examples/s]
Generating train split: 86783981 examples [1:26:58, 6954.67 examples/s]
Generating train split: 86784771 examples [1:26:58, 5624.78 examples/s]
Generating train split: 86785435 examples [1:26:58, 4877.08 examples/s]
Generating train split: 86787227 examples [1:26:58, 7506.12 examples/s]
Generating train split: 86788548 examples [1:26:59, 8648.97 examples/s]
Generating train split: 86789581 examples [1:26:59, 4774.62 examples/s]
Generating train split: 86790372 examples [1:26:59, 5146.34 examples/s]
Generating train split: 86791170 examples [1:26:59, 5615.71 examples/s]
Generating train split: 86791931 examples [1:26:59, 5249.57 examples/s]
Generating train split: 86793554 examples [1:27:00, 7439.99 examples/s]
Generating train split: 86796519 examples [1:27:00, 12362.27 examples/s]
Generating train split: 86798620 examples [1:27:00, 14440.95 examples/s]
Generating train split: 86800338 examples [1:27:00, 10674.88 examples/s]
Generating train split: 86803249 examples [1:27:00, 14450.23 examples/s]
Generating train split: 86805790 examples [1:27:00, 16907.86 examples/s]
Generating train split: 86808954 examples [1:27:00, 20487.79 examples/s]
Generating train split: 86813828 examples [1:27:00, 27779.48 examples/s]
Generating train split: 86819096 examples [1:27:01, 34479.63 examples/s]
Generating train split: 86825931 examples [1:27:01, 43844.59 examples/s]
Generating train split: 86831937 examples [1:27:01, 48437.13 examples/s]
Generating train split: 86838268 examples [1:27:01, 52723.46 examples/s]
Generating train split: 86843849 examples [1:27:01, 53604.74 examples/s]
Generating train split: 86850556 examples [1:27:01, 57013.19 examples/s]
Generating train split: 86856613 examples [1:27:01, 58051.93 examples/s]
Generating train split: 86863530 examples [1:27:01, 61312.18 examples/s]
Generating train split: 86870461 examples [1:27:01, 63676.97 examples/s]
Generating train split: 86877708 examples [1:27:01, 66287.78 examples/s]
Generating train split: 86884614 examples [1:27:02, 67078.03 examples/s]
Generating train split: 86891342 examples [1:27:02, 66182.88 examples/s]
Generating train split: 86899306 examples [1:27:02, 70165.75 examples/s]
Generating train split: 86906343 examples [1:27:02, 68373.18 examples/s]
Generating train split: 86913210 examples [1:27:02, 67207.30 examples/s]
Generating train split: 86919950 examples [1:27:02, 66917.01 examples/s]
Generating train split: 86926665 examples [1:27:02, 66077.05 examples/s]
Generating train split: 86933298 examples [1:27:02, 61774.13 examples/s]
Generating train split: 86940251 examples [1:27:02, 63925.89 examples/s]
Generating train split: 86947389 examples [1:27:02, 66046.92 examples/s]
Generating train split: 86954058 examples [1:27:03, 62272.92 examples/s]
Generating train split: 86960370 examples [1:27:03, 53462.61 examples/s]
Generating train split: 86965960 examples [1:27:03, 43057.33 examples/s]
Generating train split: 86970711 examples [1:27:03, 38034.61 examples/s]
Generating train split: 86974885 examples [1:27:03, 35505.48 examples/s]
Generating train split: 86978678 examples [1:27:03, 34397.82 examples/s]
Generating train split: 86982272 examples [1:27:04, 25787.87 examples/s]
Generating train split: 86985433 examples [1:27:04, 26914.63 examples/s]
Generating train split: 86988975 examples [1:27:04, 28768.90 examples/s]
Generating train split: 86992151 examples [1:27:04, 25331.16 examples/s]
Generating train split: 86994933 examples [1:27:04, 19748.44 examples/s]
Generating train split: 86997239 examples [1:27:04, 19011.16 examples/s]
Generating train split: 86999364 examples [1:27:05, 19144.63 examples/s]
Generating train split: 87001435 examples [1:27:05, 18046.47 examples/s]
Generating train split: 87003350 examples [1:27:05, 10997.44 examples/s]
Generating train split: 87004832 examples [1:27:05, 10269.95 examples/s]
Generating train split: 87007024 examples [1:27:05, 12274.50 examples/s]
Generating train split: 87008580 examples [1:27:05, 11492.31 examples/s]
Generating train split: 87010971 examples [1:27:06, 13945.15 examples/s]
Generating train split: 87012646 examples [1:27:06, 10906.82 examples/s]
Generating train split: 87014016 examples [1:27:06, 9452.01 examples/s] 
Generating train split: 87015178 examples [1:27:06, 6217.71 examples/s]
Generating train split: 87016594 examples [1:27:07, 7281.37 examples/s]
Generating train split: 87017741 examples [1:27:07, 7935.84 examples/s]
Generating train split: 87018799 examples [1:27:07, 8038.02 examples/s]
Generating train split: 87019786 examples [1:27:07, 5757.42 examples/s]
Generating train split: 87020568 examples [1:27:07, 5911.24 examples/s]
Generating train split: 87021321 examples [1:27:07, 6123.62 examples/s]
Generating train split: 87022053 examples [1:27:08, 4140.14 examples/s]
Generating train split: 87022626 examples [1:27:08, 2972.51 examples/s]
Generating train split: 87023074 examples [1:27:08, 3053.81 examples/s]
Generating train split: 87023587 examples [1:27:08, 3375.40 examples/s]
Generating train split: 87024036 examples [1:27:09, 2732.52 examples/s]
Generating train split: 87026282 examples [1:27:09, 6018.86 examples/s]
Generating train split: 87027208 examples [1:27:09, 5276.99 examples/s]
Generating train split: 87027976 examples [1:27:09, 4731.10 examples/s]
Generating train split: 87028967 examples [1:27:09, 5630.52 examples/s]
Generating train split: 87030702 examples [1:27:09, 7913.78 examples/s]
Generating train split: 87031733 examples [1:27:09, 8423.28 examples/s]
Generating train split: 87032760 examples [1:27:10, 7153.83 examples/s]
Generating train split: 87033633 examples [1:27:10, 5901.64 examples/s]
Generating train split: 87034362 examples [1:27:10, 6122.65 examples/s]
Generating train split: 87035082 examples [1:27:10, 3710.90 examples/s]
Generating train split: 87039537 examples [1:27:10, 9968.98 examples/s]
Generating train split: 87047897 examples [1:27:11, 23190.50 examples/s]
Generating train split: 87053275 examples [1:27:11, 29409.16 examples/s]
Generating train split: 87057483 examples [1:27:11, 15280.27 examples/s]
Generating train split: 87060650 examples [1:27:12, 10961.10 examples/s]
Generating train split: 87063046 examples [1:27:12, 8505.19 examples/s] 
Generating train split: 87064854 examples [1:27:13, 6734.48 examples/s]
Generating train split: 87066230 examples [1:27:13, 6685.22 examples/s]
Generating train split: 87068418 examples [1:27:13, 8231.43 examples/s]
Generating train split: 87069882 examples [1:27:13, 7400.44 examples/s]
Generating train split: 87071071 examples [1:27:14, 6739.96 examples/s]
Generating train split: 87073247 examples [1:27:14, 8774.27 examples/s]
Generating train split: 87074581 examples [1:27:14, 8625.34 examples/s]
Generating train split: 87075762 examples [1:27:14, 6604.99 examples/s]
Generating train split: 87076697 examples [1:27:14, 6631.47 examples/s]
Generating train split: 87078170 examples [1:27:15, 7990.54 examples/s]
Generating train split: 87079227 examples [1:27:15, 5376.93 examples/s]
Generating train split: 87080572 examples [1:27:15, 6579.58 examples/s]
Generating train split: 87087006 examples [1:27:15, 16748.16 examples/s]
Generating train split: 87094025 examples [1:27:15, 27483.30 examples/s]
Generating train split: 87098107 examples [1:27:15, 30429.06 examples/s]
Generating train split: 87102076 examples [1:27:16, 21735.47 examples/s]
Generating train split: 87105245 examples [1:27:16, 19420.94 examples/s]
Generating train split: 87107902 examples [1:27:16, 14225.47 examples/s]
Generating train split: 87109995 examples [1:27:16, 13829.32 examples/s]
Generating train split: 87111839 examples [1:27:17, 12215.62 examples/s]
Generating train split: 87113389 examples [1:27:17, 11479.75 examples/s]
Generating train split: 87114746 examples [1:27:17, 10034.14 examples/s]
Generating train split: 87115897 examples [1:27:17, 10145.87 examples/s]
Generating train split: 87123361 examples [1:27:17, 22812.14 examples/s]
Generating train split: 87131215 examples [1:27:17, 34762.26 examples/s]
Generating train split: 87135620 examples [1:27:18, 21532.42 examples/s]
Generating train split: 87139027 examples [1:27:18, 16446.49 examples/s]
Generating train split: 87141694 examples [1:27:18, 15439.42 examples/s]
Generating train split: 87143947 examples [1:27:19, 13559.86 examples/s]
Generating train split: 87145791 examples [1:27:19, 13737.60 examples/s]
Generating train split: 87147518 examples [1:27:19, 11222.93 examples/s]
Generating train split: 87149578 examples [1:27:19, 12643.51 examples/s]
Generating train split: 87151163 examples [1:27:19, 12630.09 examples/s]
Generating train split: 87152649 examples [1:27:19, 9497.38 examples/s] 
Generating train split: 87153853 examples [1:27:20, 9257.73 examples/s]
Generating train split: 87155298 examples [1:27:20, 10210.87 examples/s]
Generating train split: 87157070 examples [1:27:20, 11779.58 examples/s]
Generating train split: 87158446 examples [1:27:20, 9716.25 examples/s] 
Generating train split: 87160463 examples [1:27:20, 11851.33 examples/s]
Generating train split: 87161871 examples [1:27:20, 8052.29 examples/s] 
Generating train split: 87162983 examples [1:27:21, 8177.86 examples/s]
Generating train split: 87164584 examples [1:27:21, 9658.83 examples/s]
Generating train split: 87165786 examples [1:27:21, 9177.22 examples/s]
Generating train split: 87166873 examples [1:27:21, 6843.61 examples/s]
Generating train split: 87168505 examples [1:27:21, 8567.39 examples/s]
Generating train split: 87170382 examples [1:27:21, 10672.15 examples/s]
Generating train split: 87172318 examples [1:27:21, 12621.99 examples/s]
Generating train split: 87173826 examples [1:27:22, 11374.78 examples/s]
Generating train split: 87175159 examples [1:27:22, 11591.08 examples/s]
Generating train split: 87176457 examples [1:27:22, 10898.29 examples/s]
Generating train split: 87178192 examples [1:27:22, 12443.88 examples/s]
Generating train split: 87179551 examples [1:27:22, 8218.89 examples/s] 
Generating train split: 87180642 examples [1:27:22, 7420.31 examples/s]
Generating train split: 87181579 examples [1:27:23, 6702.43 examples/s]
Generating train split: 87182379 examples [1:27:23, 5844.24 examples/s]
Generating train split: 87183070 examples [1:27:23, 5669.75 examples/s]
Generating train split: 87183704 examples [1:27:23, 4944.11 examples/s]
Generating train split: 87184253 examples [1:27:23, 4604.29 examples/s]
Generating train split: 87185394 examples [1:27:23, 5938.39 examples/s]
Generating train split: 87186156 examples [1:27:23, 6167.24 examples/s]
Generating train split: 87186838 examples [1:27:24, 5086.06 examples/s]
Generating train split: 87188592 examples [1:27:24, 7725.60 examples/s]
Generating train split: 87190620 examples [1:27:24, 10646.06 examples/s]
Generating train split: 87191882 examples [1:27:24, 6520.18 examples/s] 
Generating train split: 87192866 examples [1:27:25, 5276.05 examples/s]
Generating train split: 87194234 examples [1:27:25, 6553.71 examples/s]
Generating train split: 87195183 examples [1:27:25, 4957.84 examples/s]
Generating train split: 87195934 examples [1:27:25, 4602.82 examples/s]
Generating train split: 87197794 examples [1:27:25, 6773.36 examples/s]
Generating train split: 87198787 examples [1:27:26, 6167.24 examples/s]
Generating train split: 87199690 examples [1:27:26, 6668.75 examples/s]
Generating train split: 87200548 examples [1:27:26, 5981.67 examples/s]
Generating train split: 87202142 examples [1:27:26, 7892.18 examples/s]
Generating train split: 87203123 examples [1:27:26, 6715.43 examples/s]
Generating train split: 87203945 examples [1:27:26, 6167.40 examples/s]
Generating train split: 87205668 examples [1:27:26, 8391.58 examples/s]
Generating train split: 87206810 examples [1:27:26, 8784.78 examples/s]
Generating train split: 87207822 examples [1:27:27, 6642.20 examples/s]
Generating train split: 87208667 examples [1:27:27, 6734.81 examples/s]
Generating train split: 87210711 examples [1:27:27, 9613.93 examples/s]
Generating train split: 87212574 examples [1:27:27, 11710.07 examples/s]
Generating train split: 87213947 examples [1:27:27, 7095.56 examples/s] 
Generating train split: 87215008 examples [1:27:28, 7689.73 examples/s]
Generating train split: 87216073 examples [1:27:28, 7292.20 examples/s]
Generating train split: 87217004 examples [1:27:28, 4290.75 examples/s]
Generating train split: 87218279 examples [1:27:28, 5400.79 examples/s]
Generating train split: 87219135 examples [1:27:29, 4543.59 examples/s]
Generating train split: 87219961 examples [1:27:29, 5091.54 examples/s]
Generating train split: 87220692 examples [1:27:29, 4561.51 examples/s]
Generating train split: 87221315 examples [1:27:29, 4089.87 examples/s]
Generating train split: 87221834 examples [1:27:30, 2812.38 examples/s]
Generating train split: 87222311 examples [1:27:30, 3077.99 examples/s]
Generating train split: 87223031 examples [1:27:30, 3761.34 examples/s]
Generating train split: 87223545 examples [1:27:30, 3841.31 examples/s]
Generating train split: 87225330 examples [1:27:30, 6729.59 examples/s]
Generating train split: 87226216 examples [1:27:30, 5535.05 examples/s]
Generating train split: 87226944 examples [1:27:30, 5626.93 examples/s]
Generating train split: 87227636 examples [1:27:31, 4146.06 examples/s]
Generating train split: 87228264 examples [1:27:31, 4444.51 examples/s]
Generating train split: 87228825 examples [1:27:31, 4348.81 examples/s]
Generating train split: 87229849 examples [1:27:31, 5135.35 examples/s]
Generating train split: 87231128 examples [1:27:31, 6779.91 examples/s]
Generating train split: 87231998 examples [1:27:31, 6985.53 examples/s]
Generating train split: 87232788 examples [1:27:32, 4599.65 examples/s]
Generating train split: 87233687 examples [1:27:32, 5393.41 examples/s]
Generating train split: 87234389 examples [1:27:32, 4386.45 examples/s]
Generating train split: 87234987 examples [1:27:32, 4675.00 examples/s]
Generating train split: 87241563 examples [1:27:32, 17397.67 examples/s]
Generating train split: 87249980 examples [1:27:32, 32708.26 examples/s]
Generating train split: 87254183 examples [1:27:33, 23799.13 examples/s]
Generating train split: 87257552 examples [1:27:33, 10774.95 examples/s]
Generating train split: 87260040 examples [1:27:34, 9852.33 examples/s] 
Generating train split: 87268908 examples [1:27:34, 18252.08 examples/s]
Generating train split: 87277201 examples [1:27:34, 26685.45 examples/s]
Generating train split: 87282438 examples [1:27:34, 19196.51 examples/s]
Generating train split: 87286429 examples [1:27:35, 10408.73 examples/s]
Generating train split: 87289351 examples [1:27:36, 8424.52 examples/s] 
Generating train split: 87297651 examples [1:27:36, 13882.53 examples/s]
Generating train split: 87306522 examples [1:27:36, 20964.16 examples/s]
Generating train split: 87311995 examples [1:27:37, 18476.35 examples/s]
Generating train split: 87316247 examples [1:27:37, 13432.14 examples/s]
Generating train split: 87319435 examples [1:27:38, 11552.04 examples/s]
Generating train split: 87322405 examples [1:27:38, 13167.67 examples/s]
Generating train split: 87324978 examples [1:27:38, 13541.40 examples/s]
Generating train split: 87327238 examples [1:27:38, 9788.69 examples/s] 
Generating train split: 87328973 examples [1:27:39, 10013.59 examples/s]
Generating train split: 87330887 examples [1:27:39, 11196.03 examples/s]
Generating train split: 87332539 examples [1:27:39, 8774.22 examples/s] 
Generating train split: 87340599 examples [1:27:39, 18864.68 examples/s]
Generating train split: 87348381 examples [1:27:39, 28192.59 examples/s]
Generating train split: 87352823 examples [1:27:39, 22755.29 examples/s]
Generating train split: 87356379 examples [1:27:41, 9624.27 examples/s] 
Generating train split: 87358972 examples [1:27:41, 10353.34 examples/s]
Generating train split: 87361238 examples [1:27:41, 11479.58 examples/s]
Generating train split: 87363438 examples [1:27:41, 11796.08 examples/s]
Generating train split: 87365382 examples [1:27:41, 11927.88 examples/s]
Generating train split: 87367675 examples [1:27:41, 13655.01 examples/s]
Generating train split: 87369581 examples [1:27:41, 14092.67 examples/s]
Generating train split: 87371385 examples [1:27:42, 12117.23 examples/s]
Generating train split: 87372905 examples [1:27:42, 10979.37 examples/s]
Generating train split: 87374335 examples [1:27:42, 11597.98 examples/s]
Generating train split: 87376306 examples [1:27:42, 13317.41 examples/s]
Generating train split: 87377849 examples [1:27:42, 13450.44 examples/s]
Generating train split: 87379336 examples [1:27:42, 8359.28 examples/s] 
Generating train split: 87380507 examples [1:27:43, 6001.81 examples/s]
Generating train split: 87381756 examples [1:27:43, 6771.31 examples/s]
Generating train split: 87383889 examples [1:27:43, 9200.64 examples/s]
Generating train split: 87392126 examples [1:27:43, 23286.38 examples/s]
Generating train split: 87399831 examples [1:27:43, 34842.77 examples/s]
Generating train split: 87404528 examples [1:27:44, 24059.31 examples/s]
Generating train split: 87408214 examples [1:27:44, 14608.48 examples/s]
Generating train split: 87410993 examples [1:27:44, 15185.40 examples/s]
Generating train split: 87413482 examples [1:27:44, 14149.48 examples/s]
Generating train split: 87415569 examples [1:27:45, 10894.99 examples/s]
Generating train split: 87421290 examples [1:27:45, 16974.13 examples/s]
Generating train split: 87429743 examples [1:27:45, 27641.41 examples/s]
Generating train split: 87434284 examples [1:27:45, 26681.60 examples/s]
Generating train split: 87438195 examples [1:27:46, 12805.26 examples/s]
Generating train split: 87441081 examples [1:27:46, 10955.09 examples/s]
Generating train split: 87448963 examples [1:27:47, 17841.40 examples/s]
Generating train split: 87457168 examples [1:27:47, 25968.70 examples/s]
Generating train split: 87462385 examples [1:27:47, 14358.83 examples/s]
Generating train split: 87466223 examples [1:27:48, 10699.08 examples/s]
Generating train split: 87469077 examples [1:27:48, 11962.17 examples/s]
Generating train split: 87471808 examples [1:27:49, 10635.80 examples/s]
Generating train split: 87473947 examples [1:27:49, 9836.90 examples/s] 
Generating train split: 87475673 examples [1:27:49, 8167.99 examples/s]
Generating train split: 87477078 examples [1:27:49, 8778.78 examples/s]
Generating train split: 87478431 examples [1:27:50, 8330.77 examples/s]
Generating train split: 87486350 examples [1:27:50, 18484.42 examples/s]
Generating train split: 87493346 examples [1:27:50, 26765.21 examples/s]
Generating train split: 87497481 examples [1:27:50, 24250.47 examples/s]
Generating train split: 87500956 examples [1:27:50, 15262.49 examples/s]
Generating train split: 87503610 examples [1:27:51, 13743.62 examples/s]
Generating train split: 87505762 examples [1:27:51, 10325.09 examples/s]
Generating train split: 87507431 examples [1:27:51, 9462.96 examples/s] 
Generating train split: 87508797 examples [1:27:52, 7897.82 examples/s]
Generating train split: 87509892 examples [1:27:52, 8147.74 examples/s]
Generating train split: 87510949 examples [1:27:52, 6681.18 examples/s]
Generating train split: 87511807 examples [1:27:52, 6145.29 examples/s]
Generating train split: 87513126 examples [1:27:52, 7170.25 examples/s]
Generating train split: 87514022 examples [1:27:53, 4636.17 examples/s]
Generating train split: 87515446 examples [1:27:53, 5930.42 examples/s]
Generating train split: 87516981 examples [1:27:53, 7001.93 examples/s]
Generating train split: 87517937 examples [1:27:53, 5061.74 examples/s]
Generating train split: 87518691 examples [1:27:54, 4638.25 examples/s]
Generating train split: 87520193 examples [1:27:54, 6185.63 examples/s]
Generating train split: 87521068 examples [1:27:54, 5397.98 examples/s]
Generating train split: 87521799 examples [1:27:54, 4493.52 examples/s]
Generating train split: 87522946 examples [1:27:54, 5573.58 examples/s]
Generating train split: 87523690 examples [1:27:55, 4530.09 examples/s]
Generating train split: 87524465 examples [1:27:55, 5071.53 examples/s]
Generating train split: 87525125 examples [1:27:55, 5312.65 examples/s]
Generating train split: 87526966 examples [1:27:55, 8003.93 examples/s]
Generating train split: 87527936 examples [1:27:55, 7345.76 examples/s]
Generating train split: 87528794 examples [1:27:55, 7273.71 examples/s]
Generating train split: 87529610 examples [1:27:56, 4177.44 examples/s]
Generating train split: 87530236 examples [1:27:56, 3660.48 examples/s]
Generating train split: 87532001 examples [1:27:56, 5795.98 examples/s]
Generating train split: 87532971 examples [1:27:56, 6487.81 examples/s]
Generating train split: 87533876 examples [1:27:56, 5949.97 examples/s]
Generating train split: 87534660 examples [1:27:56, 5624.50 examples/s]
Generating train split: 87535355 examples [1:27:57, 5778.28 examples/s]
Generating train split: 87536026 examples [1:27:57, 4455.99 examples/s]
Generating train split: 87537032 examples [1:27:57, 5352.71 examples/s]
Generating train split: 87537680 examples [1:27:57, 3566.72 examples/s]
Generating train split: 87540120 examples [1:27:57, 6888.62 examples/s]
Generating train split: 87541205 examples [1:27:58, 6076.08 examples/s]
Generating train split: 87545482 examples [1:27:58, 12475.05 examples/s]
Generating train split: 87553664 examples [1:27:58, 26305.54 examples/s]
Generating train split: 87559658 examples [1:27:58, 33719.63 examples/s]
Generating train split: 87564112 examples [1:27:58, 18912.75 examples/s]
Generating train split: 87567513 examples [1:27:59, 15543.11 examples/s]
Generating train split: 87570194 examples [1:28:00, 7496.69 examples/s] 
Generating train split: 87572143 examples [1:28:00, 6040.36 examples/s]
Generating train split: 87573609 examples [1:28:01, 6681.70 examples/s]
Generating train split: 87575071 examples [1:28:01, 6562.17 examples/s]
Generating train split: 87576281 examples [1:28:01, 6247.15 examples/s]
Generating train split: 87577284 examples [1:28:01, 6251.86 examples/s]
Generating train split: 87578173 examples [1:28:01, 6521.25 examples/s]
Generating train split: 87579042 examples [1:28:01, 6768.14 examples/s]
Generating train split: 87580057 examples [1:28:01, 7393.17 examples/s]
Generating train split: 87581947 examples [1:28:02, 9796.81 examples/s]
Generating train split: 87583143 examples [1:28:02, 6136.47 examples/s]
Generating train split: 87584071 examples [1:28:02, 4619.01 examples/s]
Generating train split: 87584794 examples [1:28:03, 4445.08 examples/s]
Generating train split: 87585417 examples [1:28:03, 4115.11 examples/s]
Generating train split: 87587438 examples [1:28:03, 6667.18 examples/s]
Generating train split: 87588424 examples [1:28:03, 5866.54 examples/s]
Generating train split: 87590295 examples [1:28:03, 8105.31 examples/s]
Generating train split: 87591421 examples [1:28:04, 5718.20 examples/s]
Generating train split: 87592313 examples [1:28:04, 5300.58 examples/s]
Generating train split: 87593060 examples [1:28:04, 3818.32 examples/s]
Generating train split: 87593646 examples [1:28:04, 3756.27 examples/s]
Generating train split: 87594891 examples [1:28:04, 5035.20 examples/s]
Generating train split: 87595616 examples [1:28:05, 4421.34 examples/s]
Generating train split: 87596214 examples [1:28:05, 3885.96 examples/s]
Generating train split: 87596721 examples [1:28:05, 3819.48 examples/s]
Generating train split: 87597190 examples [1:28:05, 3098.66 examples/s]
Generating train split: 87597632 examples [1:28:05, 3308.04 examples/s]
Generating train split: 87598278 examples [1:28:05, 3892.55 examples/s]
Generating train split: 87598914 examples [1:28:06, 4390.79 examples/s]
Generating train split: 87599506 examples [1:28:06, 4705.43 examples/s]
Generating train split: 87600703 examples [1:28:06, 6511.78 examples/s]
Generating train split: 87601433 examples [1:28:06, 5273.57 examples/s]
Generating train split: 87602058 examples [1:28:06, 4089.51 examples/s]
Generating train split: 87603145 examples [1:28:06, 5408.55 examples/s]
Generating train split: 87604267 examples [1:28:06, 6658.21 examples/s]
Generating train split: 87605088 examples [1:28:07, 5023.29 examples/s]
Generating train split: 87605753 examples [1:28:07, 4672.22 examples/s]
Generating train split: 87606547 examples [1:28:07, 5311.34 examples/s]
Generating train split: 87608344 examples [1:28:07, 8056.87 examples/s]
Generating train split: 87609334 examples [1:28:07, 8236.54 examples/s]
Generating train split: 87610290 examples [1:28:07, 5973.54 examples/s]
Generating train split: 87611251 examples [1:28:08, 6686.02 examples/s]
Generating train split: 87615368 examples [1:28:08, 14277.59 examples/s]
Generating train split: 87623359 examples [1:28:08, 29973.23 examples/s]
Generating train split: 87628656 examples [1:28:08, 35756.98 examples/s]
Generating train split: 87632800 examples [1:28:08, 16116.68 examples/s]
Generating train split: 87635915 examples [1:28:09, 9637.86 examples/s] 
Generating train split: 87638221 examples [1:28:10, 8977.88 examples/s]
Generating train split: 87640051 examples [1:28:10, 7390.58 examples/s]
Generating train split: 87641456 examples [1:28:10, 6343.75 examples/s]
Generating train split: 87642568 examples [1:28:10, 6663.24 examples/s]
Generating train split: 87643610 examples [1:28:11, 5993.49 examples/s]
Generating train split: 87644471 examples [1:28:11, 5454.44 examples/s]
Generating train split: 87645188 examples [1:28:11, 4192.47 examples/s]
Generating train split: 87645759 examples [1:28:11, 3916.52 examples/s]
Generating train split: 87646247 examples [1:28:12, 3550.65 examples/s]
Generating train split: 87647923 examples [1:28:12, 5493.24 examples/s]
Generating train split: 87648717 examples [1:28:12, 5406.96 examples/s]
Generating train split: 87650128 examples [1:28:12, 6563.93 examples/s]
Generating train split: 87650935 examples [1:28:12, 4598.63 examples/s]
Generating train split: 87651576 examples [1:28:13, 3923.73 examples/s]
Generating train split: 87652102 examples [1:28:13, 3706.97 examples/s]
Generating train split: 87652836 examples [1:28:13, 4263.75 examples/s]
Generating train split: 87653361 examples [1:28:13, 4030.24 examples/s]
Generating train split: 87653831 examples [1:28:13, 2791.66 examples/s]
Generating train split: 87654666 examples [1:28:14, 3652.58 examples/s]
Generating train split: 87655182 examples [1:28:14, 3647.10 examples/s]
Generating train split: 87655643 examples [1:28:14, 2211.14 examples/s]
Generating train split: 87656322 examples [1:28:14, 2827.44 examples/s]
Generating train split: 87657061 examples [1:28:14, 3567.88 examples/s]
Generating train split: 87657602 examples [1:28:15, 2390.82 examples/s]
Generating train split: 87658007 examples [1:28:15, 1824.00 examples/s]
Generating train split: 87658567 examples [1:28:15, 2283.64 examples/s]
Generating train split: 87658956 examples [1:28:16, 1964.99 examples/s]
Generating train split: 87659324 examples [1:28:16, 2202.03 examples/s]
Generating train split: 87659660 examples [1:28:16, 2030.66 examples/s]
Generating train split: 87659942 examples [1:28:16, 1835.30 examples/s]
Generating train split: 87660187 examples [1:28:16, 1794.96 examples/s]
Generating train split: 87660998 examples [1:28:16, 2950.89 examples/s]
Generating train split: 87661401 examples [1:28:17, 2826.74 examples/s]
Generating train split: 87662782 examples [1:28:17, 5010.43 examples/s]
Generating train split: 87663405 examples [1:28:17, 4228.90 examples/s]
Generating train split: 87664287 examples [1:28:17, 5140.98 examples/s]
Generating train split: 87664974 examples [1:28:17, 5525.66 examples/s]
Generating train split: 87666356 examples [1:28:17, 7528.74 examples/s]
Generating train split: 87668506 examples [1:28:17, 11126.63 examples/s]
Generating train split: 87675869 examples [1:28:17, 27936.12 examples/s]
Generating train split: 87681945 examples [1:28:17, 37033.15 examples/s]
Generating train split: 87685925 examples [1:28:18, 21237.04 examples/s]
Generating train split: 87689031 examples [1:28:19, 9494.50 examples/s] 
Generating train split: 87691310 examples [1:28:19, 9018.59 examples/s]
Generating train split: 87693136 examples [1:28:20, 5647.71 examples/s]
Generating train split: 87694480 examples [1:28:20, 5088.13 examples/s]
Generating train split: 87695529 examples [1:28:20, 5533.86 examples/s]
Generating train split: 87696576 examples [1:28:21, 3709.23 examples/s]
Generating train split: 87697358 examples [1:28:21, 3445.20 examples/s]
Generating train split: 87697977 examples [1:28:21, 3685.67 examples/s]
Generating train split: 87698587 examples [1:28:22, 3422.74 examples/s]
Generating train split: 87699098 examples [1:28:22, 3560.76 examples/s]
Generating train split: 87700052 examples [1:28:22, 4448.71 examples/s]
Generating train split: 87702596 examples [1:28:22, 8135.56 examples/s]
Generating train split: 87703799 examples [1:28:22, 8658.42 examples/s]
Generating train split: 87704957 examples [1:28:22, 6816.63 examples/s]
Generating train split: 87705892 examples [1:28:23, 6430.99 examples/s]
Generating train split: 87706709 examples [1:28:23, 5332.65 examples/s]
Generating train split: 87707609 examples [1:28:23, 5963.67 examples/s]
Generating train split: 87708354 examples [1:28:23, 6139.88 examples/s]
Generating train split: 87709655 examples [1:28:23, 7595.12 examples/s]
Generating train split: 87710538 examples [1:28:23, 7068.27 examples/s]
Generating train split: 87711808 examples [1:28:23, 8370.24 examples/s]
Generating train split: 87712757 examples [1:28:24, 6977.26 examples/s]
Generating train split: 87714015 examples [1:28:24, 8202.54 examples/s]
Generating train split: 87714949 examples [1:28:24, 5245.68 examples/s]
Generating train split: 87715688 examples [1:28:24, 5226.99 examples/s]
Generating train split: 87716550 examples [1:28:24, 5834.31 examples/s]
Generating train split: 87717269 examples [1:28:25, 2909.25 examples/s]
Generating train split: 87717807 examples [1:28:25, 2967.52 examples/s]
Generating train split: 87719413 examples [1:28:25, 4826.15 examples/s]
Generating train split: 87720229 examples [1:28:25, 5242.54 examples/s]
Generating train split: 87722109 examples [1:28:25, 7813.14 examples/s]
Generating train split: 87729654 examples [1:28:25, 22239.57 examples/s]
Generating train split: 87738076 examples [1:28:26, 36712.82 examples/s]
Generating train split: 87742737 examples [1:28:26, 38740.30 examples/s]
Generating train split: 87747333 examples [1:28:27, 13479.41 examples/s]
Generating train split: 87750713 examples [1:28:27, 9342.77 examples/s] 
Generating train split: 87753226 examples [1:28:28, 7186.55 examples/s]
Generating train split: 87755102 examples [1:28:28, 7933.03 examples/s]
Generating train split: 87756869 examples [1:28:29, 6347.51 examples/s]
Generating train split: 87758218 examples [1:28:29, 5375.74 examples/s]
Generating train split: 87759252 examples [1:28:29, 5380.15 examples/s]
Generating train split: 87760145 examples [1:28:30, 4555.19 examples/s]
Generating train split: 87761365 examples [1:28:30, 5371.91 examples/s]
Generating train split: 87762219 examples [1:28:30, 5229.41 examples/s]
Generating train split: 87769145 examples [1:28:30, 14573.15 examples/s]
Generating train split: 87777896 examples [1:28:30, 27154.35 examples/s]
Generating train split: 87782339 examples [1:28:31, 15908.47 examples/s]
Generating train split: 87785692 examples [1:28:31, 9621.63 examples/s] 
Generating train split: 87788164 examples [1:28:32, 8664.81 examples/s]
Generating train split: 87790090 examples [1:28:32, 8693.32 examples/s]
Generating train split: 87792511 examples [1:28:32, 10319.29 examples/s]
Generating train split: 87796994 examples [1:28:32, 14794.26 examples/s]
Generating train split: 87799620 examples [1:28:32, 13993.49 examples/s]
Generating train split: 87801819 examples [1:28:33, 9497.98 examples/s] 
Generating train split: 87803504 examples [1:28:33, 10261.58 examples/s]
Generating train split: 87805138 examples [1:28:34, 7111.29 examples/s] 
Generating train split: 87806382 examples [1:28:34, 7172.18 examples/s]
Generating train split: 87807480 examples [1:28:34, 6973.50 examples/s]
Generating train split: 87808439 examples [1:28:34, 7110.95 examples/s]
Generating train split: 87809345 examples [1:28:34, 6187.87 examples/s]
Generating train split: 87810984 examples [1:28:34, 7908.94 examples/s]
Generating train split: 87812014 examples [1:28:35, 6624.46 examples/s]
Generating train split: 87812866 examples [1:28:35, 4923.97 examples/s]
Generating train split: 87813714 examples [1:28:35, 5422.00 examples/s]
Generating train split: 87814659 examples [1:28:35, 6057.74 examples/s]
Generating train split: 87815423 examples [1:28:35, 4243.56 examples/s]
Generating train split: 87816125 examples [1:28:36, 4647.79 examples/s]
Generating train split: 87816751 examples [1:28:36, 3926.64 examples/s]
Generating train split: 87817279 examples [1:28:36, 3631.64 examples/s]
Generating train split: 87824873 examples [1:28:36, 16497.57 examples/s]
Generating train split: 87833439 examples [1:28:36, 30490.28 examples/s]
Generating train split: 87837812 examples [1:28:37, 20545.27 examples/s]
Generating train split: 87841229 examples [1:28:37, 12671.33 examples/s]
Generating train split: 87843788 examples [1:28:38, 8124.91 examples/s] 
Generating train split: 87845686 examples [1:28:38, 6749.26 examples/s]
Generating train split: 87850114 examples [1:28:38, 9910.83 examples/s]
Generating train split: 87858556 examples [1:28:39, 17915.17 examples/s]
Generating train split: 87863263 examples [1:28:39, 21060.04 examples/s]
Generating train split: 87867307 examples [1:28:39, 15792.72 examples/s]
Generating train split: 87870419 examples [1:28:39, 14462.95 examples/s]
Generating train split: 87872934 examples [1:28:40, 12679.13 examples/s]
Generating train split: 87874953 examples [1:28:40, 11477.12 examples/s]
Generating train split: 87876609 examples [1:28:40, 10991.43 examples/s]
Generating train split: 87878045 examples [1:28:41, 7978.44 examples/s] 
Generating train split: 87879610 examples [1:28:41, 8955.23 examples/s]
Generating train split: 87880859 examples [1:28:41, 8934.85 examples/s]
Generating train split: 87887502 examples [1:28:41, 18792.21 examples/s]
Generating train split: 87896656 examples [1:28:41, 33098.30 examples/s]
Generating train split: 87901357 examples [1:28:42, 17252.88 examples/s]
Generating train split: 87909225 examples [1:28:42, 25242.24 examples/s]
Generating train split: 87915355 examples [1:28:42, 30886.41 examples/s]
Generating train split: 87920577 examples [1:28:43, 10551.69 examples/s]
Generating train split: 87924342 examples [1:28:44, 7963.77 examples/s] 
Generating train split: 87927116 examples [1:28:45, 6504.93 examples/s]
Generating train split: 87929168 examples [1:28:45, 6001.04 examples/s]
Generating train split: 87931213 examples [1:28:45, 6929.01 examples/s]
Generating train split: 87932914 examples [1:28:46, 6324.07 examples/s]
Generating train split: 87934579 examples [1:28:46, 7248.24 examples/s]
Generating train split: 87936018 examples [1:28:46, 8031.29 examples/s]
Generating train split: 87937448 examples [1:28:46, 6341.69 examples/s]
Generating train split: 87938551 examples [1:28:46, 6327.18 examples/s]
Generating train split: 87939515 examples [1:28:47, 6218.81 examples/s]
Generating train split: 87940366 examples [1:28:47, 5082.19 examples/s]
Generating train split: 87941059 examples [1:28:47, 5148.04 examples/s]
Generating train split: 87942369 examples [1:28:47, 6470.11 examples/s]
Generating train split: 87943210 examples [1:28:47, 5616.86 examples/s]
Generating train split: 87945206 examples [1:28:47, 8245.37 examples/s]
Generating train split: 87953712 examples [1:28:48, 24210.96 examples/s]
Generating train split: 87961674 examples [1:28:48, 36386.42 examples/s]
Generating train split: 87966248 examples [1:28:48, 31845.97 examples/s]
Generating train split: 87970185 examples [1:28:49, 13306.93 examples/s]
Generating train split: 87973093 examples [1:28:49, 12237.56 examples/s]
Generating train split: 87975418 examples [1:28:49, 9954.90 examples/s] 
Generating train split: 87977221 examples [1:28:49, 10548.01 examples/s]
Generating train split: 87979354 examples [1:28:50, 11956.25 examples/s]
Generating train split: 87981187 examples [1:28:50, 9434.33 examples/s] 
Generating train split: 87983070 examples [1:28:50, 10702.33 examples/s]
Generating train split: 87984625 examples [1:28:50, 11116.92 examples/s]
Generating train split: 87986103 examples [1:28:50, 9500.50 examples/s] 
Generating train split: 87987332 examples [1:28:50, 9902.56 examples/s]
Generating train split: 87988914 examples [1:28:51, 11085.87 examples/s]
Generating train split: 87990337 examples [1:28:51, 11698.96 examples/s]
Generating train split: 87991765 examples [1:28:51, 12270.97 examples/s]
Generating train split: 87993124 examples [1:28:51, 8033.55 examples/s] 
Generating train split: 87994503 examples [1:28:51, 9076.48 examples/s]
Generating train split: 87996158 examples [1:28:51, 10650.58 examples/s]
Generating train split: 87997471 examples [1:28:52, 6979.74 examples/s] 
Generating train split: 87998499 examples [1:28:52, 5191.09 examples/s]
Generating train split: 87999308 examples [1:28:52, 4803.54 examples/s]
Generating train split: 87999986 examples [1:28:52, 4905.99 examples/s]
Generating train split: 88000624 examples [1:28:53, 4909.64 examples/s]
Generating train split: 88001214 examples [1:28:53, 4306.96 examples/s]
Generating train split: 88003171 examples [1:28:53, 7123.39 examples/s]
Generating train split: 88004110 examples [1:28:53, 7421.75 examples/s]
Generating train split: 88005018 examples [1:28:53, 5170.63 examples/s]
Generating train split: 88005877 examples [1:28:53, 5769.83 examples/s]
Generating train split: 88006640 examples [1:28:53, 6112.48 examples/s]
Generating train split: 88007406 examples [1:28:54, 5707.51 examples/s]
Generating train split: 88008306 examples [1:28:54, 6271.62 examples/s]
Generating train split: 88009102 examples [1:28:54, 6640.11 examples/s]
Generating train split: 88010027 examples [1:28:54, 7148.02 examples/s]
Generating train split: 88010808 examples [1:28:54, 7013.79 examples/s]
Generating train split: 88018689 examples [1:28:54, 25805.38 examples/s]
Generating train split: 88026385 examples [1:28:54, 39714.84 examples/s]
Generating train split: 88030715 examples [1:28:55, 23240.67 examples/s]
Generating train split: 88034095 examples [1:28:55, 17481.11 examples/s]
Generating train split: 88042286 examples [1:28:55, 27498.28 examples/s]
Generating train split: 88047777 examples [1:28:55, 32470.66 examples/s]
Generating train split: 88052460 examples [1:28:56, 16613.00 examples/s]
Generating train split: 88055948 examples [1:28:56, 11597.27 examples/s]
Generating train split: 88058559 examples [1:28:57, 9130.97 examples/s] 
Generating train split: 88060548 examples [1:28:57, 8917.30 examples/s]
Generating train split: 88062173 examples [1:28:57, 8940.13 examples/s]
Generating train split: 88064026 examples [1:28:58, 10059.02 examples/s]
Generating train split: 88065565 examples [1:28:58, 10290.98 examples/s]
Generating train split: 88066996 examples [1:28:58, 10126.23 examples/s]
Generating train split: 88068275 examples [1:28:58, 7921.36 examples/s] 
Generating train split: 88069309 examples [1:28:58, 6097.49 examples/s]
Generating train split: 88070212 examples [1:28:59, 6493.18 examples/s]
Generating train split: 88071052 examples [1:28:59, 5542.65 examples/s]
Generating train split: 88071754 examples [1:28:59, 5127.33 examples/s]
Generating train split: 88072356 examples [1:28:59, 4444.52 examples/s]
Generating train split: 88072873 examples [1:28:59, 3682.28 examples/s]
Generating train split: 88073396 examples [1:28:59, 3932.46 examples/s]
Generating train split: 88074219 examples [1:29:00, 4748.29 examples/s]
Generating train split: 88074788 examples [1:29:00, 4378.90 examples/s]
Generating train split: 88075292 examples [1:29:00, 3902.96 examples/s]
Generating train split: 88075728 examples [1:29:00, 3269.66 examples/s]
Generating train split: 88076892 examples [1:29:00, 4881.03 examples/s]
Generating train split: 88078642 examples [1:29:00, 7584.43 examples/s]
Generating train split: 88079575 examples [1:29:01, 5683.25 examples/s]
Generating train split: 88080342 examples [1:29:01, 5302.73 examples/s]
Generating train split: 88082564 examples [1:29:01, 8406.55 examples/s]
Generating train split: 88083632 examples [1:29:01, 6000.88 examples/s]
Generating train split: 88084476 examples [1:29:01, 5731.57 examples/s]
Generating train split: 88085436 examples [1:29:01, 6422.29 examples/s]
Generating train split: 88087253 examples [1:29:02, 8804.37 examples/s]
Generating train split: 88088361 examples [1:29:02, 5479.29 examples/s]
Generating train split: 88090374 examples [1:29:02, 7806.08 examples/s]
Generating train split: 88091581 examples [1:29:02, 6395.64 examples/s]
Generating train split: 88092550 examples [1:29:03, 5941.23 examples/s]
Generating train split: 88093374 examples [1:29:03, 4226.61 examples/s]
Generating train split: 88095352 examples [1:29:03, 6364.38 examples/s]
Generating train split: 88096550 examples [1:29:03, 7286.64 examples/s]
Generating train split: 88097642 examples [1:29:03, 6364.61 examples/s]
Generating train split: 88098544 examples [1:29:04, 5983.67 examples/s]
Generating train split: 88099945 examples [1:29:04, 7443.45 examples/s]
Generating train split: 88100973 examples [1:29:04, 7811.53 examples/s]
Generating train split: 88101924 examples [1:29:04, 7481.90 examples/s]
Generating train split: 88102793 examples [1:29:04, 7053.58 examples/s]
Generating train split: 88103583 examples [1:29:04, 4722.16 examples/s]
Generating train split: 88104210 examples [1:29:05, 4310.19 examples/s]
Generating train split: 88105971 examples [1:29:05, 6660.75 examples/s]
Generating train split: 88107803 examples [1:29:05, 8843.13 examples/s]
Generating train split: 88109034 examples [1:29:05, 9425.55 examples/s]
Generating train split: 88110176 examples [1:29:05, 8000.88 examples/s]
Generating train split: 88111142 examples [1:29:05, 6568.25 examples/s]
Generating train split: 88111948 examples [1:29:06, 5537.94 examples/s]
Generating train split: 88112627 examples [1:29:06, 5755.74 examples/s]
Generating train split: 88113304 examples [1:29:06, 4920.01 examples/s]
Generating train split: 88114207 examples [1:29:06, 5648.00 examples/s]
Generating train split: 88114867 examples [1:29:06, 5735.69 examples/s]
Generating train split: 88115707 examples [1:29:06, 6314.93 examples/s]
Generating train split: 88117591 examples [1:29:06, 9422.20 examples/s]
Generating train split: 88118652 examples [1:29:06, 7781.70 examples/s]
Generating train split: 88119941 examples [1:29:07, 8911.44 examples/s]
Generating train split: 88120963 examples [1:29:07, 6802.00 examples/s]
Generating train split: 88121804 examples [1:29:07, 5740.56 examples/s]
Generating train split: 88129854 examples [1:29:07, 20049.92 examples/s]
Generating train split: 88138124 examples [1:29:07, 33499.65 examples/s]
Generating train split: 88142645 examples [1:29:07, 32688.99 examples/s]
Generating train split: 88146741 examples [1:29:08, 19428.47 examples/s]
Generating train split: 88149897 examples [1:29:08, 13698.46 examples/s]
Generating train split: 88152311 examples [1:29:09, 10536.17 examples/s]
Generating train split: 88154167 examples [1:29:09, 8693.30 examples/s] 
Generating train split: 88156121 examples [1:29:09, 9865.85 examples/s]
Generating train split: 88157715 examples [1:29:09, 10101.00 examples/s]
Generating train split: 88165701 examples [1:29:09, 20799.51 examples/s]
Generating train split: 88173321 examples [1:29:10, 30583.64 examples/s]
Generating train split: 88177937 examples [1:29:10, 19918.01 examples/s]
Generating train split: 88181475 examples [1:29:10, 15141.87 examples/s]
Generating train split: 88184207 examples [1:29:11, 10060.96 examples/s]
Generating train split: 88186248 examples [1:29:12, 6659.94 examples/s] 
Generating train split: 88187760 examples [1:29:12, 6544.91 examples/s]
Generating train split: 88188996 examples [1:29:12, 6797.42 examples/s]
Generating train split: 88190131 examples [1:29:13, 6061.78 examples/s]
Generating train split: 88191047 examples [1:29:13, 6007.59 examples/s]
Generating train split: 88192055 examples [1:29:13, 6531.20 examples/s]
Generating train split: 88192927 examples [1:29:13, 6633.78 examples/s]
Generating train split: 88193743 examples [1:29:13, 4957.80 examples/s]
Generating train split: 88195344 examples [1:29:13, 6649.80 examples/s]
Generating train split: 88196701 examples [1:29:13, 7889.17 examples/s]
Generating train split: 88197765 examples [1:29:14, 5891.19 examples/s]
Generating train split: 88198603 examples [1:29:14, 6113.12 examples/s]
Generating train split: 88199404 examples [1:29:14, 6115.94 examples/s]
Generating train split: 88207829 examples [1:29:14, 22078.38 examples/s]
Generating train split: 88216119 examples [1:29:14, 35816.31 examples/s]
Generating train split: 88220740 examples [1:29:14, 36374.36 examples/s]
Generating train split: 88225115 examples [1:29:15, 15532.30 examples/s]
Generating train split: 88228364 examples [1:29:16, 11525.37 examples/s]
Generating train split: 88230831 examples [1:29:16, 12160.70 examples/s]
Generating train split: 88233023 examples [1:29:16, 10109.47 examples/s]
Generating train split: 88234748 examples [1:29:16, 10376.03 examples/s]
Generating train split: 88236315 examples [1:29:17, 7330.81 examples/s] 
Generating train split: 88237517 examples [1:29:17, 6423.18 examples/s]
Generating train split: 88238474 examples [1:29:17, 6690.81 examples/s]
Generating train split: 88239888 examples [1:29:17, 7750.98 examples/s]
Generating train split: 88240966 examples [1:29:18, 4822.80 examples/s]
Generating train split: 88241910 examples [1:29:18, 5231.96 examples/s]
Generating train split: 88242919 examples [1:29:18, 5928.25 examples/s]
Generating train split: 88243775 examples [1:29:18, 4847.83 examples/s]
Generating train split: 88245711 examples [1:29:18, 7132.81 examples/s]
Generating train split: 88246780 examples [1:29:18, 6605.39 examples/s]
Generating train split: 88247696 examples [1:29:19, 6050.72 examples/s]
Generating train split: 88249168 examples [1:29:19, 7586.31 examples/s]
Generating train split: 88250335 examples [1:29:19, 7985.60 examples/s]
Generating train split: 88251300 examples [1:29:19, 5182.45 examples/s]
Generating train split: 88252641 examples [1:29:19, 6485.93 examples/s]
Generating train split: 88253698 examples [1:29:20, 7095.75 examples/s]
Generating train split: 88254624 examples [1:29:20, 6972.24 examples/s]
Generating train split: 88255482 examples [1:29:20, 6455.43 examples/s]
Generating train split: 88256240 examples [1:29:20, 6074.11 examples/s]
Generating train split: 88256920 examples [1:29:20, 4049.72 examples/s]
Generating train split: 88263841 examples [1:29:20, 14952.51 examples/s]
Generating train split: 88272181 examples [1:29:21, 28154.88 examples/s]
Generating train split: 88276412 examples [1:29:21, 22404.73 examples/s]
Generating train split: 88279822 examples [1:29:21, 17219.15 examples/s]
Generating train split: 88282583 examples [1:29:21, 18796.91 examples/s]
Generating train split: 88285291 examples [1:29:22, 10119.73 examples/s]
Generating train split: 88287312 examples [1:29:22, 8647.03 examples/s] 
Generating train split: 88288890 examples [1:29:22, 8444.57 examples/s]
Generating train split: 88294288 examples [1:29:23, 14095.50 examples/s]
Generating train split: 88302916 examples [1:29:23, 24962.23 examples/s]
Generating train split: 88308113 examples [1:29:23, 28283.88 examples/s]
Generating train split: 88312394 examples [1:29:23, 18201.62 examples/s]
Generating train split: 88315665 examples [1:29:23, 19416.95 examples/s]
Generating train split: 88318716 examples [1:29:24, 15819.80 examples/s]
Generating train split: 88321139 examples [1:29:24, 16324.12 examples/s]
Generating train split: 88323396 examples [1:29:24, 10429.91 examples/s]
Generating train split: 88325115 examples [1:29:25, 9912.04 examples/s] 
Generating train split: 88326564 examples [1:29:25, 9822.14 examples/s]
Generating train split: 88327870 examples [1:29:25, 7522.93 examples/s]
Generating train split: 88329415 examples [1:29:25, 8609.49 examples/s]
Generating train split: 88330596 examples [1:29:25, 7858.20 examples/s]
Generating train split: 88331607 examples [1:29:26, 6606.81 examples/s]
Generating train split: 88332618 examples [1:29:26, 7155.64 examples/s]
Generating train split: 88333501 examples [1:29:26, 5283.76 examples/s]
Generating train split: 88334229 examples [1:29:26, 5584.70 examples/s]
Generating train split: 88334941 examples [1:29:26, 5494.21 examples/s]
Generating train split: 88337525 examples [1:29:26, 9453.88 examples/s]
Generating train split: 88338734 examples [1:29:27, 8266.50 examples/s]
Generating train split: 88340499 examples [1:29:27, 10107.75 examples/s]
Generating train split: 88341728 examples [1:29:27, 9818.84 examples/s] 
Generating train split: 88343252 examples [1:29:27, 11009.32 examples/s]
Generating train split: 88345982 examples [1:29:27, 14990.53 examples/s]
Generating train split: 88347668 examples [1:29:28, 7363.88 examples/s] 
Generating train split: 88348951 examples [1:29:28, 6110.34 examples/s]
Generating train split: 88350050 examples [1:29:28, 6782.26 examples/s]
Generating train split: 88351088 examples [1:29:28, 7358.04 examples/s]
Generating train split: 88352210 examples [1:29:28, 8090.73 examples/s]
Generating train split: 88353274 examples [1:29:29, 5132.19 examples/s]
Generating train split: 88354093 examples [1:29:29, 4197.72 examples/s]
Generating train split: 88354747 examples [1:29:29, 4522.62 examples/s]
Generating train split: 88356009 examples [1:29:29, 5878.72 examples/s]
Generating train split: 88356854 examples [1:29:29, 6339.08 examples/s]
Generating train split: 88358103 examples [1:29:29, 7535.10 examples/s]
Generating train split: 88359042 examples [1:29:29, 6436.03 examples/s]
Generating train split: 88363760 examples [1:29:30, 15046.40 examples/s]
Generating train split: 88372893 examples [1:29:30, 32732.94 examples/s]
Generating train split: 88379441 examples [1:29:30, 40859.99 examples/s]
Generating train split: 88384288 examples [1:29:31, 8409.00 examples/s] 
Generating train split: 88387777 examples [1:29:32, 7418.33 examples/s]
Generating train split: 88390372 examples [1:29:33, 6705.19 examples/s]
Generating train split: 88392336 examples [1:29:33, 7269.20 examples/s]
Generating train split: 88394082 examples [1:29:33, 6919.92 examples/s]
Generating train split: 88396401 examples [1:29:33, 8450.03 examples/s]
Generating train split: 88398066 examples [1:29:33, 8680.17 examples/s]
Generating train split: 88399532 examples [1:29:34, 7676.06 examples/s]
Generating train split: 88401277 examples [1:29:34, 8992.74 examples/s]
Generating train split: 88402635 examples [1:29:34, 6749.38 examples/s]
Generating train split: 88403694 examples [1:29:34, 7069.52 examples/s]
Generating train split: 88405205 examples [1:29:34, 8354.53 examples/s]
Generating train split: 88407491 examples [1:29:34, 11056.63 examples/s]
Generating train split: 88408981 examples [1:29:35, 7459.69 examples/s] 
Generating train split: 88410144 examples [1:29:35, 7929.83 examples/s]
Generating train split: 88411267 examples [1:29:35, 8408.43 examples/s]
Generating train split: 88412368 examples [1:29:35, 6281.60 examples/s]
Generating train split: 88413251 examples [1:29:36, 5854.42 examples/s]
Generating train split: 88415284 examples [1:29:36, 8280.50 examples/s]
Generating train split: 88416382 examples [1:29:36, 6474.65 examples/s]
Generating train split: 88417269 examples [1:29:36, 6371.97 examples/s]
Generating train split: 88418073 examples [1:29:36, 4727.55 examples/s]
Generating train split: 88419366 examples [1:29:37, 6013.98 examples/s]
Generating train split: 88420834 examples [1:29:37, 7553.51 examples/s]
Generating train split: 88421937 examples [1:29:37, 7963.11 examples/s]
Generating train split: 88423893 examples [1:29:37, 10527.87 examples/s]
Generating train split: 88431953 examples [1:29:37, 27348.47 examples/s]
Generating train split: 88436977 examples [1:29:37, 31728.81 examples/s]
Generating train split: 88440575 examples [1:29:37, 22929.30 examples/s]
Generating train split: 88443495 examples [1:29:38, 15742.39 examples/s]
Generating train split: 88445782 examples [1:29:38, 16062.82 examples/s]
Generating train split: 88447911 examples [1:29:38, 13857.23 examples/s]
Generating train split: 88449683 examples [1:29:38, 12346.72 examples/s]
Generating train split: 88458784 examples [1:29:38, 25952.41 examples/s]
Generating train split: 88466096 examples [1:29:38, 35286.26 examples/s]
Generating train split: 88470937 examples [1:29:39, 31899.79 examples/s]
Generating train split: 88475096 examples [1:29:39, 19127.58 examples/s]
Generating train split: 88478275 examples [1:29:40, 13495.65 examples/s]
Generating train split: 88480702 examples [1:29:40, 14040.18 examples/s]
Generating train split: 88482909 examples [1:29:40, 9989.21 examples/s] 
Generating train split: 88484795 examples [1:29:40, 11001.69 examples/s]
Generating train split: 88486539 examples [1:29:41, 7892.05 examples/s] 
Generating train split: 88488361 examples [1:29:41, 9089.61 examples/s]
Generating train split: 88489836 examples [1:29:41, 7472.57 examples/s]
Generating train split: 88491006 examples [1:29:41, 6944.18 examples/s]
Generating train split: 88491987 examples [1:29:42, 5371.61 examples/s]
Generating train split: 88493011 examples [1:29:42, 5997.61 examples/s]
Generating train split: 88493856 examples [1:29:42, 6139.55 examples/s]
Generating train split: 88494653 examples [1:29:42, 6429.03 examples/s]
Generating train split: 88495442 examples [1:29:42, 5429.81 examples/s]
Generating train split: 88496696 examples [1:29:42, 6760.80 examples/s]
Generating train split: 88497541 examples [1:29:43, 6412.37 examples/s]
Generating train split: 88499172 examples [1:29:43, 8496.77 examples/s]
Generating train split: 88500188 examples [1:29:43, 6455.82 examples/s]
Generating train split: 88501728 examples [1:29:43, 8180.30 examples/s]
Generating train split: 88503193 examples [1:29:43, 9580.42 examples/s]
Generating train split: 88504619 examples [1:29:43, 10612.42 examples/s]
Generating train split: 88505847 examples [1:29:44, 7782.19 examples/s] 
Generating train split: 88507472 examples [1:29:44, 9490.66 examples/s]
Generating train split: 88508975 examples [1:29:44, 10682.97 examples/s]
Generating train split: 88510251 examples [1:29:44, 9242.17 examples/s] 
Generating train split: 88511350 examples [1:29:44, 8839.35 examples/s]
Generating train split: 88512466 examples [1:29:44, 9343.88 examples/s]
Generating train split: 88513774 examples [1:29:44, 10231.54 examples/s]
Generating train split: 88514894 examples [1:29:44, 9330.90 examples/s] 
Generating train split: 88522342 examples [1:29:44, 25394.78 examples/s]
Generating train split: 88531016 examples [1:29:45, 41370.95 examples/s]
Generating train split: 88535676 examples [1:29:45, 22472.88 examples/s]
Generating train split: 88539264 examples [1:29:45, 16890.58 examples/s]
Generating train split: 88542066 examples [1:29:46, 12852.39 examples/s]
Generating train split: 88544232 examples [1:29:46, 13616.86 examples/s]
Generating train split: 88546293 examples [1:29:46, 12287.47 examples/s]
Generating train split: 88548015 examples [1:29:46, 10070.53 examples/s]
Generating train split: 88549820 examples [1:29:47, 11202.69 examples/s]
Generating train split: 88551331 examples [1:29:47, 8876.05 examples/s] 
Generating train split: 88552534 examples [1:29:47, 8871.33 examples/s]
Generating train split: 88553655 examples [1:29:47, 6265.59 examples/s]
Generating train split: 88554856 examples [1:29:47, 7066.36 examples/s]
Generating train split: 88556238 examples [1:29:48, 8196.00 examples/s]
Generating train split: 88557650 examples [1:29:48, 9335.86 examples/s]
Generating train split: 88558835 examples [1:29:48, 7827.54 examples/s]
Generating train split: 88559850 examples [1:29:48, 8275.27 examples/s]
Generating train split: 88561094 examples [1:29:48, 9174.94 examples/s]
Generating train split: 88562167 examples [1:29:48, 6101.22 examples/s]
Generating train split: 88563769 examples [1:29:49, 7872.76 examples/s]
Generating train split: 88564846 examples [1:29:49, 8429.65 examples/s]
Generating train split: 88566527 examples [1:29:49, 9950.22 examples/s]
Generating train split: 88567712 examples [1:29:49, 8068.38 examples/s]
Generating train split: 88575413 examples [1:29:49, 22374.75 examples/s]
Generating train split: 88583044 examples [1:29:49, 34068.80 examples/s]
Generating train split: 88587269 examples [1:29:50, 16462.25 examples/s]
Generating train split: 88590450 examples [1:29:50, 16583.71 examples/s]
Generating train split: 88593177 examples [1:29:50, 12396.51 examples/s]
Generating train split: 88595284 examples [1:29:51, 12537.18 examples/s]
Generating train split: 88597170 examples [1:29:51, 12544.21 examples/s]
Generating train split: 88598862 examples [1:29:51, 10621.88 examples/s]
Generating train split: 88600245 examples [1:29:51, 10901.39 examples/s]
Generating train split: 88601585 examples [1:29:51, 10691.34 examples/s]
Generating train split: 88603276 examples [1:29:51, 11856.85 examples/s]
Generating train split: 88604645 examples [1:29:51, 9695.63 examples/s] 
Generating train split: 88605791 examples [1:29:52, 9058.07 examples/s]
Generating train split: 88606817 examples [1:29:52, 9203.05 examples/s]
Generating train split: 88607823 examples [1:29:52, 7988.98 examples/s]
Generating train split: 88608697 examples [1:29:52, 7162.86 examples/s]
Generating train split: 88610705 examples [1:29:52, 9879.64 examples/s]
Generating train split: 88611847 examples [1:29:53, 6449.01 examples/s]
Generating train split: 88614214 examples [1:29:53, 9413.92 examples/s]
Generating train split: 88615585 examples [1:29:53, 10197.10 examples/s]
Generating train split: 88616921 examples [1:29:53, 9475.43 examples/s] 
Generating train split: 88618093 examples [1:29:53, 8247.04 examples/s]
Generating train split: 88619978 examples [1:29:53, 10375.70 examples/s]
Generating train split: 88621249 examples [1:29:53, 10522.09 examples/s]
Generating train split: 88622464 examples [1:29:54, 8325.61 examples/s] 
Generating train split: 88623529 examples [1:29:54, 8742.09 examples/s]
Generating train split: 88624550 examples [1:29:54, 8033.26 examples/s]
Generating train split: 88625466 examples [1:29:54, 6203.82 examples/s]
Generating train split: 88627118 examples [1:29:54, 7751.08 examples/s]
Generating train split: 88628033 examples [1:29:54, 7913.63 examples/s]
Generating train split: 88630496 examples [1:29:54, 11651.81 examples/s]
Generating train split: 88632014 examples [1:29:55, 12505.69 examples/s]
Generating train split: 88633421 examples [1:29:55, 12566.54 examples/s]
Generating train split: 88634793 examples [1:29:55, 9562.65 examples/s] 
Generating train split: 88636708 examples [1:29:55, 11657.44 examples/s]
Generating train split: 88638079 examples [1:29:55, 11735.37 examples/s]
Generating train split: 88639402 examples [1:29:55, 11392.91 examples/s]
Generating train split: 88641828 examples [1:29:55, 14530.10 examples/s]
Generating train split: 88643409 examples [1:29:56, 7311.29 examples/s] 
Generating train split: 88644618 examples [1:29:56, 8011.05 examples/s]
Generating train split: 88645812 examples [1:29:56, 7441.00 examples/s]
Generating train split: 88647313 examples [1:29:56, 8805.35 examples/s]
Generating train split: 88648481 examples [1:29:56, 9126.81 examples/s]
Generating train split: 88650383 examples [1:29:56, 11298.63 examples/s]
Generating train split: 88651735 examples [1:29:57, 9858.56 examples/s] 
Generating train split: 88653143 examples [1:29:57, 10796.15 examples/s]
Generating train split: 88654383 examples [1:29:57, 7889.95 examples/s] 
Generating train split: 88655394 examples [1:29:57, 7705.57 examples/s]
Generating train split: 88657244 examples [1:29:57, 9869.01 examples/s]
Generating train split: 88658433 examples [1:29:57, 9664.54 examples/s]
Generating train split: 88659536 examples [1:29:58, 8524.83 examples/s]
Generating train split: 88660958 examples [1:29:58, 9759.59 examples/s]
Generating train split: 88662159 examples [1:29:58, 10137.67 examples/s]
Generating train split: 88664268 examples [1:29:58, 12887.68 examples/s]
Generating train split: 88665681 examples [1:29:58, 12643.32 examples/s]
Generating train split: 88667038 examples [1:29:58, 9377.10 examples/s] 
Generating train split: 88668761 examples [1:29:58, 11063.74 examples/s]
Generating train split: 88670064 examples [1:29:58, 10152.78 examples/s]
Generating train split: 88671227 examples [1:29:59, 7794.28 examples/s] 
Generating train split: 88672570 examples [1:29:59, 8881.89 examples/s]
Generating train split: 88674222 examples [1:29:59, 10542.37 examples/s]
Generating train split: 88678497 examples [1:29:59, 18181.27 examples/s]
Generating train split: 88683875 examples [1:29:59, 27185.22 examples/s]
Generating train split: 88690011 examples [1:29:59, 36249.18 examples/s]
Generating train split: 88696402 examples [1:29:59, 43842.25 examples/s]
Generating train split: 88703031 examples [1:29:59, 50157.65 examples/s]
Generating train split: 88709662 examples [1:29:59, 54780.22 examples/s]
Generating train split: 88716751 examples [1:30:00, 59438.17 examples/s]
Generating train split: 88724022 examples [1:30:00, 63328.97 examples/s]
Generating train split: 88731509 examples [1:30:00, 66717.53 examples/s]
Generating train split: 88738565 examples [1:30:00, 67798.52 examples/s]
Generating train split: 88746126 examples [1:30:00, 70092.95 examples/s]
Generating train split: 88754202 examples [1:30:00, 73250.21 examples/s]
Generating train split: 88761573 examples [1:30:00, 72674.36 examples/s]
Generating train split: 88769463 examples [1:30:00, 74515.93 examples/s]
Generating train split: 88777305 examples [1:30:00, 75658.93 examples/s]
Generating train split: 88785557 examples [1:30:01, 77683.81 examples/s]
Generating train split: 88793612 examples [1:30:01, 78510.86 examples/s]
Generating train split: 88801946 examples [1:30:01, 79933.24 examples/s]
Generating train split: 88810142 examples [1:30:01, 80533.72 examples/s]
Generating train split: 88818212 examples [1:30:01, 79934.09 examples/s]
Generating train split: 88826589 examples [1:30:01, 81059.90 examples/s]
Generating train split: 88834936 examples [1:30:01, 81746.24 examples/s]
Generating train split: 88843647 examples [1:30:01, 83341.73 examples/s]
Generating train split: 88851990 examples [1:30:01, 82543.99 examples/s]
Generating train split: 88860263 examples [1:30:01, 82355.10 examples/s]
Generating train split: 88868513 examples [1:30:02, 79057.38 examples/s]
Generating train split: 88876447 examples [1:30:02, 77576.22 examples/s]
Generating train split: 88884230 examples [1:30:02, 75140.70 examples/s]
Generating train split: 88891777 examples [1:30:02, 71545.53 examples/s]
Generating train split: 88898978 examples [1:30:02, 69009.71 examples/s]
Generating train split: 88905917 examples [1:30:02, 67859.13 examples/s]
Generating train split: 88912723 examples [1:30:02, 62845.80 examples/s]
Generating train split: 88919072 examples [1:30:02, 48962.75 examples/s]
Generating train split: 88924445 examples [1:30:03, 44809.51 examples/s]
Generating train split: 88929280 examples [1:30:03, 39027.45 examples/s]
Generating train split: 88933492 examples [1:30:03, 31882.02 examples/s]
Generating train split: 88937035 examples [1:30:03, 25113.92 examples/s]
Generating train split: 88939953 examples [1:30:03, 21740.61 examples/s]
Generating train split: 88942429 examples [1:30:04, 18144.50 examples/s]
Generating train split: 88944480 examples [1:30:04, 15622.13 examples/s]
Generating train split: 88946218 examples [1:30:04, 15896.21 examples/s]
Generating train split: 88947948 examples [1:30:04, 10178.11 examples/s]
Generating train split: 88951429 examples [1:30:04, 13871.15 examples/s]
Generating train split: 88959278 examples [1:30:05, 25267.41 examples/s]
Generating train split: 88968006 examples [1:30:05, 36535.22 examples/s]
Generating train split: 88972874 examples [1:30:05, 22763.02 examples/s]
Generating train split: 88976620 examples [1:30:05, 17668.61 examples/s]
Generating train split: 88979545 examples [1:30:06, 14099.49 examples/s]
Generating train split: 88981838 examples [1:30:06, 10924.31 examples/s]
Generating train split: 88983613 examples [1:30:07, 9905.60 examples/s] 
Generating train split: 88985055 examples [1:30:07, 9190.91 examples/s]
Generating train split: 88986270 examples [1:30:07, 8939.19 examples/s]
Generating train split: 88987353 examples [1:30:07, 8680.51 examples/s]
Generating train split: 88988773 examples [1:30:07, 9589.00 examples/s]
Generating train split: 88989891 examples [1:30:07, 9356.75 examples/s]
Generating train split: 88998133 examples [1:30:07, 24392.64 examples/s]
Generating train split: 89006850 examples [1:30:07, 38652.63 examples/s]
Generating train split: 89011711 examples [1:30:08, 29812.00 examples/s]
Generating train split: 89015681 examples [1:30:08, 17900.49 examples/s]
Generating train split: 89018711 examples [1:30:08, 17374.22 examples/s]
Generating train split: 89021305 examples [1:30:09, 13579.01 examples/s]
Generating train split: 89023346 examples [1:30:09, 13650.55 examples/s]
Generating train split: 89025195 examples [1:30:09, 9454.46 examples/s] 
Generating train split: 89026622 examples [1:30:10, 7890.47 examples/s]
Generating train split: 89027759 examples [1:30:10, 8157.43 examples/s]
Generating train split: 89029337 examples [1:30:10, 9106.77 examples/s]
Generating train split: 89030518 examples [1:30:10, 8953.49 examples/s]
Generating train split: 89031601 examples [1:30:10, 7421.13 examples/s]
Generating train split: 89032906 examples [1:30:10, 8386.71 examples/s]
Generating train split: 89033919 examples [1:30:11, 7757.72 examples/s]
Generating train split: 89034813 examples [1:30:11, 7527.55 examples/s]
Generating train split: 89036099 examples [1:30:11, 8259.52 examples/s]
Generating train split: 89036999 examples [1:30:11, 7843.71 examples/s]
Generating train split: 89039438 examples [1:30:11, 11660.13 examples/s]
Generating train split: 89040754 examples [1:30:11, 9723.69 examples/s] 
Generating train split: 89048100 examples [1:30:11, 23900.45 examples/s]
Generating train split: 89056503 examples [1:30:11, 38399.87 examples/s]
Generating train split: 89061123 examples [1:30:12, 20730.73 examples/s]
Generating train split: 89064650 examples [1:30:12, 13171.72 examples/s]
Generating train split: 89067304 examples [1:30:13, 13906.82 examples/s]
Generating train split: 89069701 examples [1:30:13, 9654.23 examples/s] 
Generating train split: 89071514 examples [1:30:14, 7946.82 examples/s]
Generating train split: 89072924 examples [1:30:14, 8379.88 examples/s]
Generating train split: 89074298 examples [1:30:14, 9048.69 examples/s]
Generating train split: 89079116 examples [1:30:14, 15034.63 examples/s]
Generating train split: 89085958 examples [1:30:14, 24609.16 examples/s]
Generating train split: 89092703 examples [1:30:14, 33306.54 examples/s]
Generating train split: 89097326 examples [1:30:15, 14426.55 examples/s]
Generating train split: 89100742 examples [1:30:16, 8710.81 examples/s] 
Generating train split: 89103255 examples [1:30:16, 7379.31 examples/s]
Generating train split: 89105150 examples [1:30:16, 8173.05 examples/s]
Generating train split: 89106969 examples [1:30:17, 6397.35 examples/s]
Generating train split: 89108347 examples [1:30:17, 5481.56 examples/s]
Generating train split: 89110323 examples [1:30:17, 6757.80 examples/s]
Generating train split: 89111667 examples [1:30:18, 7198.12 examples/s]
Generating train split: 89112901 examples [1:30:18, 5736.11 examples/s]
Generating train split: 89113855 examples [1:30:18, 5784.76 examples/s]
Generating train split: 89114776 examples [1:30:18, 6243.27 examples/s]
Generating train split: 89115641 examples [1:30:19, 4566.24 examples/s]
Generating train split: 89123625 examples [1:30:19, 15136.72 examples/s]
Generating train split: 89133200 examples [1:30:19, 28600.98 examples/s]
Generating train split: 89138080 examples [1:30:20, 15085.80 examples/s]
Generating train split: 89141709 examples [1:30:20, 13236.83 examples/s]
Generating train split: 89144538 examples [1:30:20, 10551.50 examples/s]
Generating train split: 89146705 examples [1:30:21, 9061.23 examples/s] 
Generating train split: 89148386 examples [1:30:21, 8047.15 examples/s]
Generating train split: 89149717 examples [1:30:21, 6745.59 examples/s]
Generating train split: 89152165 examples [1:30:22, 8598.61 examples/s]
Generating train split: 89153629 examples [1:30:22, 9144.22 examples/s]
Generating train split: 89155637 examples [1:30:22, 9716.96 examples/s]
Generating train split: 89156970 examples [1:30:22, 6332.37 examples/s]
Generating train split: 89157978 examples [1:30:23, 5337.24 examples/s]
Generating train split: 89161793 examples [1:30:23, 9396.08 examples/s]
Generating train split: 89171066 examples [1:30:23, 21909.80 examples/s]
Generating train split: 89176486 examples [1:30:23, 27607.61 examples/s]
Generating train split: 89180895 examples [1:30:23, 19405.87 examples/s]
Generating train split: 89184322 examples [1:30:24, 18732.10 examples/s]
Generating train split: 89187228 examples [1:30:24, 14683.65 examples/s]
Generating train split: 89189523 examples [1:30:24, 10732.24 examples/s]
Generating train split: 89191288 examples [1:30:24, 10566.61 examples/s]
Generating train split: 89192814 examples [1:30:25, 9636.90 examples/s] 
Generating train split: 89194098 examples [1:30:25, 7988.81 examples/s]
Generating train split: 89195794 examples [1:30:25, 9231.86 examples/s]
Generating train split: 89197026 examples [1:30:25, 8412.88 examples/s]
Generating train split: 89198077 examples [1:30:26, 6412.31 examples/s]
Generating train split: 89198921 examples [1:30:26, 6340.78 examples/s]
Generating train split: 89200401 examples [1:30:26, 7745.69 examples/s]
Generating train split: 89201384 examples [1:30:26, 5856.38 examples/s]
Generating train split: 89202208 examples [1:30:26, 6100.18 examples/s]
Generating train split: 89204673 examples [1:30:26, 9565.89 examples/s]
Generating train split: 89206454 examples [1:30:26, 11298.53 examples/s]
Generating train split: 89207881 examples [1:30:27, 5852.23 examples/s] 
Generating train split: 89208951 examples [1:30:27, 4467.79 examples/s]
Generating train split: 89209781 examples [1:30:28, 3990.76 examples/s]
Generating train split: 89210457 examples [1:30:28, 4322.95 examples/s]
Generating train split: 89211134 examples [1:30:28, 4184.58 examples/s]
Generating train split: 89212067 examples [1:30:28, 4998.30 examples/s]
Generating train split: 89212751 examples [1:30:28, 4882.43 examples/s]
Generating train split: 89214815 examples [1:30:28, 7939.35 examples/s]
Generating train split: 89215863 examples [1:30:29, 5016.43 examples/s]
Generating train split: 89216682 examples [1:30:29, 5401.55 examples/s]
Generating train split: 89218556 examples [1:30:29, 7778.34 examples/s]
Generating train split: 89219676 examples [1:30:29, 7438.10 examples/s]
Generating train split: 89228051 examples [1:30:29, 22922.36 examples/s]
Generating train split: 89234695 examples [1:30:29, 32687.14 examples/s]
Generating train split: 89238924 examples [1:30:30, 22033.40 examples/s]
Generating train split: 89242263 examples [1:30:30, 14356.60 examples/s]
Generating train split: 89244810 examples [1:30:31, 11395.94 examples/s]
Generating train split: 89246782 examples [1:30:31, 10727.50 examples/s]
Generating train split: 89248430 examples [1:30:31, 7711.43 examples/s] 
Generating train split: 89250292 examples [1:30:31, 8912.32 examples/s]
Generating train split: 89251732 examples [1:30:32, 7566.56 examples/s]
Generating train split: 89252881 examples [1:30:32, 7495.14 examples/s]
Generating train split: 89253905 examples [1:30:32, 7887.75 examples/s]
Generating train split: 89255208 examples [1:30:32, 8784.03 examples/s]
Generating train split: 89256311 examples [1:30:32, 8352.02 examples/s]
Generating train split: 89257302 examples [1:30:32, 7539.77 examples/s]
Generating train split: 89259730 examples [1:30:32, 10936.69 examples/s]
Generating train split: 89261975 examples [1:30:33, 13508.24 examples/s]
Generating train split: 89263579 examples [1:30:33, 9664.30 examples/s] 
Generating train split: 89265290 examples [1:30:33, 11090.69 examples/s]
Generating train split: 89266712 examples [1:30:33, 11058.79 examples/s]
Generating train split: 89268042 examples [1:30:33, 11049.26 examples/s]
Generating train split: 89272889 examples [1:30:33, 19812.87 examples/s]
Generating train split: 89280696 examples [1:30:33, 34413.42 examples/s]
Generating train split: 89285646 examples [1:30:34, 35938.67 examples/s]
Generating train split: 89289606 examples [1:30:34, 24228.81 examples/s]
Generating train split: 89292778 examples [1:30:34, 18582.31 examples/s]
Generating train split: 89295328 examples [1:30:34, 14745.00 examples/s]
Generating train split: 89297366 examples [1:30:35, 13385.00 examples/s]
Generating train split: 89299096 examples [1:30:35, 12516.60 examples/s]
Generating train split: 89300801 examples [1:30:35, 13097.63 examples/s]
Generating train split: 89302323 examples [1:30:35, 9895.32 examples/s] 
Generating train split: 89303552 examples [1:30:36, 6940.27 examples/s]
Generating train split: 89305144 examples [1:30:36, 8181.38 examples/s]
Generating train split: 89306296 examples [1:30:36, 8211.30 examples/s]
Generating train split: 89307359 examples [1:30:36, 6356.15 examples/s]
Generating train split: 89308209 examples [1:30:36, 6389.71 examples/s]
Generating train split: 89310529 examples [1:30:36, 9396.79 examples/s]
Generating train split: 89318598 examples [1:30:37, 23904.89 examples/s]
Generating train split: 89326557 examples [1:30:37, 36030.46 examples/s]
Generating train split: 89331135 examples [1:30:37, 22830.34 examples/s]
Generating train split: 89334706 examples [1:30:38, 13835.94 examples/s]
Generating train split: 89337394 examples [1:30:38, 13519.30 examples/s]
Generating train split: 89339644 examples [1:30:38, 10094.73 examples/s]
Generating train split: 89342149 examples [1:30:38, 11779.52 examples/s]
Generating train split: 89344109 examples [1:30:39, 10712.85 examples/s]
Generating train split: 89347502 examples [1:30:39, 13992.24 examples/s]
Generating train split: 89349644 examples [1:30:39, 12783.21 examples/s]
Generating train split: 89351444 examples [1:30:39, 13545.40 examples/s]
Generating train split: 89353220 examples [1:30:39, 8593.02 examples/s] 
Generating train split: 89354593 examples [1:30:40, 8047.66 examples/s]
Generating train split: 89355742 examples [1:30:40, 7509.01 examples/s]
Generating train split: 89356724 examples [1:30:40, 7618.03 examples/s]
Generating train split: 89358672 examples [1:30:40, 9719.16 examples/s]
Generating train split: 89359906 examples [1:30:40, 6290.27 examples/s]
Generating train split: 89362150 examples [1:30:41, 8711.59 examples/s]
Generating train split: 89363497 examples [1:30:41, 8972.57 examples/s]
Generating train split: 89364727 examples [1:30:41, 9280.59 examples/s]
Generating train split: 89365903 examples [1:30:41, 8434.91 examples/s]
Generating train split: 89367674 examples [1:30:41, 10296.97 examples/s]
Generating train split: 89368918 examples [1:30:41, 9791.22 examples/s] 
Generating train split: 89370051 examples [1:30:42, 6155.19 examples/s]
Generating train split: 89370925 examples [1:30:42, 6534.40 examples/s]
Generating train split: 89372997 examples [1:30:42, 9212.15 examples/s]
Generating train split: 89380775 examples [1:30:42, 23775.09 examples/s]
Generating train split: 89388963 examples [1:30:42, 36735.22 examples/s]
Generating train split: 89393507 examples [1:30:43, 20150.92 examples/s]
Generating train split: 89402082 examples [1:30:43, 30282.22 examples/s]
Generating train split: 89409822 examples [1:30:43, 38016.38 examples/s]
Generating train split: 89415412 examples [1:30:43, 27804.92 examples/s]
Generating train split: 89419814 examples [1:30:43, 20755.97 examples/s]
Generating train split: 89428408 examples [1:30:44, 29618.98 examples/s]
Generating train split: 89433444 examples [1:30:44, 32986.67 examples/s]
Generating train split: 89438436 examples [1:30:44, 19532.77 examples/s]
Generating train split: 89442202 examples [1:30:45, 17538.98 examples/s]
Generating train split: 89445224 examples [1:30:45, 13092.42 examples/s]
Generating train split: 89447543 examples [1:30:46, 9154.78 examples/s] 
Generating train split: 89454926 examples [1:30:46, 15122.32 examples/s]
Generating train split: 89463388 examples [1:30:46, 23215.41 examples/s]
Generating train split: 89468332 examples [1:30:46, 15816.08 examples/s]
Generating train split: 89472041 examples [1:30:46, 17931.91 examples/s]
Generating train split: 89480397 examples [1:30:47, 26552.66 examples/s]
Generating train split: 89487155 examples [1:30:47, 33029.63 examples/s]
Generating train split: 89492718 examples [1:30:48, 14966.33 examples/s]
Generating train split: 89496791 examples [1:30:48, 10647.34 examples/s]
Generating train split: 89499811 examples [1:30:49, 8690.53 examples/s] 
Generating train split: 89502075 examples [1:30:49, 8635.66 examples/s]
Generating train split: 89503913 examples [1:30:49, 9456.30 examples/s]
Generating train split: 89505744 examples [1:30:50, 9396.67 examples/s]
Generating train split: 89507312 examples [1:30:50, 8396.57 examples/s]
Generating train split: 89509470 examples [1:30:50, 9984.94 examples/s]
Generating train split: 89510965 examples [1:30:50, 9439.70 examples/s]
Generating train split: 89512247 examples [1:30:50, 7339.89 examples/s]
Generating train split: 89513438 examples [1:30:51, 7943.16 examples/s]
Generating train split: 89514497 examples [1:30:51, 6760.80 examples/s]
Generating train split: 89515372 examples [1:30:51, 5276.31 examples/s]
Generating train split: 89521254 examples [1:30:51, 13200.44 examples/s]
Generating train split: 89524727 examples [1:30:51, 16956.77 examples/s]
Generating train split: 89527345 examples [1:30:52, 6536.69 examples/s] 
Generating train split: 89529256 examples [1:30:53, 5410.42 examples/s]
Generating train split: 89530695 examples [1:30:54, 4359.69 examples/s]
Generating train split: 89531776 examples [1:30:54, 4755.22 examples/s]
Generating train split: 89532787 examples [1:30:54, 3984.39 examples/s]
Generating train split: 89533566 examples [1:30:54, 3764.22 examples/s]
Generating train split: 89534200 examples [1:30:55, 3505.64 examples/s]
Generating train split: 89534721 examples [1:30:55, 3584.35 examples/s]
Generating train split: 89535493 examples [1:30:55, 4152.96 examples/s]
Generating train split: 89536064 examples [1:30:55, 3136.41 examples/s]
Generating train split: 89536513 examples [1:30:55, 3008.31 examples/s]
Generating train split: 89536908 examples [1:30:55, 3034.66 examples/s]
Generating train split: 89537405 examples [1:30:56, 3374.03 examples/s]
Generating train split: 89537814 examples [1:30:56, 3067.67 examples/s]
Generating train split: 89538254 examples [1:30:56, 3306.21 examples/s]
Generating train split: 89538789 examples [1:30:56, 3450.45 examples/s]
Generating train split: 89539168 examples [1:30:56, 3440.83 examples/s]
Generating train split: 89539818 examples [1:30:56, 4125.14 examples/s]
Generating train split: 89540261 examples [1:30:56, 3887.94 examples/s]
Generating train split: 89544488 examples [1:30:56, 13479.20 examples/s]
Generating train split: 89549252 examples [1:30:57, 22462.94 examples/s]
Generating train split: 89551776 examples [1:30:57, 11488.77 examples/s]
Generating train split: 89553698 examples [1:30:57, 9277.14 examples/s] 
Generating train split: 89559962 examples [1:30:57, 16963.83 examples/s]
Generating train split: 89566660 examples [1:30:58, 25348.87 examples/s]
Generating train split: 89570666 examples [1:30:58, 19820.24 examples/s]
Generating train split: 89573851 examples [1:30:59, 10428.69 examples/s]
Generating train split: 89576205 examples [1:30:59, 11645.89 examples/s]
Generating train split: 89578508 examples [1:30:59, 12036.94 examples/s]
Generating train split: 89580529 examples [1:30:59, 11412.77 examples/s]
Generating train split: 89582445 examples [1:30:59, 12549.26 examples/s]
Generating train split: 89584224 examples [1:30:59, 13005.62 examples/s]
Generating train split: 89592017 examples [1:30:59, 25616.93 examples/s]
Generating train split: 89601114 examples [1:31:00, 39805.91 examples/s]
Generating train split: 89606306 examples [1:31:00, 23392.47 examples/s]
Generating train split: 89610290 examples [1:31:00, 16576.38 examples/s]
Generating train split: 89613333 examples [1:31:01, 11035.39 examples/s]
Generating train split: 89615613 examples [1:31:01, 10394.65 examples/s]
Generating train split: 89617461 examples [1:31:02, 9070.32 examples/s] 
Generating train split: 89618924 examples [1:31:02, 8552.45 examples/s]
Generating train split: 89620156 examples [1:31:02, 8488.44 examples/s]
Generating train split: 89621261 examples [1:31:02, 8591.96 examples/s]
Generating train split: 89622321 examples [1:31:02, 8917.17 examples/s]
Generating train split: 89630330 examples [1:31:02, 22315.84 examples/s]
Generating train split: 89639165 examples [1:31:02, 36307.03 examples/s]
Generating train split: 89644019 examples [1:31:03, 20543.81 examples/s]
Generating train split: 89647716 examples [1:31:03, 17467.93 examples/s]
Generating train split: 89650659 examples [1:31:04, 13006.41 examples/s]
Generating train split: 89652973 examples [1:31:04, 14203.10 examples/s]
Generating train split: 89655256 examples [1:31:04, 10912.96 examples/s]
Generating train split: 89657029 examples [1:31:04, 11157.66 examples/s]
Generating train split: 89658646 examples [1:31:05, 10531.46 examples/s]
Generating train split: 89660958 examples [1:31:05, 12503.54 examples/s]
Generating train split: 89662621 examples [1:31:05, 10648.23 examples/s]
Generating train split: 89665653 examples [1:31:05, 14060.36 examples/s]
Generating train split: 89667529 examples [1:31:05, 12788.70 examples/s]
Generating train split: 89669150 examples [1:31:05, 12725.39 examples/s]
Generating train split: 89670658 examples [1:31:05, 11679.91 examples/s]
Generating train split: 89671988 examples [1:31:06, 9457.06 examples/s] 
Generating train split: 89673367 examples [1:31:06, 10275.55 examples/s]
Generating train split: 89674939 examples [1:31:06, 11434.58 examples/s]
Generating train split: 89676246 examples [1:31:06, 7666.15 examples/s] 
Generating train split: 89677747 examples [1:31:06, 8958.71 examples/s]
Generating train split: 89679108 examples [1:31:06, 9897.85 examples/s]
Generating train split: 89680343 examples [1:31:07, 8648.20 examples/s]
Generating train split: 89681398 examples [1:31:07, 8346.16 examples/s]
Generating train split: 89682368 examples [1:31:07, 8271.98 examples/s]
Generating train split: 89683646 examples [1:31:07, 9271.75 examples/s]
Generating train split: 89684799 examples [1:31:07, 9806.49 examples/s]
Generating train split: 89687066 examples [1:31:07, 13136.75 examples/s]
Generating train split: 89688493 examples [1:31:07, 8815.59 examples/s] 
Generating train split: 89689882 examples [1:31:08, 9837.42 examples/s]
Generating train split: 89691226 examples [1:31:08, 10637.88 examples/s]
Generating train split: 89692487 examples [1:31:08, 9391.10 examples/s] 
Generating train split: 89693586 examples [1:31:08, 9256.81 examples/s]
Generating train split: 89694622 examples [1:31:08, 9128.52 examples/s]
Generating train split: 89697141 examples [1:31:08, 12934.60 examples/s]
Generating train split: 89698571 examples [1:31:08, 11989.13 examples/s]
Generating train split: 89699868 examples [1:31:09, 9337.88 examples/s] 
Generating train split: 89700956 examples [1:31:09, 9388.24 examples/s]
Generating train split: 89702011 examples [1:31:09, 8018.09 examples/s]
Generating train split: 89703164 examples [1:31:09, 8560.64 examples/s]
Generating train split: 89704109 examples [1:31:09, 7993.90 examples/s]
Generating train split: 89704975 examples [1:31:09, 6355.51 examples/s]
Generating train split: 89705968 examples [1:31:09, 7054.75 examples/s]
Generating train split: 89706763 examples [1:31:10, 6333.94 examples/s]
Generating train split: 89707465 examples [1:31:10, 6104.54 examples/s]
Generating train split: 89708130 examples [1:31:10, 5641.50 examples/s]
Generating train split: 89708729 examples [1:31:10, 5018.95 examples/s]
Generating train split: 89709259 examples [1:31:10, 4463.78 examples/s]
Generating train split: 89710137 examples [1:31:10, 5403.50 examples/s]
Generating train split: 89710739 examples [1:31:10, 4332.00 examples/s]
Generating train split: 89714497 examples [1:31:11, 11287.57 examples/s]
Generating train split: 89722385 examples [1:31:11, 26835.20 examples/s]
Generating train split: 89727097 examples [1:31:11, 31453.43 examples/s]
Generating train split: 89730824 examples [1:31:11, 14694.81 examples/s]
Generating train split: 89733632 examples [1:31:12, 10046.43 examples/s]
Generating train split: 89735742 examples [1:31:12, 11115.77 examples/s]
Generating train split: 89737797 examples [1:31:12, 8730.91 examples/s] 
Generating train split: 89739382 examples [1:31:13, 9358.51 examples/s]
Generating train split: 89740892 examples [1:31:13, 7028.82 examples/s]
Generating train split: 89742826 examples [1:31:13, 8540.13 examples/s]
Generating train split: 89744220 examples [1:31:13, 8071.24 examples/s]
Generating train split: 89745402 examples [1:31:14, 6969.98 examples/s]
Generating train split: 89746642 examples [1:31:14, 7791.69 examples/s]
Generating train split: 89747948 examples [1:31:14, 8714.60 examples/s]
Generating train split: 89749070 examples [1:31:14, 6630.73 examples/s]
Generating train split: 89750445 examples [1:31:14, 7820.98 examples/s]
Generating train split: 89751696 examples [1:31:14, 8742.67 examples/s]
Generating train split: 89753035 examples [1:31:14, 9735.73 examples/s]
Generating train split: 89754208 examples [1:31:15, 6301.55 examples/s]
Generating train split: 89755853 examples [1:31:15, 8004.93 examples/s]
Generating train split: 89757006 examples [1:31:15, 8335.63 examples/s]
Generating train split: 89758072 examples [1:31:15, 5286.83 examples/s]
Generating train split: 89759778 examples [1:31:15, 6863.40 examples/s]
Generating train split: 89760774 examples [1:31:16, 6561.14 examples/s]
Generating train split: 89761956 examples [1:31:16, 7495.16 examples/s]
Generating train split: 89763030 examples [1:31:16, 8161.33 examples/s]
Generating train split: 89765604 examples [1:31:16, 12150.78 examples/s]
Generating train split: 89767078 examples [1:31:16, 9144.94 examples/s] 
Generating train split: 89768279 examples [1:31:16, 8271.89 examples/s]
Generating train split: 89769688 examples [1:31:17, 9376.00 examples/s]
Generating train split: 89771035 examples [1:31:17, 9859.87 examples/s]
Generating train split: 89772688 examples [1:31:17, 11394.63 examples/s]
Generating train split: 89773990 examples [1:31:17, 9009.25 examples/s] 
Generating train split: 89776327 examples [1:31:17, 12039.84 examples/s]
Generating train split: 89777782 examples [1:31:17, 9885.48 examples/s] 
Generating train split: 89779008 examples [1:31:17, 8575.98 examples/s]
Generating train split: 89781068 examples [1:31:18, 10927.94 examples/s]
Generating train split: 89782414 examples [1:31:18, 8384.98 examples/s] 
Generating train split: 89783887 examples [1:31:18, 9554.57 examples/s]
Generating train split: 89785091 examples [1:31:18, 10003.35 examples/s]
Generating train split: 89786282 examples [1:31:18, 6833.95 examples/s] 
Generating train split: 89787994 examples [1:31:18, 8646.03 examples/s]
Generating train split: 89789169 examples [1:31:19, 8854.75 examples/s]
Generating train split: 89790278 examples [1:31:19, 5344.31 examples/s]
Generating train split: 89791194 examples [1:31:19, 5915.13 examples/s]
Generating train split: 89793061 examples [1:31:19, 8157.53 examples/s]
Generating train split: 89794231 examples [1:31:19, 6802.85 examples/s]
Generating train split: 89795563 examples [1:31:20, 7823.26 examples/s]
Generating train split: 89796595 examples [1:31:20, 5938.99 examples/s]
Generating train split: 89797420 examples [1:31:20, 5611.43 examples/s]
Generating train split: 89799200 examples [1:31:20, 7773.08 examples/s]
Generating train split: 89801618 examples [1:31:20, 11078.06 examples/s]
Generating train split: 89803068 examples [1:31:20, 11626.54 examples/s]
Generating train split: 89804483 examples [1:31:21, 8838.61 examples/s] 
Generating train split: 89805891 examples [1:31:21, 9872.97 examples/s]
Generating train split: 89807928 examples [1:31:21, 12111.50 examples/s]
Generating train split: 89809390 examples [1:31:21, 11837.16 examples/s]
Generating train split: 89810746 examples [1:31:21, 10017.81 examples/s]
Generating train split: 89811912 examples [1:31:21, 8676.48 examples/s] 
Generating train split: 89820061 examples [1:31:21, 23797.46 examples/s]
Generating train split: 89828617 examples [1:31:22, 37928.45 examples/s]
Generating train split: 89833387 examples [1:31:22, 18282.16 examples/s]
Generating train split: 89840971 examples [1:31:22, 26197.69 examples/s]
Generating train split: 89849742 examples [1:31:22, 36295.23 examples/s]
Generating train split: 89855724 examples [1:31:23, 21683.79 examples/s]
Generating train split: 89860235 examples [1:31:23, 18926.87 examples/s]
Generating train split: 89863793 examples [1:31:24, 15225.96 examples/s]
Generating train split: 89866796 examples [1:31:24, 16865.79 examples/s]
Generating train split: 89869621 examples [1:31:24, 14930.04 examples/s]
Generating train split: 89878271 examples [1:31:24, 24773.71 examples/s]
Generating train split: 89886981 examples [1:31:24, 34506.05 examples/s]
Generating train split: 89892319 examples [1:31:25, 20868.63 examples/s]
Generating train split: 89896355 examples [1:31:25, 17283.54 examples/s]
Generating train split: 89899501 examples [1:31:26, 11537.68 examples/s]
Generating train split: 89901860 examples [1:31:26, 11002.05 examples/s]
Generating train split: 89903776 examples [1:31:26, 10190.05 examples/s]
Generating train split: 89905342 examples [1:31:26, 10065.45 examples/s]
Generating train split: 89906722 examples [1:31:27, 10421.34 examples/s]
Generating train split: 89908070 examples [1:31:27, 8858.28 examples/s] 
Generating train split: 89909890 examples [1:31:27, 10173.89 examples/s]
Generating train split: 89911177 examples [1:31:27, 9151.66 examples/s] 
Generating train split: 89912279 examples [1:31:27, 8606.51 examples/s]
Generating train split: 89913265 examples [1:31:28, 7185.91 examples/s]
Generating train split: 89914083 examples [1:31:28, 5758.61 examples/s]
Generating train split: 89914758 examples [1:31:28, 5439.55 examples/s]
Generating train split: 89915370 examples [1:31:28, 5231.92 examples/s]
Generating train split: 89916498 examples [1:31:28, 6304.81 examples/s]
Generating train split: 89917212 examples [1:31:28, 4477.53 examples/s]
Generating train split: 89917776 examples [1:31:29, 4406.14 examples/s]
Generating train split: 89918301 examples [1:31:29, 3797.78 examples/s]
Generating train split: 89918744 examples [1:31:29, 3182.49 examples/s]
Generating train split: 89919117 examples [1:31:29, 3058.98 examples/s]
Generating train split: 89919969 examples [1:31:29, 4097.10 examples/s]
Generating train split: 89920469 examples [1:31:29, 4104.70 examples/s]
Generating train split: 89920944 examples [1:31:30, 2936.14 examples/s]
Generating train split: 89922530 examples [1:31:30, 5288.29 examples/s]
Generating train split: 89923714 examples [1:31:30, 6581.63 examples/s]
Generating train split: 89924964 examples [1:31:30, 7913.02 examples/s]
Generating train split: 89926284 examples [1:31:30, 9096.19 examples/s]
Generating train split: 89927355 examples [1:31:30, 5978.26 examples/s]
Generating train split: 89928194 examples [1:31:31, 5946.36 examples/s]
Generating train split: 89928961 examples [1:31:31, 4916.86 examples/s]
Generating train split: 89930366 examples [1:31:31, 6525.00 examples/s]
Generating train split: 89931213 examples [1:31:31, 6792.40 examples/s]
Generating train split: 89932523 examples [1:31:31, 8192.15 examples/s]
Generating train split: 89933504 examples [1:31:31, 6793.99 examples/s]
Generating train split: 89934327 examples [1:31:32, 5980.86 examples/s]
Generating train split: 89936569 examples [1:31:32, 9256.33 examples/s]
Generating train split: 89937907 examples [1:31:32, 10175.88 examples/s]
Generating train split: 89939107 examples [1:31:32, 6184.42 examples/s] 
Generating train split: 89940039 examples [1:31:32, 6153.63 examples/s]
Generating train split: 89940877 examples [1:31:32, 5524.95 examples/s]
Generating train split: 89942097 examples [1:31:33, 6707.19 examples/s]
Generating train split: 89942955 examples [1:31:33, 5125.76 examples/s]
Generating train split: 89944253 examples [1:31:33, 6476.63 examples/s]
Generating train split: 89945743 examples [1:31:33, 8146.37 examples/s]
Generating train split: 89947275 examples [1:31:33, 9643.08 examples/s]
Generating train split: 89949085 examples [1:31:33, 11647.17 examples/s]
Generating train split: 89950455 examples [1:31:33, 11425.58 examples/s]
Generating train split: 89951743 examples [1:31:34, 8716.14 examples/s] 
Generating train split: 89952963 examples [1:31:34, 9424.92 examples/s]
Generating train split: 89954074 examples [1:31:34, 7337.52 examples/s]
Generating train split: 89954994 examples [1:31:34, 7577.34 examples/s]
Generating train split: 89956277 examples [1:31:34, 8532.09 examples/s]
Generating train split: 89957408 examples [1:31:34, 9141.00 examples/s]
Generating train split: 89958431 examples [1:31:35, 7311.93 examples/s]
Generating train split: 89959290 examples [1:31:35, 6434.16 examples/s]
Generating train split: 89961841 examples [1:31:35, 10348.15 examples/s]
Generating train split: 89963115 examples [1:31:35, 8258.85 examples/s] 
Generating train split: 89964334 examples [1:31:35, 8949.31 examples/s]
Generating train split: 89965414 examples [1:31:35, 7411.33 examples/s]
Generating train split: 89966616 examples [1:31:35, 8321.06 examples/s]
Generating train split: 89967618 examples [1:31:36, 5972.09 examples/s]
Generating train split: 89968411 examples [1:31:36, 5683.23 examples/s]
Generating train split: 89969129 examples [1:31:36, 5925.74 examples/s]
Generating train split: 89969963 examples [1:31:36, 6331.53 examples/s]
Generating train split: 89970691 examples [1:31:36, 5779.72 examples/s]
Generating train split: 89971457 examples [1:31:36, 5967.97 examples/s]
Generating train split: 89972461 examples [1:31:37, 6884.43 examples/s]
Generating train split: 89973478 examples [1:31:37, 7626.67 examples/s]
Generating train split: 89974735 examples [1:31:37, 8618.52 examples/s]
Generating train split: 89975640 examples [1:31:37, 5910.88 examples/s]
Generating train split: 89976374 examples [1:31:37, 4700.87 examples/s]
Generating train split: 89976987 examples [1:31:37, 4865.22 examples/s]
Generating train split: 89978461 examples [1:31:38, 6826.76 examples/s]
Generating train split: 89979307 examples [1:31:38, 3426.32 examples/s]
Generating train split: 89979940 examples [1:31:38, 3459.07 examples/s]
Generating train split: 89981018 examples [1:31:38, 4501.40 examples/s]
Generating train split: 89981716 examples [1:31:39, 4322.47 examples/s]
Generating train split: 89982323 examples [1:31:39, 4511.22 examples/s]
Generating train split: 89982906 examples [1:31:39, 3924.31 examples/s]
Generating train split: 89985045 examples [1:31:39, 7202.15 examples/s]
Generating train split: 89986027 examples [1:31:39, 7370.45 examples/s]
Generating train split: 89993583 examples [1:31:39, 22595.25 examples/s]
Generating train split: 90002696 examples [1:31:39, 39169.26 examples/s]
Generating train split: 90007471 examples [1:31:40, 24891.43 examples/s]
Generating train split: 90011216 examples [1:31:40, 13330.09 examples/s]
Generating train split: 90014011 examples [1:31:41, 12974.09 examples/s]
Generating train split: 90016320 examples [1:31:41, 12627.86 examples/s]
Generating train split: 90018285 examples [1:31:41, 10520.38 examples/s]
Generating train split: 90019845 examples [1:31:41, 9943.65 examples/s] 
Generating train split: 90021176 examples [1:31:42, 8157.97 examples/s]
Generating train split: 90024324 examples [1:31:42, 11330.37 examples/s]
Generating train split: 90026007 examples [1:31:42, 9849.62 examples/s] 
Generating train split: 90027393 examples [1:31:42, 10359.69 examples/s]
Generating train split: 90029413 examples [1:31:42, 11985.64 examples/s]
Generating train split: 90030930 examples [1:31:42, 11945.57 examples/s]
Generating train split: 90032343 examples [1:31:43, 7519.91 examples/s] 
Generating train split: 90033444 examples [1:31:43, 7179.23 examples/s]
Generating train split: 90035176 examples [1:31:43, 8853.23 examples/s]
Generating train split: 90036357 examples [1:31:43, 7211.28 examples/s]
Generating train split: 90037322 examples [1:31:43, 6850.37 examples/s]
Generating train split: 90038171 examples [1:31:44, 6701.77 examples/s]
Generating train split: 90039550 examples [1:31:44, 7938.12 examples/s]
Generating train split: 90040485 examples [1:31:44, 7562.63 examples/s]
Generating train split: 90041343 examples [1:31:44, 3381.15 examples/s]
Generating train split: 90042298 examples [1:31:45, 4100.28 examples/s]
Generating train split: 90043017 examples [1:31:45, 2911.51 examples/s]
Generating train split: 90043561 examples [1:31:45, 3171.36 examples/s]
Generating train split: 90044093 examples [1:31:46, 2365.13 examples/s]
Generating train split: 90044507 examples [1:31:46, 2201.61 examples/s]
Generating train split: 90044846 examples [1:31:46, 1942.99 examples/s]
Generating train split: 90045276 examples [1:31:46, 2205.12 examples/s]
Generating train split: 90045593 examples [1:31:46, 2354.01 examples/s]
Generating train split: 90046261 examples [1:31:46, 3133.78 examples/s]
Generating train split: 90046675 examples [1:31:47, 3326.37 examples/s]
Generating train split: 90047090 examples [1:31:47, 3358.39 examples/s]
Generating train split: 90053406 examples [1:31:47, 17483.93 examples/s]
Generating train split: 90062336 examples [1:31:47, 35593.69 examples/s]
Generating train split: 90066531 examples [1:31:47, 35021.25 examples/s]
Generating train split: 90070484 examples [1:31:48, 14065.22 examples/s]
Generating train split: 90073433 examples [1:31:48, 10629.20 examples/s]
Generating train split: 90075674 examples [1:31:49, 7772.72 examples/s] 
Generating train split: 90077363 examples [1:31:49, 7365.24 examples/s]
Generating train split: 90078716 examples [1:31:50, 5864.12 examples/s]
Generating train split: 90079763 examples [1:31:50, 4693.21 examples/s]
Generating train split: 90080555 examples [1:31:50, 4511.99 examples/s]
Generating train split: 90081220 examples [1:31:50, 4092.46 examples/s]
Generating train split: 90081828 examples [1:31:51, 4320.62 examples/s]
Generating train split: 90082392 examples [1:31:51, 4339.32 examples/s]
Generating train split: 90082929 examples [1:31:51, 4168.56 examples/s]
Generating train split: 90083410 examples [1:31:51, 4112.39 examples/s]
Generating train split: 90084177 examples [1:31:51, 4738.14 examples/s]
Generating train split: 90085220 examples [1:31:51, 5963.95 examples/s]
Generating train split: 90085908 examples [1:31:51, 4693.80 examples/s]
Generating train split: 90087103 examples [1:31:51, 6167.77 examples/s]
Generating train split: 90088347 examples [1:31:52, 7571.09 examples/s]
Generating train split: 90090037 examples [1:31:52, 9770.39 examples/s]
Generating train split: 90091159 examples [1:31:52, 8638.05 examples/s]
Generating train split: 90092148 examples [1:31:52, 8675.67 examples/s]
Generating train split: 90093116 examples [1:31:52, 8924.38 examples/s]
Generating train split: 90095045 examples [1:31:52, 11630.51 examples/s]
Generating train split: 90096293 examples [1:31:52, 11812.00 examples/s]
Generating train split: 90097552 examples [1:31:52, 10437.92 examples/s]
Generating train split: 90099735 examples [1:31:53, 13088.50 examples/s]
Generating train split: 90101122 examples [1:31:53, 10676.40 examples/s]
Generating train split: 90102318 examples [1:31:53, 10157.99 examples/s]
Generating train split: 90103422 examples [1:31:53, 8788.02 examples/s] 
Generating train split: 90104380 examples [1:31:53, 8546.48 examples/s]
Generating train split: 90105497 examples [1:31:53, 9046.46 examples/s]
Generating train split: 90106450 examples [1:31:53, 8481.62 examples/s]
Generating train split: 90108955 examples [1:31:54, 12309.78 examples/s]
Generating train split: 90110275 examples [1:31:54, 9750.69 examples/s] 
Generating train split: 90111386 examples [1:31:54, 9572.71 examples/s]
Generating train split: 90112432 examples [1:31:54, 9625.84 examples/s]
Generating train split: 90113459 examples [1:31:54, 8722.34 examples/s]
Generating train split: 90114386 examples [1:31:54, 8144.00 examples/s]
Generating train split: 90116941 examples [1:31:54, 12289.86 examples/s]
Generating train split: 90118322 examples [1:31:55, 8171.56 examples/s] 
Generating train split: 90119416 examples [1:31:55, 7808.74 examples/s]
Generating train split: 90121069 examples [1:31:55, 9296.95 examples/s]
Generating train split: 90122199 examples [1:31:55, 7680.70 examples/s]
Generating train split: 90123134 examples [1:31:55, 6847.59 examples/s]
Generating train split: 90124523 examples [1:31:55, 8139.26 examples/s]
Generating train split: 90125508 examples [1:31:56, 8270.90 examples/s]
Generating train split: 90126491 examples [1:31:56, 8595.54 examples/s]
Generating train split: 90127443 examples [1:31:56, 5955.83 examples/s]
Generating train split: 90128240 examples [1:31:56, 6332.58 examples/s]
Generating train split: 90129010 examples [1:31:56, 6514.49 examples/s]
Generating train split: 90130881 examples [1:31:56, 9065.18 examples/s]
Generating train split: 90133258 examples [1:31:56, 12456.16 examples/s]
Generating train split: 90134648 examples [1:31:57, 11144.13 examples/s]
Generating train split: 90135889 examples [1:31:57, 9213.98 examples/s] 
Generating train split: 90137440 examples [1:31:57, 10576.25 examples/s]
Generating train split: 90139656 examples [1:31:57, 13262.28 examples/s]
Generating train split: 90141156 examples [1:31:57, 7694.87 examples/s] 
Generating train split: 90142792 examples [1:31:57, 9143.45 examples/s]
Generating train split: 90144100 examples [1:31:58, 7597.74 examples/s]
Generating train split: 90145172 examples [1:31:58, 6730.77 examples/s]
Generating train split: 90146405 examples [1:31:58, 7586.64 examples/s]
Generating train split: 90148025 examples [1:31:58, 9259.21 examples/s]
Generating train split: 90149187 examples [1:31:58, 8242.84 examples/s]
Generating train split: 90152212 examples [1:31:58, 12736.42 examples/s]
Generating train split: 90153809 examples [1:31:59, 9080.21 examples/s] 
Generating train split: 90155074 examples [1:31:59, 8077.29 examples/s]
Generating train split: 90156148 examples [1:31:59, 7801.62 examples/s]
Generating train split: 90157809 examples [1:31:59, 9394.98 examples/s]
Generating train split: 90159016 examples [1:31:59, 9930.97 examples/s]
Generating train split: 90160180 examples [1:32:00, 6345.26 examples/s]
Generating train split: 90161089 examples [1:32:00, 5869.65 examples/s]
Generating train split: 90162519 examples [1:32:00, 7313.46 examples/s]
Generating train split: 90165288 examples [1:32:00, 11302.45 examples/s]
Generating train split: 90166802 examples [1:32:00, 10383.28 examples/s]
Generating train split: 90170852 examples [1:32:00, 16738.20 examples/s]
Generating train split: 90177508 examples [1:32:00, 28276.72 examples/s]
Generating train split: 90181914 examples [1:32:01, 32198.00 examples/s]
Generating train split: 90188831 examples [1:32:01, 41860.97 examples/s]
Generating train split: 90195262 examples [1:32:01, 47967.43 examples/s]
Generating train split: 90201926 examples [1:32:01, 53187.92 examples/s]
Generating train split: 90209358 examples [1:32:01, 59200.14 examples/s]
Generating train split: 90216504 examples [1:32:01, 62740.69 examples/s]
Generating train split: 90222989 examples [1:32:01, 62960.53 examples/s]
Generating train split: 90229432 examples [1:32:01, 62835.46 examples/s]
Generating train split: 90236077 examples [1:32:01, 63884.20 examples/s]
Generating train split: 90244005 examples [1:32:01, 68399.06 examples/s]
Generating train split: 90250917 examples [1:32:02, 68534.50 examples/s]
Generating train split: 90258333 examples [1:32:02, 70199.81 examples/s]
Generating train split: 90265398 examples [1:32:02, 70123.34 examples/s]
Generating train split: 90272440 examples [1:32:02, 64064.97 examples/s]
Generating train split: 90279328 examples [1:32:02, 65399.02 examples/s]
Generating train split: 90285969 examples [1:32:02, 63067.98 examples/s]
Generating train split: 90292359 examples [1:32:02, 63107.71 examples/s]
Generating train split: 90300052 examples [1:32:02, 67052.28 examples/s]
Generating train split: 90307100 examples [1:32:02, 68026.76 examples/s]
Generating train split: 90313962 examples [1:32:03, 65922.75 examples/s]
Generating train split: 90321889 examples [1:32:03, 69748.20 examples/s]
Generating train split: 90329487 examples [1:32:03, 71510.25 examples/s]
Generating train split: 90336674 examples [1:32:03, 70229.68 examples/s]
Generating train split: 90343733 examples [1:32:03, 68580.91 examples/s]
Generating train split: 90350626 examples [1:32:03, 63564.00 examples/s]
Generating train split: 90357067 examples [1:32:03, 63270.47 examples/s]
Generating train split: 90363453 examples [1:32:03, 57114.04 examples/s]
Generating train split: 90369295 examples [1:32:03, 52532.43 examples/s]
Generating train split: 90374683 examples [1:32:04, 40367.64 examples/s]
Generating train split: 90379188 examples [1:32:04, 40501.86 examples/s]
Generating train split: 90383573 examples [1:32:04, 33667.01 examples/s]
Generating train split: 90387310 examples [1:32:04, 25421.38 examples/s]
Generating train split: 90390355 examples [1:32:04, 22772.76 examples/s]
Generating train split: 90392976 examples [1:32:05, 19262.26 examples/s]
Generating train split: 90395184 examples [1:32:05, 15442.73 examples/s]
Generating train split: 90396981 examples [1:32:05, 14455.40 examples/s]
Generating train split: 90398583 examples [1:32:05, 10045.83 examples/s]
Generating train split: 90400202 examples [1:32:06, 10919.90 examples/s]
Generating train split: 90401557 examples [1:32:06, 9864.18 examples/s] 
Generating train split: 90402733 examples [1:32:06, 9883.21 examples/s]
Generating train split: 90403848 examples [1:32:06, 9799.53 examples/s]
Generating train split: 90405002 examples [1:32:06, 10145.84 examples/s]
Generating train split: 90406394 examples [1:32:06, 11025.24 examples/s]
Generating train split: 90407586 examples [1:32:06, 11155.83 examples/s]
Generating train split: 90409180 examples [1:32:06, 12328.64 examples/s]
Generating train split: 90410952 examples [1:32:06, 13711.09 examples/s]
Generating train split: 90412448 examples [1:32:07, 13969.26 examples/s]
Generating train split: 90413898 examples [1:32:07, 12291.06 examples/s]
Generating train split: 90416484 examples [1:32:07, 15821.26 examples/s]
Generating train split: 90418174 examples [1:32:07, 11407.45 examples/s]
Generating train split: 90419556 examples [1:32:07, 11845.90 examples/s]
Generating train split: 90420923 examples [1:32:07, 10058.61 examples/s]
Generating train split: 90428776 examples [1:32:07, 24775.54 examples/s]
Generating train split: 90436582 examples [1:32:08, 37232.85 examples/s]
Generating train split: 90441145 examples [1:32:08, 26957.73 examples/s]
Generating train split: 90444822 examples [1:32:08, 18113.55 examples/s]
Generating train split: 90447673 examples [1:32:08, 16315.41 examples/s]
Generating train split: 90450027 examples [1:32:09, 17251.27 examples/s]
Generating train split: 90452339 examples [1:32:09, 14842.80 examples/s]
Generating train split: 90454265 examples [1:32:09, 11803.38 examples/s]
Generating train split: 90455814 examples [1:32:09, 9951.33 examples/s] 
Generating train split: 90457074 examples [1:32:10, 9546.47 examples/s]
Generating train split: 90458207 examples [1:32:10, 6690.29 examples/s]
Generating train split: 90459310 examples [1:32:10, 7288.81 examples/s]
Generating train split: 90460685 examples [1:32:10, 8321.29 examples/s]
Generating train split: 90461751 examples [1:32:10, 5791.36 examples/s]
Generating train split: 90463417 examples [1:32:11, 7408.05 examples/s]
Generating train split: 90465151 examples [1:32:11, 9146.24 examples/s]
Generating train split: 90466411 examples [1:32:11, 5957.01 examples/s]
Generating train split: 90467890 examples [1:32:11, 7270.15 examples/s]
Generating train split: 90470173 examples [1:32:11, 9989.96 examples/s]
Generating train split: 90471649 examples [1:32:11, 10071.31 examples/s]
Generating train split: 90473437 examples [1:32:12, 11684.04 examples/s]
Generating train split: 90474907 examples [1:32:12, 9433.10 examples/s] 
Generating train split: 90482489 examples [1:32:12, 22687.60 examples/s]
Generating train split: 90490361 examples [1:32:12, 34881.80 examples/s]
Generating train split: 90494841 examples [1:32:13, 15746.50 examples/s]
Generating train split: 90498178 examples [1:32:14, 8740.26 examples/s] 
Generating train split: 90500634 examples [1:32:14, 6853.34 examples/s]
Generating train split: 90502456 examples [1:32:15, 5826.94 examples/s]
Generating train split: 90503843 examples [1:32:16, 4319.81 examples/s]
Generating train split: 90504882 examples [1:32:16, 3400.96 examples/s]
Generating train split: 90506483 examples [1:32:16, 4200.90 examples/s]
Generating train split: 90507813 examples [1:32:16, 4953.83 examples/s]
Generating train split: 90508926 examples [1:32:17, 4386.54 examples/s]
Generating train split: 90509790 examples [1:32:17, 4530.88 examples/s]
Generating train split: 90511178 examples [1:32:17, 5688.89 examples/s]
Generating train split: 90512128 examples [1:32:17, 4886.74 examples/s]
Generating train split: 90512891 examples [1:32:18, 3167.39 examples/s]
Generating train split: 90514180 examples [1:32:18, 4223.38 examples/s]
Generating train split: 90514965 examples [1:32:18, 3497.75 examples/s]
Generating train split: 90515689 examples [1:32:18, 3945.32 examples/s]
Generating train split: 90516335 examples [1:32:19, 3161.05 examples/s]
Generating train split: 90516886 examples [1:32:19, 3454.79 examples/s]
Generating train split: 90517405 examples [1:32:19, 3634.03 examples/s]
Generating train split: 90517902 examples [1:32:19, 3660.37 examples/s]
Generating train split: 90518369 examples [1:32:19, 3028.18 examples/s]
Generating train split: 90519864 examples [1:32:20, 5193.60 examples/s]
Generating train split: 90520580 examples [1:32:20, 5121.01 examples/s]
Generating train split: 90521234 examples [1:32:20, 3680.49 examples/s]
Generating train split: 90522756 examples [1:32:20, 5646.04 examples/s]
Generating train split: 90523580 examples [1:32:20, 5714.93 examples/s]
Generating train split: 90524666 examples [1:32:20, 6604.10 examples/s]
Generating train split: 90525484 examples [1:32:21, 5604.30 examples/s]
Generating train split: 90526181 examples [1:32:21, 4733.43 examples/s]
Generating train split: 90526763 examples [1:32:21, 4396.90 examples/s]
Generating train split: 90527286 examples [1:32:21, 4535.66 examples/s]
Generating train split: 90531849 examples [1:32:21, 13442.10 examples/s]
Generating train split: 90540037 examples [1:32:21, 29621.04 examples/s]
Generating train split: 90545832 examples [1:32:21, 36681.89 examples/s]
Generating train split: 90550122 examples [1:32:22, 23673.79 examples/s]
Generating train split: 90553521 examples [1:32:23, 9372.58 examples/s] 
Generating train split: 90559313 examples [1:32:23, 13740.72 examples/s]
Generating train split: 90567073 examples [1:32:23, 21012.83 examples/s]
Generating train split: 90571841 examples [1:32:23, 16376.51 examples/s]
Generating train split: 90575476 examples [1:32:24, 13342.11 examples/s]
Generating train split: 90578271 examples [1:32:24, 10446.81 examples/s]
Generating train split: 90580391 examples [1:32:25, 7931.99 examples/s] 
Generating train split: 90582226 examples [1:32:25, 8827.70 examples/s]
Generating train split: 90583889 examples [1:32:25, 8026.63 examples/s]
Generating train split: 90585227 examples [1:32:25, 7650.22 examples/s]
Generating train split: 90586927 examples [1:32:26, 8821.11 examples/s]
Generating train split: 90588221 examples [1:32:26, 4520.31 examples/s]
Generating train split: 90589181 examples [1:32:27, 4705.72 examples/s]
Generating train split: 90590467 examples [1:32:27, 5585.18 examples/s]
Generating train split: 90591422 examples [1:32:27, 4510.26 examples/s]
Generating train split: 90593293 examples [1:32:27, 6306.05 examples/s]
Generating train split: 90594375 examples [1:32:27, 5138.79 examples/s]
Generating train split: 90595227 examples [1:32:28, 5344.42 examples/s]
Generating train split: 90596013 examples [1:32:28, 5675.11 examples/s]
Generating train split: 90597008 examples [1:32:28, 6293.13 examples/s]
Generating train split: 90597815 examples [1:32:28, 5518.94 examples/s]
Generating train split: 90598588 examples [1:32:28, 5926.31 examples/s]
Generating train split: 90600857 examples [1:32:28, 9550.87 examples/s]
Generating train split: 90608544 examples [1:32:28, 25440.33 examples/s]
Generating train split: 90615059 examples [1:32:28, 35350.42 examples/s]
Generating train split: 90619181 examples [1:32:29, 14927.50 examples/s]
Generating train split: 90622263 examples [1:32:30, 8426.46 examples/s] 
Generating train split: 90624522 examples [1:32:30, 7735.13 examples/s]
Generating train split: 90626766 examples [1:32:30, 9047.48 examples/s]
Generating train split: 90628673 examples [1:32:31, 8606.59 examples/s]
Generating train split: 90630224 examples [1:32:31, 6589.58 examples/s]
Generating train split: 90631413 examples [1:32:31, 7133.89 examples/s]
Generating train split: 90632600 examples [1:32:32, 6508.90 examples/s]
Generating train split: 90633574 examples [1:32:32, 5209.14 examples/s]
Generating train split: 90641334 examples [1:32:32, 14459.71 examples/s]
Generating train split: 90649763 examples [1:32:32, 25235.62 examples/s]
Generating train split: 90654297 examples [1:32:32, 23750.75 examples/s]
Generating train split: 90658106 examples [1:32:33, 19804.98 examples/s]
Generating train split: 90661175 examples [1:32:33, 17268.30 examples/s]
Generating train split: 90663993 examples [1:32:33, 18942.98 examples/s]
Generating train split: 90666588 examples [1:32:33, 15550.31 examples/s]
Generating train split: 90668698 examples [1:32:34, 11505.39 examples/s]
Generating train split: 90670937 examples [1:32:34, 13045.30 examples/s]
Generating train split: 90672816 examples [1:32:34, 14002.43 examples/s]
Generating train split: 90674900 examples [1:32:34, 15289.46 examples/s]
Generating train split: 90676820 examples [1:32:34, 13848.34 examples/s]
Generating train split: 90678494 examples [1:32:34, 12998.84 examples/s]
Generating train split: 90679989 examples [1:32:34, 9319.09 examples/s] 
Generating train split: 90681871 examples [1:32:35, 10971.20 examples/s]
Generating train split: 90683273 examples [1:32:35, 8283.41 examples/s] 
Generating train split: 90684789 examples [1:32:35, 9431.97 examples/s]
Generating train split: 90686029 examples [1:32:35, 8768.51 examples/s]
Generating train split: 90688749 examples [1:32:35, 12360.87 examples/s]
Generating train split: 90690320 examples [1:32:35, 11380.70 examples/s]
Generating train split: 90691707 examples [1:32:36, 9935.98 examples/s] 
Generating train split: 90692897 examples [1:32:36, 8926.46 examples/s]
Generating train split: 90693933 examples [1:32:36, 8157.99 examples/s]
Generating train split: 90694850 examples [1:32:36, 7756.59 examples/s]
Generating train split: 90696164 examples [1:32:36, 8730.01 examples/s]
Generating train split: 90697114 examples [1:32:36, 8845.03 examples/s]
Generating train split: 90704569 examples [1:32:36, 24924.97 examples/s]
Generating train split: 90713971 examples [1:32:37, 42823.53 examples/s]
Generating train split: 90718820 examples [1:32:37, 20716.55 examples/s]
Generating train split: 90722501 examples [1:32:37, 19914.57 examples/s]
Generating train split: 90725605 examples [1:32:38, 15417.94 examples/s]
Generating train split: 90728045 examples [1:32:38, 14677.03 examples/s]
Generating train split: 90730127 examples [1:32:38, 10844.89 examples/s]
Generating train split: 90731745 examples [1:32:38, 10945.88 examples/s]
Generating train split: 90733531 examples [1:32:38, 11948.25 examples/s]
Generating train split: 90735090 examples [1:32:39, 11429.73 examples/s]
Generating train split: 90736483 examples [1:32:39, 8697.43 examples/s] 
Generating train split: 90738179 examples [1:32:39, 10026.02 examples/s]
Generating train split: 90739474 examples [1:32:39, 8047.73 examples/s] 
Generating train split: 90740521 examples [1:32:39, 7254.53 examples/s]
Generating train split: 90741418 examples [1:32:40, 6427.31 examples/s]
Generating train split: 90742443 examples [1:32:40, 7044.96 examples/s]
Generating train split: 90743575 examples [1:32:40, 7868.23 examples/s]
Generating train split: 90744731 examples [1:32:40, 8628.38 examples/s]
Generating train split: 90745723 examples [1:32:40, 8388.04 examples/s]
Generating train split: 90753205 examples [1:32:40, 24433.04 examples/s]
Generating train split: 90762442 examples [1:32:40, 41857.41 examples/s]
Generating train split: 90767237 examples [1:32:41, 27961.33 examples/s]
Generating train split: 90771069 examples [1:32:41, 15696.32 examples/s]
Generating train split: 90773957 examples [1:32:42, 11947.50 examples/s]
Generating train split: 90776170 examples [1:32:42, 11546.05 examples/s]
Generating train split: 90778018 examples [1:32:42, 10253.50 examples/s]
Generating train split: 90779528 examples [1:32:42, 9573.06 examples/s] 
Generating train split: 90780805 examples [1:32:42, 9386.71 examples/s]
Generating train split: 90781953 examples [1:32:43, 8419.38 examples/s]
Generating train split: 90783011 examples [1:32:43, 8752.67 examples/s]
Generating train split: 90784015 examples [1:32:43, 8451.70 examples/s]
Generating train split: 90786180 examples [1:32:43, 11005.16 examples/s]
Generating train split: 90787451 examples [1:32:43, 8676.69 examples/s] 
Generating train split: 90788506 examples [1:32:43, 8942.40 examples/s]
Generating train split: 90789540 examples [1:32:43, 8944.60 examples/s]
Generating train split: 90790543 examples [1:32:44, 8256.41 examples/s]
Generating train split: 90791703 examples [1:32:44, 8994.91 examples/s]
Generating train split: 90792681 examples [1:32:44, 7960.48 examples/s]
Generating train split: 90795303 examples [1:32:44, 12192.75 examples/s]
Generating train split: 90796695 examples [1:32:44, 11915.47 examples/s]
Generating train split: 90798006 examples [1:32:44, 7258.52 examples/s] 
Generating train split: 90799539 examples [1:32:45, 8670.59 examples/s]
Generating train split: 90800711 examples [1:32:45, 8572.05 examples/s]
Generating train split: 90801797 examples [1:32:45, 8319.59 examples/s]
Generating train split: 90802784 examples [1:32:45, 6852.67 examples/s]
Generating train split: 90804818 examples [1:32:45, 9453.97 examples/s]
Generating train split: 90805998 examples [1:32:45, 9678.74 examples/s]
Generating train split: 90807134 examples [1:32:45, 9172.45 examples/s]
Generating train split: 90808749 examples [1:32:46, 10395.53 examples/s]
Generating train split: 90809893 examples [1:32:46, 9053.99 examples/s] 
Generating train split: 90817789 examples [1:32:46, 24932.74 examples/s]
Generating train split: 90825497 examples [1:32:46, 37705.62 examples/s]
Generating train split: 90829967 examples [1:32:46, 30695.85 examples/s]
Generating train split: 90833727 examples [1:32:46, 23902.83 examples/s]
Generating train split: 90836803 examples [1:32:47, 16269.74 examples/s]
Generating train split: 90839198 examples [1:32:47, 10721.54 examples/s]
Generating train split: 90841014 examples [1:32:47, 10542.23 examples/s]
Generating train split: 90842578 examples [1:32:48, 7605.64 examples/s] 
Generating train split: 90843776 examples [1:32:48, 7866.27 examples/s]
Generating train split: 90844908 examples [1:32:49, 5382.38 examples/s]
Generating train split: 90845763 examples [1:32:49, 3879.18 examples/s]
Generating train split: 90846421 examples [1:32:49, 3350.08 examples/s]
Generating train split: 90847288 examples [1:32:50, 3885.03 examples/s]
Generating train split: 90849881 examples [1:32:50, 6654.08 examples/s]
Generating train split: 90851087 examples [1:32:50, 5948.23 examples/s]
Generating train split: 90852068 examples [1:32:50, 5693.06 examples/s]
Generating train split: 90852910 examples [1:32:50, 5758.73 examples/s]
Generating train split: 90853681 examples [1:32:50, 5086.41 examples/s]
Generating train split: 90854573 examples [1:32:51, 5685.45 examples/s]
Generating train split: 90855278 examples [1:32:51, 5794.93 examples/s]
Generating train split: 90856684 examples [1:32:51, 7539.09 examples/s]
Generating train split: 90857932 examples [1:32:51, 8302.44 examples/s]
Generating train split: 90858878 examples [1:32:51, 7537.47 examples/s]
Generating train split: 90859714 examples [1:32:51, 4875.07 examples/s]
Generating train split: 90861192 examples [1:32:52, 6588.03 examples/s]
Generating train split: 90862483 examples [1:32:52, 7834.88 examples/s]
Generating train split: 90863522 examples [1:32:52, 6404.91 examples/s]
Generating train split: 90864371 examples [1:32:52, 6434.12 examples/s]
Generating train split: 90865580 examples [1:32:52, 7567.07 examples/s]
Generating train split: 90866489 examples [1:32:52, 7718.72 examples/s]
Generating train split: 90867535 examples [1:32:52, 8316.04 examples/s]
Generating train split: 90868462 examples [1:32:53, 6139.24 examples/s]
Generating train split: 90870517 examples [1:32:53, 9105.77 examples/s]
Generating train split: 90872181 examples [1:32:53, 10816.64 examples/s]
Generating train split: 90873540 examples [1:32:53, 11249.42 examples/s]
Generating train split: 90874830 examples [1:32:53, 10409.58 examples/s]
Generating train split: 90875990 examples [1:32:53, 10673.59 examples/s]
Generating train split: 90877935 examples [1:32:53, 12902.24 examples/s]
Generating train split: 90879324 examples [1:32:53, 11878.65 examples/s]
Generating train split: 90880601 examples [1:32:54, 8062.99 examples/s] 
Generating train split: 90881631 examples [1:32:54, 6935.83 examples/s]
Generating train split: 90882706 examples [1:32:54, 7645.11 examples/s]
Generating train split: 90883773 examples [1:32:54, 8256.18 examples/s]
Generating train split: 90884736 examples [1:32:54, 6194.76 examples/s]
Generating train split: 90885525 examples [1:32:54, 6192.80 examples/s]
Generating train split: 90886263 examples [1:32:55, 6283.52 examples/s]
Generating train split: 90886988 examples [1:32:55, 4714.12 examples/s]
Generating train split: 90887670 examples [1:32:55, 5101.48 examples/s]
Generating train split: 90888278 examples [1:32:55, 5291.86 examples/s]
Generating train split: 90890301 examples [1:32:55, 8644.91 examples/s]
Generating train split: 90891304 examples [1:32:55, 6024.71 examples/s]
Generating train split: 90892118 examples [1:32:56, 5498.70 examples/s]
Generating train split: 90892980 examples [1:32:56, 6083.63 examples/s]
Generating train split: 90893728 examples [1:32:56, 4381.74 examples/s]
Generating train split: 90894549 examples [1:32:56, 5022.53 examples/s]
Generating train split: 90895926 examples [1:32:56, 6721.85 examples/s]
Generating train split: 90897587 examples [1:32:56, 8854.06 examples/s]
Generating train split: 90898689 examples [1:32:57, 8292.56 examples/s]
Generating train split: 90901044 examples [1:32:57, 11817.94 examples/s]
Generating train split: 90902440 examples [1:32:57, 10410.03 examples/s]
Generating train split: 90903782 examples [1:32:57, 11081.15 examples/s]
Generating train split: 90905047 examples [1:32:57, 8813.55 examples/s] 
Generating train split: 90906862 examples [1:32:57, 10780.28 examples/s]
Generating train split: 90908232 examples [1:32:57, 11185.51 examples/s]
Generating train split: 90909580 examples [1:32:57, 11620.06 examples/s]
Generating train split: 90911071 examples [1:32:58, 12262.54 examples/s]
Generating train split: 90912383 examples [1:32:58, 9472.34 examples/s] 
Generating train split: 90913479 examples [1:32:58, 9664.51 examples/s]
Generating train split: 90914560 examples [1:32:58, 9546.09 examples/s]
Generating train split: 90915597 examples [1:32:58, 8438.81 examples/s]
Generating train split: 90921438 examples [1:32:58, 20132.42 examples/s]
Generating train split: 90929825 examples [1:32:58, 36103.41 examples/s]
Generating train split: 90934027 examples [1:32:58, 32649.89 examples/s]
Generating train split: 90937757 examples [1:32:59, 15597.40 examples/s]
Generating train split: 90940569 examples [1:33:00, 10261.89 examples/s]
Generating train split: 90942687 examples [1:33:00, 6909.84 examples/s] 
Generating train split: 90944255 examples [1:33:01, 5914.80 examples/s]
Generating train split: 90945455 examples [1:33:01, 5689.03 examples/s]
Generating train split: 90946437 examples [1:33:01, 5638.63 examples/s]
Generating train split: 90948550 examples [1:33:01, 7392.79 examples/s]
Generating train split: 90949783 examples [1:33:01, 7985.46 examples/s]
Generating train split: 90950982 examples [1:33:02, 7096.60 examples/s]
Generating train split: 90951985 examples [1:33:02, 5659.84 examples/s]
Generating train split: 90952779 examples [1:33:02, 4684.42 examples/s]
Generating train split: 90955018 examples [1:33:02, 7182.12 examples/s]
Generating train split: 90964346 examples [1:33:03, 21625.22 examples/s]
Generating train split: 90972567 examples [1:33:03, 33071.38 examples/s]
Generating train split: 90977443 examples [1:33:03, 29748.47 examples/s]
Generating train split: 90981570 examples [1:33:04, 12438.36 examples/s]
Generating train split: 90984609 examples [1:33:04, 12451.67 examples/s]
Generating train split: 90987105 examples [1:33:04, 10835.33 examples/s]
Generating train split: 90989069 examples [1:33:04, 11202.34 examples/s]
Generating train split: 90990842 examples [1:33:05, 9279.20 examples/s] 
Generating train split: 90992562 examples [1:33:05, 10270.89 examples/s]
Generating train split: 90994068 examples [1:33:05, 9578.65 examples/s] 
Generating train split: 90996935 examples [1:33:05, 12537.31 examples/s]
Generating train split: 90998659 examples [1:33:05, 10197.07 examples/s]
Generating train split: 91000341 examples [1:33:06, 11300.35 examples/s]
Generating train split: 91001829 examples [1:33:06, 11121.56 examples/s]
Generating train split: 91003973 examples [1:33:06, 13016.57 examples/s]
Generating train split: 91005530 examples [1:33:06, 9988.94 examples/s] 
Generating train split: 91007403 examples [1:33:06, 11567.79 examples/s]
Generating train split: 91009143 examples [1:33:06, 12795.14 examples/s]
Generating train split: 91010665 examples [1:33:07, 8274.30 examples/s] 
Generating train split: 91012457 examples [1:33:07, 9838.26 examples/s]
Generating train split: 91013804 examples [1:33:07, 9730.36 examples/s]
Generating train split: 91015035 examples [1:33:07, 6596.03 examples/s]
Generating train split: 91016428 examples [1:33:07, 7719.21 examples/s]
Generating train split: 91017984 examples [1:33:07, 9154.22 examples/s]
Generating train split: 91019324 examples [1:33:08, 10029.81 examples/s]
Generating train split: 91020579 examples [1:33:08, 6611.55 examples/s] 
Generating train split: 91021566 examples [1:33:08, 6165.27 examples/s]
Generating train split: 91022426 examples [1:33:08, 6536.03 examples/s]
Generating train split: 91023267 examples [1:33:08, 5772.87 examples/s]
Generating train split: 91024032 examples [1:33:09, 6084.17 examples/s]
Generating train split: 91024760 examples [1:33:09, 5428.11 examples/s]
Generating train split: 91025393 examples [1:33:09, 4742.61 examples/s]
Generating train split: 91025931 examples [1:33:09, 4538.66 examples/s]
Generating train split: 91026430 examples [1:33:09, 4531.27 examples/s]
Generating train split: 91028443 examples [1:33:09, 7975.63 examples/s]
Generating train split: 91029366 examples [1:33:09, 6201.60 examples/s]
Generating train split: 91030134 examples [1:33:10, 6074.20 examples/s]
Generating train split: 91030837 examples [1:33:10, 5566.58 examples/s]
Generating train split: 91038525 examples [1:33:10, 20851.94 examples/s]
Generating train split: 91047793 examples [1:33:10, 37681.43 examples/s]
Generating train split: 91052496 examples [1:33:11, 18921.86 examples/s]
Generating train split: 91056047 examples [1:33:11, 16966.21 examples/s]
Generating train split: 91058924 examples [1:33:11, 17075.41 examples/s]
Generating train split: 91067564 examples [1:33:11, 27898.00 examples/s]
Generating train split: 91074308 examples [1:33:11, 35105.65 examples/s]
Generating train split: 91079393 examples [1:33:12, 20526.90 examples/s]
Generating train split: 91083241 examples [1:33:12, 20370.56 examples/s]
Generating train split: 91092149 examples [1:33:12, 30489.84 examples/s]
Generating train split: 91100476 examples [1:33:12, 39620.25 examples/s]
Generating train split: 91106438 examples [1:33:13, 13093.35 examples/s]
Generating train split: 91110760 examples [1:33:14, 10975.93 examples/s]
Generating train split: 91113995 examples [1:33:15, 9466.24 examples/s] 
Generating train split: 91116443 examples [1:33:15, 7980.91 examples/s]
Generating train split: 91118300 examples [1:33:15, 7694.96 examples/s]
Generating train split: 91119798 examples [1:33:16, 7746.10 examples/s]
Generating train split: 91121082 examples [1:33:16, 7950.90 examples/s]
Generating train split: 91122670 examples [1:33:16, 8916.73 examples/s]
Generating train split: 91123973 examples [1:33:16, 8041.50 examples/s]
Generating train split: 91125057 examples [1:33:16, 7893.97 examples/s]
Generating train split: 91126043 examples [1:33:16, 7719.93 examples/s]
Generating train split: 91127254 examples [1:33:16, 8517.54 examples/s]
Generating train split: 91128256 examples [1:33:16, 8660.57 examples/s]
Generating train split: 91135967 examples [1:33:17, 24106.83 examples/s]
Generating train split: 91144949 examples [1:33:17, 40126.74 examples/s]
Generating train split: 91149744 examples [1:33:17, 18446.26 examples/s]
Generating train split: 91156953 examples [1:33:17, 25901.00 examples/s]
Generating train split: 91165841 examples [1:33:17, 36334.21 examples/s]
Generating train split: 91171793 examples [1:33:18, 20724.25 examples/s]
Generating train split: 91176258 examples [1:33:19, 11750.08 examples/s]
Generating train split: 91179529 examples [1:33:19, 12699.69 examples/s]
Generating train split: 91187929 examples [1:33:19, 19633.78 examples/s]
Generating train split: 91195252 examples [1:33:19, 25993.47 examples/s]
Generating train split: 91200505 examples [1:33:20, 14422.51 examples/s]
Generating train split: 91204376 examples [1:33:21, 10668.50 examples/s]
Generating train split: 91207246 examples [1:33:22, 8424.51 examples/s] 
Generating train split: 91209383 examples [1:33:22, 7628.78 examples/s]
Generating train split: 91211038 examples [1:33:22, 8005.65 examples/s]
Generating train split: 91213017 examples [1:33:22, 9133.51 examples/s]
Generating train split: 91214652 examples [1:33:22, 8730.97 examples/s]
Generating train split: 91216018 examples [1:33:23, 7530.84 examples/s]
Generating train split: 91217127 examples [1:33:23, 7321.05 examples/s]
Generating train split: 91219931 examples [1:33:23, 10339.51 examples/s]
Generating train split: 91221918 examples [1:33:23, 11963.31 examples/s]
Generating train split: 91223593 examples [1:33:23, 10329.62 examples/s]
Generating train split: 91224974 examples [1:33:24, 7535.79 examples/s] 
Generating train split: 91226855 examples [1:33:24, 9259.01 examples/s]
Generating train split: 91228192 examples [1:33:24, 9902.59 examples/s]
Generating train split: 91229504 examples [1:33:24, 8993.29 examples/s]
Generating train split: 91230637 examples [1:33:24, 6784.85 examples/s]
Generating train split: 91232109 examples [1:33:24, 8101.39 examples/s]
Generating train split: 91233176 examples [1:33:25, 7354.11 examples/s]
Generating train split: 91234105 examples [1:33:25, 7611.52 examples/s]
Generating train split: 91235013 examples [1:33:25, 5451.55 examples/s]
Generating train split: 91235735 examples [1:33:25, 5493.24 examples/s]
Generating train split: 91237742 examples [1:33:25, 8022.12 examples/s]
Generating train split: 91238744 examples [1:33:26, 6983.12 examples/s]
Generating train split: 91239859 examples [1:33:26, 7807.11 examples/s]
Generating train split: 91240786 examples [1:33:26, 4126.53 examples/s]
Generating train split: 91241487 examples [1:33:26, 4492.09 examples/s]
Generating train split: 91242793 examples [1:33:26, 5850.84 examples/s]
Generating train split: 91243921 examples [1:33:26, 6843.89 examples/s]
Generating train split: 91244854 examples [1:33:27, 5563.71 examples/s]
Generating train split: 91245857 examples [1:33:27, 6379.63 examples/s]
Generating train split: 91247248 examples [1:33:27, 7942.35 examples/s]
Generating train split: 91248255 examples [1:33:27, 5792.86 examples/s]
Generating train split: 91249065 examples [1:33:27, 6134.45 examples/s]
Generating train split: 91254804 examples [1:33:27, 16687.88 examples/s]
Generating train split: 91263190 examples [1:33:28, 31952.86 examples/s]
Generating train split: 91268695 examples [1:33:28, 37423.61 examples/s]
Generating train split: 91273199 examples [1:33:28, 16124.80 examples/s]
Generating train split: 91276561 examples [1:33:29, 12674.99 examples/s]
Generating train split: 91279136 examples [1:33:29, 8815.16 examples/s] 
Generating train split: 91281070 examples [1:33:30, 7135.12 examples/s]
Generating train split: 91282531 examples [1:33:31, 5364.33 examples/s]
Generating train split: 91283626 examples [1:33:31, 4483.19 examples/s]
Generating train split: 91284462 examples [1:33:31, 4789.28 examples/s]
Generating train split: 91285296 examples [1:33:31, 4311.56 examples/s]
Generating train split: 91293212 examples [1:33:31, 12512.32 examples/s]
Generating train split: 91299575 examples [1:33:32, 19430.30 examples/s]
Generating train split: 91303481 examples [1:33:32, 20089.46 examples/s]
Generating train split: 91306870 examples [1:33:32, 11726.56 examples/s]
Generating train split: 91309407 examples [1:33:33, 9364.75 examples/s] 
Generating train split: 91311342 examples [1:33:33, 7888.70 examples/s]
Generating train split: 91312840 examples [1:33:34, 7519.64 examples/s]
Generating train split: 91314083 examples [1:33:34, 6402.46 examples/s]
Generating train split: 91315058 examples [1:33:34, 6381.21 examples/s]
Generating train split: 91315936 examples [1:33:34, 5314.09 examples/s]
Generating train split: 91317396 examples [1:33:34, 6506.77 examples/s]
Generating train split: 91318320 examples [1:33:35, 6681.14 examples/s]
Generating train split: 91319193 examples [1:33:35, 4820.31 examples/s]
Generating train split: 91320847 examples [1:33:35, 6538.82 examples/s]
Generating train split: 91322405 examples [1:33:35, 8100.17 examples/s]
Generating train split: 91323557 examples [1:33:36, 5373.70 examples/s]
Generating train split: 91324443 examples [1:33:36, 5275.40 examples/s]
Generating train split: 91325212 examples [1:33:36, 4167.64 examples/s]
Generating train split: 91326480 examples [1:33:36, 5305.23 examples/s]
Generating train split: 91327257 examples [1:33:36, 3906.67 examples/s]
Generating train split: 91328509 examples [1:33:37, 5086.25 examples/s]
Generating train split: 91331545 examples [1:33:37, 9293.24 examples/s]
Generating train split: 91339248 examples [1:33:37, 22305.34 examples/s]
Generating train split: 91345345 examples [1:33:37, 30631.25 examples/s]
Generating train split: 91349509 examples [1:33:39, 6970.44 examples/s] 
Generating train split: 91352504 examples [1:33:39, 7243.99 examples/s]
Generating train split: 91354847 examples [1:33:40, 5023.12 examples/s]
Generating train split: 91356557 examples [1:33:40, 4741.26 examples/s]
Generating train split: 91357872 examples [1:33:41, 4834.63 examples/s]
Generating train split: 91365383 examples [1:33:41, 10369.72 examples/s]
Generating train split: 91373530 examples [1:33:41, 17558.77 examples/s]
Generating train split: 91378076 examples [1:33:42, 10088.41 examples/s]
Generating train split: 91385478 examples [1:33:42, 15166.49 examples/s]
Generating train split: 91393656 examples [1:33:42, 21954.32 examples/s]
Generating train split: 91399300 examples [1:33:43, 17803.71 examples/s]
Generating train split: 91403608 examples [1:33:44, 10467.90 examples/s]
Generating train split: 91406755 examples [1:33:44, 9490.41 examples/s] 
Generating train split: 91409168 examples [1:33:45, 7621.12 examples/s]
Generating train split: 91412212 examples [1:33:45, 9284.97 examples/s]
Generating train split: 91420609 examples [1:33:45, 16331.85 examples/s]
Generating train split: 91426262 examples [1:33:45, 21104.24 examples/s]
Generating train split: 91430794 examples [1:33:46, 9059.81 examples/s] 
Generating train split: 91434066 examples [1:33:48, 5380.89 examples/s]
Generating train split: 91436430 examples [1:33:48, 5999.03 examples/s]
Generating train split: 91438461 examples [1:33:48, 5690.88 examples/s]
Generating train split: 91440025 examples [1:33:48, 6093.65 examples/s]
Generating train split: 91441413 examples [1:33:49, 4982.38 examples/s]
Generating train split: 91442463 examples [1:33:49, 4776.68 examples/s]
Generating train split: 91443322 examples [1:33:49, 5003.22 examples/s]
Generating train split: 91444470 examples [1:33:49, 5739.76 examples/s]
Generating train split: 91445370 examples [1:33:50, 5155.42 examples/s]
Generating train split: 91446115 examples [1:33:50, 3726.33 examples/s]
Generating train split: 91447148 examples [1:33:50, 4533.61 examples/s]
Generating train split: 91447861 examples [1:33:51, 3367.64 examples/s]
Generating train split: 91449401 examples [1:33:51, 4853.39 examples/s]
Generating train split: 91450216 examples [1:33:51, 3766.83 examples/s]
Generating train split: 91450855 examples [1:33:51, 3804.56 examples/s]
Generating train split: 91451764 examples [1:33:51, 4497.07 examples/s]
Generating train split: 91452400 examples [1:33:52, 4527.27 examples/s]
Generating train split: 91452985 examples [1:33:52, 4766.51 examples/s]
Generating train split: 91453570 examples [1:33:52, 4529.62 examples/s]
Generating train split: 91454107 examples [1:33:52, 3838.58 examples/s]
Generating train split: 91454565 examples [1:33:52, 3555.47 examples/s]
Generating train split: 91454970 examples [1:33:52, 3560.85 examples/s]
Generating train split: 91455754 examples [1:33:52, 4503.02 examples/s]
Generating train split: 91456262 examples [1:33:53, 3146.32 examples/s]
Generating train split: 91456674 examples [1:33:53, 3125.03 examples/s]
Generating train split: 91457778 examples [1:33:53, 4677.63 examples/s]
Generating train split: 91458368 examples [1:33:53, 4277.38 examples/s]
Generating train split: 91461243 examples [1:33:53, 9533.07 examples/s]
Generating train split: 91462464 examples [1:33:53, 9401.71 examples/s]
Generating train split: 91463588 examples [1:33:53, 9260.73 examples/s]
Generating train split: 91464656 examples [1:33:54, 7048.63 examples/s]
Generating train split: 91465690 examples [1:33:54, 7684.90 examples/s]
Generating train split: 91466901 examples [1:33:54, 8620.38 examples/s]
Generating train split: 91467896 examples [1:33:54, 6953.77 examples/s]
Generating train split: 91468950 examples [1:33:54, 7647.03 examples/s]
Generating train split: 91469849 examples [1:33:54, 6146.08 examples/s]
Generating train split: 91470592 examples [1:33:55, 5771.78 examples/s]
Generating train split: 91471267 examples [1:33:55, 5834.20 examples/s]
Generating train split: 91472284 examples [1:33:55, 6802.31 examples/s]
Generating train split: 91473049 examples [1:33:55, 5255.72 examples/s]
Generating train split: 91473691 examples [1:33:55, 5488.30 examples/s]
Generating train split: 91475648 examples [1:33:55, 8676.16 examples/s]
Generating train split: 91476676 examples [1:33:56, 6652.63 examples/s]
Generating train split: 91477532 examples [1:33:56, 5319.94 examples/s]
Generating train split: 91478747 examples [1:33:56, 6545.62 examples/s]
Generating train split: 91479598 examples [1:33:56, 5105.42 examples/s]
Generating train split: 91480342 examples [1:33:56, 5085.68 examples/s]
Generating train split: 91481501 examples [1:33:56, 6313.29 examples/s]
Generating train split: 91489519 examples [1:33:56, 22007.10 examples/s]
Generating train split: 91497780 examples [1:33:57, 35829.92 examples/s]
Generating train split: 91502254 examples [1:33:57, 17314.05 examples/s]
Generating train split: 91510352 examples [1:33:57, 26153.61 examples/s]
Generating train split: 91518429 examples [1:33:57, 35116.98 examples/s]
Generating train split: 91524173 examples [1:33:58, 21318.30 examples/s]
Generating train split: 91528515 examples [1:34:00, 7506.58 examples/s] 
Generating train split: 91531619 examples [1:34:01, 6422.70 examples/s]
Generating train split: 91539578 examples [1:34:01, 10333.07 examples/s]
Generating train split: 91547615 examples [1:34:01, 15277.25 examples/s]
Generating train split: 91552769 examples [1:34:02, 10387.68 examples/s]
Generating train split: 91556543 examples [1:34:03, 6486.18 examples/s] 
Generating train split: 91563957 examples [1:34:03, 9806.59 examples/s]
Generating train split: 91572734 examples [1:34:03, 14856.79 examples/s]
Generating train split: 91578119 examples [1:34:04, 12382.89 examples/s]
Generating train split: 91582141 examples [1:34:04, 12522.74 examples/s]
Generating train split: 91587046 examples [1:34:04, 15673.58 examples/s]
Generating train split: 91595936 examples [1:34:04, 23707.80 examples/s]
Generating train split: 91601202 examples [1:34:05, 24819.99 examples/s]
Generating train split: 91605747 examples [1:34:05, 18335.57 examples/s]
Generating train split: 91609236 examples [1:34:05, 15279.23 examples/s]
Generating train split: 91611959 examples [1:34:06, 12948.75 examples/s]
Generating train split: 91614190 examples [1:34:06, 14012.14 examples/s]
Generating train split: 91616368 examples [1:34:06, 15051.16 examples/s]
Generating train split: 91618621 examples [1:34:06, 16286.35 examples/s]
Generating train split: 91620807 examples [1:34:07, 8940.94 examples/s] 
Generating train split: 91622458 examples [1:34:07, 7769.63 examples/s]
Generating train split: 91623770 examples [1:34:07, 6148.98 examples/s]
Generating train split: 91624846 examples [1:34:08, 6562.74 examples/s]
Generating train split: 91625846 examples [1:34:08, 6587.33 examples/s]
Generating train split: 91626739 examples [1:34:08, 5730.93 examples/s]
Generating train split: 91627477 examples [1:34:08, 5958.17 examples/s]
Generating train split: 91628212 examples [1:34:08, 4214.86 examples/s]
Generating train split: 91629196 examples [1:34:08, 5050.39 examples/s]
Generating train split: 91629896 examples [1:34:09, 4897.19 examples/s]
Generating train split: 91631516 examples [1:34:09, 6941.46 examples/s]
Generating train split: 91632431 examples [1:34:09, 4382.61 examples/s]
Generating train split: 91634097 examples [1:34:09, 6215.89 examples/s]
Generating train split: 91635083 examples [1:34:10, 5411.46 examples/s]
Generating train split: 91635937 examples [1:34:10, 5631.12 examples/s]
Generating train split: 91637533 examples [1:34:10, 7508.63 examples/s]
Generating train split: 91639349 examples [1:34:10, 9714.23 examples/s]
Generating train split: 91641366 examples [1:34:10, 12072.34 examples/s]
Generating train split: 91642840 examples [1:34:10, 8041.02 examples/s] 
Generating train split: 91644751 examples [1:34:10, 10000.03 examples/s]
Generating train split: 91646426 examples [1:34:11, 11365.91 examples/s]
Generating train split: 91647886 examples [1:34:11, 10845.56 examples/s]
Generating train split: 91649201 examples [1:34:11, 8264.47 examples/s] 
Generating train split: 91650703 examples [1:34:11, 9535.13 examples/s]
Generating train split: 91652370 examples [1:34:11, 11051.69 examples/s]
Generating train split: 91653706 examples [1:34:11, 9739.51 examples/s] 
Generating train split: 91655490 examples [1:34:11, 10903.73 examples/s]
Generating train split: 91658450 examples [1:34:12, 15151.39 examples/s]
Generating train split: 91660300 examples [1:34:12, 15969.28 examples/s]
Generating train split: 91662084 examples [1:34:12, 10119.20 examples/s]
Generating train split: 91663490 examples [1:34:12, 9476.38 examples/s] 
Generating train split: 91664718 examples [1:34:13, 6812.55 examples/s]
Generating train split: 91666582 examples [1:34:13, 8636.77 examples/s]
Generating train split: 91668426 examples [1:34:13, 10274.77 examples/s]
Generating train split: 91669816 examples [1:34:13, 9352.91 examples/s] 
Generating train split: 91671014 examples [1:34:13, 9786.33 examples/s]
Generating train split: 91672188 examples [1:34:13, 9481.74 examples/s]
Generating train split: 91679755 examples [1:34:13, 24369.19 examples/s]
Generating train split: 91688548 examples [1:34:13, 39824.28 examples/s]
Generating train split: 91693309 examples [1:34:14, 32006.74 examples/s]
Generating train split: 91697292 examples [1:34:14, 12365.10 examples/s]
Generating train split: 91700214 examples [1:34:15, 10543.30 examples/s]
Generating train split: 91702477 examples [1:34:15, 10855.23 examples/s]
Generating train split: 91704429 examples [1:34:16, 8176.99 examples/s] 
Generating train split: 91705928 examples [1:34:16, 8073.31 examples/s]
Generating train split: 91708106 examples [1:34:16, 9653.95 examples/s]
Generating train split: 91709636 examples [1:34:16, 9333.59 examples/s]
Generating train split: 91710956 examples [1:34:16, 7516.94 examples/s]
Generating train split: 91713408 examples [1:34:16, 9947.14 examples/s]
Generating train split: 91714879 examples [1:34:17, 8423.51 examples/s]
Generating train split: 91716079 examples [1:34:17, 7472.86 examples/s]
Generating train split: 91717086 examples [1:34:17, 5862.51 examples/s]
Generating train split: 91717880 examples [1:34:18, 4232.02 examples/s]
Generating train split: 91718493 examples [1:34:18, 3216.69 examples/s]
Generating train split: 91719927 examples [1:34:18, 4458.52 examples/s]
Generating train split: 91721186 examples [1:34:18, 5567.08 examples/s]
Generating train split: 91722078 examples [1:34:19, 3978.48 examples/s]
Generating train split: 91722771 examples [1:34:19, 4100.62 examples/s]
Generating train split: 91730870 examples [1:34:19, 15721.75 examples/s]
Generating train split: 91738959 examples [1:34:19, 27288.66 examples/s]
Generating train split: 91743389 examples [1:34:19, 21411.38 examples/s]
Generating train split: 91746918 examples [1:34:20, 18744.90 examples/s]
Generating train split: 91755491 examples [1:34:20, 29394.82 examples/s]
Generating train split: 91762809 examples [1:34:20, 37410.83 examples/s]
Generating train split: 91768194 examples [1:34:21, 17499.10 examples/s]
Generating train split: 91772180 examples [1:34:21, 17413.43 examples/s]
Generating train split: 91780869 examples [1:34:21, 25982.32 examples/s]
Generating train split: 91787918 examples [1:34:21, 32648.09 examples/s]
Generating train split: 91793494 examples [1:34:21, 25251.57 examples/s]
Generating train split: 91801575 examples [1:34:21, 33445.97 examples/s]
Generating train split: 91808247 examples [1:34:22, 39233.51 examples/s]
Generating train split: 91814078 examples [1:34:22, 18390.90 examples/s]
Generating train split: 91822178 examples [1:34:22, 25175.63 examples/s]
Generating train split: 91828814 examples [1:34:23, 30695.56 examples/s]
Generating train split: 91834627 examples [1:34:23, 18939.28 examples/s]
Generating train split: 91838970 examples [1:34:24, 10246.08 examples/s]
Generating train split: 91842123 examples [1:34:25, 10280.60 examples/s]
Generating train split: 91844650 examples [1:34:25, 7073.15 examples/s] 
Generating train split: 91846504 examples [1:34:26, 6636.52 examples/s]
Generating train split: 91847973 examples [1:34:26, 7226.82 examples/s]
Generating train split: 91849434 examples [1:34:26, 7896.07 examples/s]
Generating train split: 91850871 examples [1:34:27, 5803.82 examples/s]
Generating train split: 91851963 examples [1:34:27, 4345.43 examples/s]
Generating train split: 91852785 examples [1:34:27, 4026.25 examples/s]
Generating train split: 91853656 examples [1:34:27, 4465.10 examples/s]
Generating train split: 91854365 examples [1:34:28, 4386.09 examples/s]
Generating train split: 91854987 examples [1:34:28, 3354.99 examples/s]
Generating train split: 91860536 examples [1:34:28, 9948.33 examples/s]
Generating train split: 91869564 examples [1:34:28, 22240.13 examples/s]
Generating train split: 91873672 examples [1:34:29, 12090.89 examples/s]
Generating train split: 91876723 examples [1:34:30, 9028.69 examples/s] 
Generating train split: 91879003 examples [1:34:30, 7220.33 examples/s]
Generating train split: 91880735 examples [1:34:30, 7200.42 examples/s]
Generating train split: 91882280 examples [1:34:30, 7987.97 examples/s]
Generating train split: 91883743 examples [1:34:31, 7850.90 examples/s]
Generating train split: 91884987 examples [1:34:31, 7083.37 examples/s]
Generating train split: 91887312 examples [1:34:31, 9222.49 examples/s]
Generating train split: 91888682 examples [1:34:31, 7446.66 examples/s]
Generating train split: 91889779 examples [1:34:32, 7241.48 examples/s]
Generating train split: 91890751 examples [1:34:32, 6329.08 examples/s]
Generating train split: 91892017 examples [1:34:32, 7343.96 examples/s]
Generating train split: 91892975 examples [1:34:32, 7735.17 examples/s]
Generating train split: 91893916 examples [1:34:32, 7426.92 examples/s]
Generating train split: 91894777 examples [1:34:32, 4823.25 examples/s]
Generating train split: 91895538 examples [1:34:33, 5271.54 examples/s]
Generating train split: 91896236 examples [1:34:33, 5402.25 examples/s]
Generating train split: 91896906 examples [1:34:33, 5549.49 examples/s]
Generating train split: 91897557 examples [1:34:33, 5295.69 examples/s]
Generating train split: 91898848 examples [1:34:33, 6967.53 examples/s]
Generating train split: 91899650 examples [1:34:34, 3671.37 examples/s]
Generating train split: 91900254 examples [1:34:34, 3976.89 examples/s]
Generating train split: 91901545 examples [1:34:34, 5533.85 examples/s]
Generating train split: 91902350 examples [1:34:34, 5937.66 examples/s]
Generating train split: 91903137 examples [1:34:34, 5151.17 examples/s]
Generating train split: 91904085 examples [1:34:34, 5792.09 examples/s]
Generating train split: 91904790 examples [1:34:34, 5613.44 examples/s]
Generating train split: 91905662 examples [1:34:34, 6056.77 examples/s]
Generating train split: 91906345 examples [1:34:35, 5825.14 examples/s]
Generating train split: 91907551 examples [1:34:35, 7307.83 examples/s]
Generating train split: 91908359 examples [1:34:35, 6793.73 examples/s]
Generating train split: 91909094 examples [1:34:35, 5287.28 examples/s]
Generating train split: 91909711 examples [1:34:35, 4042.46 examples/s]
Generating train split: 91910209 examples [1:34:35, 4175.54 examples/s]
Generating train split: 91910702 examples [1:34:36, 3768.24 examples/s]
Generating train split: 91911132 examples [1:34:36, 3474.32 examples/s]
Generating train split: 91912362 examples [1:34:36, 5293.07 examples/s]
Generating train split: 91913434 examples [1:34:36, 6527.78 examples/s]
Generating train split: 91914213 examples [1:34:36, 4067.26 examples/s]
Generating train split: 91915936 examples [1:34:36, 6337.46 examples/s]
Generating train split: 91917270 examples [1:34:37, 7713.32 examples/s]
Generating train split: 91918322 examples [1:34:37, 5813.73 examples/s]
Generating train split: 91919165 examples [1:34:37, 5020.31 examples/s]
Generating train split: 91919866 examples [1:34:38, 2977.19 examples/s]
Generating train split: 91921184 examples [1:34:38, 4183.13 examples/s]
Generating train split: 91921955 examples [1:34:38, 4692.33 examples/s]
Generating train split: 91922720 examples [1:34:38, 5038.30 examples/s]
Generating train split: 91923763 examples [1:34:38, 6065.33 examples/s]
Generating train split: 91924638 examples [1:34:38, 6543.76 examples/s]
Generating train split: 91925466 examples [1:34:38, 5387.06 examples/s]
Generating train split: 91926277 examples [1:34:38, 5924.48 examples/s]
Generating train split: 91927386 examples [1:34:39, 7075.54 examples/s]
Generating train split: 91928313 examples [1:34:39, 7413.43 examples/s]
Generating train split: 91929147 examples [1:34:39, 4357.76 examples/s]
Generating train split: 91930169 examples [1:34:39, 5318.62 examples/s]
Generating train split: 91931063 examples [1:34:39, 5966.64 examples/s]
Generating train split: 91931844 examples [1:34:39, 6100.05 examples/s]
Generating train split: 91940242 examples [1:34:40, 23883.91 examples/s]
Generating train split: 91949874 examples [1:34:40, 41692.39 examples/s]
Generating train split: 91954887 examples [1:34:40, 24539.91 examples/s]
Generating train split: 91958782 examples [1:34:41, 8572.18 examples/s] 
Generating train split: 91961593 examples [1:34:42, 8541.38 examples/s]
Generating train split: 91963820 examples [1:34:42, 8568.59 examples/s]
Generating train split: 91965634 examples [1:34:42, 9184.36 examples/s]
Generating train split: 91971959 examples [1:34:42, 15379.02 examples/s]
Generating train split: 91980144 examples [1:34:42, 24724.60 examples/s]
Generating train split: 91984751 examples [1:34:42, 25301.82 examples/s]
Generating train split: 91988806 examples [1:34:43, 16092.94 examples/s]
Generating train split: 91996997 examples [1:34:43, 24406.59 examples/s]
Generating train split: 92004745 examples [1:34:43, 32481.98 examples/s]
Generating train split: 92010268 examples [1:34:44, 16564.76 examples/s]
Generating train split: 92014354 examples [1:34:45, 11243.33 examples/s]
Generating train split: 92017371 examples [1:34:46, 8267.96 examples/s] 
Generating train split: 92019605 examples [1:34:46, 6162.99 examples/s]
Generating train split: 92021248 examples [1:34:47, 5766.61 examples/s]
Generating train split: 92022530 examples [1:34:47, 5664.94 examples/s]
Generating train split: 92023591 examples [1:34:47, 4964.77 examples/s]
Generating train split: 92024418 examples [1:34:47, 5075.31 examples/s]
Generating train split: 92025174 examples [1:34:48, 4250.12 examples/s]
Generating train split: 92027803 examples [1:34:48, 6537.99 examples/s]
Generating train split: 92028899 examples [1:34:48, 6984.25 examples/s]
Generating train split: 92029953 examples [1:34:48, 5205.69 examples/s]
Generating train split: 92030928 examples [1:34:49, 5812.38 examples/s]
Generating train split: 92031879 examples [1:34:49, 6329.88 examples/s]
Generating train split: 92032751 examples [1:34:49, 4339.76 examples/s]
Generating train split: 92033431 examples [1:34:49, 4372.78 examples/s]
Generating train split: 92034045 examples [1:34:50, 3222.92 examples/s]
Generating train split: 92035305 examples [1:34:50, 4496.37 examples/s]
Generating train split: 92036013 examples [1:34:50, 3453.14 examples/s]
Generating train split: 92037786 examples [1:34:50, 5442.29 examples/s]
Generating train split: 92038693 examples [1:34:50, 5660.64 examples/s]
Generating train split: 92039526 examples [1:34:51, 4393.27 examples/s]
Generating train split: 92040675 examples [1:34:51, 5507.43 examples/s]
Generating train split: 92041488 examples [1:34:51, 5249.43 examples/s]
Generating train split: 92042188 examples [1:34:51, 4099.37 examples/s]
Generating train split: 92042752 examples [1:34:51, 4044.83 examples/s]
Generating train split: 92043345 examples [1:34:51, 4298.68 examples/s]
Generating train split: 92043862 examples [1:34:52, 3234.82 examples/s]
Generating train split: 92044285 examples [1:34:52, 3295.74 examples/s]
Generating train split: 92044923 examples [1:34:52, 3793.58 examples/s]
Generating train split: 92045373 examples [1:34:52, 2720.64 examples/s]
Generating train split: 92046606 examples [1:34:52, 4372.86 examples/s]
Generating train split: 92047231 examples [1:34:52, 4729.29 examples/s]
Generating train split: 92047850 examples [1:34:53, 4156.96 examples/s]
Generating train split: 92048533 examples [1:34:53, 4682.37 examples/s]
Generating train split: 92049105 examples [1:34:53, 4643.43 examples/s]
Generating train split: 92049647 examples [1:34:53, 3588.33 examples/s]
Generating train split: 92050094 examples [1:34:54, 2217.93 examples/s]
Generating train split: 92051352 examples [1:34:54, 3689.13 examples/s]
Generating train split: 92051977 examples [1:34:54, 4120.97 examples/s]
Generating train split: 92052598 examples [1:34:54, 3631.76 examples/s]
Generating train split: 92053115 examples [1:34:54, 2763.62 examples/s]
Generating train split: 92053629 examples [1:34:54, 3131.99 examples/s]
Generating train split: 92054069 examples [1:34:55, 3035.10 examples/s]
Generating train split: 92054468 examples [1:34:55, 2435.11 examples/s]
Generating train split: 92055058 examples [1:34:55, 3012.50 examples/s]
Generating train split: 92055468 examples [1:34:55, 3190.52 examples/s]
Generating train split: 92055868 examples [1:34:55, 2287.77 examples/s]
Generating train split: 92056195 examples [1:34:56, 2142.90 examples/s]
Generating train split: 92056472 examples [1:34:56, 2041.28 examples/s]
Generating train split: 92057023 examples [1:34:56, 2686.42 examples/s]
Generating train split: 92057358 examples [1:34:56, 2787.05 examples/s]
Generating train split: 92057716 examples [1:34:56, 2725.06 examples/s]
Generating train split: 92058023 examples [1:34:56, 2654.10 examples/s]
Generating train split: 92058322 examples [1:34:56, 2475.99 examples/s]
Generating train split: 92058688 examples [1:34:56, 2609.81 examples/s]
Generating train split: 92059586 examples [1:34:57, 4140.82 examples/s]
Generating train split: 92060574 examples [1:34:57, 5609.42 examples/s]
Generating train split: 92061198 examples [1:34:57, 4853.23 examples/s]
Generating train split: 92061818 examples [1:34:57, 5175.46 examples/s]
Generating train split: 92062912 examples [1:34:57, 6493.34 examples/s]
Generating train split: 92063619 examples [1:34:57, 5511.07 examples/s]
Generating train split: 92064695 examples [1:34:57, 6751.10 examples/s]
Generating train split: 92065761 examples [1:34:57, 7722.03 examples/s]
Generating train split: 92066599 examples [1:34:58, 7569.72 examples/s]
Generating train split: 92067754 examples [1:34:58, 8619.81 examples/s]
Generating train split: 92068664 examples [1:34:58, 8461.18 examples/s]
Generating train split: 92070546 examples [1:34:58, 11296.07 examples/s]
Generating train split: 92075009 examples [1:34:58, 20681.58 examples/s]
Generating train split: 92079937 examples [1:34:58, 28883.39 examples/s]
Generating train split: 92086061 examples [1:34:58, 38279.53 examples/s]
Generating train split: 92093322 examples [1:34:58, 48342.26 examples/s]
Generating train split: 92100717 examples [1:34:58, 55886.78 examples/s]
Generating train split: 92108493 examples [1:34:58, 62361.79 examples/s]
Generating train split: 92116325 examples [1:34:59, 67101.90 examples/s]
Generating train split: 92123081 examples [1:34:59, 67054.73 examples/s]
Generating train split: 92130611 examples [1:34:59, 69493.23 examples/s]
Generating train split: 92138248 examples [1:34:59, 71524.73 examples/s]
Generating train split: 92146350 examples [1:34:59, 74333.69 examples/s]
Generating train split: 92153856 examples [1:34:59, 74524.04 examples/s]
Generating train split: 92161321 examples [1:34:59, 73518.64 examples/s]
Generating train split: 92169128 examples [1:34:59, 74835.56 examples/s]
Generating train split: 92176758 examples [1:34:59, 75245.14 examples/s]
Generating train split: 92184944 examples [1:34:59, 77198.54 examples/s]
Generating train split: 92192675 examples [1:35:00, 75867.25 examples/s]
Generating train split: 92200278 examples [1:35:00, 74727.31 examples/s]
Generating train split: 92207921 examples [1:35:00, 75217.94 examples/s]
Generating train split: 92215451 examples [1:35:00, 71032.41 examples/s]
Generating train split: 92222610 examples [1:35:00, 68191.57 examples/s]
Generating train split: 92229482 examples [1:35:00, 65647.30 examples/s]
Generating train split: 92236092 examples [1:35:00, 65479.44 examples/s]
Generating train split: 92242670 examples [1:35:00, 63545.39 examples/s]
Generating train split: 92249056 examples [1:35:00, 61706.19 examples/s]
Generating train split: 92255245 examples [1:35:01, 53779.14 examples/s]
Generating train split: 92260802 examples [1:35:01, 48041.27 examples/s]
Generating train split: 92265806 examples [1:35:01, 34048.88 examples/s]
Generating train split: 92269859 examples [1:35:01, 31946.77 examples/s]
Generating train split: 92273485 examples [1:35:02, 21990.97 examples/s]
Generating train split: 92276344 examples [1:35:02, 18075.07 examples/s]
Generating train split: 92278668 examples [1:35:02, 14143.96 examples/s]
Generating train split: 92280753 examples [1:35:02, 15092.93 examples/s]
Generating train split: 92283021 examples [1:35:02, 16342.36 examples/s]
Generating train split: 92285038 examples [1:35:03, 8001.74 examples/s] 
Generating train split: 92286539 examples [1:35:04, 5091.20 examples/s]
Generating train split: 92287656 examples [1:35:04, 4295.01 examples/s]
Generating train split: 92288507 examples [1:35:04, 4514.70 examples/s]
Generating train split: 92289388 examples [1:35:04, 4914.32 examples/s]
Generating train split: 92290178 examples [1:35:05, 3449.85 examples/s]
Generating train split: 92290780 examples [1:35:05, 3350.15 examples/s]
Generating train split: 92291287 examples [1:35:05, 2849.99 examples/s]
Generating train split: 92291993 examples [1:35:06, 3323.90 examples/s]
Generating train split: 92292474 examples [1:35:06, 3472.99 examples/s]
Generating train split: 92292947 examples [1:35:06, 3030.82 examples/s]
Generating train split: 92293489 examples [1:35:06, 3421.52 examples/s]
Generating train split: 92293929 examples [1:35:06, 3318.17 examples/s]
Generating train split: 92295822 examples [1:35:06, 6461.51 examples/s]
Generating train split: 92297370 examples [1:35:06, 8185.60 examples/s]
Generating train split: 92298370 examples [1:35:07, 5772.03 examples/s]
Generating train split: 92299425 examples [1:35:07, 6648.77 examples/s]
Generating train split: 92300300 examples [1:35:07, 5149.24 examples/s]
Generating train split: 92301010 examples [1:35:07, 4548.79 examples/s]
Generating train split: 92301874 examples [1:35:07, 5234.70 examples/s]
Generating train split: 92308680 examples [1:35:07, 17674.04 examples/s]
Generating train split: 92317222 examples [1:35:08, 32608.74 examples/s]
Generating train split: 92322108 examples [1:35:08, 36116.60 examples/s]
Generating train split: 92326549 examples [1:35:08, 25656.34 examples/s]
Generating train split: 92330105 examples [1:35:09, 15209.95 examples/s]
Generating train split: 92332803 examples [1:35:09, 15512.07 examples/s]
Generating train split: 92335193 examples [1:35:09, 10202.18 examples/s]
Generating train split: 92337012 examples [1:35:10, 8312.81 examples/s] 
Generating train split: 92339745 examples [1:35:10, 10389.64 examples/s]
Generating train split: 92341549 examples [1:35:10, 7283.77 examples/s] 
Generating train split: 92343701 examples [1:35:10, 8842.55 examples/s]
Generating train split: 92345316 examples [1:35:11, 5533.89 examples/s]
Generating train split: 92346507 examples [1:35:11, 5371.50 examples/s]
Generating train split: 92347493 examples [1:35:11, 5837.45 examples/s]
Generating train split: 92349901 examples [1:35:11, 8281.58 examples/s]
Generating train split: 92351303 examples [1:35:12, 5339.15 examples/s]
Generating train split: 92352365 examples [1:35:12, 4685.87 examples/s]
Generating train split: 92354644 examples [1:35:12, 6794.84 examples/s]
Generating train split: 92356083 examples [1:35:13, 7713.06 examples/s]
Generating train split: 92357350 examples [1:35:13, 5589.55 examples/s]
Generating train split: 92358330 examples [1:35:13, 4209.96 examples/s]
Generating train split: 92360042 examples [1:35:13, 5708.64 examples/s]
Generating train split: 92361619 examples [1:35:14, 7138.20 examples/s]
Generating train split: 92362816 examples [1:35:14, 4967.47 examples/s]
Generating train split: 92364027 examples [1:35:14, 5836.84 examples/s]
Generating train split: 92365004 examples [1:35:14, 4800.31 examples/s]
Generating train split: 92365794 examples [1:35:15, 4938.59 examples/s]
Generating train split: 92368272 examples [1:35:15, 8128.40 examples/s]
Generating train split: 92369522 examples [1:35:15, 6895.57 examples/s]
Generating train split: 92370539 examples [1:35:15, 6309.11 examples/s]
Generating train split: 92371401 examples [1:35:15, 5597.87 examples/s]
Generating train split: 92372125 examples [1:35:16, 4603.32 examples/s]
Generating train split: 92373273 examples [1:35:16, 5692.43 examples/s]
Generating train split: 92374091 examples [1:35:16, 6150.88 examples/s]
Generating train split: 92375277 examples [1:35:16, 6659.36 examples/s]
Generating train split: 92376061 examples [1:35:16, 6271.02 examples/s]
Generating train split: 92376772 examples [1:35:16, 5562.02 examples/s]
Generating train split: 92378007 examples [1:35:16, 6979.90 examples/s]
Generating train split: 92378812 examples [1:35:17, 5164.40 examples/s]
Generating train split: 92379467 examples [1:35:17, 4327.19 examples/s]
Generating train split: 92380312 examples [1:35:17, 4888.89 examples/s]
Generating train split: 92380901 examples [1:35:17, 3175.81 examples/s]
Generating train split: 92381544 examples [1:35:18, 3643.75 examples/s]
Generating train split: 92382051 examples [1:35:18, 3730.78 examples/s]
Generating train split: 92383731 examples [1:35:18, 6243.88 examples/s]
Generating train split: 92384565 examples [1:35:18, 6107.24 examples/s]
Generating train split: 92386028 examples [1:35:18, 7980.26 examples/s]
Generating train split: 92394049 examples [1:35:18, 25236.59 examples/s]
Generating train split: 92403292 examples [1:35:18, 42331.52 examples/s]
Generating train split: 92408225 examples [1:35:18, 33818.77 examples/s]
Generating train split: 92412373 examples [1:35:20, 10758.66 examples/s]
Generating train split: 92415384 examples [1:35:20, 7525.23 examples/s] 
Generating train split: 92417608 examples [1:35:21, 6451.76 examples/s]
Generating train split: 92419279 examples [1:35:22, 5242.19 examples/s]
Generating train split: 92425115 examples [1:35:22, 8906.07 examples/s]
Generating train split: 92434522 examples [1:35:22, 16545.15 examples/s]
Generating train split: 92439184 examples [1:35:22, 16104.38 examples/s]
Generating train split: 92442896 examples [1:35:23, 13705.78 examples/s]
Generating train split: 92451621 examples [1:35:23, 21717.37 examples/s]
Generating train split: 92457959 examples [1:35:23, 27317.26 examples/s]
Generating train split: 92463098 examples [1:35:24, 11271.22 examples/s]
Generating train split: 92466824 examples [1:35:24, 10285.50 examples/s]
Generating train split: 92474957 examples [1:35:24, 15857.07 examples/s]
Generating train split: 92481361 examples [1:35:25, 20702.15 examples/s]
Generating train split: 92486379 examples [1:35:25, 19079.11 examples/s]
Generating train split: 92490356 examples [1:35:26, 10997.44 examples/s]
Generating train split: 92493278 examples [1:35:26, 9792.78 examples/s] 
Generating train split: 92495524 examples [1:35:27, 7257.82 examples/s]
Generating train split: 92497193 examples [1:35:27, 7328.06 examples/s]
Generating train split: 92498600 examples [1:35:27, 6721.25 examples/s]
Generating train split: 92499721 examples [1:35:28, 6457.43 examples/s]
Generating train split: 92501431 examples [1:35:28, 7641.73 examples/s]
Generating train split: 92502624 examples [1:35:28, 8223.59 examples/s]
Generating train split: 92503807 examples [1:35:28, 4922.16 examples/s]
Generating train split: 92504700 examples [1:35:29, 3875.77 examples/s]
Generating train split: 92505384 examples [1:35:29, 3585.45 examples/s]
Generating train split: 92506912 examples [1:35:29, 4927.21 examples/s]
Generating train split: 92507767 examples [1:35:29, 4570.67 examples/s]
Generating train split: 92508476 examples [1:35:30, 4268.16 examples/s]
Generating train split: 92509788 examples [1:35:30, 5609.23 examples/s]
Generating train split: 92510606 examples [1:35:30, 5846.99 examples/s]
Generating train split: 92511717 examples [1:35:30, 6862.92 examples/s]
Generating train split: 92512672 examples [1:35:30, 7416.24 examples/s]
Generating train split: 92513562 examples [1:35:30, 6656.89 examples/s]
Generating train split: 92515292 examples [1:35:30, 8679.65 examples/s]
Generating train split: 92516275 examples [1:35:31, 8498.98 examples/s]
Generating train split: 92517489 examples [1:35:31, 9368.77 examples/s]
Generating train split: 92518506 examples [1:35:31, 7630.66 examples/s]
Generating train split: 92520464 examples [1:35:31, 10322.25 examples/s]
Generating train split: 92521661 examples [1:35:31, 10216.66 examples/s]
Generating train split: 92522798 examples [1:35:31, 8838.31 examples/s] 
Generating train split: 92523792 examples [1:35:32, 4851.97 examples/s]
Generating train split: 92524553 examples [1:35:32, 4594.55 examples/s]
Generating train split: 92526142 examples [1:35:32, 6363.40 examples/s]
Generating train split: 92527070 examples [1:35:32, 5861.82 examples/s]
Generating train split: 92527965 examples [1:35:32, 5790.60 examples/s]
Generating train split: 92528690 examples [1:35:32, 6015.16 examples/s]
Generating train split: 92529402 examples [1:35:33, 5694.92 examples/s]
Generating train split: 92530053 examples [1:35:33, 5018.00 examples/s]
Generating train split: 92530982 examples [1:35:33, 5349.28 examples/s]
Generating train split: 92532592 examples [1:35:33, 7574.10 examples/s]
Generating train split: 92533478 examples [1:35:33, 7485.64 examples/s]
Generating train split: 92534309 examples [1:35:33, 7412.07 examples/s]
Generating train split: 92536531 examples [1:35:33, 11070.56 examples/s]
Generating train split: 92537752 examples [1:35:34, 8658.94 examples/s] 
Generating train split: 92539277 examples [1:35:34, 10111.79 examples/s]
Generating train split: 92540455 examples [1:35:34, 7095.13 examples/s] 
Generating train split: 92541394 examples [1:35:34, 5166.85 examples/s]
Generating train split: 92542794 examples [1:35:34, 6527.75 examples/s]
Generating train split: 92543729 examples [1:35:35, 6855.14 examples/s]
Generating train split: 92544883 examples [1:35:35, 7614.71 examples/s]
Generating train split: 92545819 examples [1:35:35, 7958.74 examples/s]
Generating train split: 92547582 examples [1:35:35, 10210.90 examples/s]
Generating train split: 92549440 examples [1:35:35, 11944.95 examples/s]
Generating train split: 92550758 examples [1:35:35, 9371.43 examples/s] 
Generating train split: 92552081 examples [1:35:35, 9809.38 examples/s]
Generating train split: 92553190 examples [1:35:35, 8440.92 examples/s]
Generating train split: 92554146 examples [1:35:36, 6925.07 examples/s]
Generating train split: 92554957 examples [1:35:36, 5957.22 examples/s]
Generating train split: 92556166 examples [1:35:36, 7122.50 examples/s]
Generating train split: 92557011 examples [1:35:36, 6629.70 examples/s]
Generating train split: 92558367 examples [1:35:36, 8107.08 examples/s]
Generating train split: 92559423 examples [1:35:36, 8500.39 examples/s]
Generating train split: 92560371 examples [1:35:37, 7106.17 examples/s]
Generating train split: 92561878 examples [1:35:37, 8875.27 examples/s]
Generating train split: 92564832 examples [1:35:37, 13863.03 examples/s]
Generating train split: 92567615 examples [1:35:37, 17444.37 examples/s]
Generating train split: 92569576 examples [1:35:37, 17060.78 examples/s]
Generating train split: 92571440 examples [1:35:37, 11343.72 examples/s]
Generating train split: 92572929 examples [1:35:37, 11011.12 examples/s]
Generating train split: 92574272 examples [1:35:38, 10360.98 examples/s]
Generating train split: 92576227 examples [1:35:38, 12148.82 examples/s]
Generating train split: 92577630 examples [1:35:38, 12504.75 examples/s]
Generating train split: 92579030 examples [1:35:38, 12296.40 examples/s]
Generating train split: 92580540 examples [1:35:38, 12993.19 examples/s]
Generating train split: 92582759 examples [1:35:38, 15373.94 examples/s]
Generating train split: 92584385 examples [1:35:38, 10502.64 examples/s]
Generating train split: 92585708 examples [1:35:39, 7903.98 examples/s] 
Generating train split: 92586819 examples [1:35:39, 8451.63 examples/s]
Generating train split: 92587899 examples [1:35:39, 8365.21 examples/s]
Generating train split: 92588891 examples [1:35:39, 6848.15 examples/s]
Generating train split: 92590133 examples [1:35:39, 7847.13 examples/s]
Generating train split: 92591068 examples [1:35:39, 6505.45 examples/s]
Generating train split: 92592533 examples [1:35:40, 8088.67 examples/s]
Generating train split: 92593524 examples [1:35:40, 8388.80 examples/s]
Generating train split: 92595122 examples [1:35:40, 10141.86 examples/s]
Generating train split: 92596697 examples [1:35:40, 11549.50 examples/s]
Generating train split: 92597988 examples [1:35:40, 8030.65 examples/s] 
Generating train split: 92599487 examples [1:35:40, 9423.91 examples/s]
Generating train split: 92600661 examples [1:35:41, 6465.96 examples/s]
Generating train split: 92601590 examples [1:35:41, 6794.20 examples/s]
Generating train split: 92602483 examples [1:35:41, 5640.78 examples/s]
Generating train split: 92603224 examples [1:35:41, 3706.62 examples/s]
Generating train split: 92603796 examples [1:35:42, 3533.40 examples/s]
Generating train split: 92604315 examples [1:35:42, 3708.09 examples/s]
Generating train split: 92604798 examples [1:35:42, 3792.11 examples/s]
Generating train split: 92605261 examples [1:35:42, 3853.39 examples/s]
Generating train split: 92605713 examples [1:35:42, 2796.28 examples/s]
Generating train split: 92606213 examples [1:35:42, 3119.83 examples/s]
Generating train split: 92606599 examples [1:35:43, 3037.51 examples/s]
Generating train split: 92606968 examples [1:35:43, 2772.30 examples/s]
Generating train split: 92609456 examples [1:35:43, 7303.91 examples/s]
Generating train split: 92612661 examples [1:35:43, 12911.69 examples/s]
Generating train split: 92614657 examples [1:35:43, 14626.35 examples/s]
Generating train split: 92616406 examples [1:35:43, 13584.48 examples/s]
Generating train split: 92618658 examples [1:35:43, 15567.35 examples/s]
Generating train split: 92620403 examples [1:35:44, 7959.75 examples/s] 
Generating train split: 92621725 examples [1:35:44, 6613.89 examples/s]
Generating train split: 92622781 examples [1:35:44, 5539.94 examples/s]
Generating train split: 92623930 examples [1:35:44, 6340.27 examples/s]
Generating train split: 92624913 examples [1:35:45, 6906.14 examples/s]
Generating train split: 92625861 examples [1:35:45, 5867.27 examples/s]
Generating train split: 92626657 examples [1:35:45, 5610.52 examples/s]
Generating train split: 92629299 examples [1:35:45, 9441.50 examples/s]
Generating train split: 92632142 examples [1:35:45, 13392.06 examples/s]
Generating train split: 92633894 examples [1:35:45, 10358.37 examples/s]
Generating train split: 92635313 examples [1:35:46, 8738.55 examples/s] 
Generating train split: 92636644 examples [1:35:46, 9241.85 examples/s]
Generating train split: 92637800 examples [1:35:46, 7863.20 examples/s]
Generating train split: 92638769 examples [1:35:46, 6702.85 examples/s]
Generating train split: 92639579 examples [1:35:46, 6815.12 examples/s]
Generating train split: 92640372 examples [1:35:46, 6277.48 examples/s]
Generating train split: 92641741 examples [1:35:47, 7732.42 examples/s]
Generating train split: 92642767 examples [1:35:47, 8264.13 examples/s]
Generating train split: 92643695 examples [1:35:47, 8359.03 examples/s]
Generating train split: 92645236 examples [1:35:47, 10025.79 examples/s]
Generating train split: 92646313 examples [1:35:47, 9857.44 examples/s] 
Generating train split: 92648212 examples [1:35:47, 12252.14 examples/s]
Generating train split: 92649508 examples [1:35:47, 11822.58 examples/s]
Generating train split: 92650742 examples [1:35:48, 6990.82 examples/s] 
Generating train split: 92651712 examples [1:35:48, 6863.74 examples/s]
Generating train split: 92659839 examples [1:35:48, 21356.68 examples/s]
Generating train split: 92668488 examples [1:35:48, 35535.03 examples/s]
Generating train split: 92673216 examples [1:35:49, 16921.86 examples/s]
Generating train split: 92676761 examples [1:35:49, 13209.41 examples/s]
Generating train split: 92679473 examples [1:35:50, 10395.04 examples/s]
Generating train split: 92681542 examples [1:35:50, 8228.63 examples/s] 
Generating train split: 92683183 examples [1:35:50, 8955.51 examples/s]
Generating train split: 92684759 examples [1:35:50, 7372.39 examples/s]
Generating train split: 92686391 examples [1:35:51, 8323.31 examples/s]
Generating train split: 92687712 examples [1:35:51, 8501.54 examples/s]
Generating train split: 92689536 examples [1:35:51, 9966.74 examples/s]
Generating train split: 92690902 examples [1:35:51, 10092.44 examples/s]
Generating train split: 92692173 examples [1:35:51, 9676.57 examples/s] 
Generating train split: 92694157 examples [1:35:51, 11757.83 examples/s]
Generating train split: 92695554 examples [1:35:51, 9185.01 examples/s] 
Generating train split: 92696713 examples [1:35:52, 5565.86 examples/s]
Generating train split: 92697589 examples [1:35:52, 5912.71 examples/s]
Generating train split: 92698450 examples [1:35:52, 5389.63 examples/s]
Generating train split: 92700085 examples [1:35:52, 7196.81 examples/s]
Generating train split: 92701095 examples [1:35:52, 7731.25 examples/s]
Generating train split: 92702094 examples [1:35:53, 5041.43 examples/s]
Generating train split: 92702868 examples [1:35:53, 5373.46 examples/s]
Generating train split: 92704075 examples [1:35:53, 6459.19 examples/s]
Generating train split: 92705715 examples [1:35:53, 8443.93 examples/s]
Generating train split: 92706799 examples [1:35:53, 6370.69 examples/s]
Generating train split: 92707984 examples [1:35:54, 7368.54 examples/s]
Generating train split: 92709018 examples [1:35:54, 7929.60 examples/s]
Generating train split: 92709997 examples [1:35:54, 7529.51 examples/s]
Generating train split: 92710885 examples [1:35:54, 5818.68 examples/s]
Generating train split: 92712025 examples [1:35:54, 6758.88 examples/s]
Generating train split: 92713298 examples [1:35:54, 8025.59 examples/s]
Generating train split: 92714500 examples [1:35:54, 8896.48 examples/s]
Generating train split: 92715525 examples [1:35:55, 5824.46 examples/s]
Generating train split: 92717401 examples [1:35:55, 8186.74 examples/s]
Generating train split: 92719422 examples [1:35:55, 10602.82 examples/s]
Generating train split: 92720871 examples [1:35:55, 11433.23 examples/s]
Generating train split: 92722266 examples [1:35:55, 6546.22 examples/s] 
Generating train split: 92723346 examples [1:35:56, 4395.48 examples/s]
Generating train split: 92724499 examples [1:35:56, 5262.72 examples/s]
Generating train split: 92725422 examples [1:35:56, 4755.38 examples/s]
Generating train split: 92726471 examples [1:35:56, 5559.46 examples/s]
Generating train split: 92727309 examples [1:35:57, 3841.88 examples/s]
Generating train split: 92733824 examples [1:35:57, 12132.84 examples/s]
Generating train split: 92742257 examples [1:35:57, 23820.48 examples/s]
Generating train split: 92747523 examples [1:35:57, 28542.22 examples/s]
Generating train split: 92751878 examples [1:35:58, 14986.37 examples/s]
Generating train split: 92755131 examples [1:35:58, 13423.31 examples/s]
Generating train split: 92757705 examples [1:35:59, 11101.13 examples/s]
Generating train split: 92759711 examples [1:35:59, 10734.64 examples/s]
Generating train split: 92761406 examples [1:35:59, 10836.80 examples/s]
Generating train split: 92762927 examples [1:35:59, 7728.44 examples/s] 
Generating train split: 92765702 examples [1:35:59, 10175.21 examples/s]
Generating train split: 92767351 examples [1:36:00, 10000.74 examples/s]
Generating train split: 92769660 examples [1:36:00, 12085.04 examples/s]
Generating train split: 92771357 examples [1:36:00, 11113.48 examples/s]
Generating train split: 92772811 examples [1:36:00, 11423.05 examples/s]
Generating train split: 92774205 examples [1:36:00, 6986.37 examples/s] 
Generating train split: 92775281 examples [1:36:01, 6816.23 examples/s]
Generating train split: 92776350 examples [1:36:01, 7431.43 examples/s]
Generating train split: 92777332 examples [1:36:01, 6515.92 examples/s]
Generating train split: 92779286 examples [1:36:01, 8848.80 examples/s]
Generating train split: 92780456 examples [1:36:01, 7814.13 examples/s]
Generating train split: 92781458 examples [1:36:01, 7283.47 examples/s]
Generating train split: 92782336 examples [1:36:02, 7010.11 examples/s]
Generating train split: 92783274 examples [1:36:02, 7445.34 examples/s]
Generating train split: 92784113 examples [1:36:02, 5299.81 examples/s]
Generating train split: 92784778 examples [1:36:02, 5484.90 examples/s]
Generating train split: 92786530 examples [1:36:02, 7953.61 examples/s]
Generating train split: 92787512 examples [1:36:02, 8323.86 examples/s]
Generating train split: 92788560 examples [1:36:02, 8844.41 examples/s]
Generating train split: 92789563 examples [1:36:03, 6900.60 examples/s]
Generating train split: 92790424 examples [1:36:03, 7221.64 examples/s]
Generating train split: 92791574 examples [1:36:03, 8230.14 examples/s]
Generating train split: 92792542 examples [1:36:03, 8093.23 examples/s]
Generating train split: 92793429 examples [1:36:03, 5728.25 examples/s]
Generating train split: 92796213 examples [1:36:03, 10137.56 examples/s]
Generating train split: 92797956 examples [1:36:03, 11745.36 examples/s]
Generating train split: 92799412 examples [1:36:04, 7484.46 examples/s] 
Generating train split: 92800548 examples [1:36:04, 7675.04 examples/s]
Generating train split: 92801597 examples [1:36:04, 6127.97 examples/s]
Generating train split: 92802670 examples [1:36:04, 6885.06 examples/s]
Generating train split: 92803592 examples [1:36:04, 6984.47 examples/s]
Generating train split: 92804453 examples [1:36:05, 6119.67 examples/s]
Generating train split: 92805220 examples [1:36:05, 6409.71 examples/s]
Generating train split: 92806223 examples [1:36:05, 7189.84 examples/s]
Generating train split: 92807051 examples [1:36:05, 6257.60 examples/s]
Generating train split: 92807805 examples [1:36:05, 6446.90 examples/s]
Generating train split: 92808523 examples [1:36:05, 5552.19 examples/s]
Generating train split: 92809140 examples [1:36:05, 4418.18 examples/s]
Generating train split: 92809661 examples [1:36:06, 3646.31 examples/s]
Generating train split: 92812517 examples [1:36:06, 8218.64 examples/s]
Generating train split: 92813672 examples [1:36:06, 7287.92 examples/s]
Generating train split: 92814961 examples [1:36:06, 8368.66 examples/s]
Generating train split: 92816026 examples [1:36:06, 6937.55 examples/s]
Generating train split: 92817592 examples [1:36:06, 8644.40 examples/s]
Generating train split: 92818691 examples [1:36:07, 7281.59 examples/s]
Generating train split: 92819609 examples [1:36:07, 6029.99 examples/s]
Generating train split: 92824585 examples [1:36:07, 14024.81 examples/s]
Generating train split: 92833276 examples [1:36:07, 29113.02 examples/s]
Generating train split: 92839245 examples [1:36:07, 36040.35 examples/s]
Generating train split: 92843842 examples [1:36:08, 19554.64 examples/s]
Generating train split: 92847348 examples [1:36:08, 17404.49 examples/s]
Generating train split: 92850196 examples [1:36:08, 13780.38 examples/s]
Generating train split: 92853509 examples [1:36:08, 16326.70 examples/s]
Generating train split: 92863187 examples [1:36:09, 29062.05 examples/s]
Generating train split: 92870234 examples [1:36:09, 36694.44 examples/s]
Generating train split: 92875626 examples [1:36:09, 17544.92 examples/s]
Generating train split: 92879630 examples [1:36:10, 15142.96 examples/s]
Generating train split: 92887759 examples [1:36:10, 22407.43 examples/s]
Generating train split: 92894939 examples [1:36:10, 29105.22 examples/s]
Generating train split: 92900332 examples [1:36:11, 18542.09 examples/s]
Generating train split: 92904382 examples [1:36:11, 13667.31 examples/s]
Generating train split: 92907433 examples [1:36:12, 10391.72 examples/s]
Generating train split: 92909719 examples [1:36:12, 10789.08 examples/s]
Generating train split: 92911720 examples [1:36:12, 9489.65 examples/s] 
Generating train split: 92913577 examples [1:36:12, 10446.63 examples/s]
Generating train split: 92915251 examples [1:36:12, 10643.61 examples/s]
Generating train split: 92922710 examples [1:36:13, 20292.50 examples/s]
Generating train split: 92931788 examples [1:36:13, 32793.55 examples/s]
Generating train split: 92936822 examples [1:36:14, 13498.08 examples/s]
Generating train split: 92940502 examples [1:36:15, 8645.46 examples/s] 
Generating train split: 92943209 examples [1:36:15, 7841.08 examples/s]
Generating train split: 92945273 examples [1:36:16, 6644.16 examples/s]
Generating train split: 92946836 examples [1:36:16, 6491.34 examples/s]
Generating train split: 92948098 examples [1:36:16, 6747.87 examples/s]
Generating train split: 92949245 examples [1:36:16, 6710.80 examples/s]
Generating train split: 92950241 examples [1:36:16, 5690.61 examples/s]
Generating train split: 92951820 examples [1:36:17, 6928.23 examples/s]
Generating train split: 92953259 examples [1:36:17, 7937.56 examples/s]
Generating train split: 92954385 examples [1:36:17, 5331.60 examples/s]
Generating train split: 92956046 examples [1:36:17, 6841.65 examples/s]
Generating train split: 92957160 examples [1:36:18, 5008.00 examples/s]
Generating train split: 92958929 examples [1:36:18, 6686.76 examples/s]
Generating train split: 92960061 examples [1:36:18, 5766.92 examples/s]
Generating train split: 92960971 examples [1:36:18, 4857.00 examples/s]
Generating train split: 92962609 examples [1:36:18, 6493.22 examples/s]
Generating train split: 92963610 examples [1:36:19, 5749.11 examples/s]
Generating train split: 92965147 examples [1:36:19, 7318.38 examples/s]
Generating train split: 92966636 examples [1:36:19, 8727.52 examples/s]
Generating train split: 92967812 examples [1:36:19, 6206.74 examples/s]
Generating train split: 92969324 examples [1:36:19, 7480.26 examples/s]
Generating train split: 92971644 examples [1:36:19, 10419.53 examples/s]
Generating train split: 92973203 examples [1:36:19, 11324.48 examples/s]
Generating train split: 92974622 examples [1:36:20, 7041.25 examples/s] 
Generating train split: 92976319 examples [1:36:20, 8636.49 examples/s]
Generating train split: 92977599 examples [1:36:21, 4618.79 examples/s]
Generating train split: 92978552 examples [1:36:21, 4245.12 examples/s]
Generating train split: 92979319 examples [1:36:21, 4338.92 examples/s]
Generating train split: 92986791 examples [1:36:21, 13994.08 examples/s]
Generating train split: 92995011 examples [1:36:21, 25164.44 examples/s]
Generating train split: 92999386 examples [1:36:22, 17407.67 examples/s]
Generating train split: 93002748 examples [1:36:22, 13611.65 examples/s]
Generating train split: 93010780 examples [1:36:22, 21768.92 examples/s]
Generating train split: 93019010 examples [1:36:22, 30574.10 examples/s]
Generating train split: 93024339 examples [1:36:23, 21035.94 examples/s]
Generating train split: 93028420 examples [1:36:23, 23375.45 examples/s]
Generating train split: 93032405 examples [1:36:23, 21833.39 examples/s]
Generating train split: 93035736 examples [1:36:23, 17198.03 examples/s]
Generating train split: 93038360 examples [1:36:24, 10546.19 examples/s]
Generating train split: 93040331 examples [1:36:25, 7619.89 examples/s] 
Generating train split: 93041810 examples [1:36:25, 8167.56 examples/s]
Generating train split: 93043962 examples [1:36:25, 9660.38 examples/s]
Generating train split: 93045611 examples [1:36:25, 9785.76 examples/s]
Generating train split: 93047074 examples [1:36:25, 8567.45 examples/s]
Generating train split: 93048283 examples [1:36:26, 6591.18 examples/s]
Generating train split: 93049242 examples [1:36:26, 4732.08 examples/s]
Generating train split: 93049967 examples [1:36:26, 4386.68 examples/s]
Generating train split: 93050579 examples [1:36:27, 3370.65 examples/s]
Generating train split: 93051181 examples [1:36:27, 3659.35 examples/s]
Generating train split: 93051688 examples [1:36:27, 3798.50 examples/s]
Generating train split: 93052898 examples [1:36:27, 5035.45 examples/s]
Generating train split: 93053550 examples [1:36:27, 4454.80 examples/s]
Generating train split: 93054626 examples [1:36:27, 5531.23 examples/s]
Generating train split: 93055317 examples [1:36:28, 4559.27 examples/s]
Generating train split: 93055895 examples [1:36:28, 4517.25 examples/s]
Generating train split: 93056428 examples [1:36:28, 4382.90 examples/s]
Generating train split: 93057234 examples [1:36:28, 5097.56 examples/s]
Generating train split: 93057812 examples [1:36:28, 3688.45 examples/s]
Generating train split: 93059283 examples [1:36:28, 5753.08 examples/s]
Generating train split: 93060333 examples [1:36:28, 6754.14 examples/s]
Generating train split: 93061192 examples [1:36:29, 4846.45 examples/s]
Generating train split: 93061870 examples [1:36:29, 4354.76 examples/s]
Generating train split: 93062623 examples [1:36:29, 4923.12 examples/s]
Generating train split: 93063264 examples [1:36:29, 4174.32 examples/s]
Generating train split: 93064916 examples [1:36:29, 6430.68 examples/s]
Generating train split: 93065759 examples [1:36:30, 6788.43 examples/s]
Generating train split: 93067023 examples [1:36:30, 7530.38 examples/s]
Generating train split: 93067898 examples [1:36:30, 4546.38 examples/s]
Generating train split: 93068573 examples [1:36:30, 4844.80 examples/s]
Generating train split: 93069241 examples [1:36:30, 4357.27 examples/s]
Generating train split: 93069802 examples [1:36:31, 3475.07 examples/s]
Generating train split: 93070356 examples [1:36:31, 3758.45 examples/s]
Generating train split: 93070838 examples [1:36:31, 3158.67 examples/s]
Generating train split: 93071241 examples [1:36:31, 3158.27 examples/s]
Generating train split: 93072007 examples [1:36:31, 4014.94 examples/s]
Generating train split: 93072765 examples [1:36:31, 4719.21 examples/s]
Generating train split: 93073327 examples [1:36:32, 3649.46 examples/s]
Generating train split: 93073844 examples [1:36:32, 3879.19 examples/s]
Generating train split: 93074307 examples [1:36:32, 3572.87 examples/s]
Generating train split: 93076207 examples [1:36:32, 6880.03 examples/s]
Generating train split: 93077070 examples [1:36:32, 5636.54 examples/s]
Generating train split: 93079075 examples [1:36:32, 8604.97 examples/s]
Generating train split: 93080179 examples [1:36:33, 4972.26 examples/s]
Generating train split: 93081024 examples [1:36:33, 4151.44 examples/s]
Generating train split: 93081705 examples [1:36:33, 3652.97 examples/s]
Generating train split: 93083284 examples [1:36:33, 5333.32 examples/s]
Generating train split: 93084143 examples [1:36:34, 3807.90 examples/s]
Generating train split: 93085342 examples [1:36:34, 4840.34 examples/s]
Generating train split: 93086425 examples [1:36:34, 5579.94 examples/s]
Generating train split: 93087248 examples [1:36:34, 4171.10 examples/s]
Generating train split: 93089137 examples [1:36:35, 6336.81 examples/s]
Generating train split: 93093552 examples [1:36:35, 12962.30 examples/s]
Generating train split: 93102633 examples [1:36:35, 28542.13 examples/s]
Generating train split: 93107967 examples [1:36:35, 31893.61 examples/s]
Generating train split: 93112099 examples [1:36:35, 18302.57 examples/s]
Generating train split: 93115257 examples [1:36:36, 19227.04 examples/s]
Generating train split: 93123848 examples [1:36:36, 30458.48 examples/s]
Generating train split: 93131878 examples [1:36:36, 39897.46 examples/s]
Generating train split: 93137451 examples [1:36:37, 16894.35 examples/s]
Generating train split: 93141551 examples [1:36:37, 12508.79 examples/s]
Generating train split: 93144622 examples [1:36:38, 10023.03 examples/s]
Generating train split: 93146934 examples [1:36:38, 9889.75 examples/s] 
Generating train split: 93148839 examples [1:36:38, 10493.19 examples/s]
Generating train split: 93151324 examples [1:36:38, 12141.37 examples/s]
Generating train split: 93153296 examples [1:36:38, 12281.09 examples/s]
Generating train split: 93155060 examples [1:36:39, 10259.05 examples/s]
Generating train split: 93156923 examples [1:36:39, 11521.01 examples/s]
Generating train split: 93158490 examples [1:36:39, 10573.87 examples/s]
Generating train split: 93159832 examples [1:36:39, 7231.15 examples/s] 
Generating train split: 93161346 examples [1:36:39, 8361.77 examples/s]
Generating train split: 93162530 examples [1:36:40, 8940.26 examples/s]
Generating train split: 93163716 examples [1:36:40, 6982.93 examples/s]
Generating train split: 93166675 examples [1:36:40, 10809.81 examples/s]
Generating train split: 93168226 examples [1:36:40, 10670.95 examples/s]
Generating train split: 93169663 examples [1:36:40, 11414.03 examples/s]
Generating train split: 93171076 examples [1:36:40, 8327.29 examples/s] 
Generating train split: 93172203 examples [1:36:41, 7705.64 examples/s]
Generating train split: 93173182 examples [1:36:41, 7643.34 examples/s]
Generating train split: 93174089 examples [1:36:41, 5602.95 examples/s]
Generating train split: 93174815 examples [1:36:41, 5759.78 examples/s]
Generating train split: 93176151 examples [1:36:41, 7200.62 examples/s]
Generating train split: 93177075 examples [1:36:41, 7351.45 examples/s]
Generating train split: 93177933 examples [1:36:42, 5406.43 examples/s]
Generating train split: 93178755 examples [1:36:42, 5810.24 examples/s]
Generating train split: 93179559 examples [1:36:42, 6263.63 examples/s]
Generating train split: 93181265 examples [1:36:42, 8634.53 examples/s]
Generating train split: 93182270 examples [1:36:42, 5065.55 examples/s]
Generating train split: 93183757 examples [1:36:43, 6655.74 examples/s]
Generating train split: 93185392 examples [1:36:43, 8460.36 examples/s]
Generating train split: 93186563 examples [1:36:43, 9080.62 examples/s]
Generating train split: 93187731 examples [1:36:43, 6474.57 examples/s]
Generating train split: 93190321 examples [1:36:43, 9930.36 examples/s]
Generating train split: 93191717 examples [1:36:44, 4285.00 examples/s]
Generating train split: 93192751 examples [1:36:44, 4073.75 examples/s]
Generating train split: 93193579 examples [1:36:44, 4295.10 examples/s]
Generating train split: 93194323 examples [1:36:45, 3353.13 examples/s]
Generating train split: 93195715 examples [1:36:45, 4538.76 examples/s]
Generating train split: 93196502 examples [1:36:45, 4194.13 examples/s]
Generating train split: 93197156 examples [1:36:45, 4375.64 examples/s]
Generating train split: 93198244 examples [1:36:45, 5362.00 examples/s]
Generating train split: 93198973 examples [1:36:46, 5252.13 examples/s]
Generating train split: 93199645 examples [1:36:46, 3837.77 examples/s]
Generating train split: 93200438 examples [1:36:46, 4464.96 examples/s]
Generating train split: 93201032 examples [1:36:46, 2971.54 examples/s]
Generating train split: 93201494 examples [1:36:47, 2468.43 examples/s]
Generating train split: 93201858 examples [1:36:47, 2214.66 examples/s]
Generating train split: 93202738 examples [1:36:47, 3139.02 examples/s]
Generating train split: 93203221 examples [1:36:47, 3407.34 examples/s]
Generating train split: 93204411 examples [1:36:47, 4949.54 examples/s]
Generating train split: 93205076 examples [1:36:48, 4132.17 examples/s]
Generating train split: 93205794 examples [1:36:48, 4689.58 examples/s]
Generating train split: 93206389 examples [1:36:48, 4636.51 examples/s]
Generating train split: 93207794 examples [1:36:48, 6702.36 examples/s]
Generating train split: 93208598 examples [1:36:48, 5354.42 examples/s]
Generating train split: 93210290 examples [1:36:48, 7674.96 examples/s]
Generating train split: 93211252 examples [1:36:49, 4487.94 examples/s]
Generating train split: 93211986 examples [1:36:49, 3981.33 examples/s]
Generating train split: 93212590 examples [1:36:49, 2985.65 examples/s]
Generating train split: 93213054 examples [1:36:49, 2777.04 examples/s]
Generating train split: 93213451 examples [1:36:50, 2740.33 examples/s]
Generating train split: 93213816 examples [1:36:50, 2734.48 examples/s]
Generating train split: 93214151 examples [1:36:50, 2397.37 examples/s]
Generating train split: 93214747 examples [1:36:50, 3013.74 examples/s]
Generating train split: 93215471 examples [1:36:50, 3792.62 examples/s]
Generating train split: 93215936 examples [1:36:50, 3605.95 examples/s]
Generating train split: 93218036 examples [1:36:50, 7428.79 examples/s]
Generating train split: 93218957 examples [1:36:51, 6838.77 examples/s]
Generating train split: 93220976 examples [1:36:51, 9897.31 examples/s]
Generating train split: 93222159 examples [1:36:51, 8049.38 examples/s]
Generating train split: 93223168 examples [1:36:51, 6800.58 examples/s]
Generating train split: 93224004 examples [1:36:51, 6330.15 examples/s]
Generating train split: 93224747 examples [1:36:52, 3060.15 examples/s]
Generating train split: 93225314 examples [1:36:52, 3158.18 examples/s]
Generating train split: 93226019 examples [1:36:52, 3685.77 examples/s]
Generating train split: 93226588 examples [1:36:52, 3165.76 examples/s]
Generating train split: 93228639 examples [1:36:53, 5855.08 examples/s]
Generating train split: 93229575 examples [1:36:53, 6153.31 examples/s]
Generating train split: 93230945 examples [1:36:53, 7603.24 examples/s]
Generating train split: 93231963 examples [1:36:53, 6301.29 examples/s]
Generating train split: 93233370 examples [1:36:53, 7751.29 examples/s]
Generating train split: 93234361 examples [1:36:53, 7306.65 examples/s]
Generating train split: 93236244 examples [1:36:53, 9638.08 examples/s]
Generating train split: 93237394 examples [1:36:54, 8562.83 examples/s]
Generating train split: 93238399 examples [1:36:54, 8710.08 examples/s]
Generating train split: 93239749 examples [1:36:54, 9837.87 examples/s]
Generating train split: 93240836 examples [1:36:54, 6295.57 examples/s]
Generating train split: 93241703 examples [1:36:54, 6471.43 examples/s]
Generating train split: 93242966 examples [1:36:54, 7702.90 examples/s]
Generating train split: 93244107 examples [1:36:54, 8522.03 examples/s]
Generating train split: 93245119 examples [1:36:55, 7220.24 examples/s]
Generating train split: 93245987 examples [1:36:55, 6572.69 examples/s]
Generating train split: 93247750 examples [1:36:55, 8906.53 examples/s]
Generating train split: 93248800 examples [1:36:55, 6554.27 examples/s]
Generating train split: 93249648 examples [1:36:56, 4782.64 examples/s]
Generating train split: 93250328 examples [1:36:56, 4374.36 examples/s]
Generating train split: 93250899 examples [1:36:56, 3675.25 examples/s]
Generating train split: 93255682 examples [1:36:56, 10592.00 examples/s]
Generating train split: 93264490 examples [1:36:56, 24761.13 examples/s]
Generating train split: 93269737 examples [1:36:56, 29176.34 examples/s]
Generating train split: 93273745 examples [1:36:57, 13151.34 examples/s]
Generating train split: 93282614 examples [1:36:57, 21913.11 examples/s]
Generating train split: 93290058 examples [1:36:57, 29379.74 examples/s]
Generating train split: 93295614 examples [1:36:58, 18567.98 examples/s]
Generating train split: 93299794 examples [1:36:59, 12996.37 examples/s]
Generating train split: 93307285 examples [1:36:59, 18726.59 examples/s]
Generating train split: 93315469 examples [1:36:59, 26096.51 examples/s]
Generating train split: 93321026 examples [1:36:59, 17236.78 examples/s]
Generating train split: 93325190 examples [1:37:00, 12913.44 examples/s]
Generating train split: 93328305 examples [1:37:00, 13312.78 examples/s]
Generating train split: 93330990 examples [1:37:00, 14640.71 examples/s]
Generating train split: 93339283 examples [1:37:00, 23416.69 examples/s]
Generating train split: 93348513 examples [1:37:00, 34097.96 examples/s]
Generating train split: 93354376 examples [1:37:01, 38546.32 examples/s]
Generating train split: 93360352 examples [1:37:01, 42907.86 examples/s]
Generating train split: 93366302 examples [1:37:01, 46672.06 examples/s]
Generating train split: 93373454 examples [1:37:01, 52728.09 examples/s]
Generating train split: 93380782 examples [1:37:01, 58048.69 examples/s]
Generating train split: 93389093 examples [1:37:01, 64805.78 examples/s]
Generating train split: 93396431 examples [1:37:01, 67183.11 examples/s]
Generating train split: 93405166 examples [1:37:01, 72897.48 examples/s]
Generating train split: 93413049 examples [1:37:01, 74602.09 examples/s]
Generating train split: 93421290 examples [1:37:01, 76881.82 examples/s]
Generating train split: 93429513 examples [1:37:02, 78432.79 examples/s]
Generating train split: 93437607 examples [1:37:02, 79151.57 examples/s]
Generating train split: 93445614 examples [1:37:02, 77884.05 examples/s]
Generating train split: 93453476 examples [1:37:02, 75179.91 examples/s]
Generating train split: 93461071 examples [1:37:02, 74298.35 examples/s]
Generating train split: 93468553 examples [1:37:02, 72238.50 examples/s]
Generating train split: 93475828 examples [1:37:02, 69497.91 examples/s]
Generating train split: 93482823 examples [1:37:02, 67110.93 examples/s]
Generating train split: 93489576 examples [1:37:02, 63399.02 examples/s]
Generating train split: 93496303 examples [1:37:03, 64453.46 examples/s]
Generating train split: 93502795 examples [1:37:03, 63000.53 examples/s]
Generating train split: 93510933 examples [1:37:03, 68163.17 examples/s]
Generating train split: 93517945 examples [1:37:03, 68602.14 examples/s]
Generating train split: 93525029 examples [1:37:03, 69249.03 examples/s]
Generating train split: 93531988 examples [1:37:03, 66700.22 examples/s]
Generating train split: 93538945 examples [1:37:03, 67505.58 examples/s]
Generating train split: 93545736 examples [1:37:03, 63602.77 examples/s]
Generating train split: 93552166 examples [1:37:03, 62174.04 examples/s]
Generating train split: 93558434 examples [1:37:04, 51195.36 examples/s]
Generating train split: 93563882 examples [1:37:04, 47469.11 examples/s]
Generating train split: 93568873 examples [1:37:04, 40679.87 examples/s]
Generating train split: 93573225 examples [1:37:05, 17269.45 examples/s]
Generating train split: 93576456 examples [1:37:06, 8498.16 examples/s] 
Generating train split: 93578803 examples [1:37:06, 8311.86 examples/s]
Generating train split: 93580672 examples [1:37:07, 6713.38 examples/s]
Generating train split: 93582082 examples [1:37:07, 6756.76 examples/s]
Generating train split: 93583284 examples [1:37:07, 6928.88 examples/s]
Generating train split: 93585296 examples [1:37:07, 8418.65 examples/s]
Generating train split: 93591856 examples [1:37:07, 16388.37 examples/s]
Generating train split: 93600902 examples [1:37:07, 28684.83 examples/s]
Generating train split: 93605656 examples [1:37:08, 24184.01 examples/s]
Generating train split: 93609504 examples [1:37:08, 14920.95 examples/s]
Generating train split: 93612413 examples [1:37:08, 13347.08 examples/s]
Generating train split: 93614732 examples [1:37:09, 13753.73 examples/s]
Generating train split: 93616836 examples [1:37:09, 14726.52 examples/s]
Generating train split: 93618922 examples [1:37:09, 11583.62 examples/s]
Generating train split: 93620578 examples [1:37:09, 12026.68 examples/s]
Generating train split: 93622169 examples [1:37:09, 12653.90 examples/s]
Generating train split: 93623804 examples [1:37:09, 13331.62 examples/s]
Generating train split: 93625393 examples [1:37:10, 9042.16 examples/s] 
Generating train split: 93626964 examples [1:37:10, 10154.75 examples/s]
Generating train split: 93628912 examples [1:37:10, 11964.14 examples/s]
Generating train split: 93630440 examples [1:37:10, 11483.46 examples/s]
Generating train split: 93631830 examples [1:37:10, 8672.80 examples/s] 
Generating train split: 93633176 examples [1:37:10, 9431.89 examples/s]
Generating train split: 93634334 examples [1:37:11, 8551.51 examples/s]
Generating train split: 93642936 examples [1:37:11, 24308.71 examples/s]
Generating train split: 93651390 examples [1:37:11, 37866.78 examples/s]
Generating train split: 93656229 examples [1:37:11, 15984.96 examples/s]
Generating train split: 93659823 examples [1:37:12, 11075.60 examples/s]
Generating train split: 93662505 examples [1:37:13, 6684.27 examples/s] 
Generating train split: 93664465 examples [1:37:14, 6301.93 examples/s]
Generating train split: 93665982 examples [1:37:14, 6349.62 examples/s]
Generating train split: 93673686 examples [1:37:14, 12554.34 examples/s]
Generating train split: 93682070 examples [1:37:14, 20496.62 examples/s]
Generating train split: 93686824 examples [1:37:15, 14284.41 examples/s]
Generating train split: 93690384 examples [1:37:16, 6926.89 examples/s] 
Generating train split: 93692962 examples [1:37:17, 5515.60 examples/s]
Generating train split: 93694858 examples [1:37:18, 4353.52 examples/s]
Generating train split: 93696240 examples [1:37:18, 3912.68 examples/s]
Generating train split: 93697285 examples [1:37:18, 4250.74 examples/s]
Generating train split: 93698305 examples [1:37:19, 4198.79 examples/s]
Generating train split: 93700434 examples [1:37:19, 5662.50 examples/s]
Generating train split: 93701653 examples [1:37:19, 6373.93 examples/s]
Generating train split: 93702878 examples [1:37:19, 5631.41 examples/s]
Generating train split: 93704794 examples [1:37:19, 7404.35 examples/s]
Generating train split: 93706049 examples [1:37:20, 6750.16 examples/s]
Generating train split: 93708106 examples [1:37:20, 8746.04 examples/s]
Generating train split: 93709390 examples [1:37:20, 8498.27 examples/s]
Generating train split: 93710519 examples [1:37:20, 6179.79 examples/s]
Generating train split: 93711414 examples [1:37:20, 6520.08 examples/s]
Generating train split: 93712608 examples [1:37:20, 7490.89 examples/s]
Generating train split: 93713578 examples [1:37:21, 4702.61 examples/s]
Generating train split: 93714968 examples [1:37:21, 6051.08 examples/s]
Generating train split: 93716093 examples [1:37:21, 6919.60 examples/s]
Generating train split: 93717085 examples [1:37:21, 7172.46 examples/s]
Generating train split: 93719393 examples [1:37:21, 10433.10 examples/s]
Generating train split: 93720709 examples [1:37:22, 7961.60 examples/s] 
Generating train split: 93721779 examples [1:37:22, 6998.23 examples/s]
Generating train split: 93722993 examples [1:37:22, 7944.69 examples/s]
Generating train split: 93723985 examples [1:37:22, 7813.57 examples/s]
Generating train split: 93724906 examples [1:37:22, 7076.09 examples/s]
Generating train split: 93733590 examples [1:37:22, 24089.89 examples/s]
Generating train split: 93742543 examples [1:37:22, 39366.67 examples/s]
Generating train split: 93747452 examples [1:37:23, 26842.04 examples/s]
Generating train split: 93751347 examples [1:37:23, 15234.36 examples/s]
Generating train split: 93754272 examples [1:37:24, 13183.22 examples/s]
Generating train split: 93756581 examples [1:37:24, 9529.54 examples/s] 
Generating train split: 93758331 examples [1:37:24, 8020.93 examples/s]
Generating train split: 93760479 examples [1:37:25, 9385.83 examples/s]
Generating train split: 93770187 examples [1:37:25, 20485.65 examples/s]
Generating train split: 93778792 examples [1:37:25, 30051.62 examples/s]
Generating train split: 93783959 examples [1:37:25, 17809.07 examples/s]
Generating train split: 93787839 examples [1:37:26, 12177.74 examples/s]
Generating train split: 93790739 examples [1:37:27, 10396.20 examples/s]
Generating train split: 93792953 examples [1:37:27, 10789.45 examples/s]
Generating train split: 93794909 examples [1:37:27, 8601.53 examples/s] 
Generating train split: 93796551 examples [1:37:27, 9391.27 examples/s]
Generating train split: 93798087 examples [1:37:28, 7032.08 examples/s]
Generating train split: 93806985 examples [1:37:28, 16172.71 examples/s]
Generating train split: 93815202 examples [1:37:28, 24785.28 examples/s]
Generating train split: 93819826 examples [1:37:29, 14379.63 examples/s]
Generating train split: 93823260 examples [1:37:29, 9843.04 examples/s] 
Generating train split: 93831412 examples [1:37:29, 15744.19 examples/s]
Generating train split: 93840437 examples [1:37:30, 23423.93 examples/s]
Generating train split: 93845945 examples [1:37:30, 21497.50 examples/s]
Generating train split: 93850326 examples [1:37:30, 14853.16 examples/s]
Generating train split: 93853604 examples [1:37:31, 10021.90 examples/s]
Generating train split: 93856042 examples [1:37:31, 10642.54 examples/s]
Generating train split: 93858203 examples [1:37:32, 7382.05 examples/s] 
Generating train split: 93859807 examples [1:37:32, 6448.70 examples/s]
Generating train split: 93861043 examples [1:37:33, 5404.75 examples/s]
Generating train split: 93861993 examples [1:37:33, 5409.50 examples/s]
Generating train split: 93862830 examples [1:37:33, 4594.11 examples/s]
Generating train split: 93863491 examples [1:37:34, 4606.51 examples/s]
Generating train split: 93864509 examples [1:37:34, 5242.02 examples/s]
Generating train split: 93865210 examples [1:37:34, 4570.15 examples/s]
Generating train split: 93865868 examples [1:37:34, 4871.84 examples/s]
Generating train split: 93866703 examples [1:37:34, 5489.31 examples/s]
Generating train split: 93867374 examples [1:37:34, 4735.34 examples/s]
Generating train split: 93869339 examples [1:37:34, 7586.82 examples/s]
Generating train split: 93871072 examples [1:37:35, 9665.97 examples/s]
Generating train split: 93872276 examples [1:37:35, 6290.39 examples/s]
Generating train split: 93873641 examples [1:37:35, 7519.71 examples/s]
Generating train split: 93874699 examples [1:37:35, 7041.87 examples/s]
Generating train split: 93875620 examples [1:37:35, 6426.30 examples/s]
Generating train split: 93876428 examples [1:37:35, 6545.42 examples/s]
Generating train split: 93877448 examples [1:37:36, 6829.92 examples/s]
Generating train split: 93878217 examples [1:37:36, 6440.24 examples/s]
Generating train split: 93878916 examples [1:37:36, 5746.53 examples/s]
Generating train split: 93879536 examples [1:37:36, 4931.79 examples/s]
Generating train split: 93880074 examples [1:37:36, 4891.40 examples/s]
Generating train split: 93881891 examples [1:37:36, 7837.53 examples/s]
Generating train split: 93884058 examples [1:37:36, 11184.22 examples/s]
Generating train split: 93885349 examples [1:37:37, 10490.41 examples/s]
Generating train split: 93886518 examples [1:37:37, 9938.91 examples/s] 
Generating train split: 93889789 examples [1:37:37, 15553.32 examples/s]
Generating train split: 93892613 examples [1:37:37, 18851.64 examples/s]
Generating train split: 93894677 examples [1:37:37, 19107.39 examples/s]
Generating train split: 93896717 examples [1:37:37, 18931.55 examples/s]
Generating train split: 93898698 examples [1:37:37, 12211.90 examples/s]
Generating train split: 93900444 examples [1:37:38, 13238.28 examples/s]
Generating train split: 93902068 examples [1:37:38, 13434.16 examples/s]
Generating train split: 93904556 examples [1:37:38, 16128.91 examples/s]
Generating train split: 93906401 examples [1:37:38, 13289.64 examples/s]
Generating train split: 93909260 examples [1:37:38, 16690.84 examples/s]
Generating train split: 93911211 examples [1:37:38, 11894.31 examples/s]
Generating train split: 93916870 examples [1:37:38, 20418.11 examples/s]
Generating train split: 93926693 examples [1:37:39, 37078.76 examples/s]
Generating train split: 93931596 examples [1:37:39, 33510.78 examples/s]
Generating train split: 93935842 examples [1:37:39, 16634.21 examples/s]
Generating train split: 93939034 examples [1:37:40, 12190.69 examples/s]
Generating train split: 93945809 examples [1:37:40, 18144.50 examples/s]
Generating train split: 93953135 examples [1:37:40, 25378.09 examples/s]
Generating train split: 93957893 examples [1:37:41, 11669.62 examples/s]
Generating train split: 93961356 examples [1:37:42, 10022.93 examples/s]
Generating train split: 93963990 examples [1:37:42, 7541.75 examples/s] 
Generating train split: 93965936 examples [1:37:43, 7646.34 examples/s]
Generating train split: 93967547 examples [1:37:43, 6221.97 examples/s]
Generating train split: 93970786 examples [1:37:43, 8387.32 examples/s]
Generating train split: 93973062 examples [1:37:43, 9891.82 examples/s]
Generating train split: 93975018 examples [1:37:43, 10848.93 examples/s]
Generating train split: 93976868 examples [1:37:44, 9045.36 examples/s] 
Generating train split: 93978339 examples [1:37:44, 9361.47 examples/s]
Generating train split: 93979688 examples [1:37:44, 9916.43 examples/s]
Generating train split: 93981013 examples [1:37:44, 6906.21 examples/s]
Generating train split: 93982047 examples [1:37:44, 7324.75 examples/s]
Generating train split: 93983427 examples [1:37:45, 8438.06 examples/s]
Generating train split: 93985706 examples [1:37:45, 11272.97 examples/s]
Generating train split: 93987171 examples [1:37:45, 7134.28 examples/s] 
Generating train split: 93989324 examples [1:37:45, 9370.85 examples/s]
Generating train split: 93990755 examples [1:37:45, 9103.20 examples/s]
Generating train split: 93992496 examples [1:37:45, 10660.18 examples/s]
Generating train split: 93994099 examples [1:37:46, 11787.73 examples/s]
Generating train split: 93995737 examples [1:37:46, 12831.51 examples/s]
Generating train split: 93997257 examples [1:37:46, 12795.44 examples/s]
Generating train split: 93998695 examples [1:37:46, 11153.37 examples/s]
Generating train split: 93999954 examples [1:37:46, 10393.76 examples/s]
Generating train split: 94001098 examples [1:37:46, 9881.01 examples/s] 
Generating train split: 94003572 examples [1:37:46, 13344.41 examples/s]
Generating train split: 94005052 examples [1:37:46, 11795.40 examples/s]
Generating train split: 94006355 examples [1:37:47, 9497.92 examples/s] 
Generating train split: 94007453 examples [1:37:47, 9273.19 examples/s]
Generating train split: 94008797 examples [1:37:47, 10172.04 examples/s]
Generating train split: 94009925 examples [1:37:47, 9778.18 examples/s] 
Generating train split: 94011313 examples [1:37:47, 10771.54 examples/s]
Generating train split: 94012515 examples [1:37:47, 11066.11 examples/s]
Generating train split: 94013677 examples [1:37:47, 11159.46 examples/s]
Generating train split: 94014840 examples [1:37:48, 6771.76 examples/s] 
Generating train split: 94015756 examples [1:37:48, 6891.34 examples/s]
Generating train split: 94016995 examples [1:37:48, 7999.36 examples/s]
Generating train split: 94017967 examples [1:37:48, 7519.02 examples/s]
Generating train split: 94018838 examples [1:37:48, 6113.43 examples/s]
Generating train split: 94020617 examples [1:37:48, 8469.23 examples/s]
Generating train split: 94021669 examples [1:37:49, 7432.91 examples/s]
Generating train split: 94023506 examples [1:37:49, 9716.22 examples/s]
Generating train split: 94025302 examples [1:37:49, 11608.78 examples/s]
Generating train split: 94026663 examples [1:37:49, 11802.02 examples/s]
Generating train split: 94028046 examples [1:37:49, 12270.12 examples/s]
Generating train split: 94029958 examples [1:37:49, 14075.88 examples/s]
Generating train split: 94031466 examples [1:37:49, 14261.20 examples/s]
Generating train split: 94032965 examples [1:37:49, 9558.18 examples/s] 
Generating train split: 94034172 examples [1:37:50, 7392.50 examples/s]
Generating train split: 94035859 examples [1:37:50, 8966.56 examples/s]
Generating train split: 94037793 examples [1:37:50, 11053.02 examples/s]
Generating train split: 94039180 examples [1:37:50, 10434.00 examples/s]
Generating train split: 94040420 examples [1:37:50, 9652.59 examples/s] 
Generating train split: 94041530 examples [1:37:50, 9778.15 examples/s]
Generating train split: 94043258 examples [1:37:50, 11542.27 examples/s]
Generating train split: 94045392 examples [1:37:51, 13995.94 examples/s]
Generating train split: 94046934 examples [1:37:51, 9316.39 examples/s] 
Generating train split: 94048159 examples [1:37:51, 9076.19 examples/s]
Generating train split: 94049306 examples [1:37:51, 9546.77 examples/s]
Generating train split: 94056780 examples [1:37:51, 24278.98 examples/s]
Generating train split: 94064904 examples [1:37:51, 37667.90 examples/s]
Generating train split: 94069338 examples [1:37:52, 18016.77 examples/s]
Generating train split: 94072674 examples [1:37:52, 18757.25 examples/s]
Generating train split: 94075663 examples [1:37:53, 8855.47 examples/s] 
Generating train split: 94077847 examples [1:37:54, 6920.34 examples/s]
Generating train split: 94079495 examples [1:37:54, 6237.94 examples/s]
Generating train split: 94080770 examples [1:37:54, 5245.28 examples/s]
Generating train split: 94081754 examples [1:37:55, 4924.45 examples/s]
Generating train split: 94082913 examples [1:37:55, 5536.66 examples/s]
Generating train split: 94083800 examples [1:37:55, 4938.77 examples/s]
Generating train split: 94084551 examples [1:37:55, 5261.80 examples/s]
Generating train split: 94086069 examples [1:37:55, 6772.73 examples/s]
Generating train split: 94087033 examples [1:37:55, 6252.07 examples/s]
Generating train split: 94087923 examples [1:37:56, 6721.45 examples/s]
Generating train split: 94088775 examples [1:37:56, 6994.67 examples/s]
Generating train split: 94090138 examples [1:37:56, 8471.19 examples/s]
Generating train split: 94091137 examples [1:37:56, 8427.87 examples/s]
Generating train split: 94092083 examples [1:37:56, 5312.80 examples/s]
Generating train split: 94092832 examples [1:37:56, 5628.37 examples/s]
Generating train split: 94093564 examples [1:37:56, 5150.44 examples/s]
Generating train split: 94095026 examples [1:37:57, 6994.24 examples/s]
Generating train split: 94095904 examples [1:37:57, 7235.83 examples/s]
Generating train split: 94098334 examples [1:37:57, 11240.99 examples/s]
Generating train split: 94100758 examples [1:37:57, 14382.08 examples/s]
Generating train split: 94102386 examples [1:37:57, 7526.99 examples/s] 
Generating train split: 94103633 examples [1:37:58, 4816.81 examples/s]
Generating train split: 94105643 examples [1:37:58, 6594.60 examples/s]
Generating train split: 94106987 examples [1:37:58, 7282.78 examples/s]
Generating train split: 94108182 examples [1:37:58, 7836.03 examples/s]
Generating train split: 94109330 examples [1:37:58, 8290.06 examples/s]
Generating train split: 94110437 examples [1:37:59, 8779.46 examples/s]
Generating train split: 94111539 examples [1:37:59, 8905.84 examples/s]
Generating train split: 94112583 examples [1:37:59, 8663.41 examples/s]
Generating train split: 94113746 examples [1:37:59, 9369.34 examples/s]
Generating train split: 94114782 examples [1:37:59, 8581.48 examples/s]
Generating train split: 94116305 examples [1:37:59, 10187.29 examples/s]
Generating train split: 94117410 examples [1:37:59, 9208.05 examples/s] 
Generating train split: 94118414 examples [1:37:59, 9218.76 examples/s]
Generating train split: 94119810 examples [1:37:59, 10392.81 examples/s]
Generating train split: 94120904 examples [1:38:00, 9119.73 examples/s] 
Generating train split: 94125007 examples [1:38:00, 17045.12 examples/s]
Generating train split: 94131745 examples [1:38:00, 30222.02 examples/s]
Generating train split: 94137060 examples [1:38:00, 36462.47 examples/s]
Generating train split: 94141008 examples [1:38:00, 17386.80 examples/s]
Generating train split: 94144010 examples [1:38:01, 13036.51 examples/s]
Generating train split: 94146330 examples [1:38:01, 10108.33 examples/s]
Generating train split: 94148120 examples [1:38:02, 8145.93 examples/s] 
Generating train split: 94149510 examples [1:38:02, 7158.44 examples/s]
Generating train split: 94150620 examples [1:38:02, 6675.48 examples/s]
Generating train split: 94151659 examples [1:38:02, 7134.27 examples/s]
Generating train split: 94152617 examples [1:38:03, 6321.58 examples/s]
Generating train split: 94153518 examples [1:38:03, 6730.46 examples/s]
Generating train split: 94154351 examples [1:38:03, 5768.86 examples/s]
Generating train split: 94156290 examples [1:38:03, 8137.98 examples/s]
Generating train split: 94157357 examples [1:38:03, 5974.97 examples/s]
Generating train split: 94158441 examples [1:38:03, 6698.83 examples/s]
Generating train split: 94159506 examples [1:38:03, 7440.26 examples/s]
Generating train split: 94160685 examples [1:38:04, 8318.05 examples/s]
Generating train split: 94161794 examples [1:38:04, 8758.67 examples/s]
Generating train split: 94162806 examples [1:38:04, 8069.55 examples/s]
Generating train split: 94163904 examples [1:38:04, 8756.09 examples/s]
Generating train split: 94164868 examples [1:38:04, 6026.77 examples/s]
Generating train split: 94165956 examples [1:38:04, 6971.32 examples/s]
Generating train split: 94167639 examples [1:38:04, 9115.06 examples/s]
Generating train split: 94168750 examples [1:38:05, 9429.13 examples/s]
Generating train split: 94169852 examples [1:38:05, 8006.95 examples/s]
Generating train split: 94171468 examples [1:38:05, 9720.70 examples/s]
Generating train split: 94172583 examples [1:38:05, 9152.53 examples/s]
Generating train split: 94173609 examples [1:38:05, 7753.39 examples/s]
Generating train split: 94174486 examples [1:38:05, 6242.60 examples/s]
Generating train split: 94175546 examples [1:38:05, 7090.42 examples/s]
Generating train split: 94181796 examples [1:38:06, 19231.79 examples/s]
Generating train split: 94190932 examples [1:38:06, 36419.15 examples/s]
Generating train split: 94195854 examples [1:38:06, 38284.59 examples/s]
Generating train split: 94200272 examples [1:38:06, 18837.27 examples/s]
Generating train split: 94203610 examples [1:38:07, 13741.36 examples/s]
Generating train split: 94206168 examples [1:38:07, 10425.21 examples/s]
Generating train split: 94208128 examples [1:38:07, 11292.48 examples/s]
Generating train split: 94210037 examples [1:38:08, 9111.97 examples/s] 
Generating train split: 94211525 examples [1:38:08, 8260.25 examples/s]
Generating train split: 94212755 examples [1:38:08, 8507.17 examples/s]
Generating train split: 94213904 examples [1:38:08, 6989.42 examples/s]
Generating train split: 94215569 examples [1:38:09, 8359.20 examples/s]
Generating train split: 94216726 examples [1:38:09, 7889.05 examples/s]
Generating train split: 94217728 examples [1:38:09, 6480.92 examples/s]
Generating train split: 94225740 examples [1:38:09, 18666.44 examples/s]
Generating train split: 94234761 examples [1:38:09, 32341.99 examples/s]
Generating train split: 94239559 examples [1:38:09, 27464.28 examples/s]
Generating train split: 94243517 examples [1:38:10, 19027.97 examples/s]
Generating train split: 94246587 examples [1:38:10, 19149.65 examples/s]
Generating train split: 94249328 examples [1:38:10, 13706.33 examples/s]
Generating train split: 94251462 examples [1:38:10, 14373.67 examples/s]
Generating train split: 94253485 examples [1:38:11, 11641.26 examples/s]
Generating train split: 94255117 examples [1:38:11, 10536.26 examples/s]
Generating train split: 94256480 examples [1:38:11, 8055.28 examples/s] 
Generating train split: 94257559 examples [1:38:12, 7404.64 examples/s]
Generating train split: 94260000 examples [1:38:12, 9899.57 examples/s]
Generating train split: 94261372 examples [1:38:12, 9567.02 examples/s]
Generating train split: 94262599 examples [1:38:12, 7796.06 examples/s]
Generating train split: 94263875 examples [1:38:12, 8627.10 examples/s]
Generating train split: 94265254 examples [1:38:12, 9617.09 examples/s]
Generating train split: 94266419 examples [1:38:13, 6088.95 examples/s]
Generating train split: 94267328 examples [1:38:13, 5599.93 examples/s]
Generating train split: 94268455 examples [1:38:13, 6492.68 examples/s]
Generating train split: 94269320 examples [1:38:13, 5246.64 examples/s]
Generating train split: 94270030 examples [1:38:13, 5538.72 examples/s]
Generating train split: 94271707 examples [1:38:13, 7709.48 examples/s]
Generating train split: 94273217 examples [1:38:14, 9294.98 examples/s]
Generating train split: 94274583 examples [1:38:14, 10320.81 examples/s]
Generating train split: 94275796 examples [1:38:14, 9590.83 examples/s] 
Generating train split: 94277112 examples [1:38:14, 10295.14 examples/s]
Generating train split: 94278270 examples [1:38:14, 7872.61 examples/s] 
Generating train split: 94279212 examples [1:38:14, 6879.40 examples/s]
Generating train split: 94280824 examples [1:38:14, 8718.97 examples/s]
Generating train split: 94281875 examples [1:38:15, 5078.68 examples/s]
Generating train split: 94282992 examples [1:38:15, 5997.87 examples/s]
Generating train split: 94284652 examples [1:38:15, 7880.09 examples/s]
Generating train split: 94292572 examples [1:38:15, 22307.12 examples/s]
Generating train split: 94300747 examples [1:38:15, 35538.13 examples/s]
Generating train split: 94305391 examples [1:38:16, 20373.96 examples/s]
Generating train split: 94313910 examples [1:38:16, 30472.51 examples/s]
Generating train split: 94321500 examples [1:38:16, 38396.32 examples/s]
Generating train split: 94327205 examples [1:38:17, 17467.03 examples/s]
Generating train split: 94331415 examples [1:38:17, 13150.40 examples/s]
Generating train split: 94334579 examples [1:38:18, 10312.17 examples/s]
Generating train split: 94336957 examples [1:38:18, 8697.17 examples/s] 
Generating train split: 94338768 examples [1:38:19, 8899.02 examples/s]
Generating train split: 94340347 examples [1:38:19, 8169.70 examples/s]
Generating train split: 94341621 examples [1:38:19, 7917.23 examples/s]
Generating train split: 94342724 examples [1:38:19, 7774.53 examples/s]
Generating train split: 94343797 examples [1:38:19, 8143.94 examples/s]
Generating train split: 94345096 examples [1:38:19, 8956.16 examples/s]
Generating train split: 94346186 examples [1:38:20, 7989.06 examples/s]
Generating train split: 94347217 examples [1:38:20, 8320.33 examples/s]
Generating train split: 94348166 examples [1:38:20, 4333.21 examples/s]
Generating train split: 94349213 examples [1:38:20, 5093.71 examples/s]
Generating train split: 94350008 examples [1:38:20, 5156.23 examples/s]
Generating train split: 94350730 examples [1:38:21, 4403.60 examples/s]
Generating train split: 94351677 examples [1:38:21, 5239.04 examples/s]
Generating train split: 94352952 examples [1:38:21, 6672.63 examples/s]
Generating train split: 94355208 examples [1:38:21, 10068.86 examples/s]
Generating train split: 94356492 examples [1:38:21, 8361.51 examples/s] 
Generating train split: 94363304 examples [1:38:21, 20730.15 examples/s]
Generating train split: 94372311 examples [1:38:21, 36547.25 examples/s]
Generating train split: 94376968 examples [1:38:22, 26990.54 examples/s]
Generating train split: 94380730 examples [1:38:22, 15177.48 examples/s]
Generating train split: 94388978 examples [1:38:22, 23738.97 examples/s]
Generating train split: 94397546 examples [1:38:22, 33262.36 examples/s]
Generating train split: 94403243 examples [1:38:23, 22058.14 examples/s]
Generating train split: 94407584 examples [1:38:23, 22573.14 examples/s]
Generating train split: 94411353 examples [1:38:24, 15202.36 examples/s]
Generating train split: 94414213 examples [1:38:24, 16041.53 examples/s]
Generating train split: 94416835 examples [1:38:24, 15163.23 examples/s]
Generating train split: 94419042 examples [1:38:25, 8982.37 examples/s] 
Generating train split: 94420694 examples [1:38:25, 8307.74 examples/s]
Generating train split: 94422032 examples [1:38:25, 6563.32 examples/s]
Generating train split: 94423825 examples [1:38:25, 7632.71 examples/s]
Generating train split: 94425019 examples [1:38:26, 6811.56 examples/s]
Generating train split: 94426992 examples [1:38:26, 8497.58 examples/s]
Generating train split: 94428257 examples [1:38:26, 8245.56 examples/s]
Generating train split: 94429426 examples [1:38:26, 8113.76 examples/s]
Generating train split: 94430431 examples [1:38:26, 7484.48 examples/s]
Generating train split: 94431761 examples [1:38:26, 8557.09 examples/s]
Generating train split: 94432781 examples [1:38:27, 7844.89 examples/s]
Generating train split: 94433679 examples [1:38:27, 5691.57 examples/s]
Generating train split: 94434590 examples [1:38:27, 6275.34 examples/s]
Generating train split: 94435535 examples [1:38:27, 6892.24 examples/s]
Generating train split: 94436773 examples [1:38:27, 8085.89 examples/s]
Generating train split: 94437723 examples [1:38:27, 6060.86 examples/s]
Generating train split: 94440232 examples [1:38:28, 9753.93 examples/s]
Generating train split: 94441502 examples [1:38:28, 7059.47 examples/s]
Generating train split: 94442509 examples [1:38:28, 6312.41 examples/s]
Generating train split: 94443355 examples [1:38:28, 4860.30 examples/s]
Generating train split: 94444029 examples [1:38:29, 4554.84 examples/s]
Generating train split: 94445118 examples [1:38:29, 5307.47 examples/s]
Generating train split: 94446141 examples [1:38:29, 6184.07 examples/s]
Generating train split: 94446918 examples [1:38:29, 5963.03 examples/s]
Generating train split: 94447616 examples [1:38:29, 5563.53 examples/s]
Generating train split: 94448765 examples [1:38:29, 6770.90 examples/s]
Generating train split: 94449545 examples [1:38:29, 5890.89 examples/s]
Generating train split: 94450213 examples [1:38:30, 5973.67 examples/s]
Generating train split: 94450869 examples [1:38:30, 4814.23 examples/s]
Generating train split: 94451422 examples [1:38:30, 4510.09 examples/s]
Generating train split: 94452574 examples [1:38:30, 5856.54 examples/s]
Generating train split: 94453231 examples [1:38:30, 4501.56 examples/s]
Generating train split: 94454548 examples [1:38:30, 6114.53 examples/s]
Generating train split: 94455296 examples [1:38:31, 5898.61 examples/s]
Generating train split: 94457283 examples [1:38:31, 8964.95 examples/s]
Generating train split: 94458356 examples [1:38:31, 6340.28 examples/s]
Generating train split: 94459218 examples [1:38:31, 6327.93 examples/s]
Generating train split: 94460013 examples [1:38:31, 6010.15 examples/s]
Generating train split: 94460728 examples [1:38:31, 6188.40 examples/s]
Generating train split: 94461438 examples [1:38:32, 4920.29 examples/s]
Generating train split: 94462071 examples [1:38:32, 5198.80 examples/s]
Generating train split: 94463005 examples [1:38:32, 6103.47 examples/s]
Generating train split: 94464378 examples [1:38:32, 7881.63 examples/s]
Generating train split: 94465277 examples [1:38:32, 5679.91 examples/s]
Generating train split: 94466005 examples [1:38:32, 5313.13 examples/s]
Generating train split: 94467777 examples [1:38:32, 7802.31 examples/s]
Generating train split: 94468752 examples [1:38:33, 7501.79 examples/s]
Generating train split: 94469634 examples [1:38:33, 7383.56 examples/s]
Generating train split: 94470468 examples [1:38:33, 6696.29 examples/s]
Generating train split: 94471817 examples [1:38:33, 8235.37 examples/s]
Generating train split: 94472753 examples [1:38:33, 6613.69 examples/s]
Generating train split: 94473529 examples [1:38:33, 4624.92 examples/s]
Generating train split: 94474689 examples [1:38:34, 5810.51 examples/s]
Generating train split: 94475556 examples [1:38:34, 6370.27 examples/s]
Generating train split: 94476642 examples [1:38:34, 7286.66 examples/s]
Generating train split: 94477531 examples [1:38:34, 5411.22 examples/s]
Generating train split: 94478580 examples [1:38:34, 6296.11 examples/s]
Generating train split: 94480009 examples [1:38:34, 7979.38 examples/s]
Generating train split: 94480985 examples [1:38:34, 6355.53 examples/s]
Generating train split: 94481800 examples [1:38:35, 6470.87 examples/s]
Generating train split: 94482572 examples [1:38:35, 6035.48 examples/s]
Generating train split: 94484816 examples [1:38:35, 9523.43 examples/s]
Generating train split: 94485957 examples [1:38:35, 6455.47 examples/s]
Generating train split: 94486853 examples [1:38:35, 6429.48 examples/s]
Generating train split: 94488264 examples [1:38:35, 7866.12 examples/s]
Generating train split: 94490127 examples [1:38:36, 10045.93 examples/s]
Generating train split: 94491354 examples [1:38:36, 7336.79 examples/s] 
Generating train split: 94492344 examples [1:38:36, 7479.77 examples/s]
Generating train split: 94493959 examples [1:38:36, 9165.27 examples/s]
Generating train split: 94495082 examples [1:38:36, 6263.15 examples/s]
Generating train split: 94495961 examples [1:38:37, 6519.62 examples/s]
Generating train split: 94498022 examples [1:38:37, 9236.45 examples/s]
Generating train split: 94499239 examples [1:38:37, 7941.35 examples/s]
Generating train split: 94500884 examples [1:38:37, 9626.69 examples/s]
Generating train split: 94502095 examples [1:38:37, 5732.57 examples/s]
Generating train split: 94503100 examples [1:38:37, 6384.74 examples/s]
Generating train split: 94504053 examples [1:38:38, 6532.15 examples/s]
Generating train split: 94504936 examples [1:38:38, 6569.16 examples/s]
Generating train split: 94506984 examples [1:38:38, 9405.59 examples/s]
Generating train split: 94508168 examples [1:38:38, 7942.61 examples/s]
Generating train split: 94509562 examples [1:38:38, 9120.98 examples/s]
Generating train split: 94510673 examples [1:38:38, 7480.52 examples/s]
Generating train split: 94511602 examples [1:38:38, 7604.10 examples/s]
Generating train split: 94512492 examples [1:38:39, 7227.51 examples/s]
Generating train split: 94514458 examples [1:38:39, 9873.54 examples/s]
Generating train split: 94515595 examples [1:38:39, 9967.99 examples/s]
Generating train split: 94518378 examples [1:38:39, 14396.96 examples/s]
Generating train split: 94519984 examples [1:38:39, 14010.94 examples/s]
Generating train split: 94522195 examples [1:38:39, 16127.33 examples/s]
Generating train split: 94523940 examples [1:38:39, 16480.91 examples/s]
Generating train split: 94525678 examples [1:38:40, 11959.01 examples/s]
Generating train split: 94527108 examples [1:38:40, 10427.33 examples/s]
Generating train split: 94528333 examples [1:38:40, 10323.13 examples/s]
Generating train split: 94529948 examples [1:38:40, 11614.95 examples/s]
Generating train split: 94531246 examples [1:38:40, 5846.23 examples/s] 
Generating train split: 94532236 examples [1:38:41, 6044.91 examples/s]
Generating train split: 94533132 examples [1:38:41, 5874.33 examples/s]
Generating train split: 94533926 examples [1:38:41, 4595.01 examples/s]
Generating train split: 94535277 examples [1:38:41, 5929.02 examples/s]
Generating train split: 94536109 examples [1:38:41, 5374.08 examples/s]
Generating train split: 94536818 examples [1:38:41, 5646.38 examples/s]
Generating train split: 94537525 examples [1:38:42, 4535.19 examples/s]
Generating train split: 94538098 examples [1:38:42, 4109.49 examples/s]
Generating train split: 94539663 examples [1:38:42, 6191.69 examples/s]
Generating train split: 94540474 examples [1:38:42, 5171.61 examples/s]
Generating train split: 94547769 examples [1:38:42, 17895.92 examples/s]
Generating train split: 94557131 examples [1:38:42, 33389.84 examples/s]
Generating train split: 94561612 examples [1:38:43, 24280.02 examples/s]
Generating train split: 94565180 examples [1:38:43, 15095.78 examples/s]
Generating train split: 94567895 examples [1:38:44, 12665.28 examples/s]
Generating train split: 94575143 examples [1:38:44, 20016.21 examples/s]
Generating train split: 94583937 examples [1:38:44, 29740.82 examples/s]
Generating train split: 94588914 examples [1:38:45, 16576.98 examples/s]
Generating train split: 94592627 examples [1:38:45, 14572.85 examples/s]
Generating train split: 94595537 examples [1:38:45, 14024.72 examples/s]
Generating train split: 94597932 examples [1:38:45, 13126.62 examples/s]
Generating train split: 94599926 examples [1:38:46, 11719.68 examples/s]
Generating train split: 94601755 examples [1:38:46, 12580.71 examples/s]
Generating train split: 94603441 examples [1:38:46, 11036.32 examples/s]
Generating train split: 94604851 examples [1:38:46, 9354.97 examples/s] 
Generating train split: 94606168 examples [1:38:46, 9918.29 examples/s]
Generating train split: 94607375 examples [1:38:46, 9720.64 examples/s]
Generating train split: 94609687 examples [1:38:47, 12329.40 examples/s]
Generating train split: 94611157 examples [1:38:47, 11274.73 examples/s]
Generating train split: 94612453 examples [1:38:47, 10942.46 examples/s]
Generating train split: 94613664 examples [1:38:47, 7457.40 examples/s] 
Generating train split: 94615511 examples [1:38:47, 9389.48 examples/s]
Generating train split: 94616733 examples [1:38:47, 9712.90 examples/s]
Generating train split: 94617915 examples [1:38:48, 4993.42 examples/s]
Generating train split: 94618989 examples [1:38:48, 5740.87 examples/s]
Generating train split: 94619936 examples [1:38:48, 5022.19 examples/s]
Generating train split: 94621023 examples [1:38:48, 5836.81 examples/s]
Generating train split: 94621871 examples [1:38:49, 6048.87 examples/s]
Generating train split: 94623350 examples [1:38:49, 7614.76 examples/s]
Generating train split: 94624396 examples [1:38:49, 8190.45 examples/s]
Generating train split: 94625379 examples [1:38:49, 5955.31 examples/s]
Generating train split: 94626166 examples [1:38:49, 5444.91 examples/s]
Generating train split: 94627264 examples [1:38:49, 6464.39 examples/s]
Generating train split: 94628336 examples [1:38:49, 7306.38 examples/s]
Generating train split: 94630115 examples [1:38:50, 9650.91 examples/s]
Generating train split: 94631243 examples [1:38:50, 7471.85 examples/s]
Generating train split: 94632177 examples [1:38:50, 6741.56 examples/s]
Generating train split: 94632985 examples [1:38:50, 6946.96 examples/s]
Generating train split: 94635848 examples [1:38:50, 11774.48 examples/s]
Generating train split: 94637749 examples [1:38:50, 13421.22 examples/s]
Generating train split: 94639301 examples [1:38:51, 9144.56 examples/s] 
Generating train split: 94640544 examples [1:38:51, 8476.10 examples/s]
Generating train split: 94642184 examples [1:38:51, 9952.33 examples/s]
Generating train split: 94643420 examples [1:38:51, 7912.40 examples/s]
Generating train split: 94645024 examples [1:38:51, 9158.74 examples/s]
Generating train split: 94646156 examples [1:38:51, 8744.78 examples/s]
Generating train split: 94647181 examples [1:38:52, 6015.98 examples/s]
Generating train split: 94647982 examples [1:38:52, 5759.28 examples/s]
Generating train split: 94648697 examples [1:38:52, 5021.24 examples/s]
Generating train split: 94649299 examples [1:38:52, 4245.60 examples/s]
Generating train split: 94649804 examples [1:38:53, 3242.29 examples/s]
Generating train split: 94650374 examples [1:38:53, 3585.88 examples/s]
Generating train split: 94651174 examples [1:38:53, 4368.80 examples/s]
Generating train split: 94651737 examples [1:38:53, 3263.65 examples/s]
Generating train split: 94652183 examples [1:38:53, 2506.70 examples/s]
Generating train split: 94654317 examples [1:38:54, 5309.00 examples/s]
Generating train split: 94655214 examples [1:38:54, 5404.71 examples/s]
Generating train split: 94656004 examples [1:38:54, 4710.17 examples/s]
Generating train split: 94657505 examples [1:38:54, 6514.56 examples/s]
Generating train split: 94659029 examples [1:38:54, 8237.82 examples/s]
Generating train split: 94660126 examples [1:38:54, 7429.90 examples/s]
Generating train split: 94661068 examples [1:38:55, 6047.02 examples/s]
Generating train split: 94662270 examples [1:38:55, 7083.07 examples/s]
Generating train split: 94663680 examples [1:38:55, 8494.00 examples/s]
Generating train split: 94664803 examples [1:38:55, 9115.52 examples/s]
Generating train split: 94666532 examples [1:38:55, 11127.50 examples/s]
Generating train split: 94667790 examples [1:38:55, 9430.35 examples/s] 
Generating train split: 94668874 examples [1:38:55, 9048.31 examples/s]
Generating train split: 94670964 examples [1:38:55, 11836.51 examples/s]
Generating train split: 94672290 examples [1:38:56, 8666.82 examples/s] 
Generating train split: 94673371 examples [1:38:56, 6791.29 examples/s]
Generating train split: 94674252 examples [1:38:56, 5800.18 examples/s]
Generating train split: 94674991 examples [1:38:56, 4750.83 examples/s]
Generating train split: 94675591 examples [1:38:57, 4495.44 examples/s]
Generating train split: 94676127 examples [1:38:57, 4508.36 examples/s]
Generating train split: 94676641 examples [1:38:57, 4516.10 examples/s]
Generating train split: 94677673 examples [1:38:57, 5742.03 examples/s]
Generating train split: 94678885 examples [1:38:57, 7220.39 examples/s]
Generating train split: 94679958 examples [1:38:57, 8024.56 examples/s]
Generating train split: 94680982 examples [1:38:57, 8601.52 examples/s]
Generating train split: 94682363 examples [1:38:57, 9653.90 examples/s]
Generating train split: 94683378 examples [1:38:57, 8966.16 examples/s]
Generating train split: 94684317 examples [1:38:58, 5566.62 examples/s]
Generating train split: 94685318 examples [1:38:58, 6391.78 examples/s]
Generating train split: 94686146 examples [1:38:58, 6521.24 examples/s]
Generating train split: 94687426 examples [1:38:58, 7923.48 examples/s]
Generating train split: 94688817 examples [1:38:58, 9191.94 examples/s]
Generating train split: 94689854 examples [1:38:58, 8472.45 examples/s]
Generating train split: 94690795 examples [1:38:59, 6774.31 examples/s]
Generating train split: 94697570 examples [1:38:59, 19801.03 examples/s]
Generating train split: 94705450 examples [1:38:59, 33588.46 examples/s]
Generating train split: 94709623 examples [1:38:59, 21398.67 examples/s]
Generating train split: 94712892 examples [1:39:00, 11674.42 examples/s]
Generating train split: 94715321 examples [1:39:00, 10409.87 examples/s]
Generating train split: 94723385 examples [1:39:00, 18333.59 examples/s]
Generating train split: 94731171 examples [1:39:00, 26134.27 examples/s]
Generating train split: 94735879 examples [1:39:01, 22184.98 examples/s]
Generating train split: 94739640 examples [1:39:01, 15953.44 examples/s]
Generating train split: 94742520 examples [1:39:01, 15263.72 examples/s]
Generating train split: 94744927 examples [1:39:02, 11435.67 examples/s]
Generating train split: 94746789 examples [1:39:02, 11649.73 examples/s]
Generating train split: 94748481 examples [1:39:02, 9915.85 examples/s] 
Generating train split: 94749836 examples [1:39:02, 9791.31 examples/s]
Generating train split: 94751068 examples [1:39:02, 9457.38 examples/s]
Generating train split: 94752183 examples [1:39:03, 6891.40 examples/s]
Generating train split: 94753315 examples [1:39:03, 7519.43 examples/s]
Generating train split: 94754269 examples [1:39:03, 7172.42 examples/s]
Generating train split: 94755119 examples [1:39:03, 6689.93 examples/s]
Generating train split: 94755874 examples [1:39:03, 5988.14 examples/s]
Generating train split: 94757388 examples [1:39:04, 7745.08 examples/s]
Generating train split: 94758639 examples [1:39:04, 8725.56 examples/s]
Generating train split: 94759643 examples [1:39:04, 8685.38 examples/s]
Generating train split: 94761706 examples [1:39:04, 11301.21 examples/s]
Generating train split: 94762939 examples [1:39:04, 10572.54 examples/s]
Generating train split: 94764078 examples [1:39:04, 9460.71 examples/s] 
Generating train split: 94765092 examples [1:39:04, 9513.10 examples/s]
Generating train split: 94767273 examples [1:39:04, 12601.81 examples/s]
Generating train split: 94774127 examples [1:39:04, 27370.62 examples/s]
Generating train split: 94782655 examples [1:39:05, 43223.31 examples/s]
Generating train split: 94787319 examples [1:39:05, 25178.20 examples/s]
Generating train split: 94790965 examples [1:39:06, 14423.66 examples/s]
Generating train split: 94793709 examples [1:39:06, 13031.77 examples/s]
Generating train split: 94795913 examples [1:39:07, 7079.15 examples/s] 
Generating train split: 94797751 examples [1:39:07, 7999.40 examples/s]
Generating train split: 94799888 examples [1:39:07, 9397.62 examples/s]
Generating train split: 94801708 examples [1:39:07, 8089.17 examples/s]
Generating train split: 94803152 examples [1:39:07, 8784.57 examples/s]
Generating train split: 94804559 examples [1:39:07, 9420.37 examples/s]
Generating train split: 94805927 examples [1:39:08, 6664.51 examples/s]
Generating train split: 94808032 examples [1:39:08, 8672.18 examples/s]
Generating train split: 94810567 examples [1:39:08, 11450.65 examples/s]
Generating train split: 94812284 examples [1:39:08, 9291.87 examples/s] 
Generating train split: 94814373 examples [1:39:08, 11222.86 examples/s]
Generating train split: 94815959 examples [1:39:09, 10720.98 examples/s]
Generating train split: 94817354 examples [1:39:09, 10596.32 examples/s]
Generating train split: 94818649 examples [1:39:09, 9705.25 examples/s] 
Generating train split: 94819816 examples [1:39:09, 10019.01 examples/s]
Generating train split: 94820943 examples [1:39:10, 5272.48 examples/s] 
Generating train split: 94821802 examples [1:39:10, 4724.16 examples/s]
Generating train split: 94822555 examples [1:39:10, 5122.30 examples/s]
Generating train split: 94823443 examples [1:39:10, 5687.02 examples/s]
Generating train split: 94824193 examples [1:39:10, 4382.73 examples/s]
Generating train split: 94825527 examples [1:39:10, 5869.21 examples/s]
Generating train split: 94826354 examples [1:39:11, 5667.45 examples/s]
Generating train split: 94827090 examples [1:39:11, 5437.66 examples/s]
Generating train split: 94828788 examples [1:39:11, 7776.94 examples/s]
Generating train split: 94829752 examples [1:39:11, 8086.49 examples/s]
Generating train split: 94831496 examples [1:39:11, 10315.67 examples/s]
Generating train split: 94833089 examples [1:39:11, 11734.85 examples/s]
Generating train split: 94834396 examples [1:39:11, 7571.97 examples/s] 
Generating train split: 94835438 examples [1:39:12, 7521.86 examples/s]
Generating train split: 94836383 examples [1:39:12, 7572.66 examples/s]
Generating train split: 94837289 examples [1:39:12, 5311.75 examples/s]
Generating train split: 94838005 examples [1:39:12, 4515.27 examples/s]
Generating train split: 94838611 examples [1:39:13, 3884.31 examples/s]
Generating train split: 94839784 examples [1:39:13, 5139.35 examples/s]
Generating train split: 94840992 examples [1:39:13, 6423.79 examples/s]
Generating train split: 94841837 examples [1:39:13, 3971.99 examples/s]
Generating train split: 94842835 examples [1:39:13, 4860.17 examples/s]
Generating train split: 94843914 examples [1:39:13, 5873.28 examples/s]
Generating train split: 94844764 examples [1:39:14, 5574.57 examples/s]
Generating train split: 94845976 examples [1:39:14, 6786.19 examples/s]
Generating train split: 94846838 examples [1:39:14, 6790.77 examples/s]
Generating train split: 94847650 examples [1:39:14, 6886.19 examples/s]
Generating train split: 94848601 examples [1:39:14, 7245.92 examples/s]
Generating train split: 94849393 examples [1:39:14, 5047.56 examples/s]
Generating train split: 94850046 examples [1:39:15, 3499.84 examples/s]
Generating train split: 94851285 examples [1:39:15, 4870.99 examples/s]
Generating train split: 94852013 examples [1:39:15, 5099.21 examples/s]
Generating train split: 94852710 examples [1:39:15, 5158.21 examples/s]
Generating train split: 94853357 examples [1:39:15, 4825.90 examples/s]
Generating train split: 94861275 examples [1:39:15, 20527.83 examples/s]
Generating train split: 94869247 examples [1:39:15, 34244.65 examples/s]
Generating train split: 94873588 examples [1:39:16, 23954.40 examples/s]
Generating train split: 94877040 examples [1:39:16, 13395.59 examples/s]
Generating train split: 94879635 examples [1:39:17, 11760.27 examples/s]
Generating train split: 94881701 examples [1:39:17, 10816.83 examples/s]
Generating train split: 94883401 examples [1:39:17, 11600.28 examples/s]
Generating train split: 94885094 examples [1:39:17, 7769.42 examples/s] 
Generating train split: 94892379 examples [1:39:18, 15624.91 examples/s]
Generating train split: 94899699 examples [1:39:18, 23682.62 examples/s]
Generating train split: 94903821 examples [1:39:18, 13646.37 examples/s]
Generating train split: 94906895 examples [1:39:19, 8547.87 examples/s] 
Generating train split: 94909172 examples [1:39:20, 7877.61 examples/s]
Generating train split: 94911125 examples [1:39:20, 8863.44 examples/s]
Generating train split: 94912942 examples [1:39:20, 9595.60 examples/s]
Generating train split: 94914655 examples [1:39:20, 9440.88 examples/s]
Generating train split: 94916111 examples [1:39:20, 9135.45 examples/s]
Generating train split: 94917381 examples [1:39:20, 7770.71 examples/s]
Generating train split: 94919062 examples [1:39:20, 9126.18 examples/s]
Generating train split: 94920291 examples [1:39:21, 8238.90 examples/s]
Generating train split: 94921339 examples [1:39:21, 7959.94 examples/s]
Generating train split: 94922286 examples [1:39:21, 7296.11 examples/s]
Generating train split: 94923333 examples [1:39:21, 7903.80 examples/s]
Generating train split: 94924233 examples [1:39:21, 8096.52 examples/s]
Generating train split: 94925599 examples [1:39:21, 9360.97 examples/s]
Generating train split: 94926623 examples [1:39:22, 4092.53 examples/s]
Generating train split: 94927391 examples [1:39:22, 3447.24 examples/s]
Generating train split: 94932047 examples [1:39:22, 8836.42 examples/s]
Generating train split: 94939541 examples [1:39:22, 18852.36 examples/s]
Generating train split: 94946208 examples [1:39:23, 27353.09 examples/s]
Generating train split: 94950670 examples [1:39:23, 14992.75 examples/s]
Generating train split: 94954011 examples [1:39:24, 11970.62 examples/s]
Generating train split: 94957410 examples [1:39:24, 14364.70 examples/s]
Generating train split: 94960217 examples [1:39:24, 15321.91 examples/s]
Generating train split: 94962780 examples [1:39:24, 11564.21 examples/s]
Generating train split: 94964771 examples [1:39:24, 12296.67 examples/s]
Generating train split: 94966659 examples [1:39:25, 12807.12 examples/s]
Generating train split: 94968425 examples [1:39:25, 10351.54 examples/s]
Generating train split: 94969855 examples [1:39:25, 8936.22 examples/s] 
Generating train split: 94971055 examples [1:39:25, 9413.62 examples/s]
Generating train split: 94972245 examples [1:39:25, 8493.41 examples/s]
Generating train split: 94973270 examples [1:39:26, 7823.74 examples/s]
Generating train split: 94974647 examples [1:39:26, 8940.48 examples/s]
Generating train split: 94976762 examples [1:39:26, 11520.85 examples/s]
Generating train split: 94978123 examples [1:39:26, 9511.24 examples/s] 
Generating train split: 94979740 examples [1:39:26, 10826.11 examples/s]
Generating train split: 94981012 examples [1:39:26, 10347.76 examples/s]
Generating train split: 94982188 examples [1:39:26, 10658.15 examples/s]
Generating train split: 94983356 examples [1:39:26, 9263.37 examples/s] 
Generating train split: 94984387 examples [1:39:27, 7973.54 examples/s]
Generating train split: 94985274 examples [1:39:27, 8151.69 examples/s]
Generating train split: 94987522 examples [1:39:27, 11532.55 examples/s]
Generating train split: 94988825 examples [1:39:27, 9264.94 examples/s] 
Generating train split: 94989913 examples [1:39:27, 7722.91 examples/s]
Generating train split: 94991389 examples [1:39:27, 9130.89 examples/s]
Generating train split: 94993118 examples [1:39:27, 10918.16 examples/s]
Generating train split: 94994401 examples [1:39:28, 10070.53 examples/s]
Generating train split: 94996663 examples [1:39:28, 12997.96 examples/s]
Generating train split: 94998582 examples [1:39:28, 14448.47 examples/s]
Generating train split: 95000659 examples [1:39:28, 16097.57 examples/s]
Generating train split: 95002405 examples [1:39:28, 11289.03 examples/s]
Generating train split: 95003828 examples [1:39:28, 11688.31 examples/s]
Generating train split: 95005208 examples [1:39:28, 11406.28 examples/s]
Generating train split: 95006742 examples [1:39:29, 11992.96 examples/s]
Generating train split: 95008060 examples [1:39:29, 9073.69 examples/s] 
Generating train split: 95009410 examples [1:39:29, 9981.95 examples/s]
Generating train split: 95011275 examples [1:39:29, 11900.15 examples/s]
Generating train split: 95012640 examples [1:39:29, 12275.03 examples/s]
Generating train split: 95020835 examples [1:39:29, 30228.30 examples/s]
Generating train split: 95029287 examples [1:39:29, 44662.29 examples/s]
Generating train split: 95034171 examples [1:39:30, 26721.40 examples/s]
Generating train split: 95042823 examples [1:39:30, 37922.90 examples/s]
Generating train split: 95051830 examples [1:39:30, 48930.63 examples/s]
Generating train split: 95058237 examples [1:39:30, 28066.61 examples/s]
Generating train split: 95063118 examples [1:39:31, 22715.09 examples/s]
Generating train split: 95066961 examples [1:39:31, 20118.22 examples/s]
Generating train split: 95075759 examples [1:39:31, 29304.91 examples/s]
Generating train split: 95085141 examples [1:39:31, 39760.23 examples/s]
Generating train split: 95091327 examples [1:39:31, 30942.30 examples/s]
Generating train split: 95096230 examples [1:39:32, 20068.17 examples/s]
Generating train split: 95104220 examples [1:39:32, 27175.61 examples/s]
Generating train split: 95110948 examples [1:39:32, 32498.45 examples/s]
Generating train split: 95116277 examples [1:39:33, 20832.12 examples/s]
Generating train split: 95123669 examples [1:39:33, 27353.59 examples/s]
Generating train split: 95131948 examples [1:39:33, 35626.72 examples/s]
Generating train split: 95137959 examples [1:39:33, 31076.12 examples/s]
Generating train split: 95142851 examples [1:39:34, 24102.85 examples/s]
Generating train split: 95146694 examples [1:39:34, 24471.65 examples/s]
Generating train split: 95150172 examples [1:39:34, 22022.05 examples/s]
Generating train split: 95153084 examples [1:39:34, 18791.46 examples/s]
Generating train split: 95155480 examples [1:39:34, 16904.52 examples/s]
Generating train split: 95157517 examples [1:39:35, 16782.64 examples/s]
Generating train split: 95159447 examples [1:39:35, 17205.86 examples/s]
Generating train split: 95161370 examples [1:39:35, 14567.71 examples/s]
Generating train split: 95163004 examples [1:39:35, 13847.39 examples/s]
Generating train split: 95164497 examples [1:39:35, 12695.18 examples/s]
Generating train split: 95167308 examples [1:39:35, 15875.21 examples/s]
Generating train split: 95169086 examples [1:39:35, 14195.66 examples/s]
Generating train split: 95171606 examples [1:39:35, 16638.05 examples/s]
Generating train split: 95173463 examples [1:39:36, 13093.93 examples/s]
Generating train split: 95176359 examples [1:39:36, 16392.05 examples/s]
Generating train split: 95178316 examples [1:39:36, 15776.34 examples/s]
Generating train split: 95180106 examples [1:39:36, 14349.82 examples/s]
Generating train split: 95182420 examples [1:39:36, 16249.56 examples/s]
Generating train split: 95184219 examples [1:39:36, 13621.32 examples/s]
Generating train split: 95186369 examples [1:39:36, 15323.86 examples/s]
Generating train split: 95188319 examples [1:39:37, 16293.51 examples/s]
Generating train split: 95190101 examples [1:39:37, 10289.24 examples/s]
Generating train split: 95191508 examples [1:39:37, 9394.32 examples/s] 
Generating train split: 95192838 examples [1:39:37, 10079.23 examples/s]
Generating train split: 95194080 examples [1:39:37, 9666.24 examples/s] 
Generating train split: 95195646 examples [1:39:37, 10817.82 examples/s]
Generating train split: 95197098 examples [1:39:38, 11663.92 examples/s]
Generating train split: 95198980 examples [1:39:38, 13434.82 examples/s]
Generating train split: 95201408 examples [1:39:38, 16266.39 examples/s]
Generating train split: 95203172 examples [1:39:38, 10887.35 examples/s]
Generating train split: 95204588 examples [1:39:38, 9564.89 examples/s] 
Generating train split: 95206675 examples [1:39:38, 11686.33 examples/s]
Generating train split: 95208135 examples [1:39:39, 8868.71 examples/s] 
Generating train split: 95209312 examples [1:39:39, 8781.05 examples/s]
Generating train split: 95210392 examples [1:39:39, 9075.63 examples/s]
Generating train split: 95211461 examples [1:39:39, 8109.59 examples/s]
Generating train split: 95212389 examples [1:39:39, 7461.89 examples/s]
Generating train split: 95213715 examples [1:39:39, 8658.44 examples/s]
Generating train split: 95216042 examples [1:39:39, 12036.30 examples/s]
Generating train split: 95223852 examples [1:39:40, 28430.42 examples/s]
Generating train split: 95232435 examples [1:39:40, 43441.48 examples/s]
Generating train split: 95237320 examples [1:39:40, 30470.77 examples/s]
Generating train split: 95241275 examples [1:39:40, 28917.70 examples/s]
Generating train split: 95245336 examples [1:39:40, 31340.85 examples/s]
Generating train split: 95249026 examples [1:39:41, 20203.44 examples/s]
Generating train split: 95251918 examples [1:39:41, 20711.40 examples/s]
Generating train split: 95254613 examples [1:39:41, 20822.04 examples/s]
Generating train split: 95257140 examples [1:39:41, 15028.18 examples/s]
Generating train split: 95259169 examples [1:39:41, 15889.42 examples/s]
Generating train split: 95261227 examples [1:39:41, 16627.29 examples/s]
Generating train split: 95263221 examples [1:39:42, 13245.55 examples/s]
Generating train split: 95265194 examples [1:39:42, 14470.02 examples/s]
Generating train split: 95268057 examples [1:39:42, 17475.68 examples/s]
Generating train split: 95270143 examples [1:39:42, 15321.96 examples/s]
Generating train split: 95271977 examples [1:39:42, 15970.39 examples/s]
Generating train split: 95273788 examples [1:39:42, 14166.16 examples/s]
Generating train split: 95275841 examples [1:39:42, 15600.04 examples/s]
Generating train split: 95277566 examples [1:39:42, 14832.11 examples/s]
Generating train split: 95280038 examples [1:39:43, 17235.35 examples/s]
Generating train split: 95281901 examples [1:39:43, 13906.14 examples/s]
Generating train split: 95285347 examples [1:39:43, 18535.33 examples/s]
Generating train split: 95287482 examples [1:39:43, 17697.49 examples/s]
Generating train split: 95289464 examples [1:39:43, 14494.12 examples/s]
Generating train split: 95291140 examples [1:39:43, 12332.04 examples/s]
Generating train split: 95294429 examples [1:39:43, 16496.23 examples/s]
Generating train split: 95296479 examples [1:39:44, 17212.74 examples/s]
Generating train split: 95298463 examples [1:39:44, 15694.23 examples/s]
Generating train split: 95300224 examples [1:39:44, 11632.16 examples/s]
Generating train split: 95302661 examples [1:39:44, 14089.34 examples/s]
Generating train split: 95304395 examples [1:39:44, 10334.55 examples/s]
Generating train split: 95305796 examples [1:39:45, 9867.61 examples/s] 
Generating train split: 95307043 examples [1:39:45, 9410.83 examples/s]
Generating train split: 95308148 examples [1:39:45, 6864.40 examples/s]
Generating train split: 95309554 examples [1:39:45, 8021.01 examples/s]
Generating train split: 95310617 examples [1:39:45, 8513.93 examples/s]
Generating train split: 95311664 examples [1:39:45, 8788.16 examples/s]
Generating train split: 95312692 examples [1:39:46, 6638.66 examples/s]
Generating train split: 95314579 examples [1:39:46, 8992.59 examples/s]
Generating train split: 95316832 examples [1:39:46, 11884.39 examples/s]
Generating train split: 95318830 examples [1:39:46, 13755.68 examples/s]
Generating train split: 95320454 examples [1:39:46, 8859.04 examples/s] 
Generating train split: 95321737 examples [1:39:46, 9027.73 examples/s]
Generating train split: 95322926 examples [1:39:47, 6595.71 examples/s]
Generating train split: 95323981 examples [1:39:47, 7212.25 examples/s]
Generating train split: 95325425 examples [1:39:47, 8556.75 examples/s]
Generating train split: 95326532 examples [1:39:47, 9014.36 examples/s]
Generating train split: 95327636 examples [1:39:47, 6250.53 examples/s]
Generating train split: 95328780 examples [1:39:47, 7142.08 examples/s]
Generating train split: 95330180 examples [1:39:48, 8523.42 examples/s]
Generating train split: 95331262 examples [1:39:48, 6837.14 examples/s]
Generating train split: 95332156 examples [1:39:48, 7065.40 examples/s]
Generating train split: 95333253 examples [1:39:48, 7895.37 examples/s]
Generating train split: 95337051 examples [1:39:48, 14919.73 examples/s]
Generating train split: 95345708 examples [1:39:48, 32841.69 examples/s]
Generating train split: 95352647 examples [1:39:48, 42463.60 examples/s]
Generating train split: 95357425 examples [1:39:49, 21156.62 examples/s]
Generating train split: 95361065 examples [1:39:49, 14581.58 examples/s]
Generating train split: 95363836 examples [1:39:50, 10194.19 examples/s]
Generating train split: 95365919 examples [1:39:50, 10540.21 examples/s]
Generating train split: 95367750 examples [1:39:50, 11431.94 examples/s]
Generating train split: 95369581 examples [1:39:50, 11447.21 examples/s]
Generating train split: 95371201 examples [1:39:50, 11173.35 examples/s]
Generating train split: 95372646 examples [1:39:51, 8450.00 examples/s] 
Generating train split: 95373796 examples [1:39:51, 8284.19 examples/s]
Generating train split: 95374965 examples [1:39:51, 8327.41 examples/s]
Generating train split: 95375944 examples [1:39:51, 7968.66 examples/s]
Generating train split: 95376834 examples [1:39:51, 7519.75 examples/s]
Generating train split: 95377648 examples [1:39:52, 7135.21 examples/s]
Generating train split: 95384964 examples [1:39:52, 21274.39 examples/s]
Generating train split: 95392498 examples [1:39:52, 33939.78 examples/s]
Generating train split: 95396667 examples [1:39:52, 24900.27 examples/s]
Generating train split: 95400035 examples [1:39:52, 23498.55 examples/s]
Generating train split: 95408125 examples [1:39:52, 35004.42 examples/s]
Generating train split: 95415149 examples [1:39:52, 42767.06 examples/s]
Generating train split: 95420395 examples [1:39:53, 19667.11 examples/s]
Generating train split: 95424314 examples [1:39:54, 14072.34 examples/s]
Generating train split: 95427271 examples [1:39:54, 15425.13 examples/s]
Generating train split: 95430106 examples [1:39:54, 14673.94 examples/s]
Generating train split: 95432458 examples [1:39:54, 11334.29 examples/s]
Generating train split: 95434290 examples [1:39:55, 8158.62 examples/s] 
Generating train split: 95436710 examples [1:39:55, 9831.70 examples/s]
Generating train split: 95438404 examples [1:39:55, 8377.18 examples/s]
Generating train split: 95439755 examples [1:39:55, 7455.43 examples/s]
Generating train split: 95441669 examples [1:39:56, 8957.83 examples/s]
Generating train split: 95443009 examples [1:39:56, 7764.81 examples/s]
Generating train split: 95444523 examples [1:39:56, 8885.23 examples/s]
Generating train split: 95445740 examples [1:39:56, 8626.77 examples/s]
Generating train split: 95446838 examples [1:39:56, 5769.62 examples/s]
Generating train split: 95447684 examples [1:39:57, 6121.51 examples/s]
Generating train split: 95448576 examples [1:39:57, 6593.42 examples/s]
Generating train split: 95449465 examples [1:39:57, 6919.15 examples/s]
Generating train split: 95450305 examples [1:39:57, 6854.29 examples/s]
Generating train split: 95451872 examples [1:39:57, 8834.11 examples/s]
Generating train split: 95452896 examples [1:39:57, 7293.61 examples/s]
Generating train split: 95453870 examples [1:39:57, 7634.54 examples/s]
Generating train split: 95454748 examples [1:39:58, 5386.33 examples/s]
Generating train split: 95455932 examples [1:39:58, 6574.38 examples/s]
Generating train split: 95456778 examples [1:39:58, 6044.25 examples/s]
Generating train split: 95461505 examples [1:39:58, 14507.52 examples/s]
Generating train split: 95467816 examples [1:39:58, 25526.74 examples/s]
Generating train split: 95473794 examples [1:39:58, 33904.45 examples/s]
Generating train split: 95480576 examples [1:39:58, 42675.01 examples/s]
Generating train split: 95487191 examples [1:39:58, 49009.04 examples/s]
Generating train split: 95493323 examples [1:39:59, 52419.10 examples/s]
Generating train split: 95500292 examples [1:39:59, 57315.35 examples/s]
Generating train split: 95506765 examples [1:39:59, 59447.31 examples/s]
Generating train split: 95513420 examples [1:39:59, 61497.71 examples/s]
Generating train split: 95520704 examples [1:39:59, 64832.81 examples/s]
Generating train split: 95527961 examples [1:39:59, 67103.17 examples/s]
Generating train split: 95535031 examples [1:39:59, 68144.30 examples/s]
Generating train split: 95541938 examples [1:39:59, 68374.29 examples/s]
Generating train split: 95549408 examples [1:39:59, 70240.13 examples/s]
Generating train split: 95556726 examples [1:39:59, 71090.69 examples/s]
Generating train split: 95564413 examples [1:40:00, 72817.57 examples/s]
Generating train split: 95571716 examples [1:40:00, 72577.95 examples/s]
Generating train split: 95579297 examples [1:40:00, 73538.94 examples/s]
Generating train split: 95586668 examples [1:40:00, 73568.40 examples/s]
Generating train split: 95594045 examples [1:40:00, 72780.77 examples/s]
Generating train split: 95601329 examples [1:40:00, 68413.72 examples/s]
Generating train split: 95608552 examples [1:40:00, 68802.38 examples/s]
Generating train split: 95615477 examples [1:40:00, 62326.88 examples/s]
Generating train split: 95621906 examples [1:40:00, 62841.39 examples/s]
Generating train split: 95628297 examples [1:40:01, 57170.17 examples/s]
Generating train split: 95634158 examples [1:40:01, 49172.24 examples/s]
Generating train split: 95639340 examples [1:40:01, 33402.91 examples/s]
Generating train split: 95643619 examples [1:40:01, 35082.64 examples/s]
Generating train split: 95647794 examples [1:40:01, 33834.58 examples/s]
Generating train split: 95651638 examples [1:40:01, 31231.74 examples/s]
Generating train split: 95655079 examples [1:40:02, 18482.43 examples/s]
Generating train split: 95657724 examples [1:40:02, 19052.90 examples/s]
Generating train split: 95660235 examples [1:40:02, 15184.58 examples/s]
Generating train split: 95662256 examples [1:40:02, 14272.41 examples/s]
Generating train split: 95670017 examples [1:40:02, 24943.56 examples/s]
Generating train split: 95676351 examples [1:40:03, 32229.70 examples/s]
Generating train split: 95680702 examples [1:40:03, 19468.02 examples/s]
Generating train split: 95684033 examples [1:40:03, 20943.30 examples/s]
Generating train split: 95687203 examples [1:40:04, 11131.66 examples/s]
Generating train split: 95689565 examples [1:40:04, 9886.88 examples/s] 
Generating train split: 95691430 examples [1:40:05, 7875.27 examples/s]
Generating train split: 95692855 examples [1:40:05, 6078.10 examples/s]
Generating train split: 95693949 examples [1:40:06, 5363.18 examples/s]
Generating train split: 95694808 examples [1:40:06, 4354.30 examples/s]
Generating train split: 95695480 examples [1:40:06, 4493.58 examples/s]
Generating train split: 95696110 examples [1:40:06, 4204.28 examples/s]
Generating train split: 95697076 examples [1:40:06, 4911.75 examples/s]
Generating train split: 95697735 examples [1:40:07, 3669.81 examples/s]
Generating train split: 95699117 examples [1:40:07, 4846.18 examples/s]
Generating train split: 95699791 examples [1:40:07, 4828.91 examples/s]
Generating train split: 95700410 examples [1:40:07, 4224.10 examples/s]
Generating train split: 95700934 examples [1:40:07, 4220.36 examples/s]
Generating train split: 95702689 examples [1:40:07, 6765.93 examples/s]
Generating train split: 95704580 examples [1:40:08, 9372.52 examples/s]
Generating train split: 95705805 examples [1:40:08, 9089.11 examples/s]
Generating train split: 95706894 examples [1:40:08, 6501.21 examples/s]
Generating train split: 95709228 examples [1:40:08, 9614.90 examples/s]
Generating train split: 95710905 examples [1:40:08, 10621.70 examples/s]
Generating train split: 95712233 examples [1:40:09, 5911.42 examples/s] 
Generating train split: 95713710 examples [1:40:09, 7148.81 examples/s]
Generating train split: 95714844 examples [1:40:09, 6241.67 examples/s]
Generating train split: 95715777 examples [1:40:09, 6580.13 examples/s]
Generating train split: 95716680 examples [1:40:09, 7008.48 examples/s]
Generating train split: 95718001 examples [1:40:09, 8293.43 examples/s]
Generating train split: 95719022 examples [1:40:10, 5115.02 examples/s]
Generating train split: 95719824 examples [1:40:10, 5377.15 examples/s]
Generating train split: 95720584 examples [1:40:10, 5346.21 examples/s]
Generating train split: 95721814 examples [1:40:10, 6687.86 examples/s]
Generating train split: 95722851 examples [1:40:10, 7135.82 examples/s]
Generating train split: 95723700 examples [1:40:11, 5288.82 examples/s]
Generating train split: 95724538 examples [1:40:11, 5866.13 examples/s]
Generating train split: 95726046 examples [1:40:11, 7797.98 examples/s]
Generating train split: 95727010 examples [1:40:11, 5847.30 examples/s]
Generating train split: 95729298 examples [1:40:11, 9049.66 examples/s]
Generating train split: 95730525 examples [1:40:11, 9072.59 examples/s]
Generating train split: 95732155 examples [1:40:11, 10654.76 examples/s]
Generating train split: 95733433 examples [1:40:12, 7280.97 examples/s] 
Generating train split: 95735294 examples [1:40:12, 9341.08 examples/s]
Generating train split: 95736558 examples [1:40:12, 9562.31 examples/s]
Generating train split: 95737753 examples [1:40:12, 7404.25 examples/s]
Generating train split: 95739554 examples [1:40:12, 9368.09 examples/s]
Generating train split: 95740769 examples [1:40:12, 9116.08 examples/s]
Generating train split: 95742012 examples [1:40:13, 9829.96 examples/s]
Generating train split: 95743676 examples [1:40:13, 10938.37 examples/s]
Generating train split: 95744902 examples [1:40:13, 11152.64 examples/s]
Generating train split: 95747119 examples [1:40:13, 13725.44 examples/s]
Generating train split: 95748585 examples [1:40:13, 10438.41 examples/s]
Generating train split: 95756159 examples [1:40:13, 24810.20 examples/s]
Generating train split: 95765117 examples [1:40:13, 40301.88 examples/s]
Generating train split: 95769993 examples [1:40:14, 16118.21 examples/s]
Generating train split: 95773613 examples [1:40:15, 11551.22 examples/s]
Generating train split: 95776325 examples [1:40:15, 9521.80 examples/s] 
Generating train split: 95778394 examples [1:40:15, 8253.73 examples/s]
Generating train split: 95779999 examples [1:40:16, 8588.57 examples/s]
Generating train split: 95781446 examples [1:40:16, 7879.38 examples/s]
Generating train split: 95782633 examples [1:40:17, 4741.86 examples/s]
Generating train split: 95785253 examples [1:40:17, 6651.80 examples/s]
Generating train split: 95786656 examples [1:40:17, 5053.46 examples/s]
Generating train split: 95787716 examples [1:40:17, 5110.75 examples/s]
Generating train split: 95788625 examples [1:40:18, 4497.20 examples/s]
Generating train split: 95789644 examples [1:40:18, 5147.37 examples/s]
Generating train split: 95790450 examples [1:40:18, 5036.86 examples/s]
Generating train split: 95791153 examples [1:40:18, 4520.61 examples/s]
Generating train split: 95792033 examples [1:40:18, 5194.37 examples/s]
Generating train split: 95792724 examples [1:40:19, 4857.40 examples/s]
Generating train split: 95793324 examples [1:40:19, 2980.54 examples/s]
Generating train split: 95793882 examples [1:40:19, 3315.76 examples/s]
Generating train split: 95794366 examples [1:40:19, 2993.68 examples/s]
Generating train split: 95794777 examples [1:40:20, 2347.15 examples/s]
Generating train split: 95795366 examples [1:40:20, 2865.27 examples/s]
Generating train split: 95795769 examples [1:40:20, 2947.16 examples/s]
Generating train split: 95796164 examples [1:40:20, 3092.12 examples/s]
Generating train split: 95796896 examples [1:40:20, 3922.44 examples/s]
Generating train split: 95797366 examples [1:40:20, 3652.31 examples/s]
Generating train split: 95798927 examples [1:40:20, 6289.59 examples/s]
Generating train split: 95799677 examples [1:40:21, 5599.88 examples/s]
Generating train split: 95800402 examples [1:40:21, 5919.47 examples/s]
Generating train split: 95801071 examples [1:40:21, 4638.46 examples/s]
Generating train split: 95802607 examples [1:40:21, 6854.19 examples/s]
Generating train split: 95803456 examples [1:40:21, 4288.24 examples/s]
Generating train split: 95804776 examples [1:40:21, 5734.14 examples/s]
Generating train split: 95805636 examples [1:40:22, 6189.10 examples/s]
Generating train split: 95806594 examples [1:40:22, 6896.35 examples/s]
Generating train split: 95807614 examples [1:40:22, 7541.95 examples/s]
Generating train split: 95808514 examples [1:40:22, 6068.33 examples/s]
Generating train split: 95815810 examples [1:40:22, 20237.26 examples/s]
Generating train split: 95824107 examples [1:40:22, 34805.74 examples/s]
Generating train split: 95828500 examples [1:40:23, 21095.62 examples/s]
Generating train split: 95831902 examples [1:40:23, 11024.25 examples/s]
Generating train split: 95834418 examples [1:40:24, 9296.53 examples/s] 
Generating train split: 95841602 examples [1:40:24, 15440.99 examples/s]
Generating train split: 95850516 examples [1:40:24, 24510.07 examples/s]
Generating train split: 95855651 examples [1:40:25, 17459.36 examples/s]
Generating train split: 95859536 examples [1:40:25, 11752.16 examples/s]
Generating train split: 95867740 examples [1:40:25, 17988.29 examples/s]
Generating train split: 95876211 examples [1:40:25, 25490.08 examples/s]
Generating train split: 95881891 examples [1:40:27, 11698.14 examples/s]
Generating train split: 95886006 examples [1:40:27, 9232.75 examples/s] 
Generating train split: 95889047 examples [1:40:28, 8630.56 examples/s]
Generating train split: 95891385 examples [1:40:28, 8295.58 examples/s]
Generating train split: 95893223 examples [1:40:29, 6443.17 examples/s]
Generating train split: 95894602 examples [1:40:29, 6845.77 examples/s]
Generating train split: 95895891 examples [1:40:29, 6450.69 examples/s]
Generating train split: 95896944 examples [1:40:29, 5765.73 examples/s]
Generating train split: 95898571 examples [1:40:30, 6928.91 examples/s]
Generating train split: 95899658 examples [1:40:30, 6818.49 examples/s]
Generating train split: 95900644 examples [1:40:30, 7273.19 examples/s]
Generating train split: 95901604 examples [1:40:30, 7309.66 examples/s]
Generating train split: 95902745 examples [1:40:30, 8054.77 examples/s]
Generating train split: 95903708 examples [1:40:31, 4672.63 examples/s]
Generating train split: 95904781 examples [1:40:31, 5555.10 examples/s]
Generating train split: 95905617 examples [1:40:31, 5541.14 examples/s]
Generating train split: 95907347 examples [1:40:31, 7702.88 examples/s]
Generating train split: 95908388 examples [1:40:31, 6203.71 examples/s]
Generating train split: 95909342 examples [1:40:31, 6731.21 examples/s]
Generating train split: 95910207 examples [1:40:32, 3867.43 examples/s]
Generating train split: 95911484 examples [1:40:32, 5036.43 examples/s]
Generating train split: 95912299 examples [1:40:32, 4541.97 examples/s]
Generating train split: 95914082 examples [1:40:32, 6664.09 examples/s]
Generating train split: 95915097 examples [1:40:32, 5935.37 examples/s]
Generating train split: 95915941 examples [1:40:33, 4817.55 examples/s]
Generating train split: 95917795 examples [1:40:33, 7017.73 examples/s]
Generating train split: 95919383 examples [1:40:33, 8664.97 examples/s]
Generating train split: 95920579 examples [1:40:33, 9151.71 examples/s]
Generating train split: 95921743 examples [1:40:33, 6443.99 examples/s]
Generating train split: 95922666 examples [1:40:34, 5561.76 examples/s]
Generating train split: 95923431 examples [1:40:34, 4846.13 examples/s]
Generating train split: 95924437 examples [1:40:34, 5584.18 examples/s]
Generating train split: 95925154 examples [1:40:35, 3231.09 examples/s]
Generating train split: 95926160 examples [1:40:35, 4105.44 examples/s]
Generating train split: 95926846 examples [1:40:35, 3865.81 examples/s]
Generating train split: 95929291 examples [1:40:35, 7124.99 examples/s]
Generating train split: 95930518 examples [1:40:35, 8050.46 examples/s]
Generating train split: 95931679 examples [1:40:35, 8269.09 examples/s]
Generating train split: 95933709 examples [1:40:35, 10892.10 examples/s]
Generating train split: 95935076 examples [1:40:36, 7561.52 examples/s] 
Generating train split: 95937086 examples [1:40:36, 9762.47 examples/s]
Generating train split: 95938424 examples [1:40:36, 8045.28 examples/s]
Generating train split: 95939525 examples [1:40:36, 7368.56 examples/s]
Generating train split: 95940474 examples [1:40:36, 5814.46 examples/s]
Generating train split: 95941605 examples [1:40:37, 6643.39 examples/s]
Generating train split: 95942457 examples [1:40:37, 6527.42 examples/s]
Generating train split: 95945136 examples [1:40:37, 10573.02 examples/s]
Generating train split: 95946481 examples [1:40:37, 6320.66 examples/s] 
Generating train split: 95947684 examples [1:40:37, 7103.33 examples/s]
Generating train split: 95948747 examples [1:40:38, 3700.69 examples/s]
Generating train split: 95949534 examples [1:40:38, 3599.14 examples/s]
Generating train split: 95951692 examples [1:40:38, 5700.33 examples/s]
Generating train split: 95952833 examples [1:40:38, 6506.96 examples/s]
Generating train split: 95953944 examples [1:40:39, 5068.40 examples/s]
Generating train split: 95955102 examples [1:40:39, 5929.21 examples/s]
Generating train split: 95956029 examples [1:40:39, 5288.25 examples/s]
Generating train split: 95956800 examples [1:40:39, 5477.40 examples/s]
Generating train split: 95957781 examples [1:40:39, 6271.65 examples/s]
Generating train split: 95958583 examples [1:40:40, 5825.50 examples/s]
Generating train split: 95959480 examples [1:40:40, 6407.45 examples/s]
Generating train split: 95960234 examples [1:40:40, 5676.65 examples/s]
Generating train split: 95961161 examples [1:40:40, 6395.50 examples/s]
Generating train split: 95961899 examples [1:40:40, 6618.27 examples/s]
Generating train split: 95963066 examples [1:40:40, 7847.87 examples/s]
Generating train split: 95963922 examples [1:40:40, 8003.55 examples/s]
Generating train split: 95964786 examples [1:40:41, 5149.86 examples/s]
Generating train split: 95966396 examples [1:40:41, 7177.52 examples/s]
Generating train split: 95967324 examples [1:40:41, 7108.26 examples/s]
Generating train split: 95968550 examples [1:40:41, 8232.98 examples/s]
Generating train split: 95969510 examples [1:40:41, 8357.35 examples/s]
Generating train split: 95970447 examples [1:40:41, 7750.25 examples/s]
Generating train split: 95971299 examples [1:40:41, 6546.84 examples/s]
Generating train split: 95972399 examples [1:40:41, 7428.56 examples/s]
Generating train split: 95973220 examples [1:40:42, 7081.03 examples/s]
Generating train split: 95974899 examples [1:40:42, 9421.53 examples/s]
Generating train split: 95976591 examples [1:40:42, 11307.14 examples/s]
Generating train split: 95978068 examples [1:40:42, 12227.46 examples/s]
Generating train split: 95979379 examples [1:40:42, 10730.43 examples/s]
Generating train split: 95980542 examples [1:40:42, 6497.84 examples/s] 
Generating train split: 95981457 examples [1:40:43, 6345.55 examples/s]
Generating train split: 95982276 examples [1:40:43, 6020.26 examples/s]
Generating train split: 95983909 examples [1:40:43, 7969.76 examples/s]
Generating train split: 95984899 examples [1:40:43, 6293.09 examples/s]
Generating train split: 95985706 examples [1:40:44, 3469.99 examples/s]
Generating train split: 95986857 examples [1:40:44, 4458.59 examples/s]
Generating train split: 95987624 examples [1:40:44, 4137.53 examples/s]
Generating train split: 95988320 examples [1:40:44, 4551.70 examples/s]
Generating train split: 95988974 examples [1:40:44, 3909.79 examples/s]
Generating train split: 95989512 examples [1:40:45, 3740.87 examples/s]
Generating train split: 95991992 examples [1:40:45, 7486.34 examples/s]
Generating train split: 95993069 examples [1:40:45, 6102.00 examples/s]
Generating train split: 95993950 examples [1:40:45, 5595.03 examples/s]
Generating train split: 95995150 examples [1:40:45, 6633.17 examples/s]
Generating train split: 95996009 examples [1:40:46, 4516.18 examples/s]
Generating train split: 95997719 examples [1:40:46, 6458.30 examples/s]
Generating train split: 95998692 examples [1:40:46, 5678.05 examples/s]
Generating train split: 95999537 examples [1:40:46, 5737.98 examples/s]
Generating train split: 96000284 examples [1:40:46, 5530.43 examples/s]
Generating train split: 96001443 examples [1:40:46, 6707.22 examples/s]
Generating train split: 96002264 examples [1:40:47, 3468.19 examples/s]
Generating train split: 96004059 examples [1:40:47, 5396.67 examples/s]
Generating train split: 96005032 examples [1:40:47, 4801.20 examples/s]
Generating train split: 96005823 examples [1:40:47, 4917.36 examples/s]
Generating train split: 96006542 examples [1:40:47, 5216.70 examples/s]
Generating train split: 96007408 examples [1:40:48, 5868.71 examples/s]
Generating train split: 96008156 examples [1:40:48, 4187.89 examples/s]
Generating train split: 96009120 examples [1:40:48, 5034.72 examples/s]
Generating train split: 96010079 examples [1:40:48, 5762.94 examples/s]
Generating train split: 96010811 examples [1:40:48, 4732.82 examples/s]
Generating train split: 96011423 examples [1:40:49, 4765.10 examples/s]
Generating train split: 96012003 examples [1:40:49, 4402.64 examples/s]
Generating train split: 96013347 examples [1:40:49, 6083.11 examples/s]
Generating train split: 96014056 examples [1:40:49, 5159.40 examples/s]
Generating train split: 96015347 examples [1:40:49, 6759.62 examples/s]
Generating train split: 96016743 examples [1:40:49, 8354.71 examples/s]
Generating train split: 96017717 examples [1:40:49, 6097.29 examples/s]
Generating train split: 96018981 examples [1:40:50, 7362.22 examples/s]
Generating train split: 96019908 examples [1:40:50, 5923.85 examples/s]
Generating train split: 96020672 examples [1:40:50, 5221.67 examples/s]
Generating train split: 96022042 examples [1:40:50, 6763.92 examples/s]
Generating train split: 96023847 examples [1:40:50, 9118.67 examples/s]
Generating train split: 96024985 examples [1:40:50, 7233.26 examples/s]
Generating train split: 96025929 examples [1:40:51, 5868.63 examples/s]
Generating train split: 96026702 examples [1:40:51, 5123.62 examples/s]
Generating train split: 96027356 examples [1:40:51, 4367.56 examples/s]
Generating train split: 96029096 examples [1:40:51, 6554.32 examples/s]
Generating train split: 96029995 examples [1:40:51, 5592.55 examples/s]
Generating train split: 96031319 examples [1:40:52, 6931.87 examples/s]
Generating train split: 96032231 examples [1:40:52, 4826.92 examples/s]
Generating train split: 96033422 examples [1:40:52, 5892.07 examples/s]
Generating train split: 96034254 examples [1:40:52, 4055.04 examples/s]
Generating train split: 96035563 examples [1:40:53, 5353.71 examples/s]
Generating train split: 96036410 examples [1:40:53, 5299.52 examples/s]
Generating train split: 96037770 examples [1:40:53, 6756.74 examples/s]
Generating train split: 96038693 examples [1:40:53, 6407.93 examples/s]
Generating train split: 96040696 examples [1:40:53, 9188.92 examples/s]
Generating train split: 96042376 examples [1:40:53, 10836.71 examples/s]
Generating train split: 96043686 examples [1:40:53, 9066.40 examples/s] 
Generating train split: 96044797 examples [1:40:54, 5499.13 examples/s]
Generating train split: 96045653 examples [1:40:54, 5464.36 examples/s]
Generating train split: 96046421 examples [1:40:54, 5377.50 examples/s]
Generating train split: 96047106 examples [1:40:55, 3631.71 examples/s]
Generating train split: 96050433 examples [1:40:55, 7823.23 examples/s]
Generating train split: 96058450 examples [1:40:55, 19980.49 examples/s]
Generating train split: 96064144 examples [1:40:55, 27127.39 examples/s]
Generating train split: 96068205 examples [1:40:55, 24967.20 examples/s]
Generating train split: 96076986 examples [1:40:55, 37814.39 examples/s]
Generating train split: 96083979 examples [1:40:55, 45058.77 examples/s]
Generating train split: 96089617 examples [1:40:56, 16889.32 examples/s]
Generating train split: 96093763 examples [1:40:57, 14670.18 examples/s]
Generating train split: 96096973 examples [1:40:57, 11347.77 examples/s]
Generating train split: 96099402 examples [1:40:57, 9482.50 examples/s] 
Generating train split: 96101278 examples [1:40:58, 6971.35 examples/s]
Generating train split: 96102681 examples [1:40:58, 7350.82 examples/s]
Generating train split: 96103985 examples [1:40:58, 7416.05 examples/s]
Generating train split: 96105127 examples [1:40:59, 7016.78 examples/s]
Generating train split: 96106444 examples [1:40:59, 7801.59 examples/s]
Generating train split: 96107512 examples [1:40:59, 7468.54 examples/s]
Generating train split: 96108892 examples [1:40:59, 8523.16 examples/s]
Generating train split: 96109961 examples [1:40:59, 8748.63 examples/s]
Generating train split: 96110995 examples [1:40:59, 7881.54 examples/s]
Generating train split: 96111904 examples [1:40:59, 6633.05 examples/s]
Generating train split: 96112679 examples [1:41:00, 3918.95 examples/s]
Generating train split: 96113342 examples [1:41:00, 4110.70 examples/s]
Generating train split: 96114198 examples [1:41:00, 4816.37 examples/s]
Generating train split: 96114848 examples [1:41:01, 3297.66 examples/s]
Generating train split: 96115608 examples [1:41:01, 3921.95 examples/s]
Generating train split: 96116195 examples [1:41:01, 4185.18 examples/s]
Generating train split: 96117198 examples [1:41:01, 5319.76 examples/s]
Generating train split: 96118905 examples [1:41:01, 7860.84 examples/s]
Generating train split: 96119912 examples [1:41:01, 6395.31 examples/s]
Generating train split: 96121306 examples [1:41:01, 7938.71 examples/s]
Generating train split: 96122314 examples [1:41:02, 4941.80 examples/s]
Generating train split: 96123090 examples [1:41:02, 4617.75 examples/s]
Generating train split: 96123744 examples [1:41:02, 4542.72 examples/s]
Generating train split: 96124331 examples [1:41:02, 4358.31 examples/s]
Generating train split: 96124899 examples [1:41:02, 4601.45 examples/s]
Generating train split: 96125436 examples [1:41:03, 3857.40 examples/s]
Generating train split: 96125889 examples [1:41:03, 2737.65 examples/s]
Generating train split: 96126839 examples [1:41:03, 3823.92 examples/s]
Generating train split: 96127380 examples [1:41:03, 3893.22 examples/s]
Generating train split: 96127884 examples [1:41:03, 3678.50 examples/s]
Generating train split: 96128338 examples [1:41:04, 3075.20 examples/s]
Generating train split: 96129819 examples [1:41:04, 5246.87 examples/s]
Generating train split: 96130513 examples [1:41:04, 4012.46 examples/s]
Generating train split: 96131072 examples [1:41:04, 3423.24 examples/s]
Generating train split: 96131533 examples [1:41:04, 3019.70 examples/s]
Generating train split: 96131918 examples [1:41:05, 2663.32 examples/s]
Generating train split: 96132494 examples [1:41:05, 3005.68 examples/s]
Generating train split: 96132856 examples [1:41:05, 2873.84 examples/s]
Generating train split: 96134076 examples [1:41:05, 4655.34 examples/s]
Generating train split: 96134660 examples [1:41:05, 3506.00 examples/s]
Generating train split: 96135127 examples [1:41:05, 3112.44 examples/s]
Generating train split: 96135532 examples [1:41:06, 2969.30 examples/s]
Generating train split: 96135890 examples [1:41:06, 3077.88 examples/s]
Generating train split: 96137202 examples [1:41:06, 5192.87 examples/s]
Generating train split: 96138678 examples [1:41:06, 7391.58 examples/s]
Generating train split: 96139576 examples [1:41:06, 4507.51 examples/s]
Generating train split: 96140814 examples [1:41:06, 5844.33 examples/s]
Generating train split: 96141675 examples [1:41:07, 5739.77 examples/s]
Generating train split: 96142444 examples [1:41:07, 4187.10 examples/s]
Generating train split: 96144390 examples [1:41:07, 6684.57 examples/s]
Generating train split: 96145405 examples [1:41:07, 5526.77 examples/s]
Generating train split: 96146224 examples [1:41:08, 4741.40 examples/s]
Generating train split: 96146895 examples [1:41:08, 4075.71 examples/s]
Generating train split: 96147446 examples [1:41:08, 3273.33 examples/s]
Generating train split: 96147898 examples [1:41:08, 2898.60 examples/s]
Generating train split: 96148331 examples [1:41:08, 3109.44 examples/s]
Generating train split: 96148732 examples [1:41:09, 3093.19 examples/s]
Generating train split: 96149274 examples [1:41:09, 3498.73 examples/s]
Generating train split: 96150288 examples [1:41:09, 4899.14 examples/s]
Generating train split: 96150878 examples [1:41:09, 2917.10 examples/s]
Generating train split: 96158054 examples [1:41:09, 13852.10 examples/s]
Generating train split: 96166143 examples [1:41:09, 26248.63 examples/s]
Generating train split: 96170300 examples [1:41:10, 13740.35 examples/s]
Generating train split: 96173400 examples [1:41:11, 9196.58 examples/s] 
Generating train split: 96175718 examples [1:41:11, 7024.05 examples/s]
Generating train split: 96178187 examples [1:41:11, 8452.94 examples/s]
Generating train split: 96180141 examples [1:41:12, 7955.66 examples/s]
Generating train split: 96181699 examples [1:41:12, 8693.74 examples/s]
Generating train split: 96183225 examples [1:41:12, 8141.00 examples/s]
Generating train split: 96184496 examples [1:41:12, 8201.72 examples/s]
Generating train split: 96185639 examples [1:41:12, 8154.58 examples/s]
Generating train split: 96186676 examples [1:41:13, 7832.84 examples/s]
Generating train split: 96187610 examples [1:41:13, 8060.57 examples/s]
Generating train split: 96188534 examples [1:41:13, 5112.20 examples/s]
Generating train split: 96189347 examples [1:41:13, 5572.87 examples/s]
Generating train split: 96190351 examples [1:41:13, 6365.15 examples/s]
Generating train split: 96191557 examples [1:41:13, 7530.68 examples/s]
Generating train split: 96192494 examples [1:41:14, 7222.14 examples/s]
Generating train split: 96193347 examples [1:41:14, 6335.35 examples/s]
Generating train split: 96194233 examples [1:41:14, 6841.38 examples/s]
Generating train split: 96195019 examples [1:41:14, 6929.57 examples/s]
Generating train split: 96196037 examples [1:41:14, 7602.90 examples/s]
Generating train split: 96196866 examples [1:41:14, 7652.80 examples/s]
Generating train split: 96205024 examples [1:41:14, 27269.89 examples/s]
Generating train split: 96212947 examples [1:41:14, 41196.77 examples/s]
Generating train split: 96217368 examples [1:41:15, 13761.38 examples/s]
Generating train split: 96220622 examples [1:41:15, 14741.10 examples/s]
Generating train split: 96229658 examples [1:41:15, 24776.89 examples/s]
Generating train split: 96236076 examples [1:41:16, 31019.53 examples/s]
Generating train split: 96241279 examples [1:41:16, 13564.32 examples/s]
Generating train split: 96245098 examples [1:41:17, 15008.69 examples/s]
Generating train split: 96248479 examples [1:41:17, 13212.57 examples/s]
Generating train split: 96251134 examples [1:41:18, 8864.69 examples/s] 
Generating train split: 96253103 examples [1:41:18, 9616.88 examples/s]
Generating train split: 96256703 examples [1:41:18, 12457.27 examples/s]
Generating train split: 96259074 examples [1:41:18, 10120.20 examples/s]
Generating train split: 96260928 examples [1:41:19, 9405.02 examples/s] 
Generating train split: 96263659 examples [1:41:19, 11694.40 examples/s]
Generating train split: 96272399 examples [1:41:19, 23387.17 examples/s]
Generating train split: 96279658 examples [1:41:19, 31874.77 examples/s]
Generating train split: 96284446 examples [1:41:19, 20363.92 examples/s]
Generating train split: 96288116 examples [1:41:20, 13414.31 examples/s]
Generating train split: 96290872 examples [1:41:21, 9148.52 examples/s] 
Generating train split: 96292925 examples [1:41:21, 9042.60 examples/s]
Generating train split: 96295669 examples [1:41:21, 10864.74 examples/s]
Generating train split: 96297682 examples [1:41:21, 9946.03 examples/s] 
Generating train split: 96299314 examples [1:41:21, 10760.70 examples/s]
Generating train split: 96300946 examples [1:41:21, 11436.53 examples/s]
Generating train split: 96302808 examples [1:41:21, 12711.07 examples/s]
Generating train split: 96304476 examples [1:41:22, 11273.59 examples/s]
Generating train split: 96305896 examples [1:41:22, 8311.59 examples/s] 
Generating train split: 96307874 examples [1:41:22, 10185.95 examples/s]
Generating train split: 96310470 examples [1:41:22, 13171.54 examples/s]
Generating train split: 96312218 examples [1:41:23, 5338.64 examples/s] 
Generating train split: 96313503 examples [1:41:24, 4467.95 examples/s]
Generating train split: 96314487 examples [1:41:24, 3413.19 examples/s]
Generating train split: 96315231 examples [1:41:25, 2939.39 examples/s]
Generating train split: 96315803 examples [1:41:25, 3052.45 examples/s]
Generating train split: 96316319 examples [1:41:25, 2027.70 examples/s]
Generating train split: 96316704 examples [1:41:26, 1875.60 examples/s]
Generating train split: 96317015 examples [1:41:26, 1910.20 examples/s]
Generating train split: 96317715 examples [1:41:26, 2494.10 examples/s]
Generating train split: 96318624 examples [1:41:26, 3413.03 examples/s]
Generating train split: 96319254 examples [1:41:26, 3883.26 examples/s]
Generating train split: 96319824 examples [1:41:26, 3218.69 examples/s]
Generating train split: 96320672 examples [1:41:26, 4130.26 examples/s]
Generating train split: 96321551 examples [1:41:27, 5054.77 examples/s]
Generating train split: 96322221 examples [1:41:27, 4096.63 examples/s]
Generating train split: 96322775 examples [1:41:27, 3452.61 examples/s]
Generating train split: 96324288 examples [1:41:27, 5519.72 examples/s]
Generating train split: 96325297 examples [1:41:27, 6409.63 examples/s]
Generating train split: 96326128 examples [1:41:28, 4550.20 examples/s]
Generating train split: 96328716 examples [1:41:28, 8289.25 examples/s]
Generating train split: 96335210 examples [1:41:28, 19633.43 examples/s]
Generating train split: 96338026 examples [1:41:28, 13889.18 examples/s]
Generating train split: 96340240 examples [1:41:28, 14942.03 examples/s]
Generating train split: 96343286 examples [1:41:28, 17915.04 examples/s]
Generating train split: 96345704 examples [1:41:29, 13147.61 examples/s]
Generating train split: 96347623 examples [1:41:29, 8465.07 examples/s] 
Generating train split: 96349087 examples [1:41:30, 6980.88 examples/s]
Generating train split: 96350240 examples [1:41:30, 4888.03 examples/s]
Generating train split: 96351107 examples [1:41:30, 3991.10 examples/s]
Generating train split: 96352024 examples [1:41:31, 4481.69 examples/s]
Generating train split: 96352763 examples [1:41:31, 3424.42 examples/s]
Generating train split: 96353688 examples [1:41:31, 4066.21 examples/s]
Generating train split: 96355079 examples [1:41:31, 5384.53 examples/s]
Generating train split: 96355955 examples [1:41:32, 4138.95 examples/s]
Generating train split: 96357701 examples [1:41:32, 5979.64 examples/s]
Generating train split: 96359127 examples [1:41:32, 7350.37 examples/s]
Generating train split: 96360252 examples [1:41:32, 5999.30 examples/s]
Generating train split: 96362049 examples [1:41:32, 8011.68 examples/s]
Generating train split: 96363224 examples [1:41:32, 6339.49 examples/s]
Generating train split: 96364176 examples [1:41:33, 6134.21 examples/s]
Generating train split: 96366211 examples [1:41:33, 8422.40 examples/s]
Generating train split: 96367334 examples [1:41:33, 7300.33 examples/s]
Generating train split: 96368739 examples [1:41:33, 8516.22 examples/s]
Generating train split: 96369806 examples [1:41:33, 7984.62 examples/s]
Generating train split: 96370764 examples [1:41:33, 8279.05 examples/s]
Generating train split: 96371712 examples [1:41:33, 7655.16 examples/s]
Generating train split: 96372566 examples [1:41:34, 7510.95 examples/s]
Generating train split: 96373378 examples [1:41:34, 7176.48 examples/s]
Generating train split: 96375168 examples [1:41:34, 9732.01 examples/s]
Generating train split: 96376233 examples [1:41:34, 8565.20 examples/s]
Generating train split: 96377479 examples [1:41:34, 9478.19 examples/s]
Generating train split: 96378509 examples [1:41:34, 9102.41 examples/s]
Generating train split: 96380230 examples [1:41:34, 11162.51 examples/s]
Generating train split: 96381808 examples [1:41:34, 12373.79 examples/s]
Generating train split: 96383119 examples [1:41:35, 10217.17 examples/s]
Generating train split: 96384256 examples [1:41:35, 7968.23 examples/s] 
Generating train split: 96385217 examples [1:41:35, 8288.41 examples/s]
Generating train split: 96386170 examples [1:41:35, 4393.50 examples/s]
Generating train split: 96387968 examples [1:41:36, 6341.45 examples/s]
Generating train split: 96389014 examples [1:41:36, 6766.51 examples/s]
Generating train split: 96390005 examples [1:41:36, 6551.76 examples/s]
Generating train split: 96390874 examples [1:41:36, 6768.34 examples/s]
Generating train split: 96391832 examples [1:41:36, 7340.94 examples/s]
Generating train split: 96393389 examples [1:41:36, 9240.39 examples/s]
Generating train split: 96394463 examples [1:41:36, 8235.51 examples/s]
Generating train split: 96395624 examples [1:41:36, 8997.92 examples/s]
Generating train split: 96398012 examples [1:41:37, 12708.88 examples/s]
Generating train split: 96405737 examples [1:41:37, 29664.61 examples/s]
Generating train split: 96414575 examples [1:41:37, 45686.42 examples/s]
Generating train split: 96419546 examples [1:41:37, 24529.34 examples/s]
Generating train split: 96423380 examples [1:41:37, 23318.64 examples/s]
Generating train split: 96426681 examples [1:41:37, 22638.93 examples/s]
Generating train split: 96429608 examples [1:41:38, 16922.75 examples/s]
Generating train split: 96431939 examples [1:41:38, 17295.52 examples/s]
Generating train split: 96435137 examples [1:41:38, 19521.02 examples/s]
Generating train split: 96437543 examples [1:41:38, 12852.25 examples/s]
Generating train split: 96439518 examples [1:41:39, 13901.78 examples/s]
Generating train split: 96441423 examples [1:41:39, 13211.92 examples/s]
Generating train split: 96443088 examples [1:41:39, 11837.70 examples/s]
Generating train split: 96444668 examples [1:41:39, 12408.63 examples/s]
Generating train split: 96446109 examples [1:41:39, 10752.78 examples/s]
Generating train split: 96447354 examples [1:41:40, 7638.22 examples/s] 
Generating train split: 96448747 examples [1:41:40, 8635.67 examples/s]
Generating train split: 96449851 examples [1:41:40, 8894.87 examples/s]
Generating train split: 96450920 examples [1:41:40, 5504.05 examples/s]
Generating train split: 96457425 examples [1:41:40, 14460.26 examples/s]
Generating train split: 96466122 examples [1:41:40, 27282.06 examples/s]
Generating train split: 96470502 examples [1:41:41, 28667.13 examples/s]
Generating train split: 96474552 examples [1:41:41, 16936.40 examples/s]
Generating train split: 96477640 examples [1:41:41, 12625.31 examples/s]
Generating train split: 96479999 examples [1:41:42, 10088.71 examples/s]
Generating train split: 96481830 examples [1:41:42, 9054.49 examples/s] 
Generating train split: 96483294 examples [1:41:43, 7493.16 examples/s]
Generating train split: 96485405 examples [1:41:43, 9017.60 examples/s]
Generating train split: 96486973 examples [1:41:43, 9888.38 examples/s]
Generating train split: 96488432 examples [1:41:43, 7467.45 examples/s]
Generating train split: 96490142 examples [1:41:43, 8808.90 examples/s]
Generating train split: 96491449 examples [1:41:44, 6588.67 examples/s]
Generating train split: 96492575 examples [1:41:44, 7215.83 examples/s]
Generating train split: 96493624 examples [1:41:44, 6683.89 examples/s]
Generating train split: 96494524 examples [1:41:44, 5242.66 examples/s]
Generating train split: 96495247 examples [1:41:45, 3993.61 examples/s]
Generating train split: 96496079 examples [1:41:45, 4576.58 examples/s]
Generating train split: 96496724 examples [1:41:45, 4333.61 examples/s]
Generating train split: 96497284 examples [1:41:45, 3581.95 examples/s]
Generating train split: 96497937 examples [1:41:45, 3999.39 examples/s]
Generating train split: 96498439 examples [1:41:46, 2433.89 examples/s]
Generating train split: 96498834 examples [1:41:46, 2231.09 examples/s]
Generating train split: 96499158 examples [1:41:46, 2284.65 examples/s]
Generating train split: 96499522 examples [1:41:46, 2427.39 examples/s]
Generating train split: 96499822 examples [1:41:46, 2263.91 examples/s]
Generating train split: 96500192 examples [1:41:46, 2495.67 examples/s]
Generating train split: 96501542 examples [1:41:47, 4801.28 examples/s]
Generating train split: 96509231 examples [1:41:47, 21404.29 examples/s]
Generating train split: 96515255 examples [1:41:47, 31014.86 examples/s]
Generating train split: 96518987 examples [1:41:47, 21771.41 examples/s]
Generating train split: 96521986 examples [1:41:47, 15175.62 examples/s]
Generating train split: 96524319 examples [1:41:48, 15557.83 examples/s]
Generating train split: 96526473 examples [1:41:48, 10943.58 examples/s]
Generating train split: 96528447 examples [1:41:48, 12180.60 examples/s]
Generating train split: 96530208 examples [1:41:48, 8845.26 examples/s] 
Generating train split: 96531581 examples [1:41:49, 6077.91 examples/s]
Generating train split: 96533739 examples [1:41:49, 7765.56 examples/s]
Generating train split: 96535297 examples [1:41:49, 8829.64 examples/s]
Generating train split: 96536712 examples [1:41:49, 6885.52 examples/s]
Generating train split: 96537819 examples [1:41:50, 6669.09 examples/s]
Generating train split: 96539043 examples [1:41:50, 7391.58 examples/s]
Generating train split: 96540036 examples [1:41:50, 4979.45 examples/s]
Generating train split: 96541145 examples [1:41:50, 5825.11 examples/s]
Generating train split: 96542167 examples [1:41:50, 6548.80 examples/s]
Generating train split: 96543083 examples [1:41:51, 5426.18 examples/s]
Generating train split: 96545213 examples [1:41:51, 8129.79 examples/s]
Generating train split: 96546354 examples [1:41:51, 5874.34 examples/s]
Generating train split: 96547254 examples [1:41:51, 6231.01 examples/s]
Generating train split: 96548120 examples [1:41:51, 6378.40 examples/s]
Generating train split: 96548938 examples [1:41:52, 5755.88 examples/s]
Generating train split: 96549654 examples [1:41:52, 3964.76 examples/s]
Generating train split: 96550598 examples [1:41:52, 4806.47 examples/s]
Generating train split: 96551266 examples [1:41:52, 4887.61 examples/s]
Generating train split: 96551894 examples [1:41:52, 4260.61 examples/s]
Generating train split: 96552420 examples [1:41:52, 3956.96 examples/s]
Generating train split: 96559649 examples [1:41:53, 17168.74 examples/s]
Generating train split: 96568068 examples [1:41:53, 31665.33 examples/s]
Generating train split: 96572337 examples [1:41:53, 16847.63 examples/s]
Generating train split: 96575575 examples [1:41:54, 7716.07 examples/s] 
Generating train split: 96577924 examples [1:41:55, 5037.92 examples/s]
Generating train split: 96580246 examples [1:41:56, 6086.25 examples/s]
Generating train split: 96582132 examples [1:41:56, 5096.06 examples/s]
Generating train split: 96583551 examples [1:41:56, 5051.08 examples/s]
Generating train split: 96584694 examples [1:41:57, 5371.35 examples/s]
Generating train split: 96586390 examples [1:41:57, 6565.55 examples/s]
Generating train split: 96587625 examples [1:41:57, 5502.57 examples/s]
Generating train split: 96588594 examples [1:41:57, 5590.97 examples/s]
Generating train split: 96590092 examples [1:41:57, 6893.97 examples/s]
Generating train split: 96591143 examples [1:41:57, 7435.06 examples/s]
Generating train split: 96592400 examples [1:41:58, 8386.53 examples/s]
Generating train split: 96593499 examples [1:41:58, 6571.02 examples/s]
Generating train split: 96596822 examples [1:41:58, 11441.64 examples/s]
Generating train split: 96604570 examples [1:41:58, 25110.64 examples/s]
Generating train split: 96610299 examples [1:41:58, 32435.14 examples/s]
Generating train split: 96614435 examples [1:41:59, 10649.68 examples/s]
Generating train split: 96617454 examples [1:42:00, 6767.28 examples/s] 
Generating train split: 96619660 examples [1:42:00, 7639.36 examples/s]
Generating train split: 96622604 examples [1:42:00, 9570.02 examples/s]
Generating train split: 96625957 examples [1:42:00, 12261.77 examples/s]
Generating train split: 96632075 examples [1:42:01, 19027.57 examples/s]
Generating train split: 96638220 examples [1:42:01, 26022.30 examples/s]
Generating train split: 96644829 examples [1:42:01, 33639.40 examples/s]
Generating train split: 96652644 examples [1:42:01, 43152.52 examples/s]
Generating train split: 96659430 examples [1:42:01, 48935.45 examples/s]
Generating train split: 96666982 examples [1:42:01, 55580.39 examples/s]
Generating train split: 96674091 examples [1:42:01, 59646.31 examples/s]
Generating train split: 96680824 examples [1:42:01, 59986.50 examples/s]
Generating train split: 96687646 examples [1:42:01, 62229.35 examples/s]
Generating train split: 96694272 examples [1:42:01, 63170.91 examples/s]
Generating train split: 96701696 examples [1:42:02, 66339.10 examples/s]
Generating train split: 96708550 examples [1:42:02, 65147.50 examples/s]
Generating train split: 96715837 examples [1:42:02, 67345.59 examples/s]
Generating train split: 96722694 examples [1:42:02, 67435.40 examples/s]
Generating train split: 96729863 examples [1:42:02, 68677.04 examples/s]
Generating train split: 96736791 examples [1:42:02, 67138.87 examples/s]
Generating train split: 96743561 examples [1:42:02, 66490.68 examples/s]
Generating train split: 96750250 examples [1:42:02, 65405.45 examples/s]
Generating train split: 96756831 examples [1:42:02, 65188.69 examples/s]
Generating train split: 96763375 examples [1:42:02, 63683.28 examples/s]
Generating train split: 96769770 examples [1:42:03, 61887.97 examples/s]
Generating train split: 96775988 examples [1:42:03, 57468.73 examples/s]
Generating train split: 96782025 examples [1:42:03, 58260.60 examples/s]
Generating train split: 96787922 examples [1:42:03, 53423.56 examples/s]
Generating train split: 96793375 examples [1:42:03, 49473.43 examples/s]
Generating train split: 96798426 examples [1:42:03, 45473.41 examples/s]
Generating train split: 96803075 examples [1:42:03, 34481.69 examples/s]
Generating train split: 96806956 examples [1:42:04, 30613.06 examples/s]
Generating train split: 96810347 examples [1:42:04, 29955.92 examples/s]
Generating train split: 96813550 examples [1:42:04, 21527.21 examples/s]
Generating train split: 96817334 examples [1:42:04, 24504.51 examples/s]
Generating train split: 96820545 examples [1:42:04, 25631.00 examples/s]
Generating train split: 96823496 examples [1:42:04, 23990.34 examples/s]
Generating train split: 96826165 examples [1:42:05, 13141.65 examples/s]
Generating train split: 96835455 examples [1:42:05, 24875.50 examples/s]
Generating train split: 96843834 examples [1:42:05, 34732.89 examples/s]
Generating train split: 96849146 examples [1:42:06, 22704.22 examples/s]
Generating train split: 96853218 examples [1:42:06, 16857.76 examples/s]
Generating train split: 96856343 examples [1:42:07, 10468.05 examples/s]
Generating train split: 96858654 examples [1:42:07, 9929.60 examples/s] 
Generating train split: 96860521 examples [1:42:07, 9374.82 examples/s]
Generating train split: 96863060 examples [1:42:07, 11100.04 examples/s]
Generating train split: 96871492 examples [1:42:07, 20866.77 examples/s]
Generating train split: 96878365 examples [1:42:08, 28524.09 examples/s]
Generating train split: 96883092 examples [1:42:08, 17920.03 examples/s]
Generating train split: 96886682 examples [1:42:08, 15029.64 examples/s]
Generating train split: 96889484 examples [1:42:09, 15787.31 examples/s]
Generating train split: 96892044 examples [1:42:09, 15417.68 examples/s]
Generating train split: 96894257 examples [1:42:09, 11059.38 examples/s]
Generating train split: 96896677 examples [1:42:09, 12649.97 examples/s]
Generating train split: 96898567 examples [1:42:10, 11455.78 examples/s]
Generating train split: 96900153 examples [1:42:10, 7550.38 examples/s] 
Generating train split: 96901864 examples [1:42:10, 8687.05 examples/s]
Generating train split: 96903209 examples [1:42:10, 7143.30 examples/s]
Generating train split: 96904287 examples [1:42:11, 4021.07 examples/s]
Generating train split: 96905085 examples [1:42:11, 3768.67 examples/s]
Generating train split: 96905728 examples [1:42:12, 3485.90 examples/s]
Generating train split: 96906262 examples [1:42:12, 3367.49 examples/s]
Generating train split: 96906726 examples [1:42:12, 2472.41 examples/s]
Generating train split: 96907568 examples [1:42:12, 3143.27 examples/s]
Generating train split: 96908071 examples [1:42:13, 3081.85 examples/s]
Generating train split: 96908507 examples [1:42:13, 2697.13 examples/s]
Generating train split: 96909110 examples [1:42:13, 3180.69 examples/s]
Generating train split: 96911158 examples [1:42:13, 6251.04 examples/s]
Generating train split: 96912951 examples [1:42:13, 8600.35 examples/s]
Generating train split: 96914123 examples [1:42:13, 8038.13 examples/s]
Generating train split: 96915153 examples [1:42:14, 6305.98 examples/s]
Generating train split: 96916001 examples [1:42:14, 6246.38 examples/s]
Generating train split: 96916776 examples [1:42:14, 5788.81 examples/s]
Generating train split: 96917656 examples [1:42:14, 6096.54 examples/s]
Generating train split: 96918674 examples [1:42:14, 6967.82 examples/s]
Generating train split: 96919999 examples [1:42:14, 8094.21 examples/s]
Generating train split: 96920893 examples [1:42:15, 4699.49 examples/s]
Generating train split: 96923202 examples [1:42:15, 7716.71 examples/s]
Generating train split: 96924378 examples [1:42:15, 8234.71 examples/s]
Generating train split: 96926533 examples [1:42:15, 11002.49 examples/s]
Generating train split: 96927965 examples [1:42:15, 8823.83 examples/s] 
Generating train split: 96930832 examples [1:42:15, 12738.65 examples/s]
Generating train split: 96938687 examples [1:42:15, 27207.31 examples/s]
Generating train split: 96945932 examples [1:42:16, 37870.56 examples/s]
Generating train split: 96950545 examples [1:42:16, 16883.45 examples/s]
Generating train split: 96954004 examples [1:42:16, 17045.51 examples/s]
Generating train split: 96956952 examples [1:42:17, 9932.41 examples/s] 
Generating train split: 96959145 examples [1:42:17, 9926.92 examples/s]
Generating train split: 96960969 examples [1:42:18, 7135.52 examples/s]
Generating train split: 96962344 examples [1:42:18, 5194.94 examples/s]
Generating train split: 96963371 examples [1:42:19, 4146.00 examples/s]
Generating train split: 96964155 examples [1:42:19, 4345.87 examples/s]
Generating train split: 96965824 examples [1:42:19, 5571.64 examples/s]
Generating train split: 96970355 examples [1:42:19, 10564.20 examples/s]
Generating train split: 96978924 examples [1:42:19, 21995.09 examples/s]
Generating train split: 96983253 examples [1:42:20, 25576.82 examples/s]
Generating train split: 96987304 examples [1:42:20, 10850.48 examples/s]
Generating train split: 96990273 examples [1:42:21, 11081.58 examples/s]
Generating train split: 96992712 examples [1:42:21, 8284.95 examples/s] 
Generating train split: 96994557 examples [1:42:21, 8560.75 examples/s]
Generating train split: 96996154 examples [1:42:22, 6471.93 examples/s]
Generating train split: 96997366 examples [1:42:22, 6118.73 examples/s]
Generating train split: 97004406 examples [1:42:22, 13107.74 examples/s]
Generating train split: 97013701 examples [1:42:22, 23840.58 examples/s]
Generating train split: 97018458 examples [1:42:23, 19368.22 examples/s]
Generating train split: 97022186 examples [1:42:23, 13291.62 examples/s]
Generating train split: 97024995 examples [1:42:24, 9669.78 examples/s] 
Generating train split: 97027104 examples [1:42:25, 7143.55 examples/s]
Generating train split: 97028680 examples [1:42:25, 6531.58 examples/s]
Generating train split: 97030033 examples [1:42:25, 7117.52 examples/s]
Generating train split: 97031294 examples [1:42:25, 6820.66 examples/s]
Generating train split: 97032351 examples [1:42:26, 5867.18 examples/s]
Generating train split: 97033889 examples [1:42:26, 6656.77 examples/s]
Generating train split: 97034806 examples [1:42:26, 4700.84 examples/s]
Generating train split: 97035508 examples [1:42:27, 3819.69 examples/s]
Generating train split: 97036112 examples [1:42:27, 4065.71 examples/s]
Generating train split: 97036832 examples [1:42:27, 4484.68 examples/s]
Generating train split: 97037433 examples [1:42:27, 4273.85 examples/s]
Generating train split: 97037963 examples [1:42:27, 3948.48 examples/s]
Generating train split: 97045593 examples [1:42:27, 17237.83 examples/s]
Generating train split: 97054972 examples [1:42:27, 33145.78 examples/s]
Generating train split: 97059615 examples [1:42:27, 28640.00 examples/s]
Generating train split: 97063513 examples [1:42:28, 15803.14 examples/s]
Generating train split: 97066462 examples [1:42:28, 12236.29 examples/s]
Generating train split: 97068726 examples [1:42:29, 12254.54 examples/s]
Generating train split: 97070680 examples [1:42:29, 11628.60 examples/s]
Generating train split: 97077571 examples [1:42:29, 19706.82 examples/s]
Generating train split: 97085333 examples [1:42:29, 28530.14 examples/s]
Generating train split: 97089557 examples [1:42:29, 21526.75 examples/s]
Generating train split: 97092896 examples [1:42:30, 15405.22 examples/s]
Generating train split: 97101086 examples [1:42:30, 23966.12 examples/s]
Generating train split: 97107930 examples [1:42:30, 30694.60 examples/s]
Generating train split: 97112886 examples [1:42:31, 18743.02 examples/s]
Generating train split: 97116623 examples [1:42:31, 18935.08 examples/s]
Generating train split: 97119838 examples [1:42:31, 15822.62 examples/s]
Generating train split: 97122386 examples [1:42:32, 7318.27 examples/s] 
Generating train split: 97124234 examples [1:42:33, 6234.13 examples/s]
Generating train split: 97125638 examples [1:42:33, 5862.94 examples/s]
Generating train split: 97126754 examples [1:42:33, 5299.56 examples/s]
Generating train split: 97127639 examples [1:42:34, 4209.89 examples/s]
Generating train split: 97128318 examples [1:42:34, 3950.23 examples/s]
Generating train split: 97129162 examples [1:42:34, 4398.43 examples/s]
Generating train split: 97129802 examples [1:42:34, 4155.26 examples/s]
Generating train split: 97134409 examples [1:42:35, 9992.98 examples/s]
Generating train split: 97143034 examples [1:42:35, 22645.92 examples/s]
Generating train split: 97149642 examples [1:42:35, 30961.51 examples/s]
Generating train split: 97154304 examples [1:42:35, 19419.31 examples/s]
Generating train split: 97157876 examples [1:42:36, 12137.72 examples/s]
Generating train split: 97160547 examples [1:42:36, 8677.63 examples/s] 
Generating train split: 97164554 examples [1:42:37, 11410.36 examples/s]
Generating train split: 97172575 examples [1:42:37, 19018.31 examples/s]
Generating train split: 97177606 examples [1:42:37, 23283.45 examples/s]
Generating train split: 97182069 examples [1:42:37, 14683.62 examples/s]
Generating train split: 97185413 examples [1:42:38, 10249.46 examples/s]
Generating train split: 97187906 examples [1:42:38, 10884.00 examples/s]
Generating train split: 97190096 examples [1:42:39, 8997.86 examples/s] 
Generating train split: 97197439 examples [1:42:39, 15629.98 examples/s]
Generating train split: 97204329 examples [1:42:39, 22372.32 examples/s]
Generating train split: 97208708 examples [1:42:39, 17923.58 examples/s]
Generating train split: 97212122 examples [1:42:40, 9008.56 examples/s] 
Generating train split: 97214619 examples [1:42:41, 8684.24 examples/s]
Generating train split: 97216587 examples [1:42:41, 8093.68 examples/s]
Generating train split: 97223800 examples [1:42:41, 14135.29 examples/s]
Generating train split: 97231552 examples [1:42:41, 21663.22 examples/s]
Generating train split: 97236163 examples [1:42:41, 22005.88 examples/s]
Generating train split: 97240082 examples [1:42:42, 15448.56 examples/s]
Generating train split: 97243068 examples [1:42:42, 12915.91 examples/s]
Generating train split: 97245396 examples [1:42:42, 11610.30 examples/s]
Generating train split: 97247279 examples [1:42:43, 9850.81 examples/s] 
Generating train split: 97248764 examples [1:42:43, 10404.88 examples/s]
Generating train split: 97256321 examples [1:42:43, 19793.60 examples/s]
Generating train split: 97264815 examples [1:42:43, 30907.70 examples/s]
Generating train split: 97269676 examples [1:42:44, 19184.87 examples/s]
Generating train split: 97273369 examples [1:42:44, 12911.94 examples/s]
Generating train split: 97276138 examples [1:42:45, 9347.14 examples/s] 
Generating train split: 97278210 examples [1:42:45, 9863.05 examples/s]
Generating train split: 97280065 examples [1:42:46, 5483.06 examples/s]
Generating train split: 97281414 examples [1:42:46, 5885.05 examples/s]
Generating train split: 97289363 examples [1:42:46, 12546.33 examples/s]
Generating train split: 97298176 examples [1:42:46, 21198.72 examples/s]
Generating train split: 97303092 examples [1:42:47, 13856.23 examples/s]
Generating train split: 97312349 examples [1:42:47, 21701.86 examples/s]
Generating train split: 97320147 examples [1:42:47, 28650.61 examples/s]
Generating train split: 97326179 examples [1:42:48, 19829.12 examples/s]
Generating train split: 97330728 examples [1:42:49, 10971.67 examples/s]
Generating train split: 97334057 examples [1:42:49, 8980.20 examples/s] 
Generating train split: 97336538 examples [1:42:50, 6171.29 examples/s]
Generating train split: 97338343 examples [1:42:51, 6315.37 examples/s]
Generating train split: 97339826 examples [1:42:51, 6068.93 examples/s]
Generating train split: 97341014 examples [1:42:51, 6149.63 examples/s]
Generating train split: 97342541 examples [1:42:51, 7013.32 examples/s]
Generating train split: 97344098 examples [1:42:51, 8036.37 examples/s]
Generating train split: 97345889 examples [1:42:51, 9426.93 examples/s]
Generating train split: 97347298 examples [1:42:52, 8586.39 examples/s]
Generating train split: 97355603 examples [1:42:52, 21397.18 examples/s]
Generating train split: 97363522 examples [1:42:52, 32378.48 examples/s]
Generating train split: 97368073 examples [1:42:53, 15563.03 examples/s]
Generating train split: 97371469 examples [1:42:54, 8490.25 examples/s] 
Generating train split: 97373944 examples [1:42:54, 6380.34 examples/s]
Generating train split: 97375769 examples [1:42:55, 6260.03 examples/s]
Generating train split: 97377218 examples [1:42:55, 6160.46 examples/s]
Generating train split: 97378413 examples [1:42:55, 6050.42 examples/s]
Generating train split: 97379580 examples [1:42:55, 6630.06 examples/s]
Generating train split: 97380791 examples [1:42:55, 7322.47 examples/s]
Generating train split: 97381882 examples [1:42:56, 6254.91 examples/s]
Generating train split: 97382779 examples [1:42:56, 5333.09 examples/s]
Generating train split: 97383509 examples [1:42:56, 5554.73 examples/s]
Generating train split: 97384223 examples [1:42:56, 5154.88 examples/s]
Generating train split: 97385112 examples [1:42:56, 5770.18 examples/s]
Generating train split: 97388257 examples [1:42:56, 10933.43 examples/s]
Generating train split: 97397087 examples [1:42:56, 28197.28 examples/s]
Generating train split: 97403509 examples [1:42:57, 36899.85 examples/s]
Generating train split: 97408000 examples [1:42:57, 21612.05 examples/s]
Generating train split: 97411464 examples [1:42:57, 16809.62 examples/s]
Generating train split: 97414191 examples [1:42:58, 12557.10 examples/s]
Generating train split: 97416294 examples [1:42:58, 9203.29 examples/s] 
Generating train split: 97419553 examples [1:42:58, 11716.84 examples/s]
Generating train split: 97427881 examples [1:42:58, 21240.53 examples/s]
Generating train split: 97435644 examples [1:42:59, 29980.89 examples/s]
Generating train split: 97440633 examples [1:42:59, 17812.51 examples/s]
Generating train split: 97444389 examples [1:42:59, 17645.05 examples/s]
Generating train split: 97452769 examples [1:42:59, 26397.85 examples/s]
Generating train split: 97459417 examples [1:43:00, 32761.86 examples/s]
Generating train split: 97464707 examples [1:43:00, 15690.41 examples/s]
Generating train split: 97468602 examples [1:43:01, 11620.04 examples/s]
Generating train split: 97471517 examples [1:43:02, 8486.39 examples/s] 
Generating train split: 97473671 examples [1:43:03, 6064.54 examples/s]
Generating train split: 97475263 examples [1:43:03, 5535.13 examples/s]
Generating train split: 97476490 examples [1:43:03, 5224.36 examples/s]
Generating train split: 97477464 examples [1:43:04, 4440.53 examples/s]
Generating train split: 97478602 examples [1:43:04, 5013.68 examples/s]
Generating train split: 97479473 examples [1:43:04, 5310.30 examples/s]
Generating train split: 97480704 examples [1:43:04, 6195.38 examples/s]
Generating train split: 97481649 examples [1:43:04, 5862.04 examples/s]
Generating train split: 97482626 examples [1:43:04, 6462.91 examples/s]
Generating train split: 97483479 examples [1:43:05, 6529.78 examples/s]
Generating train split: 97484289 examples [1:43:05, 6454.21 examples/s]
Generating train split: 97485038 examples [1:43:05, 5407.98 examples/s]
Generating train split: 97487204 examples [1:43:05, 8646.03 examples/s]
Generating train split: 97488476 examples [1:43:05, 9546.17 examples/s]
Generating train split: 97489928 examples [1:43:05, 10738.24 examples/s]
Generating train split: 97491164 examples [1:43:05, 6922.07 examples/s] 
Generating train split: 97492139 examples [1:43:06, 5738.84 examples/s]
Generating train split: 97492938 examples [1:43:06, 4726.56 examples/s]
Generating train split: 97493593 examples [1:43:06, 4687.52 examples/s]
Generating train split: 97494191 examples [1:43:06, 4224.01 examples/s]
Generating train split: 97495619 examples [1:43:06, 5986.06 examples/s]
Generating train split: 97496401 examples [1:43:07, 4544.56 examples/s]
Generating train split: 97497037 examples [1:43:07, 4755.98 examples/s]
Generating train split: 97497654 examples [1:43:07, 4867.50 examples/s]
Generating train split: 97498240 examples [1:43:07, 4892.79 examples/s]
Generating train split: 97498801 examples [1:43:07, 3448.58 examples/s]
Generating train split: 97500289 examples [1:43:08, 5497.84 examples/s]
Generating train split: 97501050 examples [1:43:08, 5427.46 examples/s]
Generating train split: 97508293 examples [1:43:08, 19536.14 examples/s]
Generating train split: 97516217 examples [1:43:08, 33333.31 examples/s]
Generating train split: 97520455 examples [1:43:09, 13520.66 examples/s]
Generating train split: 97523594 examples [1:43:10, 7689.42 examples/s] 
Generating train split: 97525895 examples [1:43:10, 6782.93 examples/s]
Generating train split: 97527635 examples [1:43:11, 5786.60 examples/s]
Generating train split: 97529209 examples [1:43:11, 6552.34 examples/s]
Generating train split: 97530599 examples [1:43:11, 6805.02 examples/s]
Generating train split: 97531822 examples [1:43:11, 5345.71 examples/s]
Generating train split: 97533311 examples [1:43:11, 6371.61 examples/s]
Generating train split: 97534418 examples [1:43:12, 5430.48 examples/s]
Generating train split: 97535302 examples [1:43:12, 5180.79 examples/s]
Generating train split: 97536521 examples [1:43:12, 6156.17 examples/s]
Generating train split: 97537452 examples [1:43:12, 6671.46 examples/s]
Generating train split: 97538367 examples [1:43:12, 4999.28 examples/s]
Generating train split: 97539491 examples [1:43:13, 6002.15 examples/s]
Generating train split: 97540894 examples [1:43:13, 7489.82 examples/s]
Generating train split: 97541898 examples [1:43:13, 7808.95 examples/s]
Generating train split: 97543707 examples [1:43:13, 10128.18 examples/s]
Generating train split: 97544939 examples [1:43:13, 7932.26 examples/s] 
Generating train split: 97546649 examples [1:43:13, 9755.75 examples/s]
Generating train split: 97547859 examples [1:43:13, 8911.10 examples/s]
Generating train split: 97548916 examples [1:43:14, 6545.50 examples/s]
Generating train split: 97549775 examples [1:43:14, 6876.40 examples/s]
Generating train split: 97551753 examples [1:43:14, 9451.10 examples/s]
Generating train split: 97552925 examples [1:43:14, 6213.58 examples/s]
Generating train split: 97554133 examples [1:43:14, 7190.21 examples/s]
Generating train split: 97555596 examples [1:43:14, 8605.06 examples/s]
Generating train split: 97556733 examples [1:43:15, 6535.89 examples/s]
Generating train split: 97557656 examples [1:43:15, 6845.36 examples/s]
Generating train split: 97558538 examples [1:43:15, 4301.80 examples/s]
Generating train split: 97559215 examples [1:43:15, 4655.97 examples/s]
Generating train split: 97562139 examples [1:43:15, 8871.97 examples/s]
Generating train split: 97563492 examples [1:43:16, 9777.71 examples/s]
Generating train split: 97564848 examples [1:43:16, 7150.36 examples/s]
Generating train split: 97566304 examples [1:43:16, 8405.89 examples/s]
Generating train split: 97572147 examples [1:43:16, 18341.78 examples/s]
Generating train split: 97580320 examples [1:43:16, 32345.00 examples/s]
Generating train split: 97584572 examples [1:43:16, 31145.21 examples/s]
Generating train split: 97588405 examples [1:43:17, 11457.92 examples/s]
Generating train split: 97591223 examples [1:43:18, 11200.61 examples/s]
Generating train split: 97593504 examples [1:43:18, 7666.49 examples/s] 
Generating train split: 97595211 examples [1:43:19, 7032.44 examples/s]
Generating train split: 97596554 examples [1:43:19, 7034.82 examples/s]
Generating train split: 97598098 examples [1:43:19, 7974.08 examples/s]
Generating train split: 97599377 examples [1:43:19, 7904.46 examples/s]
Generating train split: 97600629 examples [1:43:19, 8608.23 examples/s]
Generating train split: 97601884 examples [1:43:19, 8807.50 examples/s]
Generating train split: 97602980 examples [1:43:19, 6947.39 examples/s]
Generating train split: 97604337 examples [1:43:20, 8059.64 examples/s]
Generating train split: 97605363 examples [1:43:20, 6015.80 examples/s]
Generating train split: 97606183 examples [1:43:20, 6138.30 examples/s]
Generating train split: 97607048 examples [1:43:20, 6604.01 examples/s]
Generating train split: 97607906 examples [1:43:20, 6951.13 examples/s]
Generating train split: 97608713 examples [1:43:20, 6018.62 examples/s]
Generating train split: 97609409 examples [1:43:21, 5754.24 examples/s]
Generating train split: 97617827 examples [1:43:21, 23086.53 examples/s]
Generating train split: 97627004 examples [1:43:21, 39563.61 examples/s]
Generating train split: 97631836 examples [1:43:21, 20397.02 examples/s]
Generating train split: 97635507 examples [1:43:22, 14875.72 examples/s]
Generating train split: 97638315 examples [1:43:22, 13286.34 examples/s]
Generating train split: 97640578 examples [1:43:23, 9546.28 examples/s] 
Generating train split: 97642289 examples [1:43:23, 7025.01 examples/s]
Generating train split: 97643583 examples [1:43:24, 5274.96 examples/s]
Generating train split: 97644753 examples [1:43:24, 5639.93 examples/s]
Generating train split: 97645997 examples [1:43:24, 6343.30 examples/s]
Generating train split: 97647026 examples [1:43:24, 6611.77 examples/s]
Generating train split: 97647998 examples [1:43:24, 5587.53 examples/s]
Generating train split: 97648781 examples [1:43:25, 4856.91 examples/s]
Generating train split: 97649865 examples [1:43:25, 5725.12 examples/s]
Generating train split: 97650780 examples [1:43:25, 6314.99 examples/s]
Generating train split: 97651612 examples [1:43:25, 5828.07 examples/s]
Generating train split: 97652756 examples [1:43:25, 6883.17 examples/s]
Generating train split: 97653597 examples [1:43:25, 6394.40 examples/s]
Generating train split: 97654344 examples [1:43:25, 4779.90 examples/s]
Generating train split: 97655788 examples [1:43:26, 6536.34 examples/s]
Generating train split: 97656650 examples [1:43:26, 3964.57 examples/s]
Generating train split: 97657569 examples [1:43:26, 4686.55 examples/s]
Generating train split: 97658300 examples [1:43:26, 3830.59 examples/s]
Generating train split: 97658902 examples [1:43:27, 4134.88 examples/s]
Generating train split: 97660180 examples [1:43:27, 5676.54 examples/s]
Generating train split: 97661165 examples [1:43:27, 6490.00 examples/s]
Generating train split: 97662006 examples [1:43:27, 5819.49 examples/s]
Generating train split: 97662733 examples [1:43:27, 5773.93 examples/s]
Generating train split: 97664005 examples [1:43:27, 7293.97 examples/s]
Generating train split: 97665329 examples [1:43:27, 8694.57 examples/s]
Generating train split: 97666316 examples [1:43:27, 6692.80 examples/s]
Generating train split: 97667139 examples [1:43:28, 6976.63 examples/s]
Generating train split: 97667960 examples [1:43:28, 6501.33 examples/s]
Generating train split: 97668699 examples [1:43:28, 4958.97 examples/s]
Generating train split: 97669412 examples [1:43:28, 5370.89 examples/s]
Generating train split: 97670052 examples [1:43:28, 3862.08 examples/s]
Generating train split: 97670896 examples [1:43:28, 4649.76 examples/s]
Generating train split: 97671503 examples [1:43:29, 4587.94 examples/s]
Generating train split: 97672090 examples [1:43:29, 4850.28 examples/s]
Generating train split: 97673183 examples [1:43:29, 6241.77 examples/s]
Generating train split: 97673965 examples [1:43:29, 6621.66 examples/s]
Generating train split: 97674714 examples [1:43:29, 5267.00 examples/s]
Generating train split: 97675339 examples [1:43:29, 5399.89 examples/s]
Generating train split: 97676200 examples [1:43:29, 6140.13 examples/s]
Generating train split: 97676880 examples [1:43:29, 5877.55 examples/s]
Generating train split: 97677641 examples [1:43:30, 6114.35 examples/s]
Generating train split: 97681080 examples [1:43:30, 13426.25 examples/s]
Generating train split: 97683735 examples [1:43:30, 16824.83 examples/s]
Generating train split: 97687035 examples [1:43:30, 21199.13 examples/s]
Generating train split: 97689830 examples [1:43:30, 23069.68 examples/s]
Generating train split: 97692249 examples [1:43:30, 19280.94 examples/s]
Generating train split: 97694354 examples [1:43:30, 15855.81 examples/s]
Generating train split: 97696147 examples [1:43:30, 15582.44 examples/s]
Generating train split: 97697845 examples [1:43:31, 13423.89 examples/s]
Generating train split: 97699332 examples [1:43:31, 13372.78 examples/s]
Generating train split: 97700760 examples [1:43:31, 12580.39 examples/s]
Generating train split: 97702220 examples [1:43:31, 12994.06 examples/s]
Generating train split: 97703589 examples [1:43:31, 12152.17 examples/s]
Generating train split: 97705680 examples [1:43:31, 14305.59 examples/s]
Generating train split: 97707576 examples [1:43:31, 15457.27 examples/s]
Generating train split: 97709190 examples [1:43:32, 12176.97 examples/s]
Generating train split: 97710555 examples [1:43:32, 10001.13 examples/s]
Generating train split: 97711920 examples [1:43:32, 10718.31 examples/s]
Generating train split: 97713130 examples [1:43:32, 10230.11 examples/s]
Generating train split: 97714247 examples [1:43:32, 9915.71 examples/s] 
Generating train split: 97715313 examples [1:43:32, 7464.83 examples/s]
Generating train split: 97717480 examples [1:43:32, 10317.61 examples/s]
Generating train split: 97719143 examples [1:43:33, 11706.70 examples/s]
Generating train split: 97721143 examples [1:43:33, 13712.29 examples/s]
Generating train split: 97723024 examples [1:43:33, 14823.60 examples/s]
Generating train split: 97724658 examples [1:43:33, 9505.90 examples/s] 
Generating train split: 97725955 examples [1:43:33, 9428.49 examples/s]
Generating train split: 97728260 examples [1:43:33, 12161.31 examples/s]
Generating train split: 97729770 examples [1:43:34, 11033.36 examples/s]
Generating train split: 97731105 examples [1:43:34, 7818.86 examples/s] 
Generating train split: 97732247 examples [1:43:34, 8385.76 examples/s]
Generating train split: 97733313 examples [1:43:34, 8524.98 examples/s]
Generating train split: 97734532 examples [1:43:34, 8972.14 examples/s]
Generating train split: 97735555 examples [1:43:34, 7700.11 examples/s]
Generating train split: 97736446 examples [1:43:35, 6987.03 examples/s]
Generating train split: 97737601 examples [1:43:35, 7947.80 examples/s]
Generating train split: 97739441 examples [1:43:35, 10257.09 examples/s]
Generating train split: 97740602 examples [1:43:35, 7259.62 examples/s] 
Generating train split: 97741543 examples [1:43:35, 7403.81 examples/s]
Generating train split: 97742435 examples [1:43:35, 7141.43 examples/s]
Generating train split: 97743256 examples [1:43:35, 6363.23 examples/s]
Generating train split: 97744553 examples [1:43:36, 7761.59 examples/s]
Generating train split: 97745475 examples [1:43:36, 8080.69 examples/s]
Generating train split: 97746383 examples [1:43:36, 7721.88 examples/s]
Generating train split: 97747221 examples [1:43:36, 7351.96 examples/s]
Generating train split: 97748006 examples [1:43:36, 5662.81 examples/s]
Generating train split: 97749114 examples [1:43:36, 6796.77 examples/s]
Generating train split: 97751161 examples [1:43:36, 9966.66 examples/s]
Generating train split: 97753078 examples [1:43:36, 12254.18 examples/s]
Generating train split: 97754469 examples [1:43:37, 9176.18 examples/s] 
Generating train split: 97756538 examples [1:43:37, 11626.06 examples/s]
Generating train split: 97757958 examples [1:43:37, 9830.15 examples/s] 
Generating train split: 97759161 examples [1:43:37, 8805.62 examples/s]
Generating train split: 97760217 examples [1:43:37, 8064.29 examples/s]
Generating train split: 97761203 examples [1:43:37, 8426.12 examples/s]
Generating train split: 97762145 examples [1:43:38, 6000.00 examples/s]
Generating train split: 97762988 examples [1:43:38, 6439.31 examples/s]
Generating train split: 97763995 examples [1:43:38, 7159.29 examples/s]
Generating train split: 97764836 examples [1:43:38, 7359.88 examples/s]
Generating train split: 97766252 examples [1:43:38, 8937.03 examples/s]
Generating train split: 97767248 examples [1:43:38, 8506.30 examples/s]
Generating train split: 97768182 examples [1:43:38, 8082.20 examples/s]
Generating train split: 97769044 examples [1:43:39, 7177.73 examples/s]
Generating train split: 97769816 examples [1:43:39, 6257.36 examples/s]
Generating train split: 97770520 examples [1:43:39, 6396.89 examples/s]
Generating train split: 97771331 examples [1:43:39, 6793.99 examples/s]
Generating train split: 97772316 examples [1:43:39, 7514.15 examples/s]
Generating train split: 97774053 examples [1:43:39, 10143.55 examples/s]
Generating train split: 97775136 examples [1:43:39, 7698.94 examples/s] 
Generating train split: 97776168 examples [1:43:39, 8232.09 examples/s]
Generating train split: 97777101 examples [1:43:40, 8064.84 examples/s]
Generating train split: 97778785 examples [1:43:40, 10125.60 examples/s]
Generating train split: 97779898 examples [1:43:40, 10304.47 examples/s]
Generating train split: 97780991 examples [1:43:40, 6805.37 examples/s] 
Generating train split: 97781871 examples [1:43:40, 6570.79 examples/s]
Generating train split: 97782664 examples [1:43:40, 5851.41 examples/s]
Generating train split: 97783759 examples [1:43:41, 6856.42 examples/s]
Generating train split: 97784570 examples [1:43:41, 6669.99 examples/s]
Generating train split: 97786771 examples [1:43:41, 10185.17 examples/s]
Generating train split: 97787955 examples [1:43:41, 9303.63 examples/s] 
Generating train split: 97789123 examples [1:43:41, 9807.79 examples/s]
Generating train split: 97790217 examples [1:43:41, 7659.79 examples/s]
Generating train split: 97791576 examples [1:43:41, 8914.33 examples/s]
Generating train split: 97792626 examples [1:43:42, 7959.06 examples/s]
Generating train split: 97793537 examples [1:43:42, 6905.37 examples/s]
Generating train split: 97794618 examples [1:43:42, 7644.57 examples/s]
Generating train split: 97795478 examples [1:43:42, 7785.62 examples/s]
Generating train split: 97796433 examples [1:43:42, 8187.66 examples/s]
Generating train split: 97797617 examples [1:43:42, 9114.79 examples/s]
Generating train split: 97798596 examples [1:43:42, 7257.03 examples/s]
Generating train split: 97799845 examples [1:43:42, 8453.42 examples/s]
Generating train split: 97800796 examples [1:43:43, 5098.83 examples/s]
Generating train split: 97801534 examples [1:43:43, 4766.88 examples/s]
Generating train split: 97802425 examples [1:43:43, 5493.01 examples/s]
Generating train split: 97803138 examples [1:43:43, 4492.19 examples/s]
Generating train split: 97805037 examples [1:43:43, 7082.55 examples/s]
Generating train split: 97806001 examples [1:43:44, 7371.42 examples/s]
Generating train split: 97806926 examples [1:43:44, 7653.93 examples/s]
Generating train split: 97807840 examples [1:43:44, 5253.46 examples/s]
Generating train split: 97808563 examples [1:43:44, 4529.67 examples/s]
Generating train split: 97809341 examples [1:43:44, 5082.14 examples/s]
Generating train split: 97809991 examples [1:43:44, 5085.17 examples/s]
Generating train split: 97813435 examples [1:43:45, 11237.05 examples/s]
Generating train split: 97814876 examples [1:43:45, 10946.36 examples/s]
Generating train split: 97816190 examples [1:43:45, 11196.14 examples/s]
Generating train split: 97817468 examples [1:43:45, 11068.69 examples/s]
Generating train split: 97818685 examples [1:43:45, 9731.00 examples/s] 
Generating train split: 97819765 examples [1:43:45, 7268.82 examples/s]
Generating train split: 97820648 examples [1:43:46, 5879.73 examples/s]
Generating train split: 97822872 examples [1:43:46, 8796.15 examples/s]
Generating train split: 97824568 examples [1:43:46, 10413.48 examples/s]
Generating train split: 97825899 examples [1:43:46, 8235.77 examples/s] 
Generating train split: 97826988 examples [1:43:46, 7919.86 examples/s]
Generating train split: 97827962 examples [1:43:47, 4833.67 examples/s]
Generating train split: 97828737 examples [1:43:47, 5248.35 examples/s]
Generating train split: 97831042 examples [1:43:47, 8170.28 examples/s]
Generating train split: 97832221 examples [1:43:47, 6822.13 examples/s]
Generating train split: 97833190 examples [1:43:47, 7257.38 examples/s]
Generating train split: 97834160 examples [1:43:47, 7714.61 examples/s]
Generating train split: 97835115 examples [1:43:47, 7581.23 examples/s]
Generating train split: 97835998 examples [1:43:48, 4885.18 examples/s]
Generating train split: 97836691 examples [1:43:48, 5120.94 examples/s]
Generating train split: 97837444 examples [1:43:48, 5563.79 examples/s]
Generating train split: 97838144 examples [1:43:48, 3880.84 examples/s]
Generating train split: 97841256 examples [1:43:49, 8230.58 examples/s]
Generating train split: 97842456 examples [1:43:49, 4672.23 examples/s]
Generating train split: 97844178 examples [1:43:49, 6215.89 examples/s]
Generating train split: 97845317 examples [1:43:49, 6205.53 examples/s]
Generating train split: 97846678 examples [1:43:49, 7367.12 examples/s]
Generating train split: 97847771 examples [1:43:50, 4633.82 examples/s]
Generating train split: 97849148 examples [1:43:50, 5835.74 examples/s]
Generating train split: 97850140 examples [1:43:51, 4087.87 examples/s]
Generating train split: 97850899 examples [1:43:51, 4429.59 examples/s]
Generating train split: 97851651 examples [1:43:51, 4879.31 examples/s]
Generating train split: 97852385 examples [1:43:51, 4236.62 examples/s]
Generating train split: 97853081 examples [1:43:51, 4687.12 examples/s]
Generating train split: 97853709 examples [1:43:52, 3068.86 examples/s]
Generating train split: 97854198 examples [1:43:52, 2849.05 examples/s]
Generating train split: 97854612 examples [1:43:52, 3038.51 examples/s]
Generating train split: 97855025 examples [1:43:52, 2570.52 examples/s]
Generating train split: 97855576 examples [1:43:52, 3053.15 examples/s]
Generating train split: 97855978 examples [1:43:52, 3111.58 examples/s]
Generating train split: 97856365 examples [1:43:53, 2618.97 examples/s]
Generating train split: 97856866 examples [1:43:53, 3068.87 examples/s]
Generating train split: 97857605 examples [1:43:53, 3991.68 examples/s]
Generating train split: 97858091 examples [1:43:53, 3882.53 examples/s]
Generating train split: 97858539 examples [1:43:53, 3967.27 examples/s]
Generating train split: 97858982 examples [1:43:53, 3729.30 examples/s]
Generating train split: 97859396 examples [1:43:53, 3760.28 examples/s]
Generating train split: 97860056 examples [1:43:53, 4410.87 examples/s]
Generating train split: 97861170 examples [1:43:53, 6190.88 examples/s]
Generating train split: 97861832 examples [1:43:54, 4475.26 examples/s]
Generating train split: 97862991 examples [1:43:54, 6020.94 examples/s]
Generating train split: 97864599 examples [1:43:54, 8389.09 examples/s]
Generating train split: 97865803 examples [1:43:54, 9275.41 examples/s]
Generating train split: 97866861 examples [1:43:54, 7082.12 examples/s]
Generating train split: 97867748 examples [1:43:54, 7056.15 examples/s]
Generating train split: 97868573 examples [1:43:54, 7100.27 examples/s]
Generating train split: 97874297 examples [1:43:55, 19086.26 examples/s]
Generating train split: 97883162 examples [1:43:55, 36785.33 examples/s]
Generating train split: 97887413 examples [1:43:55, 23788.10 examples/s]
Generating train split: 97890785 examples [1:43:56, 12025.09 examples/s]
Generating train split: 97893284 examples [1:43:56, 11357.84 examples/s]
Generating train split: 97895314 examples [1:43:56, 9772.30 examples/s] 
Generating train split: 97896923 examples [1:43:57, 7703.10 examples/s]
Generating train split: 97898172 examples [1:43:57, 7826.45 examples/s]
Generating train split: 97899805 examples [1:43:57, 8912.30 examples/s]
Generating train split: 97901073 examples [1:43:57, 8190.64 examples/s]
Generating train split: 97902161 examples [1:43:57, 6598.05 examples/s]
Generating train split: 97903285 examples [1:43:58, 7190.46 examples/s]
Generating train split: 97904213 examples [1:43:58, 6924.56 examples/s]
Generating train split: 97905415 examples [1:43:58, 7831.96 examples/s]
Generating train split: 97906343 examples [1:43:58, 7190.16 examples/s]
Generating train split: 97907714 examples [1:43:58, 7765.25 examples/s]
Generating train split: 97908773 examples [1:43:58, 8337.29 examples/s]
Generating train split: 97909944 examples [1:43:58, 9107.02 examples/s]
Generating train split: 97910931 examples [1:43:59, 6887.93 examples/s]
Generating train split: 97912224 examples [1:43:59, 8109.03 examples/s]
Generating train split: 97913740 examples [1:43:59, 9683.08 examples/s]
Generating train split: 97915202 examples [1:43:59, 10801.07 examples/s]
Generating train split: 97916405 examples [1:43:59, 9381.86 examples/s] 
Generating train split: 97917461 examples [1:43:59, 7256.13 examples/s]
Generating train split: 97918669 examples [1:43:59, 8231.44 examples/s]
Generating train split: 97919646 examples [1:44:00, 7631.20 examples/s]
Generating train split: 97920533 examples [1:44:00, 7752.47 examples/s]
Generating train split: 97921386 examples [1:44:00, 6195.19 examples/s]
Generating train split: 97922499 examples [1:44:00, 7216.16 examples/s]
Generating train split: 97923340 examples [1:44:00, 6787.02 examples/s]
Generating train split: 97925201 examples [1:44:00, 9423.11 examples/s]
Generating train split: 97926274 examples [1:44:00, 7724.50 examples/s]
Generating train split: 97927183 examples [1:44:01, 7695.93 examples/s]
Generating train split: 97928055 examples [1:44:01, 7557.34 examples/s]
Generating train split: 97928993 examples [1:44:01, 7949.98 examples/s]
Generating train split: 97929841 examples [1:44:01, 7349.71 examples/s]
Generating train split: 97936993 examples [1:44:01, 23207.82 examples/s]
Generating train split: 97945869 examples [1:44:01, 40307.38 examples/s]
Generating train split: 97950416 examples [1:44:01, 30890.26 examples/s]
Generating train split: 97956167 examples [1:44:01, 36825.42 examples/s]
Generating train split: 97964752 examples [1:44:02, 48666.95 examples/s]
Generating train split: 97970396 examples [1:44:02, 46094.41 examples/s]
Generating train split: 97975559 examples [1:44:02, 17205.82 examples/s]
Generating train split: 97979372 examples [1:44:03, 13469.24 examples/s]
Generating train split: 97982272 examples [1:44:03, 13760.27 examples/s]
Generating train split: 97984761 examples [1:44:03, 12088.90 examples/s]
Generating train split: 97986747 examples [1:44:04, 10840.76 examples/s]
Generating train split: 97988638 examples [1:44:04, 11471.34 examples/s]
Generating train split: 97990228 examples [1:44:04, 8809.83 examples/s] 
Generating train split: 97991472 examples [1:44:04, 9281.40 examples/s]
Generating train split: 97992919 examples [1:44:04, 10025.16 examples/s]
Generating train split: 97994212 examples [1:44:05, 9390.93 examples/s] 
Generating train split: 97995909 examples [1:44:05, 10595.95 examples/s]
Generating train split: 97997161 examples [1:44:05, 6688.97 examples/s] 
Generating train split: 97998800 examples [1:44:05, 8172.03 examples/s]
Generating train split: 97999996 examples [1:44:05, 8642.01 examples/s]
Generating train split: 98001133 examples [1:44:06, 6569.46 examples/s]
Generating train split: 98002348 examples [1:44:06, 7517.01 examples/s]
Generating train split: 98003351 examples [1:44:06, 6920.32 examples/s]
Generating train split: 98004225 examples [1:44:06, 5306.83 examples/s]
Generating train split: 98006628 examples [1:44:06, 8458.17 examples/s]
Generating train split: 98007843 examples [1:44:06, 8770.79 examples/s]
Generating train split: 98008983 examples [1:44:07, 7942.13 examples/s]
Generating train split: 98009970 examples [1:44:07, 8123.32 examples/s]
Generating train split: 98011870 examples [1:44:07, 10509.92 examples/s]
Generating train split: 98013166 examples [1:44:07, 11076.43 examples/s]
Generating train split: 98014422 examples [1:44:07, 10887.17 examples/s]
Generating train split: 98015623 examples [1:44:07, 7635.32 examples/s] 
Generating train split: 98016979 examples [1:44:07, 8778.86 examples/s]
Generating train split: 98018311 examples [1:44:08, 9783.44 examples/s]
Generating train split: 98019927 examples [1:44:08, 11256.07 examples/s]
Generating train split: 98021212 examples [1:44:08, 9627.55 examples/s] 
Generating train split: 98022325 examples [1:44:08, 8983.06 examples/s]
Generating train split: 98024042 examples [1:44:08, 10841.38 examples/s]
Generating train split: 98026152 examples [1:44:08, 13260.83 examples/s]
Generating train split: 98027897 examples [1:44:08, 14332.58 examples/s]
Generating train split: 98029450 examples [1:44:08, 11271.09 examples/s]
Generating train split: 98030942 examples [1:44:09, 12100.39 examples/s]
Generating train split: 98034024 examples [1:44:09, 16706.22 examples/s]
Generating train split: 98037006 examples [1:44:09, 20045.37 examples/s]
Generating train split: 98039202 examples [1:44:09, 11798.20 examples/s]
Generating train split: 98040916 examples [1:44:09, 10994.82 examples/s]
Generating train split: 98042390 examples [1:44:10, 8246.67 examples/s] 
Generating train split: 98043567 examples [1:44:10, 8251.46 examples/s]
Generating train split: 98044908 examples [1:44:10, 9063.63 examples/s]
Generating train split: 98046050 examples [1:44:10, 7455.36 examples/s]
Generating train split: 98046985 examples [1:44:10, 6053.92 examples/s]
Generating train split: 98048103 examples [1:44:11, 6899.62 examples/s]
Generating train split: 98048971 examples [1:44:11, 6660.24 examples/s]
Generating train split: 98049989 examples [1:44:11, 7295.97 examples/s]
Generating train split: 98050840 examples [1:44:11, 6639.09 examples/s]
Generating train split: 98052808 examples [1:44:11, 9474.36 examples/s]
Generating train split: 98054658 examples [1:44:11, 11592.97 examples/s]
Generating train split: 98057158 examples [1:44:11, 14783.00 examples/s]
Generating train split: 98058806 examples [1:44:11, 14527.86 examples/s]
Generating train split: 98061234 examples [1:44:11, 17078.54 examples/s]
Generating train split: 98063063 examples [1:44:12, 14897.08 examples/s]
Generating train split: 98064679 examples [1:44:12, 12927.70 examples/s]
Generating train split: 98066111 examples [1:44:12, 11012.52 examples/s]
Generating train split: 98067338 examples [1:44:12, 10071.08 examples/s]
Generating train split: 98068438 examples [1:44:12, 8050.99 examples/s] 
Generating train split: 98069353 examples [1:44:13, 6654.23 examples/s]
Generating train split: 98070460 examples [1:44:13, 7407.73 examples/s]
Generating train split: 98071319 examples [1:44:13, 5569.17 examples/s]
Generating train split: 98072017 examples [1:44:13, 5144.67 examples/s]
Generating train split: 98072911 examples [1:44:13, 5815.84 examples/s]
Generating train split: 98073605 examples [1:44:13, 5407.87 examples/s]
Generating train split: 98076582 examples [1:44:14, 10457.91 examples/s]
Generating train split: 98077899 examples [1:44:14, 5198.91 examples/s] 
Generating train split: 98079183 examples [1:44:14, 6187.81 examples/s]
Generating train split: 98080249 examples [1:44:14, 6594.81 examples/s]
Generating train split: 98081248 examples [1:44:15, 5504.64 examples/s]
Generating train split: 98082899 examples [1:44:15, 7281.82 examples/s]
Generating train split: 98083951 examples [1:44:15, 7578.02 examples/s]
Generating train split: 98085690 examples [1:44:15, 9558.17 examples/s]
Generating train split: 98086908 examples [1:44:15, 7292.67 examples/s]
Generating train split: 98087905 examples [1:44:15, 6027.07 examples/s]
Generating train split: 98088711 examples [1:44:16, 5947.71 examples/s]
Generating train split: 98089444 examples [1:44:16, 6065.36 examples/s]
Generating train split: 98090162 examples [1:44:16, 5055.95 examples/s]
Generating train split: 98090940 examples [1:44:16, 5547.07 examples/s]
Generating train split: 98092293 examples [1:44:16, 7177.29 examples/s]
Generating train split: 98093133 examples [1:44:16, 6177.47 examples/s]
Generating train split: 98094271 examples [1:44:16, 7285.07 examples/s]
Generating train split: 98095113 examples [1:44:17, 6096.09 examples/s]
Generating train split: 98097420 examples [1:44:17, 9715.76 examples/s]
Generating train split: 98107011 examples [1:44:17, 29835.09 examples/s]
Generating train split: 98116764 examples [1:44:17, 46763.99 examples/s]
Generating train split: 98122290 examples [1:44:18, 20448.70 examples/s]
Generating train split: 98126420 examples [1:44:18, 16497.28 examples/s]
Generating train split: 98129624 examples [1:44:18, 16243.89 examples/s]
Generating train split: 98132330 examples [1:44:18, 17225.64 examples/s]
Generating train split: 98134898 examples [1:44:19, 12440.16 examples/s]
Generating train split: 98137051 examples [1:44:19, 13606.05 examples/s]
Generating train split: 98139088 examples [1:44:19, 11335.39 examples/s]
Generating train split: 98148366 examples [1:44:19, 23320.35 examples/s]
Generating train split: 98155440 examples [1:44:19, 31372.28 examples/s]
Generating train split: 98160241 examples [1:44:20, 25496.29 examples/s]
Generating train split: 98164115 examples [1:44:20, 15923.85 examples/s]
Generating train split: 98167057 examples [1:44:21, 11747.68 examples/s]
Generating train split: 98169290 examples [1:44:21, 7582.10 examples/s] 
Generating train split: 98170936 examples [1:44:22, 5722.00 examples/s]
Generating train split: 98172169 examples [1:44:22, 5234.67 examples/s]
Generating train split: 98173157 examples [1:44:23, 5130.29 examples/s]
Generating train split: 98173973 examples [1:44:23, 4121.49 examples/s]
Generating train split: 98174786 examples [1:44:23, 4497.53 examples/s]
Generating train split: 98178067 examples [1:44:23, 7873.41 examples/s]
Generating train split: 98180185 examples [1:44:23, 9794.81 examples/s]
Generating train split: 98182376 examples [1:44:23, 11866.94 examples/s]
Generating train split: 98184194 examples [1:44:24, 10115.74 examples/s]
Generating train split: 98185681 examples [1:44:24, 10217.52 examples/s]
Generating train split: 98187048 examples [1:44:24, 9094.82 examples/s] 
Generating train split: 98188203 examples [1:44:24, 8031.18 examples/s]
Generating train split: 98189182 examples [1:44:24, 6766.43 examples/s]
Generating train split: 98191078 examples [1:44:25, 8895.08 examples/s]
Generating train split: 98192220 examples [1:44:25, 6468.23 examples/s]
Generating train split: 98193128 examples [1:44:25, 5897.85 examples/s]
Generating train split: 98193919 examples [1:44:25, 5982.08 examples/s]
Generating train split: 98194654 examples [1:44:25, 4613.74 examples/s]
Generating train split: 98195334 examples [1:44:26, 4948.51 examples/s]
Generating train split: 98197122 examples [1:44:26, 7394.41 examples/s]
Generating train split: 98198284 examples [1:44:26, 7980.84 examples/s]
Generating train split: 98199255 examples [1:44:26, 6489.18 examples/s]
Generating train split: 98200073 examples [1:44:26, 6460.42 examples/s]
Generating train split: 98202076 examples [1:44:26, 9293.47 examples/s]
Generating train split: 98203198 examples [1:44:26, 9231.19 examples/s]
Generating train split: 98204248 examples [1:44:27, 6101.09 examples/s]
Generating train split: 98205162 examples [1:44:27, 6281.62 examples/s]
Generating train split: 98205963 examples [1:44:27, 4090.13 examples/s]
Generating train split: 98206634 examples [1:44:27, 4413.54 examples/s]
Generating train split: 98207247 examples [1:44:28, 4021.11 examples/s]
Generating train split: 98207773 examples [1:44:28, 3534.55 examples/s]
Generating train split: 98208210 examples [1:44:28, 3029.60 examples/s]
Generating train split: 98208581 examples [1:44:28, 3004.23 examples/s]
Generating train split: 98209293 examples [1:44:28, 3765.86 examples/s]
Generating train split: 98209753 examples [1:44:28, 3462.67 examples/s]
Generating train split: 98210842 examples [1:44:29, 5009.83 examples/s]
Generating train split: 98211585 examples [1:44:29, 5559.56 examples/s]
Generating train split: 98212400 examples [1:44:29, 6197.94 examples/s]
Generating train split: 98213353 examples [1:44:29, 7011.05 examples/s]
Generating train split: 98214120 examples [1:44:29, 6099.64 examples/s]
Generating train split: 98221725 examples [1:44:29, 23328.83 examples/s]
Generating train split: 98229831 examples [1:44:29, 37885.67 examples/s]
Generating train split: 98234084 examples [1:44:30, 21271.33 examples/s]
Generating train split: 98237377 examples [1:44:30, 15157.39 examples/s]
Generating train split: 98239916 examples [1:44:30, 11765.92 examples/s]
Generating train split: 98241886 examples [1:44:31, 11801.61 examples/s]
Generating train split: 98243684 examples [1:44:31, 12653.55 examples/s]
Generating train split: 98245438 examples [1:44:31, 9835.60 examples/s] 
Generating train split: 98246840 examples [1:44:31, 9683.13 examples/s]
Generating train split: 98249461 examples [1:44:31, 12388.58 examples/s]
Generating train split: 98251128 examples [1:44:31, 11812.65 examples/s]
Generating train split: 98252610 examples [1:44:32, 10703.36 examples/s]
Generating train split: 98254119 examples [1:44:32, 11539.06 examples/s]
Generating train split: 98255575 examples [1:44:32, 12168.14 examples/s]
Generating train split: 98256955 examples [1:44:32, 11908.11 examples/s]
Generating train split: 98258254 examples [1:44:32, 10910.93 examples/s]
Generating train split: 98260670 examples [1:44:32, 14041.38 examples/s]
Generating train split: 98262227 examples [1:44:32, 12156.76 examples/s]
Generating train split: 98263583 examples [1:44:33, 10484.30 examples/s]
Generating train split: 98264756 examples [1:44:33, 7670.64 examples/s] 
Generating train split: 98265705 examples [1:44:33, 6639.20 examples/s]
Generating train split: 98267012 examples [1:44:33, 7770.74 examples/s]
Generating train split: 98268225 examples [1:44:33, 8581.02 examples/s]
Generating train split: 98269241 examples [1:44:33, 6885.82 examples/s]
Generating train split: 98270091 examples [1:44:34, 6863.08 examples/s]
Generating train split: 98270893 examples [1:44:34, 6996.33 examples/s]
Generating train split: 98272146 examples [1:44:34, 8260.67 examples/s]
Generating train split: 98273135 examples [1:44:34, 8644.80 examples/s]
Generating train split: 98274460 examples [1:44:34, 9668.61 examples/s]
Generating train split: 98275497 examples [1:44:34, 8237.38 examples/s]
Generating train split: 98276404 examples [1:44:34, 8246.59 examples/s]
Generating train split: 98277782 examples [1:44:34, 9638.13 examples/s]
Generating train split: 98279652 examples [1:44:34, 11994.75 examples/s]
Generating train split: 98280938 examples [1:44:35, 5725.27 examples/s] 
Generating train split: 98281916 examples [1:44:35, 4903.00 examples/s]
Generating train split: 98283345 examples [1:44:35, 6267.46 examples/s]
Generating train split: 98284324 examples [1:44:36, 5587.80 examples/s]
Generating train split: 98286145 examples [1:44:36, 7691.08 examples/s]
Generating train split: 98287264 examples [1:44:36, 8089.82 examples/s]
Generating train split: 98288335 examples [1:44:36, 8368.83 examples/s]
Generating train split: 98289357 examples [1:44:36, 5403.06 examples/s]
Generating train split: 98293868 examples [1:44:36, 11957.35 examples/s]
Generating train split: 98301938 examples [1:44:37, 25075.78 examples/s]
Generating train split: 98307453 examples [1:44:37, 31511.71 examples/s]
Generating train split: 98311749 examples [1:44:37, 16190.45 examples/s]
Generating train split: 98314978 examples [1:44:38, 13672.00 examples/s]
Generating train split: 98317521 examples [1:44:38, 10066.21 examples/s]
Generating train split: 98319447 examples [1:44:38, 9684.11 examples/s] 
Generating train split: 98321059 examples [1:44:39, 8550.97 examples/s]
Generating train split: 98322345 examples [1:44:39, 6664.49 examples/s]
Generating train split: 98323348 examples [1:44:39, 5681.02 examples/s]
Generating train split: 98324982 examples [1:44:39, 6910.25 examples/s]
Generating train split: 98326331 examples [1:44:39, 7840.57 examples/s]
Generating train split: 98327486 examples [1:44:40, 7438.76 examples/s]
Generating train split: 98328475 examples [1:44:40, 7284.54 examples/s]
Generating train split: 98329414 examples [1:44:40, 7342.93 examples/s]
Generating train split: 98330268 examples [1:44:40, 6094.52 examples/s]
Generating train split: 98330995 examples [1:44:40, 5253.28 examples/s]
Generating train split: 98331600 examples [1:44:41, 5131.77 examples/s]
Generating train split: 98332172 examples [1:44:41, 5000.18 examples/s]
Generating train split: 98332715 examples [1:44:41, 4859.28 examples/s]
Generating train split: 98333241 examples [1:44:41, 4730.15 examples/s]
Generating train split: 98333734 examples [1:44:41, 4352.48 examples/s]
Generating train split: 98334191 examples [1:44:41, 4023.49 examples/s]
Generating train split: 98334605 examples [1:44:41, 3792.57 examples/s]
Generating train split: 98335008 examples [1:44:41, 3206.29 examples/s]
Generating train split: 98337069 examples [1:44:42, 7043.67 examples/s]
Generating train split: 98337922 examples [1:44:42, 6826.39 examples/s]
Generating train split: 98339250 examples [1:44:42, 8371.20 examples/s]
Generating train split: 98340200 examples [1:44:42, 7489.87 examples/s]
Generating train split: 98341366 examples [1:44:42, 8452.77 examples/s]
Generating train split: 98345299 examples [1:44:42, 16305.70 examples/s]
Generating train split: 98353426 examples [1:44:42, 33613.37 examples/s]
Generating train split: 98358261 examples [1:44:42, 37666.87 examples/s]
Generating train split: 98362315 examples [1:44:43, 23182.48 examples/s]
Generating train split: 98365523 examples [1:44:43, 14590.72 examples/s]
Generating train split: 98367976 examples [1:44:44, 8557.31 examples/s] 
Generating train split: 98369798 examples [1:44:44, 9104.97 examples/s]
Generating train split: 98374646 examples [1:44:44, 13724.32 examples/s]
Generating train split: 98382811 examples [1:44:44, 23473.08 examples/s]
Generating train split: 98387098 examples [1:44:44, 25312.33 examples/s]
Generating train split: 98391056 examples [1:44:45, 14325.84 examples/s]
Generating train split: 98394022 examples [1:44:45, 13321.80 examples/s]
Generating train split: 98396417 examples [1:44:46, 11731.37 examples/s]
Generating train split: 98398337 examples [1:44:46, 10692.22 examples/s]
Generating train split: 98399923 examples [1:44:46, 7025.18 examples/s] 
Generating train split: 98401114 examples [1:44:47, 6488.35 examples/s]
Generating train split: 98402089 examples [1:44:47, 6432.52 examples/s]
Generating train split: 98402955 examples [1:44:47, 6235.78 examples/s]
Generating train split: 98403736 examples [1:44:47, 4234.43 examples/s]
Generating train split: 98404326 examples [1:44:48, 3442.04 examples/s]
Generating train split: 98405203 examples [1:44:48, 4042.28 examples/s]
Generating train split: 98406209 examples [1:44:48, 4901.69 examples/s]
Generating train split: 98406910 examples [1:44:48, 4459.65 examples/s]
Generating train split: 98407516 examples [1:44:48, 3928.72 examples/s]
Generating train split: 98410437 examples [1:44:48, 8192.22 examples/s]
Generating train split: 98418505 examples [1:44:49, 22263.14 examples/s]
Generating train split: 98425262 examples [1:44:49, 32095.46 examples/s]
Generating train split: 98429581 examples [1:44:49, 19218.53 examples/s]
Generating train split: 98432902 examples [1:44:50, 9693.03 examples/s] 
Generating train split: 98435349 examples [1:44:51, 7933.17 examples/s]
Generating train split: 98437210 examples [1:44:51, 7495.14 examples/s]
Generating train split: 98438682 examples [1:44:51, 8134.51 examples/s]
Generating train split: 98440138 examples [1:44:51, 7625.72 examples/s]
Generating train split: 98441341 examples [1:44:51, 7057.86 examples/s]
Generating train split: 98442352 examples [1:44:52, 6934.75 examples/s]
Generating train split: 98443254 examples [1:44:52, 6155.44 examples/s]
Generating train split: 98444822 examples [1:44:52, 7538.69 examples/s]
Generating train split: 98445786 examples [1:44:52, 7304.23 examples/s]
Generating train split: 98447452 examples [1:44:52, 8821.11 examples/s]
Generating train split: 98448502 examples [1:44:53, 5582.84 examples/s]
Generating train split: 98449309 examples [1:44:53, 4649.42 examples/s]
Generating train split: 98457088 examples [1:44:53, 15368.50 examples/s]
Generating train split: 98466302 examples [1:44:53, 28655.38 examples/s]
Generating train split: 98471026 examples [1:44:53, 23716.49 examples/s]
Generating train split: 98474829 examples [1:44:54, 13075.11 examples/s]
Generating train split: 98477656 examples [1:44:55, 8942.30 examples/s] 
Generating train split: 98479763 examples [1:44:55, 7574.17 examples/s]
Generating train split: 98481388 examples [1:44:55, 8092.52 examples/s]
Generating train split: 98483190 examples [1:44:55, 9146.01 examples/s]
Generating train split: 98484782 examples [1:44:56, 6803.83 examples/s]
Generating train split: 98486197 examples [1:44:56, 7634.55 examples/s]
Generating train split: 98487479 examples [1:44:56, 7545.08 examples/s]
Generating train split: 98495540 examples [1:44:56, 18666.63 examples/s]
Generating train split: 98503098 examples [1:44:56, 28831.77 examples/s]
Generating train split: 98507602 examples [1:44:56, 29250.85 examples/s]
Generating train split: 98511663 examples [1:44:58, 8442.56 examples/s] 
Generating train split: 98514766 examples [1:44:58, 10109.61 examples/s]
Generating train split: 98521707 examples [1:44:58, 15767.38 examples/s]
Generating train split: 98526768 examples [1:44:58, 19943.52 examples/s]
Generating train split: 98534060 examples [1:44:58, 27687.56 examples/s]
Generating train split: 98540431 examples [1:44:58, 33909.20 examples/s]
Generating train split: 98547356 examples [1:44:58, 40903.76 examples/s]
Generating train split: 98554122 examples [1:44:59, 46791.16 examples/s]
Generating train split: 98561301 examples [1:44:59, 52766.04 examples/s]
Generating train split: 98568399 examples [1:44:59, 57384.63 examples/s]
Generating train split: 98575692 examples [1:44:59, 61524.09 examples/s]
Generating train split: 98583442 examples [1:44:59, 65917.88 examples/s]
Generating train split: 98591434 examples [1:44:59, 69872.13 examples/s]
Generating train split: 98598825 examples [1:44:59, 70524.25 examples/s]
Generating train split: 98607237 examples [1:44:59, 74460.00 examples/s]
Generating train split: 98614899 examples [1:44:59, 74874.24 examples/s]
Generating train split: 98622731 examples [1:44:59, 75860.00 examples/s]
Generating train split: 98631070 examples [1:45:00, 78062.34 examples/s]
Generating train split: 98638965 examples [1:45:00, 74124.31 examples/s]
Generating train split: 98646683 examples [1:45:00, 74972.21 examples/s]
Generating train split: 98654251 examples [1:45:00, 73333.52 examples/s]
Generating train split: 98661640 examples [1:45:00, 71980.43 examples/s]
Generating train split: 98669665 examples [1:45:00, 74329.62 examples/s]
Generating train split: 98677199 examples [1:45:00, 74610.00 examples/s]
Generating train split: 98684693 examples [1:45:00, 74099.79 examples/s]
Generating train split: 98692126 examples [1:45:00, 70661.89 examples/s]
Generating train split: 98699236 examples [1:45:01, 68125.02 examples/s]
Generating train split: 98706088 examples [1:45:01, 56918.21 examples/s]
Generating train split: 98712098 examples [1:45:01, 34304.97 examples/s]
Generating train split: 98716787 examples [1:45:01, 24728.95 examples/s]
Generating train split: 98720450 examples [1:45:02, 21612.88 examples/s]
Generating train split: 98723454 examples [1:45:02, 22128.73 examples/s]
Generating train split: 98726295 examples [1:45:02, 22554.44 examples/s]
Generating train split: 98729013 examples [1:45:02, 15310.06 examples/s]
Generating train split: 98731128 examples [1:45:03, 14580.04 examples/s]
Generating train split: 98732985 examples [1:45:03, 11562.28 examples/s]
Generating train split: 98735056 examples [1:45:03, 12924.08 examples/s]
Generating train split: 98742142 examples [1:45:03, 23097.40 examples/s]
Generating train split: 98748145 examples [1:45:03, 30439.89 examples/s]
Generating train split: 98752227 examples [1:45:03, 24111.75 examples/s]
Generating train split: 98755565 examples [1:45:04, 16527.68 examples/s]
Generating train split: 98758150 examples [1:45:04, 15148.55 examples/s]
Generating train split: 98760306 examples [1:45:04, 12026.67 examples/s]
Generating train split: 98762014 examples [1:45:04, 12668.17 examples/s]
Generating train split: 98763715 examples [1:45:05, 11893.99 examples/s]
Generating train split: 98765201 examples [1:45:05, 9500.83 examples/s] 
Generating train split: 98766397 examples [1:45:05, 8150.54 examples/s]
Generating train split: 98767391 examples [1:45:05, 6877.58 examples/s]
Generating train split: 98768213 examples [1:45:06, 6429.37 examples/s]
Generating train split: 98775845 examples [1:45:06, 18140.21 examples/s]
Generating train split: 98784021 examples [1:45:06, 30427.55 examples/s]
Generating train split: 98788428 examples [1:45:06, 18401.06 examples/s]
Generating train split: 98791794 examples [1:45:07, 10247.31 examples/s]
Generating train split: 98794275 examples [1:45:08, 6045.74 examples/s] 
Generating train split: 98796093 examples [1:45:08, 5737.58 examples/s]
Generating train split: 98797506 examples [1:45:09, 4783.69 examples/s]
Generating train split: 98798578 examples [1:45:09, 4403.05 examples/s]
Generating train split: 98799423 examples [1:45:10, 4309.37 examples/s]
Generating train split: 98801203 examples [1:45:10, 5571.99 examples/s]
Generating train split: 98802216 examples [1:45:10, 4923.23 examples/s]
Generating train split: 98803368 examples [1:45:10, 5667.89 examples/s]
Generating train split: 98804258 examples [1:45:10, 6099.57 examples/s]
Generating train split: 98811733 examples [1:45:10, 17853.83 examples/s]
Generating train split: 98820668 examples [1:45:10, 31899.08 examples/s]
Generating train split: 98825349 examples [1:45:11, 21520.17 examples/s]
Generating train split: 98833985 examples [1:45:11, 31944.74 examples/s]
Generating train split: 98841352 examples [1:45:11, 39725.05 examples/s]
Generating train split: 98847158 examples [1:45:12, 21153.40 examples/s]
Generating train split: 98855611 examples [1:45:12, 29224.21 examples/s]
Generating train split: 98862116 examples [1:45:12, 34734.68 examples/s]
Generating train split: 98867979 examples [1:45:13, 12077.29 examples/s]
Generating train split: 98872210 examples [1:45:14, 9393.18 examples/s] 
Generating train split: 98880368 examples [1:45:14, 14065.06 examples/s]
Generating train split: 98886751 examples [1:45:14, 18273.53 examples/s]
Generating train split: 98891912 examples [1:45:15, 9392.33 examples/s] 
Generating train split: 98895635 examples [1:45:16, 8583.68 examples/s]
Generating train split: 98898436 examples [1:45:17, 7645.68 examples/s]
Generating train split: 98900552 examples [1:45:17, 6974.86 examples/s]
Generating train split: 98902182 examples [1:45:17, 7534.76 examples/s]
Generating train split: 98903727 examples [1:45:18, 6482.99 examples/s]
Generating train split: 98905122 examples [1:45:18, 7178.09 examples/s]
Generating train split: 98906380 examples [1:45:18, 7643.09 examples/s]
Generating train split: 98907585 examples [1:45:18, 6443.36 examples/s]
Generating train split: 98908926 examples [1:45:18, 7384.05 examples/s]
Generating train split: 98911723 examples [1:45:18, 10695.51 examples/s]
Generating train split: 98913299 examples [1:45:19, 9217.66 examples/s] 
Generating train split: 98914602 examples [1:45:19, 9023.05 examples/s]
Generating train split: 98915764 examples [1:45:19, 6392.66 examples/s]
Generating train split: 98916680 examples [1:45:19, 5281.92 examples/s]
Generating train split: 98917454 examples [1:45:19, 5635.24 examples/s]
Generating train split: 98920275 examples [1:45:20, 9418.75 examples/s]
Generating train split: 98922095 examples [1:45:20, 11055.48 examples/s]
Generating train split: 98923563 examples [1:45:20, 10163.72 examples/s]
Generating train split: 98924840 examples [1:45:20, 8336.60 examples/s] 
Generating train split: 98931456 examples [1:45:20, 19270.12 examples/s]
Generating train split: 98940068 examples [1:45:20, 33485.29 examples/s]
Generating train split: 98944560 examples [1:45:20, 28451.78 examples/s]
Generating train split: 98948332 examples [1:45:21, 16480.99 examples/s]
Generating train split: 98951196 examples [1:45:21, 14351.23 examples/s]
Generating train split: 98953501 examples [1:45:22, 9906.14 examples/s] 
Generating train split: 98955244 examples [1:45:22, 10615.79 examples/s]
Generating train split: 98963128 examples [1:45:22, 19775.71 examples/s]
Generating train split: 98972266 examples [1:45:22, 31294.94 examples/s]
Generating train split: 98977501 examples [1:45:22, 24928.58 examples/s]
Generating train split: 98981655 examples [1:45:24, 6838.04 examples/s] 
Generating train split: 98984621 examples [1:45:25, 6225.89 examples/s]
Generating train split: 98986844 examples [1:45:26, 5737.48 examples/s]
Generating train split: 98988526 examples [1:45:26, 5192.17 examples/s]
Generating train split: 98995902 examples [1:45:26, 9659.75 examples/s]
Generating train split: 99004497 examples [1:45:26, 15964.70 examples/s]
Generating train split: 99008946 examples [1:45:27, 10233.02 examples/s]
Generating train split: 99012202 examples [1:45:28, 8897.71 examples/s] 
Generating train split: 99014661 examples [1:45:28, 8166.44 examples/s]
Generating train split: 99016564 examples [1:45:29, 7398.79 examples/s]
Generating train split: 99018100 examples [1:45:29, 8078.37 examples/s]
Generating train split: 99019609 examples [1:45:29, 7694.95 examples/s]
Generating train split: 99020849 examples [1:45:29, 6180.55 examples/s]
Generating train split: 99021833 examples [1:45:30, 4378.63 examples/s]
Generating train split: 99022594 examples [1:45:30, 4673.17 examples/s]
Generating train split: 99023333 examples [1:45:30, 4861.41 examples/s]
Generating train split: 99031312 examples [1:45:30, 15648.00 examples/s]
Generating train split: 99039569 examples [1:45:30, 26842.18 examples/s]
Generating train split: 99043955 examples [1:45:31, 18506.31 examples/s]
Generating train split: 99047332 examples [1:45:31, 11658.92 examples/s]
Generating train split: 99049859 examples [1:45:32, 8701.56 examples/s] 
Generating train split: 99051758 examples [1:45:32, 9499.48 examples/s]
Generating train split: 99053584 examples [1:45:33, 7116.22 examples/s]
Generating train split: 99054974 examples [1:45:33, 7696.24 examples/s]
Generating train split: 99056322 examples [1:45:33, 5934.83 examples/s]
Generating train split: 99057357 examples [1:45:33, 6089.32 examples/s]
Generating train split: 99058854 examples [1:45:33, 7220.81 examples/s]
Generating train split: 99059946 examples [1:45:33, 7278.69 examples/s]
Generating train split: 99061524 examples [1:45:34, 8739.43 examples/s]
Generating train split: 99069499 examples [1:45:34, 22750.28 examples/s]
Generating train split: 99078038 examples [1:45:34, 36506.87 examples/s]
Generating train split: 99082850 examples [1:45:34, 21659.83 examples/s]
Generating train split: 99086539 examples [1:45:35, 15200.01 examples/s]
Generating train split: 99089358 examples [1:45:36, 8339.45 examples/s] 
Generating train split: 99091429 examples [1:45:36, 7227.50 examples/s]
Generating train split: 99093010 examples [1:45:36, 7561.81 examples/s]
Generating train split: 99094416 examples [1:45:37, 6230.00 examples/s]
Generating train split: 99095859 examples [1:45:37, 6984.44 examples/s]
Generating train split: 99097023 examples [1:45:37, 6780.83 examples/s]
Generating train split: 99098022 examples [1:45:37, 5838.36 examples/s]
Generating train split: 99098908 examples [1:45:37, 6194.68 examples/s]
Generating train split: 99099727 examples [1:45:37, 5893.19 examples/s]
Generating train split: 99100449 examples [1:45:38, 5312.34 examples/s]
Generating train split: 99101073 examples [1:45:38, 4120.45 examples/s]
Generating train split: 99106914 examples [1:45:38, 12758.75 examples/s]
Generating train split: 99115108 examples [1:45:38, 25567.27 examples/s]
Generating train split: 99119042 examples [1:45:38, 27022.84 examples/s]
Generating train split: 99122733 examples [1:45:39, 18220.75 examples/s]
Generating train split: 99125615 examples [1:45:39, 13952.53 examples/s]
Generating train split: 99127876 examples [1:45:39, 10795.26 examples/s]
Generating train split: 99129633 examples [1:45:40, 9621.87 examples/s] 
Generating train split: 99131065 examples [1:45:40, 7910.94 examples/s]
Generating train split: 99132202 examples [1:45:40, 8084.69 examples/s]
Generating train split: 99133267 examples [1:45:40, 7593.35 examples/s]
Generating train split: 99134199 examples [1:45:40, 7016.97 examples/s]
Generating train split: 99135930 examples [1:45:41, 8719.17 examples/s]
Generating train split: 99137003 examples [1:45:41, 8146.07 examples/s]
Generating train split: 99137960 examples [1:45:41, 6721.44 examples/s]
Generating train split: 99138755 examples [1:45:41, 6148.12 examples/s]
Generating train split: 99139452 examples [1:45:41, 5263.66 examples/s]
Generating train split: 99140426 examples [1:45:41, 6076.09 examples/s]
Generating train split: 99141128 examples [1:45:42, 4670.72 examples/s]
Generating train split: 99142908 examples [1:45:42, 6903.15 examples/s]
Generating train split: 99143791 examples [1:45:42, 4681.87 examples/s]
Generating train split: 99145951 examples [1:45:42, 7326.21 examples/s]
Generating train split: 99148582 examples [1:45:42, 10751.73 examples/s]
Generating train split: 99150150 examples [1:45:43, 6639.82 examples/s] 
Generating train split: 99151355 examples [1:45:43, 5058.88 examples/s]
Generating train split: 99152286 examples [1:45:43, 5243.16 examples/s]
Generating train split: 99153121 examples [1:45:44, 5359.11 examples/s]
Generating train split: 99153881 examples [1:45:44, 4359.13 examples/s]
Generating train split: 99154800 examples [1:45:44, 5070.61 examples/s]
Generating train split: 99155606 examples [1:45:44, 5509.42 examples/s]
Generating train split: 99156328 examples [1:45:45, 3624.24 examples/s]
Generating train split: 99157012 examples [1:45:45, 4077.18 examples/s]
Generating train split: 99158139 examples [1:45:45, 5320.25 examples/s]
Generating train split: 99158884 examples [1:45:45, 5567.44 examples/s]
Generating train split: 99159615 examples [1:45:45, 5845.91 examples/s]
Generating train split: 99160324 examples [1:45:45, 5718.72 examples/s]
Generating train split: 99161434 examples [1:45:45, 6985.19 examples/s]
Generating train split: 99162236 examples [1:45:45, 6049.03 examples/s]
Generating train split: 99162983 examples [1:45:45, 6210.49 examples/s]
Generating train split: 99163671 examples [1:45:46, 5720.06 examples/s]
Generating train split: 99166739 examples [1:45:46, 11657.27 examples/s]
Generating train split: 99175041 examples [1:45:46, 29755.65 examples/s]
Generating train split: 99181798 examples [1:45:46, 39801.04 examples/s]
Generating train split: 99186233 examples [1:45:46, 28499.82 examples/s]
Generating train split: 99189851 examples [1:45:46, 20185.94 examples/s]
Generating train split: 99192709 examples [1:45:47, 11269.84 examples/s]
Generating train split: 99194855 examples [1:45:47, 10151.82 examples/s]
Generating train split: 99196566 examples [1:45:48, 10630.90 examples/s]
Generating train split: 99198173 examples [1:45:48, 9526.57 examples/s] 
Generating train split: 99199498 examples [1:45:48, 7893.90 examples/s]
Generating train split: 99201007 examples [1:45:48, 8722.85 examples/s]
Generating train split: 99202151 examples [1:45:49, 5330.07 examples/s]
Generating train split: 99203022 examples [1:45:49, 3925.36 examples/s]
Generating train split: 99203692 examples [1:45:50, 3523.45 examples/s]
Generating train split: 99205384 examples [1:45:50, 4988.07 examples/s]
Generating train split: 99206254 examples [1:45:50, 3919.75 examples/s]
Generating train split: 99208431 examples [1:45:50, 6091.68 examples/s]
Generating train split: 99209557 examples [1:45:50, 6655.65 examples/s]
Generating train split: 99210628 examples [1:45:51, 5595.90 examples/s]
Generating train split: 99211492 examples [1:45:51, 5173.24 examples/s]
Generating train split: 99214976 examples [1:45:51, 9916.30 examples/s]
Generating train split: 99224251 examples [1:45:51, 25311.54 examples/s]
Generating train split: 99232050 examples [1:45:51, 35855.00 examples/s]
Generating train split: 99236948 examples [1:45:52, 20743.23 examples/s]
Generating train split: 99240681 examples [1:45:52, 15021.46 examples/s]
Generating train split: 99243537 examples [1:45:52, 13466.76 examples/s]
Generating train split: 99245825 examples [1:45:53, 11258.20 examples/s]
Generating train split: 99247629 examples [1:45:53, 8127.82 examples/s] 
Generating train split: 99249008 examples [1:45:53, 7919.88 examples/s]
Generating train split: 99250180 examples [1:45:54, 6683.31 examples/s]
Generating train split: 99251114 examples [1:45:54, 6305.61 examples/s]
Generating train split: 99251910 examples [1:45:54, 5065.68 examples/s]
Generating train split: 99252545 examples [1:45:54, 5064.26 examples/s]
Generating train split: 99254102 examples [1:45:54, 6422.92 examples/s]
Generating train split: 99254912 examples [1:45:55, 4368.85 examples/s]
Generating train split: 99256342 examples [1:45:55, 5723.03 examples/s]
Generating train split: 99257202 examples [1:45:55, 4352.31 examples/s]
Generating train split: 99257884 examples [1:45:55, 4594.46 examples/s]
Generating train split: 99259165 examples [1:45:56, 5941.38 examples/s]
Generating train split: 99260010 examples [1:45:56, 6361.17 examples/s]
Generating train split: 99260835 examples [1:45:56, 5033.55 examples/s]
Generating train split: 99261516 examples [1:45:56, 4142.47 examples/s]
Generating train split: 99262496 examples [1:45:56, 5042.54 examples/s]
Generating train split: 99263157 examples [1:45:56, 4455.91 examples/s]
Generating train split: 99263873 examples [1:45:57, 4960.49 examples/s]
Generating train split: 99264490 examples [1:45:57, 3425.30 examples/s]
Generating train split: 99264970 examples [1:45:57, 3306.80 examples/s]
Generating train split: 99265397 examples [1:45:57, 3174.86 examples/s]
Generating train split: 99265784 examples [1:45:57, 2502.73 examples/s]
Generating train split: 99266270 examples [1:45:58, 2834.10 examples/s]
Generating train split: 99266622 examples [1:45:58, 2758.65 examples/s]
Generating train split: 99268923 examples [1:45:58, 6835.67 examples/s]
Generating train split: 99269839 examples [1:45:58, 5017.72 examples/s]
Generating train split: 99270567 examples [1:45:59, 3436.61 examples/s]
Generating train split: 99271534 examples [1:45:59, 4300.51 examples/s]
Generating train split: 99272215 examples [1:45:59, 4369.76 examples/s]
Generating train split: 99272833 examples [1:45:59, 4175.20 examples/s]
Generating train split: 99273546 examples [1:45:59, 4521.04 examples/s]
Generating train split: 99274096 examples [1:46:00, 2805.02 examples/s]
Generating train split: 99274597 examples [1:46:00, 3128.37 examples/s]
Generating train split: 99275048 examples [1:46:00, 2555.56 examples/s]
Generating train split: 99276021 examples [1:46:00, 3675.33 examples/s]
Generating train split: 99276561 examples [1:46:00, 3779.10 examples/s]
Generating train split: 99277161 examples [1:46:00, 4220.83 examples/s]
Generating train split: 99277693 examples [1:46:01, 2793.50 examples/s]
Generating train split: 99278203 examples [1:46:01, 3138.64 examples/s]
Generating train split: 99278647 examples [1:46:01, 2900.31 examples/s]
Generating train split: 99281444 examples [1:46:01, 7590.81 examples/s]
Generating train split: 99282538 examples [1:46:01, 7142.86 examples/s]
Generating train split: 99283489 examples [1:46:02, 4326.31 examples/s]
Generating train split: 99284216 examples [1:46:02, 4731.06 examples/s]
Generating train split: 99285448 examples [1:46:02, 5991.76 examples/s]
Generating train split: 99286325 examples [1:46:02, 4800.43 examples/s]
Generating train split: 99287023 examples [1:46:02, 5163.22 examples/s]
Generating train split: 99287728 examples [1:46:02, 5081.78 examples/s]
Generating train split: 99289129 examples [1:46:03, 6889.66 examples/s]
Generating train split: 99290020 examples [1:46:03, 7335.92 examples/s]
Generating train split: 99290889 examples [1:46:03, 5641.86 examples/s]
Generating train split: 99292288 examples [1:46:03, 7283.32 examples/s]
Generating train split: 99293843 examples [1:46:03, 9129.84 examples/s]
Generating train split: 99294949 examples [1:46:03, 8368.72 examples/s]
Generating train split: 99296593 examples [1:46:03, 10224.83 examples/s]
Generating train split: 99297773 examples [1:46:04, 8252.73 examples/s] 
Generating train split: 99298864 examples [1:46:04, 8591.53 examples/s]
Generating train split: 99299846 examples [1:46:04, 8157.76 examples/s]
Generating train split: 99302670 examples [1:46:04, 12601.21 examples/s]
Generating train split: 99304097 examples [1:46:04, 9705.27 examples/s] 
Generating train split: 99305269 examples [1:46:05, 5783.44 examples/s]
Generating train split: 99306241 examples [1:46:05, 6351.60 examples/s]
Generating train split: 99307159 examples [1:46:05, 6565.16 examples/s]
Generating train split: 99308024 examples [1:46:05, 4883.61 examples/s]
Generating train split: 99309379 examples [1:46:05, 6264.93 examples/s]
Generating train split: 99310273 examples [1:46:06, 4258.02 examples/s]
Generating train split: 99310958 examples [1:46:06, 4580.51 examples/s]
Generating train split: 99311897 examples [1:46:06, 5250.98 examples/s]
Generating train split: 99312614 examples [1:46:06, 4328.99 examples/s]
Generating train split: 99313541 examples [1:46:06, 5155.56 examples/s]
Generating train split: 99314245 examples [1:46:06, 5404.12 examples/s]
Generating train split: 99314916 examples [1:46:07, 4866.05 examples/s]
Generating train split: 99315495 examples [1:46:07, 4800.64 examples/s]
Generating train split: 99316045 examples [1:46:07, 4567.66 examples/s]
Generating train split: 99316764 examples [1:46:07, 5145.51 examples/s]
Generating train split: 99317331 examples [1:46:07, 5207.17 examples/s]
Generating train split: 99318533 examples [1:46:07, 6828.78 examples/s]
Generating train split: 99319264 examples [1:46:07, 5092.24 examples/s]
Generating train split: 99320026 examples [1:46:07, 5396.16 examples/s]
Generating train split: 99320647 examples [1:46:08, 5019.74 examples/s]
Generating train split: 99321712 examples [1:46:08, 6016.58 examples/s]
Generating train split: 99322403 examples [1:46:08, 6224.36 examples/s]
Generating train split: 99324153 examples [1:46:08, 8932.69 examples/s]
Generating train split: 99325116 examples [1:46:08, 7984.12 examples/s]
Generating train split: 99326191 examples [1:46:08, 8633.74 examples/s]
Generating train split: 99327111 examples [1:46:08, 6889.96 examples/s]
Generating train split: 99327893 examples [1:46:09, 7013.41 examples/s]
Generating train split: 99328661 examples [1:46:09, 6428.54 examples/s]
Generating train split: 99329635 examples [1:46:09, 7123.82 examples/s]
Generating train split: 99330402 examples [1:46:09, 7024.53 examples/s]
Generating train split: 99338106 examples [1:46:09, 25003.17 examples/s]
Generating train split: 99345804 examples [1:46:09, 38257.78 examples/s]
Generating train split: 99349947 examples [1:46:09, 24058.13 examples/s]
Generating train split: 99353225 examples [1:46:10, 14647.33 examples/s]
Generating train split: 99355733 examples [1:46:10, 12628.21 examples/s]
Generating train split: 99357730 examples [1:46:10, 11371.11 examples/s]
Generating train split: 99359382 examples [1:46:11, 11383.17 examples/s]
Generating train split: 99360878 examples [1:46:11, 8529.77 examples/s] 
Generating train split: 99362628 examples [1:46:11, 9757.59 examples/s]
Generating train split: 99363973 examples [1:46:11, 8904.05 examples/s]
Generating train split: 99365282 examples [1:46:11, 9603.74 examples/s]
Generating train split: 99366495 examples [1:46:12, 7883.53 examples/s]
Generating train split: 99367552 examples [1:46:12, 8332.51 examples/s]
Generating train split: 99368554 examples [1:46:12, 8420.97 examples/s]
Generating train split: 99369517 examples [1:46:12, 6633.00 examples/s]
Generating train split: 99370321 examples [1:46:12, 6862.14 examples/s]
Generating train split: 99372352 examples [1:46:12, 9744.48 examples/s]
Generating train split: 99373516 examples [1:46:12, 9569.47 examples/s]
Generating train split: 99374674 examples [1:46:12, 10041.60 examples/s]
Generating train split: 99375784 examples [1:46:13, 6698.36 examples/s] 
Generating train split: 99376758 examples [1:46:13, 7069.94 examples/s]
Generating train split: 99377629 examples [1:46:13, 7298.61 examples/s]
Generating train split: 99378487 examples [1:46:13, 5528.41 examples/s]
Generating train split: 99379183 examples [1:46:14, 4418.12 examples/s]
Generating train split: 99379748 examples [1:46:14, 3358.08 examples/s]
Generating train split: 99381081 examples [1:46:14, 4846.49 examples/s]
Generating train split: 99382337 examples [1:46:14, 6211.40 examples/s]
Generating train split: 99384551 examples [1:46:14, 9427.53 examples/s]
Generating train split: 99386644 examples [1:46:14, 12000.85 examples/s]
Generating train split: 99394056 examples [1:46:14, 27051.10 examples/s]
Generating train split: 99401969 examples [1:46:14, 39424.32 examples/s]
Generating train split: 99406432 examples [1:46:15, 16672.68 examples/s]
Generating train split: 99409762 examples [1:46:16, 12653.34 examples/s]
Generating train split: 99418823 examples [1:46:16, 21477.31 examples/s]
Generating train split: 99426587 examples [1:46:16, 29140.38 examples/s]
Generating train split: 99431983 examples [1:46:17, 16827.15 examples/s]
Generating train split: 99435997 examples [1:46:17, 13759.23 examples/s]
Generating train split: 99439057 examples [1:46:18, 8176.50 examples/s] 
Generating train split: 99441297 examples [1:46:19, 7081.20 examples/s]
Generating train split: 99442994 examples [1:46:19, 7771.61 examples/s]
Generating train split: 99444677 examples [1:46:19, 8068.26 examples/s]
Generating train split: 99446155 examples [1:46:19, 7141.99 examples/s]
Generating train split: 99447972 examples [1:46:19, 8379.49 examples/s]
Generating train split: 99449381 examples [1:46:19, 9060.71 examples/s]
Generating train split: 99450741 examples [1:46:19, 9629.30 examples/s]
Generating train split: 99452051 examples [1:46:20, 8067.52 examples/s]
Generating train split: 99453130 examples [1:46:20, 7596.90 examples/s]
Generating train split: 99454718 examples [1:46:20, 9077.96 examples/s]
Generating train split: 99455854 examples [1:46:20, 6799.28 examples/s]
Generating train split: 99456771 examples [1:46:20, 6650.01 examples/s]
Generating train split: 99457593 examples [1:46:21, 6432.07 examples/s]
Generating train split: 99458345 examples [1:46:21, 5014.12 examples/s]
Generating train split: 99459001 examples [1:46:21, 5276.71 examples/s]
Generating train split: 99459635 examples [1:46:21, 5420.65 examples/s]
Generating train split: 99460264 examples [1:46:21, 5271.40 examples/s]
Generating train split: 99460852 examples [1:46:21, 4601.61 examples/s]
Generating train split: 99462647 examples [1:46:21, 7471.12 examples/s]
Generating train split: 99463531 examples [1:46:22, 6988.99 examples/s]
Generating train split: 99464327 examples [1:46:22, 7146.93 examples/s]
Generating train split: 99465348 examples [1:46:22, 7858.56 examples/s]
Generating train split: 99466205 examples [1:46:22, 5973.78 examples/s]
Generating train split: 99467323 examples [1:46:22, 7097.60 examples/s]
Generating train split: 99468289 examples [1:46:22, 7694.58 examples/s]
Generating train split: 99470279 examples [1:46:22, 10762.31 examples/s]
Generating train split: 99471912 examples [1:46:22, 12169.02 examples/s]
Generating train split: 99473237 examples [1:46:23, 9290.55 examples/s] 
Generating train split: 99475575 examples [1:46:23, 12226.63 examples/s]
Generating train split: 99477136 examples [1:46:23, 12940.05 examples/s]
Generating train split: 99478586 examples [1:46:23, 12968.74 examples/s]
Generating train split: 99480141 examples [1:46:23, 13078.60 examples/s]
Generating train split: 99481526 examples [1:46:23, 9511.00 examples/s] 
Generating train split: 99482907 examples [1:46:23, 10417.76 examples/s]
Generating train split: 99484118 examples [1:46:24, 8983.00 examples/s] 
Generating train split: 99485166 examples [1:46:24, 7968.92 examples/s]
Generating train split: 99486071 examples [1:46:24, 7940.75 examples/s]
Generating train split: 99487869 examples [1:46:24, 10175.91 examples/s]
Generating train split: 99489015 examples [1:46:24, 7816.51 examples/s] 
Generating train split: 99490535 examples [1:46:24, 9330.97 examples/s]
Generating train split: 99498463 examples [1:46:24, 25182.20 examples/s]
Generating train split: 99506160 examples [1:46:25, 37234.33 examples/s]
Generating train split: 99510537 examples [1:46:25, 17074.14 examples/s]
Generating train split: 99513817 examples [1:46:26, 10898.27 examples/s]
Generating train split: 99521429 examples [1:46:26, 17454.52 examples/s]
Generating train split: 99527346 examples [1:46:26, 22667.72 examples/s]
Generating train split: 99531907 examples [1:46:27, 11816.94 examples/s]
Generating train split: 99535258 examples [1:46:28, 6737.47 examples/s] 
Generating train split: 99537683 examples [1:46:29, 6553.64 examples/s]
Generating train split: 99539561 examples [1:46:29, 5950.53 examples/s]
Generating train split: 99540998 examples [1:46:29, 6369.47 examples/s]
Generating train split: 99549246 examples [1:46:29, 13204.69 examples/s]
Generating train split: 99556537 examples [1:46:29, 19992.97 examples/s]
Generating train split: 99561103 examples [1:46:30, 12470.65 examples/s]
Generating train split: 99564485 examples [1:46:31, 7772.06 examples/s] 
Generating train split: 99566968 examples [1:46:31, 8039.31 examples/s]
Generating train split: 99568985 examples [1:46:32, 6779.60 examples/s]
Generating train split: 99570518 examples [1:46:32, 5629.38 examples/s]
Generating train split: 99571689 examples [1:46:33, 5250.90 examples/s]
Generating train split: 99572626 examples [1:46:33, 5457.52 examples/s]
Generating train split: 99573971 examples [1:46:33, 6331.06 examples/s]
Generating train split: 99574979 examples [1:46:33, 5994.64 examples/s]
Generating train split: 99577381 examples [1:46:33, 8596.58 examples/s]
Generating train split: 99578701 examples [1:46:33, 8137.95 examples/s]
Generating train split: 99581744 examples [1:46:34, 12038.65 examples/s]
Generating train split: 99583452 examples [1:46:34, 7446.46 examples/s] 
Generating train split: 99584763 examples [1:46:34, 8117.36 examples/s]
Generating train split: 99586029 examples [1:46:34, 7538.61 examples/s]
Generating train split: 99587110 examples [1:46:35, 5499.91 examples/s]
Generating train split: 99588117 examples [1:46:35, 6124.09 examples/s]
Generating train split: 99589012 examples [1:46:35, 4171.92 examples/s]
Generating train split: 99590398 examples [1:46:35, 5433.64 examples/s]
Generating train split: 99591298 examples [1:46:35, 5695.29 examples/s]
Generating train split: 99593113 examples [1:46:36, 7722.99 examples/s]
Generating train split: 99594184 examples [1:46:36, 5753.80 examples/s]
Generating train split: 99595031 examples [1:46:36, 5934.74 examples/s]
Generating train split: 99595823 examples [1:46:36, 4415.47 examples/s]
Generating train split: 99596456 examples [1:46:36, 4662.69 examples/s]
Generating train split: 99597866 examples [1:46:37, 6354.20 examples/s]
Generating train split: 99598721 examples [1:46:37, 4731.66 examples/s]
Generating train split: 99599406 examples [1:46:37, 4646.78 examples/s]
Generating train split: 99600019 examples [1:46:37, 4830.06 examples/s]
Generating train split: 99600619 examples [1:46:37, 4537.80 examples/s]
Generating train split: 99601157 examples [1:46:38, 3758.69 examples/s]
Generating train split: 99601783 examples [1:46:38, 4226.71 examples/s]
Generating train split: 99602280 examples [1:46:38, 4242.79 examples/s]
Generating train split: 99602765 examples [1:46:38, 2504.08 examples/s]
Generating train split: 99604284 examples [1:46:38, 4490.66 examples/s]
Generating train split: 99605458 examples [1:46:38, 5815.09 examples/s]
Generating train split: 99606319 examples [1:46:39, 4506.27 examples/s]
Generating train split: 99607213 examples [1:46:39, 5237.18 examples/s]
Generating train split: 99608016 examples [1:46:39, 5699.10 examples/s]
Generating train split: 99609853 examples [1:46:39, 8385.62 examples/s]
Generating train split: 99610917 examples [1:46:39, 6925.96 examples/s]
Generating train split: 99612366 examples [1:46:39, 8458.55 examples/s]
Generating train split: 99613408 examples [1:46:40, 7732.43 examples/s]
Generating train split: 99614335 examples [1:46:40, 7932.84 examples/s]
Generating train split: 99615723 examples [1:46:40, 9320.98 examples/s]
Generating train split: 99616776 examples [1:46:40, 9113.10 examples/s]
Generating train split: 99617765 examples [1:46:40, 7672.98 examples/s]
Generating train split: 99618630 examples [1:46:40, 6721.63 examples/s]
Generating train split: 99619602 examples [1:46:40, 7339.20 examples/s]
Generating train split: 99620409 examples [1:46:41, 6038.83 examples/s]
Generating train split: 99621561 examples [1:46:41, 7180.17 examples/s]
Generating train split: 99622387 examples [1:46:41, 5685.37 examples/s]
Generating train split: 99623374 examples [1:46:41, 6481.72 examples/s]
Generating train split: 99624135 examples [1:46:41, 5170.15 examples/s]
Generating train split: 99626157 examples [1:46:41, 8126.73 examples/s]
Generating train split: 99627214 examples [1:46:41, 7631.41 examples/s]
Generating train split: 99628807 examples [1:46:42, 9354.10 examples/s]
Generating train split: 99629929 examples [1:46:42, 7049.01 examples/s]
Generating train split: 99630836 examples [1:46:42, 7204.33 examples/s]
Generating train split: 99631976 examples [1:46:42, 8084.97 examples/s]
Generating train split: 99637638 examples [1:46:42, 19349.42 examples/s]
Generating train split: 99647571 examples [1:46:42, 39257.97 examples/s]
Generating train split: 99652207 examples [1:46:43, 23799.52 examples/s]
Generating train split: 99655828 examples [1:46:43, 13109.35 examples/s]
Generating train split: 99658528 examples [1:46:44, 8652.23 examples/s] 
Generating train split: 99665035 examples [1:46:44, 13578.98 examples/s]
Generating train split: 99672947 examples [1:46:44, 20848.01 examples/s]
Generating train split: 99677674 examples [1:46:44, 19936.09 examples/s]
Generating train split: 99681518 examples [1:46:45, 14523.94 examples/s]
Generating train split: 99684452 examples [1:46:46, 9777.64 examples/s] 
Generating train split: 99686651 examples [1:46:46, 8459.03 examples/s]
Generating train split: 99688343 examples [1:46:46, 7476.81 examples/s]
Generating train split: 99696719 examples [1:46:47, 14654.42 examples/s]
Generating train split: 99704711 examples [1:46:47, 22376.96 examples/s]
Generating train split: 99709517 examples [1:46:47, 22477.28 examples/s]
Generating train split: 99713559 examples [1:46:48, 11198.70 examples/s]
Generating train split: 99716518 examples [1:46:48, 9033.90 examples/s] 
Generating train split: 99718752 examples [1:46:49, 7699.55 examples/s]
Generating train split: 99720454 examples [1:46:49, 8034.29 examples/s]
Generating train split: 99721951 examples [1:46:49, 8251.98 examples/s]
Generating train split: 99723289 examples [1:46:49, 7400.95 examples/s]
Generating train split: 99724377 examples [1:46:50, 5770.88 examples/s]
Generating train split: 99725230 examples [1:46:50, 6032.86 examples/s]
Generating train split: 99726413 examples [1:46:50, 6804.78 examples/s]
Generating train split: 99727341 examples [1:46:50, 4596.68 examples/s]
Generating train split: 99728060 examples [1:46:51, 4380.75 examples/s]
Generating train split: 99729031 examples [1:46:51, 5134.95 examples/s]
Generating train split: 99729744 examples [1:46:51, 4814.08 examples/s]
Generating train split: 99730707 examples [1:46:51, 5646.71 examples/s]
Generating train split: 99731655 examples [1:46:51, 6365.65 examples/s]
Generating train split: 99732437 examples [1:46:51, 6296.72 examples/s]
Generating train split: 99733170 examples [1:46:52, 4390.20 examples/s]
Generating train split: 99735066 examples [1:46:52, 7012.51 examples/s]
Generating train split: 99740742 examples [1:46:52, 17190.95 examples/s]
Generating train split: 99749198 examples [1:46:52, 32427.87 examples/s]
Generating train split: 99754981 examples [1:46:52, 38623.65 examples/s]
Generating train split: 99759665 examples [1:46:53, 11941.81 examples/s]
Generating train split: 99763076 examples [1:46:53, 10721.28 examples/s]
Generating train split: 99770025 examples [1:46:54, 16355.21 examples/s]
Generating train split: 99778445 examples [1:46:54, 24526.44 examples/s]
Generating train split: 99783728 examples [1:46:54, 13892.04 examples/s]
Generating train split: 99787609 examples [1:46:55, 8782.77 examples/s] 
Generating train split: 99790453 examples [1:46:56, 8804.14 examples/s]
Generating train split: 99792703 examples [1:46:57, 6167.70 examples/s]
Generating train split: 99794355 examples [1:46:57, 6357.56 examples/s]
Generating train split: 99795746 examples [1:46:57, 5491.16 examples/s]
Generating train split: 99796820 examples [1:46:58, 4831.41 examples/s]
Generating train split: 99797661 examples [1:46:58, 4246.79 examples/s]
Generating train split: 99798332 examples [1:46:58, 4056.94 examples/s]
Generating train split: 99799252 examples [1:46:58, 4494.54 examples/s]
Generating train split: 99799865 examples [1:46:59, 4329.18 examples/s]
Generating train split: 99802561 examples [1:46:59, 7588.55 examples/s]
Generating train split: 99803717 examples [1:46:59, 7489.16 examples/s]
Generating train split: 99804743 examples [1:46:59, 6162.69 examples/s]
Generating train split: 99805578 examples [1:46:59, 5974.25 examples/s]
Generating train split: 99806423 examples [1:46:59, 6385.94 examples/s]
Generating train split: 99807202 examples [1:47:00, 4844.64 examples/s]
Generating train split: 99810144 examples [1:47:00, 9117.07 examples/s]
Generating train split: 99819012 examples [1:47:00, 24946.89 examples/s]
Generating train split: 99825541 examples [1:47:00, 33869.83 examples/s]
Generating train split: 99830005 examples [1:47:00, 31109.33 examples/s]
Generating train split: 99833919 examples [1:47:00, 28983.71 examples/s]
Generating train split: 99837397 examples [1:47:00, 27715.64 examples/s]
Generating train split: 99840567 examples [1:47:00, 27878.94 examples/s]
Generating train split: 99845050 examples [1:47:01, 31903.70 examples/s]
Generating train split: 99850996 examples [1:47:01, 38895.24 examples/s]
Generating train split: 99856395 examples [1:47:01, 42908.05 examples/s]
Generating train split: 99862074 examples [1:47:01, 46599.33 examples/s]
Generating train split: 99866972 examples [1:47:01, 46874.51 examples/s]
Generating train split: 99872282 examples [1:47:01, 48634.95 examples/s]
Generating train split: 99878785 examples [1:47:01, 53358.40 examples/s]
Generating train split: 99886558 examples [1:47:01, 60473.81 examples/s]
Generating train split: 99894067 examples [1:47:01, 64776.13 examples/s]
Generating train split: 99901291 examples [1:47:01, 66976.10 examples/s]
Generating train split: 99908404 examples [1:47:02, 68190.29 examples/s]
Generating train split: 99915711 examples [1:47:02, 69626.25 examples/s]
Generating train split: 99922900 examples [1:47:02, 70288.66 examples/s]
Generating train split: 99930225 examples [1:47:02, 71147.38 examples/s]
Generating train split: 99937354 examples [1:47:02, 71045.18 examples/s]
Generating train split: 99944476 examples [1:47:02, 59869.74 examples/s]
Generating train split: 99950774 examples [1:47:02, 57301.87 examples/s]
Generating train split: 99956727 examples [1:47:02, 55086.47 examples/s]
Generating train split: 99962813 examples [1:47:02, 56605.21 examples/s]
Generating train split: 99968603 examples [1:47:03, 43739.35 examples/s]
Generating train split: 99973491 examples [1:47:03, 43727.10 examples/s]
Generating train split: 99978217 examples [1:47:03, 44277.23 examples/s]
Generating train split: 99983114 examples [1:47:03, 45415.70 examples/s]
Generating train split: 99987859 examples [1:47:03, 41603.33 examples/s]
Generating train split: 99992214 examples [1:47:03, 41668.41 examples/s]
Generating train split: 99996510 examples [1:47:03, 36421.32 examples/s]
Generating train split: 100000346 examples [1:47:04, 33412.36 examples/s]
Generating train split: 100003834 examples [1:47:04, 21385.16 examples/s]
Generating train split: 100006586 examples [1:47:04, 19944.34 examples/s]
Generating train split: 100009365 examples [1:47:04, 21401.56 examples/s]
Generating train split: 100011885 examples [1:47:04, 20191.51 examples/s]
Generating train split: 100014173 examples [1:47:04, 20168.69 examples/s]
Generating train split: 100016379 examples [1:47:05, 16032.72 examples/s]
Generating train split: 100018220 examples [1:47:05, 16203.29 examples/s]
Generating train split: 100020012 examples [1:47:05, 13170.57 examples/s]
Generating train split: 100021515 examples [1:47:05, 10747.11 examples/s]
Generating train split: 100022940 examples [1:47:05, 11383.25 examples/s]
Generating train split: 100024244 examples [1:47:05, 11549.04 examples/s]
Generating train split: 100025525 examples [1:47:06, 9046.02 examples/s] 
Generating train split: 100026780 examples [1:47:06, 9538.18 examples/s]
Generating train split: 100027868 examples [1:47:06, 9814.94 examples/s]
Generating train split: 100029172 examples [1:47:06, 10522.58 examples/s]
Generating train split: 100030311 examples [1:47:06, 8528.74 examples/s] 
Generating train split: 100031283 examples [1:47:06, 7231.86 examples/s]
Generating train split: 100032919 examples [1:47:06, 9095.35 examples/s]
Generating train split: 100033982 examples [1:47:07, 5722.34 examples/s]
Generating train split: 100034813 examples [1:47:07, 5893.61 examples/s]
Generating train split: 100036631 examples [1:47:07, 8096.68 examples/s]
Generating train split: 100037705 examples [1:47:07, 8283.77 examples/s]
Generating train split: 100038721 examples [1:47:08, 6115.34 examples/s]
Generating train split: 100040501 examples [1:47:08, 8215.79 examples/s]
Generating train split: 100041601 examples [1:47:08, 8393.05 examples/s]
Generating train split: 100042642 examples [1:47:08, 5962.14 examples/s]
Generating train split: 100043470 examples [1:47:08, 5598.75 examples/s]
Generating train split: 100044203 examples [1:47:08, 5286.28 examples/s]
Generating train split: 100044838 examples [1:47:09, 5109.17 examples/s]
Generating train split: 100046014 examples [1:47:09, 6428.15 examples/s]
Generating train split: 100046788 examples [1:47:09, 5733.23 examples/s]
Generating train split: 100047976 examples [1:47:09, 6795.16 examples/s]
Generating train split: 100049812 examples [1:47:09, 9410.75 examples/s]
Generating train split: 100052693 examples [1:47:09, 14148.78 examples/s]
Generating train split: 100054698 examples [1:47:09, 15622.93 examples/s]
Generating train split: 100056445 examples [1:47:10, 8180.04 examples/s] 
Generating train split: 100057772 examples [1:47:10, 8958.09 examples/s]
Generating train split: 100059391 examples [1:47:10, 9887.62 examples/s]
Generating train split: 100060704 examples [1:47:10, 10272.22 examples/s]
Generating train split: 100061975 examples [1:47:10, 6143.47 examples/s] 
Generating train split: 100068348 examples [1:47:11, 14926.58 examples/s]
Generating train split: 100076543 examples [1:47:11, 26914.36 examples/s]
Generating train split: 100080821 examples [1:47:11, 28674.20 examples/s]
Generating train split: 100084837 examples [1:47:12, 10373.08 examples/s]
Generating train split: 100087780 examples [1:47:12, 10803.49 examples/s]
Generating train split: 100090215 examples [1:47:12, 10073.14 examples/s]
Generating train split: 100092171 examples [1:47:13, 8433.17 examples/s] 
Generating train split: 100093685 examples [1:47:13, 8324.85 examples/s]
Generating train split: 100094983 examples [1:47:13, 8033.29 examples/s]
Generating train split: 100096104 examples [1:47:14, 6161.50 examples/s]
Generating train split: 100098234 examples [1:47:14, 8032.19 examples/s]
Generating train split: 100099477 examples [1:47:14, 7976.82 examples/s]
Generating train split: 100100590 examples [1:47:14, 5857.15 examples/s]
Generating train split: 100101836 examples [1:47:14, 6773.13 examples/s]
Generating train split: 100102822 examples [1:47:14, 5873.78 examples/s]
Generating train split: 100104272 examples [1:47:15, 7238.23 examples/s]
Generating train split: 100105269 examples [1:47:15, 4279.02 examples/s]
Generating train split: 100106025 examples [1:47:15, 3636.90 examples/s]
Generating train split: 100106622 examples [1:47:16, 3476.60 examples/s]
Generating train split: 100107322 examples [1:47:16, 3917.62 examples/s]
Generating train split: 100107878 examples [1:47:16, 3199.61 examples/s]
Generating train split: 100108333 examples [1:47:16, 3084.91 examples/s]
Generating train split: 100109328 examples [1:47:16, 4036.42 examples/s]
Generating train split: 100109845 examples [1:47:17, 3148.94 examples/s]
Generating train split: 100110708 examples [1:47:17, 4033.02 examples/s]
Generating train split: 100111269 examples [1:47:17, 3410.02 examples/s]
Generating train split: 100111728 examples [1:47:17, 3292.57 examples/s]
Generating train split: 100112425 examples [1:47:17, 3958.54 examples/s]
Generating train split: 100116120 examples [1:47:17, 10832.13 examples/s]
Generating train split: 100123849 examples [1:47:17, 26071.14 examples/s]
Generating train split: 100130058 examples [1:47:18, 34952.20 examples/s]
Generating train split: 100134257 examples [1:47:18, 14201.23 examples/s]
Generating train split: 100137370 examples [1:47:19, 10608.98 examples/s]
Generating train split: 100139730 examples [1:47:19, 10367.14 examples/s]
Generating train split: 100141668 examples [1:47:19, 9207.32 examples/s] 
Generating train split: 100143223 examples [1:47:20, 8514.27 examples/s]
Generating train split: 100144497 examples [1:47:20, 7177.30 examples/s]
Generating train split: 100145889 examples [1:47:20, 7960.43 examples/s]
Generating train split: 100146996 examples [1:47:20, 6672.54 examples/s]
Generating train split: 100147898 examples [1:47:20, 6348.03 examples/s]
Generating train split: 100148899 examples [1:47:21, 6886.55 examples/s]
Generating train split: 100149751 examples [1:47:21, 4801.05 examples/s]
Generating train split: 100152020 examples [1:47:21, 7442.12 examples/s]
Generating train split: 100153184 examples [1:47:21, 8139.33 examples/s]
Generating train split: 100154325 examples [1:47:21, 7350.62 examples/s]
Generating train split: 100156197 examples [1:47:21, 9533.30 examples/s]
Generating train split: 100157442 examples [1:47:22, 10054.67 examples/s]
Generating train split: 100158669 examples [1:47:22, 10480.45 examples/s]
Generating train split: 100159885 examples [1:47:22, 6220.71 examples/s] 
Generating train split: 100160829 examples [1:47:22, 6466.10 examples/s]
Generating train split: 100162500 examples [1:47:22, 8322.65 examples/s]
Generating train split: 100163598 examples [1:47:22, 6959.42 examples/s]
Generating train split: 100164695 examples [1:47:23, 7716.40 examples/s]
Generating train split: 100165670 examples [1:47:23, 5020.44 examples/s]
Generating train split: 100166428 examples [1:47:23, 4741.26 examples/s]
Generating train split: 100167364 examples [1:47:23, 5484.26 examples/s]
Generating train split: 100168105 examples [1:47:24, 4705.88 examples/s]
Generating train split: 100169243 examples [1:47:24, 5596.45 examples/s]
Generating train split: 100169931 examples [1:47:24, 5788.21 examples/s]
Generating train split: 100171643 examples [1:47:24, 8232.36 examples/s]
Generating train split: 100172629 examples [1:47:24, 8605.56 examples/s]
Generating train split: 100173616 examples [1:47:24, 5521.96 examples/s]
Generating train split: 100175076 examples [1:47:24, 7166.16 examples/s]
Generating train split: 100176057 examples [1:47:25, 7473.15 examples/s]
Generating train split: 100176996 examples [1:47:25, 5956.53 examples/s]
Generating train split: 100177777 examples [1:47:25, 5342.56 examples/s]
Generating train split: 100179626 examples [1:47:25, 7827.08 examples/s]
Generating train split: 100180650 examples [1:47:26, 4718.26 examples/s]
Generating train split: 100181430 examples [1:47:26, 3895.11 examples/s]
Generating train split: 100182047 examples [1:47:26, 3981.00 examples/s]
Generating train split: 100189512 examples [1:47:26, 14982.32 examples/s]
Generating train split: 100196730 examples [1:47:26, 24964.31 examples/s]
Generating train split: 100200555 examples [1:47:27, 13562.46 examples/s]
Generating train split: 100203423 examples [1:47:28, 6465.50 examples/s] 
Generating train split: 100205501 examples [1:47:28, 7137.64 examples/s]
Generating train split: 100207337 examples [1:47:28, 7665.76 examples/s]
Generating train split: 100208959 examples [1:47:29, 5101.99 examples/s]
Generating train split: 100210165 examples [1:47:29, 5518.93 examples/s]
Generating train split: 100211274 examples [1:47:29, 5791.65 examples/s]
Generating train split: 100212578 examples [1:47:29, 6674.90 examples/s]
Generating train split: 100213668 examples [1:47:30, 5290.87 examples/s]
Generating train split: 100215625 examples [1:47:30, 7176.15 examples/s]
Generating train split: 100216811 examples [1:47:30, 5950.15 examples/s]
Generating train split: 100224863 examples [1:47:30, 16844.02 examples/s]
Generating train split: 100233060 examples [1:47:30, 28084.26 examples/s]
Generating train split: 100237675 examples [1:47:31, 24158.54 examples/s]
Generating train split: 100241441 examples [1:47:31, 13778.09 examples/s]
Generating train split: 100244259 examples [1:47:32, 7371.13 examples/s] 
Generating train split: 100246318 examples [1:47:33, 7788.79 examples/s]
Generating train split: 100248069 examples [1:47:33, 7766.35 examples/s]
Generating train split: 100249530 examples [1:47:33, 7114.81 examples/s]
Generating train split: 100250703 examples [1:47:33, 6615.24 examples/s]
Generating train split: 100252214 examples [1:47:33, 7620.03 examples/s]
Generating train split: 100258759 examples [1:47:34, 16050.46 examples/s]
Generating train split: 100266602 examples [1:47:34, 26797.09 examples/s]
Generating train split: 100270886 examples [1:47:34, 27498.18 examples/s]
Generating train split: 100278720 examples [1:47:34, 37953.56 examples/s]
Generating train split: 100286386 examples [1:47:34, 46147.19 examples/s]
Generating train split: 100292110 examples [1:47:35, 20429.95 examples/s]
Generating train split: 100296375 examples [1:47:35, 18818.42 examples/s]
Generating train split: 100305205 examples [1:47:35, 27690.20 examples/s]
Generating train split: 100310491 examples [1:47:35, 31370.63 examples/s]
Generating train split: 100315553 examples [1:47:36, 15750.64 examples/s]
Generating train split: 100323777 examples [1:47:36, 22665.31 examples/s]
Generating train split: 100330569 examples [1:47:36, 28516.21 examples/s]
Generating train split: 100336164 examples [1:47:37, 15897.01 examples/s]
Generating train split: 100340294 examples [1:47:39, 6124.17 examples/s] 
Generating train split: 100343247 examples [1:47:40, 4588.74 examples/s]
Generating train split: 100347115 examples [1:47:40, 5917.74 examples/s]
Generating train split: 100349761 examples [1:47:41, 5787.84 examples/s]
Generating train split: 100351773 examples [1:47:41, 5986.37 examples/s]
Generating train split: 100353401 examples [1:47:42, 5166.71 examples/s]
Generating train split: 100354633 examples [1:47:42, 4419.40 examples/s]
Generating train split: 100359184 examples [1:47:42, 7456.93 examples/s]
Generating train split: 100367867 examples [1:47:42, 15037.42 examples/s]
Generating train split: 100372601 examples [1:47:43, 18883.75 examples/s]
Generating train split: 100376813 examples [1:47:43, 14013.81 examples/s]
Generating train split: 100380013 examples [1:47:44, 9975.78 examples/s] 
Generating train split: 100382406 examples [1:47:44, 9917.71 examples/s]
Generating train split: 100384391 examples [1:47:44, 9387.48 examples/s]
Generating train split: 100386004 examples [1:47:45, 8355.34 examples/s]
Generating train split: 100387301 examples [1:47:45, 7749.30 examples/s]
Generating train split: 100388912 examples [1:47:45, 8817.56 examples/s]
Generating train split: 100390149 examples [1:47:45, 6832.83 examples/s]
Generating train split: 100391132 examples [1:47:45, 5698.36 examples/s]
Generating train split: 100391924 examples [1:47:46, 5347.16 examples/s]
Generating train split: 100392613 examples [1:47:46, 4525.12 examples/s]
Generating train split: 100393167 examples [1:47:46, 3762.57 examples/s]
Generating train split: 100394144 examples [1:47:46, 4610.13 examples/s]
Generating train split: 100395262 examples [1:47:46, 5657.36 examples/s]
Generating train split: 100396015 examples [1:47:47, 3993.54 examples/s]
Generating train split: 100397051 examples [1:47:47, 4972.78 examples/s]
Generating train split: 100398578 examples [1:47:47, 6830.72 examples/s]
Generating train split: 100399535 examples [1:47:47, 4224.92 examples/s]
Generating train split: 100400273 examples [1:47:48, 4447.06 examples/s]
Generating train split: 100400954 examples [1:47:48, 3526.80 examples/s]
Generating train split: 100401754 examples [1:47:48, 4169.15 examples/s]
Generating train split: 100402888 examples [1:47:48, 5386.81 examples/s]
Generating train split: 100403977 examples [1:47:48, 6366.91 examples/s]
Generating train split: 100404822 examples [1:47:48, 6003.36 examples/s]
Generating train split: 100405568 examples [1:47:48, 6072.40 examples/s]
Generating train split: 100406445 examples [1:47:49, 6668.88 examples/s]
Generating train split: 100407201 examples [1:47:49, 4579.17 examples/s]
Generating train split: 100407807 examples [1:47:49, 4561.86 examples/s]
Generating train split: 100408679 examples [1:47:49, 5392.75 examples/s]
Generating train split: 100409335 examples [1:47:49, 4609.80 examples/s]
Generating train split: 100410027 examples [1:47:49, 5029.11 examples/s]
Generating train split: 100410626 examples [1:47:50, 4861.56 examples/s]
Generating train split: 100413361 examples [1:47:50, 10037.04 examples/s]
Generating train split: 100421877 examples [1:47:50, 28615.65 examples/s]
Generating train split: 100428392 examples [1:47:50, 38139.74 examples/s]
Generating train split: 100432724 examples [1:47:50, 26561.90 examples/s]
Generating train split: 100436220 examples [1:47:51, 18458.26 examples/s]
Generating train split: 100444633 examples [1:47:51, 29062.25 examples/s]
Generating train split: 100451282 examples [1:47:51, 35627.36 examples/s]
Generating train split: 100456263 examples [1:47:51, 22858.72 examples/s]
Generating train split: 100460094 examples [1:47:52, 16767.18 examples/s]
Generating train split: 100463041 examples [1:47:52, 14135.14 examples/s]
Generating train split: 100465368 examples [1:47:52, 13644.83 examples/s]
Generating train split: 100467356 examples [1:47:52, 12538.80 examples/s]
Generating train split: 100469022 examples [1:47:52, 12167.19 examples/s]
Generating train split: 100470511 examples [1:47:53, 9514.20 examples/s] 
Generating train split: 100471699 examples [1:47:53, 8783.47 examples/s]
Generating train split: 100473133 examples [1:47:53, 9647.29 examples/s]
Generating train split: 100474718 examples [1:47:53, 10768.87 examples/s]
Generating train split: 100475996 examples [1:47:53, 9195.73 examples/s] 
Generating train split: 100477087 examples [1:47:54, 7777.16 examples/s]
Generating train split: 100478006 examples [1:47:54, 8036.95 examples/s]
Generating train split: 100478918 examples [1:47:54, 6629.91 examples/s]
Generating train split: 100479691 examples [1:47:54, 5492.87 examples/s]
Generating train split: 100480333 examples [1:47:54, 5212.17 examples/s]
Generating train split: 100480920 examples [1:47:54, 5188.57 examples/s]
Generating train split: 100481760 examples [1:47:55, 5714.70 examples/s]
Generating train split: 100482382 examples [1:47:55, 4294.94 examples/s]
Generating train split: 100482977 examples [1:47:55, 4504.29 examples/s]
Generating train split: 100483495 examples [1:47:55, 4304.55 examples/s]
Generating train split: 100483967 examples [1:47:55, 3589.22 examples/s]
Generating train split: 100484374 examples [1:47:55, 3280.04 examples/s]
Generating train split: 100485033 examples [1:47:56, 3845.81 examples/s]
Generating train split: 100485462 examples [1:47:56, 2881.88 examples/s]
Generating train split: 100486738 examples [1:47:56, 4732.59 examples/s]
Generating train split: 100487619 examples [1:47:56, 5594.48 examples/s]
Generating train split: 100488721 examples [1:47:56, 6706.48 examples/s]
Generating train split: 100489520 examples [1:47:56, 6222.95 examples/s]
Generating train split: 100490236 examples [1:47:56, 6352.42 examples/s]
Generating train split: 100490993 examples [1:47:56, 6608.98 examples/s]
Generating train split: 100491708 examples [1:47:57, 5870.39 examples/s]
Generating train split: 100492351 examples [1:47:57, 4528.52 examples/s]
Generating train split: 100493575 examples [1:47:57, 6138.92 examples/s]
Generating train split: 100494318 examples [1:47:57, 5859.78 examples/s]
Generating train split: 100494993 examples [1:47:57, 4228.35 examples/s]
Generating train split: 100496632 examples [1:47:57, 6494.69 examples/s]
Generating train split: 100504956 examples [1:47:58, 22634.38 examples/s]
Generating train split: 100513026 examples [1:47:58, 36010.60 examples/s]
Generating train split: 100517612 examples [1:47:59, 11130.12 examples/s]
Generating train split: 100520953 examples [1:47:59, 9132.56 examples/s] 
Generating train split: 100523462 examples [1:48:00, 7479.33 examples/s]
Generating train split: 100525351 examples [1:48:00, 8077.89 examples/s]
Generating train split: 100527380 examples [1:48:00, 9260.14 examples/s]
Generating train split: 100529172 examples [1:48:01, 6516.90 examples/s]
Generating train split: 100530526 examples [1:48:01, 6332.91 examples/s]
Generating train split: 100532044 examples [1:48:01, 7314.51 examples/s]
Generating train split: 100539920 examples [1:48:01, 17098.27 examples/s]
Generating train split: 100548156 examples [1:48:01, 27770.66 examples/s]
Generating train split: 100552889 examples [1:48:02, 20677.68 examples/s]
Generating train split: 100556580 examples [1:48:02, 15364.17 examples/s]
Generating train split: 100559417 examples [1:48:02, 16013.80 examples/s]
Generating train split: 100567338 examples [1:48:02, 25133.50 examples/s]
Generating train split: 100573999 examples [1:48:02, 32218.18 examples/s]
Generating train split: 100578915 examples [1:48:03, 12846.04 examples/s]
Generating train split: 100582507 examples [1:48:04, 13713.40 examples/s]
Generating train split: 100585565 examples [1:48:04, 13235.63 examples/s]
Generating train split: 100588059 examples [1:48:04, 11282.78 examples/s]
Generating train split: 100590012 examples [1:48:05, 7577.11 examples/s] 
Generating train split: 100591481 examples [1:48:05, 6238.62 examples/s]
Generating train split: 100592611 examples [1:48:06, 5549.54 examples/s]
Generating train split: 100593873 examples [1:48:06, 6208.08 examples/s]
Generating train split: 100594864 examples [1:48:06, 5266.21 examples/s]
Generating train split: 100596204 examples [1:48:06, 6235.07 examples/s]
Generating train split: 100597238 examples [1:48:06, 6821.93 examples/s]
Generating train split: 100598207 examples [1:48:06, 6749.96 examples/s]
Generating train split: 100599090 examples [1:48:07, 6561.94 examples/s]
Generating train split: 100600287 examples [1:48:07, 7578.83 examples/s]
Generating train split: 100601205 examples [1:48:07, 7277.63 examples/s]
Generating train split: 100603869 examples [1:48:07, 11438.37 examples/s]
Generating train split: 100605212 examples [1:48:07, 8092.58 examples/s] 
Generating train split: 100606290 examples [1:48:07, 8340.07 examples/s]
Generating train split: 100607870 examples [1:48:07, 9823.50 examples/s]
Generating train split: 100609054 examples [1:48:08, 9544.72 examples/s]
Generating train split: 100610146 examples [1:48:08, 6951.20 examples/s]
Generating train split: 100611650 examples [1:48:08, 8477.80 examples/s]
Generating train split: 100613055 examples [1:48:08, 9387.11 examples/s]
Generating train split: 100614173 examples [1:48:08, 8250.71 examples/s]
Generating train split: 100615140 examples [1:48:08, 8108.81 examples/s]
Generating train split: 100616059 examples [1:48:08, 8262.58 examples/s]
Generating train split: 100616964 examples [1:48:09, 8446.13 examples/s]
Generating train split: 100617875 examples [1:48:09, 6057.32 examples/s]
Generating train split: 100618957 examples [1:48:09, 6980.89 examples/s]
Generating train split: 100619880 examples [1:48:09, 7472.99 examples/s]
Generating train split: 100620743 examples [1:48:09, 6342.63 examples/s]
Generating train split: 100621488 examples [1:48:10, 5000.40 examples/s]
Generating train split: 100623381 examples [1:48:10, 7681.10 examples/s]
Generating train split: 100624381 examples [1:48:10, 4931.81 examples/s]
Generating train split: 100625154 examples [1:48:10, 5184.18 examples/s]
Generating train split: 100627056 examples [1:48:10, 7644.09 examples/s]
Generating train split: 100628133 examples [1:48:11, 4705.17 examples/s]
Generating train split: 100628962 examples [1:48:11, 3640.89 examples/s]
Generating train split: 100629600 examples [1:48:11, 3852.12 examples/s]
Generating train split: 100630200 examples [1:48:11, 3445.07 examples/s]
Generating train split: 100630935 examples [1:48:12, 4013.12 examples/s]
Generating train split: 100631509 examples [1:48:12, 3753.86 examples/s]
Generating train split: 100631998 examples [1:48:12, 3341.88 examples/s]
Generating train split: 100633890 examples [1:48:12, 5684.80 examples/s]
Generating train split: 100634585 examples [1:48:12, 5516.17 examples/s]
Generating train split: 100636652 examples [1:48:12, 8576.09 examples/s]
Generating train split: 100637718 examples [1:48:13, 8013.51 examples/s]
Generating train split: 100639345 examples [1:48:13, 9827.96 examples/s]
Generating train split: 100640500 examples [1:48:13, 9286.69 examples/s]
Generating train split: 100642153 examples [1:48:13, 10998.95 examples/s]
Generating train split: 100643386 examples [1:48:13, 8411.89 examples/s] 
Generating train split: 100644471 examples [1:48:13, 8774.93 examples/s]
Generating train split: 100645488 examples [1:48:13, 8555.15 examples/s]
Generating train split: 100647369 examples [1:48:13, 10964.37 examples/s]
Generating train split: 100648610 examples [1:48:14, 10154.61 examples/s]
Generating train split: 100649732 examples [1:48:14, 10016.50 examples/s]
Generating train split: 100650812 examples [1:48:14, 7734.69 examples/s] 
Generating train split: 100651707 examples [1:48:14, 6427.88 examples/s]
Generating train split: 100652457 examples [1:48:14, 5466.70 examples/s]
Generating train split: 100653095 examples [1:48:15, 4994.65 examples/s]
Generating train split: 100653653 examples [1:48:15, 3752.88 examples/s]
Generating train split: 100654641 examples [1:48:15, 4655.86 examples/s]
Generating train split: 100655213 examples [1:48:15, 3557.94 examples/s]
Generating train split: 100656098 examples [1:48:15, 4262.10 examples/s]
Generating train split: 100657677 examples [1:48:15, 6395.11 examples/s]
Generating train split: 100666134 examples [1:48:16, 22740.22 examples/s]
Generating train split: 100675089 examples [1:48:16, 37041.46 examples/s]
Generating train split: 100679681 examples [1:48:16, 23910.06 examples/s]
Generating train split: 100688649 examples [1:48:16, 35362.18 examples/s]
Generating train split: 100694527 examples [1:48:16, 40023.64 examples/s]
Generating train split: 100699932 examples [1:48:17, 19389.07 examples/s]
Generating train split: 100703978 examples [1:48:17, 13695.16 examples/s]
Generating train split: 100707009 examples [1:48:18, 10531.13 examples/s]
Generating train split: 100709299 examples [1:48:19, 8448.48 examples/s] 
Generating train split: 100711038 examples [1:48:19, 6377.23 examples/s]
Generating train split: 100718388 examples [1:48:19, 11558.82 examples/s]
Generating train split: 100726645 examples [1:48:19, 18610.32 examples/s]
Generating train split: 100731306 examples [1:48:20, 17611.31 examples/s]
Generating train split: 100735030 examples [1:48:21, 10197.36 examples/s]
Generating train split: 100737757 examples [1:48:21, 8557.75 examples/s] 
Generating train split: 100739820 examples [1:48:21, 8114.14 examples/s]
Generating train split: 100741460 examples [1:48:22, 8722.43 examples/s]
Generating train split: 100748885 examples [1:48:22, 16003.25 examples/s]
Generating train split: 100756906 examples [1:48:22, 24533.05 examples/s]
Generating train split: 100761469 examples [1:48:22, 22085.24 examples/s]
Generating train split: 100765189 examples [1:48:22, 15769.83 examples/s]
Generating train split: 100768048 examples [1:48:23, 11832.09 examples/s]
Generating train split: 100770219 examples [1:48:23, 9663.37 examples/s] 
Generating train split: 100771910 examples [1:48:23, 10415.91 examples/s]
Generating train split: 100773595 examples [1:48:24, 10876.57 examples/s]
Generating train split: 100775173 examples [1:48:24, 8108.17 examples/s] 
Generating train split: 100776592 examples [1:48:24, 8870.85 examples/s]
Generating train split: 100777867 examples [1:48:24, 9467.73 examples/s]
Generating train split: 100779147 examples [1:48:25, 6493.05 examples/s]
Generating train split: 100780296 examples [1:48:25, 7199.66 examples/s]
Generating train split: 100781641 examples [1:48:25, 8263.02 examples/s]
Generating train split: 100782939 examples [1:48:25, 8942.88 examples/s]
Generating train split: 100784071 examples [1:48:25, 6742.38 examples/s]
Generating train split: 100786588 examples [1:48:25, 10041.23 examples/s]
Generating train split: 100791638 examples [1:48:25, 18281.79 examples/s]
Generating train split: 100800923 examples [1:48:25, 35087.57 examples/s]
Generating train split: 100807293 examples [1:48:26, 42053.95 examples/s]
Generating train split: 100812380 examples [1:48:26, 21454.35 examples/s]
Generating train split: 100819941 examples [1:48:26, 29654.11 examples/s]
Generating train split: 100827736 examples [1:48:26, 38239.27 examples/s]
Generating train split: 100833556 examples [1:48:27, 16530.76 examples/s]
Generating train split: 100837837 examples [1:48:28, 13695.93 examples/s]
Generating train split: 100841091 examples [1:48:28, 12985.30 examples/s]
Generating train split: 100843693 examples [1:48:28, 12717.59 examples/s]
Generating train split: 100845860 examples [1:48:28, 11125.83 examples/s]
Generating train split: 100847597 examples [1:48:29, 10429.66 examples/s]
Generating train split: 100849403 examples [1:48:29, 11341.49 examples/s]
Generating train split: 100850944 examples [1:48:29, 9467.90 examples/s] 
Generating train split: 100852195 examples [1:48:29, 9905.36 examples/s]
Generating train split: 100853441 examples [1:48:29, 8976.42 examples/s]
Generating train split: 100856315 examples [1:48:29, 12468.95 examples/s]
Generating train split: 100857920 examples [1:48:30, 12925.48 examples/s]
Generating train split: 100859480 examples [1:48:30, 12934.15 examples/s]
Generating train split: 100860975 examples [1:48:30, 12893.44 examples/s]
Generating train split: 100862398 examples [1:48:30, 12819.96 examples/s]
Generating train split: 100864888 examples [1:48:30, 15842.79 examples/s]
Generating train split: 100866608 examples [1:48:30, 15164.74 examples/s]
Generating train split: 100868223 examples [1:48:30, 13857.61 examples/s]
Generating train split: 100869875 examples [1:48:30, 14266.39 examples/s]
Generating train split: 100871756 examples [1:48:30, 15290.13 examples/s]
Generating train split: 100873852 examples [1:48:31, 16793.80 examples/s]
Generating train split: 100876055 examples [1:48:31, 18224.81 examples/s]
Generating train split: 100877933 examples [1:48:31, 10832.11 examples/s]
Generating train split: 100879406 examples [1:48:31, 11229.60 examples/s]
Generating train split: 100880830 examples [1:48:31, 11032.53 examples/s]
Generating train split: 100882139 examples [1:48:31, 10373.48 examples/s]
Generating train split: 100890139 examples [1:48:32, 25696.65 examples/s]
Generating train split: 100899090 examples [1:48:32, 40417.64 examples/s]
Generating train split: 100903894 examples [1:48:32, 26775.06 examples/s]
Generating train split: 100907699 examples [1:48:32, 18564.76 examples/s]
Generating train split: 100910654 examples [1:48:33, 16906.98 examples/s]
Generating train split: 100913098 examples [1:48:33, 13998.79 examples/s]
Generating train split: 100915378 examples [1:48:33, 15193.15 examples/s]
Generating train split: 100917422 examples [1:48:33, 15674.44 examples/s]
Generating train split: 100919383 examples [1:48:33, 12691.39 examples/s]
Generating train split: 100920989 examples [1:48:33, 13174.76 examples/s]
Generating train split: 100922680 examples [1:48:34, 13907.90 examples/s]
Generating train split: 100924304 examples [1:48:34, 13001.22 examples/s]
Generating train split: 100925765 examples [1:48:34, 9205.50 examples/s] 
Generating train split: 100927615 examples [1:48:34, 10861.20 examples/s]
Generating train split: 100929874 examples [1:48:34, 13222.41 examples/s]
Generating train split: 100931845 examples [1:48:34, 14676.23 examples/s]
Generating train split: 100934786 examples [1:48:34, 18232.78 examples/s]
Generating train split: 100936877 examples [1:48:35, 14791.09 examples/s]
Generating train split: 100938648 examples [1:48:35, 13709.39 examples/s]
Generating train split: 100940225 examples [1:48:35, 14024.05 examples/s]
Generating train split: 100941826 examples [1:48:35, 14366.02 examples/s]
Generating train split: 100943379 examples [1:48:35, 11687.45 examples/s]
Generating train split: 100944697 examples [1:48:35, 10789.60 examples/s]
Generating train split: 100945882 examples [1:48:36, 6592.64 examples/s] 
Generating train split: 100947018 examples [1:48:36, 7350.26 examples/s]
Generating train split: 100948010 examples [1:48:36, 7631.19 examples/s]
Generating train split: 100948959 examples [1:48:36, 6356.19 examples/s]
Generating train split: 100951474 examples [1:48:36, 9890.46 examples/s]
Generating train split: 100952782 examples [1:48:36, 9570.48 examples/s]
Generating train split: 100953961 examples [1:48:37, 9297.12 examples/s]
Generating train split: 100955054 examples [1:48:37, 6945.66 examples/s]
Generating train split: 100955936 examples [1:48:37, 7278.65 examples/s]
Generating train split: 100957640 examples [1:48:37, 9285.73 examples/s]
Generating train split: 100958761 examples [1:48:37, 6543.00 examples/s]
Generating train split: 100960992 examples [1:48:37, 9390.48 examples/s]
Generating train split: 100962285 examples [1:48:38, 9957.93 examples/s]
Generating train split: 100963552 examples [1:48:38, 6183.50 examples/s]
Generating train split: 100964927 examples [1:48:38, 7322.15 examples/s]
Generating train split: 100966532 examples [1:48:38, 8899.92 examples/s]
Generating train split: 100967766 examples [1:48:38, 6719.03 examples/s]
Generating train split: 100968754 examples [1:48:39, 6273.12 examples/s]
Generating train split: 100969600 examples [1:48:39, 5439.65 examples/s]
Generating train split: 100970306 examples [1:48:39, 5551.55 examples/s]
Generating train split: 100970979 examples [1:48:39, 5484.71 examples/s]
Generating train split: 100971608 examples [1:48:39, 5082.94 examples/s]
Generating train split: 100972182 examples [1:48:40, 4216.14 examples/s]
Generating train split: 100974474 examples [1:48:40, 7821.04 examples/s]
Generating train split: 100975487 examples [1:48:40, 6548.75 examples/s]
Generating train split: 100976343 examples [1:48:40, 5312.35 examples/s]
Generating train split: 100977997 examples [1:48:40, 7291.40 examples/s]
Generating train split: 100978980 examples [1:48:41, 5386.02 examples/s]
Generating train split: 100979770 examples [1:48:41, 5515.05 examples/s]
Generating train split: 100981068 examples [1:48:41, 6883.57 examples/s]
Generating train split: 100981967 examples [1:48:41, 7228.80 examples/s]
Generating train split: 100982856 examples [1:48:41, 5408.97 examples/s]
Generating train split: 100985018 examples [1:48:41, 8441.92 examples/s]
Generating train split: 100987022 examples [1:48:41, 10849.52 examples/s]
Generating train split: 100988424 examples [1:48:41, 11374.28 examples/s]
Generating train split: 100989956 examples [1:48:42, 12333.10 examples/s]
Generating train split: 100991373 examples [1:48:42, 9402.05 examples/s] 
Generating train split: 100992543 examples [1:48:42, 9769.93 examples/s]
Generating train split: 100994356 examples [1:48:42, 11700.42 examples/s]
Generating train split: 100995808 examples [1:48:42, 12289.53 examples/s]
Generating train split: 101000734 examples [1:48:42, 21907.86 examples/s]
Generating train split: 101008948 examples [1:48:42, 38228.95 examples/s]
Generating train split: 101013115 examples [1:48:42, 35813.49 examples/s]
Generating train split: 101016968 examples [1:48:43, 25146.02 examples/s]
Generating train split: 101020099 examples [1:48:43, 15369.37 examples/s]
Generating train split: 101022509 examples [1:48:44, 11378.50 examples/s]
Generating train split: 101024367 examples [1:48:44, 11642.49 examples/s]
Generating train split: 101026606 examples [1:48:44, 13129.32 examples/s]
Generating train split: 101028436 examples [1:48:44, 8953.67 examples/s] 
Generating train split: 101029844 examples [1:48:45, 7616.03 examples/s]
Generating train split: 101030979 examples [1:48:45, 7716.74 examples/s]
Generating train split: 101032579 examples [1:48:45, 8968.55 examples/s]
Generating train split: 101034546 examples [1:48:45, 10877.81 examples/s]
Generating train split: 101035976 examples [1:48:45, 6767.32 examples/s] 
Generating train split: 101037332 examples [1:48:45, 7751.06 examples/s]
Generating train split: 101038509 examples [1:48:46, 7522.98 examples/s]
Generating train split: 101039542 examples [1:48:46, 7576.52 examples/s]
Generating train split: 101040498 examples [1:48:46, 6084.21 examples/s]
Generating train split: 101041765 examples [1:48:46, 7214.99 examples/s]
Generating train split: 101042687 examples [1:48:46, 7043.82 examples/s]
Generating train split: 101043529 examples [1:48:46, 6769.02 examples/s]
Generating train split: 101044700 examples [1:48:46, 7835.54 examples/s]
Generating train split: 101045729 examples [1:48:47, 8381.89 examples/s]
Generating train split: 101046657 examples [1:48:47, 6641.68 examples/s]
Generating train split: 101054027 examples [1:48:47, 21180.58 examples/s]
Generating train split: 101062205 examples [1:48:47, 34806.97 examples/s]
Generating train split: 101066396 examples [1:48:47, 24362.15 examples/s]
Generating train split: 101069755 examples [1:48:48, 16082.31 examples/s]
Generating train split: 101072345 examples [1:48:48, 10515.89 examples/s]
Generating train split: 101074301 examples [1:48:49, 7988.84 examples/s] 
Generating train split: 101075791 examples [1:48:49, 6414.74 examples/s]
Generating train split: 101076932 examples [1:48:49, 6390.45 examples/s]
Generating train split: 101077927 examples [1:48:50, 5759.93 examples/s]
Generating train split: 101079330 examples [1:48:50, 6723.34 examples/s]
Generating train split: 101080313 examples [1:48:50, 6276.67 examples/s]
Generating train split: 101081387 examples [1:48:50, 6943.81 examples/s]
Generating train split: 101082285 examples [1:48:50, 5695.68 examples/s]
Generating train split: 101083023 examples [1:48:51, 3567.78 examples/s]
Generating train split: 101083892 examples [1:48:51, 4184.18 examples/s]
Generating train split: 101084536 examples [1:48:51, 4152.47 examples/s]
Generating train split: 101092219 examples [1:48:51, 16104.49 examples/s]
Generating train split: 101100755 examples [1:48:51, 29275.75 examples/s]
Generating train split: 101105212 examples [1:48:52, 16737.68 examples/s]
Generating train split: 101108581 examples [1:48:52, 11696.14 examples/s]
Generating train split: 101111120 examples [1:48:53, 10152.04 examples/s]
Generating train split: 101113096 examples [1:48:53, 8172.58 examples/s] 
Generating train split: 101114616 examples [1:48:53, 8801.50 examples/s]
Generating train split: 101116103 examples [1:48:53, 9303.47 examples/s]
Generating train split: 101117521 examples [1:48:54, 7634.10 examples/s]
Generating train split: 101118642 examples [1:48:54, 7545.65 examples/s]
Generating train split: 101124715 examples [1:48:54, 15740.55 examples/s]
Generating train split: 101133665 examples [1:48:54, 29048.09 examples/s]
Generating train split: 101138118 examples [1:48:55, 21587.26 examples/s]
Generating train split: 101141632 examples [1:48:55, 13532.14 examples/s]
Generating train split: 101149672 examples [1:48:55, 21388.07 examples/s]
Generating train split: 101157413 examples [1:48:55, 29012.67 examples/s]
Generating train split: 101162505 examples [1:48:56, 16201.19 examples/s]
Generating train split: 101166286 examples [1:48:57, 9421.36 examples/s] 
Generating train split: 101169054 examples [1:48:57, 9790.88 examples/s]
Generating train split: 101171349 examples [1:48:58, 9271.37 examples/s]
Generating train split: 101173379 examples [1:48:58, 10293.59 examples/s]
Generating train split: 101180144 examples [1:48:58, 17078.93 examples/s]
Generating train split: 101188650 examples [1:48:58, 26907.04 examples/s]
Generating train split: 101193548 examples [1:48:58, 18199.30 examples/s]
Generating train split: 101197266 examples [1:48:59, 13634.17 examples/s]
Generating train split: 101200091 examples [1:48:59, 9887.52 examples/s] 
Generating train split: 101202208 examples [1:49:00, 9354.91 examples/s]
Generating train split: 101203915 examples [1:49:00, 8811.26 examples/s]
Generating train split: 101205317 examples [1:49:00, 8040.70 examples/s]
Generating train split: 101206468 examples [1:49:00, 7236.74 examples/s]
Generating train split: 101207427 examples [1:49:01, 6027.09 examples/s]
Generating train split: 101208397 examples [1:49:01, 6423.06 examples/s]
Generating train split: 101209206 examples [1:49:01, 6132.08 examples/s]
Generating train split: 101211382 examples [1:49:01, 8716.78 examples/s]
Generating train split: 101212532 examples [1:49:01, 7434.04 examples/s]
Generating train split: 101213493 examples [1:49:02, 5778.12 examples/s]
Generating train split: 101214265 examples [1:49:02, 4508.55 examples/s]
Generating train split: 101214893 examples [1:49:02, 4732.75 examples/s]
Generating train split: 101215508 examples [1:49:02, 4041.29 examples/s]
Generating train split: 101216124 examples [1:49:02, 4388.94 examples/s]
Generating train split: 101216663 examples [1:49:03, 4056.14 examples/s]
Generating train split: 101218286 examples [1:49:03, 6417.89 examples/s]
Generating train split: 101219106 examples [1:49:03, 6156.37 examples/s]
Generating train split: 101219844 examples [1:49:03, 5178.52 examples/s]
Generating train split: 101220466 examples [1:49:03, 5143.02 examples/s]
Generating train split: 101221672 examples [1:49:03, 6633.80 examples/s]
Generating train split: 101226740 examples [1:49:03, 17003.31 examples/s]
Generating train split: 101235029 examples [1:49:03, 33574.42 examples/s]
Generating train split: 101238961 examples [1:49:04, 26640.00 examples/s]
Generating train split: 101242262 examples [1:49:04, 12367.29 examples/s]
Generating train split: 101244718 examples [1:49:05, 10205.13 examples/s]
Generating train split: 101247426 examples [1:49:05, 12129.62 examples/s]
Generating train split: 101249576 examples [1:49:05, 11075.25 examples/s]
Generating train split: 101251332 examples [1:49:05, 9817.81 examples/s] 
Generating train split: 101254834 examples [1:49:05, 13402.45 examples/s]
Generating train split: 101262993 examples [1:49:06, 24916.35 examples/s]
Generating train split: 101269245 examples [1:49:06, 32225.32 examples/s]
Generating train split: 101273849 examples [1:49:06, 15736.73 examples/s]
Generating train split: 101277282 examples [1:49:07, 12333.55 examples/s]
Generating train split: 101279899 examples [1:49:07, 10116.08 examples/s]
Generating train split: 101281910 examples [1:49:08, 8207.72 examples/s] 
Generating train split: 101283450 examples [1:49:08, 7716.50 examples/s]
Generating train split: 101284706 examples [1:49:08, 7309.25 examples/s]
Generating train split: 101285758 examples [1:49:08, 7091.97 examples/s]
Generating train split: 101286678 examples [1:49:09, 6817.08 examples/s]
Generating train split: 101287504 examples [1:49:09, 5796.93 examples/s]
Generating train split: 101289558 examples [1:49:09, 7995.21 examples/s]
Generating train split: 101290645 examples [1:49:09, 5281.70 examples/s]
Generating train split: 101291470 examples [1:49:09, 5114.74 examples/s]
Generating train split: 101292183 examples [1:49:10, 4523.53 examples/s]
Generating train split: 101293744 examples [1:49:10, 6193.14 examples/s]
Generating train split: 101295375 examples [1:49:10, 7980.50 examples/s]
Generating train split: 101296494 examples [1:49:10, 6983.84 examples/s]
Generating train split: 101297428 examples [1:49:10, 5632.85 examples/s]
Generating train split: 101298212 examples [1:49:11, 5887.17 examples/s]
Generating train split: 101299800 examples [1:49:11, 7799.37 examples/s]
Generating train split: 101300983 examples [1:49:11, 8493.38 examples/s]
Generating train split: 101302002 examples [1:49:11, 8101.36 examples/s]
Generating train split: 101302938 examples [1:49:11, 6449.76 examples/s]
Generating train split: 101304942 examples [1:49:11, 9188.37 examples/s]
Generating train split: 101306081 examples [1:49:12, 5769.94 examples/s]
Generating train split: 101307691 examples [1:49:12, 7424.24 examples/s]
Generating train split: 101308805 examples [1:49:12, 7562.44 examples/s]
Generating train split: 101310015 examples [1:49:12, 8353.49 examples/s]
Generating train split: 101311063 examples [1:49:12, 5222.87 examples/s]
Generating train split: 101314457 examples [1:49:12, 9704.77 examples/s]
Generating train split: 101316043 examples [1:49:13, 5431.87 examples/s]
Generating train split: 101317228 examples [1:49:13, 5438.56 examples/s]
Generating train split: 101318230 examples [1:49:13, 5540.41 examples/s]
Generating train split: 101326938 examples [1:49:14, 17204.43 examples/s]
Generating train split: 101335259 examples [1:49:14, 28402.56 examples/s]
Generating train split: 101340012 examples [1:49:14, 23856.13 examples/s]
Generating train split: 101343850 examples [1:49:14, 16682.48 examples/s]
Generating train split: 101346801 examples [1:49:15, 11931.11 examples/s]
Generating train split: 101349044 examples [1:49:15, 11278.30 examples/s]
Generating train split: 101350893 examples [1:49:16, 9188.82 examples/s] 
Generating train split: 101352341 examples [1:49:16, 7944.69 examples/s]
Generating train split: 101353495 examples [1:49:16, 7952.50 examples/s]
Generating train split: 101355210 examples [1:49:16, 9206.23 examples/s]
Generating train split: 101356715 examples [1:49:16, 10103.48 examples/s]
Generating train split: 101358224 examples [1:49:16, 11014.46 examples/s]
Generating train split: 101359592 examples [1:49:17, 6877.95 examples/s] 
Generating train split: 101362138 examples [1:49:17, 9687.94 examples/s]
Generating train split: 101363625 examples [1:49:17, 8427.41 examples/s]
Generating train split: 101364849 examples [1:49:17, 9056.19 examples/s]
Generating train split: 101366211 examples [1:49:17, 9936.89 examples/s]
Generating train split: 101367811 examples [1:49:17, 11240.74 examples/s]
Generating train split: 101369333 examples [1:49:17, 12137.77 examples/s]
Generating train split: 101370746 examples [1:49:18, 12612.49 examples/s]
Generating train split: 101372151 examples [1:49:18, 9351.89 examples/s] 
Generating train split: 101373352 examples [1:49:18, 9917.85 examples/s]
Generating train split: 101374527 examples [1:49:18, 8334.98 examples/s]
Generating train split: 101375518 examples [1:49:18, 8479.92 examples/s]
Generating train split: 101377213 examples [1:49:18, 10363.52 examples/s]
Generating train split: 101378410 examples [1:49:18, 10703.30 examples/s]
Generating train split: 101379591 examples [1:49:19, 8503.84 examples/s] 
Generating train split: 101380590 examples [1:49:19, 7896.32 examples/s]
Generating train split: 101381483 examples [1:49:19, 6996.44 examples/s]
Generating train split: 101383321 examples [1:49:19, 9419.62 examples/s]
Generating train split: 101384421 examples [1:49:19, 7476.63 examples/s]
Generating train split: 101386328 examples [1:49:19, 9827.15 examples/s]
Generating train split: 101387690 examples [1:49:19, 10676.88 examples/s]
Generating train split: 101390551 examples [1:49:20, 15035.53 examples/s]
Generating train split: 101392297 examples [1:49:20, 10598.01 examples/s]
Generating train split: 101393701 examples [1:49:20, 8953.52 examples/s] 
Generating train split: 101395997 examples [1:49:20, 11528.21 examples/s]
Generating train split: 101398975 examples [1:49:20, 15327.40 examples/s]
Generating train split: 101405604 examples [1:49:20, 27009.59 examples/s]
Generating train split: 101413471 examples [1:49:21, 39202.60 examples/s]
Generating train split: 101418048 examples [1:49:21, 22137.94 examples/s]
Generating train split: 101421575 examples [1:49:21, 14314.57 examples/s]
Generating train split: 101424246 examples [1:49:22, 10155.91 examples/s]
Generating train split: 101426260 examples [1:49:22, 9134.57 examples/s] 
Generating train split: 101428020 examples [1:49:22, 10027.05 examples/s]
Generating train split: 101429666 examples [1:49:23, 8948.34 examples/s] 
Generating train split: 101431025 examples [1:49:23, 8485.28 examples/s]
Generating train split: 101432174 examples [1:49:23, 8527.20 examples/s]
Generating train split: 101433245 examples [1:49:23, 7661.04 examples/s]
Generating train split: 101434183 examples [1:49:23, 7743.69 examples/s]
Generating train split: 101435070 examples [1:49:23, 7665.71 examples/s]
Generating train split: 101437129 examples [1:49:24, 10342.47 examples/s]
Generating train split: 101438334 examples [1:49:24, 9573.48 examples/s] 
Generating train split: 101439414 examples [1:49:24, 9704.16 examples/s]
Generating train split: 101441104 examples [1:49:24, 11435.11 examples/s]
Generating train split: 101442354 examples [1:49:24, 8599.28 examples/s] 
Generating train split: 101443390 examples [1:49:24, 7358.53 examples/s]
Generating train split: 101444274 examples [1:49:25, 5991.18 examples/s]
Generating train split: 101445348 examples [1:49:25, 6675.03 examples/s]
Generating train split: 101446139 examples [1:49:25, 5568.99 examples/s]
Generating train split: 101446799 examples [1:49:25, 4218.17 examples/s]
Generating train split: 101447329 examples [1:49:25, 4093.43 examples/s]
Generating train split: 101449427 examples [1:49:25, 7121.06 examples/s]
Generating train split: 101450396 examples [1:49:26, 6539.28 examples/s]
Generating train split: 101451230 examples [1:49:26, 5604.62 examples/s]
Generating train split: 101451963 examples [1:49:26, 5906.47 examples/s]
Generating train split: 101452675 examples [1:49:26, 5182.02 examples/s]
Generating train split: 101453540 examples [1:49:26, 5780.74 examples/s]
Generating train split: 101454204 examples [1:49:26, 5335.92 examples/s]
Generating train split: 101456277 examples [1:49:27, 8713.72 examples/s]
Generating train split: 101457312 examples [1:49:27, 7569.60 examples/s]
Generating train split: 101458560 examples [1:49:27, 8333.38 examples/s]
Generating train split: 101459503 examples [1:49:27, 7330.15 examples/s]
Generating train split: 101461715 examples [1:49:27, 10576.33 examples/s]
Generating train split: 101462948 examples [1:49:27, 8490.27 examples/s] 
Generating train split: 101463988 examples [1:49:28, 6988.39 examples/s]
Generating train split: 101465128 examples [1:49:28, 7820.35 examples/s]
Generating train split: 101466078 examples [1:49:28, 6903.44 examples/s]
Generating train split: 101466890 examples [1:49:28, 5301.32 examples/s]
Generating train split: 101467847 examples [1:49:28, 6058.45 examples/s]
Generating train split: 101468611 examples [1:49:28, 5768.42 examples/s]
Generating train split: 101469285 examples [1:49:29, 4858.51 examples/s]
Generating train split: 101470398 examples [1:49:29, 6073.84 examples/s]
Generating train split: 101471132 examples [1:49:29, 5676.38 examples/s]
Generating train split: 101472083 examples [1:49:29, 6455.05 examples/s]
Generating train split: 101472823 examples [1:49:29, 3277.36 examples/s]
Generating train split: 101473813 examples [1:49:30, 4206.17 examples/s]
Generating train split: 101474495 examples [1:49:30, 4551.79 examples/s]
Generating train split: 101475426 examples [1:49:30, 5454.14 examples/s]
Generating train split: 101476584 examples [1:49:30, 6755.16 examples/s]
Generating train split: 101477448 examples [1:49:30, 5501.75 examples/s]
Generating train split: 101478614 examples [1:49:30, 6752.92 examples/s]
Generating train split: 101479469 examples [1:49:30, 5777.75 examples/s]
Generating train split: 101480189 examples [1:49:31, 5662.81 examples/s]
Generating train split: 101480868 examples [1:49:31, 4968.56 examples/s]
Generating train split: 101481447 examples [1:49:31, 4345.16 examples/s]
Generating train split: 101482035 examples [1:49:31, 4631.59 examples/s]
Generating train split: 101482558 examples [1:49:31, 3972.10 examples/s]
Generating train split: 101483263 examples [1:49:31, 4331.58 examples/s]
Generating train split: 101484613 examples [1:49:31, 6330.15 examples/s]
Generating train split: 101485356 examples [1:49:32, 5862.96 examples/s]
Generating train split: 101486164 examples [1:49:32, 6374.52 examples/s]
Generating train split: 101486877 examples [1:49:32, 4483.94 examples/s]
Generating train split: 101487931 examples [1:49:32, 5600.21 examples/s]
Generating train split: 101488628 examples [1:49:32, 5027.57 examples/s]
Generating train split: 101489486 examples [1:49:32, 5747.64 examples/s]
Generating train split: 101490169 examples [1:49:33, 4932.86 examples/s]
Generating train split: 101492131 examples [1:49:33, 8038.92 examples/s]
Generating train split: 101493482 examples [1:49:33, 9225.06 examples/s]
Generating train split: 101494585 examples [1:49:33, 9371.67 examples/s]
Generating train split: 101495641 examples [1:49:33, 5132.73 examples/s]
Generating train split: 101496910 examples [1:49:33, 6349.94 examples/s]
Generating train split: 101497877 examples [1:49:34, 6971.18 examples/s]
Generating train split: 101498839 examples [1:49:34, 5365.17 examples/s]
Generating train split: 101499611 examples [1:49:34, 5717.43 examples/s]
Generating train split: 101501102 examples [1:49:34, 7482.56 examples/s]
Generating train split: 101502833 examples [1:49:34, 9602.90 examples/s]
Generating train split: 101504013 examples [1:49:34, 7682.42 examples/s]
Generating train split: 101505791 examples [1:49:34, 9721.32 examples/s]
Generating train split: 101506997 examples [1:49:35, 8770.77 examples/s]
Generating train split: 101508324 examples [1:49:35, 9614.87 examples/s]
Generating train split: 101509451 examples [1:49:35, 7511.23 examples/s]
Generating train split: 101511224 examples [1:49:35, 9557.62 examples/s]
Generating train split: 101512404 examples [1:49:35, 8469.97 examples/s]
Generating train split: 101513420 examples [1:49:36, 5925.18 examples/s]
Generating train split: 101514611 examples [1:49:36, 6804.04 examples/s]
Generating train split: 101515497 examples [1:49:36, 4516.51 examples/s]
Generating train split: 101516514 examples [1:49:36, 5321.45 examples/s]
Generating train split: 101517293 examples [1:49:36, 5026.81 examples/s]
Generating train split: 101524549 examples [1:49:37, 16987.04 examples/s]
Generating train split: 101533070 examples [1:49:37, 30170.59 examples/s]
Generating train split: 101537269 examples [1:49:37, 14562.65 examples/s]
Generating train split: 101540387 examples [1:49:38, 13630.74 examples/s]
Generating train split: 101542909 examples [1:49:38, 12188.64 examples/s]
Generating train split: 101544938 examples [1:49:38, 12613.75 examples/s]
Generating train split: 101546821 examples [1:49:38, 12059.96 examples/s]
Generating train split: 101548432 examples [1:49:38, 9818.58 examples/s] 
Generating train split: 101552463 examples [1:49:39, 14346.77 examples/s]
Generating train split: 101560092 examples [1:49:39, 25191.65 examples/s]
Generating train split: 101567506 examples [1:49:39, 34709.25 examples/s]
Generating train split: 101572290 examples [1:49:39, 24516.13 examples/s]
Generating train split: 101576054 examples [1:49:40, 13375.03 examples/s]
Generating train split: 101578855 examples [1:49:40, 13898.50 examples/s]
Generating train split: 101581315 examples [1:49:40, 12842.80 examples/s]
Generating train split: 101583682 examples [1:49:40, 14214.29 examples/s]
Generating train split: 101585789 examples [1:49:41, 13375.80 examples/s]
Generating train split: 101587594 examples [1:49:41, 12332.69 examples/s]
Generating train split: 101589146 examples [1:49:41, 11975.85 examples/s]
Generating train split: 101591316 examples [1:49:41, 13764.65 examples/s]
Generating train split: 101592953 examples [1:49:41, 9131.07 examples/s] 
Generating train split: 101594649 examples [1:49:41, 10249.58 examples/s]
Generating train split: 101597082 examples [1:49:42, 12746.57 examples/s]
Generating train split: 101598742 examples [1:49:42, 12137.24 examples/s]
Generating train split: 101600225 examples [1:49:42, 10862.51 examples/s]
Generating train split: 101601516 examples [1:49:42, 9231.52 examples/s] 
Generating train split: 101602600 examples [1:49:42, 6848.69 examples/s]
Generating train split: 101603641 examples [1:49:42, 7413.78 examples/s]
Generating train split: 101604559 examples [1:49:43, 6405.05 examples/s]
Generating train split: 101605371 examples [1:49:43, 6713.53 examples/s]
Generating train split: 101606158 examples [1:49:43, 5973.89 examples/s]
Generating train split: 101607280 examples [1:49:43, 7022.96 examples/s]
Generating train split: 101608092 examples [1:49:43, 6832.43 examples/s]
Generating train split: 101608855 examples [1:49:43, 6763.04 examples/s]
Generating train split: 101610056 examples [1:49:43, 7927.28 examples/s]
Generating train split: 101610917 examples [1:49:44, 6111.35 examples/s]
Generating train split: 101611629 examples [1:49:44, 5315.00 examples/s]
Generating train split: 101612927 examples [1:49:44, 6866.97 examples/s]
Generating train split: 101613740 examples [1:49:44, 6757.74 examples/s]
Generating train split: 101616113 examples [1:49:44, 10696.13 examples/s]
Generating train split: 101617364 examples [1:49:45, 6962.05 examples/s] 
Generating train split: 101618356 examples [1:49:45, 6751.05 examples/s]
Generating train split: 101619505 examples [1:49:45, 7646.80 examples/s]
Generating train split: 101620457 examples [1:49:45, 7398.25 examples/s]
Generating train split: 101621334 examples [1:49:45, 6767.18 examples/s]
Generating train split: 101622107 examples [1:49:46, 4159.91 examples/s]
Generating train split: 101622717 examples [1:49:46, 4322.48 examples/s]
Generating train split: 101623820 examples [1:49:46, 5450.73 examples/s]
Generating train split: 101624573 examples [1:49:46, 5851.74 examples/s]
Generating train split: 101625799 examples [1:49:46, 7220.91 examples/s]
Generating train split: 101626663 examples [1:49:46, 5392.58 examples/s]
Generating train split: 101627370 examples [1:49:46, 5517.37 examples/s]
Generating train split: 101628558 examples [1:49:46, 6754.16 examples/s]
Generating train split: 101629356 examples [1:49:47, 5138.54 examples/s]
Generating train split: 101636551 examples [1:49:47, 18065.25 examples/s]
Generating train split: 101644566 examples [1:49:47, 31492.22 examples/s]
Generating train split: 101648806 examples [1:49:47, 22966.54 examples/s]
Generating train split: 101652188 examples [1:49:48, 15201.43 examples/s]
Generating train split: 101654782 examples [1:49:48, 11472.68 examples/s]
Generating train split: 101656789 examples [1:49:48, 12130.37 examples/s]
Generating train split: 101664484 examples [1:49:48, 21364.26 examples/s]
Generating train split: 101672771 examples [1:49:48, 31762.63 examples/s]
Generating train split: 101677798 examples [1:49:49, 22411.56 examples/s]
Generating train split: 101681696 examples [1:49:49, 19025.79 examples/s]
Generating train split: 101684809 examples [1:49:49, 16212.32 examples/s]
Generating train split: 101687311 examples [1:49:50, 13041.38 examples/s]
Generating train split: 101689273 examples [1:49:50, 12037.04 examples/s]
Generating train split: 101690913 examples [1:49:50, 9954.00 examples/s] 
Generating train split: 101692225 examples [1:49:50, 9595.01 examples/s]
Generating train split: 101693389 examples [1:49:51, 9686.90 examples/s]
Generating train split: 101694508 examples [1:49:51, 8559.72 examples/s]
Generating train split: 101695467 examples [1:49:51, 8235.69 examples/s]
Generating train split: 101696358 examples [1:49:51, 6920.55 examples/s]
Generating train split: 101697373 examples [1:49:51, 7487.53 examples/s]
Generating train split: 101698194 examples [1:49:51, 7022.65 examples/s]
Generating train split: 101699560 examples [1:49:51, 8364.48 examples/s]
Generating train split: 101701491 examples [1:49:52, 10862.49 examples/s]
Generating train split: 101702711 examples [1:49:52, 7112.84 examples/s] 
Generating train split: 101703681 examples [1:49:52, 6049.52 examples/s]
Generating train split: 101704589 examples [1:49:52, 6570.26 examples/s]
Generating train split: 101705417 examples [1:49:52, 6344.99 examples/s]
Generating train split: 101706171 examples [1:49:53, 4541.87 examples/s]
Generating train split: 101707993 examples [1:49:53, 6813.41 examples/s]
Generating train split: 101708949 examples [1:49:53, 4893.18 examples/s]
Generating train split: 101711768 examples [1:49:53, 8515.13 examples/s]
Generating train split: 101720072 examples [1:49:53, 22058.76 examples/s]
Generating train split: 101726875 examples [1:49:53, 31526.26 examples/s]
Generating train split: 101731333 examples [1:49:54, 16447.83 examples/s]
Generating train split: 101739684 examples [1:49:54, 25439.85 examples/s]
Generating train split: 101747111 examples [1:49:54, 33291.24 examples/s]
Generating train split: 101752740 examples [1:49:55, 23861.80 examples/s]
Generating train split: 101757088 examples [1:49:56, 10614.89 examples/s]
Generating train split: 101760252 examples [1:49:56, 10075.81 examples/s]
Generating train split: 101762723 examples [1:49:57, 8906.60 examples/s] 
Generating train split: 101764801 examples [1:49:57, 9912.22 examples/s]
Generating train split: 101766752 examples [1:49:57, 7181.69 examples/s]
Generating train split: 101768222 examples [1:49:57, 7195.44 examples/s]
Generating train split: 101769478 examples [1:49:58, 7053.16 examples/s]
Generating train split: 101770855 examples [1:49:58, 7870.82 examples/s]
Generating train split: 101772024 examples [1:49:58, 6679.08 examples/s]
Generating train split: 101772965 examples [1:49:58, 5891.24 examples/s]
Generating train split: 101773748 examples [1:49:58, 5662.35 examples/s]
Generating train split: 101774435 examples [1:49:59, 5792.92 examples/s]
Generating train split: 101775113 examples [1:49:59, 5103.15 examples/s]
Generating train split: 101777492 examples [1:49:59, 8490.81 examples/s]
Generating train split: 101779207 examples [1:49:59, 10282.77 examples/s]
Generating train split: 101783612 examples [1:49:59, 17973.93 examples/s]
Generating train split: 101787125 examples [1:49:59, 22176.59 examples/s]
Generating train split: 101795031 examples [1:49:59, 36942.11 examples/s]
Generating train split: 101802022 examples [1:49:59, 45853.92 examples/s]
Generating train split: 101808671 examples [1:49:59, 51587.82 examples/s]
Generating train split: 101814720 examples [1:50:00, 54105.25 examples/s]
Generating train split: 101821398 examples [1:50:00, 57758.49 examples/s]
Generating train split: 101827374 examples [1:50:00, 57243.74 examples/s]
Generating train split: 101835227 examples [1:50:00, 63404.96 examples/s]
Generating train split: 101843503 examples [1:50:00, 69076.61 examples/s]
Generating train split: 101851542 examples [1:50:00, 72395.55 examples/s]
Generating train split: 101859453 examples [1:50:00, 74379.92 examples/s]
Generating train split: 101867703 examples [1:50:00, 76781.60 examples/s]
Generating train split: 101875427 examples [1:50:00, 76291.94 examples/s]
Generating train split: 101883803 examples [1:50:00, 78470.12 examples/s]
Generating train split: 101892154 examples [1:50:01, 79951.97 examples/s]
Generating train split: 101900176 examples [1:50:01, 79227.72 examples/s]
Generating train split: 101908117 examples [1:50:01, 78692.11 examples/s]
Generating train split: 101916004 examples [1:50:01, 78465.89 examples/s]
Generating train split: 101924421 examples [1:50:01, 80149.36 examples/s]
Generating train split: 101932498 examples [1:50:01, 80329.22 examples/s]
Generating train split: 101940536 examples [1:50:01, 79142.34 examples/s]
Generating train split: 101949263 examples [1:50:01, 81532.03 examples/s]
Generating train split: 101957431 examples [1:50:01, 79767.88 examples/s]
Generating train split: 101965438 examples [1:50:01, 78386.28 examples/s]
Generating train split: 101973565 examples [1:50:02, 79207.98 examples/s]
Generating train split: 101981502 examples [1:50:02, 74564.82 examples/s]
Generating train split: 101989019 examples [1:50:02, 74224.45 examples/s]
Generating train split: 101996486 examples [1:50:02, 71363.32 examples/s]
Generating train split: 102003665 examples [1:50:02, 70226.28 examples/s]
Generating train split: 102011298 examples [1:50:02, 71932.29 examples/s]
Generating train split: 102018528 examples [1:50:02, 68880.48 examples/s]
Generating train split: 102025455 examples [1:50:02, 66453.37 examples/s]
Generating train split: 102032146 examples [1:50:02, 62725.97 examples/s]
Generating train split: 102038475 examples [1:50:03, 45036.90 examples/s]
Generating train split: 102043679 examples [1:50:03, 21823.07 examples/s]
Generating train split: 102047575 examples [1:50:04, 16227.56 examples/s]
Generating train split: 102050548 examples [1:50:04, 16032.87 examples/s]
Generating train split: 102053210 examples [1:50:04, 17337.13 examples/s]
Generating train split: 102055783 examples [1:50:04, 17697.69 examples/s]
Generating train split: 102058160 examples [1:50:04, 15495.60 examples/s]
Generating train split: 102060144 examples [1:50:05, 13421.98 examples/s]
Generating train split: 102063034 examples [1:50:05, 15976.05 examples/s]
Generating train split: 102065283 examples [1:50:05, 17180.01 examples/s]
Generating train split: 102067368 examples [1:50:05, 10153.52 examples/s]
Generating train split: 102069073 examples [1:50:05, 11135.48 examples/s]
Generating train split: 102070708 examples [1:50:06, 10051.11 examples/s]
Generating train split: 102072080 examples [1:50:06, 8190.95 examples/s] 
Generating train split: 102073617 examples [1:50:06, 9319.78 examples/s]
Generating train split: 102074857 examples [1:50:06, 6428.97 examples/s]
Generating train split: 102075983 examples [1:50:07, 7077.21 examples/s]
Generating train split: 102076977 examples [1:50:07, 6585.89 examples/s]
Generating train split: 102078325 examples [1:50:07, 7747.50 examples/s]
Generating train split: 102079317 examples [1:50:07, 5630.71 examples/s]
Generating train split: 102080108 examples [1:50:07, 5502.29 examples/s]
Generating train split: 102081798 examples [1:50:07, 7512.62 examples/s]
Generating train split: 102082800 examples [1:50:08, 6236.29 examples/s]
Generating train split: 102083621 examples [1:50:08, 6377.67 examples/s]
Generating train split: 102084410 examples [1:50:08, 6387.98 examples/s]
Generating train split: 102085551 examples [1:50:08, 7457.55 examples/s]
Generating train split: 102086411 examples [1:50:08, 6825.37 examples/s]
Generating train split: 102087783 examples [1:50:08, 8395.95 examples/s]
Generating train split: 102089896 examples [1:50:08, 11340.21 examples/s]
Generating train split: 102091158 examples [1:50:09, 9550.27 examples/s] 
Generating train split: 102092253 examples [1:50:09, 7213.73 examples/s]
Generating train split: 102093141 examples [1:50:09, 6720.75 examples/s]
Generating train split: 102093937 examples [1:50:09, 5496.23 examples/s]
Generating train split: 102094653 examples [1:50:09, 5800.18 examples/s]
Generating train split: 102095576 examples [1:50:09, 6465.70 examples/s]
Generating train split: 102096662 examples [1:50:09, 7462.55 examples/s]
Generating train split: 102103286 examples [1:50:10, 21851.08 examples/s]
Generating train split: 102110824 examples [1:50:10, 35076.83 examples/s]
Generating train split: 102114741 examples [1:50:10, 22005.00 examples/s]
Generating train split: 102117833 examples [1:50:11, 13792.52 examples/s]
Generating train split: 102124842 examples [1:50:11, 21409.25 examples/s]
Generating train split: 102132489 examples [1:50:11, 30162.61 examples/s]
Generating train split: 102137332 examples [1:50:12, 12029.05 examples/s]
Generating train split: 102140862 examples [1:50:12, 9843.19 examples/s] 
Generating train split: 102148755 examples [1:50:12, 15393.45 examples/s]
Generating train split: 102154411 examples [1:50:13, 19630.67 examples/s]
Generating train split: 102159066 examples [1:50:13, 13047.08 examples/s]
Generating train split: 102162525 examples [1:50:14, 9681.05 examples/s] 
Generating train split: 102165094 examples [1:50:14, 8799.11 examples/s]
Generating train split: 102167085 examples [1:50:15, 9289.71 examples/s]
Generating train split: 102168858 examples [1:50:15, 9227.45 examples/s]
Generating train split: 102170379 examples [1:50:15, 5690.11 examples/s]
Generating train split: 102171510 examples [1:50:16, 4698.17 examples/s]
Generating train split: 102172439 examples [1:50:16, 5085.65 examples/s]
Generating train split: 102173324 examples [1:50:16, 5387.67 examples/s]
Generating train split: 102174160 examples [1:50:16, 4471.30 examples/s]
Generating train split: 102180566 examples [1:50:17, 12125.19 examples/s]
Generating train split: 102188689 examples [1:50:17, 22835.32 examples/s]
Generating train split: 102192794 examples [1:50:17, 20047.52 examples/s]
Generating train split: 102196140 examples [1:50:18, 11559.99 examples/s]
Generating train split: 102198625 examples [1:50:18, 11038.07 examples/s]
Generating train split: 102200649 examples [1:50:18, 8400.58 examples/s] 
Generating train split: 102202198 examples [1:50:19, 7064.74 examples/s]
Generating train split: 102203534 examples [1:50:19, 7709.88 examples/s]
Generating train split: 102204782 examples [1:50:19, 8011.32 examples/s]
Generating train split: 102205948 examples [1:50:19, 5993.68 examples/s]
Generating train split: 102207699 examples [1:50:19, 7493.95 examples/s]
Generating train split: 102208861 examples [1:50:20, 7107.37 examples/s]
Generating train split: 102209852 examples [1:50:20, 6585.39 examples/s]
Generating train split: 102211089 examples [1:50:20, 7560.94 examples/s]
Generating train split: 102212061 examples [1:50:20, 7554.55 examples/s]
Generating train split: 102212971 examples [1:50:20, 5418.47 examples/s]
Generating train split: 102213692 examples [1:50:20, 5512.49 examples/s]
Generating train split: 102217651 examples [1:50:21, 11969.87 examples/s]
Generating train split: 102225957 examples [1:50:21, 27110.39 examples/s]
Generating train split: 102233294 examples [1:50:21, 37244.95 examples/s]
Generating train split: 102237898 examples [1:50:21, 16920.81 examples/s]
Generating train split: 102241341 examples [1:50:22, 10261.27 examples/s]
Generating train split: 102243894 examples [1:50:22, 10328.60 examples/s]
Generating train split: 102246002 examples [1:50:23, 10568.17 examples/s]
Generating train split: 102247823 examples [1:50:23, 8721.08 examples/s] 
Generating train split: 102255472 examples [1:50:23, 16530.41 examples/s]
Generating train split: 102264723 examples [1:50:23, 27270.29 examples/s]
Generating train split: 102269808 examples [1:50:24, 19159.49 examples/s]
Generating train split: 102273689 examples [1:50:24, 21274.17 examples/s]
Generating train split: 102277417 examples [1:50:24, 17989.30 examples/s]
Generating train split: 102280403 examples [1:50:25, 13023.32 examples/s]
Generating train split: 102282688 examples [1:50:25, 11791.31 examples/s]
Generating train split: 102284541 examples [1:50:25, 11416.23 examples/s]
Generating train split: 102286148 examples [1:50:25, 10645.94 examples/s]
Generating train split: 102287513 examples [1:50:26, 8554.66 examples/s] 
Generating train split: 102288604 examples [1:50:26, 7523.82 examples/s]
Generating train split: 102289519 examples [1:50:26, 5966.48 examples/s]
Generating train split: 102290513 examples [1:50:26, 6494.97 examples/s]
Generating train split: 102291590 examples [1:50:26, 7193.66 examples/s]
Generating train split: 102292696 examples [1:50:26, 7889.68 examples/s]
Generating train split: 102293642 examples [1:50:27, 5469.11 examples/s]
Generating train split: 102295301 examples [1:50:27, 7334.47 examples/s]
Generating train split: 102297075 examples [1:50:27, 9274.06 examples/s]
Generating train split: 102298301 examples [1:50:27, 8833.38 examples/s]
Generating train split: 102299405 examples [1:50:27, 6788.64 examples/s]
Generating train split: 102306926 examples [1:50:27, 19304.41 examples/s]
Generating train split: 102314917 examples [1:50:28, 31857.45 examples/s]
Generating train split: 102319340 examples [1:50:28, 18421.58 examples/s]
Generating train split: 102322702 examples [1:50:28, 15699.00 examples/s]
Generating train split: 102325378 examples [1:50:29, 12187.44 examples/s]
Generating train split: 102327463 examples [1:50:29, 10271.02 examples/s]
Generating train split: 102329536 examples [1:50:29, 11508.92 examples/s]
Generating train split: 102331299 examples [1:50:29, 9581.73 examples/s] 
Generating train split: 102332719 examples [1:50:30, 8045.67 examples/s]
Generating train split: 102334126 examples [1:50:30, 8823.70 examples/s]
Generating train split: 102335330 examples [1:50:30, 6468.64 examples/s]
Generating train split: 102336292 examples [1:50:30, 6881.88 examples/s]
Generating train split: 102337236 examples [1:50:30, 7109.56 examples/s]
Generating train split: 102338145 examples [1:50:31, 5162.22 examples/s]
Generating train split: 102338858 examples [1:50:31, 4710.01 examples/s]
Generating train split: 102339469 examples [1:50:31, 4794.26 examples/s]
Generating train split: 102340520 examples [1:50:31, 5830.97 examples/s]
Generating train split: 102341243 examples [1:50:32, 4271.95 examples/s]
Generating train split: 102341833 examples [1:50:32, 4545.88 examples/s]
Generating train split: 102342414 examples [1:50:32, 3760.99 examples/s]
Generating train split: 102342893 examples [1:50:32, 3115.65 examples/s]
Generating train split: 102343802 examples [1:50:32, 4059.89 examples/s]
Generating train split: 102344339 examples [1:50:32, 3868.41 examples/s]
Generating train split: 102344820 examples [1:50:33, 3405.75 examples/s]
Generating train split: 102345812 examples [1:50:33, 4601.96 examples/s]
Generating train split: 102348740 examples [1:50:33, 9854.04 examples/s]
Generating train split: 102357589 examples [1:50:33, 28187.86 examples/s]
Generating train split: 102363885 examples [1:50:33, 36860.75 examples/s]
Generating train split: 102368266 examples [1:50:33, 21114.41 examples/s]
Generating train split: 102371648 examples [1:50:34, 12821.71 examples/s]
Generating train split: 102374184 examples [1:50:34, 11772.89 examples/s]
Generating train split: 102376234 examples [1:50:35, 6045.27 examples/s] 
Generating train split: 102377737 examples [1:50:36, 6080.02 examples/s]
Generating train split: 102379142 examples [1:50:36, 6782.08 examples/s]
Generating train split: 102380421 examples [1:50:36, 5507.77 examples/s]
Generating train split: 102381411 examples [1:50:36, 5881.69 examples/s]
Generating train split: 102382364 examples [1:50:36, 5368.95 examples/s]
Generating train split: 102383158 examples [1:50:37, 4115.25 examples/s]
Generating train split: 102389957 examples [1:50:37, 11934.19 examples/s]
Generating train split: 102397977 examples [1:50:37, 22095.31 examples/s]
Generating train split: 102402108 examples [1:50:38, 11900.15 examples/s]
Generating train split: 102405167 examples [1:50:39, 6192.47 examples/s] 
Generating train split: 102407391 examples [1:50:40, 5008.88 examples/s]
Generating train split: 102411224 examples [1:50:40, 6963.50 examples/s]
Generating train split: 102418962 examples [1:50:40, 12408.46 examples/s]
Generating train split: 102424662 examples [1:50:40, 16840.30 examples/s]
Generating train split: 102429124 examples [1:50:41, 12882.77 examples/s]
Generating train split: 102432489 examples [1:50:41, 11985.96 examples/s]
Generating train split: 102435139 examples [1:50:41, 10931.57 examples/s]
Generating train split: 102437242 examples [1:50:41, 11658.92 examples/s]
Generating train split: 102439209 examples [1:50:42, 9714.73 examples/s] 
Generating train split: 102441193 examples [1:50:42, 10959.51 examples/s]
Generating train split: 102443154 examples [1:50:42, 12239.84 examples/s]
Generating train split: 102444909 examples [1:50:42, 8684.41 examples/s] 
Generating train split: 102446270 examples [1:50:43, 7948.02 examples/s]
Generating train split: 102447504 examples [1:50:43, 8589.49 examples/s]
Generating train split: 102448672 examples [1:50:43, 7677.83 examples/s]
Generating train split: 102450829 examples [1:50:43, 10069.78 examples/s]
Generating train split: 102452164 examples [1:50:43, 10395.07 examples/s]
Generating train split: 102453706 examples [1:50:43, 11307.82 examples/s]
Generating train split: 102455045 examples [1:50:44, 7581.01 examples/s] 
Generating train split: 102456095 examples [1:50:44, 7319.10 examples/s]
Generating train split: 102457213 examples [1:50:44, 7629.07 examples/s]
Generating train split: 102458136 examples [1:50:44, 4749.70 examples/s]
Generating train split: 102458839 examples [1:50:45, 4022.75 examples/s]
Generating train split: 102459406 examples [1:50:45, 3957.06 examples/s]
Generating train split: 102459920 examples [1:50:45, 2801.43 examples/s]
Generating train split: 102460495 examples [1:50:45, 3180.92 examples/s]
Generating train split: 102460940 examples [1:50:46, 2773.80 examples/s]
Generating train split: 102461313 examples [1:50:46, 2733.98 examples/s]
Generating train split: 102461926 examples [1:50:46, 3298.69 examples/s]
Generating train split: 102462487 examples [1:50:46, 3750.56 examples/s]
Generating train split: 102462944 examples [1:50:46, 3029.49 examples/s]
Generating train split: 102463330 examples [1:50:46, 2643.79 examples/s]
Generating train split: 102471572 examples [1:50:46, 17588.07 examples/s]
Generating train split: 102480269 examples [1:50:46, 32231.86 examples/s]
Generating train split: 102484768 examples [1:50:47, 17803.90 examples/s]
Generating train split: 102488173 examples [1:50:47, 15034.71 examples/s]
Generating train split: 102490865 examples [1:50:48, 13735.69 examples/s]
Generating train split: 102497569 examples [1:50:48, 20957.65 examples/s]
Generating train split: 102506351 examples [1:50:48, 31796.32 examples/s]
Generating train split: 102511475 examples [1:50:48, 18205.64 examples/s]
Generating train split: 102515316 examples [1:50:49, 12882.25 examples/s]
Generating train split: 102518199 examples [1:50:49, 10553.64 examples/s]
Generating train split: 102520398 examples [1:50:50, 8685.57 examples/s] 
Generating train split: 102522085 examples [1:50:50, 8114.83 examples/s]
Generating train split: 102523443 examples [1:50:51, 7172.12 examples/s]
Generating train split: 102524537 examples [1:50:51, 6510.78 examples/s]
Generating train split: 102525436 examples [1:50:51, 5444.62 examples/s]
Generating train split: 102526145 examples [1:50:51, 5423.58 examples/s]
Generating train split: 102526869 examples [1:50:51, 5671.79 examples/s]
Generating train split: 102527543 examples [1:50:51, 5647.26 examples/s]
Generating train split: 102528183 examples [1:50:52, 4131.02 examples/s]
Generating train split: 102529443 examples [1:50:52, 5472.76 examples/s]
Generating train split: 102530191 examples [1:50:52, 4481.81 examples/s]
Generating train split: 102530790 examples [1:50:52, 3400.50 examples/s]
Generating train split: 102531805 examples [1:50:53, 4211.23 examples/s]
Generating train split: 102532392 examples [1:50:53, 3990.56 examples/s]
Generating train split: 102533308 examples [1:50:53, 4853.78 examples/s]
Generating train split: 102533919 examples [1:50:53, 4173.62 examples/s]
Generating train split: 102534436 examples [1:50:53, 3651.01 examples/s]
Generating train split: 102534883 examples [1:50:54, 2901.32 examples/s]
Generating train split: 102536935 examples [1:50:54, 5833.46 examples/s]
Generating train split: 102537802 examples [1:50:54, 3743.83 examples/s]
Generating train split: 102539109 examples [1:50:54, 4999.32 examples/s]
Generating train split: 102539944 examples [1:50:55, 4303.42 examples/s]
Generating train split: 102540619 examples [1:50:55, 3896.78 examples/s]
Generating train split: 102541181 examples [1:50:55, 2875.17 examples/s]
Generating train split: 102542774 examples [1:50:55, 4601.49 examples/s]
Generating train split: 102543554 examples [1:50:55, 4823.18 examples/s]
Generating train split: 102544718 examples [1:50:55, 5956.69 examples/s]
Generating train split: 102545547 examples [1:50:56, 4862.19 examples/s]
Generating train split: 102546222 examples [1:50:56, 5141.33 examples/s]
Generating train split: 102546889 examples [1:50:56, 4009.67 examples/s]
Generating train split: 102547676 examples [1:50:56, 4622.21 examples/s]
Generating train split: 102548383 examples [1:50:56, 5000.25 examples/s]
Generating train split: 102549006 examples [1:50:57, 4625.27 examples/s]
Generating train split: 102549553 examples [1:50:57, 4570.91 examples/s]
Generating train split: 102550452 examples [1:50:57, 5556.50 examples/s]
Generating train split: 102551174 examples [1:50:57, 5870.90 examples/s]
Generating train split: 102551822 examples [1:50:57, 5778.03 examples/s]
Generating train split: 102552442 examples [1:50:57, 5424.17 examples/s]
Generating train split: 102553976 examples [1:50:57, 7921.47 examples/s]
Generating train split: 102555170 examples [1:50:57, 8804.78 examples/s]
Generating train split: 102556111 examples [1:50:58, 7164.95 examples/s]
Generating train split: 102558099 examples [1:50:58, 10166.35 examples/s]
Generating train split: 102559263 examples [1:50:58, 8295.82 examples/s] 
Generating train split: 102560956 examples [1:50:58, 10151.39 examples/s]
Generating train split: 102562367 examples [1:50:58, 11072.82 examples/s]
Generating train split: 102563621 examples [1:50:58, 10214.52 examples/s]
Generating train split: 102564755 examples [1:50:58, 7402.53 examples/s] 
Generating train split: 102565672 examples [1:50:59, 7009.71 examples/s]
Generating train split: 102567031 examples [1:50:59, 8348.19 examples/s]
Generating train split: 102569066 examples [1:50:59, 11050.52 examples/s]
Generating train split: 102570366 examples [1:50:59, 9720.56 examples/s] 
Generating train split: 102571506 examples [1:50:59, 8824.15 examples/s]
Generating train split: 102572510 examples [1:50:59, 7522.56 examples/s]
Generating train split: 102573369 examples [1:50:59, 6919.11 examples/s]
Generating train split: 102574312 examples [1:51:00, 7346.27 examples/s]
Generating train split: 102575115 examples [1:51:00, 5806.48 examples/s]
Generating train split: 102576015 examples [1:51:00, 6231.42 examples/s]
Generating train split: 102576716 examples [1:51:00, 5520.96 examples/s]
Generating train split: 102578710 examples [1:51:00, 8560.29 examples/s]
Generating train split: 102579736 examples [1:51:01, 4874.58 examples/s]
Generating train split: 102586833 examples [1:51:01, 14962.37 examples/s]
Generating train split: 102594946 examples [1:51:01, 26803.97 examples/s]
Generating train split: 102599252 examples [1:51:01, 22502.69 examples/s]
Generating train split: 102602760 examples [1:51:02, 10159.48 examples/s]
Generating train split: 102605336 examples [1:51:02, 10445.12 examples/s]
Generating train split: 102607497 examples [1:51:03, 8771.00 examples/s] 
Generating train split: 102609811 examples [1:51:03, 10268.01 examples/s]
Generating train split: 102612044 examples [1:51:03, 11828.53 examples/s]
Generating train split: 102614013 examples [1:51:03, 8784.90 examples/s] 
Generating train split: 102616301 examples [1:51:03, 10618.19 examples/s]
Generating train split: 102618055 examples [1:51:04, 8815.02 examples/s] 
Generating train split: 102619458 examples [1:51:04, 8160.46 examples/s]
Generating train split: 102620791 examples [1:51:04, 8895.81 examples/s]
Generating train split: 102622002 examples [1:51:04, 6860.44 examples/s]
Generating train split: 102623889 examples [1:51:04, 8686.26 examples/s]
Generating train split: 102625123 examples [1:51:05, 7794.42 examples/s]
Generating train split: 102626172 examples [1:51:05, 7407.64 examples/s]
Generating train split: 102627088 examples [1:51:05, 6978.99 examples/s]
Generating train split: 102628965 examples [1:51:05, 9242.84 examples/s]
Generating train split: 102630583 examples [1:51:05, 10622.36 examples/s]
Generating train split: 102631843 examples [1:51:05, 10075.96 examples/s]
Generating train split: 102632992 examples [1:51:06, 7899.67 examples/s] 
Generating train split: 102633945 examples [1:51:06, 8140.56 examples/s]
Generating train split: 102634892 examples [1:51:06, 8396.47 examples/s]
Generating train split: 102636428 examples [1:51:06, 10054.79 examples/s]
Generating train split: 102637547 examples [1:51:06, 7238.30 examples/s] 
Generating train split: 102638460 examples [1:51:06, 6552.45 examples/s]
Generating train split: 102639635 examples [1:51:06, 6988.15 examples/s]
Generating train split: 102640439 examples [1:51:07, 4761.75 examples/s]
Generating train split: 102642225 examples [1:51:07, 6907.23 examples/s]
Generating train split: 102643215 examples [1:51:07, 4680.58 examples/s]
Generating train split: 102644179 examples [1:51:07, 5396.49 examples/s]
Generating train split: 102644999 examples [1:51:08, 3712.75 examples/s]
Generating train split: 102645632 examples [1:51:08, 3794.48 examples/s]
Generating train split: 102646322 examples [1:51:08, 4205.93 examples/s]
Generating train split: 102646909 examples [1:51:08, 3911.75 examples/s]
Generating train split: 102647912 examples [1:51:08, 4992.75 examples/s]
Generating train split: 102648971 examples [1:51:08, 6130.85 examples/s]
Generating train split: 102649758 examples [1:51:09, 5590.19 examples/s]
Generating train split: 102650437 examples [1:51:09, 5556.50 examples/s]
Generating train split: 102651074 examples [1:51:09, 5152.40 examples/s]
Generating train split: 102655981 examples [1:51:09, 15043.93 examples/s]
Generating train split: 102665504 examples [1:51:09, 34561.83 examples/s]
Generating train split: 102671740 examples [1:51:09, 41730.03 examples/s]
Generating train split: 102676538 examples [1:51:10, 11557.87 examples/s]
Generating train split: 102680029 examples [1:51:11, 11284.04 examples/s]
Generating train split: 102682797 examples [1:51:11, 10315.17 examples/s]
Generating train split: 102684969 examples [1:51:11, 10665.86 examples/s]
Generating train split: 102686862 examples [1:51:11, 11585.65 examples/s]
Generating train split: 102688740 examples [1:51:12, 8501.79 examples/s] 
Generating train split: 102690175 examples [1:51:12, 8820.91 examples/s]
Generating train split: 102691866 examples [1:51:12, 9927.95 examples/s]
Generating train split: 102693282 examples [1:51:12, 9155.94 examples/s]
Generating train split: 102694492 examples [1:51:12, 8130.25 examples/s]
Generating train split: 102695542 examples [1:51:13, 8532.52 examples/s]
Generating train split: 102696575 examples [1:51:13, 7234.30 examples/s]
Generating train split: 102698891 examples [1:51:13, 10111.77 examples/s]
Generating train split: 102700167 examples [1:51:13, 8912.25 examples/s] 
Generating train split: 102701467 examples [1:51:13, 9678.66 examples/s]
Generating train split: 102702619 examples [1:51:13, 7137.44 examples/s]
Generating train split: 102703538 examples [1:51:14, 6590.02 examples/s]
Generating train split: 102704402 examples [1:51:14, 6907.41 examples/s]
Generating train split: 102705220 examples [1:51:14, 3969.17 examples/s]
Generating train split: 102706663 examples [1:51:14, 5441.91 examples/s]
Generating train split: 102707526 examples [1:51:14, 5890.62 examples/s]
Generating train split: 102708569 examples [1:51:14, 6754.15 examples/s]
Generating train split: 102709480 examples [1:51:15, 5917.18 examples/s]
Generating train split: 102710570 examples [1:51:15, 6891.98 examples/s]
Generating train split: 102711429 examples [1:51:15, 4983.95 examples/s]
Generating train split: 102712129 examples [1:51:15, 4875.78 examples/s]
Generating train split: 102713208 examples [1:51:15, 5955.04 examples/s]
Generating train split: 102713976 examples [1:51:15, 5876.67 examples/s]
Generating train split: 102715316 examples [1:51:16, 7524.74 examples/s]
Generating train split: 102716205 examples [1:51:16, 3987.28 examples/s]
Generating train split: 102717045 examples [1:51:16, 4609.91 examples/s]
Generating train split: 102717771 examples [1:51:16, 3837.85 examples/s]
Generating train split: 102718794 examples [1:51:17, 4777.33 examples/s]
Generating train split: 102719489 examples [1:51:17, 4682.98 examples/s]
Generating train split: 102720104 examples [1:51:17, 3598.96 examples/s]
Generating train split: 102721613 examples [1:51:17, 5375.31 examples/s]
Generating train split: 102722368 examples [1:51:17, 4419.08 examples/s]
Generating train split: 102723220 examples [1:51:18, 5051.11 examples/s]
Generating train split: 102723885 examples [1:51:18, 5252.36 examples/s]
Generating train split: 102724534 examples [1:51:18, 4569.33 examples/s]
Generating train split: 102725096 examples [1:51:18, 4770.93 examples/s]
Generating train split: 102725656 examples [1:51:18, 3868.19 examples/s]
Generating train split: 102726397 examples [1:51:18, 4012.91 examples/s]
Generating train split: 102727467 examples [1:51:18, 5345.00 examples/s]
Generating train split: 102728164 examples [1:51:19, 5702.31 examples/s]
Generating train split: 102728819 examples [1:51:19, 5426.39 examples/s]
Generating train split: 102729461 examples [1:51:19, 5652.72 examples/s]
Generating train split: 102730078 examples [1:51:19, 4481.06 examples/s]
Generating train split: 102730595 examples [1:51:19, 3777.94 examples/s]
Generating train split: 102732215 examples [1:51:19, 6311.49 examples/s]
Generating train split: 102733011 examples [1:51:19, 6473.40 examples/s]
Generating train split: 102733784 examples [1:51:20, 6393.85 examples/s]
Generating train split: 102742033 examples [1:51:20, 24877.20 examples/s]
Generating train split: 102750603 examples [1:51:20, 38626.50 examples/s]
Generating train split: 102754843 examples [1:51:20, 17036.18 examples/s]
Generating train split: 102758028 examples [1:51:21, 14098.31 examples/s]
Generating train split: 102760523 examples [1:51:21, 12521.47 examples/s]
Generating train split: 102762533 examples [1:51:21, 13000.18 examples/s]
Generating train split: 102764405 examples [1:51:21, 13855.43 examples/s]
Generating train split: 102766902 examples [1:51:21, 15793.61 examples/s]
Generating train split: 102768966 examples [1:51:22, 13800.85 examples/s]
Generating train split: 102776958 examples [1:51:22, 26428.10 examples/s]
Generating train split: 102785383 examples [1:51:22, 38818.25 examples/s]
Generating train split: 102790444 examples [1:51:22, 22543.12 examples/s]
Generating train split: 102794316 examples [1:51:23, 13410.44 examples/s]
Generating train split: 102797600 examples [1:51:23, 15454.54 examples/s]
Generating train split: 102800606 examples [1:51:23, 16317.95 examples/s]
Generating train split: 102803325 examples [1:51:24, 8002.67 examples/s] 
Generating train split: 102805315 examples [1:51:24, 8640.39 examples/s]
Generating train split: 102807095 examples [1:51:24, 9596.92 examples/s]
Generating train split: 102808876 examples [1:51:25, 6654.73 examples/s]
Generating train split: 102810230 examples [1:51:25, 5490.13 examples/s]
Generating train split: 102811325 examples [1:51:25, 6021.56 examples/s]
Generating train split: 102812373 examples [1:51:26, 4593.32 examples/s]
Generating train split: 102813174 examples [1:51:26, 4254.60 examples/s]
Generating train split: 102813837 examples [1:51:26, 3513.24 examples/s]
Generating train split: 102814598 examples [1:51:27, 3990.13 examples/s]
Generating train split: 102815194 examples [1:51:27, 3609.97 examples/s]
Generating train split: 102815686 examples [1:51:27, 3468.80 examples/s]
Generating train split: 102823589 examples [1:51:27, 15617.18 examples/s]
Generating train split: 102831138 examples [1:51:27, 26794.12 examples/s]
Generating train split: 102835276 examples [1:51:27, 26722.60 examples/s]
Generating train split: 102838972 examples [1:51:28, 15656.05 examples/s]
Generating train split: 102841778 examples [1:51:28, 12100.43 examples/s]
Generating train split: 102849244 examples [1:51:28, 19784.45 examples/s]
Generating train split: 102858046 examples [1:51:28, 29967.41 examples/s]
Generating train split: 102863316 examples [1:51:29, 28559.06 examples/s]
Generating train split: 102867768 examples [1:51:29, 15544.32 examples/s]
Generating train split: 102871091 examples [1:51:30, 8118.04 examples/s] 
Generating train split: 102873501 examples [1:51:31, 7494.70 examples/s]
Generating train split: 102875350 examples [1:51:31, 7673.66 examples/s]
Generating train split: 102876908 examples [1:51:32, 5289.95 examples/s]
Generating train split: 102878059 examples [1:51:32, 4695.84 examples/s]
Generating train split: 102878967 examples [1:51:32, 4563.45 examples/s]
Generating train split: 102880038 examples [1:51:33, 5122.96 examples/s]
Generating train split: 102882588 examples [1:51:33, 7499.01 examples/s]
Generating train split: 102885032 examples [1:51:33, 9910.39 examples/s]
Generating train split: 102886705 examples [1:51:33, 7490.41 examples/s]
Generating train split: 102888006 examples [1:51:33, 7133.07 examples/s]
Generating train split: 102889098 examples [1:51:34, 5537.41 examples/s]
Generating train split: 102889958 examples [1:51:34, 5780.98 examples/s]
Generating train split: 102890783 examples [1:51:34, 4512.47 examples/s]
Generating train split: 102891947 examples [1:51:34, 5506.15 examples/s]
Generating train split: 102893380 examples [1:51:34, 6966.15 examples/s]
Generating train split: 102894376 examples [1:51:35, 4287.32 examples/s]
Generating train split: 102895769 examples [1:51:35, 5584.76 examples/s]
Generating train split: 102897869 examples [1:51:35, 8039.74 examples/s]
Generating train split: 102899146 examples [1:51:35, 6250.33 examples/s]
Generating train split: 102900158 examples [1:51:36, 5457.96 examples/s]
Generating train split: 102900981 examples [1:51:36, 4830.80 examples/s]
Generating train split: 102903623 examples [1:51:36, 8077.85 examples/s]
Generating train split: 102904897 examples [1:51:36, 8867.09 examples/s]
Generating train split: 102906157 examples [1:51:37, 6130.92 examples/s]
Generating train split: 102907521 examples [1:51:37, 7187.12 examples/s]
Generating train split: 102908592 examples [1:51:37, 7755.03 examples/s]
Generating train split: 102909650 examples [1:51:37, 5859.43 examples/s]
Generating train split: 102910496 examples [1:51:37, 5358.88 examples/s]
Generating train split: 102911214 examples [1:51:38, 3658.45 examples/s]
Generating train split: 102912431 examples [1:51:38, 4810.76 examples/s]
Generating train split: 102913216 examples [1:51:38, 5256.58 examples/s]
Generating train split: 102914060 examples [1:51:38, 5802.65 examples/s]
Generating train split: 102914834 examples [1:51:38, 4761.44 examples/s]
Generating train split: 102915588 examples [1:51:38, 5268.03 examples/s]
Generating train split: 102916261 examples [1:51:38, 5257.44 examples/s]
Generating train split: 102917010 examples [1:51:39, 5746.67 examples/s]
Generating train split: 102917808 examples [1:51:39, 6214.99 examples/s]
Generating train split: 102918505 examples [1:51:39, 5675.22 examples/s]
Generating train split: 102919658 examples [1:51:39, 7018.84 examples/s]
Generating train split: 102920432 examples [1:51:39, 5319.34 examples/s]
Generating train split: 102921372 examples [1:51:39, 6168.96 examples/s]
Generating train split: 102922099 examples [1:51:40, 4796.97 examples/s]
Generating train split: 102922702 examples [1:51:40, 4943.87 examples/s]
Generating train split: 102923321 examples [1:51:40, 5214.49 examples/s]
Generating train split: 102924113 examples [1:51:40, 5752.31 examples/s]
Generating train split: 102924750 examples [1:51:40, 4143.83 examples/s]
Generating train split: 102929213 examples [1:51:40, 12245.53 examples/s]
Generating train split: 102937731 examples [1:51:40, 28454.06 examples/s]
Generating train split: 102943243 examples [1:51:40, 34547.91 examples/s]
Generating train split: 102947463 examples [1:51:41, 14639.72 examples/s]
Generating train split: 102950606 examples [1:51:41, 13950.50 examples/s]
Generating train split: 102953165 examples [1:51:42, 10427.01 examples/s]
Generating train split: 102955122 examples [1:51:42, 11264.85 examples/s]
Generating train split: 102957003 examples [1:51:42, 9826.48 examples/s] 
Generating train split: 102958517 examples [1:51:43, 8001.35 examples/s]
Generating train split: 102959717 examples [1:51:43, 7126.26 examples/s]
Generating train split: 102960910 examples [1:51:43, 7648.66 examples/s]
Generating train split: 102961922 examples [1:51:43, 7216.11 examples/s]
Generating train split: 102962804 examples [1:51:43, 6741.12 examples/s]
Generating train split: 102964101 examples [1:51:43, 7836.10 examples/s]
Generating train split: 102965036 examples [1:51:44, 5337.05 examples/s]
Generating train split: 102965769 examples [1:51:44, 4995.82 examples/s]
Generating train split: 102966586 examples [1:51:44, 5206.25 examples/s]
Generating train split: 102967216 examples [1:51:44, 3846.34 examples/s]
Generating train split: 102974296 examples [1:51:44, 14375.35 examples/s]
Generating train split: 102982396 examples [1:51:45, 26595.06 examples/s]
Generating train split: 102986559 examples [1:51:45, 16131.24 examples/s]
Generating train split: 102989718 examples [1:51:46, 11943.97 examples/s]
Generating train split: 102992131 examples [1:51:46, 10891.36 examples/s]
Generating train split: 102994063 examples [1:51:46, 9894.18 examples/s] 
Generating train split: 102995632 examples [1:51:46, 8597.46 examples/s]
Generating train split: 102996899 examples [1:51:47, 8931.69 examples/s]
Generating train split: 102998737 examples [1:51:47, 10332.99 examples/s]
Generating train split: 103000146 examples [1:51:47, 9166.02 examples/s] 
Generating train split: 103001898 examples [1:51:47, 10602.51 examples/s]
Generating train split: 103003248 examples [1:51:47, 8311.73 examples/s] 
Generating train split: 103004346 examples [1:51:47, 7060.80 examples/s]
Generating train split: 103005313 examples [1:51:48, 7488.38 examples/s]
Generating train split: 103006236 examples [1:51:48, 6535.48 examples/s]
Generating train split: 103008239 examples [1:51:48, 9043.70 examples/s]
Generating train split: 103009384 examples [1:51:48, 5785.91 examples/s]
Generating train split: 103010512 examples [1:51:48, 6617.38 examples/s]
Generating train split: 103011475 examples [1:51:48, 7158.52 examples/s]
Generating train split: 103012437 examples [1:51:49, 6638.27 examples/s]
Generating train split: 103013273 examples [1:51:49, 5937.49 examples/s]
Generating train split: 103013991 examples [1:51:49, 4845.87 examples/s]
Generating train split: 103014819 examples [1:51:49, 5369.22 examples/s]
Generating train split: 103015466 examples [1:51:50, 3300.55 examples/s]
Generating train split: 103021287 examples [1:51:50, 11297.98 examples/s]
Generating train split: 103024592 examples [1:51:50, 15043.57 examples/s]
Generating train split: 103027048 examples [1:51:51, 5433.85 examples/s] 
Generating train split: 103028829 examples [1:51:51, 6452.02 examples/s]
Generating train split: 103030600 examples [1:51:52, 4511.92 examples/s]
Generating train split: 103031912 examples [1:51:52, 3840.52 examples/s]
Generating train split: 103032903 examples [1:51:53, 3395.30 examples/s]
Generating train split: 103033664 examples [1:51:54, 2513.81 examples/s]
Generating train split: 103034230 examples [1:51:54, 1973.94 examples/s]
Generating train split: 103036787 examples [1:51:54, 3616.99 examples/s]
Generating train split: 103039949 examples [1:51:54, 6137.95 examples/s]
Generating train split: 103041629 examples [1:51:55, 6284.52 examples/s]
Generating train split: 103043002 examples [1:51:55, 4866.72 examples/s]
Generating train split: 103044408 examples [1:51:55, 5837.43 examples/s]
Generating train split: 103045562 examples [1:51:56, 5188.73 examples/s]
Generating train split: 103050548 examples [1:51:56, 10935.61 examples/s]
Generating train split: 103058154 examples [1:51:56, 20661.08 examples/s]
Generating train split: 103061696 examples [1:51:56, 16517.70 examples/s]
Generating train split: 103064494 examples [1:51:56, 14926.25 examples/s]
Generating train split: 103066797 examples [1:51:57, 11523.75 examples/s]
Generating train split: 103068604 examples [1:51:57, 10073.19 examples/s]
Generating train split: 103075328 examples [1:51:57, 17759.73 examples/s]
Generating train split: 103084689 examples [1:51:57, 29978.77 examples/s]
Generating train split: 103089627 examples [1:51:57, 31591.39 examples/s]
Generating train split: 103094193 examples [1:51:58, 16063.61 examples/s]
Generating train split: 103097593 examples [1:51:58, 16396.46 examples/s]
Generating train split: 103100501 examples [1:51:58, 13327.14 examples/s]
Generating train split: 103102776 examples [1:51:59, 12333.95 examples/s]
Generating train split: 103104651 examples [1:51:59, 10144.74 examples/s]
Generating train split: 103106619 examples [1:51:59, 11330.90 examples/s]
Generating train split: 103114026 examples [1:51:59, 20811.68 examples/s]
Generating train split: 103121962 examples [1:51:59, 31206.35 examples/s]
Generating train split: 103126701 examples [1:52:00, 22555.38 examples/s]
Generating train split: 103130408 examples [1:52:00, 20457.92 examples/s]
Generating train split: 103133772 examples [1:52:00, 22532.58 examples/s]
Generating train split: 103137325 examples [1:52:00, 24914.80 examples/s]
Generating train split: 103141070 examples [1:52:00, 27511.63 examples/s]
Generating train split: 103144490 examples [1:52:00, 27189.13 examples/s]
Generating train split: 103149633 examples [1:52:00, 32860.14 examples/s]
Generating train split: 103154081 examples [1:52:01, 35765.36 examples/s]
Generating train split: 103158395 examples [1:52:01, 37683.27 examples/s]
Generating train split: 103164450 examples [1:52:01, 43916.76 examples/s]
Generating train split: 103170324 examples [1:52:01, 48077.02 examples/s]
Generating train split: 103178042 examples [1:52:01, 56395.78 examples/s]
Generating train split: 103183879 examples [1:52:01, 56316.20 examples/s]
Generating train split: 103191206 examples [1:52:01, 61232.86 examples/s]
Generating train split: 103198321 examples [1:52:01, 64108.44 examples/s]
Generating train split: 103206355 examples [1:52:01, 68894.16 examples/s]
Generating train split: 103213648 examples [1:52:02, 70068.94 examples/s]
Generating train split: 103220938 examples [1:52:02, 70872.92 examples/s]
Generating train split: 103228394 examples [1:52:02, 71956.09 examples/s]
Generating train split: 103235616 examples [1:52:02, 71770.20 examples/s]
Generating train split: 103243531 examples [1:52:02, 73967.15 examples/s]
Generating train split: 103251558 examples [1:52:02, 75848.27 examples/s]
Generating train split: 103259520 examples [1:52:02, 76956.41 examples/s]
Generating train split: 103267878 examples [1:52:02, 78938.53 examples/s]
Generating train split: 103275782 examples [1:52:02, 76915.80 examples/s]
Generating train split: 103283553 examples [1:52:02, 76329.40 examples/s]
Generating train split: 103291197 examples [1:52:03, 75525.62 examples/s]
Generating train split: 103299444 examples [1:52:03, 77534.78 examples/s]
Generating train split: 103307218 examples [1:52:03, 76877.06 examples/s]
Generating train split: 103315656 examples [1:52:03, 79058.04 examples/s]
Generating train split: 103323580 examples [1:52:03, 74606.91 examples/s]
Generating train split: 103331342 examples [1:52:03, 75445.36 examples/s]
Generating train split: 103338938 examples [1:52:03, 72181.61 examples/s]
Generating train split: 103346212 examples [1:52:03, 68715.52 examples/s]
Generating train split: 103353143 examples [1:52:03, 60184.04 examples/s]
Generating train split: 103359379 examples [1:52:04, 49683.01 examples/s]
Generating train split: 103364734 examples [1:52:04, 41427.02 examples/s]
Generating train split: 103369304 examples [1:52:04, 32968.10 examples/s]
Generating train split: 103373098 examples [1:52:04, 25258.71 examples/s]
Generating train split: 103376168 examples [1:52:04, 24627.84 examples/s]
Generating train split: 103379397 examples [1:52:05, 26021.61 examples/s]
Generating train split: 103382335 examples [1:52:05, 24618.99 examples/s]
Generating train split: 103385186 examples [1:52:05, 25429.48 examples/s]
Generating train split: 103387920 examples [1:52:05, 23881.13 examples/s]
Generating train split: 103390442 examples [1:52:05, 19160.34 examples/s]
Generating train split: 103392575 examples [1:52:05, 17357.14 examples/s]
Generating train split: 103394465 examples [1:52:06, 14269.32 examples/s]
Generating train split: 103396049 examples [1:52:06, 11841.14 examples/s]
Generating train split: 103397379 examples [1:52:06, 9401.76 examples/s] 
Generating train split: 103398477 examples [1:52:06, 8765.29 examples/s]
Generating train split: 103400138 examples [1:52:06, 10142.52 examples/s]
Generating train split: 103401312 examples [1:52:06, 8593.65 examples/s] 
Generating train split: 103402364 examples [1:52:07, 8961.18 examples/s]
Generating train split: 103403387 examples [1:52:07, 9212.45 examples/s]
Generating train split: 103404875 examples [1:52:07, 10546.47 examples/s]
Generating train split: 103406038 examples [1:52:07, 8798.59 examples/s] 
Generating train split: 103407337 examples [1:52:07, 9727.01 examples/s]
Generating train split: 103408574 examples [1:52:07, 10352.19 examples/s]
Generating train split: 103409702 examples [1:52:07, 8550.07 examples/s] 
Generating train split: 103410670 examples [1:52:07, 8702.43 examples/s]
Generating train split: 103411623 examples [1:52:08, 7377.12 examples/s]
Generating train split: 103414226 examples [1:52:08, 11561.11 examples/s]
Generating train split: 103415595 examples [1:52:08, 11425.83 examples/s]
Generating train split: 103416877 examples [1:52:08, 11116.39 examples/s]
Generating train split: 103423973 examples [1:52:08, 26067.53 examples/s]
Generating train split: 103434478 examples [1:52:08, 46833.12 examples/s]
Generating train split: 103439718 examples [1:52:08, 33915.58 examples/s]
Generating train split: 103443994 examples [1:52:09, 22818.36 examples/s]
Generating train split: 103450566 examples [1:52:09, 29830.66 examples/s]
Generating train split: 103459024 examples [1:52:09, 40190.31 examples/s]
Generating train split: 103464585 examples [1:52:09, 28150.46 examples/s]
Generating train split: 103468945 examples [1:52:10, 18778.57 examples/s]
Generating train split: 103472267 examples [1:52:10, 19444.01 examples/s]
Generating train split: 103475273 examples [1:52:10, 14506.17 examples/s]
Generating train split: 103478311 examples [1:52:11, 16490.95 examples/s]
Generating train split: 103480859 examples [1:52:11, 16109.02 examples/s]
Generating train split: 103483087 examples [1:52:11, 15732.04 examples/s]
Generating train split: 103486483 examples [1:52:11, 18766.98 examples/s]
Generating train split: 103488853 examples [1:52:11, 19213.55 examples/s]
Generating train split: 103491132 examples [1:52:11, 17174.60 examples/s]
Generating train split: 103493125 examples [1:52:11, 13842.69 examples/s]
Generating train split: 103494772 examples [1:52:12, 11659.77 examples/s]
Generating train split: 103496455 examples [1:52:12, 12374.04 examples/s]
Generating train split: 103497884 examples [1:52:12, 12351.01 examples/s]
Generating train split: 103499248 examples [1:52:12, 9688.19 examples/s] 
Generating train split: 103500376 examples [1:52:12, 7197.22 examples/s]
Generating train split: 103501284 examples [1:52:13, 6347.31 examples/s]
Generating train split: 103502921 examples [1:52:13, 7944.90 examples/s]
Generating train split: 103503931 examples [1:52:13, 7897.76 examples/s]
Generating train split: 103506477 examples [1:52:13, 11486.85 examples/s]
Generating train split: 103507901 examples [1:52:13, 9277.33 examples/s] 
Generating train split: 103509076 examples [1:52:13, 8769.54 examples/s]
Generating train split: 103510128 examples [1:52:14, 8252.27 examples/s]
Generating train split: 103511813 examples [1:52:14, 9958.08 examples/s]
Generating train split: 103512962 examples [1:52:14, 8961.57 examples/s]
Generating train split: 103514046 examples [1:52:14, 9225.37 examples/s]
Generating train split: 103515252 examples [1:52:14, 9891.34 examples/s]
Generating train split: 103516322 examples [1:52:14, 9841.52 examples/s]
Generating train split: 103517374 examples [1:52:14, 7139.07 examples/s]
Generating train split: 103518227 examples [1:52:15, 6728.73 examples/s]
Generating train split: 103519045 examples [1:52:15, 7035.70 examples/s]
Generating train split: 103520875 examples [1:52:15, 9646.40 examples/s]
Generating train split: 103521975 examples [1:52:15, 5821.23 examples/s]
Generating train split: 103522833 examples [1:52:15, 5963.33 examples/s]
Generating train split: 103524506 examples [1:52:15, 7982.54 examples/s]
Generating train split: 103526135 examples [1:52:15, 9741.85 examples/s]
Generating train split: 103527360 examples [1:52:16, 6617.31 examples/s]
Generating train split: 103528334 examples [1:52:16, 6521.00 examples/s]
Generating train split: 103529873 examples [1:52:16, 8147.96 examples/s]
Generating train split: 103530933 examples [1:52:16, 6232.68 examples/s]
Generating train split: 103531862 examples [1:52:16, 6207.81 examples/s]
Generating train split: 103533375 examples [1:52:17, 7885.44 examples/s]
Generating train split: 103534375 examples [1:52:17, 8202.87 examples/s]
Generating train split: 103535427 examples [1:52:17, 8658.77 examples/s]
Generating train split: 103536418 examples [1:52:17, 7394.11 examples/s]
Generating train split: 103537278 examples [1:52:17, 6259.71 examples/s]
Generating train split: 103538006 examples [1:52:17, 6047.36 examples/s]
Generating train split: 103539691 examples [1:52:17, 8362.38 examples/s]
Generating train split: 103540724 examples [1:52:18, 8800.20 examples/s]
Generating train split: 103542412 examples [1:52:18, 10148.19 examples/s]
Generating train split: 103543509 examples [1:52:18, 6194.79 examples/s] 
Generating train split: 103544679 examples [1:52:18, 7082.72 examples/s]
Generating train split: 103545612 examples [1:52:18, 5622.00 examples/s]
Generating train split: 103546368 examples [1:52:19, 5839.10 examples/s]
Generating train split: 103548095 examples [1:52:19, 8091.34 examples/s]
Generating train split: 103549349 examples [1:52:19, 9053.15 examples/s]
Generating train split: 103550803 examples [1:52:19, 10337.61 examples/s]
Generating train split: 103551999 examples [1:52:19, 9858.12 examples/s] 
Generating train split: 103553101 examples [1:52:20, 4680.40 examples/s]
Generating train split: 103554824 examples [1:52:20, 6436.31 examples/s]
Generating train split: 103555923 examples [1:52:20, 7193.55 examples/s]
Generating train split: 103557014 examples [1:52:20, 7337.98 examples/s]
Generating train split: 103559546 examples [1:52:20, 10989.30 examples/s]
Generating train split: 103561004 examples [1:52:20, 8914.32 examples/s] 
Generating train split: 103562216 examples [1:52:20, 7071.71 examples/s]
Generating train split: 103563200 examples [1:52:21, 7183.22 examples/s]
Generating train split: 103564106 examples [1:52:21, 6565.01 examples/s]
Generating train split: 103565298 examples [1:52:21, 7565.69 examples/s]
Generating train split: 103566324 examples [1:52:21, 7976.88 examples/s]
Generating train split: 103567238 examples [1:52:22, 4069.69 examples/s]
Generating train split: 103568044 examples [1:52:22, 4602.41 examples/s]
Generating train split: 103569992 examples [1:52:22, 7055.72 examples/s]
Generating train split: 103571197 examples [1:52:22, 7904.16 examples/s]
Generating train split: 103572295 examples [1:52:22, 5822.41 examples/s]
Generating train split: 103573175 examples [1:52:22, 5806.87 examples/s]
Generating train split: 103573981 examples [1:52:22, 5978.79 examples/s]
Generating train split: 103574728 examples [1:52:23, 5353.60 examples/s]
Generating train split: 103575376 examples [1:52:23, 5530.91 examples/s]
Generating train split: 103576576 examples [1:52:23, 6939.22 examples/s]
Generating train split: 103577386 examples [1:52:23, 6778.63 examples/s]
Generating train split: 103578265 examples [1:52:23, 7109.38 examples/s]
Generating train split: 103579036 examples [1:52:23, 6562.15 examples/s]
Generating train split: 103581767 examples [1:52:23, 11662.55 examples/s]
Generating train split: 103583081 examples [1:52:24, 9031.40 examples/s] 
Generating train split: 103584179 examples [1:52:24, 7500.58 examples/s]
Generating train split: 103585293 examples [1:52:24, 7948.29 examples/s]
Generating train split: 103586236 examples [1:52:24, 7811.09 examples/s]
Generating train split: 103587111 examples [1:52:24, 5268.11 examples/s]
Generating train split: 103587809 examples [1:52:24, 5561.29 examples/s]
Generating train split: 103588586 examples [1:52:25, 5998.83 examples/s]
Generating train split: 103589302 examples [1:52:25, 5501.79 examples/s]
Generating train split: 103589937 examples [1:52:25, 5282.16 examples/s]
Generating train split: 103592786 examples [1:52:25, 10478.76 examples/s]
Generating train split: 103601477 examples [1:52:25, 29003.84 examples/s]
Generating train split: 103607078 examples [1:52:25, 35943.74 examples/s]
Generating train split: 103611205 examples [1:52:26, 21193.33 examples/s]
Generating train split: 103614426 examples [1:52:26, 16525.61 examples/s]
Generating train split: 103616975 examples [1:52:27, 9475.07 examples/s] 
Generating train split: 103618881 examples [1:52:27, 6612.56 examples/s]
Generating train split: 103620294 examples [1:52:27, 6548.40 examples/s]
Generating train split: 103621471 examples [1:52:28, 6548.86 examples/s]
Generating train split: 103622492 examples [1:52:28, 5513.79 examples/s]
Generating train split: 103630481 examples [1:52:28, 14168.93 examples/s]
Generating train split: 103639425 examples [1:52:28, 24897.79 examples/s]
Generating train split: 103644182 examples [1:52:29, 13883.62 examples/s]
Generating train split: 103648576 examples [1:52:29, 17026.10 examples/s]
Generating train split: 103656854 examples [1:52:29, 25570.60 examples/s]
Generating train split: 103662257 examples [1:52:29, 29959.17 examples/s]
Generating train split: 103667451 examples [1:52:30, 11095.47 examples/s]
Generating train split: 103671212 examples [1:52:31, 9137.32 examples/s] 
Generating train split: 103674021 examples [1:52:32, 8392.98 examples/s]
Generating train split: 103676181 examples [1:52:32, 8033.58 examples/s]
Generating train split: 103677898 examples [1:52:32, 8084.57 examples/s]
Generating train split: 103679343 examples [1:52:32, 7426.47 examples/s]
Generating train split: 103680523 examples [1:52:32, 7809.31 examples/s]
Generating train split: 103681670 examples [1:52:33, 8174.65 examples/s]
Generating train split: 103689026 examples [1:52:33, 18486.40 examples/s]
Generating train split: 103697419 examples [1:52:33, 29782.74 examples/s]
Generating train split: 103701736 examples [1:52:33, 19099.77 examples/s]
Generating train split: 103705048 examples [1:52:33, 17789.57 examples/s]
Generating train split: 103707800 examples [1:52:34, 12630.64 examples/s]
Generating train split: 103709914 examples [1:52:34, 12596.35 examples/s]
Generating train split: 103711765 examples [1:52:34, 9369.12 examples/s] 
Generating train split: 103713204 examples [1:52:35, 7268.65 examples/s]
Generating train split: 103714312 examples [1:52:35, 6723.87 examples/s]
Generating train split: 103715237 examples [1:52:35, 6455.34 examples/s]
Generating train split: 103717058 examples [1:52:35, 8073.18 examples/s]
Generating train split: 103718162 examples [1:52:36, 7700.12 examples/s]
Generating train split: 103720288 examples [1:52:36, 10073.46 examples/s]
Generating train split: 103721934 examples [1:52:36, 11344.21 examples/s]
Generating train split: 103723367 examples [1:52:36, 7538.14 examples/s] 
Generating train split: 103725516 examples [1:52:36, 9836.39 examples/s]
Generating train split: 103726935 examples [1:52:36, 8009.34 examples/s]
Generating train split: 103728083 examples [1:52:37, 8013.35 examples/s]
Generating train split: 103729125 examples [1:52:37, 8061.27 examples/s]
Generating train split: 103730413 examples [1:52:37, 9020.80 examples/s]
Generating train split: 103731500 examples [1:52:37, 9391.92 examples/s]
Generating train split: 103732572 examples [1:52:37, 5505.83 examples/s]
Generating train split: 103733459 examples [1:52:37, 6030.11 examples/s]
Generating train split: 103734303 examples [1:52:38, 5312.34 examples/s]
Generating train split: 103735015 examples [1:52:38, 5024.16 examples/s]
Generating train split: 103735970 examples [1:52:38, 5784.67 examples/s]
Generating train split: 103736683 examples [1:52:38, 5978.02 examples/s]
Generating train split: 103737381 examples [1:52:38, 4043.99 examples/s]
Generating train split: 103739076 examples [1:52:38, 6285.21 examples/s]
Generating train split: 103740254 examples [1:52:39, 7376.21 examples/s]
Generating train split: 103741758 examples [1:52:39, 9057.11 examples/s]
Generating train split: 103743657 examples [1:52:39, 11439.84 examples/s]
Generating train split: 103745017 examples [1:52:39, 9047.57 examples/s] 
Generating train split: 103746152 examples [1:52:39, 6719.01 examples/s]
Generating train split: 103747062 examples [1:52:40, 5403.72 examples/s]
Generating train split: 103748835 examples [1:52:40, 7390.31 examples/s]
Generating train split: 103749882 examples [1:52:40, 5895.53 examples/s]
Generating train split: 103751150 examples [1:52:40, 6991.30 examples/s]
Generating train split: 103752119 examples [1:52:40, 5324.80 examples/s]
Generating train split: 103752887 examples [1:52:41, 5222.03 examples/s]
Generating train split: 103753577 examples [1:52:41, 5108.51 examples/s]
Generating train split: 103754585 examples [1:52:41, 6036.71 examples/s]
Generating train split: 103755343 examples [1:52:41, 6359.88 examples/s]
Generating train split: 103756095 examples [1:52:41, 5777.82 examples/s]
Generating train split: 103757337 examples [1:52:41, 7265.27 examples/s]
Generating train split: 103758183 examples [1:52:41, 6287.36 examples/s]
Generating train split: 103764866 examples [1:52:41, 19830.74 examples/s]
Generating train split: 103773866 examples [1:52:42, 36814.49 examples/s]
Generating train split: 103779131 examples [1:52:42, 38461.69 examples/s]
Generating train split: 103783520 examples [1:52:42, 21304.44 examples/s]
Generating train split: 103786895 examples [1:52:43, 11994.25 examples/s]
Generating train split: 103789539 examples [1:52:43, 13536.16 examples/s]
Generating train split: 103792089 examples [1:52:43, 9777.78 examples/s] 
Generating train split: 103794024 examples [1:52:44, 10434.89 examples/s]
Generating train split: 103795812 examples [1:52:44, 8621.74 examples/s] 
Generating train split: 103797319 examples [1:52:44, 9413.36 examples/s]
Generating train split: 103798754 examples [1:52:44, 6544.89 examples/s]
Generating train split: 103800723 examples [1:52:45, 8141.07 examples/s]
Generating train split: 103802083 examples [1:52:45, 7259.83 examples/s]
Generating train split: 103803194 examples [1:52:45, 6392.90 examples/s]
Generating train split: 103805347 examples [1:52:45, 8578.62 examples/s]
Generating train split: 103806626 examples [1:52:45, 8180.91 examples/s]
Generating train split: 103808209 examples [1:52:45, 9527.86 examples/s]
Generating train split: 103809454 examples [1:52:46, 8158.42 examples/s]
Generating train split: 103810500 examples [1:52:46, 6785.31 examples/s]
Generating train split: 103811566 examples [1:52:46, 7454.81 examples/s]
Generating train split: 103813693 examples [1:52:46, 10083.46 examples/s]
Generating train split: 103816092 examples [1:52:46, 13019.17 examples/s]
Generating train split: 103818282 examples [1:52:46, 14752.42 examples/s]
Generating train split: 103819966 examples [1:52:47, 11374.66 examples/s]
Generating train split: 103821424 examples [1:52:47, 11987.02 examples/s]
Generating train split: 103822829 examples [1:52:47, 10474.62 examples/s]
Generating train split: 103824048 examples [1:52:47, 10588.56 examples/s]
Generating train split: 103825259 examples [1:52:47, 10928.17 examples/s]
Generating train split: 103826594 examples [1:52:47, 11492.26 examples/s]
Generating train split: 103827824 examples [1:52:47, 8405.01 examples/s] 
Generating train split: 103828831 examples [1:52:48, 8329.94 examples/s]
Generating train split: 103829778 examples [1:52:48, 6919.88 examples/s]
Generating train split: 103830977 examples [1:52:48, 7945.90 examples/s]
Generating train split: 103831894 examples [1:52:48, 5535.98 examples/s]
Generating train split: 103832637 examples [1:52:48, 5591.18 examples/s]
Generating train split: 103834863 examples [1:52:48, 8841.58 examples/s]
Generating train split: 103836017 examples [1:52:49, 7857.48 examples/s]
Generating train split: 103837006 examples [1:52:49, 6952.74 examples/s]
Generating train split: 103843684 examples [1:52:49, 18811.29 examples/s]
Generating train split: 103851443 examples [1:52:49, 31781.21 examples/s]
Generating train split: 103855589 examples [1:52:49, 33074.44 examples/s]
Generating train split: 103859598 examples [1:52:50, 18306.15 examples/s]
Generating train split: 103862662 examples [1:52:50, 10159.98 examples/s]
Generating train split: 103864931 examples [1:52:51, 9182.24 examples/s] 
Generating train split: 103866730 examples [1:52:51, 9611.61 examples/s]
Generating train split: 103868346 examples [1:52:51, 9919.47 examples/s]
Generating train split: 103870757 examples [1:52:51, 11963.83 examples/s]
Generating train split: 103872514 examples [1:52:52, 7483.77 examples/s] 
Generating train split: 103873842 examples [1:52:52, 8185.49 examples/s]
Generating train split: 103875164 examples [1:52:52, 6324.41 examples/s]
Generating train split: 103876200 examples [1:52:52, 5745.43 examples/s]
Generating train split: 103877058 examples [1:52:53, 5044.12 examples/s]
Generating train split: 103877767 examples [1:52:53, 5041.22 examples/s]
Generating train split: 103879506 examples [1:52:53, 6980.81 examples/s]
Generating train split: 103880474 examples [1:52:53, 5949.67 examples/s]
Generating train split: 103881401 examples [1:52:53, 6425.74 examples/s]
Generating train split: 103882216 examples [1:52:53, 6137.37 examples/s]
Generating train split: 103883003 examples [1:52:53, 6474.96 examples/s]
Generating train split: 103883757 examples [1:52:54, 5659.39 examples/s]
Generating train split: 103884761 examples [1:52:54, 6531.56 examples/s]
Generating train split: 103885796 examples [1:52:54, 7409.61 examples/s]
Generating train split: 103886630 examples [1:52:54, 7452.93 examples/s]
Generating train split: 103887437 examples [1:52:54, 4937.81 examples/s]
Generating train split: 103888085 examples [1:52:54, 4707.15 examples/s]
Generating train split: 103891169 examples [1:52:54, 9882.09 examples/s]
Generating train split: 103893206 examples [1:52:55, 12189.91 examples/s]
Generating train split: 103894749 examples [1:52:55, 12274.56 examples/s]
Generating train split: 103896201 examples [1:52:55, 8556.53 examples/s] 
Generating train split: 103897368 examples [1:52:55, 9123.08 examples/s]
Generating train split: 103898535 examples [1:52:55, 8288.66 examples/s]
Generating train split: 103899547 examples [1:52:55, 6616.42 examples/s]
Generating train split: 103907442 examples [1:52:56, 19906.71 examples/s]
Generating train split: 103915860 examples [1:52:56, 33265.60 examples/s]
Generating train split: 103920446 examples [1:52:56, 25861.94 examples/s]
Generating train split: 103924171 examples [1:52:57, 15201.63 examples/s]
Generating train split: 103926986 examples [1:52:57, 15102.56 examples/s]
Generating train split: 103929401 examples [1:52:57, 14687.68 examples/s]
Generating train split: 103931608 examples [1:52:57, 15778.57 examples/s]
Generating train split: 103933729 examples [1:52:57, 12376.92 examples/s]
Generating train split: 103935427 examples [1:52:58, 9647.04 examples/s] 
Generating train split: 103936772 examples [1:52:58, 8849.72 examples/s]
Generating train split: 103937913 examples [1:52:58, 7563.57 examples/s]
Generating train split: 103940135 examples [1:52:58, 9759.60 examples/s]
Generating train split: 103942419 examples [1:52:58, 12001.31 examples/s]
Generating train split: 103944011 examples [1:52:58, 10446.02 examples/s]
Generating train split: 103945350 examples [1:52:59, 8750.81 examples/s] 
Generating train split: 103947459 examples [1:52:59, 10915.26 examples/s]
Generating train split: 103948860 examples [1:52:59, 11138.76 examples/s]
Generating train split: 103950205 examples [1:52:59, 7027.13 examples/s] 
Generating train split: 103957365 examples [1:52:59, 17227.95 examples/s]
Generating train split: 103965602 examples [1:53:00, 29221.54 examples/s]
Generating train split: 103970090 examples [1:53:00, 21668.04 examples/s]
Generating train split: 103973629 examples [1:53:00, 15677.13 examples/s]
Generating train split: 103976368 examples [1:53:01, 11312.55 examples/s]
Generating train split: 103978453 examples [1:53:01, 11182.73 examples/s]
Generating train split: 103980242 examples [1:53:01, 9419.03 examples/s] 
Generating train split: 103982600 examples [1:53:01, 11165.97 examples/s]
Generating train split: 103984601 examples [1:53:01, 12469.38 examples/s]
Generating train split: 103986382 examples [1:53:02, 8774.52 examples/s] 
Generating train split: 103987764 examples [1:53:02, 8132.43 examples/s]
Generating train split: 103988926 examples [1:53:02, 7136.33 examples/s]
Generating train split: 103989878 examples [1:53:02, 7120.90 examples/s]
Generating train split: 103991259 examples [1:53:03, 8224.40 examples/s]
Generating train split: 103993128 examples [1:53:03, 10055.72 examples/s]
Generating train split: 103994361 examples [1:53:03, 9486.35 examples/s] 
Generating train split: 103995464 examples [1:53:03, 9223.41 examples/s]
Generating train split: 103996503 examples [1:53:03, 9022.91 examples/s]
Generating train split: 103997486 examples [1:53:03, 8905.07 examples/s]
Generating train split: 103998429 examples [1:53:04, 5119.91 examples/s]
Generating train split: 103999156 examples [1:53:04, 5374.30 examples/s]
Generating train split: 104001011 examples [1:53:04, 7842.90 examples/s]
Generating train split: 104002136 examples [1:53:04, 8557.43 examples/s]
Generating train split: 104003217 examples [1:53:04, 4967.01 examples/s]
Generating train split: 104004045 examples [1:53:05, 4850.72 examples/s]
Generating train split: 104004766 examples [1:53:05, 3596.47 examples/s]
Generating train split: 104005330 examples [1:53:05, 3396.46 examples/s]
Generating train split: 104007703 examples [1:53:05, 6275.95 examples/s]
Generating train split: 104008671 examples [1:53:05, 5824.51 examples/s]
Generating train split: 104009648 examples [1:53:06, 6482.96 examples/s]
Generating train split: 104010512 examples [1:53:06, 6094.40 examples/s]
Generating train split: 104012130 examples [1:53:06, 8075.92 examples/s]
Generating train split: 104013145 examples [1:53:06, 4248.05 examples/s]
Generating train split: 104014895 examples [1:53:07, 6023.32 examples/s]
Generating train split: 104015946 examples [1:53:07, 4302.84 examples/s]
Generating train split: 104016891 examples [1:53:07, 4682.19 examples/s]
Generating train split: 104017647 examples [1:53:07, 4454.71 examples/s]
Generating train split: 104018333 examples [1:53:07, 4827.15 examples/s]
Generating train split: 104019107 examples [1:53:08, 5331.26 examples/s]
Generating train split: 104019805 examples [1:53:08, 5526.87 examples/s]
Generating train split: 104022391 examples [1:53:08, 10017.91 examples/s]
Generating train split: 104023631 examples [1:53:08, 8573.37 examples/s] 
Generating train split: 104025126 examples [1:53:08, 9940.72 examples/s]
Generating train split: 104026321 examples [1:53:08, 6410.29 examples/s]
Generating train split: 104027653 examples [1:53:09, 7430.76 examples/s]
Generating train split: 104028656 examples [1:53:09, 6068.22 examples/s]
Generating train split: 104029477 examples [1:53:09, 5565.09 examples/s]
Generating train split: 104030245 examples [1:53:09, 5913.19 examples/s]
Generating train split: 104030976 examples [1:53:09, 5419.18 examples/s]
Generating train split: 104032206 examples [1:53:09, 6646.18 examples/s]
Generating train split: 104034639 examples [1:53:09, 10514.43 examples/s]
Generating train split: 104037851 examples [1:53:10, 15659.96 examples/s]
Generating train split: 104047178 examples [1:53:10, 35359.09 examples/s]
Generating train split: 104054583 examples [1:53:10, 45646.50 examples/s]
Generating train split: 104059674 examples [1:53:10, 20716.63 examples/s]
Generating train split: 104063521 examples [1:53:11, 15162.56 examples/s]
Generating train split: 104066457 examples [1:53:11, 16032.39 examples/s]
Generating train split: 104075724 examples [1:53:11, 26800.22 examples/s]
Generating train split: 104083477 examples [1:53:11, 35271.71 examples/s]
Generating train split: 104089050 examples [1:53:12, 24179.42 examples/s]
Generating train split: 104093351 examples [1:53:12, 16666.10 examples/s]
Generating train split: 104096605 examples [1:53:12, 16681.51 examples/s]
Generating train split: 104105007 examples [1:53:12, 25298.92 examples/s]
Generating train split: 104111850 examples [1:53:12, 31901.79 examples/s]
Generating train split: 104117006 examples [1:53:13, 20948.84 examples/s]
Generating train split: 104120940 examples [1:53:13, 15663.25 examples/s]
Generating train split: 104123952 examples [1:53:14, 11505.87 examples/s]
Generating train split: 104126231 examples [1:53:15, 8643.96 examples/s] 
Generating train split: 104127943 examples [1:53:15, 8693.10 examples/s]
Generating train split: 104129412 examples [1:53:15, 8858.21 examples/s]
Generating train split: 104131284 examples [1:53:15, 10022.14 examples/s]
Generating train split: 104132752 examples [1:53:15, 8773.71 examples/s] 
Generating train split: 104133960 examples [1:53:16, 6195.86 examples/s]
Generating train split: 104135211 examples [1:53:16, 6955.41 examples/s]
Generating train split: 104136232 examples [1:53:16, 6908.16 examples/s]
Generating train split: 104137636 examples [1:53:16, 7849.07 examples/s]
Generating train split: 104138638 examples [1:53:16, 6488.79 examples/s]
Generating train split: 104140019 examples [1:53:16, 7705.00 examples/s]
Generating train split: 104140994 examples [1:53:17, 4932.65 examples/s]
Generating train split: 104142059 examples [1:53:17, 5752.89 examples/s]
Generating train split: 104142898 examples [1:53:17, 4425.48 examples/s]
Generating train split: 104143926 examples [1:53:17, 5300.72 examples/s]
Generating train split: 104151869 examples [1:53:17, 18344.62 examples/s]
Generating train split: 104160673 examples [1:53:18, 32332.87 examples/s]
Generating train split: 104165362 examples [1:53:18, 24645.98 examples/s]
Generating train split: 104169120 examples [1:53:19, 13444.24 examples/s]
Generating train split: 104171921 examples [1:53:19, 14578.11 examples/s]
Generating train split: 104180795 examples [1:53:19, 24647.12 examples/s]
Generating train split: 104187038 examples [1:53:19, 30779.23 examples/s]
Generating train split: 104192058 examples [1:53:19, 17662.32 examples/s]
Generating train split: 104195814 examples [1:53:20, 13259.61 examples/s]
Generating train split: 104198666 examples [1:53:20, 11922.43 examples/s]
Generating train split: 104200917 examples [1:53:21, 9153.31 examples/s] 
Generating train split: 104202629 examples [1:53:21, 6916.44 examples/s]
Generating train split: 104203922 examples [1:53:21, 7401.49 examples/s]
Generating train split: 104205202 examples [1:53:22, 6070.13 examples/s]
Generating train split: 104206357 examples [1:53:22, 6616.42 examples/s]
Generating train split: 104207392 examples [1:53:22, 5777.31 examples/s]
Generating train split: 104208222 examples [1:53:22, 5037.41 examples/s]
Generating train split: 104209191 examples [1:53:23, 5662.66 examples/s]
Generating train split: 104209957 examples [1:53:23, 5166.77 examples/s]
Generating train split: 104210698 examples [1:53:23, 5503.62 examples/s]
Generating train split: 104211369 examples [1:53:23, 5633.63 examples/s]
Generating train split: 104212873 examples [1:53:23, 7534.37 examples/s]
Generating train split: 104213766 examples [1:53:24, 4590.93 examples/s]
Generating train split: 104214456 examples [1:53:24, 3305.57 examples/s]
Generating train split: 104216271 examples [1:53:24, 5275.75 examples/s]
Generating train split: 104217202 examples [1:53:24, 4164.53 examples/s]
Generating train split: 104218909 examples [1:53:24, 5935.56 examples/s]
Generating train split: 104220025 examples [1:53:25, 6792.63 examples/s]
Generating train split: 104221259 examples [1:53:25, 7779.13 examples/s]
Generating train split: 104222343 examples [1:53:25, 6529.55 examples/s]
Generating train split: 104223243 examples [1:53:25, 6684.83 examples/s]
Generating train split: 104224596 examples [1:53:25, 8026.08 examples/s]
Generating train split: 104225580 examples [1:53:25, 8187.24 examples/s]
Generating train split: 104226527 examples [1:53:25, 7084.74 examples/s]
Generating train split: 104227353 examples [1:53:26, 5577.14 examples/s]
Generating train split: 104229348 examples [1:53:26, 8350.93 examples/s]
Generating train split: 104230416 examples [1:53:26, 5644.22 examples/s]
Generating train split: 104231255 examples [1:53:26, 5633.26 examples/s]
Generating train split: 104232995 examples [1:53:26, 7515.26 examples/s]
Generating train split: 104233980 examples [1:53:27, 5139.23 examples/s]
Generating train split: 104235390 examples [1:53:27, 6523.78 examples/s]
Generating train split: 104237264 examples [1:53:27, 8725.82 examples/s]
Generating train split: 104238496 examples [1:53:27, 6650.05 examples/s]
Generating train split: 104239485 examples [1:53:27, 6330.97 examples/s]
Generating train split: 104240956 examples [1:53:28, 7780.53 examples/s]
Generating train split: 104241995 examples [1:53:28, 6308.85 examples/s]
Generating train split: 104243032 examples [1:53:28, 6925.33 examples/s]
Generating train split: 104243906 examples [1:53:28, 5275.00 examples/s]
Generating train split: 104244610 examples [1:53:28, 5497.54 examples/s]
Generating train split: 104245981 examples [1:53:28, 7072.77 examples/s]
Generating train split: 104246866 examples [1:53:29, 7313.03 examples/s]
Generating train split: 104247846 examples [1:53:29, 7887.44 examples/s]
Generating train split: 104248744 examples [1:53:29, 4675.00 examples/s]
Generating train split: 104249655 examples [1:53:29, 5413.57 examples/s]
Generating train split: 104250411 examples [1:53:29, 5680.10 examples/s]
Generating train split: 104251626 examples [1:53:29, 6435.34 examples/s]
Generating train split: 104252387 examples [1:53:30, 6075.42 examples/s]
Generating train split: 104253081 examples [1:53:30, 4230.60 examples/s]
Generating train split: 104254153 examples [1:53:30, 5363.75 examples/s]
Generating train split: 104262139 examples [1:53:30, 20254.60 examples/s]
Generating train split: 104270803 examples [1:53:30, 34996.01 examples/s]
Generating train split: 104275430 examples [1:53:30, 27466.14 examples/s]
Generating train split: 104279208 examples [1:53:31, 11893.07 examples/s]
Generating train split: 104281992 examples [1:53:32, 11190.02 examples/s]
Generating train split: 104284228 examples [1:53:32, 8731.52 examples/s] 
Generating train split: 104285925 examples [1:53:32, 7906.76 examples/s]
Generating train split: 104287280 examples [1:53:33, 5971.51 examples/s]
Generating train split: 104289164 examples [1:53:33, 7192.72 examples/s]
Generating train split: 104290459 examples [1:53:33, 5875.26 examples/s]
Generating train split: 104291459 examples [1:53:34, 6050.63 examples/s]
Generating train split: 104292418 examples [1:53:34, 6507.53 examples/s]
Generating train split: 104293345 examples [1:53:34, 4594.34 examples/s]
Generating train split: 104295103 examples [1:53:34, 6294.04 examples/s]
Generating train split: 104297956 examples [1:53:34, 9791.86 examples/s]
Generating train split: 104299748 examples [1:53:34, 11282.22 examples/s]
Generating train split: 104301385 examples [1:53:35, 10000.77 examples/s]
Generating train split: 104303256 examples [1:53:35, 11664.68 examples/s]
Generating train split: 104304783 examples [1:53:35, 10517.27 examples/s]
Generating train split: 104306100 examples [1:53:35, 6549.28 examples/s] 
Generating train split: 104308132 examples [1:53:35, 8552.97 examples/s]
Generating train split: 104309427 examples [1:53:36, 5534.32 examples/s]
Generating train split: 104310423 examples [1:53:36, 5159.45 examples/s]
Generating train split: 104311642 examples [1:53:36, 6097.63 examples/s]
Generating train split: 104312612 examples [1:53:36, 6647.09 examples/s]
Generating train split: 104313567 examples [1:53:36, 7178.38 examples/s]
Generating train split: 104314895 examples [1:53:37, 8382.91 examples/s]
Generating train split: 104315944 examples [1:53:37, 7233.73 examples/s]
Generating train split: 104316838 examples [1:53:37, 7236.94 examples/s]
Generating train split: 104318198 examples [1:53:37, 8624.50 examples/s]
Generating train split: 104319191 examples [1:53:37, 7858.12 examples/s]
Generating train split: 104320084 examples [1:53:37, 6208.58 examples/s]
Generating train split: 104321878 examples [1:53:37, 8501.26 examples/s]
Generating train split: 104322906 examples [1:53:38, 7676.49 examples/s]
Generating train split: 104324276 examples [1:53:38, 8801.92 examples/s]
Generating train split: 104325287 examples [1:53:38, 7864.74 examples/s]
Generating train split: 104326710 examples [1:53:38, 9267.58 examples/s]
Generating train split: 104327770 examples [1:53:38, 8396.50 examples/s]
Generating train split: 104330490 examples [1:53:38, 12745.55 examples/s]
Generating train split: 104331970 examples [1:53:38, 10202.24 examples/s]
Generating train split: 104333473 examples [1:53:39, 11222.34 examples/s]
Generating train split: 104335325 examples [1:53:39, 12929.66 examples/s]
Generating train split: 104336804 examples [1:53:39, 8288.17 examples/s] 
Generating train split: 104337967 examples [1:53:39, 8662.79 examples/s]
Generating train split: 104339089 examples [1:53:39, 7339.42 examples/s]
Generating train split: 104340040 examples [1:53:39, 7403.64 examples/s]
Generating train split: 104341086 examples [1:53:40, 7988.22 examples/s]
Generating train split: 104342015 examples [1:53:40, 6840.40 examples/s]
Generating train split: 104343477 examples [1:53:40, 8357.87 examples/s]
Generating train split: 104344446 examples [1:53:40, 5105.07 examples/s]
Generating train split: 104345197 examples [1:53:40, 5049.11 examples/s]
Generating train split: 104345872 examples [1:53:41, 5277.30 examples/s]
Generating train split: 104346537 examples [1:53:41, 5150.78 examples/s]
Generating train split: 104347163 examples [1:53:41, 5287.63 examples/s]
Generating train split: 104348099 examples [1:53:41, 6181.24 examples/s]
Generating train split: 104349442 examples [1:53:41, 7940.85 examples/s]
Generating train split: 104351175 examples [1:53:41, 10350.90 examples/s]
Generating train split: 104352495 examples [1:53:41, 11110.40 examples/s]
Generating train split: 104354936 examples [1:53:41, 14404.45 examples/s]
Generating train split: 104357521 examples [1:53:41, 16676.86 examples/s]
Generating train split: 104359222 examples [1:53:42, 11408.56 examples/s]
Generating train split: 104360932 examples [1:53:42, 12550.94 examples/s]
Generating train split: 104362407 examples [1:53:42, 12487.75 examples/s]
Generating train split: 104363811 examples [1:53:42, 9583.38 examples/s] 
Generating train split: 104364965 examples [1:53:42, 8501.33 examples/s]
Generating train split: 104365966 examples [1:53:43, 6808.78 examples/s]
Generating train split: 104366860 examples [1:53:43, 7181.31 examples/s]
Generating train split: 104367703 examples [1:53:43, 5373.59 examples/s]
Generating train split: 104368644 examples [1:53:43, 6059.74 examples/s]
Generating train split: 104369516 examples [1:53:43, 6585.86 examples/s]
Generating train split: 104370969 examples [1:53:43, 8292.09 examples/s]
Generating train split: 104377494 examples [1:53:43, 21890.18 examples/s]
Generating train split: 104384734 examples [1:53:44, 34732.42 examples/s]
Generating train split: 104388753 examples [1:53:44, 18456.45 examples/s]
Generating train split: 104391830 examples [1:53:44, 14835.03 examples/s]
Generating train split: 104398813 examples [1:53:44, 22760.07 examples/s]
Generating train split: 104407209 examples [1:53:44, 33204.97 examples/s]
Generating train split: 104412391 examples [1:53:45, 24453.97 examples/s]
Generating train split: 104421079 examples [1:53:45, 34235.41 examples/s]
Generating train split: 104429632 examples [1:53:45, 43610.81 examples/s]
Generating train split: 104436007 examples [1:53:46, 20315.34 examples/s]
Generating train split: 104440728 examples [1:53:47, 13298.43 examples/s]
Generating train split: 104444215 examples [1:53:47, 12272.50 examples/s]
Generating train split: 104446944 examples [1:53:47, 11423.72 examples/s]
Generating train split: 104449106 examples [1:53:48, 9805.37 examples/s] 
Generating train split: 104450800 examples [1:53:48, 10269.02 examples/s]
Generating train split: 104452405 examples [1:53:48, 10753.95 examples/s]
Generating train split: 104454123 examples [1:53:48, 11678.61 examples/s]
Generating train split: 104456850 examples [1:53:48, 14331.17 examples/s]
Generating train split: 104458786 examples [1:53:48, 15072.53 examples/s]
Generating train split: 104460877 examples [1:53:48, 16260.03 examples/s]
Generating train split: 104462827 examples [1:53:49, 13006.02 examples/s]
Generating train split: 104464446 examples [1:53:49, 8651.33 examples/s] 
Generating train split: 104465698 examples [1:53:49, 7033.10 examples/s]
Generating train split: 104466707 examples [1:53:49, 6927.66 examples/s]
Generating train split: 104468398 examples [1:53:49, 8463.85 examples/s]
Generating train split: 104470235 examples [1:53:50, 10134.80 examples/s]
Generating train split: 104471526 examples [1:53:50, 7902.16 examples/s] 
Generating train split: 104472611 examples [1:53:50, 8427.65 examples/s]
Generating train split: 104473671 examples [1:53:50, 8431.63 examples/s]
Generating train split: 104474963 examples [1:53:50, 9146.34 examples/s]
Generating train split: 104476010 examples [1:53:50, 7866.56 examples/s]
Generating train split: 104476905 examples [1:53:50, 8001.86 examples/s]
Generating train split: 104478283 examples [1:53:51, 9080.37 examples/s]
Generating train split: 104479276 examples [1:53:51, 7690.03 examples/s]
Generating train split: 104480126 examples [1:53:51, 6820.14 examples/s]
Generating train split: 104481635 examples [1:53:51, 8491.97 examples/s]
Generating train split: 104483698 examples [1:53:51, 11322.06 examples/s]
Generating train split: 104484990 examples [1:53:51, 8533.84 examples/s] 
Generating train split: 104487245 examples [1:53:52, 11387.28 examples/s]
Generating train split: 104488652 examples [1:53:52, 9109.24 examples/s] 
Generating train split: 104489824 examples [1:53:52, 6955.11 examples/s]
Generating train split: 104490766 examples [1:53:52, 6812.22 examples/s]
Generating train split: 104491975 examples [1:53:52, 7764.92 examples/s]
Generating train split: 104492943 examples [1:53:52, 8157.33 examples/s]
Generating train split: 104493902 examples [1:53:53, 7088.72 examples/s]
Generating train split: 104495480 examples [1:53:53, 8923.60 examples/s]
Generating train split: 104496711 examples [1:53:53, 9711.36 examples/s]
Generating train split: 104497814 examples [1:53:53, 8110.70 examples/s]
Generating train split: 104498757 examples [1:53:53, 7871.19 examples/s]
Generating train split: 104499790 examples [1:53:53, 8423.82 examples/s]
Generating train split: 104501256 examples [1:53:53, 9813.75 examples/s]
Generating train split: 104502321 examples [1:53:54, 8097.98 examples/s]
Generating train split: 104503234 examples [1:53:54, 7242.13 examples/s]
Generating train split: 104504863 examples [1:53:54, 9188.68 examples/s]
Generating train split: 104505906 examples [1:53:54, 6262.90 examples/s]
Generating train split: 104506738 examples [1:53:54, 5369.39 examples/s]
Generating train split: 104508767 examples [1:53:54, 7967.03 examples/s]
Generating train split: 104509857 examples [1:53:55, 6185.57 examples/s]
Generating train split: 104511201 examples [1:53:55, 7424.30 examples/s]
Generating train split: 104512865 examples [1:53:55, 9234.43 examples/s]
Generating train split: 104519759 examples [1:53:55, 22318.03 examples/s]
Generating train split: 104525447 examples [1:53:55, 30496.15 examples/s]
Generating train split: 104529191 examples [1:53:56, 11793.38 examples/s]
Generating train split: 104531957 examples [1:53:56, 10693.51 examples/s]
Generating train split: 104534142 examples [1:53:57, 9306.52 examples/s] 
Generating train split: 104535858 examples [1:53:57, 7216.55 examples/s]
Generating train split: 104543742 examples [1:53:57, 14603.21 examples/s]
Generating train split: 104552645 examples [1:53:57, 24158.36 examples/s]
Generating train split: 104557612 examples [1:53:58, 20035.58 examples/s]
Generating train split: 104561507 examples [1:53:58, 13487.74 examples/s]
Generating train split: 104564426 examples [1:53:59, 9701.23 examples/s] 
Generating train split: 104566608 examples [1:53:59, 9408.93 examples/s]
Generating train split: 104568394 examples [1:53:59, 9171.05 examples/s]
Generating train split: 104569887 examples [1:53:59, 9624.08 examples/s]
Generating train split: 104571319 examples [1:54:00, 8946.33 examples/s]
Generating train split: 104573218 examples [1:54:00, 10390.81 examples/s]
Generating train split: 104574634 examples [1:54:00, 9018.44 examples/s] 
Generating train split: 104575814 examples [1:54:00, 7740.80 examples/s]
Generating train split: 104576788 examples [1:54:00, 7066.65 examples/s]
Generating train split: 104577788 examples [1:54:01, 7473.15 examples/s]
Generating train split: 104578667 examples [1:54:01, 7677.56 examples/s]
Generating train split: 104580070 examples [1:54:01, 9012.62 examples/s]
Generating train split: 104582027 examples [1:54:01, 11477.18 examples/s]
Generating train split: 104583330 examples [1:54:01, 7279.50 examples/s] 
Generating train split: 104584353 examples [1:54:01, 7161.67 examples/s]
Generating train split: 104585355 examples [1:54:01, 7706.23 examples/s]
Generating train split: 104586310 examples [1:54:02, 7954.98 examples/s]
Generating train split: 104587242 examples [1:54:02, 5928.17 examples/s]
Generating train split: 104588281 examples [1:54:02, 6746.39 examples/s]
Generating train split: 104589531 examples [1:54:02, 7960.09 examples/s]
Generating train split: 104590485 examples [1:54:02, 5657.03 examples/s]
Generating train split: 104592426 examples [1:54:02, 8165.39 examples/s]
Generating train split: 104593529 examples [1:54:03, 7830.97 examples/s]
Generating train split: 104594785 examples [1:54:03, 8716.18 examples/s]
Generating train split: 104595833 examples [1:54:03, 7899.67 examples/s]
Generating train split: 104596943 examples [1:54:03, 8572.59 examples/s]
Generating train split: 104598433 examples [1:54:03, 10074.90 examples/s]
Generating train split: 104599567 examples [1:54:03, 7483.81 examples/s] 
Generating train split: 104600492 examples [1:54:03, 6977.20 examples/s]
Generating train split: 104601684 examples [1:54:04, 7972.13 examples/s]
Generating train split: 104603452 examples [1:54:04, 10070.42 examples/s]
Generating train split: 104604612 examples [1:54:04, 6481.80 examples/s] 
Generating train split: 104609163 examples [1:54:04, 13422.18 examples/s]
Generating train split: 104617618 examples [1:54:04, 27829.47 examples/s]
Generating train split: 104624072 examples [1:54:04, 36062.24 examples/s]
Generating train split: 104628769 examples [1:54:05, 19182.15 examples/s]
Generating train split: 104632337 examples [1:54:05, 18152.52 examples/s]
Generating train split: 104635292 examples [1:54:06, 11207.43 examples/s]
Generating train split: 104637519 examples [1:54:06, 10281.97 examples/s]
Generating train split: 104639304 examples [1:54:07, 6863.39 examples/s] 
Generating train split: 104640638 examples [1:54:07, 5927.71 examples/s]
Generating train split: 104642452 examples [1:54:07, 7060.60 examples/s]
Generating train split: 104643724 examples [1:54:07, 7432.65 examples/s]
Generating train split: 104645080 examples [1:54:07, 8284.32 examples/s]
Generating train split: 104646312 examples [1:54:08, 6836.54 examples/s]
Generating train split: 104647931 examples [1:54:08, 8137.25 examples/s]
Generating train split: 104649063 examples [1:54:08, 8023.67 examples/s]
Generating train split: 104650088 examples [1:54:08, 8270.73 examples/s]
Generating train split: 104651087 examples [1:54:08, 6893.47 examples/s]
Generating train split: 104651927 examples [1:54:08, 6972.06 examples/s]
Generating train split: 104653087 examples [1:54:08, 7928.44 examples/s]
Generating train split: 104653996 examples [1:54:09, 8120.10 examples/s]
Generating train split: 104655714 examples [1:54:09, 10352.44 examples/s]
Generating train split: 104657296 examples [1:54:09, 11766.78 examples/s]
Generating train split: 104659528 examples [1:54:09, 14193.56 examples/s]
Generating train split: 104661460 examples [1:54:09, 15585.43 examples/s]
Generating train split: 104663092 examples [1:54:09, 12043.42 examples/s]
Generating train split: 104664627 examples [1:54:09, 12710.96 examples/s]
Generating train split: 104666040 examples [1:54:10, 8223.10 examples/s] 
Generating train split: 104667527 examples [1:54:10, 9432.62 examples/s]
Generating train split: 104670168 examples [1:54:10, 12937.79 examples/s]
Generating train split: 104671821 examples [1:54:10, 13132.41 examples/s]
Generating train split: 104673384 examples [1:54:10, 8607.75 examples/s] 
Generating train split: 104674624 examples [1:54:10, 9056.70 examples/s]
Generating train split: 104675818 examples [1:54:10, 9594.83 examples/s]
Generating train split: 104677011 examples [1:54:11, 9766.10 examples/s]
Generating train split: 104678154 examples [1:54:11, 10125.89 examples/s]
Generating train split: 104679461 examples [1:54:11, 10743.11 examples/s]
Generating train split: 104687369 examples [1:54:11, 28494.71 examples/s]
Generating train split: 104696162 examples [1:54:11, 44576.64 examples/s]
Generating train split: 104701044 examples [1:54:11, 29595.82 examples/s]
Generating train split: 104704960 examples [1:54:12, 25074.93 examples/s]
Generating train split: 104713605 examples [1:54:12, 36653.13 examples/s]
Generating train split: 104722351 examples [1:54:12, 45941.14 examples/s]
Generating train split: 104728046 examples [1:54:12, 35098.29 examples/s]
Generating train split: 104732672 examples [1:54:12, 25315.18 examples/s]
Generating train split: 104736309 examples [1:54:13, 20852.87 examples/s]
Generating train split: 104739236 examples [1:54:13, 18651.37 examples/s]
Generating train split: 104741675 examples [1:54:13, 11895.15 examples/s]
Generating train split: 104743528 examples [1:54:13, 12616.43 examples/s]
Generating train split: 104745362 examples [1:54:14, 12751.92 examples/s]
Generating train split: 104747048 examples [1:54:14, 9466.50 examples/s] 
Generating train split: 104749347 examples [1:54:14, 11342.60 examples/s]
Generating train split: 104750958 examples [1:54:14, 9465.22 examples/s] 
Generating train split: 104752418 examples [1:54:14, 10208.83 examples/s]
Generating train split: 104753767 examples [1:54:15, 10336.54 examples/s]
Generating train split: 104755566 examples [1:54:15, 11843.45 examples/s]
Generating train split: 104756994 examples [1:54:15, 11583.78 examples/s]
Generating train split: 104758316 examples [1:54:15, 8692.41 examples/s] 
Generating train split: 104759675 examples [1:54:15, 9574.12 examples/s]
Generating train split: 104760834 examples [1:54:15, 9943.91 examples/s]
Generating train split: 104761977 examples [1:54:15, 9646.38 examples/s]
Generating train split: 104763045 examples [1:54:16, 7431.08 examples/s]
Generating train split: 104764182 examples [1:54:16, 8229.78 examples/s]
Generating train split: 104765145 examples [1:54:16, 7037.94 examples/s]
Generating train split: 104765973 examples [1:54:16, 5982.63 examples/s]
Generating train split: 104766668 examples [1:54:16, 5122.25 examples/s]
Generating train split: 104767982 examples [1:54:16, 6636.95 examples/s]
Generating train split: 104768796 examples [1:54:17, 6719.08 examples/s]
Generating train split: 104769576 examples [1:54:17, 5087.48 examples/s]
Generating train split: 104770212 examples [1:54:17, 4606.22 examples/s]
Generating train split: 104770765 examples [1:54:17, 4230.46 examples/s]
Generating train split: 104771480 examples [1:54:17, 4766.67 examples/s]
Generating train split: 104772026 examples [1:54:17, 4109.53 examples/s]
Generating train split: 104773356 examples [1:54:18, 5989.82 examples/s]
Generating train split: 104774291 examples [1:54:18, 6371.84 examples/s]
Generating train split: 104775732 examples [1:54:18, 8251.61 examples/s]
Generating train split: 104776687 examples [1:54:18, 8361.89 examples/s]
Generating train split: 104777609 examples [1:54:18, 7587.17 examples/s]
Generating train split: 104778445 examples [1:54:18, 5408.23 examples/s]
Generating train split: 104785944 examples [1:54:18, 19078.25 examples/s]
Generating train split: 104794581 examples [1:54:19, 33823.50 examples/s]
Generating train split: 104799200 examples [1:54:19, 35409.46 examples/s]
Generating train split: 104803542 examples [1:54:19, 15859.68 examples/s]
Generating train split: 104806782 examples [1:54:20, 14185.75 examples/s]
Generating train split: 104809372 examples [1:54:20, 14655.12 examples/s]
Generating train split: 104811688 examples [1:54:20, 13241.43 examples/s]
Generating train split: 104813600 examples [1:54:20, 12441.46 examples/s]
Generating train split: 104815237 examples [1:54:20, 12538.74 examples/s]
Generating train split: 104817997 examples [1:54:20, 15195.11 examples/s]
Generating train split: 104819899 examples [1:54:21, 10417.66 examples/s]
Generating train split: 104821387 examples [1:54:21, 11114.78 examples/s]
Generating train split: 104823134 examples [1:54:21, 12271.43 examples/s]
Generating train split: 104824695 examples [1:54:21, 9564.13 examples/s] 
Generating train split: 104825963 examples [1:54:21, 8417.48 examples/s]
Generating train split: 104827035 examples [1:54:22, 8691.17 examples/s]
Generating train split: 104828076 examples [1:54:22, 6811.52 examples/s]
Generating train split: 104828932 examples [1:54:22, 6851.20 examples/s]
Generating train split: 104830438 examples [1:54:22, 8449.68 examples/s]
Generating train split: 104833397 examples [1:54:22, 13053.62 examples/s]
Generating train split: 104841454 examples [1:54:22, 29067.37 examples/s]
Generating train split: 104849289 examples [1:54:22, 41255.86 examples/s]
Generating train split: 104854052 examples [1:54:23, 16030.11 examples/s]
Generating train split: 104861216 examples [1:54:23, 22895.02 examples/s]
Generating train split: 104869429 examples [1:54:23, 31775.28 examples/s]
Generating train split: 104875126 examples [1:54:24, 24565.90 examples/s]
Generating train split: 104879575 examples [1:54:25, 13413.23 examples/s]
Generating train split: 104882857 examples [1:54:26, 7999.04 examples/s] 
Generating train split: 104885251 examples [1:54:26, 6709.70 examples/s]
Generating train split: 104887048 examples [1:54:26, 7121.85 examples/s]
Generating train split: 104888619 examples [1:54:27, 5930.86 examples/s]
Generating train split: 104889825 examples [1:54:27, 5412.35 examples/s]
Generating train split: 104890778 examples [1:54:27, 5548.05 examples/s]
Generating train split: 104891650 examples [1:54:27, 5656.89 examples/s]
Generating train split: 104892450 examples [1:54:28, 4625.68 examples/s]
Generating train split: 104893105 examples [1:54:28, 4857.37 examples/s]
Generating train split: 104893853 examples [1:54:28, 5199.89 examples/s]
Generating train split: 104894506 examples [1:54:28, 4346.44 examples/s]
Generating train split: 104895051 examples [1:54:28, 4423.96 examples/s]
Generating train split: 104896539 examples [1:54:28, 6401.81 examples/s]
Generating train split: 104897359 examples [1:54:29, 5604.46 examples/s]
Generating train split: 104898832 examples [1:54:29, 7416.56 examples/s]
Generating train split: 104899754 examples [1:54:29, 7254.72 examples/s]
Generating train split: 104900833 examples [1:54:29, 8016.30 examples/s]
Generating train split: 104901744 examples [1:54:29, 5956.00 examples/s]
Generating train split: 104903369 examples [1:54:29, 7719.10 examples/s]
Generating train split: 104904302 examples [1:54:30, 6636.86 examples/s]
Generating train split: 104905108 examples [1:54:30, 5624.47 examples/s]
Generating train split: 104905778 examples [1:54:30, 5355.86 examples/s]
Generating train split: 104906381 examples [1:54:30, 4970.47 examples/s]
Generating train split: 104906975 examples [1:54:30, 5096.27 examples/s]
Generating train split: 104907531 examples [1:54:30, 4958.84 examples/s]
Generating train split: 104908171 examples [1:54:30, 5285.84 examples/s]
Generating train split: 104909589 examples [1:54:31, 7390.91 examples/s]
Generating train split: 104910382 examples [1:54:31, 6608.67 examples/s]
Generating train split: 104911093 examples [1:54:31, 5734.57 examples/s]
Generating train split: 104913194 examples [1:54:31, 9165.04 examples/s]
Generating train split: 104914235 examples [1:54:31, 9244.05 examples/s]
Generating train split: 104916120 examples [1:54:31, 11687.78 examples/s]
Generating train split: 104917426 examples [1:54:31, 11927.69 examples/s]
Generating train split: 104918700 examples [1:54:32, 6627.75 examples/s] 
Generating train split: 104919689 examples [1:54:32, 6700.72 examples/s]
Generating train split: 104920945 examples [1:54:32, 7807.89 examples/s]
Generating train split: 104921963 examples [1:54:32, 7422.34 examples/s]
Generating train split: 104922873 examples [1:54:32, 7181.54 examples/s]
Generating train split: 104923702 examples [1:54:32, 6110.50 examples/s]
Generating train split: 104925621 examples [1:54:33, 8793.18 examples/s]
Generating train split: 104929402 examples [1:54:33, 15369.21 examples/s]
Generating train split: 104937636 examples [1:54:33, 31751.96 examples/s]
Generating train split: 104942902 examples [1:54:33, 37164.99 examples/s]
Generating train split: 104947138 examples [1:54:33, 15526.57 examples/s]
Generating train split: 104950296 examples [1:54:34, 14946.94 examples/s]
Generating train split: 104952912 examples [1:54:34, 14254.94 examples/s]
Generating train split: 104960149 examples [1:54:34, 22789.37 examples/s]
Generating train split: 104967469 examples [1:54:34, 31045.93 examples/s]
Generating train split: 104972086 examples [1:54:35, 20414.62 examples/s]
Generating train split: 104975634 examples [1:54:35, 16845.92 examples/s]
Generating train split: 104978432 examples [1:54:35, 13011.04 examples/s]
Generating train split: 104980598 examples [1:54:35, 13662.19 examples/s]
Generating train split: 104982646 examples [1:54:36, 9464.14 examples/s] 
Generating train split: 104984211 examples [1:54:36, 7887.37 examples/s]
Generating train split: 104985847 examples [1:54:36, 8844.65 examples/s]
Generating train split: 104987414 examples [1:54:36, 9707.38 examples/s]
Generating train split: 104991121 examples [1:54:37, 14220.06 examples/s]
Generating train split: 104999652 examples [1:54:37, 27777.25 examples/s]
Generating train split: 105006925 examples [1:54:37, 37387.85 examples/s]
Generating train split: 105011921 examples [1:54:38, 15909.14 examples/s]
Generating train split: 105015618 examples [1:54:38, 9852.68 examples/s] 
Generating train split: 105023602 examples [1:54:38, 15592.52 examples/s]
Generating train split: 105032426 examples [1:54:39, 23210.50 examples/s]
Generating train split: 105038089 examples [1:54:40, 10737.53 examples/s]
Generating train split: 105042184 examples [1:54:40, 11719.73 examples/s]
Generating train split: 105051681 examples [1:54:40, 18491.68 examples/s]
Generating train split: 105058061 examples [1:54:40, 23196.36 examples/s]
Generating train split: 105063622 examples [1:54:41, 14937.04 examples/s]
Generating train split: 105072635 examples [1:54:41, 21821.79 examples/s]
Generating train split: 105079484 examples [1:54:41, 27212.61 examples/s]
Generating train split: 105085443 examples [1:54:42, 15648.92 examples/s]
Generating train split: 105089829 examples [1:54:43, 13887.71 examples/s]
Generating train split: 105098033 examples [1:54:43, 20013.78 examples/s]
Generating train split: 105105340 examples [1:54:43, 25996.59 examples/s]
Generating train split: 105110871 examples [1:54:43, 17855.75 examples/s]
Generating train split: 105115019 examples [1:54:44, 10303.88 examples/s]
Generating train split: 105118050 examples [1:54:45, 10321.91 examples/s]
Generating train split: 105120492 examples [1:54:45, 10780.36 examples/s]
Generating train split: 105122605 examples [1:54:45, 9783.49 examples/s] 
Generating train split: 105124288 examples [1:54:46, 7777.20 examples/s]
Generating train split: 105125600 examples [1:54:46, 8282.39 examples/s]
Generating train split: 105126889 examples [1:54:46, 7389.35 examples/s]
Generating train split: 105127956 examples [1:54:46, 6925.18 examples/s]
Generating train split: 105128855 examples [1:54:46, 6482.41 examples/s]
Generating train split: 105130645 examples [1:54:46, 8185.61 examples/s]
Generating train split: 105131716 examples [1:54:47, 7147.63 examples/s]
Generating train split: 105132813 examples [1:54:47, 7762.69 examples/s]
Generating train split: 105133764 examples [1:54:47, 6826.78 examples/s]
Generating train split: 105136059 examples [1:54:47, 9923.32 examples/s]
Generating train split: 105137321 examples [1:54:47, 7884.88 examples/s]
Generating train split: 105138983 examples [1:54:47, 9519.00 examples/s]
Generating train split: 105140839 examples [1:54:47, 11389.83 examples/s]
Generating train split: 105142241 examples [1:54:48, 11157.43 examples/s]
Generating train split: 105143542 examples [1:54:48, 9640.22 examples/s] 
Generating train split: 105144781 examples [1:54:48, 10219.26 examples/s]
Generating train split: 105145943 examples [1:54:48, 10204.09 examples/s]
Generating train split: 105147431 examples [1:54:48, 11299.39 examples/s]
Generating train split: 105148654 examples [1:54:48, 9648.93 examples/s] 
Generating train split: 105149724 examples [1:54:49, 6713.86 examples/s]
Generating train split: 105151078 examples [1:54:49, 7982.65 examples/s]
Generating train split: 105152622 examples [1:54:49, 9537.48 examples/s]
Generating train split: 105153794 examples [1:54:49, 9641.08 examples/s]
Generating train split: 105154909 examples [1:54:49, 7911.21 examples/s]
Generating train split: 105161071 examples [1:54:49, 19380.05 examples/s]
Generating train split: 105169923 examples [1:54:49, 35542.12 examples/s]
Generating train split: 105174340 examples [1:54:50, 30017.54 examples/s]
Generating train split: 105178089 examples [1:54:50, 18118.27 examples/s]
Generating train split: 105180974 examples [1:54:50, 12502.67 examples/s]
Generating train split: 105183180 examples [1:54:51, 12614.39 examples/s]
Generating train split: 105185111 examples [1:54:51, 12250.73 examples/s]
Generating train split: 105186823 examples [1:54:51, 12810.19 examples/s]
Generating train split: 105188472 examples [1:54:51, 11006.06 examples/s]
Generating train split: 105190092 examples [1:54:51, 11864.86 examples/s]
Generating train split: 105191532 examples [1:54:51, 10818.32 examples/s]
Generating train split: 105192789 examples [1:54:52, 9751.21 examples/s] 
Generating train split: 105193894 examples [1:54:52, 9022.62 examples/s]
Generating train split: 105194884 examples [1:54:52, 9160.00 examples/s]
Generating train split: 105195868 examples [1:54:52, 8981.64 examples/s]
Generating train split: 105196808 examples [1:54:52, 8362.25 examples/s]
Generating train split: 105198884 examples [1:54:52, 11290.98 examples/s]
Generating train split: 105200115 examples [1:54:52, 11471.41 examples/s]
Generating train split: 105201684 examples [1:54:52, 12571.15 examples/s]
Generating train split: 105203008 examples [1:54:53, 9107.49 examples/s] 
Generating train split: 105204106 examples [1:54:53, 7855.70 examples/s]
Generating train split: 105205540 examples [1:54:53, 9180.07 examples/s]
Generating train split: 105206678 examples [1:54:53, 9650.41 examples/s]
Generating train split: 105207771 examples [1:54:53, 5680.84 examples/s]
Generating train split: 105209084 examples [1:54:54, 6893.56 examples/s]
Generating train split: 105210068 examples [1:54:54, 6144.98 examples/s]
Generating train split: 105211059 examples [1:54:54, 6835.71 examples/s]
Generating train split: 105212702 examples [1:54:54, 8813.58 examples/s]
Generating train split: 105213819 examples [1:54:54, 8337.56 examples/s]
Generating train split: 105214862 examples [1:54:54, 8637.24 examples/s]
Generating train split: 105215855 examples [1:54:54, 6604.23 examples/s]
Generating train split: 105216663 examples [1:54:55, 6888.59 examples/s]
Generating train split: 105217659 examples [1:54:55, 7504.62 examples/s]
Generating train split: 105218511 examples [1:54:55, 6019.78 examples/s]
Generating train split: 105219233 examples [1:54:55, 5969.21 examples/s]
Generating train split: 105220194 examples [1:54:55, 6777.68 examples/s]
Generating train split: 105221674 examples [1:54:55, 8263.71 examples/s]
Generating train split: 105222569 examples [1:54:55, 8184.47 examples/s]
Generating train split: 105223441 examples [1:54:56, 5551.94 examples/s]
Generating train split: 105224165 examples [1:54:56, 5864.03 examples/s]
Generating train split: 105224872 examples [1:54:56, 5369.05 examples/s]
Generating train split: 105226286 examples [1:54:56, 7188.15 examples/s]
Generating train split: 105227148 examples [1:54:56, 6285.43 examples/s]
Generating train split: 105227885 examples [1:54:56, 6206.97 examples/s]
Generating train split: 105228748 examples [1:54:56, 6750.56 examples/s]
Generating train split: 105230666 examples [1:54:57, 9786.75 examples/s]
Generating train split: 105231766 examples [1:54:57, 7273.68 examples/s]
Generating train split: 105232671 examples [1:54:57, 6412.53 examples/s]
Generating train split: 105241597 examples [1:54:57, 23099.77 examples/s]
Generating train split: 105249283 examples [1:54:57, 34798.12 examples/s]
Generating train split: 105253752 examples [1:54:58, 23283.97 examples/s]
Generating train split: 105257272 examples [1:54:58, 17403.93 examples/s]
Generating train split: 105262292 examples [1:54:58, 22245.97 examples/s]
Generating train split: 105268500 examples [1:54:58, 29179.99 examples/s]
Generating train split: 105274462 examples [1:54:58, 35243.18 examples/s]
Generating train split: 105280872 examples [1:54:58, 41628.23 examples/s]
Generating train split: 105288131 examples [1:54:58, 49037.59 examples/s]
Generating train split: 105294115 examples [1:54:58, 51784.63 examples/s]
Generating train split: 105301958 examples [1:54:59, 58896.81 examples/s]
Generating train split: 105308438 examples [1:54:59, 59361.22 examples/s]
Generating train split: 105316458 examples [1:54:59, 65167.06 examples/s]
Generating train split: 105323946 examples [1:54:59, 67929.17 examples/s]
Generating train split: 105331283 examples [1:54:59, 69480.95 examples/s]
Generating train split: 105338720 examples [1:54:59, 70899.06 examples/s]
Generating train split: 105346345 examples [1:54:59, 72466.86 examples/s]
Generating train split: 105354263 examples [1:54:59, 74440.57 examples/s]
Generating train split: 105362485 examples [1:54:59, 76727.69 examples/s]
Generating train split: 105370222 examples [1:54:59, 76247.35 examples/s]
Generating train split: 105378475 examples [1:55:00, 78091.62 examples/s]
Generating train split: 105386709 examples [1:55:00, 79342.22 examples/s]
Generating train split: 105394759 examples [1:55:00, 79685.50 examples/s]
Generating train split: 105403320 examples [1:55:00, 81427.90 examples/s]
Generating train split: 105411483 examples [1:55:00, 79378.69 examples/s]
Generating train split: 105419443 examples [1:55:00, 79136.28 examples/s]
Generating train split: 105427375 examples [1:55:00, 77874.39 examples/s]
Generating train split: 105435178 examples [1:55:00, 77378.29 examples/s]
Generating train split: 105442929 examples [1:55:00, 75088.66 examples/s]
Generating train split: 105450465 examples [1:55:01, 66307.04 examples/s]
Generating train split: 105457284 examples [1:55:01, 62348.89 examples/s]
Generating train split: 105463669 examples [1:55:01, 51545.69 examples/s]
Generating train split: 105469191 examples [1:55:01, 32904.62 examples/s]
Generating train split: 105473528 examples [1:55:02, 21921.30 examples/s]
Generating train split: 105476860 examples [1:55:02, 20333.26 examples/s]
Generating train split: 105479670 examples [1:55:02, 20562.41 examples/s]
Generating train split: 105482287 examples [1:55:02, 16820.43 examples/s]
Generating train split: 105484409 examples [1:55:03, 14309.50 examples/s]
Generating train split: 105486163 examples [1:55:03, 12416.93 examples/s]
Generating train split: 105487623 examples [1:55:03, 11844.84 examples/s]
Generating train split: 105488938 examples [1:55:03, 11361.84 examples/s]
Generating train split: 105490802 examples [1:55:03, 12678.43 examples/s]
Generating train split: 105492201 examples [1:55:03, 12434.11 examples/s]
Generating train split: 105493536 examples [1:55:04, 8581.37 examples/s] 
Generating train split: 105494602 examples [1:55:04, 6413.29 examples/s]
Generating train split: 105495783 examples [1:55:04, 7193.89 examples/s]
Generating train split: 105496722 examples [1:55:04, 6653.79 examples/s]
Generating train split: 105497535 examples [1:55:04, 4984.80 examples/s]
Generating train split: 105498828 examples [1:55:05, 6168.54 examples/s]
Generating train split: 105499641 examples [1:55:05, 6211.49 examples/s]
Generating train split: 105500400 examples [1:55:05, 4401.54 examples/s]
Generating train split: 105501900 examples [1:55:05, 6116.26 examples/s]
Generating train split: 105502768 examples [1:55:05, 6047.13 examples/s]
Generating train split: 105503552 examples [1:55:06, 4720.68 examples/s]
Generating train split: 105504595 examples [1:55:06, 5701.00 examples/s]
Generating train split: 105505419 examples [1:55:06, 6186.45 examples/s]
Generating train split: 105506208 examples [1:55:06, 6403.66 examples/s]
Generating train split: 105506962 examples [1:55:06, 5245.65 examples/s]
Generating train split: 105508202 examples [1:55:06, 6729.07 examples/s]
Generating train split: 105509419 examples [1:55:06, 7975.55 examples/s]
Generating train split: 105510354 examples [1:55:07, 6037.47 examples/s]
Generating train split: 105511122 examples [1:55:07, 5466.77 examples/s]
Generating train split: 105512443 examples [1:55:07, 7009.23 examples/s]
Generating train split: 105513317 examples [1:55:07, 5720.85 examples/s]
Generating train split: 105515233 examples [1:55:07, 8344.84 examples/s]
Generating train split: 105516302 examples [1:55:07, 6938.81 examples/s]
Generating train split: 105517490 examples [1:55:08, 7908.20 examples/s]
Generating train split: 105518473 examples [1:55:08, 7202.16 examples/s]
Generating train split: 105519331 examples [1:55:08, 6220.37 examples/s]
Generating train split: 105520078 examples [1:55:08, 5686.61 examples/s]
Generating train split: 105520731 examples [1:55:08, 5386.93 examples/s]
Generating train split: 105521325 examples [1:55:08, 4996.36 examples/s]
Generating train split: 105522561 examples [1:55:08, 6570.92 examples/s]
Generating train split: 105523656 examples [1:55:09, 7511.32 examples/s]
Generating train split: 105524491 examples [1:55:09, 5195.01 examples/s]
Generating train split: 105525918 examples [1:55:09, 6897.79 examples/s]
Generating train split: 105526867 examples [1:55:09, 7450.83 examples/s]
Generating train split: 105528004 examples [1:55:09, 8363.77 examples/s]
Generating train split: 105528981 examples [1:55:09, 5855.41 examples/s]
Generating train split: 105536727 examples [1:55:10, 19752.98 examples/s]
Generating train split: 105544544 examples [1:55:10, 32426.74 examples/s]
Generating train split: 105548900 examples [1:55:10, 27722.67 examples/s]
Generating train split: 105552566 examples [1:55:11, 11341.40 examples/s]
Generating train split: 105555271 examples [1:55:11, 12635.40 examples/s]
Generating train split: 105557807 examples [1:55:11, 11803.09 examples/s]
Generating train split: 105559879 examples [1:55:11, 9964.86 examples/s] 
Generating train split: 105561510 examples [1:55:12, 9470.59 examples/s]
Generating train split: 105562887 examples [1:55:12, 7214.93 examples/s]
Generating train split: 105564204 examples [1:55:12, 7939.91 examples/s]
Generating train split: 105566190 examples [1:55:12, 9673.63 examples/s]
Generating train split: 105567575 examples [1:55:12, 10250.41 examples/s]
Generating train split: 105575845 examples [1:55:12, 24530.88 examples/s]
Generating train split: 105585654 examples [1:55:13, 40685.71 examples/s]
Generating train split: 105590992 examples [1:55:13, 15159.02 examples/s]
Generating train split: 105594910 examples [1:55:14, 11301.99 examples/s]
Generating train split: 105597851 examples [1:55:15, 9155.15 examples/s] 
Generating train split: 105600061 examples [1:55:15, 9194.12 examples/s]
Generating train split: 105601895 examples [1:55:15, 9932.44 examples/s]
Generating train split: 105604091 examples [1:55:15, 11334.75 examples/s]
Generating train split: 105605984 examples [1:55:16, 8169.52 examples/s] 
Generating train split: 105607453 examples [1:55:16, 8617.02 examples/s]
Generating train split: 105608795 examples [1:55:16, 6036.43 examples/s]
Generating train split: 105610054 examples [1:55:16, 6772.20 examples/s]
Generating train split: 105611147 examples [1:55:16, 6309.32 examples/s]
Generating train split: 105612501 examples [1:55:17, 7366.45 examples/s]
Generating train split: 105613555 examples [1:55:17, 6091.19 examples/s]
Generating train split: 105614403 examples [1:55:17, 5884.51 examples/s]
Generating train split: 105615155 examples [1:55:17, 5193.06 examples/s]
Generating train split: 105616862 examples [1:55:17, 7230.24 examples/s]
Generating train split: 105617819 examples [1:55:17, 7437.71 examples/s]
Generating train split: 105618744 examples [1:55:18, 6121.32 examples/s]
Generating train split: 105619584 examples [1:55:18, 6551.46 examples/s]
Generating train split: 105620567 examples [1:55:18, 7255.48 examples/s]
Generating train split: 105621409 examples [1:55:18, 5689.18 examples/s]
Generating train split: 105622116 examples [1:55:18, 5730.75 examples/s]
Generating train split: 105622788 examples [1:55:18, 5072.96 examples/s]
Generating train split: 105623368 examples [1:55:19, 5144.62 examples/s]
Generating train split: 105623988 examples [1:55:19, 5361.57 examples/s]
Generating train split: 105624940 examples [1:55:19, 6301.30 examples/s]
Generating train split: 105625666 examples [1:55:19, 6534.32 examples/s]
Generating train split: 105626370 examples [1:55:19, 6110.22 examples/s]
Generating train split: 105627369 examples [1:55:19, 6989.53 examples/s]
Generating train split: 105628481 examples [1:55:19, 8084.40 examples/s]
Generating train split: 105629331 examples [1:55:19, 7997.90 examples/s]
Generating train split: 105630166 examples [1:55:19, 7619.46 examples/s]
Generating train split: 105632647 examples [1:55:19, 12268.81 examples/s]
Generating train split: 105633934 examples [1:55:20, 12208.12 examples/s]
Generating train split: 105635202 examples [1:55:20, 11838.84 examples/s]
Generating train split: 105636420 examples [1:55:20, 10717.37 examples/s]
Generating train split: 105637551 examples [1:55:20, 8674.86 examples/s] 
Generating train split: 105638508 examples [1:55:20, 7696.61 examples/s]
Generating train split: 105639375 examples [1:55:20, 7903.04 examples/s]
Generating train split: 105640221 examples [1:55:21, 4253.52 examples/s]
Generating train split: 105641231 examples [1:55:21, 5127.77 examples/s]
Generating train split: 105641987 examples [1:55:21, 5469.45 examples/s]
Generating train split: 105642852 examples [1:55:21, 6106.60 examples/s]
Generating train split: 105643985 examples [1:55:21, 7263.40 examples/s]
Generating train split: 105644969 examples [1:55:21, 7671.07 examples/s]
Generating train split: 105645857 examples [1:55:21, 7306.21 examples/s]
Generating train split: 105646816 examples [1:55:22, 7843.94 examples/s]
Generating train split: 105647678 examples [1:55:22, 7052.55 examples/s]
Generating train split: 105651057 examples [1:55:22, 13626.78 examples/s]
Generating train split: 105653244 examples [1:55:22, 15689.35 examples/s]
Generating train split: 105655071 examples [1:55:22, 16384.12 examples/s]
Generating train split: 105663524 examples [1:55:22, 35332.27 examples/s]
Generating train split: 105672429 examples [1:55:22, 50599.13 examples/s]
Generating train split: 105677738 examples [1:55:23, 19969.79 examples/s]
Generating train split: 105681706 examples [1:55:23, 17456.69 examples/s]
Generating train split: 105684865 examples [1:55:24, 13663.10 examples/s]
Generating train split: 105687304 examples [1:55:24, 14001.53 examples/s]
Generating train split: 105689477 examples [1:55:24, 13967.88 examples/s]
Generating train split: 105691417 examples [1:55:24, 12037.26 examples/s]
Generating train split: 105693011 examples [1:55:24, 11741.36 examples/s]
Generating train split: 105694451 examples [1:55:24, 11896.84 examples/s]
Generating train split: 105695845 examples [1:55:25, 8765.04 examples/s] 
Generating train split: 105697146 examples [1:55:25, 9448.85 examples/s]
Generating train split: 105698308 examples [1:55:25, 5761.20 examples/s]
Generating train split: 105699196 examples [1:55:26, 4640.55 examples/s]
Generating train split: 105699892 examples [1:55:26, 4465.07 examples/s]
Generating train split: 105700494 examples [1:55:26, 4452.10 examples/s]
Generating train split: 105701058 examples [1:55:26, 3896.76 examples/s]
Generating train split: 105701637 examples [1:55:26, 4200.23 examples/s]
Generating train split: 105703025 examples [1:55:26, 6010.69 examples/s]
Generating train split: 105703804 examples [1:55:27, 6093.60 examples/s]
Generating train split: 105705003 examples [1:55:27, 7408.38 examples/s]
Generating train split: 105705886 examples [1:55:27, 5808.50 examples/s]
Generating train split: 105707119 examples [1:55:27, 7148.00 examples/s]
Generating train split: 105708943 examples [1:55:27, 9661.51 examples/s]
Generating train split: 105710140 examples [1:55:27, 10223.12 examples/s]
Generating train split: 105711318 examples [1:55:27, 8742.27 examples/s] 
Generating train split: 105712334 examples [1:55:28, 6623.12 examples/s]
Generating train split: 105713174 examples [1:55:28, 5605.60 examples/s]
Generating train split: 105713869 examples [1:55:28, 5020.97 examples/s]
Generating train split: 105715099 examples [1:55:28, 6331.97 examples/s]
Generating train split: 105715880 examples [1:55:28, 6092.30 examples/s]
Generating train split: 105716598 examples [1:55:28, 5974.00 examples/s]
Generating train split: 105717269 examples [1:55:29, 4736.17 examples/s]
Generating train split: 105717999 examples [1:55:29, 5242.26 examples/s]
Generating train split: 105718781 examples [1:55:29, 5787.15 examples/s]
Generating train split: 105719438 examples [1:55:29, 4793.38 examples/s]
Generating train split: 105719994 examples [1:55:29, 3853.82 examples/s]
Generating train split: 105720454 examples [1:55:30, 2549.81 examples/s]
Generating train split: 105721268 examples [1:55:30, 3347.60 examples/s]
Generating train split: 105723084 examples [1:55:30, 5925.77 examples/s]
Generating train split: 105723970 examples [1:55:30, 4641.95 examples/s]
Generating train split: 105724689 examples [1:55:30, 4774.76 examples/s]
Generating train split: 105725822 examples [1:55:30, 5950.46 examples/s]
Generating train split: 105726608 examples [1:55:31, 4582.16 examples/s]
Generating train split: 105727719 examples [1:55:31, 5730.75 examples/s]
Generating train split: 105728503 examples [1:55:31, 5537.69 examples/s]
Generating train split: 105729204 examples [1:55:31, 3257.53 examples/s]
Generating train split: 105731877 examples [1:55:32, 6557.49 examples/s]
Generating train split: 105733048 examples [1:55:32, 7143.70 examples/s]
Generating train split: 105734157 examples [1:55:32, 4829.59 examples/s]
Generating train split: 105735648 examples [1:55:32, 6226.81 examples/s]
Generating train split: 105736685 examples [1:55:32, 6365.31 examples/s]
Generating train split: 105737616 examples [1:55:33, 5132.86 examples/s]
Generating train split: 105739582 examples [1:55:33, 7458.65 examples/s]
Generating train split: 105740691 examples [1:55:33, 7108.47 examples/s]
Generating train split: 105741658 examples [1:55:33, 7194.42 examples/s]
Generating train split: 105742561 examples [1:55:33, 4602.88 examples/s]
Generating train split: 105743597 examples [1:55:34, 5439.35 examples/s]
Generating train split: 105744393 examples [1:55:34, 4346.55 examples/s]
Generating train split: 105745276 examples [1:55:34, 5042.71 examples/s]
Generating train split: 105745982 examples [1:55:34, 5398.88 examples/s]
Generating train split: 105746885 examples [1:55:34, 6140.66 examples/s]
Generating train split: 105747659 examples [1:55:34, 5375.83 examples/s]
Generating train split: 105748488 examples [1:55:34, 5969.64 examples/s]
Generating train split: 105749229 examples [1:55:35, 6303.14 examples/s]
Generating train split: 105749945 examples [1:55:35, 5193.62 examples/s]
Generating train split: 105750818 examples [1:55:35, 5959.54 examples/s]
Generating train split: 105751510 examples [1:55:35, 4950.02 examples/s]
Generating train split: 105752183 examples [1:55:35, 5300.10 examples/s]
Generating train split: 105752791 examples [1:55:35, 4676.06 examples/s]
Generating train split: 105753324 examples [1:55:36, 3547.28 examples/s]
Generating train split: 105753904 examples [1:55:36, 3953.36 examples/s]
Generating train split: 105756363 examples [1:55:36, 8284.23 examples/s]
Generating train split: 105757950 examples [1:55:36, 9841.81 examples/s]
Generating train split: 105759126 examples [1:55:36, 9091.17 examples/s]
Generating train split: 105760177 examples [1:55:36, 6278.61 examples/s]
Generating train split: 105761020 examples [1:55:37, 6412.99 examples/s]
Generating train split: 105762784 examples [1:55:37, 8529.03 examples/s]
Generating train split: 105763832 examples [1:55:37, 4255.42 examples/s]
Generating train split: 105765466 examples [1:55:37, 5824.13 examples/s]
Generating train split: 105766503 examples [1:55:38, 4833.89 examples/s]
Generating train split: 105768024 examples [1:55:38, 6301.83 examples/s]
Generating train split: 105769062 examples [1:55:38, 4975.61 examples/s]
Generating train split: 105769881 examples [1:55:38, 5092.63 examples/s]
Generating train split: 105770627 examples [1:55:38, 5460.86 examples/s]
Generating train split: 105774935 examples [1:55:38, 12562.87 examples/s]
Generating train split: 105782389 examples [1:55:39, 25725.22 examples/s]
Generating train split: 105787730 examples [1:55:39, 32161.17 examples/s]
Generating train split: 105791781 examples [1:55:39, 12097.73 examples/s]
Generating train split: 105794766 examples [1:55:40, 13639.01 examples/s]
Generating train split: 105797550 examples [1:55:40, 10580.65 examples/s]
Generating train split: 105799684 examples [1:55:40, 11563.19 examples/s]
Generating train split: 105801716 examples [1:55:41, 9633.63 examples/s] 
Generating train split: 105803322 examples [1:55:41, 6398.94 examples/s]
Generating train split: 105805183 examples [1:55:41, 7638.89 examples/s]
Generating train split: 105807013 examples [1:55:41, 8979.90 examples/s]
Generating train split: 105808542 examples [1:55:41, 9868.41 examples/s]
Generating train split: 105810050 examples [1:55:42, 6521.77 examples/s]
Generating train split: 105812639 examples [1:55:42, 9103.34 examples/s]
Generating train split: 105820687 examples [1:55:42, 20529.87 examples/s]
Generating train split: 105829363 examples [1:55:42, 32832.06 examples/s]
Generating train split: 105834423 examples [1:55:43, 19161.23 examples/s]
Generating train split: 105838253 examples [1:55:43, 19260.11 examples/s]
Generating train split: 105841518 examples [1:55:43, 16371.26 examples/s]
Generating train split: 105844131 examples [1:55:44, 9780.79 examples/s] 
Generating train split: 105846077 examples [1:55:45, 6858.27 examples/s]
Generating train split: 105847534 examples [1:55:45, 6793.71 examples/s]
Generating train split: 105848829 examples [1:55:45, 7216.74 examples/s]
Generating train split: 105849987 examples [1:55:45, 7082.67 examples/s]
Generating train split: 105850994 examples [1:55:45, 7396.98 examples/s]
Generating train split: 105852321 examples [1:55:45, 8327.92 examples/s]
Generating train split: 105853666 examples [1:55:45, 9254.80 examples/s]
Generating train split: 105854829 examples [1:55:46, 8418.21 examples/s]
Generating train split: 105857676 examples [1:55:46, 12520.21 examples/s]
Generating train split: 105859240 examples [1:55:46, 13139.85 examples/s]
Generating train split: 105860790 examples [1:55:46, 13059.12 examples/s]
Generating train split: 105862609 examples [1:55:46, 14318.22 examples/s]
Generating train split: 105864183 examples [1:55:46, 7727.53 examples/s] 
Generating train split: 105866367 examples [1:55:47, 10045.01 examples/s]
Generating train split: 105867872 examples [1:55:47, 7042.31 examples/s] 
Generating train split: 105869047 examples [1:55:47, 6747.55 examples/s]
Generating train split: 105870043 examples [1:55:47, 6447.60 examples/s]
Generating train split: 105871560 examples [1:55:47, 7882.01 examples/s]
Generating train split: 105872616 examples [1:55:48, 8377.51 examples/s]
Generating train split: 105874228 examples [1:55:48, 10028.08 examples/s]
Generating train split: 105875457 examples [1:55:48, 8189.01 examples/s] 
Generating train split: 105876486 examples [1:55:48, 7777.77 examples/s]
Generating train split: 105877408 examples [1:55:48, 4899.43 examples/s]
Generating train split: 105878131 examples [1:55:49, 5212.65 examples/s]
Generating train split: 105879104 examples [1:55:49, 6001.56 examples/s]
Generating train split: 105881270 examples [1:55:49, 9171.05 examples/s]
Generating train split: 105882466 examples [1:55:49, 8024.52 examples/s]
Generating train split: 105883491 examples [1:55:49, 7294.98 examples/s]
Generating train split: 105884378 examples [1:55:49, 6492.69 examples/s]
Generating train split: 105885145 examples [1:55:50, 4370.74 examples/s]
Generating train split: 105885744 examples [1:55:50, 4363.95 examples/s]
Generating train split: 105888032 examples [1:55:50, 7571.75 examples/s]
Generating train split: 105889113 examples [1:55:50, 6616.89 examples/s]
Generating train split: 105890680 examples [1:55:50, 8299.26 examples/s]
Generating train split: 105891782 examples [1:55:50, 6748.65 examples/s]
Generating train split: 105892686 examples [1:55:51, 5876.29 examples/s]
Generating train split: 105893441 examples [1:55:51, 4837.88 examples/s]
Generating train split: 105895292 examples [1:55:51, 7079.06 examples/s]
Generating train split: 105896271 examples [1:55:51, 6890.37 examples/s]
Generating train split: 105897142 examples [1:55:51, 6404.29 examples/s]
Generating train split: 105897912 examples [1:55:52, 4678.32 examples/s]
Generating train split: 105898964 examples [1:55:52, 5634.49 examples/s]
Generating train split: 105900070 examples [1:55:52, 6677.35 examples/s]
Generating train split: 105900929 examples [1:55:52, 4308.37 examples/s]
Generating train split: 105902484 examples [1:55:52, 6068.37 examples/s]
Generating train split: 105904002 examples [1:55:52, 7671.85 examples/s]
Generating train split: 105905084 examples [1:55:53, 5483.82 examples/s]
Generating train split: 105906477 examples [1:55:53, 6856.89 examples/s]
Generating train split: 105908211 examples [1:55:53, 8832.66 examples/s]
Generating train split: 105910037 examples [1:55:53, 10776.59 examples/s]
Generating train split: 105911441 examples [1:55:53, 8769.98 examples/s] 
Generating train split: 105912607 examples [1:55:54, 7701.82 examples/s]
Generating train split: 105914479 examples [1:55:54, 9809.45 examples/s]
Generating train split: 105915725 examples [1:55:54, 8225.35 examples/s]
Generating train split: 105916766 examples [1:55:54, 8625.69 examples/s]
Generating train split: 105917816 examples [1:55:54, 8195.51 examples/s]
Generating train split: 105918761 examples [1:55:55, 4888.58 examples/s]
Generating train split: 105919495 examples [1:55:55, 4913.76 examples/s]
Generating train split: 105920164 examples [1:55:55, 4056.98 examples/s]
Generating train split: 105921108 examples [1:55:55, 4900.20 examples/s]
Generating train split: 105921765 examples [1:55:55, 4897.50 examples/s]
Generating train split: 105922377 examples [1:55:55, 4178.72 examples/s]
Generating train split: 105925096 examples [1:55:56, 8483.31 examples/s]
Generating train split: 105926275 examples [1:55:56, 7735.83 examples/s]
Generating train split: 105927279 examples [1:55:56, 5697.64 examples/s]
Generating train split: 105929311 examples [1:55:56, 8140.10 examples/s]
Generating train split: 105930648 examples [1:55:56, 9121.75 examples/s]
Generating train split: 105932257 examples [1:55:56, 10561.35 examples/s]
Generating train split: 105933575 examples [1:55:57, 7012.10 examples/s] 
Generating train split: 105935352 examples [1:55:57, 8879.24 examples/s]
Generating train split: 105936615 examples [1:55:57, 4800.90 examples/s]
Generating train split: 105937562 examples [1:55:58, 4422.86 examples/s]
Generating train split: 105939305 examples [1:55:58, 6075.32 examples/s]
Generating train split: 105940362 examples [1:55:58, 6473.61 examples/s]
Generating train split: 105941352 examples [1:55:58, 4888.55 examples/s]
Generating train split: 105942137 examples [1:55:58, 4650.03 examples/s]
Generating train split: 105942803 examples [1:55:59, 4029.46 examples/s]
Generating train split: 105944184 examples [1:55:59, 5515.90 examples/s]
Generating train split: 105945440 examples [1:55:59, 6764.47 examples/s]
Generating train split: 105946370 examples [1:55:59, 6942.12 examples/s]
Generating train split: 105947248 examples [1:55:59, 4756.17 examples/s]
Generating train split: 105947949 examples [1:56:00, 4773.52 examples/s]
Generating train split: 105955323 examples [1:56:00, 17296.28 examples/s]
Generating train split: 105964188 examples [1:56:00, 31987.81 examples/s]
Generating train split: 105968714 examples [1:56:00, 21034.88 examples/s]
Generating train split: 105972228 examples [1:56:00, 21082.68 examples/s]
Generating train split: 105980470 examples [1:56:00, 31754.13 examples/s]
Generating train split: 105988352 examples [1:56:00, 41108.56 examples/s]
Generating train split: 105993960 examples [1:56:01, 20048.10 examples/s]
Generating train split: 106001614 examples [1:56:01, 27100.28 examples/s]
Generating train split: 106011134 examples [1:56:01, 37407.87 examples/s]
Generating train split: 106017649 examples [1:56:02, 21172.88 examples/s]
Generating train split: 106022502 examples [1:56:02, 18931.19 examples/s]
Generating train split: 106026316 examples [1:56:03, 11375.95 examples/s]
Generating train split: 106029123 examples [1:56:03, 12348.29 examples/s]
Generating train split: 106031711 examples [1:56:04, 10297.08 examples/s]
Generating train split: 106033709 examples [1:56:04, 10811.75 examples/s]
Generating train split: 106035537 examples [1:56:04, 10321.68 examples/s]
Generating train split: 106037076 examples [1:56:04, 9059.20 examples/s] 
Generating train split: 106039746 examples [1:56:04, 11379.58 examples/s]
Generating train split: 106041491 examples [1:56:05, 12327.96 examples/s]
Generating train split: 106043194 examples [1:56:05, 12584.19 examples/s]
Generating train split: 106044790 examples [1:56:05, 9790.19 examples/s] 
Generating train split: 106046864 examples [1:56:05, 11701.36 examples/s]
Generating train split: 106048391 examples [1:56:05, 10644.96 examples/s]
Generating train split: 106049743 examples [1:56:05, 11201.39 examples/s]
Generating train split: 106051068 examples [1:56:06, 7352.86 examples/s] 
Generating train split: 106052549 examples [1:56:06, 8557.42 examples/s]
Generating train split: 106053952 examples [1:56:06, 9090.50 examples/s]
Generating train split: 106055092 examples [1:56:06, 5806.06 examples/s]
Generating train split: 106055973 examples [1:56:07, 5844.68 examples/s]
Generating train split: 106057516 examples [1:56:07, 7383.86 examples/s]
Generating train split: 106058514 examples [1:56:07, 6528.29 examples/s]
Generating train split: 106059550 examples [1:56:07, 7226.49 examples/s]
Generating train split: 106060456 examples [1:56:07, 5029.96 examples/s]
Generating train split: 106061888 examples [1:56:07, 6558.74 examples/s]
Generating train split: 106063766 examples [1:56:08, 8876.54 examples/s]
Generating train split: 106064975 examples [1:56:08, 8128.99 examples/s]
Generating train split: 106070210 examples [1:56:08, 17234.37 examples/s]
Generating train split: 106078843 examples [1:56:08, 32939.31 examples/s]
Generating train split: 106085365 examples [1:56:08, 40838.05 examples/s]
Generating train split: 106090265 examples [1:56:08, 22485.37 examples/s]
Generating train split: 106094027 examples [1:56:09, 16672.28 examples/s]
Generating train split: 106096934 examples [1:56:09, 12204.04 examples/s]
Generating train split: 106099152 examples [1:56:10, 11079.80 examples/s]
Generating train split: 106100951 examples [1:56:10, 9752.23 examples/s] 
Generating train split: 106102400 examples [1:56:10, 7654.83 examples/s]
Generating train split: 106103525 examples [1:56:10, 7618.48 examples/s]
Generating train split: 106105162 examples [1:56:11, 8777.67 examples/s]
Generating train split: 106106367 examples [1:56:11, 5955.59 examples/s]
Generating train split: 106108778 examples [1:56:11, 8273.44 examples/s]
Generating train split: 106110223 examples [1:56:11, 9184.72 examples/s]
Generating train split: 106111605 examples [1:56:12, 6795.87 examples/s]
Generating train split: 106112690 examples [1:56:12, 6217.04 examples/s]
Generating train split: 106113589 examples [1:56:12, 5008.24 examples/s]
Generating train split: 106121694 examples [1:56:12, 15669.37 examples/s]
Generating train split: 106129873 examples [1:56:12, 26702.74 examples/s]
Generating train split: 106134382 examples [1:56:12, 29151.06 examples/s]
Generating train split: 106138676 examples [1:56:13, 14534.18 examples/s]
Generating train split: 106141877 examples [1:56:13, 16480.03 examples/s]
Generating train split: 106150597 examples [1:56:13, 26719.57 examples/s]
Generating train split: 106157972 examples [1:56:13, 34621.35 examples/s]
Generating train split: 106163495 examples [1:56:14, 14267.35 examples/s]
Generating train split: 106167534 examples [1:56:16, 8263.78 examples/s] 
Generating train split: 106170464 examples [1:56:16, 8773.98 examples/s]
Generating train split: 106172877 examples [1:56:16, 8890.18 examples/s]
Generating train split: 106174848 examples [1:56:16, 9387.94 examples/s]
Generating train split: 106177088 examples [1:56:16, 10775.05 examples/s]
Generating train split: 106178996 examples [1:56:16, 11596.92 examples/s]
Generating train split: 106180813 examples [1:56:17, 9125.70 examples/s] 
Generating train split: 106182250 examples [1:56:17, 9776.91 examples/s]
Generating train split: 106184027 examples [1:56:17, 11078.69 examples/s]
Generating train split: 106185633 examples [1:56:17, 12022.79 examples/s]
Generating train split: 106187186 examples [1:56:17, 8839.90 examples/s] 
Generating train split: 106188422 examples [1:56:18, 7339.71 examples/s]
Generating train split: 106190839 examples [1:56:18, 10025.74 examples/s]
Generating train split: 106192258 examples [1:56:18, 7322.81 examples/s] 
Generating train split: 106193442 examples [1:56:18, 7983.92 examples/s]
Generating train split: 106200773 examples [1:56:18, 19689.81 examples/s]
Generating train split: 106209778 examples [1:56:18, 34031.36 examples/s]
Generating train split: 106214776 examples [1:56:19, 37101.41 examples/s]
Generating train split: 106219539 examples [1:56:19, 21443.72 examples/s]
Generating train split: 106228194 examples [1:56:19, 31667.36 examples/s]
Generating train split: 106235663 examples [1:56:19, 39230.53 examples/s]
Generating train split: 106241424 examples [1:56:20, 18274.51 examples/s]
Generating train split: 106245679 examples [1:56:20, 15337.81 examples/s]
Generating train split: 106248955 examples [1:56:21, 14695.82 examples/s]
Generating train split: 106251625 examples [1:56:21, 13832.80 examples/s]
Generating train split: 106253829 examples [1:56:21, 12803.23 examples/s]
Generating train split: 106255665 examples [1:56:21, 13411.51 examples/s]
Generating train split: 106257462 examples [1:56:21, 11088.48 examples/s]
Generating train split: 106258915 examples [1:56:22, 10927.64 examples/s]
Generating train split: 106260244 examples [1:56:22, 11255.20 examples/s]
Generating train split: 106262857 examples [1:56:22, 14077.19 examples/s]
Generating train split: 106264558 examples [1:56:22, 11564.59 examples/s]
Generating train split: 106265976 examples [1:56:22, 11611.60 examples/s]
Generating train split: 106267485 examples [1:56:22, 12165.73 examples/s]
Generating train split: 106269697 examples [1:56:22, 14211.83 examples/s]
Generating train split: 106271280 examples [1:56:23, 13269.65 examples/s]
Generating train split: 106272759 examples [1:56:23, 13628.72 examples/s]
Generating train split: 106274219 examples [1:56:23, 13759.48 examples/s]
Generating train split: 106277011 examples [1:56:23, 17514.49 examples/s]
Generating train split: 106279214 examples [1:56:23, 18557.72 examples/s]
Generating train split: 106281157 examples [1:56:23, 15049.89 examples/s]
Generating train split: 106282818 examples [1:56:23, 11434.64 examples/s]
Generating train split: 106285220 examples [1:56:23, 13701.25 examples/s]
Generating train split: 106286840 examples [1:56:24, 12938.58 examples/s]
Generating train split: 106288302 examples [1:56:24, 11938.61 examples/s]
Generating train split: 106289618 examples [1:56:24, 10666.78 examples/s]
Generating train split: 106292043 examples [1:56:24, 13568.16 examples/s]
Generating train split: 106293567 examples [1:56:24, 13093.85 examples/s]
Generating train split: 106299153 examples [1:56:24, 23370.03 examples/s]
Generating train split: 106308404 examples [1:56:24, 41036.04 examples/s]
Generating train split: 106313636 examples [1:56:24, 43989.52 examples/s]
Generating train split: 106318448 examples [1:56:25, 22957.70 examples/s]
Generating train split: 106322142 examples [1:56:26, 13856.87 examples/s]
Generating train split: 106324917 examples [1:56:26, 12739.28 examples/s]
Generating train split: 106327157 examples [1:56:26, 9408.43 examples/s] 
Generating train split: 106328863 examples [1:56:27, 7812.68 examples/s]
Generating train split: 106330192 examples [1:56:27, 6544.99 examples/s]
Generating train split: 106331233 examples [1:56:27, 6771.96 examples/s]
Generating train split: 106332922 examples [1:56:27, 8013.36 examples/s]
Generating train split: 106334104 examples [1:56:28, 6291.71 examples/s]
Generating train split: 106335032 examples [1:56:28, 5938.26 examples/s]
Generating train split: 106336039 examples [1:56:28, 6540.49 examples/s]
Generating train split: 106337648 examples [1:56:28, 8190.09 examples/s]
Generating train split: 106338732 examples [1:56:28, 6533.39 examples/s]
Generating train split: 106339734 examples [1:56:28, 7110.08 examples/s]
Generating train split: 106341124 examples [1:56:29, 8411.77 examples/s]
Generating train split: 106342166 examples [1:56:29, 7529.57 examples/s]
Generating train split: 106343070 examples [1:56:29, 7302.90 examples/s]
Generating train split: 106350982 examples [1:56:29, 23058.36 examples/s]
Generating train split: 106359513 examples [1:56:29, 37908.54 examples/s]
Generating train split: 106364151 examples [1:56:29, 38661.44 examples/s]
Generating train split: 106368611 examples [1:56:30, 18321.71 examples/s]
Generating train split: 106371978 examples [1:56:30, 12140.35 examples/s]
Generating train split: 106374507 examples [1:56:30, 12672.79 examples/s]
Generating train split: 106382777 examples [1:56:31, 21543.01 examples/s]
Generating train split: 106390340 examples [1:56:31, 29664.09 examples/s]
Generating train split: 106395368 examples [1:56:31, 16610.12 examples/s]
Generating train split: 106403450 examples [1:56:31, 23852.80 examples/s]
Generating train split: 106409919 examples [1:56:32, 29504.87 examples/s]
Generating train split: 106415381 examples [1:56:32, 14185.27 examples/s]
Generating train split: 106419380 examples [1:56:33, 11748.38 examples/s]
Generating train split: 106422403 examples [1:56:34, 8989.84 examples/s] 
Generating train split: 106424665 examples [1:56:34, 8556.77 examples/s]
Generating train split: 106426447 examples [1:56:34, 7068.99 examples/s]
Generating train split: 106428177 examples [1:56:35, 7912.79 examples/s]
Generating train split: 106429643 examples [1:56:35, 8449.75 examples/s]
Generating train split: 106431061 examples [1:56:35, 9189.13 examples/s]
Generating train split: 106432462 examples [1:56:35, 8811.24 examples/s]
Generating train split: 106434539 examples [1:56:35, 10774.72 examples/s]
Generating train split: 106436008 examples [1:56:35, 8527.64 examples/s] 
Generating train split: 106438284 examples [1:56:35, 10911.56 examples/s]
Generating train split: 106439804 examples [1:56:36, 10180.17 examples/s]
Generating train split: 106441116 examples [1:56:36, 9407.66 examples/s] 
Generating train split: 106442269 examples [1:56:36, 5518.69 examples/s]
Generating train split: 106443149 examples [1:56:36, 5644.51 examples/s]
Generating train split: 106443945 examples [1:56:37, 5068.65 examples/s]
Generating train split: 106444693 examples [1:56:37, 5189.66 examples/s]
Generating train split: 106445335 examples [1:56:37, 5062.72 examples/s]
Generating train split: 106445930 examples [1:56:37, 4081.20 examples/s]
Generating train split: 106447032 examples [1:56:37, 5269.91 examples/s]
Generating train split: 106447691 examples [1:56:38, 3891.42 examples/s]
Generating train split: 106448218 examples [1:56:38, 3751.81 examples/s]
Generating train split: 106448776 examples [1:56:38, 4012.45 examples/s]
Generating train split: 106449265 examples [1:56:38, 2963.00 examples/s]
Generating train split: 106449649 examples [1:56:38, 3100.39 examples/s]
Generating train split: 106451224 examples [1:56:38, 5547.37 examples/s]
Generating train split: 106451970 examples [1:56:39, 4927.88 examples/s]
Generating train split: 106452612 examples [1:56:39, 5155.44 examples/s]
Generating train split: 106454241 examples [1:56:39, 7622.99 examples/s]
Generating train split: 106455575 examples [1:56:39, 8989.22 examples/s]
Generating train split: 106456776 examples [1:56:39, 9757.49 examples/s]
Generating train split: 106458254 examples [1:56:39, 11085.19 examples/s]
Generating train split: 106459472 examples [1:56:39, 9722.52 examples/s] 
Generating train split: 106460551 examples [1:56:40, 5836.42 examples/s]
Generating train split: 106461387 examples [1:56:40, 5637.61 examples/s]
Generating train split: 106468564 examples [1:56:40, 17693.74 examples/s]
Generating train split: 106477856 examples [1:56:40, 33235.07 examples/s]
Generating train split: 106482518 examples [1:56:40, 22883.32 examples/s]
Generating train split: 106486177 examples [1:56:41, 17123.13 examples/s]
Generating train split: 106494595 examples [1:56:41, 26631.34 examples/s]
Generating train split: 106501542 examples [1:56:41, 33847.27 examples/s]
Generating train split: 106506788 examples [1:56:41, 27582.13 examples/s]
Generating train split: 106511026 examples [1:56:42, 19977.95 examples/s]
Generating train split: 106514309 examples [1:56:42, 21004.49 examples/s]
Generating train split: 106517385 examples [1:56:42, 12440.07 examples/s]
Generating train split: 106519693 examples [1:56:43, 8748.64 examples/s] 
Generating train split: 106528435 examples [1:56:43, 16080.31 examples/s]
Generating train split: 106538190 examples [1:56:43, 25652.40 examples/s]
Generating train split: 106543810 examples [1:56:44, 19820.86 examples/s]
Generating train split: 106548106 examples [1:56:44, 20891.55 examples/s]
Generating train split: 106556946 examples [1:56:44, 30081.72 examples/s]
Generating train split: 106562710 examples [1:56:44, 34407.44 examples/s]
Generating train split: 106568100 examples [1:56:45, 16535.18 examples/s]
Generating train split: 106572074 examples [1:56:45, 13658.69 examples/s]
Generating train split: 106575113 examples [1:56:45, 14286.55 examples/s]
Generating train split: 106584111 examples [1:56:46, 22971.01 examples/s]
Generating train split: 106591746 examples [1:56:46, 28867.31 examples/s]
Generating train split: 106596575 examples [1:56:46, 16950.84 examples/s]
Generating train split: 106600187 examples [1:56:46, 18650.65 examples/s]
Generating train split: 106603629 examples [1:56:47, 13716.43 examples/s]
Generating train split: 106606245 examples [1:56:47, 11524.69 examples/s]
Generating train split: 106608283 examples [1:56:47, 11453.64 examples/s]
Generating train split: 106610051 examples [1:56:48, 11827.22 examples/s]
Generating train split: 106611709 examples [1:56:48, 10982.08 examples/s]
Generating train split: 106613129 examples [1:56:48, 8697.35 examples/s] 
Generating train split: 106614297 examples [1:56:48, 9120.55 examples/s]
Generating train split: 106615438 examples [1:56:48, 7596.44 examples/s]
Generating train split: 106616380 examples [1:56:49, 7428.88 examples/s]
Generating train split: 106617615 examples [1:56:49, 8281.97 examples/s]
Generating train split: 106618580 examples [1:56:49, 7517.47 examples/s]
Generating train split: 106619428 examples [1:56:49, 5333.80 examples/s]
Generating train split: 106620340 examples [1:56:49, 5963.31 examples/s]
Generating train split: 106621652 examples [1:56:49, 7282.20 examples/s]
Generating train split: 106622561 examples [1:56:50, 6742.03 examples/s]
Generating train split: 106623718 examples [1:56:50, 7761.36 examples/s]
Generating train split: 106624627 examples [1:56:50, 8039.39 examples/s]
Generating train split: 106625672 examples [1:56:50, 8546.71 examples/s]
Generating train split: 106626607 examples [1:56:50, 8674.40 examples/s]
Generating train split: 106627541 examples [1:56:50, 6645.26 examples/s]
Generating train split: 106628319 examples [1:56:50, 6102.20 examples/s]
Generating train split: 106629013 examples [1:56:51, 5286.03 examples/s]
Generating train split: 106629614 examples [1:56:51, 4940.98 examples/s]
Generating train split: 106630613 examples [1:56:51, 5968.86 examples/s]
Generating train split: 106631281 examples [1:56:51, 5140.47 examples/s]
Generating train split: 106633780 examples [1:56:51, 9372.29 examples/s]
Generating train split: 106634904 examples [1:56:51, 7729.61 examples/s]
Generating train split: 106635854 examples [1:56:52, 6298.99 examples/s]
Generating train split: 106637647 examples [1:56:52, 7994.59 examples/s]
Generating train split: 106638603 examples [1:56:52, 6518.86 examples/s]
Generating train split: 106639400 examples [1:56:52, 6045.68 examples/s]
Generating train split: 106640883 examples [1:56:52, 7717.27 examples/s]
Generating train split: 106641815 examples [1:56:52, 6056.74 examples/s]
Generating train split: 106648326 examples [1:56:53, 17079.27 examples/s]
Generating train split: 106656654 examples [1:56:53, 31013.14 examples/s]
Generating train split: 106660904 examples [1:56:53, 23307.63 examples/s]
Generating train split: 106664327 examples [1:56:53, 15761.17 examples/s]
Generating train split: 106666958 examples [1:56:54, 12210.10 examples/s]
Generating train split: 106669006 examples [1:56:54, 10983.04 examples/s]
Generating train split: 106670673 examples [1:56:54, 11020.17 examples/s]
Generating train split: 106672180 examples [1:56:54, 9116.39 examples/s] 
Generating train split: 106673397 examples [1:56:55, 8868.48 examples/s]
Generating train split: 106674487 examples [1:56:55, 6643.74 examples/s]
Generating train split: 106675342 examples [1:56:55, 5623.01 examples/s]
Generating train split: 106676046 examples [1:56:56, 3550.34 examples/s]
Generating train split: 106677707 examples [1:56:56, 4910.42 examples/s]
Generating train split: 106678520 examples [1:56:56, 5030.23 examples/s]
Generating train split: 106679730 examples [1:56:56, 6097.87 examples/s]
Generating train split: 106681157 examples [1:56:56, 7554.75 examples/s]
Generating train split: 106682687 examples [1:56:56, 9116.72 examples/s]
Generating train split: 106683874 examples [1:56:57, 5949.24 examples/s]
Generating train split: 106684800 examples [1:56:57, 5882.24 examples/s]
Generating train split: 106686393 examples [1:56:57, 7389.61 examples/s]
Generating train split: 106687365 examples [1:56:57, 7508.42 examples/s]
Generating train split: 106688293 examples [1:56:57, 6170.09 examples/s]
Generating train split: 106689222 examples [1:56:57, 6670.72 examples/s]
Generating train split: 106690034 examples [1:56:58, 5565.96 examples/s]
Generating train split: 106691283 examples [1:56:58, 6903.24 examples/s]
Generating train split: 106692496 examples [1:56:58, 8033.91 examples/s]
Generating train split: 106693816 examples [1:56:58, 9121.64 examples/s]
Generating train split: 106694856 examples [1:56:58, 9248.65 examples/s]
Generating train split: 106696179 examples [1:56:58, 10254.99 examples/s]
Generating train split: 106697283 examples [1:56:58, 9580.07 examples/s] 
Generating train split: 106698308 examples [1:56:58, 7972.44 examples/s]
Generating train split: 106699406 examples [1:56:59, 8505.36 examples/s]
Generating train split: 106700327 examples [1:56:59, 5877.33 examples/s]
Generating train split: 106701076 examples [1:56:59, 6159.05 examples/s]
Generating train split: 106706375 examples [1:56:59, 16220.14 examples/s]
Generating train split: 106715531 examples [1:56:59, 33903.94 examples/s]
Generating train split: 106720523 examples [1:56:59, 37893.30 examples/s]
Generating train split: 106724979 examples [1:57:00, 17172.17 examples/s]
Generating train split: 106728326 examples [1:57:00, 15429.83 examples/s]
Generating train split: 106731021 examples [1:57:00, 16581.36 examples/s]
Generating train split: 106733769 examples [1:57:00, 18325.01 examples/s]
Generating train split: 106737047 examples [1:57:00, 21011.53 examples/s]
Generating train split: 106741452 examples [1:57:01, 25846.44 examples/s]
Generating train split: 106747614 examples [1:57:01, 34098.36 examples/s]
Generating train split: 106755247 examples [1:57:01, 44559.16 examples/s]
Generating train split: 106761985 examples [1:57:01, 50513.99 examples/s]
Generating train split: 106768483 examples [1:57:01, 54429.76 examples/s]
Generating train split: 106774969 examples [1:57:01, 57325.55 examples/s]
Generating train split: 106781600 examples [1:57:01, 59865.52 examples/s]
Generating train split: 106787849 examples [1:57:01, 55199.84 examples/s]
Generating train split: 106794902 examples [1:57:01, 59373.51 examples/s]
Generating train split: 106801343 examples [1:57:02, 60771.96 examples/s]
Generating train split: 106808534 examples [1:57:02, 63936.38 examples/s]
Generating train split: 106815054 examples [1:57:02, 62696.00 examples/s]
Generating train split: 106821429 examples [1:57:02, 62485.35 examples/s]
Generating train split: 106827754 examples [1:57:02, 60867.96 examples/s]
Generating train split: 106833892 examples [1:57:02, 60673.39 examples/s]
Generating train split: 106839996 examples [1:57:02, 57485.79 examples/s]
Generating train split: 106845802 examples [1:57:02, 56994.86 examples/s]
Generating train split: 106851551 examples [1:57:02, 54063.63 examples/s]
Generating train split: 106857011 examples [1:57:02, 51464.98 examples/s]
Generating train split: 106862202 examples [1:57:03, 39829.53 examples/s]
Generating train split: 106866584 examples [1:57:03, 40067.97 examples/s]
Generating train split: 106871822 examples [1:57:03, 43050.65 examples/s]
Generating train split: 106876394 examples [1:57:03, 41289.05 examples/s]
Generating train split: 106880721 examples [1:57:03, 39618.43 examples/s]
Generating train split: 106884823 examples [1:57:03, 34232.08 examples/s]
Generating train split: 106888442 examples [1:57:04, 26514.78 examples/s]
Generating train split: 106891982 examples [1:57:04, 28363.67 examples/s]
Generating train split: 106895149 examples [1:57:04, 25915.22 examples/s]
Generating train split: 106897994 examples [1:57:04, 22096.32 examples/s]
Generating train split: 106901995 examples [1:57:04, 25886.54 examples/s]
Generating train split: 106905641 examples [1:57:04, 28340.43 examples/s]
Generating train split: 106908769 examples [1:57:04, 25490.55 examples/s]
Generating train split: 106911560 examples [1:57:05, 21666.72 examples/s]
Generating train split: 106913964 examples [1:57:05, 17471.54 examples/s]
Generating train split: 106915973 examples [1:57:05, 11059.87 examples/s]
Generating train split: 106917533 examples [1:57:05, 11155.87 examples/s]
Generating train split: 106919047 examples [1:57:05, 11806.35 examples/s]
Generating train split: 106920521 examples [1:57:06, 12369.24 examples/s]
Generating train split: 106921984 examples [1:57:06, 9597.14 examples/s] 
Generating train split: 106923176 examples [1:57:06, 9538.42 examples/s]
Generating train split: 106928401 examples [1:57:06, 18202.09 examples/s]
Generating train split: 106937010 examples [1:57:06, 33452.38 examples/s]
Generating train split: 106942495 examples [1:57:06, 38256.10 examples/s]
Generating train split: 106947044 examples [1:57:07, 17028.62 examples/s]
Generating train split: 106950444 examples [1:57:07, 11172.31 examples/s]
Generating train split: 106952996 examples [1:57:08, 8616.98 examples/s] 
Generating train split: 106954911 examples [1:57:08, 9361.51 examples/s]
Generating train split: 106956718 examples [1:57:08, 8256.61 examples/s]
Generating train split: 106958234 examples [1:57:09, 9024.14 examples/s]
Generating train split: 106959686 examples [1:57:09, 9724.62 examples/s]
Generating train split: 106961431 examples [1:57:09, 10961.00 examples/s]
Generating train split: 106962957 examples [1:57:09, 9110.45 examples/s] 
Generating train split: 106964207 examples [1:57:09, 9506.51 examples/s]
Generating train split: 106965528 examples [1:57:09, 10085.90 examples/s]
Generating train split: 106966747 examples [1:57:09, 10062.59 examples/s]
Generating train split: 106967900 examples [1:57:10, 7949.60 examples/s] 
Generating train split: 106970914 examples [1:57:10, 12347.00 examples/s]
Generating train split: 106972490 examples [1:57:10, 11803.81 examples/s]
Generating train split: 106974229 examples [1:57:10, 12999.92 examples/s]
Generating train split: 106975746 examples [1:57:10, 10038.91 examples/s]
Generating train split: 106977434 examples [1:57:10, 11411.20 examples/s]
Generating train split: 106978813 examples [1:57:11, 6728.30 examples/s] 
Generating train split: 106980183 examples [1:57:11, 7793.51 examples/s]
Generating train split: 106981730 examples [1:57:11, 9134.10 examples/s]
Generating train split: 106982990 examples [1:57:11, 6695.52 examples/s]
Generating train split: 106984536 examples [1:57:11, 7908.60 examples/s]
Generating train split: 106986267 examples [1:57:12, 9654.50 examples/s]
Generating train split: 106987548 examples [1:57:12, 9422.49 examples/s]
Generating train split: 106989541 examples [1:57:12, 11670.40 examples/s]
Generating train split: 106990957 examples [1:57:12, 11846.24 examples/s]
Generating train split: 106992319 examples [1:57:12, 11958.65 examples/s]
Generating train split: 106993645 examples [1:57:12, 7902.77 examples/s] 
Generating train split: 106994697 examples [1:57:12, 7999.25 examples/s]
Generating train split: 106996562 examples [1:57:13, 10159.35 examples/s]
Generating train split: 106997812 examples [1:57:13, 6960.07 examples/s] 
Generating train split: 106998804 examples [1:57:13, 6744.86 examples/s]
Generating train split: 106999675 examples [1:57:13, 6948.84 examples/s]
Generating train split: 107001436 examples [1:57:13, 9114.17 examples/s]
Generating train split: 107003438 examples [1:57:13, 10939.40 examples/s]
Generating train split: 107004703 examples [1:57:14, 6082.91 examples/s] 
Generating train split: 107005678 examples [1:57:14, 5980.23 examples/s]
Generating train split: 107006531 examples [1:57:14, 5386.60 examples/s]
Generating train split: 107007939 examples [1:57:14, 6809.68 examples/s]
Generating train split: 107008867 examples [1:57:14, 6558.40 examples/s]
Generating train split: 107009699 examples [1:57:15, 5579.59 examples/s]
Generating train split: 107011281 examples [1:57:15, 7403.24 examples/s]
Generating train split: 107012220 examples [1:57:15, 5206.98 examples/s]
Generating train split: 107013524 examples [1:57:15, 6476.16 examples/s]
Generating train split: 107015291 examples [1:57:15, 8559.40 examples/s]
Generating train split: 107016436 examples [1:57:16, 6601.51 examples/s]
Generating train split: 107017362 examples [1:57:16, 5952.71 examples/s]
Generating train split: 107018143 examples [1:57:16, 3652.36 examples/s]
Generating train split: 107018737 examples [1:57:17, 2526.07 examples/s]
Generating train split: 107019667 examples [1:57:17, 3237.55 examples/s]
Generating train split: 107020373 examples [1:57:17, 3736.00 examples/s]
Generating train split: 107021000 examples [1:57:18, 1897.28 examples/s]
Generating train split: 107021461 examples [1:57:19, 1201.47 examples/s]
Generating train split: 107021799 examples [1:57:20, 964.08 examples/s] 
Generating train split: 107022051 examples [1:57:20, 989.60 examples/s]
Generating train split: 107022262 examples [1:57:20, 954.35 examples/s]
Generating train split: 107022543 examples [1:57:20, 1124.75 examples/s]
Generating train split: 107022749 examples [1:57:20, 1207.28 examples/s]
Generating train split: 107023178 examples [1:57:20, 1637.16 examples/s]
Generating train split: 107023639 examples [1:57:20, 2111.82 examples/s]
Generating train split: 107023957 examples [1:57:21, 2056.65 examples/s]
Generating train split: 107024311 examples [1:57:21, 2277.90 examples/s]
Generating train split: 107024601 examples [1:57:21, 1880.26 examples/s]
Generating train split: 107025987 examples [1:57:21, 4174.74 examples/s]
Generating train split: 107026836 examples [1:57:21, 5097.73 examples/s]
Generating train split: 107027504 examples [1:57:21, 4852.87 examples/s]
Generating train split: 107028099 examples [1:57:22, 4379.18 examples/s]
Generating train split: 107028624 examples [1:57:22, 4430.50 examples/s]
Generating train split: 107029147 examples [1:57:22, 4611.41 examples/s]
Generating train split: 107029858 examples [1:57:22, 5204.51 examples/s]
Generating train split: 107030431 examples [1:57:22, 4857.80 examples/s]
Generating train split: 107030954 examples [1:57:22, 4038.75 examples/s]
Generating train split: 107032676 examples [1:57:22, 7044.77 examples/s]
Generating train split: 107033844 examples [1:57:22, 8144.84 examples/s]
Generating train split: 107034774 examples [1:57:23, 6092.90 examples/s]
Generating train split: 107035536 examples [1:57:23, 6287.52 examples/s]
Generating train split: 107036724 examples [1:57:23, 7531.65 examples/s]
Generating train split: 107037639 examples [1:57:23, 7701.09 examples/s]
Generating train split: 107039257 examples [1:57:23, 9774.30 examples/s]
Generating train split: 107040336 examples [1:57:23, 5873.56 examples/s]
Generating train split: 107042422 examples [1:57:24, 8539.08 examples/s]
Generating train split: 107044231 examples [1:57:24, 9967.61 examples/s]
Generating train split: 107045508 examples [1:57:24, 10218.94 examples/s]
Generating train split: 107046737 examples [1:57:24, 10311.09 examples/s]
Generating train split: 107047913 examples [1:57:24, 7784.86 examples/s] 
Generating train split: 107048874 examples [1:57:24, 5883.85 examples/s]
Generating train split: 107049650 examples [1:57:25, 4939.46 examples/s]
Generating train split: 107050284 examples [1:57:25, 3719.16 examples/s]
Generating train split: 107050795 examples [1:57:25, 3304.56 examples/s]
Generating train split: 107051215 examples [1:57:25, 3377.48 examples/s]
Generating train split: 107051626 examples [1:57:26, 2880.03 examples/s]
Generating train split: 107051970 examples [1:57:26, 2340.16 examples/s]
Generating train split: 107052253 examples [1:57:26, 2102.59 examples/s]
Generating train split: 107053537 examples [1:57:26, 3689.81 examples/s]
Generating train split: 107054002 examples [1:57:26, 2670.96 examples/s]
Generating train split: 107054399 examples [1:57:27, 2779.43 examples/s]
Generating train split: 107054755 examples [1:57:27, 1834.88 examples/s]
Generating train split: 107055030 examples [1:57:27, 1954.32 examples/s]
Generating train split: 107055983 examples [1:57:27, 3182.55 examples/s]
Generating train split: 107056460 examples [1:57:27, 3197.68 examples/s]
Generating train split: 107056892 examples [1:57:28, 2395.74 examples/s]
Generating train split: 107059270 examples [1:57:28, 5872.71 examples/s]
Generating train split: 107060193 examples [1:57:28, 4783.52 examples/s]
Generating train split: 107060927 examples [1:57:28, 4317.56 examples/s]
Generating train split: 107061548 examples [1:57:29, 3685.37 examples/s]
Generating train split: 107063030 examples [1:57:29, 5423.43 examples/s]
Generating train split: 107063819 examples [1:57:29, 3881.64 examples/s]
Generating train split: 107064447 examples [1:57:29, 3949.13 examples/s]
Generating train split: 107065016 examples [1:57:29, 3840.64 examples/s]
Generating train split: 107065521 examples [1:57:30, 3711.42 examples/s]
Generating train split: 107066252 examples [1:57:30, 4110.86 examples/s]
Generating train split: 107066731 examples [1:57:30, 3637.54 examples/s]
Generating train split: 107067141 examples [1:57:30, 3034.42 examples/s]
Generating train split: 107067889 examples [1:57:30, 3826.16 examples/s]
Generating train split: 107068814 examples [1:57:30, 4941.58 examples/s]
Generating train split: 107069410 examples [1:57:30, 4309.65 examples/s]
Generating train split: 107069920 examples [1:57:31, 3679.17 examples/s]
Generating train split: 107071111 examples [1:57:31, 5301.40 examples/s]
Generating train split: 107071772 examples [1:57:31, 5354.86 examples/s]
Generating train split: 107073923 examples [1:57:31, 9077.18 examples/s]
Generating train split: 107074994 examples [1:57:31, 7562.25 examples/s]
Generating train split: 107082294 examples [1:57:31, 22012.24 examples/s]
Generating train split: 107091737 examples [1:57:31, 39367.99 examples/s]
Generating train split: 107096544 examples [1:57:32, 22133.07 examples/s]
Generating train split: 107100235 examples [1:57:32, 19248.84 examples/s]
Generating train split: 107103235 examples [1:57:32, 16922.40 examples/s]
Generating train split: 107111567 examples [1:57:32, 26960.19 examples/s]
Generating train split: 107119818 examples [1:57:33, 36331.45 examples/s]
Generating train split: 107125078 examples [1:57:33, 17291.91 examples/s]
Generating train split: 107128971 examples [1:57:33, 18400.68 examples/s]
Generating train split: 107132418 examples [1:57:34, 15598.87 examples/s]
Generating train split: 107135133 examples [1:57:34, 11478.05 examples/s]
Generating train split: 107137207 examples [1:57:35, 10796.69 examples/s]
Generating train split: 107138907 examples [1:57:35, 9856.89 examples/s] 
Generating train split: 107140316 examples [1:57:35, 8526.98 examples/s]
Generating train split: 107141449 examples [1:57:35, 8698.06 examples/s]
Generating train split: 107149572 examples [1:57:35, 19653.28 examples/s]
Generating train split: 107157671 examples [1:57:35, 30535.06 examples/s]
Generating train split: 107162337 examples [1:57:36, 26330.98 examples/s]
Generating train split: 107166193 examples [1:57:36, 14827.88 examples/s]
Generating train split: 107169089 examples [1:57:37, 11116.44 examples/s]
Generating train split: 107171289 examples [1:57:37, 11921.40 examples/s]
Generating train split: 107173353 examples [1:57:37, 9463.29 examples/s] 
Generating train split: 107176001 examples [1:57:37, 11418.54 examples/s]
Generating train split: 107177911 examples [1:57:38, 10711.65 examples/s]
Generating train split: 107179511 examples [1:57:38, 8945.59 examples/s] 
Generating train split: 107180800 examples [1:57:38, 8957.80 examples/s]
Generating train split: 107181969 examples [1:57:38, 8246.17 examples/s]
Generating train split: 107184215 examples [1:57:38, 10611.35 examples/s]
Generating train split: 107185603 examples [1:57:39, 9024.28 examples/s] 
Generating train split: 107192848 examples [1:57:39, 20484.99 examples/s]
Generating train split: 107201577 examples [1:57:39, 34191.26 examples/s]
Generating train split: 107206280 examples [1:57:39, 31894.96 examples/s]
Generating train split: 107210401 examples [1:57:39, 19133.40 examples/s]
Generating train split: 107213552 examples [1:57:40, 12089.13 examples/s]
Generating train split: 107215925 examples [1:57:40, 10736.76 examples/s]
Generating train split: 107217817 examples [1:57:41, 9927.16 examples/s] 
Generating train split: 107219358 examples [1:57:41, 9194.16 examples/s]
Generating train split: 107220929 examples [1:57:41, 10031.68 examples/s]
Generating train split: 107222296 examples [1:57:41, 8135.51 examples/s] 
Generating train split: 107223400 examples [1:57:42, 6281.94 examples/s]
Generating train split: 107224312 examples [1:57:42, 6650.49 examples/s]
Generating train split: 107225192 examples [1:57:42, 5845.88 examples/s]
Generating train split: 107231554 examples [1:57:42, 15074.30 examples/s]
Generating train split: 107239644 examples [1:57:42, 26867.67 examples/s]
Generating train split: 107243578 examples [1:57:42, 19632.99 examples/s]
Generating train split: 107246684 examples [1:57:43, 10082.58 examples/s]
Generating train split: 107248976 examples [1:57:43, 10748.06 examples/s]
Generating train split: 107251588 examples [1:57:43, 12514.38 examples/s]
Generating train split: 107253773 examples [1:57:44, 9038.25 examples/s] 
Generating train split: 107255448 examples [1:57:44, 9161.50 examples/s]
Generating train split: 107256911 examples [1:57:44, 8718.92 examples/s]
Generating train split: 107258153 examples [1:57:45, 7331.00 examples/s]
Generating train split: 107259378 examples [1:57:45, 8013.04 examples/s]
Generating train split: 107260457 examples [1:57:45, 7231.59 examples/s]
Generating train split: 107261377 examples [1:57:45, 6669.09 examples/s]
Generating train split: 107263189 examples [1:57:45, 8665.45 examples/s]
Generating train split: 107264288 examples [1:57:45, 6251.08 examples/s]
Generating train split: 107265727 examples [1:57:46, 7582.52 examples/s]
Generating train split: 107266770 examples [1:57:46, 7016.60 examples/s]
Generating train split: 107267667 examples [1:57:46, 6003.99 examples/s]
Generating train split: 107268420 examples [1:57:46, 6226.13 examples/s]
Generating train split: 107269161 examples [1:57:46, 5861.66 examples/s]
Generating train split: 107271574 examples [1:57:46, 9670.52 examples/s]
Generating train split: 107272765 examples [1:57:47, 6902.16 examples/s]
Generating train split: 107273724 examples [1:57:47, 6116.98 examples/s]
Generating train split: 107275116 examples [1:57:47, 7019.20 examples/s]
Generating train split: 107275980 examples [1:57:47, 5923.69 examples/s]
Generating train split: 107277549 examples [1:57:47, 7638.44 examples/s]
Generating train split: 107278630 examples [1:57:47, 8279.74 examples/s]
Generating train split: 107279626 examples [1:57:48, 7487.78 examples/s]
Generating train split: 107280498 examples [1:57:48, 6969.99 examples/s]
Generating train split: 107281410 examples [1:57:48, 7432.06 examples/s]
Generating train split: 107282472 examples [1:57:48, 7899.77 examples/s]
Generating train split: 107283328 examples [1:57:48, 5348.53 examples/s]
Generating train split: 107285197 examples [1:57:48, 7852.86 examples/s]
Generating train split: 107286584 examples [1:57:48, 9043.71 examples/s]
Generating train split: 107287765 examples [1:57:49, 9666.31 examples/s]
Generating train split: 107288915 examples [1:57:49, 7838.85 examples/s]
Generating train split: 107290327 examples [1:57:49, 9188.89 examples/s]
Generating train split: 107292191 examples [1:57:49, 11334.39 examples/s]
Generating train split: 107293500 examples [1:57:49, 10913.66 examples/s]
Generating train split: 107294718 examples [1:57:49, 9521.83 examples/s] 
Generating train split: 107295784 examples [1:57:49, 7988.12 examples/s]
Generating train split: 107296705 examples [1:57:50, 6494.76 examples/s]
Generating train split: 107297473 examples [1:57:50, 5599.50 examples/s]
Generating train split: 107299046 examples [1:57:50, 7433.01 examples/s]
Generating train split: 107299960 examples [1:57:50, 6766.31 examples/s]
Generating train split: 107300760 examples [1:57:51, 4989.06 examples/s]
Generating train split: 107301402 examples [1:57:51, 5206.60 examples/s]
Generating train split: 107303131 examples [1:57:51, 7268.61 examples/s]
Generating train split: 107304000 examples [1:57:51, 6648.79 examples/s]
Generating train split: 107305139 examples [1:57:51, 7643.28 examples/s]
Generating train split: 107306056 examples [1:57:51, 7758.15 examples/s]
Generating train split: 107307084 examples [1:57:51, 8240.92 examples/s]
Generating train split: 107307980 examples [1:57:52, 5575.12 examples/s]
Generating train split: 107309503 examples [1:57:52, 7377.44 examples/s]
Generating train split: 107310452 examples [1:57:52, 7722.00 examples/s]
Generating train split: 107311439 examples [1:57:52, 8196.31 examples/s]
Generating train split: 107312386 examples [1:57:52, 7927.86 examples/s]
Generating train split: 107313275 examples [1:57:52, 7536.12 examples/s]
Generating train split: 107314095 examples [1:57:52, 6997.12 examples/s]
Generating train split: 107315323 examples [1:57:52, 8227.21 examples/s]
Generating train split: 107316204 examples [1:57:53, 5981.59 examples/s]
Generating train split: 107318054 examples [1:57:53, 8511.71 examples/s]
Generating train split: 107319253 examples [1:57:53, 9297.79 examples/s]
Generating train split: 107320345 examples [1:57:53, 6222.18 examples/s]
Generating train split: 107321388 examples [1:57:53, 6982.31 examples/s]
Generating train split: 107322402 examples [1:57:53, 7478.22 examples/s]
Generating train split: 107323331 examples [1:57:53, 7666.37 examples/s]
Generating train split: 107324793 examples [1:57:54, 8931.21 examples/s]
Generating train split: 107325799 examples [1:57:54, 7331.53 examples/s]
Generating train split: 107327251 examples [1:57:54, 8890.50 examples/s]
Generating train split: 107328415 examples [1:57:54, 9534.88 examples/s]
Generating train split: 107329488 examples [1:57:54, 8468.41 examples/s]
Generating train split: 107330546 examples [1:57:54, 8961.47 examples/s]
Generating train split: 107331522 examples [1:57:54, 7195.44 examples/s]
Generating train split: 107332453 examples [1:57:55, 7589.88 examples/s]
Generating train split: 107333303 examples [1:57:55, 6725.21 examples/s]
Generating train split: 107334966 examples [1:57:55, 8968.63 examples/s]
Generating train split: 107336132 examples [1:57:55, 9617.99 examples/s]
Generating train split: 107337197 examples [1:57:55, 9475.61 examples/s]
Generating train split: 107338225 examples [1:57:55, 7512.25 examples/s]
Generating train split: 107340255 examples [1:57:55, 10324.32 examples/s]
Generating train split: 107341453 examples [1:57:56, 8758.51 examples/s] 
Generating train split: 107348820 examples [1:57:56, 23046.71 examples/s]
Generating train split: 107357551 examples [1:57:56, 38409.34 examples/s]
Generating train split: 107362224 examples [1:57:56, 23882.81 examples/s]
Generating train split: 107365867 examples [1:57:57, 16134.36 examples/s]
Generating train split: 107368671 examples [1:57:57, 8470.19 examples/s] 
Generating train split: 107370728 examples [1:57:58, 6525.83 examples/s]
Generating train split: 107372263 examples [1:57:59, 5783.48 examples/s]
Generating train split: 107373455 examples [1:57:59, 5873.78 examples/s]
Generating train split: 107374481 examples [1:57:59, 5190.89 examples/s]
Generating train split: 107376061 examples [1:57:59, 6279.42 examples/s]
Generating train split: 107377105 examples [1:57:59, 6678.64 examples/s]
Generating train split: 107378117 examples [1:57:59, 6703.42 examples/s]
Generating train split: 107379027 examples [1:58:00, 6496.18 examples/s]
Generating train split: 107380584 examples [1:58:00, 8128.64 examples/s]
Generating train split: 107381618 examples [1:58:00, 5911.67 examples/s]
Generating train split: 107382441 examples [1:58:00, 4649.65 examples/s]
Generating train split: 107383502 examples [1:58:00, 5543.53 examples/s]
Generating train split: 107384277 examples [1:58:01, 5773.67 examples/s]
Generating train split: 107385722 examples [1:58:01, 7483.46 examples/s]
Generating train split: 107386900 examples [1:58:01, 8422.54 examples/s]
Generating train split: 107387934 examples [1:58:01, 8791.43 examples/s]
Generating train split: 107389573 examples [1:58:01, 10651.81 examples/s]
Generating train split: 107390764 examples [1:58:01, 9694.74 examples/s] 
Generating train split: 107391835 examples [1:58:01, 6021.17 examples/s]
Generating train split: 107394012 examples [1:58:02, 8816.17 examples/s]
Generating train split: 107395255 examples [1:58:02, 8230.55 examples/s]
Generating train split: 107396967 examples [1:58:02, 10003.47 examples/s]
Generating train split: 107398235 examples [1:58:02, 9558.40 examples/s] 
Generating train split: 107399399 examples [1:58:02, 9972.10 examples/s]
Generating train split: 107400962 examples [1:58:02, 11328.36 examples/s]
Generating train split: 107402233 examples [1:58:02, 9828.68 examples/s] 
Generating train split: 107404894 examples [1:58:02, 13658.43 examples/s]
Generating train split: 107406445 examples [1:58:03, 9834.69 examples/s] 
Generating train split: 107407992 examples [1:58:03, 10795.82 examples/s]
Generating train split: 107409309 examples [1:58:03, 7543.94 examples/s] 
Generating train split: 107410379 examples [1:58:03, 8061.05 examples/s]
Generating train split: 107411430 examples [1:58:03, 7178.25 examples/s]
Generating train split: 107412988 examples [1:58:04, 8781.42 examples/s]
Generating train split: 107414478 examples [1:58:04, 10072.39 examples/s]
Generating train split: 107415684 examples [1:58:04, 8333.70 examples/s] 
Generating train split: 107416710 examples [1:58:04, 8722.20 examples/s]
Generating train split: 107417727 examples [1:58:04, 8970.76 examples/s]
Generating train split: 107419706 examples [1:58:04, 11513.97 examples/s]
Generating train split: 107420982 examples [1:58:04, 8549.64 examples/s] 
Generating train split: 107422514 examples [1:58:05, 9948.02 examples/s]
Generating train split: 107423712 examples [1:58:05, 10077.78 examples/s]
Generating train split: 107424857 examples [1:58:05, 7647.53 examples/s] 
Generating train split: 107426069 examples [1:58:05, 8339.20 examples/s]
Generating train split: 107427057 examples [1:58:05, 6971.41 examples/s]
Generating train split: 107428150 examples [1:58:05, 7746.29 examples/s]
Generating train split: 107429064 examples [1:58:05, 6672.10 examples/s]
Generating train split: 107429999 examples [1:58:06, 7210.41 examples/s]
Generating train split: 107430824 examples [1:58:06, 6048.64 examples/s]
Generating train split: 107431525 examples [1:58:06, 5054.16 examples/s]
Generating train split: 107435371 examples [1:58:06, 11573.53 examples/s]
Generating train split: 107443883 examples [1:58:06, 27602.94 examples/s]
Generating train split: 107450077 examples [1:58:06, 35691.38 examples/s]
Generating train split: 107454477 examples [1:58:07, 24769.29 examples/s]
Generating train split: 107457989 examples [1:58:07, 16987.49 examples/s]
Generating train split: 107460716 examples [1:58:07, 13687.18 examples/s]
Generating train split: 107462869 examples [1:58:07, 14331.80 examples/s]
Generating train split: 107464913 examples [1:58:08, 11036.15 examples/s]
Generating train split: 107473290 examples [1:58:08, 21223.04 examples/s]
Generating train split: 107481937 examples [1:58:08, 31785.12 examples/s]
Generating train split: 107486938 examples [1:58:08, 25872.43 examples/s]
Generating train split: 107490962 examples [1:58:09, 17058.31 examples/s]
Generating train split: 107494025 examples [1:58:09, 18763.04 examples/s]
Generating train split: 107502918 examples [1:58:09, 29436.22 examples/s]
Generating train split: 107509689 examples [1:58:09, 36269.51 examples/s]
Generating train split: 107515083 examples [1:58:10, 16967.12 examples/s]
Generating train split: 107519082 examples [1:58:10, 15598.34 examples/s]
Generating train split: 107522247 examples [1:58:11, 10954.10 examples/s]
Generating train split: 107524617 examples [1:58:11, 8923.53 examples/s] 
Generating train split: 107526418 examples [1:58:12, 8522.21 examples/s]
Generating train split: 107533456 examples [1:58:12, 14638.49 examples/s]
Generating train split: 107542604 examples [1:58:12, 24146.12 examples/s]
Generating train split: 107547551 examples [1:58:12, 20123.44 examples/s]
Generating train split: 107551428 examples [1:58:13, 16793.50 examples/s]
Generating train split: 107554461 examples [1:58:13, 14437.16 examples/s]
Generating train split: 107556863 examples [1:58:13, 13966.91 examples/s]
Generating train split: 107558917 examples [1:58:13, 13669.67 examples/s]
Generating train split: 107560732 examples [1:58:13, 13858.34 examples/s]
Generating train split: 107562441 examples [1:58:13, 13029.56 examples/s]
Generating train split: 107564131 examples [1:58:14, 13712.63 examples/s]
Generating train split: 107565700 examples [1:58:14, 11606.78 examples/s]
Generating train split: 107567037 examples [1:58:14, 9660.48 examples/s] 
Generating train split: 107568423 examples [1:58:14, 10208.76 examples/s]
Generating train split: 107569579 examples [1:58:14, 10183.85 examples/s]
Generating train split: 107570685 examples [1:58:14, 8141.79 examples/s] 
Generating train split: 107572508 examples [1:58:15, 10123.47 examples/s]
Generating train split: 107573700 examples [1:58:15, 8979.62 examples/s] 
Generating train split: 107575252 examples [1:58:15, 10160.48 examples/s]
Generating train split: 107576404 examples [1:58:15, 9688.03 examples/s] 
Generating train split: 107577803 examples [1:58:15, 10650.40 examples/s]
Generating train split: 107578969 examples [1:58:15, 10068.17 examples/s]
Generating train split: 107580050 examples [1:58:15, 10227.89 examples/s]
Generating train split: 107581952 examples [1:58:15, 12003.82 examples/s]
Generating train split: 107583197 examples [1:58:16, 7838.65 examples/s] 
Generating train split: 107584844 examples [1:58:16, 9521.52 examples/s]
Generating train split: 107586033 examples [1:58:16, 7608.29 examples/s]
Generating train split: 107587021 examples [1:58:16, 6820.68 examples/s]
Generating train split: 107587870 examples [1:58:16, 6266.85 examples/s]
Generating train split: 107588653 examples [1:58:17, 6535.77 examples/s]
Generating train split: 107589404 examples [1:58:17, 4023.36 examples/s]
Generating train split: 107589984 examples [1:58:17, 3864.42 examples/s]
Generating train split: 107590824 examples [1:58:17, 4595.18 examples/s]
Generating train split: 107591981 examples [1:58:17, 5897.43 examples/s]
Generating train split: 107592743 examples [1:58:17, 6201.19 examples/s]
Generating train split: 107594368 examples [1:58:18, 8517.48 examples/s]
Generating train split: 107595441 examples [1:58:18, 8801.10 examples/s]
Generating train split: 107596436 examples [1:58:18, 4832.11 examples/s]
Generating train split: 107597199 examples [1:58:18, 5000.66 examples/s]
Generating train split: 107598205 examples [1:58:18, 5746.03 examples/s]
Generating train split: 107598968 examples [1:58:19, 4063.66 examples/s]
Generating train split: 107600093 examples [1:58:19, 5185.52 examples/s]
Generating train split: 107600995 examples [1:58:19, 5893.77 examples/s]
Generating train split: 107601795 examples [1:58:19, 6010.21 examples/s]
Generating train split: 107602543 examples [1:58:19, 4418.79 examples/s]
Generating train split: 107610772 examples [1:58:19, 18457.05 examples/s]
Generating train split: 107619123 examples [1:58:20, 31774.07 examples/s]
Generating train split: 107623652 examples [1:58:20, 33765.72 examples/s]
Generating train split: 107628023 examples [1:58:20, 16609.89 examples/s]
Generating train split: 107631303 examples [1:58:21, 12461.09 examples/s]
Generating train split: 107633808 examples [1:58:21, 13591.70 examples/s]
Generating train split: 107636193 examples [1:58:21, 10409.17 examples/s]
Generating train split: 107638032 examples [1:58:22, 9717.48 examples/s] 
Generating train split: 107639559 examples [1:58:22, 9175.63 examples/s]
Generating train split: 107640841 examples [1:58:22, 8775.32 examples/s]
Generating train split: 107641959 examples [1:58:22, 7982.29 examples/s]
Generating train split: 107642912 examples [1:58:22, 7641.25 examples/s]
Generating train split: 107643776 examples [1:58:22, 6352.62 examples/s]
Generating train split: 107644694 examples [1:58:23, 6828.67 examples/s]
Generating train split: 107646502 examples [1:58:23, 9006.50 examples/s]
Generating train split: 107647595 examples [1:58:23, 7709.13 examples/s]
Generating train split: 107648518 examples [1:58:23, 6083.88 examples/s]
Generating train split: 107649908 examples [1:58:23, 7470.30 examples/s]
Generating train split: 107651157 examples [1:58:23, 8396.95 examples/s]
Generating train split: 107653313 examples [1:58:23, 11241.71 examples/s]
Generating train split: 107655115 examples [1:58:24, 12865.15 examples/s]
Generating train split: 107656593 examples [1:58:24, 10753.74 examples/s]
Generating train split: 107657880 examples [1:58:24, 11209.52 examples/s]
Generating train split: 107660139 examples [1:58:24, 13758.15 examples/s]
Generating train split: 107662707 examples [1:58:24, 16801.73 examples/s]
Generating train split: 107665097 examples [1:58:24, 18542.34 examples/s]
Generating train split: 107667082 examples [1:58:25, 10062.07 examples/s]
Generating train split: 107668618 examples [1:58:25, 10124.97 examples/s]
Generating train split: 107676275 examples [1:58:25, 22447.19 examples/s]
Generating train split: 107685362 examples [1:58:25, 36772.95 examples/s]
Generating train split: 107690375 examples [1:58:25, 24536.63 examples/s]
Generating train split: 107694286 examples [1:58:26, 15510.75 examples/s]
Generating train split: 107697246 examples [1:58:26, 12723.57 examples/s]
Generating train split: 107699546 examples [1:58:27, 9349.89 examples/s] 
Generating train split: 107701300 examples [1:58:27, 7803.36 examples/s]
Generating train split: 107702654 examples [1:58:27, 7873.74 examples/s]
Generating train split: 107703884 examples [1:58:27, 8384.95 examples/s]
Generating train split: 107705091 examples [1:58:28, 7209.10 examples/s]
Generating train split: 107706083 examples [1:58:28, 7267.85 examples/s]
Generating train split: 107708502 examples [1:58:28, 10004.59 examples/s]
Generating train split: 107709869 examples [1:58:28, 8116.89 examples/s] 
Generating train split: 107710976 examples [1:58:28, 7269.49 examples/s]
Generating train split: 107711919 examples [1:58:29, 7299.60 examples/s]
Generating train split: 107713225 examples [1:58:29, 8361.96 examples/s]
Generating train split: 107714228 examples [1:58:29, 6345.00 examples/s]
Generating train split: 107715040 examples [1:58:29, 5332.84 examples/s]
Generating train split: 107715862 examples [1:58:29, 5698.83 examples/s]
Generating train split: 107716550 examples [1:58:30, 4356.91 examples/s]
Generating train split: 107717110 examples [1:58:30, 4222.89 examples/s]
Generating train split: 107718744 examples [1:58:30, 6412.49 examples/s]
Generating train split: 107719585 examples [1:58:30, 4742.39 examples/s]
Generating train split: 107720260 examples [1:58:30, 4805.30 examples/s]
Generating train split: 107720878 examples [1:58:30, 5024.73 examples/s]
Generating train split: 107722704 examples [1:58:30, 7760.66 examples/s]
Generating train split: 107723676 examples [1:58:31, 5754.99 examples/s]
Generating train split: 107724460 examples [1:58:31, 5854.14 examples/s]
Generating train split: 107726299 examples [1:58:31, 8358.54 examples/s]
Generating train split: 107727362 examples [1:58:31, 6650.47 examples/s]
Generating train split: 107728238 examples [1:58:31, 6418.61 examples/s]
Generating train split: 107729515 examples [1:58:31, 7689.71 examples/s]
Generating train split: 107731005 examples [1:58:32, 9229.31 examples/s]
Generating train split: 107732090 examples [1:58:32, 8382.42 examples/s]
Generating train split: 107733446 examples [1:58:32, 9567.73 examples/s]
Generating train split: 107735218 examples [1:58:32, 11434.86 examples/s]
Generating train split: 107736480 examples [1:58:32, 9857.05 examples/s] 
Generating train split: 107737588 examples [1:58:32, 6617.17 examples/s]
Generating train split: 107738464 examples [1:58:33, 6452.64 examples/s]
Generating train split: 107739522 examples [1:58:33, 6956.57 examples/s]
Generating train split: 107740335 examples [1:58:33, 5719.17 examples/s]
Generating train split: 107741017 examples [1:58:33, 5121.37 examples/s]
Generating train split: 107742285 examples [1:58:33, 6558.01 examples/s]
Generating train split: 107743081 examples [1:58:33, 5677.21 examples/s]
Generating train split: 107750573 examples [1:58:33, 19664.96 examples/s]
Generating train split: 107758996 examples [1:58:34, 34118.00 examples/s]
Generating train split: 107763424 examples [1:58:34, 31138.78 examples/s]
Generating train split: 107767301 examples [1:58:34, 17986.32 examples/s]
Generating train split: 107770266 examples [1:58:35, 11219.03 examples/s]
Generating train split: 107772489 examples [1:58:35, 12396.17 examples/s]
Generating train split: 107774712 examples [1:58:35, 12490.32 examples/s]
Generating train split: 107776643 examples [1:58:36, 8416.28 examples/s] 
Generating train split: 107778115 examples [1:58:36, 7491.85 examples/s]
Generating train split: 107782660 examples [1:58:36, 12063.94 examples/s]
Generating train split: 107791102 examples [1:58:36, 22684.27 examples/s]
Generating train split: 107796983 examples [1:58:36, 28942.07 examples/s]
Generating train split: 107801601 examples [1:58:36, 25494.72 examples/s]
Generating train split: 107805420 examples [1:58:37, 15089.57 examples/s]
Generating train split: 107808293 examples [1:58:37, 12276.75 examples/s]
Generating train split: 107810524 examples [1:58:38, 9321.94 examples/s] 
Generating train split: 107812230 examples [1:58:38, 8454.10 examples/s]
Generating train split: 107813596 examples [1:58:38, 7685.35 examples/s]
Generating train split: 107815241 examples [1:58:39, 8706.00 examples/s]
Generating train split: 107817096 examples [1:58:39, 10113.13 examples/s]
Generating train split: 107818549 examples [1:58:39, 7540.73 examples/s] 
Generating train split: 107819692 examples [1:58:39, 7582.33 examples/s]
Generating train split: 107820728 examples [1:58:39, 7928.71 examples/s]
Generating train split: 107821734 examples [1:58:40, 5920.46 examples/s]
Generating train split: 107823597 examples [1:58:40, 7935.84 examples/s]
Generating train split: 107825131 examples [1:58:40, 9291.79 examples/s]
Generating train split: 107826373 examples [1:58:40, 6360.26 examples/s]
Generating train split: 107827344 examples [1:58:40, 6595.80 examples/s]
Generating train split: 107829355 examples [1:58:40, 9019.28 examples/s]
Generating train split: 107830748 examples [1:58:40, 9946.04 examples/s]
Generating train split: 107832028 examples [1:58:41, 8678.14 examples/s]
Generating train split: 107833125 examples [1:58:41, 8940.20 examples/s]
Generating train split: 107834349 examples [1:58:41, 9629.05 examples/s]
Generating train split: 107835447 examples [1:58:41, 6595.20 examples/s]
Generating train split: 107836324 examples [1:58:41, 6619.05 examples/s]
Generating train split: 107837504 examples [1:58:41, 7639.09 examples/s]
Generating train split: 107838431 examples [1:58:42, 6103.60 examples/s]
Generating train split: 107840328 examples [1:58:42, 8560.44 examples/s]
Generating train split: 107842650 examples [1:58:42, 11724.45 examples/s]
Generating train split: 107845554 examples [1:58:42, 15643.64 examples/s]
Generating train split: 107847407 examples [1:58:42, 9235.79 examples/s] 
Generating train split: 107850243 examples [1:58:42, 12415.58 examples/s]
Generating train split: 107852085 examples [1:58:43, 9109.81 examples/s] 
Generating train split: 107853531 examples [1:58:43, 9666.13 examples/s]
Generating train split: 107855498 examples [1:58:43, 11446.75 examples/s]
Generating train split: 107857051 examples [1:58:43, 8084.13 examples/s] 
Generating train split: 107858410 examples [1:58:44, 8960.43 examples/s]
Generating train split: 107859787 examples [1:58:44, 9589.70 examples/s]
Generating train split: 107861031 examples [1:58:44, 6452.23 examples/s]
Generating train split: 107862117 examples [1:58:44, 7141.33 examples/s]
Generating train split: 107863131 examples [1:58:44, 6408.07 examples/s]
Generating train split: 107863979 examples [1:58:45, 5623.38 examples/s]
Generating train split: 107866407 examples [1:58:45, 8884.67 examples/s]
Generating train split: 107867638 examples [1:58:45, 8363.59 examples/s]
Generating train split: 107868710 examples [1:58:45, 8019.50 examples/s]
Generating train split: 107870351 examples [1:58:45, 9741.06 examples/s]
Generating train split: 107871913 examples [1:58:45, 11075.47 examples/s]
Generating train split: 107879002 examples [1:58:45, 25716.80 examples/s]
Generating train split: 107883830 examples [1:58:45, 31547.14 examples/s]
Generating train split: 107887397 examples [1:58:46, 24409.20 examples/s]
Generating train split: 107890370 examples [1:58:46, 20254.90 examples/s]
Generating train split: 107892861 examples [1:58:46, 16788.36 examples/s]
Generating train split: 107894939 examples [1:58:46, 13173.60 examples/s]
Generating train split: 107902412 examples [1:58:46, 23412.92 examples/s]
Generating train split: 107909864 examples [1:58:46, 33221.98 examples/s]
Generating train split: 107914488 examples [1:58:47, 23818.22 examples/s]
Generating train split: 107918142 examples [1:58:47, 21787.87 examples/s]
Generating train split: 107925834 examples [1:58:47, 31071.00 examples/s]
Generating train split: 107932528 examples [1:58:47, 37922.66 examples/s]
Generating train split: 107937635 examples [1:58:48, 24694.71 examples/s]
Generating train split: 107941588 examples [1:58:48, 15584.80 examples/s]
Generating train split: 107944564 examples [1:58:49, 13964.10 examples/s]
Generating train split: 107946946 examples [1:58:49, 11015.90 examples/s]
Generating train split: 107948939 examples [1:58:49, 11950.37 examples/s]
Generating train split: 107950916 examples [1:58:49, 13000.93 examples/s]
Generating train split: 107952819 examples [1:58:50, 7752.31 examples/s] 
Generating train split: 107954253 examples [1:58:50, 6783.26 examples/s]
Generating train split: 107955387 examples [1:58:50, 5291.12 examples/s]
Generating train split: 107956259 examples [1:58:51, 5021.49 examples/s]
Generating train split: 107957128 examples [1:58:51, 5398.42 examples/s]
Generating train split: 107957892 examples [1:58:51, 5511.97 examples/s]
Generating train split: 107959066 examples [1:58:51, 6529.69 examples/s]
Generating train split: 107959918 examples [1:58:51, 5466.50 examples/s]
Generating train split: 107960622 examples [1:58:51, 5133.78 examples/s]
Generating train split: 107968972 examples [1:58:52, 19580.77 examples/s]
Generating train split: 107977510 examples [1:58:52, 32314.47 examples/s]
Generating train split: 107981814 examples [1:58:52, 19060.97 examples/s]
Generating train split: 107985103 examples [1:58:52, 18131.12 examples/s]
Generating train split: 107987869 examples [1:58:53, 16112.56 examples/s]
Generating train split: 107990161 examples [1:58:53, 12315.42 examples/s]
Generating train split: 107991951 examples [1:58:53, 11384.85 examples/s]
Generating train split: 107998075 examples [1:58:53, 18608.67 examples/s]
Generating train split: 108005972 examples [1:58:53, 28959.01 examples/s]
Generating train split: 108010370 examples [1:58:54, 26589.94 examples/s]
Generating train split: 108014100 examples [1:58:54, 15782.04 examples/s]
Generating train split: 108016934 examples [1:58:55, 11960.15 examples/s]
Generating train split: 108019100 examples [1:58:55, 11116.63 examples/s]
Generating train split: 108020873 examples [1:58:55, 9569.68 examples/s] 
Generating train split: 108022289 examples [1:58:55, 7569.38 examples/s]
Generating train split: 108023401 examples [1:58:56, 7949.96 examples/s]
Generating train split: 108024815 examples [1:58:56, 8804.91 examples/s]
Generating train split: 108026004 examples [1:58:56, 8438.59 examples/s]
Generating train split: 108028165 examples [1:58:56, 10769.36 examples/s]
Generating train split: 108029555 examples [1:58:56, 11280.82 examples/s]
Generating train split: 108036670 examples [1:58:56, 24590.03 examples/s]
Generating train split: 108045311 examples [1:58:56, 39483.19 examples/s]
Generating train split: 108050062 examples [1:58:56, 31350.34 examples/s]
Generating train split: 108054025 examples [1:58:57, 12423.72 examples/s]
Generating train split: 108056937 examples [1:58:58, 8978.07 examples/s] 
Generating train split: 108059108 examples [1:58:58, 8419.73 examples/s]
Generating train split: 108060828 examples [1:58:59, 7518.08 examples/s]
Generating train split: 108062179 examples [1:58:59, 7123.85 examples/s]
Generating train split: 108063298 examples [1:58:59, 7047.56 examples/s]
Generating train split: 108064353 examples [1:58:59, 7490.61 examples/s]
Generating train split: 108065364 examples [1:58:59, 6885.85 examples/s]
Generating train split: 108066699 examples [1:58:59, 7916.80 examples/s]
Generating train split: 108067704 examples [1:59:00, 6192.47 examples/s]
Generating train split: 108068516 examples [1:59:00, 5837.52 examples/s]
Generating train split: 108069225 examples [1:59:00, 5575.79 examples/s]
Generating train split: 108070793 examples [1:59:00, 7436.18 examples/s]
Generating train split: 108071710 examples [1:59:00, 6910.94 examples/s]
Generating train split: 108072695 examples [1:59:00, 7520.91 examples/s]
Generating train split: 108073561 examples [1:59:01, 6355.05 examples/s]
Generating train split: 108074295 examples [1:59:01, 5588.58 examples/s]
Generating train split: 108075060 examples [1:59:01, 5966.59 examples/s]
Generating train split: 108075739 examples [1:59:01, 5088.76 examples/s]
Generating train split: 108077678 examples [1:59:01, 8094.50 examples/s]
Generating train split: 108078660 examples [1:59:01, 7057.94 examples/s]
Generating train split: 108079554 examples [1:59:02, 7460.61 examples/s]
Generating train split: 108080427 examples [1:59:02, 5936.61 examples/s]
Generating train split: 108081145 examples [1:59:02, 5220.86 examples/s]
Generating train split: 108081759 examples [1:59:02, 5318.33 examples/s]
Generating train split: 108082360 examples [1:59:02, 4886.12 examples/s]
Generating train split: 108083604 examples [1:59:02, 6524.95 examples/s]
Generating train split: 108084580 examples [1:59:02, 7281.76 examples/s]
Generating train split: 108085399 examples [1:59:03, 4902.13 examples/s]
Generating train split: 108092754 examples [1:59:03, 17983.78 examples/s]
Generating train split: 108099937 examples [1:59:03, 29505.95 examples/s]
Generating train split: 108103964 examples [1:59:03, 25955.24 examples/s]
Generating train split: 108107390 examples [1:59:04, 14910.35 examples/s]
Generating train split: 108109995 examples [1:59:04, 15383.39 examples/s]
Generating train split: 108112335 examples [1:59:04, 9986.92 examples/s] 
Generating train split: 108114111 examples [1:59:04, 10379.34 examples/s]
Generating train split: 108115737 examples [1:59:05, 9497.44 examples/s] 
Generating train split: 108117724 examples [1:59:05, 10944.11 examples/s]
Generating train split: 108119257 examples [1:59:05, 10686.28 examples/s]
Generating train split: 108120621 examples [1:59:05, 7902.61 examples/s] 
Generating train split: 108121795 examples [1:59:05, 8409.40 examples/s]
Generating train split: 108122882 examples [1:59:06, 7427.87 examples/s]
Generating train split: 108123798 examples [1:59:06, 7170.19 examples/s]
Generating train split: 108126652 examples [1:59:06, 11203.96 examples/s]
Generating train split: 108128987 examples [1:59:06, 13760.49 examples/s]
Generating train split: 108130682 examples [1:59:06, 8755.72 examples/s] 
Generating train split: 108132631 examples [1:59:06, 10533.26 examples/s]
Generating train split: 108134246 examples [1:59:06, 11565.43 examples/s]
Generating train split: 108135963 examples [1:59:07, 12704.62 examples/s]
Generating train split: 108137540 examples [1:59:07, 9288.05 examples/s] 
Generating train split: 108139565 examples [1:59:07, 11303.33 examples/s]
Generating train split: 108141052 examples [1:59:07, 11141.25 examples/s]
Generating train split: 108142420 examples [1:59:07, 9435.56 examples/s] 
Generating train split: 108144145 examples [1:59:07, 10962.50 examples/s]
Generating train split: 108145965 examples [1:59:08, 12567.98 examples/s]
Generating train split: 108147430 examples [1:59:08, 12732.73 examples/s]
Generating train split: 108148860 examples [1:59:08, 8245.70 examples/s] 
Generating train split: 108149985 examples [1:59:08, 8222.19 examples/s]
Generating train split: 108151138 examples [1:59:08, 8870.18 examples/s]
Generating train split: 108153006 examples [1:59:08, 10988.74 examples/s]
Generating train split: 108154316 examples [1:59:08, 10175.40 examples/s]
Generating train split: 108155551 examples [1:59:09, 10675.19 examples/s]
Generating train split: 108160121 examples [1:59:09, 19376.70 examples/s]
Generating train split: 108168509 examples [1:59:09, 36270.29 examples/s]
Generating train split: 108173665 examples [1:59:09, 40433.23 examples/s]
Generating train split: 108178050 examples [1:59:09, 24209.70 examples/s]
Generating train split: 108181492 examples [1:59:10, 15490.75 examples/s]
Generating train split: 108184682 examples [1:59:10, 17757.28 examples/s]
Generating train split: 108192044 examples [1:59:10, 26971.64 examples/s]
Generating train split: 108198390 examples [1:59:10, 33919.14 examples/s]
Generating train split: 108203210 examples [1:59:11, 18803.94 examples/s]
Generating train split: 108206845 examples [1:59:11, 14357.23 examples/s]
Generating train split: 108209642 examples [1:59:11, 15047.82 examples/s]
Generating train split: 108212163 examples [1:59:12, 11137.89 examples/s]
Generating train split: 108214097 examples [1:59:12, 11530.70 examples/s]
Generating train split: 108222038 examples [1:59:12, 20759.65 examples/s]
Generating train split: 108230050 examples [1:59:12, 30415.76 examples/s]
Generating train split: 108234984 examples [1:59:12, 21870.25 examples/s]
Generating train split: 108238821 examples [1:59:13, 20166.55 examples/s]
Generating train split: 108241988 examples [1:59:13, 12866.74 examples/s]
Generating train split: 108244370 examples [1:59:13, 11212.36 examples/s]
Generating train split: 108246262 examples [1:59:14, 10478.84 examples/s]
Generating train split: 108248558 examples [1:59:14, 11997.49 examples/s]
Generating train split: 108250339 examples [1:59:14, 9806.82 examples/s] 
Generating train split: 108251760 examples [1:59:14, 10385.49 examples/s]
Generating train split: 108253184 examples [1:59:15, 7201.08 examples/s] 
Generating train split: 108255133 examples [1:59:15, 8836.88 examples/s]
Generating train split: 108256479 examples [1:59:15, 9393.40 examples/s]
Generating train split: 108257786 examples [1:59:15, 5944.77 examples/s]
Generating train split: 108258780 examples [1:59:15, 6218.35 examples/s]
Generating train split: 108259711 examples [1:59:16, 5028.11 examples/s]
Generating train split: 108261646 examples [1:59:16, 7069.81 examples/s]
Generating train split: 108263980 examples [1:59:16, 9822.66 examples/s]
Generating train split: 108271975 examples [1:59:16, 23473.50 examples/s]
Generating train split: 108278231 examples [1:59:16, 31959.13 examples/s]
Generating train split: 108282499 examples [1:59:17, 16548.97 examples/s]
Generating train split: 108285727 examples [1:59:18, 8317.09 examples/s] 
Generating train split: 108288078 examples [1:59:18, 9078.66 examples/s]
Generating train split: 108290160 examples [1:59:18, 9757.98 examples/s]
Generating train split: 108297700 examples [1:59:18, 17579.21 examples/s]
Generating train split: 108306447 examples [1:59:18, 27744.56 examples/s]
Generating train split: 108311572 examples [1:59:19, 19833.16 examples/s]
Generating train split: 108315504 examples [1:59:19, 12977.26 examples/s]
Generating train split: 108318439 examples [1:59:19, 14410.20 examples/s]
Generating train split: 108321272 examples [1:59:20, 15135.67 examples/s]
Generating train split: 108323823 examples [1:59:20, 10977.44 examples/s]
Generating train split: 108325764 examples [1:59:20, 11564.53 examples/s]
Generating train split: 108327576 examples [1:59:20, 10609.95 examples/s]
Generating train split: 108329128 examples [1:59:21, 11254.79 examples/s]
Generating train split: 108330874 examples [1:59:21, 12257.76 examples/s]
Generating train split: 108333249 examples [1:59:21, 14079.55 examples/s]
Generating train split: 108334964 examples [1:59:21, 9587.72 examples/s] 
Generating train split: 108336312 examples [1:59:21, 7611.10 examples/s]
Generating train split: 108337498 examples [1:59:22, 8241.73 examples/s]
Generating train split: 108339536 examples [1:59:22, 10355.84 examples/s]
Generating train split: 108340979 examples [1:59:22, 11170.67 examples/s]
Generating train split: 108349079 examples [1:59:22, 26715.16 examples/s]
Generating train split: 108356870 examples [1:59:22, 38485.88 examples/s]
Generating train split: 108361462 examples [1:59:22, 18256.51 examples/s]
Generating train split: 108364918 examples [1:59:23, 14634.88 examples/s]
Generating train split: 108367602 examples [1:59:23, 15612.67 examples/s]
Generating train split: 108370108 examples [1:59:23, 16304.69 examples/s]
Generating train split: 108372453 examples [1:59:23, 17070.73 examples/s]
Generating train split: 108374701 examples [1:59:23, 15381.31 examples/s]
Generating train split: 108376630 examples [1:59:24, 11555.55 examples/s]
Generating train split: 108378176 examples [1:59:24, 10526.22 examples/s]
Generating train split: 108379486 examples [1:59:24, 9059.13 examples/s] 
Generating train split: 108380582 examples [1:59:24, 8276.94 examples/s]
Generating train split: 108381531 examples [1:59:25, 6265.78 examples/s]
Generating train split: 108382801 examples [1:59:25, 7230.25 examples/s]
Generating train split: 108383705 examples [1:59:25, 6967.57 examples/s]
Generating train split: 108385998 examples [1:59:25, 9917.60 examples/s]
Generating train split: 108387224 examples [1:59:25, 5779.50 examples/s]
Generating train split: 108388162 examples [1:59:26, 5099.94 examples/s]
Generating train split: 108388925 examples [1:59:26, 5361.84 examples/s]
Generating train split: 108389672 examples [1:59:26, 4911.42 examples/s]
Generating train split: 108390482 examples [1:59:26, 5434.54 examples/s]
Generating train split: 108391173 examples [1:59:26, 5593.03 examples/s]
Generating train split: 108392713 examples [1:59:26, 7686.31 examples/s]
Generating train split: 108393637 examples [1:59:27, 7306.90 examples/s]
Generating train split: 108394493 examples [1:59:27, 5963.28 examples/s]
Generating train split: 108395702 examples [1:59:27, 7219.25 examples/s]
Generating train split: 108396787 examples [1:59:27, 8027.65 examples/s]
Generating train split: 108397711 examples [1:59:27, 7439.80 examples/s]
Generating train split: 108398834 examples [1:59:27, 8331.62 examples/s]
Generating train split: 108399759 examples [1:59:27, 8042.14 examples/s]
Generating train split: 108401578 examples [1:59:27, 10559.24 examples/s]
Generating train split: 108402722 examples [1:59:28, 8374.04 examples/s] 
Generating train split: 108403771 examples [1:59:28, 8853.81 examples/s]
Generating train split: 108404766 examples [1:59:28, 7735.94 examples/s]
Generating train split: 108405645 examples [1:59:28, 6749.90 examples/s]
Generating train split: 108406399 examples [1:59:28, 6707.65 examples/s]
Generating train split: 108407125 examples [1:59:28, 5855.82 examples/s]
Generating train split: 108408577 examples [1:59:28, 7751.43 examples/s]
Generating train split: 108409457 examples [1:59:29, 6299.16 examples/s]
Generating train split: 108410950 examples [1:59:29, 7968.10 examples/s]
Generating train split: 108411942 examples [1:59:29, 8394.24 examples/s]
Generating train split: 108413299 examples [1:59:29, 9660.84 examples/s]
Generating train split: 108414955 examples [1:59:29, 11440.65 examples/s]
Generating train split: 108416209 examples [1:59:30, 6448.72 examples/s] 
Generating train split: 108417171 examples [1:59:30, 5813.89 examples/s]
Generating train split: 108417988 examples [1:59:30, 5743.38 examples/s]
Generating train split: 108418724 examples [1:59:30, 5547.20 examples/s]
Generating train split: 108419476 examples [1:59:30, 5918.26 examples/s]
Generating train split: 108420166 examples [1:59:30, 4760.05 examples/s]
Generating train split: 108421266 examples [1:59:30, 5973.07 examples/s]
Generating train split: 108422963 examples [1:59:31, 8333.95 examples/s]
Generating train split: 108428668 examples [1:59:31, 19841.58 examples/s]
Generating train split: 108436918 examples [1:59:31, 35645.96 examples/s]
Generating train split: 108442160 examples [1:59:31, 39225.12 examples/s]
Generating train split: 108446538 examples [1:59:31, 16514.73 examples/s]
Generating train split: 108449809 examples [1:59:32, 13832.85 examples/s]
Generating train split: 108452370 examples [1:59:32, 10138.52 examples/s]
Generating train split: 108454317 examples [1:59:33, 7908.42 examples/s] 
Generating train split: 108455802 examples [1:59:33, 7455.57 examples/s]
Generating train split: 108457015 examples [1:59:33, 6398.28 examples/s]
Generating train split: 108457978 examples [1:59:34, 6233.00 examples/s]
Generating train split: 108458817 examples [1:59:34, 5279.30 examples/s]
Generating train split: 108459491 examples [1:59:34, 5024.93 examples/s]
Generating train split: 108460096 examples [1:59:34, 5043.17 examples/s]
Generating train split: 108460969 examples [1:59:34, 5652.14 examples/s]
Generating train split: 108461695 examples [1:59:34, 5933.12 examples/s]
Generating train split: 108462370 examples [1:59:35, 5137.66 examples/s]
Generating train split: 108462954 examples [1:59:35, 4904.40 examples/s]
Generating train split: 108463681 examples [1:59:35, 5383.47 examples/s]
Generating train split: 108464267 examples [1:59:35, 4248.86 examples/s]
Generating train split: 108464756 examples [1:59:35, 3468.36 examples/s]
Generating train split: 108465599 examples [1:59:35, 4101.17 examples/s]
Generating train split: 108467037 examples [1:59:35, 6144.90 examples/s]
Generating train split: 108467791 examples [1:59:36, 4554.27 examples/s]
Generating train split: 108468398 examples [1:59:36, 4716.01 examples/s]
Generating train split: 108468986 examples [1:59:36, 4835.27 examples/s]
Generating train split: 108469982 examples [1:59:36, 5924.45 examples/s]
Generating train split: 108470681 examples [1:59:36, 4811.89 examples/s]
Generating train split: 108471262 examples [1:59:37, 4203.77 examples/s]
Generating train split: 108472155 examples [1:59:37, 5149.27 examples/s]
Generating train split: 108472778 examples [1:59:37, 4759.73 examples/s]
Generating train split: 108473336 examples [1:59:37, 4924.60 examples/s]
Generating train split: 108473928 examples [1:59:37, 5160.07 examples/s]
Generating train split: 108474495 examples [1:59:37, 4974.42 examples/s]
Generating train split: 108475094 examples [1:59:37, 5103.58 examples/s]
Generating train split: 108475634 examples [1:59:37, 3905.91 examples/s]
Generating train split: 108476081 examples [1:59:38, 4017.66 examples/s]
Generating train split: 108476705 examples [1:59:38, 4393.10 examples/s]
Generating train split: 108477187 examples [1:59:38, 4406.01 examples/s]
Generating train split: 108477864 examples [1:59:38, 4995.76 examples/s]
Generating train split: 108478971 examples [1:59:38, 6571.42 examples/s]
Generating train split: 108479668 examples [1:59:38, 6652.42 examples/s]
Generating train split: 108481520 examples [1:59:38, 9965.46 examples/s]
Generating train split: 108482557 examples [1:59:38, 6770.17 examples/s]
Generating train split: 108483441 examples [1:59:39, 6884.97 examples/s]
Generating train split: 108484246 examples [1:59:39, 6896.25 examples/s]
Generating train split: 108485585 examples [1:59:39, 8430.09 examples/s]
Generating train split: 108486524 examples [1:59:39, 6711.09 examples/s]
Generating train split: 108487431 examples [1:59:39, 7161.48 examples/s]
Generating train split: 108488306 examples [1:59:39, 7135.41 examples/s]
Generating train split: 108489091 examples [1:59:39, 6991.22 examples/s]
Generating train split: 108489840 examples [1:59:39, 6934.03 examples/s]
Generating train split: 108490793 examples [1:59:40, 7525.88 examples/s]
Generating train split: 108492192 examples [1:59:40, 9248.50 examples/s]
Generating train split: 108493183 examples [1:59:40, 9039.59 examples/s]
Generating train split: 108494922 examples [1:59:40, 11325.45 examples/s]
Generating train split: 108496108 examples [1:59:40, 8963.18 examples/s] 
Generating train split: 108497267 examples [1:59:40, 9589.53 examples/s]
Generating train split: 108498317 examples [1:59:40, 9104.39 examples/s]
Generating train split: 108499294 examples [1:59:40, 7868.40 examples/s]
Generating train split: 108500159 examples [1:59:41, 7599.04 examples/s]
Generating train split: 108501565 examples [1:59:41, 9143.13 examples/s]
Generating train split: 108502580 examples [1:59:41, 9334.94 examples/s]
Generating train split: 108503914 examples [1:59:41, 10393.10 examples/s]
Generating train split: 108505392 examples [1:59:41, 11595.14 examples/s]
Generating train split: 108506771 examples [1:59:41, 12077.99 examples/s]
Generating train split: 108508016 examples [1:59:41, 8072.75 examples/s] 
Generating train split: 108509019 examples [1:59:42, 6883.49 examples/s]
Generating train split: 108510531 examples [1:59:42, 8478.28 examples/s]
Generating train split: 108511572 examples [1:59:42, 7425.98 examples/s]
Generating train split: 108512509 examples [1:59:42, 7828.85 examples/s]
Generating train split: 108513652 examples [1:59:42, 8626.99 examples/s]
Generating train split: 108515671 examples [1:59:42, 11460.27 examples/s]
Generating train split: 108516970 examples [1:59:42, 8921.34 examples/s] 
Generating train split: 108518229 examples [1:59:43, 9593.46 examples/s]
Generating train split: 108519352 examples [1:59:43, 7864.26 examples/s]
Generating train split: 108520843 examples [1:59:43, 9014.30 examples/s]
Generating train split: 108521878 examples [1:59:43, 8848.85 examples/s]
Generating train split: 108523000 examples [1:59:43, 9313.05 examples/s]
Generating train split: 108524013 examples [1:59:43, 7748.06 examples/s]
Generating train split: 108524879 examples [1:59:43, 6746.26 examples/s]
Generating train split: 108525633 examples [1:59:44, 6816.21 examples/s]
Generating train split: 108526374 examples [1:59:44, 5271.99 examples/s]
Generating train split: 108526986 examples [1:59:44, 5211.78 examples/s]
Generating train split: 108527794 examples [1:59:44, 5788.25 examples/s]
Generating train split: 108528439 examples [1:59:44, 4905.05 examples/s]
Generating train split: 108529409 examples [1:59:44, 5849.61 examples/s]
Generating train split: 108530074 examples [1:59:45, 3917.36 examples/s]
Generating train split: 108533420 examples [1:59:45, 9166.16 examples/s]
Generating train split: 108541618 examples [1:59:45, 23899.26 examples/s]
Generating train split: 108548905 examples [1:59:45, 34858.86 examples/s]
Generating train split: 108553484 examples [1:59:45, 29625.43 examples/s]
Generating train split: 108557348 examples [1:59:46, 17314.17 examples/s]
Generating train split: 108560291 examples [1:59:46, 13059.34 examples/s]
Generating train split: 108562567 examples [1:59:46, 11173.88 examples/s]
Generating train split: 108564380 examples [1:59:47, 11970.74 examples/s]
Generating train split: 108566165 examples [1:59:47, 10966.61 examples/s]
Generating train split: 108567889 examples [1:59:47, 11876.60 examples/s]
Generating train split: 108569444 examples [1:59:47, 6804.76 examples/s] 
Generating train split: 108570772 examples [1:59:47, 7572.95 examples/s]
Generating train split: 108571991 examples [1:59:48, 8063.48 examples/s]
Generating train split: 108573809 examples [1:59:48, 9791.36 examples/s]
Generating train split: 108575169 examples [1:59:48, 9036.12 examples/s]
Generating train split: 108576341 examples [1:59:48, 9051.32 examples/s]
Generating train split: 108577688 examples [1:59:48, 9933.47 examples/s]
Generating train split: 108580087 examples [1:59:48, 13124.60 examples/s]
Generating train split: 108581623 examples [1:59:49, 7834.92 examples/s] 
Generating train split: 108583300 examples [1:59:49, 9327.51 examples/s]
Generating train split: 108584646 examples [1:59:49, 10006.67 examples/s]
Generating train split: 108585965 examples [1:59:49, 9982.46 examples/s] 
Generating train split: 108593979 examples [1:59:49, 25567.32 examples/s]
Generating train split: 108600380 examples [1:59:49, 34814.35 examples/s]
Generating train split: 108604578 examples [1:59:49, 27364.87 examples/s]
Generating train split: 108608057 examples [1:59:50, 16625.82 examples/s]
Generating train split: 108615311 examples [1:59:50, 24986.87 examples/s]
Generating train split: 108623964 examples [1:59:50, 35821.92 examples/s]
Generating train split: 108629390 examples [1:59:51, 22760.90 examples/s]
Generating train split: 108633544 examples [1:59:51, 18923.00 examples/s]
Generating train split: 108636816 examples [1:59:51, 16659.07 examples/s]
Generating train split: 108639456 examples [1:59:51, 15267.97 examples/s]
Generating train split: 108641643 examples [1:59:52, 12191.88 examples/s]
Generating train split: 108647271 examples [1:59:52, 17865.63 examples/s]
Generating train split: 108655894 examples [1:59:52, 28480.54 examples/s]
Generating train split: 108663132 examples [1:59:52, 36448.19 examples/s]
Generating train split: 108668530 examples [1:59:53, 16052.48 examples/s]
Generating train split: 108672504 examples [1:59:53, 12772.84 examples/s]
Generating train split: 108675514 examples [1:59:54, 8366.46 examples/s] 
Generating train split: 108677727 examples [1:59:55, 7701.29 examples/s]
Generating train split: 108679454 examples [1:59:55, 6828.81 examples/s]
Generating train split: 108680789 examples [1:59:55, 7049.67 examples/s]
Generating train split: 108682288 examples [1:59:55, 7853.84 examples/s]
Generating train split: 108683888 examples [1:59:55, 8871.51 examples/s]
Generating train split: 108685270 examples [1:59:56, 7246.72 examples/s]
Generating train split: 108686500 examples [1:59:56, 7956.34 examples/s]
Generating train split: 108687803 examples [1:59:56, 8792.50 examples/s]
Generating train split: 108688982 examples [1:59:56, 6222.74 examples/s]
Generating train split: 108690624 examples [1:59:56, 7800.20 examples/s]
Generating train split: 108692547 examples [1:59:56, 9855.37 examples/s]
Generating train split: 108693926 examples [1:59:57, 7462.75 examples/s]
Generating train split: 108695724 examples [1:59:57, 9236.70 examples/s]
Generating train split: 108701336 examples [1:59:57, 18396.09 examples/s]
Generating train split: 108709741 examples [1:59:57, 32720.61 examples/s]
Generating train split: 108715265 examples [1:59:57, 38068.05 examples/s]
Generating train split: 108719957 examples [1:59:58, 22622.86 examples/s]
Generating train split: 108723588 examples [1:59:58, 21980.65 examples/s]
Generating train split: 108726741 examples [1:59:58, 20524.70 examples/s]
Generating train split: 108733125 examples [1:59:58, 28249.92 examples/s]
Generating train split: 108739877 examples [1:59:58, 36224.83 examples/s]
Generating train split: 108747299 examples [1:59:58, 44761.30 examples/s]
Generating train split: 108753646 examples [1:59:58, 49297.03 examples/s]
Generating train split: 108760920 examples [1:59:58, 55321.60 examples/s]
Generating train split: 108767616 examples [1:59:59, 58451.92 examples/s]
Generating train split: 108775148 examples [1:59:59, 63120.64 examples/s]
Generating train split: 108781863 examples [1:59:59, 63893.53 examples/s]
Generating train split: 108789025 examples [1:59:59, 66109.46 examples/s]
Generating train split: 108797015 examples [1:59:59, 70108.16 examples/s]
Generating train split: 108805176 examples [1:59:59, 73462.36 examples/s]
Generating train split: 108813309 examples [1:59:59, 75774.21 examples/s]
Generating train split: 108820975 examples [1:59:59, 76022.69 examples/s]
Generating train split: 108828943 examples [1:59:59, 77083.88 examples/s]
Generating train split: 108836749 examples [1:59:59, 77371.67 examples/s]
Generating train split: 108844580 examples [2:00:00, 77644.60 examples/s]
Generating train split: 108852368 examples [2:00:00, 70901.92 examples/s]
Generating train split: 108860014 examples [2:00:00, 71743.86 examples/s]
Generating train split: 108868023 examples [2:00:00, 74106.76 examples/s]
Generating train split: 108875920 examples [2:00:00, 75451.21 examples/s]
Generating train split: 108883530 examples [2:00:00, 73693.74 examples/s]
Generating train split: 108890950 examples [2:00:00, 73736.30 examples/s]
Generating train split: 108898360 examples [2:00:00, 68935.26 examples/s]
Generating train split: 108905335 examples [2:00:00, 68679.58 examples/s]
Generating train split: 108912265 examples [2:00:01, 68090.73 examples/s]
Generating train split: 108919113 examples [2:00:01, 66936.36 examples/s]
Generating train split: 108925842 examples [2:00:01, 65775.88 examples/s]
Generating train split: 108932440 examples [2:00:01, 57662.88 examples/s]
Generating train split: 108938388 examples [2:00:01, 53046.09 examples/s]
Generating train split: 108943860 examples [2:00:01, 38318.09 examples/s]
Generating train split: 108948336 examples [2:00:01, 38445.49 examples/s]
Generating train split: 108952644 examples [2:00:02, 37256.97 examples/s]
Generating train split: 108956679 examples [2:00:02, 30019.91 examples/s]
Generating train split: 108960064 examples [2:00:02, 23918.03 examples/s]
Generating train split: 108962865 examples [2:00:02, 15279.50 examples/s]
Generating train split: 108965027 examples [2:00:03, 15463.04 examples/s]
Generating train split: 108967023 examples [2:00:03, 13682.92 examples/s]
Generating train split: 108968704 examples [2:00:03, 10228.47 examples/s]
Generating train split: 108970426 examples [2:00:03, 11084.57 examples/s]
Generating train split: 108971835 examples [2:00:04, 7037.49 examples/s] 
Generating train split: 108972910 examples [2:00:04, 6314.90 examples/s]
Generating train split: 108973951 examples [2:00:04, 6794.67 examples/s]
Generating train split: 108974857 examples [2:00:04, 5041.35 examples/s]
Generating train split: 108975569 examples [2:00:05, 4253.93 examples/s]
Generating train split: 108976992 examples [2:00:05, 5602.43 examples/s]
Generating train split: 108978291 examples [2:00:05, 6796.07 examples/s]
Generating train split: 108980415 examples [2:00:05, 9477.10 examples/s]
Generating train split: 108981725 examples [2:00:05, 6688.97 examples/s]
Generating train split: 108982752 examples [2:00:06, 6200.97 examples/s]
Generating train split: 108983632 examples [2:00:06, 5355.82 examples/s]
Generating train split: 108991571 examples [2:00:06, 17300.40 examples/s]
Generating train split: 109000444 examples [2:00:06, 30680.69 examples/s]
Generating train split: 109005132 examples [2:00:06, 25336.21 examples/s]
Generating train split: 109008943 examples [2:00:07, 15296.87 examples/s]
Generating train split: 109011819 examples [2:00:07, 12221.49 examples/s]
Generating train split: 109014051 examples [2:00:07, 11686.68 examples/s]
Generating train split: 109022278 examples [2:00:08, 20531.29 examples/s]
Generating train split: 109030857 examples [2:00:08, 30433.89 examples/s]
Generating train split: 109036077 examples [2:00:08, 22285.89 examples/s]
Generating train split: 109040119 examples [2:00:08, 18138.42 examples/s]
Generating train split: 109043286 examples [2:00:09, 17536.08 examples/s]
Generating train split: 109045977 examples [2:00:09, 14612.00 examples/s]
Generating train split: 109048125 examples [2:00:09, 14804.10 examples/s]
Generating train split: 109050771 examples [2:00:09, 16353.11 examples/s]
Generating train split: 109052872 examples [2:00:09, 15729.60 examples/s]
Generating train split: 109054906 examples [2:00:09, 16441.45 examples/s]
Generating train split: 109056816 examples [2:00:10, 15629.03 examples/s]
Generating train split: 109058557 examples [2:00:10, 12017.20 examples/s]
Generating train split: 109059982 examples [2:00:10, 10974.31 examples/s]
Generating train split: 109061270 examples [2:00:10, 11338.41 examples/s]
Generating train split: 109062540 examples [2:00:10, 9309.86 examples/s] 
Generating train split: 109064401 examples [2:00:10, 11138.14 examples/s]
Generating train split: 109065796 examples [2:00:11, 11751.98 examples/s]
Generating train split: 109067124 examples [2:00:11, 11345.59 examples/s]
Generating train split: 109068372 examples [2:00:11, 9442.04 examples/s] 
Generating train split: 109070658 examples [2:00:11, 12377.69 examples/s]
Generating train split: 109076402 examples [2:00:11, 23127.90 examples/s]
Generating train split: 109084908 examples [2:00:11, 38870.09 examples/s]
Generating train split: 109089825 examples [2:00:11, 41438.03 examples/s]
Generating train split: 109094404 examples [2:00:11, 29856.99 examples/s]
Generating train split: 109098141 examples [2:00:12, 14334.21 examples/s]
Generating train split: 109100941 examples [2:00:12, 14432.15 examples/s]
Generating train split: 109109275 examples [2:00:12, 23851.37 examples/s]
Generating train split: 109116632 examples [2:00:13, 31933.24 examples/s]
Generating train split: 109121754 examples [2:00:13, 19172.59 examples/s]
Generating train split: 109125615 examples [2:00:13, 15977.37 examples/s]
Generating train split: 109128627 examples [2:00:14, 13022.22 examples/s]
Generating train split: 109130959 examples [2:00:14, 11062.48 examples/s]
Generating train split: 109132798 examples [2:00:15, 8838.45 examples/s] 
Generating train split: 109134226 examples [2:00:15, 9301.68 examples/s]
Generating train split: 109135614 examples [2:00:15, 9674.20 examples/s]
Generating train split: 109136944 examples [2:00:15, 8812.37 examples/s]
Generating train split: 109144304 examples [2:00:15, 19053.85 examples/s]
Generating train split: 109152086 examples [2:00:15, 29880.85 examples/s]
Generating train split: 109156514 examples [2:00:16, 20157.47 examples/s]
Generating train split: 109159945 examples [2:00:17, 10392.73 examples/s]
Generating train split: 109162477 examples [2:00:17, 7177.15 examples/s] 
Generating train split: 109164340 examples [2:00:18, 5939.72 examples/s]
Generating train split: 109165753 examples [2:00:19, 4478.77 examples/s]
Generating train split: 109166793 examples [2:00:19, 4465.95 examples/s]
Generating train split: 109167655 examples [2:00:19, 3961.03 examples/s]
Generating train split: 109168328 examples [2:00:19, 4175.54 examples/s]
Generating train split: 109169729 examples [2:00:19, 5252.41 examples/s]
Generating train split: 109170616 examples [2:00:20, 5540.48 examples/s]
Generating train split: 109171451 examples [2:00:20, 4978.12 examples/s]
Generating train split: 109172336 examples [2:00:20, 5574.69 examples/s]
Generating train split: 109173463 examples [2:00:20, 6593.05 examples/s]
Generating train split: 109174328 examples [2:00:20, 5409.58 examples/s]
Generating train split: 109175634 examples [2:00:20, 6819.79 examples/s]
Generating train split: 109176810 examples [2:00:20, 7818.43 examples/s]
Generating train split: 109178437 examples [2:00:21, 9738.50 examples/s]
Generating train split: 109180136 examples [2:00:21, 11477.89 examples/s]
Generating train split: 109181466 examples [2:00:21, 6990.66 examples/s] 
Generating train split: 109182497 examples [2:00:21, 6188.88 examples/s]
Generating train split: 109183352 examples [2:00:21, 5911.00 examples/s]
Generating train split: 109184116 examples [2:00:22, 5377.90 examples/s]
Generating train split: 109184775 examples [2:00:22, 5030.16 examples/s]
Generating train split: 109185354 examples [2:00:22, 4371.69 examples/s]
Generating train split: 109185977 examples [2:00:22, 4593.77 examples/s]
Generating train split: 109186640 examples [2:00:22, 4882.53 examples/s]
Generating train split: 109187181 examples [2:00:22, 4412.58 examples/s]
Generating train split: 109188250 examples [2:00:22, 5787.17 examples/s]
Generating train split: 109195986 examples [2:00:23, 22845.58 examples/s]
Generating train split: 109203551 examples [2:00:23, 36247.51 examples/s]
Generating train split: 109207764 examples [2:00:23, 27600.26 examples/s]
Generating train split: 109211241 examples [2:00:23, 14767.91 examples/s]
Generating train split: 109213865 examples [2:00:24, 10970.84 examples/s]
Generating train split: 109215886 examples [2:00:24, 11634.76 examples/s]
Generating train split: 109217767 examples [2:00:24, 11949.84 examples/s]
Generating train split: 109219490 examples [2:00:24, 9933.53 examples/s] 
Generating train split: 109220872 examples [2:00:25, 9874.67 examples/s]
Generating train split: 109222253 examples [2:00:25, 10492.11 examples/s]
Generating train split: 109223545 examples [2:00:25, 7371.54 examples/s] 
Generating train split: 109229947 examples [2:00:25, 16162.62 examples/s]
Generating train split: 109237860 examples [2:00:25, 27585.58 examples/s]
Generating train split: 109243343 examples [2:00:25, 32779.04 examples/s]
Generating train split: 109247842 examples [2:00:26, 23053.55 examples/s]
Generating train split: 109255470 examples [2:00:26, 32237.73 examples/s]
Generating train split: 109260364 examples [2:00:26, 35526.56 examples/s]
Generating train split: 109265171 examples [2:00:26, 23318.58 examples/s]
Generating train split: 109268904 examples [2:00:27, 19647.11 examples/s]
Generating train split: 109271907 examples [2:00:27, 12472.44 examples/s]
Generating train split: 109274168 examples [2:00:28, 9448.18 examples/s] 
Generating train split: 109276352 examples [2:00:28, 10680.48 examples/s]
Generating train split: 109278211 examples [2:00:28, 10197.18 examples/s]
Generating train split: 109279775 examples [2:00:28, 9074.72 examples/s] 
Generating train split: 109281052 examples [2:00:29, 6339.40 examples/s]
Generating train split: 109282034 examples [2:00:29, 4906.70 examples/s]
Generating train split: 109283657 examples [2:00:29, 6100.59 examples/s]
Generating train split: 109284667 examples [2:00:29, 5991.70 examples/s]
Generating train split: 109286133 examples [2:00:29, 7251.37 examples/s]
Generating train split: 109287186 examples [2:00:30, 7658.40 examples/s]
Generating train split: 109288211 examples [2:00:30, 6847.21 examples/s]
Generating train split: 109289085 examples [2:00:30, 5635.40 examples/s]
Generating train split: 109290426 examples [2:00:30, 6932.10 examples/s]
Generating train split: 109293044 examples [2:00:30, 10638.42 examples/s]
Generating train split: 109294410 examples [2:00:31, 7606.65 examples/s] 
Generating train split: 109296075 examples [2:00:31, 9159.93 examples/s]
Generating train split: 109297339 examples [2:00:31, 9722.19 examples/s]
Generating train split: 109298760 examples [2:00:31, 10269.18 examples/s]
Generating train split: 109299986 examples [2:00:31, 9106.88 examples/s] 
Generating train split: 109301055 examples [2:00:31, 7715.17 examples/s]
Generating train split: 109301960 examples [2:00:31, 7232.52 examples/s]
Generating train split: 109302801 examples [2:00:31, 7471.95 examples/s]
Generating train split: 109303631 examples [2:00:32, 4936.72 examples/s]
Generating train split: 109304290 examples [2:00:32, 5220.15 examples/s]
Generating train split: 109305745 examples [2:00:32, 7075.62 examples/s]
Generating train split: 109306637 examples [2:00:32, 7320.55 examples/s]
Generating train split: 109307510 examples [2:00:32, 6590.91 examples/s]
Generating train split: 109308283 examples [2:00:32, 6717.81 examples/s]
Generating train split: 109312550 examples [2:00:33, 15342.12 examples/s]
Generating train split: 109320478 examples [2:00:33, 31658.26 examples/s]
Generating train split: 109325035 examples [2:00:33, 34961.52 examples/s]
Generating train split: 109328906 examples [2:00:33, 26141.46 examples/s]
Generating train split: 109332108 examples [2:00:33, 17852.17 examples/s]
Generating train split: 109334626 examples [2:00:34, 11678.47 examples/s]
Generating train split: 109336554 examples [2:00:34, 12403.87 examples/s]
Generating train split: 109338779 examples [2:00:34, 13865.65 examples/s]
Generating train split: 109340724 examples [2:00:34, 13335.78 examples/s]
Generating train split: 109342440 examples [2:00:34, 11615.89 examples/s]
Generating train split: 109344335 examples [2:00:34, 12930.95 examples/s]
Generating train split: 109345917 examples [2:00:35, 11220.30 examples/s]
Generating train split: 109348914 examples [2:00:35, 14878.44 examples/s]
Generating train split: 109350751 examples [2:00:35, 9312.43 examples/s] 
Generating train split: 109352422 examples [2:00:35, 10467.93 examples/s]
Generating train split: 109353927 examples [2:00:36, 6872.97 examples/s] 
Generating train split: 109355076 examples [2:00:36, 5329.04 examples/s]
Generating train split: 109356019 examples [2:00:36, 5807.39 examples/s]
Generating train split: 109356921 examples [2:00:36, 5279.79 examples/s]
Generating train split: 109357679 examples [2:00:37, 5103.69 examples/s]
Generating train split: 109358664 examples [2:00:37, 5871.08 examples/s]
Generating train split: 109359418 examples [2:00:37, 6183.01 examples/s]
Generating train split: 109360185 examples [2:00:37, 5760.47 examples/s]
Generating train split: 109360867 examples [2:00:37, 5228.07 examples/s]
Generating train split: 109361613 examples [2:00:37, 5686.59 examples/s]
Generating train split: 109363499 examples [2:00:37, 8692.07 examples/s]
Generating train split: 109364505 examples [2:00:38, 5565.18 examples/s]
Generating train split: 109366822 examples [2:00:38, 8705.74 examples/s]
Generating train split: 109369392 examples [2:00:38, 12157.07 examples/s]
Generating train split: 109371141 examples [2:00:38, 13287.68 examples/s]
Generating train split: 109372808 examples [2:00:38, 13601.12 examples/s]
Generating train split: 109374410 examples [2:00:38, 10974.50 examples/s]
Generating train split: 109375754 examples [2:00:39, 8131.29 examples/s] 
Generating train split: 109376834 examples [2:00:39, 8455.10 examples/s]
Generating train split: 109377883 examples [2:00:39, 5294.19 examples/s]
Generating train split: 109378697 examples [2:00:39, 5095.22 examples/s]
Generating train split: 109381387 examples [2:00:39, 8513.68 examples/s]
Generating train split: 109382681 examples [2:00:40, 6048.84 examples/s]
Generating train split: 109383682 examples [2:00:40, 4051.23 examples/s]
Generating train split: 109384453 examples [2:00:41, 3032.29 examples/s]
Generating train split: 109385307 examples [2:00:41, 3567.94 examples/s]
Generating train split: 109385963 examples [2:00:41, 3506.30 examples/s]
Generating train split: 109386529 examples [2:00:42, 2997.14 examples/s]
Generating train split: 109387095 examples [2:00:42, 3232.00 examples/s]
Generating train split: 109387787 examples [2:00:42, 3800.50 examples/s]
Generating train split: 109388919 examples [2:00:42, 5151.69 examples/s]
Generating train split: 109389668 examples [2:00:42, 5623.67 examples/s]
Generating train split: 109390388 examples [2:00:42, 5818.47 examples/s]
Generating train split: 109391089 examples [2:00:42, 3629.02 examples/s]
Generating train split: 109391756 examples [2:00:43, 4135.85 examples/s]
Generating train split: 109392562 examples [2:00:43, 4883.67 examples/s]
Generating train split: 109393207 examples [2:00:43, 3889.25 examples/s]
Generating train split: 109393767 examples [2:00:43, 4198.73 examples/s]
Generating train split: 109394312 examples [2:00:43, 4046.04 examples/s]
Generating train split: 109394799 examples [2:00:43, 3527.36 examples/s]
Generating train split: 109395690 examples [2:00:43, 4621.86 examples/s]
Generating train split: 109397682 examples [2:00:44, 8017.52 examples/s]
Generating train split: 109398660 examples [2:00:44, 6430.83 examples/s]
Generating train split: 109399565 examples [2:00:44, 6970.46 examples/s]
Generating train split: 109400402 examples [2:00:44, 5516.27 examples/s]
Generating train split: 109401095 examples [2:00:44, 4657.27 examples/s]
Generating train split: 109401675 examples [2:00:45, 4226.83 examples/s]
Generating train split: 109402743 examples [2:00:45, 5406.92 examples/s]
Generating train split: 109403613 examples [2:00:45, 5522.57 examples/s]
Generating train split: 109404259 examples [2:00:45, 4033.24 examples/s]
Generating train split: 109406581 examples [2:00:45, 7421.35 examples/s]
Generating train split: 109407645 examples [2:00:46, 4769.50 examples/s]
Generating train split: 109408462 examples [2:00:46, 3565.08 examples/s]
Generating train split: 109409088 examples [2:00:46, 3789.62 examples/s]
Generating train split: 109409862 examples [2:00:46, 4363.71 examples/s]
Generating train split: 109410512 examples [2:00:46, 4034.49 examples/s]
Generating train split: 109411076 examples [2:00:47, 3685.15 examples/s]
Generating train split: 109412008 examples [2:00:47, 4664.48 examples/s]
Generating train split: 109412622 examples [2:00:47, 3375.04 examples/s]
Generating train split: 109413339 examples [2:00:47, 3976.82 examples/s]
Generating train split: 109414570 examples [2:00:47, 5527.68 examples/s]
Generating train split: 109415332 examples [2:00:48, 3938.00 examples/s]
Generating train split: 109416404 examples [2:00:48, 5062.46 examples/s]
Generating train split: 109417753 examples [2:00:48, 6675.23 examples/s]
Generating train split: 109418670 examples [2:00:48, 4727.69 examples/s]
Generating train split: 109419670 examples [2:00:48, 5542.46 examples/s]
Generating train split: 109420456 examples [2:00:48, 5282.16 examples/s]
Generating train split: 109422719 examples [2:00:49, 8480.32 examples/s]
Generating train split: 109423829 examples [2:00:49, 8244.29 examples/s]
Generating train split: 109424831 examples [2:00:49, 6503.87 examples/s]
Generating train split: 109427410 examples [2:00:49, 10160.50 examples/s]
Generating train split: 109428757 examples [2:00:49, 7548.93 examples/s] 
Generating train split: 109429837 examples [2:00:50, 6362.33 examples/s]
Generating train split: 109430714 examples [2:00:50, 5800.25 examples/s]
Generating train split: 109431469 examples [2:00:50, 6092.19 examples/s]
Generating train split: 109432220 examples [2:00:50, 5467.29 examples/s]
Generating train split: 109433037 examples [2:00:50, 5963.96 examples/s]
Generating train split: 109433734 examples [2:00:50, 4944.10 examples/s]
Generating train split: 109434327 examples [2:00:51, 4553.33 examples/s]
Generating train split: 109435323 examples [2:00:51, 5627.41 examples/s]
Generating train split: 109435988 examples [2:00:51, 4243.47 examples/s]
Generating train split: 109437077 examples [2:00:51, 5478.67 examples/s]
Generating train split: 109437787 examples [2:00:51, 5728.12 examples/s]
Generating train split: 109439509 examples [2:00:51, 8313.88 examples/s]
Generating train split: 109441176 examples [2:00:51, 10357.49 examples/s]
Generating train split: 109442368 examples [2:00:52, 9931.31 examples/s] 
Generating train split: 109443621 examples [2:00:52, 10204.49 examples/s]
Generating train split: 109444723 examples [2:00:52, 7528.74 examples/s] 
Generating train split: 109445640 examples [2:00:52, 6075.95 examples/s]
Generating train split: 109446391 examples [2:00:52, 5464.33 examples/s]
Generating train split: 109448221 examples [2:00:52, 7878.78 examples/s]
Generating train split: 109449636 examples [2:00:53, 9151.24 examples/s]
Generating train split: 109450747 examples [2:00:53, 8830.93 examples/s]
Generating train split: 109451769 examples [2:00:53, 6694.98 examples/s]
Generating train split: 109452985 examples [2:00:53, 7763.61 examples/s]
Generating train split: 109453980 examples [2:00:53, 8171.17 examples/s]
Generating train split: 109455276 examples [2:00:53, 9233.97 examples/s]
Generating train split: 109456323 examples [2:00:54, 6297.45 examples/s]
Generating train split: 109464372 examples [2:00:54, 20489.64 examples/s]
Generating train split: 109473339 examples [2:00:54, 35335.07 examples/s]
Generating train split: 109478140 examples [2:00:54, 18124.02 examples/s]
Generating train split: 109481741 examples [2:00:55, 13630.95 examples/s]
Generating train split: 109484490 examples [2:00:55, 15153.12 examples/s]
Generating train split: 109493625 examples [2:00:55, 25838.90 examples/s]
Generating train split: 109500447 examples [2:00:55, 32907.39 examples/s]
Generating train split: 109505743 examples [2:00:56, 19457.61 examples/s]
Generating train split: 109509734 examples [2:00:56, 14347.67 examples/s]
Generating train split: 109512767 examples [2:00:56, 13813.60 examples/s]
Generating train split: 109515246 examples [2:00:57, 12341.75 examples/s]
Generating train split: 109517237 examples [2:00:57, 11066.45 examples/s]
Generating train split: 109518862 examples [2:00:57, 10958.80 examples/s]
Generating train split: 109520656 examples [2:00:57, 11943.88 examples/s]
Generating train split: 109522207 examples [2:00:57, 11219.68 examples/s]
Generating train split: 109523577 examples [2:00:58, 9526.01 examples/s] 
Generating train split: 109524721 examples [2:00:58, 9741.24 examples/s]
Generating train split: 109525848 examples [2:00:58, 9674.35 examples/s]
Generating train split: 109527059 examples [2:00:58, 10188.03 examples/s]
Generating train split: 109528167 examples [2:00:58, 9960.50 examples/s] 
Generating train split: 109530003 examples [2:00:58, 11976.36 examples/s]
Generating train split: 109531301 examples [2:00:58, 11344.54 examples/s]
Generating train split: 109532688 examples [2:00:58, 11971.73 examples/s]
Generating train split: 109533956 examples [2:00:59, 8538.19 examples/s] 
Generating train split: 109534995 examples [2:00:59, 6979.13 examples/s]
Generating train split: 109536269 examples [2:00:59, 8071.68 examples/s]
Generating train split: 109537252 examples [2:00:59, 7229.27 examples/s]
Generating train split: 109538409 examples [2:00:59, 8089.90 examples/s]
Generating train split: 109540946 examples [2:00:59, 12014.01 examples/s]
Generating train split: 109542364 examples [2:01:00, 7758.14 examples/s] 
Generating train split: 109543637 examples [2:01:00, 8591.13 examples/s]
Generating train split: 109544789 examples [2:01:00, 8293.42 examples/s]
Generating train split: 109545832 examples [2:01:00, 6444.61 examples/s]
Generating train split: 109547716 examples [2:01:00, 8623.16 examples/s]
Generating train split: 109548852 examples [2:01:00, 9112.98 examples/s]
Generating train split: 109549983 examples [2:01:01, 5953.29 examples/s]
Generating train split: 109551209 examples [2:01:01, 6989.33 examples/s]
Generating train split: 109553199 examples [2:01:01, 9182.20 examples/s]
Generating train split: 109554413 examples [2:01:01, 6379.77 examples/s]
Generating train split: 109555433 examples [2:01:02, 7001.94 examples/s]
Generating train split: 109556411 examples [2:01:02, 7494.33 examples/s]
Generating train split: 109557393 examples [2:01:02, 6079.18 examples/s]
Generating train split: 109558718 examples [2:01:02, 7408.24 examples/s]
Generating train split: 109560633 examples [2:01:02, 9846.47 examples/s]
Generating train split: 109561868 examples [2:01:02, 9255.55 examples/s]
Generating train split: 109562975 examples [2:01:02, 8674.42 examples/s]
Generating train split: 109563971 examples [2:01:03, 7958.94 examples/s]
Generating train split: 109565604 examples [2:01:03, 9816.86 examples/s]
Generating train split: 109566727 examples [2:01:03, 10008.19 examples/s]
Generating train split: 109568043 examples [2:01:03, 10730.46 examples/s]
Generating train split: 109569226 examples [2:01:03, 11014.27 examples/s]
Generating train split: 109570397 examples [2:01:03, 8424.00 examples/s] 
Generating train split: 109571374 examples [2:01:03, 8211.46 examples/s]
Generating train split: 109572612 examples [2:01:03, 9126.96 examples/s]
Generating train split: 109573771 examples [2:01:03, 9725.57 examples/s]
Generating train split: 109574827 examples [2:01:04, 8478.43 examples/s]
Generating train split: 109575752 examples [2:01:04, 7954.23 examples/s]
Generating train split: 109577649 examples [2:01:04, 10598.14 examples/s]
Generating train split: 109578817 examples [2:01:04, 10330.78 examples/s]
Generating train split: 109579929 examples [2:01:04, 7290.36 examples/s] 
Generating train split: 109583595 examples [2:01:04, 13253.93 examples/s]
Generating train split: 109586048 examples [2:01:04, 15772.84 examples/s]
Generating train split: 109588006 examples [2:01:05, 10610.54 examples/s]
Generating train split: 109589556 examples [2:01:05, 9738.25 examples/s] 
Generating train split: 109590874 examples [2:01:05, 7215.25 examples/s]
Generating train split: 109591904 examples [2:01:06, 6893.37 examples/s]
Generating train split: 109593513 examples [2:01:06, 8382.24 examples/s]
Generating train split: 109594626 examples [2:01:06, 7371.72 examples/s]
Generating train split: 109596249 examples [2:01:06, 8946.96 examples/s]
Generating train split: 109597388 examples [2:01:06, 8268.50 examples/s]
Generating train split: 109598386 examples [2:01:06, 7135.13 examples/s]
Generating train split: 109600254 examples [2:01:06, 9381.32 examples/s]
Generating train split: 109601413 examples [2:01:07, 7813.98 examples/s]
Generating train split: 109602532 examples [2:01:07, 8386.57 examples/s]
Generating train split: 109603528 examples [2:01:07, 7774.96 examples/s]
Generating train split: 109604764 examples [2:01:07, 8769.59 examples/s]
Generating train split: 109605754 examples [2:01:07, 8560.96 examples/s]
Generating train split: 109608466 examples [2:01:07, 13047.90 examples/s]
Generating train split: 109609932 examples [2:01:08, 5621.57 examples/s] 
Generating train split: 109611719 examples [2:01:08, 7227.95 examples/s]
Generating train split: 109613009 examples [2:01:08, 5788.36 examples/s]
Generating train split: 109614923 examples [2:01:08, 7647.77 examples/s]
Generating train split: 109617642 examples [2:01:09, 10890.46 examples/s]
Generating train split: 109620186 examples [2:01:09, 13507.92 examples/s]
Generating train split: 109622105 examples [2:01:09, 12457.84 examples/s]
Generating train split: 109623765 examples [2:01:09, 10824.27 examples/s]
Generating train split: 109625159 examples [2:01:09, 7706.31 examples/s] 
Generating train split: 109626263 examples [2:01:10, 7809.59 examples/s]
Generating train split: 109633224 examples [2:01:10, 18614.95 examples/s]
Generating train split: 109640601 examples [2:01:10, 28951.37 examples/s]
Generating train split: 109644538 examples [2:01:10, 20718.53 examples/s]
Generating train split: 109647651 examples [2:01:10, 17649.27 examples/s]
Generating train split: 109650198 examples [2:01:11, 13422.39 examples/s]
Generating train split: 109652197 examples [2:01:11, 10207.97 examples/s]
Generating train split: 109653931 examples [2:01:11, 11081.18 examples/s]
Generating train split: 109655541 examples [2:01:11, 10018.73 examples/s]
Generating train split: 109656882 examples [2:01:12, 9276.23 examples/s] 
Generating train split: 109658040 examples [2:01:12, 9255.37 examples/s]
Generating train split: 109659608 examples [2:01:12, 10410.04 examples/s]
Generating train split: 109660944 examples [2:01:12, 11014.01 examples/s]
Generating train split: 109662611 examples [2:01:12, 12295.24 examples/s]
Generating train split: 109663998 examples [2:01:12, 9242.43 examples/s] 
Generating train split: 109665129 examples [2:01:12, 7617.46 examples/s]
Generating train split: 109669063 examples [2:01:13, 13502.95 examples/s]
Generating train split: 109671471 examples [2:01:13, 15720.87 examples/s]
Generating train split: 109673482 examples [2:01:13, 15536.28 examples/s]
Generating train split: 109675335 examples [2:01:13, 13845.83 examples/s]
Generating train split: 109676954 examples [2:01:13, 12915.16 examples/s]
Generating train split: 109678423 examples [2:01:13, 11473.64 examples/s]
Generating train split: 109679703 examples [2:01:14, 8959.16 examples/s] 
Generating train split: 109681013 examples [2:01:14, 9740.19 examples/s]
Generating train split: 109682827 examples [2:01:14, 11522.63 examples/s]
Generating train split: 109684165 examples [2:01:14, 8268.95 examples/s] 
Generating train split: 109685242 examples [2:01:14, 7078.38 examples/s]
Generating train split: 109686145 examples [2:01:15, 5660.42 examples/s]
Generating train split: 109687233 examples [2:01:15, 6500.24 examples/s]
Generating train split: 109688131 examples [2:01:15, 6954.93 examples/s]
Generating train split: 109688980 examples [2:01:15, 5785.54 examples/s]
Generating train split: 109689690 examples [2:01:15, 5596.48 examples/s]
Generating train split: 109691371 examples [2:01:15, 7861.67 examples/s]
Generating train split: 109692326 examples [2:01:16, 5575.40 examples/s]
Generating train split: 109693088 examples [2:01:16, 5874.21 examples/s]
Generating train split: 109694058 examples [2:01:16, 6634.50 examples/s]
Generating train split: 109694878 examples [2:01:16, 6504.35 examples/s]
Generating train split: 109695632 examples [2:01:16, 6248.12 examples/s]
Generating train split: 109697134 examples [2:01:16, 8280.06 examples/s]
Generating train split: 109699048 examples [2:01:16, 10957.93 examples/s]
Generating train split: 109700322 examples [2:01:16, 11351.73 examples/s]
Generating train split: 109701557 examples [2:01:16, 10979.52 examples/s]
Generating train split: 109702722 examples [2:01:17, 9280.46 examples/s] 
Generating train split: 109703851 examples [2:01:17, 9557.79 examples/s]
Generating train split: 109708783 examples [2:01:17, 19590.03 examples/s]
Generating train split: 109717300 examples [2:01:17, 36954.98 examples/s]
Generating train split: 109721885 examples [2:01:17, 37582.84 examples/s]
Generating train split: 109725931 examples [2:01:17, 23050.47 examples/s]
Generating train split: 109729123 examples [2:01:18, 14412.85 examples/s]
Generating train split: 109731559 examples [2:01:18, 14731.72 examples/s]
Generating train split: 109733738 examples [2:01:18, 13523.89 examples/s]
Generating train split: 109735582 examples [2:01:18, 11948.84 examples/s]
Generating train split: 109737117 examples [2:01:19, 12128.59 examples/s]
Generating train split: 109738581 examples [2:01:19, 9090.52 examples/s] 
Generating train split: 109739952 examples [2:01:19, 9652.19 examples/s]
Generating train split: 109741149 examples [2:01:19, 9049.11 examples/s]
Generating train split: 109742204 examples [2:01:19, 9020.15 examples/s]
Generating train split: 109743998 examples [2:01:19, 10854.26 examples/s]
Generating train split: 109746421 examples [2:01:19, 13897.33 examples/s]
Generating train split: 109748830 examples [2:01:20, 16380.07 examples/s]
Generating train split: 109750671 examples [2:01:20, 15982.41 examples/s]
Generating train split: 109752413 examples [2:01:20, 12628.01 examples/s]
Generating train split: 109754335 examples [2:01:20, 13997.73 examples/s]
Generating train split: 109755932 examples [2:01:20, 10180.97 examples/s]
Generating train split: 109757224 examples [2:01:20, 8841.58 examples/s] 
Generating train split: 109758348 examples [2:01:21, 9264.08 examples/s]
Generating train split: 109759443 examples [2:01:21, 6584.47 examples/s]
Generating train split: 109760312 examples [2:01:21, 6915.74 examples/s]
Generating train split: 109761709 examples [2:01:21, 8290.22 examples/s]
Generating train split: 109763196 examples [2:01:21, 9715.40 examples/s]
Generating train split: 109764369 examples [2:01:22, 6861.31 examples/s]
Generating train split: 109765297 examples [2:01:22, 6959.88 examples/s]
Generating train split: 109767150 examples [2:01:22, 9288.98 examples/s]
Generating train split: 109769340 examples [2:01:22, 11996.35 examples/s]
Generating train split: 109770788 examples [2:01:22, 6625.32 examples/s] 
Generating train split: 109771891 examples [2:01:23, 4752.83 examples/s]
Generating train split: 109772737 examples [2:01:23, 5134.50 examples/s]
Generating train split: 109773555 examples [2:01:23, 3878.84 examples/s]
Generating train split: 109774190 examples [2:01:24, 2444.06 examples/s]
Generating train split: 109774663 examples [2:01:24, 2436.96 examples/s]
Generating train split: 109775067 examples [2:01:24, 2054.88 examples/s]
Generating train split: 109775387 examples [2:01:25, 1887.85 examples/s]
Generating train split: 109778216 examples [2:01:25, 5092.36 examples/s]
Generating train split: 109779524 examples [2:01:25, 6214.88 examples/s]
Generating train split: 109780622 examples [2:01:25, 6032.08 examples/s]
Generating train split: 109781556 examples [2:01:25, 5649.22 examples/s]
Generating train split: 109782354 examples [2:01:25, 5403.74 examples/s]
Generating train split: 109783052 examples [2:01:26, 5284.35 examples/s]
Generating train split: 109783694 examples [2:01:26, 3647.92 examples/s]
Generating train split: 109784382 examples [2:01:26, 4139.11 examples/s]
Generating train split: 109785684 examples [2:01:26, 5745.71 examples/s]
Generating train split: 109786460 examples [2:01:26, 5717.99 examples/s]
Generating train split: 109787428 examples [2:01:26, 6557.10 examples/s]
Generating train split: 109788216 examples [2:01:27, 5459.27 examples/s]
Generating train split: 109788882 examples [2:01:27, 4884.42 examples/s]
Generating train split: 109790288 examples [2:01:27, 6756.75 examples/s]
Generating train split: 109793652 examples [2:01:27, 12826.86 examples/s]
Generating train split: 109797387 examples [2:01:27, 18597.03 examples/s]
Generating train split: 109799570 examples [2:01:27, 13531.60 examples/s]
Generating train split: 109801345 examples [2:01:28, 12383.08 examples/s]
Generating train split: 109802888 examples [2:01:28, 12004.53 examples/s]
Generating train split: 109804296 examples [2:01:28, 11034.28 examples/s]
Generating train split: 109805545 examples [2:01:28, 10023.20 examples/s]
Generating train split: 109806651 examples [2:01:28, 9944.99 examples/s] 
Generating train split: 109808450 examples [2:01:28, 11690.89 examples/s]
Generating train split: 109809729 examples [2:01:29, 8314.89 examples/s] 
Generating train split: 109810756 examples [2:01:29, 5110.80 examples/s]
Generating train split: 109812341 examples [2:01:29, 6609.40 examples/s]
Generating train split: 109813371 examples [2:01:30, 4771.75 examples/s]
Generating train split: 109814167 examples [2:01:30, 4808.09 examples/s]
Generating train split: 109815090 examples [2:01:30, 5442.81 examples/s]
Generating train split: 109815854 examples [2:01:30, 4053.38 examples/s]
Generating train split: 109816451 examples [2:01:30, 3363.72 examples/s]
Generating train split: 109816932 examples [2:01:31, 3330.95 examples/s]
Generating train split: 109817608 examples [2:01:31, 3870.96 examples/s]
Generating train split: 109818367 examples [2:01:31, 4537.44 examples/s]
Generating train split: 109818944 examples [2:01:31, 4638.95 examples/s]
Generating train split: 109819602 examples [2:01:31, 5057.21 examples/s]
Generating train split: 109820186 examples [2:01:31, 4634.45 examples/s]
Generating train split: 109820972 examples [2:01:31, 5334.37 examples/s]
Generating train split: 109821618 examples [2:01:31, 5495.57 examples/s]
Generating train split: 109822213 examples [2:01:32, 3737.13 examples/s]
Generating train split: 109822927 examples [2:01:32, 4396.15 examples/s]
Generating train split: 109823577 examples [2:01:32, 4726.50 examples/s]
Generating train split: 109824132 examples [2:01:32, 4656.07 examples/s]
Generating train split: 109825243 examples [2:01:32, 6176.85 examples/s]
Generating train split: 109825946 examples [2:01:32, 5152.98 examples/s]
Generating train split: 109827390 examples [2:01:32, 7251.34 examples/s]
Generating train split: 109828292 examples [2:01:32, 7678.39 examples/s]
Generating train split: 109829214 examples [2:01:33, 8075.88 examples/s]
Generating train split: 109830734 examples [2:01:33, 9996.39 examples/s]
Generating train split: 109831807 examples [2:01:33, 7801.64 examples/s]
Generating train split: 109833305 examples [2:01:33, 9417.57 examples/s]
Generating train split: 109835693 examples [2:01:33, 12960.04 examples/s]
Generating train split: 109837149 examples [2:01:33, 10547.94 examples/s]
Generating train split: 109838391 examples [2:01:34, 7187.89 examples/s] 
Generating train split: 109840025 examples [2:01:34, 8791.16 examples/s]
Generating train split: 109841198 examples [2:01:34, 7140.63 examples/s]
Generating train split: 109842156 examples [2:01:34, 6716.23 examples/s]
Generating train split: 109843068 examples [2:01:34, 7146.72 examples/s]
Generating train split: 109843935 examples [2:01:35, 5385.84 examples/s]
Generating train split: 109844632 examples [2:01:35, 4179.68 examples/s]
Generating train split: 109845555 examples [2:01:35, 4967.36 examples/s]
Generating train split: 109846223 examples [2:01:35, 4937.07 examples/s]
Generating train split: 109846832 examples [2:01:35, 3647.56 examples/s]
Generating train split: 109847333 examples [2:01:36, 3487.72 examples/s]
Generating train split: 109848882 examples [2:01:36, 5591.65 examples/s]
Generating train split: 109849654 examples [2:01:36, 3903.47 examples/s]
Generating train split: 109850763 examples [2:01:36, 5010.31 examples/s]
Generating train split: 109852338 examples [2:01:36, 6965.70 examples/s]
Generating train split: 109853340 examples [2:01:36, 6502.68 examples/s]
Generating train split: 109854202 examples [2:01:37, 6041.07 examples/s]
Generating train split: 109854989 examples [2:01:37, 6407.17 examples/s]
Generating train split: 109856777 examples [2:01:37, 8914.62 examples/s]
Generating train split: 109857845 examples [2:01:37, 4336.43 examples/s]
Generating train split: 109858646 examples [2:01:38, 3670.79 examples/s]
Generating train split: 109860056 examples [2:01:38, 5019.49 examples/s]
Generating train split: 109861125 examples [2:01:38, 5850.09 examples/s]
Generating train split: 109862043 examples [2:01:38, 4943.97 examples/s]
Generating train split: 109862780 examples [2:01:38, 5174.91 examples/s]
Generating train split: 109864595 examples [2:01:38, 7583.51 examples/s]
Generating train split: 109865628 examples [2:01:39, 6945.27 examples/s]
Generating train split: 109866523 examples [2:01:39, 5935.85 examples/s]
Generating train split: 109867469 examples [2:01:39, 6593.93 examples/s]
Generating train split: 109869475 examples [2:01:39, 9460.87 examples/s]
Generating train split: 109876684 examples [2:01:39, 24075.22 examples/s]
Generating train split: 109885067 examples [2:01:39, 38611.46 examples/s]
Generating train split: 109889568 examples [2:01:40, 20062.31 examples/s]
Generating train split: 109892996 examples [2:01:40, 13668.28 examples/s]
Generating train split: 109895609 examples [2:01:40, 13977.26 examples/s]
Generating train split: 109897899 examples [2:01:41, 11076.19 examples/s]
Generating train split: 109899682 examples [2:01:41, 8726.63 examples/s] 
Generating train split: 109901068 examples [2:01:41, 9104.36 examples/s]
Generating train split: 109903993 examples [2:01:41, 11900.22 examples/s]
Generating train split: 109911610 examples [2:01:41, 22534.68 examples/s]
Generating train split: 109918465 examples [2:01:42, 31328.09 examples/s]
Generating train split: 109922999 examples [2:01:42, 23237.35 examples/s]
Generating train split: 109930730 examples [2:01:42, 32525.54 examples/s]
Generating train split: 109939456 examples [2:01:42, 43306.60 examples/s]
Generating train split: 109945470 examples [2:01:43, 25643.10 examples/s]
Generating train split: 109950063 examples [2:01:43, 16559.73 examples/s]
Generating train split: 109953502 examples [2:01:43, 16969.05 examples/s]
Generating train split: 109962455 examples [2:01:43, 25957.94 examples/s]
Generating train split: 109971683 examples [2:01:44, 35929.94 examples/s]
Generating train split: 109977789 examples [2:01:44, 28164.37 examples/s]
Generating train split: 109982601 examples [2:01:44, 25063.73 examples/s]
Generating train split: 109990685 examples [2:01:44, 33252.29 examples/s]
Generating train split: 110000214 examples [2:01:44, 44004.89 examples/s]
Generating train split: 110006691 examples [2:01:45, 26226.86 examples/s]
Generating train split: 110011599 examples [2:01:45, 19279.88 examples/s]
Generating train split: 110015340 examples [2:01:46, 19478.93 examples/s]
Generating train split: 110018570 examples [2:01:46, 15451.43 examples/s]
Generating train split: 110021081 examples [2:01:46, 12894.64 examples/s]
Generating train split: 110023372 examples [2:01:46, 13989.91 examples/s]
Generating train split: 110025423 examples [2:01:47, 12881.21 examples/s]
Generating train split: 110027155 examples [2:01:47, 11831.11 examples/s]
Generating train split: 110028641 examples [2:01:47, 11425.14 examples/s]
Generating train split: 110037207 examples [2:01:47, 24161.68 examples/s]
Generating train split: 110046864 examples [2:01:47, 38411.85 examples/s]
Generating train split: 110052210 examples [2:01:47, 29018.50 examples/s]
Generating train split: 110056490 examples [2:01:48, 15392.91 examples/s]
Generating train split: 110059674 examples [2:01:49, 12815.89 examples/s]
Generating train split: 110062135 examples [2:01:49, 13323.41 examples/s]
Generating train split: 110064353 examples [2:01:49, 10491.39 examples/s]
Generating train split: 110066553 examples [2:01:49, 11800.63 examples/s]
Generating train split: 110068404 examples [2:01:49, 12518.53 examples/s]
Generating train split: 110070202 examples [2:01:50, 9948.34 examples/s] 
Generating train split: 110072091 examples [2:01:50, 11223.89 examples/s]
Generating train split: 110073643 examples [2:01:50, 11236.12 examples/s]
Generating train split: 110075080 examples [2:01:50, 8338.44 examples/s] 
Generating train split: 110076278 examples [2:01:50, 8908.97 examples/s]
Generating train split: 110077424 examples [2:01:50, 8710.58 examples/s]
Generating train split: 110079253 examples [2:01:51, 10585.15 examples/s]
Generating train split: 110080863 examples [2:01:51, 11783.01 examples/s]
Generating train split: 110082238 examples [2:01:51, 11685.84 examples/s]
Generating train split: 110083760 examples [2:01:51, 12547.96 examples/s]
Generating train split: 110085129 examples [2:01:51, 10979.27 examples/s]
Generating train split: 110086345 examples [2:01:51, 9168.90 examples/s] 
Generating train split: 110088481 examples [2:01:51, 11822.43 examples/s]
Generating train split: 110089845 examples [2:01:52, 9303.78 examples/s] 
Generating train split: 110090973 examples [2:01:52, 8536.33 examples/s]
Generating train split: 110091978 examples [2:01:52, 8256.34 examples/s]
Generating train split: 110092898 examples [2:01:52, 6987.54 examples/s]
Generating train split: 110093775 examples [2:01:52, 7323.48 examples/s]
Generating train split: 110094593 examples [2:01:52, 6366.62 examples/s]
Generating train split: 110096829 examples [2:01:52, 9769.85 examples/s]
Generating train split: 110097990 examples [2:01:53, 10106.20 examples/s]
Generating train split: 110099148 examples [2:01:53, 8214.00 examples/s] 
Generating train split: 110106901 examples [2:01:53, 23293.26 examples/s]
Generating train split: 110116555 examples [2:01:53, 40655.68 examples/s]
Generating train split: 110121556 examples [2:01:53, 27421.03 examples/s]
Generating train split: 110125526 examples [2:01:54, 13871.49 examples/s]
Generating train split: 110128467 examples [2:01:54, 13346.51 examples/s]
Generating train split: 110130885 examples [2:01:55, 10456.40 examples/s]
Generating train split: 110132745 examples [2:01:55, 10003.54 examples/s]
Generating train split: 110140458 examples [2:01:55, 18085.88 examples/s]
Generating train split: 110147526 examples [2:01:55, 25768.92 examples/s]
Generating train split: 110152005 examples [2:01:55, 23003.21 examples/s]
Generating train split: 110155675 examples [2:01:56, 17137.34 examples/s]
Generating train split: 110158526 examples [2:01:56, 12066.34 examples/s]
Generating train split: 110160697 examples [2:01:56, 11520.95 examples/s]
Generating train split: 110162504 examples [2:01:57, 8036.47 examples/s] 
Generating train split: 110163873 examples [2:01:57, 7091.20 examples/s]
Generating train split: 110164974 examples [2:01:58, 6683.33 examples/s]
Generating train split: 110165901 examples [2:01:58, 6108.31 examples/s]
Generating train split: 110166680 examples [2:01:58, 4958.12 examples/s]
Generating train split: 110167895 examples [2:01:58, 5874.47 examples/s]
Generating train split: 110168697 examples [2:01:59, 4354.64 examples/s]
Generating train split: 110169816 examples [2:01:59, 5268.18 examples/s]
Generating train split: 110170585 examples [2:01:59, 4216.81 examples/s]
Generating train split: 110171205 examples [2:01:59, 4248.85 examples/s]
Generating train split: 110173642 examples [2:01:59, 7550.20 examples/s]
Generating train split: 110176417 examples [2:01:59, 11386.39 examples/s]
Generating train split: 110178034 examples [2:02:00, 8384.70 examples/s] 
Generating train split: 110179348 examples [2:02:00, 9147.21 examples/s]
Generating train split: 110180636 examples [2:02:00, 6739.28 examples/s]
Generating train split: 110181657 examples [2:02:00, 7042.24 examples/s]
Generating train split: 110183536 examples [2:02:00, 9160.94 examples/s]
Generating train split: 110186389 examples [2:02:00, 12989.69 examples/s]
Generating train split: 110190629 examples [2:02:00, 19590.92 examples/s]
Generating train split: 110195523 examples [2:02:01, 26713.65 examples/s]
Generating train split: 110201626 examples [2:02:01, 35508.25 examples/s]
Generating train split: 110205797 examples [2:02:01, 36896.76 examples/s]
Generating train split: 110210399 examples [2:02:01, 39409.45 examples/s]
Generating train split: 110215911 examples [2:02:01, 43828.52 examples/s]
Generating train split: 110222396 examples [2:02:01, 49856.12 examples/s]
Generating train split: 110227863 examples [2:02:01, 51251.96 examples/s]
Generating train split: 110233251 examples [2:02:01, 51915.22 examples/s]
Generating train split: 110240039 examples [2:02:01, 56608.40 examples/s]
Generating train split: 110246569 examples [2:02:01, 59184.49 examples/s]
Generating train split: 110253371 examples [2:02:02, 61811.16 examples/s]
Generating train split: 110259593 examples [2:02:02, 61482.66 examples/s]
Generating train split: 110265879 examples [2:02:02, 61833.99 examples/s]
Generating train split: 110272095 examples [2:02:02, 61555.03 examples/s]
Generating train split: 110278386 examples [2:02:02, 61834.88 examples/s]
Generating train split: 110284954 examples [2:02:02, 62947.31 examples/s]
Generating train split: 110291263 examples [2:02:02, 58887.17 examples/s]
Generating train split: 110297222 examples [2:02:02, 55610.47 examples/s]
Generating train split: 110304499 examples [2:02:02, 60326.56 examples/s]
Generating train split: 110311496 examples [2:02:03, 63042.19 examples/s]
Generating train split: 110319215 examples [2:02:03, 67104.36 examples/s]
Generating train split: 110326000 examples [2:02:03, 65614.49 examples/s]
Generating train split: 110332620 examples [2:02:03, 65543.45 examples/s]
Generating train split: 110339219 examples [2:02:03, 64675.52 examples/s]
Generating train split: 110345731 examples [2:02:03, 62881.28 examples/s]
Generating train split: 110352332 examples [2:02:03, 63704.63 examples/s]
Generating train split: 110358724 examples [2:02:03, 62640.30 examples/s]
Generating train split: 110365009 examples [2:02:03, 52365.75 examples/s]
Generating train split: 110370537 examples [2:02:04, 38247.06 examples/s]
Generating train split: 110375065 examples [2:02:04, 27908.96 examples/s]
Generating train split: 110378681 examples [2:02:04, 25487.05 examples/s]
Generating train split: 110382021 examples [2:02:04, 26882.87 examples/s]
Generating train split: 110385208 examples [2:02:05, 18388.19 examples/s]
Generating train split: 110387710 examples [2:02:05, 16831.92 examples/s]
Generating train split: 110389898 examples [2:02:05, 17662.29 examples/s]
Generating train split: 110392061 examples [2:02:05, 15706.13 examples/s]
Generating train split: 110393904 examples [2:02:05, 11019.07 examples/s]
Generating train split: 110395356 examples [2:02:06, 8418.18 examples/s] 
Generating train split: 110396508 examples [2:02:06, 7894.25 examples/s]
Generating train split: 110401067 examples [2:02:06, 13550.74 examples/s]
Generating train split: 110410192 examples [2:02:06, 27267.10 examples/s]
Generating train split: 110417161 examples [2:02:06, 35766.28 examples/s]
Generating train split: 110422172 examples [2:02:07, 13023.98 examples/s]
Generating train split: 110425827 examples [2:02:08, 9619.96 examples/s] 
Generating train split: 110428550 examples [2:02:08, 9727.11 examples/s]
Generating train split: 110430766 examples [2:02:08, 10304.40 examples/s]
Generating train split: 110432740 examples [2:02:09, 10737.86 examples/s]
Generating train split: 110434683 examples [2:02:09, 11456.86 examples/s]
Generating train split: 110436381 examples [2:02:09, 8386.05 examples/s] 
Generating train split: 110438025 examples [2:02:09, 9418.18 examples/s]
Generating train split: 110439435 examples [2:02:09, 8553.42 examples/s]
Generating train split: 110440622 examples [2:02:10, 8425.02 examples/s]
Generating train split: 110441768 examples [2:02:10, 8899.50 examples/s]
Generating train split: 110442851 examples [2:02:10, 8387.73 examples/s]
Generating train split: 110444403 examples [2:02:10, 9820.92 examples/s]
Generating train split: 110445550 examples [2:02:10, 6572.88 examples/s]
Generating train split: 110446500 examples [2:02:10, 7046.12 examples/s]
Generating train split: 110448677 examples [2:02:10, 9906.42 examples/s]
Generating train split: 110449971 examples [2:02:11, 8698.35 examples/s]
Generating train split: 110453213 examples [2:02:11, 13542.08 examples/s]
Generating train split: 110454953 examples [2:02:11, 13453.78 examples/s]
Generating train split: 110456930 examples [2:02:11, 14914.71 examples/s]
Generating train split: 110459135 examples [2:02:11, 16678.67 examples/s]
Generating train split: 110461000 examples [2:02:11, 10512.62 examples/s]
Generating train split: 110462485 examples [2:02:12, 11026.15 examples/s]
Generating train split: 110470763 examples [2:02:12, 25783.78 examples/s]
Generating train split: 110480314 examples [2:02:12, 41612.58 examples/s]
Generating train split: 110485619 examples [2:02:12, 24905.10 examples/s]
Generating train split: 110494711 examples [2:02:12, 35727.84 examples/s]
Generating train split: 110501908 examples [2:02:12, 42604.30 examples/s]
Generating train split: 110507976 examples [2:02:13, 33509.28 examples/s]
Generating train split: 110512883 examples [2:02:13, 15598.64 examples/s]
Generating train split: 110516487 examples [2:02:14, 11677.43 examples/s]
Generating train split: 110519187 examples [2:02:15, 9508.77 examples/s] 
Generating train split: 110521239 examples [2:02:15, 9546.02 examples/s]
Generating train split: 110522975 examples [2:02:15, 8555.43 examples/s]
Generating train split: 110524848 examples [2:02:15, 9598.48 examples/s]
Generating train split: 110526372 examples [2:02:16, 8728.99 examples/s]
Generating train split: 110527628 examples [2:02:16, 6493.06 examples/s]
Generating train split: 110529726 examples [2:02:16, 8216.43 examples/s]
Generating train split: 110531254 examples [2:02:16, 9130.77 examples/s]
Generating train split: 110532592 examples [2:02:16, 9780.05 examples/s]
Generating train split: 110534063 examples [2:02:16, 10731.51 examples/s]
Generating train split: 110535429 examples [2:02:17, 8621.54 examples/s] 
Generating train split: 110536550 examples [2:02:17, 8700.64 examples/s]
Generating train split: 110538679 examples [2:02:17, 11292.80 examples/s]
Generating train split: 110540067 examples [2:02:17, 7804.57 examples/s] 
Generating train split: 110541599 examples [2:02:17, 9110.61 examples/s]
Generating train split: 110542819 examples [2:02:17, 8162.73 examples/s]
Generating train split: 110543865 examples [2:02:18, 6384.90 examples/s]
Generating train split: 110546063 examples [2:02:18, 9036.54 examples/s]
Generating train split: 110547310 examples [2:02:18, 9615.87 examples/s]
Generating train split: 110548542 examples [2:02:18, 6390.09 examples/s]
Generating train split: 110550207 examples [2:02:18, 8056.75 examples/s]
Generating train split: 110551380 examples [2:02:19, 7308.63 examples/s]
Generating train split: 110553336 examples [2:02:19, 9520.24 examples/s]
Generating train split: 110554609 examples [2:02:19, 8791.15 examples/s]
Generating train split: 110555729 examples [2:02:19, 9190.87 examples/s]
Generating train split: 110556833 examples [2:02:19, 6783.66 examples/s]
Generating train split: 110559830 examples [2:02:19, 11046.61 examples/s]
Generating train split: 110561357 examples [2:02:20, 10903.26 examples/s]
Generating train split: 110562737 examples [2:02:20, 10046.71 examples/s]
Generating train split: 110569250 examples [2:02:20, 21625.90 examples/s]
Generating train split: 110577170 examples [2:02:20, 34919.45 examples/s]
Generating train split: 110581507 examples [2:02:20, 28973.18 examples/s]
Generating train split: 110585157 examples [2:02:21, 14365.80 examples/s]
Generating train split: 110587890 examples [2:02:21, 15264.60 examples/s]
Generating train split: 110590406 examples [2:02:21, 10616.64 examples/s]
Generating train split: 110592312 examples [2:02:22, 8804.33 examples/s] 
Generating train split: 110593916 examples [2:02:22, 9501.81 examples/s]
Generating train split: 110595397 examples [2:02:22, 6304.30 examples/s]
Generating train split: 110596599 examples [2:02:22, 6894.02 examples/s]
Generating train split: 110597746 examples [2:02:23, 6248.63 examples/s]
Generating train split: 110599709 examples [2:02:23, 8078.05 examples/s]
Generating train split: 110600947 examples [2:02:23, 8657.88 examples/s]
Generating train split: 110602163 examples [2:02:23, 7129.42 examples/s]
Generating train split: 110605751 examples [2:02:23, 12012.34 examples/s]
Generating train split: 110608539 examples [2:02:23, 15099.89 examples/s]
Generating train split: 110610611 examples [2:02:24, 10397.10 examples/s]
Generating train split: 110613269 examples [2:02:24, 13071.45 examples/s]
Generating train split: 110615207 examples [2:02:24, 10127.87 examples/s]
Generating train split: 110616743 examples [2:02:24, 9975.98 examples/s] 
Generating train split: 110624677 examples [2:02:24, 22043.67 examples/s]
Generating train split: 110632411 examples [2:02:25, 33034.53 examples/s]
Generating train split: 110637061 examples [2:02:25, 19209.85 examples/s]
Generating train split: 110640615 examples [2:02:25, 18817.37 examples/s]
Generating train split: 110643632 examples [2:02:26, 15669.74 examples/s]
Generating train split: 110646048 examples [2:02:26, 10580.82 examples/s]
Generating train split: 110647876 examples [2:02:26, 9817.57 examples/s] 
Generating train split: 110649377 examples [2:02:27, 8669.43 examples/s]
Generating train split: 110650604 examples [2:02:27, 9109.65 examples/s]
Generating train split: 110651820 examples [2:02:27, 6887.70 examples/s]
Generating train split: 110653314 examples [2:02:27, 7919.72 examples/s]
Generating train split: 110654406 examples [2:02:27, 6336.15 examples/s]
Generating train split: 110656167 examples [2:02:28, 7996.99 examples/s]
Generating train split: 110657623 examples [2:02:28, 9126.62 examples/s]
Generating train split: 110659580 examples [2:02:28, 11131.75 examples/s]
Generating train split: 110661008 examples [2:02:28, 9053.96 examples/s] 
Generating train split: 110662193 examples [2:02:28, 9533.62 examples/s]
Generating train split: 110663387 examples [2:02:28, 10045.55 examples/s]
Generating train split: 110665003 examples [2:02:28, 11471.12 examples/s]
Generating train split: 110666321 examples [2:02:29, 9097.06 examples/s] 
Generating train split: 110667786 examples [2:02:29, 10287.75 examples/s]
Generating train split: 110668990 examples [2:02:29, 9778.53 examples/s] 
Generating train split: 110671252 examples [2:02:29, 12795.17 examples/s]
Generating train split: 110672706 examples [2:02:29, 6261.36 examples/s] 
Generating train split: 110673807 examples [2:02:30, 5814.51 examples/s]
Generating train split: 110674721 examples [2:02:30, 4869.15 examples/s]
Generating train split: 110675453 examples [2:02:30, 4204.79 examples/s]
Generating train split: 110676722 examples [2:02:30, 5366.09 examples/s]
Generating train split: 110677506 examples [2:02:31, 4691.01 examples/s]
Generating train split: 110678161 examples [2:02:31, 3836.89 examples/s]
Generating train split: 110683620 examples [2:02:31, 11459.85 examples/s]
Generating train split: 110692090 examples [2:02:31, 24394.91 examples/s]
Generating train split: 110696030 examples [2:02:31, 24913.08 examples/s]
Generating train split: 110699585 examples [2:02:31, 19635.50 examples/s]
Generating train split: 110702450 examples [2:02:32, 16070.13 examples/s]
Generating train split: 110704763 examples [2:02:32, 11211.12 examples/s]
Generating train split: 110706543 examples [2:02:32, 10921.87 examples/s]
Generating train split: 110708088 examples [2:02:33, 8363.42 examples/s] 
Generating train split: 110709300 examples [2:02:33, 7940.82 examples/s]
Generating train split: 110710346 examples [2:02:33, 6694.15 examples/s]
Generating train split: 110711338 examples [2:02:33, 7135.73 examples/s]
Generating train split: 110712222 examples [2:02:33, 6840.74 examples/s]
Generating train split: 110713019 examples [2:02:34, 4882.80 examples/s]
Generating train split: 110714084 examples [2:02:34, 5754.47 examples/s]
Generating train split: 110714846 examples [2:02:34, 5358.04 examples/s]
Generating train split: 110715513 examples [2:02:34, 5071.21 examples/s]
Generating train split: 110716112 examples [2:02:34, 4267.12 examples/s]
Generating train split: 110716610 examples [2:02:35, 3552.15 examples/s]
Generating train split: 110717023 examples [2:02:35, 3102.99 examples/s]
Generating train split: 110717379 examples [2:02:35, 2881.99 examples/s]
Generating train split: 110717696 examples [2:02:35, 2914.04 examples/s]
Generating train split: 110718342 examples [2:02:35, 3642.73 examples/s]
Generating train split: 110718760 examples [2:02:35, 3740.52 examples/s]
Generating train split: 110719693 examples [2:02:35, 5103.70 examples/s]
Generating train split: 110720261 examples [2:02:36, 4843.72 examples/s]
Generating train split: 110720795 examples [2:02:36, 4617.64 examples/s]
Generating train split: 110722590 examples [2:02:36, 7978.36 examples/s]
Generating train split: 110723821 examples [2:02:36, 9049.03 examples/s]
Generating train split: 110724797 examples [2:02:36, 7411.81 examples/s]
Generating train split: 110725635 examples [2:02:36, 7303.35 examples/s]
Generating train split: 110726438 examples [2:02:36, 5719.51 examples/s]
Generating train split: 110727105 examples [2:02:37, 4559.05 examples/s]
Generating train split: 110728102 examples [2:02:37, 5562.75 examples/s]
Generating train split: 110728782 examples [2:02:37, 4865.76 examples/s]
Generating train split: 110729405 examples [2:02:37, 5071.49 examples/s]
Generating train split: 110730037 examples [2:02:37, 5347.20 examples/s]
Generating train split: 110730826 examples [2:02:37, 5912.02 examples/s]
Generating train split: 110731483 examples [2:02:38, 4612.48 examples/s]
Generating train split: 110732613 examples [2:02:38, 6054.26 examples/s]
Generating train split: 110733339 examples [2:02:38, 5894.39 examples/s]
Generating train split: 110734630 examples [2:02:38, 7441.38 examples/s]
Generating train split: 110735462 examples [2:02:38, 5171.17 examples/s]
Generating train split: 110736136 examples [2:02:38, 4505.14 examples/s]
Generating train split: 110737481 examples [2:02:38, 6166.77 examples/s]
Generating train split: 110738613 examples [2:02:39, 7242.16 examples/s]
Generating train split: 110739514 examples [2:02:39, 6580.33 examples/s]
Generating train split: 110740299 examples [2:02:39, 6222.95 examples/s]
Generating train split: 110741020 examples [2:02:39, 5422.78 examples/s]
Generating train split: 110743479 examples [2:02:39, 9467.34 examples/s]
Generating train split: 110744652 examples [2:02:39, 8730.49 examples/s]
Generating train split: 110745687 examples [2:02:40, 7467.34 examples/s]
Generating train split: 110746576 examples [2:02:40, 7385.53 examples/s]
Generating train split: 110747412 examples [2:02:40, 5553.90 examples/s]
Generating train split: 110748096 examples [2:02:40, 5710.35 examples/s]
Generating train split: 110748761 examples [2:02:40, 5846.28 examples/s]
Generating train split: 110749747 examples [2:02:40, 6724.28 examples/s]
Generating train split: 110750496 examples [2:02:40, 6260.06 examples/s]
Generating train split: 110751708 examples [2:02:40, 7658.31 examples/s]
Generating train split: 110752551 examples [2:02:41, 5172.08 examples/s]
Generating train split: 110753226 examples [2:02:41, 5088.87 examples/s]
Generating train split: 110754494 examples [2:02:41, 6639.54 examples/s]
Generating train split: 110755407 examples [2:02:41, 7118.52 examples/s]
Generating train split: 110756242 examples [2:02:41, 5567.57 examples/s]
Generating train split: 110757199 examples [2:02:41, 6331.03 examples/s]
Generating train split: 110757960 examples [2:02:42, 4882.53 examples/s]
Generating train split: 110758584 examples [2:02:42, 4835.64 examples/s]
Generating train split: 110759161 examples [2:02:42, 4698.48 examples/s]
Generating train split: 110759694 examples [2:02:42, 4211.75 examples/s]
Generating train split: 110760160 examples [2:02:42, 4027.80 examples/s]
Generating train split: 110763606 examples [2:02:42, 10720.76 examples/s]
Generating train split: 110772138 examples [2:02:42, 28553.72 examples/s]
Generating train split: 110777446 examples [2:02:43, 34203.69 examples/s]
Generating train split: 110781385 examples [2:02:43, 19357.31 examples/s]
Generating train split: 110784433 examples [2:02:43, 15843.40 examples/s]
Generating train split: 110791840 examples [2:02:43, 24764.74 examples/s]
Generating train split: 110799868 examples [2:02:43, 34731.74 examples/s]
Generating train split: 110805026 examples [2:02:44, 27868.36 examples/s]
Generating train split: 110809190 examples [2:02:44, 15251.91 examples/s]
Generating train split: 110812289 examples [2:02:45, 13442.41 examples/s]
Generating train split: 110814749 examples [2:02:45, 11496.19 examples/s]
Generating train split: 110816676 examples [2:02:45, 11702.99 examples/s]
Generating train split: 110818489 examples [2:02:45, 12531.17 examples/s]
Generating train split: 110820245 examples [2:02:46, 12724.71 examples/s]
Generating train split: 110821881 examples [2:02:46, 11022.22 examples/s]
Generating train split: 110828554 examples [2:02:46, 20625.45 examples/s]
Generating train split: 110834322 examples [2:02:46, 27807.37 examples/s]
Generating train split: 110838079 examples [2:02:46, 23722.47 examples/s]
Generating train split: 110841230 examples [2:02:47, 12576.18 examples/s]
Generating train split: 110843590 examples [2:02:47, 10244.76 examples/s]
Generating train split: 110845432 examples [2:02:47, 9072.31 examples/s] 
Generating train split: 110846898 examples [2:02:48, 8560.73 examples/s]
Generating train split: 110848258 examples [2:02:48, 9204.37 examples/s]
Generating train split: 110849534 examples [2:02:48, 8043.10 examples/s]
Generating train split: 110850713 examples [2:02:48, 8548.04 examples/s]
Generating train split: 110851787 examples [2:02:48, 8807.10 examples/s]
Generating train split: 110852835 examples [2:02:49, 4972.49 examples/s]
Generating train split: 110853641 examples [2:02:49, 4773.37 examples/s]
Generating train split: 110854326 examples [2:02:49, 3891.68 examples/s]
Generating train split: 110856248 examples [2:02:49, 6007.48 examples/s]
Generating train split: 110858352 examples [2:02:49, 8477.28 examples/s]
Generating train split: 110859653 examples [2:02:50, 5938.85 examples/s]
Generating train split: 110860661 examples [2:02:50, 5822.66 examples/s]
Generating train split: 110861535 examples [2:02:50, 4942.62 examples/s]
Generating train split: 110862244 examples [2:02:50, 4825.86 examples/s]
Generating train split: 110863536 examples [2:02:51, 6120.40 examples/s]
Generating train split: 110864351 examples [2:02:51, 5638.71 examples/s]
Generating train split: 110865907 examples [2:02:51, 7495.71 examples/s]
Generating train split: 110866858 examples [2:02:51, 7333.64 examples/s]
Generating train split: 110868526 examples [2:02:51, 9360.28 examples/s]
Generating train split: 110869642 examples [2:02:51, 8668.40 examples/s]
Generating train split: 110871461 examples [2:02:51, 10870.39 examples/s]
Generating train split: 110872701 examples [2:02:51, 10562.68 examples/s]
Generating train split: 110873864 examples [2:02:52, 10357.88 examples/s]
Generating train split: 110874976 examples [2:02:52, 6958.04 examples/s] 
Generating train split: 110876163 examples [2:02:52, 7890.85 examples/s]
Generating train split: 110877136 examples [2:02:52, 6000.45 examples/s]
Generating train split: 110878247 examples [2:02:52, 6920.05 examples/s]
Generating train split: 110879301 examples [2:02:52, 7656.41 examples/s]
Generating train split: 110880790 examples [2:02:53, 9209.86 examples/s]
Generating train split: 110881885 examples [2:02:53, 7203.17 examples/s]
Generating train split: 110883410 examples [2:02:53, 8862.15 examples/s]
Generating train split: 110884498 examples [2:02:53, 8280.54 examples/s]
Generating train split: 110885473 examples [2:02:53, 7157.35 examples/s]
Generating train split: 110886598 examples [2:02:53, 8013.92 examples/s]
Generating train split: 110887726 examples [2:02:53, 8759.30 examples/s]
Generating train split: 110888835 examples [2:02:54, 9240.16 examples/s]
Generating train split: 110890655 examples [2:02:54, 11564.62 examples/s]
Generating train split: 110891907 examples [2:02:54, 11724.05 examples/s]
Generating train split: 110893148 examples [2:02:54, 8997.18 examples/s] 
Generating train split: 110894192 examples [2:02:54, 7362.37 examples/s]
Generating train split: 110901231 examples [2:02:54, 20337.16 examples/s]
Generating train split: 110910544 examples [2:02:54, 35712.53 examples/s]
Generating train split: 110914900 examples [2:02:55, 22964.59 examples/s]
Generating train split: 110918302 examples [2:02:56, 10856.74 examples/s]
Generating train split: 110920807 examples [2:02:56, 9041.34 examples/s] 
Generating train split: 110922721 examples [2:02:57, 6931.56 examples/s]
Generating train split: 110924161 examples [2:02:57, 5956.87 examples/s]
Generating train split: 110925274 examples [2:02:58, 4717.97 examples/s]
Generating train split: 110926119 examples [2:02:58, 4272.14 examples/s]
Generating train split: 110927470 examples [2:02:58, 5111.46 examples/s]
Generating train split: 110928336 examples [2:02:58, 5196.74 examples/s]
Generating train split: 110929502 examples [2:02:58, 6068.09 examples/s]
Generating train split: 110930393 examples [2:02:58, 5816.49 examples/s]
Generating train split: 110931170 examples [2:02:59, 6084.35 examples/s]
Generating train split: 110931935 examples [2:02:59, 4836.47 examples/s]
Generating train split: 110932568 examples [2:02:59, 4716.45 examples/s]
Generating train split: 110933142 examples [2:02:59, 3784.82 examples/s]
Generating train split: 110934155 examples [2:02:59, 4859.07 examples/s]
Generating train split: 110934787 examples [2:02:59, 4703.05 examples/s]
Generating train split: 110935918 examples [2:03:00, 6043.94 examples/s]
Generating train split: 110936652 examples [2:03:00, 5677.42 examples/s]
Generating train split: 110938553 examples [2:03:00, 8626.13 examples/s]
Generating train split: 110939584 examples [2:03:00, 8089.44 examples/s]
Generating train split: 110940877 examples [2:03:00, 9205.61 examples/s]
Generating train split: 110942033 examples [2:03:00, 9759.28 examples/s]
Generating train split: 110943106 examples [2:03:00, 9413.07 examples/s]
Generating train split: 110944119 examples [2:03:00, 9359.19 examples/s]
Generating train split: 110945103 examples [2:03:01, 8000.37 examples/s]
Generating train split: 110945969 examples [2:03:01, 5103.98 examples/s]
Generating train split: 110946651 examples [2:03:01, 5403.19 examples/s]
Generating train split: 110948027 examples [2:03:01, 7063.23 examples/s]
Generating train split: 110949040 examples [2:03:01, 7698.72 examples/s]
Generating train split: 110950017 examples [2:03:01, 8007.38 examples/s]
Generating train split: 110950927 examples [2:03:01, 7744.72 examples/s]
Generating train split: 110951870 examples [2:03:02, 8014.18 examples/s]
Generating train split: 110953037 examples [2:03:02, 8957.85 examples/s]
Generating train split: 110954142 examples [2:03:02, 9516.69 examples/s]
Generating train split: 110955141 examples [2:03:02, 7304.71 examples/s]
Generating train split: 110955982 examples [2:03:02, 5341.10 examples/s]
Generating train split: 110956663 examples [2:03:02, 5327.97 examples/s]
Generating train split: 110959224 examples [2:03:02, 9450.97 examples/s]
Generating train split: 110961531 examples [2:03:03, 12446.81 examples/s]
Generating train split: 110963047 examples [2:03:03, 8940.82 examples/s] 
Generating train split: 110964381 examples [2:03:03, 9665.29 examples/s]
Generating train split: 110965783 examples [2:03:03, 10543.43 examples/s]
Generating train split: 110967055 examples [2:03:03, 10723.86 examples/s]
Generating train split: 110968288 examples [2:03:03, 9615.86 examples/s] 
Generating train split: 110969385 examples [2:03:04, 9254.27 examples/s]
Generating train split: 110970495 examples [2:03:04, 9670.45 examples/s]
Generating train split: 110972679 examples [2:03:04, 12577.83 examples/s]
Generating train split: 110974039 examples [2:03:04, 11612.31 examples/s]
Generating train split: 110976222 examples [2:03:04, 14192.14 examples/s]
Generating train split: 110977754 examples [2:03:04, 11193.79 examples/s]
Generating train split: 110979038 examples [2:03:04, 9796.08 examples/s] 
Generating train split: 110986511 examples [2:03:04, 23755.72 examples/s]
Generating train split: 110994790 examples [2:03:05, 37619.02 examples/s]
Generating train split: 110999401 examples [2:03:05, 30169.78 examples/s]
Generating train split: 111003232 examples [2:03:05, 14475.82 examples/s]
Generating train split: 111006092 examples [2:03:06, 12403.04 examples/s]
Generating train split: 111008342 examples [2:03:06, 10296.82 examples/s]
Generating train split: 111010097 examples [2:03:07, 8092.39 examples/s] 
Generating train split: 111011447 examples [2:03:07, 7899.96 examples/s]
Generating train split: 111012603 examples [2:03:07, 7494.60 examples/s]
Generating train split: 111013599 examples [2:03:07, 7012.10 examples/s]
Generating train split: 111014460 examples [2:03:07, 7059.25 examples/s]
Generating train split: 111015604 examples [2:03:07, 7786.85 examples/s]
Generating train split: 111016518 examples [2:03:08, 7341.33 examples/s]
Generating train split: 111017397 examples [2:03:08, 7632.89 examples/s]
Generating train split: 111025536 examples [2:03:08, 24147.85 examples/s]
Generating train split: 111033688 examples [2:03:08, 36772.04 examples/s]
Generating train split: 111037956 examples [2:03:08, 21838.06 examples/s]
Generating train split: 111041269 examples [2:03:09, 17599.26 examples/s]
Generating train split: 111043915 examples [2:03:09, 13042.48 examples/s]
Generating train split: 111045960 examples [2:03:09, 12296.81 examples/s]
Generating train split: 111047694 examples [2:03:09, 10955.83 examples/s]
Generating train split: 111049134 examples [2:03:10, 10965.78 examples/s]
Generating train split: 111050533 examples [2:03:10, 11351.47 examples/s]
Generating train split: 111051869 examples [2:03:10, 8384.88 examples/s] 
Generating train split: 111054112 examples [2:03:10, 10639.70 examples/s]
Generating train split: 111060555 examples [2:03:10, 20727.74 examples/s]
Generating train split: 111068483 examples [2:03:10, 33102.05 examples/s]
Generating train split: 111072914 examples [2:03:10, 33636.76 examples/s]
Generating train split: 111077067 examples [2:03:11, 16925.31 examples/s]
Generating train split: 111080201 examples [2:03:12, 11021.76 examples/s]
Generating train split: 111082546 examples [2:03:12, 8518.11 examples/s] 
Generating train split: 111084325 examples [2:03:13, 5670.74 examples/s]
Generating train split: 111085644 examples [2:03:13, 5811.86 examples/s]
Generating train split: 111086773 examples [2:03:14, 4199.64 examples/s]
Generating train split: 111087613 examples [2:03:14, 3960.45 examples/s]
Generating train split: 111088290 examples [2:03:14, 3426.53 examples/s]
Generating train split: 111088819 examples [2:03:14, 3545.66 examples/s]
Generating train split: 111095841 examples [2:03:15, 11364.98 examples/s]
Generating train split: 111104915 examples [2:03:15, 22753.72 examples/s]
Generating train split: 111109364 examples [2:03:15, 17791.66 examples/s]
Generating train split: 111112823 examples [2:03:15, 14066.41 examples/s]
Generating train split: 111115497 examples [2:03:16, 13915.68 examples/s]
Generating train split: 111117770 examples [2:03:16, 11492.14 examples/s]
Generating train split: 111119573 examples [2:03:16, 12068.18 examples/s]
Generating train split: 111121295 examples [2:03:17, 8530.51 examples/s] 
Generating train split: 111122626 examples [2:03:17, 8686.76 examples/s]
Generating train split: 111123839 examples [2:03:17, 9142.12 examples/s]
Generating train split: 111125791 examples [2:03:17, 10924.98 examples/s]
Generating train split: 111127218 examples [2:03:17, 8367.94 examples/s] 
Generating train split: 111128362 examples [2:03:17, 7902.48 examples/s]
Generating train split: 111130375 examples [2:03:17, 10029.55 examples/s]
Generating train split: 111131671 examples [2:03:18, 9812.56 examples/s] 
Generating train split: 111132858 examples [2:03:18, 7781.93 examples/s]
Generating train split: 111133944 examples [2:03:18, 8351.60 examples/s]
Generating train split: 111135611 examples [2:03:18, 10069.34 examples/s]
Generating train split: 111136813 examples [2:03:18, 9219.18 examples/s] 
Generating train split: 111137883 examples [2:03:18, 6864.50 examples/s]
Generating train split: 111139477 examples [2:03:19, 8516.90 examples/s]
Generating train split: 111140546 examples [2:03:19, 8126.94 examples/s]
Generating train split: 111141512 examples [2:03:19, 5894.49 examples/s]
Generating train split: 111142391 examples [2:03:19, 6333.46 examples/s]
Generating train split: 111143184 examples [2:03:19, 6358.74 examples/s]
Generating train split: 111143929 examples [2:03:19, 5423.88 examples/s]
Generating train split: 111144567 examples [2:03:20, 5317.70 examples/s]
Generating train split: 111145171 examples [2:03:20, 4674.27 examples/s]
Generating train split: 111145741 examples [2:03:20, 4865.26 examples/s]
Generating train split: 111147421 examples [2:03:20, 7572.04 examples/s]
Generating train split: 111148752 examples [2:03:20, 8966.94 examples/s]
Generating train split: 111149768 examples [2:03:20, 6532.23 examples/s]
Generating train split: 111151927 examples [2:03:20, 9643.51 examples/s]
Generating train split: 111153153 examples [2:03:21, 9676.17 examples/s]
Generating train split: 111154308 examples [2:03:21, 6841.60 examples/s]
Generating train split: 111155635 examples [2:03:21, 8021.90 examples/s]
Generating train split: 111156674 examples [2:03:21, 5649.72 examples/s]
Generating train split: 111157789 examples [2:03:21, 6468.21 examples/s]
Generating train split: 111158905 examples [2:03:22, 7340.73 examples/s]
Generating train split: 111159855 examples [2:03:22, 7176.10 examples/s]
Generating train split: 111160728 examples [2:03:22, 5798.43 examples/s]
Generating train split: 111162178 examples [2:03:22, 7469.18 examples/s]
Generating train split: 111163111 examples [2:03:22, 4707.16 examples/s]
Generating train split: 111164735 examples [2:03:23, 6501.81 examples/s]
Generating train split: 111165731 examples [2:03:23, 6787.40 examples/s]
Generating train split: 111166660 examples [2:03:23, 4800.74 examples/s]
Generating train split: 111168851 examples [2:03:23, 7492.36 examples/s]
Generating train split: 111170306 examples [2:03:23, 8778.27 examples/s]
Generating train split: 111171563 examples [2:03:24, 6406.77 examples/s]
Generating train split: 111173214 examples [2:03:24, 7962.08 examples/s]
Generating train split: 111174986 examples [2:03:24, 9736.49 examples/s]
Generating train split: 111176300 examples [2:03:24, 8013.87 examples/s]
Generating train split: 111177385 examples [2:03:24, 8425.13 examples/s]
Generating train split: 111178460 examples [2:03:24, 8298.48 examples/s]
Generating train split: 111179445 examples [2:03:24, 8505.77 examples/s]
Generating train split: 111180408 examples [2:03:25, 7477.86 examples/s]
Generating train split: 111181378 examples [2:03:25, 7953.64 examples/s]
Generating train split: 111182256 examples [2:03:25, 7126.88 examples/s]
Generating train split: 111183042 examples [2:03:25, 5756.21 examples/s]
Generating train split: 111183698 examples [2:03:25, 5803.40 examples/s]
Generating train split: 111184336 examples [2:03:25, 5202.27 examples/s]
Generating train split: 111186174 examples [2:03:25, 8083.03 examples/s]
Generating train split: 111187377 examples [2:03:25, 8926.81 examples/s]
Generating train split: 111188386 examples [2:03:26, 8292.01 examples/s]
Generating train split: 111189308 examples [2:03:26, 7873.43 examples/s]
Generating train split: 111190159 examples [2:03:26, 5410.02 examples/s]
Generating train split: 111191002 examples [2:03:26, 5701.55 examples/s]
Generating train split: 111191683 examples [2:03:26, 4178.14 examples/s]
Generating train split: 111192395 examples [2:03:27, 4670.98 examples/s]
Generating train split: 111193374 examples [2:03:27, 5656.93 examples/s]
Generating train split: 111194493 examples [2:03:27, 6864.92 examples/s]
Generating train split: 111195325 examples [2:03:27, 5292.18 examples/s]
Generating train split: 111197121 examples [2:03:27, 7820.72 examples/s]
Generating train split: 111198134 examples [2:03:27, 6529.72 examples/s]
Generating train split: 111198994 examples [2:03:28, 6535.56 examples/s]
Generating train split: 111200088 examples [2:03:28, 7360.08 examples/s]
Generating train split: 111201467 examples [2:03:28, 8833.59 examples/s]
Generating train split: 111202987 examples [2:03:28, 10300.08 examples/s]
Generating train split: 111204136 examples [2:03:28, 6934.89 examples/s] 
Generating train split: 111205061 examples [2:03:28, 7122.59 examples/s]
Generating train split: 111205941 examples [2:03:28, 6137.47 examples/s]
Generating train split: 111206689 examples [2:03:29, 6134.75 examples/s]
Generating train split: 111207395 examples [2:03:29, 5414.27 examples/s]
Generating train split: 111208008 examples [2:03:29, 4545.37 examples/s]
Generating train split: 111208700 examples [2:03:29, 4908.02 examples/s]
Generating train split: 111209259 examples [2:03:29, 4693.88 examples/s]
Generating train split: 111210219 examples [2:03:29, 5775.46 examples/s]
Generating train split: 111210877 examples [2:03:29, 5795.45 examples/s]
Generating train split: 111211684 examples [2:03:30, 6357.28 examples/s]
Generating train split: 111212374 examples [2:03:30, 5542.32 examples/s]
Generating train split: 111213191 examples [2:03:30, 6041.21 examples/s]
Generating train split: 111213846 examples [2:03:30, 5933.06 examples/s]
Generating train split: 111214947 examples [2:03:30, 7242.04 examples/s]
Generating train split: 111215713 examples [2:03:30, 6802.09 examples/s]
Generating train split: 111216635 examples [2:03:30, 7421.00 examples/s]
Generating train split: 111217414 examples [2:03:30, 6612.99 examples/s]
Generating train split: 111218310 examples [2:03:30, 7138.38 examples/s]
Generating train split: 111219062 examples [2:03:31, 3496.83 examples/s]
Generating train split: 111220975 examples [2:03:31, 5874.05 examples/s]
Generating train split: 111221929 examples [2:03:31, 5776.80 examples/s]
Generating train split: 111222768 examples [2:03:32, 4702.35 examples/s]
Generating train split: 111223477 examples [2:03:32, 5094.44 examples/s]
Generating train split: 111224547 examples [2:03:32, 6162.86 examples/s]
Generating train split: 111227448 examples [2:03:32, 10864.96 examples/s]
Generating train split: 111228808 examples [2:03:32, 10981.66 examples/s]
Generating train split: 111230099 examples [2:03:32, 9610.20 examples/s] 
Generating train split: 111232769 examples [2:03:32, 13403.58 examples/s]
Generating train split: 111236699 examples [2:03:32, 19658.07 examples/s]
Generating train split: 111238985 examples [2:03:32, 20313.37 examples/s]
Generating train split: 111241253 examples [2:03:33, 20466.08 examples/s]
Generating train split: 111243464 examples [2:03:33, 13345.49 examples/s]
Generating train split: 111245233 examples [2:03:33, 14103.99 examples/s]
Generating train split: 111247231 examples [2:03:33, 15392.02 examples/s]
Generating train split: 111249055 examples [2:03:33, 11966.64 examples/s]
Generating train split: 111250557 examples [2:03:33, 11923.64 examples/s]
Generating train split: 111252587 examples [2:03:34, 13654.59 examples/s]
Generating train split: 111254176 examples [2:03:34, 14144.85 examples/s]
Generating train split: 111255759 examples [2:03:34, 9424.84 examples/s] 
Generating train split: 111259071 examples [2:03:34, 13871.67 examples/s]
Generating train split: 111267253 examples [2:03:34, 28238.08 examples/s]
Generating train split: 111272834 examples [2:03:34, 34634.63 examples/s]
Generating train split: 111277150 examples [2:03:35, 22451.60 examples/s]
Generating train split: 111280529 examples [2:03:35, 15072.37 examples/s]
Generating train split: 111283134 examples [2:03:35, 12116.80 examples/s]
Generating train split: 111285172 examples [2:03:36, 11156.02 examples/s]
Generating train split: 111286849 examples [2:03:36, 11679.01 examples/s]
Generating train split: 111288499 examples [2:03:36, 12417.93 examples/s]
Generating train split: 111290121 examples [2:03:36, 11461.92 examples/s]
Generating train split: 111297898 examples [2:03:36, 23707.94 examples/s]
Generating train split: 111306181 examples [2:03:36, 35414.21 examples/s]
Generating train split: 111310791 examples [2:03:37, 24973.17 examples/s]
Generating train split: 111314453 examples [2:03:37, 16262.48 examples/s]
Generating train split: 111317240 examples [2:03:37, 13014.16 examples/s]
Generating train split: 111319413 examples [2:03:38, 12408.45 examples/s]
Generating train split: 111321243 examples [2:03:38, 12618.27 examples/s]
Generating train split: 111323402 examples [2:03:38, 13989.33 examples/s]
Generating train split: 111331942 examples [2:03:38, 26792.59 examples/s]
Generating train split: 111340703 examples [2:03:38, 38386.74 examples/s]
Generating train split: 111345780 examples [2:03:39, 23938.76 examples/s]
Generating train split: 111349698 examples [2:03:39, 19267.16 examples/s]
Generating train split: 111352791 examples [2:03:39, 17580.37 examples/s]
Generating train split: 111355364 examples [2:03:39, 15866.53 examples/s]
Generating train split: 111362666 examples [2:03:39, 24341.03 examples/s]
Generating train split: 111370119 examples [2:03:40, 32660.43 examples/s]
Generating train split: 111374769 examples [2:03:40, 26828.94 examples/s]
Generating train split: 111378559 examples [2:03:40, 19028.54 examples/s]
Generating train split: 111387196 examples [2:03:40, 28640.11 examples/s]
Generating train split: 111394067 examples [2:03:40, 35421.95 examples/s]
Generating train split: 111399395 examples [2:03:41, 20467.39 examples/s]
Generating train split: 111403402 examples [2:03:41, 15583.51 examples/s]
Generating train split: 111406479 examples [2:03:42, 12490.61 examples/s]
Generating train split: 111408830 examples [2:03:42, 13247.00 examples/s]
Generating train split: 111411033 examples [2:03:42, 13175.69 examples/s]
Generating train split: 111412966 examples [2:03:42, 12348.17 examples/s]
Generating train split: 111414611 examples [2:03:43, 12381.63 examples/s]
Generating train split: 111417204 examples [2:03:43, 14681.19 examples/s]
Generating train split: 111419053 examples [2:03:43, 10703.28 examples/s]
Generating train split: 111420517 examples [2:03:43, 10703.72 examples/s]
Generating train split: 111422911 examples [2:03:43, 12879.55 examples/s]
Generating train split: 111424521 examples [2:03:43, 11129.10 examples/s]
Generating train split: 111426357 examples [2:03:44, 12497.16 examples/s]
Generating train split: 111427856 examples [2:03:44, 12529.21 examples/s]
Generating train split: 111429326 examples [2:03:44, 13002.20 examples/s]
Generating train split: 111430772 examples [2:03:44, 8157.87 examples/s] 
Generating train split: 111433013 examples [2:03:44, 10659.28 examples/s]
Generating train split: 111434474 examples [2:03:45, 7549.22 examples/s] 
Generating train split: 111435618 examples [2:03:45, 7711.61 examples/s]
Generating train split: 111437688 examples [2:03:45, 10005.56 examples/s]
Generating train split: 111439047 examples [2:03:45, 6534.15 examples/s] 
Generating train split: 111441057 examples [2:03:45, 8517.36 examples/s]
Generating train split: 111442375 examples [2:03:46, 6097.73 examples/s]
Generating train split: 111444279 examples [2:03:46, 7912.48 examples/s]
Generating train split: 111445570 examples [2:03:46, 6833.59 examples/s]
Generating train split: 111447025 examples [2:03:46, 8041.51 examples/s]
Generating train split: 111454601 examples [2:03:46, 20448.20 examples/s]
Generating train split: 111463753 examples [2:03:46, 35184.28 examples/s]
Generating train split: 111468661 examples [2:03:47, 30721.37 examples/s]
Generating train split: 111472809 examples [2:03:47, 12555.02 examples/s]
Generating train split: 111479976 examples [2:03:48, 18546.69 examples/s]
Generating train split: 111488285 examples [2:03:48, 26710.24 examples/s]
Generating train split: 111493772 examples [2:03:48, 16741.33 examples/s]
Generating train split: 111497873 examples [2:03:49, 12731.33 examples/s]
Generating train split: 111500950 examples [2:03:50, 9794.91 examples/s] 
Generating train split: 111503259 examples [2:03:50, 8068.08 examples/s]
Generating train split: 111505003 examples [2:03:51, 6897.60 examples/s]
Generating train split: 111506347 examples [2:03:51, 6933.72 examples/s]
Generating train split: 111507497 examples [2:03:51, 7303.47 examples/s]
Generating train split: 111508614 examples [2:03:51, 6369.50 examples/s]
Generating train split: 111509527 examples [2:03:51, 5916.57 examples/s]
Generating train split: 111511747 examples [2:03:51, 8121.67 examples/s]
Generating train split: 111514553 examples [2:03:51, 11315.62 examples/s]
Generating train split: 111516229 examples [2:03:52, 12180.69 examples/s]
Generating train split: 111518277 examples [2:03:52, 13908.92 examples/s]
Generating train split: 111520040 examples [2:03:52, 12200.41 examples/s]
Generating train split: 111521556 examples [2:03:52, 12284.18 examples/s]
Generating train split: 111522987 examples [2:03:52, 7774.13 examples/s] 
Generating train split: 111524108 examples [2:03:53, 7608.54 examples/s]
Generating train split: 111525113 examples [2:03:53, 7438.76 examples/s]
Generating train split: 111526056 examples [2:03:53, 7717.98 examples/s]
Generating train split: 111526956 examples [2:03:53, 7063.57 examples/s]
Generating train split: 111528224 examples [2:03:53, 8241.84 examples/s]
Generating train split: 111530015 examples [2:03:53, 10466.21 examples/s]
Generating train split: 111531216 examples [2:03:53, 9614.15 examples/s] 
Generating train split: 111532441 examples [2:03:53, 10192.03 examples/s]
Generating train split: 111533552 examples [2:03:54, 8988.92 examples/s] 
Generating train split: 111535118 examples [2:03:54, 10571.18 examples/s]
Generating train split: 111536278 examples [2:03:54, 7702.13 examples/s] 
Generating train split: 111537980 examples [2:03:54, 9579.71 examples/s]
Generating train split: 111539153 examples [2:03:54, 9820.47 examples/s]
Generating train split: 111540296 examples [2:03:54, 8632.18 examples/s]
Generating train split: 111541293 examples [2:03:54, 8352.08 examples/s]
Generating train split: 111542221 examples [2:03:55, 8340.96 examples/s]
Generating train split: 111543116 examples [2:03:55, 7540.71 examples/s]
Generating train split: 111543925 examples [2:03:55, 6629.53 examples/s]
Generating train split: 111544716 examples [2:03:55, 6847.88 examples/s]
Generating train split: 111545439 examples [2:03:55, 6792.68 examples/s]
Generating train split: 111546148 examples [2:03:55, 6279.92 examples/s]
Generating train split: 111547157 examples [2:03:55, 6615.78 examples/s]
Generating train split: 111547835 examples [2:03:56, 5939.12 examples/s]
Generating train split: 111548452 examples [2:03:56, 5502.14 examples/s]
Generating train split: 111550547 examples [2:03:56, 9174.79 examples/s]
Generating train split: 111551569 examples [2:03:56, 8139.92 examples/s]
Generating train split: 111553032 examples [2:03:56, 9660.03 examples/s]
Generating train split: 111554118 examples [2:03:56, 8224.43 examples/s]
Generating train split: 111555052 examples [2:03:56, 6467.63 examples/s]
Generating train split: 111555818 examples [2:03:57, 6351.43 examples/s]
Generating train split: 111556538 examples [2:03:57, 4865.97 examples/s]
Generating train split: 111559216 examples [2:03:57, 8909.28 examples/s]
Generating train split: 111560615 examples [2:03:57, 9967.29 examples/s]
Generating train split: 111562260 examples [2:03:57, 11450.34 examples/s]
Generating train split: 111564936 examples [2:03:57, 15219.37 examples/s]
Generating train split: 111566706 examples [2:03:57, 13877.37 examples/s]
Generating train split: 111568287 examples [2:03:58, 9757.58 examples/s] 
Generating train split: 111569721 examples [2:03:58, 10567.44 examples/s]
Generating train split: 111571043 examples [2:03:58, 9412.13 examples/s] 
Generating train split: 111572173 examples [2:03:58, 8885.61 examples/s]
Generating train split: 111573666 examples [2:03:58, 10153.84 examples/s]
Generating train split: 111574832 examples [2:03:58, 8599.45 examples/s] 
Generating train split: 111576100 examples [2:03:59, 9464.57 examples/s]
Generating train split: 111577503 examples [2:03:59, 10519.89 examples/s]
Generating train split: 111579044 examples [2:03:59, 11739.72 examples/s]
Generating train split: 111580359 examples [2:03:59, 12104.99 examples/s]
Generating train split: 111581659 examples [2:03:59, 9172.26 examples/s] 
Generating train split: 111582744 examples [2:03:59, 8314.81 examples/s]
Generating train split: 111584349 examples [2:03:59, 10002.57 examples/s]
Generating train split: 111585504 examples [2:04:00, 7796.96 examples/s] 
Generating train split: 111586888 examples [2:04:00, 9025.52 examples/s]
Generating train split: 111587974 examples [2:04:00, 7804.07 examples/s]
Generating train split: 111589613 examples [2:04:00, 9561.87 examples/s]
Generating train split: 111591232 examples [2:04:00, 11028.34 examples/s]
Generating train split: 111593403 examples [2:04:00, 13579.70 examples/s]
Generating train split: 111594966 examples [2:04:00, 14091.82 examples/s]
Generating train split: 111596978 examples [2:04:00, 15454.43 examples/s]
Generating train split: 111598619 examples [2:04:01, 12584.46 examples/s]
Generating train split: 111600073 examples [2:04:01, 12946.50 examples/s]
Generating train split: 111601479 examples [2:04:01, 10219.86 examples/s]
Generating train split: 111602664 examples [2:04:01, 9605.40 examples/s] 
Generating train split: 111604223 examples [2:04:01, 10909.58 examples/s]
Generating train split: 111605438 examples [2:04:01, 8501.64 examples/s] 
Generating train split: 111606455 examples [2:04:02, 6688.61 examples/s]
Generating train split: 111613511 examples [2:04:02, 18315.64 examples/s]
Generating train split: 111621577 examples [2:04:02, 31183.13 examples/s]
Generating train split: 111625883 examples [2:04:02, 31683.49 examples/s]
Generating train split: 111629893 examples [2:04:02, 21397.99 examples/s]
Generating train split: 111633052 examples [2:04:03, 13225.51 examples/s]
Generating train split: 111635444 examples [2:04:03, 13968.38 examples/s]
Generating train split: 111637656 examples [2:04:03, 13111.83 examples/s]
Generating train split: 111639631 examples [2:04:03, 14115.84 examples/s]
Generating train split: 111641527 examples [2:04:03, 14824.31 examples/s]
Generating train split: 111643393 examples [2:04:04, 13379.38 examples/s]
Generating train split: 111645008 examples [2:04:04, 10702.45 examples/s]
Generating train split: 111646338 examples [2:04:04, 10569.73 examples/s]
Generating train split: 111648912 examples [2:04:04, 13463.32 examples/s]
Generating train split: 111650530 examples [2:04:04, 10871.32 examples/s]
Generating train split: 111651869 examples [2:04:04, 9936.68 examples/s] 
Generating train split: 111655308 examples [2:04:05, 14683.91 examples/s]
Generating train split: 111657163 examples [2:04:05, 10258.63 examples/s]
Generating train split: 111658626 examples [2:04:05, 9727.59 examples/s] 
Generating train split: 111659899 examples [2:04:05, 10241.63 examples/s]
Generating train split: 111661435 examples [2:04:05, 11268.42 examples/s]
Generating train split: 111662790 examples [2:04:05, 9874.94 examples/s] 
Generating train split: 111663953 examples [2:04:06, 10125.89 examples/s]
Generating train split: 111665388 examples [2:04:06, 11091.67 examples/s]
Generating train split: 111667601 examples [2:04:06, 13815.89 examples/s]
Generating train split: 111669136 examples [2:04:06, 12333.18 examples/s]
Generating train split: 111671053 examples [2:04:06, 13972.33 examples/s]
Generating train split: 111672580 examples [2:04:06, 12767.49 examples/s]
Generating train split: 111673959 examples [2:04:06, 9475.49 examples/s] 
Generating train split: 111675096 examples [2:04:07, 9042.75 examples/s]
Generating train split: 111677012 examples [2:04:07, 11180.88 examples/s]
Generating train split: 111678308 examples [2:04:07, 10695.12 examples/s]
Generating train split: 111679503 examples [2:04:07, 9481.81 examples/s] 
Generating train split: 111680561 examples [2:04:07, 7758.78 examples/s]
Generating train split: 111681448 examples [2:04:07, 7073.29 examples/s]
Generating train split: 111682242 examples [2:04:08, 5581.43 examples/s]
Generating train split: 111683086 examples [2:04:08, 5966.59 examples/s]
Generating train split: 111689799 examples [2:04:08, 18446.07 examples/s]
Generating train split: 111698515 examples [2:04:08, 33944.10 examples/s]
Generating train split: 111702869 examples [2:04:08, 32222.33 examples/s]
Generating train split: 111706782 examples [2:04:08, 20125.68 examples/s]
Generating train split: 111709819 examples [2:04:09, 18674.66 examples/s]
Generating train split: 111712411 examples [2:04:09, 13404.14 examples/s]
Generating train split: 111714420 examples [2:04:09, 13939.00 examples/s]
Generating train split: 111716328 examples [2:04:09, 13793.39 examples/s]
Generating train split: 111718066 examples [2:04:10, 11771.76 examples/s]
Generating train split: 111719518 examples [2:04:10, 11001.47 examples/s]
Generating train split: 111721162 examples [2:04:10, 11883.21 examples/s]
Generating train split: 111722525 examples [2:04:10, 11431.84 examples/s]
Generating train split: 111723900 examples [2:04:10, 11925.86 examples/s]
Generating train split: 111725195 examples [2:04:10, 12037.12 examples/s]
Generating train split: 111726499 examples [2:04:10, 12226.94 examples/s]
Generating train split: 111727777 examples [2:04:11, 7450.88 examples/s] 
Generating train split: 111728792 examples [2:04:11, 7547.24 examples/s]
Generating train split: 111729821 examples [2:04:11, 8086.57 examples/s]
Generating train split: 111731038 examples [2:04:11, 8990.66 examples/s]
Generating train split: 111732082 examples [2:04:11, 8958.96 examples/s]
Generating train split: 111733085 examples [2:04:11, 8524.01 examples/s]
Generating train split: 111734009 examples [2:04:11, 8016.00 examples/s]
Generating train split: 111735191 examples [2:04:11, 8940.90 examples/s]
Generating train split: 111736150 examples [2:04:12, 7983.26 examples/s]
Generating train split: 111737006 examples [2:04:12, 5855.47 examples/s]
Generating train split: 111737872 examples [2:04:12, 6419.58 examples/s]
Generating train split: 111738623 examples [2:04:12, 6024.99 examples/s]
Generating train split: 111740431 examples [2:04:12, 8723.76 examples/s]
Generating train split: 111741458 examples [2:04:12, 7340.37 examples/s]
Generating train split: 111742324 examples [2:04:12, 7386.30 examples/s]
Generating train split: 111743165 examples [2:04:13, 6932.58 examples/s]
Generating train split: 111744969 examples [2:04:13, 9478.78 examples/s]
Generating train split: 111746041 examples [2:04:13, 5694.43 examples/s]
Generating train split: 111747160 examples [2:04:13, 6618.37 examples/s]
Generating train split: 111748075 examples [2:04:13, 6418.07 examples/s]
Generating train split: 111749978 examples [2:04:13, 8901.61 examples/s]
Generating train split: 111751104 examples [2:04:14, 9418.88 examples/s]
Generating train split: 111752236 examples [2:04:14, 7346.16 examples/s]
Generating train split: 111753168 examples [2:04:14, 7034.63 examples/s]
Generating train split: 111758547 examples [2:04:14, 16807.52 examples/s]
Generating train split: 111767752 examples [2:04:14, 34101.50 examples/s]
Generating train split: 111772060 examples [2:04:14, 33541.73 examples/s]
Generating train split: 111776036 examples [2:04:15, 17205.63 examples/s]
Generating train split: 111779054 examples [2:04:15, 10376.12 examples/s]
Generating train split: 111781310 examples [2:04:16, 8069.66 examples/s] 
Generating train split: 111783896 examples [2:04:16, 9708.39 examples/s]
Generating train split: 111792336 examples [2:04:16, 18395.18 examples/s]
Generating train split: 111800751 examples [2:04:16, 27510.38 examples/s]
Generating train split: 111805855 examples [2:04:17, 16428.15 examples/s]
Generating train split: 111809671 examples [2:04:18, 12067.85 examples/s]
Generating train split: 111812528 examples [2:04:18, 12122.24 examples/s]
Generating train split: 111814902 examples [2:04:18, 10978.47 examples/s]
Generating train split: 111816798 examples [2:04:19, 8801.24 examples/s] 
Generating train split: 111818739 examples [2:04:19, 9893.12 examples/s]
Generating train split: 111820348 examples [2:04:19, 10057.18 examples/s]
Generating train split: 111821797 examples [2:04:19, 8045.97 examples/s] 
Generating train split: 111823011 examples [2:04:19, 8607.68 examples/s]
Generating train split: 111824669 examples [2:04:19, 9913.57 examples/s]
Generating train split: 111825990 examples [2:04:19, 9153.98 examples/s]
Generating train split: 111831628 examples [2:04:20, 18096.00 examples/s]
Generating train split: 111834096 examples [2:04:20, 19300.71 examples/s]
Generating train split: 111837025 examples [2:04:20, 21580.24 examples/s]
Generating train split: 111839598 examples [2:04:20, 20708.41 examples/s]
Generating train split: 111841968 examples [2:04:20, 16705.29 examples/s]
Generating train split: 111843957 examples [2:04:20, 14942.04 examples/s]
Generating train split: 111845687 examples [2:04:21, 10757.27 examples/s]
Generating train split: 111847070 examples [2:04:21, 11156.87 examples/s]
Generating train split: 111849748 examples [2:04:21, 14195.44 examples/s]
Generating train split: 111851501 examples [2:04:21, 12201.06 examples/s]
Generating train split: 111853098 examples [2:04:21, 12952.96 examples/s]
Generating train split: 111854626 examples [2:04:21, 12465.30 examples/s]
Generating train split: 111856031 examples [2:04:21, 12612.52 examples/s]
Generating train split: 111857402 examples [2:04:22, 11377.97 examples/s]
Generating train split: 111858638 examples [2:04:22, 8684.55 examples/s] 
Generating train split: 111860404 examples [2:04:22, 10431.90 examples/s]
Generating train split: 111861630 examples [2:04:22, 8286.75 examples/s] 
Generating train split: 111863419 examples [2:04:22, 10152.42 examples/s]
Generating train split: 111864663 examples [2:04:22, 10321.43 examples/s]
Generating train split: 111865866 examples [2:04:22, 10698.61 examples/s]
Generating train split: 111867063 examples [2:04:23, 9181.56 examples/s] 
Generating train split: 111875339 examples [2:04:23, 25971.34 examples/s]
Generating train split: 111883751 examples [2:04:23, 39567.17 examples/s]
Generating train split: 111888361 examples [2:04:23, 26919.50 examples/s]
Generating train split: 111892042 examples [2:04:23, 22195.02 examples/s]
Generating train split: 111900538 examples [2:04:23, 33183.83 examples/s]
Generating train split: 111907126 examples [2:04:24, 39715.24 examples/s]
Generating train split: 111912368 examples [2:04:24, 29721.06 examples/s]
Generating train split: 111916567 examples [2:04:24, 24852.37 examples/s]
Generating train split: 111919997 examples [2:04:24, 21888.74 examples/s]
Generating train split: 111922867 examples [2:04:25, 15918.99 examples/s]
Generating train split: 111925110 examples [2:04:25, 12751.56 examples/s]
Generating train split: 111927209 examples [2:04:25, 13839.33 examples/s]
Generating train split: 111929085 examples [2:04:25, 13971.06 examples/s]
Generating train split: 111930830 examples [2:04:25, 13361.05 examples/s]
Generating train split: 111932411 examples [2:04:26, 13522.78 examples/s]
Generating train split: 111933937 examples [2:04:26, 12727.72 examples/s]
Generating train split: 111939433 examples [2:04:26, 21794.25 examples/s]
Generating train split: 111947349 examples [2:04:26, 35259.85 examples/s]
Generating train split: 111952507 examples [2:04:26, 38487.07 examples/s]
Generating train split: 111956882 examples [2:04:26, 24763.62 examples/s]
Generating train split: 111960338 examples [2:04:27, 16147.73 examples/s]
Generating train split: 111967891 examples [2:04:27, 24444.28 examples/s]
Generating train split: 111976314 examples [2:04:27, 34391.29 examples/s]
Generating train split: 111981722 examples [2:04:28, 20486.90 examples/s]
Generating train split: 111989628 examples [2:04:28, 28004.26 examples/s]
Generating train split: 111998679 examples [2:04:28, 37688.21 examples/s]
Generating train split: 112005065 examples [2:04:28, 27521.92 examples/s]
Generating train split: 112010012 examples [2:04:28, 23195.76 examples/s]
Generating train split: 112013934 examples [2:04:29, 15839.82 examples/s]
Generating train split: 112016894 examples [2:04:29, 14425.77 examples/s]
Generating train split: 112019275 examples [2:04:30, 12989.00 examples/s]
Generating train split: 112021226 examples [2:04:30, 10747.21 examples/s]
Generating train split: 112022759 examples [2:04:30, 9407.48 examples/s] 
Generating train split: 112024007 examples [2:04:30, 9190.78 examples/s]
Generating train split: 112025317 examples [2:04:30, 9683.26 examples/s]
Generating train split: 112026648 examples [2:04:31, 10255.90 examples/s]
Generating train split: 112027851 examples [2:04:31, 9640.65 examples/s] 
Generating train split: 112028935 examples [2:04:31, 8851.74 examples/s]
Generating train split: 112029901 examples [2:04:31, 8669.93 examples/s]
Generating train split: 112030818 examples [2:04:31, 8661.59 examples/s]
Generating train split: 112031718 examples [2:04:31, 6297.13 examples/s]
Generating train split: 112032508 examples [2:04:31, 6424.60 examples/s]
Generating train split: 112033233 examples [2:04:32, 6088.37 examples/s]
Generating train split: 112033893 examples [2:04:32, 5286.08 examples/s]
Generating train split: 112034921 examples [2:04:32, 6332.01 examples/s]
Generating train split: 112035723 examples [2:04:32, 6716.65 examples/s]
Generating train split: 112036467 examples [2:04:32, 5438.83 examples/s]
Generating train split: 112037100 examples [2:04:32, 4788.38 examples/s]
Generating train split: 112037648 examples [2:04:33, 4242.14 examples/s]
Generating train split: 112038129 examples [2:04:33, 4133.70 examples/s]
Generating train split: 112039604 examples [2:04:33, 6366.60 examples/s]
Generating train split: 112040491 examples [2:04:33, 6941.81 examples/s]
Generating train split: 112041274 examples [2:04:33, 6760.14 examples/s]
Generating train split: 112043195 examples [2:04:33, 9902.38 examples/s]
Generating train split: 112050552 examples [2:04:33, 26777.87 examples/s]
Generating train split: 112059394 examples [2:04:33, 43695.49 examples/s]
Generating train split: 112064128 examples [2:04:34, 31999.17 examples/s]
Generating train split: 112068035 examples [2:04:34, 18371.02 examples/s]
Generating train split: 112071025 examples [2:04:34, 16698.95 examples/s]
Generating train split: 112073490 examples [2:04:34, 15528.33 examples/s]
Generating train split: 112075582 examples [2:04:35, 12753.32 examples/s]
Generating train split: 112077282 examples [2:04:35, 11899.63 examples/s]
Generating train split: 112084920 examples [2:04:35, 22139.49 examples/s]
Generating train split: 112093312 examples [2:04:35, 33561.72 examples/s]
Generating train split: 112098157 examples [2:04:35, 31363.88 examples/s]
Generating train split: 112102349 examples [2:04:36, 18554.01 examples/s]
Generating train split: 112105537 examples [2:04:37, 10000.55 examples/s]
Generating train split: 112107892 examples [2:04:37, 9323.97 examples/s] 
Generating train split: 112109757 examples [2:04:37, 8947.40 examples/s]
Generating train split: 112111292 examples [2:04:37, 8924.61 examples/s]
Generating train split: 112112788 examples [2:04:37, 9651.15 examples/s]
Generating train split: 112114170 examples [2:04:38, 9515.53 examples/s]
Generating train split: 112117353 examples [2:04:38, 13181.82 examples/s]
Generating train split: 112119171 examples [2:04:38, 10165.31 examples/s]
Generating train split: 112120621 examples [2:04:38, 10078.60 examples/s]
Generating train split: 112121936 examples [2:04:38, 8326.65 examples/s] 
Generating train split: 112123011 examples [2:04:39, 8446.38 examples/s]
Generating train split: 112124113 examples [2:04:39, 8789.87 examples/s]
Generating train split: 112125140 examples [2:04:39, 7855.52 examples/s]
Generating train split: 112126104 examples [2:04:39, 8211.82 examples/s]
Generating train split: 112127017 examples [2:04:39, 7479.64 examples/s]
Generating train split: 112127912 examples [2:04:39, 7635.04 examples/s]
Generating train split: 112129356 examples [2:04:39, 9195.68 examples/s]
Generating train split: 112130353 examples [2:04:39, 9215.40 examples/s]
Generating train split: 112131334 examples [2:04:40, 8428.55 examples/s]
Generating train split: 112132717 examples [2:04:40, 9729.50 examples/s]
Generating train split: 112133745 examples [2:04:40, 9821.06 examples/s]
Generating train split: 112134770 examples [2:04:40, 6603.69 examples/s]
Generating train split: 112135605 examples [2:04:40, 6845.92 examples/s]
Generating train split: 112137139 examples [2:04:40, 8737.20 examples/s]
Generating train split: 112138170 examples [2:04:40, 7733.61 examples/s]
Generating train split: 112139071 examples [2:04:41, 7180.81 examples/s]
Generating train split: 112140000 examples [2:04:41, 7652.60 examples/s]
Generating train split: 112140852 examples [2:04:41, 7184.21 examples/s]
Generating train split: 112143679 examples [2:04:41, 12245.36 examples/s]
Generating train split: 112146070 examples [2:04:41, 15214.05 examples/s]
Generating train split: 112147759 examples [2:04:41, 11411.01 examples/s]
Generating train split: 112155781 examples [2:04:41, 26387.24 examples/s]
Generating train split: 112163940 examples [2:04:41, 39472.05 examples/s]
Generating train split: 112168754 examples [2:04:42, 37321.08 examples/s]
Generating train split: 112173122 examples [2:04:42, 22223.74 examples/s]
Generating train split: 112176506 examples [2:04:43, 13955.84 examples/s]
Generating train split: 112179059 examples [2:04:43, 10691.58 examples/s]
Generating train split: 112186975 examples [2:04:43, 18034.75 examples/s]
Generating train split: 112194755 examples [2:04:43, 25974.27 examples/s]
Generating train split: 112199704 examples [2:04:44, 19192.03 examples/s]
Generating train split: 112203506 examples [2:04:44, 14024.71 examples/s]
Generating train split: 112206388 examples [2:04:45, 11735.38 examples/s]
Generating train split: 112208625 examples [2:04:45, 8750.00 examples/s] 
Generating train split: 112210304 examples [2:04:45, 8565.09 examples/s]
Generating train split: 112211718 examples [2:04:46, 8568.03 examples/s]
Generating train split: 112212975 examples [2:04:46, 8976.13 examples/s]
Generating train split: 112214640 examples [2:04:46, 10110.08 examples/s]
Generating train split: 112215998 examples [2:04:46, 9411.65 examples/s] 
Generating train split: 112217180 examples [2:04:46, 7520.32 examples/s]
Generating train split: 112218138 examples [2:04:46, 7680.41 examples/s]
Generating train split: 112219061 examples [2:04:46, 7369.10 examples/s]
Generating train split: 112220966 examples [2:04:47, 9644.38 examples/s]
Generating train split: 112222122 examples [2:04:47, 8167.54 examples/s]
Generating train split: 112223112 examples [2:04:47, 8306.72 examples/s]
Generating train split: 112224061 examples [2:04:47, 7085.24 examples/s]
Generating train split: 112224871 examples [2:04:47, 6140.26 examples/s]
Generating train split: 112225572 examples [2:04:47, 5953.98 examples/s]
Generating train split: 112226961 examples [2:04:47, 7626.56 examples/s]
Generating train split: 112227920 examples [2:04:48, 8065.61 examples/s]
Generating train split: 112228820 examples [2:04:48, 7755.21 examples/s]
Generating train split: 112229664 examples [2:04:48, 6801.91 examples/s]
Generating train split: 112230402 examples [2:04:48, 6455.26 examples/s]
Generating train split: 112231832 examples [2:04:48, 8315.97 examples/s]
Generating train split: 112232742 examples [2:04:48, 5379.36 examples/s]
Generating train split: 112235092 examples [2:04:49, 8745.54 examples/s]
Generating train split: 112236396 examples [2:04:49, 9631.08 examples/s]
Generating train split: 112237640 examples [2:04:49, 6487.49 examples/s]
Generating train split: 112239060 examples [2:04:49, 7812.33 examples/s]
Generating train split: 112247426 examples [2:04:49, 22764.44 examples/s]
Generating train split: 112256226 examples [2:04:49, 36532.05 examples/s]
Generating train split: 112261003 examples [2:04:50, 18054.63 examples/s]
Generating train split: 112264585 examples [2:04:50, 16258.74 examples/s]
Generating train split: 112274071 examples [2:04:50, 26678.04 examples/s]
Generating train split: 112281737 examples [2:04:50, 34595.88 examples/s]
Generating train split: 112287420 examples [2:04:51, 24470.87 examples/s]
Generating train split: 112291819 examples [2:04:51, 14684.54 examples/s]
Generating train split: 112295087 examples [2:04:52, 11963.29 examples/s]
Generating train split: 112298263 examples [2:04:52, 13811.73 examples/s]
Generating train split: 112300964 examples [2:04:52, 12142.74 examples/s]
Generating train split: 112303101 examples [2:04:53, 11788.88 examples/s]
Generating train split: 112304911 examples [2:04:53, 11177.81 examples/s]
Generating train split: 112306457 examples [2:04:53, 9381.74 examples/s] 
Generating train split: 112307705 examples [2:04:53, 7551.79 examples/s]
Generating train split: 112308940 examples [2:04:53, 8182.40 examples/s]
Generating train split: 112310107 examples [2:04:54, 8685.49 examples/s]
Generating train split: 112311188 examples [2:04:54, 7417.01 examples/s]
Generating train split: 112316487 examples [2:04:54, 15471.44 examples/s]
Generating train split: 112324963 examples [2:04:54, 29437.73 examples/s]
Generating train split: 112332171 examples [2:04:54, 38957.91 examples/s]
Generating train split: 112337198 examples [2:04:55, 23155.01 examples/s]
Generating train split: 112341069 examples [2:04:55, 18335.21 examples/s]
Generating train split: 112344117 examples [2:04:55, 16417.37 examples/s]
Generating train split: 112346603 examples [2:04:55, 17003.53 examples/s]
Generating train split: 112349902 examples [2:04:55, 19617.13 examples/s]
Generating train split: 112352528 examples [2:04:56, 17801.39 examples/s]
Generating train split: 112354795 examples [2:04:56, 11925.69 examples/s]
Generating train split: 112356546 examples [2:04:56, 10187.84 examples/s]
Generating train split: 112357964 examples [2:04:57, 8846.05 examples/s] 
Generating train split: 112362691 examples [2:04:57, 14363.13 examples/s]
Generating train split: 112370590 examples [2:04:57, 25362.58 examples/s]
Generating train split: 112377712 examples [2:04:57, 34331.37 examples/s]
Generating train split: 112382603 examples [2:04:57, 26071.99 examples/s]
Generating train split: 112386518 examples [2:04:58, 16209.87 examples/s]
Generating train split: 112389479 examples [2:04:58, 15566.21 examples/s]
Generating train split: 112393040 examples [2:04:58, 18289.64 examples/s]
Generating train split: 112398383 examples [2:04:58, 24001.19 examples/s]
Generating train split: 112403425 examples [2:04:58, 28979.91 examples/s]
Generating train split: 112410573 examples [2:04:58, 37997.16 examples/s]
Generating train split: 112417882 examples [2:04:58, 46151.17 examples/s]
Generating train split: 112425314 examples [2:04:58, 53144.51 examples/s]
Generating train split: 112432591 examples [2:04:59, 58296.89 examples/s]
Generating train split: 112439679 examples [2:04:59, 61720.26 examples/s]
Generating train split: 112446762 examples [2:04:59, 64269.92 examples/s]
Generating train split: 112454080 examples [2:04:59, 66810.82 examples/s]
Generating train split: 112461038 examples [2:04:59, 65187.57 examples/s]
Generating train split: 112468689 examples [2:04:59, 68408.54 examples/s]
Generating train split: 112475865 examples [2:04:59, 69373.46 examples/s]
Generating train split: 112483527 examples [2:04:59, 71488.28 examples/s]
Generating train split: 112490767 examples [2:04:59, 71131.99 examples/s]
Generating train split: 112498068 examples [2:04:59, 71664.33 examples/s]
Generating train split: 112505487 examples [2:05:00, 72411.89 examples/s]
Generating train split: 112512763 examples [2:05:00, 70024.30 examples/s]
Generating train split: 112519900 examples [2:05:00, 70411.90 examples/s]
Generating train split: 112526972 examples [2:05:00, 68883.57 examples/s]
Generating train split: 112533889 examples [2:05:00, 67831.94 examples/s]
Generating train split: 112541093 examples [2:05:00, 69030.06 examples/s]
Generating train split: 112548168 examples [2:05:00, 69510.75 examples/s]
Generating train split: 112555283 examples [2:05:00, 69984.04 examples/s]
Generating train split: 112562298 examples [2:05:00, 66860.27 examples/s]
Generating train split: 112569020 examples [2:05:01, 66949.68 examples/s]
Generating train split: 112575747 examples [2:05:01, 61183.64 examples/s]
Generating train split: 112581981 examples [2:05:01, 42551.68 examples/s]
Generating train split: 112587053 examples [2:05:01, 33045.15 examples/s]
Generating train split: 112591194 examples [2:05:01, 24007.50 examples/s]
Generating train split: 112595386 examples [2:05:02, 26789.11 examples/s]
Generating train split: 112598930 examples [2:05:02, 25763.36 examples/s]
Generating train split: 112602099 examples [2:05:02, 21191.52 examples/s]
Generating train split: 112604715 examples [2:05:02, 20243.26 examples/s]
Generating train split: 112607065 examples [2:05:02, 20806.36 examples/s]
Generating train split: 112609403 examples [2:05:02, 20088.99 examples/s]
Generating train split: 112611590 examples [2:05:03, 15026.19 examples/s]
Generating train split: 112613365 examples [2:05:03, 13680.76 examples/s]
Generating train split: 112614928 examples [2:05:03, 11010.35 examples/s]
Generating train split: 112617168 examples [2:05:03, 13013.17 examples/s]
Generating train split: 112618826 examples [2:05:03, 13728.92 examples/s]
Generating train split: 112620901 examples [2:05:03, 15282.77 examples/s]
Generating train split: 112622642 examples [2:05:04, 13106.10 examples/s]
Generating train split: 112624140 examples [2:05:04, 12968.74 examples/s]
Generating train split: 112625567 examples [2:05:04, 9971.85 examples/s] 
Generating train split: 112626892 examples [2:05:04, 10613.19 examples/s]
Generating train split: 112628675 examples [2:05:04, 12216.07 examples/s]
Generating train split: 112630610 examples [2:05:04, 13918.10 examples/s]
Generating train split: 112632165 examples [2:05:04, 11498.98 examples/s]
Generating train split: 112633491 examples [2:05:05, 10031.38 examples/s]
Generating train split: 112634896 examples [2:05:05, 10877.00 examples/s]
Generating train split: 112636126 examples [2:05:05, 9960.22 examples/s] 
Generating train split: 112637227 examples [2:05:05, 8589.32 examples/s]
Generating train split: 112639325 examples [2:05:05, 11265.14 examples/s]
Generating train split: 112640624 examples [2:05:05, 7562.16 examples/s] 
Generating train split: 112641979 examples [2:05:06, 8605.36 examples/s]
Generating train split: 112643292 examples [2:05:06, 9509.92 examples/s]
Generating train split: 112644471 examples [2:05:06, 9689.04 examples/s]
Generating train split: 112645601 examples [2:05:06, 6929.62 examples/s]
Generating train split: 112646512 examples [2:05:06, 5514.68 examples/s]
Generating train split: 112647248 examples [2:05:07, 4647.19 examples/s]
Generating train split: 112648615 examples [2:05:07, 6095.43 examples/s]
Generating train split: 112649445 examples [2:05:07, 6346.37 examples/s]
Generating train split: 112651775 examples [2:05:07, 9843.49 examples/s]
Generating train split: 112653040 examples [2:05:07, 8267.94 examples/s]
Generating train split: 112654825 examples [2:05:07, 10168.50 examples/s]
Generating train split: 112656084 examples [2:05:07, 9916.44 examples/s] 
Generating train split: 112657604 examples [2:05:07, 11086.22 examples/s]
Generating train split: 112658878 examples [2:05:08, 8375.67 examples/s] 
Generating train split: 112659922 examples [2:05:08, 8706.01 examples/s]
Generating train split: 112662260 examples [2:05:08, 11955.68 examples/s]
Generating train split: 112663676 examples [2:05:08, 12150.45 examples/s]
Generating train split: 112665044 examples [2:05:08, 9884.20 examples/s] 
Generating train split: 112666245 examples [2:05:08, 10322.67 examples/s]
Generating train split: 112667412 examples [2:05:08, 10466.35 examples/s]
Generating train split: 112669412 examples [2:05:09, 12507.60 examples/s]
Generating train split: 112670759 examples [2:05:09, 9806.46 examples/s] 
Generating train split: 112672119 examples [2:05:09, 10645.00 examples/s]
Generating train split: 112674167 examples [2:05:09, 12935.53 examples/s]
Generating train split: 112675613 examples [2:05:09, 10629.31 examples/s]
Generating train split: 112677646 examples [2:05:09, 12800.94 examples/s]
Generating train split: 112679785 examples [2:05:09, 14877.56 examples/s]
Generating train split: 112681454 examples [2:05:10, 10775.09 examples/s]
Generating train split: 112682810 examples [2:05:10, 10088.47 examples/s]
Generating train split: 112684014 examples [2:05:10, 10360.57 examples/s]
Generating train split: 112685756 examples [2:05:10, 11950.15 examples/s]
Generating train split: 112687112 examples [2:05:10, 8967.25 examples/s] 
Generating train split: 112688219 examples [2:05:10, 9245.63 examples/s]
Generating train split: 112689384 examples [2:05:10, 9633.90 examples/s]
Generating train split: 112690468 examples [2:05:11, 6614.06 examples/s]
Generating train split: 112691690 examples [2:05:11, 7647.99 examples/s]
Generating train split: 112692671 examples [2:05:11, 6954.69 examples/s]
Generating train split: 112693517 examples [2:05:11, 6909.59 examples/s]
Generating train split: 112694411 examples [2:05:11, 7343.31 examples/s]
Generating train split: 112696307 examples [2:05:11, 10035.19 examples/s]
Generating train split: 112697449 examples [2:05:12, 8943.83 examples/s] 
Generating train split: 112698461 examples [2:05:12, 7459.75 examples/s]
Generating train split: 112699548 examples [2:05:12, 8188.63 examples/s]
Generating train split: 112700486 examples [2:05:12, 7079.97 examples/s]
Generating train split: 112701296 examples [2:05:12, 6587.79 examples/s]
Generating train split: 112703528 examples [2:05:12, 10043.22 examples/s]
Generating train split: 112704715 examples [2:05:13, 8022.42 examples/s] 
Generating train split: 112706045 examples [2:05:13, 9108.92 examples/s]
Generating train split: 112707128 examples [2:05:13, 8582.02 examples/s]
Generating train split: 112709082 examples [2:05:13, 11017.77 examples/s]
Generating train split: 112710720 examples [2:05:13, 12326.30 examples/s]
Generating train split: 112712183 examples [2:05:13, 12736.04 examples/s]
Generating train split: 112713562 examples [2:05:13, 8380.77 examples/s] 
Generating train split: 112714665 examples [2:05:14, 7529.09 examples/s]
Generating train split: 112715738 examples [2:05:14, 8109.27 examples/s]
Generating train split: 112716715 examples [2:05:14, 8121.57 examples/s]
Generating train split: 112717836 examples [2:05:14, 8790.51 examples/s]
Generating train split: 112718817 examples [2:05:14, 8463.64 examples/s]
Generating train split: 112721793 examples [2:05:14, 13687.43 examples/s]
Generating train split: 112723321 examples [2:05:14, 10909.76 examples/s]
Generating train split: 112724614 examples [2:05:15, 9800.31 examples/s] 
Generating train split: 112725754 examples [2:05:15, 8480.65 examples/s]
Generating train split: 112726758 examples [2:05:15, 8797.49 examples/s]
Generating train split: 112728662 examples [2:05:15, 10854.56 examples/s]
Generating train split: 112729866 examples [2:05:15, 7825.68 examples/s] 
Generating train split: 112730967 examples [2:05:15, 8392.79 examples/s]
Generating train split: 112732606 examples [2:05:15, 9985.84 examples/s]
Generating train split: 112733779 examples [2:05:16, 6097.01 examples/s]
Generating train split: 112735527 examples [2:05:16, 7955.51 examples/s]
Generating train split: 112736683 examples [2:05:16, 5805.50 examples/s]
Generating train split: 112737595 examples [2:05:16, 5139.45 examples/s]
Generating train split: 112738342 examples [2:05:17, 5006.92 examples/s]
Generating train split: 112739006 examples [2:05:17, 5047.44 examples/s]
Generating train split: 112739634 examples [2:05:17, 4398.44 examples/s]
Generating train split: 112740160 examples [2:05:17, 4152.84 examples/s]
Generating train split: 112740642 examples [2:05:17, 4179.51 examples/s]
Generating train split: 112741109 examples [2:05:17, 3577.30 examples/s]
Generating train split: 112742046 examples [2:05:18, 4733.91 examples/s]
Generating train split: 112742603 examples [2:05:18, 4587.50 examples/s]
Generating train split: 112743450 examples [2:05:18, 5460.81 examples/s]
Generating train split: 112744069 examples [2:05:18, 4351.22 examples/s]
Generating train split: 112745870 examples [2:05:18, 7243.32 examples/s]
Generating train split: 112746766 examples [2:05:18, 5930.67 examples/s]
Generating train split: 112747512 examples [2:05:18, 5823.72 examples/s]
Generating train split: 112748994 examples [2:05:19, 7752.02 examples/s]
Generating train split: 112749925 examples [2:05:19, 7823.64 examples/s]
Generating train split: 112750818 examples [2:05:19, 5735.82 examples/s]
Generating train split: 112751546 examples [2:05:19, 5645.94 examples/s]
Generating train split: 112753236 examples [2:05:19, 7983.03 examples/s]
Generating train split: 112754270 examples [2:05:19, 8508.41 examples/s]
Generating train split: 112755262 examples [2:05:20, 6748.98 examples/s]
Generating train split: 112756874 examples [2:05:20, 8726.60 examples/s]
Generating train split: 112759584 examples [2:05:20, 12984.93 examples/s]
Generating train split: 112761146 examples [2:05:20, 12843.01 examples/s]
Generating train split: 112762607 examples [2:05:20, 11908.85 examples/s]
Generating train split: 112764575 examples [2:05:20, 13753.68 examples/s]
Generating train split: 112766085 examples [2:05:21, 7651.60 examples/s] 
Generating train split: 112767680 examples [2:05:21, 9013.35 examples/s]
Generating train split: 112768975 examples [2:05:21, 8732.48 examples/s]
Generating train split: 112770123 examples [2:05:21, 7664.31 examples/s]
Generating train split: 112771967 examples [2:05:21, 9688.42 examples/s]
Generating train split: 112773308 examples [2:05:21, 10459.95 examples/s]
Generating train split: 112774566 examples [2:05:21, 10507.02 examples/s]
Generating train split: 112775773 examples [2:05:22, 8616.51 examples/s] 
Generating train split: 112776791 examples [2:05:22, 7882.35 examples/s]
Generating train split: 112777732 examples [2:05:22, 8116.53 examples/s]
Generating train split: 112778645 examples [2:05:22, 8131.26 examples/s]
Generating train split: 112779526 examples [2:05:22, 8245.31 examples/s]
Generating train split: 112781021 examples [2:05:22, 9736.14 examples/s]
Generating train split: 112782048 examples [2:05:22, 9333.46 examples/s]
Generating train split: 112783030 examples [2:05:22, 8384.26 examples/s]
Generating train split: 112783914 examples [2:05:23, 6117.97 examples/s]
Generating train split: 112784633 examples [2:05:23, 5690.85 examples/s]
Generating train split: 112785373 examples [2:05:23, 6037.91 examples/s]
Generating train split: 112786044 examples [2:05:23, 5642.58 examples/s]
Generating train split: 112786832 examples [2:05:23, 6095.07 examples/s]
Generating train split: 112787496 examples [2:05:23, 5037.74 examples/s]
Generating train split: 112789457 examples [2:05:23, 8234.36 examples/s]
Generating train split: 112790898 examples [2:05:24, 9695.07 examples/s]
Generating train split: 112792013 examples [2:05:24, 9220.44 examples/s]
Generating train split: 112794325 examples [2:05:24, 12690.52 examples/s]
Generating train split: 112796538 examples [2:05:24, 15165.34 examples/s]
Generating train split: 112798190 examples [2:05:24, 14246.36 examples/s]
Generating train split: 112799872 examples [2:05:24, 14891.66 examples/s]
Generating train split: 112801446 examples [2:05:24, 14755.69 examples/s]
Generating train split: 112802985 examples [2:05:24, 12376.15 examples/s]
Generating train split: 112804321 examples [2:05:24, 12562.25 examples/s]
Generating train split: 112805653 examples [2:05:25, 12351.72 examples/s]
Generating train split: 112806938 examples [2:05:25, 9846.08 examples/s] 
Generating train split: 112809073 examples [2:05:25, 12477.98 examples/s]
Generating train split: 112810610 examples [2:05:25, 13185.29 examples/s]
Generating train split: 112812054 examples [2:05:25, 12391.70 examples/s]
Generating train split: 112813397 examples [2:05:25, 10504.59 examples/s]
Generating train split: 112814556 examples [2:05:25, 10130.25 examples/s]
Generating train split: 112816671 examples [2:05:26, 12734.19 examples/s]
Generating train split: 112818064 examples [2:05:26, 11127.08 examples/s]
Generating train split: 112819297 examples [2:05:26, 9324.59 examples/s] 
Generating train split: 112821389 examples [2:05:26, 11765.40 examples/s]
Generating train split: 112822766 examples [2:05:26, 12072.76 examples/s]
Generating train split: 112824100 examples [2:05:26, 11470.76 examples/s]
Generating train split: 112825336 examples [2:05:26, 9063.88 examples/s] 
Generating train split: 112826839 examples [2:05:27, 10337.71 examples/s]
Generating train split: 112828014 examples [2:05:27, 9702.02 examples/s] 
Generating train split: 112830092 examples [2:05:27, 12278.95 examples/s]
Generating train split: 112831472 examples [2:05:27, 12299.56 examples/s]
Generating train split: 112832816 examples [2:05:27, 12301.53 examples/s]
Generating train split: 112834267 examples [2:05:27, 12829.78 examples/s]
Generating train split: 112835607 examples [2:05:27, 11706.37 examples/s]
Generating train split: 112836847 examples [2:05:28, 8052.94 examples/s] 
Generating train split: 112838763 examples [2:05:28, 10265.18 examples/s]
Generating train split: 112840097 examples [2:05:28, 10936.23 examples/s]
Generating train split: 112841380 examples [2:05:28, 10550.06 examples/s]
Generating train split: 112842567 examples [2:05:28, 9147.91 examples/s] 
Generating train split: 112844020 examples [2:05:28, 10318.38 examples/s]
Generating train split: 112845845 examples [2:05:28, 12243.96 examples/s]
Generating train split: 112847199 examples [2:05:29, 8550.25 examples/s] 
Generating train split: 112848542 examples [2:05:29, 9524.35 examples/s]
Generating train split: 112849712 examples [2:05:29, 9535.91 examples/s]
Generating train split: 112851120 examples [2:05:29, 10564.46 examples/s]
Generating train split: 112852315 examples [2:05:29, 9197.05 examples/s] 
Generating train split: 112854359 examples [2:05:29, 11773.27 examples/s]
Generating train split: 112855700 examples [2:05:29, 12061.71 examples/s]
Generating train split: 112857601 examples [2:05:29, 13862.70 examples/s]
Generating train split: 112859102 examples [2:05:29, 13639.75 examples/s]
Generating train split: 112860543 examples [2:05:30, 12996.67 examples/s]
Generating train split: 112862218 examples [2:05:30, 13916.28 examples/s]
Generating train split: 112863671 examples [2:05:30, 11903.61 examples/s]
Generating train split: 112865440 examples [2:05:30, 13336.15 examples/s]
Generating train split: 112866861 examples [2:05:30, 11286.48 examples/s]
Generating train split: 112868104 examples [2:05:30, 10698.66 examples/s]
Generating train split: 112869255 examples [2:05:30, 10112.69 examples/s]
Generating train split: 112871352 examples [2:05:31, 12700.76 examples/s]
Generating train split: 112873031 examples [2:05:31, 13743.86 examples/s]
Generating train split: 112874501 examples [2:05:31, 11599.93 examples/s]
Generating train split: 112875774 examples [2:05:31, 9475.94 examples/s] 
Generating train split: 112876889 examples [2:05:31, 9831.87 examples/s]
Generating train split: 112878507 examples [2:05:31, 10612.05 examples/s]
Generating train split: 112879649 examples [2:05:31, 8616.34 examples/s] 
Generating train split: 112887557 examples [2:05:32, 23712.25 examples/s]
Generating train split: 112895254 examples [2:05:32, 36083.16 examples/s]
Generating train split: 112899669 examples [2:05:32, 25453.73 examples/s]
Generating train split: 112903213 examples [2:05:32, 18393.12 examples/s]
Generating train split: 112905998 examples [2:05:33, 15271.15 examples/s]
Generating train split: 112908229 examples [2:05:33, 15396.61 examples/s]
Generating train split: 112910267 examples [2:05:33, 14931.33 examples/s]
Generating train split: 112912102 examples [2:05:33, 11156.92 examples/s]
Generating train split: 112915324 examples [2:05:33, 14351.13 examples/s]
Generating train split: 112917292 examples [2:05:33, 13890.85 examples/s]
Generating train split: 112919044 examples [2:05:34, 13000.91 examples/s]
Generating train split: 112922556 examples [2:05:34, 17282.18 examples/s]
Generating train split: 112924838 examples [2:05:34, 18481.22 examples/s]
Generating train split: 112927019 examples [2:05:34, 16749.60 examples/s]
Generating train split: 112928948 examples [2:05:34, 13192.30 examples/s]
Generating train split: 112930541 examples [2:05:34, 12090.12 examples/s]
Generating train split: 112931945 examples [2:05:35, 9774.35 examples/s] 
Generating train split: 112934002 examples [2:05:35, 11718.67 examples/s]
Generating train split: 112935658 examples [2:05:35, 12712.28 examples/s]
Generating train split: 112937157 examples [2:05:35, 10324.43 examples/s]
Generating train split: 112938410 examples [2:05:35, 8191.17 examples/s] 
Generating train split: 112945878 examples [2:05:35, 20173.10 examples/s]
Generating train split: 112953943 examples [2:05:36, 32547.47 examples/s]
Generating train split: 112958425 examples [2:05:36, 23405.40 examples/s]
Generating train split: 112961981 examples [2:05:36, 17232.58 examples/s]
Generating train split: 112964755 examples [2:05:37, 8040.63 examples/s] 
Generating train split: 112966780 examples [2:05:37, 8951.81 examples/s]
Generating train split: 112968746 examples [2:05:38, 7800.21 examples/s]
Generating train split: 112970278 examples [2:05:38, 8014.58 examples/s]
Generating train split: 112971625 examples [2:05:38, 6030.60 examples/s]
Generating train split: 112973537 examples [2:05:38, 7433.17 examples/s]
Generating train split: 112974830 examples [2:05:39, 6829.91 examples/s]
Generating train split: 112976893 examples [2:05:39, 8713.44 examples/s]
Generating train split: 112978254 examples [2:05:39, 9338.33 examples/s]
Generating train split: 112982821 examples [2:05:39, 16111.90 examples/s]
Generating train split: 112991303 examples [2:05:39, 30560.51 examples/s]
Generating train split: 112998291 examples [2:05:39, 39610.67 examples/s]
Generating train split: 113003291 examples [2:05:40, 17583.45 examples/s]
Generating train split: 113007017 examples [2:05:40, 13343.88 examples/s]
Generating train split: 113009849 examples [2:05:41, 12075.10 examples/s]
Generating train split: 113016622 examples [2:05:41, 18267.90 examples/s]
Generating train split: 113025501 examples [2:05:41, 27937.97 examples/s]
Generating train split: 113030700 examples [2:05:41, 23878.59 examples/s]
Generating train split: 113034843 examples [2:05:42, 17280.39 examples/s]
Generating train split: 113038025 examples [2:05:42, 16114.22 examples/s]
Generating train split: 113040634 examples [2:05:42, 12635.70 examples/s]
Generating train split: 113042667 examples [2:05:43, 11644.44 examples/s]
Generating train split: 113044342 examples [2:05:43, 12203.01 examples/s]
Generating train split: 113045992 examples [2:05:43, 11440.58 examples/s]
Generating train split: 113047644 examples [2:05:43, 12260.40 examples/s]
Generating train split: 113049138 examples [2:05:43, 11281.90 examples/s]
Generating train split: 113050450 examples [2:05:43, 9358.86 examples/s] 
Generating train split: 113051542 examples [2:05:44, 8127.32 examples/s]
Generating train split: 113052466 examples [2:05:44, 8172.32 examples/s]
Generating train split: 113053369 examples [2:05:44, 6997.49 examples/s]
Generating train split: 113054646 examples [2:05:44, 8087.89 examples/s]
Generating train split: 113055634 examples [2:05:44, 8443.52 examples/s]
Generating train split: 113056568 examples [2:05:44, 7511.80 examples/s]
Generating train split: 113057396 examples [2:05:44, 6485.82 examples/s]
Generating train split: 113064438 examples [2:05:44, 20163.38 examples/s]
Generating train split: 113071943 examples [2:05:45, 33003.80 examples/s]
Generating train split: 113076024 examples [2:05:45, 17113.30 examples/s]
Generating train split: 113079118 examples [2:05:45, 13731.91 examples/s]
Generating train split: 113086974 examples [2:05:46, 22310.38 examples/s]
Generating train split: 113093962 examples [2:05:46, 29780.45 examples/s]
Generating train split: 113098853 examples [2:05:46, 26738.41 examples/s]
Generating train split: 113102912 examples [2:05:46, 21404.81 examples/s]
Generating train split: 113106149 examples [2:05:47, 13949.79 examples/s]
Generating train split: 113108602 examples [2:05:47, 8856.70 examples/s] 
Generating train split: 113110424 examples [2:05:48, 9368.94 examples/s]
Generating train split: 113112418 examples [2:05:48, 10528.00 examples/s]
Generating train split: 113114190 examples [2:05:48, 10360.48 examples/s]
Generating train split: 113115729 examples [2:05:48, 10971.81 examples/s]
Generating train split: 113117235 examples [2:05:48, 11239.41 examples/s]
Generating train split: 113118655 examples [2:05:48, 8817.38 examples/s] 
Generating train split: 113119804 examples [2:05:48, 9011.96 examples/s]
Generating train split: 113121680 examples [2:05:49, 10870.07 examples/s]
Generating train split: 113123010 examples [2:05:49, 11209.17 examples/s]
Generating train split: 113124319 examples [2:05:49, 10088.38 examples/s]
Generating train split: 113125471 examples [2:05:49, 9266.90 examples/s] 
Generating train split: 113127044 examples [2:05:49, 10609.53 examples/s]
Generating train split: 113128220 examples [2:05:49, 8834.99 examples/s] 
Generating train split: 113129225 examples [2:05:50, 7289.43 examples/s]
Generating train split: 113130077 examples [2:05:50, 5237.33 examples/s]
Generating train split: 113132335 examples [2:05:50, 8091.99 examples/s]
Generating train split: 113133485 examples [2:05:50, 7432.10 examples/s]
Generating train split: 113135487 examples [2:05:50, 9687.01 examples/s]
Generating train split: 113136746 examples [2:05:50, 10048.83 examples/s]
Generating train split: 113138617 examples [2:05:50, 12007.29 examples/s]
Generating train split: 113140204 examples [2:05:51, 12946.49 examples/s]
Generating train split: 113141676 examples [2:05:51, 8839.75 examples/s] 
Generating train split: 113149539 examples [2:05:51, 22508.29 examples/s]
Generating train split: 113157239 examples [2:05:51, 34412.80 examples/s]
Generating train split: 113161775 examples [2:05:51, 29652.22 examples/s]
Generating train split: 113165623 examples [2:05:52, 13894.54 examples/s]
Generating train split: 113168481 examples [2:05:52, 14208.03 examples/s]
Generating train split: 113170947 examples [2:05:53, 10644.55 examples/s]
Generating train split: 113172839 examples [2:05:53, 9550.80 examples/s] 
Generating train split: 113174363 examples [2:05:53, 8750.81 examples/s]
Generating train split: 113175621 examples [2:05:53, 8801.34 examples/s]
Generating train split: 113177070 examples [2:05:53, 9560.54 examples/s]
Generating train split: 113178334 examples [2:05:53, 10076.31 examples/s]
Generating train split: 113179565 examples [2:05:54, 9519.89 examples/s] 
Generating train split: 113180669 examples [2:05:54, 8074.83 examples/s]
Generating train split: 113181691 examples [2:05:54, 8487.83 examples/s]
Generating train split: 113183238 examples [2:05:54, 9996.02 examples/s]
Generating train split: 113184680 examples [2:05:54, 10689.85 examples/s]
Generating train split: 113185862 examples [2:05:54, 7067.46 examples/s] 
Generating train split: 113187429 examples [2:05:55, 8653.67 examples/s]
Generating train split: 113188557 examples [2:05:55, 5567.74 examples/s]
Generating train split: 113189428 examples [2:05:55, 5817.43 examples/s]
Generating train split: 113190560 examples [2:05:55, 6768.93 examples/s]
Generating train split: 113191469 examples [2:05:55, 5953.61 examples/s]
Generating train split: 113192454 examples [2:05:55, 6690.53 examples/s]
Generating train split: 113193289 examples [2:05:56, 6709.93 examples/s]
Generating train split: 113194080 examples [2:05:56, 5388.80 examples/s]
Generating train split: 113195693 examples [2:05:56, 7509.84 examples/s]
Generating train split: 113197456 examples [2:05:56, 9739.66 examples/s]
Generating train split: 113198906 examples [2:05:56, 10599.70 examples/s]
Generating train split: 113200130 examples [2:05:56, 7003.80 examples/s] 
Generating train split: 113201096 examples [2:05:57, 6713.74 examples/s]
Generating train split: 113201957 examples [2:05:57, 5933.68 examples/s]
Generating train split: 113202962 examples [2:05:57, 6682.49 examples/s]
Generating train split: 113203834 examples [2:05:57, 6951.18 examples/s]
Generating train split: 113204636 examples [2:05:57, 6462.37 examples/s]
Generating train split: 113205360 examples [2:05:57, 5665.51 examples/s]
Generating train split: 113206000 examples [2:05:58, 5760.65 examples/s]
Generating train split: 113207105 examples [2:05:58, 6953.24 examples/s]
Generating train split: 113207865 examples [2:05:58, 5135.22 examples/s]
Generating train split: 113208884 examples [2:05:58, 6130.77 examples/s]
Generating train split: 113209616 examples [2:05:58, 5983.23 examples/s]
Generating train split: 113210299 examples [2:05:58, 4121.37 examples/s]
Generating train split: 113211034 examples [2:05:59, 4703.01 examples/s]
Generating train split: 113212375 examples [2:05:59, 6482.62 examples/s]
Generating train split: 113213205 examples [2:05:59, 6622.60 examples/s]
Generating train split: 113214621 examples [2:05:59, 8317.48 examples/s]
Generating train split: 113215579 examples [2:05:59, 5066.52 examples/s]
Generating train split: 113216331 examples [2:06:00, 4011.81 examples/s]
Generating train split: 113216925 examples [2:06:00, 3374.38 examples/s]
Generating train split: 113217574 examples [2:06:00, 3825.82 examples/s]
Generating train split: 113218825 examples [2:06:00, 5326.53 examples/s]
Generating train split: 113219819 examples [2:06:00, 6202.14 examples/s]
Generating train split: 113220768 examples [2:06:00, 6906.33 examples/s]
Generating train split: 113221893 examples [2:06:00, 7547.22 examples/s]
Generating train split: 113222826 examples [2:06:00, 7833.87 examples/s]
Generating train split: 113223701 examples [2:06:01, 7399.59 examples/s]
Generating train split: 113224707 examples [2:06:01, 8044.95 examples/s]
Generating train split: 113225570 examples [2:06:01, 7129.70 examples/s]
Generating train split: 113226341 examples [2:06:01, 6017.47 examples/s]
Generating train split: 113227033 examples [2:06:01, 5973.14 examples/s]
Generating train split: 113227840 examples [2:06:01, 6411.81 examples/s]
Generating train split: 113228593 examples [2:06:01, 6547.56 examples/s]
Generating train split: 113230111 examples [2:06:01, 8714.86 examples/s]
Generating train split: 113231033 examples [2:06:02, 7384.01 examples/s]
Generating train split: 113231846 examples [2:06:02, 5318.23 examples/s]
Generating train split: 113232509 examples [2:06:02, 5391.42 examples/s]
Generating train split: 113233135 examples [2:06:02, 4891.88 examples/s]
Generating train split: 113233700 examples [2:06:02, 5034.16 examples/s]
Generating train split: 113234412 examples [2:06:02, 5475.36 examples/s]
Generating train split: 113235008 examples [2:06:03, 4462.42 examples/s]
Generating train split: 113235912 examples [2:06:03, 5462.80 examples/s]
Generating train split: 113236981 examples [2:06:03, 6678.75 examples/s]
Generating train split: 113238349 examples [2:06:03, 8418.21 examples/s]
Generating train split: 113239285 examples [2:06:03, 7277.26 examples/s]
Generating train split: 113240439 examples [2:06:03, 8301.74 examples/s]
Generating train split: 113241756 examples [2:06:03, 9540.63 examples/s]
Generating train split: 113243417 examples [2:06:03, 11415.53 examples/s]
Generating train split: 113244643 examples [2:06:04, 8607.20 examples/s] 
Generating train split: 113247124 examples [2:06:04, 12112.02 examples/s]
Generating train split: 113248546 examples [2:06:04, 10139.71 examples/s]
Generating train split: 113249761 examples [2:06:04, 10087.48 examples/s]
Generating train split: 113250906 examples [2:06:04, 8536.83 examples/s] 
Generating train split: 113251966 examples [2:06:04, 8950.45 examples/s]
Generating train split: 113252974 examples [2:06:04, 9144.02 examples/s]
Generating train split: 113253965 examples [2:06:05, 7747.20 examples/s]
Generating train split: 113254824 examples [2:06:05, 6620.96 examples/s]
Generating train split: 113255565 examples [2:06:05, 6414.56 examples/s]
Generating train split: 113256374 examples [2:06:05, 6561.90 examples/s]
Generating train split: 113257110 examples [2:06:05, 6731.40 examples/s]
Generating train split: 113258404 examples [2:06:05, 8241.91 examples/s]
Generating train split: 113259276 examples [2:06:05, 7680.53 examples/s]
Generating train split: 113265578 examples [2:06:05, 21864.85 examples/s]
Generating train split: 113273318 examples [2:06:06, 36747.45 examples/s]
Generating train split: 113278115 examples [2:06:06, 38030.00 examples/s]
Generating train split: 113282175 examples [2:06:06, 28450.93 examples/s]
Generating train split: 113289479 examples [2:06:06, 38399.99 examples/s]
Generating train split: 113297391 examples [2:06:06, 46993.66 examples/s]
Generating train split: 113302721 examples [2:06:06, 31242.72 examples/s]
Generating train split: 113308853 examples [2:06:07, 36886.43 examples/s]
Generating train split: 113314790 examples [2:06:07, 41580.67 examples/s]
Generating train split: 113319921 examples [2:06:07, 27873.95 examples/s]
Generating train split: 113323958 examples [2:06:07, 23232.56 examples/s]
Generating train split: 113327236 examples [2:06:08, 19093.94 examples/s]
Generating train split: 113335659 examples [2:06:08, 28909.97 examples/s]
Generating train split: 113344418 examples [2:06:08, 39305.35 examples/s]
Generating train split: 113350111 examples [2:06:08, 29529.18 examples/s]
Generating train split: 113354621 examples [2:06:08, 25729.97 examples/s]
Generating train split: 113358331 examples [2:06:09, 23868.16 examples/s]
Generating train split: 113361499 examples [2:06:09, 15421.53 examples/s]
Generating train split: 113363910 examples [2:06:09, 13006.60 examples/s]
Generating train split: 113365827 examples [2:06:09, 12771.33 examples/s]
Generating train split: 113367530 examples [2:06:10, 10266.84 examples/s]
Generating train split: 113368880 examples [2:06:10, 9882.49 examples/s] 
Generating train split: 113370080 examples [2:06:10, 8574.59 examples/s]
Generating train split: 113371089 examples [2:06:10, 8567.63 examples/s]
Generating train split: 113372049 examples [2:06:11, 6122.77 examples/s]
Generating train split: 113372801 examples [2:06:11, 5541.37 examples/s]
Generating train split: 113374305 examples [2:06:11, 6971.10 examples/s]
Generating train split: 113376580 examples [2:06:11, 9545.85 examples/s]
Generating train split: 113377826 examples [2:06:11, 9764.65 examples/s]
Generating train split: 113379152 examples [2:06:11, 10505.08 examples/s]
Generating train split: 113380356 examples [2:06:12, 7136.45 examples/s] 
Generating train split: 113381715 examples [2:06:12, 8306.82 examples/s]
Generating train split: 113382792 examples [2:06:12, 8209.30 examples/s]
Generating train split: 113383785 examples [2:06:12, 6924.89 examples/s]
Generating train split: 113384627 examples [2:06:12, 6598.97 examples/s]
Generating train split: 113385410 examples [2:06:12, 6828.14 examples/s]
Generating train split: 113386177 examples [2:06:12, 6259.45 examples/s]
Generating train split: 113387240 examples [2:06:13, 7233.70 examples/s]
Generating train split: 113388041 examples [2:06:13, 6186.75 examples/s]
Generating train split: 113389560 examples [2:06:13, 7958.52 examples/s]
Generating train split: 113390647 examples [2:06:13, 8577.83 examples/s]
Generating train split: 113392026 examples [2:06:13, 9887.00 examples/s]
Generating train split: 113393567 examples [2:06:13, 11030.55 examples/s]
Generating train split: 113394740 examples [2:06:13, 10902.58 examples/s]
Generating train split: 113396219 examples [2:06:13, 11525.80 examples/s]
Generating train split: 113397419 examples [2:06:14, 9494.88 examples/s] 
Generating train split: 113398443 examples [2:06:14, 6496.39 examples/s]
Generating train split: 113399262 examples [2:06:14, 6048.99 examples/s]
Generating train split: 113399991 examples [2:06:14, 6164.90 examples/s]
Generating train split: 113400711 examples [2:06:14, 6301.32 examples/s]
Generating train split: 113401407 examples [2:06:14, 5449.86 examples/s]
Generating train split: 113402016 examples [2:06:15, 3694.86 examples/s]
Generating train split: 113402505 examples [2:06:15, 3837.02 examples/s]
Generating train split: 113402975 examples [2:06:15, 3821.95 examples/s]
Generating train split: 113403419 examples [2:06:15, 3794.37 examples/s]
Generating train split: 113404920 examples [2:06:15, 6281.18 examples/s]
Generating train split: 113405724 examples [2:06:15, 6671.73 examples/s]
Generating train split: 113406491 examples [2:06:15, 6547.01 examples/s]
Generating train split: 113407288 examples [2:06:16, 6858.41 examples/s]
Generating train split: 113408029 examples [2:06:16, 5747.24 examples/s]
Generating train split: 113408668 examples [2:06:16, 5713.94 examples/s]
Generating train split: 113409291 examples [2:06:16, 5548.43 examples/s]
Generating train split: 113410254 examples [2:06:16, 6556.57 examples/s]
Generating train split: 113410953 examples [2:06:16, 6236.29 examples/s]
Generating train split: 113411609 examples [2:06:16, 4532.02 examples/s]
Generating train split: 113412150 examples [2:06:17, 4217.38 examples/s]
Generating train split: 113412720 examples [2:06:17, 4530.08 examples/s]
Generating train split: 113413228 examples [2:06:17, 4618.06 examples/s]
Generating train split: 113413939 examples [2:06:17, 5217.27 examples/s]
Generating train split: 113414955 examples [2:06:17, 6496.31 examples/s]
Generating train split: 113415661 examples [2:06:17, 5485.90 examples/s]
Generating train split: 113416330 examples [2:06:17, 5721.07 examples/s]
Generating train split: 113417174 examples [2:06:17, 6396.03 examples/s]
Generating train split: 113418696 examples [2:06:18, 8747.77 examples/s]
Generating train split: 113419636 examples [2:06:18, 5382.55 examples/s]
Generating train split: 113420375 examples [2:06:18, 5367.64 examples/s]
Generating train split: 113421056 examples [2:06:18, 4944.85 examples/s]
Generating train split: 113423970 examples [2:06:18, 9836.39 examples/s]
Generating train split: 113425276 examples [2:06:18, 10509.83 examples/s]
Generating train split: 113426570 examples [2:06:19, 7262.18 examples/s] 
Generating train split: 113427831 examples [2:06:19, 8245.17 examples/s]
Generating train split: 113429161 examples [2:06:19, 9279.81 examples/s]
Generating train split: 113430907 examples [2:06:19, 11127.06 examples/s]
Generating train split: 113432242 examples [2:06:19, 8731.28 examples/s] 
Generating train split: 113433345 examples [2:06:19, 9080.11 examples/s]
Generating train split: 113434963 examples [2:06:19, 10639.61 examples/s]
Generating train split: 113436720 examples [2:06:20, 12316.35 examples/s]
Generating train split: 113438111 examples [2:06:20, 9310.84 examples/s] 
Generating train split: 113439256 examples [2:06:20, 6265.46 examples/s]
Generating train split: 113440156 examples [2:06:20, 5385.01 examples/s]
Generating train split: 113440890 examples [2:06:21, 5462.60 examples/s]
Generating train split: 113441607 examples [2:06:21, 5759.94 examples/s]
Generating train split: 113442306 examples [2:06:21, 5520.70 examples/s]
Generating train split: 113442943 examples [2:06:21, 5511.52 examples/s]
Generating train split: 113443709 examples [2:06:21, 5980.66 examples/s]
Generating train split: 113445234 examples [2:06:21, 8193.55 examples/s]
Generating train split: 113447368 examples [2:06:21, 11542.55 examples/s]
Generating train split: 113448646 examples [2:06:21, 10118.31 examples/s]
Generating train split: 113449949 examples [2:06:21, 10813.72 examples/s]
Generating train split: 113451134 examples [2:06:22, 9300.48 examples/s] 
Generating train split: 113452162 examples [2:06:22, 8367.83 examples/s]
Generating train split: 113453230 examples [2:06:22, 8354.83 examples/s]
Generating train split: 113455621 examples [2:06:22, 12006.62 examples/s]
Generating train split: 113456967 examples [2:06:22, 10274.07 examples/s]
Generating train split: 113458139 examples [2:06:22, 7832.57 examples/s] 
Generating train split: 113459099 examples [2:06:23, 5537.42 examples/s]
Generating train split: 113462066 examples [2:06:23, 9320.37 examples/s]
Generating train split: 113463462 examples [2:06:23, 10080.72 examples/s]
Generating train split: 113464837 examples [2:06:23, 8608.93 examples/s] 
Generating train split: 113465989 examples [2:06:23, 8291.19 examples/s]
Generating train split: 113467022 examples [2:06:23, 8682.98 examples/s]
Generating train split: 113468360 examples [2:06:24, 9710.49 examples/s]
Generating train split: 113469489 examples [2:06:24, 8610.55 examples/s]
Generating train split: 113470847 examples [2:06:24, 9692.92 examples/s]
Generating train split: 113471936 examples [2:06:24, 9209.55 examples/s]
Generating train split: 113473032 examples [2:06:24, 9632.19 examples/s]
Generating train split: 113474066 examples [2:06:24, 7831.21 examples/s]
Generating train split: 113479826 examples [2:06:24, 19110.94 examples/s]
Generating train split: 113489262 examples [2:06:24, 37515.01 examples/s]
Generating train split: 113493744 examples [2:06:25, 28031.78 examples/s]
Generating train split: 113497403 examples [2:06:25, 20359.28 examples/s]
Generating train split: 113500304 examples [2:06:25, 20558.98 examples/s]
Generating train split: 113502975 examples [2:06:25, 16969.86 examples/s]
Generating train split: 113505172 examples [2:06:26, 15960.24 examples/s]
Generating train split: 113507101 examples [2:06:26, 16082.91 examples/s]
Generating train split: 113508949 examples [2:06:26, 12163.11 examples/s]
Generating train split: 113510451 examples [2:06:26, 8375.21 examples/s] 
Generating train split: 113511612 examples [2:06:27, 6956.26 examples/s]
Generating train split: 113512550 examples [2:06:27, 5680.43 examples/s]
Generating train split: 113513295 examples [2:06:27, 4596.81 examples/s]
Generating train split: 113514154 examples [2:06:27, 5053.06 examples/s]
Generating train split: 113514812 examples [2:06:28, 4392.97 examples/s]
Generating train split: 113515358 examples [2:06:28, 4161.18 examples/s]
Generating train split: 113517933 examples [2:06:28, 7765.56 examples/s]
Generating train split: 113519041 examples [2:06:28, 6754.32 examples/s]
Generating train split: 113520340 examples [2:06:28, 7850.58 examples/s]
Generating train split: 113522623 examples [2:06:28, 10917.71 examples/s]
Generating train split: 113524547 examples [2:06:28, 12797.72 examples/s]
Generating train split: 113526114 examples [2:06:29, 10284.73 examples/s]
Generating train split: 113527729 examples [2:06:29, 11494.77 examples/s]
Generating train split: 113529128 examples [2:06:29, 8882.53 examples/s] 
Generating train split: 113530270 examples [2:06:29, 8498.32 examples/s]
Generating train split: 113531289 examples [2:06:29, 6673.62 examples/s]
Generating train split: 113533109 examples [2:06:30, 8549.47 examples/s]
Generating train split: 113534178 examples [2:06:30, 6330.51 examples/s]
Generating train split: 113536096 examples [2:06:30, 8455.22 examples/s]
Generating train split: 113537267 examples [2:06:30, 9067.20 examples/s]
Generating train split: 113538438 examples [2:06:30, 8441.42 examples/s]
Generating train split: 113539472 examples [2:06:31, 6485.28 examples/s]
Generating train split: 113541319 examples [2:06:31, 8665.22 examples/s]
Generating train split: 113544687 examples [2:06:31, 13825.32 examples/s]
Generating train split: 113552130 examples [2:06:31, 27614.63 examples/s]
Generating train split: 113559187 examples [2:06:31, 38147.70 examples/s]
Generating train split: 113563758 examples [2:06:31, 23841.31 examples/s]
Generating train split: 113567335 examples [2:06:32, 12556.86 examples/s]
Generating train split: 113569997 examples [2:06:32, 10298.94 examples/s]
Generating train split: 113572048 examples [2:06:33, 9167.23 examples/s] 
Generating train split: 113573667 examples [2:06:33, 8578.79 examples/s]
Generating train split: 113575014 examples [2:06:33, 8679.53 examples/s]
Generating train split: 113576778 examples [2:06:33, 9893.56 examples/s]
Generating train split: 113578150 examples [2:06:33, 9145.77 examples/s]
Generating train split: 113579482 examples [2:06:34, 9843.35 examples/s]
Generating train split: 113580707 examples [2:06:34, 9876.27 examples/s]
Generating train split: 113582031 examples [2:06:34, 10424.98 examples/s]
Generating train split: 113583210 examples [2:06:34, 8325.95 examples/s] 
Generating train split: 113584194 examples [2:06:34, 8063.40 examples/s]
Generating train split: 113585103 examples [2:06:34, 8004.27 examples/s]
Generating train split: 113585974 examples [2:06:34, 7282.34 examples/s]
Generating train split: 113586753 examples [2:06:35, 6404.66 examples/s]
Generating train split: 113587773 examples [2:06:35, 7211.99 examples/s]
Generating train split: 113588612 examples [2:06:35, 7413.29 examples/s]
Generating train split: 113589414 examples [2:06:35, 7254.87 examples/s]
Generating train split: 113590238 examples [2:06:35, 7502.98 examples/s]
Generating train split: 113591603 examples [2:06:35, 9087.41 examples/s]
Generating train split: 113592558 examples [2:06:35, 7859.03 examples/s]
Generating train split: 113593398 examples [2:06:35, 7372.97 examples/s]
Generating train split: 113594753 examples [2:06:35, 8881.90 examples/s]
Generating train split: 113595706 examples [2:06:36, 8271.80 examples/s]
Generating train split: 113596593 examples [2:06:36, 7899.95 examples/s]
Generating train split: 113597814 examples [2:06:36, 8995.61 examples/s]
Generating train split: 113598854 examples [2:06:36, 9365.04 examples/s]
Generating train split: 113600280 examples [2:06:36, 10680.70 examples/s]
Generating train split: 113601388 examples [2:06:36, 8179.04 examples/s] 
Generating train split: 113602781 examples [2:06:36, 9512.63 examples/s]
Generating train split: 113603858 examples [2:06:36, 9186.82 examples/s]
Generating train split: 113605373 examples [2:06:37, 10518.24 examples/s]
Generating train split: 113607467 examples [2:06:37, 13156.25 examples/s]
Generating train split: 113608875 examples [2:06:37, 12738.25 examples/s]
Generating train split: 113610227 examples [2:06:37, 11681.06 examples/s]
Generating train split: 113617534 examples [2:06:37, 27444.80 examples/s]
Generating train split: 113626457 examples [2:06:37, 44018.39 examples/s]
Generating train split: 113631271 examples [2:06:37, 37802.39 examples/s]
Generating train split: 113635492 examples [2:06:37, 32877.81 examples/s]
Generating train split: 113639177 examples [2:06:38, 14884.89 examples/s]
Generating train split: 113641933 examples [2:06:39, 12278.65 examples/s]
Generating train split: 113644080 examples [2:06:39, 12436.07 examples/s]
Generating train split: 113645977 examples [2:06:39, 11585.49 examples/s]
Generating train split: 113647587 examples [2:06:39, 10172.88 examples/s]
Generating train split: 113649544 examples [2:06:39, 11549.07 examples/s]
Generating train split: 113651059 examples [2:06:39, 9955.28 examples/s] 
Generating train split: 113653184 examples [2:06:40, 11856.35 examples/s]
Generating train split: 113654704 examples [2:06:40, 12461.07 examples/s]
Generating train split: 113656331 examples [2:06:40, 13115.84 examples/s]
Generating train split: 113657855 examples [2:06:40, 9731.59 examples/s] 
Generating train split: 113659092 examples [2:06:40, 9262.49 examples/s]
Generating train split: 113661406 examples [2:06:40, 11945.40 examples/s]
Generating train split: 113662851 examples [2:06:40, 11439.66 examples/s]
Generating train split: 113664175 examples [2:06:41, 11706.03 examples/s]
Generating train split: 113665481 examples [2:06:41, 11586.99 examples/s]
Generating train split: 113667168 examples [2:06:41, 12868.37 examples/s]
Generating train split: 113668548 examples [2:06:41, 11413.98 examples/s]
Generating train split: 113670740 examples [2:06:41, 13942.13 examples/s]
Generating train split: 113672254 examples [2:06:41, 10677.93 examples/s]
Generating train split: 113674310 examples [2:06:41, 12455.65 examples/s]
Generating train split: 113675731 examples [2:06:41, 12516.56 examples/s]
Generating train split: 113677114 examples [2:06:42, 7888.12 examples/s] 
Generating train split: 113679581 examples [2:06:42, 10837.56 examples/s]
Generating train split: 113681077 examples [2:06:42, 7329.86 examples/s] 
Generating train split: 113682247 examples [2:06:43, 7013.11 examples/s]
Generating train split: 113683253 examples [2:06:43, 6538.86 examples/s]
Generating train split: 113684114 examples [2:06:43, 6155.25 examples/s]
Generating train split: 113685728 examples [2:06:43, 7905.36 examples/s]
Generating train split: 113686737 examples [2:06:43, 7623.71 examples/s]
Generating train split: 113687651 examples [2:06:43, 6569.45 examples/s]
Generating train split: 113689247 examples [2:06:43, 8363.46 examples/s]
Generating train split: 113690781 examples [2:06:44, 9617.85 examples/s]
Generating train split: 113691899 examples [2:06:44, 6980.69 examples/s]
Generating train split: 113693479 examples [2:06:44, 8644.72 examples/s]
Generating train split: 113694581 examples [2:06:44, 8118.45 examples/s]
Generating train split: 113695563 examples [2:06:44, 6846.60 examples/s]
Generating train split: 113696802 examples [2:06:44, 7861.24 examples/s]
Generating train split: 113697736 examples [2:06:45, 7640.47 examples/s]
Generating train split: 113698607 examples [2:06:45, 7753.81 examples/s]
Generating train split: 113699465 examples [2:06:45, 7892.59 examples/s]
Generating train split: 113700611 examples [2:06:45, 8656.86 examples/s]
Generating train split: 113701532 examples [2:06:45, 8546.44 examples/s]
Generating train split: 113704078 examples [2:06:45, 13067.74 examples/s]
Generating train split: 113712840 examples [2:06:45, 33667.44 examples/s]
Generating train split: 113716437 examples [2:06:46, 11923.86 examples/s]
Generating train split: 113719096 examples [2:06:47, 8250.08 examples/s] 
Generating train split: 113721084 examples [2:06:47, 6195.36 examples/s]
Generating train split: 113722571 examples [2:06:48, 5816.24 examples/s]
Generating train split: 113723749 examples [2:06:48, 5903.86 examples/s]
Generating train split: 113724764 examples [2:06:48, 5268.27 examples/s]
Generating train split: 113725578 examples [2:06:48, 5389.72 examples/s]
Generating train split: 113726336 examples [2:06:48, 5592.65 examples/s]
Generating train split: 113727072 examples [2:06:48, 4768.50 examples/s]
Generating train split: 113727673 examples [2:06:49, 4703.11 examples/s]
Generating train split: 113728228 examples [2:06:49, 4369.56 examples/s]
Generating train split: 113729067 examples [2:06:49, 5095.77 examples/s]
Generating train split: 113730177 examples [2:06:49, 6143.71 examples/s]
Generating train split: 113730881 examples [2:06:49, 5482.16 examples/s]
Generating train split: 113731502 examples [2:06:49, 5272.71 examples/s]
Generating train split: 113732476 examples [2:06:49, 6270.11 examples/s]
Generating train split: 113733495 examples [2:06:50, 7214.55 examples/s]
Generating train split: 113734292 examples [2:06:50, 5536.59 examples/s]
Generating train split: 113735724 examples [2:06:50, 7414.61 examples/s]
Generating train split: 113736811 examples [2:06:50, 8196.15 examples/s]
Generating train split: 113737753 examples [2:06:50, 5602.35 examples/s]
Generating train split: 113738511 examples [2:06:50, 5655.97 examples/s]
Generating train split: 113739951 examples [2:06:50, 7438.22 examples/s]
Generating train split: 113742133 examples [2:06:51, 10657.11 examples/s]
Generating train split: 113743437 examples [2:06:51, 9542.66 examples/s] 
Generating train split: 113745030 examples [2:06:51, 10989.09 examples/s]
Generating train split: 113746303 examples [2:06:51, 10657.46 examples/s]
Generating train split: 113747889 examples [2:06:51, 11883.49 examples/s]
Generating train split: 113749187 examples [2:06:51, 11518.77 examples/s]
Generating train split: 113750570 examples [2:06:51, 12046.74 examples/s]
Generating train split: 113752377 examples [2:06:51, 13666.36 examples/s]
Generating train split: 113753810 examples [2:06:52, 13010.05 examples/s]
Generating train split: 113755159 examples [2:06:52, 11010.59 examples/s]
Generating train split: 113756343 examples [2:06:52, 10143.02 examples/s]
Generating train split: 113757541 examples [2:06:52, 10562.53 examples/s]
Generating train split: 113758650 examples [2:06:52, 8375.46 examples/s] 
Generating train split: 113759600 examples [2:06:52, 7597.53 examples/s]
Generating train split: 113760440 examples [2:06:52, 6782.18 examples/s]
Generating train split: 113761221 examples [2:06:53, 6997.43 examples/s]
Generating train split: 113761982 examples [2:06:53, 6015.90 examples/s]
Generating train split: 113762648 examples [2:06:53, 5784.82 examples/s]
Generating train split: 113763585 examples [2:06:53, 6596.97 examples/s]
Generating train split: 113764504 examples [2:06:53, 7200.38 examples/s]
Generating train split: 113765380 examples [2:06:53, 7602.90 examples/s]
Generating train split: 113766660 examples [2:06:53, 8945.63 examples/s]
Generating train split: 113767868 examples [2:06:53, 9796.05 examples/s]
Generating train split: 113768890 examples [2:06:54, 9171.48 examples/s]
Generating train split: 113769839 examples [2:06:54, 8924.53 examples/s]
Generating train split: 113771096 examples [2:06:54, 9902.30 examples/s]
Generating train split: 113773051 examples [2:06:54, 12592.94 examples/s]
Generating train split: 113774705 examples [2:06:54, 13670.52 examples/s]
Generating train split: 113776114 examples [2:06:54, 10262.97 examples/s]
Generating train split: 113777670 examples [2:06:54, 11467.22 examples/s]
Generating train split: 113778959 examples [2:06:54, 10253.71 examples/s]
Generating train split: 113780843 examples [2:06:55, 12264.84 examples/s]
Generating train split: 113782207 examples [2:06:55, 8091.13 examples/s] 
Generating train split: 113783291 examples [2:06:55, 8050.22 examples/s]
Generating train split: 113784983 examples [2:06:55, 9560.80 examples/s]
Generating train split: 113786123 examples [2:06:55, 9520.22 examples/s]
Generating train split: 113787271 examples [2:06:55, 9459.01 examples/s]
Generating train split: 113788310 examples [2:06:56, 8401.12 examples/s]
Generating train split: 113789237 examples [2:06:56, 7715.30 examples/s]
Generating train split: 113790623 examples [2:06:56, 8537.53 examples/s]
Generating train split: 113791527 examples [2:06:56, 7762.71 examples/s]
Generating train split: 113792391 examples [2:06:56, 7962.92 examples/s]
Generating train split: 113794151 examples [2:06:56, 10339.36 examples/s]
Generating train split: 113795272 examples [2:06:56, 10218.38 examples/s]
Generating train split: 113796350 examples [2:06:56, 7604.78 examples/s] 
Generating train split: 113797244 examples [2:06:57, 6725.18 examples/s]
Generating train split: 113798021 examples [2:06:57, 4418.27 examples/s]
Generating train split: 113799034 examples [2:06:57, 5322.85 examples/s]
Generating train split: 113799925 examples [2:06:57, 5978.86 examples/s]
Generating train split: 113800701 examples [2:06:58, 4753.94 examples/s]
Generating train split: 113801592 examples [2:06:58, 5506.58 examples/s]
Generating train split: 113802307 examples [2:06:58, 5799.84 examples/s]
Generating train split: 113803020 examples [2:06:58, 5564.09 examples/s]
Generating train split: 113804113 examples [2:06:58, 6785.46 examples/s]
Generating train split: 113805331 examples [2:06:58, 8107.66 examples/s]
Generating train split: 113806239 examples [2:06:58, 6748.25 examples/s]
Generating train split: 113807027 examples [2:06:58, 6022.88 examples/s]
Generating train split: 113815152 examples [2:06:59, 22608.95 examples/s]
Generating train split: 113824303 examples [2:06:59, 39107.07 examples/s]
Generating train split: 113829095 examples [2:06:59, 41171.03 examples/s]
Generating train split: 113833868 examples [2:06:59, 22122.99 examples/s]
Generating train split: 113837534 examples [2:07:00, 15715.93 examples/s]
Generating train split: 113840346 examples [2:07:00, 14572.92 examples/s]
Generating train split: 113842655 examples [2:07:00, 13821.81 examples/s]
Generating train split: 113845378 examples [2:07:00, 15769.44 examples/s]
Generating train split: 113848317 examples [2:07:00, 18109.84 examples/s]
Generating train split: 113853075 examples [2:07:00, 23917.77 examples/s]
Generating train split: 113857868 examples [2:07:00, 29189.62 examples/s]
Generating train split: 113863595 examples [2:07:01, 35892.20 examples/s]
Generating train split: 113869817 examples [2:07:01, 42559.11 examples/s]
Generating train split: 113875865 examples [2:07:01, 47333.09 examples/s]
Generating train split: 113882488 examples [2:07:01, 52531.65 examples/s]
Generating train split: 113889053 examples [2:07:01, 56209.52 examples/s]
Generating train split: 113895553 examples [2:07:01, 58733.70 examples/s]
Generating train split: 113902144 examples [2:07:01, 60813.68 examples/s]
Generating train split: 113909670 examples [2:07:01, 65031.50 examples/s]
Generating train split: 113917631 examples [2:07:01, 69332.29 examples/s]
Generating train split: 113925116 examples [2:07:01, 70965.55 examples/s]
Generating train split: 113933290 examples [2:07:02, 74161.42 examples/s]
Generating train split: 113940756 examples [2:07:02, 72237.05 examples/s]
Generating train split: 113948035 examples [2:07:02, 71383.17 examples/s]
Generating train split: 113955210 examples [2:07:02, 66357.49 examples/s]
Generating train split: 113961932 examples [2:07:02, 64061.66 examples/s]
Generating train split: 113968413 examples [2:07:02, 62283.80 examples/s]
Generating train split: 113974698 examples [2:07:02, 60168.55 examples/s]
Generating train split: 113980753 examples [2:07:02, 57709.58 examples/s]
Generating train split: 113986559 examples [2:07:02, 56617.00 examples/s]
Generating train split: 113992239 examples [2:07:03, 48772.84 examples/s]
Generating train split: 113997293 examples [2:07:03, 46721.68 examples/s]
Generating train split: 114002092 examples [2:07:03, 46205.54 examples/s]
Generating train split: 114006802 examples [2:07:03, 44032.51 examples/s]
Generating train split: 114011263 examples [2:07:03, 39704.85 examples/s]
Generating train split: 114015321 examples [2:07:03, 32577.80 examples/s]
Generating train split: 114018806 examples [2:07:03, 28807.98 examples/s]
Generating train split: 114021891 examples [2:07:04, 27560.87 examples/s]
Generating train split: 114024995 examples [2:07:04, 28306.72 examples/s]
Generating train split: 114027947 examples [2:07:04, 24887.48 examples/s]
Generating train split: 114030565 examples [2:07:04, 22945.35 examples/s]
Generating train split: 114032948 examples [2:07:04, 21251.48 examples/s]
Generating train split: 114036000 examples [2:07:04, 23267.28 examples/s]
Generating train split: 114038857 examples [2:07:04, 23842.01 examples/s]
Generating train split: 114042962 examples [2:07:04, 28172.45 examples/s]
Generating train split: 114045902 examples [2:07:05, 25838.47 examples/s]
Generating train split: 114048600 examples [2:07:05, 23017.74 examples/s]
Generating train split: 114051017 examples [2:07:05, 21826.22 examples/s]
Generating train split: 114053606 examples [2:07:05, 22814.95 examples/s]
Generating train split: 114056266 examples [2:07:05, 23792.42 examples/s]
Generating train split: 114058716 examples [2:07:05, 19036.57 examples/s]
Generating train split: 114060807 examples [2:07:05, 16693.52 examples/s]
Generating train split: 114062636 examples [2:07:06, 16647.80 examples/s]
Generating train split: 114064419 examples [2:07:06, 10888.13 examples/s]
Generating train split: 114073301 examples [2:07:06, 24851.92 examples/s]
Generating train split: 114082944 examples [2:07:06, 38739.21 examples/s]
Generating train split: 114088155 examples [2:07:07, 23570.35 examples/s]
Generating train split: 114092156 examples [2:07:07, 23316.90 examples/s]
Generating train split: 114095643 examples [2:07:07, 19281.07 examples/s]
Generating train split: 114098437 examples [2:07:07, 15991.16 examples/s]
Generating train split: 114100684 examples [2:07:07, 15708.03 examples/s]
Generating train split: 114102701 examples [2:07:08, 11085.19 examples/s]
Generating train split: 114104272 examples [2:07:08, 9011.61 examples/s] 
Generating train split: 114105660 examples [2:07:08, 9626.81 examples/s]
Generating train split: 114106948 examples [2:07:08, 9705.25 examples/s]
Generating train split: 114108156 examples [2:07:09, 9890.91 examples/s]
Generating train split: 114110972 examples [2:07:09, 13472.20 examples/s]
Generating train split: 114112630 examples [2:07:09, 10049.27 examples/s]
Generating train split: 114113969 examples [2:07:09, 10444.02 examples/s]
Generating train split: 114115451 examples [2:07:09, 11330.57 examples/s]
Generating train split: 114116804 examples [2:07:09, 7267.34 examples/s] 
Generating train split: 114118261 examples [2:07:10, 8466.39 examples/s]
Generating train split: 114119453 examples [2:07:10, 9121.98 examples/s]
Generating train split: 114120635 examples [2:07:10, 6979.91 examples/s]
Generating train split: 114122013 examples [2:07:10, 8025.91 examples/s]
Generating train split: 114123061 examples [2:07:10, 6088.22 examples/s]
Generating train split: 114124115 examples [2:07:10, 6844.14 examples/s]
Generating train split: 114125022 examples [2:07:11, 7157.94 examples/s]
Generating train split: 114125903 examples [2:07:11, 6030.21 examples/s]
Generating train split: 114126641 examples [2:07:11, 5302.67 examples/s]
Generating train split: 114127276 examples [2:07:11, 4420.75 examples/s]
Generating train split: 114127808 examples [2:07:11, 4493.14 examples/s]
Generating train split: 114128321 examples [2:07:11, 4586.57 examples/s]
Generating train split: 114128830 examples [2:07:12, 3399.98 examples/s]
Generating train split: 114129251 examples [2:07:12, 3138.17 examples/s]
Generating train split: 114129617 examples [2:07:12, 3137.85 examples/s]
Generating train split: 114130456 examples [2:07:12, 4230.23 examples/s]
Generating train split: 114131014 examples [2:07:12, 4520.57 examples/s]
Generating train split: 114131988 examples [2:07:12, 5790.54 examples/s]
Generating train split: 114134029 examples [2:07:12, 9584.41 examples/s]
Generating train split: 114135100 examples [2:07:13, 8010.12 examples/s]
Generating train split: 114136056 examples [2:07:13, 8360.75 examples/s]
Generating train split: 114136986 examples [2:07:13, 8530.51 examples/s]
Generating train split: 114138463 examples [2:07:13, 10136.32 examples/s]
Generating train split: 114139545 examples [2:07:13, 7401.14 examples/s] 
Generating train split: 114140435 examples [2:07:13, 6938.25 examples/s]
Generating train split: 114142040 examples [2:07:13, 8839.63 examples/s]
Generating train split: 114143062 examples [2:07:14, 6522.18 examples/s]
Generating train split: 114143902 examples [2:07:14, 6067.33 examples/s]
Generating train split: 114144638 examples [2:07:14, 6041.54 examples/s]
Generating train split: 114152607 examples [2:07:14, 21594.54 examples/s]
Generating train split: 114161518 examples [2:07:14, 37241.48 examples/s]
Generating train split: 114166204 examples [2:07:14, 31853.49 examples/s]
Generating train split: 114170193 examples [2:07:15, 21334.33 examples/s]
Generating train split: 114173320 examples [2:07:15, 20941.35 examples/s]
Generating train split: 114176100 examples [2:07:15, 18643.86 examples/s]
Generating train split: 114178457 examples [2:07:15, 16561.00 examples/s]
Generating train split: 114180798 examples [2:07:15, 17765.13 examples/s]
Generating train split: 114182900 examples [2:07:16, 12040.81 examples/s]
Generating train split: 114184555 examples [2:07:16, 10575.06 examples/s]
Generating train split: 114186161 examples [2:07:16, 11423.35 examples/s]
Generating train split: 114187616 examples [2:07:16, 10601.26 examples/s]
Generating train split: 114189515 examples [2:07:16, 12127.40 examples/s]
Generating train split: 114190954 examples [2:07:17, 11277.26 examples/s]
Generating train split: 114192243 examples [2:07:17, 11441.98 examples/s]
Generating train split: 114194122 examples [2:07:17, 13064.30 examples/s]
Generating train split: 114195567 examples [2:07:17, 12179.23 examples/s]
Generating train split: 114197565 examples [2:07:17, 13916.24 examples/s]
Generating train split: 114199069 examples [2:07:17, 12785.77 examples/s]
Generating train split: 114200673 examples [2:07:17, 13488.34 examples/s]
Generating train split: 114202095 examples [2:07:18, 8562.66 examples/s] 
Generating train split: 114203442 examples [2:07:18, 9463.77 examples/s]
Generating train split: 114205063 examples [2:07:18, 10817.32 examples/s]
Generating train split: 114206372 examples [2:07:18, 9035.78 examples/s] 
Generating train split: 114207477 examples [2:07:18, 8665.28 examples/s]
Generating train split: 114215200 examples [2:07:18, 23342.26 examples/s]
Generating train split: 114222694 examples [2:07:18, 35092.72 examples/s]
Generating train split: 114226975 examples [2:07:18, 31432.70 examples/s]
Generating train split: 114230720 examples [2:07:19, 18744.62 examples/s]
Generating train split: 114239095 examples [2:07:19, 29083.26 examples/s]
Generating train split: 114247069 examples [2:07:19, 38323.59 examples/s]
Generating train split: 114252585 examples [2:07:20, 22787.32 examples/s]
Generating train split: 114256782 examples [2:07:20, 16290.36 examples/s]
Generating train split: 114264275 examples [2:07:20, 22925.69 examples/s]
Generating train split: 114273226 examples [2:07:20, 32191.96 examples/s]
Generating train split: 114279061 examples [2:07:21, 27733.72 examples/s]
Generating train split: 114283739 examples [2:07:21, 20272.19 examples/s]
Generating train split: 114287334 examples [2:07:21, 15863.44 examples/s]
Generating train split: 114290109 examples [2:07:22, 15315.55 examples/s]
Generating train split: 114292450 examples [2:07:22, 12392.73 examples/s]
Generating train split: 114294296 examples [2:07:22, 11793.65 examples/s]
Generating train split: 114295876 examples [2:07:22, 11113.63 examples/s]
Generating train split: 114297638 examples [2:07:22, 12049.12 examples/s]
Generating train split: 114299122 examples [2:07:23, 11159.14 examples/s]
Generating train split: 114300424 examples [2:07:23, 9211.36 examples/s] 
Generating train split: 114301515 examples [2:07:23, 8406.76 examples/s]
Generating train split: 114303171 examples [2:07:23, 9833.84 examples/s]
Generating train split: 114304318 examples [2:07:23, 7499.86 examples/s]
Generating train split: 114305553 examples [2:07:24, 8331.62 examples/s]
Generating train split: 114306581 examples [2:07:24, 7314.78 examples/s]
Generating train split: 114307736 examples [2:07:24, 8053.07 examples/s]
Generating train split: 114309458 examples [2:07:24, 10016.00 examples/s]
Generating train split: 114310630 examples [2:07:24, 10376.81 examples/s]
Generating train split: 114311803 examples [2:07:24, 7224.13 examples/s] 
Generating train split: 114313329 examples [2:07:24, 8768.98 examples/s]
Generating train split: 114314448 examples [2:07:25, 8258.52 examples/s]
Generating train split: 114315476 examples [2:07:25, 8666.10 examples/s]
Generating train split: 114316481 examples [2:07:25, 7652.45 examples/s]
Generating train split: 114318109 examples [2:07:25, 9555.90 examples/s]
Generating train split: 114319502 examples [2:07:25, 10608.51 examples/s]
Generating train split: 114320699 examples [2:07:25, 6465.49 examples/s] 
Generating train split: 114321630 examples [2:07:26, 6745.88 examples/s]
Generating train split: 114322516 examples [2:07:26, 4298.09 examples/s]
Generating train split: 114323200 examples [2:07:26, 3897.30 examples/s]
Generating train split: 114323967 examples [2:07:26, 4419.44 examples/s]
Generating train split: 114324843 examples [2:07:26, 5167.11 examples/s]
Generating train split: 114325538 examples [2:07:27, 4606.89 examples/s]
Generating train split: 114326133 examples [2:07:27, 4641.68 examples/s]
Generating train split: 114326708 examples [2:07:27, 4740.69 examples/s]
Generating train split: 114327383 examples [2:07:27, 5174.99 examples/s]
Generating train split: 114327970 examples [2:07:27, 4351.02 examples/s]
Generating train split: 114329501 examples [2:07:27, 6740.14 examples/s]
Generating train split: 114330307 examples [2:07:28, 5463.17 examples/s]
Generating train split: 114330994 examples [2:07:28, 4249.54 examples/s]
Generating train split: 114331918 examples [2:07:28, 5147.70 examples/s]
Generating train split: 114332586 examples [2:07:28, 4429.04 examples/s]
Generating train split: 114333536 examples [2:07:28, 5394.43 examples/s]
Generating train split: 114335523 examples [2:07:28, 8252.16 examples/s]
Generating train split: 114336516 examples [2:07:29, 6810.70 examples/s]
Generating train split: 114337960 examples [2:07:29, 8376.80 examples/s]
Generating train split: 114339743 examples [2:07:29, 10520.04 examples/s]
Generating train split: 114348310 examples [2:07:29, 28901.97 examples/s]
Generating train split: 114355580 examples [2:07:29, 40221.79 examples/s]
Generating train split: 114360170 examples [2:07:29, 23586.65 examples/s]
Generating train split: 114363740 examples [2:07:30, 13032.87 examples/s]
Generating train split: 114366415 examples [2:07:31, 8919.24 examples/s] 
Generating train split: 114368417 examples [2:07:31, 7560.08 examples/s]
Generating train split: 114369949 examples [2:07:31, 7376.18 examples/s]
Generating train split: 114371215 examples [2:07:31, 7733.14 examples/s]
Generating train split: 114372412 examples [2:07:32, 7751.09 examples/s]
Generating train split: 114373699 examples [2:07:32, 8463.05 examples/s]
Generating train split: 114374837 examples [2:07:32, 8468.84 examples/s]
Generating train split: 114375893 examples [2:07:32, 6552.66 examples/s]
Generating train split: 114376871 examples [2:07:32, 7077.83 examples/s]
Generating train split: 114377760 examples [2:07:33, 5240.59 examples/s]
Generating train split: 114378464 examples [2:07:33, 5476.45 examples/s]
Generating train split: 114379442 examples [2:07:33, 6272.28 examples/s]
Generating train split: 114381175 examples [2:07:33, 8575.79 examples/s]
Generating train split: 114382239 examples [2:07:33, 8761.17 examples/s]
Generating train split: 114383262 examples [2:07:33, 7434.68 examples/s]
Generating train split: 114384677 examples [2:07:33, 8895.07 examples/s]
Generating train split: 114385712 examples [2:07:33, 8823.13 examples/s]
Generating train split: 114386702 examples [2:07:34, 5765.85 examples/s]
Generating train split: 114387480 examples [2:07:34, 6003.25 examples/s]
Generating train split: 114388423 examples [2:07:34, 6665.09 examples/s]
Generating train split: 114389227 examples [2:07:34, 5617.09 examples/s]
Generating train split: 114390329 examples [2:07:34, 6721.51 examples/s]
Generating train split: 114391134 examples [2:07:34, 6149.34 examples/s]
Generating train split: 114392446 examples [2:07:34, 7612.12 examples/s]
Generating train split: 114393330 examples [2:07:35, 6110.96 examples/s]
Generating train split: 114394141 examples [2:07:35, 6368.40 examples/s]
Generating train split: 114396005 examples [2:07:35, 9119.86 examples/s]
Generating train split: 114397645 examples [2:07:35, 10884.56 examples/s]
Generating train split: 114398896 examples [2:07:35, 10413.85 examples/s]
Generating train split: 114400551 examples [2:07:35, 11930.45 examples/s]
Generating train split: 114401866 examples [2:07:35, 9215.96 examples/s] 
Generating train split: 114408676 examples [2:07:36, 22261.98 examples/s]
Generating train split: 114416316 examples [2:07:36, 35268.15 examples/s]
Generating train split: 114420574 examples [2:07:36, 29259.74 examples/s]
Generating train split: 114424175 examples [2:07:36, 15144.62 examples/s]
Generating train split: 114426887 examples [2:07:37, 11438.20 examples/s]
Generating train split: 114434850 examples [2:07:37, 19402.77 examples/s]
Generating train split: 114443455 examples [2:07:37, 28934.04 examples/s]
Generating train split: 114448733 examples [2:07:37, 24553.95 examples/s]
Generating train split: 114452958 examples [2:07:38, 24584.34 examples/s]
Generating train split: 114456655 examples [2:07:38, 20373.91 examples/s]
Generating train split: 114459954 examples [2:07:38, 22295.32 examples/s]
Generating train split: 114463027 examples [2:07:38, 20796.08 examples/s]
Generating train split: 114465694 examples [2:07:38, 17750.45 examples/s]
Generating train split: 114474219 examples [2:07:38, 29531.55 examples/s]
Generating train split: 114481786 examples [2:07:39, 38550.44 examples/s]
Generating train split: 114486880 examples [2:07:39, 30788.13 examples/s]
Generating train split: 114491046 examples [2:07:39, 20238.34 examples/s]
Generating train split: 114494254 examples [2:07:39, 18571.29 examples/s]
Generating train split: 114501150 examples [2:07:40, 26026.08 examples/s]
Generating train split: 114508319 examples [2:07:40, 33733.40 examples/s]
Generating train split: 114513140 examples [2:07:40, 24561.02 examples/s]
Generating train split: 114516928 examples [2:07:40, 20195.39 examples/s]
Generating train split: 114523016 examples [2:07:40, 26184.80 examples/s]
Generating train split: 114530871 examples [2:07:41, 35281.40 examples/s]
Generating train split: 114535997 examples [2:07:41, 30455.64 examples/s]
Generating train split: 114540242 examples [2:07:41, 26754.87 examples/s]
Generating train split: 114543792 examples [2:07:41, 19855.08 examples/s]
Generating train split: 114546636 examples [2:07:41, 21145.46 examples/s]
Generating train split: 114549454 examples [2:07:42, 21005.19 examples/s]
Generating train split: 114552045 examples [2:07:42, 14360.67 examples/s]
Generating train split: 114554076 examples [2:07:42, 12255.47 examples/s]
Generating train split: 114555735 examples [2:07:42, 11540.34 examples/s]
Generating train split: 114557170 examples [2:07:43, 10657.15 examples/s]
Generating train split: 114559441 examples [2:07:43, 12676.97 examples/s]
Generating train split: 114561543 examples [2:07:43, 14274.69 examples/s]
Generating train split: 114563256 examples [2:07:43, 12512.14 examples/s]
Generating train split: 114564986 examples [2:07:43, 13479.94 examples/s]
Generating train split: 114566535 examples [2:07:43, 12886.07 examples/s]
Generating train split: 114567980 examples [2:07:43, 13190.60 examples/s]
Generating train split: 114569404 examples [2:07:44, 10076.06 examples/s]
Generating train split: 114571194 examples [2:07:44, 11709.58 examples/s]
Generating train split: 114574670 examples [2:07:44, 17008.21 examples/s]
Generating train split: 114577262 examples [2:07:44, 19164.32 examples/s]
Generating train split: 114579439 examples [2:07:44, 11789.64 examples/s]
Generating train split: 114581880 examples [2:07:44, 14032.61 examples/s]
Generating train split: 114583790 examples [2:07:45, 9051.74 examples/s] 
Generating train split: 114585266 examples [2:07:45, 8805.19 examples/s]
Generating train split: 114586538 examples [2:07:45, 9218.51 examples/s]
Generating train split: 114588766 examples [2:07:45, 11598.70 examples/s]
Generating train split: 114590302 examples [2:07:45, 12158.36 examples/s]
Generating train split: 114593274 examples [2:07:45, 15930.19 examples/s]
Generating train split: 114595175 examples [2:07:45, 15725.45 examples/s]
Generating train split: 114596966 examples [2:07:46, 13457.69 examples/s]
Generating train split: 114598515 examples [2:07:46, 10955.14 examples/s]
Generating train split: 114606576 examples [2:07:46, 25006.23 examples/s]
Generating train split: 114615182 examples [2:07:46, 38654.96 examples/s]
Generating train split: 114620089 examples [2:07:46, 27342.08 examples/s]
Generating train split: 114624004 examples [2:07:47, 13463.04 examples/s]
Generating train split: 114626901 examples [2:07:48, 11220.40 examples/s]
Generating train split: 114629142 examples [2:07:48, 10496.64 examples/s]
Generating train split: 114632153 examples [2:07:48, 12598.52 examples/s]
Generating train split: 114634282 examples [2:07:48, 11528.39 examples/s]
Generating train split: 114636032 examples [2:07:48, 11773.81 examples/s]
Generating train split: 114637652 examples [2:07:48, 11155.29 examples/s]
Generating train split: 114639066 examples [2:07:49, 10767.73 examples/s]
Generating train split: 114640343 examples [2:07:49, 11010.95 examples/s]
Generating train split: 114641596 examples [2:07:49, 9843.89 examples/s] 
Generating train split: 114642694 examples [2:07:49, 8402.83 examples/s]
Generating train split: 114643627 examples [2:07:49, 6784.75 examples/s]
Generating train split: 114644400 examples [2:07:49, 6813.12 examples/s]
Generating train split: 114645570 examples [2:07:50, 7768.56 examples/s]
Generating train split: 114646447 examples [2:07:50, 7872.15 examples/s]
Generating train split: 114647496 examples [2:07:50, 8411.95 examples/s]
Generating train split: 114648836 examples [2:07:50, 9604.73 examples/s]
Generating train split: 114650615 examples [2:07:50, 11745.42 examples/s]
Generating train split: 114651869 examples [2:07:50, 10982.03 examples/s]
Generating train split: 114654202 examples [2:07:50, 14075.75 examples/s]
Generating train split: 114656989 examples [2:07:50, 17757.65 examples/s]
Generating train split: 114658858 examples [2:07:50, 17980.84 examples/s]
Generating train split: 114660723 examples [2:07:50, 17968.48 examples/s]
Generating train split: 114662564 examples [2:07:51, 13621.32 examples/s]
Generating train split: 114664109 examples [2:07:51, 10804.46 examples/s]
Generating train split: 114665658 examples [2:07:51, 11464.34 examples/s]
Generating train split: 114666976 examples [2:07:51, 9213.83 examples/s] 
Generating train split: 114668071 examples [2:07:51, 9401.94 examples/s]
Generating train split: 114669796 examples [2:07:51, 11108.02 examples/s]
Generating train split: 114671069 examples [2:07:52, 11104.92 examples/s]
Generating train split: 114672288 examples [2:07:52, 10095.88 examples/s]
Generating train split: 114673545 examples [2:07:52, 10682.97 examples/s]
Generating train split: 114674956 examples [2:07:52, 11502.75 examples/s]
Generating train split: 114676181 examples [2:07:52, 10616.23 examples/s]
Generating train split: 114677919 examples [2:07:52, 12341.21 examples/s]
Generating train split: 114679625 examples [2:07:52, 13576.21 examples/s]
Generating train split: 114681466 examples [2:07:52, 14909.47 examples/s]
Generating train split: 114683023 examples [2:07:53, 13012.23 examples/s]
Generating train split: 114684405 examples [2:07:53, 13100.72 examples/s]
Generating train split: 114685778 examples [2:07:53, 10692.55 examples/s]
Generating train split: 114686952 examples [2:07:53, 8963.44 examples/s] 
Generating train split: 114689129 examples [2:07:53, 11689.89 examples/s]
Generating train split: 114690475 examples [2:07:53, 11206.45 examples/s]
Generating train split: 114692080 examples [2:07:53, 12343.23 examples/s]
Generating train split: 114693432 examples [2:07:54, 10665.91 examples/s]
Generating train split: 114694909 examples [2:07:54, 11582.25 examples/s]
Generating train split: 114696172 examples [2:07:54, 10762.19 examples/s]
Generating train split: 114697332 examples [2:07:54, 9810.67 examples/s] 
Generating train split: 114698374 examples [2:07:54, 9603.23 examples/s]
Generating train split: 114701275 examples [2:07:54, 14315.57 examples/s]
Generating train split: 114702831 examples [2:07:54, 14368.02 examples/s]
Generating train split: 114704358 examples [2:07:54, 13802.31 examples/s]
Generating train split: 114705804 examples [2:07:55, 12045.05 examples/s]
Generating train split: 114707356 examples [2:07:55, 12842.20 examples/s]
Generating train split: 114708710 examples [2:07:55, 12274.69 examples/s]
Generating train split: 114710041 examples [2:07:55, 12533.76 examples/s]
Generating train split: 114711342 examples [2:07:55, 10562.58 examples/s]
Generating train split: 114712629 examples [2:07:55, 11123.68 examples/s]
Generating train split: 114714932 examples [2:07:55, 14183.61 examples/s]
Generating train split: 114716449 examples [2:07:55, 11920.62 examples/s]
Generating train split: 114717773 examples [2:07:56, 11848.16 examples/s]
Generating train split: 114720221 examples [2:07:56, 15002.10 examples/s]
Generating train split: 114721854 examples [2:07:56, 14984.46 examples/s]
Generating train split: 114723445 examples [2:07:56, 12028.02 examples/s]
Generating train split: 114725541 examples [2:07:56, 14039.45 examples/s]
Generating train split: 114727910 examples [2:07:56, 16427.88 examples/s]
Generating train split: 114729720 examples [2:07:56, 12817.09 examples/s]
Generating train split: 114732423 examples [2:07:56, 15954.22 examples/s]
Generating train split: 114734290 examples [2:07:57, 15610.54 examples/s]
Generating train split: 114736049 examples [2:07:57, 11750.03 examples/s]
Generating train split: 114737494 examples [2:07:57, 11679.72 examples/s]
Generating train split: 114738841 examples [2:07:57, 10235.65 examples/s]
Generating train split: 114740016 examples [2:07:57, 9236.20 examples/s] 
Generating train split: 114741221 examples [2:07:57, 9815.42 examples/s]
Generating train split: 114742300 examples [2:07:58, 9085.27 examples/s]
Generating train split: 114743279 examples [2:07:58, 8071.41 examples/s]
Generating train split: 114745640 examples [2:07:58, 11497.46 examples/s]
Generating train split: 114746963 examples [2:07:58, 11583.87 examples/s]
Generating train split: 114748236 examples [2:07:58, 8540.27 examples/s] 
Generating train split: 114749472 examples [2:07:58, 9269.04 examples/s]
Generating train split: 114750826 examples [2:07:58, 10075.18 examples/s]
Generating train split: 114752202 examples [2:07:58, 10952.65 examples/s]
Generating train split: 114753753 examples [2:07:59, 12000.43 examples/s]
Generating train split: 114755059 examples [2:07:59, 12021.77 examples/s]
Generating train split: 114757033 examples [2:07:59, 14110.93 examples/s]
Generating train split: 114758519 examples [2:07:59, 12165.97 examples/s]
Generating train split: 114759829 examples [2:07:59, 8659.97 examples/s] 
Generating train split: 114761401 examples [2:07:59, 10044.91 examples/s]
Generating train split: 114762620 examples [2:08:00, 8102.16 examples/s] 
Generating train split: 114763625 examples [2:08:00, 8251.01 examples/s]
Generating train split: 114764600 examples [2:08:00, 7940.68 examples/s]
Generating train split: 114766170 examples [2:08:00, 9528.68 examples/s]
Generating train split: 114767248 examples [2:08:00, 7655.43 examples/s]
Generating train split: 114768142 examples [2:08:00, 7406.30 examples/s]
Generating train split: 114768976 examples [2:08:00, 7360.14 examples/s]
Generating train split: 114769771 examples [2:08:01, 6642.75 examples/s]
Generating train split: 114770588 examples [2:08:01, 6928.96 examples/s]
Generating train split: 114771323 examples [2:08:01, 6778.90 examples/s]
Generating train split: 114772029 examples [2:08:01, 5883.27 examples/s]
Generating train split: 114772652 examples [2:08:01, 5510.93 examples/s]
Generating train split: 114774365 examples [2:08:01, 8234.85 examples/s]
Generating train split: 114776166 examples [2:08:01, 10695.31 examples/s]
Generating train split: 114777692 examples [2:08:01, 11394.13 examples/s]
Generating train split: 114779540 examples [2:08:01, 13259.61 examples/s]
Generating train split: 114780951 examples [2:08:02, 12987.80 examples/s]
Generating train split: 114782303 examples [2:08:02, 10884.32 examples/s]
Generating train split: 114783591 examples [2:08:02, 11335.82 examples/s]
Generating train split: 114784804 examples [2:08:02, 11530.76 examples/s]
Generating train split: 114786838 examples [2:08:02, 13900.70 examples/s]
Generating train split: 114789560 examples [2:08:02, 17372.27 examples/s]
Generating train split: 114791357 examples [2:08:02, 11443.53 examples/s]
Generating train split: 114792816 examples [2:08:03, 12067.10 examples/s]
Generating train split: 114794638 examples [2:08:03, 13470.95 examples/s]
Generating train split: 114796199 examples [2:08:03, 11931.89 examples/s]
Generating train split: 114797847 examples [2:08:03, 12923.19 examples/s]
Generating train split: 114799289 examples [2:08:03, 12632.68 examples/s]
Generating train split: 114801503 examples [2:08:03, 15017.40 examples/s]
Generating train split: 114803130 examples [2:08:03, 13683.18 examples/s]
Generating train split: 114805674 examples [2:08:03, 16554.55 examples/s]
Generating train split: 114807453 examples [2:08:04, 16481.11 examples/s]
Generating train split: 114809380 examples [2:08:04, 17189.16 examples/s]
Generating train split: 114811172 examples [2:08:04, 11613.95 examples/s]
Generating train split: 114812616 examples [2:08:04, 12150.96 examples/s]
Generating train split: 114814165 examples [2:08:04, 12868.87 examples/s]
Generating train split: 114815629 examples [2:08:04, 11434.08 examples/s]
Generating train split: 114823422 examples [2:08:04, 26853.33 examples/s]
Generating train split: 114832418 examples [2:08:04, 42550.68 examples/s]
Generating train split: 114837389 examples [2:08:05, 33378.59 examples/s]
Generating train split: 114841532 examples [2:08:05, 19964.33 examples/s]
Generating train split: 114849660 examples [2:08:05, 29233.73 examples/s]
Generating train split: 114858414 examples [2:08:05, 39589.26 examples/s]
Generating train split: 114864304 examples [2:08:06, 30459.06 examples/s]
Generating train split: 114868991 examples [2:08:06, 23299.89 examples/s]
Generating train split: 114872675 examples [2:08:06, 22914.28 examples/s]
Generating train split: 114875899 examples [2:08:06, 21226.65 examples/s]
Generating train split: 114878670 examples [2:08:07, 18897.72 examples/s]
Generating train split: 114880998 examples [2:08:07, 18207.04 examples/s]
Generating train split: 114883103 examples [2:08:07, 14253.86 examples/s]
Generating train split: 114884815 examples [2:08:07, 14593.06 examples/s]
Generating train split: 114886494 examples [2:08:07, 10948.44 examples/s]
Generating train split: 114888551 examples [2:08:08, 12525.75 examples/s]
Generating train split: 114891869 examples [2:08:08, 16434.57 examples/s]
Generating train split: 114893964 examples [2:08:08, 16023.80 examples/s]
Generating train split: 114895877 examples [2:08:08, 15857.59 examples/s]
Generating train split: 114898791 examples [2:08:08, 18891.46 examples/s]
Generating train split: 114907523 examples [2:08:08, 35752.40 examples/s]
Generating train split: 114914913 examples [2:08:08, 44849.45 examples/s]
Generating train split: 114919871 examples [2:08:08, 38060.60 examples/s]
Generating train split: 114924171 examples [2:08:09, 22023.71 examples/s]
Generating train split: 114927492 examples [2:08:09, 16610.16 examples/s]
Generating train split: 114930078 examples [2:08:09, 16664.62 examples/s]
Generating train split: 114932404 examples [2:08:10, 12565.47 examples/s]
Generating train split: 114934258 examples [2:08:10, 13330.28 examples/s]
Generating train split: 114936083 examples [2:08:10, 11869.89 examples/s]
Generating train split: 114937609 examples [2:08:10, 11159.27 examples/s]
Generating train split: 114938945 examples [2:08:10, 9265.72 examples/s] 
Generating train split: 114940490 examples [2:08:11, 10236.43 examples/s]
Generating train split: 114941718 examples [2:08:11, 10602.53 examples/s]
Generating train split: 114944135 examples [2:08:11, 13451.33 examples/s]
Generating train split: 114946221 examples [2:08:11, 15147.41 examples/s]
Generating train split: 114948081 examples [2:08:11, 16007.92 examples/s]
Generating train split: 114949844 examples [2:08:11, 13734.48 examples/s]
Generating train split: 114951402 examples [2:08:11, 14032.29 examples/s]
Generating train split: 114952925 examples [2:08:11, 14119.75 examples/s]
Generating train split: 114960952 examples [2:08:11, 31455.10 examples/s]
Generating train split: 114969621 examples [2:08:12, 46496.11 examples/s]
Generating train split: 114974640 examples [2:08:12, 39783.62 examples/s]
Generating train split: 114979042 examples [2:08:12, 26201.41 examples/s]
Generating train split: 114982545 examples [2:08:12, 24074.07 examples/s]
Generating train split: 114985569 examples [2:08:12, 20389.27 examples/s]
Generating train split: 114988089 examples [2:08:13, 18202.50 examples/s]
Generating train split: 114990236 examples [2:08:13, 17420.92 examples/s]
Generating train split: 114992199 examples [2:08:13, 14886.38 examples/s]
Generating train split: 114993854 examples [2:08:13, 15057.09 examples/s]
Generating train split: 114995734 examples [2:08:13, 15834.59 examples/s]
Generating train split: 114997852 examples [2:08:13, 17042.17 examples/s]
Generating train split: 115000136 examples [2:08:13, 18419.33 examples/s]
Generating train split: 115002099 examples [2:08:14, 15162.01 examples/s]
Generating train split: 115003824 examples [2:08:14, 15644.43 examples/s]
Generating train split: 115005520 examples [2:08:14, 13780.99 examples/s]
Generating train split: 115007018 examples [2:08:14, 11909.58 examples/s]
Generating train split: 115008324 examples [2:08:14, 8931.00 examples/s] 
Generating train split: 115009394 examples [2:08:14, 8177.80 examples/s]
Generating train split: 115010658 examples [2:08:15, 8963.17 examples/s]
Generating train split: 115011673 examples [2:08:15, 8984.42 examples/s]
Generating train split: 115012657 examples [2:08:15, 8232.17 examples/s]
Generating train split: 115014601 examples [2:08:15, 10700.75 examples/s]
Generating train split: 115015791 examples [2:08:15, 9272.71 examples/s] 
Generating train split: 115016840 examples [2:08:15, 7548.34 examples/s]
Generating train split: 115018282 examples [2:08:15, 8905.48 examples/s]
Generating train split: 115019313 examples [2:08:15, 8986.52 examples/s]
Generating train split: 115020312 examples [2:08:16, 8640.32 examples/s]
Generating train split: 115021671 examples [2:08:16, 9801.58 examples/s]
Generating train split: 115022730 examples [2:08:16, 9309.39 examples/s]
Generating train split: 115023717 examples [2:08:16, 9337.97 examples/s]
Generating train split: 115024695 examples [2:08:16, 7765.01 examples/s]
Generating train split: 115025580 examples [2:08:16, 7992.32 examples/s]
Generating train split: 115026435 examples [2:08:16, 7969.34 examples/s]
Generating train split: 115027275 examples [2:08:16, 7720.03 examples/s]
Generating train split: 115028074 examples [2:08:17, 5515.05 examples/s]
Generating train split: 115028782 examples [2:08:17, 5832.43 examples/s]
Generating train split: 115029459 examples [2:08:17, 4078.42 examples/s]
Generating train split: 115030978 examples [2:08:17, 6079.14 examples/s]
Generating train split: 115031806 examples [2:08:17, 4953.29 examples/s]
Generating train split: 115033164 examples [2:08:18, 6501.27 examples/s]
Generating train split: 115040068 examples [2:08:18, 19373.71 examples/s]
Generating train split: 115047967 examples [2:08:18, 32920.29 examples/s]
Generating train split: 115052221 examples [2:08:18, 34152.52 examples/s]
Generating train split: 115056326 examples [2:08:18, 19889.49 examples/s]
Generating train split: 115064033 examples [2:08:18, 29428.40 examples/s]
Generating train split: 115072166 examples [2:08:19, 39413.27 examples/s]
Generating train split: 115077774 examples [2:08:19, 25276.45 examples/s]
Generating train split: 115082098 examples [2:08:19, 23778.40 examples/s]
Generating train split: 115085728 examples [2:08:19, 19776.54 examples/s]
Generating train split: 115088640 examples [2:08:20, 20105.02 examples/s]
Generating train split: 115091860 examples [2:08:20, 22095.64 examples/s]
Generating train split: 115094703 examples [2:08:20, 22157.55 examples/s]
Generating train split: 115097375 examples [2:08:20, 16280.84 examples/s]
Generating train split: 115105611 examples [2:08:20, 27651.41 examples/s]
Generating train split: 115114173 examples [2:08:20, 39092.50 examples/s]
Generating train split: 115119512 examples [2:08:21, 33848.18 examples/s]
Generating train split: 115124006 examples [2:08:21, 25614.60 examples/s]
Generating train split: 115127597 examples [2:08:21, 18193.04 examples/s]
Generating train split: 115130387 examples [2:08:21, 16892.94 examples/s]
Generating train split: 115132733 examples [2:08:22, 16334.45 examples/s]
Generating train split: 115134840 examples [2:08:22, 17018.73 examples/s]
Generating train split: 115136904 examples [2:08:22, 15222.89 examples/s]
Generating train split: 115138689 examples [2:08:22, 14901.23 examples/s]
Generating train split: 115140349 examples [2:08:22, 14858.45 examples/s]
Generating train split: 115142192 examples [2:08:22, 15622.14 examples/s]
Generating train split: 115143867 examples [2:08:22, 14445.47 examples/s]
Generating train split: 115145397 examples [2:08:23, 13339.82 examples/s]
Generating train split: 115153997 examples [2:08:23, 30410.97 examples/s]
Generating train split: 115162332 examples [2:08:23, 43706.87 examples/s]
Generating train split: 115167322 examples [2:08:23, 33160.80 examples/s]
Generating train split: 115171451 examples [2:08:23, 27776.50 examples/s]
Generating train split: 115174901 examples [2:08:23, 27451.17 examples/s]
Generating train split: 115178108 examples [2:08:23, 25425.69 examples/s]
Generating train split: 115180971 examples [2:08:24, 20032.76 examples/s]
Generating train split: 115183328 examples [2:08:24, 19366.10 examples/s]
Generating train split: 115185508 examples [2:08:24, 18090.33 examples/s]
Generating train split: 115187974 examples [2:08:24, 19440.06 examples/s]
Generating train split: 115190084 examples [2:08:24, 18069.25 examples/s]
Generating train split: 115193144 examples [2:08:24, 20896.13 examples/s]
Generating train split: 115195406 examples [2:08:25, 13356.33 examples/s]
Generating train split: 115197183 examples [2:08:25, 13599.68 examples/s]
Generating train split: 115199047 examples [2:08:25, 14591.38 examples/s]
Generating train split: 115200790 examples [2:08:25, 10624.18 examples/s]
Generating train split: 115202188 examples [2:08:25, 11221.98 examples/s]
Generating train split: 115203588 examples [2:08:25, 11165.03 examples/s]
Generating train split: 115204897 examples [2:08:26, 11179.85 examples/s]
Generating train split: 115206245 examples [2:08:26, 11709.29 examples/s]
Generating train split: 115208337 examples [2:08:26, 13933.79 examples/s]
Generating train split: 115209858 examples [2:08:26, 9052.50 examples/s] 
Generating train split: 115212084 examples [2:08:26, 11557.07 examples/s]
Generating train split: 115213596 examples [2:08:26, 11083.32 examples/s]
Generating train split: 115214954 examples [2:08:27, 9950.35 examples/s] 
Generating train split: 115216143 examples [2:08:27, 10350.44 examples/s]
Generating train split: 115217332 examples [2:08:27, 9784.88 examples/s] 
Generating train split: 115218423 examples [2:08:27, 7517.60 examples/s]
Generating train split: 115219316 examples [2:08:27, 7576.75 examples/s]
Generating train split: 115221818 examples [2:08:27, 11333.39 examples/s]
Generating train split: 115230046 examples [2:08:27, 28029.26 examples/s]
Generating train split: 115238041 examples [2:08:27, 40836.11 examples/s]
Generating train split: 115242779 examples [2:08:28, 19355.65 examples/s]
Generating train split: 115246353 examples [2:08:28, 18497.88 examples/s]
Generating train split: 115249340 examples [2:08:28, 16050.73 examples/s]
Generating train split: 115253152 examples [2:08:29, 19268.69 examples/s]
Generating train split: 115261876 examples [2:08:29, 30990.61 examples/s]
Generating train split: 115267832 examples [2:08:29, 36625.64 examples/s]
Generating train split: 115272844 examples [2:08:29, 22891.99 examples/s]
Generating train split: 115276694 examples [2:08:30, 18740.12 examples/s]
Generating train split: 115279759 examples [2:08:30, 17667.75 examples/s]
Generating train split: 115282334 examples [2:08:30, 14341.30 examples/s]
Generating train split: 115284388 examples [2:08:30, 14958.76 examples/s]
Generating train split: 115286740 examples [2:08:30, 16348.11 examples/s]
Generating train split: 115288841 examples [2:08:30, 15182.26 examples/s]
Generating train split: 115290675 examples [2:08:31, 14639.58 examples/s]
Generating train split: 115292492 examples [2:08:31, 15296.33 examples/s]
Generating train split: 115294213 examples [2:08:31, 11235.76 examples/s]
Generating train split: 115299368 examples [2:08:31, 18731.63 examples/s]
Generating train split: 115308337 examples [2:08:31, 33619.90 examples/s]
Generating train split: 115313944 examples [2:08:31, 38046.61 examples/s]
Generating train split: 115318610 examples [2:08:32, 22225.25 examples/s]
Generating train split: 115322199 examples [2:08:32, 20563.20 examples/s]
Generating train split: 115325213 examples [2:08:32, 15089.54 examples/s]
Generating train split: 115327736 examples [2:08:32, 16475.96 examples/s]
Generating train split: 115330140 examples [2:08:33, 13841.26 examples/s]
Generating train split: 115332090 examples [2:08:33, 14515.50 examples/s]
Generating train split: 115338519 examples [2:08:33, 23411.66 examples/s]
Generating train split: 115347808 examples [2:08:33, 37538.73 examples/s]
Generating train split: 115352877 examples [2:08:33, 39151.63 examples/s]
Generating train split: 115357742 examples [2:08:33, 24815.82 examples/s]
Generating train split: 115361537 examples [2:08:34, 21955.26 examples/s]
Generating train split: 115364669 examples [2:08:34, 21470.06 examples/s]
Generating train split: 115367673 examples [2:08:34, 22965.85 examples/s]
Generating train split: 115370525 examples [2:08:34, 17582.39 examples/s]
Generating train split: 115372826 examples [2:08:34, 18436.32 examples/s]
Generating train split: 115375272 examples [2:08:34, 19624.50 examples/s]
Generating train split: 115377613 examples [2:08:35, 15220.48 examples/s]
Generating train split: 115380061 examples [2:08:35, 16963.49 examples/s]
Generating train split: 115382594 examples [2:08:35, 18742.51 examples/s]
Generating train split: 115384800 examples [2:08:35, 14403.89 examples/s]
Generating train split: 115386801 examples [2:08:35, 15475.92 examples/s]
Generating train split: 115389416 examples [2:08:35, 17807.37 examples/s]
Generating train split: 115391508 examples [2:08:36, 12128.67 examples/s]
Generating train split: 115393943 examples [2:08:36, 14349.69 examples/s]
Generating train split: 115396264 examples [2:08:36, 15892.20 examples/s]
Generating train split: 115398472 examples [2:08:36, 17279.47 examples/s]
Generating train split: 115400509 examples [2:08:36, 13202.22 examples/s]
Generating train split: 115402177 examples [2:08:36, 12189.32 examples/s]
Generating train split: 115404236 examples [2:08:37, 13379.09 examples/s]
Generating train split: 115405784 examples [2:08:37, 11162.13 examples/s]
Generating train split: 115407095 examples [2:08:37, 11165.80 examples/s]
Generating train split: 115409249 examples [2:08:37, 13338.22 examples/s]
Generating train split: 115410752 examples [2:08:37, 10864.03 examples/s]
Generating train split: 115412022 examples [2:08:37, 10439.32 examples/s]
Generating train split: 115414405 examples [2:08:37, 13273.72 examples/s]
Generating train split: 115415916 examples [2:08:38, 10148.79 examples/s]
Generating train split: 115417159 examples [2:08:38, 9504.68 examples/s] 
Generating train split: 115419735 examples [2:08:38, 12797.98 examples/s]
Generating train split: 115421278 examples [2:08:38, 10024.14 examples/s]
Generating train split: 115422543 examples [2:08:38, 10001.76 examples/s]
Generating train split: 115425178 examples [2:08:38, 13396.95 examples/s]
Generating train split: 115426797 examples [2:08:39, 12358.38 examples/s]
Generating train split: 115428235 examples [2:08:39, 10026.19 examples/s]
Generating train split: 115430775 examples [2:08:39, 13101.15 examples/s]
Generating train split: 115432789 examples [2:08:39, 14615.75 examples/s]
Generating train split: 115434505 examples [2:08:39, 12607.39 examples/s]
Generating train split: 115435993 examples [2:08:39, 11609.38 examples/s]
Generating train split: 115437331 examples [2:08:39, 11807.11 examples/s]
Generating train split: 115438633 examples [2:08:40, 10354.15 examples/s]
Generating train split: 115439768 examples [2:08:40, 8293.11 examples/s] 
Generating train split: 115440725 examples [2:08:40, 7153.90 examples/s]
Generating train split: 115441534 examples [2:08:40, 7146.30 examples/s]
Generating train split: 115443510 examples [2:08:40, 9813.22 examples/s]
Generating train split: 115445114 examples [2:08:40, 11240.26 examples/s]
Generating train split: 115446397 examples [2:08:41, 9044.75 examples/s] 
Generating train split: 115447476 examples [2:08:41, 7778.44 examples/s]
Generating train split: 115448781 examples [2:08:41, 8608.17 examples/s]
Generating train split: 115449764 examples [2:08:41, 7763.95 examples/s]
Generating train split: 115451799 examples [2:08:41, 10431.68 examples/s]
Generating train split: 115453013 examples [2:08:41, 9830.49 examples/s] 
Generating train split: 115454370 examples [2:08:41, 10663.47 examples/s]
Generating train split: 115455607 examples [2:08:41, 11069.42 examples/s]
Generating train split: 115456796 examples [2:08:42, 10530.43 examples/s]
Generating train split: 115457908 examples [2:08:42, 9231.93 examples/s] 
Generating train split: 115458899 examples [2:08:42, 6947.17 examples/s]
Generating train split: 115460303 examples [2:08:42, 8382.27 examples/s]
Generating train split: 115461424 examples [2:08:42, 8967.65 examples/s]
Generating train split: 115462449 examples [2:08:42, 8484.31 examples/s]
Generating train split: 115463389 examples [2:08:42, 7953.59 examples/s]
Generating train split: 115464990 examples [2:08:43, 9872.43 examples/s]
Generating train split: 115466077 examples [2:08:43, 10111.97 examples/s]
Generating train split: 115467162 examples [2:08:43, 10160.05 examples/s]
Generating train split: 115468231 examples [2:08:43, 8153.22 examples/s] 
Generating train split: 115469931 examples [2:08:43, 10225.48 examples/s]
Generating train split: 115471673 examples [2:08:43, 11998.96 examples/s]
Generating train split: 115473475 examples [2:08:43, 13561.62 examples/s]
Generating train split: 115474940 examples [2:08:43, 12067.11 examples/s]
Generating train split: 115477114 examples [2:08:44, 14502.35 examples/s]
Generating train split: 115478680 examples [2:08:44, 13312.71 examples/s]
Generating train split: 115480120 examples [2:08:44, 13451.95 examples/s]
Generating train split: 115482433 examples [2:08:44, 15396.02 examples/s]
Generating train split: 115484037 examples [2:08:44, 13840.02 examples/s]
Generating train split: 115485898 examples [2:08:44, 15034.20 examples/s]
Generating train split: 115487475 examples [2:08:44, 10244.69 examples/s]
Generating train split: 115489481 examples [2:08:45, 12227.71 examples/s]
Generating train split: 115490978 examples [2:08:45, 10087.11 examples/s]
Generating train split: 115492846 examples [2:08:45, 11810.69 examples/s]
Generating train split: 115494474 examples [2:08:45, 12780.45 examples/s]
Generating train split: 115495963 examples [2:08:45, 12102.14 examples/s]
Generating train split: 115497330 examples [2:08:45, 10625.74 examples/s]
Generating train split: 115498520 examples [2:08:45, 10810.07 examples/s]
Generating train split: 115499973 examples [2:08:45, 11698.78 examples/s]
Generating train split: 115501230 examples [2:08:46, 7882.32 examples/s] 
Generating train split: 115502274 examples [2:08:46, 8295.80 examples/s]
Generating train split: 115503275 examples [2:08:46, 6190.22 examples/s]
Generating train split: 115506423 examples [2:08:46, 10758.76 examples/s]
Generating train split: 115507946 examples [2:08:47, 8848.75 examples/s] 
Generating train split: 115509184 examples [2:08:47, 7642.47 examples/s]
Generating train split: 115510208 examples [2:08:47, 7789.10 examples/s]
Generating train split: 115511182 examples [2:08:47, 7507.11 examples/s]
Generating train split: 115512063 examples [2:08:47, 7403.93 examples/s]
Generating train split: 115513357 examples [2:08:47, 8461.34 examples/s]
Generating train split: 115514299 examples [2:08:47, 8191.70 examples/s]
Generating train split: 115516026 examples [2:08:48, 10038.94 examples/s]
Generating train split: 115517115 examples [2:08:48, 9413.15 examples/s] 
Generating train split: 115518116 examples [2:08:48, 5690.31 examples/s]
Generating train split: 115519623 examples [2:08:48, 7265.02 examples/s]
Generating train split: 115520603 examples [2:08:48, 7086.22 examples/s]
Generating train split: 115528285 examples [2:08:48, 21334.50 examples/s]
Generating train split: 115536763 examples [2:08:48, 35666.02 examples/s]
Generating train split: 115541359 examples [2:08:49, 27053.32 examples/s]
Generating train split: 115549681 examples [2:08:49, 38176.89 examples/s]
Generating train split: 115558150 examples [2:08:49, 47740.59 examples/s]
Generating train split: 115564107 examples [2:08:50, 22632.83 examples/s]
Generating train split: 115568568 examples [2:08:50, 17830.23 examples/s]
Generating train split: 115572001 examples [2:08:50, 14824.80 examples/s]
Generating train split: 115574674 examples [2:08:51, 13150.93 examples/s]
Generating train split: 115576808 examples [2:08:51, 10605.01 examples/s]
Generating train split: 115578537 examples [2:08:51, 11335.59 examples/s]
Generating train split: 115580222 examples [2:08:51, 11469.44 examples/s]
Generating train split: 115581762 examples [2:08:52, 10504.94 examples/s]
Generating train split: 115583121 examples [2:08:52, 10990.05 examples/s]
Generating train split: 115584450 examples [2:08:52, 10836.52 examples/s]
Generating train split: 115586381 examples [2:08:52, 12503.74 examples/s]
Generating train split: 115587824 examples [2:08:52, 11293.48 examples/s]
Generating train split: 115589095 examples [2:08:52, 8379.23 examples/s] 
Generating train split: 115590127 examples [2:08:53, 6793.16 examples/s]
Generating train split: 115591340 examples [2:08:53, 7622.34 examples/s]
Generating train split: 115593049 examples [2:08:53, 9444.87 examples/s]
Generating train split: 115594521 examples [2:08:53, 10511.09 examples/s]
Generating train split: 115595766 examples [2:08:53, 9956.50 examples/s] 
Generating train split: 115596904 examples [2:08:53, 9541.64 examples/s]
Generating train split: 115599229 examples [2:08:53, 12730.70 examples/s]
Generating train split: 115600654 examples [2:08:53, 13012.92 examples/s]
Generating train split: 115602071 examples [2:08:54, 10427.64 examples/s]
Generating train split: 115603270 examples [2:08:54, 9555.35 examples/s] 
Generating train split: 115605644 examples [2:08:54, 12721.82 examples/s]
Generating train split: 115607400 examples [2:08:54, 13839.64 examples/s]
Generating train split: 115608948 examples [2:08:54, 9081.14 examples/s] 
Generating train split: 115610573 examples [2:08:54, 10221.13 examples/s]
Generating train split: 115611876 examples [2:08:55, 8189.85 examples/s] 
Generating train split: 115614067 examples [2:08:55, 10714.39 examples/s]
Generating train split: 115615717 examples [2:08:55, 11790.38 examples/s]
Generating train split: 115617170 examples [2:08:55, 9191.05 examples/s] 
Generating train split: 115619132 examples [2:08:55, 11178.88 examples/s]
Generating train split: 115621161 examples [2:08:55, 13121.76 examples/s]
Generating train split: 115622756 examples [2:08:55, 10494.90 examples/s]
Generating train split: 115624080 examples [2:08:56, 10821.88 examples/s]
Generating train split: 115630522 examples [2:08:56, 22718.73 examples/s]
Generating train split: 115639159 examples [2:08:56, 38040.90 examples/s]
Generating train split: 115643740 examples [2:08:56, 35311.77 examples/s]
Generating train split: 115647849 examples [2:08:56, 20000.45 examples/s]
Generating train split: 115651014 examples [2:08:57, 16762.47 examples/s]
Generating train split: 115653553 examples [2:08:57, 14158.11 examples/s]
Generating train split: 115655600 examples [2:08:57, 12037.79 examples/s]
Generating train split: 115657252 examples [2:08:57, 11811.93 examples/s]
Generating train split: 115658741 examples [2:08:58, 10566.82 examples/s]
Generating train split: 115660258 examples [2:08:58, 11308.05 examples/s]
Generating train split: 115662574 examples [2:08:58, 13520.64 examples/s]
Generating train split: 115664200 examples [2:08:58, 13087.98 examples/s]
Generating train split: 115666129 examples [2:08:58, 14383.89 examples/s]
Generating train split: 115667744 examples [2:08:58, 11027.55 examples/s]
Generating train split: 115669080 examples [2:08:59, 8717.61 examples/s] 
Generating train split: 115670170 examples [2:08:59, 8487.22 examples/s]
Generating train split: 115671352 examples [2:08:59, 9123.75 examples/s]
Generating train split: 115672633 examples [2:08:59, 9913.03 examples/s]
Generating train split: 115674735 examples [2:08:59, 12491.56 examples/s]
Generating train split: 115676152 examples [2:08:59, 8907.96 examples/s] 
Generating train split: 115678763 examples [2:08:59, 12320.36 examples/s]
Generating train split: 115681528 examples [2:08:59, 15699.86 examples/s]
Generating train split: 115683473 examples [2:09:00, 15357.15 examples/s]
Generating train split: 115685268 examples [2:09:00, 12073.06 examples/s]
Generating train split: 115687069 examples [2:09:00, 13286.65 examples/s]
Generating train split: 115688655 examples [2:09:00, 11186.69 examples/s]
Generating train split: 115690457 examples [2:09:00, 12556.02 examples/s]
Generating train split: 115691924 examples [2:09:00, 12606.55 examples/s]
Generating train split: 115693334 examples [2:09:00, 12657.77 examples/s]
Generating train split: 115695360 examples [2:09:01, 14552.82 examples/s]
Generating train split: 115696940 examples [2:09:01, 10613.00 examples/s]
Generating train split: 115698720 examples [2:09:01, 12127.40 examples/s]
Generating train split: 115700329 examples [2:09:01, 12560.35 examples/s]
Generating train split: 115701748 examples [2:09:01, 12139.21 examples/s]
Generating train split: 115703364 examples [2:09:01, 13121.95 examples/s]
Generating train split: 115705703 examples [2:09:01, 15777.59 examples/s]
Generating train split: 115707399 examples [2:09:01, 14828.88 examples/s]
Generating train split: 115708968 examples [2:09:02, 11919.99 examples/s]
Generating train split: 115710777 examples [2:09:02, 13324.39 examples/s]
Generating train split: 115712433 examples [2:09:02, 14115.09 examples/s]
Generating train split: 115719145 examples [2:09:02, 27897.87 examples/s]
Generating train split: 115726544 examples [2:09:02, 40371.80 examples/s]
Generating train split: 115730920 examples [2:09:02, 32721.12 examples/s]
Generating train split: 115734664 examples [2:09:03, 24411.07 examples/s]
Generating train split: 115737714 examples [2:09:03, 20169.14 examples/s]
Generating train split: 115740241 examples [2:09:03, 18951.20 examples/s]
Generating train split: 115742480 examples [2:09:03, 14835.80 examples/s]
Generating train split: 115744801 examples [2:09:03, 16165.34 examples/s]
Generating train split: 115746815 examples [2:09:03, 16730.85 examples/s]
Generating train split: 115748746 examples [2:09:04, 12113.88 examples/s]
Generating train split: 115751182 examples [2:09:04, 14280.10 examples/s]
Generating train split: 115753049 examples [2:09:04, 15163.50 examples/s]
Generating train split: 115754880 examples [2:09:04, 14343.22 examples/s]
Generating train split: 115756541 examples [2:09:04, 12180.65 examples/s]
Generating train split: 115759092 examples [2:09:04, 14940.23 examples/s]
Generating train split: 115760840 examples [2:09:05, 11835.30 examples/s]
Generating train split: 115762430 examples [2:09:05, 12638.28 examples/s]
Generating train split: 115763925 examples [2:09:05, 11633.99 examples/s]
Generating train split: 115771996 examples [2:09:05, 26755.78 examples/s]
Generating train split: 115780405 examples [2:09:05, 40413.03 examples/s]
Generating train split: 115785282 examples [2:09:05, 33815.60 examples/s]
Generating train split: 115789425 examples [2:09:06, 21285.23 examples/s]
Generating train split: 115792638 examples [2:09:06, 16695.31 examples/s]
Generating train split: 115795170 examples [2:09:06, 17302.58 examples/s]
Generating train split: 115797552 examples [2:09:06, 18311.66 examples/s]
Generating train split: 115799919 examples [2:09:06, 19067.92 examples/s]
Generating train split: 115802249 examples [2:09:06, 19402.74 examples/s]
Generating train split: 115804497 examples [2:09:07, 16950.79 examples/s]
Generating train split: 115806434 examples [2:09:07, 15158.82 examples/s]
Generating train split: 115808134 examples [2:09:07, 11002.81 examples/s]
Generating train split: 115810343 examples [2:09:07, 12800.56 examples/s]
Generating train split: 115811931 examples [2:09:07, 13355.53 examples/s]
Generating train split: 115813509 examples [2:09:07, 11828.94 examples/s]
Generating train split: 115814879 examples [2:09:08, 11680.35 examples/s]
Generating train split: 115816539 examples [2:09:08, 12735.67 examples/s]
Generating train split: 115819009 examples [2:09:08, 15598.80 examples/s]
Generating train split: 115820730 examples [2:09:08, 10623.62 examples/s]
Generating train split: 115823157 examples [2:09:08, 13262.41 examples/s]
Generating train split: 115824842 examples [2:09:08, 13541.20 examples/s]
Generating train split: 115826466 examples [2:09:08, 12646.52 examples/s]
Generating train split: 115827923 examples [2:09:09, 11429.98 examples/s]
Generating train split: 115829436 examples [2:09:09, 12198.36 examples/s]
Generating train split: 115831440 examples [2:09:09, 14070.54 examples/s]
Generating train split: 115832983 examples [2:09:09, 11574.37 examples/s]
Generating train split: 115834414 examples [2:09:09, 12167.41 examples/s]
Generating train split: 115836506 examples [2:09:09, 14279.39 examples/s]
Generating train split: 115838079 examples [2:09:09, 10486.12 examples/s]
Generating train split: 115839570 examples [2:09:10, 11065.53 examples/s]
Generating train split: 115842019 examples [2:09:10, 14073.11 examples/s]
Generating train split: 115843656 examples [2:09:10, 11865.45 examples/s]
Generating train split: 115846045 examples [2:09:10, 14480.91 examples/s]
Generating train split: 115847741 examples [2:09:10, 10761.18 examples/s]
Generating train split: 115849374 examples [2:09:10, 11818.67 examples/s]
Generating train split: 115850821 examples [2:09:10, 12217.19 examples/s]
Generating train split: 115854809 examples [2:09:11, 18708.05 examples/s]
Generating train split: 115862475 examples [2:09:11, 33259.60 examples/s]
Generating train split: 115868730 examples [2:09:11, 40984.13 examples/s]
Generating train split: 115873295 examples [2:09:11, 29394.79 examples/s]
Generating train split: 115877024 examples [2:09:11, 19673.48 examples/s]
Generating train split: 115883295 examples [2:09:12, 26644.20 examples/s]
Generating train split: 115891001 examples [2:09:12, 36116.96 examples/s]
Generating train split: 115897156 examples [2:09:12, 40879.86 examples/s]
Generating train split: 115902416 examples [2:09:12, 23558.39 examples/s]
Generating train split: 115906435 examples [2:09:13, 18457.73 examples/s]
Generating train split: 115909580 examples [2:09:13, 19983.40 examples/s]
Generating train split: 115916755 examples [2:09:13, 28138.03 examples/s]
Generating train split: 115922612 examples [2:09:13, 33711.21 examples/s]
Generating train split: 115927378 examples [2:09:13, 19522.40 examples/s]
Generating train split: 115932302 examples [2:09:13, 23583.91 examples/s]
Generating train split: 115940669 examples [2:09:14, 33395.59 examples/s]
Generating train split: 115945981 examples [2:09:14, 31672.10 examples/s]
Generating train split: 115950544 examples [2:09:14, 23532.64 examples/s]
Generating train split: 115954141 examples [2:09:15, 17607.07 examples/s]
Generating train split: 115956933 examples [2:09:15, 13516.76 examples/s]
Generating train split: 115959093 examples [2:09:15, 13703.91 examples/s]
Generating train split: 115961054 examples [2:09:15, 12454.26 examples/s]
Generating train split: 115962693 examples [2:09:15, 11410.21 examples/s]
Generating train split: 115964089 examples [2:09:16, 10262.85 examples/s]
Generating train split: 115965287 examples [2:09:16, 8533.15 examples/s] 
Generating train split: 115966264 examples [2:09:16, 8642.32 examples/s]
Generating train split: 115967579 examples [2:09:16, 9370.22 examples/s]
Generating train split: 115968635 examples [2:09:16, 8941.78 examples/s]
Generating train split: 115969603 examples [2:09:16, 8960.58 examples/s]
Generating train split: 115970665 examples [2:09:16, 9336.81 examples/s]
Generating train split: 115972836 examples [2:09:17, 12389.02 examples/s]
Generating train split: 115974176 examples [2:09:17, 12414.36 examples/s]
Generating train split: 115975495 examples [2:09:17, 12093.69 examples/s]
Generating train split: 115977728 examples [2:09:17, 14534.69 examples/s]
Generating train split: 115979230 examples [2:09:17, 11653.88 examples/s]
Generating train split: 115980699 examples [2:09:17, 12368.99 examples/s]
Generating train split: 115982037 examples [2:09:17, 11812.10 examples/s]
Generating train split: 115983296 examples [2:09:17, 11827.48 examples/s]
Generating train split: 115984539 examples [2:09:18, 11502.05 examples/s]
Generating train split: 115986633 examples [2:09:18, 13526.56 examples/s]
Generating train split: 115988025 examples [2:09:18, 10760.11 examples/s]
Generating train split: 115990075 examples [2:09:18, 12996.53 examples/s]
Generating train split: 115991574 examples [2:09:18, 13487.54 examples/s]
Generating train split: 115993029 examples [2:09:18, 12395.69 examples/s]
Generating train split: 115994361 examples [2:09:18, 11982.42 examples/s]
Generating train split: 115995650 examples [2:09:18, 12187.56 examples/s]
Generating train split: 116001129 examples [2:09:19, 23526.40 examples/s]
Generating train split: 116008579 examples [2:09:19, 37555.40 examples/s]
Generating train split: 116014172 examples [2:09:19, 42711.51 examples/s]
Generating train split: 116018652 examples [2:09:19, 34482.25 examples/s]
Generating train split: 116022498 examples [2:09:19, 20423.51 examples/s]
Generating train split: 116025477 examples [2:09:19, 20427.70 examples/s]
Generating train split: 116028192 examples [2:09:20, 15896.05 examples/s]
Generating train split: 116030365 examples [2:09:20, 14759.32 examples/s]
Generating train split: 116032236 examples [2:09:20, 14009.14 examples/s]
Generating train split: 116033978 examples [2:09:20, 14617.55 examples/s]
Generating train split: 116035660 examples [2:09:20, 12032.69 examples/s]
Generating train split: 116037067 examples [2:09:21, 12203.71 examples/s]
Generating train split: 116038459 examples [2:09:21, 12555.10 examples/s]
Generating train split: 116040432 examples [2:09:21, 14204.13 examples/s]
Generating train split: 116042003 examples [2:09:21, 12221.03 examples/s]
Generating train split: 116043361 examples [2:09:21, 10549.11 examples/s]
Generating train split: 116044840 examples [2:09:21, 11452.52 examples/s]
Generating train split: 116046511 examples [2:09:21, 12610.08 examples/s]
Generating train split: 116047882 examples [2:09:21, 11820.45 examples/s]
Generating train split: 116049148 examples [2:09:22, 10114.13 examples/s]
Generating train split: 116050579 examples [2:09:22, 11035.24 examples/s]
Generating train split: 116051776 examples [2:09:22, 11149.04 examples/s]
Generating train split: 116052961 examples [2:09:22, 10322.41 examples/s]
Generating train split: 116054050 examples [2:09:22, 10257.96 examples/s]
Generating train split: 116056993 examples [2:09:22, 15246.01 examples/s]
Generating train split: 116059233 examples [2:09:22, 17135.46 examples/s]
Generating train split: 116061045 examples [2:09:23, 11463.77 examples/s]
Generating train split: 116063390 examples [2:09:23, 13945.88 examples/s]
Generating train split: 116066220 examples [2:09:23, 17220.43 examples/s]
Generating train split: 116068286 examples [2:09:23, 15223.37 examples/s]
Generating train split: 116070217 examples [2:09:23, 16144.73 examples/s]
Generating train split: 116073715 examples [2:09:23, 20775.37 examples/s]
Generating train split: 116081997 examples [2:09:23, 36900.62 examples/s]
Generating train split: 116088402 examples [2:09:23, 44240.94 examples/s]
Generating train split: 116093205 examples [2:09:23, 39444.07 examples/s]
Generating train split: 116097505 examples [2:09:24, 26147.48 examples/s]
Generating train split: 116100942 examples [2:09:24, 21296.22 examples/s]
Generating train split: 116103747 examples [2:09:24, 19621.71 examples/s]
Generating train split: 116106177 examples [2:09:24, 18858.78 examples/s]
Generating train split: 116108365 examples [2:09:25, 15173.99 examples/s]
Generating train split: 116111065 examples [2:09:25, 17243.44 examples/s]
Generating train split: 116113143 examples [2:09:25, 17763.16 examples/s]
Generating train split: 116115185 examples [2:09:25, 15652.69 examples/s]
Generating train split: 116116970 examples [2:09:25, 16091.13 examples/s]
Generating train split: 116118758 examples [2:09:25, 15826.19 examples/s]
Generating train split: 116120455 examples [2:09:25, 14008.77 examples/s]
Generating train split: 116121955 examples [2:09:26, 12016.39 examples/s]
Generating train split: 116123269 examples [2:09:26, 11655.12 examples/s]
Generating train split: 116125303 examples [2:09:26, 13614.80 examples/s]
Generating train split: 116126782 examples [2:09:26, 12596.68 examples/s]
Generating train split: 116128570 examples [2:09:26, 13821.22 examples/s]
Generating train split: 116130179 examples [2:09:26, 14282.36 examples/s]
Generating train split: 116131946 examples [2:09:26, 14872.54 examples/s]
Generating train split: 116139236 examples [2:09:26, 30596.72 examples/s]
Generating train split: 116147514 examples [2:09:26, 45156.19 examples/s]
Generating train split: 116152288 examples [2:09:27, 29663.07 examples/s]
Generating train split: 116156115 examples [2:09:27, 21899.45 examples/s]
Generating train split: 116159173 examples [2:09:27, 19905.00 examples/s]
Generating train split: 116161773 examples [2:09:28, 15283.18 examples/s]
Generating train split: 116163841 examples [2:09:28, 14768.73 examples/s]
Generating train split: 116165672 examples [2:09:28, 12278.07 examples/s]
Generating train split: 116167747 examples [2:09:28, 13609.71 examples/s]
Generating train split: 116169417 examples [2:09:28, 12549.54 examples/s]
Generating train split: 116170890 examples [2:09:28, 12415.90 examples/s]
Generating train split: 116172276 examples [2:09:28, 12652.71 examples/s]
Generating train split: 116173789 examples [2:09:29, 13129.93 examples/s]
Generating train split: 116175200 examples [2:09:29, 10439.00 examples/s]
Generating train split: 116176392 examples [2:09:29, 10360.02 examples/s]
Generating train split: 116177526 examples [2:09:29, 9595.73 examples/s] 
Generating train split: 116180000 examples [2:09:29, 12987.32 examples/s]
Generating train split: 116181451 examples [2:09:29, 12049.72 examples/s]
Generating train split: 116182778 examples [2:09:29, 11941.01 examples/s]
Generating train split: 116184052 examples [2:09:30, 10334.33 examples/s]
Generating train split: 116186015 examples [2:09:30, 12432.36 examples/s]
Generating train split: 116189072 examples [2:09:30, 16924.73 examples/s]
Generating train split: 116190939 examples [2:09:30, 12507.03 examples/s]
Generating train split: 116192476 examples [2:09:30, 11205.92 examples/s]
Generating train split: 116194252 examples [2:09:30, 12546.73 examples/s]
Generating train split: 116195730 examples [2:09:30, 11749.02 examples/s]
Generating train split: 116197361 examples [2:09:31, 12764.62 examples/s]
Generating train split: 116198781 examples [2:09:31, 8221.91 examples/s] 
Generating train split: 116200402 examples [2:09:31, 9652.07 examples/s]
Generating train split: 116201677 examples [2:09:31, 9001.29 examples/s]
Generating train split: 116208915 examples [2:09:31, 21865.39 examples/s]
Generating train split: 116217715 examples [2:09:31, 36729.03 examples/s]
Generating train split: 116222421 examples [2:09:32, 31633.20 examples/s]
Generating train split: 116226423 examples [2:09:32, 23657.09 examples/s]
Generating train split: 116234288 examples [2:09:32, 33598.90 examples/s]
Generating train split: 116242915 examples [2:09:32, 44411.88 examples/s]
Generating train split: 116248740 examples [2:09:32, 38271.43 examples/s]
Generating train split: 116253667 examples [2:09:33, 24607.18 examples/s]
Generating train split: 116257474 examples [2:09:33, 20064.19 examples/s]
Generating train split: 116260503 examples [2:09:33, 19895.73 examples/s]
Generating train split: 116263207 examples [2:09:33, 19119.08 examples/s]
Generating train split: 116265598 examples [2:09:34, 17068.96 examples/s]
Generating train split: 116268476 examples [2:09:34, 19027.93 examples/s]
Generating train split: 116270754 examples [2:09:34, 13918.36 examples/s]
Generating train split: 116272561 examples [2:09:34, 14029.43 examples/s]
Generating train split: 116281559 examples [2:09:34, 28042.79 examples/s]
Generating train split: 116288446 examples [2:09:34, 36026.33 examples/s]
Generating train split: 116293104 examples [2:09:34, 32820.81 examples/s]
Generating train split: 116297164 examples [2:09:35, 23997.17 examples/s]
Generating train split: 116300412 examples [2:09:35, 23582.45 examples/s]
Generating train split: 116303349 examples [2:09:35, 19491.66 examples/s]
Generating train split: 116305774 examples [2:09:35, 17628.32 examples/s]
Generating train split: 116307865 examples [2:09:36, 15820.61 examples/s]
Generating train split: 116310014 examples [2:09:36, 16840.57 examples/s]
Generating train split: 116312008 examples [2:09:36, 17411.49 examples/s]
Generating train split: 116313932 examples [2:09:36, 14243.96 examples/s]
Generating train split: 116315563 examples [2:09:36, 14602.84 examples/s]
Generating train split: 116318013 examples [2:09:36, 16828.81 examples/s]
Generating train split: 116321133 examples [2:09:36, 20199.33 examples/s]
Generating train split: 116323395 examples [2:09:36, 20812.33 examples/s]
Generating train split: 116325621 examples [2:09:36, 21035.44 examples/s]
Generating train split: 116327834 examples [2:09:37, 18834.86 examples/s]
Generating train split: 116330046 examples [2:09:37, 19626.47 examples/s]
Generating train split: 116332118 examples [2:09:37, 18521.51 examples/s]
Generating train split: 116334268 examples [2:09:37, 19195.62 examples/s]
Generating train split: 116336912 examples [2:09:37, 21163.01 examples/s]
Generating train split: 116344458 examples [2:09:37, 36347.71 examples/s]
Generating train split: 116352321 examples [2:09:37, 48420.90 examples/s]
Generating train split: 116357678 examples [2:09:37, 48077.23 examples/s]
Generating train split: 116362615 examples [2:09:38, 32372.28 examples/s]
Generating train split: 116366605 examples [2:09:38, 27742.49 examples/s]
Generating train split: 116369990 examples [2:09:38, 27950.21 examples/s]
Generating train split: 116373229 examples [2:09:38, 21924.05 examples/s]
Generating train split: 116375886 examples [2:09:38, 20351.77 examples/s]
Generating train split: 116378241 examples [2:09:39, 16891.82 examples/s]
Generating train split: 116380199 examples [2:09:39, 16141.20 examples/s]
Generating train split: 116382508 examples [2:09:39, 17445.56 examples/s]
Generating train split: 116384853 examples [2:09:39, 18560.99 examples/s]
Generating train split: 116386877 examples [2:09:39, 15042.52 examples/s]
Generating train split: 116389716 examples [2:09:39, 17849.89 examples/s]
Generating train split: 116393087 examples [2:09:39, 21505.44 examples/s]
Generating train split: 116395971 examples [2:09:39, 22806.46 examples/s]
Generating train split: 116399302 examples [2:09:40, 25156.82 examples/s]
Generating train split: 116402009 examples [2:09:40, 24352.38 examples/s]
Generating train split: 116409379 examples [2:09:40, 37433.89 examples/s]
Generating train split: 116416297 examples [2:09:40, 46131.15 examples/s]
Generating train split: 116421173 examples [2:09:40, 34199.11 examples/s]
Generating train split: 116425223 examples [2:09:40, 23020.13 examples/s]
Generating train split: 116428424 examples [2:09:41, 21419.84 examples/s]
Generating train split: 116431182 examples [2:09:41, 16879.56 examples/s]
Generating train split: 116433396 examples [2:09:41, 17061.30 examples/s]
Generating train split: 116435488 examples [2:09:41, 13892.89 examples/s]
Generating train split: 116438310 examples [2:09:41, 16288.77 examples/s]
Generating train split: 116441101 examples [2:09:41, 18477.65 examples/s]
Generating train split: 116443356 examples [2:09:42, 14561.59 examples/s]
Generating train split: 116445233 examples [2:09:42, 15351.39 examples/s]
Generating train split: 116447097 examples [2:09:42, 14425.07 examples/s]
Generating train split: 116448761 examples [2:09:42, 10855.07 examples/s]
Generating train split: 116450308 examples [2:09:42, 11421.84 examples/s]
Generating train split: 116451663 examples [2:09:43, 8369.11 examples/s] 
Generating train split: 116452823 examples [2:09:43, 8898.64 examples/s]
Generating train split: 116454172 examples [2:09:43, 9789.38 examples/s]
Generating train split: 116457106 examples [2:09:43, 14040.22 examples/s]
Generating train split: 116458961 examples [2:09:43, 15105.03 examples/s]
Generating train split: 116461439 examples [2:09:43, 17532.90 examples/s]
Generating train split: 116463402 examples [2:09:43, 17253.79 examples/s]
Generating train split: 116465274 examples [2:09:44, 5582.64 examples/s] 
Generating train split: 116466647 examples [2:09:45, 3333.99 examples/s]
Generating train split: 116467651 examples [2:09:46, 3089.73 examples/s]
Generating train split: 116468424 examples [2:09:46, 2832.28 examples/s]
Generating train split: 116469031 examples [2:09:46, 2708.78 examples/s]
Generating train split: 116470071 examples [2:09:46, 3435.20 examples/s]
Generating train split: 116470724 examples [2:09:47, 3299.35 examples/s]
Generating train split: 116471268 examples [2:09:47, 3380.95 examples/s]
Generating train split: 116472135 examples [2:09:47, 4157.54 examples/s]
Generating train split: 116472739 examples [2:09:47, 4221.16 examples/s]
Generating train split: 116473298 examples [2:09:47, 4414.47 examples/s]
Generating train split: 116473940 examples [2:09:47, 4833.79 examples/s]
Generating train split: 116474679 examples [2:09:47, 5370.19 examples/s]
Generating train split: 116475298 examples [2:09:48, 4254.23 examples/s]
Generating train split: 116475812 examples [2:09:48, 4046.63 examples/s]
Generating train split: 116476670 examples [2:09:48, 5022.94 examples/s]
Generating train split: 116477560 examples [2:09:48, 5798.06 examples/s]
Generating train split: 116478213 examples [2:09:48, 4924.45 examples/s]
Generating train split: 116480643 examples [2:09:48, 9292.48 examples/s]
Generating train split: 116487377 examples [2:09:48, 23429.42 examples/s]
Generating train split: 116494024 examples [2:09:48, 34352.03 examples/s]
Generating train split: 116497938 examples [2:09:49, 21198.17 examples/s]
Generating train split: 116501012 examples [2:09:49, 14451.11 examples/s]
Generating train split: 116503392 examples [2:09:49, 15370.80 examples/s]
Generating train split: 116505663 examples [2:09:50, 11565.95 examples/s]
Generating train split: 116508480 examples [2:09:50, 13912.61 examples/s]
Generating train split: 116512573 examples [2:09:50, 18459.05 examples/s]
Generating train split: 116520835 examples [2:09:50, 30894.00 examples/s]
Generating train split: 116526313 examples [2:09:50, 36067.97 examples/s]
Generating train split: 116531005 examples [2:09:50, 24428.77 examples/s]
Generating train split: 116534706 examples [2:09:51, 19357.64 examples/s]
Generating train split: 116537646 examples [2:09:51, 19325.95 examples/s]
Generating train split: 116540279 examples [2:09:51, 18310.38 examples/s]
Generating train split: 116542584 examples [2:09:51, 14830.26 examples/s]
Generating train split: 116544470 examples [2:09:51, 14517.15 examples/s]
Generating train split: 116546195 examples [2:09:52, 14175.25 examples/s]
Generating train split: 116547793 examples [2:09:52, 13166.11 examples/s]
Generating train split: 116549709 examples [2:09:52, 14328.38 examples/s]
Generating train split: 116551283 examples [2:09:52, 13916.85 examples/s]
Generating train split: 116552766 examples [2:09:52, 11926.65 examples/s]
Generating train split: 116555127 examples [2:09:52, 14481.42 examples/s]
Generating train split: 116556732 examples [2:09:52, 13915.48 examples/s]
Generating train split: 116558233 examples [2:09:53, 10443.39 examples/s]
Generating train split: 116560376 examples [2:09:53, 12669.56 examples/s]
Generating train split: 116562546 examples [2:09:53, 14682.07 examples/s]
Generating train split: 116564525 examples [2:09:53, 15900.77 examples/s]
Generating train split: 116566318 examples [2:09:53, 13324.82 examples/s]
Generating train split: 116570428 examples [2:09:53, 19699.64 examples/s]
Generating train split: 116578381 examples [2:09:53, 34473.22 examples/s]
Generating train split: 116584463 examples [2:09:53, 41328.07 examples/s]
Generating train split: 116589086 examples [2:09:54, 31138.11 examples/s]
Generating train split: 116592917 examples [2:09:54, 24050.48 examples/s]
Generating train split: 116596034 examples [2:09:54, 22863.04 examples/s]
Generating train split: 116598805 examples [2:09:54, 19151.34 examples/s]
Generating train split: 116601123 examples [2:09:54, 19429.98 examples/s]
Generating train split: 116603374 examples [2:09:54, 20034.65 examples/s]
Generating train split: 116605607 examples [2:09:55, 19275.86 examples/s]
Generating train split: 116607698 examples [2:09:55, 18924.35 examples/s]
Generating train split: 116610341 examples [2:09:55, 20721.65 examples/s]
Generating train split: 116612884 examples [2:09:55, 21850.25 examples/s]
Generating train split: 116615177 examples [2:09:55, 16088.73 examples/s]
Generating train split: 116617440 examples [2:09:55, 17499.65 examples/s]
Generating train split: 116619439 examples [2:09:55, 16080.45 examples/s]
Generating train split: 116621236 examples [2:09:56, 14740.74 examples/s]
Generating train split: 116623340 examples [2:09:56, 16165.52 examples/s]
Generating train split: 116625417 examples [2:09:56, 17228.07 examples/s]
Generating train split: 116627259 examples [2:09:56, 14590.25 examples/s]
Generating train split: 116628876 examples [2:09:56, 13211.14 examples/s]
Generating train split: 116630307 examples [2:09:56, 12022.77 examples/s]
Generating train split: 116631591 examples [2:09:56, 9873.28 examples/s] 
Generating train split: 116634440 examples [2:09:57, 13708.77 examples/s]
Generating train split: 116636051 examples [2:09:57, 12106.89 examples/s]
Generating train split: 116637451 examples [2:09:57, 11498.38 examples/s]
Generating train split: 116638783 examples [2:09:57, 11897.03 examples/s]
Generating train split: 116640079 examples [2:09:57, 9398.67 examples/s] 
Generating train split: 116641385 examples [2:09:57, 10134.43 examples/s]
Generating train split: 116642539 examples [2:09:57, 9706.56 examples/s] 
Generating train split: 116643611 examples [2:09:58, 7466.37 examples/s]
Generating train split: 116645354 examples [2:09:58, 9454.57 examples/s]
Generating train split: 116649386 examples [2:09:58, 16314.48 examples/s]
Generating train split: 116654389 examples [2:09:58, 24441.26 examples/s]
Generating train split: 116661219 examples [2:09:58, 35665.61 examples/s]
Generating train split: 116669035 examples [2:09:58, 47043.83 examples/s]
Generating train split: 116676677 examples [2:09:58, 55138.79 examples/s]
Generating train split: 116683614 examples [2:09:58, 59158.57 examples/s]
Generating train split: 116691743 examples [2:09:58, 65526.10 examples/s]
Generating train split: 116699382 examples [2:09:59, 68682.40 examples/s]
Generating train split: 116706500 examples [2:09:59, 69383.14 examples/s]
Generating train split: 116713583 examples [2:09:59, 69555.04 examples/s]
Generating train split: 116720974 examples [2:09:59, 70800.17 examples/s]
Generating train split: 116728134 examples [2:09:59, 68653.14 examples/s]
Generating train split: 116735699 examples [2:09:59, 70682.24 examples/s]
Generating train split: 116742824 examples [2:09:59, 70563.81 examples/s]
Generating train split: 116749920 examples [2:09:59, 70441.12 examples/s]
Generating train split: 116758367 examples [2:09:59, 74562.13 examples/s]
Generating train split: 116765846 examples [2:09:59, 73954.23 examples/s]
Generating train split: 116773507 examples [2:10:00, 74719.64 examples/s]
Generating train split: 116782260 examples [2:10:00, 78493.11 examples/s]
Generating train split: 116790126 examples [2:10:00, 76258.48 examples/s]
Generating train split: 116798595 examples [2:10:00, 78712.91 examples/s]
Generating train split: 116806510 examples [2:10:00, 78839.03 examples/s]
Generating train split: 116814548 examples [2:10:00, 79280.26 examples/s]
Generating train split: 116822494 examples [2:10:00, 78718.18 examples/s]
Generating train split: 116830387 examples [2:10:00, 78753.94 examples/s]
Generating train split: 116838280 examples [2:10:00, 77643.62 examples/s]
Generating train split: 116846055 examples [2:10:01, 74229.13 examples/s]
Generating train split: 116853512 examples [2:10:01, 66228.31 examples/s]
Generating train split: 116860304 examples [2:10:01, 63765.32 examples/s]
Generating train split: 116866798 examples [2:10:01, 48560.35 examples/s]
Generating train split: 116872242 examples [2:10:01, 39542.14 examples/s]
Generating train split: 116876812 examples [2:10:02, 28651.53 examples/s]
Generating train split: 116880457 examples [2:10:02, 28194.39 examples/s]
Generating train split: 116883806 examples [2:10:02, 26011.32 examples/s]
Generating train split: 116886762 examples [2:10:02, 22620.56 examples/s]
Generating train split: 116889291 examples [2:10:02, 22511.56 examples/s]
Generating train split: 116892275 examples [2:10:02, 23919.35 examples/s]
Generating train split: 116895937 examples [2:10:02, 26793.06 examples/s]
Generating train split: 116898849 examples [2:10:02, 25891.66 examples/s]
Generating train split: 116901599 examples [2:10:03, 24052.44 examples/s]
Generating train split: 116904118 examples [2:10:03, 21687.75 examples/s]
Generating train split: 116906389 examples [2:10:03, 15124.11 examples/s]
Generating train split: 116908219 examples [2:10:03, 14130.25 examples/s]
Generating train split: 116909848 examples [2:10:03, 12161.22 examples/s]
Generating train split: 116912649 examples [2:10:04, 15153.39 examples/s]
Generating train split: 116914459 examples [2:10:04, 14938.64 examples/s]
Generating train split: 116916372 examples [2:10:04, 15868.98 examples/s]
Generating train split: 116918129 examples [2:10:04, 14414.42 examples/s]
Generating train split: 116920343 examples [2:10:04, 16218.94 examples/s]
Generating train split: 116922113 examples [2:10:04, 14309.43 examples/s]
Generating train split: 116923686 examples [2:10:04, 13875.58 examples/s]
Generating train split: 116925760 examples [2:10:04, 15529.08 examples/s]
Generating train split: 116927417 examples [2:10:04, 14756.45 examples/s]
Generating train split: 116928965 examples [2:10:05, 12419.05 examples/s]
Generating train split: 116930960 examples [2:10:05, 14114.42 examples/s]
Generating train split: 116933017 examples [2:10:05, 15715.58 examples/s]
Generating train split: 116941534 examples [2:10:05, 33911.77 examples/s]
Generating train split: 116949435 examples [2:10:05, 46180.97 examples/s]
Generating train split: 116954429 examples [2:10:05, 28463.26 examples/s]
Generating train split: 116958366 examples [2:10:06, 20668.73 examples/s]
Generating train split: 116961461 examples [2:10:06, 16169.45 examples/s]
Generating train split: 116963909 examples [2:10:06, 13983.01 examples/s]
Generating train split: 116965900 examples [2:10:06, 14378.86 examples/s]
Generating train split: 116967789 examples [2:10:07, 11311.01 examples/s]
Generating train split: 116969777 examples [2:10:07, 12564.57 examples/s]
Generating train split: 116971423 examples [2:10:07, 11708.95 examples/s]
Generating train split: 116972869 examples [2:10:07, 12177.82 examples/s]
Generating train split: 116980745 examples [2:10:07, 25788.17 examples/s]
Generating train split: 116989405 examples [2:10:07, 39522.19 examples/s]
Generating train split: 116994359 examples [2:10:08, 36635.89 examples/s]
Generating train split: 116998755 examples [2:10:08, 24459.69 examples/s]
Generating train split: 117002217 examples [2:10:08, 20005.81 examples/s]
Generating train split: 117005016 examples [2:10:08, 18223.73 examples/s]
Generating train split: 117007384 examples [2:10:09, 13059.89 examples/s]
Generating train split: 117009328 examples [2:10:09, 13931.10 examples/s]
Generating train split: 117011207 examples [2:10:09, 12610.16 examples/s]
Generating train split: 117012806 examples [2:10:09, 12957.77 examples/s]
Generating train split: 117014881 examples [2:10:09, 14424.55 examples/s]
Generating train split: 117016596 examples [2:10:09, 12999.99 examples/s]
Generating train split: 117018474 examples [2:10:10, 14208.25 examples/s]
Generating train split: 117020082 examples [2:10:10, 12202.48 examples/s]
Generating train split: 117021471 examples [2:10:10, 11985.89 examples/s]
Generating train split: 117022788 examples [2:10:10, 11362.20 examples/s]
Generating train split: 117024006 examples [2:10:10, 9691.83 examples/s] 
Generating train split: 117025544 examples [2:10:10, 10917.11 examples/s]
Generating train split: 117026748 examples [2:10:10, 9728.92 examples/s] 
Generating train split: 117027816 examples [2:10:11, 9302.70 examples/s]
Generating train split: 117029730 examples [2:10:11, 11581.79 examples/s]
Generating train split: 117030998 examples [2:10:11, 9718.41 examples/s] 
Generating train split: 117032356 examples [2:10:11, 10547.48 examples/s]
Generating train split: 117033523 examples [2:10:11, 10344.07 examples/s]
Generating train split: 117036134 examples [2:10:11, 14260.70 examples/s]
Generating train split: 117037698 examples [2:10:11, 11966.49 examples/s]
Generating train split: 117039049 examples [2:10:12, 10959.59 examples/s]
Generating train split: 117040262 examples [2:10:12, 9262.43 examples/s] 
Generating train split: 117042615 examples [2:10:12, 12288.97 examples/s]
Generating train split: 117044108 examples [2:10:12, 12903.41 examples/s]
Generating train split: 117045990 examples [2:10:12, 14375.06 examples/s]
Generating train split: 117047566 examples [2:10:12, 9228.86 examples/s] 
Generating train split: 117048816 examples [2:10:12, 9287.56 examples/s]
Generating train split: 117049987 examples [2:10:13, 8803.75 examples/s]
Generating train split: 117051768 examples [2:10:13, 10665.45 examples/s]
Generating train split: 117053029 examples [2:10:13, 10635.38 examples/s]
Generating train split: 117054235 examples [2:10:13, 7832.66 examples/s] 
Generating train split: 117056557 examples [2:10:13, 10838.94 examples/s]
Generating train split: 117058831 examples [2:10:13, 13433.65 examples/s]
Generating train split: 117060488 examples [2:10:13, 12200.41 examples/s]
Generating train split: 117061949 examples [2:10:14, 11300.22 examples/s]
Generating train split: 117063251 examples [2:10:14, 10516.66 examples/s]
Generating train split: 117065124 examples [2:10:14, 12204.69 examples/s]
Generating train split: 117066477 examples [2:10:14, 9937.42 examples/s] 
Generating train split: 117068610 examples [2:10:14, 12356.03 examples/s]
Generating train split: 117070125 examples [2:10:14, 12989.34 examples/s]
Generating train split: 117071593 examples [2:10:15, 9366.54 examples/s] 
Generating train split: 117073879 examples [2:10:15, 12051.43 examples/s]
Generating train split: 117075401 examples [2:10:15, 10983.70 examples/s]
Generating train split: 117076724 examples [2:10:15, 9516.44 examples/s] 
Generating train split: 117077854 examples [2:10:15, 9544.30 examples/s]
Generating train split: 117078938 examples [2:10:15, 9586.41 examples/s]
Generating train split: 117079986 examples [2:10:15, 9641.51 examples/s]
Generating train split: 117081026 examples [2:10:16, 8937.14 examples/s]
Generating train split: 117082549 examples [2:10:16, 10464.99 examples/s]
Generating train split: 117083674 examples [2:10:16, 10632.58 examples/s]
Generating train split: 117084794 examples [2:10:16, 10776.81 examples/s]
Generating train split: 117085920 examples [2:10:16, 10330.25 examples/s]
Generating train split: 117087509 examples [2:10:16, 11798.61 examples/s]
Generating train split: 117088726 examples [2:10:16, 11751.72 examples/s]
Generating train split: 117089934 examples [2:10:16, 11127.00 examples/s]
Generating train split: 117091069 examples [2:10:16, 8118.55 examples/s] 
Generating train split: 117092007 examples [2:10:17, 8031.06 examples/s]
Generating train split: 117092899 examples [2:10:17, 8232.59 examples/s]
Generating train split: 117093802 examples [2:10:17, 7535.97 examples/s]
Generating train split: 117094683 examples [2:10:17, 7777.33 examples/s]
Generating train split: 117095889 examples [2:10:17, 8813.89 examples/s]
Generating train split: 117096817 examples [2:10:17, 6986.46 examples/s]
Generating train split: 117098123 examples [2:10:17, 8348.17 examples/s]
Generating train split: 117099658 examples [2:10:17, 10011.32 examples/s]
Generating train split: 117100766 examples [2:10:18, 8464.64 examples/s] 
Generating train split: 117102022 examples [2:10:18, 9419.08 examples/s]
Generating train split: 117103629 examples [2:10:18, 11054.37 examples/s]
Generating train split: 117105335 examples [2:10:18, 12602.35 examples/s]
Generating train split: 117106701 examples [2:10:18, 8664.12 examples/s] 
Generating train split: 117108302 examples [2:10:18, 10168.62 examples/s]
Generating train split: 117109844 examples [2:10:18, 11359.61 examples/s]
Generating train split: 117111185 examples [2:10:19, 10769.64 examples/s]
Generating train split: 117112960 examples [2:10:19, 12422.62 examples/s]
Generating train split: 117114340 examples [2:10:19, 12564.55 examples/s]
Generating train split: 117115953 examples [2:10:19, 13460.03 examples/s]
Generating train split: 117117387 examples [2:10:19, 10614.83 examples/s]
Generating train split: 117118600 examples [2:10:19, 10389.67 examples/s]
Generating train split: 117121237 examples [2:10:19, 14211.57 examples/s]
Generating train split: 117123270 examples [2:10:19, 15586.16 examples/s]
Generating train split: 117125084 examples [2:10:20, 16214.47 examples/s]
Generating train split: 117126808 examples [2:10:20, 12761.57 examples/s]
Generating train split: 117129223 examples [2:10:20, 15384.61 examples/s]
Generating train split: 117130975 examples [2:10:20, 15139.14 examples/s]
Generating train split: 117132630 examples [2:10:20, 12788.40 examples/s]
Generating train split: 117134068 examples [2:10:20, 9617.94 examples/s] 
Generating train split: 117135237 examples [2:10:21, 7654.51 examples/s]
Generating train split: 117136381 examples [2:10:21, 8314.25 examples/s]
Generating train split: 117137394 examples [2:10:21, 6845.00 examples/s]
Generating train split: 117139287 examples [2:10:21, 9059.04 examples/s]
Generating train split: 117146951 examples [2:10:21, 23085.14 examples/s]
Generating train split: 117156055 examples [2:10:21, 38620.48 examples/s]
Generating train split: 117160963 examples [2:10:21, 32726.80 examples/s]
Generating train split: 117165125 examples [2:10:22, 22807.27 examples/s]
Generating train split: 117168404 examples [2:10:22, 18981.35 examples/s]
Generating train split: 117171071 examples [2:10:22, 14088.54 examples/s]
Generating train split: 117173154 examples [2:10:23, 13216.15 examples/s]
Generating train split: 117174926 examples [2:10:23, 11158.11 examples/s]
Generating train split: 117176361 examples [2:10:23, 9093.74 examples/s] 
Generating train split: 117177517 examples [2:10:23, 8126.16 examples/s]
Generating train split: 117181139 examples [2:10:24, 12216.22 examples/s]
Generating train split: 117183390 examples [2:10:24, 13971.47 examples/s]
Generating train split: 117186568 examples [2:10:24, 17105.73 examples/s]
Generating train split: 117188761 examples [2:10:24, 17654.10 examples/s]
Generating train split: 117191891 examples [2:10:24, 20793.48 examples/s]
Generating train split: 117194484 examples [2:10:24, 22009.77 examples/s]
Generating train split: 117196955 examples [2:10:24, 19662.53 examples/s]
Generating train split: 117199147 examples [2:10:25, 13553.39 examples/s]
Generating train split: 117202173 examples [2:10:25, 16691.90 examples/s]
Generating train split: 117204306 examples [2:10:25, 16717.67 examples/s]
Generating train split: 117206303 examples [2:10:25, 15360.88 examples/s]
Generating train split: 117208368 examples [2:10:25, 16514.25 examples/s]
Generating train split: 117210226 examples [2:10:25, 15456.28 examples/s]
Generating train split: 117211920 examples [2:10:25, 11943.35 examples/s]
Generating train split: 117213523 examples [2:10:26, 12773.95 examples/s]
Generating train split: 117214994 examples [2:10:26, 9906.95 examples/s] 
Generating train split: 117216493 examples [2:10:26, 10884.84 examples/s]
Generating train split: 117218839 examples [2:10:26, 13611.87 examples/s]
Generating train split: 117226370 examples [2:10:26, 28213.55 examples/s]
Generating train split: 117233580 examples [2:10:26, 39290.41 examples/s]
Generating train split: 117238112 examples [2:10:27, 24202.49 examples/s]
Generating train split: 117241673 examples [2:10:27, 22324.94 examples/s]
Generating train split: 117244705 examples [2:10:27, 15670.52 examples/s]
Generating train split: 117247069 examples [2:10:27, 13220.24 examples/s]
Generating train split: 117248964 examples [2:10:28, 13312.03 examples/s]
Generating train split: 117255154 examples [2:10:28, 21099.95 examples/s]
Generating train split: 117263292 examples [2:10:28, 32331.26 examples/s]
Generating train split: 117268201 examples [2:10:28, 35243.14 examples/s]
Generating train split: 117272777 examples [2:10:28, 25188.72 examples/s]
Generating train split: 117276415 examples [2:10:29, 14924.05 examples/s]
Generating train split: 117279164 examples [2:10:29, 14128.83 examples/s]
Generating train split: 117281438 examples [2:10:29, 14345.46 examples/s]
Generating train split: 117283489 examples [2:10:29, 12347.38 examples/s]
Generating train split: 117285250 examples [2:10:29, 13079.17 examples/s]
Generating train split: 117286937 examples [2:10:30, 12979.52 examples/s]
Generating train split: 117288497 examples [2:10:30, 10942.70 examples/s]
Generating train split: 117289808 examples [2:10:30, 10286.45 examples/s]
Generating train split: 117291149 examples [2:10:30, 10874.82 examples/s]
Generating train split: 117293403 examples [2:10:30, 13345.75 examples/s]
Generating train split: 117294934 examples [2:10:30, 11397.49 examples/s]
Generating train split: 117297189 examples [2:10:30, 13791.97 examples/s]
Generating train split: 117305376 examples [2:10:31, 29816.98 examples/s]
Generating train split: 117313189 examples [2:10:31, 41090.94 examples/s]
Generating train split: 117317860 examples [2:10:31, 20205.63 examples/s]
Generating train split: 117321390 examples [2:10:32, 16641.96 examples/s]
Generating train split: 117324178 examples [2:10:32, 13543.67 examples/s]
Generating train split: 117326369 examples [2:10:32, 12273.25 examples/s]
Generating train split: 117328175 examples [2:10:32, 11983.10 examples/s]
Generating train split: 117330467 examples [2:10:32, 13582.70 examples/s]
Generating train split: 117332266 examples [2:10:33, 10538.95 examples/s]
Generating train split: 117334319 examples [2:10:33, 12058.39 examples/s]
Generating train split: 117335934 examples [2:10:33, 8763.33 examples/s] 
Generating train split: 117337202 examples [2:10:33, 8988.26 examples/s]
Generating train split: 117338396 examples [2:10:33, 8341.81 examples/s]
Generating train split: 117340227 examples [2:10:34, 10094.90 examples/s]
Generating train split: 117341802 examples [2:10:34, 11232.96 examples/s]
Generating train split: 117343170 examples [2:10:34, 10539.60 examples/s]
Generating train split: 117344979 examples [2:10:34, 12211.56 examples/s]
Generating train split: 117346384 examples [2:10:34, 11866.94 examples/s]
Generating train split: 117348205 examples [2:10:34, 13233.16 examples/s]
Generating train split: 117349694 examples [2:10:34, 13644.43 examples/s]
Generating train split: 117352000 examples [2:10:34, 16158.03 examples/s]
Generating train split: 117353708 examples [2:10:35, 13320.85 examples/s]
Generating train split: 117355182 examples [2:10:35, 11068.58 examples/s]
Generating train split: 117356437 examples [2:10:35, 10088.52 examples/s]
Generating train split: 117358408 examples [2:10:35, 12144.65 examples/s]
Generating train split: 117361470 examples [2:10:35, 16472.27 examples/s]
Generating train split: 117363642 examples [2:10:35, 17732.07 examples/s]
Generating train split: 117365593 examples [2:10:35, 13303.99 examples/s]
Generating train split: 117367213 examples [2:10:36, 13434.66 examples/s]
Generating train split: 117368928 examples [2:10:36, 14165.69 examples/s]
Generating train split: 117370503 examples [2:10:36, 10752.21 examples/s]
Generating train split: 117373012 examples [2:10:36, 13694.77 examples/s]
Generating train split: 117374681 examples [2:10:36, 8544.80 examples/s] 
Generating train split: 117377036 examples [2:10:36, 10952.43 examples/s]
Generating train split: 117378650 examples [2:10:37, 8603.56 examples/s] 
Generating train split: 117379934 examples [2:10:37, 8513.48 examples/s]
Generating train split: 117387457 examples [2:10:37, 20175.67 examples/s]
Generating train split: 117396727 examples [2:10:37, 34668.38 examples/s]
Generating train split: 117401648 examples [2:10:37, 32423.41 examples/s]
Generating train split: 117405941 examples [2:10:38, 22013.05 examples/s]
Generating train split: 117409298 examples [2:10:38, 13764.30 examples/s]
Generating train split: 117411827 examples [2:10:39, 12791.09 examples/s]
Generating train split: 117413905 examples [2:10:39, 13644.86 examples/s]
Generating train split: 117415933 examples [2:10:39, 11448.06 examples/s]
Generating train split: 117418411 examples [2:10:39, 13356.52 examples/s]
Generating train split: 117425253 examples [2:10:39, 22711.33 examples/s]
Generating train split: 117433471 examples [2:10:39, 34318.85 examples/s]
Generating train split: 117438293 examples [2:10:40, 26152.62 examples/s]
Generating train split: 117442157 examples [2:10:40, 20794.53 examples/s]
Generating train split: 117445251 examples [2:10:40, 18706.08 examples/s]
Generating train split: 117447840 examples [2:10:40, 16987.78 examples/s]
Generating train split: 117450026 examples [2:10:40, 14812.02 examples/s]
Generating train split: 117451849 examples [2:10:41, 14584.26 examples/s]
Generating train split: 117453667 examples [2:10:41, 15230.64 examples/s]
Generating train split: 117455393 examples [2:10:41, 14953.39 examples/s]
Generating train split: 117457867 examples [2:10:41, 17069.85 examples/s]
Generating train split: 117459764 examples [2:10:41, 17495.10 examples/s]
Generating train split: 117461977 examples [2:10:41, 18562.61 examples/s]
Generating train split: 117463957 examples [2:10:41, 15886.36 examples/s]
Generating train split: 117465681 examples [2:10:42, 12086.47 examples/s]
Generating train split: 117467114 examples [2:10:42, 10177.20 examples/s]
Generating train split: 117468310 examples [2:10:42, 9545.47 examples/s] 
Generating train split: 117469746 examples [2:10:42, 10499.93 examples/s]
Generating train split: 117471773 examples [2:10:42, 12591.84 examples/s]
Generating train split: 117473207 examples [2:10:42, 12335.28 examples/s]
Generating train split: 117474560 examples [2:10:43, 8631.53 examples/s] 
Generating train split: 117476006 examples [2:10:43, 9732.23 examples/s]
Generating train split: 117477278 examples [2:10:43, 10375.36 examples/s]
Generating train split: 117478489 examples [2:10:43, 8393.72 examples/s] 
Generating train split: 117479799 examples [2:10:43, 9362.87 examples/s]
Generating train split: 117480912 examples [2:10:43, 9746.32 examples/s]
Generating train split: 117482018 examples [2:10:43, 8412.56 examples/s]
Generating train split: 117483471 examples [2:10:43, 9750.60 examples/s]
Generating train split: 117484872 examples [2:10:44, 10783.67 examples/s]
Generating train split: 117486063 examples [2:10:44, 10079.63 examples/s]
Generating train split: 117487156 examples [2:10:44, 8159.46 examples/s] 
Generating train split: 117489081 examples [2:10:44, 10493.09 examples/s]
Generating train split: 117490278 examples [2:10:44, 7759.25 examples/s] 
Generating train split: 117491250 examples [2:10:44, 7500.08 examples/s]
Generating train split: 117499579 examples [2:10:44, 23026.49 examples/s]
Generating train split: 117508475 examples [2:10:45, 37950.68 examples/s]
Generating train split: 117513330 examples [2:10:45, 30527.80 examples/s]
Generating train split: 117522205 examples [2:10:45, 42645.06 examples/s]
Generating train split: 117531259 examples [2:10:45, 53614.01 examples/s]
Generating train split: 117537816 examples [2:10:45, 36831.75 examples/s]
Generating train split: 117543018 examples [2:10:46, 26070.53 examples/s]
Generating train split: 117547080 examples [2:10:46, 19255.50 examples/s]
Generating train split: 117550227 examples [2:10:46, 17370.99 examples/s]
Generating train split: 117552790 examples [2:10:47, 15205.61 examples/s]
Generating train split: 117554876 examples [2:10:47, 15374.54 examples/s]
Generating train split: 117556825 examples [2:10:47, 15159.90 examples/s]
Generating train split: 117558625 examples [2:10:47, 15607.30 examples/s]
Generating train split: 117560415 examples [2:10:47, 13553.28 examples/s]
Generating train split: 117561951 examples [2:10:47, 13736.83 examples/s]
Generating train split: 117563459 examples [2:10:47, 12932.54 examples/s]
Generating train split: 117565639 examples [2:10:48, 14882.22 examples/s]
Generating train split: 117567263 examples [2:10:48, 13931.83 examples/s]
Generating train split: 117569121 examples [2:10:48, 15031.05 examples/s]
Generating train split: 117570721 examples [2:10:48, 13363.20 examples/s]
Generating train split: 117572155 examples [2:10:48, 13411.43 examples/s]
Generating train split: 117574473 examples [2:10:48, 15871.08 examples/s]
Generating train split: 117576154 examples [2:10:48, 12272.81 examples/s]
Generating train split: 117579512 examples [2:10:48, 17000.74 examples/s]
Generating train split: 117584664 examples [2:10:49, 25350.58 examples/s]
Generating train split: 117593110 examples [2:10:49, 40526.20 examples/s]
Generating train split: 117601249 examples [2:10:49, 51488.80 examples/s]
Generating train split: 117606902 examples [2:10:49, 30737.58 examples/s]
Generating train split: 117611328 examples [2:10:49, 23542.01 examples/s]
Generating train split: 117614852 examples [2:10:50, 23067.68 examples/s]
Generating train split: 117617966 examples [2:10:50, 19986.03 examples/s]
Generating train split: 117620544 examples [2:10:50, 17321.07 examples/s]
Generating train split: 117622694 examples [2:10:50, 17524.56 examples/s]
Generating train split: 117624750 examples [2:10:50, 13875.39 examples/s]
Generating train split: 117626432 examples [2:10:51, 13718.97 examples/s]
Generating train split: 117628001 examples [2:10:51, 13187.51 examples/s]
Generating train split: 117629452 examples [2:10:51, 12690.02 examples/s]
Generating train split: 117630801 examples [2:10:51, 9927.11 examples/s] 
Generating train split: 117631915 examples [2:10:51, 9088.57 examples/s]
Generating train split: 117633548 examples [2:10:51, 10312.54 examples/s]
Generating train split: 117634689 examples [2:10:52, 9138.94 examples/s] 
Generating train split: 117636917 examples [2:10:52, 11660.39 examples/s]
Generating train split: 117638229 examples [2:10:52, 11562.13 examples/s]
Generating train split: 117640031 examples [2:10:52, 13075.86 examples/s]
Generating train split: 117641448 examples [2:10:52, 11834.40 examples/s]
Generating train split: 117642721 examples [2:10:52, 11374.26 examples/s]
Generating train split: 117646799 examples [2:10:52, 18632.16 examples/s]
Generating train split: 117655271 examples [2:10:52, 35859.73 examples/s]
Generating train split: 117660937 examples [2:10:52, 41492.63 examples/s]
Generating train split: 117665431 examples [2:10:53, 30390.14 examples/s]
Generating train split: 117669138 examples [2:10:53, 21942.56 examples/s]
Generating train split: 117672099 examples [2:10:53, 19827.20 examples/s]
Generating train split: 117674616 examples [2:10:53, 16142.26 examples/s]
Generating train split: 117676676 examples [2:10:54, 16214.52 examples/s]
Generating train split: 117684816 examples [2:10:54, 28281.47 examples/s]
Generating train split: 117693134 examples [2:10:54, 39755.48 examples/s]
Generating train split: 117698288 examples [2:10:54, 32343.01 examples/s]
Generating train split: 117702556 examples [2:10:55, 18188.46 examples/s]
Generating train split: 117705772 examples [2:10:55, 16711.89 examples/s]
Generating train split: 117708419 examples [2:10:55, 14684.39 examples/s]
Generating train split: 117710568 examples [2:10:55, 13321.01 examples/s]
Generating train split: 117712356 examples [2:10:56, 11108.75 examples/s]
Generating train split: 117713801 examples [2:10:56, 10539.61 examples/s]
Generating train split: 117715075 examples [2:10:56, 8579.31 examples/s] 
Generating train split: 117716269 examples [2:10:56, 9063.30 examples/s]
Generating train split: 117717346 examples [2:10:56, 7595.25 examples/s]
Generating train split: 117718237 examples [2:10:56, 7624.80 examples/s]
Generating train split: 117719101 examples [2:10:57, 6910.17 examples/s]
Generating train split: 117719945 examples [2:10:57, 7103.96 examples/s]
Generating train split: 117720713 examples [2:10:57, 7097.86 examples/s]
Generating train split: 117722354 examples [2:10:57, 9231.25 examples/s]
Generating train split: 117723374 examples [2:10:57, 6996.10 examples/s]
Generating train split: 117724208 examples [2:10:57, 6666.77 examples/s]
Generating train split: 117725560 examples [2:10:57, 8047.76 examples/s]
Generating train split: 117726493 examples [2:10:58, 7932.06 examples/s]
Generating train split: 117727467 examples [2:10:58, 8334.00 examples/s]
Generating train split: 117728770 examples [2:10:58, 9513.27 examples/s]
Generating train split: 117731267 examples [2:10:58, 13621.27 examples/s]
Generating train split: 117732729 examples [2:10:58, 13356.17 examples/s]
Generating train split: 117734141 examples [2:10:58, 9648.50 examples/s] 
Generating train split: 117735295 examples [2:10:58, 8858.13 examples/s]
Generating train split: 117736663 examples [2:10:58, 9874.48 examples/s]
Generating train split: 117737895 examples [2:10:59, 10403.02 examples/s]
Generating train split: 117739044 examples [2:10:59, 8357.33 examples/s] 
Generating train split: 117740992 examples [2:10:59, 10715.19 examples/s]
Generating train split: 117742527 examples [2:10:59, 11783.59 examples/s]
Generating train split: 117743878 examples [2:10:59, 9924.46 examples/s] 
Generating train split: 117745026 examples [2:10:59, 9413.16 examples/s]
Generating train split: 117747800 examples [2:10:59, 13579.60 examples/s]
Generating train split: 117749764 examples [2:11:00, 15017.98 examples/s]
Generating train split: 117751445 examples [2:11:00, 10932.62 examples/s]
Generating train split: 117753907 examples [2:11:00, 13690.13 examples/s]
Generating train split: 117761765 examples [2:11:00, 28449.59 examples/s]
Generating train split: 117770511 examples [2:11:00, 42909.54 examples/s]
Generating train split: 117775607 examples [2:11:00, 26153.86 examples/s]
Generating train split: 117779575 examples [2:11:01, 21051.15 examples/s]
Generating train split: 117782753 examples [2:11:01, 16055.18 examples/s]
Generating train split: 117785250 examples [2:11:01, 15707.11 examples/s]
Generating train split: 117787766 examples [2:11:01, 17132.68 examples/s]
Generating train split: 117790046 examples [2:11:02, 16555.09 examples/s]
Generating train split: 117792090 examples [2:11:02, 15265.86 examples/s]
Generating train split: 117794076 examples [2:11:02, 16143.06 examples/s]
Generating train split: 117796058 examples [2:11:02, 16887.94 examples/s]
Generating train split: 117798060 examples [2:11:02, 17536.31 examples/s]
Generating train split: 117799967 examples [2:11:02, 14344.20 examples/s]
Generating train split: 117801590 examples [2:11:02, 13330.80 examples/s]
Generating train split: 117803518 examples [2:11:03, 14558.02 examples/s]
Generating train split: 117805106 examples [2:11:03, 10140.78 examples/s]
Generating train split: 117807962 examples [2:11:03, 13629.41 examples/s]
Generating train split: 117809712 examples [2:11:03, 11639.00 examples/s]
Generating train split: 117811185 examples [2:11:03, 11025.25 examples/s]
Generating train split: 117813099 examples [2:11:03, 12630.12 examples/s]
Generating train split: 117814589 examples [2:11:04, 12245.62 examples/s]
Generating train split: 117815973 examples [2:11:04, 11336.96 examples/s]
Generating train split: 117818251 examples [2:11:04, 13876.44 examples/s]
Generating train split: 117819790 examples [2:11:04, 10412.29 examples/s]
Generating train split: 117821065 examples [2:11:04, 10517.86 examples/s]
Generating train split: 117822908 examples [2:11:04, 12247.27 examples/s]
Generating train split: 117824309 examples [2:11:04, 11325.34 examples/s]
Generating train split: 117825576 examples [2:11:05, 10320.59 examples/s]
Generating train split: 117827535 examples [2:11:05, 12383.18 examples/s]
Generating train split: 117828906 examples [2:11:05, 12327.60 examples/s]
Generating train split: 117830610 examples [2:11:05, 13499.40 examples/s]
Generating train split: 117832045 examples [2:11:05, 13543.75 examples/s]
Generating train split: 117833464 examples [2:11:05, 13447.68 examples/s]
Generating train split: 117834855 examples [2:11:05, 11889.84 examples/s]
Generating train split: 117836101 examples [2:11:05, 10097.99 examples/s]
Generating train split: 117837199 examples [2:11:06, 9485.52 examples/s] 
Generating train split: 117838215 examples [2:11:06, 9608.56 examples/s]
Generating train split: 117839221 examples [2:11:06, 8395.01 examples/s]
Generating train split: 117840172 examples [2:11:06, 8641.88 examples/s]
Generating train split: 117842063 examples [2:11:06, 11205.06 examples/s]
Generating train split: 117843259 examples [2:11:06, 10822.77 examples/s]
Generating train split: 117844393 examples [2:11:06, 10564.87 examples/s]
Generating train split: 117845488 examples [2:11:06, 8757.14 examples/s] 
Generating train split: 117846439 examples [2:11:07, 7521.92 examples/s]
Generating train split: 117847260 examples [2:11:07, 6626.76 examples/s]
Generating train split: 117847982 examples [2:11:07, 6739.30 examples/s]
Generating train split: 117848709 examples [2:11:07, 6813.09 examples/s]
Generating train split: 117849433 examples [2:11:07, 5909.20 examples/s]
Generating train split: 117850063 examples [2:11:07, 5459.65 examples/s]
Generating train split: 117851462 examples [2:11:07, 7446.69 examples/s]
Generating train split: 117859745 examples [2:11:07, 26267.79 examples/s]
Generating train split: 117868818 examples [2:11:08, 43210.49 examples/s]
Generating train split: 117873686 examples [2:11:08, 42964.42 examples/s]
Generating train split: 117878380 examples [2:11:08, 23303.99 examples/s]
Generating train split: 117881990 examples [2:11:08, 21501.47 examples/s]
Generating train split: 117885046 examples [2:11:09, 18021.55 examples/s]
Generating train split: 117887536 examples [2:11:09, 17736.24 examples/s]
Generating train split: 117889772 examples [2:11:09, 15021.72 examples/s]
Generating train split: 117891635 examples [2:11:09, 15042.10 examples/s]
Generating train split: 117893392 examples [2:11:09, 13537.80 examples/s]
Generating train split: 117894926 examples [2:11:09, 12780.02 examples/s]
Generating train split: 117898115 examples [2:11:10, 16595.03 examples/s]
Generating train split: 117900529 examples [2:11:10, 18259.43 examples/s]
Generating train split: 117902609 examples [2:11:10, 16352.27 examples/s]
Generating train split: 117904444 examples [2:11:10, 15856.18 examples/s]
Generating train split: 117906167 examples [2:11:10, 15065.75 examples/s]
Generating train split: 117907773 examples [2:11:10, 13948.19 examples/s]
Generating train split: 117909241 examples [2:11:10, 13887.49 examples/s]
Generating train split: 117911059 examples [2:11:10, 14745.48 examples/s]
Generating train split: 117912588 examples [2:11:11, 11969.42 examples/s]
Generating train split: 117914445 examples [2:11:11, 13472.89 examples/s]
Generating train split: 117916069 examples [2:11:11, 14157.07 examples/s]
Generating train split: 117917583 examples [2:11:11, 14147.27 examples/s]
Generating train split: 117919328 examples [2:11:11, 14930.00 examples/s]
Generating train split: 117920877 examples [2:11:11, 13000.30 examples/s]
Generating train split: 117923622 examples [2:11:11, 16658.40 examples/s]
Generating train split: 117925415 examples [2:11:11, 13230.53 examples/s]
Generating train split: 117926936 examples [2:11:12, 11188.24 examples/s]
Generating train split: 117928396 examples [2:11:12, 11776.84 examples/s]
Generating train split: 117929729 examples [2:11:12, 11279.25 examples/s]
Generating train split: 117931068 examples [2:11:12, 11745.34 examples/s]
Generating train split: 117932452 examples [2:11:12, 12235.74 examples/s]
Generating train split: 117933751 examples [2:11:12, 10753.95 examples/s]
Generating train split: 117934981 examples [2:11:12, 11127.70 examples/s]
Generating train split: 117936153 examples [2:11:12, 10309.85 examples/s]
Generating train split: 117937236 examples [2:11:13, 9647.13 examples/s] 
Generating train split: 117940471 examples [2:11:13, 15324.32 examples/s]
Generating train split: 117942147 examples [2:11:13, 12625.23 examples/s]
Generating train split: 117943588 examples [2:11:13, 11143.19 examples/s]
Generating train split: 117946016 examples [2:11:13, 14034.35 examples/s]
Generating train split: 117947637 examples [2:11:13, 11772.76 examples/s]
Generating train split: 117949012 examples [2:11:14, 9451.72 examples/s] 
Generating train split: 117950153 examples [2:11:14, 9322.16 examples/s]
Generating train split: 117951222 examples [2:11:14, 7709.44 examples/s]
Generating train split: 117952804 examples [2:11:14, 9180.31 examples/s]
Generating train split: 117954638 examples [2:11:14, 11124.67 examples/s]
Generating train split: 117955937 examples [2:11:14, 9227.96 examples/s] 
Generating train split: 117957037 examples [2:11:15, 8587.69 examples/s]
Generating train split: 117958361 examples [2:11:15, 9550.70 examples/s]
Generating train split: 117959703 examples [2:11:15, 10437.96 examples/s]
Generating train split: 117960938 examples [2:11:15, 10898.24 examples/s]
Generating train split: 117962119 examples [2:11:15, 8099.15 examples/s] 
Generating train split: 117963093 examples [2:11:15, 7388.39 examples/s]
Generating train split: 117964582 examples [2:11:15, 8781.46 examples/s]
Generating train split: 117965590 examples [2:11:16, 7493.42 examples/s]
Generating train split: 117967036 examples [2:11:16, 8912.59 examples/s]
Generating train split: 117969219 examples [2:11:16, 11896.77 examples/s]
Generating train split: 117970821 examples [2:11:16, 12919.55 examples/s]
Generating train split: 117972277 examples [2:11:16, 13348.65 examples/s]
Generating train split: 117974260 examples [2:11:16, 15098.81 examples/s]
Generating train split: 117975878 examples [2:11:16, 12712.16 examples/s]
Generating train split: 117977280 examples [2:11:16, 12843.54 examples/s]
Generating train split: 117979029 examples [2:11:16, 14013.20 examples/s]
Generating train split: 117980890 examples [2:11:17, 15228.80 examples/s]
Generating train split: 117983135 examples [2:11:17, 17088.10 examples/s]
Generating train split: 117984919 examples [2:11:17, 13932.48 examples/s]
Generating train split: 117986446 examples [2:11:17, 14058.66 examples/s]
Generating train split: 117989291 examples [2:11:17, 17743.56 examples/s]
Generating train split: 117991206 examples [2:11:17, 13513.28 examples/s]
Generating train split: 117993165 examples [2:11:17, 14861.88 examples/s]
Generating train split: 117995546 examples [2:11:17, 17016.14 examples/s]
Generating train split: 117997455 examples [2:11:18, 13912.38 examples/s]
Generating train split: 117999596 examples [2:11:18, 15593.15 examples/s]
Generating train split: 118001469 examples [2:11:18, 16314.89 examples/s]
Generating train split: 118003276 examples [2:11:18, 11693.89 examples/s]
Generating train split: 118004747 examples [2:11:18, 10906.08 examples/s]
Generating train split: 118007417 examples [2:11:18, 13931.41 examples/s]
Generating train split: 118009075 examples [2:11:19, 12311.07 examples/s]
Generating train split: 118010510 examples [2:11:19, 12503.07 examples/s]
Generating train split: 118011914 examples [2:11:19, 12611.74 examples/s]
Generating train split: 118013284 examples [2:11:19, 10785.49 examples/s]
Generating train split: 118014817 examples [2:11:19, 11804.29 examples/s]
Generating train split: 118017369 examples [2:11:19, 14966.74 examples/s]
Generating train split: 118019013 examples [2:11:19, 12695.36 examples/s]
Generating train split: 118020439 examples [2:11:20, 11273.62 examples/s]
Generating train split: 118021702 examples [2:11:20, 11568.65 examples/s]
Generating train split: 118022952 examples [2:11:20, 11775.99 examples/s]
Generating train split: 118024203 examples [2:11:20, 8999.19 examples/s] 
Generating train split: 118025609 examples [2:11:20, 10090.42 examples/s]
Generating train split: 118026920 examples [2:11:20, 10780.33 examples/s]
Generating train split: 118028117 examples [2:11:20, 8512.21 examples/s] 
Generating train split: 118029270 examples [2:11:20, 9101.39 examples/s]
Generating train split: 118030525 examples [2:11:21, 9910.54 examples/s]
Generating train split: 118031637 examples [2:11:21, 9997.20 examples/s]
Generating train split: 118032718 examples [2:11:21, 10048.28 examples/s]
Generating train split: 118034488 examples [2:11:21, 12036.20 examples/s]
Generating train split: 118035762 examples [2:11:21, 11270.49 examples/s]
Generating train split: 118036944 examples [2:11:21, 9818.50 examples/s] 
Generating train split: 118038914 examples [2:11:21, 12246.57 examples/s]
Generating train split: 118040238 examples [2:11:21, 11321.63 examples/s]
Generating train split: 118041449 examples [2:11:22, 11149.10 examples/s]
Generating train split: 118043418 examples [2:11:22, 13296.60 examples/s]
Generating train split: 118044823 examples [2:11:22, 11837.23 examples/s]
Generating train split: 118046084 examples [2:11:22, 11955.61 examples/s]
Generating train split: 118047482 examples [2:11:22, 12195.69 examples/s]
Generating train split: 118048906 examples [2:11:22, 12724.23 examples/s]
Generating train split: 118050226 examples [2:11:22, 11752.35 examples/s]
Generating train split: 118051436 examples [2:11:22, 9864.95 examples/s] 
Generating train split: 118052492 examples [2:11:23, 9003.98 examples/s]
Generating train split: 118053717 examples [2:11:23, 9753.49 examples/s]
Generating train split: 118055169 examples [2:11:23, 10907.98 examples/s]
Generating train split: 118056399 examples [2:11:23, 11270.81 examples/s]
Generating train split: 118058668 examples [2:11:23, 14357.68 examples/s]
Generating train split: 118062135 examples [2:11:23, 20041.05 examples/s]
Generating train split: 118064224 examples [2:11:23, 19798.77 examples/s]
Generating train split: 118066707 examples [2:11:23, 21125.11 examples/s]
Generating train split: 118068878 examples [2:11:23, 16316.90 examples/s]
Generating train split: 118071584 examples [2:11:24, 18875.92 examples/s]
Generating train split: 118074020 examples [2:11:24, 20208.22 examples/s]
Generating train split: 118076221 examples [2:11:24, 17934.80 examples/s]
Generating train split: 118078179 examples [2:11:24, 14956.30 examples/s]
Generating train split: 118079869 examples [2:11:24, 15389.23 examples/s]
Generating train split: 118081559 examples [2:11:24, 14874.36 examples/s]
Generating train split: 118083147 examples [2:11:24, 13982.24 examples/s]
Generating train split: 118084752 examples [2:11:25, 14433.19 examples/s]
Generating train split: 118087353 examples [2:11:25, 17417.91 examples/s]
Generating train split: 118094854 examples [2:11:25, 32952.59 examples/s]
Generating train split: 118102889 examples [2:11:25, 46112.74 examples/s]
Generating train split: 118107767 examples [2:11:25, 35238.58 examples/s]
Generating train split: 118111861 examples [2:11:25, 21339.84 examples/s]
Generating train split: 118115029 examples [2:11:26, 16546.53 examples/s]
Generating train split: 118117530 examples [2:11:26, 16539.74 examples/s]
Generating train split: 118119774 examples [2:11:26, 15473.12 examples/s]
Generating train split: 118123207 examples [2:11:26, 18634.18 examples/s]
Generating train split: 118125592 examples [2:11:26, 19426.00 examples/s]
Generating train split: 118127960 examples [2:11:27, 16419.59 examples/s]
Generating train split: 118129944 examples [2:11:27, 16175.38 examples/s]
Generating train split: 118131798 examples [2:11:27, 16223.80 examples/s]
Generating train split: 118133587 examples [2:11:27, 16031.19 examples/s]
Generating train split: 118135741 examples [2:11:27, 17239.43 examples/s]
Generating train split: 118137580 examples [2:11:27, 15011.40 examples/s]
Generating train split: 118139200 examples [2:11:27, 12688.20 examples/s]
Generating train split: 118140944 examples [2:11:27, 13723.73 examples/s]
Generating train split: 118142441 examples [2:11:28, 13226.30 examples/s]
Generating train split: 118144527 examples [2:11:28, 14966.31 examples/s]
Generating train split: 118146121 examples [2:11:28, 13218.16 examples/s]
Generating train split: 118153060 examples [2:11:28, 26769.09 examples/s]
Generating train split: 118161942 examples [2:11:28, 42663.79 examples/s]
Generating train split: 118166766 examples [2:11:28, 43513.21 examples/s]
Generating train split: 118171508 examples [2:11:29, 23921.49 examples/s]
Generating train split: 118175873 examples [2:11:29, 27316.46 examples/s]
Generating train split: 118179750 examples [2:11:29, 19548.99 examples/s]
Generating train split: 118182781 examples [2:11:29, 20350.49 examples/s]
Generating train split: 118185623 examples [2:11:29, 17067.75 examples/s]
Generating train split: 118189185 examples [2:11:29, 20139.83 examples/s]
Generating train split: 118191878 examples [2:11:30, 14628.52 examples/s]
Generating train split: 118193996 examples [2:11:30, 15204.18 examples/s]
Generating train split: 118196013 examples [2:11:30, 15878.64 examples/s]
Generating train split: 118197996 examples [2:11:30, 12242.90 examples/s]
Generating train split: 118200986 examples [2:11:30, 15318.94 examples/s]
Generating train split: 118203002 examples [2:11:31, 12731.49 examples/s]
Generating train split: 118204668 examples [2:11:31, 11598.75 examples/s]
Generating train split: 118206737 examples [2:11:31, 13103.34 examples/s]
Generating train split: 118208331 examples [2:11:31, 12079.23 examples/s]
Generating train split: 118209733 examples [2:11:31, 12190.63 examples/s]
Generating train split: 118211701 examples [2:11:31, 13856.41 examples/s]
Generating train split: 118213240 examples [2:11:31, 13837.39 examples/s]
Generating train split: 118214805 examples [2:11:32, 14261.99 examples/s]
Generating train split: 118216320 examples [2:11:32, 13123.50 examples/s]
Generating train split: 118217704 examples [2:11:32, 13211.24 examples/s]
Generating train split: 118219084 examples [2:11:32, 12879.47 examples/s]
Generating train split: 118220411 examples [2:11:32, 12632.67 examples/s]
Generating train split: 118221706 examples [2:11:32, 10714.53 examples/s]
Generating train split: 118223227 examples [2:11:32, 11731.15 examples/s]
Generating train split: 118224538 examples [2:11:32, 12073.33 examples/s]
Generating train split: 118225954 examples [2:11:32, 12628.59 examples/s]
Generating train split: 118227719 examples [2:11:33, 14023.35 examples/s]
Generating train split: 118229286 examples [2:11:33, 14162.92 examples/s]
Generating train split: 118230731 examples [2:11:33, 14095.28 examples/s]
Generating train split: 118232170 examples [2:11:33, 13369.00 examples/s]
Generating train split: 118233535 examples [2:11:33, 11598.34 examples/s]
Generating train split: 118235078 examples [2:11:33, 12567.07 examples/s]
Generating train split: 118236393 examples [2:11:33, 12112.43 examples/s]
Generating train split: 118238647 examples [2:11:33, 14851.82 examples/s]
Generating train split: 118241290 examples [2:11:34, 18003.93 examples/s]
Generating train split: 118243170 examples [2:11:34, 14995.66 examples/s]
Generating train split: 118244813 examples [2:11:34, 13652.00 examples/s]
Generating train split: 118246290 examples [2:11:34, 12524.58 examples/s]
Generating train split: 118247624 examples [2:11:34, 9771.37 examples/s] 
Generating train split: 118248952 examples [2:11:34, 10489.18 examples/s]
Generating train split: 118250579 examples [2:11:34, 11787.15 examples/s]
Generating train split: 118251897 examples [2:11:35, 11869.53 examples/s]
Generating train split: 118253182 examples [2:11:35, 11531.40 examples/s]
Generating train split: 118254403 examples [2:11:35, 10573.89 examples/s]
Generating train split: 118255812 examples [2:11:35, 11407.97 examples/s]
Generating train split: 118257006 examples [2:11:35, 11104.43 examples/s]
Generating train split: 118258158 examples [2:11:35, 10589.83 examples/s]
Generating train split: 118259928 examples [2:11:35, 12350.70 examples/s]
Generating train split: 118261325 examples [2:11:35, 12758.13 examples/s]
Generating train split: 118263091 examples [2:11:35, 14122.12 examples/s]
Generating train split: 118264690 examples [2:11:36, 14651.29 examples/s]
Generating train split: 118266855 examples [2:11:36, 16671.11 examples/s]
Generating train split: 118274970 examples [2:11:36, 35501.56 examples/s]
Generating train split: 118283471 examples [2:11:36, 50067.85 examples/s]
Generating train split: 118288556 examples [2:11:36, 35556.63 examples/s]
Generating train split: 118292758 examples [2:11:36, 24347.94 examples/s]
Generating train split: 118296081 examples [2:11:37, 18295.26 examples/s]
Generating train split: 118299513 examples [2:11:37, 20726.36 examples/s]
Generating train split: 118308359 examples [2:11:37, 32799.49 examples/s]
Generating train split: 118316691 examples [2:11:37, 43051.00 examples/s]
Generating train split: 118322453 examples [2:11:37, 26671.73 examples/s]
Generating train split: 118326897 examples [2:11:38, 22273.01 examples/s]
Generating train split: 118330446 examples [2:11:38, 19602.27 examples/s]
Generating train split: 118333334 examples [2:11:38, 17221.63 examples/s]
Generating train split: 118335714 examples [2:11:38, 16747.50 examples/s]
Generating train split: 118339251 examples [2:11:39, 19710.48 examples/s]
Generating train split: 118341796 examples [2:11:39, 16161.39 examples/s]
Generating train split: 118345237 examples [2:11:39, 19275.32 examples/s]
Generating train split: 118353371 examples [2:11:39, 31443.88 examples/s]
Generating train split: 118360314 examples [2:11:39, 39750.99 examples/s]
Generating train split: 118365323 examples [2:11:40, 22522.12 examples/s]
Generating train split: 118369162 examples [2:11:40, 18200.58 examples/s]
Generating train split: 118372182 examples [2:11:40, 15205.17 examples/s]
Generating train split: 118374589 examples [2:11:40, 13582.82 examples/s]
Generating train split: 118376546 examples [2:11:41, 12723.41 examples/s]
Generating train split: 118378213 examples [2:11:41, 12859.17 examples/s]
Generating train split: 118379800 examples [2:11:41, 13358.82 examples/s]
Generating train split: 118381382 examples [2:11:41, 13583.30 examples/s]
Generating train split: 118384070 examples [2:11:41, 16408.92 examples/s]
Generating train split: 118385955 examples [2:11:41, 16958.81 examples/s]
Generating train split: 118394068 examples [2:11:41, 32966.01 examples/s]
Generating train split: 118402440 examples [2:11:41, 46297.05 examples/s]
Generating train split: 118407579 examples [2:11:42, 29378.89 examples/s]
Generating train split: 118411644 examples [2:11:42, 21864.98 examples/s]
Generating train split: 118415157 examples [2:11:42, 23993.15 examples/s]
Generating train split: 118422138 examples [2:11:42, 32545.13 examples/s]
Generating train split: 118428027 examples [2:11:42, 38087.49 examples/s]
Generating train split: 118432885 examples [2:11:43, 24771.08 examples/s]
Generating train split: 118436677 examples [2:11:43, 16838.48 examples/s]
Generating train split: 118439586 examples [2:11:44, 14318.34 examples/s]
Generating train split: 118441886 examples [2:11:44, 10909.25 examples/s]
Generating train split: 118443687 examples [2:11:44, 11641.35 examples/s]
Generating train split: 118445449 examples [2:11:44, 10888.80 examples/s]
Generating train split: 118447224 examples [2:11:44, 11876.83 examples/s]
Generating train split: 118448797 examples [2:11:44, 11806.32 examples/s]
Generating train split: 118450247 examples [2:11:45, 11040.46 examples/s]
Generating train split: 118457461 examples [2:11:45, 22955.09 examples/s]
Generating train split: 118464250 examples [2:11:45, 32663.11 examples/s]
Generating train split: 118468408 examples [2:11:45, 29690.37 examples/s]
Generating train split: 118472040 examples [2:11:45, 23523.75 examples/s]
Generating train split: 118475032 examples [2:11:45, 23226.82 examples/s]
Generating train split: 118482671 examples [2:11:45, 34219.40 examples/s]
Generating train split: 118490538 examples [2:11:46, 44344.59 examples/s]
Generating train split: 118495856 examples [2:11:46, 33964.82 examples/s]
Generating train split: 118500222 examples [2:11:46, 21088.63 examples/s]
Generating train split: 118503571 examples [2:11:47, 17822.72 examples/s]
Generating train split: 118506253 examples [2:11:47, 17015.62 examples/s]
Generating train split: 118513631 examples [2:11:47, 25587.57 examples/s]
Generating train split: 118522159 examples [2:11:47, 36179.48 examples/s]
Generating train split: 118527680 examples [2:11:47, 39343.77 examples/s]
Generating train split: 118532887 examples [2:11:48, 23600.39 examples/s]
Generating train split: 118536876 examples [2:11:48, 19819.02 examples/s]
Generating train split: 118540052 examples [2:11:48, 19119.15 examples/s]
Generating train split: 118546531 examples [2:11:48, 26031.82 examples/s]
Generating train split: 118554757 examples [2:11:48, 36022.05 examples/s]
Generating train split: 118559933 examples [2:11:48, 31000.23 examples/s]
Generating train split: 118564219 examples [2:11:49, 23009.55 examples/s]
Generating train split: 118567605 examples [2:11:49, 19857.79 examples/s]
Generating train split: 118570377 examples [2:11:49, 19600.92 examples/s]
Generating train split: 118572872 examples [2:11:49, 15955.30 examples/s]
Generating train split: 118574896 examples [2:11:50, 15118.28 examples/s]
Generating train split: 118576692 examples [2:11:50, 12127.86 examples/s]
Generating train split: 118578219 examples [2:11:50, 12621.09 examples/s]
Generating train split: 118579827 examples [2:11:50, 13251.27 examples/s]
Generating train split: 118581348 examples [2:11:50, 11798.70 examples/s]
Generating train split: 118583474 examples [2:11:50, 13733.11 examples/s]
Generating train split: 118585139 examples [2:11:50, 14375.95 examples/s]
Generating train split: 118586729 examples [2:11:51, 11707.97 examples/s]
Generating train split: 118588074 examples [2:11:51, 10932.65 examples/s]
Generating train split: 118589294 examples [2:11:51, 9140.25 examples/s] 
Generating train split: 118590337 examples [2:11:51, 8219.61 examples/s]
Generating train split: 118591939 examples [2:11:51, 9792.73 examples/s]
Generating train split: 118593054 examples [2:11:51, 8978.21 examples/s]
Generating train split: 118594057 examples [2:11:52, 8998.18 examples/s]
Generating train split: 118595613 examples [2:11:52, 10509.30 examples/s]
Generating train split: 118596753 examples [2:11:52, 9131.65 examples/s] 
Generating train split: 118597755 examples [2:11:52, 8119.88 examples/s]
Generating train split: 118598650 examples [2:11:52, 5529.74 examples/s]
Generating train split: 118599750 examples [2:11:52, 6494.42 examples/s]
Generating train split: 118600958 examples [2:11:53, 7608.42 examples/s]
Generating train split: 118601893 examples [2:11:53, 7757.41 examples/s]
Generating train split: 118602794 examples [2:11:53, 7986.53 examples/s]
Generating train split: 118603696 examples [2:11:53, 7608.37 examples/s]
Generating train split: 118604632 examples [2:11:53, 8039.33 examples/s]
Generating train split: 118605595 examples [2:11:53, 8370.18 examples/s]
Generating train split: 118606478 examples [2:11:53, 8441.95 examples/s]
Generating train split: 118607509 examples [2:11:53, 8921.03 examples/s]
Generating train split: 118608434 examples [2:11:53, 7536.93 examples/s]
Generating train split: 118610245 examples [2:11:54, 10080.29 examples/s]
Generating train split: 118611329 examples [2:11:54, 9349.32 examples/s] 
Generating train split: 118612325 examples [2:11:54, 8274.57 examples/s]
Generating train split: 118614296 examples [2:11:54, 11011.27 examples/s]
Generating train split: 118616659 examples [2:11:54, 14170.84 examples/s]
Generating train split: 118618209 examples [2:11:54, 11821.64 examples/s]
Generating train split: 118620895 examples [2:11:54, 15372.12 examples/s]
Generating train split: 118622727 examples [2:11:54, 15545.47 examples/s]
Generating train split: 118624422 examples [2:11:55, 13350.41 examples/s]
Generating train split: 118626085 examples [2:11:55, 14107.07 examples/s]
Generating train split: 118628276 examples [2:11:55, 16044.00 examples/s]
Generating train split: 118630462 examples [2:11:55, 17571.62 examples/s]
Generating train split: 118632334 examples [2:11:55, 16708.76 examples/s]
Generating train split: 118634094 examples [2:11:55, 12648.23 examples/s]
Generating train split: 118635560 examples [2:11:55, 12890.69 examples/s]
Generating train split: 118637553 examples [2:11:56, 14561.09 examples/s]
Generating train split: 118639818 examples [2:11:56, 16610.35 examples/s]
Generating train split: 118642140 examples [2:11:56, 18136.59 examples/s]
Generating train split: 118644068 examples [2:11:56, 17974.64 examples/s]
Generating train split: 118645944 examples [2:11:56, 15441.06 examples/s]
Generating train split: 118648185 examples [2:11:56, 17141.05 examples/s]
Generating train split: 118650012 examples [2:11:56, 11988.42 examples/s]
Generating train split: 118651490 examples [2:11:56, 12223.99 examples/s]
Generating train split: 118653458 examples [2:11:57, 13874.63 examples/s]
Generating train split: 118655049 examples [2:11:57, 10809.59 examples/s]
Generating train split: 118658371 examples [2:11:57, 15414.56 examples/s]
Generating train split: 118660294 examples [2:11:57, 16070.15 examples/s]
Generating train split: 118662186 examples [2:11:57, 12507.93 examples/s]
Generating train split: 118663744 examples [2:11:57, 12607.24 examples/s]
Generating train split: 118665512 examples [2:11:57, 13702.34 examples/s]
Generating train split: 118667511 examples [2:11:58, 15191.50 examples/s]
Generating train split: 118669209 examples [2:11:58, 13649.59 examples/s]
Generating train split: 118670814 examples [2:11:58, 14167.77 examples/s]
Generating train split: 118673009 examples [2:11:58, 16038.44 examples/s]
Generating train split: 118674736 examples [2:11:58, 12743.34 examples/s]
Generating train split: 118676184 examples [2:11:58, 12528.53 examples/s]
Generating train split: 118678245 examples [2:11:58, 14435.77 examples/s]
Generating train split: 118679834 examples [2:11:58, 13941.75 examples/s]
Generating train split: 118685928 examples [2:11:59, 25865.34 examples/s]
Generating train split: 118694918 examples [2:11:59, 42895.24 examples/s]
Generating train split: 118699623 examples [2:11:59, 37846.64 examples/s]
Generating train split: 118703806 examples [2:11:59, 27370.56 examples/s]
Generating train split: 118707203 examples [2:12:00, 18191.38 examples/s]
Generating train split: 118709849 examples [2:12:00, 16304.95 examples/s]
Generating train split: 118712521 examples [2:12:00, 17928.46 examples/s]
Generating train split: 118714871 examples [2:12:00, 16904.77 examples/s]
Generating train split: 118716949 examples [2:12:00, 16850.43 examples/s]
Generating train split: 118719028 examples [2:12:00, 17657.59 examples/s]
Generating train split: 118721675 examples [2:12:00, 19627.35 examples/s]
Generating train split: 118724890 examples [2:12:00, 22647.78 examples/s]
Generating train split: 118730169 examples [2:12:01, 30410.50 examples/s]
Generating train split: 118735823 examples [2:12:01, 37443.22 examples/s]
Generating train split: 118743699 examples [2:12:01, 48919.66 examples/s]
Generating train split: 118750964 examples [2:12:01, 55646.25 examples/s]
Generating train split: 118758229 examples [2:12:01, 60539.24 examples/s]
Generating train split: 118764563 examples [2:12:01, 61327.40 examples/s]
Generating train split: 118770839 examples [2:12:01, 61698.42 examples/s]
Generating train split: 118777115 examples [2:12:01, 61071.15 examples/s]
Generating train split: 118784773 examples [2:12:01, 65606.72 examples/s]
Generating train split: 118791541 examples [2:12:01, 66218.21 examples/s]
Generating train split: 118798206 examples [2:12:02, 65705.99 examples/s]
Generating train split: 118804965 examples [2:12:02, 66261.27 examples/s]
Generating train split: 118811626 examples [2:12:02, 65839.76 examples/s]
Generating train split: 118818227 examples [2:12:02, 62026.71 examples/s]
Generating train split: 118824486 examples [2:12:02, 61613.01 examples/s]
Generating train split: 118830686 examples [2:12:02, 60723.17 examples/s]
Generating train split: 118837292 examples [2:12:02, 62225.97 examples/s]
Generating train split: 118843551 examples [2:12:02, 60314.99 examples/s]
Generating train split: 118849622 examples [2:12:02, 58646.50 examples/s]
Generating train split: 118855509 examples [2:12:03, 55840.40 examples/s]
Generating train split: 118861140 examples [2:12:03, 51328.43 examples/s]
Generating train split: 118866356 examples [2:12:03, 45651.90 examples/s]
Generating train split: 118871561 examples [2:12:03, 47255.65 examples/s]
Generating train split: 118876414 examples [2:12:03, 47592.03 examples/s]
Generating train split: 118881266 examples [2:12:03, 46856.03 examples/s]
Generating train split: 118886013 examples [2:12:03, 41743.03 examples/s]
Generating train split: 118890332 examples [2:12:03, 36359.62 examples/s]
Generating train split: 118894150 examples [2:12:04, 35444.69 examples/s]
Generating train split: 118898822 examples [2:12:04, 38267.31 examples/s]
Generating train split: 118902963 examples [2:12:04, 39088.06 examples/s]
Generating train split: 118906984 examples [2:12:04, 31655.25 examples/s]
Generating train split: 118910439 examples [2:12:04, 29627.71 examples/s]
Generating train split: 118913993 examples [2:12:04, 30974.22 examples/s]
Generating train split: 118917273 examples [2:12:04, 25594.78 examples/s]
Generating train split: 118920087 examples [2:12:04, 25392.34 examples/s]
Generating train split: 118922800 examples [2:12:05, 25678.27 examples/s]
Generating train split: 118926418 examples [2:12:05, 28275.72 examples/s]
Generating train split: 118929661 examples [2:12:05, 29281.05 examples/s]
Generating train split: 118932698 examples [2:12:05, 20198.05 examples/s]
Generating train split: 118935168 examples [2:12:05, 16543.38 examples/s]
Generating train split: 118938284 examples [2:12:05, 19212.60 examples/s]
Generating train split: 118940627 examples [2:12:05, 20080.79 examples/s]
Generating train split: 118943566 examples [2:12:06, 22153.44 examples/s]
Generating train split: 118946071 examples [2:12:06, 20838.60 examples/s]
Generating train split: 118948367 examples [2:12:06, 17945.76 examples/s]
Generating train split: 118950785 examples [2:12:06, 19322.92 examples/s]
Generating train split: 118952908 examples [2:12:06, 18096.84 examples/s]
Generating train split: 118954859 examples [2:12:06, 17402.29 examples/s]
Generating train split: 118957193 examples [2:12:06, 18854.48 examples/s]
Generating train split: 118959225 examples [2:12:06, 18742.72 examples/s]
Generating train split: 118961164 examples [2:12:07, 13270.44 examples/s]
Generating train split: 118963679 examples [2:12:07, 15768.32 examples/s]
Generating train split: 118966047 examples [2:12:07, 17559.42 examples/s]
Generating train split: 118968665 examples [2:12:07, 19686.56 examples/s]
Generating train split: 118970865 examples [2:12:07, 16985.58 examples/s]
Generating train split: 118972970 examples [2:12:07, 17948.14 examples/s]
Generating train split: 118974943 examples [2:12:07, 14626.01 examples/s]
Generating train split: 118976797 examples [2:12:08, 15474.94 examples/s]
Generating train split: 118978524 examples [2:12:08, 15836.98 examples/s]
Generating train split: 118980771 examples [2:12:08, 17527.90 examples/s]
Generating train split: 118983506 examples [2:12:08, 19794.70 examples/s]
Generating train split: 118985599 examples [2:12:08, 18133.72 examples/s]
Generating train split: 118987509 examples [2:12:08, 18081.66 examples/s]
Generating train split: 118989385 examples [2:12:08, 15647.34 examples/s]
Generating train split: 118991990 examples [2:12:08, 18104.35 examples/s]
Generating train split: 118993920 examples [2:12:09, 15709.63 examples/s]
Generating train split: 118996081 examples [2:12:09, 17077.21 examples/s]
Generating train split: 118997909 examples [2:12:09, 17145.95 examples/s]
Generating train split: 118999712 examples [2:12:09, 14746.64 examples/s]
Generating train split: 119002263 examples [2:12:09, 17309.72 examples/s]
Generating train split: 119004130 examples [2:12:09, 16055.22 examples/s]
Generating train split: 119005841 examples [2:12:09, 14810.00 examples/s]
Generating train split: 119009124 examples [2:12:09, 19147.36 examples/s]
Generating train split: 119011402 examples [2:12:10, 20080.67 examples/s]
Generating train split: 119013812 examples [2:12:10, 21036.51 examples/s]
Generating train split: 119016018 examples [2:12:10, 16901.10 examples/s]
Generating train split: 119019304 examples [2:12:10, 20683.85 examples/s]
Generating train split: 119021609 examples [2:12:10, 17400.63 examples/s]
Generating train split: 119024591 examples [2:12:10, 20228.01 examples/s]
Generating train split: 119027295 examples [2:12:10, 21883.31 examples/s]
Generating train split: 119029698 examples [2:12:11, 18113.27 examples/s]
Generating train split: 119031764 examples [2:12:11, 15401.17 examples/s]
Generating train split: 119035072 examples [2:12:11, 19167.56 examples/s]
Generating train split: 119037299 examples [2:12:11, 16342.06 examples/s]
Generating train split: 119039209 examples [2:12:11, 13744.27 examples/s]
Generating train split: 119041169 examples [2:12:11, 14837.32 examples/s]
Generating train split: 119042868 examples [2:12:11, 14437.78 examples/s]
Generating train split: 119044828 examples [2:12:12, 15616.06 examples/s]
Generating train split: 119046712 examples [2:12:12, 16367.37 examples/s]
Generating train split: 119049019 examples [2:12:12, 18054.86 examples/s]
Generating train split: 119050932 examples [2:12:12, 15423.18 examples/s]
Generating train split: 119052614 examples [2:12:12, 14767.58 examples/s]
Generating train split: 119054401 examples [2:12:12, 15447.19 examples/s]
Generating train split: 119056030 examples [2:12:12, 13975.62 examples/s]
Generating train split: 119057509 examples [2:12:13, 10354.14 examples/s]
Generating train split: 119059179 examples [2:12:13, 11637.31 examples/s]
Generating train split: 119060520 examples [2:12:13, 10742.29 examples/s]
Generating train split: 119062383 examples [2:12:13, 12323.02 examples/s]
Generating train split: 119063870 examples [2:12:13, 12786.01 examples/s]
Generating train split: 119065261 examples [2:12:13, 12229.14 examples/s]
Generating train split: 119066563 examples [2:12:13, 10814.16 examples/s]
Generating train split: 119069686 examples [2:12:13, 15468.48 examples/s]
Generating train split: 119071772 examples [2:12:13, 16655.34 examples/s]
Generating train split: 119073560 examples [2:12:14, 15792.77 examples/s]
Generating train split: 119079218 examples [2:12:14, 26304.81 examples/s]
Generating train split: 119082072 examples [2:12:14, 25761.08 examples/s]
Generating train split: 119085206 examples [2:12:14, 27246.49 examples/s]
Generating train split: 119088067 examples [2:12:14, 24097.58 examples/s]
Generating train split: 119091069 examples [2:12:14, 25537.05 examples/s]
Generating train split: 119093753 examples [2:12:14, 25593.34 examples/s]
Generating train split: 119096615 examples [2:12:14, 26424.31 examples/s]
Generating train split: 119099331 examples [2:12:15, 23252.60 examples/s]
Generating train split: 119101778 examples [2:12:15, 18004.80 examples/s]
Generating train split: 119103819 examples [2:12:15, 17882.26 examples/s]
Generating train split: 119105773 examples [2:12:15, 15140.99 examples/s]
Generating train split: 119107454 examples [2:12:15, 13639.25 examples/s]
Generating train split: 119109308 examples [2:12:15, 14661.20 examples/s]
Generating train split: 119110915 examples [2:12:15, 14520.10 examples/s]
Generating train split: 119112461 examples [2:12:16, 14454.94 examples/s]
Generating train split: 119113966 examples [2:12:16, 14001.84 examples/s]
Generating train split: 119115679 examples [2:12:16, 14490.18 examples/s]
Generating train split: 119117483 examples [2:12:16, 15408.92 examples/s]
Generating train split: 119119070 examples [2:12:16, 15340.00 examples/s]
Generating train split: 119120632 examples [2:12:16, 14049.17 examples/s]
Generating train split: 119122266 examples [2:12:16, 14573.02 examples/s]
Generating train split: 119123760 examples [2:12:16, 11226.15 examples/s]
Generating train split: 119125475 examples [2:12:17, 12588.60 examples/s]
Generating train split: 119126941 examples [2:12:17, 13081.99 examples/s]
Generating train split: 119133910 examples [2:12:17, 27865.24 examples/s]
Generating train split: 119142101 examples [2:12:17, 42541.64 examples/s]
Generating train split: 119148360 examples [2:12:17, 48084.08 examples/s]
Generating train split: 119153461 examples [2:12:17, 23871.68 examples/s]
Generating train split: 119157358 examples [2:12:18, 14847.19 examples/s]
Generating train split: 119160302 examples [2:12:18, 11346.65 examples/s]
Generating train split: 119162552 examples [2:12:19, 11078.22 examples/s]
Generating train split: 119164493 examples [2:12:19, 12034.73 examples/s]
Generating train split: 119166388 examples [2:12:19, 9877.85 examples/s] 
Generating train split: 119167890 examples [2:12:19, 9920.67 examples/s]
Generating train split: 119169241 examples [2:12:19, 10248.72 examples/s]
Generating train split: 119171500 examples [2:12:19, 12404.54 examples/s]
Generating train split: 119173470 examples [2:12:20, 13858.38 examples/s]
Generating train split: 119175173 examples [2:12:20, 13710.16 examples/s]
Generating train split: 119177402 examples [2:12:20, 15679.42 examples/s]
Generating train split: 119184835 examples [2:12:20, 30179.03 examples/s]
Generating train split: 119191534 examples [2:12:20, 39763.19 examples/s]
Generating train split: 119195981 examples [2:12:20, 30073.64 examples/s]
Generating train split: 119199657 examples [2:12:21, 21707.11 examples/s]
Generating train split: 119202595 examples [2:12:21, 19587.82 examples/s]
Generating train split: 119205096 examples [2:12:21, 18155.90 examples/s]
Generating train split: 119207281 examples [2:12:21, 18587.15 examples/s]
Generating train split: 119214846 examples [2:12:21, 30312.00 examples/s]
Generating train split: 119223261 examples [2:12:21, 42519.97 examples/s]
Generating train split: 119228423 examples [2:12:21, 31950.10 examples/s]
Generating train split: 119233071 examples [2:12:22, 34845.20 examples/s]
Generating train split: 119241855 examples [2:12:22, 46601.59 examples/s]
Generating train split: 119247603 examples [2:12:22, 49200.66 examples/s]
Generating train split: 119253298 examples [2:12:22, 36856.73 examples/s]
Generating train split: 119257967 examples [2:12:22, 30476.39 examples/s]
Generating train split: 119261838 examples [2:12:22, 28349.38 examples/s]
Generating train split: 119265236 examples [2:12:23, 24363.44 examples/s]
Generating train split: 119268115 examples [2:12:23, 21288.96 examples/s]
Generating train split: 119270558 examples [2:12:23, 20911.61 examples/s]
Generating train split: 119274493 examples [2:12:23, 24601.64 examples/s]
Generating train split: 119277285 examples [2:12:23, 24979.39 examples/s]
Generating train split: 119280035 examples [2:12:23, 24293.02 examples/s]
Generating train split: 119282959 examples [2:12:23, 25495.22 examples/s]
Generating train split: 119291086 examples [2:12:24, 39926.42 examples/s]
Generating train split: 119296416 examples [2:12:24, 43402.30 examples/s]
Generating train split: 119301022 examples [2:12:24, 30985.85 examples/s]
Generating train split: 119304793 examples [2:12:24, 26122.27 examples/s]
Generating train split: 119307968 examples [2:12:24, 22771.46 examples/s]
Generating train split: 119310677 examples [2:12:24, 22549.67 examples/s]
Generating train split: 119313376 examples [2:12:24, 23473.42 examples/s]
Generating train split: 119320546 examples [2:12:25, 34536.61 examples/s]
Generating train split: 119327690 examples [2:12:25, 43639.84 examples/s]
Generating train split: 119332623 examples [2:12:25, 38286.38 examples/s]
Generating train split: 119336955 examples [2:12:25, 29807.44 examples/s]
Generating train split: 119340539 examples [2:12:25, 25028.13 examples/s]
Generating train split: 119343543 examples [2:12:25, 25272.66 examples/s]
Generating train split: 119346436 examples [2:12:26, 20189.68 examples/s]
Generating train split: 119348821 examples [2:12:26, 20065.13 examples/s]
Generating train split: 119351299 examples [2:12:26, 20990.87 examples/s]
Generating train split: 119353616 examples [2:12:26, 17823.39 examples/s]
Generating train split: 119357579 examples [2:12:26, 22402.61 examples/s]
Generating train split: 119360158 examples [2:12:26, 21171.20 examples/s]
Generating train split: 119362512 examples [2:12:26, 19144.10 examples/s]
Generating train split: 119366538 examples [2:12:27, 23917.59 examples/s]
Generating train split: 119375006 examples [2:12:27, 38747.67 examples/s]
Generating train split: 119380633 examples [2:12:27, 43263.62 examples/s]
Generating train split: 119385410 examples [2:12:27, 30153.08 examples/s]
Generating train split: 119389273 examples [2:12:27, 28728.72 examples/s]
Generating train split: 119392741 examples [2:12:27, 29097.37 examples/s]
Generating train split: 119396073 examples [2:12:28, 23682.86 examples/s]
Generating train split: 119398859 examples [2:12:28, 23679.06 examples/s]
Generating train split: 119401521 examples [2:12:28, 18609.11 examples/s]
Generating train split: 119403719 examples [2:12:28, 17334.99 examples/s]
Generating train split: 119405705 examples [2:12:28, 17834.76 examples/s]
Generating train split: 119407812 examples [2:12:28, 18539.21 examples/s]
Generating train split: 119415945 examples [2:12:28, 33598.92 examples/s]
Generating train split: 119424278 examples [2:12:28, 45972.62 examples/s]
Generating train split: 119429412 examples [2:12:29, 29892.62 examples/s]
Generating train split: 119433482 examples [2:12:29, 23919.61 examples/s]
Generating train split: 119436776 examples [2:12:29, 20419.36 examples/s]
Generating train split: 119439488 examples [2:12:29, 21165.41 examples/s]
Generating train split: 119448072 examples [2:12:30, 33265.28 examples/s]
Generating train split: 119454476 examples [2:12:30, 39743.95 examples/s]
Generating train split: 119459499 examples [2:12:30, 28029.43 examples/s]
Generating train split: 119463480 examples [2:12:30, 22736.99 examples/s]
Generating train split: 119466700 examples [2:12:30, 18697.33 examples/s]
Generating train split: 119469290 examples [2:12:31, 15956.60 examples/s]
Generating train split: 119471411 examples [2:12:31, 16414.15 examples/s]
Generating train split: 119474119 examples [2:12:31, 18251.42 examples/s]
Generating train split: 119476466 examples [2:12:31, 19148.01 examples/s]
Generating train split: 119478720 examples [2:12:31, 17060.88 examples/s]
Generating train split: 119481660 examples [2:12:31, 19657.53 examples/s]
Generating train split: 119483914 examples [2:12:32, 17979.82 examples/s]
Generating train split: 119485927 examples [2:12:32, 14265.14 examples/s]
Generating train split: 119488059 examples [2:12:32, 15640.02 examples/s]
Generating train split: 119489869 examples [2:12:32, 12587.26 examples/s]
Generating train split: 119491373 examples [2:12:32, 12756.61 examples/s]
Generating train split: 119493013 examples [2:12:32, 13534.24 examples/s]
Generating train split: 119494526 examples [2:12:32, 11429.89 examples/s]
Generating train split: 119496714 examples [2:12:33, 13680.71 examples/s]
Generating train split: 119499437 examples [2:12:33, 16775.22 examples/s]
Generating train split: 119501337 examples [2:12:33, 15409.16 examples/s]
Generating train split: 119503040 examples [2:12:33, 14700.69 examples/s]
Generating train split: 119504906 examples [2:12:33, 15612.69 examples/s]
Generating train split: 119506569 examples [2:12:33, 14327.51 examples/s]
Generating train split: 119508092 examples [2:12:33, 13741.93 examples/s]
Generating train split: 119509529 examples [2:12:33, 13815.92 examples/s]
Generating train split: 119513033 examples [2:12:34, 19350.41 examples/s]
Generating train split: 119515069 examples [2:12:34, 15732.47 examples/s]
Generating train split: 119516824 examples [2:12:34, 14476.69 examples/s]
Generating train split: 119519146 examples [2:12:34, 16421.90 examples/s]
Generating train split: 119520938 examples [2:12:34, 13869.09 examples/s]
Generating train split: 119522815 examples [2:12:34, 14980.74 examples/s]
Generating train split: 119529802 examples [2:12:34, 28412.82 examples/s]
Generating train split: 119537782 examples [2:12:34, 41715.95 examples/s]
Generating train split: 119542451 examples [2:12:35, 36866.65 examples/s]
Generating train split: 119546578 examples [2:12:35, 26421.61 examples/s]
Generating train split: 119549919 examples [2:12:35, 23543.35 examples/s]
Generating train split: 119552792 examples [2:12:35, 20569.67 examples/s]
Generating train split: 119555229 examples [2:12:35, 18422.34 examples/s]
Generating train split: 119557332 examples [2:12:36, 18082.08 examples/s]
Generating train split: 119559867 examples [2:12:36, 19564.28 examples/s]
Generating train split: 119562025 examples [2:12:36, 18876.85 examples/s]
Generating train split: 119564047 examples [2:12:36, 17707.47 examples/s]
Generating train split: 119565908 examples [2:12:36, 17199.38 examples/s]
Generating train split: 119567699 examples [2:12:36, 15297.06 examples/s]
Generating train split: 119569362 examples [2:12:36, 15605.49 examples/s]
Generating train split: 119570976 examples [2:12:36, 15150.55 examples/s]
Generating train split: 119572535 examples [2:12:37, 13300.68 examples/s]
Generating train split: 119574515 examples [2:12:37, 14758.34 examples/s]
Generating train split: 119576067 examples [2:12:37, 14909.65 examples/s]
Generating train split: 119577657 examples [2:12:37, 15041.84 examples/s]
Generating train split: 119579199 examples [2:12:37, 13063.13 examples/s]
Generating train split: 119580586 examples [2:12:37, 12159.70 examples/s]
Generating train split: 119582736 examples [2:12:37, 14470.70 examples/s]
Generating train split: 119585037 examples [2:12:37, 16696.89 examples/s]
Generating train split: 119586806 examples [2:12:38, 16769.30 examples/s]
Generating train split: 119588553 examples [2:12:38, 16844.84 examples/s]
Generating train split: 119590282 examples [2:12:38, 16466.49 examples/s]
Generating train split: 119593231 examples [2:12:38, 19738.29 examples/s]
Generating train split: 119595239 examples [2:12:38, 17113.51 examples/s]
Generating train split: 119597036 examples [2:12:38, 14610.31 examples/s]
Generating train split: 119599049 examples [2:12:38, 15770.69 examples/s]
Generating train split: 119602338 examples [2:12:38, 20074.41 examples/s]
Generating train split: 119610281 examples [2:12:38, 35749.23 examples/s]
Generating train split: 119617398 examples [2:12:39, 45443.55 examples/s]
Generating train split: 119622270 examples [2:12:39, 39074.17 examples/s]
Generating train split: 119626550 examples [2:12:39, 29537.23 examples/s]
Generating train split: 119630082 examples [2:12:39, 20492.02 examples/s]
Generating train split: 119637173 examples [2:12:39, 28906.89 examples/s]
Generating train split: 119646516 examples [2:12:40, 41330.39 examples/s]
Generating train split: 119652375 examples [2:12:40, 44970.04 examples/s]
Generating train split: 119658076 examples [2:12:40, 30940.80 examples/s]
Generating train split: 119662591 examples [2:12:40, 28832.38 examples/s]
Generating train split: 119670101 examples [2:12:40, 37165.22 examples/s]
Generating train split: 119676965 examples [2:12:40, 43596.28 examples/s]
Generating train split: 119682496 examples [2:12:41, 29612.88 examples/s]
Generating train split: 119686848 examples [2:12:41, 28045.91 examples/s]
Generating train split: 119690611 examples [2:12:41, 21551.14 examples/s]
Generating train split: 119693607 examples [2:12:41, 22169.82 examples/s]
Generating train split: 119696454 examples [2:12:42, 17894.26 examples/s]
Generating train split: 119698763 examples [2:12:42, 18317.61 examples/s]
Generating train split: 119700984 examples [2:12:42, 18631.83 examples/s]
Generating train split: 119703136 examples [2:12:42, 17785.95 examples/s]
Generating train split: 119705105 examples [2:12:42, 16617.08 examples/s]
Generating train split: 119708013 examples [2:12:42, 19324.06 examples/s]
Generating train split: 119710136 examples [2:12:42, 17652.19 examples/s]
Generating train split: 119713179 examples [2:12:42, 20572.87 examples/s]
Generating train split: 119715422 examples [2:12:43, 19161.12 examples/s]
Generating train split: 119720759 examples [2:12:43, 27521.86 examples/s]
Generating train split: 119729691 examples [2:12:43, 43518.62 examples/s]
Generating train split: 119736134 examples [2:12:43, 49124.56 examples/s]
Generating train split: 119741435 examples [2:12:43, 27203.01 examples/s]
Generating train split: 119745532 examples [2:12:44, 23399.24 examples/s]
Generating train split: 119753379 examples [2:12:44, 32567.27 examples/s]
Generating train split: 119762304 examples [2:12:44, 43449.54 examples/s]
Generating train split: 119768279 examples [2:12:44, 38381.51 examples/s]
Generating train split: 119773342 examples [2:12:44, 27864.35 examples/s]
Generating train split: 119777342 examples [2:12:44, 24862.13 examples/s]
Generating train split: 119785377 examples [2:12:45, 33908.81 examples/s]
Generating train split: 119792994 examples [2:12:45, 41377.57 examples/s]
Generating train split: 119798467 examples [2:12:45, 41520.71 examples/s]
Generating train split: 119803564 examples [2:12:45, 30767.35 examples/s]
Generating train split: 119807658 examples [2:12:45, 31537.95 examples/s]
Generating train split: 119811555 examples [2:12:45, 29476.97 examples/s]
Generating train split: 119815013 examples [2:12:46, 23117.86 examples/s]
Generating train split: 119817839 examples [2:12:46, 23430.26 examples/s]
Generating train split: 119820567 examples [2:12:46, 24014.30 examples/s]
Generating train split: 119823256 examples [2:12:46, 21145.97 examples/s]
Generating train split: 119825612 examples [2:12:46, 21480.51 examples/s]
Generating train split: 119827943 examples [2:12:46, 21066.78 examples/s]
Generating train split: 119830175 examples [2:12:46, 19486.78 examples/s]
Generating train split: 119832458 examples [2:12:46, 20275.76 examples/s]
Generating train split: 119835130 examples [2:12:47, 21914.66 examples/s]
Generating train split: 119837409 examples [2:12:47, 21314.24 examples/s]
Generating train split: 119839610 examples [2:12:47, 17944.15 examples/s]
Generating train split: 119841525 examples [2:12:47, 16337.50 examples/s]
Generating train split: 119843911 examples [2:12:47, 17887.98 examples/s]
Generating train split: 119845800 examples [2:12:47, 16957.79 examples/s]
Generating train split: 119847594 examples [2:12:47, 17195.19 examples/s]
Generating train split: 119849376 examples [2:12:48, 14164.02 examples/s]
Generating train split: 119850907 examples [2:12:48, 14329.37 examples/s]
Generating train split: 119852431 examples [2:12:48, 14360.45 examples/s]
Generating train split: 119855085 examples [2:12:48, 17528.73 examples/s]
Generating train split: 119857324 examples [2:12:48, 18653.42 examples/s]
Generating train split: 119859264 examples [2:12:48, 13748.36 examples/s]
Generating train split: 119861914 examples [2:12:48, 16601.90 examples/s]
Generating train split: 119863837 examples [2:12:48, 14927.52 examples/s]
Generating train split: 119865540 examples [2:12:49, 12940.20 examples/s]
Generating train split: 119867555 examples [2:12:49, 14495.85 examples/s]
Generating train split: 119869189 examples [2:12:49, 13211.55 examples/s]
Generating train split: 119870691 examples [2:12:49, 13617.96 examples/s]
Generating train split: 119872713 examples [2:12:49, 15248.41 examples/s]
Generating train split: 119874351 examples [2:12:49, 14629.52 examples/s]
Generating train split: 119875906 examples [2:12:49, 11564.23 examples/s]
Generating train split: 119878272 examples [2:12:50, 14267.61 examples/s]
Generating train split: 119880575 examples [2:12:50, 16381.24 examples/s]
Generating train split: 119883377 examples [2:12:50, 19149.55 examples/s]
Generating train split: 119885463 examples [2:12:50, 16334.78 examples/s]
Generating train split: 119888050 examples [2:12:50, 18575.54 examples/s]
Generating train split: 119890798 examples [2:12:50, 20832.46 examples/s]
Generating train split: 119893054 examples [2:12:50, 18232.96 examples/s]
Generating train split: 119895734 examples [2:12:50, 20340.05 examples/s]
Generating train split: 119897932 examples [2:12:50, 20443.19 examples/s]
Generating train split: 119904928 examples [2:12:51, 33709.19 examples/s]
Generating train split: 119912441 examples [2:12:51, 44522.52 examples/s]
Generating train split: 119917112 examples [2:12:51, 28658.70 examples/s]
Generating train split: 119920845 examples [2:12:51, 29106.12 examples/s]
Generating train split: 119928906 examples [2:12:51, 40279.70 examples/s]
Generating train split: 119937951 examples [2:12:51, 52147.84 examples/s]
Generating train split: 119944087 examples [2:12:52, 38895.51 examples/s]
Generating train split: 119949101 examples [2:12:52, 34794.68 examples/s]
Generating train split: 119953412 examples [2:12:52, 23119.74 examples/s]
Generating train split: 119956759 examples [2:12:52, 23324.87 examples/s]
Generating train split: 119959820 examples [2:12:53, 18695.36 examples/s]
Generating train split: 119962289 examples [2:12:53, 19142.08 examples/s]
Generating train split: 119964661 examples [2:12:53, 15740.33 examples/s]
Generating train split: 119967093 examples [2:12:53, 17102.30 examples/s]
Generating train split: 119969172 examples [2:12:53, 14705.60 examples/s]
Generating train split: 119971624 examples [2:12:53, 16507.80 examples/s]
Generating train split: 119973587 examples [2:12:54, 14870.07 examples/s]
Generating train split: 119975306 examples [2:12:54, 14108.87 examples/s]
Generating train split: 119977408 examples [2:12:54, 15501.17 examples/s]
Generating train split: 119979127 examples [2:12:54, 15534.70 examples/s]
Generating train split: 119980791 examples [2:12:54, 14997.14 examples/s]
Generating train split: 119982953 examples [2:12:54, 16641.91 examples/s]
Generating train split: 119985228 examples [2:12:54, 18210.75 examples/s]
Generating train split: 119987139 examples [2:12:54, 16590.51 examples/s]
Generating train split: 119988889 examples [2:12:55, 13234.84 examples/s]
Generating train split: 119991042 examples [2:12:55, 15098.51 examples/s]
Generating train split: 119999132 examples [2:12:55, 31119.33 examples/s]
Generating train split: 120008031 examples [2:12:55, 45248.40 examples/s]
Generating train split: 120013051 examples [2:12:55, 35588.88 examples/s]
Generating train split: 120017266 examples [2:12:55, 22321.21 examples/s]
Generating train split: 120020535 examples [2:12:56, 18776.82 examples/s]
Generating train split: 120023187 examples [2:12:56, 18104.99 examples/s]
Generating train split: 120025518 examples [2:12:56, 17782.07 examples/s]
Generating train split: 120027662 examples [2:12:56, 17663.31 examples/s]
Generating train split: 120029670 examples [2:12:56, 15344.75 examples/s]
Generating train split: 120031391 examples [2:12:57, 14690.38 examples/s]
Generating train split: 120033190 examples [2:12:57, 15347.97 examples/s]
Generating train split: 120034840 examples [2:12:57, 14417.59 examples/s]
Generating train split: 120036799 examples [2:12:57, 15589.83 examples/s]
Generating train split: 120038903 examples [2:12:57, 16861.28 examples/s]
Generating train split: 120040675 examples [2:12:57, 15199.50 examples/s]
Generating train split: 120042286 examples [2:12:57, 13414.04 examples/s]
Generating train split: 120043885 examples [2:12:57, 14008.69 examples/s]
Generating train split: 120045358 examples [2:12:57, 12986.36 examples/s]
Generating train split: 120047631 examples [2:12:58, 15397.50 examples/s]
Generating train split: 120049279 examples [2:12:58, 15287.13 examples/s]
Generating train split: 120051617 examples [2:12:58, 17432.88 examples/s]
Generating train split: 120053441 examples [2:12:58, 14633.89 examples/s]
Generating train split: 120055032 examples [2:12:58, 11911.70 examples/s]
Generating train split: 120056676 examples [2:12:58, 12838.32 examples/s]
Generating train split: 120059728 examples [2:12:58, 17030.95 examples/s]
Generating train split: 120068368 examples [2:12:58, 34583.63 examples/s]
Generating train split: 120075906 examples [2:12:59, 45396.89 examples/s]
Generating train split: 120080921 examples [2:12:59, 34483.76 examples/s]
Generating train split: 120085094 examples [2:12:59, 24805.59 examples/s]
Generating train split: 120088423 examples [2:12:59, 22096.95 examples/s]
Generating train split: 120091241 examples [2:13:00, 18450.20 examples/s]
Generating train split: 120093558 examples [2:13:00, 16959.13 examples/s]
Generating train split: 120095573 examples [2:13:00, 15131.44 examples/s]
Generating train split: 120098894 examples [2:13:00, 18337.27 examples/s]
Generating train split: 120104120 examples [2:13:00, 25190.73 examples/s]
Generating train split: 120110765 examples [2:13:00, 34430.10 examples/s]
Generating train split: 120116172 examples [2:13:00, 39178.05 examples/s]
Generating train split: 120120717 examples [2:13:01, 29489.92 examples/s]
Generating train split: 120124448 examples [2:13:01, 21532.61 examples/s]
Generating train split: 120127416 examples [2:13:01, 21807.35 examples/s]
Generating train split: 120130186 examples [2:13:01, 18733.35 examples/s]
Generating train split: 120132504 examples [2:13:01, 17548.79 examples/s]
Generating train split: 120135019 examples [2:13:02, 18898.56 examples/s]
Generating train split: 120137193 examples [2:13:02, 16079.84 examples/s]
Generating train split: 120139045 examples [2:13:02, 15482.04 examples/s]
Generating train split: 120140748 examples [2:13:02, 15315.13 examples/s]
Generating train split: 120142387 examples [2:13:02, 14361.37 examples/s]
Generating train split: 120144019 examples [2:13:02, 14776.77 examples/s]
Generating train split: 120145564 examples [2:13:02, 12309.59 examples/s]
Generating train split: 120146891 examples [2:13:03, 11052.37 examples/s]
Generating train split: 120148070 examples [2:13:03, 10523.73 examples/s]
Generating train split: 120149453 examples [2:13:03, 11274.50 examples/s]
Generating train split: 120151026 examples [2:13:03, 12367.75 examples/s]
Generating train split: 120152474 examples [2:13:03, 12910.27 examples/s]
Generating train split: 120153828 examples [2:13:03, 10951.84 examples/s]
Generating train split: 120156342 examples [2:13:03, 14418.49 examples/s]
Generating train split: 120159532 examples [2:13:03, 18941.68 examples/s]
Generating train split: 120161593 examples [2:13:04, 14630.22 examples/s]
Generating train split: 120163324 examples [2:13:04, 13337.62 examples/s]
Generating train split: 120165817 examples [2:13:04, 15862.80 examples/s]
Generating train split: 120167636 examples [2:13:04, 16323.67 examples/s]
Generating train split: 120169436 examples [2:13:04, 14165.70 examples/s]
Generating train split: 120172395 examples [2:13:04, 17745.49 examples/s]
Generating train split: 120174743 examples [2:13:04, 19166.31 examples/s]
Generating train split: 120176835 examples [2:13:04, 16085.85 examples/s]
Generating train split: 120178803 examples [2:13:05, 16929.57 examples/s]
Generating train split: 120181055 examples [2:13:05, 18305.12 examples/s]
Generating train split: 120189338 examples [2:13:05, 35348.37 examples/s]
Generating train split: 120197785 examples [2:13:05, 48792.78 examples/s]
Generating train split: 120203026 examples [2:13:05, 42946.62 examples/s]
Generating train split: 120207709 examples [2:13:05, 32256.77 examples/s]
Generating train split: 120211560 examples [2:13:06, 21856.92 examples/s]
Generating train split: 120214587 examples [2:13:06, 22138.03 examples/s]
Generating train split: 120217738 examples [2:13:06, 23831.89 examples/s]
Generating train split: 120220659 examples [2:13:06, 21260.75 examples/s]
Generating train split: 120223173 examples [2:13:06, 20340.41 examples/s]
Generating train split: 120225471 examples [2:13:06, 19310.67 examples/s]
Generating train split: 120227572 examples [2:13:06, 18527.21 examples/s]
Generating train split: 120229669 examples [2:13:07, 19073.66 examples/s]
Generating train split: 120231676 examples [2:13:07, 19293.32 examples/s]
Generating train split: 120234850 examples [2:13:07, 22505.69 examples/s]
Generating train split: 120237202 examples [2:13:07, 20897.42 examples/s]
Generating train split: 120239378 examples [2:13:07, 18889.24 examples/s]
Generating train split: 120241362 examples [2:13:07, 15372.05 examples/s]
Generating train split: 120243055 examples [2:13:07, 15362.17 examples/s]
Generating train split: 120244887 examples [2:13:07, 15971.46 examples/s]
Generating train split: 120246571 examples [2:13:08, 15496.52 examples/s]
Generating train split: 120248351 examples [2:13:08, 15956.20 examples/s]
Generating train split: 120249996 examples [2:13:08, 15066.36 examples/s]
Generating train split: 120251692 examples [2:13:08, 15558.26 examples/s]
Generating train split: 120254098 examples [2:13:08, 17876.30 examples/s]
Generating train split: 120255937 examples [2:13:08, 15921.81 examples/s]
Generating train split: 120257603 examples [2:13:08, 16063.76 examples/s]
Generating train split: 120259262 examples [2:13:08, 16051.93 examples/s]
Generating train split: 120261187 examples [2:13:08, 16922.73 examples/s]
Generating train split: 120262914 examples [2:13:09, 16119.47 examples/s]
Generating train split: 120264914 examples [2:13:09, 17079.39 examples/s]
Generating train split: 120267166 examples [2:13:09, 18583.75 examples/s]
Generating train split: 120269234 examples [2:13:09, 19151.32 examples/s]
Generating train split: 120271171 examples [2:13:09, 18170.24 examples/s]
Generating train split: 120273018 examples [2:13:09, 16457.57 examples/s]
Generating train split: 120275660 examples [2:13:09, 19109.88 examples/s]
Generating train split: 120278143 examples [2:13:09, 20650.97 examples/s]
Generating train split: 120280277 examples [2:13:09, 19087.45 examples/s]
Generating train split: 120282257 examples [2:13:10, 17334.12 examples/s]
Generating train split: 120284806 examples [2:13:10, 19347.07 examples/s]
Generating train split: 120286818 examples [2:13:10, 18808.43 examples/s]
Generating train split: 120288832 examples [2:13:10, 19156.51 examples/s]
Generating train split: 120290789 examples [2:13:10, 18766.82 examples/s]
Generating train split: 120293462 examples [2:13:10, 20960.80 examples/s]
Generating train split: 120295604 examples [2:13:10, 16192.22 examples/s]
Generating train split: 120297413 examples [2:13:10, 15570.14 examples/s]
Generating train split: 120299706 examples [2:13:11, 17323.69 examples/s]
Generating train split: 120301715 examples [2:13:11, 17927.40 examples/s]
Generating train split: 120303618 examples [2:13:11, 18121.14 examples/s]
Generating train split: 120305509 examples [2:13:11, 17748.04 examples/s]
Generating train split: 120308097 examples [2:13:11, 19977.59 examples/s]
Generating train split: 120311105 examples [2:13:11, 22806.90 examples/s]
Generating train split: 120313447 examples [2:13:11, 20318.29 examples/s]
Generating train split: 120315571 examples [2:13:11, 16836.75 examples/s]
Generating train split: 120317404 examples [2:13:12, 17093.08 examples/s]
Generating train split: 120319224 examples [2:13:12, 16851.53 examples/s]
Generating train split: 120321027 examples [2:13:12, 16874.20 examples/s]
Generating train split: 120322779 examples [2:13:12, 14627.53 examples/s]
Generating train split: 120324827 examples [2:13:12, 16069.12 examples/s]
Generating train split: 120326524 examples [2:13:12, 15479.44 examples/s]
Generating train split: 120328133 examples [2:13:12, 14356.88 examples/s]
Generating train split: 120329622 examples [2:13:12, 14227.24 examples/s]
Generating train split: 120331093 examples [2:13:13, 11549.26 examples/s]
Generating train split: 120332342 examples [2:13:13, 10601.79 examples/s]
Generating train split: 120334374 examples [2:13:13, 12805.60 examples/s]
Generating train split: 120336055 examples [2:13:13, 13772.51 examples/s]
Generating train split: 120337539 examples [2:13:13, 12874.97 examples/s]
Generating train split: 120339580 examples [2:13:13, 14503.11 examples/s]
Generating train split: 120341105 examples [2:13:13, 10181.71 examples/s]
Generating train split: 120343246 examples [2:13:14, 12472.34 examples/s]
Generating train split: 120345755 examples [2:13:14, 15238.85 examples/s]
Generating train split: 120347547 examples [2:13:14, 15400.36 examples/s]
Generating train split: 120349278 examples [2:13:14, 15071.50 examples/s]
Generating train split: 120351268 examples [2:13:14, 16300.00 examples/s]
Generating train split: 120353011 examples [2:13:14, 15829.75 examples/s]
Generating train split: 120354692 examples [2:13:14, 12873.78 examples/s]
Generating train split: 120357145 examples [2:13:14, 15581.58 examples/s]
Generating train split: 120359471 examples [2:13:14, 17492.66 examples/s]
Generating train split: 120361379 examples [2:13:15, 13399.43 examples/s]
Generating train split: 120363041 examples [2:13:15, 14086.48 examples/s]
Generating train split: 120364648 examples [2:13:15, 14033.89 examples/s]
Generating train split: 120367269 examples [2:13:15, 17020.27 examples/s]
Generating train split: 120369132 examples [2:13:15, 16484.33 examples/s]
Generating train split: 120371610 examples [2:13:15, 18636.14 examples/s]
Generating train split: 120373589 examples [2:13:15, 14936.53 examples/s]
Generating train split: 120375280 examples [2:13:16, 14236.42 examples/s]
Generating train split: 120377979 examples [2:13:16, 17242.83 examples/s]
Generating train split: 120379941 examples [2:13:16, 17572.59 examples/s]
Generating train split: 120381823 examples [2:13:16, 16954.86 examples/s]
Generating train split: 120383859 examples [2:13:16, 17788.49 examples/s]
Generating train split: 120386606 examples [2:13:16, 20390.66 examples/s]
Generating train split: 120388730 examples [2:13:16, 16707.37 examples/s]
Generating train split: 120391472 examples [2:13:16, 19307.93 examples/s]
Generating train split: 120393675 examples [2:13:16, 20009.51 examples/s]
Generating train split: 120400382 examples [2:13:17, 32689.49 examples/s]
Generating train split: 120409340 examples [2:13:17, 48496.74 examples/s]
Generating train split: 120415759 examples [2:13:17, 52940.86 examples/s]
Generating train split: 120421283 examples [2:13:17, 29577.14 examples/s]
Generating train split: 120425587 examples [2:13:17, 29325.44 examples/s]
Generating train split: 120429460 examples [2:13:18, 22779.50 examples/s]
Generating train split: 120432575 examples [2:13:18, 21015.79 examples/s]
Generating train split: 120435256 examples [2:13:18, 20649.28 examples/s]
Generating train split: 120437713 examples [2:13:18, 20515.99 examples/s]
Generating train split: 120440032 examples [2:13:18, 20686.52 examples/s]
Generating train split: 120442298 examples [2:13:18, 19280.08 examples/s]
Generating train split: 120444635 examples [2:13:18, 20080.83 examples/s]
Generating train split: 120446769 examples [2:13:19, 19631.46 examples/s]
Generating train split: 120449386 examples [2:13:19, 21252.67 examples/s]
Generating train split: 120451604 examples [2:13:19, 21183.85 examples/s]
Generating train split: 120453784 examples [2:13:19, 21022.77 examples/s]
Generating train split: 120455927 examples [2:13:19, 18702.97 examples/s]
Generating train split: 120457865 examples [2:13:20, 9007.15 examples/s] 
Generating train split: 120459332 examples [2:13:20, 5892.08 examples/s]
Generating train split: 120460439 examples [2:13:21, 4418.13 examples/s]
Generating train split: 120461369 examples [2:13:21, 4903.20 examples/s]
Generating train split: 120463415 examples [2:13:21, 6837.20 examples/s]
Generating train split: 120464763 examples [2:13:21, 7827.29 examples/s]
Generating train split: 120466020 examples [2:13:21, 8660.18 examples/s]
Generating train split: 120467277 examples [2:13:21, 7605.05 examples/s]
Generating train split: 120469033 examples [2:13:21, 9461.81 examples/s]
Generating train split: 120470298 examples [2:13:22, 7283.38 examples/s]
Generating train split: 120472388 examples [2:13:22, 9712.27 examples/s]
Generating train split: 120474660 examples [2:13:22, 12351.87 examples/s]
Generating train split: 120476284 examples [2:13:22, 12161.89 examples/s]
Generating train split: 120477773 examples [2:13:22, 11872.10 examples/s]
Generating train split: 120485516 examples [2:13:22, 27092.86 examples/s]
Generating train split: 120493879 examples [2:13:22, 41163.56 examples/s]
Generating train split: 120498684 examples [2:13:22, 35530.19 examples/s]
Generating train split: 120502848 examples [2:13:23, 26964.55 examples/s]
Generating train split: 120506262 examples [2:13:23, 25488.02 examples/s]
Generating train split: 120509297 examples [2:13:23, 21544.43 examples/s]
Generating train split: 120512972 examples [2:13:23, 24424.52 examples/s]
Generating train split: 120515856 examples [2:13:23, 24745.81 examples/s]
Generating train split: 120520220 examples [2:13:23, 29081.11 examples/s]
Generating train split: 120523501 examples [2:13:24, 23582.14 examples/s]
Generating train split: 120526266 examples [2:13:24, 19860.55 examples/s]
Generating train split: 120528603 examples [2:13:24, 19421.93 examples/s]
Generating train split: 120530778 examples [2:13:24, 18360.72 examples/s]
Generating train split: 120532771 examples [2:13:24, 18450.55 examples/s]
Generating train split: 120534759 examples [2:13:24, 18777.06 examples/s]
Generating train split: 120536733 examples [2:13:24, 18311.90 examples/s]
Generating train split: 120538626 examples [2:13:24, 17879.77 examples/s]
Generating train split: 120540660 examples [2:13:25, 18522.54 examples/s]
Generating train split: 120542551 examples [2:13:25, 16822.52 examples/s]
Generating train split: 120544280 examples [2:13:25, 16426.72 examples/s]
Generating train split: 120546558 examples [2:13:25, 18088.54 examples/s]
Generating train split: 120548437 examples [2:13:25, 18272.79 examples/s]
Generating train split: 120550301 examples [2:13:25, 14710.80 examples/s]
Generating train split: 120552134 examples [2:13:25, 15577.80 examples/s]
Generating train split: 120553805 examples [2:13:25, 14222.55 examples/s]
Generating train split: 120558301 examples [2:13:26, 21852.28 examples/s]
Generating train split: 120566980 examples [2:13:26, 38840.20 examples/s]
Generating train split: 120572660 examples [2:13:26, 43716.18 examples/s]
Generating train split: 120577366 examples [2:13:26, 27960.79 examples/s]
Generating train split: 120581110 examples [2:13:26, 25096.74 examples/s]
Generating train split: 120584318 examples [2:13:27, 20705.00 examples/s]
Generating train split: 120592295 examples [2:13:27, 31219.77 examples/s]
Generating train split: 120601449 examples [2:13:27, 43206.67 examples/s]
Generating train split: 120607095 examples [2:13:27, 42167.62 examples/s]
Generating train split: 120612228 examples [2:13:27, 33537.55 examples/s]
Generating train split: 120616465 examples [2:13:27, 26304.04 examples/s]
Generating train split: 120619901 examples [2:13:28, 24462.83 examples/s]
Generating train split: 120622896 examples [2:13:28, 20904.99 examples/s]
Generating train split: 120625393 examples [2:13:28, 19855.80 examples/s]
Generating train split: 120627637 examples [2:13:28, 19808.41 examples/s]
Generating train split: 120629798 examples [2:13:28, 20015.71 examples/s]
Generating train split: 120632237 examples [2:13:28, 20976.47 examples/s]
Generating train split: 120634855 examples [2:13:28, 22207.59 examples/s]
Generating train split: 120637202 examples [2:13:29, 19458.94 examples/s]
Generating train split: 120639276 examples [2:13:29, 17182.20 examples/s]
Generating train split: 120641717 examples [2:13:29, 18806.81 examples/s]
Generating train split: 120643989 examples [2:13:29, 19772.78 examples/s]
Generating train split: 120646148 examples [2:13:29, 20033.87 examples/s]
Generating train split: 120648234 examples [2:13:29, 17775.50 examples/s]
Generating train split: 120650108 examples [2:13:29, 15506.51 examples/s]
Generating train split: 120652308 examples [2:13:29, 17003.25 examples/s]
Generating train split: 120654300 examples [2:13:29, 17730.08 examples/s]
Generating train split: 120656468 examples [2:13:30, 18775.77 examples/s]
Generating train split: 120659583 examples [2:13:30, 22106.65 examples/s]
Generating train split: 120661879 examples [2:13:30, 17453.23 examples/s]
Generating train split: 120664091 examples [2:13:30, 18498.31 examples/s]
Generating train split: 120666691 examples [2:13:30, 20289.04 examples/s]
Generating train split: 120669000 examples [2:13:30, 21016.15 examples/s]
Generating train split: 120671223 examples [2:13:30, 17613.03 examples/s]
Generating train split: 120673153 examples [2:13:30, 17765.22 examples/s]
Generating train split: 120675614 examples [2:13:31, 19512.07 examples/s]
Generating train split: 120677680 examples [2:13:31, 17635.23 examples/s]
Generating train split: 120679557 examples [2:13:31, 17241.08 examples/s]
Generating train split: 120682189 examples [2:13:31, 19581.46 examples/s]
Generating train split: 120684248 examples [2:13:31, 17948.70 examples/s]
Generating train split: 120686163 examples [2:13:31, 18082.53 examples/s]
Generating train split: 120688029 examples [2:13:31, 17781.27 examples/s]
Generating train split: 120691247 examples [2:13:31, 21027.35 examples/s]
Generating train split: 120693394 examples [2:13:32, 19210.83 examples/s]
Generating train split: 120695363 examples [2:13:32, 16490.07 examples/s]
Generating train split: 120697549 examples [2:13:32, 17781.21 examples/s]
Generating train split: 120699429 examples [2:13:32, 16450.31 examples/s]
Generating train split: 120701153 examples [2:13:32, 16213.99 examples/s]
Generating train split: 120703045 examples [2:13:32, 16861.62 examples/s]
Generating train split: 120704777 examples [2:13:32, 14388.55 examples/s]
Generating train split: 120707081 examples [2:13:32, 16510.22 examples/s]
Generating train split: 120709830 examples [2:13:33, 19350.30 examples/s]
Generating train split: 120711888 examples [2:13:33, 15299.34 examples/s]
Generating train split: 120713653 examples [2:13:33, 15836.47 examples/s]
Generating train split: 120716507 examples [2:13:33, 18973.09 examples/s]
Generating train split: 120718586 examples [2:13:33, 19148.39 examples/s]
Generating train split: 120720631 examples [2:13:33, 19461.84 examples/s]
Generating train split: 120722673 examples [2:13:33, 19183.16 examples/s]
Generating train split: 120726091 examples [2:13:33, 23326.37 examples/s]
Generating train split: 120728513 examples [2:13:33, 22013.83 examples/s]
Generating train split: 120730792 examples [2:13:34, 16258.88 examples/s]
Generating train split: 120732980 examples [2:13:34, 17451.48 examples/s]
Generating train split: 120734951 examples [2:13:34, 17480.35 examples/s]
Generating train split: 120736852 examples [2:13:34, 16833.11 examples/s]
Generating train split: 120739674 examples [2:13:34, 19690.29 examples/s]
Generating train split: 120741774 examples [2:13:34, 19297.78 examples/s]
Generating train split: 120743792 examples [2:13:34, 16404.45 examples/s]
Generating train split: 120746699 examples [2:13:35, 19373.50 examples/s]
Generating train split: 120748856 examples [2:13:35, 19930.54 examples/s]
Generating train split: 120750969 examples [2:13:35, 16394.51 examples/s]
Generating train split: 120752791 examples [2:13:35, 16738.92 examples/s]
Generating train split: 120754596 examples [2:13:35, 14431.58 examples/s]
Generating train split: 120756871 examples [2:13:35, 16367.99 examples/s]
Generating train split: 120759171 examples [2:13:35, 18012.29 examples/s]
Generating train split: 120762860 examples [2:13:35, 22857.86 examples/s]
Generating train split: 120765309 examples [2:13:36, 17702.24 examples/s]
Generating train split: 120767363 examples [2:13:36, 18281.26 examples/s]
Generating train split: 120769660 examples [2:13:36, 19420.33 examples/s]
Generating train split: 120771784 examples [2:13:36, 19667.96 examples/s]
Generating train split: 120773880 examples [2:13:36, 19239.41 examples/s]
Generating train split: 120776583 examples [2:13:36, 21246.06 examples/s]
Generating train split: 120778792 examples [2:13:36, 19095.06 examples/s]
Generating train split: 120780852 examples [2:13:36, 19458.03 examples/s]
Generating train split: 120782874 examples [2:13:37, 17394.68 examples/s]
Generating train split: 120785163 examples [2:13:37, 18642.83 examples/s]
Generating train split: 120787110 examples [2:13:37, 18489.73 examples/s]
Generating train split: 120789823 examples [2:13:37, 20819.45 examples/s]
Generating train split: 120791985 examples [2:13:37, 16958.60 examples/s]
Generating train split: 120793841 examples [2:13:37, 15167.78 examples/s]
Generating train split: 120795490 examples [2:13:37, 14135.12 examples/s]
Generating train split: 120797231 examples [2:13:37, 14889.83 examples/s]
Generating train split: 120798806 examples [2:13:38, 14000.81 examples/s]
Generating train split: 120800269 examples [2:13:38, 13431.06 examples/s]
Generating train split: 120802888 examples [2:13:38, 16620.92 examples/s]
Generating train split: 120805497 examples [2:13:38, 19124.08 examples/s]
Generating train split: 120807510 examples [2:13:38, 17905.89 examples/s]
Generating train split: 120809383 examples [2:13:38, 15934.46 examples/s]
Generating train split: 120811300 examples [2:13:38, 16696.09 examples/s]
Generating train split: 120813055 examples [2:13:38, 15253.85 examples/s]
Generating train split: 120814876 examples [2:13:39, 15996.75 examples/s]
Generating train split: 120817604 examples [2:13:39, 18967.29 examples/s]
Generating train split: 120819581 examples [2:13:39, 16422.62 examples/s]
Generating train split: 120821342 examples [2:13:39, 15860.23 examples/s]
Generating train split: 120823496 examples [2:13:39, 17142.11 examples/s]
Generating train split: 120825283 examples [2:13:39, 17238.25 examples/s]
Generating train split: 120827556 examples [2:13:39, 18671.44 examples/s]
Generating train split: 120829473 examples [2:13:39, 16421.47 examples/s]
Generating train split: 120831198 examples [2:13:39, 16404.17 examples/s]
Generating train split: 120832893 examples [2:13:40, 14146.94 examples/s]
Generating train split: 120834424 examples [2:13:40, 14423.34 examples/s]
Generating train split: 120836604 examples [2:13:40, 16335.16 examples/s]
Generating train split: 120838794 examples [2:13:40, 17537.79 examples/s]
Generating train split: 120840615 examples [2:13:40, 13903.53 examples/s]
Generating train split: 120842776 examples [2:13:40, 15700.78 examples/s]
Generating train split: 120844512 examples [2:13:40, 15244.02 examples/s]
Generating train split: 120846148 examples [2:13:40, 15249.55 examples/s]
Generating train split: 120847754 examples [2:13:41, 13803.40 examples/s]
Generating train split: 120849209 examples [2:13:41, 13774.14 examples/s]
Generating train split: 120851010 examples [2:13:41, 14873.80 examples/s]
Generating train split: 120852552 examples [2:13:41, 13838.04 examples/s]
Generating train split: 120855745 examples [2:13:41, 18571.81 examples/s]
Generating train split: 120857706 examples [2:13:41, 17570.07 examples/s]
Generating train split: 120860128 examples [2:13:41, 19313.58 examples/s]
Generating train split: 120862334 examples [2:13:41, 19918.92 examples/s]
Generating train split: 120864497 examples [2:13:41, 20372.03 examples/s]
Generating train split: 120866588 examples [2:13:42, 19871.48 examples/s]
Generating train split: 120868606 examples [2:13:42, 16760.58 examples/s]
Generating train split: 120870483 examples [2:13:42, 17161.55 examples/s]
Generating train split: 120872956 examples [2:13:42, 19161.44 examples/s]
Generating train split: 120875148 examples [2:13:42, 19905.56 examples/s]
Generating train split: 120877213 examples [2:13:42, 16354.79 examples/s]
Generating train split: 120879562 examples [2:13:42, 17909.12 examples/s]
Generating train split: 120881483 examples [2:13:42, 17180.78 examples/s]
Generating train split: 120883307 examples [2:13:43, 14684.61 examples/s]
Generating train split: 120884891 examples [2:13:43, 13974.37 examples/s]
Generating train split: 120887231 examples [2:13:43, 16234.16 examples/s]
Generating train split: 120889329 examples [2:13:43, 17441.63 examples/s]
Generating train split: 120891179 examples [2:13:43, 15259.79 examples/s]
Generating train split: 120894010 examples [2:13:43, 18444.90 examples/s]
Generating train split: 120896006 examples [2:13:43, 13963.43 examples/s]
Generating train split: 120897693 examples [2:13:44, 14576.79 examples/s]
Generating train split: 120901036 examples [2:13:44, 19011.83 examples/s]
Generating train split: 120903202 examples [2:13:44, 14925.84 examples/s]
Generating train split: 120905009 examples [2:13:44, 14017.88 examples/s]
Generating train split: 120906996 examples [2:13:44, 15144.23 examples/s]
Generating train split: 120908836 examples [2:13:44, 15863.77 examples/s]
Generating train split: 120911394 examples [2:13:44, 18281.76 examples/s]
Generating train split: 120913386 examples [2:13:45, 15155.50 examples/s]
Generating train split: 120915099 examples [2:13:45, 15600.53 examples/s]
Generating train split: 120917385 examples [2:13:45, 17403.87 examples/s]
Generating train split: 120923091 examples [2:13:45, 27823.89 examples/s]
Generating train split: 120932161 examples [2:13:45, 44975.71 examples/s]
Generating train split: 120937004 examples [2:13:45, 38898.81 examples/s]
Generating train split: 120941281 examples [2:13:45, 32754.30 examples/s]
Generating train split: 120944965 examples [2:13:45, 27676.56 examples/s]
Generating train split: 120948108 examples [2:13:46, 25310.75 examples/s]
Generating train split: 120950909 examples [2:13:46, 23168.63 examples/s]
Generating train split: 120953408 examples [2:13:46, 18976.85 examples/s]
Generating train split: 120955507 examples [2:13:46, 19355.49 examples/s]
Generating train split: 120957609 examples [2:13:46, 19027.08 examples/s]
Generating train split: 120959630 examples [2:13:46, 18695.28 examples/s]
Generating train split: 120961575 examples [2:13:47, 15739.42 examples/s]
Generating train split: 120964011 examples [2:13:47, 17623.56 examples/s]
Generating train split: 120965915 examples [2:13:47, 17826.12 examples/s]
Generating train split: 120967803 examples [2:13:47, 18040.15 examples/s]
Generating train split: 120969777 examples [2:13:47, 18438.88 examples/s]
Generating train split: 120972194 examples [2:13:47, 20005.90 examples/s]
Generating train split: 120975794 examples [2:13:47, 24520.75 examples/s]
Generating train split: 120978318 examples [2:13:47, 21222.00 examples/s]
Generating train split: 120980567 examples [2:13:47, 20232.67 examples/s]
Generating train split: 120983877 examples [2:13:48, 23549.94 examples/s]
Generating train split: 120986351 examples [2:13:48, 21423.40 examples/s]
Generating train split: 120994614 examples [2:13:48, 37153.94 examples/s]
Generating train split: 121002779 examples [2:13:48, 49042.46 examples/s]
Generating train split: 121008059 examples [2:13:48, 35854.70 examples/s]
Generating train split: 121012404 examples [2:13:48, 24555.31 examples/s]
Generating train split: 121015837 examples [2:13:49, 19084.72 examples/s]
Generating train split: 121018567 examples [2:13:49, 19839.76 examples/s]
Generating train split: 121021176 examples [2:13:49, 15230.51 examples/s]
Generating train split: 121023961 examples [2:13:49, 17145.46 examples/s]
Generating train split: 121026252 examples [2:13:50, 14407.59 examples/s]
Generating train split: 121028139 examples [2:13:50, 14922.48 examples/s]
Generating train split: 121029977 examples [2:13:50, 13019.97 examples/s]
Generating train split: 121031539 examples [2:13:50, 13078.09 examples/s]
Generating train split: 121033267 examples [2:13:50, 13938.77 examples/s]
Generating train split: 121034831 examples [2:13:50, 14140.16 examples/s]
Generating train split: 121037278 examples [2:13:50, 16616.39 examples/s]
Generating train split: 121039095 examples [2:13:50, 15291.91 examples/s]
Generating train split: 121046365 examples [2:13:51, 29514.49 examples/s]
Generating train split: 121055184 examples [2:13:51, 44850.86 examples/s]
Generating train split: 121060165 examples [2:13:51, 41301.25 examples/s]
Generating train split: 121064689 examples [2:13:51, 28420.67 examples/s]
Generating train split: 121068333 examples [2:13:51, 28271.76 examples/s]
Generating train split: 121071722 examples [2:13:51, 22646.39 examples/s]
Generating train split: 121074506 examples [2:13:52, 22624.23 examples/s]
Generating train split: 121077139 examples [2:13:52, 21862.07 examples/s]
Generating train split: 121079577 examples [2:13:52, 19609.96 examples/s]
Generating train split: 121081803 examples [2:13:52, 20165.76 examples/s]
Generating train split: 121083973 examples [2:13:52, 20187.41 examples/s]
Generating train split: 121086098 examples [2:13:52, 17852.12 examples/s]
Generating train split: 121087987 examples [2:13:52, 17141.09 examples/s]
Generating train split: 121090698 examples [2:13:52, 19529.74 examples/s]
Generating train split: 121092767 examples [2:13:53, 18466.36 examples/s]
Generating train split: 121094699 examples [2:13:53, 18048.76 examples/s]
Generating train split: 121096556 examples [2:13:53, 16407.63 examples/s]
Generating train split: 121099200 examples [2:13:53, 18816.11 examples/s]
Generating train split: 121101171 examples [2:13:53, 18387.01 examples/s]
Generating train split: 121103067 examples [2:13:53, 18003.31 examples/s]
Generating train split: 121105019 examples [2:13:53, 18296.18 examples/s]
Generating train split: 121112385 examples [2:13:53, 33611.78 examples/s]
Generating train split: 121120214 examples [2:13:53, 46260.65 examples/s]
Generating train split: 121125024 examples [2:13:54, 43872.12 examples/s]
Generating train split: 121129570 examples [2:13:54, 31759.49 examples/s]
Generating train split: 121133312 examples [2:13:54, 25109.33 examples/s]
Generating train split: 121136401 examples [2:13:54, 20817.00 examples/s]
Generating train split: 121138965 examples [2:13:54, 20630.08 examples/s]
Generating train split: 121141361 examples [2:13:55, 19530.42 examples/s]
Generating train split: 121143526 examples [2:13:55, 17349.66 examples/s]
Generating train split: 121145420 examples [2:13:55, 17463.48 examples/s]
Generating train split: 121147366 examples [2:13:55, 17903.44 examples/s]
Generating train split: 121149252 examples [2:13:55, 16781.91 examples/s]
Generating train split: 121151854 examples [2:13:55, 19014.92 examples/s]
Generating train split: 121153865 examples [2:13:55, 17038.07 examples/s]
Generating train split: 121155673 examples [2:13:56, 14508.06 examples/s]
Generating train split: 121157944 examples [2:13:56, 16338.71 examples/s]
Generating train split: 121159717 examples [2:13:56, 16239.96 examples/s]
Generating train split: 121161599 examples [2:13:56, 16665.11 examples/s]
Generating train split: 121163346 examples [2:13:56, 16794.55 examples/s]
Generating train split: 121165709 examples [2:13:56, 18612.34 examples/s]
Generating train split: 121167626 examples [2:13:56, 15896.53 examples/s]
Generating train split: 121169334 examples [2:13:56, 15127.24 examples/s]
Generating train split: 121173933 examples [2:13:56, 22910.11 examples/s]
Generating train split: 121182887 examples [2:13:57, 40557.22 examples/s]
Generating train split: 121189343 examples [2:13:57, 47130.75 examples/s]
Generating train split: 121194378 examples [2:13:57, 35710.94 examples/s]
Generating train split: 121198585 examples [2:13:57, 19136.50 examples/s]
Generating train split: 121201777 examples [2:13:58, 18338.18 examples/s]
Generating train split: 121209303 examples [2:13:58, 27050.56 examples/s]
Generating train split: 121217926 examples [2:13:58, 37665.11 examples/s]
Generating train split: 121223432 examples [2:13:58, 31698.78 examples/s]
Generating train split: 121227957 examples [2:13:58, 23804.57 examples/s]
Generating train split: 121231520 examples [2:13:59, 19883.32 examples/s]
Generating train split: 121234387 examples [2:13:59, 20808.23 examples/s]
Generating train split: 121237168 examples [2:13:59, 18233.58 examples/s]
Generating train split: 121239495 examples [2:13:59, 18034.41 examples/s]
Generating train split: 121242693 examples [2:13:59, 20591.83 examples/s]
Generating train split: 121245158 examples [2:13:59, 16121.88 examples/s]
Generating train split: 121247963 examples [2:14:00, 18304.18 examples/s]
Generating train split: 121250211 examples [2:14:00, 18217.08 examples/s]
Generating train split: 121252325 examples [2:14:00, 16629.94 examples/s]
Generating train split: 121254203 examples [2:14:00, 16765.92 examples/s]
Generating train split: 121256574 examples [2:14:00, 18152.39 examples/s]
Generating train split: 121258532 examples [2:14:00, 16816.38 examples/s]
Generating train split: 121260331 examples [2:14:00, 15405.93 examples/s]
Generating train split: 121262551 examples [2:14:00, 17009.79 examples/s]
Generating train split: 121264992 examples [2:14:01, 18874.36 examples/s]
Generating train split: 121267412 examples [2:14:01, 20195.97 examples/s]
Generating train split: 121269527 examples [2:14:01, 17987.38 examples/s]
Generating train split: 121271424 examples [2:14:01, 15063.59 examples/s]
Generating train split: 121274858 examples [2:14:01, 19535.26 examples/s]
Generating train split: 121277067 examples [2:14:01, 19964.05 examples/s]
Generating train split: 121279233 examples [2:14:01, 14831.67 examples/s]
Generating train split: 121281111 examples [2:14:02, 15563.48 examples/s]
Generating train split: 121282911 examples [2:14:02, 14490.16 examples/s]
Generating train split: 121284532 examples [2:14:02, 13275.25 examples/s]
Generating train split: 121287259 examples [2:14:02, 16415.15 examples/s]
Generating train split: 121289090 examples [2:14:02, 14002.55 examples/s]
Generating train split: 121290995 examples [2:14:02, 15090.73 examples/s]
Generating train split: 121292670 examples [2:14:02, 14873.15 examples/s]
Generating train split: 121294524 examples [2:14:02, 15758.34 examples/s]
Generating train split: 121296197 examples [2:14:03, 15657.06 examples/s]
Generating train split: 121297832 examples [2:14:03, 13567.88 examples/s]
Generating train split: 121300458 examples [2:14:03, 16697.89 examples/s]
Generating train split: 121302265 examples [2:14:03, 16459.84 examples/s]
Generating train split: 121304011 examples [2:14:03, 15133.23 examples/s]
Generating train split: 121306226 examples [2:14:03, 16912.80 examples/s]
Generating train split: 121308006 examples [2:14:03, 16968.50 examples/s]
Generating train split: 121309764 examples [2:14:03, 16492.61 examples/s]
Generating train split: 121311464 examples [2:14:04, 12518.70 examples/s]
Generating train split: 121314053 examples [2:14:04, 15534.73 examples/s]
Generating train split: 121315829 examples [2:14:04, 12364.71 examples/s]
Generating train split: 121318793 examples [2:14:04, 16020.64 examples/s]
Generating train split: 121321845 examples [2:14:04, 19384.35 examples/s]
Generating train split: 121324106 examples [2:14:04, 14599.33 examples/s]
Generating train split: 121326581 examples [2:14:04, 16677.17 examples/s]
Generating train split: 121328618 examples [2:14:05, 17254.47 examples/s]
Generating train split: 121335708 examples [2:14:05, 30205.70 examples/s]
Generating train split: 121344191 examples [2:14:05, 44215.51 examples/s]
Generating train split: 121349209 examples [2:14:05, 39357.00 examples/s]
Generating train split: 121353654 examples [2:14:05, 27841.74 examples/s]
Generating train split: 121357233 examples [2:14:05, 22656.90 examples/s]
Generating train split: 121360177 examples [2:14:06, 23159.76 examples/s]
Generating train split: 121362983 examples [2:14:06, 23563.54 examples/s]
Generating train split: 121365705 examples [2:14:06, 21553.30 examples/s]
Generating train split: 121368603 examples [2:14:06, 22729.95 examples/s]
Generating train split: 121371092 examples [2:14:06, 18554.09 examples/s]
Generating train split: 121373197 examples [2:14:06, 17201.97 examples/s]
Generating train split: 121375579 examples [2:14:06, 18588.99 examples/s]
Generating train split: 121377624 examples [2:14:07, 16434.37 examples/s]
Generating train split: 121379413 examples [2:14:07, 15964.19 examples/s]
Generating train split: 121381324 examples [2:14:07, 16686.64 examples/s]
Generating train split: 121383080 examples [2:14:07, 16272.15 examples/s]
Generating train split: 121384767 examples [2:14:07, 15984.12 examples/s]
Generating train split: 121386505 examples [2:14:07, 16330.02 examples/s]
Generating train split: 121388227 examples [2:14:07, 16570.81 examples/s]
Generating train split: 121389919 examples [2:14:07, 15286.79 examples/s]
Generating train split: 121392113 examples [2:14:07, 16989.51 examples/s]
Generating train split: 121393862 examples [2:14:08, 15680.56 examples/s]
Generating train split: 121395478 examples [2:14:08, 13534.52 examples/s]
Generating train split: 121397874 examples [2:14:08, 16084.18 examples/s]
Generating train split: 121399814 examples [2:14:08, 16936.51 examples/s]
Generating train split: 121401603 examples [2:14:08, 16699.04 examples/s]
Generating train split: 121403342 examples [2:14:08, 15773.46 examples/s]
Generating train split: 121404968 examples [2:14:08, 15529.01 examples/s]
Generating train split: 121406567 examples [2:14:08, 14771.05 examples/s]
Generating train split: 121408574 examples [2:14:09, 16185.81 examples/s]
Generating train split: 121410231 examples [2:14:09, 14908.29 examples/s]
Generating train split: 121411864 examples [2:14:09, 15285.24 examples/s]
Generating train split: 121413433 examples [2:14:09, 14096.37 examples/s]
Generating train split: 121414882 examples [2:14:09, 14059.15 examples/s]
Generating train split: 121416316 examples [2:14:09, 12813.37 examples/s]
Generating train split: 121418224 examples [2:14:09, 14046.56 examples/s]
Generating train split: 121419791 examples [2:14:09, 14465.80 examples/s]
Generating train split: 121421373 examples [2:14:09, 14834.99 examples/s]
Generating train split: 121423394 examples [2:14:10, 16313.30 examples/s]
Generating train split: 121425423 examples [2:14:10, 17433.00 examples/s]
Generating train split: 121429326 examples [2:14:10, 23695.32 examples/s]
Generating train split: 121437667 examples [2:14:10, 41192.83 examples/s]
Generating train split: 121444038 examples [2:14:10, 47830.50 examples/s]
Generating train split: 121448880 examples [2:14:10, 33562.62 examples/s]
Generating train split: 121452869 examples [2:14:11, 24549.31 examples/s]
Generating train split: 121456074 examples [2:14:11, 24562.94 examples/s]
Generating train split: 121459065 examples [2:14:11, 20642.97 examples/s]
Generating train split: 121461578 examples [2:14:11, 20854.10 examples/s]
Generating train split: 121463976 examples [2:14:11, 21322.31 examples/s]
Generating train split: 121466348 examples [2:14:11, 21478.59 examples/s]
Generating train split: 121469497 examples [2:14:11, 23887.76 examples/s]
Generating train split: 121472075 examples [2:14:11, 20089.54 examples/s]
Generating train split: 121474295 examples [2:14:12, 18283.56 examples/s]
Generating train split: 121476283 examples [2:14:12, 18294.34 examples/s]
Generating train split: 121478230 examples [2:14:12, 18045.54 examples/s]
Generating train split: 121480111 examples [2:14:12, 17899.93 examples/s]
Generating train split: 121481954 examples [2:14:12, 16884.25 examples/s]
Generating train split: 121483689 examples [2:14:12, 15614.14 examples/s]
Generating train split: 121485285 examples [2:14:12, 14755.19 examples/s]
Generating train split: 121487325 examples [2:14:12, 16177.38 examples/s]
Generating train split: 121488995 examples [2:14:13, 14872.17 examples/s]
Generating train split: 121490611 examples [2:14:13, 15091.35 examples/s]
Generating train split: 121492156 examples [2:14:13, 13814.23 examples/s]
Generating train split: 121494701 examples [2:14:13, 16807.97 examples/s]
Generating train split: 121496763 examples [2:14:13, 17615.34 examples/s]
Generating train split: 121498595 examples [2:14:13, 16670.82 examples/s]
Generating train split: 121500311 examples [2:14:13, 12519.53 examples/s]
Generating train split: 121502228 examples [2:14:13, 13871.79 examples/s]
Generating train split: 121503787 examples [2:14:14, 12040.12 examples/s]
Generating train split: 121505142 examples [2:14:14, 11616.37 examples/s]
Generating train split: 121507136 examples [2:14:14, 13533.79 examples/s]
Generating train split: 121508640 examples [2:14:14, 13865.06 examples/s]
Generating train split: 121510122 examples [2:14:14, 12857.89 examples/s]
Generating train split: 121511483 examples [2:14:14, 12482.78 examples/s]
Generating train split: 121512788 examples [2:14:14, 12411.65 examples/s]
Generating train split: 121514066 examples [2:14:14, 11340.26 examples/s]
Generating train split: 121515537 examples [2:14:15, 12194.54 examples/s]
Generating train split: 121522892 examples [2:14:15, 28603.00 examples/s]
Generating train split: 121531400 examples [2:14:15, 44202.00 examples/s]
Generating train split: 121536117 examples [2:14:15, 35363.09 examples/s]
Generating train split: 121540135 examples [2:14:15, 26353.17 examples/s]
Generating train split: 121543422 examples [2:14:16, 20838.14 examples/s]
Generating train split: 121546097 examples [2:14:16, 21125.73 examples/s]
Generating train split: 121548640 examples [2:14:16, 21011.85 examples/s]
Generating train split: 121551035 examples [2:14:16, 20968.16 examples/s]
Generating train split: 121553343 examples [2:14:16, 19410.97 examples/s]
Generating train split: 121555438 examples [2:14:16, 18604.77 examples/s]
Generating train split: 121557634 examples [2:14:16, 19253.69 examples/s]
Generating train split: 121559646 examples [2:14:16, 16016.92 examples/s]
Generating train split: 121561601 examples [2:14:17, 16812.67 examples/s]
Generating train split: 121563461 examples [2:14:17, 17222.31 examples/s]
Generating train split: 121565283 examples [2:14:17, 14571.62 examples/s]
Generating train split: 121566867 examples [2:14:17, 14197.09 examples/s]
Generating train split: 121569603 examples [2:14:17, 17386.34 examples/s]
Generating train split: 121571475 examples [2:14:17, 13356.41 examples/s]
Generating train split: 121573265 examples [2:14:17, 14341.91 examples/s]
Generating train split: 121574896 examples [2:14:17, 14622.32 examples/s]
Generating train split: 121576501 examples [2:14:18, 12035.98 examples/s]
Generating train split: 121578534 examples [2:14:18, 13866.34 examples/s]
Generating train split: 121580099 examples [2:14:18, 14127.33 examples/s]
Generating train split: 121581640 examples [2:14:18, 14072.68 examples/s]
Generating train split: 121583510 examples [2:14:18, 15275.86 examples/s]
Generating train split: 121585121 examples [2:14:18, 12962.50 examples/s]
Generating train split: 121591561 examples [2:14:18, 25561.30 examples/s]
Generating train split: 121599633 examples [2:14:18, 39848.07 examples/s]
Generating train split: 121604100 examples [2:14:19, 33321.37 examples/s]
Generating train split: 121607951 examples [2:14:19, 29599.50 examples/s]
Generating train split: 121611321 examples [2:14:19, 22964.64 examples/s]
Generating train split: 121614092 examples [2:14:19, 19303.70 examples/s]
Generating train split: 121616422 examples [2:14:19, 20037.48 examples/s]
Generating train split: 121619773 examples [2:14:19, 22835.13 examples/s]
Generating train split: 121623257 examples [2:14:20, 25187.05 examples/s]
Generating train split: 121626089 examples [2:14:20, 25559.16 examples/s]
Generating train split: 121628865 examples [2:14:20, 22576.01 examples/s]
Generating train split: 121631330 examples [2:14:20, 21756.29 examples/s]
Generating train split: 121633771 examples [2:14:20, 22381.95 examples/s]
Generating train split: 121636117 examples [2:14:20, 17813.59 examples/s]
Generating train split: 121638108 examples [2:14:20, 17167.02 examples/s]
Generating train split: 121640391 examples [2:14:21, 18477.74 examples/s]
Generating train split: 121642379 examples [2:14:21, 15633.31 examples/s]
Generating train split: 121644638 examples [2:14:21, 17203.00 examples/s]
Generating train split: 121647103 examples [2:14:21, 18935.04 examples/s]
Generating train split: 121649334 examples [2:14:21, 19804.18 examples/s]
Generating train split: 121651429 examples [2:14:21, 15285.40 examples/s]
Generating train split: 121653810 examples [2:14:21, 17165.86 examples/s]
Generating train split: 121655752 examples [2:14:22, 14614.52 examples/s]
Generating train split: 121657419 examples [2:14:22, 14967.74 examples/s]
Generating train split: 121660223 examples [2:14:22, 18111.74 examples/s]
Generating train split: 121662234 examples [2:14:22, 15147.92 examples/s]
Generating train split: 121664305 examples [2:14:22, 16416.17 examples/s]
Generating train split: 121667129 examples [2:14:22, 19323.94 examples/s]
Generating train split: 121669258 examples [2:14:22, 15644.17 examples/s]
Generating train split: 121671070 examples [2:14:22, 14384.80 examples/s]
Generating train split: 121672691 examples [2:14:23, 13761.88 examples/s]
Generating train split: 121674187 examples [2:14:23, 11479.04 examples/s]
Generating train split: 121675945 examples [2:14:23, 12751.93 examples/s]
Generating train split: 121677364 examples [2:14:23, 12041.54 examples/s]
Generating train split: 121679657 examples [2:14:23, 14555.74 examples/s]
Generating train split: 121682659 examples [2:14:23, 18348.42 examples/s]
Generating train split: 121685397 examples [2:14:23, 20668.72 examples/s]
Generating train split: 121687627 examples [2:14:23, 20527.52 examples/s]
Generating train split: 121689787 examples [2:14:24, 20066.92 examples/s]
Generating train split: 121691871 examples [2:14:24, 18212.78 examples/s]
Generating train split: 121695667 examples [2:14:24, 23322.83 examples/s]
Generating train split: 121698141 examples [2:14:24, 19382.62 examples/s]
Generating train split: 121700279 examples [2:14:24, 17580.63 examples/s]
Generating train split: 121702942 examples [2:14:24, 19688.18 examples/s]
Generating train split: 121705078 examples [2:14:24, 16214.75 examples/s]
Generating train split: 121708079 examples [2:14:25, 19272.74 examples/s]
Generating train split: 121710717 examples [2:14:25, 20804.59 examples/s]
Generating train split: 121713006 examples [2:14:25, 17964.44 examples/s]
Generating train split: 121715551 examples [2:14:25, 19719.86 examples/s]
Generating train split: 121717710 examples [2:14:25, 19852.44 examples/s]
Generating train split: 121719836 examples [2:14:25, 16597.12 examples/s]
Generating train split: 121722272 examples [2:14:25, 18397.03 examples/s]
Generating train split: 121724290 examples [2:14:25, 14933.60 examples/s]
Generating train split: 121725993 examples [2:14:26, 15030.92 examples/s]
Generating train split: 121727647 examples [2:14:26, 14491.75 examples/s]
Generating train split: 121729800 examples [2:14:26, 16094.29 examples/s]
Generating train split: 121731525 examples [2:14:26, 16354.47 examples/s]
Generating train split: 121733243 examples [2:14:26, 15491.64 examples/s]
Generating train split: 121734912 examples [2:14:26, 15763.78 examples/s]
Generating train split: 121736541 examples [2:14:26, 12996.81 examples/s]
Generating train split: 121738050 examples [2:14:26, 13489.89 examples/s]
Generating train split: 121739495 examples [2:14:27, 12526.38 examples/s]
Generating train split: 121740827 examples [2:14:27, 11851.05 examples/s]
Generating train split: 121742181 examples [2:14:27, 12255.99 examples/s]
Generating train split: 121744375 examples [2:14:27, 14791.23 examples/s]
Generating train split: 121745929 examples [2:14:27, 13665.23 examples/s]
Generating train split: 121747364 examples [2:14:27, 12581.81 examples/s]
Generating train split: 121749654 examples [2:14:27, 15193.73 examples/s]
Generating train split: 121751258 examples [2:14:28, 11442.38 examples/s]
Generating train split: 121753257 examples [2:14:28, 13312.02 examples/s]
Generating train split: 121754799 examples [2:14:28, 12866.10 examples/s]
Generating train split: 121756224 examples [2:14:28, 11873.62 examples/s]
Generating train split: 121757515 examples [2:14:28, 11176.20 examples/s]
Generating train split: 121765893 examples [2:14:28, 28425.96 examples/s]
Generating train split: 121774529 examples [2:14:28, 43096.57 examples/s]
Generating train split: 121779463 examples [2:14:28, 33915.90 examples/s]
Generating train split: 121783594 examples [2:14:29, 27040.89 examples/s]
Generating train split: 121786995 examples [2:14:29, 28035.47 examples/s]
Generating train split: 121790351 examples [2:14:29, 24468.90 examples/s]
Generating train split: 121793217 examples [2:14:29, 20993.32 examples/s]
Generating train split: 121795653 examples [2:14:29, 20525.51 examples/s]
Generating train split: 121797936 examples [2:14:30, 17946.94 examples/s]
Generating train split: 121799923 examples [2:14:30, 18211.31 examples/s]
Generating train split: 121801883 examples [2:14:30, 17528.06 examples/s]
Generating train split: 121803723 examples [2:14:30, 16666.65 examples/s]
Generating train split: 121806464 examples [2:14:30, 19169.08 examples/s]
Generating train split: 121808483 examples [2:14:30, 12808.29 examples/s]
Generating train split: 121811369 examples [2:14:30, 15893.93 examples/s]
Generating train split: 121813380 examples [2:14:31, 12583.32 examples/s]
Generating train split: 121815031 examples [2:14:31, 12657.48 examples/s]
Generating train split: 121816560 examples [2:14:31, 12119.42 examples/s]
Generating train split: 121817955 examples [2:14:31, 10723.32 examples/s]
Generating train split: 121819465 examples [2:14:31, 11611.42 examples/s]
Generating train split: 121821482 examples [2:14:31, 13544.39 examples/s]
Generating train split: 121822995 examples [2:14:31, 13588.14 examples/s]
Generating train split: 121824469 examples [2:14:32, 11319.48 examples/s]
Generating train split: 121825734 examples [2:14:32, 10229.51 examples/s]
Generating train split: 121826859 examples [2:14:32, 9216.50 examples/s] 
Generating train split: 121831172 examples [2:14:32, 16648.48 examples/s]
Generating train split: 121840687 examples [2:14:32, 35361.17 examples/s]
Generating train split: 121847990 examples [2:14:32, 44823.00 examples/s]
Generating train split: 121853143 examples [2:14:32, 33311.55 examples/s]
Generating train split: 121857374 examples [2:14:33, 23274.61 examples/s]
Generating train split: 121860699 examples [2:14:33, 20259.25 examples/s]
Generating train split: 121863449 examples [2:14:33, 19373.18 examples/s]
Generating train split: 121865875 examples [2:14:33, 18174.13 examples/s]
Generating train split: 121868015 examples [2:14:34, 15902.06 examples/s]
Generating train split: 121869842 examples [2:14:34, 15146.46 examples/s]
Generating train split: 121871499 examples [2:14:34, 14645.85 examples/s]
Generating train split: 121873051 examples [2:14:34, 14053.32 examples/s]
Generating train split: 121874738 examples [2:14:34, 14661.49 examples/s]
Generating train split: 121876263 examples [2:14:34, 13592.99 examples/s]
Generating train split: 121882185 examples [2:14:34, 24468.67 examples/s]
Generating train split: 121890089 examples [2:14:34, 38321.40 examples/s]
Generating train split: 121894387 examples [2:14:35, 28466.02 examples/s]
Generating train split: 121897929 examples [2:14:35, 20959.94 examples/s]
Generating train split: 121900756 examples [2:14:35, 14309.55 examples/s]
Generating train split: 121902940 examples [2:14:36, 12678.22 examples/s]
Generating train split: 121904734 examples [2:14:36, 12947.22 examples/s]
Generating train split: 121906420 examples [2:14:36, 13499.22 examples/s]
Generating train split: 121908229 examples [2:14:36, 14343.98 examples/s]
Generating train split: 121910227 examples [2:14:36, 15481.38 examples/s]
Generating train split: 121912023 examples [2:14:36, 15772.97 examples/s]
Generating train split: 121914627 examples [2:14:36, 18262.66 examples/s]
Generating train split: 121916630 examples [2:14:36, 16724.26 examples/s]
Generating train split: 121918454 examples [2:14:37, 15285.55 examples/s]
Generating train split: 121920094 examples [2:14:37, 14499.77 examples/s]
Generating train split: 121921630 examples [2:14:37, 13225.11 examples/s]
Generating train split: 121923377 examples [2:14:37, 14230.80 examples/s]
Generating train split: 121924910 examples [2:14:37, 14501.65 examples/s]
Generating train split: 121927257 examples [2:14:37, 16874.09 examples/s]
Generating train split: 121930141 examples [2:14:37, 20161.83 examples/s]
Generating train split: 121932246 examples [2:14:37, 17491.51 examples/s]
Generating train split: 121935268 examples [2:14:37, 20734.15 examples/s]
Generating train split: 121937481 examples [2:14:38, 17794.02 examples/s]
Generating train split: 121939419 examples [2:14:38, 16714.39 examples/s]
Generating train split: 121947208 examples [2:14:38, 31551.63 examples/s]
Generating train split: 121955536 examples [2:14:38, 44865.30 examples/s]
Generating train split: 121960542 examples [2:14:38, 44301.82 examples/s]
Generating train split: 121965349 examples [2:14:38, 34780.60 examples/s]
Generating train split: 121969385 examples [2:14:39, 29205.55 examples/s]
Generating train split: 121972808 examples [2:14:39, 21841.42 examples/s]
Generating train split: 121975569 examples [2:14:39, 20384.56 examples/s]
Generating train split: 121978000 examples [2:14:39, 20582.56 examples/s]
Generating train split: 121980344 examples [2:14:39, 19795.27 examples/s]
Generating train split: 121982506 examples [2:14:39, 14556.37 examples/s]
Generating train split: 121984255 examples [2:14:40, 15059.58 examples/s]
Generating train split: 121985999 examples [2:14:40, 13758.70 examples/s]
Generating train split: 121987547 examples [2:14:40, 13426.23 examples/s]
Generating train split: 121989593 examples [2:14:40, 14947.23 examples/s]
Generating train split: 121991218 examples [2:14:40, 14573.24 examples/s]
Generating train split: 121992766 examples [2:14:40, 12562.29 examples/s]
Generating train split: 121994326 examples [2:14:40, 13185.15 examples/s]
Generating train split: 121995742 examples [2:14:40, 12870.80 examples/s]
Generating train split: 121997088 examples [2:14:41, 11293.09 examples/s]
Generating train split: 121998288 examples [2:14:41, 9740.64 examples/s] 
Generating train split: 122001177 examples [2:14:41, 14012.97 examples/s]
Generating train split: 122003388 examples [2:14:41, 15939.89 examples/s]
Generating train split: 122005171 examples [2:14:41, 13903.43 examples/s]
Generating train split: 122007596 examples [2:14:41, 16251.84 examples/s]
Generating train split: 122009803 examples [2:14:41, 17703.70 examples/s]
Generating train split: 122011724 examples [2:14:42, 13192.15 examples/s]
Generating train split: 122013337 examples [2:14:42, 13806.03 examples/s]
Generating train split: 122016179 examples [2:14:42, 17206.66 examples/s]
Generating train split: 122018141 examples [2:14:42, 16780.03 examples/s]
Generating train split: 122019997 examples [2:14:42, 16653.86 examples/s]
Generating train split: 122021957 examples [2:14:42, 17411.65 examples/s]
Generating train split: 122023792 examples [2:14:42, 17344.55 examples/s]
Generating train split: 122025600 examples [2:14:42, 14701.52 examples/s]
Generating train split: 122028258 examples [2:14:43, 17633.52 examples/s]
Generating train split: 122030579 examples [2:14:43, 18990.71 examples/s]
Generating train split: 122032602 examples [2:14:43, 18510.90 examples/s]
Generating train split: 122034535 examples [2:14:43, 16508.16 examples/s]
Generating train split: 122036629 examples [2:14:43, 17626.48 examples/s]
Generating train split: 122038475 examples [2:14:43, 16414.46 examples/s]
Generating train split: 122040186 examples [2:14:43, 15989.94 examples/s]
Generating train split: 122042608 examples [2:14:43, 18141.83 examples/s]
Generating train split: 122045525 examples [2:14:43, 21100.73 examples/s]
Generating train split: 122047707 examples [2:14:44, 19478.94 examples/s]
Generating train split: 122050293 examples [2:14:44, 21181.20 examples/s]
Generating train split: 122052742 examples [2:14:44, 22080.07 examples/s]
Generating train split: 122055040 examples [2:14:44, 22330.77 examples/s]
Generating train split: 122057322 examples [2:14:44, 20674.22 examples/s]
Generating train split: 122059455 examples [2:14:44, 19246.23 examples/s]
Generating train split: 122061597 examples [2:14:44, 19806.97 examples/s]
Generating train split: 122063626 examples [2:14:44, 17044.34 examples/s]
Generating train split: 122065430 examples [2:14:45, 16844.38 examples/s]
Generating train split: 122067447 examples [2:14:45, 17677.54 examples/s]
Generating train split: 122069277 examples [2:14:45, 15953.93 examples/s]
Generating train split: 122070940 examples [2:14:45, 14973.68 examples/s]
Generating train split: 122073187 examples [2:14:45, 16611.74 examples/s]
Generating train split: 122074911 examples [2:14:45, 15452.19 examples/s]
Generating train split: 122076521 examples [2:14:45, 15205.40 examples/s]
Generating train split: 122079494 examples [2:14:45, 19030.17 examples/s]
Generating train split: 122081480 examples [2:14:46, 15955.84 examples/s]
Generating train split: 122083208 examples [2:14:46, 14127.27 examples/s]
Generating train split: 122085797 examples [2:14:46, 16857.15 examples/s]
Generating train split: 122087644 examples [2:14:46, 16696.08 examples/s]
Generating train split: 122089587 examples [2:14:46, 17354.08 examples/s]
Generating train split: 122091481 examples [2:14:46, 17773.89 examples/s]
Generating train split: 122094069 examples [2:14:46, 19984.69 examples/s]
Generating train split: 122096137 examples [2:14:46, 18863.95 examples/s]
Generating train split: 122098086 examples [2:14:46, 18530.73 examples/s]
Generating train split: 122099978 examples [2:14:47, 16812.32 examples/s]
Generating train split: 122102964 examples [2:14:47, 20231.74 examples/s]
Generating train split: 122111108 examples [2:14:47, 36911.19 examples/s]
Generating train split: 122120715 examples [2:14:47, 52240.50 examples/s]
Generating train split: 122126115 examples [2:14:47, 37060.69 examples/s]
Generating train split: 122130546 examples [2:14:47, 33330.73 examples/s]
Generating train split: 122134421 examples [2:14:48, 23173.24 examples/s]
Generating train split: 122137490 examples [2:14:48, 24357.32 examples/s]
Generating train split: 122140540 examples [2:14:48, 22781.29 examples/s]
Generating train split: 122143256 examples [2:14:48, 23609.50 examples/s]
Generating train split: 122145957 examples [2:14:48, 22919.33 examples/s]
Generating train split: 122148478 examples [2:14:48, 20671.61 examples/s]
Generating train split: 122150723 examples [2:14:48, 20423.19 examples/s]
Generating train split: 122152886 examples [2:14:49, 19995.79 examples/s]
Generating train split: 122154970 examples [2:14:49, 18991.49 examples/s]
Generating train split: 122156938 examples [2:14:49, 18472.24 examples/s]
Generating train split: 122158826 examples [2:14:49, 17561.89 examples/s]
Generating train split: 122161120 examples [2:14:49, 18879.44 examples/s]
Generating train split: 122163044 examples [2:14:49, 14803.30 examples/s]
Generating train split: 122165357 examples [2:14:49, 16682.93 examples/s]
Generating train split: 122167696 examples [2:14:49, 18307.49 examples/s]
Generating train split: 122169677 examples [2:14:50, 16492.89 examples/s]
Generating train split: 122171457 examples [2:14:50, 16075.57 examples/s]
Generating train split: 122173192 examples [2:14:50, 16346.40 examples/s]
Generating train split: 122174899 examples [2:14:50, 14336.71 examples/s]
Generating train split: 122176484 examples [2:14:50, 14683.90 examples/s]
Generating train split: 122179366 examples [2:14:50, 18344.70 examples/s]
Generating train split: 122181306 examples [2:14:50, 16857.07 examples/s]
Generating train split: 122183200 examples [2:14:50, 16966.77 examples/s]
Generating train split: 122185331 examples [2:14:50, 18112.84 examples/s]
Generating train split: 122188197 examples [2:14:51, 20940.02 examples/s]
Generating train split: 122190363 examples [2:14:51, 20877.89 examples/s]
Generating train split: 122193535 examples [2:14:51, 23879.32 examples/s]
Generating train split: 122195977 examples [2:14:51, 23018.06 examples/s]
Generating train split: 122199411 examples [2:14:51, 26214.10 examples/s]
Generating train split: 122202088 examples [2:14:51, 22165.52 examples/s]
Generating train split: 122204923 examples [2:14:51, 23648.21 examples/s]
Generating train split: 122208430 examples [2:14:51, 26660.64 examples/s]
Generating train split: 122211217 examples [2:14:52, 20897.44 examples/s]
Generating train split: 122213582 examples [2:14:52, 20386.27 examples/s]
Generating train split: 122216069 examples [2:14:52, 21438.77 examples/s]
Generating train split: 122218765 examples [2:14:52, 22843.83 examples/s]
Generating train split: 122221182 examples [2:14:52, 19583.96 examples/s]
Generating train split: 122225133 examples [2:14:52, 24439.99 examples/s]
Generating train split: 122233941 examples [2:14:52, 40866.55 examples/s]
Generating train split: 122241390 examples [2:14:52, 49915.08 examples/s]
Generating train split: 122246790 examples [2:14:53, 29015.73 examples/s]
Generating train split: 122250999 examples [2:14:53, 22160.66 examples/s]
Generating train split: 122254330 examples [2:14:53, 21414.87 examples/s]
Generating train split: 122257247 examples [2:14:53, 19856.09 examples/s]
Generating train split: 122259756 examples [2:14:54, 18580.29 examples/s]
Generating train split: 122261962 examples [2:14:54, 18508.63 examples/s]
Generating train split: 122264065 examples [2:14:54, 15636.33 examples/s]
Generating train split: 122265837 examples [2:14:54, 15484.35 examples/s]
Generating train split: 122267522 examples [2:14:54, 13213.09 examples/s]
Generating train split: 122270093 examples [2:14:54, 15692.81 examples/s]
Generating train split: 122271879 examples [2:14:54, 15726.20 examples/s]
Generating train split: 122274059 examples [2:14:55, 17089.01 examples/s]
Generating train split: 122275911 examples [2:14:55, 15373.90 examples/s]
Generating train split: 122278306 examples [2:14:55, 17358.57 examples/s]
Generating train split: 122280605 examples [2:14:55, 18773.79 examples/s]
Generating train split: 122282603 examples [2:14:55, 18280.63 examples/s]
Generating train split: 122284521 examples [2:14:55, 17909.89 examples/s]
Generating train split: 122287282 examples [2:14:55, 20507.87 examples/s]
Generating train split: 122289400 examples [2:14:55, 18599.23 examples/s]
Generating train split: 122291348 examples [2:14:56, 17142.81 examples/s]
Generating train split: 122294183 examples [2:14:56, 19997.95 examples/s]
Generating train split: 122296293 examples [2:14:56, 20038.89 examples/s]
Generating train split: 122298367 examples [2:14:56, 17504.60 examples/s]
Generating train split: 122301116 examples [2:14:56, 20019.08 examples/s]
Generating train split: 122303232 examples [2:14:56, 19392.86 examples/s]
Generating train split: 122305262 examples [2:14:56, 17230.17 examples/s]
Generating train split: 122307296 examples [2:14:56, 17992.49 examples/s]
Generating train split: 122309190 examples [2:14:56, 18221.49 examples/s]
Generating train split: 122311070 examples [2:14:57, 15032.15 examples/s]
Generating train split: 122313582 examples [2:14:57, 17466.65 examples/s]
Generating train split: 122315476 examples [2:14:57, 15310.23 examples/s]
Generating train split: 122317155 examples [2:14:57, 13602.74 examples/s]
Generating train split: 122319150 examples [2:14:57, 15036.72 examples/s]
Generating train split: 122320780 examples [2:14:57, 14557.29 examples/s]
Generating train split: 122322322 examples [2:14:57, 13796.74 examples/s]
Generating train split: 122324248 examples [2:14:58, 14964.44 examples/s]
Generating train split: 122330765 examples [2:14:58, 28044.01 examples/s]
Generating train split: 122339276 examples [2:14:58, 43520.38 examples/s]
Generating train split: 122344138 examples [2:14:58, 44637.97 examples/s]
Generating train split: 122348838 examples [2:14:58, 34402.05 examples/s]
Generating train split: 122352798 examples [2:14:58, 33556.50 examples/s]
Generating train split: 122356511 examples [2:14:58, 27218.72 examples/s]
Generating train split: 122359657 examples [2:14:59, 23501.20 examples/s]
Generating train split: 122362343 examples [2:14:59, 20133.13 examples/s]
Generating train split: 122364638 examples [2:14:59, 20093.30 examples/s]
Generating train split: 122369415 examples [2:14:59, 25977.30 examples/s]
Generating train split: 122375996 examples [2:14:59, 35252.03 examples/s]
Generating train split: 122382925 examples [2:14:59, 43740.01 examples/s]
Generating train split: 122390250 examples [2:14:59, 51492.24 examples/s]
Generating train split: 122398329 examples [2:14:59, 59487.73 examples/s]
Generating train split: 122405962 examples [2:14:59, 64187.93 examples/s]
Generating train split: 122413791 examples [2:15:00, 68201.78 examples/s]
Generating train split: 122422065 examples [2:15:00, 72363.88 examples/s]
Generating train split: 122429494 examples [2:15:00, 71400.51 examples/s]
Generating train split: 122437087 examples [2:15:00, 72714.01 examples/s]
Generating train split: 122445161 examples [2:15:00, 75064.38 examples/s]
Generating train split: 122453331 examples [2:15:00, 77010.44 examples/s]
Generating train split: 122461454 examples [2:15:00, 78257.06 examples/s]
Generating train split: 122469331 examples [2:15:00, 78264.52 examples/s]
Generating train split: 122477192 examples [2:15:00, 77863.04 examples/s]
Generating train split: 122485000 examples [2:15:00, 77893.55 examples/s]
Generating train split: 122492805 examples [2:15:01, 75960.08 examples/s]
Generating train split: 122500776 examples [2:15:01, 76811.08 examples/s]
Generating train split: 122509058 examples [2:15:01, 78555.91 examples/s]
Generating train split: 122517108 examples [2:15:01, 79122.73 examples/s]
Generating train split: 122525034 examples [2:15:01, 76584.52 examples/s]
Generating train split: 122533027 examples [2:15:01, 77533.84 examples/s]
Generating train split: 122540944 examples [2:15:01, 77981.20 examples/s]
Generating train split: 122548763 examples [2:15:01, 74833.03 examples/s]
Generating train split: 122556288 examples [2:15:01, 72688.04 examples/s]
Generating train split: 122563716 examples [2:15:02, 73081.84 examples/s]
Generating train split: 122571068 examples [2:15:02, 69848.26 examples/s]
Generating train split: 122578093 examples [2:15:02, 56319.83 examples/s]
Generating train split: 122584156 examples [2:15:02, 50677.63 examples/s]
Generating train split: 122589580 examples [2:15:02, 51179.56 examples/s]
Generating train split: 122594963 examples [2:15:02, 50625.50 examples/s]
Generating train split: 122600201 examples [2:15:02, 41501.51 examples/s]
Generating train split: 122604709 examples [2:15:03, 41614.10 examples/s]
Generating train split: 122609119 examples [2:15:03, 36500.09 examples/s]
Generating train split: 122613015 examples [2:15:03, 30387.90 examples/s]
Generating train split: 122616344 examples [2:15:03, 28220.90 examples/s]
Generating train split: 122619362 examples [2:15:03, 27362.43 examples/s]
Generating train split: 122622225 examples [2:15:03, 23872.34 examples/s]
Generating train split: 122625033 examples [2:15:03, 24794.89 examples/s]
Generating train split: 122627634 examples [2:15:04, 19449.83 examples/s]
Generating train split: 122629856 examples [2:15:04, 19990.70 examples/s]
Generating train split: 122632039 examples [2:15:04, 18896.57 examples/s]
Generating train split: 122634304 examples [2:15:04, 19734.55 examples/s]
Generating train split: 122636387 examples [2:15:04, 17839.98 examples/s]
Generating train split: 122639117 examples [2:15:04, 20114.77 examples/s]
Generating train split: 122641324 examples [2:15:04, 20563.64 examples/s]
Generating train split: 122643486 examples [2:15:04, 18401.51 examples/s]
Generating train split: 122645936 examples [2:15:05, 19844.61 examples/s]
Generating train split: 122648018 examples [2:15:05, 18135.23 examples/s]
Generating train split: 122649915 examples [2:15:05, 17997.43 examples/s]
Generating train split: 122652499 examples [2:15:05, 20047.79 examples/s]
Generating train split: 122655759 examples [2:15:05, 23464.74 examples/s]
Generating train split: 122658188 examples [2:15:05, 22027.43 examples/s]
Generating train split: 122660465 examples [2:15:05, 20337.78 examples/s]
Generating train split: 122662845 examples [2:15:05, 21230.45 examples/s]
Generating train split: 122665168 examples [2:15:05, 21773.85 examples/s]
Generating train split: 122667406 examples [2:15:06, 17798.18 examples/s]
Generating train split: 122669332 examples [2:15:06, 16652.88 examples/s]
Generating train split: 122671108 examples [2:15:06, 16212.43 examples/s]
Generating train split: 122673442 examples [2:15:06, 17892.58 examples/s]
Generating train split: 122675313 examples [2:15:06, 17686.54 examples/s]
Generating train split: 122677137 examples [2:15:06, 15533.04 examples/s]
Generating train split: 122679452 examples [2:15:06, 17432.89 examples/s]
Generating train split: 122681707 examples [2:15:06, 18663.87 examples/s]
Generating train split: 122683655 examples [2:15:07, 14832.66 examples/s]
Generating train split: 122685315 examples [2:15:07, 14826.12 examples/s]
Generating train split: 122688086 examples [2:15:07, 17973.05 examples/s]
Generating train split: 122690050 examples [2:15:07, 18091.83 examples/s]
Generating train split: 122691970 examples [2:15:07, 18039.59 examples/s]
Generating train split: 122693858 examples [2:15:07, 17937.79 examples/s]
Generating train split: 122695706 examples [2:15:07, 17513.96 examples/s]
Generating train split: 122697496 examples [2:15:07, 16898.44 examples/s]
Generating train split: 122699219 examples [2:15:08, 15837.67 examples/s]
Generating train split: 122700832 examples [2:15:08, 14793.54 examples/s]
Generating train split: 122702430 examples [2:15:08, 15077.34 examples/s]
Generating train split: 122703974 examples [2:15:08, 13000.13 examples/s]
Generating train split: 122705643 examples [2:15:08, 13905.41 examples/s]
Generating train split: 122707093 examples [2:15:08, 13178.94 examples/s]
Generating train split: 122709398 examples [2:15:08, 15723.90 examples/s]
Generating train split: 122711040 examples [2:15:08, 15834.12 examples/s]
Generating train split: 122712787 examples [2:15:08, 16282.41 examples/s]
Generating train split: 122714462 examples [2:15:09, 15904.20 examples/s]
Generating train split: 122716083 examples [2:15:09, 15917.31 examples/s]
Generating train split: 122717738 examples [2:15:09, 16058.73 examples/s]
Generating train split: 122719358 examples [2:15:09, 14537.16 examples/s]
Generating train split: 122721561 examples [2:15:09, 16575.27 examples/s]
Generating train split: 122723499 examples [2:15:09, 17350.78 examples/s]
Generating train split: 122726834 examples [2:15:09, 21875.44 examples/s]
Generating train split: 122729078 examples [2:15:09, 18299.87 examples/s]
Generating train split: 122731047 examples [2:15:10, 18379.64 examples/s]
Generating train split: 122732991 examples [2:15:10, 12495.29 examples/s]
Generating train split: 122734552 examples [2:15:10, 12713.35 examples/s]
Generating train split: 122736053 examples [2:15:10, 12620.00 examples/s]
Generating train split: 122738641 examples [2:15:10, 15658.03 examples/s]
Generating train split: 122740710 examples [2:15:10, 16899.80 examples/s]
Generating train split: 122742853 examples [2:15:10, 18071.87 examples/s]
Generating train split: 122744801 examples [2:15:11, 14362.29 examples/s]
Generating train split: 122747979 examples [2:15:11, 18336.53 examples/s]
Generating train split: 122750081 examples [2:15:11, 17786.91 examples/s]
Generating train split: 122753744 examples [2:15:11, 22452.05 examples/s]
Generating train split: 122756217 examples [2:15:11, 17257.86 examples/s]
Generating train split: 122758276 examples [2:15:11, 16375.36 examples/s]
Generating train split: 122760141 examples [2:15:11, 15344.68 examples/s]
Generating train split: 122762867 examples [2:15:11, 17975.63 examples/s]
Generating train split: 122764875 examples [2:15:12, 16930.71 examples/s]
Generating train split: 122767357 examples [2:15:12, 18772.88 examples/s]
Generating train split: 122769378 examples [2:15:12, 16344.30 examples/s]
Generating train split: 122771155 examples [2:15:12, 15429.33 examples/s]
Generating train split: 122772805 examples [2:15:12, 14489.39 examples/s]
Generating train split: 122774960 examples [2:15:12, 16174.95 examples/s]
Generating train split: 122776669 examples [2:15:12, 14817.57 examples/s]
Generating train split: 122778242 examples [2:15:13, 14508.52 examples/s]
Generating train split: 122779995 examples [2:15:13, 15259.72 examples/s]
Generating train split: 122781934 examples [2:15:13, 16351.16 examples/s]
Generating train split: 122783634 examples [2:15:13, 15775.99 examples/s]
Generating train split: 122785421 examples [2:15:13, 16347.16 examples/s]
Generating train split: 122787880 examples [2:15:13, 18646.17 examples/s]
Generating train split: 122789801 examples [2:15:13, 17295.67 examples/s]
Generating train split: 122791594 examples [2:15:13, 16662.94 examples/s]
Generating train split: 122793619 examples [2:15:13, 17635.74 examples/s]
Generating train split: 122795477 examples [2:15:13, 17877.56 examples/s]
Generating train split: 122797301 examples [2:15:14, 15516.29 examples/s]
Generating train split: 122799288 examples [2:15:14, 16622.37 examples/s]
Generating train split: 122801015 examples [2:15:14, 15791.88 examples/s]
Generating train split: 122802650 examples [2:15:14, 15571.90 examples/s]
Generating train split: 122804247 examples [2:15:14, 15082.70 examples/s]
Generating train split: 122806074 examples [2:15:14, 15942.57 examples/s]
Generating train split: 122807892 examples [2:15:14, 16430.80 examples/s]
Generating train split: 122809564 examples [2:15:14, 14057.47 examples/s]
Generating train split: 122811867 examples [2:15:15, 16320.58 examples/s]
Generating train split: 122813587 examples [2:15:15, 15963.97 examples/s]
Generating train split: 122815252 examples [2:15:15, 15805.56 examples/s]
Generating train split: 122817194 examples [2:15:15, 16784.08 examples/s]
Generating train split: 122819129 examples [2:15:15, 17455.62 examples/s]
Generating train split: 122821021 examples [2:15:15, 17870.77 examples/s]
Generating train split: 122822846 examples [2:15:15, 16310.58 examples/s]
Generating train split: 122824521 examples [2:15:15, 13717.10 examples/s]
Generating train split: 122826858 examples [2:15:15, 16071.74 examples/s]
Generating train split: 122828588 examples [2:15:16, 12721.64 examples/s]
Generating train split: 122830142 examples [2:15:16, 13329.05 examples/s]
Generating train split: 122832613 examples [2:15:16, 16066.42 examples/s]
Generating train split: 122834398 examples [2:15:16, 11853.12 examples/s]
Generating train split: 122836310 examples [2:15:16, 13345.74 examples/s]
Generating train split: 122837904 examples [2:15:16, 13128.47 examples/s]
Generating train split: 122845872 examples [2:15:16, 28799.13 examples/s]
Generating train split: 122854996 examples [2:15:17, 43672.89 examples/s]
Generating train split: 122859954 examples [2:15:17, 26507.43 examples/s]
Generating train split: 122863816 examples [2:15:17, 25719.05 examples/s]
Generating train split: 122867240 examples [2:15:17, 19738.27 examples/s]
Generating train split: 122869976 examples [2:15:18, 19583.81 examples/s]
Generating train split: 122872456 examples [2:15:18, 17086.86 examples/s]
Generating train split: 122874543 examples [2:15:18, 16285.64 examples/s]
Generating train split: 122876418 examples [2:15:18, 16381.14 examples/s]
Generating train split: 122878241 examples [2:15:18, 16489.71 examples/s]
Generating train split: 122880200 examples [2:15:18, 17181.64 examples/s]
Generating train split: 122882036 examples [2:15:18, 16262.09 examples/s]
Generating train split: 122883745 examples [2:15:19, 15486.73 examples/s]
Generating train split: 122885353 examples [2:15:19, 15610.10 examples/s]
Generating train split: 122886959 examples [2:15:19, 13018.99 examples/s]
Generating train split: 122889059 examples [2:15:19, 14894.05 examples/s]
Generating train split: 122892226 examples [2:15:19, 19099.94 examples/s]
Generating train split: 122894298 examples [2:15:19, 15579.13 examples/s]
Generating train split: 122896071 examples [2:15:19, 15616.57 examples/s]
Generating train split: 122897790 examples [2:15:19, 14062.88 examples/s]
Generating train split: 122899325 examples [2:15:20, 12513.06 examples/s]
Generating train split: 122902057 examples [2:15:20, 15846.41 examples/s]
Generating train split: 122904057 examples [2:15:20, 16760.33 examples/s]
Generating train split: 122905882 examples [2:15:20, 13167.53 examples/s]
Generating train split: 122908560 examples [2:15:20, 16101.19 examples/s]
Generating train split: 122910431 examples [2:15:20, 12913.87 examples/s]
Generating train split: 122914646 examples [2:15:20, 18997.72 examples/s]
Generating train split: 122917783 examples [2:15:21, 21825.48 examples/s]
Generating train split: 122920374 examples [2:15:21, 21227.09 examples/s]
Generating train split: 122922781 examples [2:15:21, 19977.65 examples/s]
Generating train split: 122924995 examples [2:15:21, 19194.59 examples/s]
Generating train split: 122927076 examples [2:15:21, 15215.22 examples/s]
Generating train split: 122929746 examples [2:15:21, 17660.38 examples/s]
Generating train split: 122931757 examples [2:15:22, 13797.65 examples/s]
Generating train split: 122934526 examples [2:15:22, 16590.89 examples/s]
Generating train split: 122936770 examples [2:15:22, 17896.29 examples/s]
Generating train split: 122938845 examples [2:15:22, 15655.90 examples/s]
Generating train split: 122940652 examples [2:15:22, 14131.19 examples/s]
Generating train split: 122942239 examples [2:15:22, 13110.37 examples/s]
Generating train split: 122943679 examples [2:15:22, 13289.21 examples/s]
Generating train split: 122945100 examples [2:15:22, 13084.33 examples/s]
Generating train split: 122946555 examples [2:15:23, 13438.68 examples/s]
Generating train split: 122947958 examples [2:15:23, 11864.15 examples/s]
Generating train split: 122949672 examples [2:15:23, 13144.77 examples/s]
Generating train split: 122952110 examples [2:15:23, 16057.48 examples/s]
Generating train split: 122953821 examples [2:15:23, 16129.13 examples/s]
Generating train split: 122955505 examples [2:15:23, 15797.79 examples/s]
Generating train split: 122957500 examples [2:15:23, 16927.12 examples/s]
Generating train split: 122959235 examples [2:15:23, 11938.43 examples/s]
Generating train split: 122960666 examples [2:15:24, 12347.98 examples/s]
Generating train split: 122962075 examples [2:15:24, 11510.50 examples/s]
Generating train split: 122964302 examples [2:15:24, 14015.06 examples/s]
Generating train split: 122965866 examples [2:15:24, 12658.30 examples/s]
Generating train split: 122967850 examples [2:15:24, 14374.38 examples/s]
Generating train split: 122970668 examples [2:15:24, 17824.16 examples/s]
Generating train split: 122972608 examples [2:15:24, 17965.97 examples/s]
Generating train split: 122974999 examples [2:15:24, 19581.48 examples/s]
Generating train split: 122977829 examples [2:15:24, 21944.99 examples/s]
Generating train split: 122980230 examples [2:15:25, 22375.38 examples/s]
Generating train split: 122982529 examples [2:15:25, 16165.35 examples/s]
Generating train split: 122985195 examples [2:15:25, 18539.43 examples/s]
Generating train split: 122987382 examples [2:15:25, 19262.56 examples/s]
Generating train split: 122989516 examples [2:15:25, 18099.55 examples/s]
Generating train split: 122991738 examples [2:15:25, 18984.44 examples/s]
Generating train split: 122994925 examples [2:15:25, 22304.96 examples/s]
Generating train split: 122997283 examples [2:15:26, 14385.57 examples/s]
Generating train split: 122999169 examples [2:15:26, 13017.18 examples/s]
Generating train split: 123000787 examples [2:15:26, 12697.46 examples/s]
Generating train split: 123002305 examples [2:15:26, 13206.60 examples/s]
Generating train split: 123004659 examples [2:15:26, 15551.87 examples/s]
Generating train split: 123006414 examples [2:15:26, 15159.00 examples/s]
Generating train split: 123008607 examples [2:15:26, 16817.90 examples/s]
Generating train split: 123012071 examples [2:15:27, 21476.88 examples/s]
Generating train split: 123014389 examples [2:15:27, 15961.67 examples/s]
Generating train split: 123016303 examples [2:15:27, 16041.40 examples/s]
Generating train split: 123018563 examples [2:15:27, 17467.52 examples/s]
Generating train split: 123020505 examples [2:15:27, 14904.52 examples/s]
Generating train split: 123024651 examples [2:15:27, 20937.42 examples/s]
Generating train split: 123027068 examples [2:15:28, 15851.57 examples/s]
Generating train split: 123029047 examples [2:15:28, 16221.20 examples/s]
Generating train split: 123037287 examples [2:15:28, 30825.53 examples/s]
Generating train split: 123045727 examples [2:15:28, 43654.76 examples/s]
Generating train split: 123050926 examples [2:15:28, 42011.37 examples/s]
Generating train split: 123055716 examples [2:15:28, 29475.24 examples/s]
Generating train split: 123059569 examples [2:15:28, 24125.44 examples/s]
Generating train split: 123062730 examples [2:15:29, 21881.98 examples/s]
Generating train split: 123065434 examples [2:15:29, 22601.07 examples/s]
Generating train split: 123068099 examples [2:15:29, 21482.57 examples/s]
Generating train split: 123070529 examples [2:15:29, 21367.09 examples/s]
Generating train split: 123072853 examples [2:15:29, 21344.10 examples/s]
Generating train split: 123075123 examples [2:15:29, 20188.40 examples/s]
Generating train split: 123077236 examples [2:15:29, 18871.55 examples/s]
Generating train split: 123079200 examples [2:15:30, 16022.94 examples/s]
Generating train split: 123080897 examples [2:15:30, 13591.48 examples/s]
Generating train split: 123082927 examples [2:15:30, 14978.11 examples/s]
Generating train split: 123084558 examples [2:15:30, 14478.73 examples/s]
Generating train split: 123086090 examples [2:15:30, 13913.38 examples/s]
Generating train split: 123088552 examples [2:15:30, 16525.85 examples/s]
Generating train split: 123092920 examples [2:15:30, 23546.15 examples/s]
Generating train split: 123096537 examples [2:15:30, 26930.70 examples/s]
Generating train split: 123099400 examples [2:15:31, 23044.04 examples/s]
Generating train split: 123102037 examples [2:15:31, 23869.76 examples/s]
Generating train split: 123104946 examples [2:15:31, 25200.06 examples/s]
Generating train split: 123107597 examples [2:15:31, 21678.02 examples/s]
Generating train split: 123110661 examples [2:15:31, 23858.48 examples/s]
Generating train split: 123113216 examples [2:15:31, 23639.10 examples/s]
Generating train split: 123115694 examples [2:15:31, 22943.11 examples/s]
Generating train split: 123118075 examples [2:15:31, 19730.89 examples/s]
Generating train split: 123120169 examples [2:15:32, 19682.33 examples/s]
Generating train split: 123122224 examples [2:15:32, 18236.42 examples/s]
Generating train split: 123124127 examples [2:15:32, 16288.57 examples/s]
Generating train split: 123125852 examples [2:15:32, 16507.12 examples/s]
Generating train split: 123127560 examples [2:15:32, 15564.30 examples/s]
Generating train split: 123129169 examples [2:15:32, 12858.37 examples/s]
Generating train split: 123131779 examples [2:15:32, 15776.93 examples/s]
Generating train split: 123133651 examples [2:15:32, 16477.26 examples/s]
Generating train split: 123135420 examples [2:15:33, 16387.13 examples/s]
Generating train split: 123137139 examples [2:15:33, 13456.89 examples/s]
Generating train split: 123138618 examples [2:15:33, 11346.28 examples/s]
Generating train split: 123140707 examples [2:15:33, 13409.56 examples/s]
Generating train split: 123144099 examples [2:15:33, 18255.71 examples/s]
Generating train split: 123146179 examples [2:15:33, 16646.55 examples/s]
Generating train split: 123148043 examples [2:15:33, 16049.50 examples/s]
Generating train split: 123149782 examples [2:15:34, 16248.85 examples/s]
Generating train split: 123151787 examples [2:15:34, 17204.08 examples/s]
Generating train split: 123153597 examples [2:15:34, 12787.10 examples/s]
Generating train split: 123155092 examples [2:15:34, 13175.80 examples/s]
Generating train split: 123156579 examples [2:15:34, 12197.69 examples/s]
Generating train split: 123157931 examples [2:15:34, 10822.59 examples/s]
Generating train split: 123159117 examples [2:15:34, 10755.77 examples/s]
Generating train split: 123160267 examples [2:15:35, 9978.33 examples/s] 
Generating train split: 123161550 examples [2:15:35, 10625.37 examples/s]
Generating train split: 123162672 examples [2:15:35, 10109.21 examples/s]
Generating train split: 123163990 examples [2:15:35, 10871.89 examples/s]
Generating train split: 123165117 examples [2:15:35, 9729.27 examples/s] 
Generating train split: 123166300 examples [2:15:35, 10248.85 examples/s]
Generating train split: 123167427 examples [2:15:35, 10460.14 examples/s]
Generating train split: 123168505 examples [2:15:35, 9654.12 examples/s] 
Generating train split: 123169501 examples [2:15:35, 9542.55 examples/s]
Generating train split: 123170477 examples [2:15:36, 6854.48 examples/s]
Generating train split: 123171279 examples [2:15:36, 5517.44 examples/s]
Generating train split: 123171944 examples [2:15:36, 5731.01 examples/s]
Generating train split: 123172607 examples [2:15:36, 5810.30 examples/s]
Generating train split: 123173254 examples [2:15:36, 5492.98 examples/s]
Generating train split: 123173848 examples [2:15:36, 4894.17 examples/s]
Generating train split: 123174375 examples [2:15:37, 4220.08 examples/s]
Generating train split: 123174832 examples [2:15:37, 3273.55 examples/s]
Generating train split: 123175208 examples [2:15:37, 2468.33 examples/s]
Generating train split: 123175511 examples [2:15:37, 2501.75 examples/s]
Generating train split: 123175847 examples [2:15:37, 2659.38 examples/s]
Generating train split: 123176151 examples [2:15:38, 2563.22 examples/s]
Generating train split: 123176743 examples [2:15:38, 3295.57 examples/s]
Generating train split: 123177627 examples [2:15:38, 4611.75 examples/s]
Generating train split: 123178152 examples [2:15:38, 3863.15 examples/s]
Generating train split: 123178866 examples [2:15:38, 4601.69 examples/s]
Generating train split: 123179814 examples [2:15:38, 5794.76 examples/s]
Generating train split: 123180952 examples [2:15:38, 7235.72 examples/s]
Generating train split: 123182526 examples [2:15:38, 9519.57 examples/s]
Generating train split: 123183561 examples [2:15:38, 9542.54 examples/s]
Generating train split: 123185285 examples [2:15:39, 11695.10 examples/s]
Generating train split: 123189730 examples [2:15:39, 21049.09 examples/s]
Generating train split: 123195181 examples [2:15:39, 30734.51 examples/s]
Generating train split: 123198356 examples [2:15:39, 24186.49 examples/s]
Generating train split: 123201063 examples [2:15:39, 21140.54 examples/s]
Generating train split: 123204451 examples [2:15:39, 24048.84 examples/s]
Generating train split: 123207163 examples [2:15:39, 24749.67 examples/s]
Generating train split: 123209843 examples [2:15:39, 20872.90 examples/s]
Generating train split: 123212163 examples [2:15:40, 19706.45 examples/s]
Generating train split: 123214294 examples [2:15:40, 17409.19 examples/s]
Generating train split: 123217240 examples [2:15:40, 20126.49 examples/s]
Generating train split: 123219739 examples [2:15:40, 21308.51 examples/s]
Generating train split: 123222037 examples [2:15:40, 17712.42 examples/s]
Generating train split: 123224575 examples [2:15:40, 19482.63 examples/s]
Generating train split: 123227255 examples [2:15:40, 21285.51 examples/s]
Generating train split: 123229557 examples [2:15:41, 15333.35 examples/s]
Generating train split: 123231434 examples [2:15:41, 15706.78 examples/s]
Generating train split: 123233355 examples [2:15:41, 16198.49 examples/s]
Generating train split: 123235171 examples [2:15:41, 12843.54 examples/s]
Generating train split: 123237490 examples [2:15:41, 15004.65 examples/s]
Generating train split: 123239438 examples [2:15:41, 15994.10 examples/s]
Generating train split: 123241248 examples [2:15:41, 15864.41 examples/s]
Generating train split: 123243457 examples [2:15:42, 17436.77 examples/s]
Generating train split: 123245335 examples [2:15:42, 15646.43 examples/s]
Generating train split: 123247026 examples [2:15:42, 12835.84 examples/s]
Generating train split: 123248754 examples [2:15:42, 13826.76 examples/s]
Generating train split: 123250304 examples [2:15:42, 14123.96 examples/s]
Generating train split: 123251826 examples [2:15:42, 12797.80 examples/s]
Generating train split: 123253709 examples [2:15:42, 14271.82 examples/s]
Generating train split: 123255765 examples [2:15:42, 15896.57 examples/s]
Generating train split: 123257462 examples [2:15:43, 16068.36 examples/s]
Generating train split: 123263222 examples [2:15:43, 27564.01 examples/s]
Generating train split: 123271749 examples [2:15:43, 43903.04 examples/s]
Generating train split: 123276334 examples [2:15:43, 43155.31 examples/s]
Generating train split: 123280796 examples [2:15:43, 33815.76 examples/s]
Generating train split: 123284582 examples [2:15:43, 23104.67 examples/s]
Generating train split: 123287746 examples [2:15:43, 24666.35 examples/s]
Generating train split: 123290810 examples [2:15:44, 19108.29 examples/s]
Generating train split: 123293540 examples [2:15:44, 20566.67 examples/s]
Generating train split: 123296106 examples [2:15:44, 18608.70 examples/s]
Generating train split: 123298321 examples [2:15:44, 17037.54 examples/s]
Generating train split: 123306237 examples [2:15:44, 29606.65 examples/s]
Generating train split: 123314589 examples [2:15:44, 41689.47 examples/s]
Generating train split: 123319717 examples [2:15:44, 42707.70 examples/s]
Generating train split: 123324669 examples [2:15:45, 27267.99 examples/s]
Generating train split: 123328566 examples [2:15:45, 24795.71 examples/s]
Generating train split: 123331871 examples [2:15:45, 23637.53 examples/s]
Generating train split: 123334796 examples [2:15:45, 22120.22 examples/s]
Generating train split: 123337390 examples [2:15:46, 20197.02 examples/s]
Generating train split: 123339668 examples [2:15:46, 16867.66 examples/s]
Generating train split: 123341587 examples [2:15:46, 15529.15 examples/s]
Generating train split: 123343308 examples [2:15:46, 15796.43 examples/s]
Generating train split: 123345011 examples [2:15:46, 14931.97 examples/s]
Generating train split: 123347126 examples [2:15:46, 16271.54 examples/s]
Generating train split: 123348923 examples [2:15:46, 16643.01 examples/s]
Generating train split: 123350674 examples [2:15:46, 15806.07 examples/s]
Generating train split: 123352697 examples [2:15:47, 16901.21 examples/s]
Generating train split: 123354445 examples [2:15:47, 16509.96 examples/s]
Generating train split: 123356373 examples [2:15:47, 17181.75 examples/s]
Generating train split: 123358133 examples [2:15:47, 16275.90 examples/s]
Generating train split: 123359795 examples [2:15:47, 15922.61 examples/s]
Generating train split: 123361898 examples [2:15:47, 17208.86 examples/s]
Generating train split: 123363643 examples [2:15:47, 15440.94 examples/s]
Generating train split: 123365236 examples [2:15:47, 13795.41 examples/s]
Generating train split: 123367414 examples [2:15:47, 15743.56 examples/s]
Generating train split: 123369713 examples [2:15:48, 17606.38 examples/s]
Generating train split: 123371552 examples [2:15:48, 16996.49 examples/s]
Generating train split: 123374460 examples [2:15:48, 20259.73 examples/s]
Generating train split: 123376561 examples [2:15:48, 18862.88 examples/s]
Generating train split: 123378526 examples [2:15:48, 17223.42 examples/s]
Generating train split: 123381744 examples [2:15:48, 21060.36 examples/s]
Generating train split: 123386220 examples [2:15:48, 27418.21 examples/s]
Generating train split: 123394724 examples [2:15:48, 43378.65 examples/s]
Generating train split: 123401288 examples [2:15:48, 49657.23 examples/s]
Generating train split: 123406460 examples [2:15:49, 27304.43 examples/s]
Generating train split: 123410481 examples [2:15:49, 21189.36 examples/s]
Generating train split: 123413670 examples [2:15:49, 19452.94 examples/s]
Generating train split: 123416354 examples [2:15:50, 19009.90 examples/s]
Generating train split: 123421685 examples [2:15:50, 24983.00 examples/s]
Generating train split: 123429926 examples [2:15:50, 36428.62 examples/s]
Generating train split: 123436104 examples [2:15:50, 42039.01 examples/s]
Generating train split: 123441297 examples [2:15:50, 32676.42 examples/s]
Generating train split: 123445571 examples [2:15:50, 31510.93 examples/s]
Generating train split: 123449405 examples [2:15:50, 26465.69 examples/s]
Generating train split: 123452657 examples [2:15:51, 27616.76 examples/s]
Generating train split: 123455885 examples [2:15:51, 27375.80 examples/s]
Generating train split: 123458945 examples [2:15:51, 22851.74 examples/s]
Generating train split: 123461552 examples [2:15:51, 21243.97 examples/s]
Generating train split: 123463890 examples [2:15:51, 16938.08 examples/s]
Generating train split: 123466337 examples [2:15:51, 18375.22 examples/s]
Generating train split: 123469375 examples [2:15:51, 20952.84 examples/s]
Generating train split: 123472040 examples [2:15:52, 22260.44 examples/s]
Generating train split: 123474503 examples [2:15:52, 18055.61 examples/s]
Generating train split: 123483406 examples [2:15:52, 33714.95 examples/s]
Generating train split: 123491393 examples [2:15:52, 44761.29 examples/s]
Generating train split: 123496682 examples [2:15:52, 34575.01 examples/s]
Generating train split: 123501043 examples [2:15:52, 33840.08 examples/s]
Generating train split: 123505066 examples [2:15:53, 30589.69 examples/s]
Generating train split: 123508591 examples [2:15:53, 29444.70 examples/s]
Generating train split: 123511849 examples [2:15:53, 28511.56 examples/s]
Generating train split: 123514912 examples [2:15:53, 24048.65 examples/s]
Generating train split: 123517540 examples [2:15:53, 20364.99 examples/s]
Generating train split: 123519972 examples [2:15:53, 21136.75 examples/s]
Generating train split: 123522283 examples [2:15:53, 19337.73 examples/s]
Generating train split: 123524346 examples [2:15:54, 18470.65 examples/s]
Generating train split: 123527169 examples [2:15:54, 20569.88 examples/s]
Generating train split: 123529349 examples [2:15:54, 19907.80 examples/s]
Generating train split: 123531429 examples [2:15:54, 16388.37 examples/s]
Generating train split: 123533593 examples [2:15:54, 17538.04 examples/s]
Generating train split: 123535479 examples [2:15:54, 17116.67 examples/s]
Generating train split: 123537282 examples [2:15:54, 16218.38 examples/s]
Generating train split: 123539482 examples [2:15:54, 17627.90 examples/s]
Generating train split: 123541323 examples [2:15:55, 17364.13 examples/s]
Generating train split: 123543211 examples [2:15:55, 17511.38 examples/s]
Generating train split: 123545001 examples [2:15:55, 15509.62 examples/s]
Generating train split: 123546617 examples [2:15:55, 14492.25 examples/s]
Generating train split: 123548120 examples [2:15:55, 13260.21 examples/s]
Generating train split: 123549643 examples [2:15:55, 13736.16 examples/s]
Generating train split: 123551102 examples [2:15:55, 13937.50 examples/s]
Generating train split: 123552788 examples [2:15:55, 14724.07 examples/s]
Generating train split: 123554301 examples [2:15:56, 12311.86 examples/s]
Generating train split: 123556876 examples [2:15:56, 15644.00 examples/s]
Generating train split: 123559264 examples [2:15:56, 17799.74 examples/s]
Generating train split: 123561173 examples [2:15:56, 16048.05 examples/s]
Generating train split: 123562902 examples [2:15:56, 14749.71 examples/s]
Generating train split: 123565158 examples [2:15:56, 16662.45 examples/s]
Generating train split: 123567084 examples [2:15:56, 17322.73 examples/s]
Generating train split: 123568898 examples [2:15:56, 17280.62 examples/s]
Generating train split: 123571300 examples [2:15:56, 19131.69 examples/s]
Generating train split: 123578499 examples [2:15:57, 34085.25 examples/s]
Generating train split: 123586782 examples [2:15:57, 46351.96 examples/s]
Generating train split: 123591455 examples [2:15:57, 31007.56 examples/s]
Generating train split: 123595239 examples [2:15:57, 24459.37 examples/s]
Generating train split: 123598338 examples [2:15:57, 23203.55 examples/s]
Generating train split: 123601102 examples [2:15:57, 22241.33 examples/s]
Generating train split: 123603617 examples [2:15:58, 20991.40 examples/s]
Generating train split: 123605909 examples [2:15:58, 20971.65 examples/s]
Generating train split: 123608482 examples [2:15:58, 22038.28 examples/s]
Generating train split: 123610820 examples [2:15:58, 20044.66 examples/s]
Generating train split: 123612930 examples [2:15:58, 17377.65 examples/s]
Generating train split: 123614785 examples [2:15:58, 16618.62 examples/s]
Generating train split: 123619811 examples [2:15:58, 24473.08 examples/s]
Generating train split: 123627694 examples [2:15:58, 38069.31 examples/s]
Generating train split: 123634141 examples [2:15:59, 45005.37 examples/s]
Generating train split: 123639063 examples [2:15:59, 28524.10 examples/s]
Generating train split: 123642963 examples [2:15:59, 24988.31 examples/s]
Generating train split: 123646253 examples [2:15:59, 22794.48 examples/s]
Generating train split: 123649072 examples [2:15:59, 21885.65 examples/s]
Generating train split: 123651633 examples [2:16:00, 22308.41 examples/s]
Generating train split: 123654145 examples [2:16:00, 17025.70 examples/s]
Generating train split: 123659110 examples [2:16:00, 23117.38 examples/s]
Generating train split: 123665137 examples [2:16:00, 30936.03 examples/s]
Generating train split: 123672474 examples [2:16:00, 40736.29 examples/s]
Generating train split: 123677375 examples [2:16:00, 25792.82 examples/s]
Generating train split: 123681209 examples [2:16:01, 26294.84 examples/s]
Generating train split: 123684749 examples [2:16:01, 25565.08 examples/s]
Generating train split: 123687924 examples [2:16:01, 22239.97 examples/s]
Generating train split: 123690613 examples [2:16:01, 20043.57 examples/s]
Generating train split: 123692948 examples [2:16:01, 20317.45 examples/s]
Generating train split: 123695234 examples [2:16:01, 16547.19 examples/s]
Generating train split: 123697906 examples [2:16:02, 18509.50 examples/s]
Generating train split: 123700560 examples [2:16:02, 20243.85 examples/s]
Generating train split: 123702858 examples [2:16:02, 20096.30 examples/s]
Generating train split: 123705069 examples [2:16:02, 17961.28 examples/s]
Generating train split: 123707034 examples [2:16:02, 16994.05 examples/s]
Generating train split: 123708845 examples [2:16:02, 14642.47 examples/s]
Generating train split: 123710425 examples [2:16:02, 14300.75 examples/s]
Generating train split: 123712895 examples [2:16:02, 16688.20 examples/s]
Generating train split: 123714986 examples [2:16:03, 17641.80 examples/s]
Generating train split: 123717375 examples [2:16:03, 19270.20 examples/s]
Generating train split: 123719403 examples [2:16:03, 16991.01 examples/s]
Generating train split: 123721210 examples [2:16:03, 16813.55 examples/s]
Generating train split: 123722970 examples [2:16:03, 16723.25 examples/s]
Generating train split: 123725425 examples [2:16:03, 18784.60 examples/s]
Generating train split: 123727941 examples [2:16:03, 20527.38 examples/s]
Generating train split: 123730063 examples [2:16:03, 17057.19 examples/s]
Generating train split: 123732714 examples [2:16:04, 19399.95 examples/s]
Generating train split: 123734807 examples [2:16:04, 17836.58 examples/s]
Generating train split: 123736708 examples [2:16:04, 14196.30 examples/s]
Generating train split: 123739858 examples [2:16:04, 17974.12 examples/s]
Generating train split: 123741917 examples [2:16:04, 17526.60 examples/s]
Generating train split: 123744133 examples [2:16:04, 18341.94 examples/s]
Generating train split: 123746752 examples [2:16:04, 20320.85 examples/s]
Generating train split: 123749885 examples [2:16:04, 23228.80 examples/s]
Generating train split: 123752346 examples [2:16:05, 16786.03 examples/s]
Generating train split: 123755586 examples [2:16:05, 20195.70 examples/s]
Generating train split: 123757972 examples [2:16:05, 20155.99 examples/s]
Generating train split: 123760248 examples [2:16:05, 18538.15 examples/s]
Generating train split: 123763373 examples [2:16:05, 21436.66 examples/s]
Generating train split: 123765724 examples [2:16:05, 18720.24 examples/s]
Generating train split: 123767786 examples [2:16:05, 16651.62 examples/s]
Generating train split: 123770001 examples [2:16:06, 17893.32 examples/s]
Generating train split: 123771952 examples [2:16:06, 15708.38 examples/s]
Generating train split: 123774911 examples [2:16:06, 18898.65 examples/s]
Generating train split: 123776993 examples [2:16:06, 18901.46 examples/s]
Generating train split: 123779023 examples [2:16:06, 15778.53 examples/s]
Generating train split: 123781583 examples [2:16:06, 18011.01 examples/s]
Generating train split: 123783570 examples [2:16:06, 18383.46 examples/s]
Generating train split: 123785955 examples [2:16:06, 19705.56 examples/s]
Generating train split: 123788041 examples [2:16:07, 18970.49 examples/s]
Generating train split: 123790758 examples [2:16:07, 21164.78 examples/s]
Generating train split: 123793469 examples [2:16:07, 22760.66 examples/s]
Generating train split: 123795825 examples [2:16:07, 18930.10 examples/s]
Generating train split: 123798727 examples [2:16:07, 21435.43 examples/s]
Generating train split: 123801028 examples [2:16:07, 19801.97 examples/s]
Generating train split: 123803135 examples [2:16:07, 14234.48 examples/s]
Generating train split: 123804852 examples [2:16:08, 14488.82 examples/s]
Generating train split: 123806836 examples [2:16:08, 15655.86 examples/s]
Generating train split: 123808596 examples [2:16:08, 15836.07 examples/s]
Generating train split: 123811693 examples [2:16:08, 19619.39 examples/s]
Generating train split: 123813829 examples [2:16:08, 18882.31 examples/s]
Generating train split: 123815846 examples [2:16:08, 13963.44 examples/s]
Generating train split: 123817503 examples [2:16:08, 14162.10 examples/s]
Generating train split: 123820539 examples [2:16:08, 17880.42 examples/s]
Generating train split: 123822714 examples [2:16:09, 18373.20 examples/s]
Generating train split: 123824751 examples [2:16:09, 18882.42 examples/s]
Generating train split: 123827488 examples [2:16:09, 21141.74 examples/s]
Generating train split: 123829722 examples [2:16:09, 19910.07 examples/s]
Generating train split: 123831808 examples [2:16:09, 20084.97 examples/s]
Generating train split: 123835124 examples [2:16:09, 23685.61 examples/s]
Generating train split: 123837583 examples [2:16:09, 23595.27 examples/s]
Generating train split: 123840304 examples [2:16:09, 24609.33 examples/s]
Generating train split: 123842822 examples [2:16:09, 23479.35 examples/s]
Generating train split: 123845788 examples [2:16:10, 25211.85 examples/s]
Generating train split: 123848355 examples [2:16:10, 23418.52 examples/s]
Generating train split: 123850756 examples [2:16:10, 22279.86 examples/s]
Generating train split: 123853936 examples [2:16:10, 24827.32 examples/s]
Generating train split: 123856475 examples [2:16:10, 20890.79 examples/s]
Generating train split: 123858709 examples [2:16:10, 20091.39 examples/s]
Generating train split: 123861056 examples [2:16:10, 20929.10 examples/s]
Generating train split: 123863665 examples [2:16:10, 22293.20 examples/s]
Generating train split: 123865983 examples [2:16:11, 18789.48 examples/s]
Generating train split: 123867998 examples [2:16:11, 18734.56 examples/s]
Generating train split: 123870446 examples [2:16:11, 20156.88 examples/s]
Generating train split: 123872555 examples [2:16:11, 19203.53 examples/s]
Generating train split: 123874553 examples [2:16:11, 18075.91 examples/s]
Generating train split: 123877514 examples [2:16:11, 21038.77 examples/s]
Generating train split: 123879860 examples [2:16:11, 21604.87 examples/s]
Generating train split: 123882093 examples [2:16:11, 17654.94 examples/s]
Generating train split: 123884164 examples [2:16:11, 18390.96 examples/s]
Generating train split: 123886635 examples [2:16:12, 19930.85 examples/s]
Generating train split: 123888744 examples [2:16:12, 15645.93 examples/s]
Generating train split: 123891345 examples [2:16:12, 18004.08 examples/s]
Generating train split: 123893593 examples [2:16:12, 19097.01 examples/s]
Generating train split: 123895696 examples [2:16:12, 16807.74 examples/s]
Generating train split: 123897879 examples [2:16:12, 18003.80 examples/s]
Generating train split: 123899891 examples [2:16:12, 18534.35 examples/s]
Generating train split: 123901888 examples [2:16:12, 18911.39 examples/s]
Generating train split: 123903872 examples [2:16:13, 16712.24 examples/s]
Generating train split: 123906399 examples [2:16:13, 18899.00 examples/s]
Generating train split: 123908461 examples [2:16:13, 19213.29 examples/s]
Generating train split: 123910465 examples [2:16:13, 16490.16 examples/s]
Generating train split: 123912234 examples [2:16:13, 15539.66 examples/s]
Generating train split: 123913875 examples [2:16:13, 12238.32 examples/s]
Generating train split: 123915841 examples [2:16:13, 13807.14 examples/s]
Generating train split: 123918403 examples [2:16:14, 16522.12 examples/s]
Generating train split: 123920243 examples [2:16:14, 15086.47 examples/s]
Generating train split: 123922161 examples [2:16:14, 16024.19 examples/s]
Generating train split: 123925362 examples [2:16:14, 20073.54 examples/s]
Generating train split: 123927525 examples [2:16:14, 19224.98 examples/s]
Generating train split: 123929568 examples [2:16:14, 17155.66 examples/s]
Generating train split: 123935920 examples [2:16:14, 28671.88 examples/s]
Generating train split: 123944747 examples [2:16:14, 44284.69 examples/s]
Generating train split: 123949969 examples [2:16:14, 46041.72 examples/s]
Generating train split: 123954899 examples [2:16:15, 30723.51 examples/s]
Generating train split: 123958865 examples [2:16:15, 27230.81 examples/s]
Generating train split: 123962255 examples [2:16:15, 22377.54 examples/s]
Generating train split: 123965056 examples [2:16:15, 23357.97 examples/s]
Generating train split: 123967852 examples [2:16:15, 21388.49 examples/s]
Generating train split: 123970317 examples [2:16:16, 15215.73 examples/s]
Generating train split: 123972272 examples [2:16:16, 14288.12 examples/s]
Generating train split: 123975006 examples [2:16:16, 16601.02 examples/s]
Generating train split: 123977151 examples [2:16:16, 17541.39 examples/s]
Generating train split: 123979208 examples [2:16:16, 16045.72 examples/s]
Generating train split: 123981424 examples [2:16:16, 17373.80 examples/s]
Generating train split: 123984073 examples [2:16:16, 19541.27 examples/s]
Generating train split: 123986229 examples [2:16:17, 19505.64 examples/s]
Generating train split: 123988516 examples [2:16:17, 20382.89 examples/s]
Generating train split: 123990670 examples [2:16:17, 18981.42 examples/s]
Generating train split: 123992667 examples [2:16:17, 18957.62 examples/s]
Generating train split: 123994627 examples [2:16:17, 17438.42 examples/s]
Generating train split: 123996515 examples [2:16:17, 17219.00 examples/s]
Generating train split: 123999414 examples [2:16:17, 20320.03 examples/s]
Generating train split: 124001529 examples [2:16:17, 19562.02 examples/s]
Generating train split: 124004136 examples [2:16:18, 21328.31 examples/s]
Generating train split: 124006963 examples [2:16:18, 23258.98 examples/s]
Generating train split: 124009350 examples [2:16:18, 20173.81 examples/s]
Generating train split: 124011477 examples [2:16:18, 18856.36 examples/s]
Generating train split: 124015180 examples [2:16:18, 23210.31 examples/s]
Generating train split: 124017628 examples [2:16:18, 18511.56 examples/s]
Generating train split: 124019700 examples [2:16:18, 17351.80 examples/s]
Generating train split: 124022200 examples [2:16:18, 19107.80 examples/s]
Generating train split: 124024273 examples [2:16:19, 16361.78 examples/s]
Generating train split: 124026231 examples [2:16:19, 17082.09 examples/s]
Generating train split: 124029909 examples [2:16:19, 21915.10 examples/s]
Generating train split: 124032303 examples [2:16:19, 18328.43 examples/s]
Generating train split: 124035186 examples [2:16:19, 20770.87 examples/s]
Generating train split: 124037496 examples [2:16:19, 20237.02 examples/s]
Generating train split: 124040862 examples [2:16:19, 23595.02 examples/s]
Generating train split: 124043404 examples [2:16:20, 18591.65 examples/s]
Generating train split: 124046325 examples [2:16:20, 20987.43 examples/s]
Generating train split: 124048699 examples [2:16:20, 17581.38 examples/s]
Generating train split: 124051026 examples [2:16:20, 18804.41 examples/s]
Generating train split: 124053749 examples [2:16:20, 20819.78 examples/s]
Generating train split: 124057473 examples [2:16:20, 24996.61 examples/s]
Generating train split: 124065825 examples [2:16:20, 40606.74 examples/s]
Generating train split: 124072420 examples [2:16:20, 47587.74 examples/s]
Generating train split: 124077487 examples [2:16:21, 35372.92 examples/s]
Generating train split: 124081693 examples [2:16:21, 30868.41 examples/s]
Generating train split: 124085321 examples [2:16:21, 24487.45 examples/s]
Generating train split: 124088308 examples [2:16:21, 19959.93 examples/s]
Generating train split: 124091156 examples [2:16:21, 21445.27 examples/s]
Generating train split: 124093731 examples [2:16:21, 21068.52 examples/s]
Generating train split: 124096131 examples [2:16:22, 18553.92 examples/s]
Generating train split: 124098217 examples [2:16:22, 18625.41 examples/s]
Generating train split: 124100372 examples [2:16:22, 19217.98 examples/s]
Generating train split: 124102433 examples [2:16:22, 14637.42 examples/s]
Generating train split: 124104128 examples [2:16:22, 14939.30 examples/s]
Generating train split: 124105876 examples [2:16:22, 15380.38 examples/s]
Generating train split: 124107749 examples [2:16:22, 16187.84 examples/s]
Generating train split: 124110126 examples [2:16:23, 18129.60 examples/s]
Generating train split: 124113007 examples [2:16:23, 20964.54 examples/s]
Generating train split: 124115228 examples [2:16:23, 19606.66 examples/s]
Generating train split: 124117573 examples [2:16:23, 20317.65 examples/s]
Generating train split: 124119680 examples [2:16:23, 18747.76 examples/s]
Generating train split: 124122444 examples [2:16:23, 21078.46 examples/s]
Generating train split: 124124634 examples [2:16:23, 20818.84 examples/s]
Generating train split: 124126776 examples [2:16:23, 20019.15 examples/s]
Generating train split: 124129182 examples [2:16:23, 21027.10 examples/s]
Generating train split: 124131609 examples [2:16:24, 21918.17 examples/s]
Generating train split: 124133840 examples [2:16:24, 20724.92 examples/s]
Generating train split: 124137278 examples [2:16:24, 24462.51 examples/s]
Generating train split: 124139788 examples [2:16:24, 22140.89 examples/s]
Generating train split: 124142075 examples [2:16:24, 18603.09 examples/s]
Generating train split: 124147574 examples [2:16:24, 27363.00 examples/s]
Generating train split: 124155611 examples [2:16:24, 40919.57 examples/s]
Generating train split: 124160157 examples [2:16:24, 33849.52 examples/s]
Generating train split: 124164064 examples [2:16:25, 30195.37 examples/s]
Generating train split: 124167483 examples [2:16:25, 25606.09 examples/s]
Generating train split: 124170409 examples [2:16:25, 23827.11 examples/s]
Generating train split: 124173039 examples [2:16:25, 19508.31 examples/s]
Generating train split: 124175924 examples [2:16:25, 21298.37 examples/s]
Generating train split: 124178327 examples [2:16:25, 19184.39 examples/s]
Generating train split: 124180455 examples [2:16:26, 18449.62 examples/s]
Generating train split: 124183061 examples [2:16:26, 20140.76 examples/s]
Generating train split: 124185225 examples [2:16:26, 18927.69 examples/s]
Generating train split: 124187229 examples [2:16:26, 18097.28 examples/s]
Generating train split: 124189118 examples [2:16:26, 17162.86 examples/s]
Generating train split: 124195573 examples [2:16:26, 28893.74 examples/s]
Generating train split: 124204708 examples [2:16:26, 45206.53 examples/s]
Generating train split: 124209849 examples [2:16:26, 45953.00 examples/s]
Generating train split: 124214762 examples [2:16:27, 30670.42 examples/s]
Generating train split: 124218707 examples [2:16:27, 30904.11 examples/s]
Generating train split: 124222418 examples [2:16:27, 28160.59 examples/s]
Generating train split: 124225692 examples [2:16:27, 21623.62 examples/s]
Generating train split: 124228721 examples [2:16:27, 23217.65 examples/s]
Generating train split: 124231695 examples [2:16:27, 24539.58 examples/s]
Generating train split: 124234526 examples [2:16:28, 20136.63 examples/s]
Generating train split: 124237946 examples [2:16:28, 23026.89 examples/s]
Generating train split: 124240886 examples [2:16:28, 24464.67 examples/s]
Generating train split: 124243651 examples [2:16:28, 24797.13 examples/s]
Generating train split: 124246359 examples [2:16:28, 19440.63 examples/s]
Generating train split: 124248631 examples [2:16:28, 19545.12 examples/s]
Generating train split: 124250819 examples [2:16:28, 19408.82 examples/s]
Generating train split: 124252916 examples [2:16:29, 18320.54 examples/s]
Generating train split: 124259093 examples [2:16:29, 28888.80 examples/s]
Generating train split: 124267939 examples [2:16:29, 44234.87 examples/s]
Generating train split: 124274076 examples [2:16:29, 47681.38 examples/s]
Generating train split: 124279193 examples [2:16:29, 26763.57 examples/s]
Generating train split: 124283169 examples [2:16:29, 24037.07 examples/s]
Generating train split: 124286499 examples [2:16:30, 20191.77 examples/s]
Generating train split: 124289224 examples [2:16:30, 18428.79 examples/s]
Generating train split: 124291545 examples [2:16:30, 14906.82 examples/s]
Generating train split: 124293428 examples [2:16:30, 13281.71 examples/s]
Generating train split: 124295280 examples [2:16:30, 14111.20 examples/s]
Generating train split: 124296954 examples [2:16:31, 13344.49 examples/s]
Generating train split: 124298463 examples [2:16:31, 12428.66 examples/s]
Generating train split: 124301173 examples [2:16:31, 15389.70 examples/s]
Generating train split: 124302929 examples [2:16:31, 14292.54 examples/s]
Generating train split: 124304512 examples [2:16:31, 14310.18 examples/s]
Generating train split: 124306369 examples [2:16:31, 15171.07 examples/s]
Generating train split: 124309032 examples [2:16:31, 18049.00 examples/s]
Generating train split: 124310960 examples [2:16:32, 15917.85 examples/s]
Generating train split: 124312677 examples [2:16:32, 15805.44 examples/s]
Generating train split: 124319726 examples [2:16:32, 29772.80 examples/s]
Generating train split: 124328013 examples [2:16:32, 43961.62 examples/s]
Generating train split: 124332797 examples [2:16:32, 34540.23 examples/s]
Generating train split: 124336826 examples [2:16:32, 26423.65 examples/s]
Generating train split: 124340131 examples [2:16:32, 23697.61 examples/s]
Generating train split: 124342970 examples [2:16:33, 20357.25 examples/s]
Generating train split: 124345379 examples [2:16:33, 20350.97 examples/s]
Generating train split: 124347676 examples [2:16:33, 16987.75 examples/s]
Generating train split: 124350845 examples [2:16:33, 19808.12 examples/s]
Generating train split: 124353390 examples [2:16:33, 20999.62 examples/s]
Generating train split: 124355771 examples [2:16:33, 19837.72 examples/s]
Generating train split: 124358413 examples [2:16:33, 21383.57 examples/s]
Generating train split: 124360728 examples [2:16:34, 20188.90 examples/s]
Generating train split: 124362878 examples [2:16:34, 16685.18 examples/s]
Generating train split: 124364899 examples [2:16:34, 17465.32 examples/s]
Generating train split: 124367590 examples [2:16:34, 19750.03 examples/s]
Generating train split: 124369722 examples [2:16:34, 18888.81 examples/s]
Generating train split: 124371728 examples [2:16:34, 16528.48 examples/s]
Generating train split: 124373695 examples [2:16:34, 17212.62 examples/s]
Generating train split: 124375635 examples [2:16:34, 17767.54 examples/s]
Generating train split: 124377493 examples [2:16:35, 16865.96 examples/s]
Generating train split: 124379580 examples [2:16:35, 17784.31 examples/s]
Generating train split: 124381418 examples [2:16:35, 15284.76 examples/s]
Generating train split: 124383824 examples [2:16:35, 17315.84 examples/s]
Generating train split: 124385879 examples [2:16:35, 18154.60 examples/s]
Generating train split: 124388375 examples [2:16:35, 19990.60 examples/s]
Generating train split: 124390459 examples [2:16:35, 18936.81 examples/s]
Generating train split: 124394490 examples [2:16:35, 24664.13 examples/s]
Generating train split: 124397062 examples [2:16:36, 22078.41 examples/s]
Generating train split: 124399389 examples [2:16:36, 20490.77 examples/s]
Generating train split: 124401529 examples [2:16:36, 20273.68 examples/s]
Generating train split: 124403628 examples [2:16:36, 17246.61 examples/s]
Generating train split: 124405640 examples [2:16:36, 17904.27 examples/s]
Generating train split: 124407884 examples [2:16:36, 18982.91 examples/s]
Generating train split: 124410257 examples [2:16:36, 20233.87 examples/s]
Generating train split: 124412355 examples [2:16:36, 19900.95 examples/s]
Generating train split: 124414995 examples [2:16:36, 21693.30 examples/s]
Generating train split: 124417219 examples [2:16:37, 19761.65 examples/s]
Generating train split: 124419268 examples [2:16:37, 18490.75 examples/s]
Generating train split: 124421173 examples [2:16:37, 17660.72 examples/s]
Generating train split: 124422987 examples [2:16:37, 15004.26 examples/s]
Generating train split: 124424580 examples [2:16:37, 14552.10 examples/s]
Generating train split: 124426529 examples [2:16:37, 15760.83 examples/s]
Generating train split: 124428185 examples [2:16:37, 15949.20 examples/s]
Generating train split: 124430187 examples [2:16:37, 17043.87 examples/s]
Generating train split: 124431940 examples [2:16:38, 16725.25 examples/s]
Generating train split: 124433913 examples [2:16:38, 17507.95 examples/s]
Generating train split: 124435695 examples [2:16:38, 17243.16 examples/s]
Generating train split: 124438267 examples [2:16:38, 19646.32 examples/s]
Generating train split: 124440267 examples [2:16:38, 16438.65 examples/s]
Generating train split: 124442662 examples [2:16:38, 18291.06 examples/s]
Generating train split: 124445098 examples [2:16:38, 19906.50 examples/s]
Generating train split: 124448354 examples [2:16:38, 23317.60 examples/s]
Generating train split: 124450776 examples [2:16:38, 21905.71 examples/s]
Generating train split: 124453047 examples [2:16:39, 19857.84 examples/s]
Generating train split: 124455119 examples [2:16:39, 19675.40 examples/s]
Generating train split: 124458176 examples [2:16:39, 22573.23 examples/s]
Generating train split: 124460512 examples [2:16:39, 21206.02 examples/s]
Generating train split: 124462701 examples [2:16:39, 19749.01 examples/s]
Generating train split: 124465829 examples [2:16:39, 22633.25 examples/s]
Generating train split: 124468376 examples [2:16:39, 23233.71 examples/s]
Generating train split: 124470761 examples [2:16:39, 21832.78 examples/s]
Generating train split: 124473004 examples [2:16:40, 20701.94 examples/s]
Generating train split: 124475120 examples [2:16:40, 14892.29 examples/s]
Generating train split: 124477055 examples [2:16:40, 15840.61 examples/s]
Generating train split: 124479535 examples [2:16:40, 17917.37 examples/s]
Generating train split: 124481629 examples [2:16:40, 18522.49 examples/s]
Generating train split: 124483641 examples [2:16:40, 17045.77 examples/s]
Generating train split: 124486024 examples [2:16:40, 18333.63 examples/s]
Generating train split: 124488163 examples [2:16:40, 18889.39 examples/s]
Generating train split: 124490137 examples [2:16:41, 15775.27 examples/s]
Generating train split: 124492056 examples [2:16:41, 16571.89 examples/s]
Generating train split: 124494414 examples [2:16:41, 18323.21 examples/s]
Generating train split: 124496353 examples [2:16:41, 18264.96 examples/s]
Generating train split: 124498256 examples [2:16:41, 17355.76 examples/s]
Generating train split: 124500257 examples [2:16:41, 18021.52 examples/s]
Generating train split: 124505983 examples [2:16:41, 28847.92 examples/s]
Generating train split: 124514541 examples [2:16:41, 44887.02 examples/s]
Generating train split: 124519952 examples [2:16:41, 47515.45 examples/s]
Generating train split: 124524845 examples [2:16:42, 38542.39 examples/s]
Generating train split: 124529079 examples [2:16:42, 30808.88 examples/s]
Generating train split: 124532642 examples [2:16:42, 25692.56 examples/s]
Generating train split: 124535648 examples [2:16:42, 23121.62 examples/s]
Generating train split: 124538693 examples [2:16:42, 24239.95 examples/s]
Generating train split: 124541380 examples [2:16:42, 22080.57 examples/s]
Generating train split: 124543786 examples [2:16:43, 22148.91 examples/s]
Generating train split: 124546137 examples [2:16:43, 19422.96 examples/s]
Generating train split: 124548205 examples [2:16:43, 16114.80 examples/s]
Generating train split: 124550324 examples [2:16:43, 16993.33 examples/s]
Generating train split: 124552175 examples [2:16:43, 15610.88 examples/s]
Generating train split: 124560537 examples [2:16:43, 30986.78 examples/s]
Generating train split: 124569827 examples [2:16:43, 46101.29 examples/s]
Generating train split: 124575195 examples [2:16:44, 41349.20 examples/s]
Generating train split: 124579938 examples [2:16:44, 27404.63 examples/s]
Generating train split: 124583691 examples [2:16:44, 27174.82 examples/s]
Generating train split: 124587113 examples [2:16:44, 24202.51 examples/s]
Generating train split: 124594787 examples [2:16:44, 34179.39 examples/s]
Generating train split: 124603677 examples [2:16:44, 45845.81 examples/s]
Generating train split: 124609394 examples [2:16:45, 46414.49 examples/s]
Generating train split: 124614829 examples [2:16:45, 29433.01 examples/s]
Generating train split: 124619080 examples [2:16:45, 26536.28 examples/s]
Generating train split: 124622659 examples [2:16:45, 24673.46 examples/s]
Generating train split: 124625762 examples [2:16:45, 24415.50 examples/s]
Generating train split: 124628637 examples [2:16:46, 20981.76 examples/s]
Generating train split: 124631076 examples [2:16:46, 20944.02 examples/s]
Generating train split: 124633409 examples [2:16:46, 20800.05 examples/s]
Generating train split: 124635648 examples [2:16:46, 20859.35 examples/s]
Generating train split: 124638657 examples [2:16:46, 23028.37 examples/s]
Generating train split: 124641100 examples [2:16:46, 20855.66 examples/s]
Generating train split: 124643866 examples [2:16:46, 22453.51 examples/s]
Generating train split: 124646241 examples [2:16:46, 22598.41 examples/s]
Generating train split: 124648591 examples [2:16:47, 19735.40 examples/s]
Generating train split: 124650684 examples [2:16:47, 18640.53 examples/s]
Generating train split: 124652665 examples [2:16:47, 18921.29 examples/s]
Generating train split: 124655013 examples [2:16:47, 20081.17 examples/s]
Generating train split: 124657081 examples [2:16:47, 18439.56 examples/s]
Generating train split: 124659231 examples [2:16:47, 19233.55 examples/s]
Generating train split: 124661556 examples [2:16:47, 20305.44 examples/s]
Generating train split: 124663640 examples [2:16:47, 16450.04 examples/s]
Generating train split: 124665806 examples [2:16:48, 17691.87 examples/s]
Generating train split: 124667707 examples [2:16:48, 16972.74 examples/s]
Generating train split: 124669917 examples [2:16:48, 18286.56 examples/s]
Generating train split: 124672461 examples [2:16:48, 20182.54 examples/s]
Generating train split: 124675188 examples [2:16:48, 22115.65 examples/s]
Generating train split: 124677475 examples [2:16:48, 20487.93 examples/s]
Generating train split: 124679601 examples [2:16:48, 18733.23 examples/s]
Generating train split: 124683026 examples [2:16:48, 22746.31 examples/s]
Generating train split: 124686034 examples [2:16:48, 24726.84 examples/s]
Generating train split: 124688616 examples [2:16:49, 24251.29 examples/s]
Generating train split: 124691112 examples [2:16:49, 21635.40 examples/s]
Generating train split: 124693376 examples [2:16:49, 21109.39 examples/s]
Generating train split: 124695550 examples [2:16:49, 21114.48 examples/s]
Generating train split: 124697710 examples [2:16:49, 20679.96 examples/s]
Generating train split: 124700247 examples [2:16:49, 21959.15 examples/s]
Generating train split: 124703217 examples [2:16:49, 24131.33 examples/s]
Generating train split: 124706211 examples [2:16:49, 25775.89 examples/s]
Generating train split: 124709410 examples [2:16:49, 27570.03 examples/s]
Generating train split: 124712204 examples [2:16:50, 23039.95 examples/s]
Generating train split: 124716033 examples [2:16:50, 26966.66 examples/s]
Generating train split: 124720986 examples [2:16:50, 33002.65 examples/s]
Generating train split: 124724467 examples [2:16:50, 30381.32 examples/s]
Generating train split: 124727671 examples [2:16:50, 24256.55 examples/s]
Generating train split: 124730445 examples [2:16:50, 25053.14 examples/s]
Generating train split: 124734097 examples [2:16:50, 27867.76 examples/s]
Generating train split: 124737111 examples [2:16:50, 25911.18 examples/s]
Generating train split: 124739877 examples [2:16:51, 22474.91 examples/s]
Generating train split: 124742536 examples [2:16:51, 23441.31 examples/s]
Generating train split: 124745088 examples [2:16:51, 23804.07 examples/s]
Generating train split: 124747584 examples [2:16:51, 20341.84 examples/s]
Generating train split: 124749822 examples [2:16:51, 20828.69 examples/s]
Generating train split: 124753215 examples [2:16:51, 24175.26 examples/s]
Generating train split: 124756308 examples [2:16:51, 25973.75 examples/s]
Generating train split: 124759728 examples [2:16:51, 28204.91 examples/s]
Generating train split: 124762652 examples [2:16:52, 26822.54 examples/s]
Generating train split: 124765419 examples [2:16:52, 23968.89 examples/s]
Generating train split: 124767921 examples [2:16:52, 24084.00 examples/s]
Generating train split: 124771437 examples [2:16:52, 27015.58 examples/s]
Generating train split: 124774688 examples [2:16:52, 28534.19 examples/s]
Generating train split: 124778506 examples [2:16:52, 31182.08 examples/s]
Generating train split: 124781695 examples [2:16:52, 27562.29 examples/s]
Generating train split: 124785479 examples [2:16:52, 30105.62 examples/s]
Generating train split: 124790605 examples [2:16:52, 35883.28 examples/s]
Generating train split: 124799738 examples [2:16:53, 51442.58 examples/s]
Generating train split: 124807156 examples [2:16:53, 57933.10 examples/s]
Generating train split: 124813125 examples [2:16:53, 36430.85 examples/s]
Generating train split: 124817881 examples [2:16:53, 31870.52 examples/s]
Generating train split: 124821920 examples [2:16:53, 31994.43 examples/s]
Generating train split: 124825728 examples [2:16:53, 30616.18 examples/s]
Generating train split: 124829197 examples [2:16:54, 28699.30 examples/s]
Generating train split: 124832349 examples [2:16:54, 26892.98 examples/s]
Generating train split: 124835579 examples [2:16:54, 28091.50 examples/s]
Generating train split: 124838809 examples [2:16:54, 29105.39 examples/s]
Generating train split: 124841884 examples [2:16:54, 26160.33 examples/s]
Generating train split: 124844888 examples [2:16:54, 27061.60 examples/s]
Generating train split: 124849159 examples [2:16:54, 31074.30 examples/s]
Generating train split: 124853505 examples [2:16:54, 34401.71 examples/s]
Generating train split: 124857085 examples [2:16:55, 31610.53 examples/s]
Generating train split: 124860381 examples [2:16:55, 28365.00 examples/s]
Generating train split: 124863363 examples [2:16:55, 27320.76 examples/s]
Generating train split: 124866191 examples [2:16:55, 27172.13 examples/s]
Generating train split: 124869214 examples [2:16:55, 27961.64 examples/s]
Generating train split: 124872067 examples [2:16:55, 22379.36 examples/s]
Generating train split: 124875509 examples [2:16:55, 25204.14 examples/s]
Generating train split: 124878243 examples [2:16:55, 24793.35 examples/s]
Generating train split: 124880869 examples [2:16:56, 24092.50 examples/s]
Generating train split: 124884428 examples [2:16:56, 27082.81 examples/s]
Generating train split: 124887261 examples [2:16:56, 26406.62 examples/s]
Generating train split: 124890721 examples [2:16:56, 28634.23 examples/s]
Generating train split: 124893670 examples [2:16:56, 22399.50 examples/s]
Generating train split: 124897245 examples [2:16:56, 25417.18 examples/s]
Generating train split: 124900046 examples [2:16:56, 24918.27 examples/s]
Generating train split: 124902714 examples [2:16:56, 22589.66 examples/s]
Generating train split: 124906954 examples [2:16:57, 27417.87 examples/s]
Generating train split: 124910634 examples [2:16:57, 29845.39 examples/s]
Generating train split: 124913809 examples [2:16:57, 21424.96 examples/s]
Generating train split: 124916581 examples [2:16:57, 22769.44 examples/s]
Generating train split: 124919351 examples [2:16:57, 23890.54 examples/s]
Generating train split: 124922034 examples [2:16:57, 22803.75 examples/s]
Generating train split: 124925460 examples [2:16:57, 25631.48 examples/s]
Generating train split: 124928655 examples [2:16:57, 27278.71 examples/s]
Generating train split: 124931558 examples [2:16:58, 25094.02 examples/s]
Generating train split: 124934229 examples [2:16:58, 25410.41 examples/s]
Generating train split: 124937933 examples [2:16:58, 28541.55 examples/s]
Generating train split: 124942518 examples [2:16:58, 33293.99 examples/s]
Generating train split: 124945967 examples [2:16:58, 28900.53 examples/s]
Generating train split: 124950470 examples [2:16:58, 32758.21 examples/s]
Generating train split: 124955353 examples [2:16:58, 37057.08 examples/s]
Generating train split: 124959455 examples [2:16:58, 38020.71 examples/s]
Generating train split: 124963385 examples [2:16:58, 34382.09 examples/s]
Generating train split: 124967441 examples [2:16:59, 35898.30 examples/s]
Generating train split: 124971155 examples [2:16:59, 30305.30 examples/s]
Generating train split: 124974403 examples [2:16:59, 27402.14 examples/s]
Generating train split: 124977324 examples [2:16:59, 25985.94 examples/s]
Generating train split: 124980047 examples [2:16:59, 26169.92 examples/s]
Generating train split: 124982932 examples [2:16:59, 26849.83 examples/s]
Generating train split: 124985702 examples [2:16:59, 24522.19 examples/s]
Generating train split: 124988502 examples [2:16:59, 25377.00 examples/s]
Generating train split: 124991198 examples [2:17:00, 25757.95 examples/s]
Generating train split: 124993828 examples [2:17:00, 19958.55 examples/s]
Generating train split: 124997100 examples [2:17:00, 22932.97 examples/s]
Generating train split: 125000425 examples [2:17:00, 25502.63 examples/s]
Generating train split: 125003198 examples [2:17:00, 21965.88 examples/s]
Generating train split: 125006057 examples [2:17:00, 23552.24 examples/s]
Generating train split: 125010702 examples [2:17:00, 29396.09 examples/s]
Generating train split: 125015711 examples [2:17:00, 34915.76 examples/s]
Generating train split: 125020599 examples [2:17:01, 38769.05 examples/s]
Generating train split: 125027207 examples [2:17:01, 46480.01 examples/s]
Generating train split: 125034274 examples [2:17:01, 53437.14 examples/s]
Generating train split: 125042109 examples [2:17:01, 60677.00 examples/s]
Generating train split: 125049104 examples [2:17:01, 63383.39 examples/s]
Generating train split: 125055795 examples [2:17:01, 64414.50 examples/s]
Generating train split: 125062311 examples [2:17:01, 63908.34 examples/s]
Generating train split: 125069334 examples [2:17:01, 65744.57 examples/s]
Generating train split: 125076458 examples [2:17:01, 67367.17 examples/s]
Generating train split: 125083441 examples [2:17:01, 68083.92 examples/s]
Generating train split: 125091330 examples [2:17:02, 71298.09 examples/s]
Generating train split: 125098482 examples [2:17:02, 70477.94 examples/s]
Generating train split: 125106399 examples [2:17:02, 73045.78 examples/s]
Generating train split: 125113720 examples [2:17:02, 72743.76 examples/s]
Generating train split: 125121076 examples [2:17:02, 72981.66 examples/s]
Generating train split: 125128390 examples [2:17:02, 72857.14 examples/s]
Generating train split: 125135690 examples [2:17:02, 63995.15 examples/s]
Generating train split: 125142299 examples [2:17:02, 62563.57 examples/s]
Generating train split: 125148910 examples [2:17:02, 63529.47 examples/s]
Generating train split: 125156355 examples [2:17:02, 66594.65 examples/s]
Generating train split: 125163108 examples [2:17:03, 66704.61 examples/s]
Generating train split: 125169857 examples [2:17:03, 66069.37 examples/s]
Generating train split: 125176582 examples [2:17:03, 66352.90 examples/s]
Generating train split: 125183258 examples [2:17:03, 59192.30 examples/s]
Generating train split: 125189347 examples [2:17:03, 58616.35 examples/s]
Generating train split: 125195318 examples [2:17:03, 57467.41 examples/s]
Generating train split: 125201146 examples [2:17:03, 55382.64 examples/s]
Generating train split: 125206744 examples [2:17:03, 53496.15 examples/s]
Generating train split: 125212141 examples [2:17:04, 50001.92 examples/s]
Generating train split: 125217408 examples [2:17:04, 50691.57 examples/s]
Generating train split: 125222524 examples [2:17:04, 42767.67 examples/s]
Generating train split: 125227032 examples [2:17:04, 37889.71 examples/s]
Generating train split: 125231037 examples [2:17:04, 37063.24 examples/s]
Generating train split: 125234890 examples [2:17:04, 32576.83 examples/s]
Generating train split: 125238308 examples [2:17:04, 31509.79 examples/s]
Generating train split: 125242233 examples [2:17:04, 33382.74 examples/s]
Generating train split: 125245694 examples [2:17:05, 30532.03 examples/s]
Generating train split: 125248852 examples [2:17:05, 28311.77 examples/s]
Generating train split: 125251768 examples [2:17:05, 28502.80 examples/s]
Generating train split: 125254687 examples [2:17:05, 28056.70 examples/s]
Generating train split: 125257800 examples [2:17:05, 28841.90 examples/s]
Generating train split: 125260722 examples [2:17:05, 25906.22 examples/s]
Generating train split: 125263793 examples [2:17:05, 27154.91 examples/s]
Generating train split: 125266586 examples [2:17:05, 25221.17 examples/s]
Generating train split: 125269175 examples [2:17:06, 23010.76 examples/s]
Generating train split: 125271546 examples [2:17:06, 22431.52 examples/s]
Generating train split: 125273844 examples [2:17:06, 20721.00 examples/s]
Generating train split: 125276610 examples [2:17:06, 22479.62 examples/s]
Generating train split: 125280058 examples [2:17:06, 25668.84 examples/s]
Generating train split: 125283400 examples [2:17:06, 27737.29 examples/s]
Generating train split: 125286258 examples [2:17:06, 25432.94 examples/s]
Generating train split: 125288891 examples [2:17:06, 22773.12 examples/s]
Generating train split: 125291756 examples [2:17:06, 23732.36 examples/s]
Generating train split: 125294214 examples [2:17:07, 23680.60 examples/s]
Generating train split: 125296645 examples [2:17:07, 21408.98 examples/s]
Generating train split: 125299242 examples [2:17:07, 22576.39 examples/s]
Generating train split: 125301569 examples [2:17:07, 19880.21 examples/s]
Generating train split: 125303659 examples [2:17:07, 19722.24 examples/s]
Generating train split: 125306404 examples [2:17:07, 21722.83 examples/s]
Generating train split: 125308659 examples [2:17:07, 21710.80 examples/s]
Generating train split: 125310885 examples [2:17:07, 19327.72 examples/s]
Generating train split: 125312905 examples [2:17:08, 19141.43 examples/s]
Generating train split: 125314915 examples [2:17:08, 19207.08 examples/s]
Generating train split: 125316873 examples [2:17:08, 17604.35 examples/s]
Generating train split: 125319840 examples [2:17:08, 20752.70 examples/s]
Generating train split: 125323090 examples [2:17:08, 23941.34 examples/s]
Generating train split: 125325570 examples [2:17:08, 18497.54 examples/s]
Generating train split: 125328142 examples [2:17:08, 20170.34 examples/s]
Generating train split: 125330385 examples [2:17:08, 19321.48 examples/s]
Generating train split: 125333469 examples [2:17:09, 22155.16 examples/s]
Generating train split: 125335851 examples [2:17:09, 19182.91 examples/s]
Generating train split: 125337941 examples [2:17:09, 19016.93 examples/s]
Generating train split: 125340412 examples [2:17:09, 20439.72 examples/s]
Generating train split: 125348242 examples [2:17:09, 35700.28 examples/s]
Generating train split: 125356740 examples [2:17:09, 49177.26 examples/s]
Generating train split: 125362681 examples [2:17:09, 49945.65 examples/s]
Generating train split: 125367913 examples [2:17:10, 29434.42 examples/s]
Generating train split: 125372006 examples [2:17:10, 28737.85 examples/s]
Generating train split: 125375680 examples [2:17:10, 21937.98 examples/s]
Generating train split: 125378627 examples [2:17:10, 19410.52 examples/s]
Generating train split: 125381623 examples [2:17:10, 21174.67 examples/s]
Generating train split: 125384249 examples [2:17:10, 21389.50 examples/s]
Generating train split: 125386754 examples [2:17:11, 19113.11 examples/s]
Generating train split: 125388938 examples [2:17:11, 19213.59 examples/s]
Generating train split: 125391056 examples [2:17:11, 17904.03 examples/s]
Generating train split: 125392987 examples [2:17:11, 17176.70 examples/s]
Generating train split: 125394790 examples [2:17:11, 17105.19 examples/s]
Generating train split: 125396567 examples [2:17:11, 17115.01 examples/s]
Generating train split: 125398876 examples [2:17:11, 18620.13 examples/s]
Generating train split: 125400798 examples [2:17:11, 16192.46 examples/s]
Generating train split: 125402502 examples [2:17:12, 15955.26 examples/s]
Generating train split: 125405168 examples [2:17:12, 18698.61 examples/s]
Generating train split: 125407126 examples [2:17:12, 18821.44 examples/s]
Generating train split: 125409073 examples [2:17:12, 15219.17 examples/s]
Generating train split: 125411624 examples [2:17:12, 17689.54 examples/s]
Generating train split: 125413921 examples [2:17:12, 19030.23 examples/s]
Generating train split: 125415969 examples [2:17:12, 17103.84 examples/s]
Generating train split: 125417814 examples [2:17:13, 12215.81 examples/s]
Generating train split: 125419663 examples [2:17:13, 13472.54 examples/s]
Generating train split: 125421399 examples [2:17:13, 14334.45 examples/s]
Generating train split: 125423353 examples [2:17:13, 15555.11 examples/s]
Generating train split: 125425086 examples [2:17:13, 13189.39 examples/s]
Generating train split: 125426584 examples [2:17:13, 13324.54 examples/s]
Generating train split: 125428046 examples [2:17:13, 13627.56 examples/s]
Generating train split: 125429505 examples [2:17:13, 13005.31 examples/s]
Generating train split: 125430875 examples [2:17:14, 12398.85 examples/s]
Generating train split: 125434811 examples [2:17:14, 19320.42 examples/s]
Generating train split: 125442276 examples [2:17:14, 34171.96 examples/s]
Generating train split: 125449619 examples [2:17:14, 45031.13 examples/s]
Generating train split: 125454409 examples [2:17:14, 32447.51 examples/s]
Generating train split: 125458346 examples [2:17:14, 22065.14 examples/s]
Generating train split: 125461447 examples [2:17:15, 19023.46 examples/s]
Generating train split: 125464011 examples [2:17:15, 17277.47 examples/s]
Generating train split: 125466195 examples [2:17:15, 17035.56 examples/s]
Generating train split: 125469489 examples [2:17:15, 19959.63 examples/s]
Generating train split: 125471879 examples [2:17:15, 19341.42 examples/s]
Generating train split: 125474087 examples [2:17:15, 18024.46 examples/s]
Generating train split: 125476425 examples [2:17:15, 19142.51 examples/s]
Generating train split: 125478515 examples [2:17:16, 18974.92 examples/s]
Generating train split: 125480531 examples [2:17:16, 17332.62 examples/s]
Generating train split: 125482363 examples [2:17:16, 16507.79 examples/s]
Generating train split: 125485088 examples [2:17:16, 19134.17 examples/s]
Generating train split: 125487108 examples [2:17:16, 18556.32 examples/s]
Generating train split: 125490221 examples [2:17:16, 21841.10 examples/s]
Generating train split: 125492509 examples [2:17:16, 18876.27 examples/s]
Generating train split: 125494535 examples [2:17:17, 17032.42 examples/s]
Generating train split: 125497361 examples [2:17:17, 19693.96 examples/s]
Generating train split: 125499484 examples [2:17:17, 19196.73 examples/s]
Generating train split: 125501506 examples [2:17:17, 17147.02 examples/s]
Generating train split: 125503968 examples [2:17:17, 18967.41 examples/s]
Generating train split: 125505976 examples [2:17:17, 17471.18 examples/s]
Generating train split: 125507813 examples [2:17:17, 15227.64 examples/s]
Generating train split: 125509664 examples [2:17:17, 15998.69 examples/s]
Generating train split: 125511904 examples [2:17:17, 17602.86 examples/s]
Generating train split: 125513757 examples [2:17:18, 16672.14 examples/s]
Generating train split: 125515497 examples [2:17:18, 15717.43 examples/s]
Generating train split: 125517131 examples [2:17:18, 13229.02 examples/s]
Generating train split: 125519086 examples [2:17:18, 14678.93 examples/s]
Generating train split: 125521071 examples [2:17:18, 15882.34 examples/s]
Generating train split: 125523642 examples [2:17:18, 18456.59 examples/s]
Generating train split: 125526528 examples [2:17:18, 21284.39 examples/s]
Generating train split: 125529867 examples [2:17:18, 24672.96 examples/s]
Generating train split: 125532430 examples [2:17:19, 21163.79 examples/s]
Generating train split: 125535175 examples [2:17:19, 22767.68 examples/s]
Generating train split: 125537583 examples [2:17:19, 22412.38 examples/s]
Generating train split: 125539924 examples [2:17:19, 21791.25 examples/s]
Generating train split: 125542177 examples [2:17:19, 21121.21 examples/s]
Generating train split: 125544336 examples [2:17:19, 18961.47 examples/s]
Generating train split: 125546301 examples [2:17:19, 17382.74 examples/s]
Generating train split: 125548104 examples [2:17:19, 17227.89 examples/s]
Generating train split: 125549873 examples [2:17:20, 16499.41 examples/s]
Generating train split: 125556514 examples [2:17:20, 29510.23 examples/s]
Generating train split: 125564148 examples [2:17:20, 42206.03 examples/s]
Generating train split: 125568669 examples [2:17:20, 42250.14 examples/s]
Generating train split: 125573092 examples [2:17:20, 31744.94 examples/s]
Generating train split: 125576784 examples [2:17:20, 32619.50 examples/s]
Generating train split: 125580433 examples [2:17:20, 28993.71 examples/s]
Generating train split: 125583655 examples [2:17:20, 26902.66 examples/s]
Generating train split: 125586573 examples [2:17:21, 25124.13 examples/s]
Generating train split: 125589242 examples [2:17:21, 22307.13 examples/s]
Generating train split: 125591617 examples [2:17:21, 21878.18 examples/s]
Generating train split: 125593895 examples [2:17:21, 20749.97 examples/s]
Generating train split: 125596032 examples [2:17:21, 18699.37 examples/s]
Generating train split: 125597958 examples [2:17:21, 18526.15 examples/s]
Generating train split: 125599847 examples [2:17:21, 18060.53 examples/s]
Generating train split: 125601682 examples [2:17:22, 17469.60 examples/s]
Generating train split: 125603538 examples [2:17:22, 17727.17 examples/s]
Generating train split: 125605707 examples [2:17:22, 18775.99 examples/s]
Generating train split: 125607610 examples [2:17:22, 18801.16 examples/s]
Generating train split: 125609925 examples [2:17:22, 20024.37 examples/s]
Generating train split: 125611952 examples [2:17:22, 19580.02 examples/s]
Generating train split: 125614504 examples [2:17:22, 21274.62 examples/s]
Generating train split: 125616657 examples [2:17:22, 18860.64 examples/s]
Generating train split: 125618602 examples [2:17:22, 18314.16 examples/s]
Generating train split: 125620632 examples [2:17:22, 18838.69 examples/s]
Generating train split: 125622754 examples [2:17:23, 19476.26 examples/s]
Generating train split: 125624737 examples [2:17:23, 18017.76 examples/s]
Generating train split: 125627730 examples [2:17:23, 21057.11 examples/s]
Generating train split: 125630836 examples [2:17:23, 23826.38 examples/s]
Generating train split: 125633278 examples [2:17:23, 17267.14 examples/s]
Generating train split: 125635956 examples [2:17:23, 19395.70 examples/s]
Generating train split: 125638952 examples [2:17:23, 21965.23 examples/s]
Generating train split: 125641984 examples [2:17:23, 24114.59 examples/s]
Generating train split: 125644945 examples [2:17:24, 25569.75 examples/s]
Generating train split: 125647667 examples [2:17:24, 23847.37 examples/s]
Generating train split: 125654569 examples [2:17:24, 35883.69 examples/s]
Generating train split: 125663123 examples [2:17:24, 49568.31 examples/s]
Generating train split: 125670029 examples [2:17:24, 55025.26 examples/s]
Generating train split: 125675769 examples [2:17:24, 36250.02 examples/s]
Generating train split: 125680392 examples [2:17:24, 31843.00 examples/s]
Generating train split: 125684331 examples [2:17:25, 29545.78 examples/s]
Generating train split: 125687813 examples [2:17:25, 24341.80 examples/s]
Generating train split: 125690714 examples [2:17:25, 24171.46 examples/s]
Generating train split: 125693449 examples [2:17:25, 23171.03 examples/s]
Generating train split: 125695978 examples [2:17:25, 23330.01 examples/s]
Generating train split: 125698461 examples [2:17:25, 22353.41 examples/s]
Generating train split: 125701076 examples [2:17:25, 23246.92 examples/s]
Generating train split: 125703495 examples [2:17:26, 20869.99 examples/s]
Generating train split: 125705681 examples [2:17:26, 20312.84 examples/s]
Generating train split: 125707775 examples [2:17:26, 19637.44 examples/s]
Generating train split: 125709787 examples [2:17:26, 19475.74 examples/s]
Generating train split: 125711757 examples [2:17:26, 19458.67 examples/s]
Generating train split: 125713726 examples [2:17:26, 17276.68 examples/s]
Generating train split: 125715750 examples [2:17:26, 18014.96 examples/s]
Generating train split: 125717655 examples [2:17:26, 18231.72 examples/s]
Generating train split: 125721070 examples [2:17:26, 22624.33 examples/s]
Generating train split: 125729113 examples [2:17:27, 38973.06 examples/s]
Generating train split: 125736809 examples [2:17:27, 49879.94 examples/s]
Generating train split: 125741946 examples [2:17:27, 30206.29 examples/s]
Generating train split: 125746006 examples [2:17:27, 25805.88 examples/s]
Generating train split: 125749392 examples [2:17:27, 23624.00 examples/s]
Generating train split: 125752312 examples [2:17:28, 21962.08 examples/s]
Generating train split: 125754896 examples [2:17:28, 18722.12 examples/s]
Generating train split: 125758820 examples [2:17:28, 22490.15 examples/s]
Generating train split: 125761514 examples [2:17:28, 19821.98 examples/s]
Generating train split: 125763832 examples [2:17:28, 17467.21 examples/s]
Generating train split: 125765833 examples [2:17:28, 17931.11 examples/s]
Generating train split: 125767837 examples [2:17:29, 15093.84 examples/s]
Generating train split: 125770143 examples [2:17:29, 16660.76 examples/s]
Generating train split: 125772022 examples [2:17:29, 13938.62 examples/s]
Generating train split: 125773612 examples [2:17:29, 14135.62 examples/s]
Generating train split: 125776660 examples [2:17:29, 17823.35 examples/s]
Generating train split: 125778663 examples [2:17:29, 17610.30 examples/s]
Generating train split: 125780578 examples [2:17:29, 16353.60 examples/s]
Generating train split: 125782355 examples [2:17:29, 16698.12 examples/s]
Generating train split: 125785020 examples [2:17:30, 19195.57 examples/s]
Generating train split: 125787267 examples [2:17:30, 20067.38 examples/s]
Generating train split: 125789351 examples [2:17:30, 16649.99 examples/s]
Generating train split: 125791355 examples [2:17:30, 17471.03 examples/s]
Generating train split: 125793244 examples [2:17:30, 17826.63 examples/s]
Generating train split: 125795124 examples [2:17:30, 17944.71 examples/s]
Generating train split: 125797629 examples [2:17:30, 19898.30 examples/s]
Generating train split: 125799688 examples [2:17:30, 19286.33 examples/s]
Generating train split: 125801672 examples [2:17:30, 18874.88 examples/s]
Generating train split: 125804297 examples [2:17:31, 20871.20 examples/s]
Generating train split: 125807174 examples [2:17:31, 23059.36 examples/s]
Generating train split: 125809520 examples [2:17:31, 17129.95 examples/s]
Generating train split: 125812224 examples [2:17:31, 19431.03 examples/s]
Generating train split: 125814408 examples [2:17:31, 18352.10 examples/s]
Generating train split: 125816421 examples [2:17:31, 17253.73 examples/s]
Generating train split: 125819114 examples [2:17:31, 19616.03 examples/s]
Generating train split: 125821345 examples [2:17:31, 20311.98 examples/s]
Generating train split: 125823806 examples [2:17:32, 21465.52 examples/s]
Generating train split: 125826044 examples [2:17:32, 18682.93 examples/s]
Generating train split: 125828517 examples [2:17:32, 20218.63 examples/s]
Generating train split: 125830652 examples [2:17:32, 20503.71 examples/s]
Generating train split: 125832847 examples [2:17:32, 20890.72 examples/s]
Generating train split: 125835826 examples [2:17:32, 23321.72 examples/s]
Generating train split: 125838227 examples [2:17:32, 20100.86 examples/s]
Generating train split: 125840365 examples [2:17:32, 18516.91 examples/s]
Generating train split: 125842314 examples [2:17:33, 17520.83 examples/s]
Generating train split: 125844144 examples [2:17:33, 15987.67 examples/s]
Generating train split: 125846532 examples [2:17:33, 17916.58 examples/s]
Generating train split: 125848419 examples [2:17:33, 15448.22 examples/s]
Generating train split: 125850070 examples [2:17:33, 15610.38 examples/s]
Generating train split: 125852527 examples [2:17:33, 17851.20 examples/s]
Generating train split: 125855044 examples [2:17:33, 19596.63 examples/s]
Generating train split: 125857455 examples [2:17:33, 20804.30 examples/s]
Generating train split: 125859613 examples [2:17:33, 19426.10 examples/s]
Generating train split: 125861713 examples [2:17:34, 19847.00 examples/s]
Generating train split: 125863754 examples [2:17:34, 17144.26 examples/s]
Generating train split: 125865561 examples [2:17:34, 15655.92 examples/s]
Generating train split: 125867658 examples [2:17:34, 16906.04 examples/s]
Generating train split: 125869438 examples [2:17:34, 16758.84 examples/s]
Generating train split: 125872555 examples [2:17:34, 20440.25 examples/s]
Generating train split: 125874682 examples [2:17:34, 19220.73 examples/s]
Generating train split: 125876667 examples [2:17:34, 19084.40 examples/s]
Generating train split: 125879063 examples [2:17:35, 20400.94 examples/s]
Generating train split: 125881162 examples [2:17:35, 18559.59 examples/s]
Generating train split: 125883079 examples [2:17:35, 18001.59 examples/s]
Generating train split: 125885477 examples [2:17:35, 19591.04 examples/s]
Generating train split: 125887755 examples [2:17:35, 20423.73 examples/s]
Generating train split: 125889847 examples [2:17:35, 19916.25 examples/s]
Generating train split: 125893252 examples [2:17:35, 23873.07 examples/s]
Generating train split: 125895692 examples [2:17:35, 20456.04 examples/s]
Generating train split: 125897855 examples [2:17:35, 19982.31 examples/s]
Generating train split: 125899935 examples [2:17:36, 17456.33 examples/s]
Generating train split: 125901784 examples [2:17:36, 17274.72 examples/s]
Generating train split: 125903581 examples [2:17:36, 14638.88 examples/s]
Generating train split: 125905315 examples [2:17:36, 15269.08 examples/s]
Generating train split: 125907249 examples [2:17:36, 16264.05 examples/s]
Generating train split: 125909147 examples [2:17:36, 16872.62 examples/s]
Generating train split: 125911032 examples [2:17:36, 17404.62 examples/s]
Generating train split: 125912826 examples [2:17:36, 15880.44 examples/s]
Generating train split: 125914477 examples [2:17:37, 15858.73 examples/s]
Generating train split: 125917217 examples [2:17:37, 18991.82 examples/s]
Generating train split: 125919242 examples [2:17:37, 19308.14 examples/s]
Generating train split: 125921937 examples [2:17:37, 21482.59 examples/s]
Generating train split: 125924128 examples [2:17:37, 20980.88 examples/s]
Generating train split: 125926858 examples [2:17:37, 22786.25 examples/s]
Generating train split: 125929169 examples [2:17:37, 17272.72 examples/s]
Generating train split: 125931116 examples [2:17:37, 17365.46 examples/s]
Generating train split: 125933016 examples [2:17:38, 17084.67 examples/s]
Generating train split: 125934831 examples [2:17:38, 15755.35 examples/s]
Generating train split: 125936492 examples [2:17:38, 14205.73 examples/s]
Generating train split: 125938875 examples [2:17:38, 16499.87 examples/s]
Generating train split: 125940638 examples [2:17:38, 13561.12 examples/s]
Generating train split: 125942377 examples [2:17:38, 14430.71 examples/s]
Generating train split: 125943954 examples [2:17:38, 14232.70 examples/s]
Generating train split: 125945622 examples [2:17:38, 14842.35 examples/s]
Generating train split: 125947271 examples [2:17:39, 15275.00 examples/s]
Generating train split: 125948956 examples [2:17:39, 15705.88 examples/s]
Generating train split: 125951296 examples [2:17:39, 17861.72 examples/s]
Generating train split: 125953132 examples [2:17:39, 17119.92 examples/s]
Generating train split: 125955141 examples [2:17:39, 17951.33 examples/s]
Generating train split: 125957118 examples [2:17:39, 18467.14 examples/s]
Generating train split: 125958999 examples [2:17:39, 18480.40 examples/s]
Generating train split: 125960867 examples [2:17:39, 18375.82 examples/s]
Generating train split: 125963181 examples [2:17:39, 19458.95 examples/s]
Generating train split: 125965456 examples [2:17:39, 20353.83 examples/s]
Generating train split: 125967505 examples [2:17:40, 20008.22 examples/s]
Generating train split: 125969515 examples [2:17:40, 18964.06 examples/s]
Generating train split: 125971786 examples [2:17:40, 19949.54 examples/s]
Generating train split: 125974343 examples [2:17:40, 21536.17 examples/s]
Generating train split: 125976525 examples [2:17:40, 17286.51 examples/s]
Generating train split: 125979288 examples [2:17:40, 19858.36 examples/s]
Generating train split: 125982742 examples [2:17:40, 23707.45 examples/s]
Generating train split: 125985281 examples [2:17:40, 19876.79 examples/s]
Generating train split: 125987480 examples [2:17:41, 19916.69 examples/s]
Generating train split: 125990152 examples [2:17:41, 21002.06 examples/s]
Generating train split: 125992379 examples [2:17:41, 17900.20 examples/s]
Generating train split: 125995921 examples [2:17:41, 22029.87 examples/s]
Generating train split: 125998333 examples [2:17:41, 19666.10 examples/s]
Generating train split: 126000485 examples [2:17:41, 19109.35 examples/s]
Generating train split: 126003845 examples [2:17:41, 22651.24 examples/s]
Generating train split: 126006286 examples [2:17:41, 21163.78 examples/s]
Generating train split: 126008531 examples [2:17:42, 20885.82 examples/s]
Generating train split: 126011668 examples [2:17:42, 23600.79 examples/s]
Generating train split: 126014135 examples [2:17:42, 23636.83 examples/s]
Generating train split: 126016575 examples [2:17:42, 21617.19 examples/s]
Generating train split: 126018814 examples [2:17:42, 21165.61 examples/s]
Generating train split: 126021652 examples [2:17:42, 23077.63 examples/s]
Generating train split: 126024022 examples [2:17:42, 23150.94 examples/s]
Generating train split: 126026381 examples [2:17:42, 23155.52 examples/s]
Generating train split: 126029196 examples [2:17:42, 24530.13 examples/s]
Generating train split: 126031686 examples [2:17:43, 21723.93 examples/s]
Generating train split: 126033944 examples [2:17:43, 21032.79 examples/s]
Generating train split: 126036462 examples [2:17:43, 22116.34 examples/s]
Generating train split: 126040330 examples [2:17:43, 26687.23 examples/s]
Generating train split: 126043078 examples [2:17:43, 21546.24 examples/s]
Generating train split: 126045962 examples [2:17:43, 23285.41 examples/s]
Generating train split: 126049226 examples [2:17:43, 25680.53 examples/s]
Generating train split: 126051966 examples [2:17:43, 25799.67 examples/s]
Generating train split: 126054677 examples [2:17:44, 25177.81 examples/s]
Generating train split: 126057280 examples [2:17:44, 22617.07 examples/s]
Generating train split: 126060589 examples [2:17:44, 25323.02 examples/s]
Generating train split: 126063232 examples [2:17:44, 23267.45 examples/s]
Generating train split: 126065666 examples [2:17:44, 21207.96 examples/s]
Generating train split: 126067885 examples [2:17:44, 20640.73 examples/s]
Generating train split: 126070206 examples [2:17:44, 21265.13 examples/s]
Generating train split: 126072754 examples [2:17:44, 22385.41 examples/s]
Generating train split: 126075044 examples [2:17:44, 22234.54 examples/s]
Generating train split: 126077307 examples [2:17:45, 21988.47 examples/s]
Generating train split: 126080718 examples [2:17:45, 25382.59 examples/s]
Generating train split: 126083304 examples [2:17:45, 22962.66 examples/s]
Generating train split: 126085665 examples [2:17:45, 21231.72 examples/s]
Generating train split: 126088001 examples [2:17:45, 21776.91 examples/s]
Generating train split: 126090241 examples [2:17:45, 20073.05 examples/s]
Generating train split: 126092312 examples [2:17:45, 18922.04 examples/s]
Generating train split: 126094251 examples [2:17:45, 19021.27 examples/s]
Generating train split: 126096196 examples [2:17:46, 16137.77 examples/s]
Generating train split: 126097895 examples [2:17:46, 16120.47 examples/s]
Generating train split: 126099763 examples [2:17:46, 16775.42 examples/s]
Generating train split: 126104423 examples [2:17:46, 24780.66 examples/s]
Generating train split: 126111866 examples [2:17:46, 38535.47 examples/s]
Generating train split: 126118412 examples [2:17:46, 46151.18 examples/s]
Generating train split: 126123218 examples [2:17:46, 36653.10 examples/s]
Generating train split: 126127321 examples [2:17:46, 34177.96 examples/s]
Generating train split: 126131059 examples [2:17:47, 26570.91 examples/s]
Generating train split: 126134170 examples [2:17:47, 24080.98 examples/s]
Generating train split: 126136893 examples [2:17:47, 23276.43 examples/s]
Generating train split: 126139426 examples [2:17:47, 21255.40 examples/s]
Generating train split: 126142056 examples [2:17:47, 22284.01 examples/s]
Generating train split: 126144428 examples [2:17:47, 21602.79 examples/s]
Generating train split: 126146678 examples [2:17:47, 18854.11 examples/s]
Generating train split: 126148663 examples [2:17:48, 16556.36 examples/s]
Generating train split: 126150607 examples [2:17:48, 17188.35 examples/s]
Generating train split: 126153940 examples [2:17:48, 21078.52 examples/s]
Generating train split: 126156214 examples [2:17:48, 21228.00 examples/s]
Generating train split: 126158461 examples [2:17:48, 19320.78 examples/s]
Generating train split: 126160706 examples [2:17:48, 20057.20 examples/s]
Generating train split: 126164269 examples [2:17:48, 24188.54 examples/s]
Generating train split: 126166802 examples [2:17:48, 23436.00 examples/s]
Generating train split: 126169590 examples [2:17:49, 24579.27 examples/s]
Generating train split: 126174060 examples [2:17:49, 30201.35 examples/s]
Generating train split: 126183460 examples [2:17:49, 48411.35 examples/s]
Generating train split: 126189356 examples [2:17:49, 51337.28 examples/s]
Generating train split: 126194604 examples [2:17:49, 39635.69 examples/s]
Generating train split: 126199056 examples [2:17:49, 33210.93 examples/s]
Generating train split: 126202861 examples [2:17:49, 28412.30 examples/s]
Generating train split: 126206113 examples [2:17:50, 28620.45 examples/s]
Generating train split: 126211295 examples [2:17:50, 33816.43 examples/s]
Generating train split: 126219245 examples [2:17:50, 44888.39 examples/s]
Generating train split: 126226382 examples [2:17:50, 51700.23 examples/s]
Generating train split: 126232044 examples [2:17:50, 36931.73 examples/s]
Generating train split: 126236662 examples [2:17:50, 34743.40 examples/s]
Generating train split: 126240783 examples [2:17:50, 29568.52 examples/s]
Generating train split: 126244266 examples [2:17:51, 28202.50 examples/s]
Generating train split: 126247438 examples [2:17:51, 24664.43 examples/s]
Generating train split: 126250182 examples [2:17:51, 22251.02 examples/s]
Generating train split: 126253285 examples [2:17:51, 24000.65 examples/s]
Generating train split: 126255901 examples [2:17:51, 23360.42 examples/s]
Generating train split: 126258383 examples [2:17:51, 21413.45 examples/s]
Generating train split: 126261540 examples [2:17:51, 23742.45 examples/s]
Generating train split: 126264054 examples [2:17:52, 20896.68 examples/s]
Generating train split: 126266287 examples [2:17:52, 19874.24 examples/s]
Generating train split: 126268436 examples [2:17:52, 20234.26 examples/s]
Generating train split: 126270544 examples [2:17:52, 15709.90 examples/s]
Generating train split: 126273266 examples [2:17:52, 18176.31 examples/s]
Generating train split: 126275745 examples [2:17:52, 19730.82 examples/s]
Generating train split: 126277916 examples [2:17:52, 18891.11 examples/s]
Generating train split: 126280797 examples [2:17:52, 21390.45 examples/s]
Generating train split: 126283918 examples [2:17:53, 23969.15 examples/s]
Generating train split: 126286568 examples [2:17:53, 24211.69 examples/s]
Generating train split: 126289100 examples [2:17:53, 20109.64 examples/s]
Generating train split: 126291298 examples [2:17:53, 20540.26 examples/s]
Generating train split: 126293484 examples [2:17:53, 17151.99 examples/s]
Generating train split: 126296603 examples [2:17:53, 20423.54 examples/s]
Generating train split: 126299084 examples [2:17:53, 21506.47 examples/s]
Generating train split: 126302397 examples [2:17:53, 24535.17 examples/s]
Generating train split: 126305020 examples [2:17:54, 23935.33 examples/s]
Generating train split: 126312647 examples [2:17:54, 38158.68 examples/s]
Generating train split: 126322179 examples [2:17:54, 54133.59 examples/s]
Generating train split: 126327872 examples [2:17:54, 44673.49 examples/s]
Generating train split: 126332807 examples [2:17:54, 37527.00 examples/s]
Generating train split: 126337041 examples [2:17:54, 36231.43 examples/s]
Generating train split: 126341000 examples [2:17:54, 30146.81 examples/s]
Generating train split: 126344373 examples [2:17:55, 29456.69 examples/s]
Generating train split: 126347549 examples [2:17:55, 26953.98 examples/s]
Generating train split: 126350418 examples [2:17:55, 21997.34 examples/s]
Generating train split: 126352835 examples [2:17:55, 21948.90 examples/s]
Generating train split: 126356547 examples [2:17:55, 25290.57 examples/s]
Generating train split: 126359295 examples [2:17:55, 23351.32 examples/s]
Generating train split: 126361806 examples [2:17:55, 22034.42 examples/s]
Generating train split: 126364127 examples [2:17:55, 21943.20 examples/s]
Generating train split: 126366399 examples [2:17:56, 21754.61 examples/s]
Generating train split: 126368625 examples [2:17:56, 21135.01 examples/s]
Generating train split: 126371031 examples [2:17:56, 21885.36 examples/s]
Generating train split: 126373255 examples [2:17:56, 20673.02 examples/s]
Generating train split: 126376099 examples [2:17:56, 22749.65 examples/s]
Generating train split: 126378424 examples [2:17:56, 21318.05 examples/s]
Generating train split: 126380599 examples [2:17:56, 21414.69 examples/s]
Generating train split: 126382780 examples [2:17:56, 21497.81 examples/s]
Generating train split: 126384956 examples [2:17:57, 19055.00 examples/s]
Generating train split: 126386932 examples [2:17:57, 18359.35 examples/s]
Generating train split: 126389679 examples [2:17:57, 20743.49 examples/s]
Generating train split: 126392098 examples [2:17:57, 21668.80 examples/s]
Generating train split: 126394338 examples [2:17:57, 21849.86 examples/s]
Generating train split: 126396564 examples [2:17:57, 18027.67 examples/s]
Generating train split: 126398533 examples [2:17:57, 18420.09 examples/s]
Generating train split: 126400476 examples [2:17:57, 17564.38 examples/s]
Generating train split: 126402310 examples [2:17:57, 15880.18 examples/s]
Generating train split: 126404146 examples [2:17:58, 16487.40 examples/s]
Generating train split: 126406190 examples [2:17:58, 17515.53 examples/s]
Generating train split: 126408009 examples [2:17:58, 17223.04 examples/s]
Generating train split: 126410273 examples [2:17:58, 18708.88 examples/s]
Generating train split: 126412188 examples [2:17:58, 17178.66 examples/s]
Generating train split: 126414653 examples [2:17:58, 19184.09 examples/s]
Generating train split: 126416957 examples [2:17:58, 20221.68 examples/s]
Generating train split: 126419031 examples [2:17:58, 15742.79 examples/s]
Generating train split: 126420930 examples [2:17:59, 16508.61 examples/s]
Generating train split: 126422741 examples [2:17:59, 16466.78 examples/s]
Generating train split: 126425106 examples [2:17:59, 18331.11 examples/s]
Generating train split: 126427048 examples [2:17:59, 16360.63 examples/s]
Generating train split: 126430052 examples [2:17:59, 19806.31 examples/s]
Generating train split: 126432295 examples [2:17:59, 20446.54 examples/s]
Generating train split: 126434452 examples [2:17:59, 18009.13 examples/s]
Generating train split: 126436691 examples [2:17:59, 18969.85 examples/s]
Generating train split: 126438962 examples [2:17:59, 19907.13 examples/s]
Generating train split: 126441039 examples [2:18:00, 18161.23 examples/s]
Generating train split: 126443622 examples [2:18:00, 20025.79 examples/s]
Generating train split: 126445934 examples [2:18:00, 20852.96 examples/s]
Generating train split: 126448219 examples [2:18:00, 21391.73 examples/s]
Generating train split: 126450414 examples [2:18:00, 20242.19 examples/s]
Generating train split: 126452488 examples [2:18:00, 19725.67 examples/s]
Generating train split: 126454999 examples [2:18:00, 21200.25 examples/s]
Generating train split: 126457706 examples [2:18:00, 22576.23 examples/s]
Generating train split: 126460008 examples [2:18:01, 18492.13 examples/s]
Generating train split: 126463231 examples [2:18:01, 21914.85 examples/s]
Generating train split: 126471691 examples [2:18:01, 38359.51 examples/s]
Generating train split: 126479556 examples [2:18:01, 48855.78 examples/s]
Generating train split: 126484761 examples [2:18:01, 35055.80 examples/s]
Generating train split: 126489034 examples [2:18:01, 29825.22 examples/s]
Generating train split: 126492647 examples [2:18:01, 30353.99 examples/s]
Generating train split: 126496141 examples [2:18:02, 28865.30 examples/s]
Generating train split: 126499339 examples [2:18:02, 21528.97 examples/s]
Generating train split: 126501950 examples [2:18:02, 21971.82 examples/s]
Generating train split: 126504946 examples [2:18:02, 23629.67 examples/s]
Generating train split: 126507622 examples [2:18:02, 22161.89 examples/s]
Generating train split: 126510421 examples [2:18:02, 23473.58 examples/s]
Generating train split: 126512965 examples [2:18:02, 20450.35 examples/s]
Generating train split: 126515197 examples [2:18:03, 20202.97 examples/s]
Generating train split: 126517639 examples [2:18:03, 21224.67 examples/s]
Generating train split: 126519885 examples [2:18:03, 19772.80 examples/s]
Generating train split: 126523380 examples [2:18:03, 23591.47 examples/s]
Generating train split: 126525884 examples [2:18:03, 22191.18 examples/s]
Generating train split: 126528294 examples [2:18:03, 22615.86 examples/s]
Generating train split: 126530908 examples [2:18:03, 23396.24 examples/s]
Generating train split: 126534167 examples [2:18:03, 25928.88 examples/s]
Generating train split: 126536827 examples [2:18:03, 23514.91 examples/s]
Generating train split: 126539478 examples [2:18:04, 24290.16 examples/s]
Generating train split: 126542361 examples [2:18:04, 25522.97 examples/s]
Generating train split: 126544974 examples [2:18:04, 21255.38 examples/s]
Generating train split: 126547254 examples [2:18:04, 21363.26 examples/s]
Generating train split: 126550012 examples [2:18:04, 22960.47 examples/s]
Generating train split: 126552407 examples [2:18:04, 21355.78 examples/s]
Generating train split: 126554942 examples [2:18:04, 22327.92 examples/s]
Generating train split: 126557546 examples [2:18:04, 23333.21 examples/s]
Generating train split: 126560135 examples [2:18:04, 23843.37 examples/s]
Generating train split: 126562730 examples [2:18:05, 24438.07 examples/s]
Generating train split: 126565223 examples [2:18:05, 24134.88 examples/s]
Generating train split: 126567953 examples [2:18:05, 25032.68 examples/s]
Generating train split: 126570485 examples [2:18:05, 21238.56 examples/s]
Generating train split: 126572724 examples [2:18:05, 20094.15 examples/s]
Generating train split: 126575048 examples [2:18:05, 20903.93 examples/s]
Generating train split: 126577787 examples [2:18:05, 22494.22 examples/s]
Generating train split: 126580388 examples [2:18:05, 23450.63 examples/s]
Generating train split: 126582791 examples [2:18:06, 17860.98 examples/s]
Generating train split: 126585409 examples [2:18:06, 19778.59 examples/s]
Generating train split: 126587647 examples [2:18:06, 20294.85 examples/s]
Generating train split: 126589835 examples [2:18:06, 19281.20 examples/s]
Generating train split: 126591880 examples [2:18:06, 19461.99 examples/s]
Generating train split: 126594086 examples [2:18:06, 20157.01 examples/s]
Generating train split: 126597007 examples [2:18:06, 22524.50 examples/s]
Generating train split: 126599330 examples [2:18:06, 22383.78 examples/s]
Generating train split: 126601756 examples [2:18:06, 22912.57 examples/s]
Generating train split: 126604845 examples [2:18:07, 25157.88 examples/s]
Generating train split: 126607398 examples [2:18:07, 25196.59 examples/s]
Generating train split: 126609940 examples [2:18:07, 18934.64 examples/s]
Generating train split: 126612088 examples [2:18:07, 17748.32 examples/s]
Generating train split: 126614049 examples [2:18:07, 17565.24 examples/s]
Generating train split: 126616416 examples [2:18:07, 19054.89 examples/s]
Generating train split: 126619061 examples [2:18:07, 20957.54 examples/s]
Generating train split: 126621268 examples [2:18:07, 20626.94 examples/s]
Generating train split: 126623409 examples [2:18:08, 18154.63 examples/s]
Generating train split: 126626050 examples [2:18:08, 20232.94 examples/s]
Generating train split: 126628450 examples [2:18:08, 21122.91 examples/s]
Generating train split: 126630649 examples [2:18:08, 20053.24 examples/s]
Generating train split: 126632729 examples [2:18:08, 19787.15 examples/s]
Generating train split: 126635719 examples [2:18:08, 22543.38 examples/s]
Generating train split: 126638200 examples [2:18:08, 23138.82 examples/s]
Generating train split: 126641141 examples [2:18:08, 24919.23 examples/s]
Generating train split: 126643683 examples [2:18:08, 24344.82 examples/s]
Generating train split: 126646452 examples [2:18:08, 25255.90 examples/s]
Generating train split: 126649010 examples [2:18:09, 24300.40 examples/s]
Generating train split: 126651572 examples [2:18:09, 24626.14 examples/s]
Generating train split: 126654061 examples [2:18:09, 22926.55 examples/s]
Generating train split: 126660855 examples [2:18:09, 35373.71 examples/s]
Generating train split: 126669135 examples [2:18:09, 48790.71 examples/s]
Generating train split: 126674187 examples [2:18:09, 38090.41 examples/s]
Generating train split: 126678470 examples [2:18:09, 31789.89 examples/s]
Generating train split: 126682124 examples [2:18:10, 29723.81 examples/s]
Generating train split: 126685431 examples [2:18:10, 27229.08 examples/s]
Generating train split: 126688385 examples [2:18:10, 25478.03 examples/s]
Generating train split: 126691086 examples [2:18:10, 22493.97 examples/s]
Generating train split: 126695150 examples [2:18:10, 26393.51 examples/s]
Generating train split: 126698024 examples [2:18:10, 25361.50 examples/s]
Generating train split: 126700722 examples [2:18:10, 24737.82 examples/s]
Generating train split: 126703308 examples [2:18:11, 23580.55 examples/s]
Generating train split: 126705741 examples [2:18:11, 22623.61 examples/s]
Generating train split: 126708051 examples [2:18:11, 20553.93 examples/s]
Generating train split: 126710409 examples [2:18:11, 21291.40 examples/s]
Generating train split: 126712588 examples [2:18:11, 19454.54 examples/s]
Generating train split: 126714591 examples [2:18:11, 18328.88 examples/s]
Generating train split: 126717430 examples [2:18:11, 20732.73 examples/s]
Generating train split: 126719995 examples [2:18:11, 21964.48 examples/s]
Generating train split: 126722261 examples [2:18:11, 21815.99 examples/s]
Generating train split: 126724490 examples [2:18:12, 21146.24 examples/s]
Generating train split: 126727901 examples [2:18:12, 24728.46 examples/s]
Generating train split: 126731217 examples [2:18:12, 27077.62 examples/s]
Generating train split: 126734631 examples [2:18:12, 28810.46 examples/s]
Generating train split: 126737561 examples [2:18:12, 24521.24 examples/s]
Generating train split: 126740397 examples [2:18:12, 25487.77 examples/s]
Generating train split: 126743163 examples [2:18:12, 26021.56 examples/s]
Generating train split: 126745849 examples [2:18:12, 22564.41 examples/s]
Generating train split: 126749858 examples [2:18:12, 27022.39 examples/s]
Generating train split: 126758226 examples [2:18:13, 42113.09 examples/s]
Generating train split: 126765515 examples [2:18:13, 50592.92 examples/s]
Generating train split: 126770870 examples [2:18:13, 43929.06 examples/s]
Generating train split: 126775620 examples [2:18:13, 35806.59 examples/s]
Generating train split: 126779667 examples [2:18:13, 31517.38 examples/s]
Generating train split: 126783191 examples [2:18:13, 30761.10 examples/s]
Generating train split: 126786519 examples [2:18:14, 27279.86 examples/s]
Generating train split: 126789666 examples [2:18:14, 28201.70 examples/s]
Generating train split: 126792665 examples [2:18:14, 27266.75 examples/s]
Generating train split: 126795516 examples [2:18:14, 24618.56 examples/s]
Generating train split: 126798088 examples [2:18:14, 23234.17 examples/s]
Generating train split: 126800644 examples [2:18:14, 23787.31 examples/s]
Generating train split: 126803696 examples [2:18:14, 25509.68 examples/s]
Generating train split: 126806319 examples [2:18:14, 22970.61 examples/s]
Generating train split: 126809205 examples [2:18:14, 24433.98 examples/s]
Generating train split: 126811737 examples [2:18:15, 24632.99 examples/s]
Generating train split: 126815790 examples [2:18:15, 28994.90 examples/s]
Generating train split: 126819005 examples [2:18:15, 29879.10 examples/s]
Generating train split: 126822055 examples [2:18:15, 26038.40 examples/s]
Generating train split: 126825296 examples [2:18:15, 27699.75 examples/s]
Generating train split: 126828186 examples [2:18:15, 26455.79 examples/s]
Generating train split: 126830917 examples [2:18:15, 25853.13 examples/s]
Generating train split: 126833570 examples [2:18:15, 24182.50 examples/s]
Generating train split: 126836909 examples [2:18:15, 26573.53 examples/s]
Generating train split: 126839641 examples [2:18:16, 26339.15 examples/s]
Generating train split: 126842872 examples [2:18:16, 27990.02 examples/s]
Generating train split: 126845720 examples [2:18:16, 27443.98 examples/s]
Generating train split: 126849181 examples [2:18:16, 29451.10 examples/s]
Generating train split: 126852164 examples [2:18:16, 26856.48 examples/s]
Generating train split: 126855611 examples [2:18:16, 28925.55 examples/s]
Generating train split: 126859221 examples [2:18:16, 29943.38 examples/s]
Generating train split: 126862266 examples [2:18:16, 29646.65 examples/s]
Generating train split: 126865269 examples [2:18:16, 29105.70 examples/s]
Generating train split: 126868207 examples [2:18:17, 27301.64 examples/s]
Generating train split: 126871302 examples [2:18:17, 28287.78 examples/s]
Generating train split: 126874170 examples [2:18:17, 25383.14 examples/s]
Generating train split: 126876826 examples [2:18:17, 25685.63 examples/s]
Generating train split: 126879447 examples [2:18:17, 25627.80 examples/s]
Generating train split: 126882057 examples [2:18:17, 24075.89 examples/s]
Generating train split: 126886162 examples [2:18:17, 28669.24 examples/s]
Generating train split: 126890117 examples [2:18:17, 31702.25 examples/s]
Generating train split: 126893900 examples [2:18:17, 32828.87 examples/s]
Generating train split: 126897236 examples [2:18:18, 28616.87 examples/s]
Generating train split: 126900232 examples [2:18:18, 27780.17 examples/s]
Generating train split: 126903104 examples [2:18:18, 22661.67 examples/s]
Generating train split: 126905565 examples [2:18:18, 19898.62 examples/s]
Generating train split: 126907903 examples [2:18:18, 20668.72 examples/s]
Generating train split: 126910116 examples [2:18:18, 19431.18 examples/s]
Generating train split: 126912787 examples [2:18:18, 21172.94 examples/s]
Generating train split: 126915016 examples [2:18:19, 19967.09 examples/s]
Generating train split: 126917098 examples [2:18:19, 18478.05 examples/s]
Generating train split: 126919462 examples [2:18:19, 19723.02 examples/s]
Generating train split: 126921507 examples [2:18:19, 19051.40 examples/s]
Generating train split: 126923471 examples [2:18:19, 18763.04 examples/s]
Generating train split: 126925382 examples [2:18:19, 18831.33 examples/s]
Generating train split: 126931031 examples [2:18:19, 29280.86 examples/s]
Generating train split: 126939491 examples [2:18:19, 44973.42 examples/s]
Generating train split: 126946035 examples [2:18:19, 50336.03 examples/s]
Generating train split: 126951195 examples [2:18:20, 37544.47 examples/s]
Generating train split: 126955506 examples [2:18:20, 29467.53 examples/s]
Generating train split: 126959071 examples [2:18:20, 28774.01 examples/s]
Generating train split: 126962371 examples [2:18:20, 25105.52 examples/s]
Generating train split: 126965213 examples [2:18:20, 25217.59 examples/s]
Generating train split: 126967982 examples [2:18:20, 22368.99 examples/s]
Generating train split: 126970409 examples [2:18:21, 20095.52 examples/s]
Generating train split: 126972557 examples [2:18:21, 20137.40 examples/s]
Generating train split: 126974987 examples [2:18:21, 20965.47 examples/s]
Generating train split: 126977175 examples [2:18:21, 18921.70 examples/s]
Generating train split: 126979439 examples [2:18:21, 19783.51 examples/s]
Generating train split: 126982140 examples [2:18:21, 21618.16 examples/s]
Generating train split: 126985062 examples [2:18:21, 23645.75 examples/s]
Generating train split: 126987517 examples [2:18:21, 23169.46 examples/s]
Generating train split: 126990228 examples [2:18:21, 24253.47 examples/s]
Generating train split: 126993563 examples [2:18:22, 26820.57 examples/s]
Generating train split: 127001926 examples [2:18:22, 43175.17 examples/s]
Generating train split: 127010235 examples [2:18:22, 54807.98 examples/s]
Generating train split: 127015823 examples [2:18:22, 37923.63 examples/s]
Generating train split: 127020409 examples [2:18:22, 31455.78 examples/s]
Generating train split: 127024245 examples [2:18:22, 26966.67 examples/s]
Generating train split: 127027493 examples [2:18:23, 24302.75 examples/s]
Generating train split: 127030381 examples [2:18:23, 25093.74 examples/s]
Generating train split: 127033201 examples [2:18:23, 22802.37 examples/s]
Generating train split: 127035707 examples [2:18:23, 21619.62 examples/s]
Generating train split: 127038011 examples [2:18:23, 19771.43 examples/s]
Generating train split: 127041020 examples [2:18:23, 22027.42 examples/s]
Generating train split: 127043377 examples [2:18:23, 22367.64 examples/s]
Generating train split: 127045726 examples [2:18:24, 21131.37 examples/s]
Generating train split: 127047925 examples [2:18:24, 20421.25 examples/s]
Generating train split: 127053526 examples [2:18:24, 29573.09 examples/s]
Generating train split: 127062481 examples [2:18:24, 45680.38 examples/s]
Generating train split: 127067874 examples [2:18:24, 47937.56 examples/s]
Generating train split: 127072920 examples [2:18:24, 41782.90 examples/s]
Generating train split: 127077403 examples [2:18:24, 32981.59 examples/s]
Generating train split: 127081180 examples [2:18:24, 32756.13 examples/s]
Generating train split: 127084784 examples [2:18:25, 28584.78 examples/s]
Generating train split: 127088117 examples [2:18:25, 29628.42 examples/s]
Generating train split: 127091322 examples [2:18:25, 29162.89 examples/s]
Generating train split: 127094401 examples [2:18:25, 23189.50 examples/s]
Generating train split: 127097002 examples [2:18:25, 23682.45 examples/s]
Generating train split: 127099587 examples [2:18:25, 23328.97 examples/s]
Generating train split: 127102750 examples [2:18:25, 25367.71 examples/s]
Generating train split: 127105437 examples [2:18:25, 24486.19 examples/s]
Generating train split: 127108503 examples [2:18:26, 26073.32 examples/s]
Generating train split: 127111218 examples [2:18:26, 22937.85 examples/s]
Generating train split: 127114395 examples [2:18:26, 25155.09 examples/s]
Generating train split: 127117038 examples [2:18:26, 24621.06 examples/s]
Generating train split: 127119606 examples [2:18:26, 23939.51 examples/s]
Generating train split: 127122118 examples [2:18:26, 24253.54 examples/s]
Generating train split: 127125275 examples [2:18:26, 26273.79 examples/s]
Generating train split: 127133549 examples [2:18:26, 42292.57 examples/s]
Generating train split: 127141375 examples [2:18:26, 52641.27 examples/s]
Generating train split: 127146772 examples [2:18:27, 38334.29 examples/s]
Generating train split: 127151252 examples [2:18:27, 29624.07 examples/s]
Generating train split: 127154937 examples [2:18:27, 25064.55 examples/s]
Generating train split: 127158008 examples [2:18:27, 25301.35 examples/s]
Generating train split: 127160947 examples [2:18:27, 23090.81 examples/s]
Generating train split: 127163540 examples [2:18:28, 20828.53 examples/s]
Generating train split: 127165822 examples [2:18:28, 19701.02 examples/s]
Generating train split: 127167917 examples [2:18:28, 11312.65 examples/s]
Generating train split: 127169519 examples [2:18:29, 5916.37 examples/s] 
Generating train split: 127170701 examples [2:18:30, 4672.92 examples/s]
Generating train split: 127171599 examples [2:18:30, 4571.95 examples/s]
Generating train split: 127172470 examples [2:18:30, 4995.06 examples/s]
Generating train split: 127173258 examples [2:18:30, 5146.10 examples/s]
Generating train split: 127173990 examples [2:18:30, 5132.38 examples/s]
Generating train split: 127175675 examples [2:18:30, 7081.42 examples/s]
Generating train split: 127177009 examples [2:18:30, 8190.85 examples/s]
Generating train split: 127178975 examples [2:18:30, 10636.13 examples/s]
Generating train split: 127180539 examples [2:18:31, 11795.09 examples/s]
Generating train split: 127181941 examples [2:18:31, 12081.15 examples/s]
Generating train split: 127183310 examples [2:18:31, 11761.49 examples/s]
Generating train split: 127185419 examples [2:18:31, 14149.27 examples/s]
Generating train split: 127189975 examples [2:18:31, 22598.97 examples/s]
Generating train split: 127197373 examples [2:18:31, 36860.00 examples/s]
Generating train split: 127204117 examples [2:18:31, 45515.37 examples/s]
Generating train split: 127208888 examples [2:18:32, 26188.07 examples/s]
Generating train split: 127212619 examples [2:18:32, 23764.18 examples/s]
Generating train split: 127215796 examples [2:18:32, 21807.18 examples/s]
Generating train split: 127218537 examples [2:18:32, 20984.77 examples/s]
Generating train split: 127221010 examples [2:18:32, 21405.87 examples/s]
Generating train split: 127223429 examples [2:18:32, 17855.52 examples/s]
Generating train split: 127225929 examples [2:18:32, 19268.05 examples/s]
Generating train split: 127228273 examples [2:18:33, 19952.60 examples/s]
Generating train split: 127230628 examples [2:18:33, 20804.21 examples/s]
Generating train split: 127233521 examples [2:18:33, 22854.71 examples/s]
Generating train split: 127235954 examples [2:18:33, 21243.27 examples/s]
Generating train split: 127238198 examples [2:18:33, 20417.86 examples/s]
Generating train split: 127241477 examples [2:18:33, 23619.98 examples/s]
Generating train split: 127243956 examples [2:18:33, 19587.52 examples/s]
Generating train split: 127246366 examples [2:18:33, 20660.91 examples/s]
Generating train split: 127249572 examples [2:18:34, 23522.74 examples/s]
Generating train split: 127252082 examples [2:18:34, 18745.72 examples/s]
Generating train split: 127255192 examples [2:18:34, 21576.50 examples/s]
Generating train split: 127257616 examples [2:18:34, 20527.81 examples/s]
Generating train split: 127259862 examples [2:18:34, 20121.88 examples/s]
Generating train split: 127262214 examples [2:18:34, 20970.98 examples/s]
Generating train split: 127265000 examples [2:18:34, 22792.03 examples/s]
Generating train split: 127268533 examples [2:18:34, 26169.90 examples/s]
Generating train split: 127271256 examples [2:18:35, 20334.48 examples/s]
Generating train split: 127275475 examples [2:18:35, 25476.77 examples/s]
Generating train split: 127278628 examples [2:18:35, 26989.57 examples/s]
Generating train split: 127281585 examples [2:18:35, 22437.63 examples/s]
Generating train split: 127284548 examples [2:18:35, 24072.45 examples/s]
Generating train split: 127287209 examples [2:18:35, 22483.21 examples/s]
Generating train split: 127289756 examples [2:18:35, 23209.93 examples/s]
Generating train split: 127292327 examples [2:18:35, 23840.05 examples/s]
Generating train split: 127295523 examples [2:18:36, 26027.42 examples/s]
Generating train split: 127298230 examples [2:18:36, 20172.52 examples/s]
Generating train split: 127300518 examples [2:18:36, 20653.48 examples/s]
Generating train split: 127302858 examples [2:18:36, 21181.81 examples/s]
Generating train split: 127305130 examples [2:18:36, 19715.91 examples/s]
Generating train split: 127307216 examples [2:18:36, 19938.92 examples/s]
Generating train split: 127309904 examples [2:18:36, 21733.82 examples/s]
Generating train split: 127312158 examples [2:18:36, 19424.88 examples/s]
Generating train split: 127314440 examples [2:18:37, 20283.52 examples/s]
Generating train split: 127317918 examples [2:18:37, 24175.29 examples/s]
Generating train split: 127320446 examples [2:18:37, 22812.82 examples/s]
Generating train split: 127323103 examples [2:18:37, 23756.36 examples/s]
Generating train split: 127325737 examples [2:18:37, 24238.38 examples/s]
Generating train split: 127328228 examples [2:18:37, 20156.03 examples/s]
Generating train split: 127330388 examples [2:18:37, 18414.25 examples/s]
Generating train split: 127332344 examples [2:18:37, 17588.25 examples/s]
Generating train split: 127334245 examples [2:18:37, 17926.96 examples/s]
Generating train split: 127336377 examples [2:18:38, 18631.61 examples/s]
Generating train split: 127338293 examples [2:18:38, 17909.09 examples/s]
Generating train split: 127340679 examples [2:18:38, 19371.03 examples/s]
Generating train split: 127343153 examples [2:18:38, 20845.16 examples/s]
Generating train split: 127345287 examples [2:18:38, 18630.76 examples/s]
Generating train split: 127347696 examples [2:18:38, 20027.37 examples/s]
Generating train split: 127351268 examples [2:18:38, 24293.28 examples/s]
Generating train split: 127354358 examples [2:18:38, 26128.04 examples/s]
Generating train split: 127357044 examples [2:18:39, 22051.24 examples/s]
Generating train split: 127359405 examples [2:18:39, 20992.67 examples/s]
Generating train split: 127361656 examples [2:18:39, 21376.03 examples/s]
Generating train split: 127363893 examples [2:18:39, 20744.27 examples/s]
Generating train split: 127366228 examples [2:18:39, 21440.39 examples/s]
Generating train split: 127368432 examples [2:18:39, 19748.48 examples/s]
Generating train split: 127370472 examples [2:18:39, 17365.15 examples/s]
Generating train split: 127372912 examples [2:18:39, 19110.83 examples/s]
Generating train split: 127376311 examples [2:18:39, 23000.00 examples/s]
Generating train split: 127379374 examples [2:18:40, 25065.84 examples/s]
Generating train split: 127381990 examples [2:18:40, 22211.97 examples/s]
Generating train split: 127384796 examples [2:18:40, 23726.38 examples/s]
Generating train split: 127390974 examples [2:18:40, 34004.15 examples/s]
Generating train split: 127399416 examples [2:18:40, 48034.72 examples/s]
Generating train split: 127406568 examples [2:18:40, 54717.08 examples/s]
Generating train split: 127412248 examples [2:18:40, 42571.46 examples/s]
Generating train split: 127417065 examples [2:18:41, 35818.26 examples/s]
Generating train split: 127421197 examples [2:18:41, 29986.84 examples/s]
Generating train split: 127424932 examples [2:18:41, 31467.30 examples/s]
Generating train split: 127428487 examples [2:18:41, 29409.83 examples/s]
Generating train split: 127431715 examples [2:18:41, 23561.80 examples/s]
Generating train split: 127435002 examples [2:18:41, 25364.87 examples/s]
Generating train split: 127437860 examples [2:18:41, 25780.96 examples/s]
Generating train split: 127440676 examples [2:18:42, 25159.31 examples/s]
Generating train split: 127444042 examples [2:18:42, 27212.61 examples/s]
Generating train split: 127446919 examples [2:18:42, 22605.68 examples/s]
Generating train split: 127449404 examples [2:18:42, 19720.39 examples/s]
Generating train split: 127451580 examples [2:18:42, 18823.65 examples/s]
Generating train split: 127453621 examples [2:18:42, 19165.40 examples/s]
Generating train split: 127456202 examples [2:18:42, 20727.23 examples/s]
Generating train split: 127459405 examples [2:18:42, 23637.90 examples/s]
Generating train split: 127461902 examples [2:18:43, 23536.17 examples/s]
Generating train split: 127464345 examples [2:18:43, 23571.97 examples/s]
Generating train split: 127466769 examples [2:18:43, 23385.70 examples/s]
Generating train split: 127469247 examples [2:18:43, 23717.05 examples/s]
Generating train split: 127471653 examples [2:18:43, 23565.12 examples/s]
Generating train split: 127474031 examples [2:18:43, 23031.17 examples/s]
Generating train split: 127482725 examples [2:18:43, 41338.44 examples/s]
Generating train split: 127490786 examples [2:18:43, 52598.75 examples/s]
Generating train split: 127496148 examples [2:18:43, 42664.15 examples/s]
Generating train split: 127500789 examples [2:18:44, 34057.48 examples/s]
Generating train split: 127504694 examples [2:18:44, 32943.84 examples/s]
Generating train split: 127508329 examples [2:18:44, 26823.83 examples/s]
Generating train split: 127511384 examples [2:18:44, 25536.66 examples/s]
Generating train split: 127514185 examples [2:18:44, 24243.18 examples/s]
Generating train split: 127516773 examples [2:18:44, 21621.95 examples/s]
Generating train split: 127519062 examples [2:18:45, 21680.59 examples/s]
Generating train split: 127521324 examples [2:18:45, 19668.48 examples/s]
Generating train split: 127524098 examples [2:18:45, 21530.38 examples/s]
Generating train split: 127527016 examples [2:18:45, 23419.73 examples/s]
Generating train split: 127529474 examples [2:18:45, 20638.03 examples/s]
Generating train split: 127531666 examples [2:18:45, 19483.07 examples/s]
Generating train split: 127533711 examples [2:18:45, 19544.69 examples/s]
Generating train split: 127536302 examples [2:18:45, 21182.33 examples/s]
Generating train split: 127539568 examples [2:18:45, 24260.91 examples/s]
Generating train split: 127542077 examples [2:18:46, 22841.85 examples/s]
Generating train split: 127544674 examples [2:18:46, 23678.23 examples/s]
Generating train split: 127547103 examples [2:18:46, 22240.68 examples/s]
Generating train split: 127549874 examples [2:18:46, 23703.00 examples/s]
Generating train split: 127552625 examples [2:18:46, 24607.41 examples/s]
Generating train split: 127555133 examples [2:18:46, 20777.35 examples/s]
Generating train split: 127563827 examples [2:18:46, 37553.71 examples/s]
Generating train split: 127571937 examples [2:18:46, 48720.32 examples/s]
Generating train split: 127577197 examples [2:18:47, 44701.54 examples/s]
Generating train split: 127581997 examples [2:18:47, 32485.22 examples/s]
Generating train split: 127585927 examples [2:18:47, 28294.38 examples/s]
Generating train split: 127589280 examples [2:18:47, 24998.20 examples/s]
Generating train split: 127592164 examples [2:18:47, 24770.56 examples/s]
Generating train split: 127594910 examples [2:18:47, 23494.00 examples/s]
Generating train split: 127597441 examples [2:18:48, 21352.60 examples/s]
Generating train split: 127601284 examples [2:18:48, 25041.03 examples/s]
Generating train split: 127604009 examples [2:18:48, 23069.77 examples/s]
Generating train split: 127606691 examples [2:18:48, 23923.76 examples/s]
Generating train split: 127609227 examples [2:18:48, 23455.86 examples/s]
Generating train split: 127611673 examples [2:18:48, 20268.51 examples/s]
Generating train split: 127614081 examples [2:18:48, 21159.03 examples/s]
Generating train split: 127616718 examples [2:18:48, 22471.34 examples/s]
Generating train split: 127619065 examples [2:18:49, 21910.74 examples/s]
Generating train split: 127621330 examples [2:18:49, 21498.99 examples/s]
Generating train split: 127623622 examples [2:18:49, 21856.14 examples/s]
Generating train split: 127625850 examples [2:18:49, 19746.01 examples/s]
Generating train split: 127629188 examples [2:18:49, 23331.69 examples/s]
Generating train split: 127632123 examples [2:18:49, 24970.91 examples/s]
Generating train split: 127636136 examples [2:18:49, 28764.76 examples/s]
Generating train split: 127639088 examples [2:18:49, 26583.00 examples/s]
Generating train split: 127641827 examples [2:18:49, 26607.29 examples/s]
Generating train split: 127646068 examples [2:18:50, 30980.75 examples/s]
Generating train split: 127652922 examples [2:18:50, 41622.87 examples/s]
Generating train split: 127661502 examples [2:18:50, 54360.23 examples/s]
Generating train split: 127667073 examples [2:18:50, 40301.19 examples/s]
Generating train split: 127671733 examples [2:18:50, 32055.73 examples/s]
Generating train split: 127675596 examples [2:18:50, 30416.38 examples/s]
Generating train split: 127679087 examples [2:18:50, 27592.62 examples/s]
Generating train split: 127682173 examples [2:18:51, 26026.75 examples/s]
Generating train split: 127685784 examples [2:18:51, 28199.66 examples/s]
Generating train split: 127688839 examples [2:18:51, 23102.40 examples/s]
Generating train split: 127691433 examples [2:18:51, 22427.19 examples/s]
Generating train split: 127693894 examples [2:18:51, 22737.46 examples/s]
Generating train split: 127696308 examples [2:18:51, 22121.42 examples/s]
Generating train split: 127698906 examples [2:18:51, 23065.19 examples/s]
Generating train split: 127701787 examples [2:18:51, 24559.80 examples/s]
Generating train split: 127704947 examples [2:18:52, 26467.30 examples/s]
Generating train split: 127707676 examples [2:18:52, 26690.59 examples/s]
Generating train split: 127712312 examples [2:18:52, 32270.26 examples/s]
Generating train split: 127715611 examples [2:18:52, 31686.75 examples/s]
Generating train split: 127718829 examples [2:18:52, 24977.42 examples/s]
Generating train split: 127721716 examples [2:18:52, 25923.92 examples/s]
Generating train split: 127724512 examples [2:18:52, 26113.11 examples/s]
Generating train split: 127727272 examples [2:18:52, 23796.71 examples/s]
Generating train split: 127730107 examples [2:18:53, 24953.14 examples/s]
Generating train split: 127733042 examples [2:18:53, 26114.47 examples/s]
Generating train split: 127735744 examples [2:18:53, 20641.14 examples/s]
Generating train split: 127738043 examples [2:18:53, 20614.98 examples/s]
Generating train split: 127740698 examples [2:18:53, 22068.69 examples/s]
Generating train split: 127743135 examples [2:18:53, 22662.75 examples/s]
Generating train split: 127745513 examples [2:18:53, 22635.13 examples/s]
Generating train split: 127747860 examples [2:18:53, 22456.66 examples/s]
Generating train split: 127750515 examples [2:18:53, 23559.94 examples/s]
Generating train split: 127753747 examples [2:18:54, 26041.51 examples/s]
Generating train split: 127756397 examples [2:18:54, 23219.52 examples/s]
Generating train split: 127759639 examples [2:18:54, 25678.14 examples/s]
Generating train split: 127763109 examples [2:18:54, 28152.27 examples/s]
Generating train split: 127770957 examples [2:18:54, 42409.82 examples/s]
Generating train split: 127780100 examples [2:18:54, 56515.41 examples/s]
Generating train split: 127785908 examples [2:18:54, 37994.30 examples/s]
Generating train split: 127790622 examples [2:18:55, 29377.27 examples/s]
Generating train split: 127794449 examples [2:18:55, 27398.64 examples/s]
Generating train split: 127797806 examples [2:18:55, 24703.75 examples/s]
Generating train split: 127800745 examples [2:18:55, 25586.24 examples/s]
Generating train split: 127803668 examples [2:18:55, 25628.25 examples/s]
Generating train split: 127806477 examples [2:18:55, 24927.91 examples/s]
Generating train split: 127809176 examples [2:18:55, 25409.87 examples/s]
Generating train split: 127812100 examples [2:18:56, 26327.58 examples/s]
Generating train split: 127814841 examples [2:18:56, 23689.41 examples/s]
Generating train split: 127817567 examples [2:18:56, 24557.32 examples/s]
Generating train split: 127820406 examples [2:18:56, 25535.33 examples/s]
Generating train split: 127823045 examples [2:18:56, 24426.33 examples/s]
Generating train split: 127825557 examples [2:18:56, 23804.34 examples/s]
Generating train split: 127827979 examples [2:18:56, 22249.00 examples/s]
Generating train split: 127830393 examples [2:18:56, 22734.04 examples/s]
Generating train split: 127832705 examples [2:18:56, 21527.29 examples/s]
Generating train split: 127834897 examples [2:18:57, 20828.55 examples/s]
Generating train split: 127837004 examples [2:18:57, 19163.97 examples/s]
Generating train split: 127839024 examples [2:18:57, 19390.60 examples/s]
Generating train split: 127840994 examples [2:18:57, 18697.41 examples/s]
Generating train split: 127842965 examples [2:18:57, 18846.03 examples/s]
Generating train split: 127844965 examples [2:18:57, 19064.96 examples/s]
Generating train split: 127847898 examples [2:18:57, 21911.79 examples/s]
Generating train split: 127850151 examples [2:18:57, 22069.12 examples/s]
Generating train split: 127852379 examples [2:18:57, 20636.47 examples/s]
Generating train split: 127854993 examples [2:18:58, 22161.32 examples/s]
Generating train split: 127857248 examples [2:18:58, 19149.91 examples/s]
Generating train split: 127860065 examples [2:18:58, 21424.95 examples/s]
Generating train split: 127862306 examples [2:18:58, 20764.90 examples/s]
Generating train split: 127864461 examples [2:18:58, 18814.20 examples/s]
Generating train split: 127866567 examples [2:18:58, 19385.51 examples/s]
Generating train split: 127869213 examples [2:18:58, 21259.08 examples/s]
Generating train split: 127871414 examples [2:18:58, 20978.95 examples/s]
Generating train split: 127874742 examples [2:18:58, 24391.27 examples/s]
Generating train split: 127877242 examples [2:18:59, 23215.49 examples/s]
Generating train split: 127879646 examples [2:18:59, 23436.01 examples/s]
Generating train split: 127882779 examples [2:18:59, 25669.63 examples/s]
Generating train split: 127885389 examples [2:18:59, 23353.16 examples/s]
Generating train split: 127887787 examples [2:18:59, 19646.56 examples/s]
Generating train split: 127889886 examples [2:18:59, 18628.59 examples/s]
Generating train split: 127891840 examples [2:18:59, 18131.36 examples/s]
Generating train split: 127893878 examples [2:18:59, 18690.71 examples/s]
Generating train split: 127897842 examples [2:19:00, 24233.61 examples/s]
Generating train split: 127901823 examples [2:19:00, 28492.93 examples/s]
Generating train split: 127904791 examples [2:19:00, 27817.58 examples/s]
Generating train split: 127908375 examples [2:19:00, 30053.52 examples/s]
Generating train split: 127911462 examples [2:19:00, 25905.55 examples/s]
Generating train split: 127914275 examples [2:19:00, 26475.19 examples/s]
Generating train split: 127917037 examples [2:19:00, 21607.64 examples/s]
Generating train split: 127920557 examples [2:19:00, 24827.17 examples/s]
Generating train split: 127923994 examples [2:19:01, 27204.75 examples/s]
Generating train split: 127926929 examples [2:19:01, 26524.23 examples/s]
Generating train split: 127929725 examples [2:19:01, 26418.12 examples/s]
Generating train split: 127933210 examples [2:19:01, 28694.90 examples/s]
Generating train split: 127936175 examples [2:19:01, 23543.10 examples/s]
Generating train split: 127939015 examples [2:19:01, 24621.42 examples/s]
Generating train split: 127941661 examples [2:19:01, 22304.66 examples/s]
Generating train split: 127944894 examples [2:19:01, 24773.47 examples/s]
Generating train split: 127947534 examples [2:19:01, 23269.30 examples/s]
Generating train split: 127950050 examples [2:19:02, 23706.21 examples/s]
Generating train split: 127952514 examples [2:19:02, 17759.04 examples/s]
Generating train split: 127956005 examples [2:19:02, 21505.21 examples/s]
Generating train split: 127958479 examples [2:19:02, 20612.91 examples/s]
Generating train split: 127961084 examples [2:19:02, 21901.90 examples/s]
Generating train split: 127964100 examples [2:19:02, 24003.07 examples/s]
Generating train split: 127966671 examples [2:19:02, 23236.79 examples/s]
Generating train split: 127971979 examples [2:19:02, 31175.08 examples/s]
Generating train split: 127981004 examples [2:19:03, 47445.11 examples/s]
Generating train split: 127988617 examples [2:19:03, 55521.22 examples/s]
Generating train split: 127994416 examples [2:19:03, 47121.42 examples/s]
Generating train split: 127999515 examples [2:19:03, 34746.80 examples/s]
Generating train split: 128003703 examples [2:19:03, 31769.53 examples/s]
Generating train split: 128007390 examples [2:19:03, 29745.18 examples/s]
Generating train split: 128010709 examples [2:19:04, 28989.05 examples/s]
Generating train split: 128013829 examples [2:19:04, 27832.14 examples/s]
Generating train split: 128016760 examples [2:19:04, 25056.33 examples/s]
Generating train split: 128019383 examples [2:19:04, 21742.61 examples/s]
Generating train split: 128022143 examples [2:19:04, 23010.39 examples/s]
Generating train split: 128024579 examples [2:19:04, 23170.55 examples/s]
Generating train split: 128027163 examples [2:19:04, 23833.80 examples/s]
Generating train split: 128029632 examples [2:19:04, 21792.23 examples/s]
Generating train split: 128031932 examples [2:19:05, 22068.31 examples/s]
Generating train split: 128034391 examples [2:19:05, 22728.62 examples/s]
Generating train split: 128036727 examples [2:19:05, 21709.77 examples/s]
Generating train split: 128038941 examples [2:19:05, 19769.83 examples/s]
Generating train split: 128041371 examples [2:19:05, 20940.49 examples/s]
Generating train split: 128043519 examples [2:19:05, 19313.16 examples/s]
Generating train split: 128045712 examples [2:19:05, 19981.83 examples/s]
Generating train split: 128048257 examples [2:19:05, 21436.99 examples/s]
Generating train split: 128050448 examples [2:19:05, 19915.01 examples/s]
Generating train split: 128053180 examples [2:19:06, 21856.40 examples/s]
Generating train split: 128055747 examples [2:19:06, 22894.98 examples/s]
Generating train split: 128058734 examples [2:19:06, 24821.65 examples/s]
Generating train split: 128061271 examples [2:19:06, 24757.72 examples/s]
Generating train split: 128064912 examples [2:19:06, 28127.79 examples/s]
Generating train split: 128069283 examples [2:19:06, 32684.17 examples/s]
Generating train split: 128078593 examples [2:19:06, 50478.23 examples/s]
Generating train split: 128085432 examples [2:19:06, 55722.14 examples/s]
Generating train split: 128091061 examples [2:19:06, 40211.64 examples/s]
Generating train split: 128095736 examples [2:19:07, 31163.04 examples/s]
Generating train split: 128099585 examples [2:19:07, 30899.18 examples/s]
Generating train split: 128103700 examples [2:19:07, 33077.27 examples/s]
Generating train split: 128107446 examples [2:19:07, 26936.59 examples/s]
Generating train split: 128110596 examples [2:19:07, 27358.87 examples/s]
Generating train split: 128113670 examples [2:19:07, 27888.73 examples/s]
Generating train split: 128116709 examples [2:19:08, 26276.87 examples/s]
Generating train split: 128119518 examples [2:19:08, 26280.51 examples/s]
Generating train split: 128122775 examples [2:19:08, 27859.24 examples/s]
Generating train split: 128125683 examples [2:19:08, 25599.62 examples/s]
Generating train split: 128128473 examples [2:19:08, 26121.63 examples/s]
Generating train split: 128131391 examples [2:19:08, 26934.53 examples/s]
Generating train split: 128134151 examples [2:19:08, 24791.03 examples/s]
Generating train split: 128136702 examples [2:19:08, 24465.00 examples/s]
Generating train split: 128140559 examples [2:19:08, 28278.94 examples/s]
Generating train split: 128143483 examples [2:19:09, 28537.36 examples/s]
Generating train split: 128146403 examples [2:19:09, 28452.11 examples/s]
Generating train split: 128149755 examples [2:19:09, 29878.71 examples/s]
Generating train split: 128157264 examples [2:19:09, 43012.71 examples/s]
Generating train split: 128164075 examples [2:19:09, 50372.69 examples/s]
Generating train split: 128170363 examples [2:19:09, 53635.68 examples/s]
Generating train split: 128175775 examples [2:19:09, 33851.29 examples/s]
Generating train split: 128180112 examples [2:19:10, 30485.87 examples/s]
Generating train split: 128183862 examples [2:19:10, 27844.12 examples/s]
Generating train split: 128187138 examples [2:19:10, 22811.10 examples/s]
Generating train split: 128189855 examples [2:19:10, 22480.20 examples/s]
Generating train split: 128192403 examples [2:19:10, 21071.42 examples/s]
Generating train split: 128195166 examples [2:19:10, 22384.49 examples/s]
Generating train split: 128198317 examples [2:19:10, 24464.99 examples/s]
Generating train split: 128200967 examples [2:19:11, 21626.18 examples/s]
Generating train split: 128203314 examples [2:19:11, 20430.10 examples/s]
Generating train split: 128206956 examples [2:19:11, 24199.42 examples/s]
Generating train split: 128210087 examples [2:19:11, 25587.81 examples/s]
Generating train split: 128212809 examples [2:19:11, 24938.35 examples/s]
Generating train split: 128215417 examples [2:19:11, 24017.06 examples/s]
Generating train split: 128218258 examples [2:19:11, 25170.44 examples/s]
Generating train split: 128220846 examples [2:19:11, 23917.24 examples/s]
Generating train split: 128228126 examples [2:19:11, 37084.64 examples/s]
Generating train split: 128237722 examples [2:19:12, 53442.63 examples/s]
Generating train split: 128243332 examples [2:19:12, 50119.66 examples/s]
Generating train split: 128248569 examples [2:19:12, 34568.54 examples/s]
Generating train split: 128252822 examples [2:19:12, 32605.35 examples/s]
Generating train split: 128256629 examples [2:19:12, 29081.64 examples/s]
Generating train split: 128259944 examples [2:19:12, 29319.80 examples/s]
Generating train split: 128263168 examples [2:19:12, 29280.72 examples/s]
Generating train split: 128266307 examples [2:19:13, 29255.97 examples/s]
Generating train split: 128269735 examples [2:19:13, 30509.06 examples/s]
Generating train split: 128272916 examples [2:19:13, 26318.33 examples/s]
Generating train split: 128275719 examples [2:19:13, 22575.37 examples/s]
Generating train split: 128278905 examples [2:19:13, 24604.05 examples/s]
Generating train split: 128281564 examples [2:19:13, 24089.30 examples/s]
Generating train split: 128284112 examples [2:19:13, 22834.30 examples/s]
Generating train split: 128286494 examples [2:19:14, 21106.78 examples/s]
Generating train split: 128289484 examples [2:19:14, 23255.30 examples/s]
Generating train split: 128293009 examples [2:19:14, 26379.74 examples/s]
Generating train split: 128295845 examples [2:19:14, 26909.18 examples/s]
Generating train split: 128298626 examples [2:19:14, 21999.88 examples/s]
Generating train split: 128301690 examples [2:19:14, 24086.78 examples/s]
Generating train split: 128304292 examples [2:19:14, 22220.07 examples/s]
Generating train split: 128306779 examples [2:19:14, 22842.04 examples/s]
Generating train split: 128309181 examples [2:19:14, 22841.88 examples/s]
Generating train split: 128311552 examples [2:19:15, 20326.01 examples/s]
Generating train split: 128313819 examples [2:19:15, 20868.72 examples/s]
Generating train split: 128316062 examples [2:19:15, 21273.59 examples/s]
Generating train split: 128318260 examples [2:19:15, 16245.73 examples/s]
Generating train split: 128321013 examples [2:19:15, 18829.89 examples/s]
Generating train split: 128323244 examples [2:19:15, 19686.13 examples/s]
Generating train split: 128325397 examples [2:19:15, 18102.59 examples/s]
Generating train split: 128328679 examples [2:19:15, 21782.44 examples/s]
Generating train split: 128331030 examples [2:19:16, 21733.03 examples/s]
Generating train split: 128333324 examples [2:19:16, 19808.82 examples/s]
Generating train split: 128336149 examples [2:19:16, 21969.33 examples/s]
Generating train split: 128339633 examples [2:19:16, 25408.55 examples/s]
Generating train split: 128342805 examples [2:19:16, 27115.84 examples/s]
Generating train split: 128345627 examples [2:19:16, 22442.61 examples/s]
Generating train split: 128348618 examples [2:19:16, 24287.98 examples/s]
Generating train split: 128351229 examples [2:19:16, 24586.69 examples/s]
Generating train split: 128353872 examples [2:19:17, 25061.92 examples/s]
Generating train split: 128357240 examples [2:19:17, 27337.25 examples/s]
Generating train split: 128360055 examples [2:19:17, 26911.11 examples/s]
Generating train split: 128363354 examples [2:19:17, 28616.31 examples/s]
Generating train split: 128366266 examples [2:19:17, 27226.59 examples/s]
Generating train split: 128369045 examples [2:19:17, 23599.37 examples/s]
Generating train split: 128371522 examples [2:19:17, 21959.52 examples/s]
Generating train split: 128373816 examples [2:19:17, 21767.13 examples/s]
Generating train split: 128376064 examples [2:19:17, 20180.11 examples/s]
Generating train split: 128379851 examples [2:19:18, 24636.61 examples/s]
Generating train split: 128382436 examples [2:19:18, 21222.22 examples/s]
Generating train split: 128384945 examples [2:19:18, 22166.81 examples/s]
Generating train split: 128387553 examples [2:19:18, 23153.12 examples/s]
Generating train split: 128389981 examples [2:19:18, 22383.57 examples/s]
Generating train split: 128392298 examples [2:19:18, 22260.81 examples/s]
Generating train split: 128395065 examples [2:19:18, 23731.07 examples/s]
Generating train split: 128397533 examples [2:19:18, 23868.43 examples/s]
Generating train split: 128399957 examples [2:19:19, 20448.54 examples/s]
Generating train split: 128402211 examples [2:19:19, 20975.88 examples/s]
Generating train split: 128404774 examples [2:19:19, 22223.85 examples/s]
Generating train split: 128407068 examples [2:19:19, 20584.22 examples/s]
Generating train split: 128409206 examples [2:19:19, 18534.37 examples/s]
Generating train split: 128411146 examples [2:19:19, 18642.94 examples/s]
Generating train split: 128413611 examples [2:19:19, 20215.24 examples/s]
Generating train split: 128415730 examples [2:19:19, 20471.36 examples/s]
Generating train split: 128419577 examples [2:19:19, 25532.42 examples/s]
Generating train split: 128423675 examples [2:19:20, 29939.02 examples/s]
Generating train split: 128426733 examples [2:19:20, 25472.36 examples/s]
Generating train split: 128429444 examples [2:19:20, 23232.58 examples/s]
Generating train split: 128431901 examples [2:19:20, 23454.60 examples/s]
Generating train split: 128435623 examples [2:19:20, 27053.26 examples/s]
Generating train split: 128438463 examples [2:19:20, 25858.53 examples/s]
Generating train split: 128441145 examples [2:19:20, 22541.94 examples/s]
Generating train split: 128443526 examples [2:19:20, 22179.44 examples/s]
Generating train split: 128446770 examples [2:19:21, 24795.36 examples/s]
Generating train split: 128452425 examples [2:19:21, 33302.62 examples/s]
Generating train split: 128460829 examples [2:19:21, 47336.33 examples/s]
Generating train split: 128465904 examples [2:19:21, 47859.52 examples/s]
Generating train split: 128470861 examples [2:19:21, 37602.14 examples/s]
Generating train split: 128475084 examples [2:19:21, 34431.81 examples/s]
Generating train split: 128478881 examples [2:19:21, 30892.99 examples/s]
Generating train split: 128482348 examples [2:19:21, 31731.57 examples/s]
Generating train split: 128485747 examples [2:19:22, 31756.26 examples/s]
Generating train split: 128489085 examples [2:19:22, 29099.97 examples/s]
Generating train split: 128492135 examples [2:19:22, 28185.06 examples/s]
Generating train split: 128495038 examples [2:19:22, 26722.80 examples/s]
Generating train split: 128497778 examples [2:19:22, 23546.69 examples/s]
Generating train split: 128500218 examples [2:19:22, 23112.29 examples/s]
Generating train split: 128502584 examples [2:19:22, 23034.00 examples/s]
Generating train split: 128505139 examples [2:19:22, 23417.62 examples/s]
Generating train split: 128507957 examples [2:19:22, 24599.02 examples/s]
Generating train split: 128510654 examples [2:19:23, 25208.28 examples/s]
Generating train split: 128513210 examples [2:19:23, 21082.03 examples/s]
Generating train split: 128516360 examples [2:19:23, 23613.79 examples/s]
Generating train split: 128518870 examples [2:19:23, 20876.87 examples/s]
Generating train split: 128522719 examples [2:19:23, 25225.73 examples/s]
Generating train split: 128526463 examples [2:19:23, 28407.80 examples/s]
Generating train split: 128530392 examples [2:19:23, 31344.33 examples/s]
Generating train split: 128533986 examples [2:19:23, 32386.63 examples/s]
Generating train split: 128537805 examples [2:19:24, 34027.66 examples/s]
Generating train split: 128541300 examples [2:19:24, 30123.85 examples/s]
Generating train split: 128544461 examples [2:19:24, 27427.68 examples/s]
Generating train split: 128547337 examples [2:19:24, 24931.69 examples/s]
Generating train split: 128549947 examples [2:19:24, 24425.53 examples/s]
Generating train split: 128552464 examples [2:19:24, 24039.94 examples/s]
Generating train split: 128554923 examples [2:19:24, 23064.94 examples/s]
Generating train split: 128557269 examples [2:19:24, 22447.50 examples/s]
Generating train split: 128560140 examples [2:19:25, 24115.56 examples/s]
Generating train split: 128562595 examples [2:19:25, 23983.28 examples/s]
Generating train split: 128565374 examples [2:19:25, 25023.72 examples/s]
Generating train split: 128568525 examples [2:19:25, 26850.62 examples/s]
Generating train split: 128571245 examples [2:19:25, 22347.87 examples/s]
Generating train split: 128574070 examples [2:19:25, 23833.29 examples/s]
Generating train split: 128579085 examples [2:19:25, 30865.76 examples/s]
Generating train split: 128586895 examples [2:19:25, 43904.83 examples/s]
Generating train split: 128593937 examples [2:19:25, 51398.67 examples/s]
Generating train split: 128599295 examples [2:19:26, 38362.98 examples/s]
Generating train split: 128603767 examples [2:19:26, 37056.20 examples/s]
Generating train split: 128607907 examples [2:19:26, 30175.96 examples/s]
Generating train split: 128611398 examples [2:19:26, 30927.79 examples/s]
Generating train split: 128614852 examples [2:19:26, 29789.64 examples/s]
Generating train split: 128618085 examples [2:19:26, 27917.96 examples/s]
Generating train split: 128621048 examples [2:19:26, 26061.09 examples/s]
Generating train split: 128623776 examples [2:19:27, 25616.10 examples/s]
Generating train split: 128626723 examples [2:19:27, 26489.19 examples/s]
Generating train split: 128629480 examples [2:19:27, 26705.67 examples/s]
Generating train split: 128632210 examples [2:19:27, 21756.57 examples/s]
Generating train split: 128634640 examples [2:19:27, 22344.68 examples/s]
Generating train split: 128637504 examples [2:19:27, 23931.04 examples/s]
Generating train split: 128640023 examples [2:19:27, 23406.23 examples/s]
Generating train split: 128644754 examples [2:19:27, 29810.36 examples/s]
Generating train split: 128653930 examples [2:19:27, 46973.21 examples/s]
Generating train split: 128662414 examples [2:19:28, 57692.49 examples/s]
Generating train split: 128668420 examples [2:19:28, 46127.38 examples/s]
Generating train split: 128673570 examples [2:19:28, 40113.26 examples/s]
Generating train split: 128678059 examples [2:19:28, 35048.86 examples/s]
Generating train split: 128681959 examples [2:19:28, 29528.20 examples/s]
Generating train split: 128685281 examples [2:19:28, 28644.58 examples/s]
Generating train split: 128688383 examples [2:19:29, 27377.94 examples/s]
Generating train split: 128691410 examples [2:19:29, 28007.63 examples/s]
Generating train split: 128694335 examples [2:19:29, 27896.82 examples/s]
Generating train split: 128697210 examples [2:19:29, 25957.33 examples/s]
Generating train split: 128699885 examples [2:19:29, 24757.54 examples/s]
Generating train split: 128706360 examples [2:19:29, 34900.98 examples/s]
Generating train split: 128714515 examples [2:19:29, 47303.39 examples/s]
Generating train split: 128720318 examples [2:19:29, 49869.75 examples/s]
Generating train split: 128725548 examples [2:19:29, 44205.04 examples/s]
Generating train split: 128730252 examples [2:19:30, 36405.52 examples/s]
Generating train split: 128734288 examples [2:19:30, 35057.30 examples/s]
Generating train split: 128738058 examples [2:19:30, 29712.59 examples/s]
Generating train split: 128742015 examples [2:19:30, 31865.47 examples/s]
Generating train split: 128745478 examples [2:19:30, 29938.07 examples/s]
Generating train split: 128748663 examples [2:19:30, 26182.74 examples/s]
Generating train split: 128751769 examples [2:19:30, 27280.58 examples/s]
Generating train split: 128754665 examples [2:19:31, 27399.51 examples/s]
Generating train split: 128757744 examples [2:19:31, 28235.25 examples/s]
Generating train split: 128760951 examples [2:19:31, 29242.14 examples/s]
Generating train split: 128763956 examples [2:19:31, 26295.78 examples/s]
Generating train split: 128766687 examples [2:19:31, 24110.84 examples/s]
Generating train split: 128769836 examples [2:19:31, 25973.20 examples/s]
Generating train split: 128772897 examples [2:19:31, 27131.88 examples/s]
Generating train split: 128775699 examples [2:19:31, 25842.00 examples/s]
Generating train split: 128778618 examples [2:19:32, 26700.33 examples/s]
Generating train split: 128781466 examples [2:19:32, 27142.91 examples/s]
Generating train split: 128784228 examples [2:19:32, 24321.39 examples/s]
Generating train split: 128786745 examples [2:19:32, 24443.47 examples/s]
Generating train split: 128789713 examples [2:19:32, 25878.87 examples/s]
Generating train split: 128792375 examples [2:19:32, 22931.03 examples/s]
Generating train split: 128794768 examples [2:19:32, 23059.21 examples/s]
Generating train split: 128797141 examples [2:19:32, 23118.67 examples/s]
Generating train split: 128799505 examples [2:19:32, 21375.47 examples/s]
Generating train split: 128802805 examples [2:19:33, 24283.82 examples/s]
Generating train split: 128806261 examples [2:19:33, 26932.70 examples/s]
Generating train split: 128809028 examples [2:19:33, 25124.55 examples/s]
Generating train split: 128811650 examples [2:19:33, 25393.20 examples/s]
Generating train split: 128816269 examples [2:19:33, 31172.99 examples/s]
Generating train split: 128824930 examples [2:19:33, 46941.77 examples/s]
Generating train split: 128832757 examples [2:19:33, 55981.94 examples/s]
Generating train split: 128838487 examples [2:19:33, 45343.80 examples/s]
Generating train split: 128843441 examples [2:19:34, 35831.72 examples/s]
Generating train split: 128847590 examples [2:19:34, 31282.64 examples/s]
Generating train split: 128851169 examples [2:19:34, 29520.29 examples/s]
Generating train split: 128854869 examples [2:19:34, 31109.19 examples/s]
Generating train split: 128858258 examples [2:19:34, 28258.79 examples/s]
Generating train split: 128861299 examples [2:19:34, 26659.97 examples/s]
Generating train split: 128864403 examples [2:19:34, 27667.10 examples/s]
Generating train split: 128867303 examples [2:19:35, 26889.76 examples/s]
Generating train split: 128870083 examples [2:19:35, 26548.96 examples/s]
Generating train split: 128874261 examples [2:19:35, 30504.17 examples/s]
Generating train split: 128877411 examples [2:19:35, 28851.73 examples/s]
Generating train split: 128880380 examples [2:19:35, 28982.72 examples/s]
Generating train split: 128883335 examples [2:19:35, 23042.98 examples/s]
Generating train split: 128885860 examples [2:19:35, 23022.14 examples/s]
Generating train split: 128888537 examples [2:19:35, 23945.32 examples/s]
Generating train split: 128891059 examples [2:19:35, 23828.47 examples/s]
Generating train split: 128893540 examples [2:19:36, 23655.50 examples/s]
Generating train split: 128896167 examples [2:19:36, 24368.04 examples/s]
Generating train split: 128898657 examples [2:19:36, 23936.10 examples/s]
Generating train split: 128901235 examples [2:19:36, 24428.13 examples/s]
Generating train split: 128904064 examples [2:19:36, 25532.87 examples/s]
Generating train split: 128906782 examples [2:19:36, 26010.19 examples/s]
Generating train split: 128909420 examples [2:19:36, 25989.27 examples/s]
Generating train split: 128912033 examples [2:19:36, 23472.43 examples/s]
Generating train split: 128915268 examples [2:19:36, 25903.27 examples/s]
Generating train split: 128917926 examples [2:19:37, 23947.48 examples/s]
Generating train split: 128920660 examples [2:19:37, 24265.09 examples/s]
Generating train split: 128923287 examples [2:19:37, 24773.42 examples/s]
Generating train split: 128925813 examples [2:19:37, 21661.61 examples/s]
Generating train split: 128928075 examples [2:19:37, 19218.83 examples/s]
Generating train split: 128930545 examples [2:19:37, 20546.79 examples/s]
Generating train split: 128933101 examples [2:19:37, 21806.51 examples/s]
Generating train split: 128935474 examples [2:19:37, 22275.27 examples/s]
Generating train split: 128937875 examples [2:19:37, 22753.17 examples/s]
Generating train split: 128940913 examples [2:19:38, 24911.21 examples/s]
Generating train split: 128943457 examples [2:19:38, 23415.51 examples/s]
Generating train split: 128946468 examples [2:19:38, 25272.53 examples/s]
Generating train split: 128949046 examples [2:19:38, 25207.49 examples/s]
Generating train split: 128956554 examples [2:19:38, 39511.34 examples/s]
Generating train split: 128963581 examples [2:19:38, 48438.92 examples/s]
Generating train split: 128968527 examples [2:19:38, 40237.62 examples/s]
Generating train split: 128972843 examples [2:19:38, 33942.90 examples/s]
Generating train split: 128976585 examples [2:19:39, 30114.04 examples/s]
Generating train split: 128979884 examples [2:19:39, 27423.58 examples/s]
Generating train split: 128982840 examples [2:19:39, 26597.90 examples/s]
Generating train split: 128985631 examples [2:19:39, 24967.55 examples/s]
Generating train split: 128988213 examples [2:19:39, 23535.78 examples/s]
Generating train split: 128990712 examples [2:19:39, 23796.76 examples/s]
Generating train split: 128993136 examples [2:19:39, 23857.78 examples/s]
Generating train split: 128995561 examples [2:19:39, 23125.10 examples/s]
Generating train split: 128998307 examples [2:19:40, 23952.24 examples/s]
Generating train split: 129000728 examples [2:19:40, 22934.66 examples/s]
Generating train split: 129003932 examples [2:19:40, 25405.69 examples/s]
Generating train split: 129007070 examples [2:19:40, 27068.03 examples/s]
Generating train split: 129009820 examples [2:19:40, 25052.98 examples/s]
Generating train split: 129013652 examples [2:19:40, 28677.46 examples/s]
Generating train split: 129016605 examples [2:19:40, 25574.17 examples/s]
Generating train split: 129019276 examples [2:19:40, 23776.99 examples/s]
Generating train split: 129021923 examples [2:19:40, 24402.03 examples/s]
Generating train split: 129024440 examples [2:19:41, 24367.77 examples/s]
Generating train split: 129027794 examples [2:19:41, 26875.87 examples/s]
Generating train split: 129031351 examples [2:19:41, 29309.88 examples/s]
Generating train split: 129034359 examples [2:19:41, 28547.57 examples/s]
Generating train split: 129038479 examples [2:19:41, 32120.86 examples/s]
Generating train split: 129041758 examples [2:19:41, 30900.06 examples/s]
Generating train split: 129044897 examples [2:19:41, 28496.44 examples/s]
Generating train split: 129047810 examples [2:19:41, 28396.50 examples/s]
Generating train split: 129050696 examples [2:19:41, 28017.49 examples/s]
Generating train split: 129054209 examples [2:19:42, 29989.08 examples/s]
Generating train split: 129057257 examples [2:19:42, 28149.18 examples/s]
Generating train split: 129060532 examples [2:19:42, 29063.86 examples/s]
Generating train split: 129063482 examples [2:19:42, 28158.82 examples/s]
Generating train split: 129066493 examples [2:19:42, 28699.50 examples/s]
Generating train split: 129069391 examples [2:19:42, 28535.89 examples/s]
Generating train split: 129072875 examples [2:19:42, 30304.23 examples/s]
Generating train split: 129075984 examples [2:19:42, 30442.40 examples/s]
Generating train split: 129079051 examples [2:19:42, 24781.47 examples/s]
Generating train split: 129081994 examples [2:19:43, 25874.72 examples/s]
Generating train split: 129085112 examples [2:19:43, 27197.76 examples/s]
Generating train split: 129087959 examples [2:19:43, 24966.05 examples/s]
Generating train split: 129091318 examples [2:19:43, 27208.23 examples/s]
Generating train split: 129094150 examples [2:19:43, 26780.78 examples/s]
Generating train split: 129096918 examples [2:19:43, 21850.15 examples/s]
Generating train split: 129099295 examples [2:19:43, 21430.95 examples/s]
Generating train split: 129101577 examples [2:19:43, 21688.96 examples/s]
Generating train split: 129104342 examples [2:19:44, 23134.59 examples/s]
Generating train split: 129106749 examples [2:19:44, 23172.22 examples/s]
Generating train split: 129109126 examples [2:19:44, 22949.76 examples/s]
Generating train split: 129111505 examples [2:19:44, 23142.53 examples/s]
Generating train split: 129113856 examples [2:19:44, 21679.60 examples/s]
Generating train split: 129116744 examples [2:19:44, 23656.58 examples/s]
Generating train split: 129119281 examples [2:19:44, 24137.72 examples/s]
Generating train split: 129122616 examples [2:19:44, 26759.40 examples/s]
Generating train split: 129125333 examples [2:19:44, 26352.76 examples/s]
Generating train split: 129127998 examples [2:19:45, 25278.10 examples/s]
Generating train split: 129130659 examples [2:19:45, 25641.80 examples/s]
Generating train split: 129133247 examples [2:19:45, 24581.92 examples/s]
Generating train split: 129135731 examples [2:19:45, 22887.57 examples/s]
Generating train split: 129138236 examples [2:19:45, 23322.97 examples/s]
Generating train split: 129142770 examples [2:19:45, 29456.25 examples/s]
Generating train split: 129151424 examples [2:19:45, 45699.18 examples/s]
Generating train split: 129158357 examples [2:19:45, 52463.24 examples/s]
Generating train split: 129163727 examples [2:19:45, 45158.12 examples/s]
Generating train split: 129168508 examples [2:19:46, 33328.93 examples/s]
Generating train split: 129172440 examples [2:19:46, 29754.76 examples/s]
Generating train split: 129175866 examples [2:19:46, 25909.18 examples/s]
Generating train split: 129178808 examples [2:19:46, 22780.28 examples/s]
Generating train split: 129182369 examples [2:19:46, 25295.81 examples/s]
Generating train split: 129185213 examples [2:19:46, 25706.54 examples/s]
Generating train split: 129188030 examples [2:19:47, 25678.21 examples/s]
Generating train split: 129191200 examples [2:19:47, 27107.98 examples/s]
Generating train split: 129194062 examples [2:19:47, 26534.52 examples/s]
Generating train split: 129196818 examples [2:19:47, 26205.17 examples/s]
Generating train split: 129199513 examples [2:19:47, 24869.96 examples/s]
Generating train split: 129202103 examples [2:19:47, 25139.35 examples/s]
Generating train split: 129204657 examples [2:19:47, 22853.57 examples/s]
Generating train split: 129208038 examples [2:19:47, 25728.85 examples/s]
Generating train split: 129211191 examples [2:19:47, 27297.30 examples/s]
Generating train split: 129213995 examples [2:19:48, 26977.87 examples/s]
Generating train split: 129218875 examples [2:19:48, 33127.68 examples/s]
Generating train split: 129222265 examples [2:19:48, 28342.47 examples/s]
Generating train split: 129225279 examples [2:19:48, 25762.10 examples/s]
Generating train split: 129228009 examples [2:19:48, 24821.38 examples/s]
Generating train split: 129230594 examples [2:19:48, 23126.43 examples/s]
Generating train split: 129232980 examples [2:19:48, 22755.66 examples/s]
Generating train split: 129236140 examples [2:19:48, 25023.98 examples/s]
Generating train split: 129238722 examples [2:19:48, 25156.78 examples/s]
Generating train split: 129241290 examples [2:19:49, 23152.79 examples/s]
Generating train split: 129243668 examples [2:19:49, 22944.98 examples/s]
Generating train split: 129247711 examples [2:19:49, 27700.51 examples/s]
Generating train split: 129256478 examples [2:19:49, 44472.91 examples/s]
Generating train split: 129264276 examples [2:19:49, 54027.84 examples/s]
Generating train split: 129269858 examples [2:19:49, 44682.09 examples/s]
Generating train split: 129274725 examples [2:19:49, 36284.84 examples/s]
Generating train split: 129278852 examples [2:19:50, 29540.71 examples/s]
Generating train split: 129282306 examples [2:19:50, 28890.87 examples/s]
Generating train split: 129285530 examples [2:19:50, 27211.31 examples/s]
Generating train split: 129288480 examples [2:19:50, 23697.61 examples/s]
Generating train split: 129291045 examples [2:19:50, 22829.53 examples/s]
Generating train split: 129294618 examples [2:19:50, 25665.27 examples/s]
Generating train split: 129297376 examples [2:19:50, 21836.63 examples/s]
Generating train split: 129300313 examples [2:19:51, 23469.22 examples/s]
Generating train split: 129302857 examples [2:19:51, 21279.59 examples/s]
Generating train split: 129305150 examples [2:19:51, 19878.05 examples/s]
Generating train split: 129307972 examples [2:19:51, 21800.58 examples/s]
Generating train split: 129311142 examples [2:19:51, 24140.83 examples/s]
Generating train split: 129313693 examples [2:19:51, 21817.90 examples/s]
Generating train split: 129316144 examples [2:19:51, 22461.79 examples/s]
Generating train split: 129318487 examples [2:19:51, 20886.40 examples/s]
Generating train split: 129321467 examples [2:19:52, 23111.60 examples/s]
Generating train split: 129325875 examples [2:19:52, 28593.57 examples/s]
Generating train split: 129328868 examples [2:19:52, 26291.70 examples/s]
Generating train split: 129331612 examples [2:19:52, 23559.69 examples/s]
Generating train split: 129334218 examples [2:19:52, 24137.53 examples/s]
Generating train split: 129336731 examples [2:19:52, 23613.40 examples/s]
Generating train split: 129339201 examples [2:19:52, 23894.11 examples/s]
Generating train split: 129342451 examples [2:19:52, 26113.68 examples/s]
Generating train split: 129345125 examples [2:19:52, 24409.99 examples/s]
Generating train split: 129347622 examples [2:19:53, 22211.65 examples/s]
Generating train split: 129351477 examples [2:19:53, 26446.83 examples/s]
Generating train split: 129354235 examples [2:19:53, 23369.50 examples/s]
Generating train split: 129356708 examples [2:19:53, 22705.53 examples/s]
Generating train split: 129360497 examples [2:19:53, 26599.56 examples/s]
Generating train split: 129368952 examples [2:19:53, 42143.25 examples/s]
Generating train split: 129376042 examples [2:19:53, 50077.63 examples/s]
Generating train split: 129381313 examples [2:19:54, 39297.97 examples/s]
Generating train split: 129385780 examples [2:19:54, 31433.45 examples/s]
Generating train split: 129389507 examples [2:19:54, 30369.53 examples/s]
Generating train split: 129392945 examples [2:19:54, 27196.81 examples/s]
Generating train split: 129395959 examples [2:19:54, 27096.06 examples/s]
Generating train split: 129398874 examples [2:19:54, 26714.01 examples/s]
Generating train split: 129401682 examples [2:19:54, 24433.29 examples/s]
Generating train split: 129404236 examples [2:19:55, 23864.47 examples/s]
Generating train split: 129406984 examples [2:19:55, 24659.44 examples/s]
Generating train split: 129409512 examples [2:19:55, 22290.38 examples/s]
Generating train split: 129412316 examples [2:19:55, 23715.52 examples/s]
Generating train split: 129415544 examples [2:19:55, 25962.20 examples/s]
Generating train split: 129418231 examples [2:19:55, 22732.63 examples/s]
Generating train split: 129420632 examples [2:19:55, 20970.54 examples/s]
Generating train split: 129422829 examples [2:19:55, 21009.38 examples/s]
Generating train split: 129425000 examples [2:19:55, 20650.24 examples/s]
Generating train split: 129427631 examples [2:19:56, 22142.19 examples/s]
Generating train split: 129429906 examples [2:19:56, 20346.74 examples/s]
Generating train split: 129432225 examples [2:19:56, 21023.78 examples/s]
Generating train split: 129435275 examples [2:19:56, 23476.08 examples/s]
Generating train split: 129437687 examples [2:19:56, 21582.57 examples/s]
Generating train split: 129439917 examples [2:19:56, 21578.61 examples/s]
Generating train split: 129442849 examples [2:19:56, 23692.28 examples/s]
Generating train split: 129446155 examples [2:19:56, 26241.02 examples/s]
Generating train split: 129448829 examples [2:19:56, 23924.63 examples/s]
Generating train split: 129451301 examples [2:19:57, 24130.58 examples/s]
Generating train split: 129454228 examples [2:19:57, 25554.89 examples/s]
Generating train split: 129456838 examples [2:19:57, 23872.50 examples/s]
Generating train split: 129460596 examples [2:19:57, 27622.78 examples/s]
Generating train split: 129463878 examples [2:19:57, 29068.57 examples/s]
Generating train split: 129466844 examples [2:19:57, 24443.42 examples/s]
Generating train split: 129470449 examples [2:19:57, 27352.16 examples/s]
Generating train split: 129473408 examples [2:19:57, 27919.30 examples/s]
Generating train split: 129476327 examples [2:19:58, 24594.84 examples/s]
Generating train split: 129479052 examples [2:19:58, 25260.54 examples/s]
Generating train split: 129482285 examples [2:19:58, 27131.68 examples/s]
Generating train split: 129485109 examples [2:19:58, 25793.21 examples/s]
Generating train split: 129488979 examples [2:19:58, 29276.29 examples/s]
Generating train split: 129495259 examples [2:19:58, 38609.30 examples/s]
Generating train split: 129501680 examples [2:19:58, 45887.32 examples/s]
Generating train split: 129509801 examples [2:19:58, 56083.80 examples/s]
Generating train split: 129516493 examples [2:19:58, 59249.14 examples/s]
Generating train split: 129523949 examples [2:19:58, 63744.07 examples/s]
Generating train split: 129531114 examples [2:19:59, 66076.53 examples/s]
Generating train split: 129538111 examples [2:19:59, 67227.81 examples/s]
Generating train split: 129545679 examples [2:19:59, 69720.58 examples/s]
Generating train split: 129552684 examples [2:19:59, 69681.85 examples/s]
Generating train split: 129559683 examples [2:19:59, 69416.96 examples/s]
Generating train split: 129567790 examples [2:19:59, 72864.07 examples/s]
Generating train split: 129575165 examples [2:19:59, 73098.50 examples/s]
Generating train split: 129582505 examples [2:19:59, 70915.81 examples/s]
Generating train split: 129589989 examples [2:19:59, 72058.08 examples/s]
Generating train split: 129597217 examples [2:19:59, 72122.35 examples/s]
Generating train split: 129604450 examples [2:20:00, 71488.44 examples/s]
Generating train split: 129612316 examples [2:20:00, 73593.49 examples/s]
Generating train split: 129619709 examples [2:20:00, 73673.08 examples/s]
Generating train split: 129627097 examples [2:20:00, 73470.20 examples/s]
Generating train split: 129634452 examples [2:20:00, 72365.06 examples/s]
Generating train split: 129641706 examples [2:20:00, 71345.03 examples/s]
Generating train split: 129649139 examples [2:20:00, 72193.93 examples/s]
Generating train split: 129656370 examples [2:20:00, 68069.55 examples/s]
Generating train split: 129663231 examples [2:20:00, 64962.96 examples/s]
Generating train split: 129669791 examples [2:20:01, 57537.96 examples/s]
Generating train split: 129675717 examples [2:20:01, 43183.72 examples/s]
Generating train split: 129680638 examples [2:20:01, 40077.60 examples/s]
Generating train split: 129685059 examples [2:20:01, 34954.08 examples/s]
Generating train split: 129688900 examples [2:20:01, 33144.57 examples/s]
Generating train split: 129692437 examples [2:20:01, 30455.98 examples/s]
Generating train split: 129696220 examples [2:20:02, 32071.05 examples/s]
Generating train split: 129699601 examples [2:20:02, 27901.79 examples/s]
Generating train split: 129702560 examples [2:20:02, 25807.88 examples/s]
Generating train split: 129705595 examples [2:20:02, 26840.92 examples/s]
Generating train split: 129709702 examples [2:20:02, 30337.58 examples/s]
Generating train split: 129713392 examples [2:20:02, 31968.71 examples/s]
Generating train split: 129717286 examples [2:20:02, 33841.94 examples/s]
Generating train split: 129720787 examples [2:20:02, 27704.17 examples/s]
Generating train split: 129723808 examples [2:20:03, 26214.37 examples/s]
Generating train split: 129726607 examples [2:20:03, 23897.08 examples/s]
Generating train split: 129729135 examples [2:20:03, 21763.27 examples/s]
Generating train split: 129732332 examples [2:20:03, 24125.81 examples/s]
Generating train split: 129734887 examples [2:20:03, 21646.21 examples/s]
Generating train split: 129737421 examples [2:20:03, 22504.98 examples/s]
Generating train split: 129740173 examples [2:20:03, 23776.29 examples/s]
Generating train split: 129742656 examples [2:20:03, 22968.70 examples/s]
Generating train split: 129746677 examples [2:20:04, 27547.34 examples/s]
Generating train split: 129750029 examples [2:20:04, 29121.51 examples/s]
Generating train split: 129753028 examples [2:20:04, 26632.64 examples/s]
Generating train split: 129755923 examples [2:20:04, 27246.36 examples/s]
Generating train split: 129758733 examples [2:20:04, 26259.37 examples/s]
Generating train split: 129761584 examples [2:20:04, 26861.26 examples/s]
Generating train split: 129764567 examples [2:20:04, 27655.78 examples/s]
Generating train split: 129767369 examples [2:20:04, 27085.81 examples/s]
Generating train split: 129770109 examples [2:20:04, 27150.55 examples/s]
Generating train split: 129773355 examples [2:20:04, 28656.06 examples/s]
Generating train split: 129776773 examples [2:20:05, 30261.19 examples/s]
Generating train split: 129780835 examples [2:20:05, 33309.42 examples/s]
Generating train split: 129784185 examples [2:20:05, 29725.48 examples/s]
Generating train split: 129787253 examples [2:20:05, 25055.64 examples/s]
Generating train split: 129789930 examples [2:20:05, 23423.94 examples/s]
Generating train split: 129792406 examples [2:20:05, 21924.84 examples/s]
Generating train split: 129794689 examples [2:20:05, 21156.09 examples/s]
Generating train split: 129797271 examples [2:20:05, 22307.88 examples/s]
Generating train split: 129799614 examples [2:20:06, 22579.37 examples/s]
Generating train split: 129801924 examples [2:20:06, 21123.00 examples/s]
Generating train split: 129805988 examples [2:20:06, 26311.83 examples/s]
Generating train split: 129808716 examples [2:20:06, 26330.34 examples/s]
Generating train split: 129811417 examples [2:20:06, 24269.01 examples/s]
Generating train split: 129813922 examples [2:20:06, 22678.48 examples/s]
Generating train split: 129816258 examples [2:20:06, 22091.09 examples/s]
Generating train split: 129818513 examples [2:20:06, 19672.32 examples/s]
Generating train split: 129820547 examples [2:20:07, 17237.03 examples/s]
Generating train split: 129823214 examples [2:20:07, 19479.52 examples/s]
Generating train split: 129825278 examples [2:20:07, 15641.00 examples/s]
Generating train split: 129827150 examples [2:20:07, 16325.46 examples/s]
Generating train split: 129828934 examples [2:20:07, 15699.78 examples/s]
Generating train split: 129830607 examples [2:20:08, 7165.67 examples/s] 
Generating train split: 129831862 examples [2:20:08, 5817.32 examples/s]
Generating train split: 129832845 examples [2:20:08, 5874.07 examples/s]
Generating train split: 129833831 examples [2:20:08, 6404.48 examples/s]
Generating train split: 129835335 examples [2:20:08, 7851.23 examples/s]
Generating train split: 129837031 examples [2:20:09, 9609.26 examples/s]
Generating train split: 129838418 examples [2:20:09, 10528.89 examples/s]
Generating train split: 129840020 examples [2:20:09, 11809.94 examples/s]
Generating train split: 129841974 examples [2:20:09, 13675.72 examples/s]
Generating train split: 129843783 examples [2:20:09, 14801.26 examples/s]
Generating train split: 129845924 examples [2:20:09, 16553.83 examples/s]
Generating train split: 129848694 examples [2:20:09, 19577.97 examples/s]
Generating train split: 129851284 examples [2:20:09, 21370.71 examples/s]
Generating train split: 129853502 examples [2:20:09, 20000.19 examples/s]
Generating train split: 129856423 examples [2:20:09, 22544.19 examples/s]
Generating train split: 129859201 examples [2:20:10, 24002.01 examples/s]
Generating train split: 129861664 examples [2:20:10, 20357.03 examples/s]
Generating train split: 129863837 examples [2:20:10, 17280.42 examples/s]
Generating train split: 129866143 examples [2:20:10, 18635.05 examples/s]
Generating train split: 129868666 examples [2:20:10, 20282.48 examples/s]
Generating train split: 129870833 examples [2:20:10, 19940.34 examples/s]
Generating train split: 129872924 examples [2:20:10, 20169.61 examples/s]
Generating train split: 129876521 examples [2:20:10, 24511.56 examples/s]
Generating train split: 129879148 examples [2:20:11, 25008.12 examples/s]
Generating train split: 129881712 examples [2:20:11, 24305.81 examples/s]
Generating train split: 129884191 examples [2:20:11, 22174.39 examples/s]
Generating train split: 129886730 examples [2:20:11, 22994.71 examples/s]
Generating train split: 129889091 examples [2:20:11, 23074.24 examples/s]
Generating train split: 129891438 examples [2:20:11, 20005.54 examples/s]
Generating train split: 129893532 examples [2:20:11, 20020.22 examples/s]
Generating train split: 129896115 examples [2:20:11, 21558.57 examples/s]
Generating train split: 129898679 examples [2:20:11, 22673.49 examples/s]
Generating train split: 129901849 examples [2:20:12, 25220.99 examples/s]
Generating train split: 129904433 examples [2:20:12, 24427.82 examples/s]
Generating train split: 129906919 examples [2:20:12, 23076.25 examples/s]
Generating train split: 129912669 examples [2:20:12, 32558.43 examples/s]
Generating train split: 129920924 examples [2:20:12, 46670.97 examples/s]
Generating train split: 129925761 examples [2:20:12, 46960.37 examples/s]
Generating train split: 129930575 examples [2:20:12, 38929.22 examples/s]
Generating train split: 129935296 examples [2:20:12, 40913.19 examples/s]
Generating train split: 129939647 examples [2:20:12, 39719.68 examples/s]
Generating train split: 129947678 examples [2:20:13, 50519.22 examples/s]
Generating train split: 129954567 examples [2:20:13, 55561.82 examples/s]
Generating train split: 129960356 examples [2:20:13, 42316.27 examples/s]
Generating train split: 129965209 examples [2:20:13, 39020.90 examples/s]
Generating train split: 129969571 examples [2:20:13, 33524.08 examples/s]
Generating train split: 129973323 examples [2:20:13, 32004.08 examples/s]
Generating train split: 129976793 examples [2:20:14, 29253.69 examples/s]
Generating train split: 129979911 examples [2:20:14, 26180.77 examples/s]
Generating train split: 129982673 examples [2:20:14, 25944.69 examples/s]
Generating train split: 129985363 examples [2:20:14, 25220.03 examples/s]
Generating train split: 129988245 examples [2:20:14, 26090.96 examples/s]
Generating train split: 129990916 examples [2:20:14, 25650.05 examples/s]
Generating train split: 129993518 examples [2:20:14, 23653.37 examples/s]
Generating train split: 129995937 examples [2:20:14, 20011.23 examples/s]
Generating train split: 129999073 examples [2:20:15, 22662.67 examples/s]
Generating train split: 130001829 examples [2:20:15, 23897.88 examples/s]
Generating train split: 130004622 examples [2:20:15, 24959.41 examples/s]
Generating train split: 130007632 examples [2:20:15, 26357.58 examples/s]
Generating train split: 130010363 examples [2:20:15, 26540.18 examples/s]
Generating train split: 130013087 examples [2:20:15, 23774.51 examples/s]
Generating train split: 130015558 examples [2:20:15, 22714.11 examples/s]
Generating train split: 130018387 examples [2:20:15, 24168.05 examples/s]
Generating train split: 130021300 examples [2:20:15, 25513.75 examples/s]
Generating train split: 130023917 examples [2:20:16, 22208.82 examples/s]
Generating train split: 130026260 examples [2:20:16, 22376.89 examples/s]
Generating train split: 130028581 examples [2:20:16, 21631.65 examples/s]
Generating train split: 130030812 examples [2:20:16, 20888.02 examples/s]
Generating train split: 130033304 examples [2:20:16, 21926.32 examples/s]
Generating train split: 130035623 examples [2:20:16, 22268.29 examples/s]
Generating train split: 130038925 examples [2:20:16, 25251.66 examples/s]
Generating train split: 130041492 examples [2:20:16, 24080.64 examples/s]
Generating train split: 130044514 examples [2:20:16, 25739.02 examples/s]
Generating train split: 130047228 examples [2:20:17, 26108.77 examples/s]
Generating train split: 130049876 examples [2:20:17, 25728.22 examples/s]
Generating train split: 130052602 examples [2:20:17, 26167.31 examples/s]
Generating train split: 130056010 examples [2:20:17, 28316.52 examples/s]
Generating train split: 130058857 examples [2:20:17, 25955.69 examples/s]
Generating train split: 130061694 examples [2:20:17, 26621.64 examples/s]
Generating train split: 130064576 examples [2:20:17, 27243.04 examples/s]
Generating train split: 130067342 examples [2:20:17, 25888.91 examples/s]
Generating train split: 130069970 examples [2:20:17, 25658.30 examples/s]
Generating train split: 130073144 examples [2:20:17, 27378.49 examples/s]
Generating train split: 130076890 examples [2:20:18, 30277.22 examples/s]
Generating train split: 130079956 examples [2:20:18, 29800.48 examples/s]
Generating train split: 130082967 examples [2:20:18, 28341.88 examples/s]
Generating train split: 130085832 examples [2:20:18, 25062.64 examples/s]
Generating train split: 130088426 examples [2:20:18, 22641.50 examples/s]
Generating train split: 130092311 examples [2:20:18, 26703.21 examples/s]
Generating train split: 130095125 examples [2:20:18, 24574.80 examples/s]
Generating train split: 130097729 examples [2:20:18, 24939.86 examples/s]
Generating train split: 130100966 examples [2:20:19, 26908.95 examples/s]
Generating train split: 130103981 examples [2:20:19, 27749.06 examples/s]
Generating train split: 130106824 examples [2:20:19, 27115.54 examples/s]
Generating train split: 130109598 examples [2:20:19, 27283.32 examples/s]
Generating train split: 130112362 examples [2:20:19, 24142.96 examples/s]
Generating train split: 130114870 examples [2:20:19, 22601.94 examples/s]
Generating train split: 130117972 examples [2:20:19, 24785.61 examples/s]
Generating train split: 130120541 examples [2:20:19, 21062.74 examples/s]
Generating train split: 130123038 examples [2:20:19, 21981.82 examples/s]
Generating train split: 130125639 examples [2:20:20, 23023.42 examples/s]
Generating train split: 130128117 examples [2:20:20, 23272.50 examples/s]
Generating train split: 130131262 examples [2:20:20, 25525.60 examples/s]
Generating train split: 130134157 examples [2:20:20, 26384.85 examples/s]
Generating train split: 130137638 examples [2:20:20, 28795.95 examples/s]
Generating train split: 130140578 examples [2:20:20, 28537.87 examples/s]
Generating train split: 130143467 examples [2:20:20, 26526.02 examples/s]
Generating train split: 130146170 examples [2:20:20, 26426.62 examples/s]
Generating train split: 130149074 examples [2:20:20, 27123.16 examples/s]
Generating train split: 130151829 examples [2:20:21, 26330.41 examples/s]
Generating train split: 130156302 examples [2:20:21, 31546.00 examples/s]
Generating train split: 130159503 examples [2:20:21, 29175.93 examples/s]
Generating train split: 130162483 examples [2:20:21, 28582.64 examples/s]
Generating train split: 130165398 examples [2:20:21, 27859.99 examples/s]
Generating train split: 130168220 examples [2:20:21, 27742.89 examples/s]
Generating train split: 130171023 examples [2:20:21, 26149.64 examples/s]
Generating train split: 130173668 examples [2:20:21, 25493.23 examples/s]
Generating train split: 130176239 examples [2:20:21, 24407.91 examples/s]
Generating train split: 130178701 examples [2:20:22, 22143.42 examples/s]
Generating train split: 130180964 examples [2:20:22, 20211.54 examples/s]
Generating train split: 130183442 examples [2:20:22, 21358.19 examples/s]
Generating train split: 130185632 examples [2:20:22, 20902.92 examples/s]
Generating train split: 130187766 examples [2:20:22, 19572.88 examples/s]
Generating train split: 130190728 examples [2:20:22, 22218.10 examples/s]
Generating train split: 130193013 examples [2:20:22, 21811.30 examples/s]
Generating train split: 130195270 examples [2:20:22, 22011.99 examples/s]
Generating train split: 130197926 examples [2:20:22, 23260.56 examples/s]
Generating train split: 130201240 examples [2:20:23, 26064.01 examples/s]
Generating train split: 130204322 examples [2:20:23, 27435.35 examples/s]
Generating train split: 130207094 examples [2:20:23, 27184.06 examples/s]
Generating train split: 130209834 examples [2:20:23, 26787.97 examples/s]
Generating train split: 130212890 examples [2:20:23, 27870.38 examples/s]
Generating train split: 130215984 examples [2:20:23, 28756.20 examples/s]
Generating train split: 130218872 examples [2:20:23, 26243.61 examples/s]
Generating train split: 130221547 examples [2:20:23, 25257.18 examples/s]
Generating train split: 130224405 examples [2:20:23, 26135.65 examples/s]
Generating train split: 130227322 examples [2:20:24, 26969.66 examples/s]
Generating train split: 130230065 examples [2:20:24, 26073.16 examples/s]
Generating train split: 130234504 examples [2:20:24, 31236.97 examples/s]
Generating train split: 130242893 examples [2:20:24, 46374.63 examples/s]
Generating train split: 130252414 examples [2:20:24, 60584.52 examples/s]
Generating train split: 130258589 examples [2:20:24, 58399.08 examples/s]
Generating train split: 130264524 examples [2:20:24, 43367.98 examples/s]
Generating train split: 130269477 examples [2:20:24, 38454.07 examples/s]
Generating train split: 130273812 examples [2:20:25, 36817.33 examples/s]
Generating train split: 130277836 examples [2:20:25, 35472.38 examples/s]
Generating train split: 130281606 examples [2:20:25, 32360.37 examples/s]
Generating train split: 130285013 examples [2:20:25, 30619.94 examples/s]
Generating train split: 130288179 examples [2:20:25, 29193.76 examples/s]
Generating train split: 130291159 examples [2:20:25, 24888.58 examples/s]
Generating train split: 130293875 examples [2:20:25, 25332.89 examples/s]
Generating train split: 130296507 examples [2:20:26, 23124.93 examples/s]
Generating train split: 130299535 examples [2:20:26, 24833.27 examples/s]
Generating train split: 130302538 examples [2:20:26, 26150.90 examples/s]
Generating train split: 130305253 examples [2:20:26, 25990.47 examples/s]
Generating train split: 130307918 examples [2:20:26, 24218.60 examples/s]
Generating train split: 130310738 examples [2:20:26, 25244.05 examples/s]
Generating train split: 130313324 examples [2:20:26, 25236.79 examples/s]
Generating train split: 130315892 examples [2:20:26, 22351.90 examples/s]
Generating train split: 130319628 examples [2:20:26, 26076.14 examples/s]
Generating train split: 130323078 examples [2:20:27, 28350.56 examples/s]
Generating train split: 130326022 examples [2:20:27, 22622.16 examples/s]
Generating train split: 130328532 examples [2:20:27, 23182.55 examples/s]
Generating train split: 130331036 examples [2:20:27, 22680.23 examples/s]
Generating train split: 130333430 examples [2:20:27, 22827.82 examples/s]
Generating train split: 130341536 examples [2:20:27, 38429.67 examples/s]
Generating train split: 130349652 examples [2:20:27, 50032.87 examples/s]
Generating train split: 130354914 examples [2:20:27, 43652.57 examples/s]
Generating train split: 130359606 examples [2:20:28, 37370.35 examples/s]
Generating train split: 130363697 examples [2:20:28, 36946.30 examples/s]
Generating train split: 130367637 examples [2:20:28, 32844.21 examples/s]
Generating train split: 130371207 examples [2:20:28, 33447.08 examples/s]
Generating train split: 130375015 examples [2:20:28, 34589.39 examples/s]
Generating train split: 130378618 examples [2:20:28, 28709.57 examples/s]
Generating train split: 130381962 examples [2:20:28, 29781.24 examples/s]
Generating train split: 130385247 examples [2:20:28, 30509.09 examples/s]
Generating train split: 130388453 examples [2:20:29, 26473.23 examples/s]
Generating train split: 130391296 examples [2:20:29, 26411.66 examples/s]
Generating train split: 130394073 examples [2:20:29, 26345.66 examples/s]
Generating train split: 130397356 examples [2:20:29, 28045.05 examples/s]
Generating train split: 130400395 examples [2:20:29, 28595.36 examples/s]
Generating train split: 130403329 examples [2:20:29, 25294.09 examples/s]
Generating train split: 130405969 examples [2:20:29, 25114.16 examples/s]
Generating train split: 130409401 examples [2:20:29, 27573.76 examples/s]
Generating train split: 130412257 examples [2:20:30, 25855.30 examples/s]
Generating train split: 130415154 examples [2:20:30, 26684.54 examples/s]
Generating train split: 130417992 examples [2:20:30, 27099.84 examples/s]
Generating train split: 130420760 examples [2:20:30, 24704.09 examples/s]
Generating train split: 130423830 examples [2:20:30, 26287.65 examples/s]
Generating train split: 130427059 examples [2:20:30, 27924.88 examples/s]
Generating train split: 130429912 examples [2:20:30, 21010.95 examples/s]
Generating train split: 130433142 examples [2:20:30, 23577.44 examples/s]
Generating train split: 130435782 examples [2:20:31, 22238.59 examples/s]
Generating train split: 130438643 examples [2:20:31, 23800.48 examples/s]
Generating train split: 130441229 examples [2:20:31, 24313.32 examples/s]
Generating train split: 130443792 examples [2:20:31, 21863.77 examples/s]
Generating train split: 130446304 examples [2:20:31, 22657.09 examples/s]
Generating train split: 130448763 examples [2:20:31, 23170.22 examples/s]
Generating train split: 130451161 examples [2:20:31, 20464.82 examples/s]
Generating train split: 130453664 examples [2:20:31, 21571.31 examples/s]
Generating train split: 130455915 examples [2:20:31, 18768.88 examples/s]
Generating train split: 130458019 examples [2:20:32, 18985.84 examples/s]
Generating train split: 130461130 examples [2:20:32, 22107.03 examples/s]
Generating train split: 130463462 examples [2:20:32, 22319.27 examples/s]
Generating train split: 130465779 examples [2:20:32, 22513.73 examples/s]
Generating train split: 130469111 examples [2:20:32, 25553.03 examples/s]
Generating train split: 130471731 examples [2:20:32, 23308.72 examples/s]
Generating train split: 130474430 examples [2:20:32, 24294.36 examples/s]
Generating train split: 130481800 examples [2:20:32, 38077.08 examples/s]
Generating train split: 130489471 examples [2:20:32, 49087.93 examples/s]
Generating train split: 130494546 examples [2:20:33, 41529.09 examples/s]
Generating train split: 130499008 examples [2:20:33, 34615.68 examples/s]
Generating train split: 130502849 examples [2:20:33, 33544.01 examples/s]
Generating train split: 130506458 examples [2:20:33, 31405.91 examples/s]
Generating train split: 130509778 examples [2:20:33, 29241.54 examples/s]
Generating train split: 130513411 examples [2:20:33, 30923.13 examples/s]
Generating train split: 130516637 examples [2:20:33, 29475.79 examples/s]
Generating train split: 130519685 examples [2:20:34, 28690.28 examples/s]
Generating train split: 130522907 examples [2:20:34, 29599.23 examples/s]
Generating train split: 130525938 examples [2:20:34, 29594.20 examples/s]
Generating train split: 130528936 examples [2:20:34, 28003.38 examples/s]
Generating train split: 130531971 examples [2:20:34, 28633.65 examples/s]
Generating train split: 130535188 examples [2:20:34, 29564.74 examples/s]
Generating train split: 130538179 examples [2:20:34, 25878.95 examples/s]
Generating train split: 130541339 examples [2:20:34, 27374.81 examples/s]
Generating train split: 130544674 examples [2:20:34, 29001.04 examples/s]
Generating train split: 130547654 examples [2:20:34, 28427.71 examples/s]
Generating train split: 130550563 examples [2:20:35, 28039.41 examples/s]
Generating train split: 130553793 examples [2:20:35, 29205.88 examples/s]
Generating train split: 130556753 examples [2:20:35, 27822.56 examples/s]
Generating train split: 130560158 examples [2:20:35, 29554.28 examples/s]
Generating train split: 130563245 examples [2:20:35, 29911.08 examples/s]
Generating train split: 130566277 examples [2:20:35, 24989.63 examples/s]
Generating train split: 130569345 examples [2:20:35, 26444.01 examples/s]
Generating train split: 130572471 examples [2:20:35, 27639.35 examples/s]
Generating train split: 130575351 examples [2:20:36, 25412.21 examples/s]
Generating train split: 130578265 examples [2:20:36, 26369.18 examples/s]
Generating train split: 130580994 examples [2:20:36, 26201.35 examples/s]
Generating train split: 130583676 examples [2:20:36, 24582.71 examples/s]
Generating train split: 130586820 examples [2:20:36, 26384.67 examples/s]
Generating train split: 130589819 examples [2:20:36, 27376.88 examples/s]
Generating train split: 130592647 examples [2:20:36, 27589.93 examples/s]
Generating train split: 130595450 examples [2:20:36, 26398.68 examples/s]
Generating train split: 130598128 examples [2:20:36, 24673.98 examples/s]
Generating train split: 130602066 examples [2:20:37, 28680.97 examples/s]
Generating train split: 130605003 examples [2:20:37, 28104.61 examples/s]
Generating train split: 130607861 examples [2:20:37, 27576.27 examples/s]
Generating train split: 130610652 examples [2:20:37, 26548.25 examples/s]
Generating train split: 130613429 examples [2:20:37, 26736.66 examples/s]
Generating train split: 130616126 examples [2:20:37, 26393.14 examples/s]
Generating train split: 130620505 examples [2:20:37, 31305.62 examples/s]
Generating train split: 130623891 examples [2:20:37, 32038.17 examples/s]
Generating train split: 130627165 examples [2:20:37, 32215.12 examples/s]
Generating train split: 130630416 examples [2:20:37, 30278.94 examples/s]
Generating train split: 130633744 examples [2:20:38, 31119.58 examples/s]
Generating train split: 130636892 examples [2:20:38, 28538.12 examples/s]
Generating train split: 130640069 examples [2:20:38, 29395.59 examples/s]
Generating train split: 130643622 examples [2:20:38, 31099.95 examples/s]
Generating train split: 130646783 examples [2:20:38, 28385.05 examples/s]
Generating train split: 130649803 examples [2:20:38, 28844.49 examples/s]
Generating train split: 130652751 examples [2:20:38, 27307.15 examples/s]
Generating train split: 130655536 examples [2:20:38, 26831.18 examples/s]
Generating train split: 130658962 examples [2:20:38, 28711.03 examples/s]
Generating train split: 130661879 examples [2:20:39, 28197.50 examples/s]
Generating train split: 130664727 examples [2:20:39, 27962.78 examples/s]
Generating train split: 130667634 examples [2:20:39, 28270.61 examples/s]
Generating train split: 130670808 examples [2:20:39, 29265.19 examples/s]
Generating train split: 130673748 examples [2:20:39, 25901.31 examples/s]
Generating train split: 130676420 examples [2:20:39, 23948.49 examples/s]
Generating train split: 130679324 examples [2:20:39, 25224.01 examples/s]
Generating train split: 130681917 examples [2:20:39, 24114.81 examples/s]
Generating train split: 130684481 examples [2:20:39, 24516.04 examples/s]
Generating train split: 130687205 examples [2:20:40, 25248.60 examples/s]
Generating train split: 130690473 examples [2:20:40, 27346.90 examples/s]
Generating train split: 130693252 examples [2:20:40, 24560.66 examples/s]
Generating train split: 130696433 examples [2:20:40, 26509.38 examples/s]
Generating train split: 130699533 examples [2:20:40, 27742.54 examples/s]
Generating train split: 130702381 examples [2:20:40, 26930.37 examples/s]
Generating train split: 130705416 examples [2:20:40, 27844.63 examples/s]
Generating train split: 130708906 examples [2:20:40, 29400.34 examples/s]
Generating train split: 130711876 examples [2:20:40, 28163.00 examples/s]
Generating train split: 130715321 examples [2:20:41, 29919.21 examples/s]
Generating train split: 130718348 examples [2:20:41, 29784.99 examples/s]
Generating train split: 130721352 examples [2:20:41, 28035.11 examples/s]
Generating train split: 130724195 examples [2:20:41, 27882.43 examples/s]
Generating train split: 130728601 examples [2:20:41, 32410.99 examples/s]
Generating train split: 130731894 examples [2:20:41, 30096.89 examples/s]
Generating train split: 130734965 examples [2:20:41, 29372.27 examples/s]
Generating train split: 130739009 examples [2:20:41, 32409.16 examples/s]
Generating train split: 130742305 examples [2:20:41, 31087.49 examples/s]
Generating train split: 130745467 examples [2:20:42, 30630.46 examples/s]
Generating train split: 130748573 examples [2:20:42, 30266.65 examples/s]
Generating train split: 130751804 examples [2:20:42, 30836.67 examples/s]
Generating train split: 130755114 examples [2:20:42, 31473.40 examples/s]
Generating train split: 130762063 examples [2:20:42, 42540.84 examples/s]
Generating train split: 130771412 examples [2:20:42, 57506.91 examples/s]
Generating train split: 130777226 examples [2:20:42, 48595.03 examples/s]
Generating train split: 130782881 examples [2:20:42, 50676.47 examples/s]
Generating train split: 130792451 examples [2:20:42, 62938.43 examples/s]
Generating train split: 130799025 examples [2:20:43, 53047.40 examples/s]
Generating train split: 130804775 examples [2:20:43, 43045.50 examples/s]
Generating train split: 130809648 examples [2:20:43, 37840.19 examples/s]
Generating train split: 130813886 examples [2:20:43, 32589.45 examples/s]
Generating train split: 130817892 examples [2:20:43, 34097.81 examples/s]
Generating train split: 130821640 examples [2:20:43, 31892.38 examples/s]
Generating train split: 130825064 examples [2:20:44, 29635.47 examples/s]
Generating train split: 130829151 examples [2:20:44, 32202.53 examples/s]
Generating train split: 130832564 examples [2:20:44, 27616.92 examples/s]
Generating train split: 130835750 examples [2:20:44, 28589.04 examples/s]
Generating train split: 130838797 examples [2:20:44, 24979.26 examples/s]
Generating train split: 130841609 examples [2:20:44, 25708.44 examples/s]
Generating train split: 130844499 examples [2:20:44, 26482.96 examples/s]
Generating train split: 130847267 examples [2:20:44, 25496.76 examples/s]
Generating train split: 130850273 examples [2:20:45, 26666.51 examples/s]
Generating train split: 130853018 examples [2:20:45, 25157.41 examples/s]
Generating train split: 130855598 examples [2:20:45, 22729.84 examples/s]
Generating train split: 130860216 examples [2:20:45, 28712.65 examples/s]
Generating train split: 130863246 examples [2:20:45, 26205.94 examples/s]
Generating train split: 130866136 examples [2:20:45, 26870.15 examples/s]
Generating train split: 130868932 examples [2:20:45, 26489.95 examples/s]
Generating train split: 130871661 examples [2:20:45, 25434.33 examples/s]
Generating train split: 130874260 examples [2:20:45, 25352.62 examples/s]
Generating train split: 130876848 examples [2:20:46, 25444.08 examples/s]
Generating train split: 130879988 examples [2:20:46, 27058.18 examples/s]
Generating train split: 130883480 examples [2:20:46, 29301.13 examples/s]
Generating train split: 130886442 examples [2:20:46, 27996.16 examples/s]
Generating train split: 130889293 examples [2:20:46, 28097.40 examples/s]
Generating train split: 130892135 examples [2:20:46, 27151.08 examples/s]
Generating train split: 130894879 examples [2:20:46, 27089.34 examples/s]
Generating train split: 130898305 examples [2:20:46, 29145.34 examples/s]
Generating train split: 130901239 examples [2:20:46, 28208.93 examples/s]
Generating train split: 130904084 examples [2:20:47, 26186.77 examples/s]
Generating train split: 130907272 examples [2:20:47, 27738.75 examples/s]
Generating train split: 130910095 examples [2:20:47, 24745.14 examples/s]
Generating train split: 130913893 examples [2:20:47, 28202.87 examples/s]
Generating train split: 130919952 examples [2:20:47, 37041.37 examples/s]
Generating train split: 130928681 examples [2:20:47, 51127.61 examples/s]
Generating train split: 130934007 examples [2:20:47, 48963.53 examples/s]
Generating train split: 130939072 examples [2:20:47, 42775.57 examples/s]
Generating train split: 130948173 examples [2:20:47, 55126.32 examples/s]
Generating train split: 130957636 examples [2:20:48, 65704.68 examples/s]
Generating train split: 130964598 examples [2:20:48, 50496.69 examples/s]
Generating train split: 130970439 examples [2:20:48, 43225.80 examples/s]
Generating train split: 130975446 examples [2:20:48, 33927.41 examples/s]
Generating train split: 130979553 examples [2:20:48, 34327.57 examples/s]
Generating train split: 130983505 examples [2:20:48, 33378.44 examples/s]
Generating train split: 130987198 examples [2:20:49, 30027.67 examples/s]
Generating train split: 130990460 examples [2:20:49, 27736.31 examples/s]
Generating train split: 130994402 examples [2:20:49, 30282.62 examples/s]
Generating train split: 130997652 examples [2:20:49, 30261.41 examples/s]
Generating train split: 131000838 examples [2:20:49, 28250.86 examples/s]
Generating train split: 131004802 examples [2:20:49, 31062.77 examples/s]
Generating train split: 131013553 examples [2:20:49, 45797.98 examples/s]
Generating train split: 131021323 examples [2:20:49, 54454.55 examples/s]
Generating train split: 131027080 examples [2:20:50, 42144.49 examples/s]
Generating train split: 131031936 examples [2:20:50, 37732.11 examples/s]
Generating train split: 131036201 examples [2:20:50, 36097.11 examples/s]
Generating train split: 131040153 examples [2:20:50, 32979.67 examples/s]
Generating train split: 131043700 examples [2:20:50, 30176.07 examples/s]
Generating train split: 131046898 examples [2:20:50, 29309.26 examples/s]
Generating train split: 131050728 examples [2:20:50, 31410.40 examples/s]
Generating train split: 131054015 examples [2:20:51, 27707.59 examples/s]
Generating train split: 131057677 examples [2:20:51, 29821.80 examples/s]
Generating train split: 131061072 examples [2:20:51, 30863.46 examples/s]
Generating train split: 131064288 examples [2:20:51, 28664.50 examples/s]
Generating train split: 131067661 examples [2:20:51, 29940.31 examples/s]
Generating train split: 131070767 examples [2:20:51, 30234.99 examples/s]
Generating train split: 131073867 examples [2:20:51, 27074.12 examples/s]
Generating train split: 131076680 examples [2:20:51, 26951.28 examples/s]
Generating train split: 131079629 examples [2:20:51, 27548.88 examples/s]
Generating train split: 131082585 examples [2:20:52, 28066.33 examples/s]
Generating train split: 131085883 examples [2:20:52, 29365.88 examples/s]
Generating train split: 131088861 examples [2:20:52, 29130.22 examples/s]
Generating train split: 131092163 examples [2:20:52, 30217.07 examples/s]
Generating train split: 131095417 examples [2:20:52, 30782.90 examples/s]
Generating train split: 131098514 examples [2:20:52, 27289.40 examples/s]
Generating train split: 131101325 examples [2:20:52, 26751.77 examples/s]
Generating train split: 131104156 examples [2:20:52, 27168.23 examples/s]
Generating train split: 131107138 examples [2:20:52, 27899.91 examples/s]
Generating train split: 131110105 examples [2:20:53, 28381.82 examples/s]
Generating train split: 131113009 examples [2:20:53, 28316.96 examples/s]
Generating train split: 131115860 examples [2:20:53, 24430.24 examples/s]
Generating train split: 131119366 examples [2:20:53, 27208.51 examples/s]
Generating train split: 131122726 examples [2:20:53, 28926.72 examples/s]
Generating train split: 131125721 examples [2:20:53, 27092.57 examples/s]
Generating train split: 131128517 examples [2:20:53, 26766.82 examples/s]
Generating train split: 131131256 examples [2:20:53, 26443.64 examples/s]
Generating train split: 131134606 examples [2:20:53, 28390.32 examples/s]
Generating train split: 131138060 examples [2:20:54, 30098.59 examples/s]
Generating train split: 131141112 examples [2:20:54, 28226.80 examples/s]
Generating train split: 131144248 examples [2:20:54, 29088.55 examples/s]
Generating train split: 131148245 examples [2:20:54, 32130.58 examples/s]
Generating train split: 131151504 examples [2:20:54, 27264.24 examples/s]
Generating train split: 131154680 examples [2:20:54, 28407.74 examples/s]
Generating train split: 131158276 examples [2:20:54, 30433.60 examples/s]
Generating train split: 131161989 examples [2:20:54, 32122.68 examples/s]
Generating train split: 131165291 examples [2:20:54, 31469.76 examples/s]
Generating train split: 131168511 examples [2:20:55, 30821.04 examples/s]
Generating train split: 131171640 examples [2:20:55, 28665.55 examples/s]
Generating train split: 131174727 examples [2:20:55, 29209.30 examples/s]
Generating train split: 131179079 examples [2:20:55, 33197.35 examples/s]
Generating train split: 131187283 examples [2:20:55, 47104.25 examples/s]
Generating train split: 131195287 examples [2:20:55, 56615.24 examples/s]
Generating train split: 131201069 examples [2:20:55, 42339.15 examples/s]
Generating train split: 131205916 examples [2:20:56, 33914.31 examples/s]
Generating train split: 131209956 examples [2:20:56, 32363.96 examples/s]
Generating train split: 131213637 examples [2:20:56, 31481.58 examples/s]
Generating train split: 131217090 examples [2:20:56, 29857.01 examples/s]
Generating train split: 131220276 examples [2:20:56, 28535.03 examples/s]
Generating train split: 131223255 examples [2:20:56, 28510.93 examples/s]
Generating train split: 131226425 examples [2:20:56, 29290.47 examples/s]
Generating train split: 131229430 examples [2:20:56, 28077.05 examples/s]
Generating train split: 131232297 examples [2:20:56, 26797.36 examples/s]
Generating train split: 131235014 examples [2:20:57, 24181.18 examples/s]
Generating train split: 131237756 examples [2:20:57, 24989.47 examples/s]
Generating train split: 131240840 examples [2:20:57, 26069.94 examples/s]
Generating train split: 131243501 examples [2:20:57, 24619.59 examples/s]
Generating train split: 131246263 examples [2:20:57, 25406.09 examples/s]
Generating train split: 131248847 examples [2:20:57, 24116.72 examples/s]
Generating train split: 131251405 examples [2:20:57, 24493.64 examples/s]
Generating train split: 131254161 examples [2:20:57, 25340.43 examples/s]
Generating train split: 131256720 examples [2:20:57, 25066.10 examples/s]
Generating train split: 131259249 examples [2:20:58, 25050.24 examples/s]
Generating train split: 131261772 examples [2:20:58, 22875.99 examples/s]
Generating train split: 131264410 examples [2:20:58, 23827.12 examples/s]
Generating train split: 131267962 examples [2:20:58, 27073.48 examples/s]
Generating train split: 131275009 examples [2:20:58, 39486.85 examples/s]
Generating train split: 131283878 examples [2:20:58, 53746.46 examples/s]
Generating train split: 131289758 examples [2:20:58, 53355.42 examples/s]
Generating train split: 131295175 examples [2:20:58, 40016.25 examples/s]
Generating train split: 131299713 examples [2:20:59, 34694.58 examples/s]
Generating train split: 131303657 examples [2:20:59, 32554.15 examples/s]
Generating train split: 131307232 examples [2:20:59, 30431.93 examples/s]
Generating train split: 131310496 examples [2:20:59, 27398.54 examples/s]
Generating train split: 131313407 examples [2:20:59, 24312.46 examples/s]
Generating train split: 131316405 examples [2:20:59, 25514.05 examples/s]
Generating train split: 131319099 examples [2:20:59, 25004.89 examples/s]
Generating train split: 131321697 examples [2:21:00, 24414.06 examples/s]
Generating train split: 131324687 examples [2:21:00, 25806.47 examples/s]
Generating train split: 131327342 examples [2:21:00, 24869.96 examples/s]
Generating train split: 131330266 examples [2:21:00, 26032.32 examples/s]
Generating train split: 131332919 examples [2:21:00, 23204.16 examples/s]
Generating train split: 131335319 examples [2:21:00, 21228.46 examples/s]
Generating train split: 131337521 examples [2:21:00, 21132.45 examples/s]
Generating train split: 131340783 examples [2:21:00, 24126.97 examples/s]
Generating train split: 131343435 examples [2:21:00, 24765.61 examples/s]
Generating train split: 131346836 examples [2:21:01, 27337.99 examples/s]
Generating train split: 131349998 examples [2:21:01, 28527.42 examples/s]
Generating train split: 131353745 examples [2:21:01, 31096.16 examples/s]
Generating train split: 131356905 examples [2:21:01, 28439.64 examples/s]
Generating train split: 131359821 examples [2:21:01, 27834.36 examples/s]
Generating train split: 131362666 examples [2:21:01, 24920.73 examples/s]
Generating train split: 131365248 examples [2:21:01, 23850.38 examples/s]
Generating train split: 131368314 examples [2:21:01, 25528.36 examples/s]
Generating train split: 131371933 examples [2:21:02, 28393.56 examples/s]
Generating train split: 131374859 examples [2:21:02, 26120.34 examples/s]
Generating train split: 131378711 examples [2:21:02, 29401.30 examples/s]
Generating train split: 131381749 examples [2:21:02, 27575.53 examples/s]
Generating train split: 131385163 examples [2:21:02, 29322.52 examples/s]
Generating train split: 131388348 examples [2:21:02, 29962.06 examples/s]
Generating train split: 131391417 examples [2:21:02, 26223.91 examples/s]
Generating train split: 131394158 examples [2:21:02, 25682.77 examples/s]
Generating train split: 131396930 examples [2:21:02, 26217.33 examples/s]
Generating train split: 131399619 examples [2:21:03, 26357.37 examples/s]
Generating train split: 131402302 examples [2:21:03, 25099.13 examples/s]
Generating train split: 131404855 examples [2:21:03, 25188.76 examples/s]
Generating train split: 131408524 examples [2:21:03, 28434.72 examples/s]
Generating train split: 131411422 examples [2:21:03, 28581.76 examples/s]
Generating train split: 131414316 examples [2:21:03, 26061.07 examples/s]
Generating train split: 131417611 examples [2:21:03, 27893.38 examples/s]
Generating train split: 131420464 examples [2:21:03, 26292.40 examples/s]
Generating train split: 131423391 examples [2:21:03, 27101.99 examples/s]
Generating train split: 131426153 examples [2:21:04, 24931.53 examples/s]
Generating train split: 131429495 examples [2:21:04, 26774.41 examples/s]
Generating train split: 131432499 examples [2:21:04, 27563.95 examples/s]
Generating train split: 131435304 examples [2:21:04, 26711.86 examples/s]
Generating train split: 131439253 examples [2:21:04, 30250.52 examples/s]
Generating train split: 131442329 examples [2:21:04, 27034.29 examples/s]
Generating train split: 131446018 examples [2:21:04, 29640.94 examples/s]
Generating train split: 131449088 examples [2:21:04, 28035.24 examples/s]
Generating train split: 131451974 examples [2:21:04, 26906.29 examples/s]
Generating train split: 131455842 examples [2:21:05, 30059.97 examples/s]
Generating train split: 131459471 examples [2:21:05, 31341.75 examples/s]
Generating train split: 131462675 examples [2:21:05, 28024.41 examples/s]
Generating train split: 131465821 examples [2:21:05, 28918.71 examples/s]
Generating train split: 131468804 examples [2:21:05, 26065.63 examples/s]
Generating train split: 131472367 examples [2:21:05, 28392.19 examples/s]
Generating train split: 131475310 examples [2:21:05, 27463.06 examples/s]
Generating train split: 131478130 examples [2:21:05, 26178.60 examples/s]
Generating train split: 131481213 examples [2:21:05, 27387.75 examples/s]
Generating train split: 131484561 examples [2:21:06, 29059.07 examples/s]
Generating train split: 131487634 examples [2:21:06, 29341.96 examples/s]
Generating train split: 131490606 examples [2:21:06, 28213.68 examples/s]
Generating train split: 131493701 examples [2:21:06, 28975.50 examples/s]
Generating train split: 131496630 examples [2:21:06, 28395.08 examples/s]
Generating train split: 131500108 examples [2:21:06, 30216.79 examples/s]
Generating train split: 131503161 examples [2:21:06, 28835.29 examples/s]
Generating train split: 131506075 examples [2:21:06, 26022.82 examples/s]
Generating train split: 131508890 examples [2:21:06, 26500.14 examples/s]
Generating train split: 131511598 examples [2:21:07, 25224.45 examples/s]
Generating train split: 131516549 examples [2:21:07, 31793.17 examples/s]
Generating train split: 131519834 examples [2:21:07, 28279.73 examples/s]
Generating train split: 131522793 examples [2:21:07, 27055.13 examples/s]
Generating train split: 131525594 examples [2:21:07, 25948.16 examples/s]
Generating train split: 131528261 examples [2:21:07, 24423.11 examples/s]
Generating train split: 131530753 examples [2:21:07, 23051.50 examples/s]
Generating train split: 131533448 examples [2:21:07, 24007.21 examples/s]
Generating train split: 131536574 examples [2:21:08, 25667.25 examples/s]
Generating train split: 131540656 examples [2:21:08, 29804.07 examples/s]
Generating train split: 131543716 examples [2:21:08, 25069.22 examples/s]
Generating train split: 131546835 examples [2:21:08, 26604.41 examples/s]
Generating train split: 131549953 examples [2:21:08, 27752.14 examples/s]
Generating train split: 131552857 examples [2:21:08, 26270.85 examples/s]
Generating train split: 131555582 examples [2:21:08, 26352.63 examples/s]
Generating train split: 131558450 examples [2:21:08, 26979.09 examples/s]
Generating train split: 131561301 examples [2:21:08, 27367.57 examples/s]
Generating train split: 131564314 examples [2:21:09, 28139.55 examples/s]
Generating train split: 131567953 examples [2:21:09, 30444.86 examples/s]
Generating train split: 131571572 examples [2:21:09, 32087.65 examples/s]
Generating train split: 131574881 examples [2:21:09, 32375.19 examples/s]
Generating train split: 131578148 examples [2:21:09, 31662.37 examples/s]
Generating train split: 131581338 examples [2:21:09, 31225.88 examples/s]
Generating train split: 131584583 examples [2:21:09, 31549.37 examples/s]
Generating train split: 131587752 examples [2:21:09, 29341.58 examples/s]
Generating train split: 131590729 examples [2:21:09, 28860.37 examples/s]
Generating train split: 131594223 examples [2:21:09, 30561.20 examples/s]
Generating train split: 131597311 examples [2:21:10, 30305.58 examples/s]
Generating train split: 131600371 examples [2:21:10, 29059.99 examples/s]
Generating train split: 131603490 examples [2:21:10, 29583.34 examples/s]
Generating train split: 131607268 examples [2:21:10, 31929.49 examples/s]
Generating train split: 131610489 examples [2:21:10, 29637.67 examples/s]
Generating train split: 131613507 examples [2:21:10, 29279.27 examples/s]
Generating train split: 131616466 examples [2:21:10, 28262.75 examples/s]
Generating train split: 131619321 examples [2:21:10, 27990.40 examples/s]
Generating train split: 131622671 examples [2:21:10, 29487.90 examples/s]
Generating train split: 131626360 examples [2:21:11, 31586.08 examples/s]
Generating train split: 131629549 examples [2:21:11, 28067.09 examples/s]
Generating train split: 131632440 examples [2:21:11, 28201.71 examples/s]
Generating train split: 131636333 examples [2:21:11, 31024.04 examples/s]
Generating train split: 131639503 examples [2:21:11, 30839.30 examples/s]
Generating train split: 131643169 examples [2:21:11, 32485.36 examples/s]
Generating train split: 131647448 examples [2:21:11, 35457.87 examples/s]
Generating train split: 131651038 examples [2:21:11, 30134.89 examples/s]
Generating train split: 131654215 examples [2:21:11, 29724.54 examples/s]
Generating train split: 131657299 examples [2:21:12, 29015.83 examples/s]
Generating train split: 131660486 examples [2:21:12, 29780.64 examples/s]
Generating train split: 131663533 examples [2:21:12, 28708.67 examples/s]
Generating train split: 131666811 examples [2:21:12, 29801.88 examples/s]
Generating train split: 131669840 examples [2:21:12, 28152.36 examples/s]
Generating train split: 131673234 examples [2:21:12, 29540.28 examples/s]
Generating train split: 131676235 examples [2:21:12, 23669.04 examples/s]
Generating train split: 131678809 examples [2:21:12, 23688.66 examples/s]
Generating train split: 131681824 examples [2:21:13, 25306.63 examples/s]
Generating train split: 131684492 examples [2:21:13, 24512.67 examples/s]
Generating train split: 131687446 examples [2:21:13, 25828.87 examples/s]
Generating train split: 131690118 examples [2:21:13, 25866.35 examples/s]
Generating train split: 131692768 examples [2:21:13, 25670.28 examples/s]
Generating train split: 131697266 examples [2:21:13, 31106.20 examples/s]
Generating train split: 131701050 examples [2:21:13, 32960.28 examples/s]
Generating train split: 131704394 examples [2:21:13, 31614.69 examples/s]
Generating train split: 131707603 examples [2:21:13, 30293.11 examples/s]
Generating train split: 131711121 examples [2:21:14, 31649.23 examples/s]
Generating train split: 131714327 examples [2:21:14, 28721.02 examples/s]
Generating train split: 131717274 examples [2:21:14, 27343.04 examples/s]
Generating train split: 131720074 examples [2:21:14, 27032.15 examples/s]
Generating train split: 131722873 examples [2:21:14, 27284.52 examples/s]
Generating train split: 131725780 examples [2:21:14, 27777.30 examples/s]
Generating train split: 131728610 examples [2:21:14, 27909.82 examples/s]
Generating train split: 131731427 examples [2:21:14, 25004.65 examples/s]
Generating train split: 131735104 examples [2:21:14, 28164.35 examples/s]
Generating train split: 131738087 examples [2:21:15, 28614.68 examples/s]
Generating train split: 131741016 examples [2:21:15, 28455.62 examples/s]
Generating train split: 131743909 examples [2:21:15, 26921.23 examples/s]
Generating train split: 131747434 examples [2:21:15, 29233.69 examples/s]
Generating train split: 131750412 examples [2:21:15, 28593.88 examples/s]
Generating train split: 131753622 examples [2:21:15, 29554.33 examples/s]
Generating train split: 131756609 examples [2:21:15, 26626.54 examples/s]
Generating train split: 131759565 examples [2:21:15, 27404.77 examples/s]
Generating train split: 131762908 examples [2:21:15, 29066.51 examples/s]
Generating train split: 131765877 examples [2:21:16, 27457.48 examples/s]
Generating train split: 131768674 examples [2:21:16, 25749.21 examples/s]
Generating train split: 131771366 examples [2:21:16, 25943.42 examples/s]
Generating train split: 131774002 examples [2:21:16, 24542.12 examples/s]
Generating train split: 131777736 examples [2:21:16, 28002.61 examples/s]
Generating train split: 131780715 examples [2:21:16, 28480.99 examples/s]
Generating train split: 131784084 examples [2:21:16, 29838.17 examples/s]
Generating train split: 131787838 examples [2:21:16, 32048.14 examples/s]
Generating train split: 131791085 examples [2:21:16, 30716.39 examples/s]
Generating train split: 131794191 examples [2:21:17, 28451.67 examples/s]
Generating train split: 131797415 examples [2:21:17, 29478.50 examples/s]
Generating train split: 131800770 examples [2:21:17, 30605.57 examples/s]
Generating train split: 131803870 examples [2:21:17, 27941.25 examples/s]
Generating train split: 131807585 examples [2:21:17, 30433.02 examples/s]
Generating train split: 131811504 examples [2:21:17, 32860.88 examples/s]
Generating train split: 131814866 examples [2:21:17, 32494.65 examples/s]
Generating train split: 131823670 examples [2:21:17, 48350.85 examples/s]
Generating train split: 131830869 examples [2:21:17, 55179.56 examples/s]
Generating train split: 131836494 examples [2:21:18, 41654.17 examples/s]
Generating train split: 131841232 examples [2:21:18, 36665.44 examples/s]
Generating train split: 131845491 examples [2:21:18, 37982.65 examples/s]
Generating train split: 131849666 examples [2:21:18, 32472.19 examples/s]
Generating train split: 131853343 examples [2:21:18, 33431.94 examples/s]
Generating train split: 131856979 examples [2:21:18, 33524.34 examples/s]
Generating train split: 131860537 examples [2:21:18, 32537.13 examples/s]
Generating train split: 131863935 examples [2:21:18, 31574.41 examples/s]
Generating train split: 131867185 examples [2:21:19, 29517.66 examples/s]
Generating train split: 131870257 examples [2:21:19, 29628.90 examples/s]
Generating train split: 131873314 examples [2:21:19, 29854.24 examples/s]
Generating train split: 131876342 examples [2:21:19, 29628.77 examples/s]
Generating train split: 131879344 examples [2:21:19, 28808.87 examples/s]
Generating train split: 131882249 examples [2:21:19, 27569.02 examples/s]
Generating train split: 131885651 examples [2:21:19, 29297.45 examples/s]
Generating train split: 131888609 examples [2:21:19, 28097.41 examples/s]
Generating train split: 131891451 examples [2:21:19, 27516.08 examples/s]
Generating train split: 131894858 examples [2:21:20, 29344.16 examples/s]
Generating train split: 131897821 examples [2:21:20, 27587.29 examples/s]
Generating train split: 131901534 examples [2:21:20, 30221.74 examples/s]
Generating train split: 131904606 examples [2:21:20, 28376.39 examples/s]
Generating train split: 131907657 examples [2:21:20, 28887.05 examples/s]
Generating train split: 131910600 examples [2:21:20, 26658.04 examples/s]
Generating train split: 131913326 examples [2:21:20, 26281.37 examples/s]
Generating train split: 131915997 examples [2:21:20, 26090.98 examples/s]
Generating train split: 131918787 examples [2:21:20, 26572.05 examples/s]
Generating train split: 131921687 examples [2:21:21, 27203.20 examples/s]
Generating train split: 131924512 examples [2:21:21, 27481.85 examples/s]
Generating train split: 131928546 examples [2:21:21, 31226.83 examples/s]
Generating train split: 131932104 examples [2:21:21, 32497.26 examples/s]
Generating train split: 131935412 examples [2:21:21, 32663.78 examples/s]
Generating train split: 131938697 examples [2:21:21, 31163.48 examples/s]
Generating train split: 131942394 examples [2:21:21, 32832.39 examples/s]
Generating train split: 131945702 examples [2:21:21, 28971.38 examples/s]
Generating train split: 131948695 examples [2:21:21, 29180.19 examples/s]
Generating train split: 131952381 examples [2:21:22, 31251.55 examples/s]
Generating train split: 131955583 examples [2:21:22, 30614.16 examples/s]
Generating train split: 131958747 examples [2:21:22, 30903.43 examples/s]
Generating train split: 131961876 examples [2:21:22, 30097.88 examples/s]
Generating train split: 131964913 examples [2:21:22, 28187.57 examples/s]
Generating train split: 131967789 examples [2:21:22, 28331.09 examples/s]
Generating train split: 131970667 examples [2:21:22, 28163.35 examples/s]
Generating train split: 131973512 examples [2:21:22, 25357.94 examples/s]
Generating train split: 131976107 examples [2:21:22, 24938.86 examples/s]
Generating train split: 131978809 examples [2:21:23, 25501.27 examples/s]
Generating train split: 131982462 examples [2:21:23, 28571.93 examples/s]
Generating train split: 131985364 examples [2:21:23, 28384.21 examples/s]
Generating train split: 131989284 examples [2:21:23, 31478.82 examples/s]
Generating train split: 131994168 examples [2:21:23, 36507.47 examples/s]
Generating train split: 131997870 examples [2:21:23, 32173.37 examples/s]
Generating train split: 132001206 examples [2:21:23, 30118.19 examples/s]
Generating train split: 132005225 examples [2:21:23, 32722.84 examples/s]
Generating train split: 132008602 examples [2:21:23, 29784.48 examples/s]
Generating train split: 132011813 examples [2:21:24, 30388.20 examples/s]
Generating train split: 132014941 examples [2:21:24, 27988.61 examples/s]
Generating train split: 132017827 examples [2:21:24, 28206.66 examples/s]
Generating train split: 132020776 examples [2:21:24, 28549.41 examples/s]
Generating train split: 132023691 examples [2:21:24, 26587.10 examples/s]
Generating train split: 132026410 examples [2:21:24, 25072.99 examples/s]
Generating train split: 132030090 examples [2:21:24, 28177.59 examples/s]
Generating train split: 132032979 examples [2:21:24, 27838.28 examples/s]
Generating train split: 132035822 examples [2:21:24, 24194.88 examples/s]
Generating train split: 132039489 examples [2:21:25, 27370.00 examples/s]
Generating train split: 132042359 examples [2:21:25, 25426.90 examples/s]
Generating train split: 132045231 examples [2:21:25, 26251.44 examples/s]
Generating train split: 132048130 examples [2:21:25, 26964.87 examples/s]
Generating train split: 132050907 examples [2:21:25, 26241.08 examples/s]
Generating train split: 132053593 examples [2:21:25, 26229.52 examples/s]
Generating train split: 132056254 examples [2:21:25, 25153.92 examples/s]
Generating train split: 132058810 examples [2:21:25, 24851.89 examples/s]
Generating train split: 132061316 examples [2:21:25, 23063.18 examples/s]
Generating train split: 132065999 examples [2:21:26, 29493.18 examples/s]
Generating train split: 132073216 examples [2:21:26, 41390.79 examples/s]
Generating train split: 132079386 examples [2:21:26, 47037.56 examples/s]
Generating train split: 132084228 examples [2:21:26, 41659.47 examples/s]
Generating train split: 132088601 examples [2:21:26, 40322.27 examples/s]
Generating train split: 132092774 examples [2:21:26, 32321.77 examples/s]
Generating train split: 132096336 examples [2:21:26, 31636.36 examples/s]
Generating train split: 132099896 examples [2:21:26, 32564.03 examples/s]
Generating train split: 132103486 examples [2:21:27, 33411.76 examples/s]
Generating train split: 132107174 examples [2:21:27, 34299.03 examples/s]
Generating train split: 132110972 examples [2:21:27, 35301.48 examples/s]
Generating train split: 132114597 examples [2:21:27, 32920.82 examples/s]
Generating train split: 132119378 examples [2:21:27, 36959.86 examples/s]
Generating train split: 132127709 examples [2:21:27, 49919.28 examples/s]
Generating train split: 132135717 examples [2:21:27, 58484.37 examples/s]
Generating train split: 132141722 examples [2:21:27, 49776.53 examples/s]
Generating train split: 132147030 examples [2:21:28, 42531.62 examples/s]
Generating train split: 132151670 examples [2:21:28, 35780.85 examples/s]
Generating train split: 132155644 examples [2:21:28, 33271.43 examples/s]
Generating train split: 132159240 examples [2:21:28, 32300.04 examples/s]
Generating train split: 132162647 examples [2:21:28, 32084.67 examples/s]
Generating train split: 132165971 examples [2:21:28, 30457.90 examples/s]
Generating train split: 132169100 examples [2:21:28, 30621.14 examples/s]
Generating train split: 132172222 examples [2:21:28, 28536.72 examples/s]
Generating train split: 132175171 examples [2:21:29, 28605.05 examples/s]
Generating train split: 132178076 examples [2:21:29, 27272.25 examples/s]
Generating train split: 132180838 examples [2:21:29, 27311.19 examples/s]
Generating train split: 132183594 examples [2:21:29, 27317.90 examples/s]
Generating train split: 132186974 examples [2:21:29, 29138.25 examples/s]
Generating train split: 132189916 examples [2:21:29, 28585.99 examples/s]
Generating train split: 132192790 examples [2:21:29, 25497.44 examples/s]
Generating train split: 132195408 examples [2:21:29, 24857.95 examples/s]
Generating train split: 132197940 examples [2:21:29, 23609.19 examples/s]
Generating train split: 132200343 examples [2:21:30, 23441.43 examples/s]
Generating train split: 132203242 examples [2:21:30, 24949.87 examples/s]
Generating train split: 132206085 examples [2:21:30, 25880.28 examples/s]
Generating train split: 132208898 examples [2:21:30, 26396.00 examples/s]
Generating train split: 132212545 examples [2:21:30, 29306.89 examples/s]
Generating train split: 132215511 examples [2:21:30, 26639.07 examples/s]
Generating train split: 132219806 examples [2:21:30, 31107.27 examples/s]
Generating train split: 132223004 examples [2:21:30, 30930.11 examples/s]
Generating train split: 132226160 examples [2:21:30, 28317.12 examples/s]
Generating train split: 132229147 examples [2:21:31, 28727.52 examples/s]
Generating train split: 132233594 examples [2:21:31, 33090.77 examples/s]
Generating train split: 132236979 examples [2:21:31, 27704.10 examples/s]
Generating train split: 132241333 examples [2:21:31, 31696.64 examples/s]
Generating train split: 132244723 examples [2:21:31, 31640.88 examples/s]
Generating train split: 132248196 examples [2:21:31, 32456.23 examples/s]
Generating train split: 132252996 examples [2:21:31, 36786.00 examples/s]
Generating train split: 132261051 examples [2:21:31, 49235.17 examples/s]
Generating train split: 132268421 examples [2:21:31, 56285.24 examples/s]
Generating train split: 132274181 examples [2:21:32, 40884.12 examples/s]
Generating train split: 132278957 examples [2:21:32, 38943.42 examples/s]
Generating train split: 132283328 examples [2:21:32, 35683.38 examples/s]
Generating train split: 132287254 examples [2:21:32, 34804.71 examples/s]
Generating train split: 132290969 examples [2:21:32, 34971.60 examples/s]
Generating train split: 132294637 examples [2:21:32, 32886.54 examples/s]
Generating train split: 132298051 examples [2:21:32, 32536.30 examples/s]
Generating train split: 132301419 examples [2:21:33, 32817.31 examples/s]
Generating train split: 132305570 examples [2:21:33, 35163.03 examples/s]
Generating train split: 132309191 examples [2:21:33, 35408.82 examples/s]
Generating train split: 132315300 examples [2:21:33, 42709.01 examples/s]
Generating train split: 132324367 examples [2:21:33, 56538.57 examples/s]
Generating train split: 132330133 examples [2:21:33, 53302.73 examples/s]
Generating train split: 132335576 examples [2:21:33, 50881.44 examples/s]
Generating train split: 132340754 examples [2:21:33, 41260.01 examples/s]
Generating train split: 132345212 examples [2:21:33, 41577.30 examples/s]
Generating train split: 132349609 examples [2:21:34, 42164.00 examples/s]
Generating train split: 132357753 examples [2:21:34, 52608.05 examples/s]
Generating train split: 132365880 examples [2:21:34, 60495.93 examples/s]
Generating train split: 132372180 examples [2:21:34, 52580.14 examples/s]
Generating train split: 132377790 examples [2:21:34, 44187.88 examples/s]
Generating train split: 132382639 examples [2:21:34, 43098.83 examples/s]
Generating train split: 132387246 examples [2:21:34, 40027.29 examples/s]
Generating train split: 132391459 examples [2:21:34, 37643.89 examples/s]
Generating train split: 132395552 examples [2:21:35, 38424.30 examples/s]
Generating train split: 132399513 examples [2:21:35, 38422.32 examples/s]
Generating train split: 132403444 examples [2:21:35, 33750.39 examples/s]
Generating train split: 132406967 examples [2:21:35, 30406.72 examples/s]
Generating train split: 132410139 examples [2:21:35, 30210.63 examples/s]
Generating train split: 132413253 examples [2:21:35, 28827.95 examples/s]
Generating train split: 132416197 examples [2:21:35, 28316.42 examples/s]
Generating train split: 132419073 examples [2:21:35, 27978.35 examples/s]
Generating train split: 132421898 examples [2:21:36, 26883.42 examples/s]
Generating train split: 132424876 examples [2:21:36, 27651.76 examples/s]
Generating train split: 132428210 examples [2:21:36, 29192.94 examples/s]
Generating train split: 132435295 examples [2:21:36, 41006.42 examples/s]
Generating train split: 132443969 examples [2:21:36, 54190.96 examples/s]
Generating train split: 132450466 examples [2:21:36, 55391.75 examples/s]
Generating train split: 132456078 examples [2:21:36, 40642.97 examples/s]
Generating train split: 132460758 examples [2:21:36, 38837.51 examples/s]
Generating train split: 132465063 examples [2:21:37, 34955.30 examples/s]
Generating train split: 132468886 examples [2:21:37, 34815.67 examples/s]
Generating train split: 132476755 examples [2:21:37, 45328.71 examples/s]
Generating train split: 132484368 examples [2:21:37, 52355.22 examples/s]
Generating train split: 132489993 examples [2:21:37, 49375.29 examples/s]
Generating train split: 132495217 examples [2:21:37, 42570.26 examples/s]
Generating train split: 132499812 examples [2:21:37, 41164.87 examples/s]
Generating train split: 132507608 examples [2:21:37, 50164.25 examples/s]
Generating train split: 132516814 examples [2:21:38, 60994.26 examples/s]
Generating train split: 132523346 examples [2:21:38, 53531.37 examples/s]
Generating train split: 132529149 examples [2:21:38, 47716.87 examples/s]
Generating train split: 132534310 examples [2:21:38, 37380.54 examples/s]
Generating train split: 132538608 examples [2:21:38, 33329.89 examples/s]
Generating train split: 132542347 examples [2:21:38, 33086.86 examples/s]
Generating train split: 132545940 examples [2:21:38, 31211.59 examples/s]
Generating train split: 132549240 examples [2:21:39, 29268.02 examples/s]
Generating train split: 132552282 examples [2:21:39, 29290.30 examples/s]
Generating train split: 132555826 examples [2:21:39, 30450.07 examples/s]
Generating train split: 132558954 examples [2:21:39, 28769.40 examples/s]
Generating train split: 132561898 examples [2:21:39, 28330.28 examples/s]
Generating train split: 132564780 examples [2:21:39, 25445.06 examples/s]
Generating train split: 132567769 examples [2:21:39, 26478.94 examples/s]
Generating train split: 132570799 examples [2:21:39, 27485.92 examples/s]
Generating train split: 132574229 examples [2:21:40, 29339.81 examples/s]
Generating train split: 132577450 examples [2:21:40, 30128.81 examples/s]
Generating train split: 132580510 examples [2:21:40, 29801.03 examples/s]
Generating train split: 132583524 examples [2:21:40, 27947.02 examples/s]
Generating train split: 132587477 examples [2:21:40, 31157.44 examples/s]
Generating train split: 132591368 examples [2:21:40, 33354.35 examples/s]
Generating train split: 132594761 examples [2:21:40, 29504.05 examples/s]
Generating train split: 132598087 examples [2:21:40, 30468.85 examples/s]
Generating train split: 132601225 examples [2:21:40, 27091.45 examples/s]
Generating train split: 132605333 examples [2:21:41, 30691.41 examples/s]
Generating train split: 132608558 examples [2:21:41, 28541.28 examples/s]
Generating train split: 132611538 examples [2:21:41, 26847.33 examples/s]
Generating train split: 132614735 examples [2:21:41, 28153.02 examples/s]
Generating train split: 132617648 examples [2:21:41, 26118.21 examples/s]
Generating train split: 132620775 examples [2:21:41, 27439.02 examples/s]
Generating train split: 132623593 examples [2:21:41, 26006.15 examples/s]
Generating train split: 132626260 examples [2:21:41, 24568.85 examples/s]
Generating train split: 132628763 examples [2:21:42, 23890.96 examples/s]
Generating train split: 132631192 examples [2:21:42, 23427.15 examples/s]
Generating train split: 132633797 examples [2:21:42, 24126.47 examples/s]
Generating train split: 132637478 examples [2:21:42, 27648.12 examples/s]
Generating train split: 132640429 examples [2:21:42, 28154.81 examples/s]
Generating train split: 132644749 examples [2:21:42, 32489.05 examples/s]
Generating train split: 132648044 examples [2:21:42, 27993.78 examples/s]
Generating train split: 132650989 examples [2:21:42, 27074.76 examples/s]
Generating train split: 132653791 examples [2:21:42, 25281.51 examples/s]
Generating train split: 132656404 examples [2:21:43, 25312.86 examples/s]
Generating train split: 132660076 examples [2:21:43, 28365.93 examples/s]
Generating train split: 132662996 examples [2:21:43, 28465.35 examples/s]
Generating train split: 132666070 examples [2:21:43, 29086.55 examples/s]
Generating train split: 132669675 examples [2:21:43, 31066.30 examples/s]
Generating train split: 132672822 examples [2:21:43, 27853.05 examples/s]
Generating train split: 132676169 examples [2:21:43, 29309.85 examples/s]
Generating train split: 132679179 examples [2:21:43, 27813.44 examples/s]
Generating train split: 132682557 examples [2:21:43, 29433.21 examples/s]
Generating train split: 132685571 examples [2:21:43, 28867.47 examples/s]
Generating train split: 132688507 examples [2:21:44, 28379.12 examples/s]
Generating train split: 132691491 examples [2:21:44, 28784.73 examples/s]
Generating train split: 132695692 examples [2:21:44, 32542.18 examples/s]
Generating train split: 132698978 examples [2:21:44, 29998.34 examples/s]
Generating train split: 132702037 examples [2:21:44, 27967.40 examples/s]
Generating train split: 132705757 examples [2:21:44, 30430.12 examples/s]
Generating train split: 132708873 examples [2:21:44, 26344.41 examples/s]
Generating train split: 132712347 examples [2:21:44, 28409.19 examples/s]
Generating train split: 132715398 examples [2:21:45, 28387.75 examples/s]
Generating train split: 132718335 examples [2:21:45, 26361.00 examples/s]
Generating train split: 132721062 examples [2:21:45, 26549.21 examples/s]
Generating train split: 132723928 examples [2:21:45, 27062.43 examples/s]
Generating train split: 132727427 examples [2:21:45, 29256.45 examples/s]
Generating train split: 132730404 examples [2:21:45, 27401.82 examples/s]
Generating train split: 132733211 examples [2:21:45, 26440.77 examples/s]
Generating train split: 132736245 examples [2:21:45, 27505.39 examples/s]
Generating train split: 132739047 examples [2:21:45, 26457.22 examples/s]
Generating train split: 132742035 examples [2:21:46, 27401.28 examples/s]
Generating train split: 132745620 examples [2:21:46, 29767.35 examples/s]
Generating train split: 132748765 examples [2:21:46, 30202.34 examples/s]
Generating train split: 132752180 examples [2:21:46, 31345.17 examples/s]
Generating train split: 132755335 examples [2:21:46, 28745.17 examples/s]
Generating train split: 132758269 examples [2:21:46, 26875.00 examples/s]
Generating train split: 132761197 examples [2:21:46, 27510.11 examples/s]
Generating train split: 132763998 examples [2:21:46, 24093.54 examples/s]
Generating train split: 132767806 examples [2:21:46, 27682.31 examples/s]
Generating train split: 132770702 examples [2:21:47, 26207.07 examples/s]
Generating train split: 132773574 examples [2:21:47, 26826.56 examples/s]
Generating train split: 132776831 examples [2:21:47, 28300.99 examples/s]
Generating train split: 132780010 examples [2:21:47, 29084.14 examples/s]
Generating train split: 132782976 examples [2:21:47, 27707.27 examples/s]
Generating train split: 132786958 examples [2:21:47, 31034.77 examples/s]
Generating train split: 132790118 examples [2:21:47, 27051.01 examples/s]
Generating train split: 132793044 examples [2:21:47, 27620.11 examples/s]
Generating train split: 132796373 examples [2:21:47, 29151.04 examples/s]
Generating train split: 132799450 examples [2:21:48, 29599.64 examples/s]
Generating train split: 132802563 examples [2:21:48, 29935.92 examples/s]
Generating train split: 132805852 examples [2:21:48, 30763.04 examples/s]
Generating train split: 132809017 examples [2:21:48, 31010.06 examples/s]
Generating train split: 132812143 examples [2:21:48, 30658.81 examples/s]
Generating train split: 132815656 examples [2:21:48, 31961.52 examples/s]
Generating train split: 132818874 examples [2:21:48, 31689.56 examples/s]
Generating train split: 132822056 examples [2:21:48, 31125.94 examples/s]
Generating train split: 132825189 examples [2:21:48, 29472.77 examples/s]
Generating train split: 132828637 examples [2:21:48, 30886.29 examples/s]
Generating train split: 132831791 examples [2:21:49, 31060.95 examples/s]
Generating train split: 132834945 examples [2:21:49, 31194.03 examples/s]
Generating train split: 132838082 examples [2:21:49, 31076.90 examples/s]
Generating train split: 132841442 examples [2:21:49, 31813.42 examples/s]
Generating train split: 132844634 examples [2:21:49, 30887.25 examples/s]
Generating train split: 132848032 examples [2:21:49, 31778.17 examples/s]
Generating train split: 132851233 examples [2:21:49, 30398.17 examples/s]
Generating train split: 132854291 examples [2:21:49, 27623.99 examples/s]
Generating train split: 132857116 examples [2:21:49, 27708.36 examples/s]
Generating train split: 132859940 examples [2:21:50, 27574.18 examples/s]
Generating train split: 132863702 examples [2:21:50, 30386.06 examples/s]
Generating train split: 132866778 examples [2:21:50, 30457.10 examples/s]
Generating train split: 132869851 examples [2:21:50, 29938.02 examples/s]
Generating train split: 132872932 examples [2:21:50, 30174.60 examples/s]
Generating train split: 132881335 examples [2:21:50, 45904.61 examples/s]
Generating train split: 132889110 examples [2:21:50, 55276.89 examples/s]
Generating train split: 132894701 examples [2:21:50, 49926.12 examples/s]
Generating train split: 132899829 examples [2:21:50, 41063.90 examples/s]
Generating train split: 132904278 examples [2:21:51, 37161.25 examples/s]
Generating train split: 132908267 examples [2:21:51, 33755.60 examples/s]
Generating train split: 132911851 examples [2:21:51, 31155.54 examples/s]
Generating train split: 132915120 examples [2:21:51, 30990.32 examples/s]
Generating train split: 132918327 examples [2:21:51, 29008.85 examples/s]
Generating train split: 132921303 examples [2:21:51, 27237.21 examples/s]
Generating train split: 132924076 examples [2:21:51, 27302.70 examples/s]
Generating train split: 132926842 examples [2:21:51, 27263.86 examples/s]
Generating train split: 132929932 examples [2:21:52, 28240.20 examples/s]
Generating train split: 132933135 examples [2:21:52, 29291.92 examples/s]
Generating train split: 132937166 examples [2:21:52, 32422.00 examples/s]
Generating train split: 132941291 examples [2:21:52, 34970.26 examples/s]
Generating train split: 132948992 examples [2:21:52, 47238.39 examples/s]
Generating train split: 132958192 examples [2:21:52, 60413.64 examples/s]
Generating train split: 132964309 examples [2:21:52, 50341.51 examples/s]
Generating train split: 132969674 examples [2:21:52, 40329.37 examples/s]
Generating train split: 132974216 examples [2:21:53, 32975.49 examples/s]
Generating train split: 132978037 examples [2:21:53, 30033.84 examples/s]
Generating train split: 132982421 examples [2:21:53, 32861.00 examples/s]
Generating train split: 132986102 examples [2:21:53, 29070.11 examples/s]
Generating train split: 132989690 examples [2:21:53, 30549.10 examples/s]
Generating train split: 132993019 examples [2:21:53, 27748.86 examples/s]
Generating train split: 132996415 examples [2:21:53, 29182.26 examples/s]
Generating train split: 133004605 examples [2:21:54, 42277.88 examples/s]
Generating train split: 133013975 examples [2:21:54, 55747.89 examples/s]
Generating train split: 133020026 examples [2:21:54, 55966.03 examples/s]
Generating train split: 133025964 examples [2:21:54, 40774.30 examples/s]
Generating train split: 133030850 examples [2:21:54, 39637.48 examples/s]
Generating train split: 133035374 examples [2:21:54, 36768.88 examples/s]
Generating train split: 133039444 examples [2:21:54, 33205.54 examples/s]
Generating train split: 133043074 examples [2:21:55, 31218.83 examples/s]
Generating train split: 133046392 examples [2:21:55, 30134.27 examples/s]
Generating train split: 133050149 examples [2:21:55, 31867.91 examples/s]
Generating train split: 133056719 examples [2:21:55, 40347.36 examples/s]
Generating train split: 133065867 examples [2:21:55, 53827.98 examples/s]
Generating train split: 133072361 examples [2:21:55, 55968.46 examples/s]
Generating train split: 133078229 examples [2:21:55, 46476.60 examples/s]
Generating train split: 133083325 examples [2:21:55, 39253.89 examples/s]
Generating train split: 133087712 examples [2:21:56, 39112.65 examples/s]
Generating train split: 133091941 examples [2:21:56, 36073.20 examples/s]
Generating train split: 133095781 examples [2:21:56, 32860.07 examples/s]
Generating train split: 133099438 examples [2:21:56, 33699.27 examples/s]
Generating train split: 133102958 examples [2:21:56, 30711.18 examples/s]
Generating train split: 133106768 examples [2:21:56, 32494.85 examples/s]
Generating train split: 133110155 examples [2:21:56, 30334.40 examples/s]
Generating train split: 133113294 examples [2:21:57, 27155.50 examples/s]
Generating train split: 133116885 examples [2:21:57, 29248.84 examples/s]
Generating train split: 133119937 examples [2:21:57, 26897.26 examples/s]
Generating train split: 133122730 examples [2:21:57, 26667.35 examples/s]
Generating train split: 133126670 examples [2:21:57, 29965.46 examples/s]
Generating train split: 133129765 examples [2:21:57, 30180.96 examples/s]
Generating train split: 133132861 examples [2:21:57, 30036.40 examples/s]
Generating train split: 133136199 examples [2:21:57, 30959.50 examples/s]
Generating train split: 133139337 examples [2:21:57, 27330.51 examples/s]
Generating train split: 133142958 examples [2:21:58, 29599.97 examples/s]
Generating train split: 133146028 examples [2:21:58, 27904.84 examples/s]
Generating train split: 133149158 examples [2:21:58, 28802.04 examples/s]
Generating train split: 133152324 examples [2:21:58, 29587.08 examples/s]
Generating train split: 133155342 examples [2:21:58, 27531.06 examples/s]
Generating train split: 133158474 examples [2:21:58, 28482.29 examples/s]
Generating train split: 133161379 examples [2:21:58, 27926.56 examples/s]
Generating train split: 133164221 examples [2:21:58, 25109.63 examples/s]
Generating train split: 133167393 examples [2:21:58, 26619.10 examples/s]
Generating train split: 133170578 examples [2:21:59, 28040.17 examples/s]
Generating train split: 133173608 examples [2:21:59, 28662.99 examples/s]
Generating train split: 133176526 examples [2:21:59, 26970.51 examples/s]
Generating train split: 133179273 examples [2:21:59, 27104.63 examples/s]
Generating train split: 133182588 examples [2:21:59, 28637.50 examples/s]
Generating train split: 133185491 examples [2:21:59, 25577.78 examples/s]
Generating train split: 133188811 examples [2:21:59, 27579.60 examples/s]
Generating train split: 133191953 examples [2:21:59, 28624.31 examples/s]
Generating train split: 133194880 examples [2:21:59, 27157.20 examples/s]
Generating train split: 133198179 examples [2:22:00, 28749.25 examples/s]
Generating train split: 133201111 examples [2:22:00, 25282.50 examples/s]
Generating train split: 133205201 examples [2:22:00, 29296.38 examples/s]
Generating train split: 133208921 examples [2:22:00, 31427.07 examples/s]
Generating train split: 133212189 examples [2:22:00, 26152.25 examples/s]
Generating train split: 133215659 examples [2:22:00, 28252.16 examples/s]
Generating train split: 133219616 examples [2:22:00, 31161.15 examples/s]
Generating train split: 133222917 examples [2:22:00, 31631.91 examples/s]
Generating train split: 133226751 examples [2:22:00, 33497.41 examples/s]
Generating train split: 133233253 examples [2:22:01, 42453.72 examples/s]
Generating train split: 133239243 examples [2:22:01, 47481.98 examples/s]
Generating train split: 133247137 examples [2:22:01, 56670.10 examples/s]
Generating train split: 133253520 examples [2:22:01, 58776.28 examples/s]
Generating train split: 133260720 examples [2:22:01, 62666.63 examples/s]
Generating train split: 133267514 examples [2:22:01, 64196.68 examples/s]
Generating train split: 133274024 examples [2:22:01, 64451.71 examples/s]
Generating train split: 133281803 examples [2:22:01, 68421.45 examples/s]
Generating train split: 133289446 examples [2:22:01, 70799.63 examples/s]
Generating train split: 133297291 examples [2:22:01, 73075.88 examples/s]
Generating train split: 133304615 examples [2:22:02, 73016.21 examples/s]
Generating train split: 133312547 examples [2:22:02, 74865.33 examples/s]
Generating train split: 133320050 examples [2:22:02, 74374.60 examples/s]
Generating train split: 133327504 examples [2:22:02, 73202.53 examples/s]
Generating train split: 133334836 examples [2:22:02, 71596.93 examples/s]
Generating train split: 133342463 examples [2:22:02, 72954.39 examples/s]
Generating train split: 133349840 examples [2:22:02, 73152.38 examples/s]
Generating train split: 133357174 examples [2:22:02, 71460.19 examples/s]
Generating train split: 133364756 examples [2:22:02, 72723.20 examples/s]
Generating train split: 133372053 examples [2:22:03, 67328.04 examples/s]
Generating train split: 133378881 examples [2:22:03, 65919.95 examples/s]
Generating train split: 133385773 examples [2:22:03, 66723.11 examples/s]
Generating train split: 133392497 examples [2:22:03, 61278.79 examples/s]
Generating train split: 133398808 examples [2:22:03, 61761.48 examples/s]
Generating train split: 133405070 examples [2:22:03, 55711.49 examples/s]
Generating train split: 133410789 examples [2:22:03, 54398.15 examples/s]
Generating train split: 133416338 examples [2:22:03, 52550.01 examples/s]
Generating train split: 133421658 examples [2:22:03, 45885.85 examples/s]
Generating train split: 133426419 examples [2:22:04, 43441.09 examples/s]
Generating train split: 133430972 examples [2:22:04, 43953.15 examples/s]
Generating train split: 133435466 examples [2:22:04, 43673.28 examples/s]
Generating train split: 133440597 examples [2:22:04, 45736.03 examples/s]
Generating train split: 133445237 examples [2:22:04, 45035.04 examples/s]
Generating train split: 133449791 examples [2:22:04, 41555.33 examples/s]
Generating train split: 133454022 examples [2:22:04, 37829.16 examples/s]
Generating train split: 133457898 examples [2:22:04, 35334.61 examples/s]
Generating train split: 133461514 examples [2:22:05, 35065.34 examples/s]
Generating train split: 133465072 examples [2:22:05, 35111.65 examples/s]
Generating train split: 133468627 examples [2:22:05, 32626.68 examples/s]
Generating train split: 133471939 examples [2:22:05, 31572.95 examples/s]
Generating train split: 133475252 examples [2:22:05, 31794.97 examples/s]
Generating train split: 133478473 examples [2:22:05, 31905.66 examples/s]
Generating train split: 133481684 examples [2:22:05, 31553.13 examples/s]
Generating train split: 133484904 examples [2:22:05, 31692.21 examples/s]
Generating train split: 133488092 examples [2:22:05, 29540.45 examples/s]
Generating train split: 133492034 examples [2:22:05, 32263.00 examples/s]
Generating train split: 133495316 examples [2:22:06, 31712.55 examples/s]
Generating train split: 133498531 examples [2:22:06, 31613.63 examples/s]
Generating train split: 133501716 examples [2:22:06, 30956.11 examples/s]
Generating train split: 133505161 examples [2:22:06, 31932.20 examples/s]
Generating train split: 133508520 examples [2:22:06, 32393.56 examples/s]
Generating train split: 133511773 examples [2:22:06, 29299.83 examples/s]
Generating train split: 133514774 examples [2:22:06, 28035.41 examples/s]
Generating train split: 133517734 examples [2:22:06, 28445.47 examples/s]
Generating train split: 133520616 examples [2:22:06, 27491.57 examples/s]
Generating train split: 133523394 examples [2:22:07, 26881.09 examples/s]
Generating train split: 133526106 examples [2:22:07, 26582.13 examples/s]
Generating train split: 133528785 examples [2:22:07, 25333.38 examples/s]
Generating train split: 133531348 examples [2:22:07, 24438.67 examples/s]
Generating train split: 133534640 examples [2:22:07, 26720.49 examples/s]
Generating train split: 133537342 examples [2:22:07, 24089.00 examples/s]
Generating train split: 133540200 examples [2:22:07, 25254.18 examples/s]
Generating train split: 133542984 examples [2:22:07, 25569.95 examples/s]
Generating train split: 133545585 examples [2:22:08, 23585.69 examples/s]
Generating train split: 133549378 examples [2:22:08, 27419.20 examples/s]
Generating train split: 133552209 examples [2:22:08, 27476.25 examples/s]
Generating train split: 133555765 examples [2:22:08, 29715.53 examples/s]
Generating train split: 133558804 examples [2:22:08, 29775.80 examples/s]
Generating train split: 133561820 examples [2:22:08, 28918.89 examples/s]
Generating train split: 133565611 examples [2:22:08, 31486.24 examples/s]
Generating train split: 133568798 examples [2:22:08, 31088.31 examples/s]
Generating train split: 133571935 examples [2:22:08, 28865.21 examples/s]
Generating train split: 133574872 examples [2:22:08, 26947.92 examples/s]
Generating train split: 133578122 examples [2:22:09, 28399.92 examples/s]
Generating train split: 133581535 examples [2:22:09, 29978.82 examples/s]
Generating train split: 133585120 examples [2:22:09, 31643.64 examples/s]
Generating train split: 133588331 examples [2:22:09, 30984.92 examples/s]
Generating train split: 133591927 examples [2:22:09, 32405.98 examples/s]
Generating train split: 133595207 examples [2:22:09, 30933.87 examples/s]
Generating train split: 133598341 examples [2:22:09, 29692.62 examples/s]
Generating train split: 133601742 examples [2:22:09, 30855.64 examples/s]
Generating train split: 133606046 examples [2:22:09, 34288.88 examples/s]
Generating train split: 133609512 examples [2:22:10, 28826.38 examples/s]
Generating train split: 133612565 examples [2:22:10, 28891.99 examples/s]
Generating train split: 133616817 examples [2:22:10, 32512.07 examples/s]
Generating train split: 133620200 examples [2:22:10, 31966.25 examples/s]
Generating train split: 133623491 examples [2:22:10, 31548.33 examples/s]
Generating train split: 133626931 examples [2:22:10, 32254.26 examples/s]
Generating train split: 133630209 examples [2:22:10, 28763.99 examples/s]
Generating train split: 133633807 examples [2:22:10, 30670.53 examples/s]
Generating train split: 133636969 examples [2:22:11, 27982.21 examples/s]
Generating train split: 133640275 examples [2:22:11, 29304.99 examples/s]
Generating train split: 133643745 examples [2:22:11, 30740.36 examples/s]
Generating train split: 133647021 examples [2:22:11, 31255.93 examples/s]
Generating train split: 133650212 examples [2:22:11, 28121.24 examples/s]
Generating train split: 133653356 examples [2:22:11, 28940.16 examples/s]
Generating train split: 133656364 examples [2:22:11, 29246.99 examples/s]
Generating train split: 133659352 examples [2:22:11, 28550.22 examples/s]
Generating train split: 133662259 examples [2:22:11, 27836.68 examples/s]
Generating train split: 133666177 examples [2:22:11, 30991.98 examples/s]
Generating train split: 133669317 examples [2:22:12, 30137.38 examples/s]
Generating train split: 133672468 examples [2:22:12, 30515.20 examples/s]
Generating train split: 133675547 examples [2:22:12, 29627.84 examples/s]
Generating train split: 133678617 examples [2:22:12, 29903.86 examples/s]
Generating train split: 133682265 examples [2:22:12, 31799.58 examples/s]
Generating train split: 133685469 examples [2:22:12, 30945.90 examples/s]
Generating train split: 133688585 examples [2:22:12, 29804.59 examples/s]
Generating train split: 133691623 examples [2:22:12, 29953.22 examples/s]
Generating train split: 133694643 examples [2:22:12, 28881.71 examples/s]
Generating train split: 133698486 examples [2:22:13, 31578.22 examples/s]
Generating train split: 133701670 examples [2:22:13, 29300.41 examples/s]
Generating train split: 133704836 examples [2:22:13, 29936.15 examples/s]
Generating train split: 133707875 examples [2:22:13, 29217.00 examples/s]
Generating train split: 133711717 examples [2:22:13, 31701.73 examples/s]
Generating train split: 133714927 examples [2:22:13, 31338.58 examples/s]
Generating train split: 133718141 examples [2:22:13, 31519.07 examples/s]
Generating train split: 133721908 examples [2:22:13, 33302.24 examples/s]
Generating train split: 133725467 examples [2:22:13, 33834.27 examples/s]
Generating train split: 133728873 examples [2:22:14, 30891.21 examples/s]
Generating train split: 133732023 examples [2:22:14, 30084.57 examples/s]
Generating train split: 133735074 examples [2:22:14, 30017.94 examples/s]
Generating train split: 133738107 examples [2:22:14, 29699.56 examples/s]
Generating train split: 133741323 examples [2:22:14, 30369.14 examples/s]
Generating train split: 133745633 examples [2:22:14, 33962.28 examples/s]
Generating train split: 133749485 examples [2:22:14, 35276.04 examples/s]
Generating train split: 133753036 examples [2:22:14, 30477.03 examples/s]
Generating train split: 133756218 examples [2:22:14, 30161.19 examples/s]
Generating train split: 133760102 examples [2:22:14, 32322.69 examples/s]
Generating train split: 133763421 examples [2:22:15, 31244.75 examples/s]
Generating train split: 133766608 examples [2:22:15, 31221.73 examples/s]
Generating train split: 133769774 examples [2:22:15, 25155.44 examples/s]
Generating train split: 133772495 examples [2:22:16, 11263.27 examples/s]
Generating train split: 133774532 examples [2:22:16, 7086.16 examples/s] 
Generating train split: 133776051 examples [2:22:16, 7415.33 examples/s]
Generating train split: 133777396 examples [2:22:16, 8026.49 examples/s]
Generating train split: 133779531 examples [2:22:17, 9895.90 examples/s]
Generating train split: 133782339 examples [2:22:17, 12931.36 examples/s]
Generating train split: 133784444 examples [2:22:17, 14491.16 examples/s]
Generating train split: 133787002 examples [2:22:17, 16880.94 examples/s]
Generating train split: 133790397 examples [2:22:17, 20902.37 examples/s]
Generating train split: 133793407 examples [2:22:17, 23213.80 examples/s]
Generating train split: 133798057 examples [2:22:17, 29210.37 examples/s]
Generating train split: 133801366 examples [2:22:17, 30073.63 examples/s]
Generating train split: 133804604 examples [2:22:17, 29191.84 examples/s]
Generating train split: 133807687 examples [2:22:18, 29418.14 examples/s]
Generating train split: 133810754 examples [2:22:18, 29707.47 examples/s]
Generating train split: 133814553 examples [2:22:18, 32069.53 examples/s]
Generating train split: 133817833 examples [2:22:18, 31650.99 examples/s]
Generating train split: 133821061 examples [2:22:18, 31415.07 examples/s]
Generating train split: 133824462 examples [2:22:18, 32153.59 examples/s]
Generating train split: 133827708 examples [2:22:18, 29805.28 examples/s]
Generating train split: 133830745 examples [2:22:18, 29227.93 examples/s]
Generating train split: 133833901 examples [2:22:18, 29854.47 examples/s]
Generating train split: 133836923 examples [2:22:18, 27460.24 examples/s]
Generating train split: 133840997 examples [2:22:19, 31051.61 examples/s]
Generating train split: 133845249 examples [2:22:19, 34234.48 examples/s]
Generating train split: 133849218 examples [2:22:19, 35779.77 examples/s]
Generating train split: 133852864 examples [2:22:19, 33685.99 examples/s]
Generating train split: 133856299 examples [2:22:19, 33162.65 examples/s]
Generating train split: 133859724 examples [2:22:19, 33427.91 examples/s]
Generating train split: 133863102 examples [2:22:19, 32107.46 examples/s]
Generating train split: 133866602 examples [2:22:19, 32907.64 examples/s]
Generating train split: 133869956 examples [2:22:19, 33082.36 examples/s]
Generating train split: 133874450 examples [2:22:20, 36498.99 examples/s]
Generating train split: 133878470 examples [2:22:20, 37574.19 examples/s]
Generating train split: 133882262 examples [2:22:20, 37670.25 examples/s]
Generating train split: 133886150 examples [2:22:20, 37984.26 examples/s]
Generating train split: 133890029 examples [2:22:20, 38191.55 examples/s]
Generating train split: 133893879 examples [2:22:20, 38280.60 examples/s]
Generating train split: 133897715 examples [2:22:20, 37182.23 examples/s]
Generating train split: 133901456 examples [2:22:20, 33108.74 examples/s]
Generating train split: 133904867 examples [2:22:20, 33163.52 examples/s]
Generating train split: 133908248 examples [2:22:20, 32911.72 examples/s]
Generating train split: 133911969 examples [2:22:21, 34106.99 examples/s]
Generating train split: 133916192 examples [2:22:21, 36415.58 examples/s]
Generating train split: 133919871 examples [2:22:21, 35249.40 examples/s]
Generating train split: 133923439 examples [2:22:21, 32967.75 examples/s]
Generating train split: 133926791 examples [2:22:21, 32129.76 examples/s]
Generating train split: 133930327 examples [2:22:21, 32949.52 examples/s]
Generating train split: 133934259 examples [2:22:21, 34739.33 examples/s]
Generating train split: 133941453 examples [2:22:21, 45426.62 examples/s]
Generating train split: 133950740 examples [2:22:21, 59238.71 examples/s]
Generating train split: 133956764 examples [2:22:22, 58847.59 examples/s]
Generating train split: 133962713 examples [2:22:22, 53204.92 examples/s]
Generating train split: 133968178 examples [2:22:22, 42125.88 examples/s]
Generating train split: 133972832 examples [2:22:22, 39269.52 examples/s]
Generating train split: 133977072 examples [2:22:22, 33953.91 examples/s]
Generating train split: 133980766 examples [2:22:22, 34023.29 examples/s]
Generating train split: 133984381 examples [2:22:22, 28800.85 examples/s]
Generating train split: 133987505 examples [2:22:23, 29151.57 examples/s]
Generating train split: 133990599 examples [2:22:23, 27927.33 examples/s]
Generating train split: 133994392 examples [2:22:23, 30331.11 examples/s]
Generating train split: 133997568 examples [2:22:23, 29769.99 examples/s]
Generating train split: 134001861 examples [2:22:23, 33230.04 examples/s]
Generating train split: 134006750 examples [2:22:23, 37450.60 examples/s]
Generating train split: 134010621 examples [2:22:23, 35173.15 examples/s]
Generating train split: 134014247 examples [2:22:23, 34176.17 examples/s]
Generating train split: 134018004 examples [2:22:23, 35081.92 examples/s]
Generating train split: 134021573 examples [2:22:24, 31038.27 examples/s]
Generating train split: 134025194 examples [2:22:24, 32383.32 examples/s]
Generating train split: 134028959 examples [2:22:24, 33576.77 examples/s]
Generating train split: 134032398 examples [2:22:24, 31985.52 examples/s]
Generating train split: 134040018 examples [2:22:24, 44040.76 examples/s]
Generating train split: 134046790 examples [2:22:24, 50668.01 examples/s]
Generating train split: 134052027 examples [2:22:24, 48745.52 examples/s]
Generating train split: 134057043 examples [2:22:24, 41518.66 examples/s]
Generating train split: 134061458 examples [2:22:25, 40088.36 examples/s]
Generating train split: 134065644 examples [2:22:25, 38538.73 examples/s]
Generating train split: 134070203 examples [2:22:25, 40258.24 examples/s]
Generating train split: 134074347 examples [2:22:25, 40206.64 examples/s]
Generating train split: 134078447 examples [2:22:25, 38508.09 examples/s]
Generating train split: 134082707 examples [2:22:25, 39600.31 examples/s]
Generating train split: 134086724 examples [2:22:25, 36618.94 examples/s]
Generating train split: 134090643 examples [2:22:25, 37303.57 examples/s]
Generating train split: 134094501 examples [2:22:25, 37631.40 examples/s]
Generating train split: 134098324 examples [2:22:26, 34826.46 examples/s]
Generating train split: 134101872 examples [2:22:26, 32828.17 examples/s]
Generating train split: 134108724 examples [2:22:26, 42344.42 examples/s]
Generating train split: 134117743 examples [2:22:26, 55543.83 examples/s]
Generating train split: 134124274 examples [2:22:26, 57827.13 examples/s]
Generating train split: 134130225 examples [2:22:26, 41775.28 examples/s]
Generating train split: 134135149 examples [2:22:26, 39635.06 examples/s]
Generating train split: 134139628 examples [2:22:27, 37103.23 examples/s]
Generating train split: 134143694 examples [2:22:27, 37770.87 examples/s]
Generating train split: 134147749 examples [2:22:27, 35195.48 examples/s]
Generating train split: 134151473 examples [2:22:27, 34692.18 examples/s]
Generating train split: 134155079 examples [2:22:27, 34867.95 examples/s]
Generating train split: 134158665 examples [2:22:27, 34270.22 examples/s]
Generating train split: 134162156 examples [2:22:27, 33186.55 examples/s]
Generating train split: 134165520 examples [2:22:27, 31148.05 examples/s]
Generating train split: 134168678 examples [2:22:27, 28450.69 examples/s]
Generating train split: 134172419 examples [2:22:28, 30737.54 examples/s]
Generating train split: 134175586 examples [2:22:28, 30547.27 examples/s]
Generating train split: 134178997 examples [2:22:28, 31430.75 examples/s]
Generating train split: 134182186 examples [2:22:28, 30324.26 examples/s]
Generating train split: 134185399 examples [2:22:28, 30782.11 examples/s]
Generating train split: 134188512 examples [2:22:28, 29793.08 examples/s]
Generating train split: 134191519 examples [2:22:28, 29246.22 examples/s]
Generating train split: 134195680 examples [2:22:28, 32727.56 examples/s]
Generating train split: 134198995 examples [2:22:28, 32135.05 examples/s]
Generating train split: 134202240 examples [2:22:29, 30074.69 examples/s]
Generating train split: 134205934 examples [2:22:29, 31943.99 examples/s]
Generating train split: 134209170 examples [2:22:29, 31155.99 examples/s]
Generating train split: 134212316 examples [2:22:29, 31108.64 examples/s]
Generating train split: 134216603 examples [2:22:29, 34472.92 examples/s]
Generating train split: 134220117 examples [2:22:29, 34647.90 examples/s]
Generating train split: 134224119 examples [2:22:29, 36202.42 examples/s]
Generating train split: 134227768 examples [2:22:29, 34829.74 examples/s]
Generating train split: 134231283 examples [2:22:29, 32828.84 examples/s]
Generating train split: 134235093 examples [2:22:29, 34297.36 examples/s]
Generating train split: 134238717 examples [2:22:30, 34840.53 examples/s]
Generating train split: 134246393 examples [2:22:30, 46956.54 examples/s]
Generating train split: 134255213 examples [2:22:30, 59007.97 examples/s]
Generating train split: 134261199 examples [2:22:30, 51801.19 examples/s]
Generating train split: 134266596 examples [2:22:30, 40597.62 examples/s]
Generating train split: 134271152 examples [2:22:30, 36470.56 examples/s]
Generating train split: 134275180 examples [2:22:30, 36995.89 examples/s]
Generating train split: 134279164 examples [2:22:31, 35089.53 examples/s]
Generating train split: 134282877 examples [2:22:31, 32496.42 examples/s]
Generating train split: 134286527 examples [2:22:31, 33441.98 examples/s]
Generating train split: 134290004 examples [2:22:31, 30189.24 examples/s]
Generating train split: 134293493 examples [2:22:31, 31327.01 examples/s]
Generating train split: 134297133 examples [2:22:31, 32631.61 examples/s]
Generating train split: 134300500 examples [2:22:31, 31258.92 examples/s]
Generating train split: 134303755 examples [2:22:31, 31595.67 examples/s]
Generating train split: 134307660 examples [2:22:31, 33653.59 examples/s]
Generating train split: 134311082 examples [2:22:32, 32513.20 examples/s]
Generating train split: 134314376 examples [2:22:32, 30534.28 examples/s]
Generating train split: 134319700 examples [2:22:32, 36663.73 examples/s]
Generating train split: 134323460 examples [2:22:32, 33741.33 examples/s]
Generating train split: 134326937 examples [2:22:32, 32996.40 examples/s]
Generating train split: 134330305 examples [2:22:32, 30852.67 examples/s]
Generating train split: 134333486 examples [2:22:32, 31084.91 examples/s]
Generating train split: 134337132 examples [2:22:32, 32473.01 examples/s]
Generating train split: 134340435 examples [2:22:32, 31539.40 examples/s]
Generating train split: 134343894 examples [2:22:33, 32378.13 examples/s]
Generating train split: 134347163 examples [2:22:33, 31804.96 examples/s]
Generating train split: 134350370 examples [2:22:33, 31289.35 examples/s]
Generating train split: 134353529 examples [2:22:33, 30480.70 examples/s]
Generating train split: 134357029 examples [2:22:33, 31688.96 examples/s]
Generating train split: 134360799 examples [2:22:33, 33415.62 examples/s]
Generating train split: 134364434 examples [2:22:33, 34263.75 examples/s]
Generating train split: 134367882 examples [2:22:33, 33982.50 examples/s]
Generating train split: 134371294 examples [2:22:33, 29452.66 examples/s]
Generating train split: 134374352 examples [2:22:34, 27736.65 examples/s]
Generating train split: 134377678 examples [2:22:34, 29045.62 examples/s]
Generating train split: 134380839 examples [2:22:34, 29738.42 examples/s]
Generating train split: 134383881 examples [2:22:34, 28468.84 examples/s]
Generating train split: 134387160 examples [2:22:34, 29637.99 examples/s]
Generating train split: 134390174 examples [2:22:34, 29256.13 examples/s]
Generating train split: 134394325 examples [2:22:34, 32712.63 examples/s]
Generating train split: 134397796 examples [2:22:34, 33233.70 examples/s]
Generating train split: 134401912 examples [2:22:34, 35381.41 examples/s]
Generating train split: 134405482 examples [2:22:35, 33608.88 examples/s]
Generating train split: 134408878 examples [2:22:35, 28920.76 examples/s]
Generating train split: 134412403 examples [2:22:35, 30552.39 examples/s]
Generating train split: 134415578 examples [2:22:35, 29854.45 examples/s]
Generating train split: 134418644 examples [2:22:35, 29460.01 examples/s]
Generating train split: 134422822 examples [2:22:35, 32847.66 examples/s]
Generating train split: 134426179 examples [2:22:35, 32053.14 examples/s]
Generating train split: 134429435 examples [2:22:35, 31768.10 examples/s]
Generating train split: 134432885 examples [2:22:35, 32526.96 examples/s]
Generating train split: 134437351 examples [2:22:36, 36008.25 examples/s]
Generating train split: 134440990 examples [2:22:36, 34873.89 examples/s]
Generating train split: 134444513 examples [2:22:36, 32980.92 examples/s]
Generating train split: 134448320 examples [2:22:36, 34393.17 examples/s]
Generating train split: 134452607 examples [2:22:36, 36789.97 examples/s]
Generating train split: 134456339 examples [2:22:36, 35219.83 examples/s]
Generating train split: 134459904 examples [2:22:36, 33148.37 examples/s]
Generating train split: 134463670 examples [2:22:36, 34380.75 examples/s]
Generating train split: 134467155 examples [2:22:36, 32092.08 examples/s]
Generating train split: 134470421 examples [2:22:37, 32020.84 examples/s]
Generating train split: 134474546 examples [2:22:37, 34576.77 examples/s]
Generating train split: 134478056 examples [2:22:37, 34144.78 examples/s]
Generating train split: 134481501 examples [2:22:37, 32323.08 examples/s]
Generating train split: 134484771 examples [2:22:37, 31813.76 examples/s]
Generating train split: 134487980 examples [2:22:37, 30936.20 examples/s]
Generating train split: 134491091 examples [2:22:37, 30163.76 examples/s]
Generating train split: 134494912 examples [2:22:37, 32380.68 examples/s]
Generating train split: 134498396 examples [2:22:37, 33059.96 examples/s]
Generating train split: 134502130 examples [2:22:37, 34299.37 examples/s]
Generating train split: 134505591 examples [2:22:38, 32013.06 examples/s]
Generating train split: 134508836 examples [2:22:38, 31628.47 examples/s]
Generating train split: 134512544 examples [2:22:38, 33167.74 examples/s]
Generating train split: 134515897 examples [2:22:38, 31971.66 examples/s]
Generating train split: 134519423 examples [2:22:38, 32897.19 examples/s]
Generating train split: 134523228 examples [2:22:38, 34365.76 examples/s]
Generating train split: 134526695 examples [2:22:38, 30436.64 examples/s]
Generating train split: 134530881 examples [2:22:38, 33507.02 examples/s]
Generating train split: 134534340 examples [2:22:38, 30228.47 examples/s]
Generating train split: 134538165 examples [2:22:39, 32221.74 examples/s]
Generating train split: 134541857 examples [2:22:39, 33493.55 examples/s]
Generating train split: 134545308 examples [2:22:39, 31752.44 examples/s]
Generating train split: 134548696 examples [2:22:39, 32248.49 examples/s]
Generating train split: 134551980 examples [2:22:39, 31676.19 examples/s]
Generating train split: 134555198 examples [2:22:39, 28500.21 examples/s]
Generating train split: 134558600 examples [2:22:39, 29953.55 examples/s]
Generating train split: 134561985 examples [2:22:39, 30998.68 examples/s]
Generating train split: 134565630 examples [2:22:39, 32529.92 examples/s]
Generating train split: 134568937 examples [2:22:40, 32338.08 examples/s]
Generating train split: 134572208 examples [2:22:40, 31407.37 examples/s]
Generating train split: 134575993 examples [2:22:40, 33214.28 examples/s]
Generating train split: 134579351 examples [2:22:40, 32052.63 examples/s]
Generating train split: 134583208 examples [2:22:40, 33887.78 examples/s]
Generating train split: 134586790 examples [2:22:40, 34421.30 examples/s]
Generating train split: 134590258 examples [2:22:40, 29859.70 examples/s]
Generating train split: 134593423 examples [2:22:40, 30296.96 examples/s]
Generating train split: 134597895 examples [2:22:40, 34252.07 examples/s]
Generating train split: 134601419 examples [2:22:41, 34398.36 examples/s]
Generating train split: 134604933 examples [2:22:41, 34375.37 examples/s]
Generating train split: 134608421 examples [2:22:41, 34147.87 examples/s]
Generating train split: 134612252 examples [2:22:41, 35340.94 examples/s]
Generating train split: 134620167 examples [2:22:41, 48152.90 examples/s]
Generating train split: 134629668 examples [2:22:41, 61958.25 examples/s]
Generating train split: 134635928 examples [2:22:41, 60761.08 examples/s]
Generating train split: 134642053 examples [2:22:41, 48311.17 examples/s]
Generating train split: 134647319 examples [2:22:42, 43883.59 examples/s]
Generating train split: 134652067 examples [2:22:42, 36853.34 examples/s]
Generating train split: 134656143 examples [2:22:42, 32964.26 examples/s]
Generating train split: 134659739 examples [2:22:42, 33373.77 examples/s]
Generating train split: 134663392 examples [2:22:42, 34096.64 examples/s]
Generating train split: 134667124 examples [2:22:42, 34893.05 examples/s]
Generating train split: 134670753 examples [2:22:42, 32277.43 examples/s]
Generating train split: 134674643 examples [2:22:42, 33793.27 examples/s]
Generating train split: 134678958 examples [2:22:43, 36272.59 examples/s]
Generating train split: 134682689 examples [2:22:43, 33102.51 examples/s]
Generating train split: 134686113 examples [2:22:43, 31278.36 examples/s]
Generating train split: 134690121 examples [2:22:43, 33560.49 examples/s]
Generating train split: 134693801 examples [2:22:43, 34429.79 examples/s]
Generating train split: 134697326 examples [2:22:43, 33587.21 examples/s]
Generating train split: 134700744 examples [2:22:43, 31814.93 examples/s]
Generating train split: 134704796 examples [2:22:43, 34170.50 examples/s]
Generating train split: 134708275 examples [2:22:43, 29964.58 examples/s]
Generating train split: 134711401 examples [2:22:44, 29197.77 examples/s]
Generating train split: 134714837 examples [2:22:44, 30552.71 examples/s]
Generating train split: 134718752 examples [2:22:44, 32578.30 examples/s]
Generating train split: 134722080 examples [2:22:44, 30962.98 examples/s]
Generating train split: 134725261 examples [2:22:44, 31179.67 examples/s]
Generating train split: 134729326 examples [2:22:44, 33837.10 examples/s]
Generating train split: 134732761 examples [2:22:44, 31470.51 examples/s]
Generating train split: 134736128 examples [2:22:44, 32065.17 examples/s]
Generating train split: 134739528 examples [2:22:44, 32602.63 examples/s]
Generating train split: 134742827 examples [2:22:45, 30126.83 examples/s]
Generating train split: 134746044 examples [2:22:45, 30679.49 examples/s]
Generating train split: 134749931 examples [2:22:45, 32970.15 examples/s]
Generating train split: 134753282 examples [2:22:45, 32034.51 examples/s]
Generating train split: 134756531 examples [2:22:45, 31852.02 examples/s]
Generating train split: 134759766 examples [2:22:45, 31964.23 examples/s]
Generating train split: 134762994 examples [2:22:45, 31267.95 examples/s]
Generating train split: 134766359 examples [2:22:45, 31917.41 examples/s]
Generating train split: 134769586 examples [2:22:45, 31841.41 examples/s]
Generating train split: 134772779 examples [2:22:45, 30657.78 examples/s]
Generating train split: 134777491 examples [2:22:46, 35328.66 examples/s]
Generating train split: 134781851 examples [2:22:46, 37693.81 examples/s]
Generating train split: 134785657 examples [2:22:46, 32958.58 examples/s]
Generating train split: 134789076 examples [2:22:46, 32876.63 examples/s]
Generating train split: 134792452 examples [2:22:46, 31876.85 examples/s]
Generating train split: 134795702 examples [2:22:46, 30169.64 examples/s]
Generating train split: 134798776 examples [2:22:46, 29622.68 examples/s]
Generating train split: 134801781 examples [2:22:46, 27533.56 examples/s]
Generating train split: 134807355 examples [2:22:47, 35005.12 examples/s]
Generating train split: 134815500 examples [2:22:47, 47762.84 examples/s]
Generating train split: 134822460 examples [2:22:47, 53903.56 examples/s]
Generating train split: 134828036 examples [2:22:47, 49126.06 examples/s]
Generating train split: 134833163 examples [2:22:47, 39748.78 examples/s]
Generating train split: 134837554 examples [2:22:47, 40501.32 examples/s]
Generating train split: 134841909 examples [2:22:47, 38375.43 examples/s]
Generating train split: 134846147 examples [2:22:47, 39364.77 examples/s]
Generating train split: 134850256 examples [2:22:48, 37429.10 examples/s]
Generating train split: 134854133 examples [2:22:48, 36269.50 examples/s]
Generating train split: 134857856 examples [2:22:48, 36300.07 examples/s]
Generating train split: 134861890 examples [2:22:48, 37300.51 examples/s]
Generating train split: 134865686 examples [2:22:48, 34651.80 examples/s]
Generating train split: 134869668 examples [2:22:48, 36011.69 examples/s]
Generating train split: 134873514 examples [2:22:48, 36657.73 examples/s]
Generating train split: 134877228 examples [2:22:48, 36026.01 examples/s]
Generating train split: 134880868 examples [2:22:48, 34517.69 examples/s]
Generating train split: 134884350 examples [2:22:49, 30234.12 examples/s]
Generating train split: 134889303 examples [2:22:49, 35217.34 examples/s]
Generating train split: 134893324 examples [2:22:49, 36560.67 examples/s]
Generating train split: 134897103 examples [2:22:49, 33349.01 examples/s]
Generating train split: 134901034 examples [2:22:49, 34918.05 examples/s]
Generating train split: 134904639 examples [2:22:49, 31671.52 examples/s]
Generating train split: 134907940 examples [2:22:49, 31618.15 examples/s]
Generating train split: 134912056 examples [2:22:49, 34149.41 examples/s]
Generating train split: 134915560 examples [2:22:49, 32546.54 examples/s]
Generating train split: 134918885 examples [2:22:50, 31849.84 examples/s]
Generating train split: 134922131 examples [2:22:50, 30774.92 examples/s]
Generating train split: 134925909 examples [2:22:50, 32683.09 examples/s]
Generating train split: 134929766 examples [2:22:50, 34317.30 examples/s]
Generating train split: 134933866 examples [2:22:50, 36214.00 examples/s]
Generating train split: 134938659 examples [2:22:50, 39600.65 examples/s]
Generating train split: 134947572 examples [2:22:50, 54096.88 examples/s]
Generating train split: 134954975 examples [2:22:50, 59953.25 examples/s]
Generating train split: 134961028 examples [2:22:50, 52894.72 examples/s]
Generating train split: 134966517 examples [2:22:51, 44720.02 examples/s]
Generating train split: 134971309 examples [2:22:51, 42240.64 examples/s]
Generating train split: 134975766 examples [2:22:51, 40492.38 examples/s]
Generating train split: 134979964 examples [2:22:51, 38002.11 examples/s]
Generating train split: 134983878 examples [2:22:51, 36676.64 examples/s]
Generating train split: 134987616 examples [2:22:51, 33210.05 examples/s]
Generating train split: 134991215 examples [2:22:51, 33675.08 examples/s]
Generating train split: 134994657 examples [2:22:51, 29580.92 examples/s]
Generating train split: 134997778 examples [2:22:52, 29959.89 examples/s]
Generating train split: 135000865 examples [2:22:52, 29905.67 examples/s]
Generating train split: 135003944 examples [2:22:52, 30116.04 examples/s]
Generating train split: 135007009 examples [2:22:52, 30055.58 examples/s]
Generating train split: 135010211 examples [2:22:52, 30594.69 examples/s]
Generating train split: 135013295 examples [2:22:52, 30332.92 examples/s]
Generating train split: 135017315 examples [2:22:52, 33174.44 examples/s]
Generating train split: 135020657 examples [2:22:52, 32602.04 examples/s]
Generating train split: 135023941 examples [2:22:52, 31043.77 examples/s]
Generating train split: 135027792 examples [2:22:53, 33132.16 examples/s]
Generating train split: 135031287 examples [2:22:53, 33650.53 examples/s]
Generating train split: 135034676 examples [2:22:53, 33360.07 examples/s]
Generating train split: 135038585 examples [2:22:53, 35014.40 examples/s]
Generating train split: 135042104 examples [2:22:53, 34855.64 examples/s]
Generating train split: 135045613 examples [2:22:53, 30075.42 examples/s]
Generating train split: 135049605 examples [2:22:53, 32687.12 examples/s]
Generating train split: 135053512 examples [2:22:53, 34441.63 examples/s]
Generating train split: 135057064 examples [2:22:53, 33388.51 examples/s]
Generating train split: 135061451 examples [2:22:54, 36301.70 examples/s]
Generating train split: 135065470 examples [2:22:54, 37386.24 examples/s]
Generating train split: 135069265 examples [2:22:54, 36022.77 examples/s]
Generating train split: 135072919 examples [2:22:54, 33607.84 examples/s]
Generating train split: 135077273 examples [2:22:54, 36258.08 examples/s]
Generating train split: 135081107 examples [2:22:54, 36833.81 examples/s]
Generating train split: 135085052 examples [2:22:54, 37569.00 examples/s]
Generating train split: 135088855 examples [2:22:54, 36120.58 examples/s]
Generating train split: 135092885 examples [2:22:54, 37297.17 examples/s]
Generating train split: 135096651 examples [2:22:54, 35682.63 examples/s]
Generating train split: 135104815 examples [2:22:55, 48651.93 examples/s]
Generating train split: 135114294 examples [2:22:55, 61892.56 examples/s]
Generating train split: 135120613 examples [2:22:55, 59299.78 examples/s]
Generating train split: 135126660 examples [2:22:55, 45651.21 examples/s]
Generating train split: 135131774 examples [2:22:55, 42628.81 examples/s]
Generating train split: 135136420 examples [2:22:55, 39961.99 examples/s]
Generating train split: 135140689 examples [2:22:55, 37262.84 examples/s]
Generating train split: 135144608 examples [2:22:56, 35914.61 examples/s]
Generating train split: 135148317 examples [2:22:56, 34613.98 examples/s]
Generating train split: 135151850 examples [2:22:56, 34389.44 examples/s]
Generating train split: 135155339 examples [2:22:56, 30973.31 examples/s]
Generating train split: 135158618 examples [2:22:56, 31407.56 examples/s]
Generating train split: 135161818 examples [2:22:56, 29638.19 examples/s]
Generating train split: 135164841 examples [2:22:56, 29445.34 examples/s]
Generating train split: 135168314 examples [2:22:56, 30833.32 examples/s]
Generating train split: 135171433 examples [2:22:56, 29170.14 examples/s]
Generating train split: 135174388 examples [2:22:57, 28558.53 examples/s]
Generating train split: 135177672 examples [2:22:57, 29722.35 examples/s]
Generating train split: 135180679 examples [2:22:57, 29078.55 examples/s]
Generating train split: 135183928 examples [2:22:57, 30013.73 examples/s]
Generating train split: 135186957 examples [2:22:57, 29438.25 examples/s]
Generating train split: 135190671 examples [2:22:57, 31625.23 examples/s]
Generating train split: 135194586 examples [2:22:57, 33799.04 examples/s]
Generating train split: 135197998 examples [2:22:57, 33325.76 examples/s]
Generating train split: 135201350 examples [2:22:57, 32861.52 examples/s]
Generating train split: 135204660 examples [2:22:58, 32555.79 examples/s]
Generating train split: 135208639 examples [2:22:58, 34654.79 examples/s]
Generating train split: 135212119 examples [2:22:58, 33540.72 examples/s]
Generating train split: 135215491 examples [2:22:58, 31069.31 examples/s]
Generating train split: 135219153 examples [2:22:58, 32597.19 examples/s]
Generating train split: 135222541 examples [2:22:58, 32954.63 examples/s]
Generating train split: 135225879 examples [2:22:58, 32712.71 examples/s]
Generating train split: 135229176 examples [2:22:58, 32244.27 examples/s]
Generating train split: 135232425 examples [2:22:58, 30684.83 examples/s]
Generating train split: 135235520 examples [2:22:58, 30572.04 examples/s]
Generating train split: 135239067 examples [2:22:59, 31872.84 examples/s]
Generating train split: 135242275 examples [2:22:59, 28824.80 examples/s]
Generating train split: 135245223 examples [2:22:59, 28525.12 examples/s]
Generating train split: 135248117 examples [2:22:59, 28475.03 examples/s]
Generating train split: 135251281 examples [2:22:59, 29356.49 examples/s]
Generating train split: 135254244 examples [2:22:59, 28622.44 examples/s]
Generating train split: 135257815 examples [2:22:59, 30608.62 examples/s]
Generating train split: 135260908 examples [2:22:59, 30683.90 examples/s]
Generating train split: 135265201 examples [2:22:59, 34212.75 examples/s]
Generating train split: 135269175 examples [2:23:00, 35826.26 examples/s]
Generating train split: 135272777 examples [2:23:00, 35623.73 examples/s]
Generating train split: 135277206 examples [2:23:00, 38160.23 examples/s]
Generating train split: 135281039 examples [2:23:00, 38018.84 examples/s]
Generating train split: 135285040 examples [2:23:00, 38537.12 examples/s]
Generating train split: 135288905 examples [2:23:00, 38304.21 examples/s]
Generating train split: 135292743 examples [2:23:00, 33085.26 examples/s]
Generating train split: 135296179 examples [2:23:00, 31556.41 examples/s]
Generating train split: 135299935 examples [2:23:00, 33129.60 examples/s]
Generating train split: 135303752 examples [2:23:01, 34501.56 examples/s]
Generating train split: 135312322 examples [2:23:01, 48920.44 examples/s]
Generating train split: 135319216 examples [2:23:01, 54665.75 examples/s]
Generating train split: 135324812 examples [2:23:01, 48446.91 examples/s]
Generating train split: 135329871 examples [2:23:01, 42010.33 examples/s]
Generating train split: 135334355 examples [2:23:01, 39970.52 examples/s]
Generating train split: 135338552 examples [2:23:01, 36231.93 examples/s]
Generating train split: 135342341 examples [2:23:01, 35031.21 examples/s]
Generating train split: 135345953 examples [2:23:02, 33622.58 examples/s]
Generating train split: 135349991 examples [2:23:02, 35314.19 examples/s]
Generating train split: 135353631 examples [2:23:02, 35510.13 examples/s]
Generating train split: 135357239 examples [2:23:02, 33415.32 examples/s]
Generating train split: 135361177 examples [2:23:02, 34997.73 examples/s]
Generating train split: 135364742 examples [2:23:02, 32734.23 examples/s]
Generating train split: 135368085 examples [2:23:02, 32911.33 examples/s]
Generating train split: 135371424 examples [2:23:02, 31227.66 examples/s]
Generating train split: 135374588 examples [2:23:02, 30661.66 examples/s]
Generating train split: 135377884 examples [2:23:03, 31284.37 examples/s]
Generating train split: 135381177 examples [2:23:03, 31732.08 examples/s]
Generating train split: 135384471 examples [2:23:03, 32017.08 examples/s]
Generating train split: 135387983 examples [2:23:03, 32822.42 examples/s]
Generating train split: 135391287 examples [2:23:03, 30382.27 examples/s]
Generating train split: 135394728 examples [2:23:03, 31348.69 examples/s]
Generating train split: 135397898 examples [2:23:03, 31423.00 examples/s]
Generating train split: 135401067 examples [2:23:03, 31259.22 examples/s]
Generating train split: 135404210 examples [2:23:03, 31101.90 examples/s]
Generating train split: 135408410 examples [2:23:03, 34249.64 examples/s]
Generating train split: 135411857 examples [2:23:04, 32852.11 examples/s]
Generating train split: 135415169 examples [2:23:04, 32451.47 examples/s]
Generating train split: 135418450 examples [2:23:04, 31821.91 examples/s]
Generating train split: 135422161 examples [2:23:04, 33327.18 examples/s]
Generating train split: 135425786 examples [2:23:04, 34134.32 examples/s]
Generating train split: 135429225 examples [2:23:04, 33363.99 examples/s]
Generating train split: 135432582 examples [2:23:04, 33345.21 examples/s]
Generating train split: 135435925 examples [2:23:04, 31900.06 examples/s]
Generating train split: 135439334 examples [2:23:04, 32440.16 examples/s]
Generating train split: 135442595 examples [2:23:05, 30321.42 examples/s]
Generating train split: 135447131 examples [2:23:05, 34487.96 examples/s]
Generating train split: 135450637 examples [2:23:05, 32618.97 examples/s]
Generating train split: 135454076 examples [2:23:05, 33103.79 examples/s]
Generating train split: 135457851 examples [2:23:05, 34403.12 examples/s]
Generating train split: 135461333 examples [2:23:05, 32951.17 examples/s]
Generating train split: 135464826 examples [2:23:05, 33494.98 examples/s]
Generating train split: 135468215 examples [2:23:05, 31897.45 examples/s]
Generating train split: 135472333 examples [2:23:05, 34449.42 examples/s]
Generating train split: 135475817 examples [2:23:06, 31173.69 examples/s]
Generating train split: 135479254 examples [2:23:06, 32032.01 examples/s]
Generating train split: 135482523 examples [2:23:06, 30757.06 examples/s]
Generating train split: 135485665 examples [2:23:06, 30435.36 examples/s]
Generating train split: 135488887 examples [2:23:06, 30918.22 examples/s]
Generating train split: 135492864 examples [2:23:06, 33417.86 examples/s]
Generating train split: 135496242 examples [2:23:06, 32403.62 examples/s]
Generating train split: 135499520 examples [2:23:06, 32267.89 examples/s]
Generating train split: 135503185 examples [2:23:06, 33512.07 examples/s]
Generating train split: 135506567 examples [2:23:06, 32548.76 examples/s]
Generating train split: 135510382 examples [2:23:07, 34127.29 examples/s]
Generating train split: 135514414 examples [2:23:07, 35828.77 examples/s]
Generating train split: 135518015 examples [2:23:07, 33594.45 examples/s]
Generating train split: 135521419 examples [2:23:07, 32753.48 examples/s]
Generating train split: 135525130 examples [2:23:07, 33960.87 examples/s]
Generating train split: 135529270 examples [2:23:07, 36066.32 examples/s]
Generating train split: 135532906 examples [2:23:07, 32958.58 examples/s]
Generating train split: 135536271 examples [2:23:07, 31780.80 examples/s]
Generating train split: 135539500 examples [2:23:07, 30827.97 examples/s]
Generating train split: 135543233 examples [2:23:08, 32479.58 examples/s]
Generating train split: 135546687 examples [2:23:08, 33047.34 examples/s]
Generating train split: 135550022 examples [2:23:08, 32627.58 examples/s]
Generating train split: 135553704 examples [2:23:08, 33803.98 examples/s]
Generating train split: 135557106 examples [2:23:08, 33497.15 examples/s]
Generating train split: 135561106 examples [2:23:08, 35381.03 examples/s]
Generating train split: 135564661 examples [2:23:08, 34347.92 examples/s]
Generating train split: 135568829 examples [2:23:08, 36444.16 examples/s]
Generating train split: 135572492 examples [2:23:08, 35529.51 examples/s]
Generating train split: 135576064 examples [2:23:09, 33688.22 examples/s]
Generating train split: 135579468 examples [2:23:09, 32599.17 examples/s]
Generating train split: 135583170 examples [2:23:09, 33786.53 examples/s]
Generating train split: 135587228 examples [2:23:09, 35720.66 examples/s]
Generating train split: 135590831 examples [2:23:09, 31571.49 examples/s]
Generating train split: 135594097 examples [2:23:09, 30788.51 examples/s]
Generating train split: 135597247 examples [2:23:09, 30267.99 examples/s]
Generating train split: 135600433 examples [2:23:09, 30698.65 examples/s]
Generating train split: 135603547 examples [2:23:09, 30597.77 examples/s]
Generating train split: 135606752 examples [2:23:10, 30971.63 examples/s]
Generating train split: 135610265 examples [2:23:10, 32166.03 examples/s]
Generating train split: 135613966 examples [2:23:10, 33433.85 examples/s]
Generating train split: 135617714 examples [2:23:10, 34424.03 examples/s]
Generating train split: 135621178 examples [2:23:10, 31112.78 examples/s]
Generating train split: 135624939 examples [2:23:10, 32887.82 examples/s]
Generating train split: 135628294 examples [2:23:10, 30701.96 examples/s]
Generating train split: 135631441 examples [2:23:10, 28593.13 examples/s]
Generating train split: 135635413 examples [2:23:10, 31492.67 examples/s]
Generating train split: 135638650 examples [2:23:11, 31680.62 examples/s]
Generating train split: 135642593 examples [2:23:11, 33843.98 examples/s]
Generating train split: 135646034 examples [2:23:11, 32882.70 examples/s]
Generating train split: 135649369 examples [2:23:11, 32364.55 examples/s]
Generating train split: 135653274 examples [2:23:11, 34242.34 examples/s]
Generating train split: 135656729 examples [2:23:11, 32942.91 examples/s]
Generating train split: 135660156 examples [2:23:11, 33270.28 examples/s]
Generating train split: 135664145 examples [2:23:11, 35175.21 examples/s]
Generating train split: 135667688 examples [2:23:11, 35128.05 examples/s]
Generating train split: 135671220 examples [2:23:11, 34320.65 examples/s]
Generating train split: 135674675 examples [2:23:12, 33888.17 examples/s]
Generating train split: 135678081 examples [2:23:12, 30712.78 examples/s]
Generating train split: 135681233 examples [2:23:12, 28751.49 examples/s]
Generating train split: 135684181 examples [2:23:12, 26748.15 examples/s]
Generating train split: 135687180 examples [2:23:12, 27588.84 examples/s]
Generating train split: 135690506 examples [2:23:12, 29113.15 examples/s]
Generating train split: 135693469 examples [2:23:12, 28527.23 examples/s]
Generating train split: 135697863 examples [2:23:12, 32834.62 examples/s]
Generating train split: 135701207 examples [2:23:12, 32052.26 examples/s]
Generating train split: 135704460 examples [2:23:13, 31922.39 examples/s]
Generating train split: 135709025 examples [2:23:13, 35853.32 examples/s]
Generating train split: 135712655 examples [2:23:13, 35358.59 examples/s]
Generating train split: 135716458 examples [2:23:13, 36123.97 examples/s]
Generating train split: 135720135 examples [2:23:13, 36201.85 examples/s]
Generating train split: 135724352 examples [2:23:13, 37953.05 examples/s]
Generating train split: 135728166 examples [2:23:13, 37859.01 examples/s]
Generating train split: 135731965 examples [2:23:13, 34081.35 examples/s]
Generating train split: 135735857 examples [2:23:13, 35411.50 examples/s]
Generating train split: 135739479 examples [2:23:14, 35117.71 examples/s]
Generating train split: 135743041 examples [2:23:14, 34158.30 examples/s]
Generating train split: 135746504 examples [2:23:14, 32408.74 examples/s]
Generating train split: 135750229 examples [2:23:14, 33742.88 examples/s]
Generating train split: 135754529 examples [2:23:14, 36317.20 examples/s]
Generating train split: 135758205 examples [2:23:14, 33011.81 examples/s]
Generating train split: 135761827 examples [2:23:14, 33858.43 examples/s]
Generating train split: 135765286 examples [2:23:14, 33834.50 examples/s]
Generating train split: 135768846 examples [2:23:14, 34321.57 examples/s]
Generating train split: 135772906 examples [2:23:15, 36075.97 examples/s]
Generating train split: 135776556 examples [2:23:15, 34978.41 examples/s]
Generating train split: 135780356 examples [2:23:15, 35830.75 examples/s]
Generating train split: 135783964 examples [2:23:15, 34416.51 examples/s]
Generating train split: 135788152 examples [2:23:15, 36522.02 examples/s]
Generating train split: 135791849 examples [2:23:15, 35447.01 examples/s]
Generating train split: 135795426 examples [2:23:15, 31457.95 examples/s]
Generating train split: 135799275 examples [2:23:15, 33305.23 examples/s]
Generating train split: 135802705 examples [2:23:15, 33274.44 examples/s]
Generating train split: 135807149 examples [2:23:15, 36393.38 examples/s]
Generating train split: 135811297 examples [2:23:16, 37815.87 examples/s]
Generating train split: 135815131 examples [2:23:16, 35579.09 examples/s]
Generating train split: 135818754 examples [2:23:16, 32790.01 examples/s]
Generating train split: 135822111 examples [2:23:16, 32566.73 examples/s]
Generating train split: 135825418 examples [2:23:16, 31350.54 examples/s]
Generating train split: 135829483 examples [2:23:16, 33875.73 examples/s]
Generating train split: 135837128 examples [2:23:16, 45813.33 examples/s]
Generating train split: 135846191 examples [2:23:16, 58620.17 examples/s]
Generating train split: 135852201 examples [2:23:17, 50010.13 examples/s]
Generating train split: 135857525 examples [2:23:17, 45766.99 examples/s]
Generating train split: 135862370 examples [2:23:17, 44206.12 examples/s]
Generating train split: 135866972 examples [2:23:17, 42722.49 examples/s]
Generating train split: 135871363 examples [2:23:17, 41583.52 examples/s]
Generating train split: 135875606 examples [2:23:17, 38237.62 examples/s]
Generating train split: 135879520 examples [2:23:17, 37170.66 examples/s]
Generating train split: 135883286 examples [2:23:17, 36036.80 examples/s]
Generating train split: 135886922 examples [2:23:18, 34035.56 examples/s]
Generating train split: 135890892 examples [2:23:18, 35486.03 examples/s]
Generating train split: 135894872 examples [2:23:18, 36661.06 examples/s]
Generating train split: 135898588 examples [2:23:18, 32399.20 examples/s]
Generating train split: 135901941 examples [2:23:18, 31541.42 examples/s]
Generating train split: 135905434 examples [2:23:18, 32428.19 examples/s]
Generating train split: 135908891 examples [2:23:18, 32991.47 examples/s]
Generating train split: 135912727 examples [2:23:18, 34496.62 examples/s]
Generating train split: 135916232 examples [2:23:18, 32291.24 examples/s]
Generating train split: 135920817 examples [2:23:19, 35980.78 examples/s]
Generating train split: 135924495 examples [2:23:19, 35943.46 examples/s]
Generating train split: 135928467 examples [2:23:19, 37021.63 examples/s]
Generating train split: 135932216 examples [2:23:19, 36993.05 examples/s]
Generating train split: 135936759 examples [2:23:19, 39325.13 examples/s]
Generating train split: 135940715 examples [2:23:19, 38708.06 examples/s]
Generating train split: 135946278 examples [2:23:19, 43639.78 examples/s]
Generating train split: 135950670 examples [2:23:19, 42402.87 examples/s]
Generating train split: 135954942 examples [2:23:19, 38286.45 examples/s]
Generating train split: 135958862 examples [2:23:19, 36093.96 examples/s]
Generating train split: 135962783 examples [2:23:20, 36912.03 examples/s]
Generating train split: 135966544 examples [2:23:20, 37040.84 examples/s]
Generating train split: 135970741 examples [2:23:20, 38431.26 examples/s]
Generating train split: 135974631 examples [2:23:20, 38419.36 examples/s]
Generating train split: 135978509 examples [2:23:20, 36046.73 examples/s]
Generating train split: 135982693 examples [2:23:20, 37656.42 examples/s]
Generating train split: 135986503 examples [2:23:20, 34715.10 examples/s]
Generating train split: 135990045 examples [2:23:20, 33787.33 examples/s]
Generating train split: 135993653 examples [2:23:20, 34410.60 examples/s]
Generating train split: 135997140 examples [2:23:21, 33668.37 examples/s]
Generating train split: 136000535 examples [2:23:21, 30004.53 examples/s]
Generating train split: 136005152 examples [2:23:21, 34243.02 examples/s]
Generating train split: 136008697 examples [2:23:21, 34498.57 examples/s]
Generating train split: 136012295 examples [2:23:21, 34878.59 examples/s]
Generating train split: 136016063 examples [2:23:21, 35649.81 examples/s]
Generating train split: 136019719 examples [2:23:21, 35907.92 examples/s]
Generating train split: 136024328 examples [2:23:21, 38845.70 examples/s]
Generating train split: 136028249 examples [2:23:21, 35670.55 examples/s]
Generating train split: 136032786 examples [2:23:22, 38352.02 examples/s]
Generating train split: 136037060 examples [2:23:22, 39557.20 examples/s]
Generating train split: 136041073 examples [2:23:22, 35709.59 examples/s]
Generating train split: 136044747 examples [2:23:22, 33648.38 examples/s]
Generating train split: 136052869 examples [2:23:22, 46257.51 examples/s]
Generating train split: 136059730 examples [2:23:22, 52384.42 examples/s]
Generating train split: 136065183 examples [2:23:22, 47309.59 examples/s]
Generating train split: 136070145 examples [2:23:22, 41684.53 examples/s]
Generating train split: 136074578 examples [2:23:23, 41149.03 examples/s]
Generating train split: 136078870 examples [2:23:23, 40242.62 examples/s]
Generating train split: 136083142 examples [2:23:23, 40871.43 examples/s]
Generating train split: 136087326 examples [2:23:23, 37122.14 examples/s]
Generating train split: 136091168 examples [2:23:23, 37445.69 examples/s]
Generating train split: 136095179 examples [2:23:23, 38154.73 examples/s]
Generating train split: 136099066 examples [2:23:23, 37782.70 examples/s]
Generating train split: 136103768 examples [2:23:23, 40369.71 examples/s]
Generating train split: 136112634 examples [2:23:23, 54208.40 examples/s]
Generating train split: 136120896 examples [2:23:23, 62441.34 examples/s]
Generating train split: 136127241 examples [2:23:24, 55850.97 examples/s]
Generating train split: 136133019 examples [2:23:24, 50557.28 examples/s]
Generating train split: 136138293 examples [2:23:24, 38916.67 examples/s]
Generating train split: 136142695 examples [2:23:24, 38708.84 examples/s]
Generating train split: 136146925 examples [2:23:24, 37860.58 examples/s]
Generating train split: 136150946 examples [2:23:24, 38180.41 examples/s]
Generating train split: 136158451 examples [2:23:24, 47580.32 examples/s]
Generating train split: 136166224 examples [2:23:25, 55626.84 examples/s]
Generating train split: 136172091 examples [2:23:25, 55395.04 examples/s]
Generating train split: 136177845 examples [2:23:25, 44522.32 examples/s]
Generating train split: 136182777 examples [2:23:25, 40420.97 examples/s]
Generating train split: 136187196 examples [2:23:25, 39044.85 examples/s]
Generating train split: 136191345 examples [2:23:25, 39050.98 examples/s]
Generating train split: 136195429 examples [2:23:25, 37135.34 examples/s]
Generating train split: 136199271 examples [2:23:25, 35284.99 examples/s]
Generating train split: 136202880 examples [2:23:26, 33818.54 examples/s]
Generating train split: 136206319 examples [2:23:26, 33920.22 examples/s]
Generating train split: 136209749 examples [2:23:26, 30491.26 examples/s]
Generating train split: 136213524 examples [2:23:26, 32332.29 examples/s]
Generating train split: 136216845 examples [2:23:26, 30164.87 examples/s]
Generating train split: 136221330 examples [2:23:26, 33978.55 examples/s]
Generating train split: 136224925 examples [2:23:26, 34465.73 examples/s]
Generating train split: 136228459 examples [2:23:26, 31798.73 examples/s]
Generating train split: 136232165 examples [2:23:26, 33191.30 examples/s]
Generating train split: 136235570 examples [2:23:27, 32779.78 examples/s]
Generating train split: 136239249 examples [2:23:27, 33893.60 examples/s]
Generating train split: 136243721 examples [2:23:27, 36967.15 examples/s]
Generating train split: 136247465 examples [2:23:27, 37088.27 examples/s]
Generating train split: 136251216 examples [2:23:27, 37140.05 examples/s]
Generating train split: 136254958 examples [2:23:27, 34142.63 examples/s]
Generating train split: 136258442 examples [2:23:27, 33869.85 examples/s]
Generating train split: 136262562 examples [2:23:27, 35913.15 examples/s]
Generating train split: 136267148 examples [2:23:27, 38753.57 examples/s]
Generating train split: 136271106 examples [2:23:28, 38990.53 examples/s]
Generating train split: 136275045 examples [2:23:28, 32665.41 examples/s]
Generating train split: 136279245 examples [2:23:28, 35083.63 examples/s]
Generating train split: 136282931 examples [2:23:28, 34702.11 examples/s]
Generating train split: 136287352 examples [2:23:28, 37287.96 examples/s]
Generating train split: 136291583 examples [2:23:28, 38686.34 examples/s]
Generating train split: 136295547 examples [2:23:28, 36666.18 examples/s]
Generating train split: 136299296 examples [2:23:28, 33679.21 examples/s]
Generating train split: 136302764 examples [2:23:28, 32429.55 examples/s]
Generating train split: 136306677 examples [2:23:29, 34213.18 examples/s]
Generating train split: 136313623 examples [2:23:29, 43926.81 examples/s]
Generating train split: 136322521 examples [2:23:29, 56645.98 examples/s]
Generating train split: 136328365 examples [2:23:29, 52054.02 examples/s]
Generating train split: 136333778 examples [2:23:29, 50727.78 examples/s]
Generating train split: 136338990 examples [2:23:29, 47600.26 examples/s]
Generating train split: 136343864 examples [2:23:29, 43033.27 examples/s]
Generating train split: 136348314 examples [2:23:29, 42166.37 examples/s]
Generating train split: 136352623 examples [2:23:30, 41030.65 examples/s]
Generating train split: 136357012 examples [2:23:30, 41742.84 examples/s]
Generating train split: 136361244 examples [2:23:30, 41178.12 examples/s]
Generating train split: 136365398 examples [2:23:30, 38755.08 examples/s]
Generating train split: 136369314 examples [2:23:30, 38025.44 examples/s]
Generating train split: 136373151 examples [2:23:30, 37406.84 examples/s]
Generating train split: 136376906 examples [2:23:30, 34583.57 examples/s]
Generating train split: 136380408 examples [2:23:30, 34120.89 examples/s]
Generating train split: 136383845 examples [2:23:30, 31723.24 examples/s]
Generating train split: 136387922 examples [2:23:31, 34068.20 examples/s]
Generating train split: 136391389 examples [2:23:31, 31958.38 examples/s]
Generating train split: 136395121 examples [2:23:31, 33394.70 examples/s]
Generating train split: 136399084 examples [2:23:31, 35102.83 examples/s]
Generating train split: 136402651 examples [2:23:31, 33076.10 examples/s]
Generating train split: 136406595 examples [2:23:31, 34822.81 examples/s]
Generating train split: 136410141 examples [2:23:31, 33600.61 examples/s]
Generating train split: 136413783 examples [2:23:31, 34380.53 examples/s]
Generating train split: 136417268 examples [2:23:31, 32640.87 examples/s]
Generating train split: 136420579 examples [2:23:32, 31004.95 examples/s]
Generating train split: 136424045 examples [2:23:32, 31975.44 examples/s]
Generating train split: 136427485 examples [2:23:32, 32633.75 examples/s]
Generating train split: 136430811 examples [2:23:32, 32793.84 examples/s]
Generating train split: 136434120 examples [2:23:32, 30899.15 examples/s]
Generating train split: 136437246 examples [2:23:32, 30435.95 examples/s]
Generating train split: 136440314 examples [2:23:32, 29034.00 examples/s]
Generating train split: 136445337 examples [2:23:32, 34907.37 examples/s]
Generating train split: 136453459 examples [2:23:32, 48041.48 examples/s]
Generating train split: 136461627 examples [2:23:32, 57739.37 examples/s]
Generating train split: 136467531 examples [2:23:33, 49461.88 examples/s]
Generating train split: 136472773 examples [2:23:33, 41439.06 examples/s]
Generating train split: 136477307 examples [2:23:33, 33599.26 examples/s]
Generating train split: 136481128 examples [2:23:34, 17422.78 examples/s]
Generating train split: 136484004 examples [2:23:34, 15378.96 examples/s]
Generating train split: 136486335 examples [2:23:34, 15330.27 examples/s]
Generating train split: 136488418 examples [2:23:34, 15147.52 examples/s]
Generating train split: 136490628 examples [2:23:34, 16309.10 examples/s]
Generating train split: 136492617 examples [2:23:34, 16106.05 examples/s]
Generating train split: 136495075 examples [2:23:35, 17858.11 examples/s]
Generating train split: 136497454 examples [2:23:35, 19209.62 examples/s]
Generating train split: 136500101 examples [2:23:35, 20985.17 examples/s]
Generating train split: 136502398 examples [2:23:35, 21490.00 examples/s]
Generating train split: 136505396 examples [2:23:35, 23761.35 examples/s]
Generating train split: 136508876 examples [2:23:35, 26835.44 examples/s]
Generating train split: 136512610 examples [2:23:35, 29811.84 examples/s]
Generating train split: 136515970 examples [2:23:35, 30896.56 examples/s]
Generating train split: 136519212 examples [2:23:35, 31333.63 examples/s]
Generating train split: 136522398 examples [2:23:35, 29485.74 examples/s]
Generating train split: 136526355 examples [2:23:36, 32299.08 examples/s]
Generating train split: 136533322 examples [2:23:36, 43027.19 examples/s]
Generating train split: 136542808 examples [2:23:36, 58108.18 examples/s]
Generating train split: 136548733 examples [2:23:36, 54602.10 examples/s]
Generating train split: 136554318 examples [2:23:36, 45937.87 examples/s]
Generating train split: 136559221 examples [2:23:36, 42816.80 examples/s]
Generating train split: 136563725 examples [2:23:36, 39482.94 examples/s]
Generating train split: 136567850 examples [2:23:36, 39678.53 examples/s]
Generating train split: 136571943 examples [2:23:37, 38509.43 examples/s]
Generating train split: 136575877 examples [2:23:37, 37506.12 examples/s]
Generating train split: 136582435 examples [2:23:37, 44948.06 examples/s]
Generating train split: 136592127 examples [2:23:37, 59230.14 examples/s]
Generating train split: 136598275 examples [2:23:37, 58488.48 examples/s]
Generating train split: 136604295 examples [2:23:37, 51289.12 examples/s]
Generating train split: 136609680 examples [2:23:37, 44642.23 examples/s]
Generating train split: 136614449 examples [2:23:37, 41758.33 examples/s]
Generating train split: 136619885 examples [2:23:37, 44789.38 examples/s]
Generating train split: 136628439 examples [2:23:38, 55219.60 examples/s]
Generating train split: 136635819 examples [2:23:38, 60176.20 examples/s]
Generating train split: 136642129 examples [2:23:38, 50347.83 examples/s]
Generating train split: 136647620 examples [2:23:38, 44200.53 examples/s]
Generating train split: 136652461 examples [2:23:38, 43394.82 examples/s]
Generating train split: 136657081 examples [2:23:38, 39052.40 examples/s]
Generating train split: 136661228 examples [2:23:38, 37052.76 examples/s]
Generating train split: 136665087 examples [2:23:39, 36984.37 examples/s]
Generating train split: 136669046 examples [2:23:39, 37637.84 examples/s]
Generating train split: 136672899 examples [2:23:39, 32695.56 examples/s]
Generating train split: 136676915 examples [2:23:39, 34531.28 examples/s]
Generating train split: 136680989 examples [2:23:39, 36127.84 examples/s]
Generating train split: 136684734 examples [2:23:39, 35039.80 examples/s]
Generating train split: 136688891 examples [2:23:39, 36732.62 examples/s]
Generating train split: 136692666 examples [2:23:39, 36998.87 examples/s]
Generating train split: 136696424 examples [2:23:39, 36020.51 examples/s]
Generating train split: 136700080 examples [2:23:40, 32281.87 examples/s]
Generating train split: 136704920 examples [2:23:40, 36546.67 examples/s]
Generating train split: 136708701 examples [2:23:40, 35578.02 examples/s]
Generating train split: 136712349 examples [2:23:40, 35189.58 examples/s]
Generating train split: 136716700 examples [2:23:40, 37449.34 examples/s]
Generating train split: 136720504 examples [2:23:40, 35339.95 examples/s]
Generating train split: 136724697 examples [2:23:40, 37143.43 examples/s]
Generating train split: 136729096 examples [2:23:40, 39041.85 examples/s]
Generating train split: 136733055 examples [2:23:40, 36657.79 examples/s]
Generating train split: 136736790 examples [2:23:41, 33814.16 examples/s]
Generating train split: 136741200 examples [2:23:41, 36526.02 examples/s]
Generating train split: 136745495 examples [2:23:41, 37986.70 examples/s]
Generating train split: 136749364 examples [2:23:41, 37855.91 examples/s]
Generating train split: 136753197 examples [2:23:41, 36535.55 examples/s]
Generating train split: 136756895 examples [2:23:41, 35655.19 examples/s]
Generating train split: 136760612 examples [2:23:41, 36027.09 examples/s]
Generating train split: 136764247 examples [2:23:41, 33854.48 examples/s]
Generating train split: 136767843 examples [2:23:41, 34433.48 examples/s]
Generating train split: 136771322 examples [2:23:42, 33048.71 examples/s]
Generating train split: 136775634 examples [2:23:42, 35850.99 examples/s]
Generating train split: 136779287 examples [2:23:42, 36031.80 examples/s]
Generating train split: 136782929 examples [2:23:42, 30797.04 examples/s]
Generating train split: 136786431 examples [2:23:42, 31895.89 examples/s]
Generating train split: 136789755 examples [2:23:42, 31937.32 examples/s]
Generating train split: 136793360 examples [2:23:42, 33015.99 examples/s]
Generating train split: 136797589 examples [2:23:42, 35622.43 examples/s]
Generating train split: 136802136 examples [2:23:42, 38448.79 examples/s]
Generating train split: 136806048 examples [2:23:43, 34140.21 examples/s]
Generating train split: 136809593 examples [2:23:43, 31603.52 examples/s]
Generating train split: 136814204 examples [2:23:43, 35374.60 examples/s]
Generating train split: 136818365 examples [2:23:43, 37057.70 examples/s]
Generating train split: 136822195 examples [2:23:43, 37355.12 examples/s]
Generating train split: 136826023 examples [2:23:43, 37038.74 examples/s]
Generating train split: 136830786 examples [2:23:43, 40049.08 examples/s]
Generating train split: 136834846 examples [2:23:43, 38439.60 examples/s]
Generating train split: 136838789 examples [2:23:43, 38719.49 examples/s]
Generating train split: 136842914 examples [2:23:44, 39398.58 examples/s]
Generating train split: 136846891 examples [2:23:44, 37004.40 examples/s]
Generating train split: 136852352 examples [2:23:44, 41934.04 examples/s]
Generating train split: 136857862 examples [2:23:44, 45679.15 examples/s]
Generating train split: 136862506 examples [2:23:44, 44349.25 examples/s]
Generating train split: 136867686 examples [2:23:44, 46473.20 examples/s]
Generating train split: 136872383 examples [2:23:44, 39457.24 examples/s]
Generating train split: 136876537 examples [2:23:44, 37905.85 examples/s]
Generating train split: 136880473 examples [2:23:44, 34648.72 examples/s]
Generating train split: 136884072 examples [2:23:45, 33976.65 examples/s]
Generating train split: 136888351 examples [2:23:45, 36243.28 examples/s]
Generating train split: 136892077 examples [2:23:45, 31882.67 examples/s]
Generating train split: 136895738 examples [2:23:45, 33059.23 examples/s]
Generating train split: 136899196 examples [2:23:45, 33450.61 examples/s]
Generating train split: 136903049 examples [2:23:45, 34831.74 examples/s]
Generating train split: 136906614 examples [2:23:45, 32202.26 examples/s]
Generating train split: 136910202 examples [2:23:45, 33173.88 examples/s]
Generating train split: 136913599 examples [2:23:45, 33378.58 examples/s]
Generating train split: 136921892 examples [2:23:46, 47452.65 examples/s]
Generating train split: 136930025 examples [2:23:46, 57202.34 examples/s]
Generating train split: 136935876 examples [2:23:46, 50090.92 examples/s]
Generating train split: 136941133 examples [2:23:46, 44455.60 examples/s]
Generating train split: 136945841 examples [2:23:46, 44628.62 examples/s]
Generating train split: 136950495 examples [2:23:46, 37895.64 examples/s]
Generating train split: 136954554 examples [2:23:46, 37031.72 examples/s]
Generating train split: 136958449 examples [2:23:47, 34013.28 examples/s]
Generating train split: 136962002 examples [2:23:47, 30926.93 examples/s]
Generating train split: 136966086 examples [2:23:47, 33261.32 examples/s]
Generating train split: 136969557 examples [2:23:47, 33233.50 examples/s]
Generating train split: 136972987 examples [2:23:47, 30914.05 examples/s]
Generating train split: 136976562 examples [2:23:47, 32154.95 examples/s]
Generating train split: 136980023 examples [2:23:47, 32804.61 examples/s]
Generating train split: 136983415 examples [2:23:47, 33110.67 examples/s]
Generating train split: 136987728 examples [2:23:47, 35938.78 examples/s]
Generating train split: 136991848 examples [2:23:47, 37417.23 examples/s]
Generating train split: 136995630 examples [2:23:48, 36881.38 examples/s]
Generating train split: 136999349 examples [2:23:48, 36428.84 examples/s]
Generating train split: 137003195 examples [2:23:48, 37004.36 examples/s]
Generating train split: 137007303 examples [2:23:48, 38185.82 examples/s]
Generating train split: 137011144 examples [2:23:48, 36833.83 examples/s]
Generating train split: 137014851 examples [2:23:48, 33841.41 examples/s]
Generating train split: 137018948 examples [2:23:48, 35712.92 examples/s]
Generating train split: 137023010 examples [2:23:48, 37069.89 examples/s]
Generating train split: 137026767 examples [2:23:48, 36585.52 examples/s]
Generating train split: 137030466 examples [2:23:49, 35611.20 examples/s]
Generating train split: 137034064 examples [2:23:49, 34860.79 examples/s]
Generating train split: 137038544 examples [2:23:49, 37432.20 examples/s]
Generating train split: 137042312 examples [2:23:49, 35923.35 examples/s]
Generating train split: 137046292 examples [2:23:49, 37009.94 examples/s]
Generating train split: 137051808 examples [2:23:49, 42223.14 examples/s]
Generating train split: 137056293 examples [2:23:49, 42967.99 examples/s]
Generating train split: 137060658 examples [2:23:49, 43141.71 examples/s]
Generating train split: 137065004 examples [2:23:49, 40529.53 examples/s]
Generating train split: 137069109 examples [2:23:50, 37915.05 examples/s]
Generating train split: 137072961 examples [2:23:50, 35747.20 examples/s]
Generating train split: 137077473 examples [2:23:50, 38239.17 examples/s]
Generating train split: 137081370 examples [2:23:50, 35956.56 examples/s]
Generating train split: 137085029 examples [2:23:50, 35675.20 examples/s]
Generating train split: 137088650 examples [2:23:50, 35814.78 examples/s]
Generating train split: 137092264 examples [2:23:50, 35748.91 examples/s]
Generating train split: 137096024 examples [2:23:50, 36269.11 examples/s]
Generating train split: 137099679 examples [2:23:50, 35797.76 examples/s]
Generating train split: 137103273 examples [2:23:51, 33419.03 examples/s]
Generating train split: 137106933 examples [2:23:51, 34289.01 examples/s]
Generating train split: 137111104 examples [2:23:51, 36380.68 examples/s]
Generating train split: 137115010 examples [2:23:51, 37128.99 examples/s]
Generating train split: 137118995 examples [2:23:51, 37879.80 examples/s]
Generating train split: 137122805 examples [2:23:51, 37150.42 examples/s]
Generating train split: 137126545 examples [2:23:51, 34343.24 examples/s]
Generating train split: 137130359 examples [2:23:51, 35314.50 examples/s]
Generating train split: 137133993 examples [2:23:51, 35596.52 examples/s]
Generating train split: 137141730 examples [2:23:51, 47625.17 examples/s]
Generating train split: 137150313 examples [2:23:52, 58751.27 examples/s]
Generating train split: 137156279 examples [2:23:52, 43332.01 examples/s]
Generating train split: 137161251 examples [2:23:52, 42489.72 examples/s]
Generating train split: 137165941 examples [2:23:52, 39649.00 examples/s]
Generating train split: 137170686 examples [2:23:52, 41505.18 examples/s]
Generating train split: 137175114 examples [2:23:52, 35329.41 examples/s]
Generating train split: 137179570 examples [2:23:52, 37481.08 examples/s]
Generating train split: 137187608 examples [2:23:53, 48205.15 examples/s]
Generating train split: 137195529 examples [2:23:53, 56356.65 examples/s]
Generating train split: 137201575 examples [2:23:53, 54829.09 examples/s]
Generating train split: 137207352 examples [2:23:53, 45098.38 examples/s]
Generating train split: 137212457 examples [2:23:53, 46500.93 examples/s]
Generating train split: 137217465 examples [2:23:53, 44779.19 examples/s]
Generating train split: 137222200 examples [2:23:53, 44771.96 examples/s]
Generating train split: 137226858 examples [2:23:53, 39966.51 examples/s]
Generating train split: 137231046 examples [2:23:54, 39957.29 examples/s]
Generating train split: 137235177 examples [2:23:54, 38233.65 examples/s]
Generating train split: 137239096 examples [2:23:54, 38044.19 examples/s]
Generating train split: 137244090 examples [2:23:54, 41225.91 examples/s]
Generating train split: 137248297 examples [2:23:54, 41205.52 examples/s]
Generating train split: 137252473 examples [2:23:54, 38409.01 examples/s]
Generating train split: 137257298 examples [2:23:54, 41076.53 examples/s]
Generating train split: 137261479 examples [2:23:54, 39570.56 examples/s]
Generating train split: 137265498 examples [2:23:54, 37832.50 examples/s]
Generating train split: 137269408 examples [2:23:55, 38179.66 examples/s]
Generating train split: 137273271 examples [2:23:55, 35885.91 examples/s]
Generating train split: 137278775 examples [2:23:55, 41099.97 examples/s]
Generating train split: 137282974 examples [2:23:55, 35302.21 examples/s]
Generating train split: 137287476 examples [2:23:55, 37361.46 examples/s]
Generating train split: 137291796 examples [2:23:55, 38891.25 examples/s]
Generating train split: 137295822 examples [2:23:55, 39065.44 examples/s]
Generating train split: 137300292 examples [2:23:55, 40644.41 examples/s]
Generating train split: 137304443 examples [2:23:55, 36347.67 examples/s]
Generating train split: 137309167 examples [2:23:56, 39249.96 examples/s]
Generating train split: 137313226 examples [2:23:56, 35144.58 examples/s]
Generating train split: 137317651 examples [2:23:56, 37494.92 examples/s]
Generating train split: 137321880 examples [2:23:56, 38784.40 examples/s]
Generating train split: 137325884 examples [2:23:56, 36885.10 examples/s]
Generating train split: 137330489 examples [2:23:56, 39380.71 examples/s]
Generating train split: 137335370 examples [2:23:56, 42010.37 examples/s]
Generating train split: 137339661 examples [2:23:56, 39206.39 examples/s]
Generating train split: 137343677 examples [2:23:56, 39010.98 examples/s]
Generating train split: 137347642 examples [2:23:57, 35332.18 examples/s]
Generating train split: 137351554 examples [2:23:57, 35923.84 examples/s]
Generating train split: 137355988 examples [2:23:57, 38209.04 examples/s]
Generating train split: 137359889 examples [2:23:57, 38105.44 examples/s]
Generating train split: 137363758 examples [2:23:57, 37430.95 examples/s]
Generating train split: 137367911 examples [2:23:57, 38594.41 examples/s]
Generating train split: 137371816 examples [2:23:57, 38641.33 examples/s]
Generating train split: 137375905 examples [2:23:57, 39266.70 examples/s]
Generating train split: 137380154 examples [2:23:57, 40187.50 examples/s]
Generating train split: 137384200 examples [2:23:58, 38059.29 examples/s]
Generating train split: 137389216 examples [2:23:58, 41481.08 examples/s]
Generating train split: 137393404 examples [2:23:58, 39001.65 examples/s]
Generating train split: 137397359 examples [2:23:58, 36814.58 examples/s]
Generating train split: 137401098 examples [2:23:58, 34924.11 examples/s]
Generating train split: 137405055 examples [2:23:58, 36156.39 examples/s]
Generating train split: 137409068 examples [2:23:58, 36996.85 examples/s]
Generating train split: 137412805 examples [2:23:58, 36729.63 examples/s]
Generating train split: 137416517 examples [2:23:58, 35214.67 examples/s]
Generating train split: 137420766 examples [2:23:59, 37229.62 examples/s]
Generating train split: 137424524 examples [2:23:59, 35177.15 examples/s]
Generating train split: 137428556 examples [2:23:59, 36600.84 examples/s]
Generating train split: 137432266 examples [2:23:59, 36274.90 examples/s]
Generating train split: 137436221 examples [2:23:59, 37206.64 examples/s]
Generating train split: 137440888 examples [2:23:59, 39940.27 examples/s]
Generating train split: 137444919 examples [2:23:59, 38107.00 examples/s]
Generating train split: 137449961 examples [2:23:59, 41594.33 examples/s]
Generating train split: 137454170 examples [2:23:59, 40379.26 examples/s]
Generating train split: 137458446 examples [2:23:59, 41041.99 examples/s]
Generating train split: 137463346 examples [2:24:00, 43344.52 examples/s]
Generating train split: 137467721 examples [2:24:00, 39461.28 examples/s]
Generating train split: 137472572 examples [2:24:00, 41946.52 examples/s]
Generating train split: 137476853 examples [2:24:00, 37897.19 examples/s]
Generating train split: 137480766 examples [2:24:00, 37700.51 examples/s]
Generating train split: 137484787 examples [2:24:00, 38368.15 examples/s]
Generating train split: 137488693 examples [2:24:00, 36677.97 examples/s]
Generating train split: 137492987 examples [2:24:00, 38341.44 examples/s]
Generating train split: 137496875 examples [2:24:00, 37226.69 examples/s]
Generating train split: 137502042 examples [2:24:01, 41270.96 examples/s]
Generating train split: 137511483 examples [2:24:01, 56471.10 examples/s]
Generating train split: 137518961 examples [2:24:01, 61767.66 examples/s]
Generating train split: 137525245 examples [2:24:01, 51565.92 examples/s]
Generating train split: 137530752 examples [2:24:01, 50651.58 examples/s]
Generating train split: 137539740 examples [2:24:01, 60939.90 examples/s]
Generating train split: 137548372 examples [2:24:01, 66891.68 examples/s]
Generating train split: 137555334 examples [2:24:01, 55888.28 examples/s]
Generating train split: 137561394 examples [2:24:02, 53372.31 examples/s]
Generating train split: 137567050 examples [2:24:02, 48526.16 examples/s]
Generating train split: 137572165 examples [2:24:02, 46249.40 examples/s]
Generating train split: 137576966 examples [2:24:02, 43209.47 examples/s]
Generating train split: 137581410 examples [2:24:02, 43425.48 examples/s]
Generating train split: 137585850 examples [2:24:02, 40459.15 examples/s]
Generating train split: 137590128 examples [2:24:02, 41032.84 examples/s]
Generating train split: 137594387 examples [2:24:02, 41433.44 examples/s]
Generating train split: 137598581 examples [2:24:03, 41474.96 examples/s]
Generating train split: 137602767 examples [2:24:03, 37247.66 examples/s]
Generating train split: 137607017 examples [2:24:03, 38636.56 examples/s]
Generating train split: 137610968 examples [2:24:03, 36748.68 examples/s]
Generating train split: 137614723 examples [2:24:03, 36854.80 examples/s]
Generating train split: 137618974 examples [2:24:03, 38423.01 examples/s]
Generating train split: 137623719 examples [2:24:03, 40944.66 examples/s]
Generating train split: 137627860 examples [2:24:03, 40310.70 examples/s]
Generating train split: 137631931 examples [2:24:03, 40180.48 examples/s]
Generating train split: 137635974 examples [2:24:03, 38584.59 examples/s]
Generating train split: 137639872 examples [2:24:04, 37265.72 examples/s]
Generating train split: 137643632 examples [2:24:04, 37336.87 examples/s]
Generating train split: 137647392 examples [2:24:04, 36505.44 examples/s]
Generating train split: 137651165 examples [2:24:04, 36844.59 examples/s]
Generating train split: 137656000 examples [2:24:04, 40153.13 examples/s]
Generating train split: 137660576 examples [2:24:04, 41760.84 examples/s]
Generating train split: 137664771 examples [2:24:04, 39383.70 examples/s]
Generating train split: 137668759 examples [2:24:04, 39055.65 examples/s]
Generating train split: 137672696 examples [2:24:04, 37741.72 examples/s]
Generating train split: 137676553 examples [2:24:05, 37954.12 examples/s]
Generating train split: 137680373 examples [2:24:05, 37858.63 examples/s]
Generating train split: 137684187 examples [2:24:05, 37930.91 examples/s]
Generating train split: 137687993 examples [2:24:05, 35625.87 examples/s]
Generating train split: 137691587 examples [2:24:05, 34043.22 examples/s]
Generating train split: 137695747 examples [2:24:05, 36027.35 examples/s]
Generating train split: 137699395 examples [2:24:05, 35060.00 examples/s]
Generating train split: 137702936 examples [2:24:05, 34008.65 examples/s]
Generating train split: 137706367 examples [2:24:05, 32214.94 examples/s]
Generating train split: 137709801 examples [2:24:06, 32329.82 examples/s]
Generating train split: 137713472 examples [2:24:06, 33543.79 examples/s]
Generating train split: 137717414 examples [2:24:06, 35191.06 examples/s]
Generating train split: 137721590 examples [2:24:06, 37074.29 examples/s]
Generating train split: 137725333 examples [2:24:06, 36072.79 examples/s]
Generating train split: 137729534 examples [2:24:06, 37771.19 examples/s]
Generating train split: 137733643 examples [2:24:06, 38657.39 examples/s]
Generating train split: 137737532 examples [2:24:06, 37128.81 examples/s]
Generating train split: 137741917 examples [2:24:06, 39048.39 examples/s]
Generating train split: 137745859 examples [2:24:06, 37143.99 examples/s]
Generating train split: 137750433 examples [2:24:07, 39548.42 examples/s]
Generating train split: 137754433 examples [2:24:07, 37894.72 examples/s]
Generating train split: 137758526 examples [2:24:07, 38724.97 examples/s]
Generating train split: 137762430 examples [2:24:07, 38073.94 examples/s]
Generating train split: 137766769 examples [2:24:07, 39585.10 examples/s]
Generating train split: 137770755 examples [2:24:07, 37595.62 examples/s]
Generating train split: 137774554 examples [2:24:07, 34866.72 examples/s]
Generating train split: 137778541 examples [2:24:07, 36211.31 examples/s]
Generating train split: 137782224 examples [2:24:07, 35225.23 examples/s]
Generating train split: 137786256 examples [2:24:08, 36630.60 examples/s]
Generating train split: 137790366 examples [2:24:08, 37876.86 examples/s]
Generating train split: 137794198 examples [2:24:08, 35995.60 examples/s]
Generating train split: 137797845 examples [2:24:08, 34148.04 examples/s]
Generating train split: 137801310 examples [2:24:08, 32476.32 examples/s]
Generating train split: 137805850 examples [2:24:08, 35836.43 examples/s]
Generating train split: 137809500 examples [2:24:08, 34468.34 examples/s]
Generating train split: 137814047 examples [2:24:08, 37497.06 examples/s]
Generating train split: 137817854 examples [2:24:08, 34861.11 examples/s]
Generating train split: 137821421 examples [2:24:09, 31803.84 examples/s]
Generating train split: 137824688 examples [2:24:09, 30933.31 examples/s]
Generating train split: 137828268 examples [2:24:09, 32151.48 examples/s]
Generating train split: 137834406 examples [2:24:09, 40141.16 examples/s]
Generating train split: 137843282 examples [2:24:09, 53792.80 examples/s]
Generating train split: 137851136 examples [2:24:09, 60877.85 examples/s]
Generating train split: 137857380 examples [2:24:09, 49829.28 examples/s]
Generating train split: 137862795 examples [2:24:09, 43185.23 examples/s]
Generating train split: 137867813 examples [2:24:10, 44807.81 examples/s]
Generating train split: 137872637 examples [2:24:10, 42859.83 examples/s]
Generating train split: 137877169 examples [2:24:10, 41137.94 examples/s]
Generating train split: 137881449 examples [2:24:10, 40297.30 examples/s]
Generating train split: 137885588 examples [2:24:10, 40349.59 examples/s]
Generating train split: 137889700 examples [2:24:10, 39613.95 examples/s]
Generating train split: 137894493 examples [2:24:10, 41877.74 examples/s]
Generating train split: 137898739 examples [2:24:10, 41190.13 examples/s]
Generating train split: 137902908 examples [2:24:10, 40375.72 examples/s]
Generating train split: 137907281 examples [2:24:11, 41153.43 examples/s]
Generating train split: 137911422 examples [2:24:11, 38265.08 examples/s]
Generating train split: 137915340 examples [2:24:11, 38502.08 examples/s]
Generating train split: 137919530 examples [2:24:11, 39456.26 examples/s]
Generating train split: 137923514 examples [2:24:11, 37897.04 examples/s]
Generating train split: 137927344 examples [2:24:11, 37370.35 examples/s]
Generating train split: 137931494 examples [2:24:11, 38468.21 examples/s]
Generating train split: 137935477 examples [2:24:11, 38858.45 examples/s]
Generating train split: 137940552 examples [2:24:11, 42239.94 examples/s]
Generating train split: 137944809 examples [2:24:12, 42062.66 examples/s]
Generating train split: 137949029 examples [2:24:12, 38388.39 examples/s]
Generating train split: 137952938 examples [2:24:12, 36312.65 examples/s]
Generating train split: 137956842 examples [2:24:12, 37051.05 examples/s]
Generating train split: 137960776 examples [2:24:12, 37645.10 examples/s]
Generating train split: 137964585 examples [2:24:12, 37736.45 examples/s]
Generating train split: 137968910 examples [2:24:12, 39308.05 examples/s]
Generating train split: 137973241 examples [2:24:12, 40468.08 examples/s]
Generating train split: 137977322 examples [2:24:12, 40025.15 examples/s]
Generating train split: 137986209 examples [2:24:12, 54341.53 examples/s]
Generating train split: 137994612 examples [2:24:13, 63093.86 examples/s]
Generating train split: 138000975 examples [2:24:13, 53810.25 examples/s]
Generating train split: 138006628 examples [2:24:13, 45821.26 examples/s]
Generating train split: 138011579 examples [2:24:13, 41546.53 examples/s]
Generating train split: 138016032 examples [2:24:13, 37172.84 examples/s]
Generating train split: 138019984 examples [2:24:13, 36703.39 examples/s]
Generating train split: 138023822 examples [2:24:13, 35462.57 examples/s]
Generating train split: 138027471 examples [2:24:14, 34909.29 examples/s]
Generating train split: 138031668 examples [2:24:14, 36708.89 examples/s]
Generating train split: 138035425 examples [2:24:14, 32950.50 examples/s]
Generating train split: 138039131 examples [2:24:14, 33979.11 examples/s]
Generating train split: 138046564 examples [2:24:14, 44726.08 examples/s]
Generating train split: 138055631 examples [2:24:14, 57397.23 examples/s]
Generating train split: 138062451 examples [2:24:14, 60449.30 examples/s]
Generating train split: 138068689 examples [2:24:14, 50821.21 examples/s]
Generating train split: 138074168 examples [2:24:15, 47348.86 examples/s]
Generating train split: 138079198 examples [2:24:15, 44186.33 examples/s]
Generating train split: 138083841 examples [2:24:15, 43247.32 examples/s]
Generating train split: 138088308 examples [2:24:15, 42254.47 examples/s]
Generating train split: 138092628 examples [2:24:15, 37942.58 examples/s]
Generating train split: 138096547 examples [2:24:15, 37574.98 examples/s]
Generating train split: 138100386 examples [2:24:15, 36093.54 examples/s]
Generating train split: 138104097 examples [2:24:15, 36355.38 examples/s]
Generating train split: 138108543 examples [2:24:15, 38522.34 examples/s]
Generating train split: 138112456 examples [2:24:16, 37180.47 examples/s]
Generating train split: 138116212 examples [2:24:16, 37067.58 examples/s]
Generating train split: 138120388 examples [2:24:16, 38369.37 examples/s]
Generating train split: 138124254 examples [2:24:16, 35031.99 examples/s]
Generating train split: 138127835 examples [2:24:16, 32038.07 examples/s]
Generating train split: 138131123 examples [2:24:16, 30111.40 examples/s]
Generating train split: 138136192 examples [2:24:16, 35422.95 examples/s]
Generating train split: 138140323 examples [2:24:16, 37003.95 examples/s]
Generating train split: 138144133 examples [2:24:16, 36520.42 examples/s]
Generating train split: 138148257 examples [2:24:17, 37836.19 examples/s]
Generating train split: 138152571 examples [2:24:17, 39333.93 examples/s]
Generating train split: 138156629 examples [2:24:17, 39678.35 examples/s]
Generating train split: 138161469 examples [2:24:17, 42211.94 examples/s]
Generating train split: 138165748 examples [2:24:17, 42373.58 examples/s]
Generating train split: 138170015 examples [2:24:17, 42047.84 examples/s]
Generating train split: 138174245 examples [2:24:17, 40083.31 examples/s]
Generating train split: 138178675 examples [2:24:17, 41281.38 examples/s]
Generating train split: 138182837 examples [2:24:17, 37777.81 examples/s]
Generating train split: 138187912 examples [2:24:18, 41330.45 examples/s]
Generating train split: 138192132 examples [2:24:18, 39643.98 examples/s]
Generating train split: 138196162 examples [2:24:18, 38709.30 examples/s]
Generating train split: 138200155 examples [2:24:18, 39045.94 examples/s]
Generating train split: 138204108 examples [2:24:18, 38874.13 examples/s]
Generating train split: 138209276 examples [2:24:18, 42163.41 examples/s]
Generating train split: 138214888 examples [2:24:18, 46174.06 examples/s]
Generating train split: 138219537 examples [2:24:18, 41222.79 examples/s]
Generating train split: 138224509 examples [2:24:18, 43500.01 examples/s]
Generating train split: 138228964 examples [2:24:19, 40836.31 examples/s]
Generating train split: 138233429 examples [2:24:19, 41864.66 examples/s]
Generating train split: 138237702 examples [2:24:19, 39168.81 examples/s]
Generating train split: 138242618 examples [2:24:19, 41843.63 examples/s]
Generating train split: 138246936 examples [2:24:19, 42211.57 examples/s]
Generating train split: 138251223 examples [2:24:19, 38902.89 examples/s]
Generating train split: 138255565 examples [2:24:19, 40127.40 examples/s]
Generating train split: 138259652 examples [2:24:19, 38800.86 examples/s]
Generating train split: 138264079 examples [2:24:19, 40309.58 examples/s]
Generating train split: 138268161 examples [2:24:20, 40064.47 examples/s]
Generating train split: 138272216 examples [2:24:20, 36910.54 examples/s]
Generating train split: 138275979 examples [2:24:20, 36759.63 examples/s]
Generating train split: 138280049 examples [2:24:20, 37831.15 examples/s]
Generating train split: 138284471 examples [2:24:20, 39635.33 examples/s]
Generating train split: 138289204 examples [2:24:20, 41796.08 examples/s]
Generating train split: 138293434 examples [2:24:20, 41594.63 examples/s]
Generating train split: 138297976 examples [2:24:20, 42565.85 examples/s]
Generating train split: 138302258 examples [2:24:20, 41982.20 examples/s]
Generating train split: 138306482 examples [2:24:20, 40696.08 examples/s]
Generating train split: 138310636 examples [2:24:21, 40931.80 examples/s]
Generating train split: 138315304 examples [2:24:21, 42590.61 examples/s]
Generating train split: 138319586 examples [2:24:21, 39680.10 examples/s]
Generating train split: 138324532 examples [2:24:21, 42407.84 examples/s]
Generating train split: 138328828 examples [2:24:21, 42210.03 examples/s]
Generating train split: 138333092 examples [2:24:21, 39405.68 examples/s]
Generating train split: 138337811 examples [2:24:21, 41548.79 examples/s]
Generating train split: 138342031 examples [2:24:21, 38602.60 examples/s]
Generating train split: 138345964 examples [2:24:21, 37202.51 examples/s]
Generating train split: 138350198 examples [2:24:22, 38582.28 examples/s]
Generating train split: 138356490 examples [2:24:22, 45382.77 examples/s]
Generating train split: 138364884 examples [2:24:22, 56381.44 examples/s]
Generating train split: 138370654 examples [2:24:22, 50710.71 examples/s]
Generating train split: 138375907 examples [2:24:22, 47526.89 examples/s]
Generating train split: 138380814 examples [2:24:22, 45265.80 examples/s]
Generating train split: 138385460 examples [2:24:22, 45253.65 examples/s]
Generating train split: 138390061 examples [2:24:22, 44990.68 examples/s]
Generating train split: 138394612 examples [2:24:22, 44440.52 examples/s]
Generating train split: 138399100 examples [2:24:23, 43648.54 examples/s]
Generating train split: 138403490 examples [2:24:23, 41458.68 examples/s]
Generating train split: 138408125 examples [2:24:23, 42699.37 examples/s]
Generating train split: 138412432 examples [2:24:23, 42583.58 examples/s]
Generating train split: 138416840 examples [2:24:23, 42989.31 examples/s]
Generating train split: 138421155 examples [2:24:23, 41842.50 examples/s]
Generating train split: 138425357 examples [2:24:23, 40935.64 examples/s]
Generating train split: 138429466 examples [2:24:23, 40217.50 examples/s]
Generating train split: 138434868 examples [2:24:23, 44153.07 examples/s]
Generating train split: 138439322 examples [2:24:24, 44173.56 examples/s]
Generating train split: 138443764 examples [2:24:24, 37145.77 examples/s]
Generating train split: 138447681 examples [2:24:24, 37097.44 examples/s]
Generating train split: 138451530 examples [2:24:24, 37411.73 examples/s]
Generating train split: 138455700 examples [2:24:24, 38592.43 examples/s]
Generating train split: 138460411 examples [2:24:24, 40884.97 examples/s]
Generating train split: 138464573 examples [2:24:24, 39763.27 examples/s]
Generating train split: 138468611 examples [2:24:24, 39743.50 examples/s]
Generating train split: 138472622 examples [2:24:24, 38478.64 examples/s]
Generating train split: 138477145 examples [2:24:25, 40345.16 examples/s]
Generating train split: 138481213 examples [2:24:25, 39400.51 examples/s]
Generating train split: 138487925 examples [2:24:25, 47334.02 examples/s]
Generating train split: 138496825 examples [2:24:25, 59423.21 examples/s]
Generating train split: 138504286 examples [2:24:25, 63867.03 examples/s]
Generating train split: 138510743 examples [2:24:25, 51270.15 examples/s]
Generating train split: 138516311 examples [2:24:25, 46409.41 examples/s]
Generating train split: 138521320 examples [2:24:25, 42808.39 examples/s]
Generating train split: 138525874 examples [2:24:26, 40673.55 examples/s]
Generating train split: 138530126 examples [2:24:26, 38254.53 examples/s]
Generating train split: 138534908 examples [2:24:26, 40576.64 examples/s]
Generating train split: 138539114 examples [2:24:26, 39154.63 examples/s]
Generating train split: 138546494 examples [2:24:26, 48170.43 examples/s]
Generating train split: 138556048 examples [2:24:26, 60996.40 examples/s]
Generating train split: 138562429 examples [2:24:26, 60406.85 examples/s]
Generating train split: 138568673 examples [2:24:26, 52354.13 examples/s]
Generating train split: 138574218 examples [2:24:27, 47097.64 examples/s]
Generating train split: 138579209 examples [2:24:27, 45115.67 examples/s]
Generating train split: 138583908 examples [2:24:27, 43763.36 examples/s]
Generating train split: 138588415 examples [2:24:27, 42779.64 examples/s]
Generating train split: 138592782 examples [2:24:27, 40944.42 examples/s]
Generating train split: 138597063 examples [2:24:27, 41426.67 examples/s]
Generating train split: 138601432 examples [2:24:27, 41963.53 examples/s]
Generating train split: 138605665 examples [2:24:27, 39521.34 examples/s]
Generating train split: 138610451 examples [2:24:27, 41776.65 examples/s]
Generating train split: 138615357 examples [2:24:28, 43806.46 examples/s]
Generating train split: 138619793 examples [2:24:28, 43042.65 examples/s]
Generating train split: 138624141 examples [2:24:28, 39388.49 examples/s]
Generating train split: 138628547 examples [2:24:28, 40652.67 examples/s]
Generating train split: 138632681 examples [2:24:28, 40612.43 examples/s]
Generating train split: 138637325 examples [2:24:28, 42233.40 examples/s]
Generating train split: 138641598 examples [2:24:28, 41805.51 examples/s]
Generating train split: 138645812 examples [2:24:28, 38733.69 examples/s]
Generating train split: 138650310 examples [2:24:28, 40427.02 examples/s]
Generating train split: 138654812 examples [2:24:28, 41723.99 examples/s]
Generating train split: 138659031 examples [2:24:29, 40900.64 examples/s]
Generating train split: 138664736 examples [2:24:29, 45524.02 examples/s]
Generating train split: 138669338 examples [2:24:29, 41727.09 examples/s]
Generating train split: 138673603 examples [2:24:29, 41289.20 examples/s]
Generating train split: 138677902 examples [2:24:29, 41732.08 examples/s]
Generating train split: 138682128 examples [2:24:29, 41731.24 examples/s]
Generating train split: 138691287 examples [2:24:29, 56099.16 examples/s]
Generating train split: 138699486 examples [2:24:29, 63639.66 examples/s]
Generating train split: 138705938 examples [2:24:29, 54193.68 examples/s]
Generating train split: 138711650 examples [2:24:30, 51751.33 examples/s]
Generating train split: 138717049 examples [2:24:30, 46249.11 examples/s]
Generating train split: 138722353 examples [2:24:30, 47926.13 examples/s]
Generating train split: 138727351 examples [2:24:30, 46256.47 examples/s]
Generating train split: 138732112 examples [2:24:30, 45565.18 examples/s]
Generating train split: 138737448 examples [2:24:30, 47649.53 examples/s]
Generating train split: 138742299 examples [2:24:30, 40271.57 examples/s]
Generating train split: 138746563 examples [2:24:30, 38743.88 examples/s]
Generating train split: 138751380 examples [2:24:31, 41124.64 examples/s]
Generating train split: 138755657 examples [2:24:31, 39411.99 examples/s]
Generating train split: 138759711 examples [2:24:31, 38323.72 examples/s]
Generating train split: 138763617 examples [2:24:31, 38037.96 examples/s]
Generating train split: 138767596 examples [2:24:31, 38444.71 examples/s]
Generating train split: 138773432 examples [2:24:31, 43983.09 examples/s]
Generating train split: 138777903 examples [2:24:31, 41835.50 examples/s]
Generating train split: 138782150 examples [2:24:31, 41274.88 examples/s]
Generating train split: 138786550 examples [2:24:31, 42030.59 examples/s]
Generating train split: 138794266 examples [2:24:32, 52082.93 examples/s]
Generating train split: 138803341 examples [2:24:32, 63234.80 examples/s]
Generating train split: 138809759 examples [2:24:32, 50993.62 examples/s]
Generating train split: 138815297 examples [2:24:32, 46114.53 examples/s]
Generating train split: 138820267 examples [2:24:32, 45214.26 examples/s]
Generating train split: 138825035 examples [2:24:32, 45288.12 examples/s]
Generating train split: 138829745 examples [2:24:32, 42891.07 examples/s]
Generating train split: 138834653 examples [2:24:32, 44482.41 examples/s]
Generating train split: 138839221 examples [2:24:33, 44181.69 examples/s]
Generating train split: 138843730 examples [2:24:33, 37720.18 examples/s]
Generating train split: 138847698 examples [2:24:33, 38139.10 examples/s]
Generating train split: 138852010 examples [2:24:33, 39387.32 examples/s]
Generating train split: 138856378 examples [2:24:33, 40533.39 examples/s]
Generating train split: 138860530 examples [2:24:33, 40556.64 examples/s]
Generating train split: 138864652 examples [2:24:33, 36309.50 examples/s]
Generating train split: 138868468 examples [2:24:33, 36671.88 examples/s]
Generating train split: 138872237 examples [2:24:33, 35613.15 examples/s]
Generating train split: 138875967 examples [2:24:34, 36073.91 examples/s]
Generating train split: 138879632 examples [2:24:34, 35721.30 examples/s]
Generating train split: 138884166 examples [2:24:34, 38446.24 examples/s]
Generating train split: 138888558 examples [2:24:34, 39977.52 examples/s]
Generating train split: 138892806 examples [2:24:34, 40666.05 examples/s]
Generating train split: 138897339 examples [2:24:34, 41879.38 examples/s]
Generating train split: 138902390 examples [2:24:34, 44412.58 examples/s]
Generating train split: 138908545 examples [2:24:34, 49485.43 examples/s]
Generating train split: 138917091 examples [2:24:34, 60177.59 examples/s]
Generating train split: 138925571 examples [2:24:34, 67516.21 examples/s]
Generating train split: 138932354 examples [2:24:35, 59914.25 examples/s]
Generating train split: 138938519 examples [2:24:35, 55328.15 examples/s]
Generating train split: 138944230 examples [2:24:35, 51983.09 examples/s]
Generating train split: 138949569 examples [2:24:35, 49390.13 examples/s]
Generating train split: 138954603 examples [2:24:35, 43397.19 examples/s]
Generating train split: 138959112 examples [2:24:35, 41723.82 examples/s]
Generating train split: 138963392 examples [2:24:35, 39500.64 examples/s]
Generating train split: 138967632 examples [2:24:35, 40213.52 examples/s]
Generating train split: 138971715 examples [2:24:36, 40042.19 examples/s]
Generating train split: 138975849 examples [2:24:36, 40376.25 examples/s]
Generating train split: 138980351 examples [2:24:36, 41668.29 examples/s]
Generating train split: 138984549 examples [2:24:36, 41382.16 examples/s]
Generating train split: 138988737 examples [2:24:36, 41519.74 examples/s]
Generating train split: 138992906 examples [2:24:36, 41507.65 examples/s]
Generating train split: 138997332 examples [2:24:36, 42282.71 examples/s]
Generating train split: 139002157 examples [2:24:36, 44030.91 examples/s]
Generating train split: 139006570 examples [2:24:36, 42169.31 examples/s]
Generating train split: 139010826 examples [2:24:37, 39873.05 examples/s]
Generating train split: 139016154 examples [2:24:37, 43624.97 examples/s]
Generating train split: 139020581 examples [2:24:37, 42005.28 examples/s]
Generating train split: 139025192 examples [2:24:37, 43156.37 examples/s]
Generating train split: 139029552 examples [2:24:37, 40319.44 examples/s]
Generating train split: 139034363 examples [2:24:37, 42468.57 examples/s]
Generating train split: 139038800 examples [2:24:37, 42960.91 examples/s]
Generating train split: 139044633 examples [2:24:37, 47340.76 examples/s]
Generating train split: 139049742 examples [2:24:37, 48421.80 examples/s]
Generating train split: 139054985 examples [2:24:37, 49284.19 examples/s]
Generating train split: 139059943 examples [2:24:38, 44400.76 examples/s]
Generating train split: 139064501 examples [2:24:38, 42194.69 examples/s]
Generating train split: 139068808 examples [2:24:38, 42415.03 examples/s]
Generating train split: 139073121 examples [2:24:38, 41370.00 examples/s]
Generating train split: 139078030 examples [2:24:38, 43512.12 examples/s]
Generating train split: 139082429 examples [2:24:38, 42043.23 examples/s]
Generating train split: 139088347 examples [2:24:38, 46857.65 examples/s]
Generating train split: 139093097 examples [2:24:38, 45141.83 examples/s]
Generating train split: 139097664 examples [2:24:38, 43327.17 examples/s]
Generating train split: 139102948 examples [2:24:39, 45971.05 examples/s]
Generating train split: 139107994 examples [2:24:39, 47215.89 examples/s]
Generating train split: 139112891 examples [2:24:39, 47712.82 examples/s]
Generating train split: 139117694 examples [2:24:39, 45307.78 examples/s]
Generating train split: 139122276 examples [2:24:39, 44020.00 examples/s]
Generating train split: 139126712 examples [2:24:39, 43708.85 examples/s]
Generating train split: 139131110 examples [2:24:39, 43776.89 examples/s]
Generating train split: 139135808 examples [2:24:39, 44680.54 examples/s]
Generating train split: 139140297 examples [2:24:39, 42137.26 examples/s]
Generating train split: 139144887 examples [2:24:40, 43194.06 examples/s]
Generating train split: 139149609 examples [2:24:40, 44334.89 examples/s]
Generating train split: 139154079 examples [2:24:40, 41286.03 examples/s]
Generating train split: 139159981 examples [2:24:40, 46223.05 examples/s]
Generating train split: 139168860 examples [2:24:40, 58322.13 examples/s]
Generating train split: 139175665 examples [2:24:40, 61126.34 examples/s]
Generating train split: 139181871 examples [2:24:40, 50688.37 examples/s]
Generating train split: 139187299 examples [2:24:40, 48899.55 examples/s]
Generating train split: 139192443 examples [2:24:41, 45078.59 examples/s]
Generating train split: 139197153 examples [2:24:41, 41484.65 examples/s]
Generating train split: 139201670 examples [2:24:41, 42351.22 examples/s]
Generating train split: 139206042 examples [2:24:41, 41325.26 examples/s]
Generating train split: 139210969 examples [2:24:41, 43424.28 examples/s]
Generating train split: 139215413 examples [2:24:41, 43399.32 examples/s]
Generating train split: 139219821 examples [2:24:41, 42005.84 examples/s]
Generating train split: 139224320 examples [2:24:41, 42740.07 examples/s]
Generating train split: 139228796 examples [2:24:41, 43309.71 examples/s]
Generating train split: 139234723 examples [2:24:41, 47914.27 examples/s]
Generating train split: 139239557 examples [2:24:42, 47634.00 examples/s]
Generating train split: 139244352 examples [2:24:42, 45797.84 examples/s]
Generating train split: 139248976 examples [2:24:42, 41794.63 examples/s]
Generating train split: 139253240 examples [2:24:42, 39698.55 examples/s]
Generating train split: 139257277 examples [2:24:42, 37780.30 examples/s]
Generating train split: 139261115 examples [2:24:42, 37677.68 examples/s]
Generating train split: 139264921 examples [2:24:42, 36201.86 examples/s]
Generating train split: 139268574 examples [2:24:42, 35552.77 examples/s]
Generating train split: 139272375 examples [2:24:43, 36228.74 examples/s]
Generating train split: 139277067 examples [2:24:43, 39185.05 examples/s]
Generating train split: 139282056 examples [2:24:43, 42253.26 examples/s]
Generating train split: 139287053 examples [2:24:43, 44484.54 examples/s]
Generating train split: 139291668 examples [2:24:43, 44972.51 examples/s]
Generating train split: 139296194 examples [2:24:43, 44532.74 examples/s]
Generating train split: 139300679 examples [2:24:43, 44621.36 examples/s]
Generating train split: 139305161 examples [2:24:43, 44101.76 examples/s]
Generating train split: 139309767 examples [2:24:43, 44525.73 examples/s]
Generating train split: 139314237 examples [2:24:43, 42244.01 examples/s]
Generating train split: 139318522 examples [2:24:44, 42400.80 examples/s]
Generating train split: 139322792 examples [2:24:44, 40725.89 examples/s]
Generating train split: 139327375 examples [2:24:44, 42014.25 examples/s]
Generating train split: 139331605 examples [2:24:44, 39954.69 examples/s]
Generating train split: 139336360 examples [2:24:44, 42086.71 examples/s]
Generating train split: 139340613 examples [2:24:44, 40762.61 examples/s]
Generating train split: 139344728 examples [2:24:44, 38746.14 examples/s]
Generating train split: 139349407 examples [2:24:44, 40792.55 examples/s]
Generating train split: 139353535 examples [2:24:44, 39821.35 examples/s]
Generating train split: 139357936 examples [2:24:45, 40996.34 examples/s]
Generating train split: 139362093 examples [2:24:45, 41143.47 examples/s]
Generating train split: 139366229 examples [2:24:45, 39753.67 examples/s]
Generating train split: 139370258 examples [2:24:45, 39688.13 examples/s]
Generating train split: 139374789 examples [2:24:45, 41298.03 examples/s]
Generating train split: 139379741 examples [2:24:45, 43677.20 examples/s]
Generating train split: 139384195 examples [2:24:45, 43927.36 examples/s]
Generating train split: 139389202 examples [2:24:45, 45703.83 examples/s]
Generating train split: 139393786 examples [2:24:45, 43548.51 examples/s]
Generating train split: 139398638 examples [2:24:45, 44961.21 examples/s]
Generating train split: 139403505 examples [2:24:46, 46040.59 examples/s]
Generating train split: 139408142 examples [2:24:46, 43999.32 examples/s]
Generating train split: 139413637 examples [2:24:46, 47087.81 examples/s]
Generating train split: 139418384 examples [2:24:46, 46565.24 examples/s]
Generating train split: 139423075 examples [2:24:46, 43700.61 examples/s]
Generating train split: 139427499 examples [2:24:46, 42882.70 examples/s]
Generating train split: 139431825 examples [2:24:46, 42173.93 examples/s]
Generating train split: 139436071 examples [2:24:46, 37200.09 examples/s]
Generating train split: 139439910 examples [2:24:46, 35717.07 examples/s]
Generating train split: 139443876 examples [2:24:47, 36734.39 examples/s]
Generating train split: 139447778 examples [2:24:47, 37343.81 examples/s]
Generating train split: 139451950 examples [2:24:47, 38480.44 examples/s]
Generating train split: 139455937 examples [2:24:47, 38866.38 examples/s]
Generating train split: 139459859 examples [2:24:47, 37211.36 examples/s]
Generating train split: 139463619 examples [2:24:47, 35948.38 examples/s]
Generating train split: 139467940 examples [2:24:47, 37966.42 examples/s]
Generating train split: 139471778 examples [2:24:47, 37822.47 examples/s]
Generating train split: 139476233 examples [2:24:47, 39759.93 examples/s]
Generating train split: 139481022 examples [2:24:48, 42132.73 examples/s]
Generating train split: 139485265 examples [2:24:48, 40080.92 examples/s]
Generating train split: 139489323 examples [2:24:48, 39482.31 examples/s]
Generating train split: 139493781 examples [2:24:48, 40836.22 examples/s]
Generating train split: 139497900 examples [2:24:48, 39569.85 examples/s]
Generating train split: 139503073 examples [2:24:48, 43020.58 examples/s]
Generating train split: 139508208 examples [2:24:48, 45409.59 examples/s]
Generating train split: 139512782 examples [2:24:48, 42631.52 examples/s]
Generating train split: 139517107 examples [2:24:48, 42096.05 examples/s]
Generating train split: 139521363 examples [2:24:48, 40739.13 examples/s]
Generating train split: 139526437 examples [2:24:49, 43538.89 examples/s]
Generating train split: 139530970 examples [2:24:49, 44037.16 examples/s]
Generating train split: 139536695 examples [2:24:49, 47844.48 examples/s]
Generating train split: 139541515 examples [2:24:49, 45969.05 examples/s]
Generating train split: 139546148 examples [2:24:49, 44225.15 examples/s]
Generating train split: 139550618 examples [2:24:49, 41616.44 examples/s]
Generating train split: 139554826 examples [2:24:49, 40112.60 examples/s]
Generating train split: 139558920 examples [2:24:49, 40323.36 examples/s]
Generating train split: 139563518 examples [2:24:49, 41910.52 examples/s]
Generating train split: 139567742 examples [2:24:50, 41979.57 examples/s]
Generating train split: 139573018 examples [2:24:50, 45034.74 examples/s]
Generating train split: 139578332 examples [2:24:50, 47392.49 examples/s]
Generating train split: 139583104 examples [2:24:50, 47079.82 examples/s]
Generating train split: 139588535 examples [2:24:50, 49193.92 examples/s]
Generating train split: 139593479 examples [2:24:50, 46899.80 examples/s]
Generating train split: 139598351 examples [2:24:50, 47361.66 examples/s]
Generating train split: 139603115 examples [2:24:50, 45179.96 examples/s]
Generating train split: 139607674 examples [2:24:50, 43733.49 examples/s]
Generating train split: 139612084 examples [2:24:51, 41384.99 examples/s]
Generating train split: 139616267 examples [2:24:51, 39666.20 examples/s]
Generating train split: 139620392 examples [2:24:51, 40046.14 examples/s]
Generating train split: 139624423 examples [2:24:51, 38312.44 examples/s]
Generating train split: 139629988 examples [2:24:51, 43054.07 examples/s]
Generating train split: 139635329 examples [2:24:51, 45974.79 examples/s]
Generating train split: 139639993 examples [2:24:51, 42596.70 examples/s]
Generating train split: 139644659 examples [2:24:51, 43705.15 examples/s]
Generating train split: 139649113 examples [2:24:51, 40950.03 examples/s]
Generating train split: 139653284 examples [2:24:52, 37893.71 examples/s]
Generating train split: 139657166 examples [2:24:52, 35963.48 examples/s]
Generating train split: 139660824 examples [2:24:52, 34585.70 examples/s]
Generating train split: 139664331 examples [2:24:52, 33647.80 examples/s]
Generating train split: 139667723 examples [2:24:52, 33567.27 examples/s]
Generating train split: 139672048 examples [2:24:52, 36228.91 examples/s]
Generating train split: 139675716 examples [2:24:52, 35473.80 examples/s]
Generating train split: 139680229 examples [2:24:52, 38192.23 examples/s]
Generating train split: 139684083 examples [2:24:52, 36617.03 examples/s]
Generating train split: 139688553 examples [2:24:53, 38881.06 examples/s]
Generating train split: 139693006 examples [2:24:53, 40486.43 examples/s]
Generating train split: 139697096 examples [2:24:53, 39535.63 examples/s]
Generating train split: 139701412 examples [2:24:53, 40573.19 examples/s]
Generating train split: 139705497 examples [2:24:53, 38004.13 examples/s]
Generating train split: 139709409 examples [2:24:53, 38291.60 examples/s]
Generating train split: 139713766 examples [2:24:53, 39430.14 examples/s]
Generating train split: 139717751 examples [2:24:53, 38167.13 examples/s]
Generating train split: 139722369 examples [2:24:53, 40434.15 examples/s]
Generating train split: 139728333 examples [2:24:53, 45976.29 examples/s]
Generating train split: 139732974 examples [2:24:54, 42339.91 examples/s]
Generating train split: 139737788 examples [2:24:54, 43930.85 examples/s]
Generating train split: 139742252 examples [2:24:54, 42302.45 examples/s]
Generating train split: 139749589 examples [2:24:54, 50975.25 examples/s]
Generating train split: 139758124 examples [2:24:54, 60762.32 examples/s]
Generating train split: 139764415 examples [2:24:54, 60315.83 examples/s]
Generating train split: 139770542 examples [2:24:54, 51567.17 examples/s]
Generating train split: 139775975 examples [2:24:54, 50322.57 examples/s]
Generating train split: 139781201 examples [2:24:55, 48635.43 examples/s]
Generating train split: 139786651 examples [2:24:55, 50120.84 examples/s]
Generating train split: 139791776 examples [2:24:55, 47437.57 examples/s]
Generating train split: 139796616 examples [2:24:55, 45619.46 examples/s]
Generating train split: 139801254 examples [2:24:55, 45392.84 examples/s]
Generating train split: 139805843 examples [2:24:55, 45489.08 examples/s]
Generating train split: 139810425 examples [2:24:55, 45096.73 examples/s]
Generating train split: 139814975 examples [2:24:55, 45135.37 examples/s]
Generating train split: 139819730 examples [2:24:55, 45812.80 examples/s]
Generating train split: 139824330 examples [2:24:55, 42243.84 examples/s]
Generating train split: 139828626 examples [2:24:56, 41617.85 examples/s]
Generating train split: 139832920 examples [2:24:56, 41920.75 examples/s]
Generating train split: 139837145 examples [2:24:56, 41810.42 examples/s]
Generating train split: 139841360 examples [2:24:56, 40740.70 examples/s]
Generating train split: 139846209 examples [2:24:56, 42957.42 examples/s]
Generating train split: 139850541 examples [2:24:56, 42937.94 examples/s]
Generating train split: 139855019 examples [2:24:56, 43473.60 examples/s]
Generating train split: 139860261 examples [2:24:56, 46094.00 examples/s]
Generating train split: 139867624 examples [2:24:56, 54232.47 examples/s]
Generating train split: 139876908 examples [2:24:57, 65705.06 examples/s]
Generating train split: 139884762 examples [2:24:57, 69499.49 examples/s]
Generating train split: 139891737 examples [2:24:57, 56773.72 examples/s]
Generating train split: 139897820 examples [2:24:57, 52632.67 examples/s]
Generating train split: 139903400 examples [2:24:57, 50662.66 examples/s]
Generating train split: 139908683 examples [2:24:57, 48859.12 examples/s]
Generating train split: 139913717 examples [2:24:57, 48546.30 examples/s]
Generating train split: 139918675 examples [2:24:57, 47193.30 examples/s]
Generating train split: 139924864 examples [2:24:57, 51094.56 examples/s]
Generating train split: 139930071 examples [2:24:58, 48851.61 examples/s]
Generating train split: 139935940 examples [2:24:58, 51531.57 examples/s]
Generating train split: 139941169 examples [2:24:58, 50619.06 examples/s]
Generating train split: 139946968 examples [2:24:58, 52690.60 examples/s]
Generating train split: 139952298 examples [2:24:58, 52841.73 examples/s]
Generating train split: 139959273 examples [2:24:58, 57752.71 examples/s]
Generating train split: 139967002 examples [2:24:58, 63476.13 examples/s]
Generating train split: 139975488 examples [2:24:58, 69786.89 examples/s]
Generating train split: 139984058 examples [2:24:58, 74507.37 examples/s]
Generating train split: 139992164 examples [2:24:59, 76436.77 examples/s]
Generating train split: 140000443 examples [2:24:59, 78326.85 examples/s]
Generating train split: 140009031 examples [2:24:59, 80547.38 examples/s]
Generating train split: 140017192 examples [2:24:59, 80859.43 examples/s]
Generating train split: 140025378 examples [2:24:59, 81146.39 examples/s]
Generating train split: 140033503 examples [2:24:59, 80662.40 examples/s]
Generating train split: 140042293 examples [2:24:59, 82821.46 examples/s]
Generating train split: 140050581 examples [2:24:59, 81022.24 examples/s]
Generating train split: 140059209 examples [2:24:59, 82550.91 examples/s]
Generating train split: 140067479 examples [2:24:59, 81676.12 examples/s]
Generating train split: 140076043 examples [2:25:00, 82814.25 examples/s]
Generating train split: 140084572 examples [2:25:00, 83535.41 examples/s]
Generating train split: 140092941 examples [2:25:00, 82826.37 examples/s]
Generating train split: 140101513 examples [2:25:00, 83648.52 examples/s]
Generating train split: 140109895 examples [2:25:00, 83578.73 examples/s]
Generating train split: 140118266 examples [2:25:00, 80311.37 examples/s]
Generating train split: 140126342 examples [2:25:00, 80014.21 examples/s]
Generating train split: 140134364 examples [2:25:00, 79257.17 examples/s]
Generating train split: 140142311 examples [2:25:00, 78276.73 examples/s]
Generating train split: 140150156 examples [2:25:00, 78139.75 examples/s]
Generating train split: 140157979 examples [2:25:01, 74860.52 examples/s]
Generating train split: 140165507 examples [2:25:01, 74394.77 examples/s]
Generating train split: 140172975 examples [2:25:01, 72993.71 examples/s]
Generating train split: 140180296 examples [2:25:01, 68655.30 examples/s]
Generating train split: 140187225 examples [2:25:01, 59047.19 examples/s]
Generating train split: 140193379 examples [2:25:01, 57833.43 examples/s]
Generating train split: 140199330 examples [2:25:01, 54617.87 examples/s]
Generating train split: 140204920 examples [2:25:01, 51641.09 examples/s]
Generating train split: 140210793 examples [2:25:02, 53457.06 examples/s]
Generating train split: 140219125 examples [2:25:02, 61478.52 examples/s]
Generating train split: 140228395 examples [2:25:02, 70121.13 examples/s]
Generating train split: 140235979 examples [2:25:02, 71718.92 examples/s]
Generating train split: 140245070 examples [2:25:02, 77242.85 examples/s]
Generating train split: 140252928 examples [2:25:02, 73063.45 examples/s]
Generating train split: 140260364 examples [2:25:02, 65145.52 examples/s]
Generating train split: 140267122 examples [2:25:02, 60290.37 examples/s]
Generating train split: 140273350 examples [2:25:02, 58545.08 examples/s]
Generating train split: 140281938 examples [2:25:03, 65657.38 examples/s]
Generating train split: 140290264 examples [2:25:03, 70430.00 examples/s]
Generating train split: 140297499 examples [2:25:03, 62611.38 examples/s]
Generating train split: 140304030 examples [2:25:03, 54692.43 examples/s]
Generating train split: 140309823 examples [2:25:03, 55396.63 examples/s]
Generating train split: 140315605 examples [2:25:03, 55168.11 examples/s]
Generating train split: 140321303 examples [2:25:03, 54153.81 examples/s]
Generating train split: 140326845 examples [2:25:03, 52192.56 examples/s]
Generating train split: 140333492 examples [2:25:03, 56037.90 examples/s]
Generating train split: 140342349 examples [2:25:04, 65076.88 examples/s]
Generating train split: 140350273 examples [2:25:04, 69058.92 examples/s]
Generating train split: 140357301 examples [2:25:04, 56430.10 examples/s]
Generating train split: 140363408 examples [2:25:04, 52886.34 examples/s]
Generating train split: 140369043 examples [2:25:04, 53449.91 examples/s]
Generating train split: 140375545 examples [2:25:04, 56441.63 examples/s]
Generating train split: 140381409 examples [2:25:04, 56203.74 examples/s]
Generating train split: 140387184 examples [2:25:04, 56111.76 examples/s]
Generating train split: 140393019 examples [2:25:05, 56726.46 examples/s]
Generating train split: 140402872 examples [2:25:05, 68687.17 examples/s]
Generating train split: 140411856 examples [2:25:05, 74799.94 examples/s]
Generating train split: 140419444 examples [2:25:05, 64009.16 examples/s]
Generating train split: 140426190 examples [2:25:05, 56974.30 examples/s]
Generating train split: 140432239 examples [2:25:05, 57340.99 examples/s]
Generating train split: 140438217 examples [2:25:05, 54788.15 examples/s]
Generating train split: 140443869 examples [2:25:05, 53027.61 examples/s]
Generating train split: 140449292 examples [2:25:06, 47355.52 examples/s]
Generating train split: 140454185 examples [2:25:06, 46464.99 examples/s]
Generating train split: 140458931 examples [2:25:06, 45501.76 examples/s]
Generating train split: 140463550 examples [2:25:06, 40310.56 examples/s]
Generating train split: 140470191 examples [2:25:06, 46823.63 examples/s]
Generating train split: 140475092 examples [2:25:06, 25060.22 examples/s]
Generating train split: 140478855 examples [2:25:07, 17919.58 examples/s]
Generating train split: 140483447 examples [2:25:07, 21702.24 examples/s]
Generating train split: 140490279 examples [2:25:07, 29242.52 examples/s]
Generating train split: 140495938 examples [2:25:07, 34376.56 examples/s]
Generating train split: 140500754 examples [2:25:07, 36892.23 examples/s]
Generating train split: 140506177 examples [2:25:07, 40874.99 examples/s]
Generating train split: 140511128 examples [2:25:07, 42918.08 examples/s]
Generating train split: 140516060 examples [2:25:08, 43857.32 examples/s]
Generating train split: 140522590 examples [2:25:08, 49602.62 examples/s]
Generating train split: 140532155 examples [2:25:08, 62353.18 examples/s]
Generating train split: 140540659 examples [2:25:08, 68755.95 examples/s]
Generating train split: 140547836 examples [2:25:08, 60870.97 examples/s]
Generating train split: 140554300 examples [2:25:08, 56180.03 examples/s]
Generating train split: 140560232 examples [2:25:08, 56232.08 examples/s]
Generating train split: 140566077 examples [2:25:08, 56035.44 examples/s]
Generating train split: 140571839 examples [2:25:08, 55233.35 examples/s]
Generating train split: 140577475 examples [2:25:09, 55140.70 examples/s]
Generating train split: 140584497 examples [2:25:09, 59360.83 examples/s]
Generating train split: 140590517 examples [2:25:09, 57276.86 examples/s]
Generating train split: 140596314 examples [2:25:09, 51147.64 examples/s]
Generating train split: 140602310 examples [2:25:09, 53452.66 examples/s]
Generating train split: 140607795 examples [2:25:09, 51057.45 examples/s]
Generating train split: 140613006 examples [2:25:09, 50776.42 examples/s]
Generating train split: 140618484 examples [2:25:09, 51863.10 examples/s]
Generating train split: 140623944 examples [2:25:09, 52608.32 examples/s]
Generating train split: 140629252 examples [2:25:10, 47007.77 examples/s]
Generating train split: 140634095 examples [2:25:10, 45187.81 examples/s]
Generating train split: 140639472 examples [2:25:10, 47456.76 examples/s]
Generating train split: 140644319 examples [2:25:10, 47297.12 examples/s]
Generating train split: 140649818 examples [2:25:10, 49441.25 examples/s]
Generating train split: 140654829 examples [2:25:10, 47192.11 examples/s]
Generating train split: 140659605 examples [2:25:10, 46758.70 examples/s]
Generating train split: 140664323 examples [2:25:10, 46345.83 examples/s]
Generating train split: 140668984 examples [2:25:10, 46316.44 examples/s]
Generating train split: 140673683 examples [2:25:11, 46494.90 examples/s]
Generating train split: 140678352 examples [2:25:11, 46521.61 examples/s]
Generating train split: 140683015 examples [2:25:11, 45568.21 examples/s]
Generating train split: 140688483 examples [2:25:11, 48203.84 examples/s]
Generating train split: 140693327 examples [2:25:11, 46434.44 examples/s]
Generating train split: 140698532 examples [2:25:11, 48005.81 examples/s]
Generating train split: 140703359 examples [2:25:11, 47290.17 examples/s]
Generating train split: 140708105 examples [2:25:11, 43197.82 examples/s]
Generating train split: 140712644 examples [2:25:11, 43767.66 examples/s]
Generating train split: 140717282 examples [2:25:11, 44383.87 examples/s]
Generating train split: 140722281 examples [2:25:12, 45961.70 examples/s]
Generating train split: 140731031 examples [2:25:12, 58011.48 examples/s]
Generating train split: 140740380 examples [2:25:12, 68388.73 examples/s]
Generating train split: 140747290 examples [2:25:12, 59096.08 examples/s]
Generating train split: 140753472 examples [2:25:12, 52755.95 examples/s]
Generating train split: 140759034 examples [2:25:12, 50256.72 examples/s]
Generating train split: 140764342 examples [2:25:12, 50959.80 examples/s]
Generating train split: 140769838 examples [2:25:12, 51947.02 examples/s]
Generating train split: 140775158 examples [2:25:13, 50679.09 examples/s]
Generating train split: 140780646 examples [2:25:13, 51799.83 examples/s]
Generating train split: 140785895 examples [2:25:13, 50181.15 examples/s]
Generating train split: 140793948 examples [2:25:13, 58673.58 examples/s]
Generating train split: 140804357 examples [2:25:13, 71630.82 examples/s]
Generating train split: 140811866 examples [2:25:13, 72630.22 examples/s]
Generating train split: 140821055 examples [2:25:13, 78251.18 examples/s]
Generating train split: 140830414 examples [2:25:13, 82756.43 examples/s]
Generating train split: 140838764 examples [2:25:13, 73448.54 examples/s]
Generating train split: 140846345 examples [2:25:14, 63726.85 examples/s]
Generating train split: 140853079 examples [2:25:14, 63013.55 examples/s]
Generating train split: 140859637 examples [2:25:14, 61458.52 examples/s]
Generating train split: 140865947 examples [2:25:14, 58281.24 examples/s]
Generating train split: 140871904 examples [2:25:14, 58614.02 examples/s]
Generating train split: 140877855 examples [2:25:14, 56295.23 examples/s]
Generating train split: 140883555 examples [2:25:14, 55046.27 examples/s]
Generating train split: 140889102 examples [2:25:14, 52720.89 examples/s]
Generating train split: 140894413 examples [2:25:14, 50933.42 examples/s]
Generating train split: 140900311 examples [2:25:15, 53111.46 examples/s]
Generating train split: 140905663 examples [2:25:15, 51123.78 examples/s]
Generating train split: 140910807 examples [2:25:15, 51175.91 examples/s]
Generating train split: 140915953 examples [2:25:15, 47047.00 examples/s]
Generating train split: 140920821 examples [2:25:15, 47489.02 examples/s]
Generating train split: 140930345 examples [2:25:15, 60823.32 examples/s]
Generating train split: 140938743 examples [2:25:15, 67412.00 examples/s]
Generating train split: 140946465 examples [2:25:15, 70229.14 examples/s]
Generating train split: 140954088 examples [2:25:15, 71952.63 examples/s]
Generating train split: 140961366 examples [2:25:16, 69206.87 examples/s]
Generating train split: 140969646 examples [2:25:16, 73099.58 examples/s]
Generating train split: 140978597 examples [2:25:16, 77870.43 examples/s]
Generating train split: 140986447 examples [2:25:16, 72393.06 examples/s]
Generating train split: 140993806 examples [2:25:16, 66552.49 examples/s]
Generating train split: 141000614 examples [2:25:16, 61400.65 examples/s]
Generating train split: 141006914 examples [2:25:16, 58166.01 examples/s]
Generating train split: 141012853 examples [2:25:16, 56527.35 examples/s]
Generating train split: 141018627 examples [2:25:16, 56824.29 examples/s]
Generating train split: 141024375 examples [2:25:17, 54092.78 examples/s]
Generating train split: 141033503 examples [2:25:17, 64130.20 examples/s]
Generating train split: 141042446 examples [2:25:17, 71159.57 examples/s]
Generating train split: 141049728 examples [2:25:17, 69161.68 examples/s]
Generating train split: 141056763 examples [2:25:17, 65022.04 examples/s]
Generating train split: 141063380 examples [2:25:17, 62734.36 examples/s]
Generating train split: 141072760 examples [2:25:17, 71199.18 examples/s]
Generating train split: 141082723 examples [2:25:17, 78463.70 examples/s]
Generating train split: 141090714 examples [2:25:17, 69031.98 examples/s]
Generating train split: 141097897 examples [2:25:18, 69484.08 examples/s]
Generating train split: 141107136 examples [2:25:18, 75696.38 examples/s]
Generating train split: 141116007 examples [2:25:18, 79324.82 examples/s]
Generating train split: 141124111 examples [2:25:18, 68077.01 examples/s]
Generating train split: 141133886 examples [2:25:18, 75730.96 examples/s]
Generating train split: 141142220 examples [2:25:18, 77753.57 examples/s]
Generating train split: 141150302 examples [2:25:18, 65671.32 examples/s]
Generating train split: 141157371 examples [2:25:18, 55400.09 examples/s]
Generating train split: 141163484 examples [2:25:19, 51556.84 examples/s]
Generating train split: 141169033 examples [2:25:19, 48518.52 examples/s]
Generating train split: 141174320 examples [2:25:19, 49493.72 examples/s]
Generating train split: 141179490 examples [2:25:19, 49409.46 examples/s]
Generating train split: 141184611 examples [2:25:19, 49723.01 examples/s]
Generating train split: 141189754 examples [2:25:19, 50162.91 examples/s]
Generating train split: 141194852 examples [2:25:19, 49804.65 examples/s]
Generating train split: 141199890 examples [2:25:19, 49485.45 examples/s]
Generating train split: 141204880 examples [2:25:19, 48313.70 examples/s]
Generating train split: 141209749 examples [2:25:20, 47515.40 examples/s]
Generating train split: 141214520 examples [2:25:20, 46241.14 examples/s]
Generating train split: 141219172 examples [2:25:20, 46288.50 examples/s]
Generating train split: 141224607 examples [2:25:20, 48578.79 examples/s]
Generating train split: 141230024 examples [2:25:20, 50170.21 examples/s]
Generating train split: 141235059 examples [2:25:20, 49311.92 examples/s]
Generating train split: 141240428 examples [2:25:20, 50576.16 examples/s]
Generating train split: 141245506 examples [2:25:20, 49495.71 examples/s]
Generating train split: 141250848 examples [2:25:20, 50599.20 examples/s]
Generating train split: 141255926 examples [2:25:21, 48347.42 examples/s]
Generating train split: 141260793 examples [2:25:21, 47559.52 examples/s]
Generating train split: 141265680 examples [2:25:21, 47844.87 examples/s]
Generating train split: 141270489 examples [2:25:21, 47747.56 examples/s]
Generating train split: 141275275 examples [2:25:21, 46728.69 examples/s]
Generating train split: 141281018 examples [2:25:21, 49817.40 examples/s]
Generating train split: 141286019 examples [2:25:21, 47373.25 examples/s]
Generating train split: 141290792 examples [2:25:21, 45715.66 examples/s]
Generating train split: 141296617 examples [2:25:21, 49214.47 examples/s]
Generating train split: 141302280 examples [2:25:21, 51336.46 examples/s]
Generating train split: 141307458 examples [2:25:22, 50161.73 examples/s]
Generating train split: 141313571 examples [2:25:22, 53306.03 examples/s]
Generating train split: 141318942 examples [2:25:22, 49130.52 examples/s]
Generating train split: 141324354 examples [2:25:22, 50497.62 examples/s]
Generating train split: 141329478 examples [2:25:22, 50068.48 examples/s]
Generating train split: 141334543 examples [2:25:22, 48651.41 examples/s]
Generating train split: 141340148 examples [2:25:22, 50728.42 examples/s]
Generating train split: 141345264 examples [2:25:22, 49767.79 examples/s]
Generating train split: 141350979 examples [2:25:22, 51854.95 examples/s]
Generating train split: 141356200 examples [2:25:23, 51838.25 examples/s]
Generating train split: 141361949 examples [2:25:23, 53465.85 examples/s]
Generating train split: 141367620 examples [2:25:23, 54389.86 examples/s]
Generating train split: 141373907 examples [2:25:23, 56895.21 examples/s]
Generating train split: 141379614 examples [2:25:23, 56909.20 examples/s]
Generating train split: 141385327 examples [2:25:23, 53090.03 examples/s]
Generating train split: 141392125 examples [2:25:23, 57276.53 examples/s]
Generating train split: 141397916 examples [2:25:23, 51037.60 examples/s]
Generating train split: 141404293 examples [2:25:23, 54444.50 examples/s]
Generating train split: 141409894 examples [2:25:24, 54347.24 examples/s]
Generating train split: 141415443 examples [2:25:24, 50673.39 examples/s]
Generating train split: 141420622 examples [2:25:24, 50976.41 examples/s]
Generating train split: 141425811 examples [2:25:24, 50400.46 examples/s]
Generating train split: 141431219 examples [2:25:24, 51411.79 examples/s]
Generating train split: 141436703 examples [2:25:24, 52390.30 examples/s]
Generating train split: 141441998 examples [2:25:24, 47900.81 examples/s]
Generating train split: 141446882 examples [2:25:24, 47039.68 examples/s]
Generating train split: 141451656 examples [2:25:24, 46725.93 examples/s]
Generating train split: 141456375 examples [2:25:25, 46640.78 examples/s]
Generating train split: 141461379 examples [2:25:25, 47587.04 examples/s]
Generating train split: 141466694 examples [2:25:25, 49198.08 examples/s]
Generating train split: 141472492 examples [2:25:25, 51738.66 examples/s]
Generating train split: 141477929 examples [2:25:25, 52506.60 examples/s]
Generating train split: 141483197 examples [2:25:25, 51000.52 examples/s]
Generating train split: 141488322 examples [2:25:25, 50855.19 examples/s]
Generating train split: 141494071 examples [2:25:25, 52753.36 examples/s]
Generating train split: 141499378 examples [2:25:25, 52821.55 examples/s]
Generating train split: 141504833 examples [2:25:25, 53309.38 examples/s]
Generating train split: 141510729 examples [2:25:26, 54893.25 examples/s]
Generating train split: 141516238 examples [2:25:26, 54768.50 examples/s]
Generating train split: 141521726 examples [2:25:26, 52291.65 examples/s]
Generating train split: 141526982 examples [2:25:26, 52138.86 examples/s]
Generating train split: 141532217 examples [2:25:26, 47433.94 examples/s]
Generating train split: 141537972 examples [2:25:26, 50110.00 examples/s]
Generating train split: 141543071 examples [2:25:26, 49689.67 examples/s]
Generating train split: 141548103 examples [2:25:26, 44181.53 examples/s]
Generating train split: 141552813 examples [2:25:26, 44951.01 examples/s]
Generating train split: 141559131 examples [2:25:27, 49941.05 examples/s]
Generating train split: 141564524 examples [2:25:27, 51043.26 examples/s]
Generating train split: 141569729 examples [2:25:27, 48565.16 examples/s]
Generating train split: 141574819 examples [2:25:27, 49198.50 examples/s]
Generating train split: 141579813 examples [2:25:27, 45852.84 examples/s]
Generating train split: 141585643 examples [2:25:27, 49247.94 examples/s]
Generating train split: 141591172 examples [2:25:27, 50931.98 examples/s]
Generating train split: 141596377 examples [2:25:27, 51233.57 examples/s]
Generating train split: 141601559 examples [2:25:27, 49163.78 examples/s]
Generating train split: 141606530 examples [2:25:28, 46878.98 examples/s]
Generating train split: 141611467 examples [2:25:28, 47506.62 examples/s]
Generating train split: 141616275 examples [2:25:28, 46863.84 examples/s]
Generating train split: 141621339 examples [2:25:28, 47916.72 examples/s]
Generating train split: 141626761 examples [2:25:28, 49727.32 examples/s]
Generating train split: 141632132 examples [2:25:28, 50885.80 examples/s]
Generating train split: 141637241 examples [2:25:28, 49949.63 examples/s]
Generating train split: 141642624 examples [2:25:28, 50920.93 examples/s]
Generating train split: 141647738 examples [2:25:28, 46995.08 examples/s]
Generating train split: 141652850 examples [2:25:28, 48127.67 examples/s]
Generating train split: 141657723 examples [2:25:29, 47594.63 examples/s]
Generating train split: 141662529 examples [2:25:29, 45777.51 examples/s]
Generating train split: 141667150 examples [2:25:29, 44474.20 examples/s]
Generating train split: 141675554 examples [2:25:29, 55559.94 examples/s]
Generating train split: 141684707 examples [2:25:29, 65842.16 examples/s]
Generating train split: 141691408 examples [2:25:29, 56983.99 examples/s]
Generating train split: 141697394 examples [2:25:29, 55897.79 examples/s]
Generating train split: 141703178 examples [2:25:29, 55399.26 examples/s]
Generating train split: 141708861 examples [2:25:29, 53798.84 examples/s]
Generating train split: 141714336 examples [2:25:30, 50167.25 examples/s]
Generating train split: 141719463 examples [2:25:30, 46042.64 examples/s]
Generating train split: 141724708 examples [2:25:30, 47689.04 examples/s]
Generating train split: 141729716 examples [2:25:30, 48273.81 examples/s]
Generating train split: 141734635 examples [2:25:30, 47509.53 examples/s]
Generating train split: 141740129 examples [2:25:30, 49534.84 examples/s]
Generating train split: 141745133 examples [2:25:30, 48392.55 examples/s]
Generating train split: 141750021 examples [2:25:30, 47189.70 examples/s]
Generating train split: 141754846 examples [2:25:30, 47476.53 examples/s]
Generating train split: 141759704 examples [2:25:31, 47774.50 examples/s]
Generating train split: 141764502 examples [2:25:31, 46889.42 examples/s]
Generating train split: 141769215 examples [2:25:31, 46026.77 examples/s]
Generating train split: 141773835 examples [2:25:31, 45763.12 examples/s]
Generating train split: 141778490 examples [2:25:31, 45974.17 examples/s]
Generating train split: 141783602 examples [2:25:31, 47480.05 examples/s]
Generating train split: 141788370 examples [2:25:31, 45476.97 examples/s]
Generating train split: 141792953 examples [2:25:31, 44368.44 examples/s]
Generating train split: 141797414 examples [2:25:31, 42182.59 examples/s]
Generating train split: 141802086 examples [2:25:32, 43435.03 examples/s]
Generating train split: 141808283 examples [2:25:32, 48711.35 examples/s]
Generating train split: 141813204 examples [2:25:32, 44197.52 examples/s]
Generating train split: 141817738 examples [2:25:32, 43637.79 examples/s]
Generating train split: 141822978 examples [2:25:32, 46038.66 examples/s]
Generating train split: 141828651 examples [2:25:32, 49029.59 examples/s]
Generating train split: 141833969 examples [2:25:32, 50207.59 examples/s]
Generating train split: 141839056 examples [2:25:32, 48548.17 examples/s]
Generating train split: 141843986 examples [2:25:32, 48760.66 examples/s]
Generating train split: 141848900 examples [2:25:33, 46834.80 examples/s]
Generating train split: 141853925 examples [2:25:33, 47801.52 examples/s]
Generating train split: 141859686 examples [2:25:33, 50626.97 examples/s]
Generating train split: 141864795 examples [2:25:33, 48212.47 examples/s]
Generating train split: 141870751 examples [2:25:33, 51414.46 examples/s]
Generating train split: 141875950 examples [2:25:33, 49181.90 examples/s]
Generating train split: 141881593 examples [2:25:33, 51210.38 examples/s]
Generating train split: 141886769 examples [2:25:33, 49916.40 examples/s]
Generating train split: 141892369 examples [2:25:33, 51639.41 examples/s]
Generating train split: 141897571 examples [2:25:33, 47728.95 examples/s]
Generating train split: 141902424 examples [2:25:34, 46580.52 examples/s]
Generating train split: 141907267 examples [2:25:34, 47052.13 examples/s]
Generating train split: 141912024 examples [2:25:34, 46644.68 examples/s]
Generating train split: 141916717 examples [2:25:34, 45621.59 examples/s]
Generating train split: 141921305 examples [2:25:34, 45253.40 examples/s]
Generating train split: 141926153 examples [2:25:34, 46170.08 examples/s]
Generating train split: 141930793 examples [2:25:34, 46103.69 examples/s]
Generating train split: 141935584 examples [2:25:34, 46609.56 examples/s]
Generating train split: 141940255 examples [2:25:34, 46528.76 examples/s]
Generating train split: 141945054 examples [2:25:35, 46960.76 examples/s]
Generating train split: 141949829 examples [2:25:35, 47176.79 examples/s]
Generating train split: 141954681 examples [2:25:35, 47556.47 examples/s]
Generating train split: 141959440 examples [2:25:35, 45277.36 examples/s]
Generating train split: 141964101 examples [2:25:35, 45641.98 examples/s]
Generating train split: 141968690 examples [2:25:35, 45025.03 examples/s]
Generating train split: 141973217 examples [2:25:35, 44479.19 examples/s]
Generating train split: 141978672 examples [2:25:35, 47402.05 examples/s]
Generating train split: 141984439 examples [2:25:35, 50406.44 examples/s]
Generating train split: 141989513 examples [2:25:35, 49461.21 examples/s]
Generating train split: 141994802 examples [2:25:36, 50462.81 examples/s]
Generating train split: 142000118 examples [2:25:36, 51231.80 examples/s]
Generating train split: 142005889 examples [2:25:36, 53116.44 examples/s]
Generating train split: 142011439 examples [2:25:36, 53812.91 examples/s]
Generating train split: 142017130 examples [2:25:36, 54718.73 examples/s]
Generating train split: 142022610 examples [2:25:36, 54252.73 examples/s]
Generating train split: 142028051 examples [2:25:36, 51709.18 examples/s]
Generating train split: 142033262 examples [2:25:36, 45424.69 examples/s]
Generating train split: 142038622 examples [2:25:36, 47577.96 examples/s]
Generating train split: 142043783 examples [2:25:37, 48669.28 examples/s]
Generating train split: 142050233 examples [2:25:37, 53053.93 examples/s]
Generating train split: 142055645 examples [2:25:37, 49883.56 examples/s]
Generating train split: 142060744 examples [2:25:37, 48528.49 examples/s]
Generating train split: 142065673 examples [2:25:37, 46784.30 examples/s]
Generating train split: 142070416 examples [2:25:37, 46851.04 examples/s]
Generating train split: 142076107 examples [2:25:37, 49667.21 examples/s]
Generating train split: 142082124 examples [2:25:37, 52666.69 examples/s]
Generating train split: 142087437 examples [2:25:37, 49457.82 examples/s]
Generating train split: 142092456 examples [2:25:37, 48540.94 examples/s]
Generating train split: 142097356 examples [2:25:38, 48604.70 examples/s]
Generating train split: 142103049 examples [2:25:38, 50977.02 examples/s]
Generating train split: 142108182 examples [2:25:38, 50169.97 examples/s]
Generating train split: 142113359 examples [2:25:38, 50615.13 examples/s]
Generating train split: 142118440 examples [2:25:38, 48671.99 examples/s]
Generating train split: 142123333 examples [2:25:38, 48562.39 examples/s]
Generating train split: 142128708 examples [2:25:38, 50048.19 examples/s]
Generating train split: 142133735 examples [2:25:38, 47440.62 examples/s]
Generating train split: 142138828 examples [2:25:38, 48215.52 examples/s]
Generating train split: 142143894 examples [2:25:39, 48907.03 examples/s]
Generating train split: 142148809 examples [2:25:39, 48617.14 examples/s]
Generating train split: 142154191 examples [2:25:39, 50098.99 examples/s]
Generating train split: 142159227 examples [2:25:39, 48381.12 examples/s]
Generating train split: 142164094 examples [2:25:39, 47829.08 examples/s]
Generating train split: 142169045 examples [2:25:39, 48301.60 examples/s]
Generating train split: 142175003 examples [2:25:39, 51579.57 examples/s]
Generating train split: 142180187 examples [2:25:39, 51177.12 examples/s]
Generating train split: 142185327 examples [2:25:39, 50591.08 examples/s]
Generating train split: 142190918 examples [2:25:39, 52101.75 examples/s]
Generating train split: 142196144 examples [2:25:40, 48239.42 examples/s]
Generating train split: 142201568 examples [2:25:40, 49906.10 examples/s]
Generating train split: 142210975 examples [2:25:40, 62535.26 examples/s]
Generating train split: 142220229 examples [2:25:40, 71223.59 examples/s]
Generating train split: 142227451 examples [2:25:40, 64630.67 examples/s]
Generating train split: 142234110 examples [2:25:40, 58208.70 examples/s]
Generating train split: 142240152 examples [2:25:40, 54423.11 examples/s]
Generating train split: 142245819 examples [2:25:40, 54968.54 examples/s]
Generating train split: 142251452 examples [2:25:41, 52875.32 examples/s]
Generating train split: 142256838 examples [2:25:41, 52180.80 examples/s]
Generating train split: 142262119 examples [2:25:41, 51599.26 examples/s]
Generating train split: 142267327 examples [2:25:41, 50150.09 examples/s]
Generating train split: 142272665 examples [2:25:41, 51008.63 examples/s]
Generating train split: 142277804 examples [2:25:41, 47472.95 examples/s]
Generating train split: 142282617 examples [2:25:41, 46319.03 examples/s]
Generating train split: 142287917 examples [2:25:41, 48140.43 examples/s]
Generating train split: 142293554 examples [2:25:41, 50451.48 examples/s]
Generating train split: 142298913 examples [2:25:41, 51340.44 examples/s]
Generating train split: 142304097 examples [2:25:42, 49417.49 examples/s]
Generating train split: 142309517 examples [2:25:42, 50757.65 examples/s]
Generating train split: 142314635 examples [2:25:42, 49360.14 examples/s]
Generating train split: 142319681 examples [2:25:42, 49660.83 examples/s]
Generating train split: 142324673 examples [2:25:42, 48467.10 examples/s]
Generating train split: 142329916 examples [2:25:42, 49600.46 examples/s]
Generating train split: 142335764 examples [2:25:42, 52181.32 examples/s]
Generating train split: 142341005 examples [2:25:42, 51597.31 examples/s]
Generating train split: 142346426 examples [2:25:42, 52335.37 examples/s]
Generating train split: 142351995 examples [2:25:43, 53305.00 examples/s]
Generating train split: 142357339 examples [2:25:43, 49103.34 examples/s]
Generating train split: 142362606 examples [2:25:43, 50099.72 examples/s]
Generating train split: 142367674 examples [2:25:43, 47522.97 examples/s]
Generating train split: 142372777 examples [2:25:43, 48477.87 examples/s]
Generating train split: 142377675 examples [2:25:43, 44069.42 examples/s]
Generating train split: 142382279 examples [2:25:43, 44578.80 examples/s]
Generating train split: 142386935 examples [2:25:43, 45122.14 examples/s]
Generating train split: 142391523 examples [2:25:43, 42877.64 examples/s]
Generating train split: 142399458 examples [2:25:44, 52981.84 examples/s]
Generating train split: 142408061 examples [2:25:44, 62342.75 examples/s]
Generating train split: 142414450 examples [2:25:44, 59575.05 examples/s]
Generating train split: 142420538 examples [2:25:44, 54673.56 examples/s]
Generating train split: 142426151 examples [2:25:44, 49197.69 examples/s]
Generating train split: 142431759 examples [2:25:44, 50948.28 examples/s]
Generating train split: 142437012 examples [2:25:44, 50762.03 examples/s]
Generating train split: 142442199 examples [2:25:44, 49808.61 examples/s]
Generating train split: 142447999 examples [2:25:44, 52041.98 examples/s]
Generating train split: 142453691 examples [2:25:45, 53402.08 examples/s]
Generating train split: 142460018 examples [2:25:45, 55967.56 examples/s]
Generating train split: 142465667 examples [2:25:45, 52331.25 examples/s]
Generating train split: 142470984 examples [2:25:45, 50862.93 examples/s]
Generating train split: 142476301 examples [2:25:45, 51471.27 examples/s]
Generating train split: 142481897 examples [2:25:45, 52714.20 examples/s]
Generating train split: 142487205 examples [2:25:45, 50082.43 examples/s]
Generating train split: 142492268 examples [2:25:45, 49921.13 examples/s]
Generating train split: 142498575 examples [2:25:45, 53664.81 examples/s]
Generating train split: 142504410 examples [2:25:46, 55018.80 examples/s]
Generating train split: 142509946 examples [2:25:46, 53226.89 examples/s]
Generating train split: 142515875 examples [2:25:46, 54960.42 examples/s]
Generating train split: 142521410 examples [2:25:46, 54792.76 examples/s]
Generating train split: 142527567 examples [2:25:46, 56758.13 examples/s]
Generating train split: 142533273 examples [2:25:46, 54196.77 examples/s]
Generating train split: 142538731 examples [2:25:46, 52858.58 examples/s]
Generating train split: 142544509 examples [2:25:46, 54257.99 examples/s]
Generating train split: 142549979 examples [2:25:46, 53788.86 examples/s]
Generating train split: 142555543 examples [2:25:46, 54302.98 examples/s]
Generating train split: 142561000 examples [2:25:47, 52240.87 examples/s]
Generating train split: 142566952 examples [2:25:47, 54299.09 examples/s]
Generating train split: 142573529 examples [2:25:47, 57627.79 examples/s]
Generating train split: 142579327 examples [2:25:47, 55908.66 examples/s]
Generating train split: 142584959 examples [2:25:47, 53319.88 examples/s]
Generating train split: 142590330 examples [2:25:47, 50644.07 examples/s]
Generating train split: 142595983 examples [2:25:47, 52267.69 examples/s]
Generating train split: 142601258 examples [2:25:47, 51184.80 examples/s]
Generating train split: 142607067 examples [2:25:47, 53127.01 examples/s]
Generating train split: 142612586 examples [2:25:48, 53711.58 examples/s]
Generating train split: 142618490 examples [2:25:48, 55246.61 examples/s]
Generating train split: 142624047 examples [2:25:48, 53154.08 examples/s]
Generating train split: 142629404 examples [2:25:48, 52176.13 examples/s]
Generating train split: 142635076 examples [2:25:48, 53460.98 examples/s]
Generating train split: 142640591 examples [2:25:48, 53885.97 examples/s]
Generating train split: 142645999 examples [2:25:48, 52362.01 examples/s]
Generating train split: 142651363 examples [2:25:48, 52480.86 examples/s]
Generating train split: 142656638 examples [2:25:48, 50006.57 examples/s]
Generating train split: 142661668 examples [2:25:48, 47734.15 examples/s]
Generating train split: 142666487 examples [2:25:49, 47387.45 examples/s]
Generating train split: 142671697 examples [2:25:49, 48711.77 examples/s]
Generating train split: 142676614 examples [2:25:49, 48826.45 examples/s]
Generating train split: 142682020 examples [2:25:49, 50331.92 examples/s]
Generating train split: 142688274 examples [2:25:49, 53894.74 examples/s]
Generating train split: 142694899 examples [2:25:49, 57538.42 examples/s]
Generating train split: 142700688 examples [2:25:49, 54693.37 examples/s]
Generating train split: 142706453 examples [2:25:49, 55529.06 examples/s]
Generating train split: 142712105 examples [2:25:49, 55804.71 examples/s]
Generating train split: 142718114 examples [2:25:50, 57036.32 examples/s]
Generating train split: 142723838 examples [2:25:50, 57070.40 examples/s]
Generating train split: 142729560 examples [2:25:50, 52916.25 examples/s]
Generating train split: 142734932 examples [2:25:50, 52514.40 examples/s]
Generating train split: 142740244 examples [2:25:50, 50474.29 examples/s]
Generating train split: 142745623 examples [2:25:50, 51403.26 examples/s]
Generating train split: 142751905 examples [2:25:50, 54660.87 examples/s]
Generating train split: 142757417 examples [2:25:50, 53184.43 examples/s]
Generating train split: 142763271 examples [2:25:50, 54674.61 examples/s]
Generating train split: 142768890 examples [2:25:50, 55096.74 examples/s]
Generating train split: 142774436 examples [2:25:51, 53334.50 examples/s]
Generating train split: 142779811 examples [2:25:51, 51550.56 examples/s]
Generating train split: 142784999 examples [2:25:51, 46503.09 examples/s]
Generating train split: 142790971 examples [2:25:51, 50022.38 examples/s]
Generating train split: 142796740 examples [2:25:51, 52124.29 examples/s]
Generating train split: 142802049 examples [2:25:51, 51744.34 examples/s]
Generating train split: 142807479 examples [2:25:51, 52464.01 examples/s]
Generating train split: 142812790 examples [2:25:51, 50445.92 examples/s]
Generating train split: 142817886 examples [2:25:51, 46631.46 examples/s]
Generating train split: 142822943 examples [2:25:52, 47702.23 examples/s]
Generating train split: 142828284 examples [2:25:52, 49282.52 examples/s]
Generating train split: 142834185 examples [2:25:52, 52047.37 examples/s]
Generating train split: 142839455 examples [2:25:52, 48340.77 examples/s]
Generating train split: 142845338 examples [2:25:52, 51225.95 examples/s]
Generating train split: 142853868 examples [2:25:52, 60879.27 examples/s]
Generating train split: 142863835 examples [2:25:52, 72055.50 examples/s]
Generating train split: 142871174 examples [2:25:52, 67544.38 examples/s]
Generating train split: 142878077 examples [2:25:52, 60978.25 examples/s]
Generating train split: 142884377 examples [2:25:53, 58133.94 examples/s]
Generating train split: 142890340 examples [2:25:53, 57767.41 examples/s]
Generating train split: 142896480 examples [2:25:53, 58746.53 examples/s]
Generating train split: 142902449 examples [2:25:53, 57937.27 examples/s]
Generating train split: 142908682 examples [2:25:53, 59134.69 examples/s]
Generating train split: 142914653 examples [2:25:53, 58871.26 examples/s]
Generating train split: 142920582 examples [2:25:53, 58797.88 examples/s]
Generating train split: 142926498 examples [2:25:53, 53544.55 examples/s]
Generating train split: 142931960 examples [2:25:53, 53152.97 examples/s]
Generating train split: 142937355 examples [2:25:54, 52991.16 examples/s]
Generating train split: 142942924 examples [2:25:54, 53714.33 examples/s]
Generating train split: 142948333 examples [2:25:54, 51924.08 examples/s]
Generating train split: 142954110 examples [2:25:54, 53572.79 examples/s]
Generating train split: 142959502 examples [2:25:54, 49245.71 examples/s]
Generating train split: 142964971 examples [2:25:54, 50717.96 examples/s]
Generating train split: 142970124 examples [2:25:54, 48892.40 examples/s]
Generating train split: 142976516 examples [2:25:54, 52993.63 examples/s]
Generating train split: 142981889 examples [2:25:54, 48404.77 examples/s]
Generating train split: 142986855 examples [2:25:55, 47640.09 examples/s]
Generating train split: 142992371 examples [2:25:55, 49675.58 examples/s]
Generating train split: 142997412 examples [2:25:55, 49138.45 examples/s]
Generating train split: 143003367 examples [2:25:55, 52084.36 examples/s]
Generating train split: 143008628 examples [2:25:55, 51771.70 examples/s]
Generating train split: 143013960 examples [2:25:55, 52202.64 examples/s]
Generating train split: 143019216 examples [2:25:55, 51597.75 examples/s]
Generating train split: 143024705 examples [2:25:55, 52556.94 examples/s]
Generating train split: 143030017 examples [2:25:55, 52714.70 examples/s]
Generating train split: 143035675 examples [2:25:55, 53846.78 examples/s]
Generating train split: 143041084 examples [2:25:56, 52419.56 examples/s]
Generating train split: 143046433 examples [2:25:56, 52709.77 examples/s]
Generating train split: 143051722 examples [2:25:56, 48596.87 examples/s]
Generating train split: 143056657 examples [2:25:56, 47976.63 examples/s]
Generating train split: 143061505 examples [2:25:56, 44337.80 examples/s]
Generating train split: 143066021 examples [2:25:56, 43964.51 examples/s]
Generating train split: 143071387 examples [2:25:56, 46610.25 examples/s]
Generating train split: 143076109 examples [2:25:56, 44016.29 examples/s]
Generating train split: 143081462 examples [2:25:56, 46609.37 examples/s]
Generating train split: 143086198 examples [2:25:57, 46296.02 examples/s]
Generating train split: 143091480 examples [2:25:57, 48142.89 examples/s]
Generating train split: 143097861 examples [2:25:57, 52668.48 examples/s]
Generating train split: 143103173 examples [2:25:57, 48735.70 examples/s]
Generating train split: 143108939 examples [2:25:57, 51207.37 examples/s]
Generating train split: 143114182 examples [2:25:57, 51547.27 examples/s]
Generating train split: 143119394 examples [2:25:57, 49718.41 examples/s]
Generating train split: 143125006 examples [2:25:57, 51511.21 examples/s]
Generating train split: 143130207 examples [2:25:57, 50703.10 examples/s]
Generating train split: 143135826 examples [2:25:58, 52260.89 examples/s]
Generating train split: 143141257 examples [2:25:58, 52854.90 examples/s]
Generating train split: 143146566 examples [2:25:58, 51448.38 examples/s]
Generating train split: 143151744 examples [2:25:58, 49931.60 examples/s]
Generating train split: 143156838 examples [2:25:58, 50216.97 examples/s]
Generating train split: 143162077 examples [2:25:58, 50842.75 examples/s]
Generating train split: 143167363 examples [2:25:58, 51424.03 examples/s]
Generating train split: 143172524 examples [2:25:58, 50360.48 examples/s]
Generating train split: 143178332 examples [2:25:58, 52614.00 examples/s]
Generating train split: 143184086 examples [2:25:58, 54044.92 examples/s]
Generating train split: 143190128 examples [2:25:59, 55904.08 examples/s]
Generating train split: 143195739 examples [2:25:59, 55532.80 examples/s]
Generating train split: 143201302 examples [2:25:59, 40998.15 examples/s]
Generating train split: 143205954 examples [2:25:59, 29841.72 examples/s]
Generating train split: 143209717 examples [2:25:59, 22458.90 examples/s]
Generating train split: 143212722 examples [2:26:00, 18651.38 examples/s]
Generating train split: 143215167 examples [2:26:00, 15670.16 examples/s]
Generating train split: 143217162 examples [2:26:00, 15870.23 examples/s]
Generating train split: 143221258 examples [2:26:00, 20238.69 examples/s]
Generating train split: 143225582 examples [2:26:00, 24821.28 examples/s]
Generating train split: 143230669 examples [2:26:00, 30584.67 examples/s]
Generating train split: 143235972 examples [2:26:00, 35979.40 examples/s]
Generating train split: 143241929 examples [2:26:01, 42006.12 examples/s]
Generating train split: 143247548 examples [2:26:01, 45779.40 examples/s]
Generating train split: 143252734 examples [2:26:01, 47456.11 examples/s]
Generating train split: 143257773 examples [2:26:01, 47122.32 examples/s]
Generating train split: 143262700 examples [2:26:01, 46578.20 examples/s]
Generating train split: 143268393 examples [2:26:01, 49480.41 examples/s]
Generating train split: 143273693 examples [2:26:01, 50472.96 examples/s]
Generating train split: 143279511 examples [2:26:01, 52708.02 examples/s]
Generating train split: 143284983 examples [2:26:01, 53290.13 examples/s]
Generating train split: 143290375 examples [2:26:02, 48113.27 examples/s]
Generating train split: 143295317 examples [2:26:02, 47536.78 examples/s]
Generating train split: 143300573 examples [2:26:02, 48934.31 examples/s]
Generating train split: 143306115 examples [2:26:02, 50684.27 examples/s]
Generating train split: 143311247 examples [2:26:02, 50360.25 examples/s]
Generating train split: 143316338 examples [2:26:02, 48411.51 examples/s]
Generating train split: 143321364 examples [2:26:02, 48918.78 examples/s]
Generating train split: 143326753 examples [2:26:02, 50329.52 examples/s]
Generating train split: 143332524 examples [2:26:02, 52443.27 examples/s]
Generating train split: 143337817 examples [2:26:02, 52558.30 examples/s]
Generating train split: 143343102 examples [2:26:03, 48840.04 examples/s]
Generating train split: 143348065 examples [2:26:03, 48865.52 examples/s]
Generating train split: 143353465 examples [2:26:03, 50320.44 examples/s]
Generating train split: 143358766 examples [2:26:03, 51087.58 examples/s]
Generating train split: 143364007 examples [2:26:03, 51460.91 examples/s]
Generating train split: 143369519 examples [2:26:03, 52521.77 examples/s]
Generating train split: 143374796 examples [2:26:03, 51283.28 examples/s]
Generating train split: 143379948 examples [2:26:03, 49862.48 examples/s]
Generating train split: 143386003 examples [2:26:03, 52937.84 examples/s]
Generating train split: 143391883 examples [2:26:04, 54622.17 examples/s]
Generating train split: 143397874 examples [2:26:04, 56173.26 examples/s]
Generating train split: 143403890 examples [2:26:04, 57327.82 examples/s]
Generating train split: 143409640 examples [2:26:04, 52049.66 examples/s]
Generating train split: 143414946 examples [2:26:04, 50219.90 examples/s]
Generating train split: 143420047 examples [2:26:04, 48029.79 examples/s]
Generating train split: 143425236 examples [2:26:04, 49080.74 examples/s]
Generating train split: 143431073 examples [2:26:04, 51676.52 examples/s]
Generating train split: 143437933 examples [2:26:04, 56512.77 examples/s]
Generating train split: 143447323 examples [2:26:04, 67353.13 examples/s]
Generating train split: 143456130 examples [2:26:05, 73399.74 examples/s]
Generating train split: 143463550 examples [2:26:05, 64402.09 examples/s]
Generating train split: 143470239 examples [2:26:05, 59290.09 examples/s]
Generating train split: 143476406 examples [2:26:05, 58529.28 examples/s]
Generating train split: 143482420 examples [2:26:05, 53283.10 examples/s]
Generating train split: 143488215 examples [2:26:05, 54467.88 examples/s]
Generating train split: 143494413 examples [2:26:05, 56476.44 examples/s]
Generating train split: 143500179 examples [2:26:05, 56509.70 examples/s]
Generating train split: 143505917 examples [2:26:06, 48216.51 examples/s]
Generating train split: 143510990 examples [2:26:06, 48150.00 examples/s]
Generating train split: 143515981 examples [2:26:06, 47923.82 examples/s]
Generating train split: 143521269 examples [2:26:06, 49254.72 examples/s]
Generating train split: 143526293 examples [2:26:06, 47541.19 examples/s]
Generating train split: 143531988 examples [2:26:06, 50131.18 examples/s]
Generating train split: 143538525 examples [2:26:06, 54437.95 examples/s]
Generating train split: 143544051 examples [2:26:06, 52959.01 examples/s]
Generating train split: 143549410 examples [2:26:06, 52410.68 examples/s]
Generating train split: 143554706 examples [2:26:07, 52265.71 examples/s]
Generating train split: 143560427 examples [2:26:07, 53625.39 examples/s]
Generating train split: 143566190 examples [2:26:07, 54787.96 examples/s]
Generating train split: 143571706 examples [2:26:07, 52019.98 examples/s]
Generating train split: 143576949 examples [2:26:07, 52071.07 examples/s]
Generating train split: 143582701 examples [2:26:07, 53646.12 examples/s]
Generating train split: 143588093 examples [2:26:07, 51539.84 examples/s]
Generating train split: 143593954 examples [2:26:07, 53555.28 examples/s]
Generating train split: 143599509 examples [2:26:07, 54132.20 examples/s]
Generating train split: 143605338 examples [2:26:07, 55308.75 examples/s]
Generating train split: 143612171 examples [2:26:08, 59121.94 examples/s]
Generating train split: 143618114 examples [2:26:08, 58993.15 examples/s]
Generating train split: 143624030 examples [2:26:08, 58085.46 examples/s]
Generating train split: 143629860 examples [2:26:08, 57742.46 examples/s]
Generating train split: 143636266 examples [2:26:08, 59541.99 examples/s]
Generating train split: 143642243 examples [2:26:08, 56255.55 examples/s]
Generating train split: 143647921 examples [2:26:08, 55730.48 examples/s]
Generating train split: 143653536 examples [2:26:08, 54714.54 examples/s]
Generating train split: 143660150 examples [2:26:08, 57966.66 examples/s]
Generating train split: 143665986 examples [2:26:09, 53354.09 examples/s]
Generating train split: 143671406 examples [2:26:09, 49584.74 examples/s]
Generating train split: 143676459 examples [2:26:09, 48891.36 examples/s]
Generating train split: 143682264 examples [2:26:09, 51384.48 examples/s]
Generating train split: 143687482 examples [2:26:09, 46536.17 examples/s]
Generating train split: 143692466 examples [2:26:09, 47393.01 examples/s]
Generating train split: 143697315 examples [2:26:09, 47323.03 examples/s]
Generating train split: 143702299 examples [2:26:09, 48014.58 examples/s]
Generating train split: 143708151 examples [2:26:09, 51004.07 examples/s]
Generating train split: 143713929 examples [2:26:10, 52956.66 examples/s]
Generating train split: 143719268 examples [2:26:10, 51881.58 examples/s]
Generating train split: 143725183 examples [2:26:10, 53977.79 examples/s]
Generating train split: 143730621 examples [2:26:10, 53619.89 examples/s]
Generating train split: 143736554 examples [2:26:10, 55282.78 examples/s]
Generating train split: 143743025 examples [2:26:10, 58053.83 examples/s]
Generating train split: 143748850 examples [2:26:10, 57217.22 examples/s]
Generating train split: 143754597 examples [2:26:10, 56601.72 examples/s]
Generating train split: 143760271 examples [2:26:10, 55064.20 examples/s]
Generating train split: 143765804 examples [2:26:10, 54203.03 examples/s]
Generating train split: 143771356 examples [2:26:11, 54559.93 examples/s]
Generating train split: 143776829 examples [2:26:11, 52944.59 examples/s]
Generating train split: 143782151 examples [2:26:11, 51776.40 examples/s]
Generating train split: 143790693 examples [2:26:11, 61402.54 examples/s]
Generating train split: 143800911 examples [2:26:11, 73229.99 examples/s]
Generating train split: 143808313 examples [2:26:11, 62805.84 examples/s]
Generating train split: 143814910 examples [2:26:11, 58517.29 examples/s]
Generating train split: 143821007 examples [2:26:11, 58233.47 examples/s]
Generating train split: 143827002 examples [2:26:11, 58477.16 examples/s]
Generating train split: 143832981 examples [2:26:12, 58629.26 examples/s]
Generating train split: 143839643 examples [2:26:12, 60864.94 examples/s]
Generating train split: 143845812 examples [2:26:12, 60162.53 examples/s]
Generating train split: 143851883 examples [2:26:12, 58437.19 examples/s]
Generating train split: 143857778 examples [2:26:12, 57932.23 examples/s]
Generating train split: 143863604 examples [2:26:12, 55451.75 examples/s]
Generating train split: 143869191 examples [2:26:12, 54114.86 examples/s]
Generating train split: 143874631 examples [2:26:12, 52170.96 examples/s]
Generating train split: 143879979 examples [2:26:12, 52492.65 examples/s]
Generating train split: 143885257 examples [2:26:13, 51241.79 examples/s]
Generating train split: 143890591 examples [2:26:13, 51816.26 examples/s]
Generating train split: 143895951 examples [2:26:13, 52312.93 examples/s]
Generating train split: 143902177 examples [2:26:13, 55210.72 examples/s]
Generating train split: 143907715 examples [2:26:13, 54184.92 examples/s]
Generating train split: 143913608 examples [2:26:13, 55562.84 examples/s]
Generating train split: 143920043 examples [2:26:13, 58124.81 examples/s]
Generating train split: 143925875 examples [2:26:13, 55063.85 examples/s]
Generating train split: 143931432 examples [2:26:13, 54586.24 examples/s]
Generating train split: 143937842 examples [2:26:13, 57317.98 examples/s]
Generating train split: 143944742 examples [2:26:14, 60712.27 examples/s]
Generating train split: 143950846 examples [2:26:14, 58192.20 examples/s]
Generating train split: 143956711 examples [2:26:14, 54589.50 examples/s]
Generating train split: 143962251 examples [2:26:14, 51760.74 examples/s]
Generating train split: 143968789 examples [2:26:14, 55446.79 examples/s]
Generating train split: 143974876 examples [2:26:14, 56949.69 examples/s]
Generating train split: 143980653 examples [2:26:14, 56371.81 examples/s]
Generating train split: 143986338 examples [2:26:14, 54295.77 examples/s]
Generating train split: 143992861 examples [2:26:14, 57361.65 examples/s]
Generating train split: 143998659 examples [2:26:15, 52178.74 examples/s]
Generating train split: 144004230 examples [2:26:15, 53124.74 examples/s]
Generating train split: 144009978 examples [2:26:15, 54318.60 examples/s]
Generating train split: 144015494 examples [2:26:15, 52793.10 examples/s]
Generating train split: 144021325 examples [2:26:15, 54332.27 examples/s]
Generating train split: 144026818 examples [2:26:15, 53582.22 examples/s]
Generating train split: 144032209 examples [2:26:15, 53661.19 examples/s]
Generating train split: 144038238 examples [2:26:15, 55581.14 examples/s]
Generating train split: 144044498 examples [2:26:15, 57623.67 examples/s]
Generating train split: 144051202 examples [2:26:16, 60383.85 examples/s]
Generating train split: 144057276 examples [2:26:16, 57953.00 examples/s]
Generating train split: 144063119 examples [2:26:16, 57550.50 examples/s]
Generating train split: 144070087 examples [2:26:16, 61064.64 examples/s]
Generating train split: 144076229 examples [2:26:16, 59132.62 examples/s]
Generating train split: 144082172 examples [2:26:16, 59110.15 examples/s]
Generating train split: 144088111 examples [2:26:16, 55565.56 examples/s]
Generating train split: 144094242 examples [2:26:16, 57153.16 examples/s]
Generating train split: 144100863 examples [2:26:16, 59731.77 examples/s]
Generating train split: 144106972 examples [2:26:16, 60101.89 examples/s]
Generating train split: 144113032 examples [2:26:17, 57176.58 examples/s]
Generating train split: 144118816 examples [2:26:17, 55656.48 examples/s]
Generating train split: 144124424 examples [2:26:17, 54167.48 examples/s]
Generating train split: 144131256 examples [2:26:17, 58145.93 examples/s]
Generating train split: 144140835 examples [2:26:17, 68919.02 examples/s]
Generating train split: 144149548 examples [2:26:17, 74189.40 examples/s]
Generating train split: 144157046 examples [2:26:17, 68325.89 examples/s]
Generating train split: 144164033 examples [2:26:17, 66418.98 examples/s]
Generating train split: 144170776 examples [2:26:17, 62401.89 examples/s]
Generating train split: 144177169 examples [2:26:18, 62808.87 examples/s]
Generating train split: 144183540 examples [2:26:18, 57391.94 examples/s]
Generating train split: 144190497 examples [2:26:18, 60541.62 examples/s]
Generating train split: 144196678 examples [2:26:18, 59168.91 examples/s]
Generating train split: 144203629 examples [2:26:18, 62024.08 examples/s]
Generating train split: 144210332 examples [2:26:18, 63436.58 examples/s]
Generating train split: 144217422 examples [2:26:18, 65582.48 examples/s]
Generating train split: 144224042 examples [2:26:18, 64461.87 examples/s]
Generating train split: 144230542 examples [2:26:18, 63793.00 examples/s]
Generating train split: 144236957 examples [2:26:19, 62283.44 examples/s]
Generating train split: 144243223 examples [2:26:19, 61673.62 examples/s]
Generating train split: 144249423 examples [2:26:19, 61361.42 examples/s]
Generating train split: 144255576 examples [2:26:19, 61330.27 examples/s]
Generating train split: 144261726 examples [2:26:19, 59280.65 examples/s]
Generating train split: 144268420 examples [2:26:19, 60788.46 examples/s]
Generating train split: 144274525 examples [2:26:19, 60639.10 examples/s]
Generating train split: 144280599 examples [2:26:19, 58875.95 examples/s]
Generating train split: 144286598 examples [2:26:19, 59181.19 examples/s]
Generating train split: 144292615 examples [2:26:19, 59463.30 examples/s]
Generating train split: 144298577 examples [2:26:20, 57227.71 examples/s]
Generating train split: 144304334 examples [2:26:20, 54968.02 examples/s]
Generating train split: 144309866 examples [2:26:20, 53821.05 examples/s]
Generating train split: 144315475 examples [2:26:20, 54438.13 examples/s]
Generating train split: 144321495 examples [2:26:20, 56081.17 examples/s]
Generating train split: 144327128 examples [2:26:20, 55605.56 examples/s]
Generating train split: 144332709 examples [2:26:20, 55654.85 examples/s]
Generating train split: 144338290 examples [2:26:20, 54430.39 examples/s]
Generating train split: 144344777 examples [2:26:20, 57412.86 examples/s]
Generating train split: 144351268 examples [2:26:21, 59595.56 examples/s]
Generating train split: 144357991 examples [2:26:21, 61840.93 examples/s]
Generating train split: 144364964 examples [2:26:21, 64169.53 examples/s]
Generating train split: 144371407 examples [2:26:21, 63334.81 examples/s]
Generating train split: 144378133 examples [2:26:21, 64479.72 examples/s]
Generating train split: 144384595 examples [2:26:21, 63063.21 examples/s]
Generating train split: 144390915 examples [2:26:21, 61590.50 examples/s]
Generating train split: 144397346 examples [2:26:21, 62377.33 examples/s]
Generating train split: 144403598 examples [2:26:21, 61840.82 examples/s]
Generating train split: 144409797 examples [2:26:21, 59878.80 examples/s]
Generating train split: 144416846 examples [2:26:22, 62910.07 examples/s]
Generating train split: 144423165 examples [2:26:22, 62915.17 examples/s]
Generating train split: 144429866 examples [2:26:22, 64101.43 examples/s]
Generating train split: 144436290 examples [2:26:22, 63837.59 examples/s]
Generating train split: 144442687 examples [2:26:22, 59755.41 examples/s]
Generating train split: 144448731 examples [2:26:22, 59452.53 examples/s]
Generating train split: 144455755 examples [2:26:22, 62499.33 examples/s]
Generating train split: 144462152 examples [2:26:22, 62893.54 examples/s]
Generating train split: 144468487 examples [2:26:22, 58322.09 examples/s]
Generating train split: 144474758 examples [2:26:23, 59505.35 examples/s]
Generating train split: 144480791 examples [2:26:23, 56662.62 examples/s]
Generating train split: 144487538 examples [2:26:23, 59656.64 examples/s]
Generating train split: 144493623 examples [2:26:23, 59952.17 examples/s]
Generating train split: 144499673 examples [2:26:23, 58865.68 examples/s]
Generating train split: 144505601 examples [2:26:23, 58109.65 examples/s]
Generating train split: 144511445 examples [2:26:23, 58087.76 examples/s]
Generating train split: 144517497 examples [2:26:23, 58772.17 examples/s]
Generating train split: 144523402 examples [2:26:23, 58726.30 examples/s]
Generating train split: 144529289 examples [2:26:23, 57219.35 examples/s]
Generating train split: 144536598 examples [2:26:24, 61836.27 examples/s]
Generating train split: 144543842 examples [2:26:24, 64826.00 examples/s]
Generating train split: 144550359 examples [2:26:24, 61532.79 examples/s]
Generating train split: 144556575 examples [2:26:24, 61611.98 examples/s]
Generating train split: 144562771 examples [2:26:24, 61344.88 examples/s]
Generating train split: 144568929 examples [2:26:24, 60021.75 examples/s]
Generating train split: 144574954 examples [2:26:24, 51118.20 examples/s]
Generating train split: 144581101 examples [2:26:24, 53794.39 examples/s]
Generating train split: 144587048 examples [2:26:24, 55313.33 examples/s]
Generating train split: 144592750 examples [2:26:25, 55188.68 examples/s]
Generating train split: 144598623 examples [2:26:25, 56161.94 examples/s]
Generating train split: 144606690 examples [2:26:25, 63204.63 examples/s]
Generating train split: 144615956 examples [2:26:25, 71751.85 examples/s]
Generating train split: 144623223 examples [2:26:25, 69221.26 examples/s]
Generating train split: 144630235 examples [2:26:25, 60359.31 examples/s]
Generating train split: 144636528 examples [2:26:25, 54540.82 examples/s]
Generating train split: 144642236 examples [2:26:25, 54601.45 examples/s]
Generating train split: 144648429 examples [2:26:25, 56513.70 examples/s]
Generating train split: 144654235 examples [2:26:26, 55973.82 examples/s]
Generating train split: 144660795 examples [2:26:26, 58619.05 examples/s]
Generating train split: 144666749 examples [2:26:26, 56071.68 examples/s]
Generating train split: 144672447 examples [2:26:26, 53428.83 examples/s]
Generating train split: 144678281 examples [2:26:26, 54747.51 examples/s]
Generating train split: 144684145 examples [2:26:26, 55350.30 examples/s]
Generating train split: 144689749 examples [2:26:26, 51751.14 examples/s]
Generating train split: 144695884 examples [2:26:26, 54385.62 examples/s]
Generating train split: 144701395 examples [2:26:26, 53103.68 examples/s]
Generating train split: 144706763 examples [2:26:27, 52549.49 examples/s]
Generating train split: 144712067 examples [2:26:27, 47352.56 examples/s]
Generating train split: 144719246 examples [2:26:27, 53879.99 examples/s]
Generating train split: 144726661 examples [2:26:27, 59476.99 examples/s]
Generating train split: 144733056 examples [2:26:27, 60727.97 examples/s]
Generating train split: 144739250 examples [2:26:27, 56626.60 examples/s]
Generating train split: 144745043 examples [2:26:27, 55172.32 examples/s]
Generating train split: 144750651 examples [2:26:27, 53849.70 examples/s]
Generating train split: 144756514 examples [2:26:27, 55152.30 examples/s]
Generating train split: 144762404 examples [2:26:28, 56212.69 examples/s]
Generating train split: 144769127 examples [2:26:28, 59371.92 examples/s]
Generating train split: 144775115 examples [2:26:28, 57231.60 examples/s]
Generating train split: 144780883 examples [2:26:28, 56009.15 examples/s]
Generating train split: 144786517 examples [2:26:28, 53351.98 examples/s]
Generating train split: 144791901 examples [2:26:28, 52018.16 examples/s]
Generating train split: 144798669 examples [2:26:28, 56383.77 examples/s]
Generating train split: 144806803 examples [2:26:28, 63492.64 examples/s]
Generating train split: 144813590 examples [2:26:28, 64744.59 examples/s]
Generating train split: 144820125 examples [2:26:29, 64010.22 examples/s]
Generating train split: 144827300 examples [2:26:29, 66268.30 examples/s]
Generating train split: 144834612 examples [2:26:29, 68221.35 examples/s]
Generating train split: 144841469 examples [2:26:29, 67281.09 examples/s]
Generating train split: 144848224 examples [2:26:29, 65360.25 examples/s]
Generating train split: 144854800 examples [2:26:29, 62615.22 examples/s]
Generating train split: 144861099 examples [2:26:29, 59853.51 examples/s]
Generating train split: 144868485 examples [2:26:29, 63752.60 examples/s]
Generating train split: 144874928 examples [2:26:29, 63569.55 examples/s]
Generating train split: 144881326 examples [2:26:29, 63108.58 examples/s]
Generating train split: 144887677 examples [2:26:30, 62609.47 examples/s]
Generating train split: 144893963 examples [2:26:30, 61551.02 examples/s]
Generating train split: 144900133 examples [2:26:30, 60909.87 examples/s]
Generating train split: 144906632 examples [2:26:30, 62088.93 examples/s]
Generating train split: 144913583 examples [2:26:30, 64238.55 examples/s]
Generating train split: 144920495 examples [2:26:30, 65658.22 examples/s]
Generating train split: 144927082 examples [2:26:30, 65165.33 examples/s]
Generating train split: 144933611 examples [2:26:30, 65200.52 examples/s]
Generating train split: 144940138 examples [2:26:30, 61130.53 examples/s]
Generating train split: 144946613 examples [2:26:31, 62086.66 examples/s]
Generating train split: 144952875 examples [2:26:31, 59218.23 examples/s]
Generating train split: 144958853 examples [2:26:31, 57453.70 examples/s]
Generating train split: 144965587 examples [2:26:31, 60204.63 examples/s]
Generating train split: 144972111 examples [2:26:31, 61622.62 examples/s]
Generating train split: 144978325 examples [2:26:31, 59553.43 examples/s]
Generating train split: 144985788 examples [2:26:31, 63830.15 examples/s]
Generating train split: 144992231 examples [2:26:31, 63129.95 examples/s]
Generating train split: 144998589 examples [2:26:31, 63227.31 examples/s]
Generating train split: 145005659 examples [2:26:31, 65413.63 examples/s]
Generating train split: 145012233 examples [2:26:32, 65489.25 examples/s]
Generating train split: 145018871 examples [2:26:32, 65744.68 examples/s]
Generating train split: 145025459 examples [2:26:32, 60847.07 examples/s]
Generating train split: 145031636 examples [2:26:32, 59068.59 examples/s]
Generating train split: 145037608 examples [2:26:32, 58990.96 examples/s]
Generating train split: 145043560 examples [2:26:32, 58312.00 examples/s]
Generating train split: 145049430 examples [2:26:32, 57037.15 examples/s]
Generating train split: 145055164 examples [2:26:32, 56852.82 examples/s]
Generating train split: 145060870 examples [2:26:32, 54352.63 examples/s]
Generating train split: 145066692 examples [2:26:33, 55401.69 examples/s]
Generating train split: 145073108 examples [2:26:33, 57904.13 examples/s]
Generating train split: 145079420 examples [2:26:33, 59406.13 examples/s]
Generating train split: 145085385 examples [2:26:33, 55846.19 examples/s]
Generating train split: 145091565 examples [2:26:33, 57490.46 examples/s]
Generating train split: 145097366 examples [2:26:33, 55998.06 examples/s]
Generating train split: 145103005 examples [2:26:33, 54685.03 examples/s]
Generating train split: 145110044 examples [2:26:33, 59136.53 examples/s]
Generating train split: 145116849 examples [2:26:33, 61698.59 examples/s]
Generating train split: 145123065 examples [2:26:33, 58788.21 examples/s]
Generating train split: 145128998 examples [2:26:34, 57974.04 examples/s]
Generating train split: 145135616 examples [2:26:34, 60292.91 examples/s]
Generating train split: 145142128 examples [2:26:34, 61684.33 examples/s]
Generating train split: 145148336 examples [2:26:34, 61735.11 examples/s]
Generating train split: 145154536 examples [2:26:34, 60036.51 examples/s]
Generating train split: 145161992 examples [2:26:34, 64246.86 examples/s]
Generating train split: 145168629 examples [2:26:34, 64858.89 examples/s]
Generating train split: 145176410 examples [2:26:34, 68658.30 examples/s]
Generating train split: 145183771 examples [2:26:34, 70118.81 examples/s]
Generating train split: 145190814 examples [2:26:35, 67853.79 examples/s]
Generating train split: 145197825 examples [2:26:35, 68501.61 examples/s]
Generating train split: 145204706 examples [2:26:35, 68294.89 examples/s]
Generating train split: 145211551 examples [2:26:35, 67134.86 examples/s]
Generating train split: 145218289 examples [2:26:35, 64970.44 examples/s]
Generating train split: 145224816 examples [2:26:35, 61662.39 examples/s]
Generating train split: 145231024 examples [2:26:35, 56238.85 examples/s]
Generating train split: 145236755 examples [2:26:35, 53616.43 examples/s]
Generating train split: 145242193 examples [2:26:35, 52980.98 examples/s]
Generating train split: 145247950 examples [2:26:36, 54211.74 examples/s]
Generating train split: 145253640 examples [2:26:36, 54943.57 examples/s]
Generating train split: 145259172 examples [2:26:36, 53558.46 examples/s]
Generating train split: 145264557 examples [2:26:36, 53543.63 examples/s]
Generating train split: 145270292 examples [2:26:36, 54637.44 examples/s]
Generating train split: 145275992 examples [2:26:36, 55314.36 examples/s]
Generating train split: 145282007 examples [2:26:36, 56704.90 examples/s]
Generating train split: 145288551 examples [2:26:36, 59271.98 examples/s]
Generating train split: 145294905 examples [2:26:36, 60520.63 examples/s]
Generating train split: 145300979 examples [2:26:36, 57699.73 examples/s]
Generating train split: 145307469 examples [2:26:37, 59759.98 examples/s]
Generating train split: 145315105 examples [2:26:37, 64580.65 examples/s]
Generating train split: 145322080 examples [2:26:37, 66095.29 examples/s]
Generating train split: 145328722 examples [2:26:37, 61691.04 examples/s]
Generating train split: 145335542 examples [2:26:37, 63525.89 examples/s]
Generating train split: 145341967 examples [2:26:37, 59930.60 examples/s]
Generating train split: 145348046 examples [2:26:37, 59529.48 examples/s]
Generating train split: 145355144 examples [2:26:37, 62751.76 examples/s]
Generating train split: 145361479 examples [2:26:37, 62862.68 examples/s]
Generating train split: 145367810 examples [2:26:38, 60206.85 examples/s]
Generating train split: 145373884 examples [2:26:38, 58923.87 examples/s]
Generating train split: 145379812 examples [2:26:38, 58201.51 examples/s]
Generating train split: 145385888 examples [2:26:38, 58902.54 examples/s]
Generating train split: 145391848 examples [2:26:38, 59100.11 examples/s]
Generating train split: 145398176 examples [2:26:38, 60313.11 examples/s]
Generating train split: 145405375 examples [2:26:38, 63733.25 examples/s]
Generating train split: 145411769 examples [2:26:38, 57303.89 examples/s]
Generating train split: 145417639 examples [2:26:38, 53864.21 examples/s]
Generating train split: 145423156 examples [2:26:39, 49865.86 examples/s]
Generating train split: 145430112 examples [2:26:39, 54984.69 examples/s]
Generating train split: 145436600 examples [2:26:39, 57653.09 examples/s]
Generating train split: 145442516 examples [2:26:39, 57790.75 examples/s]
Generating train split: 145448399 examples [2:26:39, 53695.22 examples/s]
Generating train split: 145453983 examples [2:26:39, 54252.42 examples/s]
Generating train split: 145459501 examples [2:26:39, 53578.53 examples/s]
Generating train split: 145465800 examples [2:26:39, 56202.34 examples/s]
Generating train split: 145471780 examples [2:26:39, 57227.07 examples/s]
Generating train split: 145478374 examples [2:26:39, 59736.67 examples/s]
Generating train split: 145484392 examples [2:26:40, 59427.09 examples/s]
Generating train split: 145490363 examples [2:26:40, 58283.53 examples/s]
Generating train split: 145496428 examples [2:26:40, 58919.30 examples/s]
Generating train split: 145502345 examples [2:26:40, 58200.85 examples/s]
Generating train split: 145508352 examples [2:26:40, 58723.58 examples/s]
Generating train split: 145514238 examples [2:26:40, 58362.51 examples/s]
Generating train split: 145520090 examples [2:26:40, 57516.05 examples/s]
Generating train split: 145525849 examples [2:26:40, 57086.88 examples/s]
Generating train split: 145531563 examples [2:26:40, 56750.65 examples/s]
Generating train split: 145537250 examples [2:26:40, 56421.64 examples/s]
Generating train split: 145543216 examples [2:26:41, 57371.58 examples/s]
Generating train split: 145550314 examples [2:26:41, 61375.72 examples/s]
Generating train split: 145557123 examples [2:26:41, 63359.28 examples/s]
Generating train split: 145563466 examples [2:26:41, 60154.26 examples/s]
Generating train split: 145569531 examples [2:26:41, 59039.65 examples/s]
Generating train split: 145576487 examples [2:26:41, 62049.24 examples/s]
Generating train split: 145583958 examples [2:26:41, 65728.77 examples/s]
Generating train split: 145590569 examples [2:26:41, 64475.06 examples/s]
Generating train split: 145598404 examples [2:26:41, 68511.28 examples/s]
Generating train split: 145605857 examples [2:26:42, 70269.24 examples/s]
Generating train split: 145612916 examples [2:26:42, 69698.79 examples/s]
Generating train split: 145620066 examples [2:26:42, 70203.97 examples/s]
Generating train split: 145627105 examples [2:26:42, 66252.04 examples/s]
Generating train split: 145633789 examples [2:26:42, 62473.45 examples/s]
Generating train split: 145640304 examples [2:26:42, 63168.55 examples/s]
Generating train split: 145646682 examples [2:26:42, 63057.98 examples/s]
Generating train split: 145653432 examples [2:26:42, 64314.68 examples/s]
Generating train split: 145659895 examples [2:26:42, 63238.49 examples/s]
Generating train split: 145666737 examples [2:26:42, 64736.29 examples/s]
Generating train split: 145673235 examples [2:26:43, 64670.97 examples/s]
Generating train split: 145679729 examples [2:26:43, 61354.71 examples/s]
Generating train split: 145685915 examples [2:26:43, 61175.41 examples/s]
Generating train split: 145692845 examples [2:26:43, 63453.78 examples/s]
Generating train split: 145699224 examples [2:26:43, 58224.49 examples/s]
Generating train split: 145706043 examples [2:26:43, 60965.48 examples/s]
Generating train split: 145712238 examples [2:26:43, 60862.67 examples/s]
Generating train split: 145718406 examples [2:26:43, 61088.10 examples/s]
Generating train split: 145724565 examples [2:26:43, 60248.09 examples/s]
Generating train split: 145730841 examples [2:26:44, 60974.82 examples/s]
Generating train split: 145736970 examples [2:26:44, 60344.73 examples/s]
Generating train split: 145743115 examples [2:26:44, 60653.17 examples/s]
Generating train split: 145749724 examples [2:26:44, 62239.14 examples/s]
Generating train split: 145756326 examples [2:26:44, 63333.06 examples/s]
Generating train split: 145763008 examples [2:26:44, 64359.18 examples/s]
Generating train split: 145769456 examples [2:26:44, 63694.49 examples/s]
Generating train split: 145775836 examples [2:26:44, 63078.96 examples/s]
Generating train split: 145783111 examples [2:26:44, 65908.06 examples/s]
Generating train split: 145789721 examples [2:26:44, 65717.08 examples/s]
Generating train split: 145796299 examples [2:26:45, 63225.32 examples/s]
Generating train split: 145802646 examples [2:26:45, 62010.51 examples/s]
Generating train split: 145808873 examples [2:26:45, 57502.37 examples/s]
Generating train split: 145814692 examples [2:26:45, 56951.29 examples/s]
Generating train split: 145820437 examples [2:26:45, 54476.44 examples/s]
Generating train split: 145826043 examples [2:26:45, 54895.45 examples/s]
Generating train split: 145831854 examples [2:26:45, 55788.36 examples/s]
Generating train split: 145838037 examples [2:26:45, 57499.21 examples/s]
Generating train split: 145844157 examples [2:26:45, 58554.40 examples/s]
Generating train split: 145850231 examples [2:26:46, 59194.49 examples/s]
Generating train split: 145856167 examples [2:26:46, 58546.03 examples/s]
Generating train split: 145862043 examples [2:26:46, 57294.27 examples/s]
Generating train split: 145868489 examples [2:26:46, 59371.41 examples/s]
Generating train split: 145874442 examples [2:26:46, 59412.54 examples/s]
Generating train split: 145880398 examples [2:26:46, 58021.53 examples/s]
Generating train split: 145886221 examples [2:26:46, 56042.83 examples/s]
Generating train split: 145891849 examples [2:26:46, 51631.50 examples/s]
Generating train split: 145897087 examples [2:26:46, 51429.68 examples/s]
Generating train split: 145904406 examples [2:26:46, 57508.25 examples/s]
Generating train split: 145911187 examples [2:26:47, 60442.79 examples/s]
Generating train split: 145920782 examples [2:26:47, 70700.30 examples/s]
Generating train split: 145929401 examples [2:26:47, 75178.15 examples/s]
Generating train split: 145936995 examples [2:26:47, 64462.15 examples/s]
Generating train split: 145943761 examples [2:26:47, 62121.17 examples/s]
Generating train split: 145950204 examples [2:26:47, 58758.54 examples/s]
Generating train split: 145956539 examples [2:26:47, 59942.97 examples/s]
Generating train split: 145963662 examples [2:26:47, 63010.25 examples/s]
Generating train split: 145970092 examples [2:26:47, 61926.36 examples/s]
Generating train split: 145976375 examples [2:26:48, 59011.98 examples/s]
Generating train split: 145982355 examples [2:26:48, 58674.01 examples/s]
Generating train split: 145988988 examples [2:26:48, 60806.18 examples/s]
Generating train split: 145995125 examples [2:26:48, 58504.35 examples/s]
Generating train split: 146001022 examples [2:26:48, 58607.18 examples/s]
Generating train split: 146006991 examples [2:26:48, 58889.98 examples/s]
Generating train split: 146013189 examples [2:26:48, 59785.28 examples/s]
Generating train split: 146019729 examples [2:26:48, 61410.70 examples/s]
Generating train split: 146025894 examples [2:26:48, 61405.94 examples/s]
Generating train split: 146032050 examples [2:26:49, 60977.24 examples/s]
Generating train split: 146039008 examples [2:26:49, 63490.97 examples/s]
Generating train split: 146045451 examples [2:26:49, 63731.28 examples/s]
Generating train split: 146051952 examples [2:26:49, 64039.85 examples/s]
Generating train split: 146058373 examples [2:26:49, 61799.62 examples/s]
Generating train split: 146064867 examples [2:26:49, 62709.81 examples/s]
Generating train split: 146071166 examples [2:26:49, 62515.43 examples/s]
Generating train split: 146077429 examples [2:26:49, 62113.61 examples/s]
Generating train split: 146083649 examples [2:26:49, 58924.97 examples/s]
Generating train split: 146090082 examples [2:26:49, 60458.16 examples/s]
Generating train split: 146096166 examples [2:26:50, 60315.44 examples/s]
Generating train split: 146102230 examples [2:26:50, 59873.04 examples/s]
Generating train split: 146108413 examples [2:26:50, 60418.07 examples/s]
Generating train split: 146114473 examples [2:26:50, 59866.53 examples/s]
Generating train split: 146120478 examples [2:26:50, 59095.69 examples/s]
Generating train split: 146126858 examples [2:26:50, 60451.08 examples/s]
Generating train split: 146133609 examples [2:26:50, 62510.28 examples/s]
Generating train split: 146140530 examples [2:26:50, 64459.57 examples/s]
Generating train split: 146146989 examples [2:26:50, 64226.56 examples/s]
Generating train split: 146154696 examples [2:26:50, 68034.37 examples/s]
Generating train split: 146161524 examples [2:26:51, 66907.16 examples/s]
Generating train split: 146168238 examples [2:26:51, 66607.32 examples/s]
Generating train split: 146175308 examples [2:26:51, 67814.54 examples/s]
Generating train split: 146183639 examples [2:26:51, 72402.92 examples/s]
Generating train split: 146191098 examples [2:26:51, 73039.38 examples/s]
Generating train split: 146198421 examples [2:26:51, 70139.72 examples/s]
Generating train split: 146205466 examples [2:26:51, 68668.05 examples/s]
Generating train split: 146212362 examples [2:26:51, 68224.48 examples/s]
Generating train split: 146220867 examples [2:26:51, 73087.77 examples/s]
Generating train split: 146229214 examples [2:26:52, 76095.11 examples/s]
Generating train split: 146236851 examples [2:26:52, 73776.05 examples/s]
Generating train split: 146244261 examples [2:26:52, 71633.84 examples/s]
Generating train split: 146252309 examples [2:26:52, 74154.77 examples/s]
Generating train split: 146260177 examples [2:26:52, 75437.54 examples/s]
Generating train split: 146267759 examples [2:26:52, 75237.45 examples/s]
Generating train split: 146275317 examples [2:26:52, 74532.63 examples/s]
Generating train split: 146282785 examples [2:26:52, 71170.41 examples/s]
Generating train split: 146289948 examples [2:26:52, 70841.96 examples/s]
Generating train split: 146297061 examples [2:26:52, 68713.80 examples/s]
Generating train split: 146303960 examples [2:26:53, 67334.20 examples/s]
Generating train split: 146310947 examples [2:26:53, 68048.16 examples/s]
Generating train split: 146317773 examples [2:26:53, 64669.17 examples/s]
Generating train split: 146324292 examples [2:26:53, 64104.64 examples/s]
Generating train split: 146330732 examples [2:26:53, 61961.55 examples/s]
Generating train split: 146338770 examples [2:26:53, 67132.14 examples/s]
Generating train split: 146345537 examples [2:26:53, 63002.54 examples/s]
Generating train split: 146352088 examples [2:26:53, 63690.37 examples/s]
Generating train split: 146359232 examples [2:26:53, 65870.69 examples/s]
Generating train split: 146365875 examples [2:26:54, 65031.56 examples/s]
Generating train split: 146373550 examples [2:26:54, 68413.52 examples/s]
Generating train split: 146382204 examples [2:26:54, 73704.94 examples/s]
Generating train split: 146389624 examples [2:26:54, 72620.60 examples/s]
Generating train split: 146396927 examples [2:26:54, 72258.84 examples/s]
Generating train split: 146404180 examples [2:26:54, 68397.65 examples/s]
Generating train split: 146411472 examples [2:26:54, 69677.35 examples/s]
Generating train split: 146418944 examples [2:26:54, 71073.99 examples/s]
Generating train split: 146426103 examples [2:26:54, 69614.24 examples/s]
Generating train split: 146433099 examples [2:26:54, 68964.52 examples/s]
Generating train split: 146440947 examples [2:26:55, 71672.96 examples/s]
Generating train split: 146448149 examples [2:26:55, 71252.14 examples/s]
Generating train split: 146455312 examples [2:26:55, 67948.69 examples/s]
Generating train split: 146462160 examples [2:26:55, 67744.85 examples/s]
Generating train split: 146468967 examples [2:26:55, 67836.95 examples/s]
Generating train split: 146476178 examples [2:26:55, 69034.93 examples/s]
Generating train split: 146483098 examples [2:26:55, 66539.33 examples/s]
Generating train split: 146491293 examples [2:26:55, 70952.62 examples/s]
Generating train split: 146498447 examples [2:26:55, 71107.10 examples/s]
Generating train split: 146505588 examples [2:26:56, 66887.16 examples/s]
Generating train split: 146512346 examples [2:26:56, 64100.55 examples/s]
Generating train split: 146518818 examples [2:26:56, 60477.82 examples/s]
Generating train split: 146525354 examples [2:26:56, 61785.45 examples/s]
Generating train split: 146532905 examples [2:26:56, 65612.81 examples/s]
Generating train split: 146539545 examples [2:26:56, 63798.97 examples/s]
Generating train split: 146547025 examples [2:26:56, 66896.38 examples/s]
Generating train split: 146553775 examples [2:26:56, 66131.88 examples/s]
Generating train split: 146560436 examples [2:26:56, 64998.04 examples/s]
Generating train split: 146567167 examples [2:26:57, 65653.02 examples/s]
Generating train split: 146574870 examples [2:26:57, 68961.76 examples/s]
Generating train split: 146582233 examples [2:26:57, 70326.60 examples/s]
Generating train split: 146589294 examples [2:26:57, 70033.43 examples/s]
Generating train split: 146596313 examples [2:26:57, 64826.20 examples/s]
Generating train split: 146602892 examples [2:26:57, 63369.57 examples/s]
Generating train split: 146609295 examples [2:26:57, 62926.32 examples/s]
Generating train split: 146615633 examples [2:26:57, 61949.01 examples/s]
Generating train split: 146621900 examples [2:26:57, 62139.35 examples/s]
Generating train split: 146629840 examples [2:26:57, 67113.58 examples/s]
Generating train split: 146637440 examples [2:26:58, 69698.80 examples/s]
Generating train split: 146645075 examples [2:26:58, 71631.80 examples/s]
Generating train split: 146652266 examples [2:26:58, 69476.54 examples/s]
Generating train split: 146659245 examples [2:26:58, 68465.58 examples/s]
Generating train split: 146666113 examples [2:26:58, 68366.73 examples/s]
Generating train split: 146672978 examples [2:26:58, 68263.83 examples/s]
Generating train split: 146679889 examples [2:26:58, 68471.91 examples/s]
Generating train split: 146687256 examples [2:26:58, 69983.60 examples/s]
Generating train split: 146695347 examples [2:26:58, 73226.68 examples/s]
Generating train split: 146704113 examples [2:26:58, 77484.95 examples/s]
Generating train split: 146711877 examples [2:26:59, 71777.67 examples/s]
Generating train split: 146719154 examples [2:26:59, 70778.40 examples/s]
Generating train split: 146726294 examples [2:26:59, 70674.97 examples/s]
Generating train split: 146733405 examples [2:26:59, 70630.30 examples/s]
Generating train split: 146740601 examples [2:26:59, 71001.22 examples/s]
Generating train split: 146747864 examples [2:26:59, 71472.05 examples/s]
Generating train split: 146755038 examples [2:26:59, 71550.03 examples/s]
Generating train split: 146762216 examples [2:26:59, 70559.15 examples/s]
Generating train split: 146769289 examples [2:26:59, 69469.12 examples/s]
Generating train split: 146776657 examples [2:27:00, 70657.25 examples/s]
Generating train split: 146783733 examples [2:27:00, 66954.57 examples/s]
Generating train split: 146790479 examples [2:27:00, 64412.77 examples/s]
Generating train split: 146796967 examples [2:27:00, 63891.32 examples/s]
Generating train split: 146803788 examples [2:27:00, 65113.54 examples/s]
Generating train split: 146810609 examples [2:27:00, 65929.07 examples/s]
Generating train split: 146817858 examples [2:27:00, 67819.06 examples/s]
Generating train split: 146825475 examples [2:27:00, 70242.59 examples/s]
Generating train split: 146832537 examples [2:27:00, 70338.43 examples/s]
Generating train split: 146839588 examples [2:27:00, 69974.21 examples/s]
Generating train split: 146846856 examples [2:27:01, 70772.06 examples/s]
Generating train split: 146854877 examples [2:27:01, 73565.15 examples/s]
Generating train split: 146862828 examples [2:27:01, 75307.97 examples/s]
Generating train split: 146870821 examples [2:27:01, 76682.59 examples/s]
Generating train split: 146879211 examples [2:27:01, 78836.10 examples/s]
Generating train split: 146887247 examples [2:27:01, 79290.72 examples/s]
Generating train split: 146895424 examples [2:27:01, 80025.61 examples/s]
Generating train split: 146903438 examples [2:27:01, 79762.90 examples/s]
Generating train split: 146911416 examples [2:27:01, 78656.92 examples/s]
Generating train split: 146919291 examples [2:27:01, 75993.76 examples/s]
Generating train split: 146926918 examples [2:27:02, 75858.17 examples/s]
Generating train split: 146934526 examples [2:27:02, 74931.38 examples/s]
Generating train split: 146942885 examples [2:27:02, 77431.65 examples/s]
Generating train split: 146951016 examples [2:27:02, 78568.54 examples/s]
Generating train split: 146959183 examples [2:27:02, 79482.29 examples/s]
Generating train split: 146967985 examples [2:27:02, 82006.58 examples/s]
Generating train split: 146976205 examples [2:27:02, 81901.68 examples/s]
Generating train split: 146985296 examples [2:27:02, 84551.28 examples/s]
Generating train split: 146993765 examples [2:27:02, 84590.26 examples/s]
Generating train split: 147002236 examples [2:27:02, 81715.38 examples/s]
Generating train split: 147011038 examples [2:27:03, 83551.00 examples/s]
Generating train split: 147019886 examples [2:27:03, 84974.38 examples/s]
Generating train split: 147028407 examples [2:27:03, 83300.33 examples/s]
Generating train split: 147036879 examples [2:27:03, 83680.59 examples/s]
Generating train split: 147045335 examples [2:27:03, 83908.54 examples/s]
Generating train split: 147053743 examples [2:27:03, 79413.49 examples/s]
Generating train split: 147061747 examples [2:27:03, 78479.37 examples/s]
Generating train split: 147069634 examples [2:27:03, 78283.90 examples/s]
Generating train split: 147078127 examples [2:27:03, 80188.10 examples/s]
Generating train split: 147086183 examples [2:27:04, 77514.92 examples/s]
Generating train split: 147093974 examples [2:27:04, 75356.83 examples/s]
Generating train split: 147101543 examples [2:27:04, 69781.64 examples/s]
Generating train split: 147108611 examples [2:27:04, 66847.74 examples/s]
Generating train split: 147115950 examples [2:27:04, 68624.92 examples/s]
Generating train split: 147123531 examples [2:27:04, 70618.84 examples/s]
Generating train split: 147130652 examples [2:27:04, 68730.35 examples/s]
Generating train split: 147137586 examples [2:27:04, 68596.85 examples/s]
Generating train split: 147144579 examples [2:27:04, 68964.27 examples/s]
Generating train split: 147151508 examples [2:27:05, 67827.49 examples/s]
Generating train split: 147158627 examples [2:27:05, 68786.50 examples/s]
Generating train split: 147165527 examples [2:27:05, 66807.15 examples/s]
Generating train split: 147172228 examples [2:27:05, 25824.63 examples/s]
Generating train split: 147177229 examples [2:27:05, 28992.31 examples/s]
Generating train split: 147183164 examples [2:27:06, 33946.46 examples/s]
Generating train split: 147189116 examples [2:27:06, 38779.69 examples/s]
Generating train split: 147194736 examples [2:27:06, 42478.72 examples/s]
Generating train split: 147201193 examples [2:27:06, 47573.11 examples/s]
Generating train split: 147207178 examples [2:27:06, 50613.58 examples/s]
Generating train split: 147213018 examples [2:27:06, 52289.88 examples/s]
Generating train split: 147220401 examples [2:27:06, 58110.96 examples/s]
Generating train split: 147226748 examples [2:27:06, 59572.60 examples/s]
Generating train split: 147233200 examples [2:27:06, 60973.77 examples/s]
Generating train split: 147239536 examples [2:27:06, 61457.23 examples/s]
Generating train split: 147246561 examples [2:27:07, 64004.62 examples/s]
Generating train split: 147253135 examples [2:27:07, 64351.52 examples/s]
Generating train split: 147260185 examples [2:27:07, 66133.87 examples/s]
Generating train split: 147267420 examples [2:27:07, 67971.63 examples/s]
Generating train split: 147274277 examples [2:27:07, 67132.58 examples/s]
Generating train split: 147282098 examples [2:27:07, 70370.33 examples/s]
Generating train split: 147289177 examples [2:27:07, 69713.09 examples/s]
Generating train split: 147296172 examples [2:27:07, 69252.02 examples/s]
Generating train split: 147303924 examples [2:27:07, 71684.08 examples/s]
Generating train split: 147311116 examples [2:27:07, 71382.20 examples/s]
Generating train split: 147318306 examples [2:27:08, 71521.72 examples/s]
Generating train split: 147325468 examples [2:27:08, 70067.09 examples/s]
Generating train split: 147333440 examples [2:27:08, 72876.16 examples/s]
Generating train split: 147341156 examples [2:27:08, 74119.74 examples/s]
Generating train split: 147349854 examples [2:27:08, 77915.24 examples/s]
Generating train split: 147357662 examples [2:27:08, 75695.81 examples/s]
Generating train split: 147365268 examples [2:27:08, 68609.82 examples/s]
Generating train split: 147372403 examples [2:27:08, 69344.57 examples/s]
Generating train split: 147379954 examples [2:27:08, 71072.76 examples/s]
Generating train split: 147387148 examples [2:27:09, 68925.76 examples/s]
Generating train split: 147394569 examples [2:27:09, 70402.25 examples/s]
Generating train split: 147401890 examples [2:27:09, 71203.59 examples/s]
Generating train split: 147409840 examples [2:27:09, 73599.97 examples/s]
Generating train split: 147417575 examples [2:27:09, 74670.81 examples/s]
Generating train split: 147425079 examples [2:27:09, 68703.77 examples/s]
Generating train split: 147432060 examples [2:27:09, 67251.23 examples/s]
Generating train split: 147438861 examples [2:27:09, 65768.00 examples/s]
Generating train split: 147446396 examples [2:27:09, 68422.70 examples/s]
Generating train split: 147453580 examples [2:27:10, 69381.07 examples/s]
Generating train split: 147460608 examples [2:27:10, 69612.05 examples/s]
Generating train split: 147468735 examples [2:27:10, 73007.94 examples/s]
Generating train split: 147476074 examples [2:27:10, 71567.55 examples/s]
Generating train split: 147484142 examples [2:27:10, 74215.53 examples/s]
Generating train split: 147491602 examples [2:27:10, 71417.33 examples/s]
Generating train split: 147498990 examples [2:27:10, 72108.83 examples/s]
Generating train split: 147506311 examples [2:27:10, 72407.50 examples/s]
Generating train split: 147514090 examples [2:27:10, 73980.98 examples/s]
Generating train split: 147521742 examples [2:27:10, 74713.02 examples/s]
Generating train split: 147529236 examples [2:27:11, 71160.41 examples/s]
Generating train split: 147536769 examples [2:27:11, 72339.41 examples/s]
Generating train split: 147545673 examples [2:27:11, 77190.02 examples/s]
Generating train split: 147553958 examples [2:27:11, 78813.80 examples/s]
Generating train split: 147562609 examples [2:27:11, 81066.74 examples/s]
Generating train split: 147571422 examples [2:27:11, 83158.92 examples/s]
Generating train split: 147580417 examples [2:27:11, 85171.30 examples/s]
Generating train split: 147589146 examples [2:27:11, 85801.03 examples/s]
Generating train split: 147597755 examples [2:27:11, 83202.45 examples/s]
Generating train split: 147606217 examples [2:27:11, 83591.50 examples/s]
Generating train split: 147614609 examples [2:27:12, 80787.79 examples/s]
Generating train split: 147622721 examples [2:27:12, 78378.35 examples/s]
Generating train split: 147630593 examples [2:27:12, 78152.82 examples/s]
Generating train split: 147639601 examples [2:27:12, 81574.02 examples/s]
Generating train split: 147648270 examples [2:27:12, 83035.59 examples/s]
Generating train split: 147656921 examples [2:27:12, 84051.11 examples/s]
Generating train split: 147665348 examples [2:27:12, 83239.57 examples/s]
Generating train split: 147674159 examples [2:27:12, 84631.67 examples/s]
Generating train split: 147682644 examples [2:27:12, 84233.55 examples/s]
Generating train split: 147691869 examples [2:27:12, 86582.83 examples/s]
Generating train split: 147701863 examples [2:27:13, 90538.78 examples/s]
Generating train split: 147711204 examples [2:27:13, 91365.77 examples/s]
Generating train split: 147720359 examples [2:27:13, 79146.57 examples/s]
Generating train split: 147728582 examples [2:27:13, 75965.67 examples/s]
Generating train split: 147736404 examples [2:27:13, 75616.54 examples/s]
Generating train split: 147744305 examples [2:27:13, 76532.55 examples/s]
Generating train split: 147752169 examples [2:27:13, 77093.62 examples/s]
Generating train split: 147759966 examples [2:27:13, 75899.24 examples/s]
Generating train split: 147767620 examples [2:27:13, 73433.64 examples/s]
Generating train split: 147775017 examples [2:27:14, 73375.72 examples/s]
Generating train split: 147782404 examples [2:27:14, 71648.82 examples/s]
Generating train split: 147789611 examples [2:27:14, 71076.20 examples/s]
Generating train split: 147796737 examples [2:27:14, 70504.87 examples/s]
Generating train split: 147805041 examples [2:27:14, 74109.75 examples/s]
Generating train split: 147813624 examples [2:27:14, 77512.23 examples/s]
Generating train split: 147821409 examples [2:27:14, 74797.73 examples/s]
Generating train split: 147829414 examples [2:27:14, 75511.54 examples/s]
Generating train split: 147836994 examples [2:27:14, 71339.74 examples/s]
Generating train split: 147844183 examples [2:27:15, 68928.03 examples/s]
Generating train split: 147851245 examples [2:27:15, 69398.63 examples/s]
Generating train split: 147858224 examples [2:27:15, 62356.66 examples/s]
Generating train split: 147864657 examples [2:27:15, 62875.57 examples/s]
Generating train split: 147872571 examples [2:27:15, 67370.13 examples/s]
Generating train split: 147880981 examples [2:27:15, 72099.23 examples/s]
Generating train split: 147888453 examples [2:27:15, 72851.28 examples/s]
Generating train split: 147896186 examples [2:27:15, 74145.90 examples/s]
Generating train split: 147904500 examples [2:27:15, 76746.04 examples/s]
Generating train split: 147912232 examples [2:27:16, 74341.42 examples/s]
Generating train split: 147919725 examples [2:27:16, 73901.63 examples/s]
Generating train split: 147927639 examples [2:27:16, 75420.93 examples/s]
Generating train split: 147935785 examples [2:27:16, 77167.07 examples/s]
Generating train split: 147943528 examples [2:27:16, 75608.34 examples/s]
Generating train split: 147952178 examples [2:27:16, 78775.80 examples/s]
Generating train split: 147961008 examples [2:27:16, 81579.79 examples/s]
Generating train split: 147969195 examples [2:27:16, 74867.10 examples/s]
Generating train split: 147977300 examples [2:27:16, 76594.33 examples/s]
Generating train split: 147985058 examples [2:27:16, 76269.88 examples/s]
Generating train split: 147992752 examples [2:27:17, 76428.81 examples/s]
Generating train split: 148000904 examples [2:27:17, 77899.46 examples/s]
Generating train split: 148009944 examples [2:27:17, 81543.67 examples/s]
Generating train split: 148018139 examples [2:27:17, 80374.74 examples/s]
Generating train split: 148026210 examples [2:27:17, 77426.71 examples/s]
Generating train split: 148034024 examples [2:27:17, 77618.68 examples/s]
Generating train split: 148042482 examples [2:27:17, 79622.52 examples/s]
Generating train split: 148050720 examples [2:27:17, 80427.15 examples/s]
Generating train split: 148058995 examples [2:27:17, 81097.98 examples/s]
Generating train split: 148067136 examples [2:27:17, 80492.05 examples/s]
Generating train split: 148075420 examples [2:27:18, 81178.89 examples/s]
Generating train split: 148084543 examples [2:27:18, 84142.49 examples/s]
Generating train split: 148093102 examples [2:27:18, 84555.22 examples/s]
Generating train split: 148101566 examples [2:27:18, 81464.31 examples/s]
Generating train split: 148109749 examples [2:27:18, 78432.37 examples/s]
Generating train split: 148117642 examples [2:27:18, 74653.87 examples/s]
Generating train split: 148126218 examples [2:27:18, 77747.15 examples/s]
Generating train split: 148134762 examples [2:27:18, 79940.29 examples/s]
Generating train split: 148143152 examples [2:27:18, 81049.58 examples/s]
Generating train split: 148151672 examples [2:27:19, 82254.56 examples/s]
Generating train split: 148161051 examples [2:27:19, 85635.03 examples/s]
Generating train split: 148169646 examples [2:27:19, 85258.94 examples/s]
Generating train split: 148178870 examples [2:27:19, 87297.67 examples/s]
Generating train split: 148187630 examples [2:27:19, 85472.77 examples/s]
Generating train split: 148196205 examples [2:27:19, 83078.02 examples/s]
Generating train split: 148204546 examples [2:27:19, 82986.17 examples/s]
Generating train split: 148213650 examples [2:27:19, 85309.36 examples/s]
Generating train split: 148222555 examples [2:27:19, 86389.03 examples/s]
Generating train split: 148231214 examples [2:27:19, 82411.76 examples/s]
Generating train split: 148240572 examples [2:27:20, 85586.26 examples/s]
Generating train split: 148249190 examples [2:27:20, 85656.40 examples/s]
Generating train split: 148257887 examples [2:27:20, 86010.01 examples/s]
Generating train split: 148266517 examples [2:27:20, 85827.61 examples/s]
Generating train split: 148275893 examples [2:27:20, 88153.29 examples/s]
Generating train split: 148284725 examples [2:27:20, 87421.68 examples/s]
Generating train split: 148293478 examples [2:27:20, 86372.61 examples/s]
Generating train split: 148302128 examples [2:27:20, 85728.30 examples/s]
Generating train split: 148311014 examples [2:27:20, 86643.22 examples/s]
Generating train split: 148320262 examples [2:27:20, 88352.81 examples/s]
Generating train split: 148329110 examples [2:27:21, 87354.77 examples/s]
Generating train split: 148337949 examples [2:27:21, 87650.58 examples/s]
Generating train split: 148347519 examples [2:27:21, 90039.85 examples/s]
Generating train split: 148356543 examples [2:27:21, 87712.30 examples/s]
Generating train split: 148365341 examples [2:27:21, 86144.22 examples/s]
Generating train split: 148373975 examples [2:27:21, 84817.30 examples/s]
Generating train split: 148382473 examples [2:27:21, 84040.75 examples/s]
Generating train split: 148390931 examples [2:27:21, 84162.20 examples/s]
Generating train split: 148399362 examples [2:27:21, 83841.38 examples/s]
Generating train split: 148407870 examples [2:27:22, 84180.27 examples/s]
Generating train split: 148417362 examples [2:27:22, 87339.33 examples/s]
Generating train split: 148426107 examples [2:27:22, 86582.65 examples/s]
Generating train split: 148434772 examples [2:27:22, 85841.24 examples/s]
Generating train split: 148443362 examples [2:27:22, 85082.08 examples/s]
Generating train split: 148451875 examples [2:27:22, 84450.29 examples/s]
Generating train split: 148460336 examples [2:27:22, 83039.65 examples/s]
Generating train split: 148468952 examples [2:27:22, 83952.29 examples/s]
Generating train split: 148477799 examples [2:27:22, 85261.87 examples/s]
Generating train split: 148486807 examples [2:27:22, 86688.70 examples/s]
Generating train split: 148495650 examples [2:27:23, 87174.19 examples/s]
Generating train split: 148504376 examples [2:27:23, 86940.50 examples/s]
Generating train split: 148513085 examples [2:27:23, 85996.13 examples/s]
Generating train split: 148521983 examples [2:27:23, 86869.63 examples/s]
Generating train split: 148530926 examples [2:27:23, 87625.17 examples/s]
Generating train split: 148539941 examples [2:27:23, 88360.56 examples/s]
Generating train split: 148548890 examples [2:27:23, 88672.25 examples/s]
Generating train split: 148558550 examples [2:27:23, 91035.55 examples/s]
Generating train split: 148567722 examples [2:27:23, 91212.30 examples/s]
Generating train split: 148576846 examples [2:27:23, 90959.00 examples/s]
Generating train split: 148586134 examples [2:27:24, 91493.68 examples/s]
Generating train split: 148595291 examples [2:27:24, 80494.96 examples/s]
Generating train split: 148604101 examples [2:27:24, 82563.47 examples/s]
Generating train split: 148612547 examples [2:27:24, 78842.17 examples/s]
Generating train split: 148620701 examples [2:27:24, 79571.25 examples/s]
Generating train split: 148629007 examples [2:27:24, 80528.13 examples/s]
Generating train split: 148637594 examples [2:27:24, 82033.44 examples/s]
Generating train split: 148646699 examples [2:27:24, 84635.75 examples/s]
Generating train split: 148655927 examples [2:27:24, 86850.26 examples/s]
Generating train split: 148665597 examples [2:27:24, 89750.71 examples/s]
Generating train split: 148674611 examples [2:27:25, 85962.40 examples/s]
Generating train split: 148683283 examples [2:27:25, 85603.28 examples/s]
Generating train split: 148691894 examples [2:27:25, 82716.64 examples/s]
Generating train split: 148700210 examples [2:27:25, 78368.70 examples/s]
Generating train split: 148708120 examples [2:27:25, 75381.91 examples/s]
Generating train split: 148716145 examples [2:27:25, 76701.32 examples/s]
Generating train split: 148725127 examples [2:27:25, 80413.34 examples/s]
Generating train split: 148733231 examples [2:27:25, 80543.35 examples/s]
Generating train split: 148741340 examples [2:27:25, 77573.26 examples/s]
Generating train split: 148751473 examples [2:27:26, 84353.62 examples/s]
Generating train split: 148762056 examples [2:27:26, 90561.71 examples/s]
Generating train split: 148771470 examples [2:27:26, 91585.39 examples/s]
Generating train split: 148780686 examples [2:27:26, 88778.24 examples/s]
Generating train split: 148789629 examples [2:27:26, 83036.33 examples/s]
Generating train split: 148798032 examples [2:27:26, 81837.79 examples/s]
Generating train split: 148807690 examples [2:27:26, 85937.81 examples/s]
Generating train split: 148816373 examples [2:27:26, 85760.45 examples/s]
Generating train split: 148825132 examples [2:27:26, 86239.17 examples/s]
Generating train split: 148834363 examples [2:27:27, 87997.04 examples/s]
Generating train split: 148843593 examples [2:27:27, 89187.86 examples/s]
Generating train split: 148852956 examples [2:27:27, 90476.63 examples/s]
Generating train split: 148862034 examples [2:27:27, 89617.43 examples/s]
Generating train split: 148871011 examples [2:27:27, 89639.00 examples/s]
Generating train split: 148880576 examples [2:27:27, 91392.28 examples/s]
Generating train split: 148889727 examples [2:27:27, 91214.55 examples/s]
Generating train split: 148899255 examples [2:27:27, 92418.14 examples/s]
Generating train split: 148909120 examples [2:27:27, 94247.54 examples/s]
Generating train split: 148918835 examples [2:27:27, 95100.94 examples/s]
Generating train split: 148928349 examples [2:27:28, 91787.88 examples/s]
Generating train split: 148937567 examples [2:27:28, 85858.24 examples/s]
Generating train split: 148946239 examples [2:27:28, 82953.98 examples/s]
Generating train split: 148954619 examples [2:27:28, 82319.43 examples/s]
Generating train split: 148964684 examples [2:27:28, 87489.36 examples/s]
Generating train split: 148973496 examples [2:27:28, 85333.06 examples/s]
Generating train split: 148982092 examples [2:27:28, 83157.42 examples/s]
Generating train split: 148990631 examples [2:27:28, 83771.20 examples/s]
Generating train split: 148999231 examples [2:27:28, 84339.08 examples/s]
Generating train split: 149007706 examples [2:27:28, 83870.35 examples/s]
Generating train split: 149016113 examples [2:27:29, 82736.88 examples/s]
Generating train split: 149024402 examples [2:27:29, 81641.58 examples/s]
Generating train split: 149032591 examples [2:27:29, 80245.17 examples/s]
Generating train split: 149041184 examples [2:27:29, 81844.13 examples/s]
Generating train split: 149049799 examples [2:27:29, 83086.29 examples/s]
Generating train split: 149059875 examples [2:27:29, 88274.67 examples/s]
Generating train split: 149068730 examples [2:27:29, 87136.21 examples/s]
Generating train split: 149077459 examples [2:27:29, 87162.31 examples/s]
Generating train split: 149086506 examples [2:27:29, 88141.18 examples/s]
Generating train split: 149096238 examples [2:27:30, 90846.54 examples/s]
Generating train split: 149106388 examples [2:27:30, 93994.07 examples/s]
Generating train split: 149115799 examples [2:27:30, 92231.00 examples/s]
Generating train split: 149125042 examples [2:27:30, 89585.18 examples/s]
Generating train split: 149134031 examples [2:27:30, 88161.98 examples/s]
Generating train split: 149142873 examples [2:27:30, 87309.19 examples/s]
Generating train split: 149151633 examples [2:27:30, 84019.35 examples/s]
Generating train split: 149160068 examples [2:27:30, 83333.18 examples/s]
Generating train split: 149168839 examples [2:27:30, 84572.82 examples/s]
Generating train split: 149177320 examples [2:27:30, 80738.16 examples/s]
Generating train split: 149185694 examples [2:27:31, 81587.67 examples/s]
Generating train split: 149195188 examples [2:27:31, 85424.92 examples/s]
Generating train split: 149203773 examples [2:27:31, 82485.56 examples/s]
Generating train split: 149212117 examples [2:27:31, 82714.05 examples/s]
Generating train split: 149221680 examples [2:27:31, 86453.98 examples/s]
Generating train split: 149230941 examples [2:27:31, 88254.58 examples/s]
Generating train split: 149240514 examples [2:27:31, 90433.96 examples/s]
Generating train split: 149249588 examples [2:27:31, 89179.23 examples/s]
Generating train split: 149259317 examples [2:27:31, 91558.35 examples/s]
Generating train split: 149269348 examples [2:27:31, 94098.89 examples/s]
Generating train split: 149279488 examples [2:27:32, 96197.79 examples/s]
Generating train split: 149289131 examples [2:27:32, 95193.06 examples/s]
Generating train split: 149298673 examples [2:27:32, 94165.66 examples/s]
Generating train split: 149309311 examples [2:27:32, 97743.26 examples/s]
Generating train split: 149319262 examples [2:27:32, 98215.99 examples/s]
Generating train split: 149329105 examples [2:27:32, 96638.68 examples/s]
Generating train split: 149338848 examples [2:27:32, 96868.57 examples/s]
Generating train split: 149348978 examples [2:27:32, 98171.49 examples/s]
Generating train split: 149358806 examples [2:27:32, 94415.58 examples/s]
Generating train split: 149368292 examples [2:27:33, 92917.90 examples/s]
Generating train split: 149377610 examples [2:27:33, 91872.47 examples/s]
Generating train split: 149386912 examples [2:27:33, 92184.17 examples/s]
Generating train split: 149396162 examples [2:27:33, 90187.03 examples/s]
Generating train split: 149405399 examples [2:27:33, 90819.63 examples/s]
Generating train split: 149414495 examples [2:27:33, 90657.51 examples/s]
Generating train split: 149423576 examples [2:27:33, 89847.22 examples/s]
Generating train split: 149432647 examples [2:27:33, 90077.49 examples/s]
Generating train split: 149441675 examples [2:27:33, 89135.99 examples/s]
Generating train split: 149450599 examples [2:27:33, 88934.34 examples/s]
Generating train split: 149459509 examples [2:27:34, 87441.58 examples/s]
Generating train split: 149468271 examples [2:27:34, 82702.09 examples/s]
Generating train split: 149476601 examples [2:27:34, 78604.33 examples/s]
Generating train split: 149484530 examples [2:27:34, 74985.83 examples/s]
Generating train split: 149492097 examples [2:27:34, 74441.31 examples/s]
Generating train split: 149501357 examples [2:27:34, 79501.49 examples/s]
Generating train split: 149511255 examples [2:27:34, 85035.82 examples/s]
Generating train split: 149521186 examples [2:27:34, 89144.98 examples/s]
Generating train split: 149530303 examples [2:27:34, 89713.79 examples/s]
Generating train split: 149539324 examples [2:27:35, 89481.85 examples/s]
Generating train split: 149548318 examples [2:27:35, 87633.15 examples/s]
Generating train split: 149557119 examples [2:27:35, 86998.37 examples/s]
Generating train split: 149565944 examples [2:27:35, 87344.50 examples/s]
Generating train split: 149574699 examples [2:27:35, 86925.25 examples/s]
Generating train split: 149583854 examples [2:27:35, 88290.12 examples/s]
Generating train split: 149592703 examples [2:27:35, 86617.76 examples/s]
Generating train split: 149601380 examples [2:27:35, 84503.09 examples/s]
Generating train split: 149609850 examples [2:27:35, 84420.78 examples/s]
Generating train split: 149619574 examples [2:27:35, 88160.30 examples/s]
Generating train split: 149628418 examples [2:27:36, 87095.46 examples/s]
Generating train split: 149637155 examples [2:27:36, 86586.88 examples/s]
Generating train split: 149645888 examples [2:27:36, 86788.30 examples/s]
Generating train split: 149654902 examples [2:27:36, 87774.73 examples/s]
Generating train split: 149664320 examples [2:27:36, 89655.63 examples/s]
Generating train split: 149673669 examples [2:27:36, 90776.81 examples/s]
Generating train split: 149682758 examples [2:27:36, 90663.20 examples/s]
Generating train split: 149691835 examples [2:27:36, 89762.69 examples/s]
Generating train split: 149700827 examples [2:27:36, 89279.72 examples/s]
Generating train split: 149709772 examples [2:27:36, 88923.97 examples/s]
Generating train split: 149718701 examples [2:27:37, 89020.98 examples/s]
Generating train split: 149727612 examples [2:27:37, 89038.85 examples/s]
Generating train split: 149737088 examples [2:27:37, 90714.63 examples/s]
Generating train split: 149746754 examples [2:27:37, 92487.25 examples/s]
Generating train split: 149756019 examples [2:27:37, 92308.79 examples/s]
Generating train split: 149765778 examples [2:27:37, 93864.21 examples/s]
Generating train split: 149775375 examples [2:27:37, 94481.04 examples/s]
Generating train split: 149785505 examples [2:27:37, 96512.77 examples/s]
Generating train split: 149795344 examples [2:27:37, 97064.85 examples/s]
Generating train split: 149805066 examples [2:27:37, 94757.90 examples/s]
Generating train split: 149814560 examples [2:27:38, 92885.69 examples/s]
Generating train split: 149823876 examples [2:27:38, 91393.72 examples/s]
Generating train split: 149833037 examples [2:27:38, 90688.67 examples/s]
Generating train split: 149842352 examples [2:27:38, 91389.57 examples/s]
Generating train split: 149851966 examples [2:27:38, 92776.16 examples/s]
Generating train split: 149861442 examples [2:27:38, 93350.46 examples/s]
Generating train split: 149871149 examples [2:27:38, 94422.09 examples/s]
Generating train split: 149880597 examples [2:27:38, 92355.24 examples/s]
Generating train split: 149889849 examples [2:27:38, 92134.96 examples/s]
Generating train split: 149899347 examples [2:27:38, 92952.80 examples/s]
Generating train split: 149908665 examples [2:27:39, 91645.94 examples/s]
Generating train split: 149917842 examples [2:27:39, 83272.86 examples/s]
Generating train split: 149926314 examples [2:27:39, 45233.10 examples/s]
Generating train split: 149932870 examples [2:27:39, 43534.56 examples/s]
Generating train split: 149938747 examples [2:27:39, 46281.30 examples/s]
Generating train split: 149945820 examples [2:27:40, 51342.33 examples/s]
Generating train split: 149953381 examples [2:27:40, 56879.13 examples/s]
Generating train split: 149961676 examples [2:27:40, 63280.92 examples/s]
Generating train split: 149968776 examples [2:27:40, 65271.48 examples/s]
Generating train split: 149977369 examples [2:27:40, 70854.28 examples/s]
Generating train split: 149986895 examples [2:27:40, 77643.84 examples/s]
Generating train split: 149997180 examples [2:27:40, 84799.84 examples/s]
Generating train split: 150007378 examples [2:27:40, 89765.17 examples/s]
Generating train split: 150018286 examples [2:27:40, 95377.17 examples/s]
Generating train split: 150028301 examples [2:27:40, 96774.26 examples/s]
Generating train split: 150038105 examples [2:27:41, 97143.00 examples/s]
Generating train split: 150048500 examples [2:27:41, 99145.99 examples/s]
Generating train split: 150058830 examples [2:27:41, 100358.46 examples/s]
Generating train split: 150068912 examples [2:27:41, 100235.57 examples/s]
Generating train split: 150078995 examples [2:27:41, 97230.25 examples/s] 
Generating train split: 150088767 examples [2:27:41, 94729.19 examples/s]
Generating train split: 150098282 examples [2:27:41, 92491.03 examples/s]
Generating train split: 150108015 examples [2:27:41, 93840.91 examples/s]
Generating train split: 150117924 examples [2:27:41, 95348.81 examples/s]
Generating train split: 150128057 examples [2:27:41, 97081.34 examples/s]
Generating train split: 150138388 examples [2:27:42, 98916.04 examples/s]
Generating train split: 150148314 examples [2:27:42, 97612.12 examples/s]
Generating train split: 150158098 examples [2:27:42, 94267.78 examples/s]
Generating train split: 150167568 examples [2:27:42, 93263.70 examples/s]
Generating train split: 150177803 examples [2:27:42, 95870.79 examples/s]
Generating train split: 150187601 examples [2:27:42, 96477.80 examples/s]
Generating train split: 150197273 examples [2:27:42, 94876.62 examples/s]
Generating train split: 150206789 examples [2:27:42, 93382.05 examples/s]
Generating train split: 150216142 examples [2:27:42, 92279.92 examples/s]
Generating train split: 150226257 examples [2:27:42, 94858.53 examples/s]
Generating train split: 150236570 examples [2:27:43, 97288.47 examples/s]
Generating train split: 150246323 examples [2:27:43, 96574.10 examples/s]
Generating train split: 150256348 examples [2:27:43, 97659.42 examples/s]
Generating train split: 150266131 examples [2:27:43, 96844.53 examples/s]
Generating train split: 150275830 examples [2:27:43, 96280.66 examples/s]
Generating train split: 150285468 examples [2:27:43, 95039.75 examples/s]
Generating train split: 150295037 examples [2:27:43, 95207.07 examples/s]
Generating train split: 150304567 examples [2:27:43, 91429.68 examples/s]
Generating train split: 150314355 examples [2:27:43, 93272.02 examples/s]
Generating train split: 150323716 examples [2:27:44, 91467.86 examples/s]
Generating train split: 150332896 examples [2:27:44, 89149.09 examples/s]
Generating train split: 150341855 examples [2:27:44, 86493.89 examples/s]
Generating train split: 150351145 examples [2:27:44, 88300.81 examples/s]
Generating train split: 150360338 examples [2:27:44, 89322.93 examples/s]
Generating train split: 150369568 examples [2:27:44, 90148.88 examples/s]
Generating train split: 150378601 examples [2:27:44, 90155.97 examples/s]
Generating train split: 150388303 examples [2:27:44, 92183.79 examples/s]
Generating train split: 150398205 examples [2:27:44, 94183.26 examples/s]
Generating train split: 150408461 examples [2:27:44, 96663.15 examples/s]
Generating train split: 150418155 examples [2:27:45, 94639.25 examples/s]
Generating train split: 150427639 examples [2:27:45, 92644.63 examples/s]
Generating train split: 150436929 examples [2:27:45, 90566.71 examples/s]
Generating train split: 150447119 examples [2:27:45, 93835.87 examples/s]
Generating train split: 150457950 examples [2:27:45, 98033.73 examples/s]
Generating train split: 150468742 examples [2:27:45, 100943.57 examples/s]
Generating train split: 150478873 examples [2:27:45, 100438.73 examples/s]
Generating train split: 150489125 examples [2:27:45, 101048.55 examples/s]
Generating train split: 150499245 examples [2:27:45, 100975.04 examples/s]
Generating train split: 150510682 examples [2:27:45, 104951.82 examples/s]
Generating train split: 150521191 examples [2:27:46, 104947.09 examples/s]
Generating train split: 150531697 examples [2:27:46, 100198.87 examples/s]
Generating train split: 150541900 examples [2:27:46, 100716.59 examples/s]
Generating train split: 150552012 examples [2:27:46, 100100.60 examples/s]
Generating train split: 150562879 examples [2:27:46, 102597.95 examples/s]
Generating train split: 150573170 examples [2:27:46, 102647.40 examples/s]
Generating train split: 150583869 examples [2:27:46, 103932.63 examples/s]
Generating train split: 150594422 examples [2:27:46, 104400.48 examples/s]
Generating train split: 150605292 examples [2:27:46, 105666.55 examples/s]
Generating train split: 150616303 examples [2:27:46, 106980.97 examples/s]
Generating train split: 150627027 examples [2:27:47, 105220.89 examples/s]
Generating train split: 150637569 examples [2:27:47, 103624.37 examples/s]
Generating train split: 150648086 examples [2:27:47, 104073.20 examples/s]
Generating train split: 150658786 examples [2:27:47, 104934.58 examples/s]
Generating train split: 150669287 examples [2:27:47, 103930.52 examples/s]
Generating train split: 150679697 examples [2:27:47, 99942.19 examples/s] 
Generating train split: 150689732 examples [2:27:47, 99241.48 examples/s]
Generating train split: 150699688 examples [2:27:47, 98676.52 examples/s]
Generating train split: 150709665 examples [2:27:47, 98980.99 examples/s]
Generating train split: 150719575 examples [2:27:48, 98590.86 examples/s]
Generating train split: 150729449 examples [2:27:48, 95528.66 examples/s]
Generating train split: 150739028 examples [2:27:48, 94418.61 examples/s]
Generating train split: 150748494 examples [2:27:48, 93382.10 examples/s]
Generating train split: 150758218 examples [2:27:48, 94461.37 examples/s]
Generating train split: 150767686 examples [2:27:48, 94455.31 examples/s]
Generating train split: 150778101 examples [2:27:48, 97311.48 examples/s]
Generating train split: 150788045 examples [2:27:48, 97913.20 examples/s]
Generating train split: 150797894 examples [2:27:48, 98078.93 examples/s]
Generating train split: 150807723 examples [2:27:48, 91965.18 examples/s]
Generating train split: 150817649 examples [2:27:49, 94022.76 examples/s]
Generating train split: 150827125 examples [2:27:49, 92763.64 examples/s]
Generating train split: 150836787 examples [2:27:49, 93873.59 examples/s]
Generating train split: 150846804 examples [2:27:49, 95693.50 examples/s]
Generating train split: 150856413 examples [2:27:49, 93984.79 examples/s]
Generating train split: 150865869 examples [2:27:49, 94149.69 examples/s]
Generating train split: 150875883 examples [2:27:49, 95901.58 examples/s]
Generating train split: 150885845 examples [2:27:49, 96991.63 examples/s]
Generating train split: 150895558 examples [2:27:49, 96141.40 examples/s]
Generating train split: 150905194 examples [2:27:49, 95162.85 examples/s]
Generating train split: 150914898 examples [2:27:50, 95712.55 examples/s]
Generating train split: 150924574 examples [2:27:50, 95978.28 examples/s]
Generating train split: 150934835 examples [2:27:50, 97932.60 examples/s]
Generating train split: 150945035 examples [2:27:50, 99142.46 examples/s]
Generating train split: 150954958 examples [2:27:50, 97250.87 examples/s]
Generating train split: 150964754 examples [2:27:50, 97433.79 examples/s]
Generating train split: 150974846 examples [2:27:50, 98433.51 examples/s]
Generating train split: 150985258 examples [2:27:50, 100089.14 examples/s]
Generating train split: 150995274 examples [2:27:50, 98355.46 examples/s] 
Generating train split: 151005128 examples [2:27:51, 93614.48 examples/s]
Generating train split: 151014542 examples [2:27:51, 90835.40 examples/s]
Generating train split: 151024209 examples [2:27:51, 92488.22 examples/s]
Generating train split: 151033993 examples [2:27:51, 94009.77 examples/s]
Generating train split: 151044081 examples [2:27:51, 96005.00 examples/s]
Generating train split: 151053717 examples [2:27:51, 95261.68 examples/s]
Generating train split: 151063266 examples [2:27:51, 93449.22 examples/s]
Generating train split: 151072630 examples [2:27:51, 92082.78 examples/s]
Generating train split: 151081861 examples [2:27:51, 91797.80 examples/s]
Generating train split: 151091764 examples [2:27:51, 93886.40 examples/s]
Generating train split: 151101174 examples [2:27:52, 92344.46 examples/s]
Generating train split: 151110829 examples [2:27:52, 93544.17 examples/s]
Generating train split: 151120202 examples [2:27:52, 93302.71 examples/s]
Generating train split: 151129830 examples [2:27:52, 94152.25 examples/s]
Generating train split: 151139259 examples [2:27:52, 93995.42 examples/s]
Generating train split: 151148908 examples [2:27:52, 94717.26 examples/s]
Generating train split: 151158873 examples [2:27:52, 96177.02 examples/s]
Generating train split: 151168800 examples [2:27:52, 97075.72 examples/s]
Generating train split: 151178600 examples [2:27:52, 97335.88 examples/s]
Generating train split: 151188352 examples [2:27:52, 92227.96 examples/s]
Generating train split: 151197651 examples [2:27:53, 91050.93 examples/s]
Generating train split: 151206797 examples [2:27:53, 87940.75 examples/s]
Generating train split: 151215640 examples [2:27:53, 87188.24 examples/s]
Generating train split: 151224388 examples [2:27:53, 85834.84 examples/s]
Generating train split: 151234403 examples [2:27:53, 89936.61 examples/s]
Generating train split: 151244702 examples [2:27:53, 93732.84 examples/s]
Generating train split: 151254369 examples [2:27:53, 94561.40 examples/s]
Generating train split: 151264208 examples [2:27:53, 95655.01 examples/s]
Generating train split: 151274103 examples [2:27:53, 96612.15 examples/s]
Generating train split: 151283892 examples [2:27:53, 96959.56 examples/s]
Generating train split: 151293881 examples [2:27:54, 97829.47 examples/s]
Generating train split: 151303676 examples [2:27:54, 95447.14 examples/s]
Generating train split: 151313247 examples [2:27:54, 92392.78 examples/s]
Generating train split: 151323237 examples [2:27:54, 94557.38 examples/s]
Generating train split: 151333641 examples [2:27:54, 97302.04 examples/s]
Generating train split: 151343409 examples [2:27:54, 95827.84 examples/s]
Generating train split: 151353014 examples [2:27:54, 95150.32 examples/s]
Generating train split: 151362590 examples [2:27:54, 95318.10 examples/s]
Generating train split: 151372150 examples [2:27:54, 92599.38 examples/s]
Generating train split: 151381615 examples [2:27:55, 93185.60 examples/s]
Generating train split: 151390964 examples [2:27:55, 93224.17 examples/s]
Generating train split: 151401177 examples [2:27:55, 95842.55 examples/s]
Generating train split: 151410780 examples [2:27:55, 94429.75 examples/s]
Generating train split: 151420674 examples [2:27:55, 95741.98 examples/s]
Generating train split: 151430261 examples [2:27:55, 95296.84 examples/s]
Generating train split: 151440245 examples [2:27:55, 96602.45 examples/s]
Generating train split: 151450688 examples [2:27:55, 98903.89 examples/s]
Generating train split: 151460602 examples [2:27:55, 98598.75 examples/s]
Generating train split: 151470467 examples [2:27:55, 98305.89 examples/s]
Generating train split: 151480303 examples [2:27:56, 96433.65 examples/s]
Generating train split: 151489965 examples [2:27:56, 93874.08 examples/s]
Generating train split: 151499513 examples [2:27:56, 94317.49 examples/s]
Generating train split: 151509409 examples [2:27:56, 95651.16 examples/s]
Generating train split: 151519532 examples [2:27:56, 97265.38 examples/s]
Generating train split: 151529313 examples [2:27:56, 97415.04 examples/s]
Generating train split: 151539077 examples [2:27:56, 96947.75 examples/s]
Generating train split: 151549903 examples [2:27:56, 100297.74 examples/s]
Generating train split: 151560126 examples [2:27:56, 100850.19 examples/s]
Generating train split: 151570769 examples [2:27:56, 102485.64 examples/s]
Generating train split: 151581059 examples [2:27:57, 102588.76 examples/s]
Generating train split: 151591420 examples [2:27:57, 102891.90 examples/s]
Generating train split: 151602026 examples [2:27:57, 103810.74 examples/s]
Generating train split: 151612990 examples [2:27:57, 105521.42 examples/s]
Generating train split: 151623876 examples [2:27:57, 106479.26 examples/s]
Generating train split: 151634748 examples [2:27:57, 107138.69 examples/s]
Generating train split: 151645472 examples [2:27:57, 102612.21 examples/s]
Generating train split: 151655783 examples [2:27:57, 101815.34 examples/s]
Generating train split: 151666274 examples [2:27:57, 102678.71 examples/s]
Generating train split: 151676571 examples [2:27:57, 99845.38 examples/s] 
Generating train split: 151686585 examples [2:27:58, 96724.27 examples/s]
Generating train split: 151696588 examples [2:27:58, 97642.06 examples/s]
Generating train split: 151706522 examples [2:27:58, 98128.13 examples/s]
Generating train split: 151716363 examples [2:27:58, 96978.43 examples/s]
Generating train split: 151726207 examples [2:27:58, 97396.40 examples/s]
Generating train split: 151735970 examples [2:27:58, 96659.64 examples/s]
Generating train split: 151745653 examples [2:27:58, 94647.36 examples/s]
Generating train split: 151755137 examples [2:27:58, 93444.07 examples/s]
Generating train split: 151764492 examples [2:27:58, 92703.42 examples/s]
Generating train split: 151774060 examples [2:27:59, 93550.49 examples/s]
Generating train split: 151784103 examples [2:27:59, 95542.65 examples/s]
Generating train split: 151794664 examples [2:27:59, 98499.19 examples/s]
Generating train split: 151804524 examples [2:27:59, 98114.91 examples/s]
Generating train split: 151815106 examples [2:27:59, 100382.02 examples/s]
Generating train split: 151825345 examples [2:27:59, 100967.80 examples/s]
Generating train split: 151835702 examples [2:27:59, 101721.18 examples/s]
Generating train split: 151845887 examples [2:27:59, 100951.06 examples/s]
Generating train split: 151855995 examples [2:27:59, 100936.61 examples/s]
Generating train split: 151866284 examples [2:27:59, 101506.05 examples/s]
Generating train split: 151876449 examples [2:28:00, 99424.48 examples/s] 
Generating train split: 151886415 examples [2:28:00, 98083.47 examples/s]
Generating train split: 151897036 examples [2:28:00, 100435.42 examples/s]
Generating train split: 151907208 examples [2:28:00, 100777.71 examples/s]
Generating train split: 151917299 examples [2:28:00, 99174.56 examples/s] 
Generating train split: 151927231 examples [2:28:00, 95433.59 examples/s]
Generating train split: 151937556 examples [2:28:00, 97673.03 examples/s]
Generating train split: 151947538 examples [2:28:00, 98271.72 examples/s]
Generating train split: 151957391 examples [2:28:00, 98048.90 examples/s]
Generating train split: 151967457 examples [2:28:00, 98794.55 examples/s]
Generating train split: 151977356 examples [2:28:01, 97563.01 examples/s]
Generating train split: 151987134 examples [2:28:01, 97547.13 examples/s]
Generating train split: 151997087 examples [2:28:01, 98098.92 examples/s]
Generating train split: 152007627 examples [2:28:01, 100264.07 examples/s]
Generating train split: 152017664 examples [2:28:01, 94896.00 examples/s] 
Generating train split: 152027221 examples [2:28:01, 94753.40 examples/s]
Generating train split: 152037066 examples [2:28:01, 95823.28 examples/s]
Generating train split: 152047350 examples [2:28:01, 97851.13 examples/s]
Generating train split: 152057937 examples [2:28:01, 100186.29 examples/s]
Generating train split: 152068130 examples [2:28:01, 100688.93 examples/s]
Generating train split: 152078223 examples [2:28:02, 100348.17 examples/s]
Generating train split: 152088570 examples [2:28:02, 101262.53 examples/s]
Generating train split: 152099205 examples [2:28:02, 102745.15 examples/s]
Generating train split: 152109803 examples [2:28:02, 103689.53 examples/s]
Generating train split: 152121077 examples [2:28:02, 106382.93 examples/s]
Generating train split: 152131997 examples [2:28:02, 107200.54 examples/s]
Generating train split: 152142794 examples [2:28:02, 107427.06 examples/s]
Generating train split: 152153546 examples [2:28:02, 106289.16 examples/s]
Generating train split: 152164634 examples [2:28:02, 107630.23 examples/s]
Generating train split: 152175439 examples [2:28:02, 107741.17 examples/s]
Generating train split: 152186222 examples [2:28:03, 106605.20 examples/s]
Generating train split: 152196897 examples [2:28:03, 105500.08 examples/s]
Generating train split: 152207458 examples [2:28:03, 104791.07 examples/s]
Generating train split: 152217946 examples [2:28:03, 103543.53 examples/s]
Generating train split: 152228905 examples [2:28:03, 105283.26 examples/s]
Generating train split: 152239706 examples [2:28:03, 106060.78 examples/s]
Generating train split: 152250321 examples [2:28:03, 104428.83 examples/s]
Generating train split: 152261187 examples [2:28:03, 105639.23 examples/s]
Generating train split: 152271852 examples [2:28:03, 105901.06 examples/s]
Generating train split: 152282721 examples [2:28:04, 106706.18 examples/s]
Generating train split: 152294079 examples [2:28:04, 108751.97 examples/s]
Generating train split: 152304967 examples [2:28:04, 108616.72 examples/s]
Generating train split: 152316005 examples [2:28:04, 109106.73 examples/s]
Generating train split: 152326919 examples [2:28:04, 104504.12 examples/s]
Generating train split: 152337732 examples [2:28:04, 105525.71 examples/s]
Generating train split: 152348333 examples [2:28:04, 104395.19 examples/s]
Generating train split: 152358807 examples [2:28:04, 103931.99 examples/s]
Generating train split: 152369226 examples [2:28:04, 102985.60 examples/s]
Generating train split: 152379548 examples [2:28:04, 102553.25 examples/s]
Generating train split: 152390441 examples [2:28:05, 104414.17 examples/s]
Generating train split: 152401433 examples [2:28:05, 106006.28 examples/s]
Generating train split: 152412046 examples [2:28:05, 103700.48 examples/s]
Generating train split: 152422439 examples [2:28:05, 102740.55 examples/s]
Generating train split: 152432724 examples [2:28:05, 102301.06 examples/s]
Generating train split: 152443342 examples [2:28:05, 103413.77 examples/s]
Generating train split: 152454747 examples [2:28:05, 106557.89 examples/s]
Generating train split: 152465754 examples [2:28:05, 107570.73 examples/s]
Generating train split: 152477723 examples [2:28:05, 111170.51 examples/s]
Generating train split: 152488856 examples [2:28:05, 110894.16 examples/s]
Generating train split: 152501258 examples [2:28:06, 114780.26 examples/s]
Generating train split: 152514053 examples [2:28:06, 118714.77 examples/s]
Generating train split: 152526472 examples [2:28:06, 120318.65 examples/s]
Generating train split: 152538925 examples [2:28:06, 121540.91 examples/s]
Generating train split: 152551092 examples [2:28:06, 119262.31 examples/s]
Generating train split: 152563031 examples [2:28:06, 116136.44 examples/s]
Generating train split: 152574673 examples [2:28:06, 113708.58 examples/s]
Generating train split: 152586073 examples [2:28:06, 112512.69 examples/s]
Generating train split: 152597349 examples [2:28:06, 110027.12 examples/s]
Generating train split: 152608377 examples [2:28:06, 109219.02 examples/s]
Generating train split: 152619312 examples [2:28:07, 106544.17 examples/s]
Generating train split: 152629993 examples [2:28:07, 103962.72 examples/s]
Generating train split: 152640408 examples [2:28:07, 102831.73 examples/s]
Generating train split: 152650903 examples [2:28:07, 103419.16 examples/s]
Generating train split: 152661614 examples [2:28:07, 104492.68 examples/s]
Generating train split: 152672086 examples [2:28:07, 104484.40 examples/s]
Generating train split: 152682811 examples [2:28:07, 105276.76 examples/s]
Generating train split: 152693351 examples [2:28:07, 104429.46 examples/s]
Generating train split: 152703991 examples [2:28:07, 104983.13 examples/s]
Generating train split: 152714500 examples [2:28:08, 104536.74 examples/s]
Generating train split: 152724974 examples [2:28:08, 102965.17 examples/s]
Generating train split: 152735718 examples [2:28:08, 104248.43 examples/s]
Generating train split: 152746505 examples [2:28:08, 105299.30 examples/s]
Generating train split: 152757044 examples [2:28:08, 103902.23 examples/s]
Generating train split: 152767735 examples [2:28:08, 104784.72 examples/s]
Generating train split: 152778230 examples [2:28:08, 103525.61 examples/s]
Generating train split: 152788594 examples [2:28:08, 103320.51 examples/s]
Generating train split: 152799702 examples [2:28:08, 105592.35 examples/s]
Generating train split: 152811290 examples [2:28:08, 108619.87 examples/s]
Generating train split: 152822173 examples [2:28:09, 107042.91 examples/s]
Generating train split: 152832895 examples [2:28:09, 105396.53 examples/s]
Generating train split: 152843460 examples [2:28:09, 102477.72 examples/s]
Generating train split: 152854603 examples [2:28:09, 105054.88 examples/s]
Generating train split: 152865135 examples [2:28:09, 104187.23 examples/s]
Generating train split: 152875573 examples [2:28:09, 103526.94 examples/s]
Generating train split: 152886500 examples [2:28:09, 105183.75 examples/s]
Generating train split: 152898714 examples [2:28:09, 110187.32 examples/s]
Generating train split: 152911546 examples [2:28:09, 115538.83 examples/s]
Generating train split: 152924017 examples [2:28:09, 118254.93 examples/s]
Generating train split: 152935881 examples [2:28:10, 118343.83 examples/s]
Generating train split: 152947872 examples [2:28:10, 118801.06 examples/s]
Generating train split: 152959776 examples [2:28:10, 117162.81 examples/s]
Generating train split: 152971518 examples [2:28:10, 116452.61 examples/s]
Generating train split: 152983178 examples [2:28:10, 114516.19 examples/s]
Generating train split: 152994641 examples [2:28:10, 111163.63 examples/s]
Generating train split: 153005956 examples [2:28:10, 111716.16 examples/s]
Generating train split: 153017218 examples [2:28:10, 111960.65 examples/s]
Generating train split: 153028462 examples [2:28:10, 112078.83 examples/s]
Generating train split: 153039694 examples [2:28:10, 110443.92 examples/s]
Generating train split: 153050759 examples [2:28:11, 109666.44 examples/s]
Generating train split: 153062083 examples [2:28:11, 110696.00 examples/s]
Generating train split: 153073161 examples [2:28:11, 109067.59 examples/s]
Generating train split: 153084082 examples [2:28:11, 107479.55 examples/s]
Generating train split: 153094840 examples [2:28:11, 105391.96 examples/s]
Generating train split: 153106013 examples [2:28:11, 107210.68 examples/s]
Generating train split: 153116752 examples [2:28:11, 107187.67 examples/s]
Generating train split: 153127623 examples [2:28:11, 107633.67 examples/s]
Generating train split: 153138398 examples [2:28:11, 104519.27 examples/s]
Generating train split: 153149084 examples [2:28:12, 105169.36 examples/s]
Generating train split: 153159711 examples [2:28:12, 105456.36 examples/s]
Generating train split: 153170279 examples [2:28:12, 102882.42 examples/s]
Generating train split: 153180889 examples [2:28:12, 103806.69 examples/s]
Generating train split: 153192041 examples [2:28:12, 106054.08 examples/s]
Generating train split: 153202867 examples [2:28:12, 106702.78 examples/s]
Generating train split: 153213560 examples [2:28:12, 106374.95 examples/s]
Generating train split: 153224210 examples [2:28:12, 106300.38 examples/s]
Generating train split: 153235013 examples [2:28:12, 106787.09 examples/s]
Generating train split: 153245811 examples [2:28:12, 107142.38 examples/s]
Generating train split: 153257073 examples [2:28:13, 108736.25 examples/s]
Generating train split: 153268053 examples [2:28:13, 109049.42 examples/s]
Generating train split: 153278961 examples [2:28:13, 107311.32 examples/s]
Generating train split: 153289701 examples [2:28:13, 106389.50 examples/s]
Generating train split: 153300361 examples [2:28:13, 106137.99 examples/s]
Generating train split: 153311412 examples [2:28:13, 107411.77 examples/s]
Generating train split: 153322166 examples [2:28:13, 107380.81 examples/s]
Generating train split: 153332921 examples [2:28:13, 105045.67 examples/s]
Generating train split: 153343731 examples [2:28:13, 105916.47 examples/s]
Generating train split: 153354339 examples [2:28:13, 105400.96 examples/s]
Generating train split: 153365074 examples [2:28:14, 105977.04 examples/s]
Generating train split: 153375686 examples [2:28:14, 105745.20 examples/s]
Generating train split: 153386268 examples [2:28:14, 104530.24 examples/s]
Generating train split: 153396734 examples [2:28:14, 103556.04 examples/s]
Generating train split: 153407163 examples [2:28:14, 103750.89 examples/s]
Generating train split: 153417644 examples [2:28:14, 104033.61 examples/s]
Generating train split: 153428101 examples [2:28:14, 104166.65 examples/s]
Generating train split: 153438533 examples [2:28:14, 104096.82 examples/s]
Generating train split: 153448965 examples [2:28:14, 101662.34 examples/s]
Generating train split: 153459144 examples [2:28:14, 101023.05 examples/s]
Generating train split: 153470120 examples [2:28:15, 103567.45 examples/s]
Generating train split: 153481338 examples [2:28:15, 106082.05 examples/s]
Generating train split: 153492386 examples [2:28:15, 107351.45 examples/s]
Generating train split: 153503806 examples [2:28:15, 109384.68 examples/s]
Generating train split: 153515523 examples [2:28:15, 111670.18 examples/s]
Generating train split: 153526705 examples [2:28:15, 111642.36 examples/s]
Generating train split: 153537878 examples [2:28:15, 107603.80 examples/s]
Generating train split: 153548680 examples [2:28:15, 103183.95 examples/s]
Generating train split: 153559243 examples [2:28:15, 103852.43 examples/s]
Generating train split: 153570091 examples [2:28:15, 105176.08 examples/s]
Generating train split: 153580642 examples [2:28:16, 105141.80 examples/s]
Generating train split: 153591797 examples [2:28:16, 106995.09 examples/s]
Generating train split: 153602887 examples [2:28:16, 108110.80 examples/s]
Generating train split: 153613896 examples [2:28:16, 108665.20 examples/s]
Generating train split: 153624792 examples [2:28:16, 105509.07 examples/s]
Generating train split: 153636391 examples [2:28:16, 108559.26 examples/s]
Generating train split: 153647289 examples [2:28:16, 107227.40 examples/s]
Generating train split: 153658752 examples [2:28:16, 109374.49 examples/s]
Generating train split: 153670508 examples [2:28:16, 111766.91 examples/s]
Generating train split: 153681707 examples [2:28:17, 111170.75 examples/s]
Generating train split: 153692837 examples [2:28:17, 110927.61 examples/s]
Generating train split: 153703953 examples [2:28:17, 110938.29 examples/s]
Generating train split: 153715060 examples [2:28:17, 110660.73 examples/s]
Generating train split: 153726964 examples [2:28:17, 113153.88 examples/s]
Generating train split: 153738286 examples [2:28:17, 106423.93 examples/s]
Generating train split: 153749016 examples [2:28:17, 103132.66 examples/s]
Generating train split: 153759408 examples [2:28:17, 101957.71 examples/s]
Generating train split: 153770165 examples [2:28:17, 103548.41 examples/s]
Generating train split: 153780950 examples [2:28:17, 104763.02 examples/s]
Generating train split: 153791459 examples [2:28:18, 103675.82 examples/s]
Generating train split: 153802401 examples [2:28:18, 105333.59 examples/s]
Generating train split: 153813386 examples [2:28:18, 106662.16 examples/s]
Generating train split: 153824621 examples [2:28:18, 108318.26 examples/s]
Generating train split: 153835467 examples [2:28:18, 107730.82 examples/s]
Generating train split: 153846921 examples [2:28:18, 109727.01 examples/s]
Generating train split: 153857915 examples [2:28:18, 109751.81 examples/s]
Generating train split: 153868898 examples [2:28:18, 73445.04 examples/s] 
Generating train split: 153877832 examples [2:28:19, 47556.84 examples/s]
Generating train split: 153887568 examples [2:28:19, 55712.74 examples/s]
Generating train split: 153897144 examples [2:28:19, 63291.63 examples/s]
Generating train split: 153907233 examples [2:28:19, 71303.19 examples/s]
Generating train split: 153917799 examples [2:28:19, 79314.65 examples/s]
Generating train split: 153928117 examples [2:28:19, 85279.16 examples/s]
Generating train split: 153939226 examples [2:28:19, 92058.53 examples/s]
Generating train split: 153949628 examples [2:28:20, 95297.21 examples/s]
Generating train split: 153960572 examples [2:28:20, 99263.40 examples/s]
Generating train split: 153970984 examples [2:28:20, 100001.43 examples/s]
Generating train split: 153982290 examples [2:28:20, 103761.57 examples/s]
Generating train split: 153992935 examples [2:28:20, 103908.78 examples/s]
Generating train split: 154004241 examples [2:28:20, 106559.24 examples/s]
Generating train split: 154016282 examples [2:28:20, 110645.74 examples/s]
Generating train split: 154027451 examples [2:28:20, 110196.33 examples/s]
Generating train split: 154038580 examples [2:28:20, 110518.15 examples/s]
Generating train split: 154049975 examples [2:28:20, 111500.58 examples/s]
Generating train split: 154061576 examples [2:28:21, 112814.88 examples/s]
Generating train split: 154073136 examples [2:28:21, 113610.78 examples/s]
Generating train split: 154084899 examples [2:28:21, 114776.59 examples/s]
Generating train split: 154096391 examples [2:28:21, 114189.74 examples/s]
Generating train split: 154107826 examples [2:28:21, 113751.57 examples/s]
Generating train split: 154119283 examples [2:28:21, 113956.07 examples/s]
Generating train split: 154130886 examples [2:28:21, 114536.20 examples/s]
Generating train split: 154142685 examples [2:28:21, 115548.21 examples/s]
Generating train split: 154154346 examples [2:28:21, 115858.28 examples/s]
Generating train split: 154166231 examples [2:28:21, 116712.61 examples/s]
Generating train split: 154177913 examples [2:28:22, 116177.78 examples/s]
Generating train split: 154189551 examples [2:28:22, 115744.74 examples/s]
Generating train split: 154201142 examples [2:28:22, 115435.87 examples/s]
Generating train split: 154213249 examples [2:28:22, 117073.74 examples/s]
Generating train split: 154224976 examples [2:28:22, 116060.45 examples/s]
Generating train split: 154236877 examples [2:28:22, 116893.48 examples/s]
Generating train split: 154249016 examples [2:28:22, 118180.33 examples/s]
Generating train split: 154260990 examples [2:28:22, 118640.12 examples/s]
Generating train split: 154272875 examples [2:28:22, 118214.31 examples/s]
Generating train split: 154284718 examples [2:28:22, 117247.62 examples/s]
Generating train split: 154296446 examples [2:28:23, 116504.62 examples/s]
Generating train split: 154308659 examples [2:28:23, 118163.29 examples/s]
Generating train split: 154320479 examples [2:28:23, 113906.71 examples/s]
Generating train split: 154331908 examples [2:28:23, 113109.48 examples/s]
Generating train split: 154343452 examples [2:28:23, 113789.01 examples/s]
Generating train split: 154354859 examples [2:28:23, 111228.49 examples/s]
Generating train split: 154366005 examples [2:28:23, 111132.81 examples/s]
Generating train split: 154378181 examples [2:28:23, 114229.21 examples/s]
Generating train split: 154389752 examples [2:28:23, 114634.05 examples/s]
Generating train split: 154401339 examples [2:28:23, 114967.19 examples/s]
Generating train split: 154412848 examples [2:28:24, 109031.01 examples/s]
Generating train split: 154423821 examples [2:28:24, 105240.33 examples/s]
Generating train split: 154434637 examples [2:28:24, 106044.62 examples/s]
Generating train split: 154445545 examples [2:28:24, 106883.45 examples/s]
Generating train split: 154457122 examples [2:28:24, 109456.70 examples/s]
Generating train split: 154468111 examples [2:28:24, 109271.72 examples/s]
Generating train split: 154479518 examples [2:28:24, 110681.68 examples/s]
Generating train split: 154490691 examples [2:28:24, 110963.20 examples/s]
Generating train split: 154501814 examples [2:28:24, 109973.42 examples/s]
Generating train split: 154512950 examples [2:28:24, 110344.72 examples/s]
Generating train split: 154523997 examples [2:28:25, 109275.40 examples/s]
Generating train split: 154535357 examples [2:28:25, 110545.28 examples/s]
Generating train split: 154546925 examples [2:28:25, 112028.72 examples/s]
Generating train split: 154558135 examples [2:28:25, 109763.42 examples/s]
Generating train split: 154569705 examples [2:28:25, 111473.77 examples/s]
Generating train split: 154581168 examples [2:28:25, 112392.53 examples/s]
Generating train split: 154593061 examples [2:28:25, 114285.17 examples/s]
Generating train split: 154604508 examples [2:28:25, 113462.15 examples/s]
Generating train split: 154616259 examples [2:28:25, 114648.19 examples/s]
Generating train split: 154627809 examples [2:28:26, 114863.14 examples/s]
Generating train split: 154639301 examples [2:28:26, 113458.31 examples/s]
Generating train split: 154650670 examples [2:28:26, 111571.09 examples/s]
Generating train split: 154661850 examples [2:28:26, 111441.21 examples/s]
Generating train split: 154673014 examples [2:28:26, 111284.83 examples/s]
Generating train split: 154684584 examples [2:28:26, 112587.34 examples/s]
Generating train split: 154695860 examples [2:28:26, 112565.61 examples/s]
Generating train split: 154707123 examples [2:28:26, 110915.42 examples/s]
Generating train split: 154718893 examples [2:28:26, 112877.94 examples/s]
Generating train split: 154730656 examples [2:28:26, 114251.83 examples/s]
Generating train split: 154742099 examples [2:28:27, 114118.39 examples/s]
Generating train split: 154753520 examples [2:28:27, 110635.21 examples/s]
Generating train split: 154764616 examples [2:28:27, 109707.69 examples/s]
Generating train split: 154776049 examples [2:28:27, 111052.64 examples/s]
Generating train split: 154788000 examples [2:28:27, 113503.34 examples/s]
Generating train split: 154799379 examples [2:28:27, 112896.50 examples/s]
Generating train split: 154810681 examples [2:28:27, 112613.72 examples/s]
Generating train split: 154822922 examples [2:28:27, 115514.10 examples/s]
Generating train split: 154834958 examples [2:28:27, 116917.57 examples/s]
Generating train split: 154846671 examples [2:28:27, 115731.50 examples/s]
Generating train split: 154859584 examples [2:28:28, 119700.47 examples/s]
Generating train split: 154871569 examples [2:28:28, 116037.87 examples/s]
Generating train split: 154883205 examples [2:28:28, 114151.37 examples/s]
Generating train split: 154895316 examples [2:28:28, 116153.01 examples/s]
Generating train split: 154907517 examples [2:28:28, 117838.05 examples/s]
Generating train split: 154919330 examples [2:28:28, 116371.73 examples/s]
Generating train split: 154930984 examples [2:28:28, 116122.35 examples/s]
Generating train split: 154942610 examples [2:28:28, 112865.83 examples/s]
Generating train split: 154954654 examples [2:28:28, 115059.39 examples/s]
Generating train split: 154966191 examples [2:28:28, 110610.10 examples/s]
Generating train split: 154977651 examples [2:28:29, 111739.57 examples/s]
Generating train split: 154988868 examples [2:28:29, 110960.23 examples/s]
Generating train split: 155001388 examples [2:28:29, 115108.08 examples/s]
Generating train split: 155013192 examples [2:28:29, 115947.49 examples/s]
Generating train split: 155024824 examples [2:28:29, 114624.45 examples/s]
Generating train split: 155036434 examples [2:28:29, 115033.93 examples/s]
Generating train split: 155047956 examples [2:28:29, 112606.03 examples/s]
Generating train split: 155059751 examples [2:28:29, 114149.06 examples/s]
Generating train split: 155071195 examples [2:28:29, 113347.77 examples/s]
Generating train split: 155082547 examples [2:28:30, 112976.30 examples/s]
Generating train split: 155094761 examples [2:28:30, 115639.07 examples/s]
Generating train split: 155106643 examples [2:28:30, 116552.34 examples/s]
Generating train split: 155118363 examples [2:28:30, 116726.86 examples/s]
Generating train split: 155130181 examples [2:28:30, 117123.34 examples/s]
Generating train split: 155142403 examples [2:28:30, 118633.50 examples/s]
Generating train split: 155154272 examples [2:28:30, 118093.84 examples/s]
Generating train split: 155166422 examples [2:28:30, 119104.66 examples/s]
Generating train split: 155178358 examples [2:28:30, 119172.00 examples/s]
Generating train split: 155190287 examples [2:28:30, 117741.92 examples/s]
Generating train split: 155202070 examples [2:28:31, 117650.36 examples/s]
Generating train split: 155213854 examples [2:28:31, 114841.29 examples/s]
Generating train split: 155225425 examples [2:28:31, 115073.72 examples/s]
Generating train split: 155236946 examples [2:28:31, 114594.03 examples/s]
Generating train split: 155248444 examples [2:28:31, 114680.12 examples/s]
Generating train split: 155259930 examples [2:28:31, 112483.06 examples/s]
Generating train split: 155272019 examples [2:28:31, 114938.17 examples/s]
Generating train split: 155284143 examples [2:28:31, 116773.49 examples/s]
Generating train split: 155295881 examples [2:28:31, 116939.97 examples/s]
Generating train split: 155307599 examples [2:28:31, 117008.56 examples/s]
Generating train split: 155319709 examples [2:28:32, 118213.01 examples/s]
Generating train split: 155331555 examples [2:28:32, 118150.48 examples/s]
Generating train split: 155343376 examples [2:28:32, 118129.32 examples/s]
Generating train split: 155355205 examples [2:28:32, 117630.25 examples/s]
Generating train split: 155367618 examples [2:28:32, 119560.96 examples/s]
Generating train split: 155380847 examples [2:28:32, 123332.85 examples/s]
Generating train split: 155393192 examples [2:28:32, 119731.75 examples/s]
Generating train split: 155405193 examples [2:28:32, 119415.70 examples/s]
Generating train split: 155417168 examples [2:28:32, 117830.27 examples/s]
Generating train split: 155428970 examples [2:28:32, 116042.44 examples/s]
Generating train split: 155440606 examples [2:28:33, 114105.94 examples/s]
Generating train split: 155452472 examples [2:28:33, 115428.92 examples/s]
Generating train split: 155464032 examples [2:28:33, 114721.28 examples/s]
Generating train split: 155475720 examples [2:28:33, 115319.96 examples/s]
Generating train split: 155487644 examples [2:28:33, 116473.95 examples/s]
Generating train split: 155499335 examples [2:28:33, 116599.51 examples/s]
Generating train split: 155511003 examples [2:28:33, 116506.94 examples/s]
Generating train split: 155523053 examples [2:28:33, 117652.05 examples/s]
Generating train split: 155535732 examples [2:28:33, 120371.73 examples/s]
Generating train split: 155547804 examples [2:28:33, 120466.74 examples/s]
Generating train split: 155559861 examples [2:28:34, 120328.16 examples/s]
Generating train split: 155571896 examples [2:28:34, 119135.92 examples/s]
Generating train split: 155583817 examples [2:28:34, 118227.13 examples/s]
Generating train split: 155595689 examples [2:28:34, 118330.65 examples/s]
Generating train split: 155607532 examples [2:28:34, 117213.82 examples/s]
Generating train split: 155619263 examples [2:28:34, 116995.88 examples/s]
Generating train split: 155631607 examples [2:28:34, 118872.25 examples/s]
Generating train split: 155643837 examples [2:28:34, 119848.40 examples/s]
Generating train split: 155655829 examples [2:28:34, 119258.60 examples/s]
Generating train split: 155667759 examples [2:28:34, 118717.06 examples/s]
Generating train split: 155679799 examples [2:28:35, 119173.59 examples/s]
Generating train split: 155692476 examples [2:28:35, 121407.01 examples/s]
Generating train split: 155704621 examples [2:28:35, 119374.85 examples/s]
Generating train split: 155716711 examples [2:28:35, 119804.97 examples/s]
Generating train split: 155728701 examples [2:28:35, 119164.86 examples/s]
Generating train split: 155741050 examples [2:28:35, 120402.45 examples/s]
Generating train split: 155753099 examples [2:28:35, 119313.55 examples/s]
Generating train split: 155765039 examples [2:28:35, 114603.87 examples/s]
Generating train split: 155776553 examples [2:28:35, 114703.85 examples/s]
Generating train split: 155788511 examples [2:28:36, 116127.31 examples/s]
Generating train split: 155800166 examples [2:28:36, 115043.43 examples/s]
Generating train split: 155812065 examples [2:28:36, 116172.17 examples/s]
Generating train split: 155824071 examples [2:28:36, 117296.79 examples/s]
Generating train split: 155835819 examples [2:28:36, 115881.90 examples/s]
Generating train split: 155847420 examples [2:28:36, 114713.07 examples/s]
Generating train split: 155859047 examples [2:28:36, 115129.50 examples/s]
Generating train split: 155870572 examples [2:28:36, 114139.27 examples/s]
Generating train split: 155882007 examples [2:28:36, 110853.98 examples/s]
Generating train split: 155893325 examples [2:28:36, 111496.23 examples/s]
Generating train split: 155904510 examples [2:28:37, 111133.71 examples/s]
Generating train split: 155915791 examples [2:28:37, 111615.53 examples/s]
Generating train split: 155927290 examples [2:28:37, 112581.50 examples/s]
Generating train split: 155938566 examples [2:28:37, 110340.37 examples/s]
Generating train split: 155950007 examples [2:28:37, 111532.63 examples/s]
Generating train split: 155961847 examples [2:28:37, 113518.72 examples/s]
Generating train split: 155973977 examples [2:28:37, 115810.93 examples/s]
Generating train split: 155985572 examples [2:28:37, 115280.71 examples/s]
Generating train split: 155997123 examples [2:28:37, 115321.13 examples/s]
Generating train split: 156008727 examples [2:28:37, 115499.83 examples/s]
Generating train split: 156020525 examples [2:28:38, 116196.94 examples/s]
Generating train split: 156032164 examples [2:28:38, 115618.84 examples/s]
Generating train split: 156043732 examples [2:28:38, 112868.98 examples/s]
Generating train split: 156055048 examples [2:28:38, 112248.73 examples/s]
Generating train split: 156066635 examples [2:28:38, 113302.87 examples/s]
Generating train split: 156078931 examples [2:28:38, 116156.35 examples/s]
Generating train split: 156090947 examples [2:28:38, 117317.07 examples/s]
Generating train split: 156102691 examples [2:28:38, 116448.27 examples/s]
Generating train split: 156114354 examples [2:28:38, 113765.47 examples/s]
Generating train split: 156126328 examples [2:28:38, 115480.39 examples/s]
Generating train split: 156138763 examples [2:28:39, 118093.22 examples/s]
Generating train split: 156150789 examples [2:28:39, 118706.10 examples/s]
Generating train split: 156162673 examples [2:28:39, 115026.36 examples/s]
Generating train split: 156174533 examples [2:28:39, 116062.11 examples/s]
Generating train split: 156186165 examples [2:28:39, 115828.11 examples/s]
Generating train split: 156198393 examples [2:28:39, 117696.45 examples/s]
Generating train split: 156210180 examples [2:28:39, 117105.44 examples/s]
Generating train split: 156221921 examples [2:28:39, 117183.34 examples/s]
Generating train split: 156233655 examples [2:28:39, 115258.15 examples/s]
Generating train split: 156245202 examples [2:28:39, 113540.78 examples/s]
Generating train split: 156257523 examples [2:28:40, 116364.78 examples/s]
Generating train split: 156269856 examples [2:28:40, 118394.52 examples/s]
Generating train split: 156281718 examples [2:28:40, 115937.03 examples/s]
Generating train split: 156293725 examples [2:28:40, 117113.96 examples/s]
Generating train split: 156305452 examples [2:28:40, 114273.36 examples/s]
Generating train split: 156317132 examples [2:28:40, 114978.42 examples/s]
Generating train split: 156329003 examples [2:28:40, 116073.51 examples/s]
Generating train split: 156340629 examples [2:28:40, 115993.93 examples/s]
Generating train split: 156352929 examples [2:28:40, 118042.26 examples/s]
Generating train split: 156364757 examples [2:28:41, 117544.12 examples/s]
Generating train split: 156376758 examples [2:28:41, 118265.58 examples/s]
Generating train split: 156389906 examples [2:28:41, 122179.60 examples/s]
Generating train split: 156402310 examples [2:28:41, 122680.60 examples/s]
Generating train split: 156414595 examples [2:28:41, 121776.45 examples/s]
Generating train split: 156426793 examples [2:28:41, 120819.00 examples/s]
Generating train split: 156438884 examples [2:28:41, 119468.47 examples/s]
Generating train split: 156450836 examples [2:28:41, 117598.97 examples/s]
Generating train split: 156462612 examples [2:28:41, 114970.12 examples/s]
Generating train split: 156474130 examples [2:28:41, 113530.29 examples/s]
Generating train split: 156485497 examples [2:28:42, 112466.10 examples/s]
Generating train split: 156497099 examples [2:28:42, 113479.18 examples/s]
Generating train split: 156508457 examples [2:28:42, 112609.42 examples/s]
Generating train split: 156519741 examples [2:28:42, 112656.47 examples/s]
Generating train split: 156531695 examples [2:28:42, 114669.19 examples/s]
Generating train split: 156543182 examples [2:28:42, 113302.79 examples/s]
Generating train split: 156554523 examples [2:28:42, 112980.71 examples/s]
Generating train split: 156565883 examples [2:28:42, 113137.55 examples/s]
Generating train split: 156577568 examples [2:28:42, 114237.58 examples/s]
Generating train split: 156588997 examples [2:28:43, 73451.28 examples/s] 
Generating train split: 156598194 examples [2:28:43, 61650.70 examples/s]
Generating train split: 156605899 examples [2:28:43, 61684.76 examples/s]
Generating train split: 156613869 examples [2:28:43, 65479.67 examples/s]
Generating train split: 156622676 examples [2:28:43, 70707.15 examples/s]
Generating train split: 156633096 examples [2:28:43, 79035.00 examples/s]
Generating train split: 156643559 examples [2:28:43, 85725.40 examples/s]
Generating train split: 156654887 examples [2:28:43, 93209.76 examples/s]
Generating train split: 156665610 examples [2:28:44, 97106.81 examples/s]
Generating train split: 156677129 examples [2:28:44, 102241.55 examples/s]
Generating train split: 156688762 examples [2:28:44, 106305.80 examples/s]
Generating train split: 156700305 examples [2:28:44, 108941.74 examples/s]
Generating train split: 156712153 examples [2:28:44, 111713.75 examples/s]
Generating train split: 156723682 examples [2:28:44, 112736.23 examples/s]
Generating train split: 156735208 examples [2:28:44, 113450.75 examples/s]
Generating train split: 156746698 examples [2:28:44, 113868.41 examples/s]
Generating train split: 156758132 examples [2:28:44, 110306.16 examples/s]
Generating train split: 156769216 examples [2:28:44, 108749.86 examples/s]
Generating train split: 156781114 examples [2:28:45, 111705.74 examples/s]
Generating train split: 156792329 examples [2:28:45, 107321.10 examples/s]
Generating train split: 156803284 examples [2:28:45, 107923.07 examples/s]
Generating train split: 156814120 examples [2:28:45, 107942.91 examples/s]
Generating train split: 156825513 examples [2:28:45, 109697.52 examples/s]
Generating train split: 156836645 examples [2:28:45, 110149.77 examples/s]
Generating train split: 156847691 examples [2:28:45, 107545.08 examples/s]
Generating train split: 156858473 examples [2:28:45, 106471.19 examples/s]
Generating train split: 156869214 examples [2:28:45, 106726.20 examples/s]
Generating train split: 156881268 examples [2:28:46, 110757.74 examples/s]
Generating train split: 156892898 examples [2:28:46, 112365.02 examples/s]
Generating train split: 156904148 examples [2:28:46, 110624.50 examples/s]
Generating train split: 156915319 examples [2:28:46, 110941.18 examples/s]
Generating train split: 156926432 examples [2:28:46, 109487.30 examples/s]
Generating train split: 156938713 examples [2:28:46, 113402.18 examples/s]
Generating train split: 156950398 examples [2:28:46, 114391.50 examples/s]
Generating train split: 156962042 examples [2:28:46, 114988.67 examples/s]
Generating train split: 156974387 examples [2:28:46, 117484.83 examples/s]
Generating train split: 156986147 examples [2:28:46, 113869.26 examples/s]
Generating train split: 156997911 examples [2:28:47, 114935.35 examples/s]
Generating train split: 157009427 examples [2:28:47, 113877.39 examples/s]
Generating train split: 157020842 examples [2:28:47, 111353.73 examples/s]
Generating train split: 157032085 examples [2:28:47, 111640.86 examples/s]
Generating train split: 157043538 examples [2:28:47, 112461.12 examples/s]
Generating train split: 157054801 examples [2:28:47, 108251.42 examples/s]
Generating train split: 157065681 examples [2:28:47, 107600.25 examples/s]
Generating train split: 157076474 examples [2:28:47, 106191.05 examples/s]
Generating train split: 157087187 examples [2:28:47, 106460.74 examples/s]
Generating train split: 157098785 examples [2:28:47, 109244.18 examples/s]
Generating train split: 157109732 examples [2:28:48, 109258.89 examples/s]
Generating train split: 157120674 examples [2:28:48, 106540.80 examples/s]
Generating train split: 157131357 examples [2:28:48, 105733.08 examples/s]
Generating train split: 157142576 examples [2:28:48, 107593.50 examples/s]
Generating train split: 157153352 examples [2:28:48, 107491.27 examples/s]
Generating train split: 157165033 examples [2:28:48, 110222.25 examples/s]
Generating train split: 157176075 examples [2:28:48, 109603.76 examples/s]
Generating train split: 157187629 examples [2:28:48, 111328.31 examples/s]
Generating train split: 157198897 examples [2:28:48, 111723.85 examples/s]
Generating train split: 157210085 examples [2:28:48, 111470.36 examples/s]
Generating train split: 157221248 examples [2:28:49, 110427.88 examples/s]
Generating train split: 157232928 examples [2:28:49, 112282.26 examples/s]
Generating train split: 157244510 examples [2:28:49, 113322.31 examples/s]
Generating train split: 157255851 examples [2:28:49, 113031.27 examples/s]
Generating train split: 157267172 examples [2:28:49, 112239.68 examples/s]
Generating train split: 157278405 examples [2:28:49, 111780.64 examples/s]
Generating train split: 157289592 examples [2:28:49, 108405.03 examples/s]
Generating train split: 157301340 examples [2:28:49, 111019.60 examples/s]
Generating train split: 157312586 examples [2:28:49, 111408.02 examples/s]
Generating train split: 157324336 examples [2:28:50, 113187.24 examples/s]
Generating train split: 157335724 examples [2:28:50, 113363.60 examples/s]
Generating train split: 157347203 examples [2:28:50, 113736.16 examples/s]
Generating train split: 157358594 examples [2:28:50, 112627.18 examples/s]
Generating train split: 157370266 examples [2:28:50, 113803.32 examples/s]
Generating train split: 157381665 examples [2:28:50, 111607.15 examples/s]
Generating train split: 157393080 examples [2:28:50, 112349.12 examples/s]
Generating train split: 157404497 examples [2:28:50, 112855.75 examples/s]
Generating train split: 157415791 examples [2:28:50, 112061.55 examples/s]
Generating train split: 157427022 examples [2:28:50, 111529.99 examples/s]
Generating train split: 157438561 examples [2:28:51, 112659.26 examples/s]
Generating train split: 157449886 examples [2:28:51, 112816.34 examples/s]
Generating train split: 157461219 examples [2:28:51, 112968.80 examples/s]
Generating train split: 157472527 examples [2:28:51, 108276.13 examples/s]
Generating train split: 157483413 examples [2:28:51, 107775.58 examples/s]
Generating train split: 157494925 examples [2:28:51, 109884.36 examples/s]
Generating train split: 157505947 examples [2:28:51, 105898.48 examples/s]
Generating train split: 157516582 examples [2:28:51, 104543.36 examples/s]
Generating train split: 157527101 examples [2:28:51, 104720.59 examples/s]
Generating train split: 157538224 examples [2:28:51, 106596.81 examples/s]
Generating train split: 157549486 examples [2:28:52, 108342.24 examples/s]
Generating train split: 157560849 examples [2:28:52, 109895.33 examples/s]
Generating train split: 157571858 examples [2:28:52, 108653.12 examples/s]
Generating train split: 157582848 examples [2:28:52, 109000.24 examples/s]
Generating train split: 157593768 examples [2:28:52, 108639.45 examples/s]
Generating train split: 157604644 examples [2:28:52, 108038.99 examples/s]
Generating train split: 157615454 examples [2:28:52, 107299.74 examples/s]
Generating train split: 157626195 examples [2:28:52, 106856.78 examples/s]
Generating train split: 157636888 examples [2:28:52, 106439.95 examples/s]
Generating train split: 157647553 examples [2:28:52, 106494.00 examples/s]
Generating train split: 157658650 examples [2:28:53, 107800.88 examples/s]
Generating train split: 157670293 examples [2:28:53, 110338.63 examples/s]
Generating train split: 157682398 examples [2:28:53, 113515.08 examples/s]
Generating train split: 157693754 examples [2:28:53, 112997.76 examples/s]
Generating train split: 157705531 examples [2:28:53, 114415.44 examples/s]
Generating train split: 157716977 examples [2:28:53, 113057.24 examples/s]
Generating train split: 157728303 examples [2:28:53, 111852.57 examples/s]
Generating train split: 157739853 examples [2:28:53, 112912.23 examples/s]
Generating train split: 157751608 examples [2:28:53, 114269.15 examples/s]
Generating train split: 157763049 examples [2:28:53, 114283.05 examples/s]
Generating train split: 157774491 examples [2:28:54, 113924.10 examples/s]
Generating train split: 157786220 examples [2:28:54, 114908.93 examples/s]
Generating train split: 157797720 examples [2:28:54, 114375.20 examples/s]
Generating train split: 157809173 examples [2:28:54, 113762.06 examples/s]
Generating train split: 157821024 examples [2:28:54, 115161.34 examples/s]
Generating train split: 157833200 examples [2:28:54, 117123.89 examples/s]
Generating train split: 157844931 examples [2:28:54, 114447.26 examples/s]
Generating train split: 157856505 examples [2:28:54, 114802.04 examples/s]
Generating train split: 157868090 examples [2:28:54, 115085.07 examples/s]
Generating train split: 157879906 examples [2:28:54, 115986.53 examples/s]
Generating train split: 157891632 examples [2:28:55, 116358.07 examples/s]
Generating train split: 157903289 examples [2:28:55, 116213.77 examples/s]
Generating train split: 157914920 examples [2:28:55, 114444.18 examples/s]
Generating train split: 157926376 examples [2:28:55, 112186.50 examples/s]
Generating train split: 157937621 examples [2:28:55, 112184.03 examples/s]
Generating train split: 157948861 examples [2:28:55, 108508.66 examples/s]
Generating train split: 157959951 examples [2:28:55, 109165.52 examples/s]
Generating train split: 157970902 examples [2:28:55, 108211.00 examples/s]
Generating train split: 157981747 examples [2:28:55, 104940.49 examples/s]
Generating train split: 157992278 examples [2:28:56, 104969.06 examples/s]
Generating train split: 158003381 examples [2:28:56, 106718.24 examples/s]
Generating train split: 158014411 examples [2:28:56, 107737.07 examples/s]
Generating train split: 158025522 examples [2:28:56, 108682.58 examples/s]
Generating train split: 158036421 examples [2:28:56, 107273.53 examples/s]
Generating train split: 158047163 examples [2:28:56, 107167.26 examples/s]
Generating train split: 158058609 examples [2:28:56, 109315.96 examples/s]
Generating train split: 158069565 examples [2:28:56, 109090.72 examples/s]
Generating train split: 158080496 examples [2:28:56, 108674.75 examples/s]
Generating train split: 158092028 examples [2:28:56, 110615.55 examples/s]
Generating train split: 158104047 examples [2:28:57, 113451.59 examples/s]
Generating train split: 158116079 examples [2:28:57, 115481.03 examples/s]
Generating train split: 158128286 examples [2:28:57, 117422.51 examples/s]
Generating train split: 158140875 examples [2:28:57, 119926.13 examples/s]
Generating train split: 158152885 examples [2:28:57, 118613.63 examples/s]
Generating train split: 158164779 examples [2:28:57, 118693.33 examples/s]
Generating train split: 158176928 examples [2:28:57, 119486.11 examples/s]
Generating train split: 158188936 examples [2:28:57, 119627.42 examples/s]
Generating train split: 158200905 examples [2:28:57, 118302.30 examples/s]
Generating train split: 158212741 examples [2:28:57, 117442.58 examples/s]
Generating train split: 158224499 examples [2:28:58, 113382.20 examples/s]
Generating train split: 158235869 examples [2:28:58, 113122.04 examples/s]
Generating train split: 158247205 examples [2:28:58, 111523.31 examples/s]
Generating train split: 158258585 examples [2:28:58, 112156.16 examples/s]
Generating train split: 158269814 examples [2:28:58, 110098.02 examples/s]
Generating train split: 158280847 examples [2:28:58, 109050.09 examples/s]
Generating train split: 158291766 examples [2:28:58, 108503.54 examples/s]
Generating train split: 158302660 examples [2:28:58, 108627.56 examples/s]
Generating train split: 158313541 examples [2:28:58, 108414.71 examples/s]
Generating train split: 158325312 examples [2:28:58, 111159.30 examples/s]
Generating train split: 158336810 examples [2:28:59, 112267.66 examples/s]
Generating train split: 158348046 examples [2:28:59, 108623.84 examples/s]
Generating train split: 158359049 examples [2:28:59, 108995.25 examples/s]
Generating train split: 158369973 examples [2:28:59, 104828.77 examples/s]
Generating train split: 158380682 examples [2:28:59, 105451.60 examples/s]
Generating train split: 158392067 examples [2:28:59, 107851.90 examples/s]
Generating train split: 158403158 examples [2:28:59, 108747.01 examples/s]
Generating train split: 158414427 examples [2:28:59, 109905.88 examples/s]
Generating train split: 158425709 examples [2:28:59, 110758.21 examples/s]
Generating train split: 158436801 examples [2:29:00, 106224.28 examples/s]
Generating train split: 158448315 examples [2:29:00, 108794.36 examples/s]
Generating train split: 158460016 examples [2:29:00, 111188.93 examples/s]
Generating train split: 158471873 examples [2:29:00, 113364.59 examples/s]
Generating train split: 158483993 examples [2:29:00, 115656.97 examples/s]
Generating train split: 158496022 examples [2:29:00, 116996.46 examples/s]
Generating train split: 158507747 examples [2:29:00, 115649.55 examples/s]
Generating train split: 158519327 examples [2:29:00, 113042.59 examples/s]
Generating train split: 158530653 examples [2:29:00, 113023.06 examples/s]
Generating train split: 158541971 examples [2:29:00, 112719.71 examples/s]
Generating train split: 158553538 examples [2:29:01, 113556.10 examples/s]
Generating train split: 158564908 examples [2:29:01, 110503.95 examples/s]
Generating train split: 158576342 examples [2:29:01, 111607.82 examples/s]
Generating train split: 158587524 examples [2:29:01, 108648.42 examples/s]
Generating train split: 158598415 examples [2:29:01, 108317.21 examples/s]
Generating train split: 158609888 examples [2:29:01, 110175.75 examples/s]
Generating train split: 158621613 examples [2:29:01, 112241.19 examples/s]
Generating train split: 158633762 examples [2:29:01, 114947.64 examples/s]
Generating train split: 158645275 examples [2:29:01, 113044.88 examples/s]
Generating train split: 158656605 examples [2:29:01, 112162.99 examples/s]
Generating train split: 158667836 examples [2:29:02, 110145.51 examples/s]
Generating train split: 158679330 examples [2:29:02, 111545.21 examples/s]
Generating train split: 158690788 examples [2:29:02, 112424.39 examples/s]
Generating train split: 158702060 examples [2:29:02, 111446.09 examples/s]
Generating train split: 158713214 examples [2:29:02, 109838.02 examples/s]
Generating train split: 158724457 examples [2:29:02, 110586.97 examples/s]
Generating train split: 158735536 examples [2:29:02, 110278.61 examples/s]
Generating train split: 158746591 examples [2:29:02, 107784.70 examples/s]
Generating train split: 158758781 examples [2:29:02, 111899.20 examples/s]
Generating train split: 158769996 examples [2:29:02, 111132.00 examples/s]
Generating train split: 158781140 examples [2:29:03, 110474.46 examples/s]
Generating train split: 158792202 examples [2:29:03, 108144.06 examples/s]
Generating train split: 158803031 examples [2:29:03, 105514.43 examples/s]
Generating train split: 158813612 examples [2:29:03, 104159.48 examples/s]
Generating train split: 158824855 examples [2:29:03, 106542.56 examples/s]
Generating train split: 158835532 examples [2:29:03, 106223.24 examples/s]
Generating train split: 158847449 examples [2:29:03, 110015.31 examples/s]
Generating train split: 158858468 examples [2:29:03, 109783.01 examples/s]
Generating train split: 158869459 examples [2:29:03, 109524.97 examples/s]
Generating train split: 158880422 examples [2:29:04, 106843.73 examples/s]
Generating train split: 158891139 examples [2:29:04, 105260.53 examples/s]
Generating train split: 158902994 examples [2:29:04, 109128.62 examples/s]
Generating train split: 158914779 examples [2:29:04, 111681.15 examples/s]
Generating train split: 158925972 examples [2:29:04, 107046.37 examples/s]
Generating train split: 158936882 examples [2:29:04, 107604.51 examples/s]
Generating train split: 158948938 examples [2:29:04, 111380.77 examples/s]
Generating train split: 158961101 examples [2:29:04, 114360.80 examples/s]
Generating train split: 158974038 examples [2:29:04, 118781.84 examples/s]
Generating train split: 158985947 examples [2:29:04, 115865.06 examples/s]
Generating train split: 158997582 examples [2:29:05, 115907.84 examples/s]
Generating train split: 159009201 examples [2:29:05, 114758.73 examples/s]
Generating train split: 159020707 examples [2:29:05, 114511.46 examples/s]
Generating train split: 159032304 examples [2:29:05, 114902.33 examples/s]
Generating train split: 159043806 examples [2:29:05, 113621.13 examples/s]
Generating train split: 159055324 examples [2:29:05, 114050.19 examples/s]
Generating train split: 159067163 examples [2:29:05, 115303.25 examples/s]
Generating train split: 159078700 examples [2:29:05, 112926.85 examples/s]
Generating train split: 159090410 examples [2:29:05, 114143.32 examples/s]
Generating train split: 159102053 examples [2:29:05, 114805.68 examples/s]
Generating train split: 159113596 examples [2:29:06, 114989.55 examples/s]
Generating train split: 159125316 examples [2:29:06, 115596.96 examples/s]
Generating train split: 159136887 examples [2:29:06, 114807.91 examples/s]
Generating train split: 159148387 examples [2:29:06, 114569.88 examples/s]
Generating train split: 159161113 examples [2:29:06, 118312.60 examples/s]
Generating train split: 159172963 examples [2:29:06, 116418.51 examples/s]
Generating train split: 159184629 examples [2:29:06, 113796.27 examples/s]
Generating train split: 159196490 examples [2:29:06, 115197.98 examples/s]
Generating train split: 159208034 examples [2:29:06, 112879.10 examples/s]
Generating train split: 159219343 examples [2:29:06, 112055.79 examples/s]
Generating train split: 159230601 examples [2:29:07, 112153.37 examples/s]
Generating train split: 159241829 examples [2:29:07, 110266.33 examples/s]
Generating train split: 159252881 examples [2:29:07, 108809.64 examples/s]
Generating train split: 159264339 examples [2:29:07, 110472.27 examples/s]
Generating train split: 159276380 examples [2:29:07, 113350.33 examples/s]
Generating train split: 159287741 examples [2:29:07, 112527.34 examples/s]
Generating train split: 159299007 examples [2:29:07, 109821.36 examples/s]
Generating train split: 159311016 examples [2:29:07, 112797.22 examples/s]
Generating train split: 159322321 examples [2:29:07, 108491.25 examples/s]
Generating train split: 159334113 examples [2:29:08, 111094.65 examples/s]
Generating train split: 159346048 examples [2:29:08, 113489.08 examples/s]
Generating train split: 159357441 examples [2:29:08, 111947.09 examples/s]
Generating train split: 159368665 examples [2:29:08, 108129.19 examples/s]
Generating train split: 159379521 examples [2:29:08, 105551.08 examples/s]
Generating train split: 159390122 examples [2:29:08, 105149.42 examples/s]
Generating train split: 159400746 examples [2:29:08, 105463.22 examples/s]
Generating train split: 159411311 examples [2:29:08, 103500.03 examples/s]
Generating train split: 159421686 examples [2:29:08, 101281.74 examples/s]
Generating train split: 159431843 examples [2:29:08, 99680.52 examples/s] 
Generating train split: 159441828 examples [2:29:09, 98552.93 examples/s]
Generating train split: 159452760 examples [2:29:09, 101632.39 examples/s]
Generating train split: 159465090 examples [2:29:09, 107943.57 examples/s]
Generating train split: 159476065 examples [2:29:09, 108443.05 examples/s]
Generating train split: 159487751 examples [2:29:09, 110930.51 examples/s]
Generating train split: 159499947 examples [2:29:09, 114208.79 examples/s]
Generating train split: 159511395 examples [2:29:09, 113098.75 examples/s]
Generating train split: 159523537 examples [2:29:09, 115555.84 examples/s]
Generating train split: 159535216 examples [2:29:09, 115916.71 examples/s]
Generating train split: 159547423 examples [2:29:09, 117732.72 examples/s]
Generating train split: 159559217 examples [2:29:10, 115529.74 examples/s]
Generating train split: 159571646 examples [2:29:10, 118110.79 examples/s]
Generating train split: 159584154 examples [2:29:10, 120132.29 examples/s]
Generating train split: 159596218 examples [2:29:10, 120275.17 examples/s]
Generating train split: 159608272 examples [2:29:10, 116184.20 examples/s]
Generating train split: 159619928 examples [2:29:10, 112381.29 examples/s]
Generating train split: 159631612 examples [2:29:10, 113623.78 examples/s]
Generating train split: 159643018 examples [2:29:10, 113279.63 examples/s]
Generating train split: 159655511 examples [2:29:10, 116671.93 examples/s]
Generating train split: 159667456 examples [2:29:11, 117468.45 examples/s]
Generating train split: 159679580 examples [2:29:11, 118548.55 examples/s]
Generating train split: 159691956 examples [2:29:11, 120073.78 examples/s]
Generating train split: 159703997 examples [2:29:11, 117932.76 examples/s]
Generating train split: 159716501 examples [2:29:11, 119981.06 examples/s]
Generating train split: 159728518 examples [2:29:11, 117982.87 examples/s]
Generating train split: 159740337 examples [2:29:11, 117141.59 examples/s]
Generating train split: 159752535 examples [2:29:11, 118550.94 examples/s]
Generating train split: 159765403 examples [2:29:11, 121506.58 examples/s]
Generating train split: 159777976 examples [2:29:11, 122725.79 examples/s]
Generating train split: 159790552 examples [2:29:12, 123583.67 examples/s]
Generating train split: 159802968 examples [2:29:12, 123698.56 examples/s]
Generating train split: 159815537 examples [2:29:12, 124260.46 examples/s]
Generating train split: 159828184 examples [2:29:12, 124921.05 examples/s]
Generating train split: 159840684 examples [2:29:12, 124350.18 examples/s]
Generating train split: 159853122 examples [2:29:12, 121231.23 examples/s]
Generating train split: 159865664 examples [2:29:12, 122424.35 examples/s]
Generating train split: 159877930 examples [2:29:12, 120962.02 examples/s]
Generating train split: 159890616 examples [2:29:12, 122658.61 examples/s]
Generating train split: 159903036 examples [2:29:12, 123096.52 examples/s]
Generating train split: 159915967 examples [2:29:13, 124925.83 examples/s]
Generating train split: 159928485 examples [2:29:13, 122262.12 examples/s]
Generating train split: 159940838 examples [2:29:13, 122625.95 examples/s]
Generating train split: 159953126 examples [2:29:13, 121658.76 examples/s]
Generating train split: 159965316 examples [2:29:13, 121667.84 examples/s]
Generating train split: 159978005 examples [2:29:13, 123209.61 examples/s]
Generating train split: 159991080 examples [2:29:13, 125414.43 examples/s]
Generating train split: 160003819 examples [2:29:13, 125968.76 examples/s]
Generating train split: 160016434 examples [2:29:13, 123389.85 examples/s]
Generating train split: 160028789 examples [2:29:13, 122903.71 examples/s]
Generating train split: 160041090 examples [2:29:14, 118950.23 examples/s]
Generating train split: 160053446 examples [2:29:14, 120276.15 examples/s]
Generating train split: 160065505 examples [2:29:14, 118811.25 examples/s]
Generating train split: 160078298 examples [2:29:14, 121454.33 examples/s]
Generating train split: 160090876 examples [2:29:14, 122716.88 examples/s]
Generating train split: 160103658 examples [2:29:14, 124217.02 examples/s]
Generating train split: 160116294 examples [2:29:14, 124834.32 examples/s]
Generating train split: 160129225 examples [2:29:14, 126160.01 examples/s]
Generating train split: 160142018 examples [2:29:14, 126655.85 examples/s]
Generating train split: 160154703 examples [2:29:15, 122577.17 examples/s]
Generating train split: 160167005 examples [2:29:15, 121123.62 examples/s]
Generating train split: 160179146 examples [2:29:15, 118932.88 examples/s]
Generating train split: 160191069 examples [2:29:15, 105081.60 examples/s]
Generating train split: 160202458 examples [2:29:15, 107407.62 examples/s]
Generating train split: 160214250 examples [2:29:15, 110288.19 examples/s]
Generating train split: 160225809 examples [2:29:15, 111762.19 examples/s]
Generating train split: 160237176 examples [2:29:15, 111476.70 examples/s]
Generating train split: 160248621 examples [2:29:15, 112322.53 examples/s]
Generating train split: 160260266 examples [2:29:15, 113508.04 examples/s]
Generating train split: 160271683 examples [2:29:16, 109162.45 examples/s]
Generating train split: 160283104 examples [2:29:16, 110599.76 examples/s]
Generating train split: 160295592 examples [2:29:16, 114729.30 examples/s]
Generating train split: 160307314 examples [2:29:16, 115429.15 examples/s]
Generating train split: 160319811 examples [2:29:16, 118200.61 examples/s]
Generating train split: 160332953 examples [2:29:16, 122117.00 examples/s]
Generating train split: 160345203 examples [2:29:16, 119667.55 examples/s]
Generating train split: 160357202 examples [2:29:16, 118912.87 examples/s]
Generating train split: 160369116 examples [2:29:16, 115720.90 examples/s]
Generating train split: 160380726 examples [2:29:16, 114681.92 examples/s]
Generating train split: 160392216 examples [2:29:17, 111558.53 examples/s]
Generating train split: 160404725 examples [2:29:17, 115442.85 examples/s]
Generating train split: 160416318 examples [2:29:17, 113456.94 examples/s]
Generating train split: 160428413 examples [2:29:17, 115586.62 examples/s]
Generating train split: 160439999 examples [2:29:17, 115331.76 examples/s]
Generating train split: 160451994 examples [2:29:17, 116684.33 examples/s]
Generating train split: 160463957 examples [2:29:17, 117514.43 examples/s]
Generating train split: 160475731 examples [2:29:17, 117233.00 examples/s]
Generating train split: 160488364 examples [2:29:17, 119933.31 examples/s]
Generating train split: 160500798 examples [2:29:18, 121206.96 examples/s]
Generating train split: 160512928 examples [2:29:18, 119061.00 examples/s]
Generating train split: 160524850 examples [2:29:18, 117577.16 examples/s]
Generating train split: 160536623 examples [2:29:18, 114341.77 examples/s]
Generating train split: 160548086 examples [2:29:18, 49048.81 examples/s] 
Generating train split: 160556723 examples [2:29:19, 54113.20 examples/s]
Generating train split: 160566114 examples [2:29:19, 61091.52 examples/s]
Generating train split: 160577740 examples [2:29:19, 72143.17 examples/s]
Generating train split: 160589792 examples [2:29:19, 82906.49 examples/s]
Generating train split: 160601735 examples [2:29:19, 91719.96 examples/s]
Generating train split: 160613106 examples [2:29:19, 97342.80 examples/s]
Generating train split: 160624106 examples [2:29:19, 98649.27 examples/s]
Generating train split: 160635302 examples [2:29:19, 102252.14 examples/s]
Generating train split: 160646810 examples [2:29:19, 105841.64 examples/s]
Generating train split: 160658045 examples [2:29:19, 107699.53 examples/s]
Generating train split: 160669476 examples [2:29:20, 109572.84 examples/s]
Generating train split: 160681366 examples [2:29:20, 112283.17 examples/s]
Generating train split: 160693426 examples [2:29:20, 114708.66 examples/s]
Generating train split: 160705727 examples [2:29:20, 117130.69 examples/s]
Generating train split: 160718144 examples [2:29:20, 119204.34 examples/s]
Generating train split: 160730669 examples [2:29:20, 120956.91 examples/s]
Generating train split: 160742938 examples [2:29:20, 121442.20 examples/s]
Generating train split: 160755125 examples [2:29:20, 121410.98 examples/s]
Generating train split: 160767303 examples [2:29:20, 119704.42 examples/s]
Generating train split: 160779298 examples [2:29:20, 115475.90 examples/s]
Generating train split: 160791475 examples [2:29:21, 117294.14 examples/s]
Generating train split: 160803248 examples [2:29:21, 116974.48 examples/s]
Generating train split: 160815185 examples [2:29:21, 117646.54 examples/s]
Generating train split: 160827211 examples [2:29:21, 118389.00 examples/s]
Generating train split: 160839078 examples [2:29:21, 118328.96 examples/s]
Generating train split: 160852069 examples [2:29:21, 121765.37 examples/s]
Generating train split: 160864258 examples [2:29:21, 121123.74 examples/s]
Generating train split: 160876391 examples [2:29:21, 117533.77 examples/s]
Generating train split: 160888333 examples [2:29:21, 118077.07 examples/s]
Generating train split: 160900177 examples [2:29:21, 115610.77 examples/s]
Generating train split: 160912515 examples [2:29:22, 117865.75 examples/s]
Generating train split: 160924943 examples [2:29:22, 119732.74 examples/s]
Generating train split: 160937186 examples [2:29:22, 120497.22 examples/s]
Generating train split: 160949416 examples [2:29:22, 120983.81 examples/s]
Generating train split: 160961530 examples [2:29:22, 120099.49 examples/s]
Generating train split: 160973557 examples [2:29:22, 116996.00 examples/s]
Generating train split: 160985302 examples [2:29:22, 111994.38 examples/s]
Generating train split: 160997545 examples [2:29:22, 114936.48 examples/s]
Generating train split: 161009554 examples [2:29:22, 116391.92 examples/s]
Generating train split: 161022113 examples [2:29:22, 119057.54 examples/s]
Generating train split: 161034058 examples [2:29:23, 117837.56 examples/s]
Generating train split: 161046511 examples [2:29:23, 119787.98 examples/s]
Generating train split: 161059252 examples [2:29:23, 122019.04 examples/s]
Generating train split: 161071616 examples [2:29:23, 122466.21 examples/s]
Generating train split: 161083880 examples [2:29:23, 120748.42 examples/s]
Generating train split: 161095984 examples [2:29:23, 117572.11 examples/s]
Generating train split: 161109012 examples [2:29:23, 121237.78 examples/s]
Generating train split: 161121989 examples [2:29:23, 123741.90 examples/s]
Generating train split: 161134405 examples [2:29:23, 121526.46 examples/s]
Generating train split: 161146589 examples [2:29:24, 121434.15 examples/s]
Generating train split: 161158772 examples [2:29:24, 115916.90 examples/s]
Generating train split: 161170481 examples [2:29:24, 116252.81 examples/s]
Generating train split: 161182461 examples [2:29:24, 117238.17 examples/s]
Generating train split: 161195251 examples [2:29:24, 120344.29 examples/s]
Generating train split: 161207335 examples [2:29:24, 120428.50 examples/s]
Generating train split: 161219406 examples [2:29:24, 117989.32 examples/s]
Generating train split: 161231423 examples [2:29:24, 118580.30 examples/s]
Generating train split: 161244401 examples [2:29:24, 121858.18 examples/s]
Generating train split: 161257491 examples [2:29:24, 124522.64 examples/s]
Generating train split: 161270261 examples [2:29:25, 125466.25 examples/s]
Generating train split: 161282836 examples [2:29:25, 124241.74 examples/s]
Generating train split: 161295597 examples [2:29:25, 125213.98 examples/s]
Generating train split: 161308566 examples [2:29:25, 126501.98 examples/s]
Generating train split: 161321229 examples [2:29:25, 123385.67 examples/s]
Generating train split: 161333590 examples [2:29:25, 123051.35 examples/s]
Generating train split: 161345915 examples [2:29:25, 120791.77 examples/s]
Generating train split: 161358026 examples [2:29:25, 120836.24 examples/s]
Generating train split: 161370136 examples [2:29:25, 120373.26 examples/s]
Generating train split: 161383090 examples [2:29:25, 123056.69 examples/s]
Generating train split: 161395411 examples [2:29:26, 121395.48 examples/s]
Generating train split: 161407989 examples [2:29:26, 122664.00 examples/s]
Generating train split: 161421311 examples [2:29:26, 125766.93 examples/s]
Generating train split: 161433899 examples [2:29:26, 125678.71 examples/s]
Generating train split: 161446487 examples [2:29:26, 123602.84 examples/s]
Generating train split: 161458862 examples [2:29:26, 122097.65 examples/s]
Generating train split: 161471085 examples [2:29:26, 120889.95 examples/s]
Generating train split: 161483192 examples [2:29:26, 119555.89 examples/s]
Generating train split: 161495165 examples [2:29:26, 115143.29 examples/s]
Generating train split: 161507677 examples [2:29:26, 117982.74 examples/s]
Generating train split: 161519805 examples [2:29:27, 118914.44 examples/s]
Generating train split: 161531724 examples [2:29:27, 118660.78 examples/s]
Generating train split: 161543622 examples [2:29:27, 113007.22 examples/s]
Generating train split: 161554992 examples [2:29:27, 112976.03 examples/s]
Generating train split: 161566872 examples [2:29:27, 114656.48 examples/s]
Generating train split: 161579394 examples [2:29:27, 117699.69 examples/s]
Generating train split: 161591208 examples [2:29:27, 115253.51 examples/s]
Generating train split: 161602770 examples [2:29:27, 113117.71 examples/s]
Generating train split: 161614128 examples [2:29:27, 111060.37 examples/s]
Generating train split: 161625422 examples [2:29:28, 111589.43 examples/s]
Generating train split: 161637704 examples [2:29:28, 114846.42 examples/s]
Generating train split: 161649223 examples [2:29:28, 107535.69 examples/s]
Generating train split: 161660080 examples [2:29:28, 103892.44 examples/s]
Generating train split: 161670566 examples [2:29:28, 103296.67 examples/s]
Generating train split: 161680954 examples [2:29:28, 101799.72 examples/s]
Generating train split: 161691183 examples [2:29:28, 101074.98 examples/s]
Generating train split: 161701332 examples [2:29:28, 100808.91 examples/s]
Generating train split: 161711431 examples [2:29:28, 100854.01 examples/s]
Generating train split: 161722130 examples [2:29:28, 102651.17 examples/s]
Generating train split: 161732419 examples [2:29:29, 101799.09 examples/s]
Generating train split: 161744247 examples [2:29:29, 106631.08 examples/s]
Generating train split: 161756761 examples [2:29:29, 112078.60 examples/s]
Generating train split: 161768362 examples [2:29:29, 113244.64 examples/s]
Generating train split: 161779918 examples [2:29:29, 113905.53 examples/s]
Generating train split: 161791318 examples [2:29:29, 113631.28 examples/s]
Generating train split: 161802697 examples [2:29:29, 109508.59 examples/s]
Generating train split: 161813695 examples [2:29:29, 108089.60 examples/s]
Generating train split: 161825772 examples [2:29:29, 111753.31 examples/s]
Generating train split: 161837714 examples [2:29:30, 113973.76 examples/s]
Generating train split: 161850189 examples [2:29:30, 117153.51 examples/s]
Generating train split: 161862001 examples [2:29:30, 117413.74 examples/s]
Generating train split: 161874485 examples [2:29:30, 119588.95 examples/s]
Generating train split: 161887161 examples [2:29:30, 121705.16 examples/s]
Generating train split: 161899416 examples [2:29:30, 121942.05 examples/s]
Generating train split: 161911629 examples [2:29:30, 120365.55 examples/s]
Generating train split: 161924181 examples [2:29:30, 121870.72 examples/s]
Generating train split: 161936383 examples [2:29:30, 119072.05 examples/s]
Generating train split: 161948858 examples [2:29:30, 120709.47 examples/s]
Generating train split: 161961167 examples [2:29:31, 121375.15 examples/s]
Generating train split: 161973343 examples [2:29:31, 121479.63 examples/s]
Generating train split: 161985504 examples [2:29:31, 121284.65 examples/s]
Generating train split: 161998158 examples [2:29:31, 122805.49 examples/s]
Generating train split: 162010454 examples [2:29:31, 120365.72 examples/s]
Generating train split: 162022511 examples [2:29:31, 119697.15 examples/s]
Generating train split: 162034495 examples [2:29:31, 118950.62 examples/s]
Generating train split: 162046410 examples [2:29:31, 116653.64 examples/s]
Generating train split: 162058088 examples [2:29:31, 113457.54 examples/s]
Generating train split: 162069781 examples [2:29:31, 114426.87 examples/s]
Generating train split: 162081453 examples [2:29:32, 115079.82 examples/s]
Generating train split: 162093422 examples [2:29:32, 116396.24 examples/s]
Generating train split: 162105326 examples [2:29:32, 117135.63 examples/s]
Generating train split: 162117552 examples [2:29:32, 118622.53 examples/s]
Generating train split: 162129443 examples [2:29:32, 116660.31 examples/s]
Generating train split: 162141984 examples [2:29:32, 119240.24 examples/s]
Generating train split: 162154572 examples [2:29:32, 121188.34 examples/s]
Generating train split: 162167128 examples [2:29:32, 122447.16 examples/s]
Generating train split: 162179513 examples [2:29:32, 122834.96 examples/s]
Generating train split: 162191819 examples [2:29:32, 122729.61 examples/s]
Generating train split: 162204102 examples [2:29:33, 118250.30 examples/s]
Generating train split: 162215982 examples [2:29:33, 118342.01 examples/s]
Generating train split: 162228553 examples [2:29:33, 120467.93 examples/s]
Generating train split: 162240880 examples [2:29:33, 121270.20 examples/s]
Generating train split: 162253104 examples [2:29:33, 121516.64 examples/s]
Generating train split: 162265273 examples [2:29:33, 121232.79 examples/s]
Generating train split: 162277407 examples [2:29:33, 120192.21 examples/s]
Generating train split: 162289692 examples [2:29:33, 120980.21 examples/s]
Generating train split: 162301808 examples [2:29:33, 119284.16 examples/s]
Generating train split: 162313749 examples [2:29:33, 116924.45 examples/s]
Generating train split: 162325455 examples [2:29:34, 114836.52 examples/s]
Generating train split: 162336969 examples [2:29:34, 114629.57 examples/s]
Generating train split: 162349627 examples [2:29:34, 118116.08 examples/s]
Generating train split: 162361611 examples [2:29:34, 118597.49 examples/s]
Generating train split: 162373508 examples [2:29:34, 118146.26 examples/s]
Generating train split: 162385349 examples [2:29:34, 116731.07 examples/s]
Generating train split: 162397034 examples [2:29:34, 115702.31 examples/s]
Generating train split: 162408623 examples [2:29:34, 115017.67 examples/s]
Generating train split: 162420140 examples [2:29:34, 114282.88 examples/s]
Generating train split: 162431575 examples [2:29:35, 113587.78 examples/s]
Generating train split: 162444018 examples [2:29:35, 116772.35 examples/s]
Generating train split: 162455706 examples [2:29:35, 116736.21 examples/s]
Generating train split: 162467399 examples [2:29:35, 113538.98 examples/s]
Generating train split: 162479653 examples [2:29:35, 116169.63 examples/s]
Generating train split: 162491507 examples [2:29:35, 116852.02 examples/s]
Generating train split: 162503212 examples [2:29:35, 113851.24 examples/s]
Generating train split: 162515209 examples [2:29:35, 115605.40 examples/s]
Generating train split: 162528195 examples [2:29:35, 119787.70 examples/s]
Generating train split: 162540199 examples [2:29:35, 118068.59 examples/s]
Generating train split: 162553275 examples [2:29:36, 121748.37 examples/s]
Generating train split: 162566030 examples [2:29:36, 123445.06 examples/s]
Generating train split: 162579267 examples [2:29:36, 126092.44 examples/s]
Generating train split: 162591903 examples [2:29:36, 124117.43 examples/s]
Generating train split: 162604340 examples [2:29:36, 122630.84 examples/s]
Generating train split: 162617663 examples [2:29:36, 125726.79 examples/s]
Generating train split: 162630496 examples [2:29:36, 126450.50 examples/s]
Generating train split: 162643163 examples [2:29:36, 124982.02 examples/s]
Generating train split: 162655687 examples [2:29:36, 122108.45 examples/s]
Generating train split: 162667921 examples [2:29:36, 120638.51 examples/s]
Generating train split: 162680489 examples [2:29:37, 122088.75 examples/s]
Generating train split: 162693827 examples [2:29:37, 125393.92 examples/s]
Generating train split: 162707386 examples [2:29:37, 128406.81 examples/s]
Generating train split: 162720810 examples [2:29:37, 130127.33 examples/s]
Generating train split: 162733839 examples [2:29:37, 128354.52 examples/s]
Generating train split: 162746692 examples [2:29:37, 126864.19 examples/s]
Generating train split: 162759405 examples [2:29:37, 123110.95 examples/s]
Generating train split: 162772575 examples [2:29:37, 125593.32 examples/s]
Generating train split: 162785164 examples [2:29:37, 123829.13 examples/s]
Generating train split: 162798090 examples [2:29:37, 125412.88 examples/s]
Generating train split: 162810666 examples [2:29:38, 120703.89 examples/s]
Generating train split: 162822842 examples [2:29:38, 120986.40 examples/s]
Generating train split: 162835458 examples [2:29:38, 122483.26 examples/s]
Generating train split: 162848201 examples [2:29:38, 123887.68 examples/s]
Generating train split: 162860630 examples [2:29:38, 121910.42 examples/s]
Generating train split: 162872848 examples [2:29:38, 118926.36 examples/s]
Generating train split: 162885719 examples [2:29:38, 121747.94 examples/s]
Generating train split: 162899131 examples [2:29:38, 125331.56 examples/s]
Generating train split: 162911695 examples [2:29:38, 125066.55 examples/s]
Generating train split: 162924221 examples [2:29:39, 124780.46 examples/s]
Generating train split: 162936716 examples [2:29:39, 120929.39 examples/s]
Generating train split: 162948846 examples [2:29:39, 118301.83 examples/s]
Generating train split: 162961165 examples [2:29:39, 119696.39 examples/s]
Generating train split: 162973807 examples [2:29:39, 121622.42 examples/s]
Generating train split: 162987014 examples [2:29:39, 124678.19 examples/s]
Generating train split: 162999522 examples [2:29:39, 120966.40 examples/s]
Generating train split: 163011658 examples [2:29:39, 120450.53 examples/s]
Generating train split: 163023737 examples [2:29:39, 119869.84 examples/s]
Generating train split: 163035752 examples [2:29:39, 117942.05 examples/s]
Generating train split: 163047579 examples [2:29:40, 116305.65 examples/s]
Generating train split: 163059236 examples [2:29:40, 111629.67 examples/s]
Generating train split: 163071289 examples [2:29:40, 114129.68 examples/s]
Generating train split: 163082748 examples [2:29:40, 112605.48 examples/s]
Generating train split: 163094047 examples [2:29:40, 108830.10 examples/s]
Generating train split: 163105693 examples [2:29:40, 110988.17 examples/s]
Generating train split: 163116830 examples [2:29:40, 110868.91 examples/s]
Generating train split: 163127951 examples [2:29:40, 108938.90 examples/s]
Generating train split: 163139798 examples [2:29:40, 111687.05 examples/s]
Generating train split: 163150995 examples [2:29:40, 111355.81 examples/s]
Generating train split: 163162150 examples [2:29:41, 109447.91 examples/s]
Generating train split: 163173117 examples [2:29:41, 102981.81 examples/s]
Generating train split: 163183495 examples [2:29:41, 97995.49 examples/s] 
Generating train split: 163193379 examples [2:29:41, 91244.21 examples/s]
Generating train split: 163204515 examples [2:29:41, 96643.57 examples/s]
Generating train split: 163216667 examples [2:29:41, 103538.13 examples/s]
Generating train split: 163227180 examples [2:29:41, 95074.29 examples/s] 
Generating train split: 163236912 examples [2:29:42, 49717.05 examples/s]
Generating train split: 163244388 examples [2:29:42, 52623.35 examples/s]
Generating train split: 163252871 examples [2:29:42, 58702.47 examples/s]
Generating train split: 163263169 examples [2:29:42, 68113.73 examples/s]
Generating train split: 163273853 examples [2:29:42, 77123.43 examples/s]
Generating train split: 163285490 examples [2:29:42, 86914.86 examples/s]
Generating train split: 163296618 examples [2:29:42, 93318.23 examples/s]
Generating train split: 163308318 examples [2:29:42, 99745.74 examples/s]
Generating train split: 163319115 examples [2:29:43, 102031.34 examples/s]
Generating train split: 163330673 examples [2:29:43, 105887.96 examples/s]
Generating train split: 163342998 examples [2:29:43, 110922.57 examples/s]
Generating train split: 163355015 examples [2:29:43, 113615.28 examples/s]
Generating train split: 163366888 examples [2:29:43, 115087.71 examples/s]
Generating train split: 163378763 examples [2:29:43, 116137.71 examples/s]
Generating train split: 163391840 examples [2:29:43, 120445.67 examples/s]
Generating train split: 163404055 examples [2:29:43, 120946.49 examples/s]
Generating train split: 163416205 examples [2:29:43, 120493.30 examples/s]
Generating train split: 163428824 examples [2:29:43, 122182.93 examples/s]
Generating train split: 163441076 examples [2:29:44, 121987.22 examples/s]
Generating train split: 163454092 examples [2:29:44, 124413.25 examples/s]
Generating train split: 163467494 examples [2:29:44, 127246.50 examples/s]
Generating train split: 163480407 examples [2:29:44, 127800.48 examples/s]
Generating train split: 163493484 examples [2:29:44, 128649.95 examples/s]
Generating train split: 163506359 examples [2:29:44, 128297.35 examples/s]
Generating train split: 163520086 examples [2:29:44, 130949.58 examples/s]
Generating train split: 163533194 examples [2:29:44, 130340.52 examples/s]
Generating train split: 163546373 examples [2:29:44, 130747.29 examples/s]
Generating train split: 163559451 examples [2:29:44, 128860.24 examples/s]
Generating train split: 163572362 examples [2:29:45, 126481.58 examples/s]
Generating train split: 163585041 examples [2:29:45, 124391.09 examples/s]
Generating train split: 163597512 examples [2:29:45, 121931.05 examples/s]
Generating train split: 163610307 examples [2:29:45, 123645.55 examples/s]
Generating train split: 163622697 examples [2:29:45, 115149.14 examples/s]
Generating train split: 163634674 examples [2:29:45, 116416.53 examples/s]
Generating train split: 163647958 examples [2:29:45, 121110.02 examples/s]
Generating train split: 163661208 examples [2:29:45, 124377.34 examples/s]
Generating train split: 163673733 examples [2:29:45, 124607.68 examples/s]
Generating train split: 163686446 examples [2:29:46, 125304.75 examples/s]
Generating train split: 163699026 examples [2:29:46, 120678.37 examples/s]
Generating train split: 163711167 examples [2:29:46, 112932.13 examples/s]
Generating train split: 163722601 examples [2:29:46, 112133.20 examples/s]
Generating train split: 163735128 examples [2:29:46, 115812.25 examples/s]
Generating train split: 163747152 examples [2:29:46, 117048.21 examples/s]
Generating train split: 163760001 examples [2:29:46, 120362.99 examples/s]
Generating train split: 163772432 examples [2:29:46, 121515.42 examples/s]
Generating train split: 163784939 examples [2:29:46, 122523.64 examples/s]
Generating train split: 163797223 examples [2:29:46, 120997.95 examples/s]
Generating train split: 163810166 examples [2:29:47, 123447.50 examples/s]
Generating train split: 163822570 examples [2:29:47, 123618.52 examples/s]
Generating train split: 163834959 examples [2:29:47, 122501.86 examples/s]
Generating train split: 163847686 examples [2:29:47, 123868.93 examples/s]
Generating train split: 163860084 examples [2:29:47, 121678.58 examples/s]
Generating train split: 163872277 examples [2:29:47, 117874.36 examples/s]
Generating train split: 163884107 examples [2:29:47, 114693.82 examples/s]
Generating train split: 163896675 examples [2:29:47, 117795.93 examples/s]
Generating train split: 163908881 examples [2:29:47, 118979.03 examples/s]
Generating train split: 163921262 examples [2:29:47, 120370.19 examples/s]
Generating train split: 163933823 examples [2:29:48, 121878.69 examples/s]
Generating train split: 163946062 examples [2:29:48, 122013.94 examples/s]
Generating train split: 163959099 examples [2:29:48, 124460.32 examples/s]
Generating train split: 163971568 examples [2:29:48, 121974.65 examples/s]
Generating train split: 163984421 examples [2:29:48, 123886.25 examples/s]
Generating train split: 163998048 examples [2:29:48, 127535.59 examples/s]
Generating train split: 164011052 examples [2:29:48, 128230.92 examples/s]
Generating train split: 164023897 examples [2:29:48, 126089.90 examples/s]
Generating train split: 164036934 examples [2:29:48, 127323.02 examples/s]
Generating train split: 164050476 examples [2:29:49, 129712.84 examples/s]
Generating train split: 164063475 examples [2:29:49, 129220.10 examples/s]
Generating train split: 164076409 examples [2:29:49, 125952.21 examples/s]
Generating train split: 164089124 examples [2:29:49, 126252.00 examples/s]
Generating train split: 164102609 examples [2:29:49, 128749.01 examples/s]
Generating train split: 164115501 examples [2:29:49, 128556.26 examples/s]
Generating train split: 164128496 examples [2:29:49, 128966.10 examples/s]
Generating train split: 164141688 examples [2:29:49, 129804.44 examples/s]
Generating train split: 164154676 examples [2:29:49, 126736.91 examples/s]
Generating train split: 164167600 examples [2:29:49, 127460.05 examples/s]
Generating train split: 164180364 examples [2:29:50, 125959.15 examples/s]
Generating train split: 164192988 examples [2:29:50, 125184.45 examples/s]
Generating train split: 164205694 examples [2:29:50, 125702.04 examples/s]
Generating train split: 164218810 examples [2:29:50, 127279.46 examples/s]
Generating train split: 164231555 examples [2:29:50, 123227.03 examples/s]
Generating train split: 164243916 examples [2:29:50, 122472.15 examples/s]
Generating train split: 164257592 examples [2:29:50, 126647.09 examples/s]
Generating train split: 164270286 examples [2:29:50, 124578.43 examples/s]
Generating train split: 164282766 examples [2:29:50, 123236.18 examples/s]
Generating train split: 164295115 examples [2:29:50, 121658.64 examples/s]
Generating train split: 164307298 examples [2:29:51, 119675.74 examples/s]
Generating train split: 164319277 examples [2:29:51, 119694.31 examples/s]
Generating train split: 164331528 examples [2:29:51, 120504.30 examples/s]
Generating train split: 164343849 examples [2:29:51, 121273.79 examples/s]
Generating train split: 164356242 examples [2:29:51, 122019.26 examples/s]
Generating train split: 164368960 examples [2:29:51, 123532.80 examples/s]
Generating train split: 164381989 examples [2:29:51, 125526.68 examples/s]
Generating train split: 164394553 examples [2:29:51, 122265.72 examples/s]
Generating train split: 164407054 examples [2:29:51, 123046.37 examples/s]
Generating train split: 164419388 examples [2:29:51, 122446.36 examples/s]
Generating train split: 164432193 examples [2:29:52, 124093.62 examples/s]
Generating train split: 164445294 examples [2:29:52, 126142.37 examples/s]
Generating train split: 164459162 examples [2:29:52, 129875.92 examples/s]
Generating train split: 164473505 examples [2:29:52, 133920.51 examples/s]
Generating train split: 164486913 examples [2:29:52, 130454.98 examples/s]
Generating train split: 164500112 examples [2:29:52, 130887.71 examples/s]
Generating train split: 164513225 examples [2:29:52, 128087.08 examples/s]
Generating train split: 164526063 examples [2:29:52, 127719.84 examples/s]
Generating train split: 164539033 examples [2:29:52, 128278.46 examples/s]
Generating train split: 164551889 examples [2:29:53, 126023.73 examples/s]
Generating train split: 164564756 examples [2:29:53, 126795.35 examples/s]
Generating train split: 164577596 examples [2:29:53, 127259.00 examples/s]
Generating train split: 164590385 examples [2:29:53, 127439.40 examples/s]
Generating train split: 164603207 examples [2:29:53, 127670.00 examples/s]
Generating train split: 164616312 examples [2:29:53, 128658.85 examples/s]
Generating train split: 164629570 examples [2:29:53, 129788.52 examples/s]
Generating train split: 164642924 examples [2:29:53, 130861.62 examples/s]
Generating train split: 164656017 examples [2:29:53, 127601.92 examples/s]
Generating train split: 164668808 examples [2:29:53, 125259.03 examples/s]
Generating train split: 164681359 examples [2:29:54, 120150.96 examples/s]
Generating train split: 164693445 examples [2:29:54, 119965.07 examples/s]
Generating train split: 164706501 examples [2:29:54, 123022.87 examples/s]
Generating train split: 164719824 examples [2:29:54, 125961.88 examples/s]
Generating train split: 164732453 examples [2:29:54, 121611.15 examples/s]
Generating train split: 164744683 examples [2:29:54, 116177.77 examples/s]
Generating train split: 164756387 examples [2:29:54, 112998.39 examples/s]
Generating train split: 164767746 examples [2:29:54, 109993.98 examples/s]
Generating train split: 164779095 examples [2:29:54, 110958.41 examples/s]
Generating train split: 164790452 examples [2:29:54, 111660.87 examples/s]
Generating train split: 164801669 examples [2:29:55, 108620.90 examples/s]
Generating train split: 164814425 examples [2:29:55, 114049.19 examples/s]
Generating train split: 164827279 examples [2:29:55, 118250.57 examples/s]
Generating train split: 164840090 examples [2:29:55, 121097.55 examples/s]
Generating train split: 164852245 examples [2:29:55, 120899.03 examples/s]
Generating train split: 164864378 examples [2:29:55, 119203.76 examples/s]
Generating train split: 164876611 examples [2:29:55, 120075.85 examples/s]
Generating train split: 164889182 examples [2:29:55, 121712.72 examples/s]
Generating train split: 164901636 examples [2:29:55, 122529.44 examples/s]
Generating train split: 164915173 examples [2:29:56, 126322.43 examples/s]
Generating train split: 164927819 examples [2:29:56, 125565.41 examples/s]
Generating train split: 164942158 examples [2:29:56, 130820.57 examples/s]
Generating train split: 164955580 examples [2:29:56, 131819.68 examples/s]
Generating train split: 164968770 examples [2:29:56, 127544.49 examples/s]
Generating train split: 164982934 examples [2:29:56, 131607.03 examples/s]
Generating train split: 164996589 examples [2:29:56, 133038.53 examples/s]
Generating train split: 165010535 examples [2:29:56, 134926.66 examples/s]
Generating train split: 165024057 examples [2:29:56, 131463.49 examples/s]
Generating train split: 165037837 examples [2:29:56, 133271.22 examples/s]
Generating train split: 165051566 examples [2:29:57, 134398.46 examples/s]
Generating train split: 165065041 examples [2:29:57, 132253.57 examples/s]
Generating train split: 165078298 examples [2:29:57, 127769.76 examples/s]
Generating train split: 165091115 examples [2:29:57, 127410.47 examples/s]
Generating train split: 165104316 examples [2:29:57, 128729.73 examples/s]
Generating train split: 165117233 examples [2:29:57, 126595.82 examples/s]
Generating train split: 165130385 examples [2:29:57, 127998.14 examples/s]
Generating train split: 165143342 examples [2:29:57, 128428.13 examples/s]
Generating train split: 165156202 examples [2:29:57, 127594.17 examples/s]
Generating train split: 165168971 examples [2:29:57, 123297.59 examples/s]
Generating train split: 165181336 examples [2:29:58, 120580.00 examples/s]
Generating train split: 165193434 examples [2:29:58, 115948.76 examples/s]
Generating train split: 165205075 examples [2:29:58, 115089.75 examples/s]
Generating train split: 165217298 examples [2:29:58, 117120.17 examples/s]
Generating train split: 165229672 examples [2:29:58, 119008.34 examples/s]
Generating train split: 165242570 examples [2:29:58, 121922.92 examples/s]
Generating train split: 165255272 examples [2:29:58, 123390.15 examples/s]
Generating train split: 165267644 examples [2:29:58, 119474.03 examples/s]
Generating train split: 165279640 examples [2:29:58, 118113.75 examples/s]
Generating train split: 165291490 examples [2:29:59, 115840.12 examples/s]
Generating train split: 165305093 examples [2:29:59, 121657.33 examples/s]
Generating train split: 165318206 examples [2:29:59, 124424.23 examples/s]
Generating train split: 165331340 examples [2:29:59, 126426.64 examples/s]
Generating train split: 165344302 examples [2:29:59, 127368.64 examples/s]
Generating train split: 165357125 examples [2:29:59, 127614.53 examples/s]
Generating train split: 165371131 examples [2:29:59, 131288.81 examples/s]
Generating train split: 165384289 examples [2:29:59, 129073.32 examples/s]
Generating train split: 165397228 examples [2:29:59, 128714.46 examples/s]
Generating train split: 165410116 examples [2:29:59, 125907.34 examples/s]
Generating train split: 165422726 examples [2:30:00, 120653.89 examples/s]
Generating train split: 165434861 examples [2:30:00, 117464.56 examples/s]
Generating train split: 165446666 examples [2:30:00, 117503.73 examples/s]
Generating train split: 165459118 examples [2:30:00, 119507.84 examples/s]
Generating train split: 165472577 examples [2:30:00, 123897.17 examples/s]
Generating train split: 165485706 examples [2:30:00, 126031.45 examples/s]
Generating train split: 165498338 examples [2:30:00, 124650.98 examples/s]
Generating train split: 165510849 examples [2:30:00, 124681.77 examples/s]
Generating train split: 165524327 examples [2:30:00, 127654.72 examples/s]
Generating train split: 165537107 examples [2:30:00, 127394.08 examples/s]
Generating train split: 165551553 examples [2:30:01, 132439.38 examples/s]
Generating train split: 165564820 examples [2:30:01, 132099.90 examples/s]
Generating train split: 165578583 examples [2:30:01, 133737.19 examples/s]
Generating train split: 165591969 examples [2:30:01, 132536.49 examples/s]
Generating train split: 165605728 examples [2:30:01, 134021.47 examples/s]
Generating train split: 165619138 examples [2:30:01, 131076.69 examples/s]
Generating train split: 165632263 examples [2:30:01, 129510.28 examples/s]
Generating train split: 165645238 examples [2:30:01, 126640.51 examples/s]
Generating train split: 165657922 examples [2:30:01, 126638.68 examples/s]
Generating train split: 165671071 examples [2:30:01, 128006.77 examples/s]
Generating train split: 165683885 examples [2:30:02, 126827.28 examples/s]
Generating train split: 165696589 examples [2:30:02, 124944.01 examples/s]
Generating train split: 165709098 examples [2:30:02, 123372.65 examples/s]
Generating train split: 165721457 examples [2:30:02, 119005.36 examples/s]
Generating train split: 165733409 examples [2:30:02, 117463.10 examples/s]
Generating train split: 165745184 examples [2:30:02, 116024.16 examples/s]
Generating train split: 165757899 examples [2:30:02, 119213.22 examples/s]
Generating train split: 165769850 examples [2:30:02, 117918.87 examples/s]
Generating train split: 165781665 examples [2:30:02, 115837.90 examples/s]
Generating train split: 165795262 examples [2:30:03, 121669.14 examples/s]
Generating train split: 165808334 examples [2:30:03, 124308.37 examples/s]
Generating train split: 165821116 examples [2:30:03, 125305.08 examples/s]
Generating train split: 165833976 examples [2:30:03, 126230.35 examples/s]
Generating train split: 165847373 examples [2:30:03, 128490.61 examples/s]
Generating train split: 165860619 examples [2:30:03, 129635.17 examples/s]
Generating train split: 165873602 examples [2:30:03, 127362.56 examples/s]
Generating train split: 165886393 examples [2:30:03, 127512.39 examples/s]
Generating train split: 165899180 examples [2:30:03, 121892.52 examples/s]
Generating train split: 165912702 examples [2:30:03, 125699.47 examples/s]
Generating train split: 165926861 examples [2:30:04, 130317.40 examples/s]
Generating train split: 165939955 examples [2:30:04, 127566.68 examples/s]
Generating train split: 165953460 examples [2:30:04, 129739.19 examples/s]
Generating train split: 165966742 examples [2:30:04, 130613.64 examples/s]
Generating train split: 165979835 examples [2:30:04, 128362.37 examples/s]
Generating train split: 165993289 examples [2:30:04, 130140.79 examples/s]
Generating train split: 166006957 examples [2:30:04, 132049.05 examples/s]
Generating train split: 166020200 examples [2:30:04, 126380.77 examples/s]
Generating train split: 166032912 examples [2:30:04, 121646.02 examples/s]
Generating train split: 166045323 examples [2:30:04, 122318.94 examples/s]
Generating train split: 166057623 examples [2:30:05, 118072.10 examples/s]
Generating train split: 166069490 examples [2:30:05, 114512.25 examples/s]
Generating train split: 166082727 examples [2:30:05, 119531.35 examples/s]
Generating train split: 166095371 examples [2:30:05, 121489.80 examples/s]
Generating train split: 166108676 examples [2:30:05, 124851.43 examples/s]
Generating train split: 166122463 examples [2:30:05, 128663.51 examples/s]
Generating train split: 166135391 examples [2:30:05, 125952.74 examples/s]
Generating train split: 166149508 examples [2:30:05, 130361.44 examples/s]
Generating train split: 166162585 examples [2:30:05, 126073.67 examples/s]
Generating train split: 166175252 examples [2:30:06, 123156.08 examples/s]
Generating train split: 166188538 examples [2:30:06, 125910.77 examples/s]
Generating train split: 166201824 examples [2:30:06, 127927.45 examples/s]
Generating train split: 166215253 examples [2:30:06, 129749.60 examples/s]
Generating train split: 166228799 examples [2:30:06, 131426.37 examples/s]
Generating train split: 166242149 examples [2:30:06, 131998.42 examples/s]
Generating train split: 166255372 examples [2:30:06, 130792.78 examples/s]
Generating train split: 166268474 examples [2:30:06, 130191.14 examples/s]
Generating train split: 166281692 examples [2:30:06, 130738.79 examples/s]
Generating train split: 166295937 examples [2:30:06, 134164.33 examples/s]
Generating train split: 166309486 examples [2:30:07, 134529.38 examples/s]
Generating train split: 166322947 examples [2:30:07, 130647.12 examples/s]
Generating train split: 166336040 examples [2:30:07, 130487.64 examples/s]
Generating train split: 166349125 examples [2:30:07, 127101.80 examples/s]
Generating train split: 166361863 examples [2:30:07, 127000.55 examples/s]
Generating train split: 166375093 examples [2:30:07, 128534.14 examples/s]
Generating train split: 166388795 examples [2:30:07, 131022.37 examples/s]
Generating train split: 166401919 examples [2:30:07, 122277.57 examples/s]
Generating train split: 166414817 examples [2:30:07, 124130.96 examples/s]
Generating train split: 166427339 examples [2:30:08, 123232.00 examples/s]
Generating train split: 166440334 examples [2:30:08, 125133.53 examples/s]
Generating train split: 166453362 examples [2:30:08, 126633.74 examples/s]
Generating train split: 166466081 examples [2:30:08, 125878.54 examples/s]
Generating train split: 166479362 examples [2:30:08, 127902.70 examples/s]
Generating train split: 166492183 examples [2:30:08, 127626.33 examples/s]
Generating train split: 166505625 examples [2:30:08, 129626.17 examples/s]
Generating train split: 166519213 examples [2:30:08, 131485.34 examples/s]
Generating train split: 166532819 examples [2:30:08, 132803.08 examples/s]
Generating train split: 166546114 examples [2:30:08, 128101.34 examples/s]
Generating train split: 166558980 examples [2:30:09, 125092.44 examples/s]
Generating train split: 166572338 examples [2:30:09, 127527.23 examples/s]
Generating train split: 166586053 examples [2:30:09, 130314.64 examples/s]
Generating train split: 166599554 examples [2:30:09, 131690.12 examples/s]
Generating train split: 166612992 examples [2:30:09, 132446.09 examples/s]
Generating train split: 166626279 examples [2:30:09, 130899.46 examples/s]
Generating train split: 166639910 examples [2:30:09, 132494.53 examples/s]
Generating train split: 166653192 examples [2:30:09, 130915.34 examples/s]
Generating train split: 166667284 examples [2:30:09, 133816.42 examples/s]
Generating train split: 166681388 examples [2:30:09, 135956.36 examples/s]
Generating train split: 166695004 examples [2:30:10, 134390.23 examples/s]
Generating train split: 166709255 examples [2:30:10, 136741.40 examples/s]
Generating train split: 166722957 examples [2:30:10, 135070.13 examples/s]
Generating train split: 166737500 examples [2:30:10, 138090.65 examples/s]
Generating train split: 166751334 examples [2:30:10, 138103.90 examples/s]
Generating train split: 166765157 examples [2:30:10, 136406.74 examples/s]
Generating train split: 166779786 examples [2:30:10, 139323.24 examples/s]
Generating train split: 166793731 examples [2:30:10, 134774.33 examples/s]
Generating train split: 166807259 examples [2:30:10, 129147.88 examples/s]
Generating train split: 166820248 examples [2:30:10, 127697.34 examples/s]
Generating train split: 166833943 examples [2:30:11, 130301.54 examples/s]
Generating train split: 166847030 examples [2:30:11, 130424.24 examples/s]
Generating train split: 166860429 examples [2:30:11, 131426.05 examples/s]
Generating train split: 166873609 examples [2:30:11, 130376.77 examples/s]
Generating train split: 166886666 examples [2:30:11, 125787.58 examples/s]
Generating train split: 166900009 examples [2:30:11, 127975.67 examples/s]
Generating train split: 166912851 examples [2:30:11, 127319.51 examples/s]
Generating train split: 166925612 examples [2:30:11, 125091.19 examples/s]
Generating train split: 166938151 examples [2:30:11, 124280.63 examples/s]
Generating train split: 166951979 examples [2:30:12, 128358.42 examples/s]
Generating train split: 166965154 examples [2:30:12, 129344.90 examples/s]
Generating train split: 166979635 examples [2:30:12, 133893.23 examples/s]
Generating train split: 166993196 examples [2:30:12, 134368.08 examples/s]
Generating train split: 167006655 examples [2:30:12, 132334.20 examples/s]
Generating train split: 167019917 examples [2:30:12, 129153.12 examples/s]
Generating train split: 167032863 examples [2:30:12, 126861.15 examples/s]
Generating train split: 167045587 examples [2:30:12, 124398.53 examples/s]
Generating train split: 167058311 examples [2:30:12, 125169.71 examples/s]
Generating train split: 167072083 examples [2:30:12, 128820.32 examples/s]
Generating train split: 167086594 examples [2:30:13, 133614.98 examples/s]
Generating train split: 167100825 examples [2:30:13, 136178.31 examples/s]
Generating train split: 167115390 examples [2:30:13, 138967.87 examples/s]
Generating train split: 167129671 examples [2:30:13, 140089.22 examples/s]
Generating train split: 167143702 examples [2:30:13, 136440.67 examples/s]
Generating train split: 167158387 examples [2:30:13, 139443.45 examples/s]
Generating train split: 167172359 examples [2:30:13, 104603.26 examples/s]
Generating train split: 167184107 examples [2:30:14, 69749.21 examples/s] 
Generating train split: 167194418 examples [2:30:14, 75797.91 examples/s]
Generating train split: 167206441 examples [2:30:14, 84947.86 examples/s]
Generating train split: 167218022 examples [2:30:14, 91958.49 examples/s]
Generating train split: 167230315 examples [2:30:14, 99532.97 examples/s]
Generating train split: 167242183 examples [2:30:14, 104455.59 examples/s]
Generating train split: 167254227 examples [2:30:14, 108747.75 examples/s]
Generating train split: 167265804 examples [2:30:14, 109543.49 examples/s]
Generating train split: 167277798 examples [2:30:14, 112480.39 examples/s]
Generating train split: 167289706 examples [2:30:14, 114332.49 examples/s]
Generating train split: 167302274 examples [2:30:15, 117611.48 examples/s]
Generating train split: 167315045 examples [2:30:15, 120538.54 examples/s]
Generating train split: 167327960 examples [2:30:15, 123064.15 examples/s]
Generating train split: 167340374 examples [2:30:15, 119379.99 examples/s]
Generating train split: 167352563 examples [2:30:15, 120076.09 examples/s]
Generating train split: 167366494 examples [2:30:15, 125703.24 examples/s]
Generating train split: 167379657 examples [2:30:15, 127408.42 examples/s]
Generating train split: 167394136 examples [2:30:15, 132552.10 examples/s]
Generating train split: 167408876 examples [2:30:15, 136940.54 examples/s]
Generating train split: 167422900 examples [2:30:16, 137917.96 examples/s]
Generating train split: 167437810 examples [2:30:16, 141256.99 examples/s]
Generating train split: 167451976 examples [2:30:16, 134967.33 examples/s]
Generating train split: 167466719 examples [2:30:16, 138571.94 examples/s]
Generating train split: 167481507 examples [2:30:16, 141235.13 examples/s]
Generating train split: 167496252 examples [2:30:16, 143062.68 examples/s]
Generating train split: 167511755 examples [2:30:16, 146573.94 examples/s]
Generating train split: 167527383 examples [2:30:16, 149406.50 examples/s]
Generating train split: 167542349 examples [2:30:16, 148975.08 examples/s]
Generating train split: 167557264 examples [2:30:16, 146838.46 examples/s]
Generating train split: 167571991 examples [2:30:17, 146146.80 examples/s]
Generating train split: 167586633 examples [2:30:17, 145617.20 examples/s]
Generating train split: 167601287 examples [2:30:17, 145877.79 examples/s]
Generating train split: 167616724 examples [2:30:17, 148356.77 examples/s]
Generating train split: 167631570 examples [2:30:17, 146367.94 examples/s]
Generating train split: 167646424 examples [2:30:17, 146953.32 examples/s]
Generating train split: 167662297 examples [2:30:17, 150428.29 examples/s]
Generating train split: 167677376 examples [2:30:17, 150535.84 examples/s]
Generating train split: 167692617 examples [2:30:17, 151046.66 examples/s]
Generating train split: 167707746 examples [2:30:17, 145004.83 examples/s]
Generating train split: 167722310 examples [2:30:18, 142031.53 examples/s]
Generating train split: 167736957 examples [2:30:18, 143284.41 examples/s]
Generating train split: 167751528 examples [2:30:18, 143952.94 examples/s]
Generating train split: 167766622 examples [2:30:18, 145988.08 examples/s]
Generating train split: 167781265 examples [2:30:18, 145886.36 examples/s]
Generating train split: 167795876 examples [2:30:18, 143905.69 examples/s]
Generating train split: 167810446 examples [2:30:18, 144387.56 examples/s]
Generating train split: 167824989 examples [2:30:18, 144643.45 examples/s]
Generating train split: 167840845 examples [2:30:18, 148775.82 examples/s]
Generating train split: 167856431 examples [2:30:18, 150867.06 examples/s]
Generating train split: 167871960 examples [2:30:19, 152177.17 examples/s]
Generating train split: 167887517 examples [2:30:19, 153147.47 examples/s]
Generating train split: 167902852 examples [2:30:19, 150434.78 examples/s]
Generating train split: 167917918 examples [2:30:19, 147295.69 examples/s]
Generating train split: 167932675 examples [2:30:19, 147025.12 examples/s]
Generating train split: 167947614 examples [2:30:19, 147712.00 examples/s]
Generating train split: 167962399 examples [2:30:19, 147053.74 examples/s]
Generating train split: 167977125 examples [2:30:19, 146790.58 examples/s]
Generating train split: 167992523 examples [2:30:19, 148868.33 examples/s]
Generating train split: 168007417 examples [2:30:19, 145298.09 examples/s]
Generating train split: 168021982 examples [2:30:20, 142364.95 examples/s]
Generating train split: 168036250 examples [2:30:20, 141913.33 examples/s]
Generating train split: 168050456 examples [2:30:20, 141340.57 examples/s]
Generating train split: 168065418 examples [2:30:20, 143761.91 examples/s]
Generating train split: 168079884 examples [2:30:20, 143998.53 examples/s]
Generating train split: 168094586 examples [2:30:20, 144883.16 examples/s]
Generating train split: 168109086 examples [2:30:20, 144739.97 examples/s]
Generating train split: 168123581 examples [2:30:20, 141832.47 examples/s]
Generating train split: 168138606 examples [2:30:20, 144252.66 examples/s]
Generating train split: 168153304 examples [2:30:21, 145017.64 examples/s]
Generating train split: 168168520 examples [2:30:21, 147112.69 examples/s]
Generating train split: 168184396 examples [2:30:21, 150563.44 examples/s]
Generating train split: 168200949 examples [2:30:21, 154982.19 examples/s]
Generating train split: 168216853 examples [2:30:21, 156177.99 examples/s]
Generating train split: 168232486 examples [2:30:21, 153037.86 examples/s]
Generating train split: 168247820 examples [2:30:21, 149530.42 examples/s]
Generating train split: 168262814 examples [2:30:21, 149337.66 examples/s]
Generating train split: 168277780 examples [2:30:21, 147571.18 examples/s]
Generating train split: 168292648 examples [2:30:21, 147849.88 examples/s]
Generating train split: 168307491 examples [2:30:22, 147985.44 examples/s]
Generating train split: 168323115 examples [2:30:22, 150430.45 examples/s]
Generating train split: 168339582 examples [2:30:22, 154629.93 examples/s]
Generating train split: 168355059 examples [2:30:22, 153776.51 examples/s]
Generating train split: 168370457 examples [2:30:22, 153492.29 examples/s]
Generating train split: 168385867 examples [2:30:22, 153631.41 examples/s]
Generating train split: 168401249 examples [2:30:22, 150626.16 examples/s]
Generating train split: 168416632 examples [2:30:22, 151560.58 examples/s]
Generating train split: 168432465 examples [2:30:22, 153550.46 examples/s]
Generating train split: 168447849 examples [2:30:22, 153528.30 examples/s]
Generating train split: 168464008 examples [2:30:23, 155883.18 examples/s]
Generating train split: 168479612 examples [2:30:23, 153700.50 examples/s]
Generating train split: 168495398 examples [2:30:23, 154895.71 examples/s]
Generating train split: 168511518 examples [2:30:23, 156737.28 examples/s]
Generating train split: 168527361 examples [2:30:23, 157197.64 examples/s]
Generating train split: 168543092 examples [2:30:23, 152794.88 examples/s]
Generating train split: 168558412 examples [2:30:23, 151165.77 examples/s]
Generating train split: 168573763 examples [2:30:23, 151832.49 examples/s]
Generating train split: 168589937 examples [2:30:23, 154708.03 examples/s]
Generating train split: 168605435 examples [2:30:23, 152808.78 examples/s]
Generating train split: 168620785 examples [2:30:24, 152993.93 examples/s]
Generating train split: 168636118 examples [2:30:24, 146641.09 examples/s]
Generating train split: 168651344 examples [2:30:24, 147990.45 examples/s]
Generating train split: 168666200 examples [2:30:24, 147850.54 examples/s]
Generating train split: 168682384 examples [2:30:24, 151898.61 examples/s]
Generating train split: 168697615 examples [2:30:24, 149918.86 examples/s]
Generating train split: 168713153 examples [2:30:24, 151475.21 examples/s]
Generating train split: 168728340 examples [2:30:24, 150000.23 examples/s]
Generating train split: 168743370 examples [2:30:24, 149392.05 examples/s]
Generating train split: 168758343 examples [2:30:24, 148662.72 examples/s]
Generating train split: 168773238 examples [2:30:25, 147295.06 examples/s]
Generating train split: 168788934 examples [2:30:25, 150125.09 examples/s]
Generating train split: 168804339 examples [2:30:25, 151237.44 examples/s]
Generating train split: 168819491 examples [2:30:25, 149594.43 examples/s]
Generating train split: 168835864 examples [2:30:25, 153749.06 examples/s]
Generating train split: 168852065 examples [2:30:25, 156170.86 examples/s]
Generating train split: 168867812 examples [2:30:25, 156551.72 examples/s]
Generating train split: 168883477 examples [2:30:25, 155109.32 examples/s]
Generating train split: 168898999 examples [2:30:25, 152222.89 examples/s]
Generating train split: 168914237 examples [2:30:26, 150458.89 examples/s]
Generating train split: 168929884 examples [2:30:26, 152198.85 examples/s]
Generating train split: 168945550 examples [2:30:26, 153483.49 examples/s]
Generating train split: 168961284 examples [2:30:26, 154605.74 examples/s]
Generating train split: 168976944 examples [2:30:26, 155179.17 examples/s]
Generating train split: 168992485 examples [2:30:26, 149683.77 examples/s]
Generating train split: 169007722 examples [2:30:26, 150460.17 examples/s]
Generating train split: 169023482 examples [2:30:26, 152535.58 examples/s]
Generating train split: 169038779 examples [2:30:26, 151637.93 examples/s]
Generating train split: 169053985 examples [2:30:26, 151166.20 examples/s]
Generating train split: 169070094 examples [2:30:27, 154068.20 examples/s]
Generating train split: 169085685 examples [2:30:27, 154606.32 examples/s]
Generating train split: 169101161 examples [2:30:27, 152214.78 examples/s]
Generating train split: 169116444 examples [2:30:27, 152335.99 examples/s]
Generating train split: 169131700 examples [2:30:27, 147764.15 examples/s]
Generating train split: 169147767 examples [2:30:27, 151495.99 examples/s]
Generating train split: 169163660 examples [2:30:27, 153636.44 examples/s]
Generating train split: 169179617 examples [2:30:27, 155357.74 examples/s]
Generating train split: 169195187 examples [2:30:27, 153628.04 examples/s]
Generating train split: 169210569 examples [2:30:27, 147148.73 examples/s]
Generating train split: 169225350 examples [2:30:28, 140439.54 examples/s]
Generating train split: 169240063 examples [2:30:28, 142307.07 examples/s]
Generating train split: 169254384 examples [2:30:28, 139998.57 examples/s]
Generating train split: 169268778 examples [2:30:28, 141077.04 examples/s]
Generating train split: 169283359 examples [2:30:28, 142448.13 examples/s]
Generating train split: 169299063 examples [2:30:28, 146728.40 examples/s]
Generating train split: 169314146 examples [2:30:28, 147887.99 examples/s]
Generating train split: 169328975 examples [2:30:28, 145902.35 examples/s]
Generating train split: 169344321 examples [2:30:28, 148084.44 examples/s]
Generating train split: 169359478 examples [2:30:28, 149106.08 examples/s]
Generating train split: 169375648 examples [2:30:29, 152826.74 examples/s]
Generating train split: 169392193 examples [2:30:29, 156550.69 examples/s]
Generating train split: 169408098 examples [2:30:29, 157291.98 examples/s]
Generating train split: 169424266 examples [2:30:29, 158601.03 examples/s]
Generating train split: 169440799 examples [2:30:29, 160557.20 examples/s]
Generating train split: 169456869 examples [2:30:29, 158365.85 examples/s]
Generating train split: 169472742 examples [2:30:29, 157420.47 examples/s]
Generating train split: 169488494 examples [2:30:29, 154723.09 examples/s]
Generating train split: 169503984 examples [2:30:29, 154045.80 examples/s]
Generating train split: 169520183 examples [2:30:30, 156362.67 examples/s]
Generating train split: 169536648 examples [2:30:30, 158758.58 examples/s]
Generating train split: 169552548 examples [2:30:30, 158491.64 examples/s]
Generating train split: 169568432 examples [2:30:30, 155623.93 examples/s]
Generating train split: 169584909 examples [2:30:30, 158297.85 examples/s]
Generating train split: 169600799 examples [2:30:30, 158451.43 examples/s]
Generating train split: 169617437 examples [2:30:30, 160748.04 examples/s]
Generating train split: 169633526 examples [2:30:30, 157865.83 examples/s]
Generating train split: 169649721 examples [2:30:30, 159056.72 examples/s]
Generating train split: 169665660 examples [2:30:30, 156228.92 examples/s]
Generating train split: 169682131 examples [2:30:31, 158683.31 examples/s]
Generating train split: 169698028 examples [2:30:31, 156855.32 examples/s]
Generating train split: 169713742 examples [2:30:31, 156897.74 examples/s]
Generating train split: 169729471 examples [2:30:31, 155921.61 examples/s]
Generating train split: 169745094 examples [2:30:31, 155927.21 examples/s]
Generating train split: 169761160 examples [2:30:31, 157279.54 examples/s]
Generating train split: 169776898 examples [2:30:31, 155211.28 examples/s]
Generating train split: 169793535 examples [2:30:31, 158468.46 examples/s]
Generating train split: 169809396 examples [2:30:31, 157004.12 examples/s]
Generating train split: 169825114 examples [2:30:31, 156185.94 examples/s]
Generating train split: 169840753 examples [2:30:32, 154508.21 examples/s]
Generating train split: 169856212 examples [2:30:32, 88326.89 examples/s] 
Generating train split: 169868347 examples [2:30:32, 88371.84 examples/s]
Generating train split: 169880909 examples [2:30:32, 96015.40 examples/s]
Generating train split: 169896522 examples [2:30:32, 109638.02 examples/s]
Generating train split: 169912384 examples [2:30:32, 121593.88 examples/s]
Generating train split: 169928814 examples [2:30:32, 132631.69 examples/s]
Generating train split: 169945161 examples [2:30:33, 140941.42 examples/s]
Generating train split: 169961856 examples [2:30:33, 148156.24 examples/s]
Generating train split: 169978555 examples [2:30:33, 153476.12 examples/s]
Generating train split: 169995364 examples [2:30:33, 157655.43 examples/s]
Generating train split: 170011546 examples [2:30:33, 158847.26 examples/s]
Generating train split: 170027811 examples [2:30:33, 159917.52 examples/s]
Generating train split: 170044005 examples [2:30:33, 158573.11 examples/s]
Generating train split: 170060797 examples [2:30:33, 161308.79 examples/s]
Generating train split: 170077423 examples [2:30:33, 162764.03 examples/s]
Generating train split: 170093966 examples [2:30:33, 163536.32 examples/s]
Generating train split: 170110506 examples [2:30:34, 164054.37 examples/s]
Generating train split: 170126961 examples [2:30:34, 163542.59 examples/s]
Generating train split: 170143628 examples [2:30:34, 164461.85 examples/s]
Generating train split: 170161385 examples [2:30:34, 168313.67 examples/s]
Generating train split: 170178405 examples [2:30:34, 168836.24 examples/s]
Generating train split: 170195322 examples [2:30:34, 168903.39 examples/s]
Generating train split: 170212307 examples [2:30:34, 169145.23 examples/s]
Generating train split: 170229399 examples [2:30:34, 169671.11 examples/s]
Generating train split: 170246375 examples [2:30:34, 169091.66 examples/s]
Generating train split: 170263934 examples [2:30:34, 171033.30 examples/s]
Generating train split: 170281072 examples [2:30:35, 170536.54 examples/s]
Generating train split: 170298131 examples [2:30:35, 168917.05 examples/s]
Generating train split: 170315280 examples [2:30:35, 169661.77 examples/s]
Generating train split: 170333205 examples [2:30:35, 172489.46 examples/s]
Generating train split: 170350466 examples [2:30:35, 171781.62 examples/s]
Generating train split: 170367671 examples [2:30:35, 169871.49 examples/s]
Generating train split: 170384699 examples [2:30:35, 165485.80 examples/s]
Generating train split: 170401564 examples [2:30:35, 166346.77 examples/s]
Generating train split: 170419364 examples [2:30:35, 169751.09 examples/s]
Generating train split: 170436531 examples [2:30:35, 170288.16 examples/s]
Generating train split: 170453582 examples [2:30:36, 168128.01 examples/s]
Generating train split: 170470424 examples [2:30:36, 162745.14 examples/s]
Generating train split: 170486761 examples [2:30:36, 162463.50 examples/s]
Generating train split: 170503056 examples [2:30:36, 162127.41 examples/s]
Generating train split: 170520237 examples [2:30:36, 164964.92 examples/s]
Generating train split: 170537514 examples [2:30:36, 167218.08 examples/s]
Generating train split: 170554961 examples [2:30:36, 169332.63 examples/s]
Generating train split: 170571921 examples [2:30:36, 167829.55 examples/s]
Generating train split: 170589522 examples [2:30:36, 170209.62 examples/s]
Generating train split: 170606960 examples [2:30:36, 171432.70 examples/s]
Generating train split: 170624311 examples [2:30:37, 172029.21 examples/s]
Generating train split: 170641542 examples [2:30:37, 171385.18 examples/s]
Generating train split: 170658993 examples [2:30:37, 172284.13 examples/s]
Generating train split: 170676253 examples [2:30:37, 171130.19 examples/s]
Generating train split: 170694176 examples [2:30:37, 173488.55 examples/s]
Generating train split: 170712275 examples [2:30:37, 175686.80 examples/s]
Generating train split: 170729857 examples [2:30:37, 171377.87 examples/s]
Generating train split: 170747933 examples [2:30:37, 174068.47 examples/s]
Generating train split: 170765373 examples [2:30:37, 173725.99 examples/s]
Generating train split: 170782973 examples [2:30:37, 174336.20 examples/s]
Generating train split: 170800426 examples [2:30:38, 172541.62 examples/s]
Generating train split: 170818464 examples [2:30:38, 174802.96 examples/s]
Generating train split: 170835959 examples [2:30:38, 173751.06 examples/s]
Generating train split: 170853372 examples [2:30:38, 171852.91 examples/s]
Generating train split: 170870575 examples [2:30:38, 169767.84 examples/s]
Generating train split: 170887873 examples [2:30:38, 170686.50 examples/s]
Generating train split: 170905304 examples [2:30:38, 171719.85 examples/s]
Generating train split: 170922494 examples [2:30:38, 167417.01 examples/s]
Generating train split: 170939852 examples [2:30:38, 169192.54 examples/s]
Generating train split: 170957344 examples [2:30:39, 170834.97 examples/s]
Generating train split: 170974864 examples [2:30:39, 172104.42 examples/s]
Generating train split: 170992258 examples [2:30:39, 172588.31 examples/s]
Generating train split: 171009699 examples [2:30:39, 173094.14 examples/s]
Generating train split: 171027020 examples [2:30:39, 170921.75 examples/s]
Generating train split: 171044963 examples [2:30:39, 173382.22 examples/s]
Generating train split: 171062722 examples [2:30:39, 174612.38 examples/s]
Generating train split: 171080197 examples [2:30:39, 173063.98 examples/s]
Generating train split: 171097628 examples [2:30:39, 173397.73 examples/s]
Generating train split: 171115792 examples [2:30:39, 175830.90 examples/s]
Generating train split: 171133409 examples [2:30:40, 175355.72 examples/s]
Generating train split: 171150949 examples [2:30:40, 175027.69 examples/s]
Generating train split: 171168459 examples [2:30:40, 174406.92 examples/s]
Generating train split: 171186745 examples [2:30:40, 176862.46 examples/s]
Generating train split: 171205057 examples [2:30:40, 178664.30 examples/s]
Generating train split: 171222936 examples [2:30:40, 174053.11 examples/s]
Generating train split: 171240381 examples [2:30:40, 173240.64 examples/s]
Generating train split: 171257731 examples [2:30:40, 172922.98 examples/s]
Generating train split: 171275058 examples [2:30:40, 172673.03 examples/s]
Generating train split: 171292342 examples [2:30:40, 171366.75 examples/s]
Generating train split: 171309500 examples [2:30:41, 169422.71 examples/s]
Generating train split: 171326574 examples [2:30:41, 169744.02 examples/s]
Generating train split: 171344574 examples [2:30:41, 172774.56 examples/s]
Generating train split: 171363122 examples [2:30:41, 176538.37 examples/s]
Generating train split: 171380792 examples [2:30:41, 174813.35 examples/s]
Generating train split: 171398283 examples [2:30:41, 173482.17 examples/s]
Generating train split: 171415645 examples [2:30:41, 171299.65 examples/s]
Generating train split: 171433183 examples [2:30:41, 172440.93 examples/s]
Generating train split: 171451246 examples [2:30:41, 174852.48 examples/s]
Generating train split: 171468743 examples [2:30:41, 174599.82 examples/s]
Generating train split: 171486232 examples [2:30:42, 173994.82 examples/s]
Generating train split: 171504739 examples [2:30:42, 177276.18 examples/s]
Generating train split: 171522482 examples [2:30:42, 174360.36 examples/s]
Generating train split: 171539963 examples [2:30:42, 170468.12 examples/s]
Generating train split: 171557041 examples [2:30:42, 168492.53 examples/s]
Generating train split: 171573931 examples [2:30:42, 167791.54 examples/s]
Generating train split: 171591468 examples [2:30:42, 169950.25 examples/s]
Generating train split: 171608986 examples [2:30:42, 171431.04 examples/s]
Generating train split: 171626163 examples [2:30:42, 169923.70 examples/s]
Generating train split: 171643176 examples [2:30:42, 169746.46 examples/s]
Generating train split: 171660174 examples [2:30:43, 169480.22 examples/s]
Generating train split: 171677969 examples [2:30:43, 171925.48 examples/s]
Generating train split: 171696716 examples [2:30:43, 176488.48 examples/s]
Generating train split: 171715400 examples [2:30:43, 179537.54 examples/s]
Generating train split: 171734282 examples [2:30:43, 182279.21 examples/s]
Generating train split: 171752606 examples [2:30:43, 182503.31 examples/s]
Generating train split: 171770979 examples [2:30:43, 182834.17 examples/s]
Generating train split: 171789297 examples [2:30:43, 180139.39 examples/s]
Generating train split: 171807349 examples [2:30:43, 180202.98 examples/s]
Generating train split: 171825412 examples [2:30:43, 180305.75 examples/s]
Generating train split: 171844354 examples [2:30:44, 183019.63 examples/s]
Generating train split: 171862664 examples [2:30:44, 181796.73 examples/s]
Generating train split: 171880863 examples [2:30:44, 181652.69 examples/s]
Generating train split: 171899244 examples [2:30:44, 182229.32 examples/s]
Generating train split: 171917612 examples [2:30:44, 182599.64 examples/s]
Generating train split: 171935904 examples [2:30:44, 179893.56 examples/s]
Generating train split: 171953936 examples [2:30:44, 178951.31 examples/s]
Generating train split: 171971851 examples [2:30:44, 177750.47 examples/s]
Generating train split: 171990392 examples [2:30:44, 179984.46 examples/s]
Generating train split: 172008985 examples [2:30:45, 181713.31 examples/s]
Generating train split: 172027706 examples [2:30:45, 183291.37 examples/s]
Generating train split: 172046045 examples [2:30:45, 182525.75 examples/s]
Generating train split: 172064311 examples [2:30:45, 180017.57 examples/s]
Generating train split: 172082338 examples [2:30:45, 176382.42 examples/s]
Generating train split: 172100012 examples [2:30:45, 173590.83 examples/s]
Generating train split: 172117682 examples [2:30:45, 174484.03 examples/s]
Generating train split: 172135660 examples [2:30:45, 176032.95 examples/s]
Generating train split: 172154891 examples [2:30:45, 180805.94 examples/s]
Generating train split: 172173009 examples [2:30:45, 174714.29 examples/s]
Generating train split: 172191286 examples [2:30:46, 177035.76 examples/s]
Generating train split: 172210098 examples [2:30:46, 180280.34 examples/s]
Generating train split: 172228190 examples [2:30:46, 180171.95 examples/s]
Generating train split: 172247075 examples [2:30:46, 182681.22 examples/s]
Generating train split: 172265381 examples [2:30:46, 182717.09 examples/s]
Generating train split: 172283676 examples [2:30:46, 182411.94 examples/s]
Generating train split: 172301958 examples [2:30:46, 182120.62 examples/s]
Generating train split: 172320294 examples [2:30:46, 182478.53 examples/s]
Generating train split: 172338678 examples [2:30:46, 182874.28 examples/s]
Generating train split: 172356977 examples [2:30:46, 179626.25 examples/s]
Generating train split: 172375765 examples [2:30:47, 182057.29 examples/s]
Generating train split: 172394641 examples [2:30:47, 184012.07 examples/s]
Generating train split: 172413691 examples [2:30:47, 185883.94 examples/s]
Generating train split: 172432403 examples [2:30:47, 186193.46 examples/s]
Generating train split: 172451050 examples [2:30:47, 184436.69 examples/s]
Generating train split: 172469518 examples [2:30:47, 180493.00 examples/s]
Generating train split: 172487813 examples [2:30:47, 181180.78 examples/s]
Generating train split: 172507172 examples [2:30:47, 184806.22 examples/s]
Generating train split: 172526108 examples [2:30:47, 186100.52 examples/s]
Generating train split: 172545701 examples [2:30:47, 188963.00 examples/s]
Generating train split: 172564888 examples [2:30:48, 189804.64 examples/s]
Generating train split: 172584898 examples [2:30:48, 192826.55 examples/s]
Generating train split: 172604217 examples [2:30:48, 192715.58 examples/s]
Generating train split: 172623515 examples [2:30:48, 190809.78 examples/s]
Generating train split: 172642629 examples [2:30:48, 188920.46 examples/s]
Generating train split: 172661543 examples [2:30:48, 184949.27 examples/s]
Generating train split: 172680239 examples [2:30:48, 185496.12 examples/s]
Generating train split: 172699783 examples [2:30:48, 188415.56 examples/s]
Generating train split: 172719036 examples [2:30:48, 189615.08 examples/s]
Generating train split: 172738428 examples [2:30:48, 190863.20 examples/s]
Generating train split: 172757746 examples [2:30:49, 191544.53 examples/s]
Generating train split: 172777118 examples [2:30:49, 192148.49 examples/s]
Generating train split: 172796353 examples [2:30:49, 191703.27 examples/s]
Generating train split: 172815540 examples [2:30:49, 191144.00 examples/s]
Generating train split: 172834658 examples [2:30:49, 189532.45 examples/s]
Generating train split: 172853621 examples [2:30:49, 189299.17 examples/s]
Generating train split: 172873033 examples [2:30:49, 190702.19 examples/s]
Generating train split: 172892579 examples [2:30:49, 192068.60 examples/s]
Generating train split: 172911958 examples [2:30:49, 192563.23 examples/s]
Generating train split: 172931233 examples [2:30:49, 189480.28 examples/s]
Generating train split: 172951873 examples [2:30:50, 194480.53 examples/s]
Generating train split: 172971341 examples [2:30:50, 190627.41 examples/s]
Generating train split: 172990448 examples [2:30:50, 189162.85 examples/s]
Generating train split: 173009387 examples [2:30:50, 187673.75 examples/s]
Generating train split: 173029613 examples [2:30:50, 191954.74 examples/s]
Generating train split: 173049564 examples [2:30:50, 194148.12 examples/s]
Generating train split: 173070063 examples [2:30:50, 197361.51 examples/s]
Generating train split: 173089852 examples [2:30:50, 197433.87 examples/s]
Generating train split: 173109653 examples [2:30:50, 197543.59 examples/s]
Generating train split: 173130066 examples [2:30:50, 199469.15 examples/s]
Generating train split: 173150437 examples [2:30:51, 200653.76 examples/s]
Generating train split: 173170538 examples [2:30:51, 200290.50 examples/s]
Generating train split: 173190584 examples [2:30:51, 199067.52 examples/s]
Generating train split: 173211598 examples [2:30:51, 202315.18 examples/s]
Generating train split: 173231867 examples [2:30:51, 201809.06 examples/s]
Generating train split: 173252563 examples [2:30:51, 203302.26 examples/s]
Generating train split: 173272916 examples [2:30:51, 199779.09 examples/s]
Generating train split: 173293668 examples [2:30:51, 202002.12 examples/s]
Generating train split: 173313885 examples [2:30:51, 197541.54 examples/s]
Generating train split: 173334304 examples [2:30:52, 199419.35 examples/s]
Generating train split: 173355440 examples [2:30:52, 202902.53 examples/s]
Generating train split: 173375991 examples [2:30:52, 203675.39 examples/s]
Generating train split: 173397295 examples [2:30:52, 206385.98 examples/s]
Generating train split: 173418743 examples [2:30:52, 208757.85 examples/s]
Generating train split: 173439802 examples [2:30:52, 209244.92 examples/s]
Generating train split: 173460995 examples [2:30:52, 210036.02 examples/s]
Generating train split: 173482173 examples [2:30:52, 210493.75 examples/s]
Generating train split: 173503878 examples [2:30:52, 212452.17 examples/s]
Generating train split: 173525159 examples [2:30:52, 212302.54 examples/s]
Generating train split: 173546397 examples [2:30:53, 211737.41 examples/s]
Generating train split: 173567575 examples [2:30:53, 210809.76 examples/s]
Generating train split: 173589220 examples [2:30:53, 212476.69 examples/s]
Generating train split: 173610473 examples [2:30:53, 210578.25 examples/s]
Generating train split: 173631582 examples [2:30:53, 209749.48 examples/s]
Generating train split: 173654197 examples [2:30:53, 214565.56 examples/s]
Generating train split: 173675809 examples [2:30:53, 215014.99 examples/s]
Generating train split: 173697325 examples [2:30:53, 211820.47 examples/s]
Generating train split: 173718545 examples [2:30:54, 122879.25 examples/s]
Generating train split: 173736882 examples [2:30:54, 134766.73 examples/s]
Generating train split: 173756547 examples [2:30:54, 148338.90 examples/s]
Generating train split: 173776892 examples [2:30:54, 161487.17 examples/s]
Generating train split: 173796457 examples [2:30:54, 170131.27 examples/s]
Generating train split: 173817058 examples [2:30:54, 179658.35 examples/s]
Generating train split: 173837700 examples [2:30:54, 187023.28 examples/s]
Generating train split: 173858118 examples [2:30:54, 191822.31 examples/s]
Generating train split: 173878092 examples [2:30:54, 189855.99 examples/s]
Generating train split: 173898352 examples [2:30:54, 193467.54 examples/s]
Generating train split: 173918266 examples [2:30:55, 195062.40 examples/s]
Generating train split: 173938116 examples [2:30:55, 196011.12 examples/s]
Generating train split: 173957928 examples [2:30:55, 192486.68 examples/s]
Generating train split: 173977362 examples [2:30:55, 187281.13 examples/s]
Generating train split: 173997817 examples [2:30:55, 192239.15 examples/s]
Generating train split: 174018167 examples [2:30:55, 195498.81 examples/s]
Generating train split: 174039836 examples [2:30:55, 201725.61 examples/s]
Generating train split: 174061075 examples [2:30:55, 204835.47 examples/s]
Generating train split: 174081632 examples [2:30:55, 201223.16 examples/s]
Generating train split: 174103140 examples [2:30:56, 205213.94 examples/s]
Generating train split: 174124799 examples [2:30:56, 208569.07 examples/s]
Generating train split: 174146212 examples [2:30:56, 210139.36 examples/s]
Generating train split: 174167961 examples [2:30:56, 212268.30 examples/s]
Generating train split: 174190330 examples [2:30:56, 215604.45 examples/s]
Generating train split: 174213420 examples [2:30:56, 220107.80 examples/s]
Generating train split: 174235822 examples [2:30:56, 221248.94 examples/s]
Generating train split: 174258831 examples [2:30:56, 223858.23 examples/s]
Generating train split: 174282598 examples [2:30:56, 227989.56 examples/s]
Generating train split: 174305783 examples [2:30:56, 229130.67 examples/s]
Generating train split: 174328708 examples [2:30:57, 228129.48 examples/s]
Generating train split: 174351773 examples [2:30:57, 228876.81 examples/s]
Generating train split: 174375162 examples [2:30:57, 230371.06 examples/s]
Generating train split: 174398620 examples [2:30:57, 231608.11 examples/s]
Generating train split: 174421783 examples [2:30:57, 230407.94 examples/s]
Generating train split: 174445682 examples [2:30:57, 232955.29 examples/s]
Generating train split: 174470021 examples [2:30:57, 236009.52 examples/s]
Generating train split: 174493648 examples [2:30:57, 233991.20 examples/s]
Generating train split: 174517540 examples [2:30:57, 235371.94 examples/s]
Generating train split: 174541295 examples [2:30:57, 235982.33 examples/s]
Generating train split: 174564906 examples [2:30:58, 235957.18 examples/s]
Generating train split: 174588844 examples [2:30:58, 236943.36 examples/s]
Generating train split: 174612579 examples [2:30:58, 234966.22 examples/s]
Generating train split: 174636087 examples [2:30:58, 234650.79 examples/s]
Generating train split: 174659578 examples [2:30:58, 234144.12 examples/s]
Generating train split: 174682997 examples [2:30:58, 231716.67 examples/s]
Generating train split: 174706666 examples [2:30:58, 233186.29 examples/s]
Generating train split: 174730871 examples [2:30:58, 235757.62 examples/s]
Generating train split: 174754798 examples [2:30:58, 236775.46 examples/s]
Generating train split: 174779166 examples [2:30:58, 238816.24 examples/s]
Generating train split: 174803083 examples [2:30:59, 238512.23 examples/s]
Generating train split: 174826968 examples [2:30:59, 237225.92 examples/s]
Generating train split: 174850726 examples [2:30:59, 235100.21 examples/s]
Generating train split: 174874291 examples [2:30:59, 234160.14 examples/s]
Generating train split: 174897711 examples [2:30:59, 233181.07 examples/s]
Generating train split: 174921086 examples [2:30:59, 233314.99 examples/s]
Generating train split: 174944455 examples [2:30:59, 232776.38 examples/s]
Generating train split: 174967742 examples [2:30:59, 229699.49 examples/s]
Generating train split: 174992687 examples [2:30:59, 235457.34 examples/s]
Generating train split: 175017405 examples [2:30:59, 238845.79 examples/s]
Generating train split: 175042394 examples [2:31:00, 242098.78 examples/s]
Generating train split: 175066833 examples [2:31:00, 242693.58 examples/s]
Generating train split: 175092844 examples [2:31:00, 247817.77 examples/s]
Generating train split: 175118025 examples [2:31:00, 248967.28 examples/s]
Generating train split: 175142965 examples [2:31:00, 247715.36 examples/s]
Generating train split: 175168373 examples [2:31:00, 249531.29 examples/s]
Generating train split: 175193545 examples [2:31:00, 250144.50 examples/s]
Generating train split: 175219288 examples [2:31:00, 252245.30 examples/s]
Generating train split: 175244670 examples [2:31:00, 252704.08 examples/s]
Generating train split: 175269967 examples [2:31:00, 246583.13 examples/s]
Generating train split: 175295650 examples [2:31:01, 249523.85 examples/s]
Generating train split: 175322210 examples [2:31:01, 254282.97 examples/s]
Generating train split: 175347948 examples [2:31:01, 255188.71 examples/s]
Generating train split: 175373504 examples [2:31:01, 252089.47 examples/s]
Generating train split: 175399587 examples [2:31:01, 254613.49 examples/s]
Generating train split: 175426204 examples [2:31:01, 257977.26 examples/s]
Generating train split: 175452027 examples [2:31:01, 257502.09 examples/s]
Generating train split: 175478076 examples [2:31:01, 258350.62 examples/s]
Generating train split: 175506463 examples [2:31:01, 265916.84 examples/s]
Generating train split: 175533443 examples [2:31:01, 267067.50 examples/s]
Generating train split: 175560158 examples [2:31:02, 266382.51 examples/s]
Generating train split: 175586832 examples [2:31:02, 266180.22 examples/s]
Generating train split: 175614822 examples [2:31:02, 270199.14 examples/s]
Generating train split: 175641891 examples [2:31:02, 269957.43 examples/s]
Generating train split: 175669261 examples [2:31:02, 271001.01 examples/s]
Generating train split: 175698001 examples [2:31:02, 275875.24 examples/s]
Generating train split: 175726109 examples [2:31:02, 277420.21 examples/s]
Generating train split: 175753900 examples [2:31:02, 277400.58 examples/s]
Generating train split: 175781999 examples [2:31:02, 278395.82 examples/s]
Generating train split: 175809863 examples [2:31:02, 277419.33 examples/s]
Generating train split: 175837784 examples [2:31:03, 277856.35 examples/s]
Generating train split: 175866876 examples [2:31:03, 281674.05 examples/s]
Generating train split: 175896439 examples [2:31:03, 285810.27 examples/s]
Generating train split: 175925091 examples [2:31:03, 285944.53 examples/s]
Generating train split: 175953952 examples [2:31:03, 286692.03 examples/s]
Generating train split: 175985451 examples [2:31:03, 295093.81 examples/s]
Generating train split: 176014963 examples [2:31:03, 286589.22 examples/s]
Generating train split: 176043679 examples [2:31:03, 230833.69 examples/s]
Generating train split: 176073408 examples [2:31:03, 247538.34 examples/s]
Generating train split: 176104939 examples [2:31:04, 265445.93 examples/s]
Generating train split: 176137762 examples [2:31:04, 282602.39 examples/s]
Generating train split: 176169505 examples [2:31:04, 292321.78 examples/s]
Generating train split: 176202254 examples [2:31:04, 302307.42 examples/s]
Generating train split: 176235477 examples [2:31:04, 311002.12 examples/s]
Generating train split: 176269206 examples [2:31:04, 318699.84 examples/s]
Generating train split: 176303673 examples [2:31:04, 326302.57 examples/s]
Generating train split: 176338944 examples [2:31:04, 334069.50 examples/s]
Generating train split: 176373744 examples [2:31:04, 338194.42 examples/s]
Generating train split: 176409111 examples [2:31:04, 342762.11 examples/s]
Generating train split: 176444037 examples [2:31:05, 344693.63 examples/s]
Generating train split: 176478591 examples [2:31:05, 344746.77 examples/s]
Generating train split: 176513729 examples [2:31:05, 346637.08 examples/s]
Generating train split: 176550112 examples [2:31:05, 351692.23 examples/s]
Generating train split: 176586025 examples [2:31:05, 353792.22 examples/s]
Generating train split: 176622894 examples [2:31:05, 358110.28 examples/s]
Generating train split: 176660738 examples [2:31:05, 364116.16 examples/s]
Generating train split: 176699710 examples [2:31:05, 371719.87 examples/s]
Generating train split: 176736917 examples [2:31:05, 368581.29 examples/s]
Generating train split: 176746022 examples [2:31:06, 19495.06 examples/s] 
Unable to verify splits sizes.
Dataset webdataset downloaded and prepared to /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f. Subsequent calls will reuse this data.
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
Found cached dataset webdataset (/fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f)
Loading Dataset info from /fsx_0/user/zhaojiang/wb/webdataset/default-5e4e9de28fd39dca/0.0.0/e9ef0843eead451e800ef3bd9a9ee86b731520f88aa20be2d598ddfeef5b3f7f
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
Using auto half precision backend
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py:1616: FutureWarning: `tokenizer` is deprecated and will be removed in version 5.0.0 for `LLaVATrainer.__init__`. Use `processing_class` instead.
  trainer = LLaVATrainer(
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
***** Running training *****
  Num examples = 194,420,624
  Num Epochs = 3
  Instantaneous batch size per device = 8
  Total train batch size (w. parallel, distributed & accumulation) = 1,024
  Gradient Accumulation steps = 1
  Total optimization steps = 569,592
  Number of trainable parameters = 1,365,239,712
Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"
wandb: Currently logged in as: jchen169 to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
wandb: Using wandb-core as the SDK backend.  Please refer to https://wandb.me/wandb-core for more information.
wandb: Tracking run with wandb version 0.19.6
wandb: Run data is saved locally in /opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/wandb/run-20250217_072243-8pje4n6a
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run qwen-vl-diff-clip-16-nodes_early_pool2d_4
wandb: ⭐️ View project at https://wandb.ai/jchen169/huggingface
wandb: 🚀 View run at https://wandb.ai/jchen169/huggingface/runs/8pje4n6a

  0%|          | 0/569592 [00:00<?, ?it/s]
  0%|          | 1/569592 [00:35<5558:47:02, 35.13s/it]
                                                       

  0%|          | 1/569592 [00:49<5558:47:02, 35.13s/it]
  0%|          | 2/569592 [00:50<3748:13:49, 23.69s/it]
                                                       

  0%|          | 2/569592 [00:50<3748:13:49, 23.69s/it]
  0%|          | 3/569592 [00:51<2108:14:30, 13.32s/it]
                                                       

  0%|          | 3/569592 [00:51<2108:14:30, 13.32s/it]
  0%|          | 4/569592 [00:52<1335:02:17,  8.44s/it]
                                                       

  0%|          | 4/569592 [00:52<1335:02:17,  8.44s/it]
  0%|          | 5/569592 [00:53<909:33:58,  5.75s/it] 
                                                      

  0%|          | 5/569592 [00:53<909:33:58,  5.75s/it]
  0%|          | 6/569592 [00:54<653:00:50,  4.13s/it]
                                                      

  0%|          | 6/569592 [00:54<653:00:50,  4.13s/it]
  0%|          | 7/569592 [00:55<489:33:08,  3.09s/it]
                                                      

  0%|          | 7/569592 [00:55<489:33:08,  3.09s/it]
  0%|          | 8/569592 [00:56<380:04:25,  2.40s/it]
                                                      

  0%|          | 8/569592 [00:56<380:04:25,  2.40s/it]
  0%|          | 9/569592 [00:57<306:37:08,  1.94s/it]
                                                      

  0%|          | 9/569592 [00:57<306:37:08,  1.94s/it]
  0%|          | 10/569592 [01:03<498:10:15,  3.15s/it]
                                                       

  0%|          | 10/569592 [01:03<498:10:15,  3.15s/it]
  0%|          | 11/569592 [01:04<404:41:50,  2.56s/it]
                                                       

  0%|          | 11/569592 [01:04<404:41:50,  2.56s/it]
  0%|          | 12/569592 [01:05<326:48:19,  2.07s/it]
                                                       

  0%|          | 12/569592 [01:05<326:48:19,  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (99899280 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2.07s/it]
  0%|          | 13/569592 [01:06<285:00:29,  1.80s/it]
                                                       

  0%|          | 13/569592 [01:06<285:00:29,  1.80s/it]
  0%|          | 14/569592 [01:14<552:47:37,  3.49s/it]
                                                       

  0%|          | 14/569592 [01:14<552:47:37,  3.49s/it]
  0%|          | 15/569592 [01:15<433:48:09,  2.74s/it]
                                                       

  0%|          | 15/569592 [01:15<433:48:09,  2.74s/it]
  0%|          | 16/569592 [01:16<347:39:15,  2.20s/it]
                                                       

  0%|          | 16/569592 [01:16<347:39:15,  2.20s/it]
  0%|          | 17/569592 [01:17<330:33:27,  2.09s/it]
                                                       

  0%|          | 17/569592 [01:17<330:33:27,  2.09s/it]
  0%|          | 18/569592 [01:24<540:32:22,  3.42s/it]
                                                       

  0%|          | 18/569592 [01:24<540:32:22,  3.42s/it]
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  0%|          | 19/569592 [01:25<425:20:32,  2.69s/it]
                                                       

  0%|          | 19/569592 [01:25<425:20:32,  2.69s/it]
  0%|          | 20/569592 [01:26<341:37:25,  2.16s/it]
                                                       

  0%|          | 20/569592 [01:26<341:37:25,  2.16s/it]
  0%|          | 21/569592 [01:27<298:00:39,  1.88s/it]
                                                       

  0%|          | 21/569592 [01:27<298:00:39,  1.88s/it]
  0%|          | 22/569592 [01:33<511:43:00,  3.23s/it]
                                                       

  0%|          | 22/569592 [01:33<511:43:00,  3.23s/it]
  0%|          | 23/569592 [01:34<404:25:06,  2.56s/it]
                                                       

  0%|          | 23/569592 [01:34<404:25:06,  2.56s/it]
  0%|          | 24/569592 [01:36<352:31:37,  2.23s/it]
                                                       

  0%|          | 24/569592 [01:36<352:31:37,  2.23s/it]
  0%|          | 25/569592 [01:37<317:08:40,  2.00s/it]
                                                       

  0%|          | 25/569592 [01:37<317:08:40,  2.00s/it]
  0%|          | 26/569592 [01:45<562:56:43,  3.56s/it]
                                                       

  0%|          | 26/569592 [01:45<562:56:43,  3.56s/it]
  0%|          | 27/569592 [01:46<443:53:49,  2.81s/it]
                                                       

  0%|          | 27/569592 [01:46<443:53:49,  2.81s/it]
  0%|          | 28/569592 [01:47<370:49:12,  2.34s/it]
                                                       

  0%|          | 28/569592 [01:47<370:49:12,  2.34s/it]
  0%|          | 29/569592 [01:48<304:55:53,  1.93s/it]
                                                       

  0%|          | 29/569592 [01:48<304:55:53,  1.93s/it]
  0%|          | 30/569592 [01:55<566:25:24,  3.58s/it]
                                                       

  0%|          | 30/569592 [01:55<566:25:24,  3.58s/it]
  0%|          | 31//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
569592 [01:56<443:57:54,  2.81s/it]
                                                       

  0%|          | 31/569592 [01:56<443:57:54,  2.81s/it]
  0%|          | 32/569592 [01:57<355:03:16,  2.24s/it]
                                                       

  0%|          | 32/569592 [01:57<355:03:16,  2.24s/it]
  0%|          | 33/569592 [01:58<294:48:36,  1.86s/it]
                                                       

  0%|          | 33/569592 [01:58<294:48:36,  1.86s/it]
  0%|          | 34/569592 [02:06<565:51:07,  3.58s/it]
                                                       

  0%|          | 34/569592 [02:06<565:51:07,  3.58s/it]
  0%|          | 35/569592 [02:07<441:22:35,  2.79s/it]
                                                       

  0%|          | 35/569592 [02:07<441:22:35,  2.79s/it]
  0%|          | 36/569592 [02:08<355:40:17,  2.25s/it]
                                                       

  0%|          | 36/569592 [02:08<355:40:17,  2.25s/it]
  0%|          | 37/569592 [02:09<301:39:37,  1.91s/it]
                                                       

  0%|          | 37/569592 [02:09<301:39:37,  1.91s/it]
  0%|          | 38/569592 [02:17<617:11:02,  3.90s/it]
                                                       

  0%|          | 38/569592 [02:17<617:11:02,  3.90s/it]
  0%|          | 39/569592 [02:18<478:02:06,  3.02s/it]
                                                       

  0%|          | 39/569592 [02:18<478:02:06,  3.02s/it]
  0%|          | 40/569592 [02:19<378:18:39,  2.39s/it]
                                                       

  0%|          | 40/569592 [02:19<378:18:39,  2.39s/it]
  0%|          | 41/569592 [02:20<317:22:33,  2.01s/it]
                                                       

  0%|          | 41/569592 [02:20<317:22:33,  2.01s/it]
  0%|          | 42/569592 [02:27<543:59:18,  3.44s/it]
                                                       

  0%|          | 42/569592 [02:27<543:59:18,  3.44s/it]
  0%|          | 43/569592 [02:28<429:44:29,  2.72s/it]
                                                       

  0%|          | 43/569592 [02:28<429:44:29,  2.72s/it]
  0%|          | 44/569592 [02:29<346:11:15,  2.19s/it]
                                                       

  0%|          | 44/569592 [02:29<346:11:15,  2.19s/it]
  0%|          | 45/569592 [02:30<288:13:39,  1.82s/it]
                                                       

  0%|          | 45/569592 [02:30<288:13:39,  1.82s/it]
  0%|          | 46/569592 [02:37<527:19:01,  3.33s/it]
                                                       

  0%|          | 46/569592 [02:37<527:19:01,  3.33s/it]
  0%|          | 47/569592 [02:38<414:18:59,  2.62s/it]
                                                       

  0%|          | 47/569592 [02:38<414:18:59,  2.62s/it]
  0%|          | 48/569592 [02:39<335:39:53,  2.12s/it]
                                                       

  0%|          | 48/569592 [02:39<335:39:53,  2.12s/it]
  0%|          | 49/569592 [02:40<281:25:56,  1.78s/it]
                                                       

  0%|          | 49/569592 [02:40<281:25:56,  1.78s/it]
  0%|          | 50/569592 [02:47<532:55:15,  3.37s/it]
                                                       

  0%|          | 50/569592 [02:47<532:55:15,  3.37s/it]
  0%|          | 51/569592 [02:48<418:34:45,  2.65s/it]
                                                       

  0%|          | 51/569592 [02:48<418:34:45,  2.65s/it]
  0%|          | 52/569592 [02:49<337:35:57,  2.13s/it]
                                                       

  0%|          | 52/569592 [02:49<337:35:57,  2.13s/it]
  0%|          | 53/569592 [02:50<281:50:12,  1.78s/it]
                                                       

  0%|          | 53/569592 [02:50<281:50:12,  1.78s/it]
  0%|          | 54/569592 [02:57<545:08:10,  3.45s/it]
                                                       

  0%|          | 54/569592 [02:57<545:08:10,  3.45s/it]
  0%|          | 55/569592 [02:58<425:36:01,  2.69s/it]
                                                       

  0%|          | 55/569592 [02:58<425:36:01,  2.69s/it]
  0%|          | 56/569592 [02:59<345:36:37,  2.18s/it]
                                                       

  0%|          | 56/569592 [02:59<345:36:37,  2.18s/it]
  0%|          | 57/569592 [03:00<288:53:55,  1.83s/it]
                                                       

  0%|          | 57/569592 [03:00<288:53:55,  1.83s/it]
  0%|          | 58/569592 [03:07<537:31:20,  3.40s/it]
                                                       

  0%|          | 58/569592 [03:07<537:31:20,  3.40s/it]
  0%|          | 59/569592 [03:08<419:45:09,  2.65s/it]
                                                       

  0%|          | 59/569592 [03:08<419:45:09,  2.65s/it]
  0%|          | 60/569592 [03:09<338:16:47,  2.14s/it]
                                                       

  0%|          | 60/569592 [03:09<338:16:47,  2.14s/it]
  0%|          | 61/569592 [03:10<283:10:29,  1.79s/it]
                                                       

  0%|          | 61/569592 [03:10<283:10:29,  1.79s/it]
  0%|          | 62/569592 [03:18<559:48:00,  3.54s/it]
                                                       

  0%|          | 62/569592 [03:18<559:48:00,  3.54s/it]
  0%|          | 63/569592 [03:18<434:37:48,  2.75s/it]
                                                       

  0%|          | 63/569592 [03:18<434:37:48,  2.75s/it]
  0%|          | 64/569592 [03:19<348:41:34,  2.20s/it]
                                                       

  0%|          | 64/569592 [03:19<348:41:34,  2.20s/it]
  0%|          | 65/569592 [03:20<290:36:42,  1.84s/it]
                                                       

  0%|          | 65/569592 [03:20<290:36:42,  1.84s/it]
  0%|          | 66/569592 [03:27<541:25:38,  3.42s/it]
                                                       

  0%|          | 66/569592 [03:27<541:25:38,  3.42s/it]
  0%|          | 67/569592 [03:28<423:47:31,  2.68s/it]
                                                       

  0%|          | 67/569592 [03:28<423:47:31,  2.68s/it]
  0%|          | 68/569592 [03:29<341:33:15,  2.16s/it]
                                                       

  0%|          | 68/569592 [03:29<341:33:15,  2.16s/it]
  0%|          | 69/569592 [03:30<283:50:49,  1.79s/it]
                                                       

  0%|          | 69/569592 [03:30<283:50:49,  1.79s/it]
  0%|          | 70/569592 [03:36<486:07:55,  3.07s/it]
                                                       

  0%|          | 70/569592 [03:36<486:07:55,  3.07s/it]
  0%|          | 71/569592 [03:37<386:16:17,  2.44s/it]
                                                       

  0%|          | 71/569592 [03:37<386:16:17,  2.44s/it]
  0%|          | 72/569592 [03:39<367:07:07,  2.32s/it]
                                                       

  0%|          | 72/569592 [03:39<367:07:07,  2.32s/it]
  0%|          | 73/569592 [03:40<302:28:22,  1.91s/it]
                                                       

  0%|          | 73/569592 [03:40<302:28:22,  1.91s/it]
  0%|          | 74/569592 [03:47<517:27:11,  3.27s/it]
                                                       

  0%|          | 74/569592 [03:47<517:27:11,  3.27s/it]
  0%|          | 75/569592 [03:48<406:38:31,  2.57s/it]
                                                       

  0%|          | 75/569592 [03:48<406:38:31,  2.57s/it]
  0%|          | 76/569592 [03:51<424:35:28,  2.68s/it]
                                                       

  0%|          | 76/569592 [03:51<424:35:28,  2.68s/it]
  0%|          | 77/569592 [03:52<341:52:09,  2.16s/it]
                                                       

  0%|          | 77/569592 [03:52<341:52:09,  2.16s/it]
  0%|          | 78/569592 [03:56<433:31:12,  2.74s/it]
                                                       

  0%|          | 78/569592 [03:56<433:31:12,  2.74s/it]
  0%|          | 79/569592 [03:57<350:38:30,  2.22s/it]
                                                       

  0%|          | 79/569592 [03:57<350:38:30,  2.22s/it]
  0%|          | 80/569592 [03:59<371:16:00,  2.35s/it]
                                                       

  0%|          | 80/569592 [04:02<371:16:00,  2.35s/it]
  0%|          | 81/569592 [04:03<452:34:09,  2.86s/it]
                                                       

  0%|          | 81/569592 [04:03<452:34:09,  2.86s/it]
  0%|          | 82/569592 [04:06<429:24:32,  2.71s/it]
                                                       

  0%|          | 82/569592 [04:06<429:24:32,  2.71s/it]
  0%|          | 83/569592 [04:07<344:25:02,  2.18s/it]
                                                       

  0%|          | 83/569592 [04:07<344:25:02,  2.18s/it]
  0%|          | 84/569592 [04:10<399:57:22,  2.53s/it]
                                                       

  0%|          | 84/569592 [04:10<399:57:22,  2.53s/it]
  0%|          | 85/569592 [04:11<329:22:18,  2.08s/it]
                                                      /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95787276 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 

  0%|          | 85/569592 [04:11<329:22:18,  2.08s/it]
  0%|          | 86/569592 [04:15<418:20:26,  2.64s/it]
                                                       

  0%|          | 86/569592 [04:15<418:20:26,  2.64s/it]
  0%|          | 87/569592 [04:16<342:31:10,  2.17s/it]
                                                       

  0%|          | 87/569592 [04:16<342:31:10,  2.17s/it]
  0%|          | 88/569592 [04:20<436:22:51,  2.76s/it]
                                                       

  0%|          | 88/569592 [04:20<436:22:51,  2.76s/it]
  0%|          | 89/569592 [04:21<351:59:42,  2.23s/it]
                                                       

  0%|          | 89/569592 [04:21<351:59:42,  2.23s/it]
  0%|          | 90/569592 [04:25<429:28:52,  2.71s/it]
                                                       

  0%|          | 90/569592 [04:25<429:28:52,  2.71s/it]
  0%|          | 91/569592 [04:26<347:28:25,  2.20s/it]
                                                       

  0%|          | 91/569592 [04:26<347:28:25,  2.20s/it]
  0%|          | 92/569592 [04:30<450:21:14,  2.85s/it]
                                                       

  0%|          | 92/569592 [04:30<450:21:14,  2.85s/it]
  0%|          | 93/569592 [04:31<362:17:44,  2.29s/it]
                                                       

  0%|          | 93/569592 [04:31<362:17:44,  2.29s/it]
  0%|          | 94/569592 [04:35<426:33:56,  2.70s/it]
                                                       

  0%|          | 94/569592 [04:35<426:33:56,  2.70s/it]
  0%|          | 95/569592 [04:36<341:46:05,  2.16s/it]
                                                       

  0%|          | 95/569592 [04:36<341:46:05,  2.16s/it]
  0%|          | 96/569592 [04:40<451:31:26,  2.85s/it]
                                                       

  0%|          | 96/569592 [04:40<451:31:26,  2.85s/it]
  0%|          | 97/569592 [04:41<363:51:10,  2.30s/it]
                                                       

  0%|          | 97/569592 [04:41<363:51:10,  2.30s/it]
  0%|          | 98/569592 [04:46<478:34:06,  3.03s/it]
                                                       

  0%|          | 98/569592 [04:46<478:34:06,  3.03s/it]
  0%|          | 99/569592 [04:47<378:03:05,  2.39s/it]
                                                       

  0%|          | 99/569592 [04:47<378:03:05,  2.39s/it]
  0%|          | 100/569592 [04:50<420:03:04,  2.66s/it]
                                                        

  0%|          | 100/569592 [04:50<420:03:04,  2.66s/it]
  0%|          | 101/569592 [04:51<343:06:18,  2.17s/it]
                                                        

  0%|          | 101/569592 [04:51<343:06:18,  2.17s/it]
  0%|          | 102/569592 [04:55<431:04:40,  2.73s/it]
                                                        

  0%|          | 102/569592 [04:55<431:04:40,  2.73s/it]
  0%|          | 103/569592 [04:56<347:21:43,  2.20s/it]
                                                        

  0%|          | 103/569592 [04:56<347:21:43,  2.20s/it]
  0%|          | 104/569592 [05:00<435:16:14,  2.75s/it]
                                                        

  0%|          | 104/569592 [05:00<435:16:14,  2.75s/it]
  0%|          | 105/569592 [05:01<348:52:11,  2.21s/it]
                                                        

  0%|          | 105/569592 [05:01<348:52:11,  2.21s/it]
  0%|          | 106/569592 [05:06<454:45:05,  2.87s/it]
                                                        

  0%|          | 106/569592 [05:06<454:45:05,  2.87s/it]
  0%|          | 107/569592 [05:07<362:33:00,  2.29s/it]
                                                        

  0%|          | 107/569592 [05:07<362:33:00,  2.29s/it]
  0%|          | 108/569592 [05:09<374:59:17,  2.37s/it]
                                                        

  0%|          | 108/569592 [05:09<374:59:17,  2.37s/it]
  0%|          | 109/569592 [05:11<346:03:49,  2.19s/it]
                                                        

  0%|          | 109/569592 [05:11<346:03:49,  2.19s/it]
  0%|          | 110/569592 [05:16<479:55:43,  3.03s/it]
                                                        

  0%|          | 110/569592 [05:16<479:55:43,  3.03s/it]
  0%|          | 111/569592 [05:17<381:11:33,  2.41s/it]
                                                        

  0%|          | 111/569592 [05:17<381:11:33,  2.41s/it]
  0%|          | 112/569592 [05:19<383:21:48,  2.42s/it]
                                                        

  0%|          | 112/569592 [05:19<383:21:48,  2.42s/it]
  0%|          | 113/569592 [05:22<397:15:05,  2.51s/it]
                                                        

  0%|          | 113/569592 [05:22<397:15:05,  2.51s/it]
  0%|          | 114/569592 [05:29<584:17:02,  3.69s/it]
                                                        

  0%|          | 114/569592 [05:29<584:17:02,  3.69s/it]
  0%|          | 115/569592 [05:34<679:31:58,  4.30s/it]
                                                        

/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101754940 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  0%|          | 115/569592 [05:34<679:31:58,  4.30s/it]
  0%|          | 116/569592 [05:40<735:18:20,  4.65s/it]
                                                        

  0%|          | 116/569592 [05:40<735:18:20,  4.65s/it]
  0%|          | 117/569592 [05:46<797:57:54,  5.04s/it]
                                                        

  0%|          | 117/569592 [05:46<797:57:54,  5.04s/it]
  0%|          | 118/569592 [05:47<601:06:42,  3.80s/it]
                                                        

  0%|          | 118/569592 [05:47<601:06:42,  3.80s/it]
  0%|          | 119/569592 [05:48<463:58:06,  2.93s/it]
                                                        

  0%|          | 119/569592 [05:48<463:58:06,  2.93s/it]
  0%|          | 120/569592 [05:49<371:29:51,  2.35s/it]
                                                        

  0%|          | 120/569592 [05:49<371:29:51,  2.35s/it]
  0%|          | 121/569592 [05:50<308:57:03,  1.95s/it]
                                                        

  0%|          | 121/569592 [05:50<308:57:03,  1.95s/it]
  0%|          | 122/569592 [05:51<263:32:16,  1.67s/it]
                                                        

  0%|          | 122/569592 [05:51<263:32:16,  1.67s/it]
  0%|          | 123/569592 [05:52<230:10:58,  1.46s/it]
                                                        

  0%|          | 123/569592 [05:52<230:10:58,  1.46s/it]
  0%|          | 124/569592 [05:52<206:27:37,  1.31s/it]
                                                        

  0%|          | 124/569592 [05:52<206:27:37,  1.31s/it]
  0%|          | 125/569592 [05:53<189:27:12,  1.20s/it]
                                                        

  0%|          | 125/569592 [05:53<189:27:12,  1.20s/it]
  0%|          | 126/569592 [05:59<420:38:55,  2.66s/it]
                                                        

  0%|          | 126/569592 [06:00<420:38:55,  2.66s/it]
  0%|          | 127/569592 [06:01<342:57:25,  2.17s/it]
                                                        

  0%|          | 127/569592 [06:01<342:57:25,  2.17s/it]
  0%|          | 128/569592 [06:03<354:01:27,  2.24s/it]
                                                        

  0%|          | 128/569592 [06:03<354:01:27,  2.24s/it]
  0%|          | 129/569592 [06:04<300:20:05,  1.90s/it]
                                                        

  0%|          | 129/569592 [06:04<300:20:05,  1.90s/it]
  0%|          | 130/569592 [06:09<453:50:31,  2.87s/it]
                                                        

  0%|          | 130/569592 [06:09<453:50:31,  2.87s/it]
  0%|          | 131/569592 [06:10<372:24:53,  2.35s/it]
                                                        

  0%|          | 131/569592 [06:10<372:24:53,  2.35s/it]
  0%|          | 132/569592 [06:13<383:29:15,  2.42s/it]
                                                        

  0%|          | 132/569592 [06:13<383:29:15,  2.42s/it]
  0%|          | 133/569592 [06:14<314:09:09,  1.99s/it]
                                                        

  0%|          | 133/569592 [06:14<314:09:09,  1.99s/it]
  0%|          | 134/569592 [06:20<510:36:45,  3.23s/it]
                                                        

  0%|          | 134/569592 [06:20<510:36:45,  3.23s/it]
  0%|          | 135/569592 [06:21<402:22:37,  2.54s/it]
                                                        

  0%|          | 135/569592 [06:21<402:22:37,  2.54s/it]
  0%|          | 136/569592 [06:23<356:21:20,  2.25s/it]
                                                        

  0%|          | 136/569592 [06:23<356:21:20,  2.25s/it]
  0%|          | 137/569592 [06:23<294:55:18,  1.86s/it]
                                                        

  0%|          | 137/569592 [06:23<294:55:18,  1.86s/it]
  0%|          | 138/569592 [06:30<515:22:04,  3.26s/it]
                                                        

  0%|          | 138/569592 [06:30<515:22:04,  3.26s/it]
  0%|          | 139/569592 [06:31<412:10:33,  2.61s/it]
                                                        

  0%|          | 139/569592 [06:31<412:10:33,  2.61s/it]
  0%|          | 140/569592 [06:32<349:50:01,  2.21s/it]
                                                        

  0%|          | 140/569592 [06:32<349:50:01,  2.21s/it]
  0%|          | 141/569592 [06:33<289:55:21,  1.83s/it]
                                                        

  0%|          | 141/569592 [06:33<289:55:21,  1.83s/it]
  0%|          | 142/569592 [06:40<520:41:29,  3.29s/it]
                                                        

  0%|          | 142/569592 [06:40<520:41:29,  3.29s/it]
  0%|          | 143/569592 [06:42<461:18:19,  2.92s/it]
                                                        

  0%|          | 143/569592 [06:42<461:18:19,  2.92s/it]
  0%|          | 144/569592 [06:43<371:22:43,  2.35s/it]
                                                        

  0%|          | 144/569592 [06:43<371:22:43,  2.35s/it]
  0%|          | 145/569592 [06:44<306:14:19,  1.94s/it]
                                                        

  0%|          | 145/569592 [06:44<306:14:19,  1.94s/it]
  0%|          | 146/569592 [06:51<535:16:03,  3.38s/it]
                                                        

  0%|          | 146/569592 [06:51<535:16:03,  3.38s/it]
  0%|          | 147/569592 [06:53<460:53:42,  2.91s/it]
                                                        

  0%|          | 147/569592 [06:53<460:53:42,  2.91s/it]
  0%|          | 148/569592 [06:54<369:24:35,  2.34s/it]
                                                        

  0%|          | 148/569592 [06:54<369:24:35,  2.34s/it]
  0%|          | 149/569592 [06:55<305:31:00,  1.93s/it]
                                                        

  0%|          | 149/569592 [06:55<305:31:00,  1.93s/it]
  0%|          | 150/569592 [07:00<455:55:06,  2.88s/it]
                                                        

  0%|          | 150/569592 [07:00<455:55:06,  2.88s/it]
  0%|          | 151/569592 [07:03<472:24:38,  2.99s/it]
                                                        

  0%|          | 151/569592 [07:03<472:24:38,  2.99s/it]
  0%|          | 152/569592 [07:04<375:17:13,  2.37s/it]
                                                        

  0%|          | 152/569592 [07:04<375:17:13,  2.37s/it]
  0%|          | 153/569592 [07:05<309:51:55,  1.96s/it]
                                                        

  0%|          | 153/569592 [07:05<309:51:55,  1.96s/it]
  0%|          | 154/569592 [07:10<450:32:41,  2.85s/it]
                                                        

  0%|          | 154/569592 [07:10<450:32:41,  2.85s/it]
  0%|          | 155/569592 [07:14<505:18:28,  3.19s/it]
                                                        

  0%|          | 155/569592 [07:14<505:18:28,  3.19s/it]
  0%|          | 156/569592 [07:15<398:45:36,  2.52s/it]
                                                        

  0%|          | 156/569592 [07:15<398:45:36,  2.52s/it]
  0%|          | 157/569592 [07:16<340:35:49,  2.15s/it]
  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90761022 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                      

  0%|          | 157/569592 [07:16<340:35:49,  2.15s/it]
  0%|          | 158/569592 [07:20<408:33:23,  2.58s/it]
                                                        

  0%|          | 158/569592 [07:20<408:33:23,  2.58s/it]
  0%|          | 159/569592 [07:23<454:06:32,  2.87s/it]
                                                        

  0%|          | 159/569592 [07:23<454:06:32,  2.87s/it]
  0%|          | 160/569592 [07:24<364:02:24,  2.30s/it]
                                                        

  0%|          | 160/569592 [07:24<364:02:24,  2.30s/it]
  0%|          | 161/569592 [07:25<300:56:22,  1.90s/it]
                                                        

  0%|          | 161/569592 [07:25<300:56:22,  1.90s/it]
  0%|          | 162/569592 [07:30<454:44:58,  2.87s/it]
                                                        

  0%|          | 162/569592 [07:30<454:44:58,  2.87s/it]
  0%|          | 163/569592 [07:34<495:26:05,  3.13s/it]
                                                        

  0%|          | 163/569592 [07:34<495:26:05,  3.13s/it]
  0%|          | 164/569592 [07:35<393:59:17,  2.49s/it]
                                                        

  0%|          | 164/569592 [07:35<393:59:17,  2.49s/it]
  0%|          | 165/569592 [07:36<347:30:18,  2.20s/it]
                                                        

  0%|          | 165/569592 [07:36<347:30:18,  2.20s/it]
  0%|          | 166/569592 [07:40<433:59:36,  2.74s/it]
                                                        

  0%|          | 166/569592 [07:41<433:59:36,  2.74s/it]
  0%|          | 167/569592 [07:43<442:44:30,  2.80s/it]
                                                        

  0%|          | 167/569592 [07:43<442:44:30,  2.80s/it]
  0%|          | 168/569592 [07:44<354:40:53,  2.24s/it]
                                                        

  0%|          | 168/569592 [07:44<354:40:53,  2.24s/it]
  0%|          | 169/569592 [07:45<300:37:16,  1.90s/it]
                                                        

  0%|          | 169/569592 [07:45<300:37:16,  1.90s/it]
  0%|          | 170/569592 [07:50<401:33:56,  2.54s/it]
                                                        

  0%|          | 170/569592 [07:50<401:33:56,  2.54s/it]
  0%|          | 171/569592 [07:53<462:22:49,  2.92s/it]
                                                        

  0%|          | 171/569592 [07:53<462:22:49,  2.92s/it]
  0%|          | 172/569592 [07:54<370:45:03,  2.34s/it]
                                                        

  0%|          | 172/569592 [07:54<370:45:03,  2.34s/it]
  0%|          | 173/569592 [07:57<369:25:33,  2.34s/it]
                                                        

  0%|          | 173/569592 [07:57<369:25:33,  2.34s/it]
  0%|          | 174/569592 [08:00<396:43:35,  2.51s/it]
                                                        

  0%|          | 174/569592 [08:00<396:43:35,  2.51s/it]
  0%|          | 175/569592 [08:04<465:35:51,  2.94s/it]
                                                        

  0%|          | 175/569592 [08:04<465:35:51,  2.94s/it]
  0%|          | 176/569592 [08:04<370:25:59,  2.34s/it]
                                                        

  0%|          | 176/569592 [08:04<370:25:59,  2.34s/it]
  0%|          | 177/569592 [08:07<357:18:39,  2.26s/it]
                                                        

  0%|          | 177/569592 [08:07<357:18:39,  2.26s/it]
  0%|          | 178/569592 [08:10<432:13:41,  2.73s/it]
                                                        

  0%|          | 178/569592 [08:10<432:13:41,  2.73s/it]
  0%|          | 179/569592 [08:14<463:23:15,  2.93s/it]
                                                        

  0%|          | 179/569592 [08:14<463:23:15,  2.93s/it]
  0%|          | 180/569592 [08:15<369:08:38,  2.33s/it]
                                                        

  0%|          | 180/569592 [08:15<369:08:38,  2.33s/it]
  0%|          | 181/569592 [08:16<303:51:48,  1.92s/it]
                                                        

  0%|          | 181/569592 [08:16<303:51:48,  1.92s/it]
  0%|          | 182/569592 [08:21<464:03:06,  2.93s/it]
                                                        

  0%|          | 182/569592 [08:21<464:03:06,  2.93s/it]
  0%|          | 183/569592 [08:24<472:34:14,  2.99s/it]
                                                        

  0%|          | 183/569592 [08:24<472:34:14,  2.99s/it]
  0%|          | 184/569592 [08:25<374:57:09,  2.37s/it]
                                                        

  0%|          | 184/569592 [08:25<374:57:09,  2.37s/it]
  0%|          | 185/569592 [08:26<324:35:41,  2.05s/it]
                                                        

  0%|          | 185/569592 [08:26<324:35:41,  2.05s/it]
  0%|          | 186/569592 [08:29<366:43:12,  2.32s/it]
                                                        

  0%|          | 186/569592 [08:29<366:43:12,  2.32s/it]
  0%|          | 187/569592 [08:33<455:11:28,  2.88s/it]
                                                        

  0%|          | 187/569592 [08:33<455:11:28,  2.88s/it]
  0%|          | 188/569592 [08:34<369:54:56,  2.34s/it]
                                                        

  0%|          | 188/569592 [08:35<369:54:56,  2.34s/it]
  0%|          | 189/569592 [08:35<304:30:37,  1.93s/it]
                                                        

  0%|          | 189/569592 [08:35<304:30:37,  1.93s/it]
  0%|          | 190/569592 [08:39<399:15:38,  2.52s/it]
                                                        

  0%|          | 190/569592 [08:39<399:15:38,  2.52s/it]
  0%|          | 191/569592 [08:44<494:09:41,  3.12s/it]
                                                        

  0%|          | 191/569592 [08:44<494:09:41,  3.12s/it]
  0%|          | 192/569592 [08:45<391:18:32,  2.47s/it]
                                                        

  0%|          | 192/569592 [08:45<391:18:32,  2.47s/it]
  0%|          | 193/569592 [08:46<321:13:46,  2.03s/it]
                                                        

  0%|          | 193/569592 [08:46<321:13:46,  2.03s/it]
  0%|          | 194/569592 [08:50<398:10:46,  2.52s/it]
                                                        

  0%|          | 194/569592 [08:50<398:10:46,  2.52s/it]
  0%|          | 195/569592 [08:54<475:18:29,  3.01s/it]
                                                        

  0%|          | 195/569592 [08:54<475:18:29,  3.01s/it]
  0%|          | 196/569592 [08:56<459:17:50,  2.90s/it]
                                                        

  0%|          | 196/569592 [08:56<459:17:50,  2.90s/it]
  0%|          | 197/569592 [08:57<365:30:52,  2.31s/it]
                                                        

  0%|          | 197/569592 [08:57<365:30:52,  2.31s/it]
  0%|          | 198/569592 [09:00<391:59:45,  2.48s/it]
                                                        

  0%|          | 198/569592 [09:00<391:59:45,  2.48s/it]
  0%|          | 199/569592 [09:04<452:47:20,  2.86s/it]
                                                        

  0%|          | 199/569592 [09:04<452:47:20,  2.86s/it]
  0%|          | 200/569592 [09:07<469:34:12,  2.97s/it]
                                                        

  0%|          | 200/569592 [09:07<469:34:12,  2.97s/it]
  0%|          | 201/569592 [09:08<373:07:15,  2.36s/it]
                                                        

  0%|          | 201/569592 [09:08<373:07:15,  2.36s/it]
  0%|          | 202/569592 [09:10<376:10:40,  2.38s/it]
                                                        

  0%|          | 202/569592 [09:10<376:10:40,  2.38s/it]
  0%|          | 203/569592 [09:15<457:39:03,  2.89s/it]
                                                        

  0%|          | 203/569592 [09:15<457:39:03,  2.89s/it]
  0%|          | 204/569592 [09:17<437:38:07,  2.77s/it]
                                                        

  0%|          | 204/569592 [09:17<437:38:07,  2.77s/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/it]
  0%|          | 205/569592 [09:18<350:48:54,  2.22s/it]
                                                        

  0%|          | 205/569592 [09:18<350:48:54,  2.22s/it]
  0%|          | 206/569592 [09:20<325:45:39,  2.06s/it]
                                                        

  0%|          | 206/569592 [09:20<325:45:39,  2.06s/it]
  0%|          | 207/569592 [09:24<429:59:19,  2.72s/it]
                                                        

  0%|          | 207/569592 [09:24<429:59:19,  2.72s/it]
  0%|          | 208/569592 [09:27<445:33:22,  2.82s/it]
                                                        

  0%|          | 208/569592 [09:27<445:33:22,  2.82s/it]
  0%|          | 209/569592 [09:28<357:39:22,  2.26s/it]
                                                        

  0%|          | 209/569592 [09:28<357:39:22,  2.26s/it]
  0%|          | 210/569592 [09:30<348:58:35,  2.21s/it]
                                                        

  0%|          | 210/569592 [09:30<348:58:35,  2.21s/it]
  0%|          | 211/569592 [09:33<390:04:38,  2.47s/it]
                                                        

  0%|          | 211/569592 [09:33<390:04:38,  2.47s/it]
  0%|          | 212/569592 [09:37<448:02:54,  2.83s/it]
                                                        

  0%|          | 212/569592 [09:37<448:02:54,  2.83s/it]
  0%|          | 213/569592 [09:38<358:57:07,  2.27s/it]
                                                        

  0%|          | 213/569592 [09:38<358:57:07,  2.27s/it]
  0%|          | 214/569592 [09:40<346:04:02,  2.19s/it]
                                                        

  0%|          | 214/569592 [09:40<346:04:02,  2.19s/it]
  0%|          | 215/569592 [09:44<430:15:10,  2.72s/it]
                                                        

  0%|          | 215/569592 [09:44<430:15:10,  2.72s/it]
  0%|          | 216/569592 [09:46<430:22:37,  2.72s/it]
                                                        

  0%|          | 216/569592 [09:46<430:22:37,  2.72s/it]
  0%|          | 217/569592 [09:47<345:38:03,  2.19s/it]
                                                        

  0%|          | 217/569592 [09:47<345:38:03,  2.19s/it]
  0%|          | 218/569592 [09:50<387:53:30,  2.45s/it]
                                                        

  0%|          | 218/569592 [09:50<387:53:30,  2.45s/it]
  0%|          | 219/569592 [09:53<396:53:10,  2.51s/it]
                                                        

  0%|          | 219/569592 [09:53<396:53:10,  2.51s/it]
  0%|          | 220/569592 [09:56<423:16:33,  2.68s/it]
                                                        

  0%|          | 220/569592 [09:56<423:16:33,  2.68s/it]
  0%|          | 221/569592 [09:57<354:23:50,  2.24s/it]
                                                        

  0%|          | 221/569592 [09:57<354:23:50,  2.24s/it]
  0%|          | 222/569592 [10:00<379:40:27,  2.40s/it]
                                                        

  0%|          | 222/569592 [10:00<379:40:27,  2.40s/it]
  0%|          | 223/569592 [10:04<437:29:17,  2.77s/it]
                                                        

  0%|          | 223/569592 [10:04<437:29:17,  2.77s/it]
  0%|          | 224/569592 [10:06<435:40:22,  2.75s/it]
                                                        

  0%|          | 224/569592 [10:06<435:40:22,  2.75s/it]
  0%|          | 225/569592 [10:07<350:00:06,  2.21s/it]
                                                        

  0%|          | 225/569592 [10:07<350:00:06,  2.21s/it]
  0%|          | 226/569592 [10:10<383:35:17,  2.43s/it]
                                                        

  0%|          | 226/569592 [10:10<383:35:17,  2.43s/it]
  0%|          | 227/569592 [10:13<398:24:55,  2.52s/it]
                                                        

  0%|          | 227/569592 [10:13<398:24:55,  2.52s/it]
  0%|          | 228/569592 [10:18<494:35:31,  3.13s/it]
                                                        

  0%|          | 228/569592 [10:18<494:35:31,  3.13s/it]
  0%|          | 229/569592 [10:23<591:47:09,  3.74s/it]
                                                        

  0%|          | 229/569592 [10:23<591:47:09,  3.74s/it]
  0%|          | 230/569592 [10:26<584:21:41,  3.69s/it]
                                                        

  0%|          | 230/569592 [10:26<584:21:41,  3.69s/it]
  0%|          | 231/569592 [10:31<633:47:39,  4.01s/it]
                                                        

  0%|          | 231/569592 [10:31<633:47:39,  4.01s/it]
  0%|          | 232/569592 [10:35<620:47:51,  3.93s/it]
                                                        

  0%|          | 232/569592 [10:35<620:47:51,  3.93s/it]
  0%|          | 233/569592 [10:39<639:16:31,  4.04s/it]
                                                        

  0%|          | 233/569592 [10:39<639:16:31,  4.04s/it]
  0%|          | 234/569592 [10:44<700:07:08,  4.43s/it]
                                                        

  0%|          | 234/569592 [10:44<700:07:08,  4.43s/it]
  0%|          | 235/569592 [10:48<662:31:25,  4.19s/it]
                                                        

  0%|          | 235/569592 [10:48<662:31:25,  4.19s/it]
  0%|          | 236/569592 [10:49<506:21:11,  3.20s/it]
                                                        

  0%|          | 236/569592 [10:49<506:21:11,  3.20s/it]
  0%|          | 237/569592 [10:50<397:21:23,  2.51s/it]
                                                        

  0%|          | 237/569592 [10:50<397:21:23,  2.51s/it]
  0%|          | 238/569592 [10:51<324:52:57,  2.05s/it]
                                                        

  0%|          | 238/569592 [10:51<324:52:57,  2.05s/it]
  0%|          | 239/569592 [10:52<272:12:04,  1.72s/it]
                                                        

  0%|          | 239/569592 [10:52<272:12:04,  1.72s/it]
  0%|          | 240/569592 [10:53<240:29:29,  1.52s/it]
                                                        

  0%|          | 240/569592 [10:53<240:29:29,  1.52s/it]
  0%|          | 241/569592 [10:54<213:10:28,  1.35s/it]
                                                        

  0%|          | 241/569592 [10:54<213:10:28,  1.35s/it]
  0%|          | 242/569592 [10:55<192:41:15,  1.22s/it]
                                                        

  0%|          | 242/569592 [10:55<192:41:15,  1.22s/it]
  0%|          | 243/569592 [10:57<219:17:50,  1.39s/it]
                                                        

  0%|          | 243/569592 [10:57<219:17:50,  1.39s/it]
  0%|          | 244/569592 [11:02<406:24:00,  2.57s/it]
                                                        

  0%|          | 244/569592 [11:02<406:24:00,  2.57s/it]
  0%|          | 245/569592 [11:03<336:00:52,  2.12s/it]
                                                        

  0%|          | 245/569592 [11:03<336:00:52,  2.12s/it]
  0%|          | 246/569592 [11:04<281:29:33,  1.78s/it]
                                                        

  0%|          | 246/569592 [11:04<281:29:33,  1.78s/it]
  0%|          | 247/569592 [11:06<307:18:00,  1.94s/it]
                                                        

  0%|          | 247/569592 [11:06<307:18:00,  1.94s/it]
  0%|          | 248/569592 [11:12<470:18:42,  2.97s/it]
                                                        

  0%|          | 248/569592 [11:12<470:18:42,  2.97s/it]
  0%|          | 249/569592 [11:13<387:43:46,  2.45s/it]
                                                        

  0%|          | 249/569592 [11:13<387:43:46,  2.45s/it]
  0%|          | 250/569592 [11:14<317:19:29,  2.01s/it]
                                                        

  0%|          | 250/569592 [11:14<317:19:29,  2.01s/it]
  0%|          | 251/569592 [11:17<361:23:21,  2.29s/it]
                                                        

  0%|          | 251/569592 [11:17<361:23:21,  2.29s/it]
  0%|          | 252/569592 [11:22<481:24:24,  3.04s/it]
                                                        

  0%|          | 252/569592 [11:22<481:24:24,  3.04s/it]
  0%|          | 253/569592 [11:24<432:11:20,  2.73s/it]
                                                        

  0%|          | 253/569592 [11:24<432:11:20,  2.73s/it]
  0%|          | 254/569592 [11:25<349:18:51,  2.21s/it]
                                                        

  0%|          | 254/569592 [11:25<349:18:51,  2.21s/it]
  0%|          | 255/569592 [11:27<381:11:10,  2.41s/it]
                                                        

  0%|          | 255/569592 [11:27<381:11:10,  2.41s/it]
  0%|          | 256/569592 [11:32<463:06:07,  2.93s/it]
                                                        

  0%|          | 256/569592 [11:32<463:06:07,  2.93s/it]
  0%|          | 257/569592 [11:33<402:51:10,  2.55s/it]
                                                        

  0%|          | 257/569592 [11:33<402:51:10,  2.55s/it]
  0%|          | 258/569592 [11:35<385:22:20,  2.44s/it]
                                                        

  0%|          | 258/569592 [11:35<385:22:20,  2.44s/it]
  0%|          | 259/569592 [11:38<384:14:28,  2.43s/it]
                                                        

  0%|          | 259/569592 [11:38<384:14:28,  2.43s/it]
  0%|          | 260/569592 [11:42<452:40:57,  2.86s/it]
                                                        

  0%|          | 260/569592 [11:42<452:40:57,  2.86s/it]
  0%|          | 261/569592 [11:43<383:36:32,  2.43s/it]
                                                        

  0%|          | 261/569592 [11:43<383:36:32,  2.43s/it]
  0%|          | 262/569592 [11:46<401:40:34,  2.54s/it]
                                                        

  0%|          | 262/569592 [11:46<401:40:34,  2.54s/it]
  0%|          | 263/569592 [11:49<422:23:41,  2.67s/it]
                                                        

  0%|          | 263/569592 [11:49<422:23:41,  2.67s/it]
  0%|          | 264/569592 [11:53<493:12:01,  3.12s/it]
                                                        

  0%|          | 264/569592 [11:53<493:12:01,  3.12s/it]
  0%|          | 265/569592 [11:54<407:40:42,  2.58s/it]
                                                        

  0%|          | 265/569592 [11:54<407:40:42,  2.58s/it]
  0%|          | 266/569592 [11:56<346:59:25,  2.19s/it]
                                                        

  0%|          | 266/569592 [11:56<346:59:25,  2.19s/it]
  0%|          | 267/569592 [11:58<348:26:09,  2.20s/it]
                                                        

  0%|          | 267/569592 [11:58<348:26:09,  2.20s/it]
  0%|          | 268/569592 [12:03<462:40:14,  2.93s/it]
                                                        

  0%|          | 268/569592 [12:03<462:40:14,  2.93s/it]
  0%|          | 269/569592 [12:03<368:53:49,  2.33s/it]
                                                        

  0%|          | 269/569592 [12:03<368:53:49,  2.33s/it]
  0%|          | 270/569592 [12:09<501:08:20,  3.17s/it]
                                                        

  0%|          | 270/569592 [12:09<501:08:20,  3.17s/it]
  0%|          | 271/569592 [12:10<397:54:08,  2.52s/it]
                                                        

  0%|          | 271/569592 [12:10<397:54:08,  2.52s/it]
  0%|          | 272/569592 [12:14<476:34:12,  3.01s/it]
                                                        

  0%|          | 272/569592 [12:14<476:34:12,  3.01s/it]
  0%|          | 273/569592 [12:15<384:04:05,  2.43s/it]
                                                        

  0%|          | 273/569592 [12:15<384:04:05,  2.43s/it]
  0%|          | 274/569592 [12:17<355:35:52,  2.25s/it]
                                                        

  0%|          | 274/569592 [12:17<355:35:52,  2.25s/it]
  0%|          | 275/569592 [12:19<373:47:11,  2.36s/it]
                                                        

  0%|          | 275/569592 [12:19<373:47:11,  2.36s/it]
  0%|          | 276/569592 [12:23<423:31:04,  2.68s/it]
                                                        

  0%|          | 276/569592 [12:23<423:31:04,  2.68s/it]
  0%|          | 277/569592 [12:24<370:49:15,  2.34s/it]
                                                        

  0%|          | 277/569592 [12:24<370:49:15,  2.34s/it]
  0%|          | 278/569592 [12:28<452:50:14,  2.86s/it]
                                                        

  0%|          | 278/569592 [12:28<452:50:14,  2.86s/it]
  0%|          | 279/569592 [12:30<410:02:43,  2.59s/it]
                                                        

  0%|          | 279/569592 [12:30<410:02:43,  2.59s/it]
  0%|          | 280/569592 [12:33<410:22:13,  2.59s/it]
                                                        

  0%|          | 280/569592 [12:33<410:22:13,  2.59s/it]
  0%|          | 281/569592 [12:34<334:05:03,  2.11s/it]
                                                        

  0%|          | 281/569592 [12:34<334:05:03,  2.11s/it]
  0%|          | 282/569592 [12:37<398:40:53,  2.52s/it]
                                                        

  0%|          | 282/569592 [12:37<398:40:53,  2.52s/it]
  0%|          | 283/569592 [12:41<455:52:30,  2.88s/it]
                                                        

  0%|          | 283/569592 [12:41<455:52:30,  2.88s/it]
  0%|          | 284/569592 [12:43<407:27:18,  2.58s/it]
                                                        

  0%|          | 284/569592 [12:43<407:27:18,  2.58s/it]
  0%|          | 285/569592 [12:44<341:08:51,  2.16s/it]
                                                        

  0%|          | 285/569592 [12:44<341:08:51,  2.16s/it]
  0%|          | 286/569592 [12:49<460:20:28,  2.91s/it]
                                                        

  0%|          | 286/569592 [12:49<460:20:28,  2.91s/it]
  0%|          | 287/569592 [12:52<462:21:07,  2.92s/it]
                                                        

  0%|          | 287/569592 [12:52<462:21:07,  2.92s/it]
  0%|          | 288/569592 [12:53<386:39:11,  2.45s/it/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
]
                                                        

  0%|          | 288/569592 [12:53<386:39:11,  2.45s/it]
  0%|          | 289/569592 [12:55<362:26:37,  2.29s/it]
                                                        

  0%|          | 289/569592 [12:55<362:26:37,  2.29s/it]
  0%|          | 290/569592 [12:58<379:13:04,  2.40s/it]
                                                        

  0%|          | 290/569592 [12:58<379:13:04,  2.40s/it]
  0%|          | 291/569592 [13:02<460:47:26,  2.91s/it]
                                                        

  0%|          | 291/569592 [13:02<460:47:26,  2.91s/it]
  0%|          | 292/569592 [13:04<406:57:01,  2.57s/it]
                                                        

  0%|          | 292/569592 [13:04<406:57:01,  2.57s/it]
  0%|          | 293/569592 [13:06<384:14:43,  2.43s/it]
                                                        

  0%|          | 293/569592 [13:06<384:14:43,  2.43s/it]
  0%|          | 294/569592 [13:09<421:23:39,  2.66s/it]
                                                        

  0%|          | 294/569592 [13:09<421:23:39,  2.66s/it]
  0%|          | 295/569592 [13:11<383:59:48,  2.43s/it]
                                                        

  0%|          | 295/569592 [13:11<383:59:48,  2.43s/it]
  0%|          | 296/569592 [13:14<437:43:15,  2.77s/it]
                                                        

  0%|          | 296/569592 [13:14<437:43:15,  2.77s/it]
  0%|          | 297/569592 [13:15<351:50:09,  2.22s/it]
                                                        

  0%|          | 297/569592 [13:15<351:50:09,  2.22s/it]
  0%|          | 298/569592 [13:19<415:26:52,  2.63s/it]
                                                        

  0%|          | 298/569592 [13:19<415:26:52,  2.63s/it]
  0%|          | 299/569592 [13:22<422:26:36,  2.67s/it]
                                                        

  0%|          | 299/569592 [13:22<422:26:36,  2.67s/it]
  0%|          | 300/569592 [13:24<406:14:40,  2.57s/it]
                                                        

  0%|          | 300/569592 [13:24<406:14:40,  2.57s/it]
  0%|          | 301/569592 [13:27<428:15:29,  2.71s/it]
                                                        

  0%|          | 301/569592 [13:27<428:15:29,  2.71s/it]
  0%|          | 302/569592 [13:29<405:25:59,  2.56s/it]
                                                        

  0%|          | 302/569592 [13:29<405:25:59,  2.56s/it]
  0%|          | 303/569592 [13:31<368:59:57,  2.33s/it]
                                                        

  0%|          | 303/569592 [13:31<368:59:57,  2.33s/it]
  0%|          | 304/569592 [13:34<388:09:20,  2.45s/it]
                                                        

  0%|          | 304/569592 [13:34<388:09:20,  2.45s/it]
  0%|          | 305/569592 [13:36<387:15:32,  2.45s/it]
                                                        

  0%|          | 305/569592 [13:36<387:15:32,  2.45s/it]
  0%|          | 306/569592 [13/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94349568 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:39<411:16:59,  2.60s/it]
                                                        

  0%|          | 306/569592 [13:39<411:16:59,  2.60s/it]
  0%|          | 307/569592 [13:40<352:35:04,  2.23s/it]
                                                        

  0%|          | 307/569592 [13:40<352:35:04,  2.23s/it]
  0%|          | 308/569592 [13:44<430:48:48,  2.72s/it]
                                                        

  0%|          | 308/569592 [13:44<430:48:48,  2.72s/it]
  0%|          | 309/569592 [13:47<406:01:04,  2.57s/it]
                                                        

  0%|          | 309/569592 [13:47<406:01:04,  2.57s/it]
  0%|          | 310/569592 [13:49<405:13:37,  2.56s/it]
                                                        

  0%|          | 310/569592 [13:49<405:13:37,  2.56s/it]
  0%|          | 311/569592 [13:50<329:28:26,  2.08s/it]
                                                        

  0%|          | 311/569592 [13:50<329:28:26,  2.08s/it]
  0%|          | 312/569592 [13:54<405:23:37,  2.56s/it]
                                                        

  0%|          | 312/569592 [13:54<405:23:37,  2.56s/it]
  0%|          | 313/569592 [13:58<476:40:57,  3.01s/it]
                                                        

  0%|          | 313/569592 [13:58<476:40:57,  3.01s/it]
  0%|          | 314/569592 [13:59<403:23:21,  2.55s/it]
                                                        

  0%|          | 314/569592 [13:59<403:23:21,  2.55s/it]
  0%|          | 315/569592 [14:01<350:05:45,  2.21s/it]
                                                        

  0%|          | 315/569592 [14:01<350:05:45,  2.21s/it]
  0%|          | 316/569592 [14:04<395:48:19,  2.50s/it]
                                                        

  0%|          | 316/569592 [14:04<395:48:19,  2.50s/it]
  0%|          | 317/569592 [14:08<474:21:43,  3.00s/it]
                                                        

  0%|          | 317/569592 [14:08<474:21:43,  3.00s/it]
  0%|          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
| 318/569592 [14:10<401:38:44,  2.54s/it]
                                                        

  0%|          | 318/569592 [14:10<401:38:44,  2.54s/it]
  0%|          | 319/569592 [14:11<332:20:29,  2.10s/it]
                                                        

  0%|          | 319/569592 [14:11<332:20:29,  2.10s/it]
  0%|          | 320/569592 [14:15<454:23:25,  2.87s/it]
                                                        

  0%|          | 320/569592 [14:15<454:23:25,  2.87s/it]
  0%|          | 321/569592 [14:18<463:11:26,  2.93s/it]
                                                        

  0%|          | 321/569592 [14:18<463:11:26,  2.93s/it]
  0%|          | 322/569592 [14:20<392:54:48,  2.48s/it]
                                                        

  0%|          | 322/569592 [14:20<392:54:48,  2.48s/it]
  0%|          | 323/569592 [14:21<320:57:32,  2.03s/it]
                                                        

  0%|          | 323/569592 [14:21<320:57:32,  2.03s/it]
  0%|          | 324/569592 [14:25<429:31:03,  2.72s/it]
                                                        

  0%|          | 324/569592 [14:25<429:31:03,  2.72s/it]
  0%|          | 325/569592 [14:29<484:42:44,  3.07s/it]
                                                        

  0%|          | 325/569592 [14:29<484:42:44,  3.07s/it]
  0%|          | 326/569592 [14:30<393:55:21,  2.49s/it]
                                                        

  0%|          | 326/569592 [14:30<393:55:21,  2.49s/it]
  0%|          | 327/569592 [14:31<319:36:42,  2.02s/it]
                                                        

  0%|          | 327/569592 [14:31<319:36:42,  2.02s/it]
  0%|          | 328/569592 [14:35<421:45:42,  2.67s/it]
                                                        

  0%|          | 328/569592 [14:35<421:45:42,  2.67s/it]
  0%|          | 329/569592 [14:38<443:16:24,  2.80s/it]
                                                        

  0%|          | 329/569592 [14:38<443:16:24,  2.80s/it]
  0%|          | 330/569592 [14:41<421:07:27,  2.66s/it]
                                                        

  0%|          | 330/569592 [14:41<421:07:27,  2.66s/it]
  0%|          | 331/569592 [14:42<339:55:44,  2.15s/it]
                                                        

  0%|          | 331/569592 [14:42<339:55:44,  2.15s/it]
  0%|          | 332/569592 [14:45<388:06:07,  2.45s/it]
                                                        

  0%|          | 332/569592 [14:45<388:06:07,  2.45s/it]
  0%|          | 333/569592 [14:50<502:26:21,  3.18s/it]
                                                        

  0%|          | 333/569592 [14:50<502:26:21,  3.18s/it]
  0%|          | 334/569592 [14:51<395:52:39,  2.50s/it]
                                                        

  0%|          | 334/569592 [14:51<395:52:39,  2.50s/it]
  0%|          | 335/569592 [14:52<325:55:09,  2.06s/it]
                                                        

  0%|          | 335/569592 [14:52<325:55:09,  2.06s/it]
  0%|          | 336/569592 [14:54<366:02:59,  2.31s/it]
                                                        

  0%|          | 336/569592 [14:55<366:02:59,  2.31s/it]
  0%|          | 337/569592 [14:59<453:02:24,  2.87s/it]
                                                        

  0%|          | 337/569592 [14:59<453:02:24,  2.87s/it]
  0%|          | 338/569592 [15:02<460:43:33,  2.91s/it]
                                                        

  0%|          | 338/569592 [15:02<460:43:33,  2.91s/it]
  0%|          | 339/569592 [15:03<367:31:00,  2.32s/it]
                                                        

  0%|          | 339/569592 [15:03<367:31:00,  2.32s/it]
  0%|          | 340/569592 [15:05<354:08:44,  2.24s/it]
                                                        

  0%|          | 340/569592 [15:05<354:08:44,  2.24s/it]
  0%|          | 341/569592 [15:10<521:29:57,  3.30s/it]
                                                        

  0%|          | 341/569592 [15:10<521:29:57,  3.30s/it]
  0%|          | 342/569592 [15:12<420:43:49,  2.66s/it]
                                                        

  0%|          | 342/569592 [15:12<420:43:49,  2.66s/it]
  0%|          | 343/569592 [15:17<533:06:47,  3.37s/it]
                                                        

  0%|          | 343/569592 [15:17<533:06:47,  3.37s/it]
  0%|          | 344/569592 [15:20<553:16:54,  3.50s/it]
                                                        

  0%|          | 344/569592 [15:20<553:16:54,  3.50s/it]
  0%|          | 345/569592 [15:21<428:54:57,  2.71s/it]
                                                        

  0%|          | 345/569592 [15:21<428:54:57,  2.71s/it]
  0%|          | 346/569592 [15:26<524:13:46,  3.32s/it]
                                                        

  0%|          | 346/569592 [15:26<524:13:46,  3.32s/it]
  0%|          | 347/569592 [15:31<591:32:16,  3.74s/it]
                                                        

  0%|          | 347/569592 [15:31<591:32:16,  3.74s/it]
  0%|          | 348/569592 [15:36<643:18:45,  4.07s/it]
                                                        

  0%|          | 348/569592 [15:36<643:18:45,  4.07s/it]
  0%|          | 349/569592 [15:39<631:14:16,  3.99s/it]
                                                        

  0%|          | 349/569592 [15:39<631:14:16,  3.99s/it]
  0%|          | 350/569592 [15:43<594:53:23,  3.76s/it]
                                                        

  0%|          | 350/569592 [15:43<594:53:23,  3.76s/it]
  0%|          | 351/569592 [15:46<579:29:21,  3.66s/it]
                                                        

  0%|          | 351/569592 [15:46<579:29:21,  3.66s/it]
  0%|          | 352/569592 [15:52<674:57:39,  4.27s/it]
                                                        

  0%|          | 352/569592 [15:52<674:57:39,  4.27s/it]
  0%|          | 353/569592 [15:55<646:20:12,  4.09s/it]
                                                        

  0%|          | 353/569592 [15:55<646:20:12,  4.09s/it]
  0%|          | 354/569592 [15:56<493:34:20,  3.12s/it]
                                                        

  0%|          | 354/569592 [15:56<493:34:20,  3.12s/it]
  0%|          | 355/569592 [15:57<389:53:19,  2.47s/it]
                                                        

  0%|          | 355/569592 [15:57<389:53:19,  2.47s/it]
  0%|          | 356/569592 [15:58<319:48:21,  2.02s/it]
                                                        

  0%|          | 356/569592 [15:58<319:48:21,  2.02s/it]
  0%|          | 357/569592 [15:59<271:20:56,  1.72s/it]
                                                        

  0%|          | 357/569592 [15:59<271:20:56,  1.72s/it]
  0%|          | 358/569592 [16:00<234:28:21,  1.48s/it]
                                                        

  0%|          | 358/569592 [16:00<234:28:21,  1.48s/it]
  0%|          | 359/569592 [16:01<208:40:37,  1.32s/it]
                                                        

  0%|          | 359/569592 [16:01<208:40:37,  1.32s/it]
  0%|          | 360/569592 [16:02<192:27:54,  1.22s/it]
                                                        

  0%|          | 360/569592 [16:02<192:27:54,  1.22s/it]
  0%|          | 361/569592 [16:04<217:32:44,  1.38s/it]
                                                        

  0%|          | 361/569592 [16:04<217:32:44,  1.38s/it]
  0%|          | 362/569592 [16:10<448:20:52,  2.84s/it]
                                                        

  0%|          | 362/569592 [16:10<448:20:52,  2.84s/it]
  0%|          | 363/569592 [16:11<360:07:10,  2.28s/it]
                                                        

  0%|          | 363/569592 [16:11<360:07:10,  2.28s/it]
  0%|          | 364/569592 [16:12<297:39:26,  1.88s/it]
                                                        

  0%|          | 364/569592 [16:12<297:39:26,  1.88s/it]
  0%|          | 365/569592 [16:14<289:24:18,  1.83s/it]
                                                        

  0%|   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
       | 365/569592 [16:14<289:24:18,  1.83s/it]
  0%|          | 366/569592 [16:19<461:59:29,  2.92s/it]
                                                        

  0%|          | 366/569592 [16:19<461:59:29,  2.92s/it]
  0%|          | 367/569592 [16:20<373:06:51,  2.36s/it]
                                                        

  0%|          | 367/569592 [16:20<373:06:51,  2.36s/it]
  0%|          | 368/569592 [16:23<385:52:09,  2.44s/it]
                                                        

  0%|          | 368/569592 [16:23<385:52:09,  2.44s/it]
  0%|          | 369/569592 [16:25<356:09:06,  2.25s/it]
                                                        

  0%|          | 369/569592 [16:25<356:09:06,  2.25s/it]
  0%|          | 370/569592 [16:29<463:54:35,  2.93s/it]
                                                        

  0%|          | 370/569592 [16:29<463:54:35,  2.93s/it]
  0%|          | 371/569592 [16:30<373:16:37,  2.36s/it]
                                                        

  0%|          | 371/569592 [16:30<373:16:37,  2.36s/it]
  0%|          | 372/569592 [16:33<398:48:22,  2.52s/it]
                                                        

  0%|          | 372/569592 [16:33<398:48:22,  2.52s/it]
  0%|          | 373/569592 [16:37<460:06:46,  2.91s/it]
                                                        

  0%|          | 373/569592 [16:37<460:06:46,  2.91s/it]
  0%|          | 374/569592 [16:41<501:00:48,  3.17s/it]
                                                        

  0%|          | 374/569592 [16:41<501:00:48,  3.17s/it]
  0%|          | 375/569592 [16:42<402:21:41,  2.54s/it]
                                                        

  0%|          | 375/569592 [16:42<402:21:41,  2.54s/it]
  0%|          | 376/569592 [16:43<354:42:13,  2.24s/it]
                                                        

  0%|          | 376/569592 [16:43<354:42:13,  2.24s/it]
  0%|          | 377/569592 [16:46<362:54:25,  2.30s/it]
                                                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
      

  0%|          | 377/569592 [16:46<362:54:25,  2.30s/it]
  0%|          | 378/569592 [16:51<507:25:03,  3.21s/it]
                                                        

  0%|          | 378/569592 [16:51<507:25:03,  3.21s/it]
  0%|          | 379/569592 [16:52<400:15:52,  2.53s/it]
                                                        

  0%|          | 379/569592 [16:52<400:15:52,  2.53s/it]
  0%|          | 380/569592 [16:53<338:34:42,  2.14s/it]
                                                        

  0%|          | 380/569592 [16:53<338:34:42,  2.14s/it]
  0%|          | 381/569592 [16:56<362:59:22,  2.30s/it]
                                                        

  0%|          | 381/569592 [16:56<362:59:22,  2.30s/it]
  0%|          | 382/569592 [17:01<507:15:04,  3.21s/it]
                                                        

  0%|          | 382/569592 [17:01<507:15:04,  3.21s/it]
  0%|          | 383/569592 [17:02<400:53:27,  2.54s/it]
                                                        

  0%|          | 383/569592 [17:02<400:53:27,  2.54s/it]
  0%|          | 384/569592 [17:03<328:01:50,  2.07s/it]
                                                        

  0%|          | 384/569592 [17:03<328:01:50,  2.07s/it]
  0%|          | 385/569592 [17:06<341:39:38,  2.16s/it]
                                                        

  0%|          | 385/569592 [17:06<341:39:38,  2.16s/it]
  0%|          | 386/569592 [17:12<521:40:26,  3.30s/it]
                                                        

  0%|          | 386/569592 [17:12<521:40:26,  3.30s/it]
  0%|          | 387/569592 [17:13<415:17:00,  2.63s/it]
                                                        

  0%|          | 387/569592 [17:13<415:17:00,  2.63s/it]
  0%|          | 388/569592 [17:14<338:36:23,  2.14s/it]
                                                        

  0%|          | 388/569592 [17:14<338:36:23,  2.14s/it]
  0%|          | 389/569592 [17:16<371:03:32,  2.35s/it]
                                                        

  0%|          | 389/569592 [17:16<371:03:32,  2.35s/it]
  0%|          | 390/569592 [17:22<510:45:54,  3.23s/it]
                                                        

  0%|          | 390/569592 [17:22<510:45:54,  3.23s/it]
  0%|          | 391/569592 [17:23<404:06:50,  2.56s/it]
                                                        

  0%|          | 391/569592 [17:23<404:06:50,  2.56s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  0%|          | 392/569592 [17:24<331:14:49,  2.10s/it]
                                                        

  0%|          | 392/569592 [17:24<331:14:49,  2.10s/it]
  0%|          | 393/569592 [17:26<349:56:13,  2.21s/it]
                                                        

  0%|          | 393/569592 [17:26<349:56:13,  2.21s/it]
  0%|          | 394/569592 [17:31<479:27:24,  3.03s/it]
                                                        

  0%|          | 394/569592 [17:31<479:27:24,  3.03s/it]
  0%|          | 395/569592 [17:32<381:26:25,  2.41s/it]
                                                        

  0%|          | 395/569592 [17:32<381:26:25,  2.41s/it]
  0%|          | 396/569592 [17:35<402:35:57,  2.55s/it]
                                                        

  0%|          | 396/569592 [17:35<402:35:57,  2.55s/it]
  0%|          | 397/569592 [17:38<423:09:52,  2.68s/it]
                                                        

  0%|          | 397/569592 [17:38<423:09:52,  2.68s/it]
  0%|          | 398/569592 [17:41<431:04:10,  2.73s/it]
                                                        

  0%|          | 398/569592 [17:41<431:04:10,  2.73s/it]
  0%|          | 399/569592 [17:42<349:20:35,  2.21s/it]
                                                        

  0%|          | 399/569592 [17:42<349:20:35,  2.21s/it]
  0%|          | 400/569592 [17:44<358:30:11,  2.27s/it]
                                                        

  0%|          | 400/569592 [17:44<358:30:11,  2.27s/it]
  0%|          | 401/569592 [17:48<413:55:10,  2.62s/it]
                                                        

  0%|          | 401/569592 [17:48<413:55:10,  2.62s/it]
  0%|          | 402/569592 [17:51<450:36:58,  2.85s/it]
                                                        

  0%|          | 402/569592 [17:51<450:36:58,  2.85s/it]
  0%|          | 403/569592 [17:53<386:22:41,  2.44s/it]
                                                        

  0%|          | 403/569592 [17:53<386:22:41,  2.44s/it]
  0%|          | 404/569592 [17:54<345:34:03,  2.19s/it]
                                                        

  0%|          | 404/569592 [17:54<345:34:03,  2.19s/it]
  0%|          | 405/569592 [17:58<435:10:40,  2.75s/it]
                                                        

  0%|          | 405/569592 [17:58<435:10:40,  2.75s/it]
  0%|          | 406/569592 [18:01<452:14:44,  2.86s/it]
                                                        

  0%|          | 406/569592 [18:01<452:14:44,  2.86s/it]
  0%|          | 407/569592 [18:03<385:44:02,  2.44s/it]
                                                        

  0%|          | 407/569592 [18:03<385:44:02,  2.44s/it]
  0%|          | 408/569592 [18:04<349:57:27,  2.21s/it]
                                                        

  0%|          | 408/569592 [18:04<349:57:27,  2.21s/it]
  0%|          | 409/569592 [18:09<445:50:53,  2.82s/it]
                                                        

  0%|          | 409/569592 [18:09<445:50:53,  2.82s/it]
  0%|          | 410/569592 [18:11<437:13:29,  2.77s/it]
                                                        

  0%|          | 410/569592 [18:11<437:13:29,  2.77s/it]
  0%|          | 411/569592 [18:13<386:11:06,  2.44s/it]
                                                        

  0%|          | 411/569592 [18:13<386:11:06,  2.44s/it]
  0%|          | 412/569592 [18:15<357:47:44,  2.26s/it]
                                                        

  0%|          | 412/569592 [18:15<357:47:44,  2.26s/it]
  0%|          | 413/569592 [18:18<422:42:59,  2.67s/it]
                                                        

  0%|          | 413/569592 [18:19<422:42:59,  2.67s/it]
  0%|          | 414/569592 [18:22<458:45:06,  2.90s/it]
                                                        

  0%|          | 414/569592 [18:22<458:45:06,  2.90s/it]
  0%|          | 415/569592 [18:23<366:41:38,  2.32s/it]
                                                        

  0%|          | 415/569592 [18:23<366:41:38,  2.32s/it]
  0%|          | 416/569592 [18:26<399:18:11,  2.53s/it]
                                                        

  0%|          | 416/569592 [18:26<399:18:11,  2.53s/it]
  0%|          | 417/569592 [18:29<414:37:49,  2.62s/it]
                                                        

  0%|          | 417/569592 [18:30<414:37:49,  2.62s/it]
  0%|          | 418/569592 [18:32<439:02:58,  2.78s/it]
                                                        

  0%|          | 418/569592 [18:32<439:02:58,  2.78s/it]
  0%|          | 419/569592 [18:33<351:56:29,  2.23s/it]
                                                        

  0%|          | 419/569592 [18:33<351:56:29,  2.23s/it]
  0%|          | 420/569592 [18:35<355:31:38,  2.25s/it]
                                                        

  0%|          | 420/569592 [18:35<355:31:38,  2.25s/it]
  0%|          | 421/569592 [18:39<417:11:58,  2.64s/it]
                                                        

  0%|          | 421/569592 [18:39<417:11:58,  2.64s/it]
  0%|          | 422/569592 [18:43<475:41:05,  3.01s/it]
                                                        

  0%|          | 422/569592 [18:43<475:41:05,  3.01s/it]
  0%|          | 423/569592 [18:43<377:41:25,  2.39s/it]
                                                        

  0%|          | 423/569592 [18:43<377:41:25,  2.39s/it]
  0%|          | 424/569592 [18:45<349:04:11,  2.21s/it]
                                                        

  0%|          | 424/569592 [18:45<349:04:11,  2.21s/it]
  0%|          | 425/569592 [18:48<387:53:47,  2.45s/it]
                                                        

  0%|          | 425/569592 [18:48<387:53:47,  2.45s/it]
  0%|          | 426/569592 [18:52<431:42:07,  2.73s/it]
                                                        

  0%|          | 426/569592 [18:52<431:42:07,  2.73s/it]
  0%|          | 427/569592 [18:53<389:06:30,  2.46s/it]
                                                        

  0%|          | 427/569592 [18:54<389:06:30,  2.46s/it]
  0%|          | 428/569592 [18:55<363:23:53,  2.30s/it]
                                                        

  0%|          | 428/569592 [18:55<363:23:53,  2.30s/it]
  0%|          | 429/569592 [19:00<455:36:38,  2.88s/it]
                                                        

  0%|          | 429/569592 [19:00<455:36:38,  2.88s/it]
  0%|          | 430/569592 [19:03<499:39:03,  3.16s/it]
                                                        

  0%|          | 430/569592 [19:03<499:39:03,  3.16s/it]
  0%|          | 431/569592 [19:04<392:38:45,  2.48s/it]
                                                        

  0%|          | 431/569592 [19:04<392:38:45,  2.48s/it]
  0%|          | 432/569592 [19:05<321:34:35,  2.03s/it]
                                                        

  0%|          | 432/569592 [19:05<321:34:35,  2.03s/it]
  0%|          | 433/569592 [19:08<341:11:04,  2.16s/it]
                                                        

/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102718903 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  0%|          | 433/569592 [19:08<341:11:04,  2.16s/it]
  0%|          | 434/569592 [19:12<460:47:02,  2.91s/it]
                                                        

  0%|          | 434/569592 [19:12<460:47:02,  2.91s/it]
  0%|          | 435/569592 [19:14<399:16:31,  2.53s/it]
                                                        

  0%|          | 435/569592 [19:14<399:16:31,  2.53s/it]
  0%|          | 436/569592 [19:16<358:56:34,  2.27s/it]
                                                        

  0%|          | 436/569592 [19:16<358:56:34,  2.27s/it]
  0%|          | 437/569592 [19:18<351:58:40,  2.23s/it]
                                                        

  0%|          | 437/569592 [19:18<351:58:40,  2.23s/it]
  0%|          | 438/569592 [19:24<519:39:24,  3.29s/it]
                                                        

  0%|          | 438/569592 [19:24<519:39:24,  3.29s/it]
  0%|          | 439/569592 [19:25<407:34:06,  2.58s/it]
                                                        

  0%|          | 439/569592 [19:25<407:34:06,  2.58s/it]
  0%|          | 440/569592 [19:26<348:12:25,  2.20s/it]
                                                        

  0%|          | 440/569592 [19:26<348:12:25,  2.20s/it]
  0%|          | 441/569592 [19:29<383:22:58,  2.42s/it]
                                                        

  0%|          | 441/569592 [19:29<383:22:58,  2.42s/it]
  0%|          | 442/569592 [19:33<483:54:46,  3.06s/it]
                                                        

  0%|          | 442/569592 [19:33<483:54:46,  3.06s/it]
  0%|          | 443/569592 [19:35<404:21:53,  2.56s/it]
                                                        

  0%|          | 443/569592 [19:35<404:21:53,  2.56s/it]
  0%|          | 444/569592 [19:36<359:27:10,  2.27s/it]
                                                        

  0%|          | 444/569592 [19:36<359:27:10,  2.27s/it]
  0%|          | 445/569592 [19:39<383:17:03,  2.42s/it]
                                                        

  0%|          | 445/569592 [19:39<383:17:03,  2.42s/it]
  0%|          | 446/569592 [19:44<493:23:11,  3.12s/it]
                                                        

  0%|          | 446/569592 [19:44<493:23:11,  3.12s/it]
  0%|          | 447/569592 [19:45<391:22:11,  2.48s/it]
                                                        

  0%|          | 447/569592 [19:45<391:22:11,  2.48s/it]
  0%|          | 448/569592 [19:47<364:25:17,  2.31s/it]
                                                        

  0%|          | 448/569592 [19:47<364:25:17,  2.31s/it]
  0%|          | 449/569592 [19:48<302:22:17,  1.91s/it]
                                                        

  0%|          | 449/569592 [19:48<302:22:17,  1.91s/it]
  0%|          | 450/569592 [19:54<502:50:10,  3.18s/it]
                                                        

  0%|          | 450/569592 [19:54<502:50:10,  3.18s/it]
  0%|          | 451/569592 [19:55<421:47:55,  2.67s/it]
                                                        

  0%|          | 451/569592 [19:55<421:47:55,  2.67s/it]
  0%|          | 452/569592 [19:57<370:12:13,  2.34s/it]
                                                        

  0%|          | 452/569592 [19:57<370:12:13,  2.34s/it]
  0%|          | 453/569592 [19:59<341:22:23,  2.16s/it]
                                                        

  0%|          | 453/569592 [19:59<341:22:23,  2.16s/it]
  0%|          | 454/569592 [20:04<478:27:30,  3.03s/it]
                                                        

  0%|          | 454/569592 [20:04<478:27:30,  3.03s/it]
  0%|          | 455/569592 [20:05<404:04:10,  2.56s/it]
                                                        

  0%|          | 455/569592 [20:05<404:04:10,  2.56s/it]
  0%|          | 456/569592 [20:11<542:00:06,  3.43s/it]
                                                        

  0%|          | 456/569592 [20:11<542:00:06,  3.43s/it]
  0%|          | 457/569592 [20:16<613:11:55,  3.88s/it]
                                                        

  0%|          | 457/569592 [20:16<613:11:55,  3.88s/it]
  0%|          | 458/569592 [20:19<602:29:28,  3.81s/it]
                                                        

  0%|          | 458/569592 [20:19<602:29:28,  3.81s/it]
  0%|          | 459/569592 [20:24<636:28:00,  4.03s/it]
                                                        

  0%|          | 459/569592 [20:24<636:28:00,  4.03s/it]
  0%|          | 460/569592 [20:29<695:08:30,  4.40s/it]
                                                        

  0%|          | 460/569592 [20:29<695:08:30,  4.40s/it]
  0%|          | 461/569592 [20:33<657:49:04,  4.16s/it]
                                                        

  0%|          | 461/569592 [20:33<657:49:04,  4.16s/it]
  0%|          | 462/569592 [20:36<621:46:26,  3.93s/it]
                                                        

  0%|          | 462/569592 [20:36<621:46:26,  3.93s/it]
  0%|          | 463/569592 [20:41<660:47:17,  4.18s/it]
                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97128300 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                      

  0%|          | 463/569592 [20:41<660:47:17,  4.18s/it]
  0%|          | 464/569592 [20:45<681:44:59,  4.31s/it]
                                                        

  0%|          | 464/569592 [20:45<681:44:59,  4.31s/it]
  0%|          | 465/569592 [20:50<685:49:10,  4.34s/it]
                                                        

  0%|          | 465/569592 [20:50<685:49:10,  4.34s/it]
  0%|          | 466/569592 [20:54<684:00:55,  4.33s/it]
                                                        

  0%|          | 466/569592 [20:54<684:00:55,  4.33s/it]
  0%|          | 467/569592 [20:59<719:24:55,  4.55s/it]
                                                        

  0%|          | 467/569592 [20:59<719:24:55,  4.55s/it]
  0%|          | 468/569592 [21:03<699:48:25,  4.43s/it]
                                                        

  0%|          | 468/569592 [21:03<699:48:25,  4.43s/it]
  0%|          | 469/569592 [21:07<671:36:40,  4.25s/it]
                                                        

  0%|          | 469/569592 [21:07<671:36:40,  4.25s/it]
  0%|          | 470/569592 [21:13<724:34:20,  4.58s/it]
                                                        

  0%|          | 470/569592 [21:13<724:34:20,  4.58s/it]
  0%|          | 471/569592 [21:13<549:56:46,  3.48s/it]
                                                        

  0%|          | 471/569592 [21:13<549:56:46,  3.48s/it]
  0%|          | 472/569592 [21:14<429:09:04,  2.71s/it]
                                                        

  0%|          | 472/569592 [21:14<429:09:04,  2.71s/it]
  0%|          | 473/569592 [21:15<345:15:22,  2.18s/it]
                                                        

  0%|          | 473/569592 [21:15<345:15:22,  2.18s/it]
  0%|          | 474/569592 [21:16<286:36:06,  1.81s/it]
                                                        

  0%|          | 474/569592 [21:16<286:36:06,  1.81s/it]
  0%|          | 475/569592 [21:17<246:22:21,  1.56s/it]
                                                        

  0%|          | 475/569592 [21:17<246:22:21,  1.56s/it]
  0%|          | 476/569592 [21:18<217:29:59,  1.38s/it]
                                                        

  0%|          | 476/569592 [21:18<217:29:59,  1.38s/it]
  0%|          | 477/569592 [21:19<197:03:34,  1.25s/it]
                                                        

  0%|          | 477/569592 [21:19<197:03:34,  1.25s/it]
  0%|          | 478/569592 [21:20<184:24:59,  1.17s/it]
                                                        

  0%|          | 478/569592 [21:20<184:24:59,  1.17s/it]
  0%|          | 479/569592 [21:28<492:36:04,  3.12s/it]
                                                        

  0%|          | 479/569592 [21:28<492:36:04,  3.12s/it]
  0%|          | 480/569592 [21:29<390:43:21,  2.47s/it]
                                                        

  0%|          | 480/569592 [21:29<390:43:21,  2.47s/it]
  0%|          | 481/569592 [21:30<318:18:38,  2.01s/it]
                                                        

  0%|          | 481/569592 [21:30<318:18:38,  2.01s/it]
  0%|          | 482/569592 [21:31<268:05:34,  1.70s/it]
                                                        

  0%|          | 482/569592 [21:31<268:05:34,  1.70s/it]
  0%|          | 483/569592 [21:38<521:30:50,  3.30s/it]
                                                        

  0%|          | 483/569592 [21:38<521:30:50,  3.30s/it]
  0%|          | 484/569592 [21:39<414:32:08,  2.62s/it]
                                                        

  0%|          | 484/569592 [21:39<414:32:08,  2.62s/it]
  0%|          | 485/569592 [21:40<335:07:06,  2.12s/it]
                                                        

  0%|          | 485/569592 [21:40<335:07:06,  2.12s/it]
  0%|          | 486/569592 [21:41<280:23:55,  1.77s/it]
                                                        

  0%|          | 486/569592 [21:41<280:23:55,  1.77s/it]
  0%|          | 487/569592 [21:46<453:45:39,  2.87s/it]
                                                        

  0%|          | 487/569592 [21:46<453:45:39,  2.87s/it]
  0%|          | 488/569592 [21:49<461:03:22,  2.92s/it]
                                                        

  0%|          | 488/569592 [21:49<461:03:22,  2.92s/it]
  0%|          | 489/569592 [21:50<373:01:51,  2.36s/it]
                                                        

  0%|          | 489/569592 [21:50<373:01:51,  2.36s/it]
  0%|          | 490/569592 [21:51<306:35:27,  1.94s/it]
                                                        

  0%|          | 490/569592 [21:51<306:35:27,  1.94s/it]
  0%|          | 491/569592 [21:58<535:10:51,  3.39s/it]
                                                        

  0%|          | 491/569592 [21:58<535:10:51,  3.39s/it]
  0%|          | 492/569592 [22:00<459:21:08,  2.91s/it]
                                                        

  0%|          | 492/569592 [22:00<459:21:08,  2.91s/it]
  0%|          | 493/569592 [22:01<366:06:42,  2.32s/it]
                                                        

  0%|          | 493/569592 [22:01<366:06:42,  2.32s/it]
  0%|          | 494/569592 [22:02<301:54:25,  1.91s/it]
                                                        

  0%|          | 494/569592 [22:02<301:54:25,  1.91s/it]
  0%|          | 495/569592 [22:08<523:06:59,  3.31s/it]
                                                        

  0%|          | 495/569592 [22:08<523:06:59,  3.31s/it]
  0%|          | 496/569592 [22:10<433:25:23,  2.74s/it]
                                                        

  0%|          | 496/569592 [22:10<433:25:23,  2.74s/it]
  0%|          | 497/569592 [22:11<351:24:16,  2.22s/it]
                                                        

  0%|          | 497/569592 [22:11<351:24:16,  2.22s/it]
  0%|          | 498/569592 [22:12<291:47:57,  1.85s/it]
                                                        

  0%|          | 498/569592 [22:12<291:47:57,  1.85s/it]
  0%|          | 499/569592 [22:19<542:52:44,  3.43s/it]
                                                        

  0%|          | 499/569592 [22:19<542:52:44,  3.43s/it]
  0%|          | 500/569592 [22:20<429:12:07,  2.72s/it]
                                                        

  0%|          | 500/569592 [22:20<429:12:07,  2.72s/it]
  0%|          | 501/569592 [22:21<346:54:39,  2.19s/it]
                                                        

  0%|          | 501/569592 [22:21<346:54:39,  2.19s/it]
  0%|          | 502/569592 [22:22<312:26:50,  1.98s/it]
                                                        

  0%|          | 502/569592 [22:22<312:26:50,  1.98s/it]
  0%|          | 503/569592 [22:29<543:32:13,  3.44s/it]
                                                        

  0%|          | 503/569592 [22:29<543:32:13,  3.44s/it]
  0%|          | 504/569592 [22:30<430:29:07,  2.72s/it]
                                                        

  0%|          | 504/569592 [22:30<430:29:07,  2.72s/it]
  0%|          | 505/569592 [22:31<345:21:17,  2.18s/it]
                                                        

  0%|          | 505/569592 [22:31<345:21:17,  2.18s/it]
  0%|          | 506/569592 [22:32<287:11:02,  1.82s/it]
                                                        

  0%|          | 506/569592 [22:32<287:11:02,  1.82s/it]
  0%|          | 507/569592 [22:39<547:36:25,  3.46s/it]
                                                        

  0%|          | 507/569592 [22:39<547:36:25,  3.46s/it]
  0%|          | 508/569592 [22:40<429:35:19,  2.72s/it]
                                                        

  0%|          | 508/569592 [22:40<429:35:19,  2.72s/it]
  0%|          | 509/569592 [22:41<345:46:55,  2.19s/it]
                                                        

  0%|          | 509/569592 [22:41<345:46:55,  2.19s/it]
  0%|          | 510/569592 [22:42<288:03:56,  1.82s/it]
                                                        

  0%|          | 510/569592 [22:42<288:03:56,  1.82s/it]
  0%|          | 511/569592 [22:49<530:46:21,  3.36s/it]
                                                        

  0%|          | 511/569592 [22:49<530:46:21,  3.36s/it]
  0%|          | 512/569592 [22:50<421:29:47,  2.67s/it]
                                                        

  0%|          | 512/569592 [22:50<421:29:47,  2.67s/it]
  0%|          | 513/569592 [22:51<340:14:19,  2.15s/it]
                                                        

  0%|          | 513/569592 [22:51<340:14:19,  2.15s/it]
  0%|          | 514/569592 [22:52<283:28:47,  1.79s/it]
                                                        

  0%|          | 514/569592 [22:52<283:28:47,  1.79s/it]
  0%|          | 515/569592 [22:59<510:13:17,  3.23s/it]
                                                        

  0%|          | 515/569592 [22:59<510:13:17,  3.23s/it]
  0%|          | 516/569592 [23:00<412:38:46,  2.61s/it]
                                                        

  0%|          | 516/569592 [23:00<412:38:46,  2.61s/it]
  0%|          | 517/569592 [23:01<334:05:43,  2.11s/it]
                                                        

  0%|          | 517/569592 [23:01<334:05:43,  2.11s/it]
  0%|          | 518/569592 [23:02<281:09:09,  1.78s/it]
                                                        

  0%|          | 518/569592 [23:02<281:09:09,  1.78s/it]
  0%|          | 519/569592 [23:09<516:58:44,  3.27s/it]
                                                        

  0%|          | 519/569592 [23:09<516:58:44,  3.27s/it]
  0%|          | 520/569592 [23:10<426:27:49,  2.70s/it]
                                                        

  0%|          | 520/569592 [23:10<426:27:49,  2.70s/it]
  0%|          | 521/569592 [23:11<342:20:41,  2.17s/it]
                                                        

  0%|          | 521/569592 [23:11<342:20:41,  2.17s/it]
  0%|          | 522/569592 [23:12<290:23:36,  1.84s/it]
                                                        

  0%|          | 522/569592 [23:12<290:23:36,  1.84s/it]
  0%|          | 523/569592 [23:18<497:15:32,  3.15s/it]
                                                        

  0%|          | 523/569592 [23:18<497:15:32,  3.15s/it]
  0%|          | 524/569592 [23:19<393:21:37,  2.49s/it]
                                                        

  0%|          | 524/569592 [23:19<393:21:37,  2.49s/it]
  0%|          | 525/569592 [23:20<319:26:53,  2.02s/it]
                                                        

  0%|          | 525/569592 [23:20<319:26:53,  2.02s/it]
  0%|          | 526/569592 [23:22<315:20:59,  1.99s/it]
                                                        

  0%|          | 526/569592 [23:22<315:20:59,  1.99s/it]
  0%|          | 527/569592 [23:28<496:17:57,  3.14s/it]
                                                        

  0%|          | 527/569592 [23:28<496:17:57,  3.14s/it]
  0%|          | 528/569592 [23:31<490:12:01,  3.10s/it]
                                                        

  0%|          | 528/569592 [23:31<490:12:01,  3.10s/it]
  0%|          | 529/569592 [23:32<386:26:23,  2.44s/it]
                                                        

  0%|          | 529/569592 [23:32<386:26:23,  2.44s/it]
  0%|          | 530/569592 [23:33<314:29:44,  1.99s/it]
                                                        

  0%|          | 530/569592 [23:33<314:29:44,  1.99s/it]
  0%|          | 531/569592 [23:39<515:50:05,  3.26s/it]
                                                        

  0%|          | 531/569592 [23:39<515:50:05,  3.26s/it]
  0%|          | 532/569592 [23:41<468:13:16,  2.96s/it]
                                                        

  0%|          | 532/569592 [23:41<468:13:16,  2.96s/it]
  0%|          | 533/569592 [23:42<371:23:40,  2.35s/it]
                                                        

  0%|          | 533/569592 [23:42<371:23:40,  2.35s/it]
  0%|          | 534/569592 [23:43<311:27:31,  1.97s/it]
                                                        

  0%|          | 534/569592 [23:43<311:27:31,  1.97s/it]
  0%|          | 535/569592 [23:47<428:28:51,  2.71s/it]
                                                        

  0%|          | 535/569592 [23:47<428:28:51,  2.71s/it]
  0%|          | 536/569592 [23:51<470:29:26,  2.98s/it]
                                                        

  0%|          | 536/569592 [23:51<470:29:26,  2.98s/it]
  0%|          | 537/569592 [23:52<374:51:18,  2.37s/it]
                                                        

  0%|          | 537/569592 [23:52<374:51:18,  2.37s/it]
  0%|          | 538/569592 [23:53<308:50:47,  1.95s/it]
                                                        

  0%|          | 538/569592 [23:53<308:50:47,  1.95s/it]
  0%|          | 539/569592 [23:58<454:37:31,  2.88s/it]
                                                        

  0%|          | 539/569592 [23:58<454:37:31,  2.88s/it]
  0%|          | 540/569592 [24:01<471:15:34,  2.98s/it]
                                                        

  0%|          | 540/569592 [24:01<471:15:34,  2.98s/it]
  0%|          | 541/569592 [24:02<374:12:49,  2.37s/it]
                                                        

  0%|          | 541/569592 [24:02<374:12:49,  2.37s/it]
  0%|          | 542/569592 [24:03<307:33:10,  1.95s/it]
                                                        

  0%|          | 542/569592 [24:03<307:33:10,  1.95s/it]
  0%|          | 543/569592 [24:09<496:40:04,  3.14s/it]
                                                        

  0%|          | 543/569592 [24:09<496:40:04,  3.14s/it]
  0%|          | 544/569592 [24:11<444:49:25,  2.81s/it]
                                                        

  0%|          | 544/569592 [24:11<444:49:25,  2.81s/it]
  0%|          | 545/569592 [24:12<360:18:57,  2.28s/it]
                                                        

  0%|          | 545/569592 [24:12<360:18:57,  2.28s/it]
  0%|          | 546/569592 [24:13<296:48:48,  1.88s/it]
                                                        

  0%|          | 546/569592 [24:13<296:48:48,  1.88s/it]
  0%|          | 547/569592 [24:20<529:43:21,  3.35s/it]
                                                        

  0%|          | 547/569592 [24:20<529:43:21,  3.35s/it]
  0%|          | 548/569592 [24:21<415:50:15,  2.63s/it]
                                                        

  0%|          | 548/569592 [24:21<415:50:15,  2.63s/it]
  0%|          | 549/569592 [24:22<337:48:10,  2.14s/it]
                                                        

  0%|          | 549/569592 [24:22<337:48:10,  2.14s/it]
  0%|          | 550/569592 [24:26<415:33:20,  2.63s/it]
                                                        

  0%|          | 550/569592 [24:26<415:33:20,  2.63s/it]
  0%|          | 551/569592 [24:29<437:17:01,  2.77s/it]
                                                        

  0%|          | 551/569592 [24:29<437:17:01,  2.77s/it]
  0%|          | 552/569592 [24:32<478:11:53,  3.03s/it]
                                                        

  0%|          | 552/569592 [24:32<478:11:53,  3.03s/it]
  0%|          | 553/569592 [24:33<378:32:00,  2.39s/it]
                                                        

  0%|          | 553/569592 [24:33<378:32:00,  2.39s/it]
  0%|          | 554/569592 [24:35<361:31:06,  2.29s/it]
                                                        

  0%|          | 554/569592 [24:35<361:31:06,  2.29s/it]
  0%|          | 555/569592 [24:39<418:02:18,  2.64s/it]
                                                        

  0%|          | 555/569592 [24:39<418:02:18,  2.64s/it]
  0%|          | 556/569592 [24:41<397:02:09,  2.51s/it]
                                                        

  0%|          | 556/569592 [24:41<397:02:09,  2.51s/it]
  0%|          | 557/569592 [24:42<329:21:59,  2.08s/it]
                                                        

  0%|          | 557/569592 [24:42<329:21:59,  2.08s/it]
  0%|          | 558/569592 [24:46<397:48:14,  2.52s/it]
                                                        

  0%|          | 558/569592 [24:46<397:48:14,  2.52s/it]
  0%|          | 559/569592 [24:49<441:35:30,  2.79s/it]
                                                        

  0%|          | 559/569592 [24:49<441:35:30,  2.79s/it]
  0%|          | 560/569592 [24:50<377:04:57,  2.39s/it]
                                                        

  0%|          | 560/569592 [24:50<377:04:57,  2.39s/it]
  0%|          | 561/569592 [24:51<308:57:48,  1.95s/it]
                                                        

  0%|          | 561/569592 [24:51<308:57:48,  1.95s/it]
  0%|          | 562/569592 [24:55<367:58:07,  2.33s/it]
                                                        

  0%|          | 562/569592 [24:55<367:58:07,  2.33s/it]
  0%|          | 563/569592 [24:59<451:55:09,  2.86s/it]
                                                        

  0%|          | 563/569592 [24:59<451:55:09,  2.86s/it]
  0%|          | 564/569592 [25:00<390:53:55,  2.47s/it]
                                                        

  0%|          | 564/569592 [25:00<390:53:55,  2.47s/it]
  0%|          | 565/569592 [25:01<318:52:25,  2.02s/it]
                                                        

  0%|          | 565/569592 [25:01<318:52:25,  2.02s/it]
  0%|          | 566/569592 [25:06<460:33:09,  2.91s/it]
                                                        

  0%|          | 566/569592 [25:06<460:33:09,  2.91s/it]
  0%|          | 567/569592 [25:10<521:56:01,  3.30s/it]
                                                        

  0%|          | 567/569592 [25:10<521:56:01,  3.30s/it]
  0%|          | 568/569592 [25:11<410:48:20,  2.60s/it]
                                                        

  0%|          | 568/569592 [25:11<410:48:20,  2.60s/it]
  0%|          | 569/569592 [25:15<437:19:25,  2.77s/it]
                                                        

  0%|          | 569/569592 [25:15<437:19:25,  2.77s/it]
  0%|          | 570/569592 [25:16<383:38:23,  2.43s/it]
                                                        

  0%|          | 570/569592 [25:16<383:38:23,  2.43s/it]
  0%|          | 571/569592 [25:21<502:12:06,  3.18s/it]
                                                        

  0%|          | 571/569592 [25:21<502:12:06,  3.18s/it]
  0%|          | 572/569592 [25:25<556:34:56,  3.52s/it]
                                                        

  0%|          | 572/569592 [25:25<556:34:56,  3.52s/it]
  0%|          | 573/569592 [25:29<556:35:17,  3.52s/it]
                                                        

  0%|          | 573/569592 [25:29<556:35:17,  3.52s/it]
  0%|          | 574/569592 [25:34<613:54:57,  3.88s/it]
                                                        

  0%|          | 574/569592 [25:34<613:54:57,  3.88s/it]
  0%|          | 575/569592 [25:38<626:05:25,  3.96s/it]
                                                        

  0%|          | 575/569592 [25:38<626:05:25,  3.96s/it]
  0%|          | 576/569592 [25:41<586:29:15,  3.71s/it]
                                                        

  0%|          | 576/569592 [25:41<586:29:15,  3.71s/it]
  0%|          | 577/569592 [25:44<546:33:27,  3.46s/it]
                                                        

  0%|          | 577/569592 [25:44<546:33:27,  3.46s/it]
  0%|          | 578/569592 [25:47<533:14:48,  3.37s/it]
                                                        

  0%|          | 578/569592 [25:47<533:14:48,  3.37s/it]
  0%|          | 579/569592 [25:52<594:26:54,  3.76s/it]
                                                        

  0%|          | 579/569592 [25:52<594:26:54,  3.76s/it]
  0%|          | 580/569592 [25:56<633:05:30,  4.01s/it]
                                                        

  0%|          | 580/569592 [25:56<633:05:30,  4.01s/it]
  0%|          | 581/569592 [26:01<646:56:17,  4.09s/it]
                                                        

  0%|          | 581/569592 [26:01<646:56:17,  4.09s/it]
  0%|          | 582/569592 [26:05<654:54:22,  4.14s/it]
                                                        

  0%|          | 582/569592 [26:05<654:54:22,  4.14s/it]
  0%|          | 583/569592 [26:10<701:31:03,  4.44s/it]
                                                        

  0%|          | 583/569592 [26:10<701:31:03,  4.44s/it]
  0%|          | 584/569592 [26:15<712:16:18,  4.51s/it]
                                                        

  0%|          | 584/569592 [26:15<712:16:18,  4.51s/it]
  0%|          | 585/569592 [26:18<673:17:30,  4.26s/it]
                                                        

  0%|          | 585/569592 [26:19<673:17:30,  4.26s/it]
  0%|          | 586/569592 [26:23<710:53:06,  4.50s/it]
                                                        

  0%|          | 586/569592 [26:23<710:53:06,  4.50s/it]
  0%|          | 587/569592 [26:29<751:19:00,  4.75s/it]
                                                        

  0%|          | 587/569592 [26:29<751:19:00,  4.75s/it]
  0%|          | 588/569592 [26:34<764:17:17,  4.84s/it]
                                                        

  0%|          | 588/569592 [26:34<764:17:17,  4.84s/it]
  0%|          | 589/569592 [26:35<576:07:48,  3.65s/it]
                                                        

  0%|          | 589/569592 [26:35<576:07:48,  3.65s/it]
  0%|          | 590/569592 [26:36<446:39:37,  2.83s/it]
                                                        

  0%|          | 590/569592 [26:36<446:39:37,  2.83s/it]
  0%|          | 591/569592 [26:37<360:21:36,  2.28s/it]
                                                        

  0%|          | 591/569592 [26:37<360:21:36,  2.28s/it]
  0%|          | 592/569592 [26:37<298:04:51,  1.89s/it]
                                                        

  0%|          | 592/569592 [26:38<298:04:51,  1.89s/it]
  0%|          | 593/569592 [26:38<254:27:55,  1.61s/it]
                                                        

  0%|          | 593/569592 [26:38<254:27:55,  1.61s/it]
  0%|          | 594/569592 [26:39<224:42:47,  1.42s/it]
                                                        

  0%|          | 594/569592 [26:39<224:42:47,  1.42s/it]
  0%|          | 595/569592 [26:40<201:16:21,  1.27s/it]
                                                        

  0%|          | 595/569592 [26:40<201:16:21,  1.27s/it]
  0%|          | 596/569592 [26:41<184:42:01,  1.17s/it]
                                                        

  0%|          | 596/569592 [26:41<184:42:01,  1.17s/it]
  0%|          | 597/569592 [26:47<398:09:07,  2.52s/it]
                                                        

  0%|          | 597/569592 [26:47<398:09:07,  2.52s/it]
  0%|          | 598/569592 [26:49<355:47:16,  2.25s/it]
                                                        

  0%|          | 598/569592 [26:49<355:47:16,  2.25s/it]
  0%|          | 599/569592 [26:50<295:18:30,  1.87s/it]
                                                        

  0%|          | 599/569592 [26:50<295:18:30,  1.87s/it]
  0%|          | 600/569592 [26:51<272:00:00,  1.72s/it]
                                                        

  0%|          | 600/569592 [26:51<272:00:00,  1.72s/it]
  0%|          | 601/569592 [26:57<473:59:22,  3.00s/it]
                                                        

  0%|          | 601/569592 [26:57<473:59:22,  3.00s/it]
  0%|          | 602/569592 [26:58<377:56:45,  2.39s/it]
                                                        

  0%|          | 602/569592 [26:58<377:56:45,  2.39s/it]
  0%|          | 603/569592 [26:59<320:07:17,  2.03s/it]
                                                        

  0%|          | 603/569592 [26:59<320:07:17,  2.03s/it]
  0%|          | 604/569592 [27:01<327:29:00,  2.07s/it]
                                                        

  0%|          | 604/569592 [27:01<327:29:00,  2.07s/it]
  0%|          | 605/569592 [27:07<505:23:38,  3.20s/it]
                                                        

  0%|          | 605/569592 [27:07<505:23:38,  3.20s/it]
  0%|          | 606/569592 [27:09<457:49:58,  2.90s/it]
                                                        

  0%|          | 606/569592 [27:09<457:49:58,  2.90s/it]
  0%|          | 607/569592 [27:10<365:08:39,  2.31s/it]
                                                        

  0%|          | 607/569592 [27:10<365:08:39,  2.31s/it]
  0%|          | 608/569592 [27:13<409:10:16,  2.59s/it]
                                                        

  0%|          | 608/569592 [27:13<409:10:16,  2.59s/it]
  0%|          | 609/569592 [27:17<460:25:09,  2.91s/it]
                                                        

  0%|          | 609/569592 [27:17<460:25:09,  2.91s/it]
  0%|          | 610/569592 [27:19<414:56:32,  2.63s/it]
                                                        

  0%|          | 610/569592 [27:19<414:56:32,  2.63s/it]
  0%|          | 611/569592 [27:20<334:48:14,  2.12s/it]
                                                        

  0%|          | 611/569592 [27:20<334:48:14,  2.12s/it]
  0%|          | 612/569592 [27:23<395:30:51,  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2.50s/it]
                                                        

  0%|          | 612/569592 [27:23<395:30:51,  2.50s/it]
  0%|          | 613/569592 [27:27<437:50:06,  2.77s/it]
                                                        

  0%|          | 613/569592 [27:27<437:50:06,  2.77s/it]
  0%|          | 614/569592 [27:30<459:39:10,  2.91s/it]
                                                        

  0%|          | 614/569592 [27:30<459:39:10,  2.91s/it]
  0%|          | 615/569592 [27:31<367:40:30,  2.33s/it]
                                                        

  0%|          | 615/569592 [27:31<367:40:30,  2.33s/it]
  0%|          | 616/569592 [27:33<375:30:38,  2.38s/it]
                                                        

  0%|          | 616/569592 [27:33<375:30:38,  2.38s/it]
  0%|          | 617/569592 [27:38<457:46:07,  2.90s/it]
                                                        

  0%|          | 617/569592 [27:38<457:46:07,  2.90s/it]
  0%|          | 618/569592 [27:41<459:25:29,  2.91s/it]
                                                        

  0%|          | 618/569592 [27:41<459:25:29,  2.91s/it]
  0%|          | 619/569592 [27:42<376:23:24,  2.38s/it]
                                                        

  0%|          | 619/569592 [27:42<376:23:24,  2.38s/it]
  0%|          | 620/569592 [27:44<349:55:03,  2.21s/it]
                                                        

  0%|          | 620/569592 [27:44<349:55:03,  2.21s/it]
  0%|          | 621/569592 [27:47<429:46:36,  2.72s/it]
                                                        

  0%|          | 621/569592 [27:48<429:46:36,  2.72s/it]
  0%|          | 622/569592 [27:51<451:47:25,  2.86s/it]
                                                        

  0%|          | 622/569592 [27:51<451:47:25,  2.86s/it]
  0%|          | 623/569592 [27:52<362:26:43,  2.29s/it]
                                                        

  0%|          | 623/569592 [27:52<362:26:43,  2.29s/it]
  0%|          | 624/569592 [27:54<358:01:44,  2.27s/it]
                                                        

  0%|          | 624/569592 [27:54<358:01:44,  2.27s/it]
  0%|          | 625/569592 [27:59<494:53:23,  3.13s/it]
                                                        

  0%|          | 625/569592 [27:59<494:53:23,  3.13s/it]
  0%|          | 626/569592 [28:02<470:23:58,  2.98s/it]
                                                        

  0%|          | 626/569592 [28:02<470:23:58,  2.98s/it]
  0%|          | 627/569592 [28:03<378:38:58,  2.40s/it]
                                                        

  0%|          | 627/569592 [28:03<378:38:58,  2.40s/it]
  0%|          | 628/569592 [28:04<344:59:58,  2.18s/it]
                                                        

  0%|          | 628/569592 [28:04<344:59:58,  2.18s/it]
  0%|          | 629/569592 [28:09<455:14:57,  2.88s/it]
                                                        

  0%|          | 629/569592 [28:09<455:14:57,  2.88s/it]
  0%|          | 630/569592 [28:12<456:32:23,  2.89s/it]
                                                        

  0%|          | 630/569592 [28:12<456:32:23,  2.89s/it]
  0%|          | 631/569592 [28:13<367:00:08,  2.32s/it]
                                                        

  0%|          | 631/569592 [28:13<367:00:08,  2.32s/it]
  0%|          | 632/569592 [28:15<351:03:57,  2.22s/it]
                                                        

  0%|          | 632/569592 [28:15<351:03:57,  2.22s/it]
  0%|          | 633/569592 [28:18<417:57:07,  2.64s/it]
                                                        

  0%|          | 633/569592 [28:18<417:57:07,  2.64s/it]
  0%|          | 634/569592 [28:22<464:03:34,  2.94s/it]
                                                        

  0%|          | 634/569592 [28:22<464:03:34,  2.94s/it]
  0%|          | 635/569592 [28:23<383:39:57,  2.43s/it]
                                                        

  0%|          | 635/569592 [28:23<383:39:57,  2.43s/it]
  0%|          | 636/569592 [28:25<342:58:05,  2.17s/it]
                                                        

  0%|          | 636/569592 [28:25<342:58:05,  2.17s/it]
  0%|          | 637/569592 [28:30<478:01:05,  3.02s/it]
                                                        

  0%|          | 637/569592 [28:30<478:01:05,  3.02s/it]
  0%|          | 638/569592 [28:32<439:30:57,  2.78s/it]
                                                        

  0%|          | 638/569592 [28:32<439:30:57,  2.78s/it]
  0%|          | 639/569592 [28:33<352:48:28,  2.23s/it]
                                                        

  0%|          | 639/569592 [28:33<352:48:28,  2.23s/it]
  0%|          | 640/569592 [28:35<330:31:26,  2.09s/it]
                                                        

  0%|          | 640/569592 [28:35<330:31:26,  2.09s/it]
  0%|          | 641/569592 [28:40<477:12:45,  3.02s/it]
                                                        

  0%|          | 641/569592 [28:40<477:12:45,  3.02s/it]
  0%|          | 642/569592 [28:42<436:16:19,  2.76s/it]
                                                        

  0%|          | 642/569592 [28:42<436:16:19,  2.76s/it]
  0%|          | 643/569592 [28:44<410:56:05,  2.60s/it]
                                                        

  0%|          | 643/569592 [28:44<410:56:05,  2.60s/it]
  0%|          | 644/569592 [28:45<333:42:20,  2.11s/it]
                                                        

  0%|          | 644/569592 [28:45<333:42:20,  2.11s/it]
  0%|          | 645/569592 [28:50<463:31:54,  2.93s/it]
                                                        

  0%|          | 645/569592 [28:50<463:31:54,  2.93s/it]
  0%|          | 646/569592 [28:52<429:41:41,  2.72s/it]
                                                        

  0%|          | 646/569592 [28:52<429:41:41,  2.72s/it]
  0%|          | 647/569592 [28:53<345:48:25,  2.19s/it]
                                                        

  0%|          | 647/569592 [28:53<345:48:25,  2.19s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100239104 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  0%|          | 648/569592 [28:55<342:09:30,  2.17s/it]
                                                        

  0%|          | 648/569592 [28:55<342:09:30,  2.17s/it]
  0%|          | 649/569592 [29:00<478:52:39,  3.03s/it]
                                                        

  0%|          | 649/569592 [29:00<478:52:39,  3.03s/it]
  0%|          | 650/569592 [29:03<438:19:22,  2.77s/it]
                                                        

  0%|          | 650/569592 [29:03<438:19:22,  2.77s/it]
  0%|          | 651/569592 [29:04<352:15:35,  2.23s/it]
                                                        

  0%|          | 651/569592 [29:04<352:15:35,  2.23s/it]
  0%|          | 652/569592 [29:05<337:28:08,  2.14s/it]
                                                        

  0%|          | 652/569592 [29:05<337:28:08,  2.14s/it]
  0%|          | 653/569592 [29:11<478:02:29,  3.02s/it]
                                                        

  0%|          | 653/569592 [29:11<478:02:29,  3.02s/it]
  0%|          | 654/569592 [29:13<447:02:22,  2.83s/it]
                                                        

  0%|          | 654/569592 [29:13<447:02:22,  2.83s/it]
  0%|          | 655/569592 [29:14<358:25:48,  2.27s/it]
                                                        

  0%|          | 655/569592 [29:14<358:25:48,  2.27s/it]
  0%|          | 656/569592 [29:15<308:10:24,  1.95s/it]
                                                        

  0%|          | 656/569592 [29:15<308:10:24,  1.95s/it]
  0%|          | 657/569592 [29:19<425:19:35,  2.69s/it]
                                                        

  0%|          | 657/569592 [29:20<425:19:35,  2.69s/it]
  0%|          | 658/569592 [29:23<462:37:02,  2.93s/it]
                                                        

  0%|          | 658/569592 [29:23<462:37:02,  2.93s/it]
  0%|          | 659/569592 [29:25<428:42:12,  2.71s/it]
                                                        

  0%|          | 659/569592 [29:25<428:42:12,  2.71s/it]
  0%|          | 660/569592 [29:26<343:56:36,  2.18s/it]
                                                        

  0%|          | 660/569592 [29:26<343:56:36,  2.18s/it]
  0%|          | 661/569592 [29:31<483:40:27,  3.06s/it]
                                                        

  0%|          | 661/569592 [29:31<483:40:27,  3.06s/it]
  0%|          | 662/569592 [29:32<383:00:53,  2.42s/it]
                                                        

  0%|          | 662/569592 [29:32<383:00:53,  2.42s/it]
  0%|          | 663/569592 [29:35<421:24:34,  2.67s/it]
                                                        

  0%|          | 663/569592 [29:35<421:24:34,  2.67s/it]
  0%|          | 664/569592 [29:36<340:32:26,  2.15s/it]
                                                        

  0%|          | 664/569592 [29:36<340:32:26,  2.15s/it]
  0%|          | 665/569592 [29:41<465:45:14,  2.95s/it]
                                                        

  0%|          | 665/569592 [29:41<465:45:14,  2.95s/it]
  0%|          | 666/569592 [29:42<385:09:14,  2.44s/it]
                                                        

  0%|          | 666/569592 [29:42<385:09:14,  2.44s/it]
  0%|          | 667/569592 [29:45<412:34:26,  2.61s/it]
                                                        

  0%|          | 667/569592 [29:45<412:34:26,  2.61s/it]
  0%|          | 668/569592 [29:47<363:47:10,  2.30s/it]
                                                        

  0%|          | 668/569592 [29:47<363:47:10,  2.30s/it]
  0%|          | 669/569592 [29:51<452:57:24,  2.87s/it]
                                                        

  0%|          | 669/569592 [29:52<452:57:24,  2.87s/it]
  0%|          | 670/569592 [29:53<404:05:43,  2.56s/it]
                                                        

  0%|          | 670/569592 [29:53<404:05:43,  2.56s/it]
  0%|          | 671/569592 [29:55<355:44:57,  2.25s/it]
                                                        

  0%|          | 671/569592 [29:55<355:44:57,  2.25s/it]
  0%|          | 672/569592 [29:56<295:05:25,  1.87s/it]
                                                        

  0%|          | 672/569592 [29:56<295:05:25,  1.87s/it]
  0%|          | 673/569592 [30:01<464:20:59,  2.94s/it]
                                                        

  0%|          | 673/569592 [30:01<464:20:59,  2.94s/it]
  0%|          | 674/569592 [30:04<484:32:59,  3.07s/it]
                                                        

  0%|          | 674/569592 [30:04<484:32:59,  3.07s/it]
  0%|          | 675/569592 [30:05<388:28:25,  2.46s/it]
                                                        

  0%|          | 675/569592 [30:05<388:28:25,  2.46s/it]
  0%|          | 676/569592 [30:06<322:35:13,  2.04s/it]
                                                        

  0%|          | 676/569592 [30:06<322:35:13,  2.04s/it]
  0%|          | 677/569592 [30:11<436:16:02,  2.76s/it]
                                                        

  0%|          | 677/569592 [30:11<436:16:02,  2.76s/it]
  0%|          | 678/569592 [30:13<416:59:09,  2.64s/it]
                                                        

  0%|          | 678/569592 [30:13<416:59:09,  2.64s/it]
  0%|          | 679/569592 [30:17<466:08:00,  2.95s/it]
                                                        

  0%|          | 679/569592 [30:17<466:08:00,  2.95s/it]
  0%|          | 680/569592 [30:21<509:13:47,  3.22s/it]
                                                        

  0%|          | 680/569592 [30:21<509:13:47,  3.22s/it]
  0%|          | 681/569592 [30:22<399:24:06,  2.53s/it]
                                                        

  0%|          | 681/569592 [30:22<399:24:06,  2.53s/it]
  0%|          | 682/569592 [30:24<380:51:02,  2.41s/it]
                                                        

  0%|          | 682/569592 [30:24<380:51:02,  2.41s/it]
  0%|          | 683/569592 [30:26<357:34:12,  2.26s/it]
                                                        

  0%|          | 683/569592 [30:26<357:34:12,  2.26s/it]
  0%|          | 684/569592 [30:29<412:55:28,  2.61s/it]
                                                        

  0%|          | 684/569592 [30:29<412:55:28,  2.61s/it]
  0%|          | 685/569592 [30:33<472:06:27,  2.99s/it]
                                                        

  0%|          | 685/569592 [30:33<472:06:27,  2.99s/it]
  0%|          | 686/569592 [30:37<505:18:45,  3.20s/it]
                                                        

  0%|          | 686/569592 [30:37<505:18:45,  3.20s/it]
  0%|          | 687/569592 [30:38<408:33:30,  2.59s/it]
                                                        

  0%|          | 687/569592 [30:38<408:33:30,  2.59s/it]
  0%|          | 688/569592 [30:42<494:04:46,  3.13s/it]
                                                        

  0%|          | 688/569592 [30:42<494:04:46,  3.13s/it]
  0%|          | 689/569592 [30:47<587:55:30,  3.72s/it]
                                                        

  0%|          | 689/569592 [30:47<587:55:30,  3.72s/it]
  0%|          | 690/569592 [30:51<561:25:20,  3.55s/it]
                                                        

  0%|          | 690/569592 [30:51<561:25:20,  3.55s/it]
  0%|          | 691/569592 [30:55<623:38:55,  3.95s/it]
                                                        

  0%|          | 691/569592 [30:55<623:38:55,  3.95s/it]
  0%|          | 692/569592 [31:00<662:13:49,  4.19s/it]
                                                        

  0%|          | 692/569592 [31:00<662:13:49,  4.19s/it]
  0%|          | 693/569592 [31:04<628:04:06,  3.97s/it]
                                                        

  0%|          | 693/569592 [31:04<628:04:06,  3.97s/it]
  0%|          | 694/569592 [31:09<674:04:52,  4.27s/it]
                                                        

  0%|          | 694/569592 [31:09<674:04:52,  4.27s/it]
  0%|          | 695/569592 [31:13<695:13:49,  4.40s/it]
                                                        

  0%|          | 695/569592 [31:13<695:13:49,  4.40s/it]
  0%|          | 696/569592 [31:18<701:36:45,  4.44s/it]
                                                        

  0%|          | 696/569592 [31:18<701:36:45,  4.44s/it]
  0%|          | 697/569592 [31:22<713:56:05,  4.52s/it]
                                                        

  0%|          | 697/569592 [31:23<713:56:05,  4.52s/it]
  0%|          | 698/569592 [31:27<723:13:50,  4.58s/it]
                                                        

  0%|          | 698/569592 [31:27<723:13:50,  4.58s/it]
  0%|          | 699/569592 [31:32<722:21:30,  4.57s/it]
                                                        

  0%|          | 699/569592 [31:32<722:21:30,  4.57s/it]
  0%|          | 700/569592 [31:37<753:57:07,  4.77s/it]
                                                        

  0%|          | 700/569592 [31:37<753:57:07,  4.77s/it]
  0%|          | 701/569592 [31:38<568:56:26,  3.60s/it]
                                                        

  0%|          | 701/569592 [31:38<568:56:26,  3.60s/it]
  0%|          | 702/569592 [31:43<638:08:54,  4.04s/it]
                                                        

  0%|          | 702/569592 [31:43<638:08:54,  4.04s/it]
  0%|          | 703/569592 [31:47<649:20:05,  4.11s/it]
                                                        

  0%|          | 703/569592 [31:47<649:20:05,  4.11s/it]
  0%|          | 704/569592 [31:52<687:24:41,  4.35s/it]
                                                        

  0%|          | 704/569592 [31:52<687:24:41,  4.35s/it]
  0%|          | 705/569592 [31:57<714:49:21,  4.52s/it]
                                                        

  0%|          | 705/569592 [31:57<714:49:21,  4.52s/it]
  0%|          | 706/569592 [31:58<542:38:44,  3.43s/it]
                                                        

  0%|          | 706/569592 [31:58<542:38:44,  3.43s/it]
  0%|          | 707/569592 [31:59<423:13:07,  2.68s/it]
                                                        

  0%|          | 707/569592 [31:59<423:13:07,  2.68s/it]
  0%|          | 708/569592 [32:00<342:37:02,  2.17s/it]
                                                        

  0%|          | 708/569592 [32:00<342:37:02,  2.17s/it]
  0%|          | 709/569592 [32:01<287:57:26,  1.82s/it]
                                                        

  0%|          | 709/569592 [32:01<287:57:26,  1.82s/it]
  0%|          | 710/569592 [32:02<247:22:27,  1.57s/it]
                                                        

  0%|          | 710/569592 [32:02<247:22:27,  1.57s/it]
  0%|          | 711/569592 [32:03<219:05:15,  1.39s/it]
                                                        

  0%|          | 711/569592 [32:03<219:05:15,  1.39s/it]
  0%|          | 712/569592 [32:04<198:20:02,  1.26s/it]
                                                        

  0%|          | 712/569592 [32:04<198:20:02,  1.26s/it]
  0%|          | 713/569592 [32:05<184:30:15,  1.17s/it]
                          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                              

  0%|          | 713/569592 [32:05<184:30:15,  1.17s/it]
  0%|          | 714/569592 [32:10<399:21:34,  2.53s/it]
                                                        

  0%|          | 714/569592 [32:10<399:21:34,  2.53s/it]
  0%|          | 715/569592 [32:11<330:32:40,  2.09s/it]
                                                        

  0%|          | 715/569592 [32:11<330:32:40,  2.09s/it]
  0%|          | 716/569592 [32:13<318:20:17,  2.01s/it]
                                                        

  0%|          | 716/569592 [32:13<318:20:17,  2.01s/it]
  0%|          | 717/569592 [32:14<269:10:46,  1.70s/it]
                                                        

  0%|          | 717/569592 [32:14<269:10:46,  1.70s/it]
  0%|          | 718/569592 [32:21<525:30:43,  3.33s/it]
                                                        

  0%|          | 718/569592 [32:21<525:30:43,  3.33s/it]
  0%|          | 719/569592 [32:23<421:46:43,  2.67s/it]
                                                        

  0%|          | 719/569592 [32:23<421:46:43,  2.67s/it]
  0%|          | 720/569592 [32:24<344:22:58,  2.18s/it]
                                                        

  0%|          | 720/569592 [32:24<344:22:58,  2.18s/it]
  0%|          | 721/569592 [32:25<305:55:01,  1.94s/it]
                                                        

  0%|          | 721/569592 [32:25<305:55:01,  1.94s/it]
  0%|          | 722/569592 [32:31<489:11:32,  3.10s/it]
                                                        

  0%|          | 722/569592 [32:31<489:11:32,  3.10s/it]
  0%|          | 723/569592 [32:32<391:01:18,  2.47s/it]
                                                        

  0%|          | 723/569592 [32:32<391:01:18,  2.47s/it]
  0%|          | 724/569592 [32:33<330:37:14,  2.09s/it]
                                                        

  0%|          | 724/569592 [32:33<330:37:14,  2.09s/it]
  0%|          | 725/569592 [32:35<312:15:56,  1.98s/it]
                                                        

  0%|          | 725/569592 [32:35<312:15:56,  1.98s/it]
  0%|          | 726/569592 [32:42<555:00:13,  3.51s/it]
                                                        

  0%|          | 726/569592 [32:42<555:00:13,  3.51s/it]
  0%|          | 727/569592 [32:43<438:26:27,  2.77s/it]
                                                        

  0%|          | 727/569592 [32:43<438:26:27,  2.77s/it]
  0%|          | 728/569592 [32:44<352:39:37,  2.23s/it]
                                                        

  0%|          | 728/569592 [32:44<352:39:37,  2.23s/it]
  0%|          | 729/569592 [32:45<292:53:01,  1.85s/it]
                                                        

  0%|          | 729/569592 [32:45<292:53:01,  1.85s/it]
  0%|          | 730/569592 [32:52<561:17:47,  3.55s/it]
                                                        

  0%|          | 730/569592 [32:52<561:17:47,  3.55s/it]
  0%|          | 731/569592 [32:53<443:57:54,  2.81s/it]
                                                        

  0%|          | 731/569592 [32:53<443:57:54,  2.81s/it]
  0%|          | 732/569592 [32:54<356:57:34,  2.26s/it]
                                                        

  0%|          | 732/569592 [32:54<356:57:34,  2.26s/it]
  0%|          | 733/569592 [32:56<320:28:30,  2.03s/it]
                                                        

  0%|          | 733/569592 [32:56<320:28:30,  2.03s/it]
  0%|          | 734/569592 [33:01<491:12:42,  3.11s/it]
                                                        

  0%|          | 734/569592 [33:01<491:12:42,  3.11s/it]
  0%|          | 735/569592 [33:03<407:40:48,  2.58s/it]
                                                        

  0%|          | 735/569592 [33:03<407:40:48,  2.58s/it]
  0%|          | 736/569592 [33:04<330:22:07,  2.09s/it]
                                                        

  0%|          | 736/569592 [33:04<330:22:07,  2.09s/it]
  0%|          | 737/569592 [33:06<323:17:42,  2.05s/it]
                                                        

  0%|          | 737/569592 [33:06<323:17:42,  2.05s/it]
  0%|          | 738/569592 [33:12<530:58:57,  3.36s/it]
                                                        

  0%|          | 738/569592 [33:12<530:58:57,  3.36s/it]
  0%|          | 739/569592 [33:13<416:07:30,  2.63s/it]
                                                        

  0%|          | 739/569592 [33:13<416:07:30,  2.63s/it]
  0%|          | 740/569592 [33:14<344:56:59,  2.18s/it]
                                                        

  0%|          | 740/569592 [33:14<344:56:59,  2.18s/it]
  0%|          | 741/569592 [33:15<287:26:03,  1.82s/it]
                                                        

  0%|          | 741/569592 [33:15<287:26:03,  1.82s/it]
  0%|          | 742/569592 [33:22<532:08:47,  3.37s/it]
                                                        

  0%|          | 742/569592 [33:22<532:08:47,  3.37s/it]
  0%|          | 743/569592 [33:23<424:09:01,  2.68s/it]
                                                        

  0%|          | 743/569592 [33:23<424:09:01,  2.68s/it]
  0%|          | 744/569592 [33:24<356:13:12,  2.25s/it]
                                                        

  0%|          | 744/569592 [33:24<356:13:12,  2.25s/it]
  0%|          | 745/569592 [33:26<324:26:20,  2.05s/it]
                                                        

  0%|          | 745/569592 [33:26<324:26:20,  2.05s/it]
  0%|          | 746/569592 [33:32<527:43:48,  3.34s/it]
                                                        

  0%|          | 746/569592 [33:32<527:43:48,  3.34s/it]
  0%|          | 747/569592 [33:33<415:56:22,  2.63s/it]
                                                        

  0%|          | 747/569592 [33:33<415:56:22,  2.63s/it]
  0%|          | 748/569592 [33:34<335:30:44,  2.12s/it]
                                                        

  0%|          | 748/569592 [33:34<335:30:44,  2.12s/it]
  0%|          | 749/569592 [33:37<343:49:01,  2.18s/it]
                                                        

  0%|          | 749/569592 [33:37<343:49:01,  2.18s/it]
  0%|          | 750/569592 [33:44<614:23:37,  3.89s/it]
                                                        

  0%|          | 750/569592 [33:45<614:23:37,  3.89s/it]
  0%|          | 751/569592 [33:45<475:14:29,  3.01s/it]
                                                        

  0%|          | 751/569592 [33:45<475:14:29,  3.01s/it]
  0%|          | 752/569592 [33:46<378:39:22,  2.40s/it]
                                                        

  0%|          | 752/569592 [33:46<378:39:22,  2.40s/it]
  0%|          | 753/569592 [33:48<330:22:17,  2.09s/it]
                                                        

  0%|          | 753/569592 [33:48<330:22:17,  2.09s/it]
  0%|          | 754/569592 [33:53<493:34:24,  3.12s/it]
                                                        

  0%|          | 754/569592 [33:53<493:34:24,  3.12s/it]
  0%|          | 755/569592 [33:54<389:40:24,  2.47s/it]
                                                        

  0%|          | 755/569592 [33:54<389:40:24,  2.47s/it]
  0%|          | 756/569592 [33:55<317:49:20,  2.01s/it]
                                                        

  0%|          | 756/569592 [33:55<317:49:20,  2.01s/it]
  0%|          | 757/569592 [33:56<268:04:56,  1.70s/it]
                                                        

  0%|          | 757/569592 [33:56<268:04:56,  1.70s/it]
  0%|          | 758/569592 [34:04<537:33:58,  3.40s/it]
                                                        

  0%|          | 758/569592 [34:04<537:33:58,  3.40s/it]
  0%|          | 759/569592 [34:04<420:36:26,  2.66s/it]
                                                        

  0%|          | 759/569592 [34:05<420:36:26,  2.66s/it]
  0%|          | 760/569592 [34:06<385:15:03,  2.44s/it]
                                                        

  0%|          | 760/569592 [34:06<385:15:03,  2.44s/it]
  0%|          | 761/569592 [34:07<315:36:22,  2.00s/it]
                                                        

  0%|          | 761/569592 [34:07<315:36:22,  2.00s/it]
  0%|          | 762/569592 [34:16<623:39:27,  3.95s/it]
                                                        

  0%|          | 762/569592 [34:16<623:39:27,  3.95s/it]
  0%|          | 763/569592 [34:17<482:28:12,  3.05s/it]
                                                        

  0%|          | 763/569592 [34:17<482:28:12,  3.05s/it]
  0%|          | 764/569592 [34:18<381:45:24,  2.42s/it]
                                                        

  0%|          | 764/569592 [34:18<381:45:24,  2.42s/it]
  0%|          | 765/569592 [34:19<316:50:30,  2.01s/it]
                                                        

  0%|          | 765/569592 [34:19<316:50:30,  2.01s/it]
  0%|          | 766/569592 [34:26<545:41:08,  3.45s/it]
                                                        

  0%|          | 766/569592 [34:26<545:41:08,  3.45s/it]
  0%|          | 767/569592 [34:27<431:47:59,  2.73s/it]
                                                        

  0%|          | 767/569592 [34:27<431:47:59,  2.73s/it]
  0%|          | 768/569592 [34:28<350:36:19,  2.22s/it]
                                                        

  0%|          | 768/569592 [34:28<350:36:19,  2.22s/it]
  0%|          | 769/569592 [34:29<289:32:01,  1.83s/it]
                                                        

  0%|          | 769/569592 [34:29<289:32:01,  1.83s/it]
  0%|          | 770/569592 [34:36<536:51:29,  3.40s/it]
                                                        

  0%|          | 770/569592 [34:36<536:51:29,  3.40s/it]
  0%|          | 771/569592 [34:37<419:34:16,  2.66s/it]
                                                        

  0%|          | 771/569592 [34:37<419:34:16,  2.66s/it]
  0%|          | 772/569592 [34:38<339:10:05,  2.15s/it]
                                                        

  0%|          | 772/569592 [34:38<339:10:05,  2.15s/it]
  0%|          | 773/569592 [34:39<282:17:45,  1.79s/it]
                                                        

  0%|          | 773/569592 [34:39<282:17:45,  1.79s/it]
  0%|          | 774/569592 [34:46<535:25:40,  3.39s/it]
                                                        

  0%|          | 774/569592 [34:46<535:25:40,  3.39s/it]
  0%|          | 775/569592 [34:47<420:34:46,  2.66s/it]
                                                        

  0%|          | 775/569592 [34:47<420:34:46,  2.66s/it]
  0%|          | 776/569592 [34:48<340:16:50,  2.15s/it]
                                                        

  0%|          | 776/569592 [34:48<340:16:50,  2.15s/it]
  0%|          | 777/569592 [34:49<283:55:31,  1.80s/it]
                                                        

  0%|          | 777/569592 [34:49<283:55:31,  1.80s/it]
  0%|          | 778/569592 [34:55<518:46:46,  3.28s/it]
                                                        

  0%|          | 778/569592 [34:55<518:46:46,  3.28s/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/it]
  0%|          | 779/569592 [34:56<412:14:39,  2.61s/it]
                                                        

  0%|          | 779/569592 [34:56<412:14:39,  2.61s/it]
  0%|          | 780/569592 [34:57<332:49:14,  2.11s/it]
                                                        

  0%|          | 780/569592 [34:57<332:49:14,  2.11s/it]
  0%|          | 781/569592 [34:59<300:05:30,  1.90s/it]
                                                        

  0%|          | 781/569592 [34:59<300:05:30,  1.90s/it]
  0%|          | 782/569592 [35:05<505:26:51,  3.20s/it]
                                                        

  0%|          | 782/569592 [35:05<505:26:51,  3.20s/it]
  0%|          | 783/569592 [35:06<399:10:19,  2.53s/it]
                                                        

  0%|          | 783/569592 [35:06<399:10:19,  2.53s/it]
  0%|          | 784/569592 [35:07<348:29:19,  2.21s/it]
                                                        

  0%|          | 784/569592 [35:07<348:29:19/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95501700 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
,  2.21s/it]
  0%|          | 785/569592 [35:08<292:14:08,  1.85s/it]
                                                        

  0%|          | 785/569592 [35:08<292:14:08,  1.85s/it]
  0%|          | 786/569592 [35:13<440:07:24,  2.79s/it]
                                                        

  0%|          | 786/569592 [35:13<440:07:24,  2.79s/it]
  0%|          | 787/569592 [35:14<354:47:17,  2.25s/it]
                                                        

  0%|          | 787/569592 [35:14<354:47:17,  2.25s/it]
  0%|          | 788/569592 [35:18<410:03:51,  2.60s/it]
                                                        

  0%|          | 788/569592 [35:18<410:03:51,  2.60s/it]
  0%|          | 789/569592 [35:19<331:53:23,  2.10s/it]
                                                        

  0%|          | 789/569592 [35:19<331:53:23,  2.10s/it]
  0%|          | 790/569592 [35:24<490:39:31,  3.11s/it]
                                                        

  0%|          | 790/569592 [35:24<490:39:31,  3.11s/it]
  0%|          | 791/569592 [35:25<395:04:17,  2.50s/it]
                                                        

  0%|          | 791/569592 [35:25<395:04:17,  2.50s/it]
  0%|          | 792/569592 [35:28<431:10:20,  2.73s/it]
                                                        

  0%|          | 792/569592 [35:28<431:10:20,  2.73s/it]
  0%|          | 793/569592 [35:29<345:45:46,  2.19s/it]
                                                        

  0%|          | 793/569592 [35:29<345:45:46,  2.19s/it]
  0%|          | 794/569592 [35:33<402:19:05,  2.55s/it]
                                                        

  0%|          | 794/569592 [35:33<402:19:05,  2.55s/it]
  0%|          | 795/569592 [35:34<331:12:08,  2.10s/it]
                                                        

  0%|          | 795/569592 [35:34<331:12:08,  2.10s/it]
  0%|          | 796/569592 [35:38<424:56:11,  2.69s/it]
                                                        

  0%|          | 796/569592 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90017188 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
[35:38<424:56:11,  2.69s/it]
  0%|          | 797/569592 [35:43<529:42:04,  3.35s/it]
                                                        

  0%|          | 797/569592 [35:43<529:42:04,  3.35s/it]
  0%|          | 798/569592 [35:47<579:22:49,  3.67s/it]
                                                        

  0%|          | 798/569592 [35:47<579:22:49,  3.67s/it]
  0%|          | 799/569592 [35:52<623:25:36,  3.95s/it]
                                                        

  0%|          | 799/569592 [35:52<623:25:36,  3.95s/it]
  0%|          | 800/569592 [35:56<625:27:17,  3.96s/it]
                                                        

  0%|          | 800/569592 [35:56<625:27:17,  3.96s/it]
  0%|          | 801/569592 [36:00<654:31:44,  4.14s/it]
                                                        

  0%|          | 801/569592 [36:00<654:31:44,  4.14s/it]
  0%|          | 802/569592 [36:04<615:15:54,  3.89s/it]
                                                        

  0%|          | 802/569592 [36:04<615:15:54,  3.89s/it]
  0%|          | 803/569592 [36:08<651:40:05,  4.12s/it]
                                                        

  0%|          | 803/569592 [36:08<651:40:05,  4.12s/it]
  0%|          | 804/569592 [36:13<679:56:19,  4.30s/it]
                                                        

  0%|          | 804/569592 [36:13<679:56:19,  4.30s/it]
  0%|          | 805/569592 [36:16<621:41:10,  3.93s/it]
                                                        

  0%|          | 805/569592 [36:16<621:41:10,  3.93s/it]
  0%|          | 806/569592 [36:19<588:48:55,  3.73s/it]
                                                        

  0%|          | 806/569592 [36:19<588:48:55,  3.73s/it]
  0%|          | 807/569592 [36:24<654:12:32,  4.14s/it]
                                                        

  0%|          | 807/569592 [36:24<654:12:32,  4.14s/it]
  0%|          | 808/569592 [36:29<678:01:57,  4.29s/it]
                                                        

  0%|       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   | 808/569592 [36:29<678:01:57,  4.29s/it]
  0%|          | 809/569592 [36:34<698:12:26,  4.42s/it]
                                                        

  0%|          | 809/569592 [36:34<698:12:26,  4.42s/it]
  0%|          | 810/569592 [36:39<734:28:36,  4.65s/it]
                                                        

  0%|          | 810/569592 [36:39<734:28:36,  4.65s/it]
  0%|          | 811/569592 [36:44<739:05:48,  4.68s/it]
                                                        

  0%|          | 811/569592 [36:44<739:05:48,  4.68s/it]
  0%|          | 812/569592 [36:49<756:31:48,  4.79s/it]
                                                        

  0%|          | 812/569592 [36:49<756:31:48,  4.79s/it]
  0%|          | 813/569592 [36:52<680:12:54,  4.31s/it]
                                                        

  0%|          | 813/569592 [36:52<680:12:54,  4.31s/it]
  0%|          | 814/569592 [36:57<698:23:58,  4.42s/it]
                                                        

  0%|          | 814/569592 [36:57<698:23:58,  4.42s/it]
  0%|          | 815/569592 [37:00<667:38:15,  4.23s/it]
                                                        

  0%|          | 815/569592 [37:00<667:38:15,  4.23s/it]
  0%|          | 816/569592 [37:05<685:51:40,  4.34s/it]
                                                        

  0%|          | 816/569592 [37:05<685:51:40,  4.34s/it]
  0%|          | 817/569592 [37:08<633:56:42,  4.01s/it]
                                                        

  0%|          | 817/569592 [37:08<633:56:42,  4.01s/it]
  0%|          | 818/569592 [37:13<673:54:51,  4.27s/it]
                                                        

  0%|          | 818/569592 [37:13<673:54:51,  4.27s/it]
  0%|          | 819/569592 [37:18<693:43:44,  4.39s/it]
                                                        

  0%|          | 819/569592 [37:18<693:43:44,  4.39s/it]
  0%|          | 820/569592 [37:22<701:13:13,  4.44s/it]
                                                        

  0%|          | 820/569592 [37:22<701:13:13,  4.44s/it]
  0%|          | 821/569592 [37:27<707:55:48,  4.48s/it]
                                                        

  0%|          | 821/569592 [37:27<707:55:48,  4.48s/it]
  0%|          | 822/569592 [37:30<639:55:24,  4.05s/it]
                                                        

  0%|          | 822/569592 [37:30<639:55:24,  4.05s/it]
  0%|          | 823/569592 [37:35<687:25:12,  4.35s/it]
                                                        

  0%|          | 823/569592 [37:35<687:25:12,  4.35s/it]
  0%|          | 824/569592 [37:36<524:03:45,  3.32s/it]
                                                        

  0%|          | 824/569592 [37:36<524:03:45,  3.32s/it]
  0%|          | 825/569592 [37:37<411:34:41,  2.61s/it]
                                                        

  0%|          | 825/569592 [37:37<411:34:41,  2.61s/it]
  0%|          | 826/569592 [37:38<333:45:55,  2.11s/it]
                                                        

  0%|          | 826/569592 [37:38<333:45:55,  2.11s/it]
  0%|          | 827/569592 [37:39<280:18:18,  1.77s/it]
                                                        

  0%|          | 827/569592 [37:39<280:18:18,  1.77s/it]
  0%|          | 828/569592 [37:40<241:23:00,  1.53s/it]
                                                        

  0%|          | 828/569592 [37:40<241:23:00,  1.53s/it]
  0%|          | 829/569592 [37:41<214:35:53,  1.36s/it]
                                                        

  0%|          | 829/569592 [37:41<214:35:53,  1.36s/it]
  0%|          | 830/569592 [37:42<200:34:26,  1.27s/it]
                                                        

  0%|          | 830/569592 [37:42<200:34:26,  1.27s/it]
  0%|          | 831/569592 [37:43<186:13:08,  1.18s/it]
                                                        

  0%|          | 831/569592 [37:43<186:13:08,  1.18s/it]
  0%|          | 832/569592 [37:49<405:20:44,  2.57s/it]
                                                        

  0%|          | 832/569592 [37:49<405:20:44,  2.57s/it]
  0%|          | 833/569592 [37:50<334:44:04,  2.12s/it]
                                                        

  0%|          | 833/569592 [37:50<334:44:04,  2.12s/it]
  0%|          | 834/569592 [37:51<300:33:00,  1.90s/it]
                                                        

  0%|          | 834/569592 [37:51<300:33:00,  1.90s/it]
  0%|          | 835/569592 [37:52<256:45:36,  1.63s/it]
                                                        

  0%|          | 835/569592 [37:52<256:45:36,  1.63s/it]
  0%|          | 836/569592 [37:59<499:17:59,  3.16s/it]
                                                        

  0%|          | 836/569592 [37:59<499:17:59,  3.16s/it]
  0%|          | 837/569592 [38:00<409:39:38,  2.59s/it]
                                                        

  0%|          | 837/569592 [38:00<409:39:38,  2.59s/it]
  0%|          | 838/569592 [38:01<332:31:56,  2.10s/it]
                                                        

  0%|          | 838/569592 [38:01<332:31:56,  2.10s/it]
  0%|          | 839/569592 [38:02<277:31:26,  1.76s/it]
                                                        

  0%|          | 839/569592 [38:02<277:31:26,  1.76s/it]
  0%|          | 840/569592 [38:09<504:28:42,  3.19s/it]
                                                        

  0%|          | 840/569592 [38:09<504:28:42,  3.19s/it]
  0%|          | 841/569592 [38:10<423:54:28,  2.68s/it]
                                                        

  0%|          | 841/569592 [38:10<423:54:28,  2.68s/it]
  0%|          | 842/569592 [38:11<342:01:27,  2.16s/it]
                                                        

  0%|          | 842/569592 [38:11<342:01:27,  2.16s/it]
  0%|          | 843/569592 [38:12<306:02:34,  1.94s/it]
                                                        

  0%|          | 843/569592 [38:12<306:02:34,  1.94s/it]
  0%|          | 844/569592 [38:19<543:10:10,  3.44s/it]
                                                        

  0%|          | 844/569592 [38:19<543:10:10,  3.44s/it]
  0%|          | 845/569592 [38:20<433:09:29,  2.74s/it]
                                                        

  0%|          | 845/569592 [38:20<433:09:29,  2.74s/it]
  0%|          | 846/569592 [38:21<348:58:16,  2.21s/it]
                                                        

  0%|          | 846/569592 [38:21<348:58:16,  2.21s/it]
  0%|          | 847/569592 [38:23<303:12:22,  1.92s/it]
                                                        

  0%|          | 847/569592 [38:23<303:12:22,  1.92s/it]
  0%|          | 848/569592 [38:29<527:10:27,  3.34s/it]
                                                        

  0%|          | 848/569592 [38:29<527:10:27,  3.34s/it]
  0%|          | 849/569592 [38:31<442:33:46,  2.80s/it]
                                                        

  0%|          | 849/569592 [38:31<442:33:46,  2.80s/it]
  0%|          | 850/569592 [38:32<358:26:16,  2.27s/it]
                                                        

  0%|          | 850/569592 [38:32<358:26:16,  2.27s/it]
  0%|          | 851/569592 [38:33<296:40:40,  1.88s/it]
                                                        

  0%|          | 851/569592 [38:33<296:40:40,  1.88s/it]
  0%|          | 852/569592 [38:40<530:11:58,  3.36s/it]
                                                        

  0%|          | 852/569592 [38:40<530:11:58,  3.36s/it]
  0%|          | 853/569592 [38:41<431:37:12,  2.73s/it]
                                                        

  0%|          | 853/569592 [38:41<431:37:12,  2.73s/it]
  0%|          | 854/569592 [38:42<346:55:54,  2.20s/it]
                                                        

  0%|          | 854/569592 [38:42<346:55:54,  2.20s/it]
  0%|          | 855/569592 [38:43<288:41:24,  1.83s/it]
                                                        

  0%|          | 855/569592 [38:43<288:41:24,  1.83s/it]
  0%|          | 856/569592 [38:50<533:19:56,  3.38s/it]
                                                        

  0%|          | 856/569592 [38:50<533:19:56,  3.38s/it]
  0%|          | 857/569592 [38:51<421:41:37,  2.67s/it]
                                                        

  0%|          | 857/569592 [38:51<421:41:37,  2.67s/it]
  0%|          | 858/569592 [38:53<392:15:09,  2.48s/it]
                                                        

  0%|          | 858/569592 [38:53<392:15:09,  2.48s/it]
  0%|          | 859/569592 [38:54<321:13:34,  2.03s/it]
                                                        

  0%|          | 859/569592 [38:54<321:13:34,  2.03s/it]
  0%|          | 860/569592 [39:00<532:23:11,  3.37s/it]
                                                        

  0%|          | 860/569592 [39:00<532:23:11,  3.37s/it]
  0%|          | 861/569592 [39:02<431:02:52,  2.73s/it]
                                                        

  0%|          | 861/569592 [39:02<431:02:52,  2.73s/it]
  0%|          | 862/569592 [39:03<349:18:13,  2.21s/it]
                                                        

  0%|          | 862/569592 [39:03<349:18:13,  2.21s/it]
  0%|          | 863/569592 [39:04<289:34:46,  1.83s/it]
                                                        

  0%|          | 863/569592 [39:04<289:34:46,  1.83s/it]
  0%|          | 864/569592 [39:09<472:30:15,  2.99s/it]
                                                        

  0%|          | 864/569592 [39:09<472:30:15,  2.99s/it]
  0%|          | 865/569592 [39:12<453:20:16,  2.87s/it]
                                                        

  0%|          | 865/569592 [39:12<453:20:16,  2.87s/it]
  0%|          | 866/569592 [39:13<363:21:22,  2.30s/it]
                                                        

  0%|          | 866/569592 [39:13<363:21:22,  2.30s/it]
  0%|          | 867/569592 [39:14<304:14:56,  1.93s/it]
                                                        

  0%|          | 867/569592 [39:14<304:14:56,  1.93s/it]
  0%|          | 868/569592 [39:20<523:30:32,  3.31s/it]
                                                        

  0%|          | 868/569592 [39:20<523:30:32,  3.31s/it]
  0%|          | 869/569592 [39:22<458:13:28,  2.90s/it]
                                                        

  0%|          | 869/569592 [39:22<458:13:28,  2.90s/it]
  0%|          | 870/569592 [39:24<411:19:37,  2.60s/it]
                                                        

  0%|          | 870/569592 [39:24<411:19:37,  2.60s/it]
  0%|          | 871/569592 [39:25<332:36:36,  2.11s/it]
                                                        

  0%|          | 871/569592 [39:25<332:36:36,  2.11s/it]
  0%|          | 872/569592 [39:29<424:50:00,  2.69s/it]
                                                        

  0%|          | 872/569592 [39:29<424:50:00,  2.69s/it]
  0%|          | 873/569592 [39:33<460:48:30,  2.92s/it]
                                                        

  0%|          | 873/569592 [39:33<460:48:30,  2.92s/it]
  0%|          | 874/569592 [39:35<421:14:27,  2.67s/it]
                                                        

  0%|          | 874/569592 [39:35<421:14:27,  2.67s/it]
  0%|          | 875/569592 [39:36<338:51:45,  2.15s/it]
                                                        

  0%|          | 875/569592 [39:36<338:51:45,  2.15s/it]
  0%|          | 876/569592 [39:40<423:36:19,  2.68s/it]
                                                        

  0%|          | 876/569592 [39:40<423:36:19,  2.68s/it]
  0%|          | 877/569592 [39:42<398:53:32,  2.53s/it]
                                                        

  0%|          | 877/569592 [39:42<398:53:32,  2.53s/it]
  0%|          | 878/569592 [39:45<418:53:20,  2.65s/it]
                                                        

  0%|          | 878/569592 [39:45<418:53:20,  2.65s/it]
  0%|          | 879/569592 [39:46<339:46:48,  2.15s/it]
                                                        

  0%|          | 879/569592 [39:46<339:46:48,  2.15s/it]
  0%|          | 880/569592 [39:50<461:45:20,  2.92s/it]
                                                        

  0%|          | 880/569592 [39:50<461:45:20,  2.92s/it]
  0%|          | 881/569592 [39:53<462:42:24,  2.93s/it]
                                                        

  0%|          | 881/569592 [39:53<462:42:24,  2.93s/it]
  0%|          | 882/569592 [39:55<388:00:14,  2.46s/it]
                                                        

  0%|          | 882/569592 [39:55<388:00:14,  2.46s/it]
  0%|          | 883/569592 [39:56<318:50:59,  2.02s/it]
                                                        

  0%|          | 883/569592 [39:56<318:50:59,  2.02s/it]
  0%|          | 884/569592 [40:01<465:14:57,  2.95s/it]
                                                        

  0%|          | 884/569592 [40:01<465:14:57,  2.95s/it]
  0%|          | 885/569592 [40:03<429:51:48,  2.72s/it]
                                                        

  0%|          | 885/569592 [40:03<429:51:48,  2.72s/it]
  0%|          | 886/569592 [40:05<401:01:25,  2.54s/it]
                                                        

  0%|          | 886/569592 [40:05<401:01:25,  2.54s/it]
  0%|          | 887/569592 [40:06<326:51:46,  2.07s/it]
                                                        

  0%|          | 887/569592 [40:06<326:51:46,  2.07s/it]
  0%|          | 888/569592 [40:10<390:48:40,  2.47s/it]
                                                        

  0%|          | 888/569592 [40:10<390:48:40,  2.47s/it]
  0%|          | 889/569592 [40:14<467:12:15,  2.96s/it]
                                                        

  0%|          | 889/569592 [40:14<467:12:15,  2.96s/it]
  0%|          | 890/569592 [40:16<416:15:56,  2.64s/it]
                                                        

  0%|          | 890/569592 [40:16<416:15:56,  2.64s/it]
  0%|          | 891/569592 [40:17<340:53:57,  2.16s/it]
                                                        

  0%|          | 891/569592 [40:17<340:53:57,  2.16s/it]
  0%|          | 892/569592 [40:20<423:29:03,  2.68s/it]
                                                        

  0%|          | 892/569592 [40:20<423:29:03,  2.68s/it]
  0%|          | 893/569592 [40:23<436:20:58,  2.76s/it]
                                                        

  0%|          | 893/569592 [40:23<436:20:58,  2.76s/it]
  0%|          | 894/569592 [40:26<409:32:58,  2.59s/it]
                                                        

  0%|          | 894/569592 [40:26<409:32:58,  2.59s/it]
  0%|          | 895/569592 [40:27<347:26:28,  2.20s/it]
                                                        

  0%|          | 895/569592 [40:27<347:26:28,  2.20s/it]
  0%|          | 896/569592 [40:31<442:00:02,  2.80s/it]
                                                        

  0%|          | 896/569592 [40:31<442:00:02,  2.80s/it]
  0%|          | 897/569592 [40:34<426:44:17,  2.70s/it]
                                                        

  0%|          | 897/569592 [40:34<426:44:17,  2.70s/it]
  0%|          | 898/569592 [40:34<342:28:09,  2.17s/it]
                                                        

  0%|          | 898/569592 [40:35<342:28:09,  2.17s/it]
  0%|          | 899/569592 [40:35<285:36:23,  1.81s/it]
                                                        

  0%|          | 899/569592 [40:35<285:36:23,  1.81s/it]
  0%|          | 900/569592 [40:41<473:43:34,  3.00s/it]
                                                        

  0%|          | 900/569592 [40:41<473:43:34,  3.00s/it]
  0%|          | 901/569592 [40:43<435:15:26,  2.76s/it]
                                                        

  0%|          | 901/569592 [40:43<435:15:26,  2.76s/it]
  0%|          | 902/569592 [40:46<420:13:48,  2.66s/it]
                                                        

  0%|          | 902/569592 [40:46<420:13:48,  2.66s/it]
  0%|          | 903/569592 [40:47<353:55:53,  2.24s/it]
                                                        

  0%|          | 903/569592 [40:47<353:55:53,  2.24s/it]
  0%|          | 904/569592 [40:52<472:20:12,  2.99s/it]
                                                        

  0%|          | 904/569592 [40:52<472:20:12,  2.99s/it]
  0%|          | 905/569592 [40:53<381:15:59,  2.41s/it]
                                                        

  0%|          | 905/569592 [40:53<381:15:59,  2.41s/it]
  0%|          | 906/569592 [40:54<333:30:00,  2.11s/it]
                                                        

  0%|          | 906/569592 [40:54<333:30:00,  2.11s/it]
  0%|          | 907/569592 [40:56<301:03:29,  1.91s/it]
                                                        

  0%|          | 907/569592 [40:56<301:03:29,  1.91s/it]
  0%|          | 908/569592 [41:02<523:00:09,  3.31s/it]
                                                        

  0%|          | 908/569592 [41:02<523:00:09,  3.31s/it]
  0%|          | 909/569592 [41:06<519:23:57,  3.29s/it]
                                                        

  0%|          | 909/569592 [41:06<519:23:57,  3.29s/it]
  0%|          | 910/569592 [41:06<406:24:43,  2.57s/it]
                                                        

  0%|          | 910/569592 [41:07<406:24:43,  2.57s/it]
  0%|          | 911/569592 [41:08<333:32:22,  2.11s/it]
                                                        

  0%|          | 911/569592 [41:08<333:32:22,  2.11s/it]
  0%|          | 912/569592 [41:13<481:22:34,  3.05s/it]
                                                        

  0%|          | 912/569592 [41:13<481:22:34,  3.05s/it]
  0%|          | 913/569592 [41:16<502:30:02,  3.18s/it]
                                                        

  0%|          | 913/569592 [41:16<502:30:02,  3.18s/it]
  0%|          | 914/569592 [41:21<578:43:32,  3.66s/it]
                                                        

  0%|          | 914/569592 [41:21<578:43:32,  3.66s/it]
  0%|          | 915/569592 [41:25<579:10:52,  3.67s/it]
                                                        

  0%|          | 915/569592 [41:25<579:10:52,  3.67s/it]
  0%|          | 916/569592 [41:28<576:34:09,  3.65s/it]
                                                        

  0%|          | 916/569592 [41:28<576:34:09,  3.65s/it]
  0%|          | 917/569592 [41:33<622:46:23,  3.94s/it]
                                                        

  0%|          | 917/569592 [41:33<622:46:23,  3.94s/it]
  0%|          | 918/569592 [41:38<654:17:58,  4.14s/it]
                                                        

  0%|          | 918/569592 [41:38<654:17:58,  4.14s/it]
  0%|          | 919/569592 [41:42<679:30:01,  4.30s/it]
                                                        

  0%|          | 919/569592 [41:43<679:30:01,  4.30s/it]
  0%|          | 920/569592 [41:47<687:15:00,  4.35s/it]
                                                        

  0%|          | 920/569592 [41:47<687:15:00,  4.35s/it]
  0%|          | 921/569592 [41:51<703:32:39,  4.45s/it]
                                                        

  0%|          | 921/569592 [41:51<703:32:39,  4.45s/it]
  0%|          | 922/569592 [41:52<533:41:40,  3.38s/it]
                                                        

  0%|          | 922/569592 [41:52<533:41:40,  3.38s/it]
  0%|          | 923/569592 [41:57<597:54:03,  3.79s/it]
                                                        

  0%|          | 923/569592 [41:57<597:54:03,  3.79s/it]
  0%|          | 924/569592 [42:01<621:16:09,  3.93s/it]
                                                        

  0%|          | 924/569592 [42:01<621:16:09,  3.93s/it]
  0%|          | 925/569592 [42:07<689:46:04,  4.37s/it]
                                                        

  0%|          | 925/569592 [42:07<689:46:04,  4.37s/it]
  0%|          | 926/569592 [42:10<647:55:42,  4.10s/it]
                                                        

  0%|          | 926/569592 [42:10<647:55:42,  4.10s/it]
  0%|          | 927/569592 [42:14<651:31:39,  4.12s/it]
                                                        

  0%|          | 927/569592 [42:14<651:31:39,  4.12s/it]
  0%|          | 928/569592 [42:17<595:02:00,  3.77s/it]
                                                        

  0%|          | 928/569592 [42:17<595:02:00,  3.77s/it]
  0%|          | 929/569592 [42:22<643:18:16,  4.07s/it]
                                                        

  0%|          | 929/569592 [42:22<643:18:16,  4.07s/it]
  0%|          | 930/569592 [42:27<679:15:39,  4.30s/it]
                                                        

  0%|          | 930/569592 [42:27<679:15:39,  4.30s/it]
  0%|          | 931/569592 [42:31<648:26:11,  4.11s/it]
                                                        

  0%|          | 931/569592 [42:31<648:26:11,  4.11s/it]
  0%|          | 932/569592 [42:35<666:19:20,  4.22s/it]
                                                        

  0%|          | 932/569592 [42:35<666:19:20,  4.22s/it]
  0%|          | 933/569592 [42:38<619:30:28,  3.92s/it]
                                                        

  0%|          | 933/569592 [42:38<619:30:28,  3.92s/it]
  0%|          | 934/569592 [42:43<644:16:43,  4.08s/it]
                                                        

  0%|          | 934/569592 [42:43<644:16:43,  4.08s/it]
  0%|          | 935/569592 [42:46<625:22:25,  3.96s/it]
                                                        

  0%|          | 935/569592 [42:46<625:22:25,  3.96s/it]
  0%|          | 936/569592 [42:51<658:59:26,  4.17s/it]
                                                        

  0%|          | 936/569592 [42:51<658:59:26,  4.17s/it]
  0%|          | 937/569592 [42:56<683:35:32,  4.33s/it]
                                                        

  0%|          | 937/569592 [42:56<683:35:32,  4.33s/it]
  0%|          | 938/569592 [43:00<698:30:42,  4.42s/it]
                                                        

  0%|          | 938/569592 [43:00<698:30:42,  4.42s/it]
  0%|          | 939/569592 [43:04<645:42:49,  4.09s/it]
                                                        

  0%|          | 939/569592 [43:04<645:42:49,  4.09s/it]
  0%|          | 940/569592 [43:07<609:59:01,  3.86s/it]
                                                        

  0%|          | 940/569592 [43:07<609:59:01,  3.86s/it]
  0%|          | 941/569592 [43:12<683:57:13,  4.33s/it]
                                                        

  0%|          | 941/569592 [43:12<683:57:13,  4.33s/it]
  0%|          | 942/569592 [43:13<520:06:45,  3.29s/it]
                                                        

  0%|          | 942/569592 [43:13<520:06:45,  3.29s/it]
  0%|          | 943/569592 [43:14<407:06:59,  2.58s/it]
                                                        

  0%|          | 943/569592 [43:14<407:06:59,  2.58s/it]
  0%|          | 944/569592 [43:15<333:02:55,  2.11s/it]
                                                        

  0%|          | 944/569592 [43:15<333:02:55,  2.11s/it]
  0%|          | 945/569592 [43:16<278:50:48,  1.77s/it]
                                                        

  0%|          | 945/569592 [43:16<278:50:48,  1.77s/it]
  0%|          | 946/569592 [43:17<244:11:53,  1.55s/it]
                                                        

  0%|          | 946/569592 [43:17<244:11:53,  1.55s/it]
  0%|          | 947/569592 [43:18<215:52:59,  1.37s/it]
                                                        

  0%|          | 947/569592 [43:18<215:52:59,  1.37s/it]
  0%|          | 948/569592 [43:19<195:00:00,  1.23s/it]
                                                        

  0%|          | 948/569592 [43:19<195:00:00,  1.23s/it]
  0%|          | 949/569592 [43:20<182:09:48,  1.15s/it]
                                                        

  0%|          | 949/569592 [43:20<182:09:48,  1.15s/it]
  0%|          | 950/569592 [43:26<427:48:54,  2.71s/it]
                                                        

  0%|          | 950/569592 [43:26<427:48:54,  2.71s/it]
  0%|          | 951/569592 [43:27<347:34:24,  2.20s/it]
                                                        

  0%|          | 951/569592 [43:27<347:34:24,  2.20s/it]
  0%|          | 952/569592 [43:28<288:42:23,  1.83s/it]
                                                        

  0%|          | 952/569592 [43:28<288:42:23,  1.83s/it]
  0%|          | 953/569592 [43:30<284:50:01,  1.80s/it]
                                                        

  0%|          | 953/569592 [43:30<284:50:01,  1.80s/it]
  0%|          | 954/569592 [43:36<486:04:14,  3.08s/it]
                                                        

  0%|          | 954/569592 [43:36<486:04:14,  3.08s/it]
  0%|          | 955/569592 [43:37<385:13:58,  2.44s/it]
                                                        

  0%|          | 955/569592 [43:37<385:13:58,  2.44s/it]
  0%|          | 956/569592 [43:38<315:55:59,  2.00s/it]
                                                        

  0%|          | 956/569592 [43:38<315:55:59,  2.00s/it]
  0%|          | 957/569592 [43:40<318:46:26,  2.02s/it]
                                                        

  0%|          | 957/569592 [43:40<318:46:26,  2.02s/it]
  0%|          | 958/569592 [43:46<501:48:58,  3.18s/it]
                                                        

  0%|          | 958/569592 [43:46<501:48:58,  3.18s/it]
  0%|          | 959/569592 [43:47<397:30:24,  2.52s/it]
                                                        

  0%|          | 959/569592 [43:47<397:30:24,  2.52s/it]
  0%|          | 960/569592 [43:49<352:31:36,  2.23s/it]
                                                        

  0%|          | 960/569592 [43:49<352:31:36,  2.23s/it]
  0%|          | 961/569592 [43:51<360:47:53,  2.28s/it]
                                                        

  0%|          | 961/569592 [43:51<360:47:53,  2.28s/it]
  0%|          | 962/569592 [43:56<493:58:27,  3.13s/it]
                                                        

  0%|          | 962/569592 [43:56<493:58:27,  3.13s/it]
  0%|          | 963/569592 [43:57<396:34:49,  2.51s/it]
                                                        

  0%|          | 963/569592 [43:57<396:34:49,  2.51s/it]
  0%|          | 964/569592 [43:59<388:48:39,  2.46s/it]
                                                        

  0%|          | 964/569592 [44:00<388:48:39,  2.46s/it]
  0%|          | 965/569592 [44:01<349:04:56,  2.21s/it]
                                                        

  0%|          | 965/569592 [44:01<349:04:56,  2.21s/it]
  0%|          | 966/569592 [44:06<497:30:38,  3.15s/it]
                                                        

  0%|          | 966/569592 [44:06<497:30:38,  3.15s/it]
  0%|          | 967/569592 [44:08<436:39:10,  2.76s/it]
                                                        

  0%|          | 967/569592 [44:08<436:39:10,  2.76s/it]
  0%|          | 968/569592 [44:10<397:30:27,  2.52s/it]
                                                        

  0%|          | 968/569592 [44:10<397:30:27,  2.52s/it]
  0%|          | 969/569592 [44:11<322:01:08,  2.04s/it]
                          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                              

  0%|          | 969/569592 [44:11<322:01:08,  2.04s/it]
  0%|          | 970/569592 [44:17<500:48:33,  3.17s/it]
                                                        

  0%|          | 970/569592 [44:17<500:48:33,  3.17s/it]
  0%|          | 971/569592 [44:18<395:45:13,  2.51s/it]
                                                        

  0%|          | 971/569592 [44:18<395:45:13,  2.51s/it]
  0%|          | 972/569592 [44:20<357:36:20,  2.26s/it]
                                                        

  0%|          | 972/569592 [44:20<357:36:20,  2.26s/it]
  0%|          | 973/569592 [44:22<338:30:03,  2.14s/it]
                                                        

  0%|          | 973/569592 [44:22<338:30:03,  2.14s/it]
  0%|          | 974/569592 [44:27<504:41:00,  3.20s/it]
                                                        

  0%|          | 974/569592 [44:27<504:41:00,  3.20s/it]
  0%|          | 975/569592 [44:28<403:10:38,  2.55s/it]
                                                        

  0%|          | 975/569592 [44:28<403:10:38,  2.55s/it]
  0%|          | 976/569592 [44:30<384:09:58,  2.43s/it]
                                                        

  0%|          | 976/569592 [44:30<384:09:58,  2.43s/it]
  0%|          | 977/569592 [44:31<322:29:07,  2.04s/it]
                                                        

  0%|          | 977/569592 [44:32<322:29:07,  2.04s/it]
  0%|          | 978/569592 [44:38<548:55:44,  3.48s/it]
                                                        

  0%|          | 978/569592 [44:38<548:55:44,  3.48s/it]
  0%|          | 979/569592 [44:39<429:26:59,  2.72s/it]
                                                        

  0%|          | 979/569592 [44:39<429:26:59,  2.72s/it]
  0%|          | 980/569592 [44:41<377:40:51,  2.39s/it]
                                                        

  0%|          | 980/569592 [44:41<377:40:51,  2.39s/it]
  0%|          | 981/569592 [44:42<309:29:18,  1.96s/it]
                                                        

  0%|          | 981/569592 [44:42<309:29:18,  1.96s/it]
  0%|          | 982/569592 [44:49<549:25:44,  3.48s/it]
                                                        

  0%|          | 982/569592 [44:49<549:25:44,  3.48s/it]
  0%|          | 983/569592 [44:50<430:05:07,  2.72s/it]
                                                        

  0%|          | 983/569592 [44:50<430:05:07,  2.72s/it]
  0%|          | 984/569592 [44:54<509:28:39,  3.23s/it]
                                                        

  0%|          | 984/569592 [44:54<509:28:39,  3.23s/it]
  0%|          | 985/569592 [44:55<401:58:47,  2.55s/it]
                                                        

  0%|          | 985/569592 [44:55<401:58:47,  2.55s/it]
  0%|          | 986/569592 [44:59<464:17:54,  2.94s/it]
                                                        

  0%|          | 986/569592 [44:59<464:17:54,  2.94s/it]
  0%|          | 987/569592 [45:00<369:49:55,  2.34s/it]
                                                        

  0%|          | 987/569592 [45:00<369:49:55,  2.34s/it]
  0%|          | 988/569592 [45:05<479:22:45,  3.04s/it]
                                                        

  0%|          | 988/569592 [45:05<479:22:45,  3.04s/it]
  0%|          | 989/569592 [45:06<380:12:55,  2.41s/it]
                                                        

  0%|          | 989/569592 [45:06<380:12:55,  2.41s/it]
  0%|          | 990/569592 [45:09<439:54:20,  2.79s/it]
                                                        

  0%|          | 990/569592 [45:09<439:54:20,  2.79s/it]
  0%|          | 991/569592 [45:10<351:54:26,  2.23s/it]
                                                        

  0%|          | 991/569592 [45:10<351:54:26,  2.23s/it]
  0%|          | 992/569592 [45:15<466:23:23,  2.95s/it]
                                                        

  0%|          | 992/569592 [45:15<466:23:23,  2.95s/it]
  0%|          | 993/569592 [45:16<370:55:42,  2.35s/it]
                                                        

  0%|          | 993/569592 [45:16<370:55:42,  2.35s/it]
  0%|          | 994/569592 [45:20<449:40:25,  2.85s/it]
                                                        

  0%|          | 994/569592 [45:20<449:40:25,  2.85s/it]
  0%|          | 995/569592 [45:21<359:25:21,  2.28s/it]
                                                        

  0%|          | 995/569592 [45:21<359:25:21,  2.28s/it]
  0%|          | 996/569592 [45:25<463:28:22,  2.93s/it]
                                                        

  0%|          | 996/569592 [45:25<463:28:22,  2.93s/it]
  0%|          | 997/569592 [45:26<370:48:27,  2.35s/it]
                                                        

  0%|          | 997/569592 [45:26<370:48:27,  2.35s/it]
  0%|          | 998/569592 [45:30<428:07:16,  2.71s/it]
                                                        

  0%|          | 998/569592 [45:30<428:07:16,  2.71s/it]
  0%|          | 999/569592 [45:31<345:00:28,  2.18s/it]
                                                        

  0%|          | 999/569592 [45:31<345:00:28,  2.18s/it]
  0%|          | 1000/569592 [45:34<419:41:48,  2.66s/it]
                                                         

  0%|          | 1000/569592 [45:34<419:41:48,  2.66s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-1000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-1000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-1000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-1000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-1000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-1000/special_tokens_map.json

  0%|          | 1001/569592 [47:32<5846:50:52, 37.02s/it]
                                                          

  0%|          | 1001/569592 [47:32<5846:50:52, 37.02s/it]
  0%|          | 1002/569592 [47:33<4134:40:16, 26.18s/it]
                                                          

  0%|          | 1002/569592 [47:33<4134:40:16, 26.18s/it]
  0%|          | 1003/569592 [47:33<2939:23:07, 18.61s/it]
                                                          

  0%|          | 1003/569592 [47:33<2939:23:07, 18.61s/it]
  0%|          | 1004/569592 [47:34<2104:20:14, 13.32s/it]
                                                          

  0%|          | 1004/569592 [47:34<2104:20:14, 13.32s/it]
  0%|          | 1005/569592 [47:35<1517:57:23,  9.61s/it]
                                                          

  0%|          | 1005/569592 [47:35<1517:57:23,  9.61s/it]
  0%|          | 1006/569592 [47:36<1109:52:56,  7.03s/it]
                                                          

  0%|          | 1006/569592 [47:36<1109:52:56,  7.03s/it]
  0%|          | 1007/569592 [47:37<821:52:46,  5.20s/it] 
                                                         

  0%|          | 1007/569592 [47:37<821:52:46,  5.20s/it]
  0%|          | 1008/569592 [47:38<622:27:53,  3.94s/it]
                                                         

  0%|          | 1008/569592 [47:38<622:27:53,  3.94s/it]
  0%|          | 1009/569592 [47:44<712:23:02,  4.51s/it]
                                                         

  0%|          | 1009/569592 [47:44<712:23:02,  4.51s/it]
  0%|          | 1010/569592 [47:45<546:17:42,  3.46s/it]
                                                         

  0%|          | 1010/569592 [47:45<546:17:42,  3.46s/it]
  0%|          | 1011/569592 [47:46<442:01:31,  2.80s/it]
                                                         

  0%|          | 1011/569592 [47:46<442:01:31,  2.80s/it]
  0%|          | 1012/569592 [47:47<354:20:10,  2.24s/it]
                                                         

  0%|          | 1012/569592 [47:47<354:20:10,  2.24s/it]
  0%|          | 1013/569592 [47:54<567:34:10,  3.59s/it]
                                                         

  0%|          | 1013/569592 [47:54<567:34:10,  3.59s/it]
  0%|          | 1014/569592 [47:56<480:25:16,  3.04s/it]
                                                         

  0%|          | 1014/569592 [47:56<480:25:16,  3.04s/it]
  0%|          | 1015/569592 [47:57<384:22:23,  2.43s/it]
                                                         

  0%|          | 1015/569592 [47:57<384:22:23,  2.43s/it]
  0%|          | 1016/569592 [47:58<316:30:45,  2.00s/it]
                                                         

  0%|          | 1016/569592 [47:58<316:30:45,  2.00s/it]
  0%|          | 1017/569592 [48:04<486:10:54,  3.08s/it]
                                                         

  0%|          | 1017/569592 [48:04<486:10:54,  3.08s/it]
  0%|          | 1018/569592 [48:06<470:33:43,  2.98s/it]
                                                         

  0%|          | 1018/569592 [48:06<470:33:43,  2.98s/it]
  0%|          | 1019/569592 [48:07<378:27:47,  2.40s/it]
                                                         

  0%|          | 1019/569592 [48:07<378:27:47,  2.40s/it]
  0%|          | 1020/569592 [48:08<310:11:24,  1.96s/it]
                                                         

  0%|          | 1020/569592 [48:08<310:11:24,  1.96s/it]
  0%|          | 1021/569592 [48:13<463:00:50,  2.93s/it]
                                                         

  0%|          | 1021/569592 [48:13<463:00:50,  2.93s/it]
  0%|          | 1022/569592 [48:16<434:33:03,  2.75s/it]
                                                         

  0%|          | 1022/569592 [48:16<434:33:03,  2.75s/it]
  0%|          | 1023/569592 [48:17<354:27:28,  2.24s/it]
                                                         

  0%|          | 1023/569592 [48:17<354:27:28,  2.24s/it]
  0%|          | 1024/569592 [48:18<292:35:50,  1.85s/it]
                                                         

  0%|          | 1024/569592 [48:18<292:35:50,  1.85s/it]
  0%|          | 1025/569592 [48:24<513:07:47,  3.25s/it]
                                                         

  0%|          | 1025/569592 [48:24<513:07:47,  3.25s/it]
  0%|          | 1026/569592 [48:28<528:11:21,  3.34s/it]
                                                         

  0%|          | 1026/569592 [48:28<528:11:21,  3.34s/it]
  0%|          | 1027/569592 [48:32<585:37:38,  3.71s/it]
                                                         

  0%|          | 1027/569592 [48:32<585:37:38,  3.71s/it]
  0%|          | 1028/569592 [48:38<676:03:59,  4.28s/it]
                                                         

  0%|          | 1028/569592 [48:38<676:03:59,  4.28s/it]
  0%|          | 1029/569592 [48:42<665:15:04,  4.21s/it]
                                                         

  0%|          | 1029/569592 [48:42<665:15:04,  4.21s/it]
  0%|          | 1030/569592 [48:46<667:53:14,  4.23s/it]
                                                         

  0%|          | 1030/569592 [48:46<667:53:14,  4.23s/it]
  0%|          | 1031/569592 [48:51<687:53:17,  4.36s/it]
                                                         

  0%|          | 1031/569592 [48:51<687:53:17,  4.36s/it]
  0%|          | 1032/569592 [48:56<703:25:05,  4.45s/it]
                                                         

  0%|          | 1032/569592 [48:56<703:25:05,  4.45s/it]
  0%|          | 1033/569592 [48:59<637:50:01,  4.04s/it]
                                                         

  0%|          | 1033/569592 [48:59<637:50:01,  4.04s/it]
  0%|          | 1034/569592 [49:02<610:12:58,  3.86s/it]
                                                         

  0%|          | 1034/569592 [49:02<610:12:58,  3.86s/it]
  0%|          | 1035/569592 [49:06<595:37:14,  3.77s/it]
                                                         

  0%|          | 1035/569592 [49:06<595:37:14,  3.77s/it]
  0%|          | 1036/569592 [49:11<671:08:30,  4.25s/it]
                                                         

  0%|          | 1036/569592 [49:11<671:08:30,  4.25s/it]
  0%|          | 1037/569592 [49:16<713:43:11,  4.52s/it]
                                                         

  0%|          | 1037/569592 [49:16<713:43:11,  4.52s/it]
  0%|          | 1038/569592 [49:21<744:17:59,  4.71s/it]
                                                         

  0%|          | 1038/569592 [49:21<744:17:59,  4.71s/it]
  0%|          | 1039/569592 [49:25<706:18:00,  4.47s/it]
                                                         

  0%|          | 1039/569592 [49:25<706:18:00,  4.47s/it]
  0%|          | 1040/569592 [49:30<738:35:38,  4.68s/it]
                                                         

  0%|          | 1040/569592 [49:31<738:35:38,  4.68s/it]
  0%|          | 1041/569592 [49:38<866:24:03,  5.49s/it]
                                                         

  0%|          | 1041/569592 [49:38<866:24:03,  5.49s/it]
  0%|          | 1042/569592 [49:42<811:41:32,  5.14s/it]
                                                         

  0%|          | 1042/569592 [49:42<811:41:32,  5.14s/it]
  0%|          | 1043/569592 [49:47<811:32:58,  5.14s/it]
                                                         

  0%|          | 1043/569592 [49:47<811:32:58,  5.14s/it]
  0%|          | 1044/569592 [49:48<610:06:57,  3.86s/it]
                                                         

  0%|          | 1044/569592 [49:48<610:06:57,  3.86s/it]
  0%|          | 1045/569592 [49:53<660:08:22,  4.18s/it]
                                                         

  0%|          | 1045/569592 [49:53<660:08:22,  4.18s/it]
  0%|          | 1046/569592 [49:58<702:28:13,  4.45s/it]
                                                         

  0%|          | 1046/569592 [49:58<702:28:13,  4.45s/it]
  0%|          | 1047/569592 [50:03<735:59:35,  4.66s/it]
                                                         

  0%|          | 1047/569592 [50:03<735:59:35,  4.66s/it]
  0%|          | 1048/569592 [50:07<685:51:21,  4.34s/it]
                                                         

  0%|          | 1048/569592 [50:07<685:51:21,  4.34s/it]
  0%|          | 1049/569592 [50:10<645:48:45,  4.09s/it]
                                                         

  0%|          | 1049/569592 [50:10<645:48:45,  4.09s/it]
  0%|          | 1050/569592 [50:16<696:05:36,  4.41s/it]
                                                         

  0%|          | 1050/569592 [50:16<696:05:36,  4.41s/it]
  0%|          | 1051/569592 [50:20<673:10:34,  4.26s/it]
                                                         

  0%|          | 1051/569592 [50:20<673:10:34,  4.26s/it]
  0%|          | 1052/569592 [50:23<635:20:33,  4.02s/it]
                                                         

  0%|          | 1052/569592 [50:23<635:20:33,  4.02s/it]
  0%|          | 1053/569592 [50:28<678:22:01,  4.30s/it]
                                                         

  0%|          | 1053/569592 [50:28<678:22:01,  4.30s/it]
  0%|          | 1054/569592 [50:33<691:41:55,  4.38s/it]
                                                         

  0%|          | 1054/569592 [50:33<691:41:55,  4.38s/it]
  0%|          | 1055/569592 [50:36<655:20:22,  4.15s/it]
                                                         

  0%|          | 1055/569592 [50:36<655:20:22,  4.15s/it]
  0%|          | 1056/569592 [50:42<715:06:30,  4.53s/it]
                                                         

  0%|          | 1056/569592 [50:42<715:06:30,  4.53s/it]
  0%|          | 1057/569592 [50:45<664:00:55,  4.20s/it]
                                                         

  0%|          | 1057/569592 [50:45<664:00:55,  4.20s/it]
  0%|          | 1058/569592 [50:46<514:59:08,  3.26s/it]
                                                         

  0%|          | 1058/569592 [50:46<514:59:08,  3.26s/it]
  0%|          | 1059/569592 [50:51<584:25:17,  3.70s/it]
                                                         

  0%|          | 1059/569592 [50:51<584:25:17,  3.70s/it]
  0%|          | 1060/569592 [50:52<458:29:07,  2.90s/it]
                                                         

  0%|          | 1060/569592 [50:52<458:29:07,  2.90s/it]
  0%|          | 1061/569592 [50:53<366:29:19,  2.32s/it]
                                                         

  0%|          | 1061/569592 [50:53<366:29:19,  2.32s/it]
  0%|          | 1062/569592 [50:54<302:26:30,  1.92s/it]
                                                         

  0%|          | 1062/569592 [50:54<302:26:30,  1.92s/it]
  0%|          | 1063/569592 [50:55<256:26:17,  1.62s/it]
                                                         

  0%|          | 1063/569592 [50:55<256:26:17,  1.62s/it]
  0%|          | 1064/569592 [50:56<226:13:57,  1.43s/it]
                                                         

  0%|          | 1064/569592 [50:56<226:13:57,  1.43s/it]
  0%|          | 1065/569592 [50:57<217:13:57,  1.38s/it]
                                                         

  0%|          | 1065/569592 [50:57<217:13:57,  1.38s/it]
  0%|          | 1066/569592 [50:58<217:50:49,  1.38s/it]
                                                         

  0%|          | 1066/569592 [50:58<217:50:49,  1.38s/it]
  0%|          | 1067/569592 [51:00<211:23:29,  1.34s/it]
                                                         

  0%|          | 1067/569592 [51:00<211:23:29,  1.34s/it]
  0%|          | 1068/569592 [51:05<382:38:24,  2.42s/it]
                                                         

  0%|          | 1068/569592 [51:05<382:38:24,  2.42s/it]
  0%|          | 1069/569592 [51:06<330:56:24,  2.10s/it]
                                                         

  0%|          | 1069/569592 [51:06<330:56:24,  2.10s/it]
  0%|          | 1070/569592 [51:09<378:42:48,  2.40s/it]
                                                         

  0%|          | 1070/569592 [51:09<378:42:48,  2.40s/it]
  0%|          | 1071/569592 [51:10<317:29:30,  2.01s/it]
                                                         

  0%|          | 1071/569592 [51:10<317:29:30,  2.01s/it]
  0%|          | 1072/569592 [51:15<470:15:25,  2.98s/it]
                                                         

  0%|          | 1072/569592 [51:15<470:15:25,  2.98s/it]
  0%|          | 1073/569592 [51:16<374:57:20,  2.37s/it]
                                                         

  0%|          | 1073/569592 [51:16<374:57:20,  2.37s/it]
  0%|          | 1074/569592 [51:19<374:42:53,  2.37s/it]
                                                         

  0%|          | 1074/569592 [51:19<374:42:53,  2.37s/it]
  0%|          | 1075/569592 [51:20<333:07:20,  2.11s/it]
                                                         

  0%|          | 1075/569592 [51:20<333:07:20,  2.11s/it]
  0%|          | 1076/569592 [51:25<476:42:25,  3.02s/it]
                                                         

  0%|          | 1076/569592 [51:25<476:42:25,  3.02s/it]
  0%|          | 1077/569592 [51:26<388:13:56,  2.46s/it]
                                                         

  0%|          | 1077/569592 [51:26<388:13:56,  2.46s/it]
  0%|          | 1078/569592 [51:28<349:12:19,  2.21s/it]
                                                         

  0%|          | 1078/569592 [51:28<349:12:19,  2.21s/it]
  0%|          | 1079/569592 [51:30<333:55:33,  2.11s/it]
                                                         

  0%|          | 1079/569592 [51:30<333:55:33,  2.11s/it]
  0%|          | 1080/569592 [51:36<524:21:50,  3.32s/it]
                                                         

  0%|          | 1080/569592 [51:36<524:21:50,  3.32s/it]
  0%|          | 1081/569592 [51:37<422:28:31,  2.68s/it]
                                                         

  0%|          | 1081/569592 [51:37<422:28:31,  2.68s/it]
  0%|          | 1082/569592 [51:39<359:21:10,  2.28s/it]
                                                         

  0%|          | 1082/569592 [51:39<359:21:10,  2.28s/it]
  0%|          | 1083/569592 [51:40<328:57:46,  2.08s/it]
                                                         

  0%|          | 1083/569592 [51:40<328:57:46,  2.08s/it]
  0%|          | 1084/569592 [51:45<466:54:50,  2.96s/it]
                                                         

  0%|          | 1084/569592 [51:45<466:54:50,  2.96s/it]
  0%|          | 1085/569592 [51:47<417:27:16,  2.64s/it]
                                                         

  0%|          | 1085/569592 [51:47<417:27:16,  2.64s/it]
  0%|          | 1086/569592 [51:49<370:37:48,  2.35s/it]
                                                         

  0%|          | 1086/569592 [51:49<370:37:48,  2.35s/it]
  0%|          | 1087/569592 [51:50<314:52:06,  1.99s/it]
                                                         

  0%|          | 1087/569592 [51:50<314:52:06,  1.99s/it]
  0%|          | 1088/569592 [51:55<457:01:39,  2.89s/it]
                                                         

  0%|          | 1088/569592 [51:55<457:01:39,  2.89s/it]
  0%|          | 1089/569592 [51:56<375:29:43,  2.38s/it]
                                                         

  0%|          | 1089/569592 [51:56<375:29:43,  2.38s/it]
  0%|          | 1090/569592 [51:58<339:37:14,  2.15s/it]
                                                         

  0%|          | 1090/569592 [51:58<339:37:14,  2.15s/it]
  0%|          | 1091/569592 [52:01<401:37:01,  2.54s/it]
                                                         

  0%|          | 1091/569592 [52:01<401:37:01,  2.54s/it]
  0%|          | 1092/569592 [52:06<487:24:29,  3.09s/it]
                                                         

  0%|          | 1092/569592 [52:06<487:24:29,  3.09s/it]
  0%|          | 1093/569592 [52:07<406:31:59,  2.57s/it]
                                                         

  0%|          | 1093/569592 [52:07<406:31:59,  2.57s/it]
  0%|          | 1094/569592 [52:09<383:09:09,  2.43s/it]
                                                         

  0%|          | 1094/569592 [52:09<383:09:09,  2.43s/it]
  0%|          | 1095/569592 [52:11<371:21:51,  2.35s/it]
                                                         

  0%|          | 1095/569592 [52:11<371:21:51,  2.35s/it]
  0%|          | 1096/569592 [52:16<479:56:08,  3.04s/it]
                                                         

  0%|          | 1096/569592 [52:16<479:56:08,  3.04s/it]
  0%|          | 1097/569592 [52:17<412:28:03,  2.61s/it]
                                                         

  0%|          | 1097/569592 [52:17<412:28:03,  2.61s/it]
  0%|          | 1098/569592 [52:19<351:45:40,  2.23s/it]
                                                         

  0%|          | 1098/569592 [52:19<351:45:40,  2.23s/it]
  0%|          | 1099/569592 [52:20<325:31:42,  2.06s/it]
                                                         

  0%|          | 1099/569592 [52:20<325:31:42,  2.06s/it]
  0%|          | 1100/569592 [52:26<482:43:43,  3.06s/it]
                                                         

  0%|          | 1100/569592 [52:26<482:43:43,  3.06s/it]
  0%|          | 1101/569592 [52:28<441:37:11,  2.80s/it]
                                                         

  0%|          | 1101/569592 [52:28<441:37:11,  2.80s/it]
  0%|          | 1102/569592 [52:29<366:12:25,  2.32s/it]
                                                         

  0%|          | 1102/569592 [52:29<366:12:25,  2.32s/it]
  0%|          | 1103/569592 [52:32<383:45:35,  2.43s/it]
                                                         

  0%|          | 1103/569592 [52:32<383:45:35,  2.43s/it]
  0%|          | 1104/569592 [52:37<498:09:30,  3.15s/it]
                                                         

  0%|          | 1104/569592 [52:37<498:09:30,  3.15s/it]
  0%|          | 1105/569592 [52:38<398:10:44,  2.52s/it]
                                                         

  0%|          | 1105/569592 [52:38<398:10:44,  2.52s/it]
  0%|          | 1106/569592 [52:39<350:12:28,  2.22s/it]
                                                         

  0%|          | 1106/569592 [52:39<350:12:28,  2.22s/it]
  0%|          | 1107/569592 [52:42<352:49:04,  2.23s/it]
                                                         

  0%|          | 1107/569592 [52:42<352:49:04,  2.23s/it]
  0%|          | 1108/569592 [52:46<443:53:56,  2.81s/it]
                                                         

  0%|          | 1108/569592 [52:46<443:53:56,  2.81s/it]
  0%|          | 1109/569592 [52:47<365:26:22,  2.31s/it]
                                                         

  0%|          | 1109/569592 [52:47<365:26:22,  2.31s/it]
  0%|          | 1110/569592 [52:49<361:02:53,  2.29s/it]
                                                         

  0%|          | 1110/569592 [52:49<361:02:53,  2.29s/it]
  0%|          | 1111/569592 [52:52<394:16:39,  2.50s/it]
                                                         

  0%|          | 1111/569592 [52:52<394:16:39,  2.50s/it]
  0%|          | 1112/569592 [52:56<465:07:58,  2.95s/it]
                                                         

  0%|          | 1112/569592 [52:56<465:07:58,  2.95s/it]
  0%|          | 1113/569592 [52:58<407:11:49,  2.58s/it]
                                                         

  0%|          | 1113/569592 [52:58<407:11:49,  2.58s/it]
  0%|          | 1114/569592 [53:01<413:48:14,  2.62s/it]
                                                         

  0%|          | 1114/569592 [53:01<413:48:14,  2.62s/it]
  0%|          | 1115/569592 [53:01<335:26:58,  2.12s/it]
                                                         

  0%|          | 1115/569592 [53:02<335:26:58,  2.12s/it]
  0%|          | 1116/569592 [53:06<466:19:51,  2.95s/it]
                                                         

  0%|          | 1116/569592 [53:06<466:19:51,  2.95s/it]
  0%|          | 1117/569592 [53:07<372:20:46,  2.36s/it]
                                                         

  0%|          | 1117/569592 [53:07<372:20:46,  2.36s/it]
  0%|          | 1118/569592 [53:11<417:50:28,  2.65s/it]
                                                         

  0%|          | 1118/569592 [53:11<417:50:28,  2.65s/it]
  0%|          | 1119/569592 [53:12<341:08:32,  2.16s/it]
                                                         

  0%|          | 1119/569592 [53:12<341:08:32,  2.16s/it]
  0%|          | 1120/569592 [53:16<464:09:35,  2.94s/it]
                                                         

  0%|          | 1120/569592 [53:16<464:09:35,  2.94s/it]
  0%|          | 1121/569592 [53:18<382:31:08,  2.42s/it]
                                                         

  0%|          | 1121/569592 [53:18<382:31:08,  2.42s/it]
  0%|          | 1122/569592 [53:19<350:16:01,  2.22s/it]
                                                         

  0%|          | 1122/569592 [53:19<350:16:01,  2.22s/it]
  0%|          | 1123/569592 [53:21<330:36:27,  2.09s/it]
                                                         

  0%|          | 1123/569592 [53:21<330:36:27,  2.09s/it]
  0%|          | 1124/569592 [53:27<514:55:09,  3.26s/it]
                                                         

  0%|          | 1124/569592 [53:27<514:55:09,  3.26s/it]
  0%|          | 1125/569592 [53:29<424:50:50,  2.69s/it]
                                                         

  0%|          | 1125/569592 [53:29<424:50:50,  2.69s/it]
  0%|          | 1126/569592 [53:30<355:15:09,  2.25s/it]
                                                         

  0%|          | 1126/569592 [53:30<355:15:09,  2.25s/it]
  0%|          | 1127/569592 [53:33<381:01:59,  2.41s/it]
                                                         

  0%|          | 1127/569592 [53:33<381:01:59,  2.41s/it]
  0%|          | 1128/569592 [53:37<488:10:20,  3.09s/it]
                                                         

  0%|          | 1128/569592 [53:37<488:10:20,  3.09s/it]
  0%|          | 1129/569592 [53:39<406:45:33,  2.58s/it]
                                                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101412842 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
       

  0%|          | 1129/569592 [53:39<406:45:33,  2.58s/it]
  0%|          | 1130/569592 [53:40<335:45:47,  2.13s/it]
                                                         

  0%|          | 1130/569592 [53:40<335:45:47,  2.13s/it]
  0%|          | 1131/569592 [53:42<332:59:31,  2.11s/it]
                                                         

  0%|          | 1131/569592 [53:42<332:59:31,  2.11s/it]
  0%|          | 1132/569592 [53:47<498:02:49,  3.15s/it]
                                                         

  0%|          | 1132/569592 [53:47<498:02:49,  3.15s/it]
  0%|          | 1133/569592 [53:49<406:59:07,  2.58s/it]
                                                         

  0%|          | 1133/569592 [53:49<406:59:07,  2.58s/it]
  0%|          | 1134/569592 [53:50<366:21:58,  2.32s/it]
                                                         

  0%|          | 1134/569592 [53:50<366:21:58,  2.32s/it]
  0%|          | 1135/569592 [53:52<317:13:59,  2.01s/it]
                                                         

  0%|          | 1135/569592 [53:52<317:13:59,  2.01s/it]
  0%|          | 1136/569592 [53:57<492:02:53,  3.12s/it]
                                                         

  0%|          | 1136/569592 [53:57<492:02:53,  3.12s/it]
  0%|          | 1137/569592 [53:59<407:50:32,  2.58s/it]
                                                         

  0%|          | 1137/569592 [53:59<407:50:32,  2.58s/it]
  0%|          | 1138/569592 [54:02<441:25:00,  2.80s/it]
                                                         

  0%|          | 1138/569592 [54:02<441:25:00,  2.80s/it]
  0%|          | 1139/569592 [54:03<354:55:37,  2.25s/it]
                                                         

  0%|          | 1139/569592 [54:03<354:55:37,  2.25s/it]
  0%|          | 1140/569592 [54:08<506:34:41,  3.21s/it]
                                                         

  0%|          | 1140/569592 [54:08<506:34:41,  3.21s/it]
  0%|          | 1141/569592 [54:09<399:13:50,  2.53s/it]
                                                         

  0%|          | 1141/569592 [54:09<399:13:50,  2.53s/it]
  0%|          | 1142/569592 [54:10<325:31:54,  2.06s/it]
                                                         

  0%|          | 1142/569592 [54:10<325:31:54,  2.06s/it]
  0%|          | 1143/569592 [54:12<287:58:39,  1.82s/it]
                                                         

  0%|          | 1143/569592 [54:12<287:58:39,  1.82s/it]
  0%|          | 1144/569592 [54:17<467:03:31,  2.96s/it]
                                                         

  0%|          | 1144/569592 [54:17<467:03:31,  2.96s/it]
  0%|          | 1145/569592 [54:22<557:57:25,  3.53s/it]
                                                         

  0%|          | 1145/569592 [54:22<557:57:25,  3.53s/it]
  0%|          | 1146/569592 [54:27<631:18:16,  4.00s/it]
                                                         

  0%|          | 1146/569592 [54:27<631:18:16,  4.00s/it]
  0%|          | 1147/569592 [54:32<663:57:19,  4.20s/it]
                                                         

  0%|          | 1147/569592 [54:32<663:57:19,  4.20s/it]
  0%|          | 1148/569592 [54:36<683:43:55,  4.33s/it]
                                                         

  0%|          | 1148/569592 [54:36<683:43:55,  4.33s/it]
  0%|          | 1149/569592 [54:39<623:01:12,  3.95s/it]
                                                         

  0%|          | 1149/569592 [54:39<623:01:12,  3.95s/it]
  0%|          | 1150/569592 [54:44<665:09:43,  4.21s/it]
                                                         

  0%|          | 1150/569592 [54:44<665:09:43,  4.21s/it]
  0%|          | 1151/569592 [54:49<706:19:43,  4.47s/it]
                                                         

  0%|          | 1151/569592 [54:49<706:19:43,  4.47s/it]
  0%|          | 1152/569592 [54:54<712:05:36,  4.51s/it]
                                                         

  0%|          | 1152/569592 [54:54<712:05:36,  4.51s/it]
  0%|          | 1153/569592 [54:58<703:49:23,  4.46s/it]
                                                         

  0%|          | 1153/569592 [54:58<703:49:23,  4.46s/it]
  0%|          | 1154/569592 [55:03<711:46:21,  4.51s/it]
                                                         

  0%|          | 1154/569592 [55:03<711:46:21,  4.51s/it]
  0%|          | 1155/569592 [55:07<703:59:16,  4.46s/it]
                                                         

  0%|          | 1155/569592 [55:07<703:59:16,  4.46s/it]
  0%|          | 1156/569592 [55:12<713:03:15,  4.52s/it]
                                                         

  0%|          | 1156/569592 [55:12<713:03:15,  4.52s/it]
  0%|          | 1157/569592 [55:17<727:38:51,  4.61s/it]
                                                         

  0%|          | 1157/569592 [55:17<727:38:51,  4.61s/it]
  0%|          | 1158/569592 [55:22<737:05:30,  4.67s/it]
                                                         

  0%|          | 1158/569592 [55:22<737:05:30,  4.67s/it]
  0%|          | 1159/569592 [55:27<768:03:34,  4.86s/it]
                                                         

  0%|          | 1159/569592 [55:27<768:03:34,  4.86s/it]
  0%|          | 1160/569592 [55:31<715:56:49,  4.53s/it]
                                                         

  0%|          | 1160/569592 [55:31<715:56:49,  4.53s/it]
  0%|          | 1161/569592 [55:35<700:42:12,  4.44s/it]
                                                         

  0%|          | 1161/569592 [55:35<700:42:12,  4.44s/it]
  0%|          | 1162/569592 [55:40<725:53:47,  4.60s/it]
                                                         

  0%|          | 1162/569592 [55:40<725:53:47,  4.60s/it]
  0%|          | 1163/569592 [55:45<730:29:41,  4.63s/it]
                                                         

  0%|          | 1163/569592 [55:45<730:29:41,  4.63s/it]
  0%|          | 1164/569592 [55:49<738:38:13,  4.68s/it]
                                                         

  0%|          | 1164/569592 [55:49<738:38:13,  4.68s/it]
  0%|          | 1165/569592 [55:52<664:20:59,  4.21s/it]
                                                         

  0%|          | 1165/569592 [55:52<664:20:59,  4.21s/it]
  0%|          | 1166/569592 [55:57<692:26:42,  4.39s/it]
                                                         

  0%|          | 1166/569592 [55:58<692:26:42,  4.39s/it]
  0%|          | 1167/569592 [56:04<826:21:17,  5.23s/it]
                                                         

  0%|          | 1167/569592 [56:04<826:21:17,  5.23s/it]
  0%|          | 1168/569592 [56:07<722:24:07,  4.58s/it]
                                                         

  0%|          | 1168/569592 [56:07<722:24:07,  4.58s/it]
  0%|          | 1169/569592 [56:13<759:31:44,  4.81s/it]
                                                         

  0%|          | 1169/569592 [56:13<759:31:44,  4.81s/it]
  0%|          | 1170/569592 [56:14<573:02:49,  3.63s/it]
                                                         

  0%|          | 1170/569592 [56:14<573:02:49,  3.63s/it]
  0%|          | 1171/569592 [56:19<629:53:55,  3.99s/it]
                                                         

  0%|          | 1171/569592 [56:19<629:53:55,  3.99s/it]
  0%|          | 1172/569592 [56:19<486:14:22,  3.08s/it]
                                                         

  0%|          | 1172/569592 [56:20<486:14:22,  3.08s/it]
  0%|          | 1173/569592 [56:24<568:56:31,  3.60s/it]
                                                         

  0%|          | 1173/569592 [56:24<568:56:31,  3.60s/it]
  0%|          | 1174/569592 [56:25<441:26:12,  2.80s/it]
                                                         

  0%|          | 1174/569592 [56:25<441:26:12,  2.80s/it]
  0%|          | 1175/569592 [56:29<488:12:20,  3.09s/it]
                                                         

  0%|          | 1175/569592 [56:29<488:12:20,  3.09s/it]
  0%|          | 1176/569592 [56:33<552:56:33,  3.50s/it]
                                                         

  0%|          | 1176/569592 [56:33<552:56:33,  3.50s/it]
  0%|          | 1177/569592 [56:34<429:41:20,  2.72s/it]
                                                         

  0%|          | 1177/569592 [56:34<429:41:20,  2.72s/it]
  0%|          | 1178/569592 [56:35<347:02:18,  2.20s/it]
                                                         

  0%|          | 1178/569592 [56:35<347:02:18,  2.20s/it]
  0%|          | 1179/569592 [56:36<291:13:41,  1.84s/it]
                                                         

  0%|          | 1179/569592 [56:36<291:13:41,  1.84s/it]
  0%|          | 1180/569592 [56:37<251:09:20,  1.59s/it]
                                                         

  0%|          | 1180/569592 [56:37<251:09:20,  1.59s/it]
  0%|          | 1181/569592 [56:38<221:41:29,  1.40s/it]
                                                         

  0%|          | 1181/569592 [56:38<221:41:29,  1.40s/it]
  0%|          | 1182/569592 [56:39<203:19:31,  1.29s/it]
                                                         

  0%|          | 1182/569592 [56:39<203:19:31,  1.29s/it]
  0%|          | 1183/569592 [56:40<186:09:31,  1.18s/it]
                                                         

  0%|          | 1183/569592 [56:40<186:09:31,  1.18s/it]
  0%|          | 1184/569592 [56:43<237:22:32,  1.50s/it]
                                                         

  0%|          | 1184/569592 [56:43<237:22:32,  1.50s/it]
  0%|          | 1185/569592 [56:47<396:38:32,  2.51s/it]
                                                         

  0%|          | 1185/569592 [56:47<396:38:32,  2.51s/it]
  0%|          | 1186/569592 [56:48<324:19:12,  2.05s/it]
                                                         

  0%|          | 1186/569592 [56:48<324:19:12,  2.05s/it]
  0%|          | 1187/569592 [56:49<270:35:46,  1.71s/it]
                                                         

  0%|          | 1187/569592 [56:49<270:35:46,  1.71s/it]
  0%|          | 1188/569592 [56:53<351:33:53,  2.23s/it]
                                                         

  0%|          | 1188/569592 [56:53<351:33:53,  2.23s/it]
  0%|          | 1189/569592 [56:57<449:21:14,  2.85s/it]
                                                         

  0%|          | 1189/569592 [56:57<449:21:14,  2.85s/it]
  0%|          | 1190/569592 [56:58<363:17:17,  2.30s/it]
                                                         

  0%|          | 1190/569592 [56:58<363:17:17,  2.30s/it]
  0%|          | 1191/569592 [56:59<305:56:06,  1.94s/it]
                                                         

  0%|          | 1191/569592 [56:59<305:56:06,  1.94s/it]
  0%|          | 1192/569592 [57:02<347:15:32,  2.20s/it]
                                                         

  0%|          | 1192/569592 [57:02<347:15:32,  2.20s/it]
  0%|          | 1193/569592 [57:07<491:29:15,  3.11s/it]
                                                         

  0%|          | 1193/569592 [57:07<491:29:15,  3.11s/it]
  0%|          | 1194/569592 [57:09<424:47:25,  2.69s/it]
                                                         

  0%|          | 1194/569592 [57:09<424:47:25,  2.69s/it]
  0%|          | 1195/569592 [57:10<342:06:03,  2.17s/it]
                                                         

  0%|          | 1195/569592 [57:10<342:06:03,  2.17s/it]
  0%|          | 1196/569592 [57:12<350:41:18,  2.22s/it]
                                                         

  0%|          | 1196/569592 [57:12<350:41:18,  2.22s/it]
  0%|          | 1197/569592 [57:17<467:51:58,  2.96s/it]
                                                         

  0%|          | 1197/569592 [57:17<467:51:58,  2.96s/it]
  0%|          | 1198/569592 [57:19<418:03:23,  2.65s/it]
                                                         

  0%|          | 1198/569592 [57:19<418:03:23,  2.65s/it]
  0%|          | 1199/569592 [57:20<339:54:34,  2.15s/it]
                                                         

  0%|          | 1199/569592 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
[57:20<339:54:34,  2.15s/it]
  0%|          | 1200/569592 [57:22<362:54:26,  2.30s/it]
                                                         

  0%|          | 1200/569592 [57:22<362:54:26,  2.30s/it]
  0%|          | 1201/569592 [57:26<433:58:33,  2.75s/it]
                                                         

  0%|          | 1201/569592 [57:26<433:58:33,  2.75s/it]
  0%|          | 1202/569592 [57:29<450:55:18,  2.86s/it]
                                                         

  0%|          | 1202/569592 [57:29<450:55:18,  2.86s/it]
  0%|          | 1203/569592 [57:30<366:16:43,  2.32s/it]
                                                         

  0%|          | 1203/569592 [57:30<366:16:43,  2.32s/it]
  0%|          | 1204/569592 [57:35<463:36:27,  2.94s/it]
                                                         

  0%|          | 1204/569592 [57:35<463:36:27,  2.94s/it]
  0%|          | 1205/569592 [57:37<436:17:05,  2.76s/it]
                                                         

  0%|          | 1205/569592 [57:37<436:17:05,  2.76s/it]
  0%|          | 1206/569592 [57:40<433:27:10,  2.75s/it]
                                                         

  0%|          | 1206/569592 [57:40<433:27:10,  2.75s/it]
  0%|          | 1207/569592 [57:41<352:39:45,  2.23s/it]
                                                         

  0%|          | 1207/569592 [57:41<352:39:45,  2.23s/it]
  0%|          | 1208/569592 [57:45<433:48:05,  2.75s/it]
                                                         

  0%|          | 1208/569592 [57:45<433:48:05,  2.75s/it]
  0%|          | 1209/569592 [57:47<416:44:03,  2.64s/it]
                                                         

  0%|          | 1209/569592 [57:47<416:44:03,  2.64s/it]
  0%|          | 1210/569592 [57:50<404:12:56,  2.56s/it]
                                                         

  0%|          | 1210/569592 [57:50<404:12:56,  2.56s/it]
  0%|          | 1211/569592 [57:51<332:56:10,  2.11s/it]
                                                         

  0%|          | 1211/569592 [57:51<332:56:10,  2.11s/it]
  0%|          | 1212/569592 [57:55<447:21:38,  2.83s/it]
                                                         

  0%|          | 1212/569592 [57:55<447:21:38,  2.83s/it]
  0%|          | 1213/569592 [57:58<432:44:30,  2.74s/it]
                                                         

  0%|          | 1213/569592 [57:58<432:44:30,  2.74s/it]
  0%|          | 1214/569592 [58:02<509:09:25,  3.22s/it]
                                                         

  0%|          | 1214/569592 [58:02<509:09:25,  3.22s/it]
  0%|          | 1215/569592 [58:03<406:06:25,  2.57s/it]
                                                         

  0%|          | 1215/569592 [58:03<406:06:25,  2.57s/it]
  0%|          | 1216/569592 [58:05<397:25:51,  2.52s/it]
                                                         

  0%|          | 1216/569592 [58:06<397:25:51,  2.52s/it]
  0%|          | 1217/569592 [58:08<385:59:39,  2.44s/it]
                                                         

  0%|          | 1217/569592 [58:08<385:59:39,  2.44s/it]
  0%|          | 1218/569592 [58:12<468:38:20,  2.97s/it]
                                                         

  0%|          | 1218/569592 [58:12<468:38:20,  2.97s/it]
  0%|          | 1219/569592 [58:13<373:47:32,  2.37s/it]
                                                         

  0%|          | 1219/569592 [58:13<373:47:32,  2.37s/it]
  0%|          | 1220/569592 [58:16<406:01:50,  2.57s/it]
                                                         

  0%|          | 1220/569592 [58:16<406:01:50,  2.57s/it]
  0%|          | 1221/569592 [58:18<367:18:30,  2.33s/it]
                                                         

  0%|          | 1221/569592 [58:18<367:18:30,  2.33s/it]
  0%|          | 1222/569592 [58:22<458:13:02,  2.90s/it]
                                                         

  0%|          | 1222/569592 [58:22<458:13:02,  2.90s/it]
  0%|          | 1223/569592 [58:23<367:01:28,  2.32s/it]
                                                         

  0%|          | 1223/569592 [58:23<367:01:28,  2.32s/it]
  0%|          | 1224/569592 [58:26<410:05:25,  2.60s/it]
                                                         

  0%|          | 1224/569592 [58:26<410:05:25,  2.60s/it]
  0%|          | 1225/569592 [58:28<394:15:30,  2.50s/it]
                                                         

  0%|          | 1225/569592 [58:28<394:15:30,  2.50s/it]
  0%|          | 1226/569592 [58:32<457:29:58,  2.90s/it]
                                                         

  0%|          | 1226/569592 [58:32<457:29:58,  2.90s/it]
  0%|          | 1227/569592 [58:33<366:48:38,  2.32s/it]
                                                         

  0%|          | 1227/569592 [58:33<366:48:38,  2.32s/it]
  0%|          | 1228/569592 [58:37<421:11:03,  2.67s/it]
                                                         

  0%|          | 1228/569592 [58:37<421:11:03,  2.67s/it]
  0%|          |/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 1229/569592 [58:38<358:39:56,  2.27s/it]
                                                         

  0%|          | 1229/569592 [58:38<358:39:56,  2.27s/it]
  0%|          | 1230/569592 [58:43<498:21:30,  3.16s/it]
                                                         

  0%|          | 1230/569592 [58:43<498:21:30,  3.16s/it]
  0%|          | 1231/569592 [58:44<394:13:32,  2.50s/it]
                                                         

  0%|          | 1231/569592 [58:44<394:13:32,  2.50s/it]
  0%|          | 1232/569592 [58:47<401:32:15,  2.54s/it]
                                                         

  0%|          | 1232/569592 [58:47<401:32:15,  2.54s/it]
  0%|          | 1233/569592 [58:48<330:29:30,  2.09s/it]
                                                         

  0%|          | 1233/569592 [58:48<330:29:30,  2.09s/it]
  0%|          | 1234/569592 [58:54<501:36:32,  3.18s/it]
                                                         

  0%|          | 1234/569592 [58:54<501:36:32,  3.18s/it]
  0%|          | 1235/569592 [58:55<395:55:14,  2.51s/it]
                                                         

  0%|          | 1235/569592 [58:55<395:55:14,  2.51s/it]
  0%|          | 1236/569592 [58:58<416:36:19,  2.64s/it]
                                                         

  0%|          | 1236/569592 [58:58<416:36:19,  2.64s/it]
  0%|          | 1237/569592 [58:59<358:19:06,  2.27s/it]
                                                         

  0%|          | 1237/569592 [58:59<358:19:06,  2.27s/it]
  0%|          | 1238/569592 [59:04<477:54:03,  3.03s/it]
                                                         

  0%|          | 1238/569592 [59:04<477:54:03,  3.03s/it]
  0%|          | 1239/569592 [59:05<379:07:04,  2.40s/it]
                                                         

  0%|          | 1239/569592 [59:05<379:07:04,  2.40s/it]
  0%|          | 1240/569592 [59:07<378:12:31,  2.40s/it]
                                                         

  0%|          | 1240/569592 [59:07<378:12:31,  2.40s/it]
  0%|          | 1241/569592 [59:10<399:11:27,  2.53s/it]
                                                         

  0%|          | 1241/569592 [59:10<399:11:27,  2.53s/it]
  0%|          | 1242/569592 [59:15<519:07:08,  3.29s/it]
                                                         

  0%|          | 1242/569592 [59:15<519:07:08,  3.29s/it]
  0%|          | 1243/569592 [59:16<407:04:41,  2.58s/it]
                                                         

  0%|          | 1243/569592 [59:16<407:04:41,  2.58s/it]
  0%|          | 1244/569592 [59:17<331:07:43,  2.10s/it]
                                                         

  0%|          | 1244/569592 [59:17<331:07:43,  2.10s/it]
  0%|          | 1245/569592 [59:19<332:32:12,  2.11s/it]
                                                         

  0%|          | 1245/569592 [59:19<332:32:12,  2.11s/it]
  0%|          | 1246/569592 [59:25<522:46:32,  3.31s/it]
                                                         

  0%|          | 1246/569592 [59:25<522:46:32,  3.31s/it]
  0%|          | 1247/569592 [59:26<411:26:56,  2.61s/it]
                                                         

  0%|          | 1247/569592 [59:26<411:26:56,  2.61s/it]
  0%|          | 1248/569592 [59:28<377:05:40,  2.39s/it]
                                                         

  0%|          | 1248/569592 [59:28<377:05:40,  2.39s/it]
  0%|          | 1249/569592 [59:29<309:13:51,  1.96s/it]
                                                         

  0%|          | 1249/569592 [59:29<309:13:51,  1.96s/it]
  0%|          | 1250/569592 [59:35<504:11:22,  3.19s/it]
                                                         

  0%|          | 1250/569592 [59:35<504:11:22,  3.19s/it]
  0%|          | 1251/569592 [59:38<511:34:28,  3.24s/it]
                                                         

  0%|          | 1251/569592 [59:38<511:34:28,  3.24s/it]
  0%|          | 1252/569592 [59:40<426:15:28,  2.70s/it]
                                                         

  0%|          | 1252/569592 [59:40<426:15:28,  2.70s/it]
  0%|          | 1253/569592 [59:41<341:43:32,  2.16s/it]
                                                         

  0%|          | 1253/569592 [59:41<341:43:32,  2.16s/it]
  0%|          | 1254/569592 [59:44<387:11:11,  2.45s/it]
                                                         

  0%|          | 1254/569592 [59:44<387:11:11,  2.45s/it]
  0%|          | 1255/569592 [59:45<316:39:24,  2.01s/it]
                                                         

  0%|          | 1255/569592 [59:45<316:39:24,  2.01s/it]
  0%|          | 1256/569592 [59:50<465:55:48,  2.95s/it]
                                                         

  0%|          | 1256/569592 [59:50<465:55:48,  2.95s/it]
  0%|          | 1257/569592 [59:56<607:50:05,  3.85s/it]
                                                         

  0%|          | 1257/569592 [59:56<607:50:05,  3.85s/it]
  0%|          | 1258/569592 [59:59<565:36:09,  3.58s/it]
                                                         

  0%|          | 1258/569592 [59:59<565:36:09,  3.58s/it]
  0%|          | 1259/569592 [1:00:02<537:25:12,  3.40s/it]
                                                           

  0%|          | 1259/569592 [1:00:02<537:25:12,  3.40s/it]
  0%|          | 1260/569592 [1:00:05<524:10:35,  3.32s/it]
                                                           

  0%|          | 1260/569592 [1:00:05<524:10:35,  3.32s/it]
  0%|          | 1261/569592 [1:00:06<411:51:46,  2.61s/it]
                                                           

  0%|          | 1261/569592 [1:00:06<411:51:46,  2.61s/it]
  0%|          | 1262/569592 [1:00:10<495:47:41,  3.14s/it]
                                                           

  0%|          | 1262/569592 [1:00:10<495:47:41,  3.14s/it]
  0%|          | 1263/569592 [1:00:14<504:15:07,  3.19s/it]
                                                           

  0%|          | 1263/569592 [1:00:14<504:15:07,  3.19s/it]
  0%|          | 1264/569592 [1:00:19<603:04:58,  3.82s/it]
                                                           

  0%|          | 1264/569592 [1:00:19<603:04:58,  3.82s/it]
  0%|          | 1265/569592 [1:00:22<573:29:44,  3.63s/it]
                                                           

  0%|          | 1265/569592 [1:00:22<573:29:44,  3.63s/it]
  0%|          | 1266/569592 [1:00:27<622:00:12,  3.94s/it]
                                                           

  0%|          | 1266/569592 [1:00:27<622:00:12,  3.94s/it]
  0%|          | 1267/569592 [1:00:31<627:25:04,  3.97s/it]
                                                           

  0%|          | 1267/569592 [1:00:31<627:25:04,  3.97s/it]
  0%|          | 1268/569592 [1:00:35<654:40:24,  4.15s/it]
                                                           

  0%|          | 1268/569592 [1:00:35<654:40:24,  4.15s/it]
  0%|          | 1269/569592 [1:00:43<819:56:52,  5.19s/it]
                                                           

  0%|          | 1269/569592 [1:00:43<819:56:52,  5.19s/it]
  0%|          | 1270/569592 [1:00:46<714:24:36,  4.53s/it]
                                                           

  0%|          | 1270/569592 [1:00:46<714:24:36,  4.53s/it]
  0%|          | 1271/569592 [1:00:51<726:32:46,  4.60s/it]
                                                           

  0%|          | 1271/569592 [1:00:51<726:32:46,  4.60s/it]
  0%|          | 1272/569592 [1:00:55<728:09:29,  4.61s/it]
                                                           

  0%|          | 1272/569592 [1:00:56<728:09:29,  4.61s/it]
  0%|          | 1273/569592 [1:01:00<733:44:14,  4.65s/it]
                                                           

  0%|          | 1273/569592 [1:01:00<733:44:14,  4.65s/it]
  0%|          | 1274/569592 [1:01:03<669:30:40,  4.24s/it]
                                                           

  0%|          | 1274/569592 [1:01:03<669:30:40,  4.24s/it]
  0%|          | 1275/569592 [1:01:08<692:56:50,  4.39s/it]
                                                           

  0%|          | 1275/569592 [1:01:08<692:56:50,  4.39s/it]
  0%|          | 1276/569592 [1:01:13<720:01:18,  4.56s/it]
                                                           

  0%|          | 1276/569592 [1:01:13<720:01:18,  4.56s/it]
  0%|          | 1277/569592 [1:01:18<724:39:52,  4.59s/it]
                                                           

  0%|          | 1277/569592 [1:01:18<724:39:52,  4.59s/it]
  0%|          | 1278/569592 [1:01:21<665:41:57,  4.22s/it]
                                                           

  0%|          | 1278/569592 [1:01:21<665:41:57,  4.22s/it]
  0%|          | 1279/569592 [1:01:26<690:49:05,  4.38s/it]
                                                           

  0%|          | 1279/569592 [1:01:26<690:49:05,  4.38s/it]
  0%|          | 1280/569592 [1:01:30<658:59:06,  4.17s/it]
                                                           

  0%|          | 1280/569592 [1:01:30<658:59:06,  4.17s/it]
  0%|          | 1281/569592 [1:01:35<703:30:05,  4.46s/it]
                                                           

  0%|          | 1281/569592 [1:01:35<703:30:05,  4.46s/it]
  0%|          | 1282/569592 [1:01:39<711:58:34,  4.51s/it]
                                                           

  0%|          | 1282/569592 [1:01:39<711:58:34,  4.51s/it]
  0%|          | 1283/569592 [1:01:43<655:25:25,  4.15s/it]
                                                           

  0%|          | 1283/569592 [1:01:43<655:25:25,  4.15s/it]
  0%|          | 1284/569592 [1:01:48<697:42:59,  4.42s/it]
                                                           

  0%|          | 1284/569592 [1:01:48<697:42:59,  4.42s/it]
  0%|          | 1285/569592 [1:01:51<628:24:57,  3.98s/it]
                                                           

  0%|          | 1285/569592 [1:01:51<628:24:57,  3.98s/it]
  0%|          | 1286/569592 [1:01:55<629:54:28,  3.99s/it]
                                                           

  0%|          | 1286/569592 [1:01:55<629:54:28,  3.99s/it]
  0%|          | 1287/569592 [1:01:59<664:32:05,  4.21s/it]
                                                           

  0%|          | 1287/569592 [1:01:59<664:32:05,  4.21s/it]
  0%|          | 1288/569592 [1:02:00<506:46:49,  3.21s/it]
                                                           

  0%|          | 1288/569592 [1:02:00<506:46:49,  3.21s/it]
  0%|          | 1289/569592 [1:02:05<576:58:14,  3.65s/it]
                                                           

  0%|          | 1289/569592 [1:02:05<576:58:14,  3.65s/it]
  0%|          | 1290/569592 [1:02:06<447:21:51,  2.83s/it]
                                                           

  0%|          | 1290/569592 [1:02:06<447:21:51,  2.83s/it]
  0%|          | 1291/569592 [1:02:11<541:39:11,  3.43s/it]
                                                           

  0%|          | 1291/569592 [1:02:11<541:39:11,  3.43s/it]
  0%|          | 1292/569592 [1:02:12<425:14:40,  2.69s/it]
                                                           

  0%|          | 1292/569592 [1:02:12<425:14:40,  2.69s/it]
  0%|          | 1293/569592 [1:02:15<452:23:19,  2.87s/it]
                                                           

  0%|          | 1293/569592 [1:02:15<452:23:19,  2.87s/it]
  0%|          | 1294/569592 [1:02:18<465:05:24,  2.95s/it]
                                                           

  0%|          | 1294/569592 [1:02:18<465:05:24,  2.95s/it]
  0%|          | 1295/569592 [1:02:19<375:33:24,  2.38s/it]
                                                           

  0%|          | 1295/569592 [1:02:19<375:33:24,  2.38s/it]
  0%|          | 1296/569592 [1:02:20<314:22:41,  1.99s/it]
                                                           

  0%|          | 1296/569592 [1:02:20<314:22:41,  1.99s/it]
  0%|          | 1297/569592 [1:02:21<272:35:41,  1.73s/it]
                                                           

  0%|          | 1297/569592 [1:02:21<272:35:41,  1.73s/it]
  0%|          | 1298/569592 [1:02:22<239:09:04,  1.51s/it]
                                                           

  0%|          | 1298/569592 [1:02:22<239:09:04,  1.51s/it]
  0%|          | 1299/569592 [1:02:23<212:04:19,  1.34s/it]
                                                           

  0%|          | 1299/569592 [1:02:23<212:04:19,  1.34s/it]
  0%|          | 1300/569592 [1:02:24<192:58:28,  1.22s/it]
                                                           

  0%|          | 1300/569592 [1:02:24<192:58:28,  1.22s/it]
  0%|          | 1301/569592 [1:02:25<179:37:04,  1.14s/it]
                                                           

  0%|          | 1301/569592 [1:02:25<179:37:04,  1.14s/it]
  0%|          | 1302/569592 [1:02:28<253:53:35,  1.61s/it]
                                                           

  0%|          | 1302/569592 [1:02:28<253:53:35,  1.61s/it]
  0%|          | 1303/569592 [1:02:32<380:54:47,  2.41s/it]
                                                           

  0%|          | 1303/569592 [1:02:32<380:54:47,  2.41s/it]
  0%|          | 1304/569592 [1:02:34<359:31:14,  2.28s/it]
                                                           

  0%|          | 1304/569592 [1:02:34<359:31:14,  2.28s/it]
  0%|          | 1305/569592 [1:02:35<309:28:36,  1.96s/it]
                                                           

  0%|          | 1305/569592 [1:02:35<309:28:36,  1.96s/it]
  0%|          | 1306/569592 [1:02:39<381:49:10,  2.42s/it]
                                                           

  0%|          | 1306/569592 [1:02:39<381:49:10,  2.42s/it]
  0%|          | 1307/569592 [1:02:42<435:38:05,  2.76s/it]
                                                           

  0%|          | 1307/569592 [1:02:42<435:38:05,  2.76s/it]
  0%|          | 1308/569592 [1:02:44<371:26:51,  2.35s/it]
                                                           

  0%|          | 1308/569592 [1:02:44<371:26:51,  2.35s/it]
  0%|          | 1309/569592 [1:02:46<344:53:54,  2./home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
18s/it]
                                                           

  0%|          | 1309/569592 [1:02:46<344:53:54,  2.18s/it]
  0%|          | 1310/569592 [1:02:50<444:09:38,  2.81s/it]
                                                           

  0%|          | 1310/569592 [1:02:50<444:09:38,  2.81s/it]
  0%|          | 1311/569592 [1:02:52<425:17:59,  2.69s/it]
                                                           

  0%|          | 1311/569592 [1:02:52<425:17:59,  2.69s/it]
  0%|          | 1312/569592 [1:02:54<378:31:38,  2.40s/it]
                                                           

  0%|          | 1312/569592 [1:02:54<378:31:38,  2.40s/it]
  0%|          | 1313/569592 [1:02:56<369:26:35,  2.34s/it]
                                                           

  0%|          | 1313/569592 [1:02:56<369:26:35,  2.34s/it]
  0%|          | 1314/569592 [1:03:01<481:28:19,  3.05s/it]
                                                           

  0%|          | 1314/569592 [1:03:01<481:28:19,  3.05s/it]
  0%|          | 1315/569592 [1:03:03<426:21:00,  2.70s/it]
                                                           

  0%|          | 1315/569592 [1:03:03<426:21:00,  2.70s/it]
  0%|          | 1316/569592 [1:03:05<382:41:35,  2.42s/it]
                                                           

  0%|          | 1316/569592 [1:03:05<382:41:35,  2.42s/it]
  0%|          | 1317/569592 [1:03:06<358:25:37,  2.27s/it]
                                                           

  0%|          | 1317/569592 [1:03:06<358:25:37,  2.27s/it]
  0%|          | 1318/569592 [1:03:09<349:42:49,  2.22s/it]
                                                           

  0%|          | 1318/569592 [1:03:09<349:42:49,  2.22s/it]
  0%|          | 1319/569592 [1:03:14<500:34:01,  3.17s/it]
                                                           

  0%|          | 1319/569592 [1:03:14<500:34:01,  3.17s/it]
  0%|          | 1320/569592 [1:03:15<398:36:55,  2.53s/it]
                                                           

  0%|          | 1320/569592 [1:03:15<398:36:55,  2.53s/it]
  0%|          | 1321/569592 [1:03:17<374:47:25,  2.37s/it]
                                                           

  0%|          | 1321/569592 [1:03:17<374:47:25,  2.37s/it]
  0%|          | 1322/569592 [1:03:20<416:36:07,  2.64s/it]
                                                           

  0%|          | 1322/569592 [1:03:20<416:36:07,  2.64s/it]
  0%|          | 1323/569592 [1:03:23<437:40:19,  2.77s/it]
                                                           

  0%|          | 1323/569592 [1:03:23<437:40:19,  2.77s/it]
  0%|          | 1324/569592 [1:03:26<452:19:32,  2.87s/it]
                                                           

  0%|          | 1324/569592 [1:03:26<452:19:32,  2.87s/it]
  0%|          | 1325/569592 [1:03:27<365:10:56,  2.31s/it]
                                                           

  0%|          | 1325/569592 [1:03:27<365:10:56,  2.31s/it]
  0%|          | 1326/569592 [1:03:30<393:34:19,  2.49s/it]
                                                           

  0%|          | 1326/569592 [1:03:30<393:34:19,  2.49s/it]
  0%|          | 1327/569592 [1:03:34<443:59:59,  2.81s/it]
                                                           

  0%|          | 1327/569592 [1:03:34<443:59:59,  2.81s/it]
  0%|          | 1328/569592 [1:03:36<389:12:16,  2.47s/it]
                                                           

  0%|          | 1328/569592 [1:03:36<389:12:16,  2.47s/it]
  0%|          | 1329/569592 [1:03:37<320:19:29,  2.03s/it]
                                                           

  0%|          | 1329/569592 [1:03:37<320:19:29,  2.03s/it]
  0%|          | 1330/569592 [1:03:40<369:17:50,  2.34s/it]
                                                           

  0%|          | 1330/569592 [1:03:40<369:17:50,  2.34s/it]
  0%|          | 1331/569592 [1:03:43<440:27:27,  2.79s/it]
                                                           

  0%|          | 1331/569592 [1:03:43<440:27:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95971008 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
27,  2.79s/it]
  0%|          | 1332/569592 [1:03:47<476:31:47,  3.02s/it]
                                                           

  0%|          | 1332/569592 [1:03:47<476:31:47,  3.02s/it]
  0%|          | 1333/569592 [1:03:48<377:20:18,  2.39s/it]
                                                           

  0%|          | 1333/569592 [1:03:48<377:20:18,  2.39s/it]
  0%|          | 1334/569592 [1:03:50<369:12:13,  2.34s/it]
                                                           

  0%|          | 1334/569592 [1:03:51<369:12:13,  2.34s/it]
  0%|          | 1335/569592 [1:03:55<477:00:34,  3.02s/it]
                                                           

  0%|          | 1335/569592 [1:03:55<477:00:34,  3.02s/it]
  0%|          | 1336/569592 [1:03:58<467:09:56,  2.96s/it]
                                                           

  0%|          | 1336/569592 [1:03:58<467:09:56,  2.96s/it]
  0%|          | 1337/569592 [1:03:59<372:20:26,  2.36s/it]
                                                           

  0%|          | 1337/569592 [1:03:59<372:20:26,  2.36s/it]
  0%|          | 1338/569592 [1:04:01<359:05:00,  2.27s/it]
                                                           

  0%|          | 1338/569592 [1:04:01<359:05:00,  2.27s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102402000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  0%|          | 1339/569592 [1:04:04<410:24:32,  2.60s/it]
                                                           

  0%|          | 1339/569592 [1:04:04<410:24:32,  2.60s/it]
  0%|          | 1340/569592 [1:04:07<417:05:22,  2.64s/it]
                                                           

  0%|          | 1340/569592 [1:04:07<417:05:22,  2.64s/it]
  0%|          | 1341/569592 [1:04:08<339:39:39,  2.15s/it]
                                                           

  0%|          | 1341/569592 [1:04:08<339:39:39,  2.15s/it]
  0%|          | 1342/569592 [1:04:10<336:44:34,  2.13s/it]
                                                           

  0%|          | 1342/569592 [1:04:10<336:44:34,  2.13s/it]
  0%|          | 1343/569592 [1:04:14<415:50:39,  2.63s/it]
                                                           

  0%|          | 1343/569592 [1:04:14<415:50:39,  2.63s/it]
  0%|          | 1344/569592 [1:04:19<534:05:29,  3.38s/it]
                                                          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 

  0%|          | 1344/569592 [1:04:19<534:05:29,  3.38s/it]
  0%|          | 1345/569592 [1:04:20<422:14:39,  2.68s/it]
                                                           

  0%|          | 1345/569592 [1:04:20<422:14:39,  2.68s/it]
  0%|          | 1346/569592 [1:04:21<342:17:07,  2.17s/it]
                                                           

  0%|          | 1346/569592 [1:04:21<342:17:07,  2.17s/it]
  0%|          | 1347/569592 [1:04:24<408:47:22,  2.59s/it]
                                                           

  0%|          | 1347/569592 [1:04:24<408:47:22,  2.59s/it]
  0%|          | 1348/569592 [1:04:27<420:54:48,  2.67s/it]
                                                           

  0%|          | 1348/569592 [1:04:27<420:54:48,  2.67s/it]
  0%|          | 1349/569592 [1:04:28<348:54:54,  2.21s/it]
                                                           

  0%|          | 1349/569592 [1:04:28<348:54:54,  2.21s/it]
  0%|          | 1350/569592 [1:04:30<310:02:01,  1.96s/it]
                                                           

  0%|          | 1350/569592 [1:04:30<310:02:01,  1.96s/it]
  0%|          | 1351/569592 [1:04:35<447:06:40,  2.83s/it]
                                                           

  0%|          | 1351/569592 [1:04:35<447:06:40,  2.83s/it]
  0%|          | 1352/569592 [1:04:39<526:04:31,  3.33s/it]
                                                           

  0%|          | 1352/569592 [1:04:39<526:04:31,  3.33s/it]
  0%|          | 1353/569592 [1:04:40<415:47:35,  2.63s/it]
                                                           

  0%|          | 1353/569592 [1:04:40<415:47:35,  2.63s/it]
  0%|          | 1354/569592 [1:04:41<335:41:44,  2.13s/it]
                                                           

  0%|          | 1354/569592 [1:04:41<335:41:44,  2.13s/it]
  0%|          | 1355/569592 [1:04:45<402:58:18,  2.55s/it]
                                                           

  0%|          | 1355/569592 [1:04:45<402:58:18,  2.55s/it]
  0%|          | 1356/569592 [1:04:49<500:28:50,  3.17s/it]
                                                           

  0%|          | 1356/569592 [1:04:49<500:28:50,  3.17s/it]
  0%|          | 1357/569592 [1:04:50<394:12:41,  2.50s/it]
                                                           

  0%|          | 1357/569592 [1:04:50<394:12:41,  2.50s/it]
  0%|          | 1358/569592 [1:04:51<319:48:24,  2.03s/it]
                                                           

  0%|          | 1358/569592 [1:04:51<319:48:24,  2.03s/it]
  0%|          | 1359/569592 [1:04:55<423:04:33,  2.68s/it]
                                                           

  0%|          | 1359/569592 [1:04:55<423:04:33,  2.68s/it]
  0%|          | 1360/569592 [1:04:58<425:24:07,  2.70s/it]
                                                           

  0%|          | 1360/569592 [1:04:58<425:24:07,  2.70s/it]
  0%|          | 1361/569592 [1:04:59<343:26:06,  2.18s/it]
                                                           

  0%|          | 1361/569592 [1:04:59<343:26:06,  2.18s/it]
  0%|          | 1362/569592 [1:05:00<286:02:48,  1.81s/it]
                                                           

  0%|          | 1362/569592 [1:05:00<286:02:48,  1.81s/it]
  0%|          | 1363/569592 [1:05:06<498:09:30,  3.16s/it]
                                                           

  0%|          | 1363/569592 [1:05:06<498:09:30,  3.16s/it]
  0%|          | 1364/569592 [1:05:09<484:03:57,  3.07s/it]
                                                           

  0%|          | 1364/569592 [1:05:09<484:03:57,  3.07s/it]
  0%|          | 1365/569592 [1:05:11<416:45:09,  2.64s/it]
                                                           

  0%|          | 1365/569592 [1:05:11<416:45:09,  2.64s/it]
  0%|          | 1366/569592 [1:05:12<348:39:45,  2.21s/it]
                                                           

  0%|          | 1366/569592 [1:05:12<348:39:45,  2.21s/it]
  0%|          | 1367/569592 [1:05:15<400:46:17,  2.54s/it]
                                                           

  0%|          | 1367/569592 [1:05:15<400:46:17,  2.54s/it]
  0%|          | 1368/569592 [1:05:19<441:04:06,  2.79s/it]
                                                           

  0%|          | 1368/569592 [1:05:19<441:04:06,  2.79s/it]
  0%|          | 1369/569592 [1:05:21<435:55:50,  2.76s/it]
                                                           

  0%|          | 1369/569592 [1:05:21<435:55:50,  2.76s/it]
  0%|          | 1370/569592 [1:05:26<539:57:40,  3.42s/it]
                                                           

  0%|          | 1370/569592 [1:05:26<539:57:40,  3.42s/it]
  0%|          | 1371/569592 [1:05:27<421:07:02,  2.67s/it]
                                                           

  0%|          | 1371/569592 [1:05:27<421:07:02,  2.67s/it]
  0%|          | 1372/569592 [1:05:30<452:54:16,  2.87s/it]
                                                           

  0%|          | 1372/569592 [1:05:31<452:54:16,  2.87s/it]
  0%|          | 1373/569592 [1:05:35<525:38:42,  3.33s/it]
                                                           

  0%|          | 1373/569592 [1:05:35<525:38:42,  3.33s/it]
  0%|          | 1374/569592 [1:05:40<595:28:55,  3.77s/it]
                                                           

  0%|          | 1374/569592 [1:05:40<595:28:55,  3.77s/it]
  0%|          | 1375/569592 [1:05:44<632:21:22,  4.01s/it]
                                                           

  0%|          | 1375/569592 [1:05:44<632:21:22,  4.01s/it]
  0%|          | 1376/569592 [1:05:47<588:03:59,  3.73s/it]
                                                           

  0%|          | 1376/569592 [1:05:47<588:03:59,  3.73s/it]
  0%|          | 1377/569592 [1:05:53<656:39:11,  4.16s/it]
                                                           

  0%|          | 1377/569592 [1:05:53<656:39:11,  4.16s/it]
  0%|          | 1378/569592 [1:05:56<607:18:02,  3.85s/it]
                                                           

  0%|          | 1378/569592 [1:05:56<607:18:02,  3.85s/it]
  0%|          | 1379/569592 [1:06:00<643:45:54,  4.08s/it]
                                                           

  0%|          | 1379/569592 [1:06:00<643:45:54,  4.08s/it]
  0%|          | 1380/569592 [1:06:05<665:24:20,  4.22s/it]
                                                           

  0%|          | 1380/569592 [1:06:05<665:24:20,  4.22s/it]
  0%|          | 1381/569592 [1:06:08<617:09:40,  3.91s/it]
                                                           

  0%|          | 1381/569592 [1:06:08<617:09:40,  3.91s/it]
  0%|          | 1382/569592 [1:06:13<664:42:10,  4.21s/it]
                                                           

  0%|          | 1382/569592 [1:06:13<664:42:10,  4.21s/it]
  0%|          | 1383/569592 [1:06:14<507:41:32,  3.22s/it]
                                                           

  0%|          | 1383/569592 [1:06:14<507:41:32,  3.22s/it]
  0%|          | 1384/569592 [1:06:18<576:01:54,  3.65s/it]
                                                           

  0%|          | 1384/569592 [1:06:18<576:01:54,  3.65s/it]
  0%|          | 1385/569592 [1:06:23<637:54:06,  4.04s/it]
                                                           

  0%|          | 1385/569592 [1:06:23<637:54:06,  4.04s/it]
  0%|          | 1386/569592 [1:06:28<668:37:37,  4.24s/it]
                                                           

  0%|          | 1386/569592 [1:06:28<668:37:37,  4.24s/it]
  0%|          | 1387/569592 [1:06:32<673:06:29,  4.26s/it]
                                                           

  0%|          | 1387/569592 [1:06:32<673:06:29,  4.26s/it]
  0%|          | 1388/569592 [1:06:36<630:07:45,  3.99s/it]
                                                           

  0%|          | 1388/569592 [1:06:36<630:07:45,  3.99s/it]
  0%|          | 1389/569592 [1:06:40<649:47:17,  4.12s/it]
                                                           

  0%|          | 1389/569592 [1:06:40<649:47:17,  4.12s/it]
  0%|          | 1390/569592 [1:06:45<685:20:53,  4.34s/it]
                                                           

  0%|          | 1390/569592 [1:06:45<685:20:53,  4.34s/it]
  0%|          | 1391/569592 [1:06:50<700:38:09,  4.44s/it]
                                                           

  0%|          | 1391/569592 [1:06:50<700:38:09,  4.44s/it]
  0%|          | 1392/569592 [1:06:54<675:44:11,  4.28s/it]
                                                           

  0%|          | 1392/569592 [1:06:54<675:44:11,  4.28s/it]
  0%|          | 1393/569592 [1:06:58<692:45:30,  4.39s/it]
                                                           

  0%|          | 1393/569592 [1:06:58<692:45:30,  4.39s/it]
  0%|          | 1394/569592 [1:07:02<649:38:59,  4.12s/it]
                                                           

  0%|          | 1394/569592 [1:07:02<649:38:59,  4.12s/it]
  0%|          | 1395/569592 [1:07:07<692:31:49,  4.39s/it]
                                                           

  0%|          | 1395/569592 [1:07:07<692:31:49,  4.39s/it]
  0%|          | 1396/569592 [1:07:10<624:46:26,  3.96s/it]
                                                           

  0%|          | 1396/569592 [1:07:10<624:46:26,  3.96s/it]
  0%|          | 1397/569592 [1:07:16<742:50:38,  4.71s/it]
                                                           

  0%|          | 1397/569592 [1:07:16<742:50:38,  4.71s/it]
  0%|          | 1398/569592 [1:07:21<744:44:29,  4.72s/it]
                                                           

  0%|          | 1398/569592 [1:07:21<744:44:29,  4.72s/it]
  0%|          | 1399/569592 [1:07:24<682:50:51,  4.33s/it]
                                                           

  0%|          | 1399/569592 [1:07:24<682:50:51,  4.33s/it]
  0%|          | 1400/569592 [1:07:25<519:54:02,  3.29s/it]
                                                           

  0%|          | 1400/569592 [1:07:25<519:54:02,  3.29s/it]
  0%|          | 1401/569592 [1:07:29<558:10:16,  3.54s/it]
                                                           

  0%|          | 1401/569592 [1:07:29<558:10:16,  3.54s/it]
  0%|          | 1402/569592 [1:07:34<620:35:00,  3.93s/it]
                                                           

  0%|          | 1402/569592 [1:07:34<620:35:00,  3.93s/it]
  0%|          | 1403/569592 [1:07:38<635:39:22,  4.03s/it]
                                                           

  0%|          | 1403/569592 [1:07:38<635:39:22,  4.03s/it]
  0%|          | 1404/569592 [1:07:43<662:48:30,  4.20s/it]
                                                           

  0%|          | 1404/569592 [1:07:43<662:48:30,  4.20s/it]
  0%|          | 1405/569592 [1:07:48<697:34:55,  4.42s/it]
                                                           

  0%|          | 1405/569592 [1:07:48<697:34:55,  4.42s/it]
  0%|          | 1406/569592 [1:07:49<535:26:21,  3.39s/it]
                                                           

  0%|          | 1406/569592 [1:07:49<535:26:21,  3.39s/it]
  0%|          | 1407/569592 [1:07:54<604:34:01,  3.83s/it]
                                                           

  0%|          | 1407/569592 [1:07:54<604:34:01,  3.83s/it]
  0%|          | 1408/569592 [1:07:55<470:42:13,  2.98s/it]
                                                           

  0%|          | 1408/569592 [1:07:55<470:42:13,  2.98s/it]
  0%|          | 1409/569592 [1:07:59<518:32:59,  3.29s/it]
                                                           

  0%|          | 1409/569592 [1:07:59<518:32:59,  3.29s/it]
  0%|          | 1410/569592 [1:08:04<595:04:10,  3.77s/it]
                                                           

  0%|          | 1410/569592 [1:08:04<595:04:10,  3.77s/it]
  0%|          | 1411/569592 [1:08:05<459:53:56,  2.91s/it]
                                                           

  0%|          | 1411/569592 [1:08:05<459:53:56,  2.91s/it]
  0%|          | 1412/569592 [1:08:08<464:07:08,  2.94s/it]
                                                           

  0%|          | 1412/569592 [1:08:08<464:07:08,  2.94s/it]
  0%|          | 1413/569592 [1:08:09<380:57:09,  2.41s/it]
                                                           

  0%|          | 1413/569592 [1:08:09<380:57:09,  2.41s/it]
  0%|          | 1414/569592 [1:08:10<314:54:44,  2.00s/it]
                                                           

  0%|          | 1414/569592 [1:08:10<314:54:44,  2.00s/it]
  0%|          | 1415/569592 [1:08:11<267:07:52,  1.69s/it]
                                                           

  0%|          | 1415/569592 [1:08:11<267:07:52,  1.69s/it]
  0%|          | 1416/569592 [1:08:12<233:29:16,  1.48s/it]
                                                           

  0%|          | 1416/569592 [1:08:12<233:29:16,  1.48s/it]
  0%|          | 1417/569592 [1:08:13<209:15:17,  1.33s/it]
                                                           

  0%|          | 1417/569592 [1:08:13<209:15:17,  1.33s/it]
  0%|          | 1418/569592 [1:08:14<191:50:13,  1.22s/it]
                                                           

  0%|          | 1418/569592 [1:08:14<191:50:13,  1.22s/it]
  0%|          | 1419/569592 [1:08:17<291:41:31,  1.85s/it]
                                                           

  0%|          | 1419/569592 [1:08:17<291:41:31,  1.85s/it]
  0%|          | 1420/569592 [1:08:18<255:22:40,  1.62s/it]
                                                           

  0%|          | 1420/569592 [1:08:18<255:22:40,  1.62s/it]
  0%|          | 1421/569592 [1:08:21<295:30:07,  1.87s/it]
                                                           

  0%|          | 1421/569592 [1:08:21<295:30:07,  1.87s/it]
  0%|          | 1422/569592 [1:08:22<280:37:18,  1.78s/it]
                                                           

  0%|          | 1422/569592 [1:08:22<280:37:18,  1.78s/it]
  0%|          | 1423/569592 [1:08:26<398:18:56,  2.52s/it]
                                                           

  0%|          | 1423/569592 [1:08:26<398:18:56,  2.52s/it]
  0%|          | 1424/569592 [1:08:28<335:48:18,  2.13s/it]
                                                           

  0%|          | 1424/569592 [1:08:28<335:48:18,  2.13s/it]
  0%|          | 1425/569592 [1:08:31<401:38:00,  2.54s/it]
                                                           

  0%|          | 1425/569592 [1:08:31<401:38:00,  2.54s/it]
  0%|          | 1426/569592 [1:08:33<384:55:17,  2.44s/it]
                                                           

  0%|          | 1426/569592 [1:08:33<384:55:17,  2.44s/it]
  0%|          | 1427/569592 [1:08:36<418:19:29,  2.65s/it]
                                                           

  0%|          | 1427/569592 [1:08:36<418:19:29,  2.65s/it]
  0%|          | 1428/569592 [1:08:39<402:49:23,  2.55s/it]
                                                           

  0%|          | 1428/569592 [1:08:39<402:49:23,  2.55s/it]
  0%|          | 1429/569592 [1:08:41<377:33:26,  2.39s/it]
                                                           

  0%|          | 1429/569592 [1:08:41<377:33:26,  2.39s/it]
  0%|          | 1430/569592 [1:08:43<346:12:18,  2.19s/it]
                                                           

  0%|          | 1430/569592 [1:08:43<346:12:18,  2.19s/it]
  0%|          | 1431/569592 [1:08:47<439:40:14,  2.79s/it]
                                                           

  0%|          | 1431/569592 [1:08:47<439:40:14,  2.79s/it]
  0%|          | 1432/569592 [1:08:48<357:12:16,  2.26s/it]
                                                           

  0%|          | 1432/569592 [1:08:48<357:12:16,  2.26s/it]
  0%|          | 1433/569592 [1:08:52<461:55:11,  2.93s/it]
                                                           

  0%|          | 1433/569592 [1:08:52<461:55:11,  2.93s/it]
  0%|          | 1434/569592 [1:08:53<370:09:06,  2.35s/it]
                                                           

  0%|          | 1434/569592 [1:08:53<370:09:06,  2.35s/it]
  0%|          | 1435/569592 [1:08:57<419:05:39,  2.66s/it]
                                                           

  0%|          | 1435/569592 [1:08:57<419:05:39,  2.66s/it]
  0%|          | 1436/569592 [1:08:58<360:07:51,  2.28s/it]
                                                           

  0%|          | 1436/569592 [1:08:58<360:07:51,  2.28s/it]
  0%|          | 1437/569592 [1:09:02<438:10:21,  2.78s/it]
                                                           

  0%|          | 1437/569592 [1:09:02<438:10:21,  2.78s/it]
  0%|          | 1438/569592 [1:09:03<351:26:17,  2.23s/it]
                                                           

  0%|          | 1438/569592 [1:09:03<351:26:17,  2.23s/it]
  0%|          | 1439/569592 [1:09:07<433:58:47,  2.75s/it]
                                                           

  0%|          | 1439/569592 [1:09:07<433:58:47,  2.75s/it]
  0%|          | 1440/569592 [1:09:08<373:43:22,  2.37s/it]
                                                           

  0%|          | 1440/569592 [1:09:08<373:43:22,  2.37s/it]
  0%|          | 1441/569592 [1:09:11<385:00:34,  2.44s/it]
                                                           

  0%|          | 1441/569592 [1:09:11<385:00:34,  2.44s/it]
  0%|          | 1442/569592 [1:09:13<380:05:12,  2.41s/it]
                                                           

  0%|          | 1442/569592 [1:09:13<380:05:12,  2.41s/it]
  0%|          | 1443/569592 [1:09:18<483:24:14,  3.06s/it]
                                                           

  0%|          | 1443/569592 [1:09:18<483:24:14,  3.06s/it]
  0%|          | 1444/569592 [1:09:20<430:28:16,  2.73s/it]
                                                           

  0%|          | 1444/569592 [1:09:20<430:28:16,  2.73s/it]
  0%|          | 1445/569592 [1:09:23<473:17:43,  3.00s/it]
                                                           

  0%|          | 1445/569592 [1:09:23<473:17:43,  3.00s/it]
  0%|          | 1446/569592 [1:09:24<377:48:53,  2.39s/it]
                                                           

  0%|          | 1446/569592 [1:09:24<377:48:53,  2.39s/it]
  0%|          | 1447/569592 [1:09:28<428:03:01,  2.71s/it]
                                                           

  0%|          | 1447/569592 [1:09:28<428:03:01,  2.71s/it]
  0%|          | 1448/569592 [1:09:30<398:14:24,  2.52s/it]
                                                           

  0%|          | 1448/569592 [1:09:30<398:14:24,  2.52s/it]
  0%|          | 1449/569592 [1:09:32<398:29:06,  2.52s/it]
                                                           

  0%|          | 1449/569592 [1:09:33<398:29:06,  2.52s/it]
  0%|          | 1450/569592 [1:09:34<356:36:22,  2.26s/it]
                                                           

  0%|          | 1450/569592 [1:09:34<356:36:22,  2.26s/it]
  0%|          | 1451/569592 [1:09:38<415:41:42,  2.63s/it]
                                                           

  0%|          | 1451/569592 [1:09:38<415:41:42,  2.63s/it]
  0%|          | 1452/569592 [1:09:40<387:03:20,  2.45s/it]
                                                           

  0%|          | 1452/569592 [1:09:40<387:03:20,  2.45s/it]
  0%|          | 1453/569592 [1:09:43<442:46:17,  2.81s/it]
                                                           

  0%|          | 1453/569592 [1:09:43<442:46:17,  2.81s/it]
  0%|          | 1454/569592 [1:09:44<357:03:02,  2.26s/it]
                                                           

  0%|          | 1454/569592 [1:09:44<357:03:02,  2.26s/it]
  0%|          | 1455/569592 [1:09:48<402:55:25,  2.55s/it]
                                                           

  0%|          | 1455/569592 [1:09:48<402:55:25,  2.55s/it]
  0%|          | 1456/569592 [1:09:51<438:51:45,  2.78s/it]
                                                           

  0%|          | 1456/569592 [1:09:51<438:51:45,  2.78s/it]
  0%|          | 1457/569592 [1:09:54<437:40:44,  2.77s/it]
                                                           

  0%|          | 1457/569592 [1:09:54<437:40:44,  2.77s/it]
  0%|          | 1458/569592 [1:09:55<355:15:53,  2.25s/it]
                                                           

  0%|          | 1458/569592 [1:09:55<355:15:53,  2.25s/it]
  0%|          | 1459/569592 [1:09:58<401:09:09,  2.54s/it]
                                                           

  0%|          | 1459/569592 [1:09:58<401:09:09,  2.54s/it]
  0%|          | 1460/569592 [1:10:00<385:33:02,  2.44s/it]
                                                           

  0%|          | 1460/569592 [1:10:00<385:33:02,  2.44s/it]
  0%|          | 1461/569592 [1:10:04<444:15:39,  2.82s/it]
                                                           

  0%|          | 1461/569592 [1:10:04<444:15:39,  2.82s/it]
  0%|          | 1462/569592 [1:10:05<367:12:21,  2.33s/it]
                                                           

  0%|          | 1462/569592 [1:10:05<367:12:21,  2.33s/it]
  0%|          | 1463/569592 [1:10:08<419:00:30,  2.66s/it]
                                                           

  0%|          | 1463/569592 [1:10:08<419:00:30,  2.66s/it]
  0%|          | 1464/569592 [1:10:11<396:09:53,  2.51s/it]
                                                           

  0%|          | 1464/569592 [1:10:11<396:09:53,  2.51s/it]
  0%|          | 1465/569592 [1:10:14<451:12:19,  2.86s/it]
                                                           

  0%|          | 1465/569592 [1:10:14<451:12:19,  2.86s/it]
  0%|          | 1466/569592 [1:10:15<364:20:48,  2.31s/it]
                                                           

  0%|          | 1466/569592 [1:10:15<364:20:48,  2.31s/it]
  0%|          | 1467/569592 [1:10:17<338:19:54,  2.14s/it]
                                                           

  0%|          | 1467/569592 [1:10:17<338:19:54,  2.14s/it]
  0%|          | 1468/569592 [1:10:20<395:05:39,  2.50s/it]
                                                           

  0%|          | 1468/569592 [1:10:20<395:05:39,  2.50s/it]
  0%|          | 1469/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/569592 [1:10:23<426:43:37,  2.70s/it]
                                                           

  0%|          | 1469/569592 [1:10:24<426:43:37,  2.70s/it]
  0%|          | 1470/569592 [1:10:27<462:44:28,  2.93s/it]
                                                           

  0%|          | 1470/569592 [1:10:27<462:44:28,  2.93s/it]
  0%|          | 1471/569592 [1:10:28<372:34:08,  2.36s/it]
                                                           

  0%|          | 1471/569592 [1:10:28<372:34:08,  2.36s/it]
  0%|          | 1472/569592 [1:10:31<424:45:14,  2.69s/it]
                                                           

  0%|          | 1472/569592 [1:10:31<424:45:14,  2.69s/it]
  0%|          | 1473/569592 [1:10:35<447:18:12,  2.83s/it]
                                                           

  0%|          | 1473/569592 [1:10:35<447:18:12,  2.83s/it]
  0%|          | 1474/569592 [1:10:37<449:11:05,  2.85s/it]
                                                           

  0%|          | 1474/569592 [1:10:38<449:11:05,  2.85s/it]
  0%|          | 1475/569592 [1:10:39<366:23:29,  2.32s/it]
                                                           

  0%|          | 1475/569592 [1:10:39<366:23:29,  2.32s/it]
  0%|          | 1476/569592 [1:10:41<365:10:34,  2.31s/it]
                                                           

  0%|          | 1476/569592 [1:10:41<365:10:34,  2.31s/it]
  0%|          | 1477/569592 [1:10:44<419:24:26,  2.66s/it]
                                                           

  0%|          | 1477/569592 [1:10:44<419:24:26,  2.66s/it]
  0%|          | 1478/569592 [1:10:48<450:39:00,  2.86s/it]
                                                           

  0%|          | 1478/569592 [1:10:48<450:39:00,  2.86s/it]
  0%|          | 1479/569592 [1:10:49<360:39:21,  2.29s/it]
                                                           

  0%|          | 1479/569592 [1:10:49<360:39:21,  2.29s/it]
  0%|          | 1480/569592 [1:10:51<361:08:09,  2.29s/it]
                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95691240 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                         

  0%|          | 1480/569592 [1:10:51<361:08:09,  2.29s/it]
  0%|          | 1481/569592 [1:10:54<414:18:14,  2.63s/it]
                                                           

  0%|          | 1481/569592 [1:10:54<414:18:14,  2.63s/it]
  0%|          | 1482/569592 [1:10:58<450:47:24,  2.86s/it]
                                                           

  0%|          | 1482/569592 [1:10:58<450:47:24,  2.86s/it]
  0%|          | 1483/569592 [1:11:03<563:16:58,  3.57s/it]
                                                           

  0%|          | 1483/569592 [1:11:03<563:16:58,  3.57s/it]
  0%|          | 1484/569592 [1:11:04<438:24:19,  2.78s/it]
                                                           

  0%|          | 1484/569592 [1:11:04<438:24:19,  2.78s/it]
  0%|          | 1485/569592 [1:11:08<479:47:18,  3.04s/it]
                                                           

  0%|          | 1485/569592 [1:11:08<479:47:18,  3.04s/it]
  0%|          | 1486/569592 [1:11:12<569:43:43,  3.61s/it]
                                                           

  0%|          | 1486/569592 [1:11:12<569:43:43,  3.61s/it]
  0%|          | 1487/569592 [1:11:13<441:49:12,  2.80s/it]
                                                           

  0%|          | 1487/569592 [1:11:13<441:49:12,  2.80s/it]
  0%|          | 1488/569592 [1:11:17<463:12:22,  2.94s/it]
                                                           

  0%|          | 1488/569592 [1:11:17<463:12:22,  2.94s/it]
  0%|          | 1489/569592 [1:11:18<369:24:35,  2.34s/it]
                                                           

  0%|          | 1489/569592 [1:11:18<369:24:35,  2.34s/it]
  0%|          | 1490/569592 [1:11:19<304:31:07,  1.93s/it]
                                                           

  0%|          | 1490/569592 [1:11:19<304:31:07,  1.93s/it]
  0%|          | 1491/569592 [1:11:22<376:10:41,  2.38s/it]
                                                           

  0%|          | 1491/569592 [1:11:22<376:10:41,  2.38s/it]
  0%|          | 1492/569592 [1:11:27<500:39:12,  3.17s/it]
                                                           

  0%|          | 1492/569592 [1:11:27<500:39:12,  3.17s/it]
  0%|          | 1493/569592 [1:11:32<599:31:20,  3.80s/it]
                                                           

  0%|          | 1493/569592 [1:11:32<599:31:20,  3.80s/it]
  0%|          | 1494/569592 [1:11:38<676:39:26,  4.29s/it]
                                                           

  0%|          | 1494/569592 [1:11:38<676:39:26,  4.29s/it]
  0%|          | 1495/569592 [1:11:41<627:15:25,  3.97s/it]
                                                           

  0%|          | 1495/569592 [1:11:41<627:15:25,  3.97s/it]
  0%|          | 1496/569592 [1:11:42<480:22:03,  3.04s/it]
                                                           

  0%|          | 1496/569592 [1:11:42<480:22:03,  3.04s/it]
  0%|          | 1497/569592 [1:11:46<514:08:41,  3.26s/it]
                                                           

  0%|          | 1497/569592 [1:11:46<514:08:41,  3.26s/it]
  0%|          | 1498/569592 [1:11:51<596:20:48,  3.78s/it]
                                                           

  0%|          | 1498/569592 [1:11:51<596:20:48,  3.78s/it]
  0%|          | 1499/569592 [1:11:55<639:04:37,  4.05s/it]
                                                           

  0%|          | 1499/569592 [1:11:55<639:04:37,  4.05s/it]
  0%|          | 1500/569592 [1:11:58<596:01:58,  3.78s/it]
                                                           

  0%|          | 1500/569592 [1:11:58<596:01:58,  3.78s/it]
  0%|          | 1501/569592 [1:12:03<643:10:30,  4.08s/it]
                                                           

  0%|          | 1501/569592 [1:12:03<643:10:30,  4.08s/it]
  0%|          | 1502/569592 [1:12:08<673:22:44,  4.27s/it]
                                                           

  0%|          | 1502/569592 [1:12:08<673:22:44,  4.27s/it]
  0%|          | 1503/569592 [1:12:11<618:53:11,  3.92s/it]
                                                           

  0%|          | 1503/569592 [1:12:11<618:53:11,  3.92s/it]
  0%|          | 1504/569592 [1:12:17<701:37:31,  4.45s/it]
                                                           

  0%|          | 1504/569592 [1:12:17<701:37:31,  4.45s/it]
  0%|          | 1505/569592 [1:12:21<705:15:48,  4.47s/it]
                                                           

  0%|          | 1505/569592 [1:12:21<705:15:48,  4.47s/it]
  0%|          | 1506/569592 [1:12:26<706:48:10,  4.48s/it]
                                                           

  0%|          | 1506/569592 [1:12:26<706:48:10,  4.48s/it]
  0%|          | 1507/569592 [1:12:29<651:15:34,  4.13s/it]
                                                           

  0%|          | 1507/569592 [1:12:29<651:15:34,  4.13s/it]
  0%|          | 1508/569592 [1:12:35<759:23:26,  4.81s/it]
                                                           

  0%|          | 1508/569592 [1:12:35<759:23:26,  4.81s/it]
  0%|          | 1509/569592 [1:12:39<687:49:20,  4.36s/it]
                                                           

  0%|          | 1509/569592 [1:12:39<687:49:20,  4.36s/it]
  0%|          | 1510/569592 [1:12:43<702:28:34,  4.45s/it]
                                                           

  0%|          | 1510/569592 [1:12:43<702:28:34,  4.45s/it]
  0%|          | 1511/569592 [1:12:47<663:32:36,  4.20s/it]
                                                           

  0%|          | 1511/569592 [1:12:47<663:32:36,  4.20s/it]
  0%|          | 1512/569592 [1:12:51<667:04:40,  4.23s/it]
                                                           

  0%|          | 1512/569592 [1:12:51<667:04:40,  4.23s/it]
  0%|          | 1513/569592 [1:12:55<649:55:11,  4.12s/it]
                                                           

  0%|          | 1513/569592 [1:12:55<649:55:11,  4.12s/it]
  0%|          | 1514/569592 [1:12:59<617:17:44,  3.91s/it]
                                                           

  0%|          | 1514/569592 [1:12:59<617:17:44,  3.91s/it]
  0%|          | 1515/569592 [1:13:03<647:54:31,  4.11s/it]
                                                           

  0%|          | 1515/569592 [1:13:03<647:54:31,  4.11s/it]
  0%|          | 1516/569592 [1:13:08<698:55:10,  4.43s/it]
                                                           

  0%|          | 1516/569592 [1:13:08<698:55:10,  4.43s/it]
  0%|          | 1517/569592 [1:13:09<530:29:39,  3.36s/it]
                                                           

  0%|          | 1517/569592 [1:13:09<530:29:39,  3.36s/it]
  0%|          | 1518/569592 [1:13:14<582:25:32,  3.69s/it]
                                                           

  0%|          | 1518/569592 [1:13:14<582:25:32,  3.69s/it]
  0%|          | 1519/569592 [1:13:17<589:11:55,  3.73s/it]
                                                           

  0%|          | 1519/569592 [1:13:18<589:11:55,  3.73s/it]
  0%|          | 1520/569592 [1:13:22<613:41:08,  3.89s/it]
                                                           

  0%|          | 1520/569592 [1:13:22<613:41:08,  3.89s/it]
  0%|          | 1521/569592 [1:13:25<593:32:59,  3.76s/it]
                                                           

  0%|          | 1521/569592 [1:13:25<593:32:59,  3.76s/it]
  0%|          | 1522/569592 [1:13:29<608:51:56,  3.86s/it]
                                                           

  0%|          | 1522/569592 [1:13:29<608:51:56,  3.86s/it]
  0%|          | 1523/569592 [1:13:32<568:07:34,  3.60s/it]
                                                           

  0%|          | 1523/569592 [1:13:32<568:07:34,  3.60s/it]
  0%|          | 1524/569592 [1:13:37<625:07:56,  3.96s/it]
                                                           

  0%|          | 1524/569592 [1:13:37<625:07:56,  3.96s/it]
  0%|          | 1525/569592 [1:13:38<479:37:11,  3.04s/it]
                                                           

  0%|          | 1525/569592 [1:13:38<479:37:11,  3.04s/it]
  0%|          | 1526/569592 [1:13:39<379:20:25,  2.40s/it]
                                                           

  0%|          | 1526/569592 [1:13:39<379:20:25,  2.40s/it]
  0%|          | 1527/569592 [1:13:44<502:08:46,  3.18s/it]
                                                           

  0%|          | 1527/569592 [1:13:44<502:08:46,  3.18s/it]
  0%|          | 1528/569592 [1:13:47<507:20:35,  3.22s/it]
                                                           

  0%|          | 1528/569592 [1:13:47<507:20:35,  3.22s/it]
  0%|          | 1529/569592 [1:13:50<497:15:26,  3.15s/it]
                                                           

  0%|          | 1529/569592 [1:13:50<497:15:26,  3.15s/it]
  0%|          | 1530/569592 [1:13:51<391:15:56,  2.48s/it]
                                                           

  0%|          | 1530/569592 [1:13:51<391:15:56,  2.48s/it]
  0%|          | 1531/569592 [1:13:52<319:10:42,  2.02s/it]
   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                        

  0%|          | 1531/569592 [1:13:52<319:10:42,  2.02s/it]
  0%|          | 1532/569592 [1:13:53<267:42:36,  1.70s/it]
                                                           

  0%|          | 1532/569592 [1:13:53<267:42:36,  1.70s/it]
  0%|          | 1533/569592 [1:13:54<232:18:05,  1.47s/it]
                                                           

  0%|          | 1533/569592 [1:13:54<232:18:05,  1.47s/it]
  0%|          | 1534/569592 [1:13:55<206:38:55,  1.31s/it]
                                                           

  0%|          | 1534/569592 [1:13:55<206:38:55,  1.31s/it]
  0%|          | 1535/569592 [1:13:56<188:44:46,  1.20s/it]
                                                           

  0%|          | 1535/569592 [1:13:56<188:44:46,  1.20s/it]
  0%|          | 1536/569592 [1:13:57<178:55:34,  1.13s/it]
                                                           

  0%|          | 1536/569592 [1:13:57<178:55:34,  1.13s/it]
  0%|          | 1537/569592 [1:14:00<288:18:01,  1.83s/it]
                                                           

  0%|          | 1537/569592 [1:14:00<288:18:01,  1.83s/it]
  0%|          | 1538/569592 [1:14:04<389:13:56,  2.47s/it]
                                                           

  0%|          | 1538/569592 [1:14:04<389:13:56,  2.47s/it]
  0%|          | 1539/569592 [1:14:05<318:55:29,  2.02s/it]
                                                           

  0%|          | 1539/569592 [1:14:05<318:55:29,  2.02s/it]
  0%|          | 1540/569592 [1:14:07<322:40:53,  2.04s/it]
                                                           

  0%|          | 1540/569592 [1:14:07<322:40:53,  2.04s/it]
  0%|          | 1541/569592 [1:14:10<368:43:05,  2.34s/it]
                                                           

  0%|          | 1541/569592 [1:14:10<368:43:05,  2.34s/it]
  0%|          | 1542/569592 [1:14:14<427:33:26,  2.71s/it]
                                                           

  0%|          | 1542/569592 [1:14:14<427:33:26,  2.71s/it]
  0%|          | 1543/569592 [1:14:15<348:33:03,  2.21s/it]
                                                           

  0%|          | 1543/569592 [1:14:15<348:33:03,  2.21s/it]
  0%|          | 1544/569592 [1:14:18<398:37:37,  2.53s/it]
                                                           

  0%|          | 1544/569592 [1:14:18<398:37:37,  2.53s/it]
  0%|          | 1545/569592 [1:14:20<367:24:45,  2.33s/it]
                                                           

  0%|          | 1545/569592 [1:14:20<367:24:45,  2.33s/it]
  0%|          | 1546/569592 [1:14:25<473:44:56,  3.00s/it]
                                                           

  0%|          | 1546/569592 [1:14:25<473:44:56,  3.00s/it]
  0%|          | 1547/569592 [1:14:26<379:18:40,  2.40s/it]
                                                           

  0%|          | 1547/569592 [1:14:26<379:18:40,  2.40s/it]
  0%|          | 1548/569592 [1:14:27<335:07:48,  2.12s/it]
                                                           

  0%|          | 1548/569592 [1:14:27<335:07:48,  2.12s/it]
  0%|          | 1549/569592 [1:14:30<393:22:44,  2.49s/it]
                                                           

  0%|          | 1549/569592 [1:14:30<393:22:44,  2.49s/it]
  0%|          | 1550/569592 [1:14:36<551:38:40,  3.50s/it]
                                                           

  0%|          | 1550/569592 [1:14:36<551:38:40,  3.50s/it]
  0%|          | 1551/569592 [1:14:37<431:13:44,  2.73s/it]
                                                           

  0%|          | 1551/569592 [1:14:37<431:13:44,  2.73s/it]
  0%|          | 1552/569592 [1:14:38<347:28:30,  2.20s/it]
                                                           

  0%|          | 1552/569592 [1:14:38<347:28:30,  2.20s/it]
  0%|          | 1553/569592 [1:14:40<340:51:32,  2.16s/it]
                                                           

  0%|          | 1553/569592 [1:14:40<340:51:32,  2.16s/it]
  0%|          | 1554/569592 [1:14:45<473:09:00,  3.00s/it]
                                                           

  0%|          | 1554/569592 [1:14:45<473:09:00,  3.00s/it]
  0%|          | 1555/569592 [1:14:46<376:40:40,  2.39s/it]
                                                           

  0%|          | 1555/569592 [1:14:46<376:40:40,  2.39s/it]
  0%|          | 1556/569592 [1:14:49<396:46:03,  2.51s/it]
                                                           

  0%|          | 1556/569592 [1:14:49<396:46:03,  2.51s/it]
  0%|          | 1557/569592 [1:14:51<351:48:46,  2.23s/it]
                                                           

  0%|          | 1557/569592 [1:14:51<351:48:46,  2.23s/it]
  0%|          | 1558/569592 [1:14:55<446:05:47,  2.83s/it]
                                                           

  0%|          | 1558/569592 [1:14:55<446:05:47,  2.83s/it]
  0%|          | 1559/569592 [1:14:56<357:32:17,  2.27s/it]
                                                           

  0%|          | 1559/569592 [1:14:56<357:32:17,  2.27s/it]
  0%|          | 1560/569592 [1:14:59<418:01:56,  2.65s/it]
                                                           

  0%|          | 1560/569592 [1:14:59<418:01:56,  2.65s/it]
  0%|          | 1561/569592 [1:15:01<363:25:27,  2.30s/it]
                                                           

  0%|          | 1561/569592 [1:15:01<363:25:27,  2.30s/it]
  0%|          | 1562/569592 [1:15:06<521:25:39,  3.30s/it]
                                                           

  0%|          | 1562/569592 [1:15:06<521:25:39,  3.30s/it]
  0%|          | 1563/569592 [1:15:07<410:22:49,  2.60s/it]
                                                           

  0%|          | 1563/569592 [1:15:07<410:22:49,  2.60s/it]
  0%|          | 1564/569592 [1:15:09<386:29:01,  2.45s/it]
                                                           

  0%|          | 1564/569592 [1:15:10<386:29:01,  2.45s/it]
  0%|          | 1565/569592 [1:15:12<383:44:21,  2.43s/it]
                                                           

  0%|          | 1565/569592 [1:15:12<383:44:21,  2.43s/it]
  0%|          | 1566/569592 [1:15:17<492:44:30,  3.12s/it]
                                                           

  0%|          | 1566/569592 [1:15:17<492:44:30,  3.12s/it]
  0%|          | 1567/569592 [1:15:18<388:58:47,  2.47s/it]
                                                           

  0%|          | 1567/569592 [1:15:18<388:58:47,  2.47s/it]
  0%|          | 1568/569592 [1:15:20<368:05:51,  2.33s/it]
                                                           

  0%|          | 1568/569592 [1:15:20<368:05:51,  2.33s/it]
  0%|          | 1569/569592 [1:15:21<328:44:10,  2.08s/it]
                                                           

  0%|          | 1569/569592 [1:15:21<328:44:10,  2.08s/it]
  0%|          | 1570/569592 [1:15:27<503:07:00,  3.19s/it]
                                                           

  0%|          | 1570/569592 [1:15:27<503:07:00,  3.19s/it]
  0%|          | 1571/569592 [1:15:28<396:58:50,  2.52s/it]
                                                           

  0%|          | 1571/569592 [1:15:28<396:58:50,  2.52s/it]
  0%|          | 1572/569592 [1:15:30<371:00:22,  2.35s/it]
                                                           

  0%|          | 1572/569592 [1:15:30<371:00:22,  2.35s/it]
  0%|          | 1573/569592 [1:15:31<319:52:15,  2.03s/it]
                                                           

  0%|          | 1573/569592 [1:15:31<319:52:15,  2.03s/it]
  0%|          | 1574/569592 [1:15:38<531:44:13,  3.37s/it]
                                                           

  0%|          | 1574/569592 [1:15:38<531:44:13,  3.37s/it]
  0%|          | 1575/569592 [1:15:38<417:38:50,  2.65s/it]
                                                           

  0%|          | 1575/569592 [1:15:39<417:38:50,  2.65s/it]
  0%|          | 1576/569592 [1:15:41<398:07:51,  2.52s/it]
                                                           

  0%|          | 1576/569592 [1:15:41<398:07:51,  2.52s/it]
  0%|          | 1577/569592 [1:15:42<325:53:14,  2.07s/it]
                                                           

  0%|          | 1577/569592 [1:15:42<325:53:14,  2.07s/it]
  0%|          | 1578/569592 [1:15:47<464:06:38,  2.94s/it]
                                                           

  0%|          | 1578/569592 [1:15:47<464:06:38,  2.94s/it]
  0%|          | 1579/569592 [1:15:48<372:57:35,  2.36s/it]
                                                           

  0%|          | 1579/569592 [1:15:48<372:57:35,  2.36s/it]
  0%|          | 1580/569592 [1:15:52<457:51:30,  2.90s/it]
                                                           

  0%|          | 1580/569592 [1:15:52<457:51:30,  2.90s/it]
  0%|          | 1581/569592 [1:15:53<366:13:37,  2.32s/it]
                                                           

  0%|          | 1581/569592 [1:15:53<366:13:37,  2.32s/it]
  0%|          | 1582/569592 [1:15:59<539:31:50,  3.42s/it]
                                                           

  0%|          | 1582/569592 [1:15:59<539:31:50,  3.42s/it]
  0%|          | 1583/569592 [1:16:00<425:28:08,  2.70s/it]
                                                           

  0%|          | 1583/569592 [1:16:00<425:28:08,  2.70s/it]
  0%|          | 1584/569592 [1:16:01<348:04:07,  2.21s/it]
                                                           

  0%|          | 1584/569592 [1:16:01<348:04:07,  2.21s/it]
  0%|          | 1585/569592 [1:16:03<349:20:33,  2.21s/it]
                                                           

  0%|          | 1585/569592 [1:16:03<349:20:33,  2.21s/it]
  0%|          | 1586/569592 [1:16:09<521:07:30,  3.30s/it]
                                                           

  0%|          | 1586/569592 [1:16:09<521:07:30,  3.30s/it]
  0%|          | 1587/569592 [1:16:10<425:40:37,  2.70s/it]
                                                           

  0%|          | 1587/569592 [1:16:10<425:40:37,  2.70s/it]
  0%|          | 1588/569592 [1:16:11<343:50:15,  2.18s/it]
                                                           

  0%|          | 1588/569592 [1:16:11<343:50:15,  2.18s/it]
  0%|          | 1589/569592 [1:16:13<318:11:37,  2.02s/it]
                                                           

  0%|          | 1589/569592 [1:16:13<318:11:37,  2.02s/it]
  0%|          | 1590/569592 [1:16:18<487:44:49,  3.09s/it]
                                                           

  0%|          | 1590/569592 [1:16:18<487:44:49,  3.09s/it]
  0%|          | 1591/569592 [1:16:19<388:23:50,  2.46s/it]
                                                           

  0%|          | 1591/569592 [1:16:19<388:23:50,  2.46s/it]
  0%|          | 1592/569592 [1:16:23<455:10:22,  2.88s/it]
                                                           

  0%|          | 1592/569592 [1:16:23<455:10:22,  2.88s/it]
  0%|          | 1593/569592 [1:16:24<363:59:42,  2.31s/it]
                                                           

  0%|          | 1593/569592 [1:16:24<363:59:42,  2.31s/it]
  0%|          | 1594/569592 [1:16:29<472:10:57,  2.99s/it]
                                                           

  0%|          | 1594/569592 [1:16:29<472:10:57,  2.99s/it]
  0%|          | 1595/569592 [1:16:30<376:58:51,  2.39s/it]
                                                           

  0%|          | 1595/569592 [1:16:30<376:58:51,  2.39s/it]
  0%|          | 1596/569592 [1:16:34<449:40:42,  2.85s/it]
                                                           

  0%|          | 1596/569592 [1:16:34<449:40:42,  2.85s/it]
  0%|          | 1597/569592 [1:16:37<470:48:38,  2.98s/it]
                                                           

  0%|          | 1597/569592 [1:16:37<470:48:38,  2.98s/it]
  0%|          | 1598/569592 [1:16:39<419:47:46,  2.66s/it]
                                                           

  0%|          | 1598/569592 [1:16:39<419:47:46,  2.66s/it]
  0%|          | 1599/569592 [1:16:40<337:50:09,  2.14s/it]
                                                           

  0%|          | 1599/569592 [1:16:40<337:50:09,  2.14s/it]
  0%|          | 1600/569592 [1:16:43<360:40:46,  2.29s/it]
                                                           

  0%|          | 1600/569592 [1:16:43<360:40:46,  2.29s/it]
  0%|          | 1601/569592 [1:16:46<420:24:18,  2.66s/it]
                                                           

  0%|          | 1601/569592 [1:16:46<420:24:18,  2.66s/it]
  0%|          | 1602/569592 [1:16:51<535:27:16,  3.39s/it]
                                                           

  0%|          | 1602/569592 [1:16:51<535:27:16,  3.39s/it]
  0%|          | 1603/569592 [1:16:54<517:46:26,  3.28s/it]
                                                           

  0%|          | 1603/569592 [1:16:54<517:46:26,  3.28s/it]
  0%|          | 1604/569592 [1:16:59<591:23:08,  3.75s/it]
                                                           

  0%|          | 1604/569592 [1:16:59<591:23:08,  3.75s/it]
  0%|          | 1605/569592 [1:17:03<613:41:14,  3.89s/it]
                                                           

  0%|          | 1605/569592 [1:17:03<613:41:14,  3.89s/it]
  0%|          | 1606/569592 [1:17:04<471:27:11,  2.99s/it]
                                                           

  0%|          | 1606/569592 [1:17:04<471:27:11,  2.99s/it]
  0%|          | 1607/569592 [1:17:09<558:08:42,  3.54s/it]
                                                           

  0%|          | 1607/569592 [1:17:09<558:08:42,  3.54s/it]
  0%|          | 1608/569592 [1:17:12<545:58:57,  3.46s/it]
                                                           

  0%|          | 1608/569592 [1:17:12<545:58:57,  3.46s/it]
  0%|          | 1609/569592 [1:17:13<428:07:07,  2.71s/it]
                                                           

  0%|          | 1609/569592 [1:17:13<428:07:07,  2.71s/it]
  0%|          | 1610/569592 [1:17:16<453:59:18,  2.88s/it]
                                                           

  0%|          | 1610/569592 [1:17:16<453:59:18,  2.88s/it]
  0%|          | 1611/569592 [1:17:20<469:29:48,  2.98s/it]
                                                           

  0%|          | 1611/569592 [1:17:20<469:29:48,  2.98s/it]
  0%|          | 1612/569592 [1:17:25<583:17:36,  3.70s/it]
                                                           

  0%|          | 1612/569592 [1:17:25<583:17:36,  3.70s/it]
  0%|          | 1613/569592 [1:17:30<650:07:55,  4.12s/it]
                                                           

  0%|          | 1613/569592 [1:17:30<650:07:55,  4.12s/it]
  0%|          | 1614/569592 [1:17:34<616:18:27,  3.91s/it]
                                                           

  0%|          | 1614/569592 [1:17:34<616:18:27,  3.91s/it]
  0%|          | 1615/569592 [1:17:38<655:16:50,  4.15s/it]
                                                           

  0%|          | 1615/569592 [1:17:38<655:16:50,  4.15s/it]
  0%|          | 1616/569592 [1:17:43<665:37:40,  4.22s/it]
                                                           

  0%|          | 1616/569592 [1:17:43<665:37:40,  4.22s/it]
  0%|          | 1617/569592 [1:17:48<711:58:00,  4.51s/it]
                                                           

  0%|          | 1617/569592 [1:17:48<711:58:00,  4.51s/it]
  0%|          | 1618/569592 [1:17:52<714:17:27,  4.53s/it]
                                                           

  0%|          | 1618/569592 [1:17:52<714:17:27,  4.53s/it]
  0%|          | 1619/569592 [1:17:57<726:42:50,  4.61s/it]
                                                           

  0%|          | 1619/569592 [1:17:57<726:42:50,  4.61s/it]
  0%|          | 1620/569592 [1:18:02<736:14:41,  4.67s/it]
                                                           

  0%|          | 1620/569592 [1:18:02<736:14:41,  4.67s/it]
  0%|          | 1621/569592 [1:18:06<720:21:56,  4.57s/it]
                                                           

  0%|          | 1621/569592 [1:18:06<720:21:56,  4.57s/it]
  0%|          | 1622/569592 [1:18:11<736:47:38,  4.67s/it]
                                                           

  0%|          | 1622/569592 [1:18:11<736:47:38,  4.67s/it]
  0%|          | 1623/569592 [1:18:14<659:47:38,  4.18s/it]
                                                           

  0%|          | 1623/569592 [1:18:14<659:47:38,  4.18s/it]
  0%|          | 1624/569592 [1:18:17<608:51:31,  3.86s/it]
                                                           

  0%|          | 1624/569592 [1:18:17<608:51:31,  3.86s/it]
  0%|          | 1625/569592 [1:18:22<655:22:08,  4.15s/it]
                                                           

  0%|          | 1625/569592 [1:18:22<655:22:08,  4.15s/it]
  0%|          | 1626/569592 [1:18:27<668:52:33,  4.24s/it]
                                                           

  0%|          | 1626/569592 [1:18:27<668:52:33,  4.24s/it]
  0%|          | 1627/569592 [1:18:31<690:24:23,  4.38s/it]
                                                           

  0%|          | 1627/569592 [1:18:31<690:24:23,  4.38s/it]
  0%|          | 1628/569592 [1:18:35<670:35:28,  4.25s/it]
                                                           

  0%|          | 1628/569592 [1:18:35<670:35:28,  4.25s/it]
  0%|          | 1629/569592 [1:18:40<693:19:20,  4.39s/it]
                                                           

  0%|          | 1629/569592 [1:18:40<693:19:20,  4.39s/it]
  0%|          | 1630/569592 [1:18:45<704:17:54,  4.46s/it]
                                                           

  0%|          | 1630/569592 [1:18:45<704:17:54,  4.46s/it]
  0%|          | 1631/569592 [1:18:50<726:10:31,  4.60s/it]
                                                           

  0%|          | 1631/569592 [1:18:50<726:10:31,  4.60s/it]
  0%|          | 1632/569592 [1:18:54<728:28:05,  4.62s/it]
                                                           

  0%|          | 1632/569592 [1:18:54<728:28:05,  4.62s/it]
  0%|          | 1633/569592 [1:18:59<741:15:13,  4.70s/it]
                                                           

  0%|          | 1633/569592 [1:18:59<741:15:13,  4.70s/it]
  0%|          | 1634/569592 [1:19:03<675:53:53,  4.28s/it]
                                                           

  0%|          | 1634/569592 [1:19:03<675:53:53,  4.28s/it]
  0%|          | 1635/569592 [1:19:06<629:42:41,  3.99s/it]
                                                           

  0%|          | 1635/569592 [1:19:06<629:42:41,  3.99s/it]
  0%|          | 1636/569592 [1:19:11<668:03:12,  4.23s/it]
                                                           

  0%|          | 1636/569592 [1:19:11<668:03:12,  4.23s/it]
  0%|          | 1637/569592 [1:19:15<688:57:53,  4.37s/it]
                                                           

  0%|          | 1637/569592 [1:19:15<688:57:53,  4.37s/it]
  0%|          | 1638/569592 [1:19:20<702:41:46,  4.45s/it]
                                                           

  0%|          | 1638/569592 [1:19:20<702:41:46,  4.45s/it]
  0%|          | 1639/569592 [1:19:21<533:45:33,  3.38s/it]
                                                           

  0%|          | 1639/569592 [1:19:21<533:45:33,  3.38s/it]
  0%|          | 1640/569592 [1:19:26<608:22:31,  3.86s/it]
                                                           

  0%|          | 1640/569592 [1:19:26<608:22:31,  3.86s/it]
  0%|          | 1641/569592 [1:19:30<648:23:09,  4.11s/it]
                                                           

  0%|          | 1641/569592 [1:19:31<648:23:09,  4.11s/it]
  0%|          | 1642/569592 [1:19:33<592:50:28,  3.76s/it]
                                                           

  0%|          | 1642/569592 [1:19:33<592:50:28,  3.76s/it]
  0%|          | 1643/569592 [1:19:34<457:21:57,  2.90s/it]
                                                           

  0%|          | 1643/569592 [1:19:34<457:21:57,  2.90s/it]
  0%|          | 1644/569592 [1:19:39<546:55:24,  3.47s/it]
                                                           

  0%|          | 1644/569592 [1:19:39<546:55:24,  3.47s/it]
  0%|          | 1645/569592 [1:19:40<425:59:03,  2.70s/it]
                                                           

  0%|          | 1645/569592 [1:19:40<425:59:03,  2.70s/it]
  0%|          | 1646/569592 [1:19:43<457:54:02,  2.90s/it]
                                                           

  0%|          | 1646/569592 [1:19:43<457:54:02,  2.90s/it]
  0%|          | 1647/569592 [1:19:44<364:04:23,  2.31s/it]
                                                           

  0%|          | 1647/569592 [1:19:44<364:04:23,  2.31s/it]
  0%|          | 1648/569592 [1:19:45<299:13:56,  1.90s/it]
                                                           

  0%|          | 1648/569592 [1:19:45<299:13:56,  1.90s/it]
  0%|          | 1649/569592 [1:19:46<254:49:15,  1.62s/it]
                                                           

  0%|          | 1649/569592 [1:19:46<254:49:15,  1.62s/it]
  0%|          | 1650/569592 [1:19:47<222:04:03,  1.41s/it]
                                                           

  0%|          | 1650/569592 [1:19:47<222:04:03,  1.41s/it]
  0%|          | 1651/569592 [1:19:48<201:53:08,  1.28s/it]
                                                           

  0%|          | 1651/569592 [1:19:48<201:53:08,  1.28s/it]
  0%|          | 1652/569592 [1:19:49<185:02:26,  1.17s/it]
                                                           

  0%|          | 1652/569592 [1:19:49<185:02:26,  1.17s/it]
  0%|          | 1653/569592 [1:19:52<274:46:55,  1.74s/it]
                                                           

  0%|          | 1653/569592 [1:19:52<274:46:55,  1.74s/it]
  0%|          | 1654/569592 [1:19:54<278:13:15,  1.76s/it]
                                                           

  0%|          | 1654/569592 [1:19:54<278:13:15,  1.76s/it]
  0%|          | 1655/569592 [1:19:57<358:00:06,  2.27s/it]
                                                           

  0%|          | 1655/569592 [1:19:57<358:00:06,  2.27s/it]
  0%|          | 1656/569592 [1:19:58<299:15:15,  1.90s/it]
                                                           

  0%|          | 1656/569592 [1:19:58<299:15:15,  1.90s/it]
  0%|          | 1657/569592 [1:20:03<406:46:41,  2.58s/it]
                                                           

  0%|          | 1657/569592 [1:20:03<406:46:41,  2.58s/it]
  0%|          | 1658/569592 [1:20:04<366:42:33,  2.32s/it]
                                                           

  0%|          | 1658/569592 [1:20:04<366:42:33,  2.32s/it]
  0%|          | 1659/569592 [1:20:07<379:57:09,  2.41s/it]
                                                           

  0%|          | 1659/569592 [1:20:07<379:57:09,  2.41s/it]
  0%|          | 1660/569592 [1:20:08<312:34:23,  1.98s/it]
                                                           

  0%|          | 1660/569592 [1:20:08<312:34:23,  1.98s/it]
  0%|          | 1661/569592 [1:20:12<427:57:51,  2.71s/it]
                                                           

  0%|          | 1661/569592 [1:20:12<427:57:51,  2.71s/it]
  0%|          | 1662/569592 [1:20:15<408:47:15,  2.59s/it]
                                                           

  0%|          | 1662/569592 [1:20:15<408:47:15,  2.59s/it]
  0%|          | 1663/569592 [1:20:16<367:12:02,  2.33s/it]
                                                           

  0%|          | 1663/569592 [1:20:16<367:12:02,  2.33s/it]
  0%|          | 1664/569592 [1:20:18<336:21:12,  2.13s/it]
                                                           

  0%|          | 1664/569592 [1:20:18<336:21:12,  2.13s/it]
  0%|          | 1665/569592 [1:20:24<524:06:35,  3.32s/it]
                                                           

  0%|          | 1665/569592 [1:20:24<524:06:35,  3.32s/it]
  0%|          | 1666/569592 [1:20:26<458:44:58,  2.91s/it]
                                                           

  0%|          | 1666/569592 [1:20:26<458:44:58,  2.91s/it]
  0%|          | 1667/569592 [1:20:27<367:41:52,  2.33s/it]
                                                           

  0%|          | 1667/569592 [1:20:27<367:41:52,  2.33s/it]
  0%|          | 1668/569592 [1:20:28<308:05:29,  1.95s/it]
                                                           

  0%|          | 1668/569592 [1:20:28<308:05:29,  1.95s/it]
  0%|          | 1669/569592 [1:20:34<483:42:30,  3.07s/it]
                                                           

  0%|          | 1669/569592 [1:20:34<483:42:30,  3.07s/it]
  0%|          | 1670/569592 [1:20:36<445:53:21,  2.83s/it]
                                                           

  0%|          | 1670/569592 [1:20:36<445:53:21,  2.83s/it]
  0%|          | 1671/569592 [1:20:37<378:07:51,  2.40s/it]
                                                           

  0%|          | 1671/569592 [1:20:37<378:07:51,  2.40s/it]
  0%|          | 1672/569592 [1:20:39<360:57:41,  2.29s/it]
                                                           

  0%|          | 1672/569592 [1:20:39<360:57:41,  2.29s/it]
  0%|          | 1673/569592 [1:20:43<422:01:16,  2.68s/it]
                                                           

  0%|          | 1673/569592 [1:20:43<422:01:16,  2.68s/it]
  0%|          | 1674/569592 [1:20:46<437:20:33,  2.77s/it]
                                                           

  0%|          | 1674/569592 [1:20:46<437:20:33,  2.77s/it]
  0%|          | 1675/569592 [1:20:49<425:11:37,  2.70s/it]
                                                           

  0%|          | 1675/569592 [1:20:49<425:11:37,  2.70s/it]
  0%|          | 1676/569592 [1:20:49<341:48:54,  2.17s/it]
                                                           

  0%|          | 1676/569592 [1:20:50<341:48:54,  2.17s/it]
  0%|          | 1677/569592 [1:20:54<448:47:43,  2.84s/it]
                                                           

  0%|          | 1677/569592 [1:20:54<448:47:43,  2.84s/it]
  0%|          | 1678/569592 [1:20:56<408:15:00,  2.59s/it]
                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                       

  0%|          | 1678/569592 [1:20:56<408:15:00,  2.59s/it]
  0%|          | 1679/569592 [1:20:58<401:40:11,  2.55s/it]
                                                           

  0%|          | 1679/569592 [1:20:58<401:40:11,  2.55s/it]
  0%|          | 1680/569592 [1:20:59<333:43:16,  2.12s/it]
                                                           

  0%|          | 1680/569592 [1:20:59<333:43:16,  2.12s/it]
  0%|          | 1681/569592 [1:21:04<459:33:10,  2.91s/it]
                                                           

  0%|          | 1681/569592 [1:21:04<459:33:10,  2.91s/it]
  0%|          | 1682/569592 [1:21:06<389:44:50,  2.47s/it]
                                                           

  0%|          | 1682/569592 [1:21:06<389:44:50,  2.47s/it]
  0%|          | 1683/569592 [1:21:09<433:48:41,  2.75s/it]
                                                           

  0%|          | 1683/569592 [1:21:09<433:48:41,  2.75s/it]
  0%|          | 1684/569592 [1:21:10<352:32:40,  2.23s/it]
                                                           

  0%|          | 1684/569592 [1:21:10<352:32:40,  2.23s/it]
  0%|          | 1685/569592 [1:21:14<424:20:24,  2.69s/it]
                                                           

  0%|          | 1685/569592 [1:21:14<424:20:24,  2.69s/it]
  0%|          | 1686/569592 [1:21:16<395:59:50,  2.51s/it]
                                                           

  0%|          | 1686/569592 [1:21:16<395:59:50,  2.51s/it]
  0%|          | 1687/569592 [1:21:20<461:03:41,  2.92s/it]
                                                           

  0%|          | 1687/569592 [1:21:20<461:03:41,  2.92s/it]
  0%|          | 1688/569592 [1:21:21<370:38:01,  2.35s/it]
                                                           

  0%|          | 1688/569592 [1:21:21<370:38:01,  2.35s/it]
  0%|          | 1689/569592 [1:21:23<382:23:55,  2.42s/it]
                                                           

  0%|          | 1689/569592 [1:21:23<382:23:55,  2.42s/it]
  0%|          | 1690/569592 [1:21:27<426:34:32,  2.70s/it]
                                                           

  0%|          | 1690/569592 [1:21:27<426:34:32,  2.70s/it]
  0%|          | 1691/569592 [1:21:30<434:54:58,  2.76s/it]
                                                           

  0%|          | 1691/569592 [1:21:30<434:54:58,  2.76s/it]
  0%|          | 1692/569592 [1:21:31<349:39:06,  2.22s/it]
                                                           

  0%|          | 1692/569592 [1:21:31<349:39:06,  2.22s/it]
  0%|          | 1693/569592 [1:21:33<377:24:53,  2.39s/it]
                                                           

  0%|          | 1693/569592 [1:21:33<377:24:53,  2.39s/it]
  0%|          | 1694/569592 [1:21:38<471:11:24,  2.99s/it]
                                                           

  0%|          | 1694/569592 [1:21:38<471:11:24,  2.99s/it]
  0%|          | 1695/569592 [1:21:39<404:09:02,  2.56s/it]
                                                           

  0%|          | 1695/569592 [1:21:39<404:09:02,  2.56s/it]
  0%|          | 1696/569592 [1:21:40<327:08:54,  2.07s/it]
                                                           

  0%|          | 1696/569592 [1:21:40<327:08:54,  2.07s/it]
  0%|          | 1697/569592 [1:21:44<382:43:54,  2.43s/it]
                                                           

  0%|          | 1697/569592 [1:21:44<382:43:54,  2.43s/it]
  0%|          | 1698/569592 [1:21:48<476:30:23,  3.02s/it]
                                                           

  0%|          | 1698/569592 [1:21:48<476:30:23,  3.02s/it]
  0%|          | 1699/569592 [1:21:49<404:51:56,  2.57s/it]
                                                           

  0%|          | 1699/569592 [1:21:50<404:51:56,  2.57s/it]
  0%|          | 1700/569592 [1:21:51<359:41:30,  2.28s/it]
                                                           

  0%|          | 1700/569592 [1:21:51<359:41:30,  2.28s/it]
  0%|          | 1701/569592 [1:21:53<363:47:56,  2.31s/it]
                                                           

  0%|          | 1701/569592 [1:21:53<363:47:56,  2.31s/it]
  0%|          | 1702/569592 [1:21:58<463:39:44,  2.94s/it]
                                                           

  0%|          | 1702/569592 [1:21:58<463:39:44,  2.94s/it]
  0%|          | 1703/569592 [1:21:59<370:52:01,  2.35s/it]
                                                           

  0%|          | 1703/569592 [1:21:59<370:52:01,  2.35s/it]
  0%|          | 1704/569592 [1:22:01<354:51:17,  2.25s/it]
                                                           

  0%|          | 1704/569592 [1:22:01<354:51:17,  2.25s/it]
  0%|          | 1705/569592 [1:22:04<375:12:24,  2.38s/it]
                                                           

  0%|          | 1705/569592 [1:22:04<375:12:24,  2.38s/it]
  0%|          | 1706/569592 [1:22:08<483:04:20,  3.06s/it]
                                                           

  0%|          | 1706/569592 [1:22:08<483:04:20,  3.06s/it]
  0%|          | 1707/569592 [1:22:09<396:42:01,  2.51s/it]
                                                           

  0%|          | 1707/569592 [1:22:09<396:42:01,  2.51s/it]
  0%|          | 1708/569592 [1:22:11<370:21:57,  2.35s/it]
                                                           

  0%|          | 1708/569592 [1:22:11<370:21:57,  2.35s/it]
  0%|          | 1709/569592 [1:22:14<383:09:05,  2.43s/it]
                                                           

  0%|          | 1709/569592 [1:22:14<383:09:05,  2.43s/it]
  0%|          | 1710/569592 [1:22:17<429:00:34,  2.72s/it]
                                                           

  0%|          | 1710/569592 [1:22:17<429:00:34,  2.72s/it]
  0%|          | 1711/569592 [1:22:20<404:20:39,  2.56s/it]
                                                           

  0%|          | 1711/569592 [1:22:20<404:20:39,  2.56s/it]
  0%|          | 1712/569592 [1:22:22<378:01:39,  2.40s/it]
                                                           

  0%|          | 1712/569592 [1:22:22<378:01:39,  2.40s/it]
  0%|          | 1713/569592 [1:22:24<398:52:24,  2.53s/it]
                                                           

  0%|          | 1713/569592 [1:22:24<398:52:24,  2.53s/it]
  0%|          | 1714/569592 [1:22:29<515:41:13,  3.27s/it]
                                                           

  0%|          | 1714/569592 [1:22:29<515:41:13,  3.27s/it]
  0%|          | 1715/569592 [1:22:30<408:47:27,  2.59s/it]
                                                           

  0%|          | 1715/569592 [1:22:30<408:47:27,  2.59s/it]
  0%|          | 1716/569592 [1:22:34<470:09:14,  2.98s/it]
                                                           

  0%|          | 1716/569592 [1:22:34<470:09:14,  2.98s/it]
  0%|          | 1717/569592 [1:22:35<372:00:32,  2.36s/it]
                                                           

  0%|          | 1717/569592 [1:22:35<372:00:32,  2.36s/it]
  0%|          | 1718/569592 [1:22:40<493:53:19,  3.13s/it]
                                                           

  0%|          | 1718/569592 [1:22:40<493:53:19,  3.13s/it]
  0%|          | 1719/569592 [1:22:43<493:48:41,  3.13s/it]
                                                           

  0%|          | 1719/569592 [1:22:43<493:48:41,  3.13s/it]
  0%|          | 1720/569592 [1:22:47<512:19:53,  3.25s/it]
                                                           

  0%|          | 1720/569592 [1:22:47<512:19:53,  3.25s/it]
  0%|          | 1721/569592 [1:22:50<505:55:48,  3.21s/it]
                                                           

  0%|          | 1721/569592 [1:22:50<505:55:48,  3.21s/it]
  0%|          | 1722/569592 [1:22:54<528:58:00,  3.35s/it]
                                                           

  0%|          | 1722/569592 [1:22:54<528:58:00,  3.35s/it]
  0%|          | 1723/569592 [1:22:55<413:04:10,  2.62s/it]
                                                           

  0%| /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
         | 1723/569592 [1:22:55<413:04:10,  2.62s/it]
  0%|          | 1724/569592 [1:22:58<439:48:06,  2.79s/it]
                                                           

  0%|          | 1724/569592 [1:22:58<439:48:06,  2.79s/it]
  0%|          | 1725/569592 [1:23:03<560:12:42,  3.55s/it]
                                                           

  0%|          | 1725/569592 [1:23:03<560:12:42,  3.55s/it]
  0%|          | 1726/569592 [1:23:06<535:36:13,  3.40s/it]
                                                           

  0%|          | 1726/569592 [1:23:06<535:36:13,  3.40s/it]
  0%|          | 1727/569592 [1:23:07<418:20:08,  2.65s/it]
                                                           

  0%|          | 1727/569592 [1:23:07<418:20:08,  2.65s/it]
  0%|          | 1728/569592 [1:23:12<516:29:23,  3.27s/it]
                                                           

  0%|          | 1728/569592 [1:23:12<516:29:23,  3.27s/it]
  0%|          | 1729/569592 [1:23:16<581:42:50,  3.69s/it]
                                                           

  0%|          | 1729/569592 [1:23:16<581:42:50,  3.69s/it]
  0%|          | 1730/569592 [1:23:20<584:24:54,  3.70s/it]
                                                           

  0%|          | 1730/569592 [1:23:20<584:24:54,  3.70s/it]
  0%|          | 1731/569592 [1:23:25<630:53:54,  4.00s/it]
                                                           

  0%|          | 1731/569592 [1:23:25<630:53:54,  4.00s/it]
  0%|          | 1732/569592 [1:23:30<663:12:48,  4.20s/it]
                                                           

  0%|          | 1732/569592 [1:23:30<663:12:48,  4.20s/it]
  0%|          | 1733/569592 [1:23:34<671:47:08,  4.26s/it]
                                                           

  0%|          | 1733/569592 [1:23:34<671:47:08,  4.26s/it]
  0%|          | 1734/569592 [1:23:39<692:40:59,  4.39s/it]
                                                           

  0%|          | 1734/569592 [1:23:39<692:40:59,  4.39s/it]
  0%|          | 1735/569592 [1:23:43<714:10:59,  4.53s/it]
                                                           

  0%|          | 1735/569592 [1:23:43<714:10:59,  4.53s/it]
  0%|          | 1736/569592 [1:23:48<722:14:35,  4.58s/it]
                                                           

  0%|          | 1736/569592 [1:23:48<722:14:35,  4.58s/it]
  0%|          | 1737/569592 [1:23:53<733:10:05,  4.65s/it]
                                                           

  0%|          | 1737/569592 [1:23:53<733:10:05,  4.65s/it]
  0%|          | 1738/569592 [1:23:58<734:10:41,  4.65s/it]
                                                           

  0%|          | 1738/569592 [1:23:58<734:10:41,  4.65s/it]
  0%|          | 1739/569592 [1:24:02<730:22:48,  4.63s/it]
                                                           

  0%|          | 1739/569592 [1:24:02<730:22:48,  4.63s/it]
  0%|          | 1740/569592 [1:24:07<728:21:34,  4.62s/it]
                                                           

  0%|          | 1740/569592 [1:24:07<728:21:34,  4.62s/it]
  0%|          | 1741/569592 [1:24:10<684:23:48,  4.34s/it]
                                                           

  0%|          | 1741/569592 [1:24:10<684:23:48,  4.34s/it]
  0%|          | 1742/569592 [1:24:15<702:35:10,  4.45s/it]
                                                           

  0%|          | 1742/569592 [1:24:15<702:35:10,  4.45s/it]
  0%|          | 1743/569592 [1:24:20<710:57:19,  4.51s/it]
                                                           

  0%|          | 1743/569592 [1:24:20<710:57:19,  4.51s/it]
  0%|          | 1744/569592 [1:24:24<714:40:19,  4.53s/it]
                                                           

  0%|          | 1744/569592 [1:24:24<714:40:19,  4.53s/it]
  0%|          | 1745/569592 [1:24:28<675:59:27,  4.29s/it]
                                                           

  0%|          | 1745/569592 [1:24:28<675:59:27,  4.29s/it]
  0%|          | 1746/569592 [1:24:31<619:59:29,  3.93s/it]
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                           

  0%|          | 1746/569592 [1:24:31<619:59:29,  3.93s/it]
  0%|          | 1747/569592 [1:24:35<610:25:54,  3.87s/it]
                                                           

  0%|          | 1747/569592 [1:24:35<610:25:54,  3.87s/it]
  0%|          | 1748/569592 [1:24:39<623:54:24,  3.96s/it]
                                                           

  0%|          | 1748/569592 [1:24:39<623:54:24,  3.96s/it]
  0%|          | 1749/569592 [1:24:44<660:20:55,  4.19s/it]
                                                           

  0%|          | 1749/569592 [1:24:44<660:20:55,  4.19s/it]
  0%|          | 1750/569592 [1:24:49<684:34:31,  4.34s/it]
                                                           

  0%|          | 1750/569592 [1:24:49<684:34:31,  4.34s/it]
  0%|          | 1751/569592 [1:24:53<701:51:41,  4.45s/it]
                                                           

  0%|          | 1751/569592 [1:24:53<701:51:41,  4.45s/it]
  0%|          | 1752/569592 [1:24:57<649:27:45,  4.12s/it]
                                                           

  0%|          | 1752/569592 [1:24:57<649:27:45,  4.12s/it]
  0%|          | 1753/569592 [1:24:58<501:46:11,  3.18s/it]
                                                           

  0%|          | 1753/569592 [1:24:58<501:46:11,  3.18s/it]
  0%|          | 1754/569592 [1:24:59<407:47:10,  2.59s/it]
                                                           

  0%|          | 1754/569592 [1:24:59<407:47:10,  2.59s/it]
  0%|          | 1755/569592 [1:25:02<440:15:14,  2.79s/it]
                                                           

  0%|          | 1755/569592 [1:25:02<440:15:14,  2.79s/it]
  0%|          | 1756/569592 [1:25:07<555:44:43,  3.52s/it]
                                                           

  0%|          | 1756/569592 [1:25:07<555:44:43,  3.52s/it]
  0%|          | 1757/569592 [1:25:12<608:09:56,  3.86s/it]
                                                           

  0%|          | 1757/569592 [1:25:12<608:09:56,  3.86s/it]
  0%|          | 1758/569592 [1:25:16<596:42:51,  3.78s/it]
                                                           

  0%|          | 1758/569592 [1:25:16<596:42:51,  3.78s/it]
  0%|          | 1759/569592 [1:25:16<460:42:36,  2.92s/it]
                                                           

  0%|          | 1759/569592 [1:25:16<460:42:36,  2.92s/it]
  0%|          | 1760/569592 [1:25:21<550:58:43,  3.49s/it]
                                                           

  0%|          | 1760/569592 [1:25:21<550:58:43,  3.49s/it]
  0%|          | 1761/569592 [1:25:22<433:12:13,  2.75s/it]
                                                           

  0%|          | 1761/569592 [1:25:22<433:12:13,  2.75s/it]
  0%|          | 1762/569592 [1:25:25<454:00:34,  2.88s/it]
                                                           

  0%|          | 1762/569592 [1:25:25<454:00:34,  2.88s/it]
  0%|          | 1763/569592 [1:25:29<469:39:19,  2.98s/it]
                                                           

  0%|          | 1763/569592 [1:25:29<469:39:19,  2.98s/it]
  0%|          | 1764/569592 [1:25:30<374:30:01,  2.37s/it]
                                                           

  0%|          | 1764/569592 [1:25:30<374:30:01,  2.37s/it]
  0%|          | 1765/569592 [1:25:31<307:30:25,  1.95s/it]
                                                           

  0%|          | 1765/569592 [1:25:31<307:30:25,  1.95s/it]
  0%|          | 1766/569592 [1:25:32<261:04:51,  1.66s/it]
                                                           

  0%|          | 1766/569592 [1:25:32<261:04:51,  1.66s/it]
  0%|          | 1767/569592 [1:25:33<228:23:28,  1.45s/it]
                                                           

  0%|          | 1767/569592 [1:25:33<228:23:28,  1.45s/it]
  0%|          | 1768/569592 [1:25:33<203:52:13,  1.29s/it]
                                                           

  0%|          | 1768/569592 [1:25:33<203:52:13,  1.29s/it]
  0%|          | 1769/569592 [1:25:35<210:43:14,  1.34s/it]
                                                           

  0%|          | 1769/569592 [1:25:35<210:43:14,  1.34s/it]
  0%|          | 1770/569592 [1:25:36<191:40:57,  1.22s/it]
                                                           

  0%|          | 1770/569592 [1:25:36<191:40:57,  1.22s/it]
  0%|          | 1771/569592 [1:25:38<240:23:55,  1.52s/it]
                                                           

  0%|          | 1771/569592 [1:25:38<240:23:55,  1.52s/it]
  0%|          | 1772/569592 [1:25:43<387:29:08,  2.46s/it]
                                                           

  0%|          | 1772/569592 [1:25:43<387:29:08,  2.46s/it]
  0%|          | 1773/569592 [1:25:44<347:33:18,  2.20s/it]
                                                           

  0%|          | 1773/569592 [1:25:44<347:33:18,  2.20s/it]
  0%|          | 1774/569592 [1:25:45<298:03:45,  1.89s/it]
                                                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98917434 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
       

  0%|          | 1774/569592 [1:25:45<298:03:45,  1.89s/it]
  0%|          | 1775/569592 [1:25:49<368:21:14,  2.34s/it]
                                                           

  0%|          | 1775/569592 [1:25:49<368:21:14,  2.34s/it]
  0%|          | 1776/569592 [1:25:52<423:27:22,  2.68s/it]
                                                           

  0%|          | 1776/569592 [1:25:52<423:27:22,  2.68s/it]
  0%|          | 1777/569592 [1:25:55<433:06:47,  2.75s/it]
                                                           

  0%|          | 1777/569592 [1:25:55<433:06:47,  2.75s/it]
  0%|          | 1778/569592 [1:25:56<348:29:47,  2.21s/it]
                                                           

  0%|          | 1778/569592 [1:25:56<348:29:47,  2.21s/it]
  0%|          | 1779/569592 [1:25:59<389:19:05,  2.47s/it]
                                                           

  0%|          | 1779/569592 [1:25:59<389:19:05,  2.47s/it]
  0%|          | 1780/569592 [1:26:02<401:29:03,  2.55s/it]
                                                           

  0%|          | 1780/569592 [1:26:02<401:29:03,  2.55s/it]
  0%|          | 1781/569592 [1:26:06<464:16:32,  2.94s/it]
                                                           

  0%|          | 1781/569592 [1:26:06<464:16:32,  2.94s/it]
  0%|          | 1782/569592 [1:26:07<374:15:51,  2.37s/it]
                                                           

  0%|          | 1782/569592 [1:26:07<374:15:51,  2.37s/it]
  0%|          | 1783/569592 [1:26:09<343:05:36,  2.18s/it]
                                                           

  0%|          | 1783/569592 [1:26:09<343:05:36,  2.18s/it]
  0%|          | 1784/569592 [1:26:13<444:52:37,  2.82s/it]
                                                           

  0%|          | 1784/569592 [1:26:13<444:52:37,  2.82s/it]
  0%|          | 1785/569592 [1:26:15<418:05:54,  2.65s/it]
                                                           

  0%|          | 1785/569592 [1:26:15<418:05:54,  2.65s/it]
  0%|          | 1786/569592 [1:26:16<339:34:22,  2.15s/it]
                                                           

  0%|          | 1786/569592 [1:26:16<339:34:22,  2.15s/it]
  0%|          | 1787/569592 [1:26:19<368:35:37,  2.34s/it]
                                                           

  0%|          | 1787/569592 [1:26:19<368:35:37,  2.34s/it]
  0%|          | 1788/569592 [1:26:23<435:50:35,  2.76s/it]
                                                           

  0%|          | 1788/569592 [1:26:23<435:50:35,  2.76s/it]
  0%|          | 1789/569592 [1:26:26<456:14:00,  2.89s/it]
                                                           

  0%|          | 1789/569592 [1:26:26<456:14:00,  2.89s/it]
  0%|          | 1790/569592 [1:26:27<364:47:18,  2.31s/it]
                                                           

  0%|          | 1790/569592 [1:26:27<364:47:18,  2.31s/it]
  0%|          | 1791/569592 [1:26:30<413:15:09,  2.62s/it]
                                                           

  0%|          | 1791/569592 [1:26:30<413:15:09,  2.62s/it]
  0%|          | 1792/569592 [1:26:33<442:44:22,  2.81s/it]
                                                           

  0%|          | 1792/569592 [1:26:33<442:44:22,  2.81s/it]
  0%|          | 1793/569592 [1:26:36<430:39:16,  2.73s/it]
                                                           

  0%|          | 1793/569592 [1:26:36<430:39:16,  2.73s/it]
  0%|          | 1794/569592 [1:26:37<354:46:41,  2.25s/it]
                                                           

  0%|          | 1794/569592 [1:26:37<354:46:41,  2.25s/it]
  0%|          | 1795/569592 [1:26:40<401:09:15,  2.54s/it]
                                                           

  0%|          | 1795/569592 [1:26:40<401:09:15,  2.54s/it]
  0%|          | 1796/569592 [1:26:44<475:13:50,  3.01s/it]
                                                           

  0%|          | 1796/569592 [1:26:45<475:13:50,  3.01s/it]
  0%|          | 1797/569592 [1:26:46<411:37:09,  2.61s/it]
                                                           

  0%|          | 1797/569592 [1:26:46<411:37:09,  2.61s/it]
  0%|          | 1798/569592 [1:26:47<332:58:59,  2.11s/it]
                                                           

  0%|          | 1798/569592 [1:26:47<332:58:59,  2.11s/it]
  0%|          | 1799/569592 [1:26:50<359:46:01,  2.28s/it]
                                                           

  0%|          | 1799/569592 [1:26:50<359:46:01,  2.28s/it]
  0%|          | 1800/569592 [1:26:54<464:03:16,  2.94s/it]
                                                           

  0%|          | 1800/569592 [1:26:54<464:03:16,  2.94s/it]
  0%|          | 1801/569592 [1:26:58<484:06:02,  3.07s/it]
                                                           

  0%|          | 1801/569592 [1:26:58<484:06:02,  3.07s/it]
  0%|          | 1802/569592 [1:26:59<387:47:46,  2.46s/it]
                                                           

  0%|          | 1802/569592 [1:26:59<387:47:46,  2.46s/it]
  0%|          | 1803/569592 [1:27:00<352:42:40,  2.24s/it]
                                                           

  0%|          | 1803/569592 [1:27:00<352:42:40,  2.24s/it]
  0%|          | 1804/569592 [1:27:06<493:12:03,  3.13s/it]
                                                           

  0%|          | 1804/569592 [1:27:06<493:12:03,  3.13s/it]
  0%|          | 1805/569592 [1:27:07<426:27:58,  2.70s/it]
                                                           

  0%|          | 1805/569592 [1:27:07<426:27:58,  2.70s/it]
  0%|          | 1806/569592 [1:27:08<345:00:34,  2.19s/it]
                                                           

  0%|          | 1806/569592 [1:27:08<345:00:34,  2.19s/it]
  0%|          | 1807/569592 [1:27:10<328:34:30,  2.08s/it]
                                                           

  0%|          | 1807/569592 [1:27:10<328:34:30,  2.08s/it]
  0%|          | 1808/569592 [1:27:16<487:58:44,  3.09s/it]
                                                           

  0%|          | 1808/569592 [1:27:16<487:58:44,  3.09s/it]
  0%|          | 1809/569592 [1:27:17<385:49:01,  2.45s/it]
                                                           

  0%|          | 1809/569592 [1:27:17<385:49:01,  2.45s/it]
  0%|          | 1810/569592 [1:27:18<354:16:31,  2.25s/it]
                                                           

  0%|          | 1810/569592 [1:27:18<354:16:31,  2.25s/it]
  0%|          | 1811/569592 [1:27:20<318:37:47,  2.02s/it]
                                                           

  0%|          | 1811/569592 [1:27:20<318:37:47,  2.02s/it]
  0%|          | 1812/569592 [1:27:25<457:46:27,  2.90s/it]
                                                           

  0%|          | 1812/569592 [1:27:25<457:46:27,  2.90s/it]
  0%|          | 1813/569592 [1:27:27<425:07:09,  2.70s/it]
                                                           

  0%|          | 1813/569592 [1:27:27<425:07:09,  2.70s/it]
  0%|          | 1814/569592 [1:27:28<369:41:13,  2.34s/it]
                                                           

  0%|          | 1814/569592 [1:27:28<369:41:13,  2.34s/it]
  0%|          | 1815/569592 [1:27:30<340:28:30,  2.16s/it]
                                                           

  0%|          | 1815/569592 [1:27:30<340:28:30,  2.16s/it]
  0%|          | 1816/569592 [1:27:35<476:09:38,  3.02s/it]
                                                           

  0%|          | 1816/569592 [1:27:35<476:09:38,  3.02s/it]
  0%|          | 1817/569592 [1:27:38<483:19:37,  3.06s/it]
                                                           

  0%|          | 1817/569592 [1:27:38<483:19:37,  3.06s/it]
  0%|          | 1818/569592 [1:27:39<383:18:25,  2.43s/it]
                                                           

  0%|          | 1818/569592 [1:27:39<383:18:25,  2.43s/it]
  0%|          | 1819/569592 [1:27:40<317:43:40,  2.01s/it]
                                                           

  0%|          | 1819/569592 [1:27:40<317:43:40,  2.01s/it]
  0%|          | 1820/569592 [1:27:48<568:20:32,  3.60s/it]
                                                           

  0%|          | 1820/569592 [1:27:48<568:20:32,  3.60s/it]
  0%|          | 1821/569592 [1:27:49<442:02:24,  2.80s/it]
                                                           

  0%|          | 1821/569592 [1:27:49<442:02:24,  2.80s/it]
  0%|          | 1822/569592 [1:27:50<353:03:40,  2.24s/it]
                                                           

  0%|          | 1822/569592 [1:27:50<353:03:40,  2.24s/it]
  0%|          | 1823/569592 [1:27:53<410:22:43,  2.60s/it]
                                                           

  0%|          | 1823/569592 [1:27:53<410:22:43,  2.60s/it]
  0%|          | 1824/569592 [1:27:57<454:02:52,  2.88s/it]
                                                           

  0%|          | 1824/569592 [1:27:57<454:02:52,  2.88s/it]
  0%|          | 1825/569592 [1:27:58<405:03:01,  2.57s/it]
                                                           

  0%|          | 1825/569592 [1:27:58<405:03:01,  2.57s/it]
  0%|          | 1826/569592 [1:27:59<330:53:34,  2.10s/it]
                                                           

  0%|          | 1826/569592 [1:27:59<330:53:34,  2.10s/it]
  0%|          | 1827/569592 [1:28:01<321:33:17,  2.04s/it]
                                                           

  0%|          | 1827/569592 [1:28:01<321:33:17,  2.04s/it]
  0%|          | 1828/569592 [1:28:08<524:30:40,  3.33s/it]
                                                           

  0%|          | 1828/569592 [1:28:08<524:30:40,  3.33s/it]
  0%|          | 1829/569592 [1:28:13<602:58:31,  3.82s/it]
                                                           

  0%|          | 1829/569592 [1:28:13<602:58:31,  3.82s/it]
  0%|          | 1830/569592 [1:28:13<464:47:33,  2.95s/it]
                                                           

  0%|          | 1830/569592 [1:28:14<464:47:33,  2.95s/it]
  0%|          | 1831/569592 [1:28:17<484:56:12,  3.07s/it]
                                                           

  0%|          | 1831/569592 [1:28:17<484:56:12,  3.07s/it]
  0%|          | 1832/569592 [1:28:20<491:06:05,  3.11s/it]
                                                           

  0%|          | 1832/569592 [1:28:20<491:06:05,  3.11s/it]
  0%|          | 1833/569592 [1:28:25<573:18:17,  3.64s/it]
                                                           

  0%|          | 1833/569592 [1:28:25<573:18:17,  3.64s/it]
  0%|          | 1834/569592 [1:28:26<444:10:43,  2.82s/it]
                                                           

  0%|          | 1834/569592 [1:28:26<444:10:43,  2.82s/it]
  0%|          | 1835/569592 [1:28:27<354:21:18,  2.25s/it]
                                                           

  0%|          | 1835/569592 [1:28:27<354:21:18,  2.25s/it]
  0%|          | 1836/569592 [1:28:28<294:06:55,  1.86s/it]
                                                           

  0%|          | 1836/569592 [1:28:28<294:06:55,  1.86s/it]
  0%|          | 1837/569592 [1:28:32<394:31:07,  2.50s/it]
                                                           

  0%|          | 1837/569592 [1:28:32<394:31:07,  2.50s/it]
  0%|          | 1838/569592 [1:28:37<533:20:08,  3.38s/it]
                                                           

  0%|          | 1838/569592 [1:28:38<533:20:08,  3.38s/it]
  0%|          | 1839/569592 [1:28:42<597:41:20,  3.79s/it]
                                                           

  0%|          | 1839/569592 [1:28:42<597:41:20,  3.79s/it]
  0%|          | 1840/569592 [1:28:46<601:07:12,  3.81s/it]
                                                           

  0%|          | 1840/569592 [1:28:46<601:07:12,  3.81s/it]
  0%|          | 1841/569592 [1:28:50<644:26:16,  4.09s/it]
                                                           

  0%|          | 1841/569592 [1:28:50<644:26:16,  4.09s/it]
  0%|          | 1842/569592 [1:28:55<675:26:43,  4.28s/it]
                                                           

  0%|          | 1842/569592 [1:28:55<675:26:43,  4.28s/it]
  0%|          | 1843/569592 [1:29:00<693:12:57,  4.40s/it]
                                                           

  0%|          | 1843/569592 [1:29:00<693:12:57,  4.40s/it]
  0%|          | 1844/569592 [1:29:05<705:25:30,  4.47s/it]
                                                           

  0%|          | 1844/569592 [1:29:05<705:25:30,  4.47s/it]
  0%|          | 1845/569592 [1:29:08<647:30:35,  4.11s/it]
                                                           

  0%|          | 1845/569592 [1:29:08<647:30:35,  4.11s/it]
  0%|          | 1846/569592 [1:29:13<679:28:22,  4.31s/it]
                                                           

  0%|          | 1846/569592 [1:29:13<679:28:22,  4.31s/it]
  0%|          | 1847/569592 [1:29:17<685:21:34,  4.35s/it]
                                                           

  0%|          | 1847/569592 [1:29:17<685:21:34,  4.35s/it]
  0%|          | 1848/569592 [1:29:21<666:31:15,  4.23s/it]
                                                           

  0%|          | 1848/569592 [1:29:21<666:31:15,  4.23s/it]
  0%|          | 1849/569592 [1:29:26<684:42:55,  4.34s/it]
                                                           

  0%|          | 1849/569592 [1:29:26<684:42:55,  4.34s/it]
  0%|          | 1850/569592 [1:29:30<710:13:40,  4.50s/it]
                                                           

  0%|          | 1850/569592 [1:29:30<710:13:40,  4.50s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92254938 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  0%|          | 1851/569592 [1:29:35<712:58:21,  4.52s/it]
                                                           

  0%|          | 1851/569592 [1:29:35<712:58:21,  4.52s/it]
  0%|          | 1852/569592 [1:29:40<723:03:19,  4.58s/it]
                                                           

  0%|          | 1852/569592 [1:29:40<723:03:19,  4.58s/it]
  0%|          | 1853/569592 [1:29:44<728:39:15,  4.62s/it]
                                                           

  0%|          | 1853/569592 [1:29:44<728:39:15,  4.62s/it]
  0%|          | 1854/569592 [1:29:49<711:32:10,  4.51s/it]
                                                           

  0%|          | 1854/569592 [1:29:49<711:32:10,  4.51s/it]
  0%|          | 1855/569592 [1:29:53<718:14:20,  4.55s/it]
                                                           

  0%|          | 1855/569592 [1:29:53<718:14:20,  4.55s/it]
  0%|          | 1856/569592 [1:29:58<734:14:21,  4.66s/it]
                                                          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (104675620 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 

  0%|          | 1856/569592 [1:29:58<734:14:21,  4.66s/it]
  0%|          | 1857/569592 [1:30:03<740:24:02,  4.69s/it]
                                                           

  0%|          | 1857/569592 [1:30:03<740:24:02,  4.69s/it]
  0%|          | 1858/569592 [1:30:08<738:39:00,  4.68s/it]
                                                           

  0%|          | 1858/569592 [1:30:08<738:39:00,  4.68s/it]
  0%|          | 1859/569592 [1:30:13<745:23:07,  4.73s/it]
                                                           

  0%|          | 1859/569592 [1:30:13<745:23:07,  4.73s/it]
  0%|          | 1860/569592 [1:30:16<703:44:32,  4.46s/it]
                                                           

  0%|          | 1860/569592 [1:30:16<703:44:32,  4.46s/it]
  0%|          | 1861/569592 [1:30:22<745:49:39,  4.73s/it]
                                                           

  0%|          | 1861/569592 [1:30:22<745:49:39,  4.73s/it]
  0%|          | 1862/569592 [1:30:25<664:52:03,  4.22s/it]
                                                           

  0%|          | 1862/569592 [1:30:25<664:52:03,  4.22s/it]
  0%|          | 1863/569592 [1:30:29<673:34:22,  4.27s/it]
                                                           

  0%|          | 1863/569592 [1:30:29<673:34:22,  4.27s/it]
  0%|          | 1864/569592 [1:30:34<695:23:46,  4.41s/it]
                                                           

  0%|          | 1864/569592 [1:30:34<695:23:46,  4.41s/it]
  0%|          | 1865/569592 [1:30:39<710:48:22,  4.51s/it]
                                                           

  0%|          | 1865/569592 [1:30:39<710:48:22,  4.51s/it]
  0%|          | 1866/569592 [1:30:43<711:16:10,  4.51s/it]
                                                           

  0%|          | 1866/569592 [1:30:43<711:16:10,  4.51s/it]
  0%|          | 1867/569592 [1:30:44<538:59:02,  3.42s/it]
                                                           

  0%|          | 1867/569592 [1:30:44<538:59:02,  3.42s/it]
  0%|          | 1868/569592 [1:30:47<524:57:22,  3.33s/it]
                                                           

  0%|          | 1868/569592 [1:30:47<524:57:22,  3.33s/it]
  0%|          | 1869/569592 [1:30:52<600:18:53,  3.81s/it]
                                                           

  0%|          | 1869/569592 [1:30:52<600:18:53,  3.81s/it]
  0%|          | 1870/569592 [1:30:57<642:08:15,  4.07s/it]
                                                           

  0%|          | 1870/569592 [1:30:57<642:08:15,  4.07s/it]
  0%|          | 1871/569592 [1:31:00<596:27:29,  3.78s/it]
                                                           

  0%|          | 1871/569592 [1:31:00<596:27:29,  3.78s/it]
  0%|          | 1872/569592 [1:31:01<460:35:34,  2.92s/it]
                                                           

  0%|          | 1872/569592 [1:31:01<460:35:34,  2.92s/it]
  0%|          | 1873/569592 [1:31:06<549:29:46,  3.48s/it]
                                                           

  0%|          | 1873/569592 [1:31:06<549:29:46,  3.48s/it]
  0%|          | 1874/569592 [1:31:09<534:52:47,  3.39s/it]
                                                           

  0%|          | 1874/569592 [1:31:09<534:52:47,  3.39s/it]
  0%|          | 1875/569592 [1:31:14<608:50:38,  3.86s/it]
                                                           

  0%|          | 1875/569592 [1:31:14<608:50:38,  3.86s/it]
  0%|          | 1876/569592 [1:31:18<652:31:39,  4.14s/it]
                                                           

  0%|          | 1876/569592 [1:31:18<652:31:39,  4.14s/it]
  0%|          | 1877/569592 [1:31:19<504:42:48,  3.20s/it]
                                                           

  0%|          | 1877/569592 [1:31:19<504:42:48,  3.20s/it]
  0%|          | 1878/569592 [1:31:20<395:52:19,  2.51s/it]
                                                           

  0%|          | 1878/569592 [1:31:20<395:52:19,  2.51s/it]
  0%|          | 1879/569592 [1:31:21<324:25:14,  2.06s/it]
                                                           

  0%|          | 1879/569592 [1:31:21<324:25:14,  2.06s/it]
  0%|          | 1880/569592 [1:31:25<415:32:34,  2.64s/it]
                                                           

  0%|          | 1880/569592 [1:31:25<415:32:34,  2.64s/it]
  0%|          | 1881/569592 [1:31:29<449:50:22,  2.85s/it]
                                                           

  0%|          | 1881/569592 [1:31:29<449:50:22,  2.85s/it]
  0%|          | 1882/569592 [1:31:30<361:44:37,  2.29s/it]
                                                           

  0%|          | 1882/569592 [1:31:30<361:44:37,  2.29s/it]
  0%|          | 1883/569592 [1:31:31<298:29:05,  1.89s/it]
                                                           

  0%|          | 1883/569592 [1:31:31<298:29:05,  1.89s/it]
  0%|          | 1884/569592 [1:31:32<253:34:02,  1.61s/it]
                                                           

  0%|          | 1884/569592 [1:31:32<253:34:02,  1.61s/it]
  0%|          | 1885/569592 [1:31:33<227:36:46,  1.44s/it]
                                                           

  0%|          | 1885/569592 [1:31:33<227:36:46,  1.44s/it]
  0%|          | 1886/569592 [1:31:34<219:05:59,  1.39s/it]
                                                           

  0%|          | 1886/569592 [1:31:34<219:05:59,  1.39s/it]
  0%|          | 1887/569592 [1:31:35<197:49:27,  1.25s/it]
                                                           

  0%|          | 1887/569592 [1:31:35<197:49:27,  1.25s/it]
  0%|          | 1888/569592 [1:31:36<189:22:29,  1.20s/it]
                                                           

  0%|          | 1888/569592 [1:31:36<189:22:29,  1.20s/it]
  0%|          | 1889/569592 [1:31:43<461:58:04,  2.93s/it]
                                                           

  0%|          | 1889/569592 [1:31:43<461:58:04,  2.93s/it]
  0%|          | 1890/569592 [1:31:44<386:49:06,  2.45s/it]
                                                           

  0%|          | 1890/569592 [1:31:44<386:49:06,  2.45s/it]
  0%|          | 1891/569592 [1:31:45<316:08:53,  2.00s/it]
                                                           

  0%|          | 1891/569592 [1:31:45<316:08:53,  2.00s/it]
  0%|          | 1892/569592 [1:31:46<264:51:48,  1.68s/it]
                                                           

  0%|          | 1892/569592 [1:31:46<264:51:48,  1.68s/it]
  0%|          | 1893/569592 [1:31:52<452:32:30,  2.87s/it]
                                                           

  0%|          | 1893/569592 [1:31:52<452:32:30,  2.87s/it]
  0%|          | 1894/569592 [1:31:54<419:24:33,  2.66s/it]
                                                           

  0%|          | 1894/569592 [1:31:54<419:24:33,  2.66s/it]
  0%|          | 1895/569592 [1:31:55<345:05:56,  2.19s/it]
                                                           

  0%|          | 1895/569592 [1:31:55<345:05:56,  2.19s/it]
  0%|          | 1896/569592 [1:31:56<293:20:05,  1.86s/it]
                                                           

  0%|          | 1896/569592 [1:31:56<293:20:05,  1.86s/it]
  0%|          | 1897/569592 [1:32:03<521:15:34,  3.31s/it]
                                                           

  0%|          | 1897/569592 [1:32:03<521:15:34,  3.31s/it]
  0%|          | 1898/569592 [1:32:04<413:40:43,  2.62s/it]
                                                           

  0%|          | 1898/569592 [1:32:04<413:40:43,  2.62s/it]
  0%|          | 1899/569592 [1:32:05<335:41:37,  2.13s/it]
                                                           

  0%|          | 1899/569592 [1:32:05<335:41:37,  2.13s/it]
  0%|          | 1900/569592 [1:32:06<309:37:26,  1.96s/it]
                                                           

  0%|          | 1900/569592 [1:32:06<309:37:26,  1.96s/it]
  0%|          | 1901/569592 [1:32:13<508:11:35,  3.22s/it]
                                                           

  0%|          | 1901/569592 [1:32:13<508:11:35,  3.22s/it]
  0%|          | 1902/569592 [1:32:14<413:39:55,  2.62s/it]
                                                           

  0%|          | 1902/569592 [1:32:14<413:39:55,  2.62s/it]
  0%|          | 1903/569592 [1:32:15<365:36:01,  2.32s/it]
                                                           

  0%|          | 1903/569592 [1:32:15<365:36:01,  2.32s/it]
  0%|          | 1904/569592 [1:32:17<317:00:02,  2.01s/it]
                                                           

  0%|          | 1904/569592 [1:32:17<317:00:02,  2.01s/it]
  0%|          | 1905/569592 [1:32:21<448:11:31,  2.84s/it]
                                                           

  0%|          | 1905/569592 [1:32:21<448:11:31,  2.84s/it]
  0%|          | 1906/569592 [1:32:23<376:22:19,  2.39s/it]
                                                           

  0%|          | 1906/569592 [1:32:23<376:22:19,  2.39s/it]
  0%|          | 1907/569592 [1:32:25<388:45:57,  2.47s/it]
                                                           

  0%|          | 1907/569592 [1:32:25<388:45:57,  2.47s/it]
  0%|          | 1908/569592 [1:32:28<373:18:31,  2.37s/it]
                                                           

  0%|          | 1908/569592 [1:32:28<373:18:31,  2.37s/it]
  0%|          | 1909/569592 [1:32:33<517:41:34,  3.28s/it]
                                                           

  0%|          | 1909/569592 [1:32:33<517:41:34,  3.28s/it]
  0%|          | 1910/569592 [1:32:34<412:59:17,  2.62s/it]
                                                           

  0%|          | 1910/569592 [1:32:34<412:59:17,  2.62s/it]
  0%|          | 1911/569592 [1:32:35<342:10:54,  2.17s/it]
                                                           

  0%|          | 1911/569592 [1:32:35<342:10:54,  2.17s/it]
  0%|          | 1912/569592 [1:32:38<359:31:50,  2.28s/it]
                                                           

  0%|          | 1912/569592 [1:32:38<359:31:50,  2.28s/it]
  0%|          | 1913/569592 [1:32:43<483:26:58,  3.07s/it]
                                                           

  0%|          | 1913/569592 [1:32:43<483:26:58,  3.07s/it]
  0%|          | 1914/569592 [1:32:44<400:55:06,  2.54s/it]
                                                           

  0%|          | 1914/569592 [1:32:44<400:55:06,  2.54s/it]
  0%|          | 1915/569592 [1:32:46<383:59:17,  2.44s/it]
                                                           

  0%|          | 1915/569592 [1:32:46<383:59:17,  2.44s/it]
  0%|          | 1916/569592 [1:32:48<338:32:33,  2.15s/it]
                                                           

  0%|          | 1916/569592 [1:32:48<338:32:33,  2.15s/it]
  0%|          | 1917/569592 [1:32:54<534:45:07,  3.39s/it]
                                                           

  0%|          | 1917/569592 [1:32:54<534:45:07,  3.39s/it]
  0%|          | 1918/569592 [1:32:55<418:05:53,  2.65s/it]
                                                           

  0%|          | 1918/569592 [1:32:55<418:05:53,  2.65s/it]
  0%|          | 1919/569592 [1:32:56<354:09:07,  2.25s/it]
                                                           

  0%|          | 1919/569592 [1:32:56<354:09:07,  2.25s/it]
  0%|          | 1920/569592 [1:32:58<317:23:20,  2.01s/it]
                                                           

  0%|          | 1920/569592 [1:32:58<317:23:20,  2.01s/it]
  0%|          | 1921/569592 [1:33:04<515:55:37,  3.27s/it]
                                                           

  0%|          | 1921/569592 [1:33:04<515:55:37,  3.27s/it]
  0%|          | 1922/569592 [1:33:05<422:06:44,  2.68s/it]
                                                           

  0%|          | 1922/569592 [1:33:05<422:06:44,  2.68s/it]
  0%|          | 1923/569592 [1:33:06<340:23:23,  2.16s/it]
                                                           

  0%|          | 1923/569592 [1:33:06<340:23:23,  2.16s/it]
  0%|          | 1924/569592 [1:33:08<312:31:46,  1.98s/it]
                                      /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                     

  0%|          | 1924/569592 [1:33:08<312:31:46,  1.98s/it]
  0%|          | 1925/569592 [1:33:14<527:53:59,  3.35s/it]
                                                           

  0%|          | 1925/569592 [1:33:14<527:53:59,  3.35s/it]
  0%|          | 1926/569592 [1:33:16<437:32:08,  2.77s/it]
                                                           

  0%|          | 1926/569592 [1:33:16<437:32:08,  2.77s/it]
  0%|          | 1927/569592 [1:33:16<349:45:34,  2.22s/it]
                                                           

  0%|          | 1927/569592 [1:33:16<349:45:34,  2.22s/it]
  0%|          | 1928/569592 [1:33:17<290:19:41,  1.84s/it]
                                                           

  0%|          | 1928/569592 [1:33:17<290:19:41,  1.84s/it]
  0%|          | 1929/569592 [1:33:24<535:44:32,  3.40s/it]
                                                           

  0%|          | 1929/569592 [1:33:24<535:44:32,  3.40s/it]
  0%|          | 1930/569592 [1:33:2/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
6<435:51:42,  2.76s/it]
                                                           

  0%|          | 1930/569592 [1:33:26<435:51:42,  2.76s/it]
  0%|          | 1931/569592 [1:33:27<350:36:34,  2.22s/it]
                                                           

  0%|          | 1931/569592 [1:33:27<350:36:34,  2.22s/it]
  0%|          | 1932/569592 [1:33:28<325:23:25,  2.06s/it]
                                                           

  0%|          | 1932/569592 [1:33:28<325:23:25,  2.06s/it]
  0%|          | 1933/569592 [1:33:35<530:32:10,  3.36s/it]
                                                           

  0%|          | 1933/569592 [1:33:35<530:32:10,  3.36s/it]
  0%|          | 1934/569592 [1:33:36<420:00:11,  2.66s/it]
                                                           

  0%|          | 1934/569592 [1:33:36<420:00:11,  2.66s/it]
  0%|          | 1935/569592 [1:33:37<338:13:05,  2.14s/it]
                                                           

  0%|          | 1935/569592 [1:33:37<338:13:05,  2.14s/it]
  0%|          | 1936/569592 [1:33:38<281:52:24,  1.79s/it]
                                                           

  0%|          | 1936/569592 [1:33:38<281:52:24,  1.79s/it]
  0%|          | 1937/569592 [1:33:45<519:52:16,  3.30s/it]
                                                           

  0%|          | 1937/569592 [1:33:45<519:52:16,  3.30s/it]
  0%|          | 1938/569592 [1:33:45<409:01:29,  2.59s/it]
                                                           

  0%|          | 1938/569592 [1:33:46<409:01:29,  2.59s/it]
  0%|          | 1939/569592 [1:33:46<331:23:51,  2.10s/it]
                                                           

  0%|          | 1939/569592 [1:33:46<331:23:51,  2.10s/it]
  0%|          | 1940/569592 [1:33:48<305:01:44,  1.93s/it]
                                                           

  0%|          | 1940/569592 [1:33:48<305:01:44,  1.93s/it]
  0%|          | 1941/569592 [1:33:55<557:56:14,  3.54s/it]
                                                           

  0%|          | 1941/569592 [1:33:55<557:56:14,  3.54s/it]
  0%|          | 1942/569592 [1:33:59<548:32:13,  3.48s/it]
                                                           

  0%|          | 1942/569592 [1:33:59<548:32:13,  3.48s/it]
  0%|          | 1943/569592 [1:34:00<430:41:47,  2.73s/it]
                                                           

  0%|          | 1943/569592 [1:34:00<430:41:47,  2.73s/it]
  0%|          | 1944/569592 [1:34:01<346:19:54,  2.20s/it]
                                                           

  0%|          | 1944/569592 [1:34:01<346:19:54,  2.20s/it]
  0%|          | 1945/569592 [1:34:07<529:04:43,  3.36s/it]
                                                           

  0%|          | 1945/569592 [1:34:07<529:04:43,  3.36s/it]
  0%|          | 1946/569592 [1:34:08<416:07:25,  2.64s/it]
                                                           

  0%|          | 1946/569592 [1:34:08<416:07:25,  2.64s/it]
  0%|          | 1947/569592 [1:34:09<336:24:13,  2.13s/it]
                                                           

  0%|          | 1947/569592 [1:34:09<336:24:13,  2.13s/it]
  0%|          | 1948/569592 [1:34:10<284:09:46,  1.80s/it]
                                                           

  0%|          | 1948/569592 [1:34:10<284:09:46,  1.80s/it]
  0%|          | 1949/569592 [1:34:17<545:57:59,  3.46s/it]
                                                           

  0%|          | 1949/569592 [1:34:17<545:57:59,  3.46s/it]
  0%|          | 1950/569592 [1:34:22<634:23:26,  4.02s/it]
                                                           

  0%|          | 1950/569592 [1:34:22<634:23:26,  4.02s/it]
  0%|          | 1951/569592 [1:34:23<487:59:08,  3.09s/it]
                                                           

  0%|          | 1951/569592 [1:34:23<487:59:08,  3.09s/it]
  0%|          | 1952/569592 [1:34:24<384:40:51,  2.44s/it]
                                                           

  0%|          | 1952/569592 [1:34:24<384:40:51,  2.44s/it]
  0%|          | 1953/569592 [1:34:26<348:19:02,  2.21s/it]
                                                           

  0%|          | 1953/569592 [1:34:26<348:19:02,  2.21s/it]
  0%|          | 1954/569592 [1:34:29<408:32:29,  2.59s/it]
                                                           

  0%|          | 1954/569592 [1:34:29<408:32:29,  2.59s/it]
  0%|          | 1955/569592 [1:34:34<520:15:36,  3.30s/it]
                                                           

  0%|          | 1955/569592 [1:34:34<520:15:36,  3.30s/it]
  0%|          | 1956/569592 [1:34:39<587:44:03,  3.73s/it]
                                                           

  0%|          | 1956/569592 [1:34:39<587:44:03,  3.73s/it]
  0%|          | 1957/569592 [1:34:44<634:12:06,  4.02s/it]
                                                           

  0%|          | 1957/569592 [1:34:44<634:12:06,  4.02s/it]
  0%|          | 1958/569592 [1:34:48<642:57:57,  4.08s/it]
                                                           

  0%|          | 1958/569592 [1:34:48<642:57:57,  4.08s/it]
  0%|          | 1959/569592 [1:34:51<594:48:15,  3.77s/it]
                                                           

  0%|          | 1959/569592 [1:34:51<594:48:15,  3.77s/it]
  0%|          | 1960/569592 [1:34:56<636:26:14,  4.04s/it]
                                                           

  0%|          | 1960/569592 [1:34:56<636:26:14,  4.04s/it]
  0%|          | 1961/569592 [1:35:01<681:41:33,  4.32s/it]
                                                           

  0%|          | 1961/569592 [1:35:01<681:41:33,  4.32s/it]
  0%|          | 1962/569592 [1:35:05<693:32:40,  4.40s/it]
                                                           

  0%|          | 1962/569592 [1:35:05<693:32:40,  4.40s/it]
  0%|          | 1963/569592 [1:35:10<708:36:25,  4.49s/it]
                                                           

  0%|          | 1963/569592 [1:35:10<708:36:25,  4.49s/it]
  0%|          | 1964/569592 [1:35:13<648:21:48,  4.11s/it]
                                                           

  0%|          | 1964/569592 [1:35:13<648:21:48,  4.11s/it]
  0%|          | 1965/569592 [1:35:18<676:40:35,  4.29s/it]
                                                           

  0%|          | 1965/569592 [1:35:18<676:40:35,  4.29s/it]
  0%|          | 1966/569592 [1:35:22<692:49:39,  4.39s/it]
                                                           

  0%|          | 1966/569592 [1:35:22<692:49:39,  4.39s/it]
  0%|          | 1967/569592 [1:35:26<638:37:19,  4.05s/it]
                                                           

  0%|          | 1967/569592 [1:35:26<638:37:19,  4.05s/it]
  0%|          | 1968/569592 [1:35:30<646:17:35,  4.10s/it]
                                                           

  0%|          | 1968/569592 [1:35:30<646:17:35,  4.10s/it]
  0%|          | 1969/569592 [1:35:35<679:24:37,  4.31s/it]
                                                           

  0%|          | 1969/569592 [1:35:35<679:24:37,  4.31s/it]
  0%|          | 1970/569592 [1:35:40<721:49:28,  4.58s/it]
                                                           

  0%|          | 1970/569592 [1:35:40<721:49:28,  4.58s/it]
  0%|          | 1971/569592 [1:35:45<733:00:49,  4.65s/it]
                                                           

  0%|          | 1971/569592 [1:35:45<733:00:49,  4.65s/it]
  0%|          | 1972/569592 [1:35:49<736:15:55,  4.67s/it]
                                                           

  0%|          | 1972/569592 [1:35:49<736:15:55,  4.67s/it]
  0%|          | 1973/569592 [1:35:53<676:38:12,  4.29s/it]
                                                           

  0%|          | 1973/569592 [1:35:53<676:38:12,  4.29s/it]
  0%|          | 1974/569592 [1:35:57<692:48:43,  4.39s/it]
                                                           

  0%|          | 1974/569592 [1:35:57<692:48:43,  4.39s/it]
  0%|          | 1975/569592 [1:36:02<684:57:02,  4.34s/it]
                                                           

  0%|          | 1975/569592 [1:36:02<684:57:02,  4.34s/it]
  0%|          | 1976/569592 [1:36:06<701:49:22,  4.45s/it]
                                                           

  0%|          | 1976/569592 [1:36:06<701:49:22,  4.45s/it]
  0%|          | 1977/569592 [1:36:11<709:15:54,  4.50s/it]
                                                           

  0%|          | 1977/569592 [1:36:11<709:15:54,  4.50s/it]
  0%|          | 1978/569592 [1:36:15<687:11:35,  4.36s/it]
                                                           

  0%|          | 1978/569592 [1:36:15<687:11:35,  4.36s/it]
  0%|          | 1979/569592 [1:36:20<704:16:00,  4.47s/it]
                                                           

  0%|          | 1979/569592 [1:36:20<704:16:00,  4.47s/it]
  0%|          | 1980/569592 [1:36:24<715:41:01,  4.54s/it]
                                                           

  0%|          | 1980/569592 [1:36:24<715:41:01,  4.54s/it]
  0%|          | 1981/569592 [1:36:27<642:57:52,  4.08s/it]
                                                           

  0%|          | 1981/569592 [1:36:27<642:57:52,  4.08s/it]
  0%|          | 1982/569592 [1:36:32<667:03:38,  4.23s/it]
                                                           

  0%|          | 1982/569592 [1:36:32<667:03:38,  4.23s/it]
  0%|          | 1983/569592 [1:36:35<616:26:23,  3.91s/it]
                                                           

  0%|          | 1983/569592 [1:36:35<616:26:23,  3.91s/it]
  0%|          | 1984/569592 [1:36:40<649:58:16,  4.12s/it]
                                                           

  0%|          | 1984/569592 [1:36:40<649:58:16,  4.12s/it]
  0%|          | 1985/569592 [1:36:43<611:37:29,  3.88s/it]
                                                           

  0%|          | 1985/569592 [1:36:43<611:37:29,  3.88s/it]
  0%|          | 1986/569592 [1:36:46<575:32:46,  3.65s/it]
                                                           

  0%|          | 1986/569592 [1:36:46<575:32:46,  3.65s/it]
  0%|          | 1987/569592 [1:36:50<559:04:02,  3.55s/it]
                                                           

  0%|          | 1987/569592 [1:36:50<559:04:02,  3.55s/it]
  0%|          | 1988/569592 [1:36:53<547:10:29,  3.47s/it]
                                                           

  0%|          | 1988/569592 [1:36:53<547:10:29,  3.47s/it]
  0%|          | 1989/569592 [1:36:54<427:26:26,  2.71s/it]
                                                           

  0%|          | 1989/569592 [1:36:54<427:26:26,  2.71s/it]
  0%|          | 1990/569592 [1:36:55<345:42:12,  2.19s/it]
                                                           

  0%|          | 1990/569592 [1:36:55<345:42:12,  2.19s/it]
  0%|          | 1991/569592 [1:37:00<483:14:21,  3.06s/it]
                                                           

  0%|          | 1991/569592 [1:37:00<483:14:21,  3.06s/it]
  0%|          | 1992/569592 [1:37:04<524:02:45,  3.32s/it]
                                                           

  0%|          | 1992/569592 [1:37:04<524:02:45,  3.32s/it]
  0%|          | 1993/569592 [1:37:07<537:31:43,  3.41s/it]
                                                           

  0%|          | 1993/569592 [1:37:07<537:31:43,  3.41s/it]
  0%|          | 1994/569592 [1:37:10<521:53:53,  3.31s/it]
                                                           

  0%|          | 1994/569592 [1:37:10<521:53:53,  3.31s/it]
  0%|          | 1995/569592 [1:37:11<409:50:30,  2.60s/it]
                                                           

  0%|          | 1995/569592 [1:37:11<409:50:30,  2.60s/it]
  0%|          | 1996/569592 [1:37:12<335:50:33,  2.13s/it]
                                                           

  0%|          | 1996/569592 [1:37:12<335:50:33,  2.13s/it]
  0%|          | 1997/569592 [1:37:16<415:19:37,  2.63s/it]
                                                           

  0%|          | 1997/569592 [1:37:16<415:19:37,  2.63s/it]
  0%|          | 1998/569592 [1:37:17<336:37:04,  2.14s/it]
                                                           

  0%|          | 1998/569592 [1:37:17<336:37:04,  2.14s/it]
  0%|          | 1999/569592 [1:37:21<393:13:25,  2.49s/it]
                                                           

  0%|          | 1999/569592 [1:37:21<393:13:25,  2.49s/it]
  0%|          | 2000/569592 [1:37:21<320:39:33,  2.03s/it]
                                                           

  0%|          | 2000/569592 [1:37:22<320:39:33,  2.03s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-2000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-2000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-2000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-2000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-2000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-2000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-1000] due to args.save_total_limit

  0%|          | 2001/569592 [1:39:22<5937:45:14, 37.66s/it]
                                                            

  0%|          | 2001/569592 [1:39:22<5937:45:14, 37.66s/it]
  0%|          | 2002/569592 [1:39:23<4198:30:00, 26.63s/it]
                                                            

  0%|          | 2002/569592 [1:39:23<4198:30:00, 26.63s/it]
  0%|          | 2003/569592 [1:39:24<2984:17:03, 18.93s/it]
                                                            

  0%|          | 2003/569592 [1:39:24<2984:17:03, 18.93s/it]
  0%|          | 2004/569592 [1:39:25<2140:11:29, 13.57s/it]
                                                            

  0%|          | 2004/569592 [1:39:25<2140:11:29, 13.57s/it]
  0%|          | 2005/569592 [1:39:26<1547:29:56,  9.82s/it]
                                                            

  0%|          | 2005/569592 [1:39:26<1547:29:56,  9.82s/it]
  0%|          | 2006/569592 [1:39:27<1127:31:19,  7.15s/it]
                                                            

  0%|          | 2006/569592 [1:39:27<1127:31:19,  7.15s/it]
  0%|          | 2007/569592 [1:39:28<837:03:18,  5.31s/it] 
                                                           

  0%|          | 2007/569592 [1:39:28<837:03:18,  5.31s/it]
  0%|          | 2008/569592 [1:39:29<631:38:26,  4.01s/it]
                                                           

  0%|          | 2008/569592 [1:39:29<631:38:26,  4.01s/it]
  0%|          | 2009/569592 [1:39:31<540:19:02,  3.43s/it]
                                                           

  0%|          | 2009/569592 [1:39:31<540:19:02,  3.43s/it]
  0%|          | 2010/569592 [1:39:36<616:30:55,  3.91s/it]
                                                           

  0%|          | 2010/569592 [1:39:36<616:30:55,  3.91s/it]
  0%|          | 2011/569592 [1:39:37<480:56:13,  3.05s/it]
                                                           

  0%|          | 2011/569592 [1:39:37<480:56:13,  3.05s/it]
  0%|          | 2012/569592 [1:39:39<426:54:07,  2.71s/it]
                                                           

  0%|          | 2012/569592 [1:39:39<426:54:07,  2.71s/it]
  0%|          | 2013/569592 [1:39:42<406:50:47,  2.58s/it]
                                                           

  0%|          | 2013/569592 [1:39:42<406:50:47,  2.58s/it]
  0%|          | 2014/569592 [1:39:47<525:19:37,  3.33s/it]
                                                           

  0%|          | 2014/569592 [1:39:47<525:19:37,  3.33s/it]
  0%|          | 2015/569592 [1:39:48<418:22:56,  2.65s/it]
                                                           

  0%|          | 2015/569592 [1:39:48<418:22:56,  2.65s/it]
  0%|          | 2016/569592 [1:39:49<360:52:45,  2.29s/it]
                                                           

  0%|          | 2016/569592 [1:39:49<360:52:45,  2.29s/it]
  0%|          | 2017/569592 [1:39:51<334:30:44,  2.12s/it]
                                                           

  0%|          | 2017/569592 [1:39:51<334:30:44,  2.12s/it]
  0%|          | 2018/569592 [1:39:56<484:05:47,  3.07s/it]
                                                           

  0%|          | 2018/569592 [1:39:56<484:05:47,  3.07s/it]
  0%|          | 2019/569592 [1:39:57<386:34:16,  2.45s/it]
                                                           

  0%|          | 2019/569592 [1:39:57<386:34:16,  2.45s/it]
  0%|          | 2020/569592 [1:39:59<353:17:34,  2.24s/it]
                                                           

  0%|          | 2020/569592 [1:39:59<353:17:34,  2.24s/it]
  0%|          | 2021/569592 [1:40:00<321:32:01,  2.04s/it]
                                                           

  0%|          | 2021/569592 [1:40:00<321:32:01,  2.04s/it]
  0%|          | 2022/569592 [1:40:06<507:25:05,  3.22s/it]
                                                           

  0%|          | 2022/569592 [1:40:06<507:25:05,  3.22s/it]
  0%|          | 2023/569592 [1:40:08<435:31:27,  2.76s/it]
                                                           

  0%|          | 2023/569592 [1:40:08<435:31:27,  2.76s/it]
  0%|          | 2024/569592 [1:40:09<352:22:17,  2.24s/it]
                                                           

  0%|          | 2024/569592 [1:40:09<352:22:17,  2.24s/it]
  0%|          | 2025/569592 [1:40:11<355:08:08,  2.25s/it]
                                                           

  0%|          | 2025/569592 [1:40:11<355:08:08,  2.25s/it]
  0%|          | 2026/569592 [1:40:17<531:47:31,  3.37s/it]
                                                           

  0%|          | 2026/569592 [1:40:17<531:47:31,  3.37s/it]
  0%|          | 2027/569592 [1:40:19<425:27:13,  2.70s/it]
                                                           

  0%|          | 2027/569592 [1:40:19<425:27:13,  2.70s/it]
  0%|          | 2028/569592 [1:40:20<343:44:40,  2.18s/it]
                                                           

  0%|          | 2028/569592 [1:40:20<343:44:40,  2.18s/it]
  0%|          | 2029/569592 [1:40:21<308:10:12,  1.95s/it]
                                                           

  0%|          | 2029/569592 [1:40:21<308:10:12,  1.95s/it]
  0%|          | 2030/569592 [1:40:28<536:12:00,  3.40s/it]
                                                           

  0%|          | 2030/569592 [1:40:28<536:12:00,  3.40s/it]
  0%|          | 2031/569592 [1:40:29<420:44:14,  2.67s/it]
                                                           

  0%|          | 2031/569592 [1:40:29<420:44:14,  2.67s/it]
  0%|          | 2032/569592 [1:40:30<340:25:59,  2.16s/it]
                                                           

  0%|          | 2032/569592 [1:40:30<340:25:59,  2.16s/it]
  0%|          | 2033/569592 [1:40:33<414:41:53,  2.63s/it]
                                                           

  0%|          | 2033/569592 [1:40:33<414:41:53,  2.63s/it]
  0%|          | 2034/569592 [1:40:38<492:31:31,  3.12s/it]
                                                           

  0%|          | 2034/569592 [1:40:38<492:31:31,  3.12s/it]
  0%|          | 2035/569592 [1:40:39<397:23:47,  2.52s/it]
                                                           

  0%|          | 2035/569592 [1:40:39<397:23:47,  2.52s/it]
  0%|          | 2036/569592 [1:40:40<323:49:11,  2.05s/it]
                                                           

  0%|          | 2036/569592 [1:40:40<323:49:11,  2.05s/it]
  0%|          | 2037/569592 [1:40:42<344:08:12,  2.18s/it]
                                                           

  0%|          | 2037/569592 [1:40:42<344:08:12,  2.18s/it]
  0%|          | 2038/569592 [1:40:49<563:20:44,  3.57s/it]
                                                           

  0%|          | 2038/569592 [1:40:49<563:20:44,  3.57s/it]
  0%|          | 2039/569592 [1:40:50<444:43:29,  2.82s/it]
                                                           

  0%|          | 2039/569592 [1:40:50<444:43:29,  2.82s/it]
  0%|          | 2040/569592 [1:40:51<358:02:03,  2.27s/it]
                                                           

  0%|          | 2040/569592 [1:40:51<358:02:03,  2.27s/it]
  0%|          | 2041/569592 [1:40:54<366:40:04,  2.33s/it]
                                                           

  0%|          | 2041/569592 [1:40:54<366:40:04,  2.33s/it]
  0%|          | 2042/569592 [1:40:59<528:41:57,  3.35s/it]
                                                           

  0%|          | 2042/569592 [1:40:59<528:41:57,  3.35s/it]
  0%|          | 2043/569592 [1:41:00<416:41:00,  2.64s/it]
                                                           

  0%|          | 2043/569592 [1:41:00<416:41:00,  2.64s/it]
  0%|          | 2044/569592 [1:41:01<336:15:49,  2.13s/it]
                                                           

  0%|          | 2044/569592 [1:41:01<336:15:49,  2.13s/it]
  0%|          | 2045/569592 [1:41:04<343:57:24,  2.18s/it]
                                                           

  0%|          | 2045/569592 [1:41:04<343:57:24,  2.18s/it]
  0%|          | 2046/569592 [1:41:09<494:17:05,  3.14s/it]
                                                           

  0%|          | 2046/569592 [1:41:09<494:17:05,  3.14s/it]
  0%|          | 2047/569592 [1:41:10<396:31:16,  2.52s/it]
                                                           

  0%|          | 2047/569592 [1:41:10<396:31:16,  2.52s/it]
  0%|          | 2048/569592 [1:41:11<323:49:14,  2.05s/it]
                                                           

  0%|          | 2048/569592 [1:41:11<323:49:14,  2.05s/it]
  0%|          | 2049/569592 [1:41:14<358:00:12,  2.27s/it]
                                                           

  0%|          | 2049/569592 [1:41:14<358:00:12,  2.27s/it]
  0%|          | 2050/569592 [1:41:20<552:20:35,  3.50s/it]
                                                           

  0%|          | 2050/569592 [1:41:20<552:20:35,  3.50s/it]
  0%|          | 2051/569592 [1:41:21<434:40:47,  2.76s/it]
                                                           

  0%|          | 2051/569592 [1:41:21<434:40:47,  2.76s/it]
  0%|          | 2052/569592 [1:41:22<348:19:21,  2.21s/it]
                                                           

  0%|          | 2052/569592 [1:41:22<348:19:21,  2.21s/it]
  0%|          | 2053/569592 [1:41:25<404:27:02,  2.57s/it]
                                                           

  0%|          | 2053/569592 [1:41:25<404:27:02,  2.57s/it]
  0%|          | 2054/569592 [1:41:29<460:19:03,  2.92s/it]
                                                           

  0%|          | 2054/569592 [1:41:29<460:19:03,  2.92s/it]
  0%|          | 2055/569592 [1:41:30<374:52:45,  2.38s/it]
                                                           

  0%|          | 2055/569592 [1:41:30<374:52:45,  2.38s/it]
  0%|          | 2056/569592 [1:41:31<309:05:48,  1.96s/it]
                                                           

  0%|          | 2056/569592 [1:41:31<309:05:48,  1.96s/it]
  0%|          | 2057/569592 [1:41:36<458:10:22,  2.91s/it]
                                                           

  0%|          | 2057/569592 [1:41:36<458:10:22,  2.91s/it]
  0%|          | 2058/569592 [1:41:40<479:05:13,  3.04s/it]
                                                           

  0%|          | 2058/569592 [1:41:40<479:05:13,  3.04s/it]
  0%|          | 2059/569592 [1:41:41<394:46:53,  2.50s/it]
                                                           

  0%|          | 2059/569592 [1:41:41<394:46:53,  2.50s/it]
  0%|          | 2060/569592 [1:41:42<320:50:42,  2.04s/it]
                                                           

  0%|          | 2060/569592 [1:41:42<320:50:42,  2.04s/it]
  0%|          | 2061/569592 [1:41:43<274:46:30,  1.74s/it]
                                                           

  0%|          | 2061/569592 [1:41:43<274:46:30,  1.74s/it]
  0%|          | 2062/569592 [1:41:49<490:36:16,  3.11s/it]
                                                           

  0%|          | 2062/569592 [1:41:49<490:36:16,  3.11s/it]
  0%|          | 2063/569592 [1:41:52<473:59:19,  3.01s/it]
                                                           

  0%|          | 2063/569592 [1:41:52<473:59:19,  3.01s/it]
  0%|          | 2064/569592 [1:41:55<487:32:59,  3.09s/it]
                                                           

  0%|          | 2064/569592 [1:41:55<487:32:59,  3.09s/it]
  0%|          | 2065/569592 [1:42:00<580:44:43,  3.68s/it]
                                                           

  0%|          | 2065/569592 [1:42:00<580:44:43,  3.68s/it]
  0%|          | 2066/569592 [1:42:06<652:36:04,  4.14s/it]
                                                           

  0%|          | 2066/569592 [1:42:06<652:36:04,  4.14s/it]
  0%|          | 2067/569592 [1:42:07<500:53:36,  3.18s/it]
                                                           

  0%|          | 2067/569592 [1:42:07<500:53:36,  3.18s/it]
  0%|          | 2068/569592 [1:42:07<394:53:19,  2.50s/it]
                                                           

  0%|          | 2068/569592 [1:42:07<394:53:19,  2.50s/it]
  0%|          | 2069/569592 [1:42:12<480:26:01,  3.05s/it]
                                                           

  0%|          | 2069/569592 [1:42:12<480:26:01,  3.05s/it]
  0%|          | 2070/569592 [1:42:17<564:12:56,  3.58s/it]
                                                           

  0%|          | 2070/569592 [1:42:17<564:12:56,  3.58s/it]
  0%|          | 2071/569592 [1:42:21<609:22:17,  3.87s/it]
                                                           

  0%|          | 2071/569592 [1:42:21<609:22:17,  3.87s/it]
  0%|          | 2072/569592 [1:42:26<649:37:54,  4.12s/it]
                                                           

  0%|          | 2072/569592 [1:42:26<649:37:54,  4.12s/it]
  0%|          | 2073/569592 [1:42:30<669:41:37,  4.25s/it]
                                                           

  0%|          | 2073/569592 [1:42:30<669:41:37,  4.25s/it]
  0%|          | 2074/569592 [1:42:34<621:13:24,  3.94s/it]
                   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                        

  0%|          | 2074/569592 [1:42:34<621:13:24,  3.94s/it]
  0%|          | 2075/569592 [1:42:38<620:35:02,  3.94s/it]
                                                           

  0%|          | 2075/569592 [1:42:38<620:35:02,  3.94s/it]
  0%|          | 2076/569592 [1:42:46<850:26:40,  5.39s/it]
                                                           

  0%|          | 2076/569592 [1:42:46<850:26:40,  5.39s/it]
  0%|          | 2077/569592 [1:42:50<787:54:38,  5.00s/it]
                                                           

  0%|          | 2077/569592 [1:42:50<787:54:38,  5.00s/it]
  0%|          | 2078/569592 [1:42:55<774:53:36,  4.92s/it]
                                                           

  0%|          | 2078/569592 [1:42:55<774:53:36,  4.92s/it]
  0%|          | 2079/569592 [1:43:00<768:11:59,  4.87s/it]
                                                           

  0%|          | 2079/569592 [1:43:00<768:11:59,  4.87s/it]
  0%|          | 2080/569592 [1:43:03<696:19:39,  4.42s/it]
                                                           

  0%|          | 2080/569592 [1:43:03<696:19:39,  4.42s/it]
  0%|          | 2081/569592 [1:43:07<678:16:16,  4.30s/it]
                                                           

  0%|          | 2081/569592 [1:43:07<678:16:16,  4.30s/it]
  0%|          | 2082/569592 [1:43:13<764:00:39,  4.85s/it]
                                                           

  0%|          | 2082/569592 [1:43:13<764:00:39,  4.85s/it]
  0%|          | 2083/569592 [1:43:17<713:26:07,  4.53s/it]
                                                           

  0%|          | 2083/569592 [1:43:18<713:26:07,  4.53s/it]
  0%|          | 2084/569592 [1:43:22<735:39:25,  4.67s/it]
                                                           

  0%|          | 2084/569592 [1:43:22<735:39:25,  4.67s/it]
  0%|          | 2085/569592 [1:43:27<721:42:20,  4.58s/it]
                                                           

  0%|          | 2085/569592 [1:43:27<721:42:20,  4.58s/it]
  0%|          | 2086/569592 [1:43:31<720:08:59,  4.57s/it]
                                                           

  0%|          | 2086/569592 [1:43:31<720:08:59,  4.57s/it]
  0%|          | 2087/569592 [1:43:37<761:34:32,  4.83s/it]
                                                           

  0%|          | 2087/569592 [1:43:37<761:34:32,  4.83s/it]
  0%|          | 2088/569592 [1:43:40<704:10:21,  4.47s/it]
                                                           

  0%|          | 2088/569592 [1:43:40<704:10:21,  4.47s/it]
  0%|          | 2089/569592 [1:43:44<695:21:32,  4.41s/it]
                                                           

  0%|          | 2089/569592 [1:43:44<695:21:32,  4.41s/it]
  0%|          | 2090/569592 [1:43:48<632:45:28,  4.01s/it]
                                                           

  0%|          | 2090/569592 [1:43:48<632:45:28,  4.01s/it]
  0%|          | 2091/569592 [1:43:53<691:29:00,  4.39s/it]
                                                           

  0%|          | 2091/569592 [1:43:53<691:29:00,  4.39s/it]
  0%|          | 2092/569592 [1:43:56<650:55:14,  4.13s/it]
                                                           

  0%|          | 2092/569592 [1:43:56<650:55:14,  4.13s/it]
  0%|          | 2093/569592 [1:44:01<679:14:56,  4.31s/it]
                                                           

  0%|          | 2093/569592 [1:44:01<679:14:56,  4.31s/it]
  0%|          | 2094/569592 [1:44:05<652:31:57,  4.14s/it]
                                                           

  0%|          | 2094/569592 [1:44:05<652:31:57,  4.14s/it]
  0%|          | 2095/569592 [1:44:08<602:05:27,  3.82s/it]
                                                           

  0%|          | 2095/569592 [1:44:08<602:05:27,  3.82s/it]
  0%|          | 2096/569592 [1:44:13<651:43:12,  4.13s/it]
                                                           

  0%|          | 2096/569592 [1:44:13<651:43:12,  4.13s/it]
  0%|          | 2097/569592 [1:44:17<679:05:52,  4.31s/it]
                                                           

  0%|          | 2097/569592 [1:44:17<679:05:52,  4.31s/it]
  0%|          | 2098/569592 [1:44:20<618:44:53,  3.93s/it]
                                                           

  0%|          | 2098/569592 [1:44:21<618:44:53,  3.93s/it]
  0%|          | 2099/569592 [1:44:24<584:42:59,  3.71s/it]
                                                           

  0%|          | 2099/569592 [1:44:24<584:42:59,  3.71s/it]
  0%|          | 2100/569592 [1:44:27<568:45:14,  3.61s/it]
                                                           

  0%|          | 2100/569592 [1:44:27<568:45:14,  3.61s/it]
  0%|          | 2101/569592 [1:44:30<548:06:22,  3.48s/it]
                                                           

  0%|          | 2101/569592 [1:44:30<548:06:22,  3.48s/it]
  0%|          | 2102/569592 [1:44:34<566:30:38,  3.59s/it]
                                                           

  0%|          | 2102/569592 [1:44:34<566:30:38,  3.59s/it]
  0%|          | 2103/569592 [1:44:38<581:50:01,  3.69s/it]
                                                           

  0%|          | 2103/569592 [1:44:38<581:50:01,  3.69s/it]
  0%|          | 2104/569592 [1:44:39<458:01:24,  2.91s/it]
                                                           

  0%|          | 2104/569592 [1:44:39<458:01:24,  2.91s/it]
  0%|          | 2105/569592 [1:44:44<545:45:15,  3.46s/it]
                                                           

  0%|          | 2105/569592 [1:44:44<545:45:15,  3.46s/it]
  0%|          | 2106/569592 [1:44:45<425:13:05,  2.70s/it]
                                                           

  0%|          | 2106/569592 [1:44:45<425:13:05,  2.70s/it]
  0%|          | 2107/569592 [1:44:46<342:06:28,  2.17s/it]
                                                           

  0%|          | 2107/569592 [1:44:46<342:06:28,  2.17s/it]
  0%|          | 2108/569592 [1:44:49<404:40:15,  2.57s/it]
                                                           

  0%|          | 2108/569592 [1:44:49<404:40:15,  2.57s/it]
  0%|          | 2109/569592 [1:44:50<334:38:38,  2.12s/it]
                                                           

  0%|          | 2109/569592 [1:44:50<334:38:38,  2.12s/it]
  0%|          | 2110/569592 [1:44:54<426:24:04,  2.71s/it]
                                                           

  0%|          | 2110/569592 [1:44:54<426:24:04,  2.71s/it]
  0%|          | 2111/569592 [1:44:58<485:48:49,  3.08s/it]
                                                           

  0%|          | 2111/569592 [1:44:58<485:48:49,  3.08s/it]
  0%|          | 2112/569592 [1:45:02<494:12:33,  3.14s/it]
                                                           

  0%|          | 2112/569592 [1:45:02<494:12:33,  3.14s/it]
  0%|          | 2113/569592 [1:45:03<391:33:04,  2.48s/it]
                                                           

  0%|          | 2113/569592 [1:45:03<391:33:04,  2.48s/it]
  0%|  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
        | 2114/569592 [1:45:03<318:30:01,  2.02s/it]
                                                           

  0%|          | 2114/569592 [1:45:03<318:30:01,  2.02s/it]
  0%|          | 2115/569592 [1:45:04<267:19:02,  1.70s/it]
                                                           

  0%|          | 2115/569592 [1:45:04<267:19:02,  1.70s/it]
  0%|          | 2116/569592 [1:45:05<232:56:58,  1.48s/it]
                                                           

  0%|          | 2116/569592 [1:45:05<232:56:58,  1.48s/it]
  0%|          | 2117/569592 [1:45:06<209:14:12,  1.33s/it]
                                                           

  0%|          | 2117/569592 [1:45:06<209:14:12,  1.33s/it]
  0%|          | 2118/569592 [1:45:07<190:41:53,  1.21s/it]
                                                           

  0%|          | 2118/569592 [1:45:07<190:41:53,  1.21s/it]
  0%|          | 2119/569592 [1:45:08<180:58:33,  1.15s/it]
                                                           

  0%|          | 2119/569592 [1:45:08<180:58:33,  1.15s/it]
  0%|          | 2120/569592 [1:45:11<272:58:36,  1.73s/it]
                                                           

  0%|          | 2120/569592 [1:45:11<272:58:36,  1.73s/it]
  0%|          | 2121/569592 [1:45:16<428:01:27,  2.72s/it]
                                                           

  0%|          | 2121/569592 [1:45:16<428:01:27,  2.72s/it]
  0%|          | 2122/569592 [1:45:18<379:54:54,  2.41s/it]
                                                           

  0%|          | 2122/569592 [1:45:18<379:54:54,  2.41s/it]
  0%|          | 2123/569592 [1:45:19<311:41:51,  1.98s/it]
                                                           

  0%|          | 2123/569592 [1:45:19<311:41:51,  1.98s/it]
  0%|          | 2124/569592 [1:45:21<325:26:49,  2.06s/it]
                                                           

  0%|          | 2124/569592 [1:45:21<325:26:49,  2.06s/it]
  0%|          | 2125/569592 [1:45:25<404:40:58,  2.57s/it]
                                                           

  0%|          | 2125/569592 [1:45:25<404:40:58,  2.57s/it]
  0%|          | 2126/569592 [1:45:29<457:25:49,  2.90s/it]
                                                           

  0%|          | 2126/569592 [1:45:29<457:25:49,  2.90s/it]
  0%|          | 2127/569592 [1:45:30<364:45:12,  2.31s/it]
                                                           

  0%|          | 2127/569592 [1:45:30<364:45:12,  2.31s/it]
  0%|          | 2128/569592 [1:45:31<320:08:18,  2.03s/it]
                                                           

  0%|          | 2128/569592 [1:45:31<320:08:18,  2.03s/it]
  0%|          | 2129/569592 [1:45:36<462:34:22,  2.93s/it]
                                                           

  0%|          | 2129/569592 [1:45:36<462:34:22,  2.93s/it]
  0%|          | 2130/569592 [1:45:39<471:02:48,  2.99s/it]
                                                           

  0%|          | 2130/569592 [1:45:39<471:02:48,  2.99s/it]
  0%|          | 2131/569592 [1:45:40<377:26:36,  2.39s/it]
                                                           

  0%|          | 2131/569592 [1:45:40<377:26:36,  2.39s/it]
  0%|          | 2132/569592 [1:45:42<352:22:21,  2.24s/it]
                                                           

  0%|          | 2132/569592 [1:45:42<352:22:21,  2.24s/it]
  0%|          | 2133/569592 [1:45:47<490:57:37,  3.11s/it]
                                                           

  0%|          | 2133/569592 [1:45:47<490:57:37,  3.11s/it]
  0%|          | 2134/569592 [1:45:50<466:03:02,  2.96s/it]
                                                           

  0%|          | 2134/569592 [1:45:50<466:03:02,  2.96s/it]
  0%|          | 2135/569592 [1:45:51<373:06:54,  2.37s/it]
                                                           

  0%|          | 2135/569592 [1:45:51<373:06:54,  2.37s/it]
  0%|          | 2136/569592 [1:45:53<345:40:04,  2.19s/it]
                                                           

/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93146440 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  0%|          | 2136/569592 [1:45:53<345:40:04,  2.19s/it]
  0%|          | 2137/569592 [1:45:58<481:15:13,  3.05s/it]
                                                           

  0%|          | 2137/569592 [1:45:58<481:15:13,  3.05s/it]
  0%|          | 2138/569592 [1:46:00<423:56:08,  2.69s/it]
                                                           

  0%|          | 2138/569592 [1:46:00<423:56:08,  2.69s/it]
  0%|          | 2139/569592 [1:46:01<342:37:00,  2.17s/it]
                                                           

  0%|          | 2139/569592 [1:46:01<342:37:00,  2.17s/it]
  0%|          | 2140/569592 [1:46:03<350:04:33,  2.22s/it]
                                                           

  0%|          | 2140/569592 [1:46:03<350:04:33,  2.22s/it]
  0%|          | 2141/569592 [1:46:08<484:47:14,  3.08s/it]
                                                           

  0%|          | 2141/569592 [1:46:08<484:47:14,  3.08s/it]
  0%|          | 2142/569592 [1:46:09<414:30:50,  2.63s/it]
                                                           

  0%|          | 2142/569592 [1:46:10<414:30:50,  2.63s/it]
  0%|          | 2143/569592 [1:46:11<359:29:20,  2.28s/it]
                                                           

  0%|          | 2143/569592 [1:46:11<359:29:20,  2.28s/it]
  0%|          | 2144/569592 [1:46:13<346:14:52,  2.20s/it]
                                                           

  0%|          | 2144/569592 [1:46:13<346:14:52,  2.20s/it]
  0%|          | 2145/569592 [1:46:18<494:14:31,  3.14s/it]
                                                           

  0%|          | 2145/569592 [1:46:18<494:14:31,  3.14s/it]
  0%|          | 2146/569592 [1:46:19<390:20:19,  2.48s/it]
                                                           

  0%|          | 2146/569592 [1:46:19<390:20:19,  2.48s/it]
  0%|          | 2147/569592 [1:46:21<375:28:02,  2.38s/it]
                                                           

  0%|          | 2147/569592 [1:46:21<375:28:02,  2.38s/i/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
t]
  0%|          | 2148/569592 [1:46:23<357:21:44,  2.27s/it]
                                                           

  0%|          | 2148/569592 [1:46:23<357:21:44,  2.27s/it]
  0%|          | 2149/569592 [1:46:29<510:33:26,  3.24s/it]
                                                           

  0%|          | 2149/569592 [1:46:29<510:33:26,  3.24s/it]
  0%|          | 2150/569592 [1:46:30<418:15:56,  2.65s/it]
                                                           

  0%|          | 2150/569592 [1:46:30<418:15:56,  2.65s/it]
  0%|          | 2151/569592 [1:46:33<424:48:49,  2.70s/it]
                                                           

  0%|          | 2151/569592 [1:46:33<424:48:49,  2.70s/it]
  0%|          | 2152/569592 [1:46:34<344:17:17,  2.18s/it]
                                                           

  0%|          | 2152/569592 [1:46:34<344:17:17,  2.18s/it]
  0%|          | 2153/569592 [1:46:40<507:54:54,  3.22s/it]
                                                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95332944 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
   

  0%|          | 2153/569592 [1:46:40<507:54:54,  3.22s/it]
  0%|          | 2154/569592 [1:46:42<465:12:01,  2.95s/it]
                                                           

  0%|          | 2154/569592 [1:46:42<465:12:01,  2.95s/it]
  0%|          | 2155/569592 [1:46:43<373:16:04,  2.37s/it]
                                                           

  0%|          | 2155/569592 [1:46:43<373:16:04,  2.37s/it]
  0%|          | 2156/569592 [1:46:44<305:47:08,  1.94s/it]
                                                           

  0%|          | 2156/569592 [1:46:44<305:47:08,  1.94s/it]
  0%|          | 2157/569592 [1:46:49<462:35:23,  2.93s/it]
                                                           

  0%|          | 2157/569592 [1:46:49<462:35:23,  2.93s/it]
  0%|          | 2158/569592 [1:46:52<456:40:02,  2.90s/it]
                                                           

  0%|          | 2158/569592 [1:46:52<456:40:02,  2.90s/it]
  0%|          | 2159/569592 [1:46:53<365:46:25,  2.32s/it]
                                                           

  0%|          | 2159/569592 [1:46:53<365:46:25,  2.32s/it]
  0%|          | 2160/569592 [1:46:54<318:41:49,  2.02s/it]
                                                           

  0%|          | 2160/569592 [1:46:54<318:41:49,  2.02s/it]
  0%|          | 2161/569592 [1:46:59<441:27:07,  2.80s/it]
                                                           

  0%|          | 2161/569592 [1:46:59<441:27:07,  2.80s/it]
  0%|          | 2162/569592 [1:47:02<471:23:33,  2.99s/it]
                                                           

  0%|          | 2162/569592 [1:47:02<471:23:33,  2.99s/it]
  0%|          | 2163/569592 [1:47:03<374:01:27,  2.37s/it]
                                                           

  0%|          | 2163/569592 [1:47:03<374:01:27,  2.37s/it]
  0%|          | 2164/569592 [1:47:04<318:09:58,  2.02s/it]
                                                           

  0%|          | 2164/569592 [1:47:04<318:09:58,  2.02s/it]
  0%|          | 2165/569592 [1:47:09<417:14:22,  2.65s/it]
                                                           

  0%|          | 2165/569592 [1:47:09<417:14:22,  2.65s/it]
  0%|          | 2166/569592 [1:47:14<534:15:15,  3.39s/it]
                                                           

  0%|          | 2166/569592 [1:47:14<534:15:15,  3.39s/it]
  0%|          | 2167/569592 [1:47:15<416:43:37,  2.64s/it]
                                                           

  0%|          | 2167/569592 [1:47:15<416:43:37,  2.64s/it]
  0%|          | 2168/569592 [1:47:16<353:15:39,  2.24s/it]
                                                           

  0%|          | 2168/569592 [1:47:16<353:15:39,  2.24s/it]
  0%|          | 2169/569592 [1:47:20<425:05:44,  2.70s/it]
                                                           

  0%|          | 2169/569592 [1:47:20<425:05:44,  2.70s/it]
  0%|          | 2170/569592 [1:47:21<360:08:25,  2.28s/it]
                                                           

  0%|          | 2170/569592 [1:47:21<360:08:25,  2.28s/it]
  0%|          | 2171/569592 [1:47:22<297:23:30,  1.89s/it]
                                                           

  0%|          | 2171/569592 [1:47:22<297:23:30,  1.89s/it]
  0%|          | 2172/569592 [1:47:24<309:04:06,  1.96s/it]
                                                           

  0%|          | 2172/569592 [1:47:24<309:04:06,  1.96s/it]
  0%|          | 2173/569592 [1:47:28<418:08:04,  2.65s/it]
                                                           

  0%|          | 2173/569592 [1:47:28<418:08:04,  2.65s/it]
  0%|          | 2174/569592 [1:47:32<478:03:28,  3.03s/it]
                                                           

  0%|          | 2174/569592 [1:47:32<478:03:28,  3.03s/it]
  0%|          | 2175/569592 [1:47:33<379:33:17,  2.41s/it]
                                                           

  0%|          | 2175/569592 [1:47:33<379:33:17,  2.41s/it]
  0%|          | 2176/569592 [1:47:35<374:06:50,  2.37s/it]
                                                           

  0%|          | 2176/569592 [1:47:35<374:06:50,  2.37s/it]
  0%|          | 2177/569592 [1:47:38<404:58:06,  2.57s/it]
                                                           

  0%|          | 2177/569592 [1:47:39<404:58:06,  2.57s/it]
  0%|          | 2178/569592 [1:47:42<456:22:05,  2.90s/it]
                                                           

  0%|          | 2178/569592 [1:47:42<456:22:05,  2.90s/it]
  0%|          | 2179/569592 [1:47:43<364:53:58,  2.32s/it]
                                                           

  0%|          | 2179/569592 [1:47:43<364:53:58,  2.32s/it]
  0%|          | 2180/569592 [1:47:45<321:33:00,  2.04s/it]
                                                           

  0%|          | 2180/569592 [1:47:45<321:33:00,  2.04s/it]
  0%|          | 2181/569592 [1:47:49<421:11:17,  2.67s/it]
                                                           

  0%|          | 2181/569592 [1:47:49<421:11:17,  2.67s/it]
  0%|          | 2182/569592 [1:47:53<493:37:30,  3.13s/it]
                                                           

  0%|          | 2182/569592 [1:47:53<493:37:30,  3.13s/it]
  0%|          | 2183/569592 [1:47:58<595:31:47,  3.78s/it]
                                                           

  0%|          | 2183/569592 [1:47:58<595:31:47,  3.78s/it]
  0%|          | 2184/569592 [1:48:03<639:04:35,  4.05s/it]
                                                           

  0%|          | 2184/569592 [1:48:03<639:04:35,  4.05s/it]
  0%|          | 2185/569592 [1:48:07<624:06:36,  3.96s/it]
                                                           

  0%|          | 2185/569592 [1:48:07<624:06:36,  3.96s/it]
  0%|          | 2186/569592 [1:48:11<633:28:49,  4.02s/it]
                                                           

  0%|          | 2186/569592 [1:48:11<633:28:49,  4.02s/it]
  0%|          | 2187/569592 [1:48:14<593:06:58,  3.76s/it]
                                                           

  0%|          | 2187/569592 [1:48:14<593:06:58,  3.76s/it]
  0%|          | 2188/569592 [1:48:17<562:56:49,  3.57s/it]
                                                           

  0%|          | 2188/569592 [1:48:17<562:56:49,  3.57s/it]
  0%|          | 2189/569592 [1:48:22<616:51:57,  3.91s/it]
                                                           

  0%|          | 2189/569592 [1:48:22<616:51:57,  3.91s/it]
  0%|          | 2190/569592 [1:48:25<569:19:49,  3.61s/it]
                                                           

  0%|          | 2190/569592 [1:48:25<569:19:49,  3.61s/it]
  0%|          | 2191/569592 [1:48:28<565:24:54,  3.59s/it]
                                                           

  0%|          | 2191/569592 [1:48:28<565:24:54,  3.59s/it]
  0%|          | 2192/569592 [1:48:32<572:56:07,  3.64s/it]
                                                           

  0%|          | 2192/569592 [1:48:32<572:56:07,  3.64s/it]
  0%|          | 2193/569592 [1:48:36<584:33/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93641436 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:19,  3.71s/it]
                                                           

  0%|          | 2193/569592 [1:48:36<584:33:19,  3.71s/it]
  0%|          | 2194/569592 [1:48:40<598:10:00,  3.80s/it]
                                                           

  0%|          | 2194/569592 [1:48:40<598:10:00,  3.80s/it]
  0%|          | 2195/569592 [1:48:41<460:48:04,  2.92s/it]
                                                           

  0%|          | 2195/569592 [1:48:41<460:48:04,  2.92s/it]
  0%|          | 2196/569592 [1:48:45<541:31:04,  3.44s/it]
                                                           

  0%|          | 2196/569592 [1:48:45<541:31:04,  3.44s/it]
  0%|          | 2197/569592 [1:48:50<605:40:49,  3.84s/it]
                                                           

  0%|          | 2197/569592 [1:48:50<605:40:49,  3.84s/it]
  0%|          | 2198/569592 [1:48:55<663:16:57,  4.21s/it]
                                                           

  0%|          | 2198/569592 [1:48:55<663:16:57,  4.21s/it]
  0%|          | 2199/569592 [1:49:00<693:28:41,  4.40s/it]
                                                           

  0%|          | 2199/569592 [1:49:00<693:28:41,  4.40s/it]
  0%|          | 2200/569592 [1:49:05<704:05:51,  4.47s/it]
                                                           

  0%|          | 2200/569592 [1:49:05<704:05:51,  4.47s/it]
  0%|          | 2201/569592 [1:49:10<723:01:08,  4.59s/it]
                                                           

  0%|          | 2201/569592 [1:49:10<723:01:08,  4.59s/it]
  0%|          | 2202/569592 [1:49:14<725:04:47,  4.60s/it]
                                                           

  0%|          | 2202/569592 [1:49:14<725:04:47,  4.60s/it]
  0%|          | 2203/569592 [1:49:19<740:58:59,  4.70s/it]
                                                           

  0%|          | 2203/569592 [1:49:19<740:58:59,  4.70s/it]
  0%|          | 2204/569592 [1:49:23<684:26:14,  4.34s/it]
                                                           

  0%|          | 2204/569592 [1:49:23<684:26:14,  4.34s/it]
  0%|          | 2205/569592 [1:49:27<671:59:25,  4.26s/it]
                                                           

  0%|          | 2205/569592 [1:49:27<671:59:25,  4.26s/it]
  0%|          | 2206/569592 [1:49:31<657:40:26,  4.17s/it]
                                                           

  0%|          | 2206/569592 [1:49:31<657:40:26,  4.17s/it]
  0%|          | 2207/569592 [1:49:37<751:43:01,  4.77s/it]
                                                           

  0%|          | 2207/569592 [1:49:37<751:43:01,  4.77s/it]
  0%|          | 2208/569592 [1:49:41<748:15:07,  4.75s/it]
                                                           

  0%|          | 2208/569592 [1:49:42<748:15:07,  4.75s/it]
  0%|          | 2209/569592 [1:49:46<715:54:16,  4.54s/it]
                                                           

  0%|          | 2209/569592 [1:49:46<715:54:16,  4.54s/it]
  0%|          | 2210/569592 [1:49:50<724:46:40,  4.60s/it]
                                                           

  0%|          | 2210/569592 [1:49:50<724:46:40,  4.60s/it]
  0%|          | 2211/569592 [1:49:55<714:05:56,  4.53s/it]
                                                           

  0%|          | 2211/569592 [1:49:55<714:05:56,  4.53s/it]
  0%|          | 2212/569592 [1:49:56<541:33:38,  3.44s/it]
                                                           

  0%|          | 2212/569592 [1:49:56<541:33:38,  3.44s/it]
  0%|          | 2213/569592 [1:50:00<607:32:21,  3.85s/it]
                                                           

  0%|          | 2213/569592 [1:50:00<607:32:21,  3.85s/it]
  0%|          | 2214/569592 [1:50:04<585:48:44,  3.72s/it]
                                                           

  0%|          | 2214/569592 [1:50:04<585:48:44,  3.72s/it]
  0%|          | 2215/569592 [1:50:07<562:48:46,  3.57s/it]
                                                           

  0%|          | 2215/569592 [1:50:07<562:48:46,  3.57s/it]
  0%|          | 2216/569592 [1:50:10<536:42:36,  3.41s/it]
                                                           

  0%|          | 2216/569592 [1:50:10<536:42:36,  3.41s/it]
  0%|          | 2217/569592 [1:50:15<615:41:02,  3.91s/it]
                                                           

  0%|          | 2217/569592 [1:50:15<615:41:02,  3.91s/it]
  0%|          | 2218/569592 [1:50:20<670:49:12,  4.26s/it]
                                                           

  0%|          | 2218/569592 [1:50:20<670:49:12,  4.26s/it]
  0%|          | 2219/569592 [1:50:21<511:32:45,  3.25s/it]
                                                           

  0%|          | 2219/569592 [1:50:21<511:32:45,  3.25s/it]
  0%|          | 2220/569592 [1:50:24<511:38:11,  3.25s/it]
                                                           

  0%|          | 2220/569592 [1:50:24<511:38:11,  3.25s/it]
  0%|          | 2221/569592 [1:50:29<587:26:32,  3.73s/it]
                                                           

  0%|          | 2221/569592 [1:50:29<587:26:32,  3.73s/it]
  0%|          | 2222/569592 [1:50:32<558:49:13,  3.55s/it]
                                                           

  0%|          | 2222/569592 [1:50:32<558:49:13,  3.55s/it]
  0%|          | 2223/569592 [1:50:33<433:21:45,  2.75s/it]
                                                           

  0%|          | 2223/569592 [1:50:33<433:21:45,  2.75s/it]
  0%|          | 2224/569592 [1:50:34<347:45:14,  2.21s/it]
                                                           

  0%|          | 2224/569592 [1:50:34<347:45:14,  2.21s/it]
  0%|          | 2225/569592 [1:50:38<411:18:22,  2.61s/it]
                                                           

  0%|          | 2225/569592 [1:50:38<411:18:22,  2.61s/it]
  0%|          | 2226/569592 [1:50:42<474:39:21,  3.01s/it]
                                                           

  0%|          | 2226/569592 [1:50:42<474:39:21,  3.01s/it]
  0%|          | 2227/569592 [1:50:43<377:35:40,  2.40s/it]
                                                           

  0%|          | 2227/569592 [1:50:43<377:35:40,  2.40s/it]
  0%|          | 2228/569592 [1:50:47<486:55:17,  3.09s/it]
                                                           

  0%|          | 2228/569592 [1:50:47<486:55:17,  3.09s/it]
  0%|          | 2229/569592 [1:50:51<497:09:00,  3.15s/it]
                                                           

  0%|          | 2229/569592 [1:50:51<497:09:00,  3.15s/it]
  0%|          | 2230/569592 [1:50:52<392:59:11,  2.49s/it]
                                                           

  0%|          | 2230/569592 [1:50:52<392:59:11,  2.49s/it]
  0%|          | 2231/569592 [1:50:53<321:03:14,  2.04s/it]
                                                           

  0%|          | 2231/569592 [1:50:53<321:03:14,  2.04s/it]
  0%|          | 2232/569592 [1:50:53<269:42:57,  1.71s/it]
                                                           

  0%|          | 2232/569592 [1:50:53<269:42:57,  1.71s/it]
  0%|          | 2233/569592 [1:50:54<235:06:20,  1.49s/it]
                                                           

  0%|          | 2233/569592 [1:50:54<235:06:20,  1.49s/it]
  0%|          | 2234/569592 [1:50:55<210:23:58,  1.34s/it]
                                                           

  0%|          | 2234/569592 [1:50:55<210:23:58,  1.34s/it]
  0%|          | 2235/569592 [1:50:56<190:48:29,  1.21s/it]
                                                           

  0%|          | 2235/569592 [1:50:56<190:48:29,  1.21s/it]
  0%|          | 2236/569592 [1:50:57<185:27:47,  1.18s/it]
                                                           

  0%|          | 2236/569592 [1:50:57<185:27:47,  1.18s/it]
  0%|          | 2237/569592 [1:51:00<249:29:07,  1.58s/it]
                                                           

  0%|          | 2237/569592 [1:51:00<249:29:07,  1.58s/it]
  0%|          | 2238/569592 [1:51:04<378:52:03,  2.40s/it]
                               /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96855372 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                            

  0%|          | 2238/569592 [1:51:04<378:52:03,  2.40s/it]
  0%|          | 2239/569592 [1:51:06<370:23:28,  2.35s/it]
                                                           

  0%|          | 2239/569592 [1:51:07<370:23:28,  2.35s/it]
  0%|          | 2240/569592 [1:51:08<307:22:45,  1.95s/it]
                                                           

  0%|          | 2240/569592 [1:51:08<307:22:45,  1.95s/it]
  0%|          | 2241/569592 [1:51:10<336:08:39,  2.13s/it]
                                                           

  0%|          | 2241/569592 [1:51:10<336:08:39,  2.13s/it]
  0%|          | 2242/569592 [1:51:16<493:59:32,  3.13s/it]
                                                           

  0%|          | 2242/569592 [1:51:16<493:59:32,  3.13s/it]
  0%|          | 2243/569592 [1:51:17<399:00:55,  2.53s/it]
                                                           

  0%|          | 2243/569592 [1:51:17<399:00:55,  2.53s/it]
  0%|          | 2244/569592 [1:51:18<325:02:44,  2.06s/it]
                                                           

  0%|          | 2244/569592 [1:51:18<325:02:44,  2.06s/it]
  0%|          | 2245/569592 [1:51:20<361:32:00,  2.29s/it]
                                                           

  0%|          | 2245/569592 [1:51:21<361:32:00,  2.29s/it]
  0%|          | 2246/569592 [1:51:25<445:17:02,  2.83s/it]
                                                           

  0%|          | 2246/569592 [1:51:25<445:17:02,  2.83s/it]
  0%|          | 2247/569592 [1:51:27<408:57:51,  2.60s/it]
                                                           

  0%|          | 2247/569592 [1:51:27<408:57:51,  2.60s/it]
  0%|          | 2248/569592 [1:51:28<336:01:09,  2.13s/it]
                                                           

  0%|          | 2248/569592 [1:51:28<336:01:09,  2.13s/it]
  0%|          | 2249/569592 [1:51:31<389:29:55,  2.47s/it]
                                                           

  0%|          | 2249/569592 [1:51:31<389:29:55,  2.47s/it]
  0%|          | 2250/569592 [1:51:35<454:58:07,  2.89s/it]
                                                           

  0%|          | 2250/569592 [1:51:35<454:58:07,  2.89s/it]
  0%|          | 2251/569592 [1:51:37<407:31:09,  2.59s/it]
                                                           

  0%|          | 2251/569592 [1:51:37<407:31:09,  2.59s/it]
  0%|          | 2252/569592 [1:51:38<330:34:15,  2.10s/it]
                                                           

  0%|          | 2252/569592 [1:51:38<330:34:15,  2.10s/it]
  0%|          | 2253/569592 [1:51:43<475:44:07,  3.02s/it]
                                                           

  0%|          | 2253/569592 [1:51:43<475:44:07,  3.02s/it]
  0%|          | 2254/569592 [1:51:45<441:04:18,  2.80s/it]
                                                           

  0%|          | 2254/569592 [1:51:45<441:04:18,  2.80s/it]
  0%|          | 2255/569592 [1:51:47<398:37:29,  2.53s/it]
                                                           

  0%|          | 2255/569592 [1:51:47<398:37:29,  2.53s/it]
  0%|          | 2256/569592 [1:51:48<323:42:29,  2.05s/it]
                                                           

  0%|          | 2256/569592 [1:51:48<323:42:29,  2.05s/it]
  0%|          | 2257/569592 [1:51:52<407:52:23,  2.59s/it]
                                                           

  0%|          | 2257/569592 [1:51:52<407:52:23,  2.59s/it]
  0%|          | 2258/569592 [1:51:55<442:19:22,  2.81s/it]
                                                           

  0%|          | 2258/569592 [1:51:55<442:19:22,  2.81s/it]
  0%|          | 2259/569592 [1:51:57<415:35:35,  2.64s/it]
                                                           

  0%|          | 2259/569592 [1:51:57<415:35:35,  2.64s/it]
  0%|          | 2260/569592 [1:51:59<370:05:01,  2.35s/it]
                                                           

  0%|          | 2260/569592 [1:51:59<370:05:01,  2.35s/it]
  0%|          | 2261/569592 [1:52:02<405:50:23,  2.58s/it]
                                                           

  0%|          | 2261/569592 [1:52:02<405:50:23,  2.58s/it]
  0%|          | 2262/569592 [1:52:07<515:44:55,  3.27s/it]
                                                           

  0%|          | 2262/569592 [1:52:07<515:44:55,  3.27s/it]
  0%|          | 2263/569592 [1:52:09<466:07:59,  2.96s/it]
                                                           

  0%|          | 2263/569592 [1:52:09<466:07:59,  2.96s/it]
  0%|          | 2264/569592 [1:52:10<371:43:34,  2.36s/it]
                                                           

  0%|          | 2264/569592 [1:52:10<371:43:34,  2.36s/it]
  0%|          | 2265/569592 [1:52:13<386:44:25,  2.45s/it]
                                                           

  0%|          | 2265/569592 [1:52:13<386:44:25,  2.45s/it]
  0%|          | 2266/569592 [1:52:17<473:24:10,  3.00s/it]
                                                           

  0%|          | 2266/569592 [1:52:17<473:24:10,  3.00s/it]
  0%|          | 2267/569592 [1:52:19<439:16:13,  2.79s/it]
                                                           

  0%|          | 2267/569592 [1:52:19<439:16:13,  2.79s/it]
  0%|          | 2268/569592 [1:52:20<352:16:10,  2.24s/it]
                                                           

  0%|          | 2268/569592 [1:52:20<352:16:10,  2.24s/it]
  0%|          | 2269/569592 [1:52:23<365:06:39,  2.32s/it]
                                                           

  0%|          | 2269/569592 [1:52:23<365:06:39,  2.32s/it]
  0%|          | 2270/569592 [1:52:26<418:24:01,  2.66s/it]
                                                           

  0%|          | 2270/569592 [1:52:27<418:24:01,  2.66s/it]
  0%|          | 2271/569592 [1:52:29<441:50:36,  2.80s/it]
                                                           

  0%|          | 2271/569592 [1:52:29<441:50:36,  2.80s/it]
  0%|          | 2272/569592 [1:52:31<402:13:16,  2.55s/it]
                                                           

  0%|          | 2272/569592 [1:52:31<402:13:16,  2.55s/it]
  0%|          | 2273/569592 [1:52:33<362:02:57,  2.30s/it]
                                                           

  0%|          | 2273/569592 [1:52:33<362:02:57,  2.30s/it]
  0%|          | 2274/569592 [1:52:38<476:41:17,  3.02s/it]
                                                           

  0%|          | 2274/569592 [1:52:38<476:41:17,  3.02s/it]
  0%|          | 2275/569592 [1:52:39<411:04:25,  2.61s/it]
                                                           

  0%|          | 2275/569592 [1:52:40<411:04:25,  2.61s/it]
  0%|          | 2276/569592 [1:52:41<378:50:21,  2.40s/it]
                                                           

  0%|          | 2276/569592 [1:52:41<378:50:21,  2.40s/it]
  0%|          | 2277/569592 [1:52:44<381:12:46,  2.42s/it]
                                                           

  0%|          | 2277/569592 [1:52:44<381:12:46,  2.42s/it]
  0%|          | 2278/569592 [1:52:47<398:04:57,  2.53s/it]
                                                           

  0%|          | 2278/569592 [1:52:47<398:04:57,  2.53s/it]
  0%|          | 2279/569592 [1:52:50<441:38:10,  2.80s/it]
                                                           

  0%|          | 2279/569592 [1:52:50<441:38:10,  2.80s/it]
  0%|          | 2280/569592 [1:52:51<358:00:23,  2.27s/it]
                                                           

  0%|          | 2280/569592 [1:52:51<358:00:23,  2.27s/it]
  0%|          | 2281/569592 [1:52:54<398:00:53,  2.53s/it]
                                                           

  0%|          | 2281/569592 [1:52:54<398:00:53,  2.53s/it]
  0%|          | 2282/569592 [1:52:59<520:21:40,  3.30s/it]
                                                           

  0%|          | 2282/569592 [1:52:59<520:21:40,  3.30s/it]
  0%|          | 2283/569592 [1:53:00<409:46:01,  2.60s/it]
                                                           

  0%|          | 2283/569592 [1:53:00<409:46:01,  2.60s/it]
  0%|          | 2284/569592 [1:53:01<332:04:16,  2.11s/it]
                                                           

  0%|          | 2284/569592 [1:53:01<332:04:16,  2.11s/it]
  0%|          | 2285/569592 [1:53:03<330:38:37,  2.10s/it]
                                                           

  0%|          | 2285/569592 [1:53:03<330:38:37,  2.10s/it]
  0%|          | 2286/569592 [1:53:07<405:31:11,  2.57s/it]
                                                           

  0%|          | 2286/569592 [1:53:07<405:31:11,  2.57s/it]
  0%|          | 2287/569592 [1:53:11<448:25:14,  2.85s/it]
                                                           

  0%|          | 2287/569592 [1:53:11<448:25:14,  2.85s/it]
  0%|          | 2288/569592 [1:53:12<363:19:33,  2.31s/it]
                                                           

  0%|          | 2288/569592 [1:53:12<363:19:33,  2.31s/it]
  0%|          | 2289/569592 [1:53:15<421:31:59,  2.67s/it]
                                                           

  0%|          | 2289/569592 [1:53:15<421:31:59,  2.67s/it]
  0%|          | 2290/569592 [1:53:17<386:17:02,  2.45s/it]
                                                           

  0%|          | 2290/569592 [1:53:17<386:17:02,  2.45s/it]
  0%|          | 2291/569592 [1:53:22<512:13:12,  3.25s/it]
                                                           

  0%|          | 2291/569592 [1:53:22<512:13:12,  3.25s/it]
  0%|          | 2292/569592 [1:53:23<404:22:11,  2.57s/it]
                                                           

  0%|          | 2292/569592 [1:53:23<404:22:11,  2.57s/it]
  0%|          | 2293/569592 [1:53:25<376:10:55,  2.39s/it]
                                                           

  0%|          | 2293/569592 [1:53:25<376:10:55,  2.39s/it]
  0%|          | 2294/569592 [1:53:27<360:38:44,  2.29s/it]
                                                           

  0%|          | 2294/569592 [1:53:27<360:38:44,  2.29s/it]
  0%|          | 2295/569592 [1:53:34<558:30:17,  3.54s/it]
                                                           

  0%|          | 2295/569592 [1:53:34<558:30:17,  3.54s/it]
  0%|          | 2296/569592 [1:53:35<434:17:36,  2.76s/it]
                                                           

  0%|          | 2296/569592 [1:53:35<434:17:36,  2.76s/it]
  0%|          | 2297/569592 [1:53:39<536:34:12,  3.41s/it]
                                                           

  0%|          | 2297/569592 [1:53:39<536:34:12,  3.41s/it]
  0%|          | 2298/569592 [1:53:44<570:04:42,  3.62s/it]
                                                           

  0%|          | 2298/569592 [1:53:44<570:04:42,  3.62s/it]
  0%|          | 2299/569592 [1:53:47<584:47:59,  3.71s/it]
                                                           

  0%|          | 2299/569592 [1:53:48<584:47:59,  3.71s/it]
  0%|          | 2300/569592 [1:53:51<554:32:41,  3.52s/it]
                                                           

  0%|          | 2300/569592 [1:53:51<554:32:41,  3.52s/it]
  0%|          | 2301/569592 [1:53:56<638:26:24,  4.05s/it]
                                                           

  0%|          | 2301/569592 [1:53:56<638:26:24,  4.05s/it]
  0%|          | 2302/569592 [1:53:57<489:28:22,  3.11s/it]
                                                           

  0%|          | 2302/569592 [1:53:57<489:28:22,  3.11s/it]
  0%|          | 2303/569592 [1:54:00<489:56:40,  3.11s/it]
                                                           

  0%|          | 2303/569592 [1:54:00<489:56:40,  3.11s/it]
  0%|          | 2304/569592 [1:54:05<571:24:40,  3.63s/it]
                                                           

  0%|          | 2304/569592 [1:54:05<571:24:40,  3.63s/it]
  0%|          | 2305/569592 [1:54:10<641:38:57,  4.07s/it]
                                                           

  0%|          | 2305/569592 [1:54:10<641:38:57,  4.07s/it]
  0%|          | 2306/569592 [1:54:14<634:03:14,  4.02s/it]
                                                           

  0%|          | 2306/569592 [1:54:14<634:03:14,  4.02s/it]
  0%|          | 2307/569592 [1:54:19<669:28:43,  4.25s/it]
                                                           

  0%|          | 2307/569592 [1:54:19<669:28:43,  4.25s/it]
  0%|          | 2308/569592 [1:54:23<688:22:09,  4.37s/it]
                                                           

  0%|          | 2308/569592 [1:54:23<688:22:09,  4.37s/it]
  0%|          | 2309/569592 [1:54:28<701:00:27,  4.45s/it]
                                                           

  0%|          | 2309/569592 [1:54:28<701:00:27,  4.45s/it]
  0%|          | 2310/569592 [1:54:32<703:52:22,  4.47s/it]
                                                           

  0%|          | 2310/569592 [1:54:32<703:52:22,  4.47s/it]
  0%|          | 2311/569592 [1:54:39<819:57:34,  5.20s/it]
                                                           

  0%|          | 2311/569592 [1:54:39<819:57:34,  5.20s/it]
  0%|          | 2312/569592 [1:54:44<791:30:08,  5.02s/it]
                                                           

  0%|          | 2312/569592 [1:54:44<791:30:08,  5.02s/it]
  0%|          | 2313/569592 [1:54:48<774:50:32,  4.92s/it]
                                                           

  0%|          | 2313/569592 [1:54:49<774:50:32,  4.92s/it]
  0%|          | 2314/569592 [1:54:52<705:43:45,  4.48s/it]
                                                           

  0%|          | 2314/569592 [1:54:52<705:43:45,  4.48s/it]
  0%|          | 2315/569592 [1:54:57<717:13:27,  4.55s/it]
                                                           

  0%|          | 2315/569592 [1:54:57<717:13:27,  4.55s/it]
  0%|          | 2316/569592 [1:55:01<686:17:11,  4.36s/it]
                                                           

  0%|          | 2316/569592 [1:55:01<686:17:11,  4.36s/it]
  0%|          | 2317/569592 [1:55:04<643:36:40,  4.08s/it]
                                                           

  0%|          | 2317/569592 [1:55:04<643:36:40,  4.08s/it]
  0%|          | 2318/569592 [1:55:08<624:52:20,  3.97s/it]
                                                           

  0%|          | 2318/569592 [1:55:08<624:52:20,  3.97s/it]
  0%|          | 2319/569592 [1:55:13<673:21:04,  4.27s/it]
                                                           

  0%|          | 2319/569592 [1:55:13<673:21:04,  4.27s/it]
  0%|          | 2320/569592 [1:55:18<699:29:52,  4.44s/it]
                                                           

  0%|          | 2320/569592 [1:55:18<699:29:52,  4.44s/it]
  0%|          | 2321/569592 [1:55:21<636:59:21,  4.04s/it]
                                                           

  0%|          | 2321/569592 [1:55:21<636:59:21,  4.04s/it]
  0%|          | 2322/569592 [1:55:24<620:06:09,  3.94s/it]
                                                           

  0%|          | 2322/569592 [1:55:24<620:06:09,  3.94s/it]
  0%|          | 2323/569592 [1:55:29<678:04:28,  4.30s/it]
                                                           

  0%|          | 2323/569592 [1:55:30<678:04:28,  4.30s/it]
  0%|          | 2324/569592 [1:55:35<712:08:39,  4.52s/it]
                                                           

  0%|          | 2324/569592 [1:55:35<712:08:39,  4.52s/it]
  0%|          | 2325/569592 [1:55:39<700:26:19,  4.45s/it]
                                                           

  0%|          | 2325/569592 [1:55:39<700:26:19,  4.45s/it]
  0%|          | 2326/569592 [1:55:44<713:53:31,  4.53s/it]
                                                           

  0%|          | 2326/569592 [1:55:44<713:53:31,  4.53s/it]
  0%|          | 2327/569592 [1:55:47<667:54:43,  4.24s/it]
                                                           

  0%|          | 2327/569592 [1:55:47<667:54:43,  4.24s/it]
  0%|          | 2328/569592 [1:55:51<637:29:45,  4.05s/it]
                                                           

  0%|          | 2328/569592 [1:55:51<637:29:45,  4.05s/it]
  0%|          | 2329/569592 [1:55:54<584:30:19,  3.71s/it]
                                                           

  0%|          | 2329/569592 [1:55:54<584:30:19,  3.71s/it]
  0%|          | 2330/569592 [1:55:57<554:56:03,  3.52s/it]
                                                           

  0%|          | 2330/569592 [1:55:57<554:56:03,  3.52s/it]
  0%|          | 2331/569592 [1:56:00<555:15:18,  3.52s/it]
                                                           

  0%|          | 2331/569592 [1:56:00<555:15:18,  3.52s/it]
  0%|          | 2332/569592 [1:56:01<432:31:51,  2.74s/it]
                                                           

  0%|          | 2332/569592 [1:56:02<432:31:51,  2.74s/it]
  0%|          | 2333/569592 [1:56:06<531:35:42,  3.37s/it]
                                                           

  0%|          | 2333/569592 [1:56:06<531:35:42,  3.37s/it]
  0%|          | 2334/569592 [1:56:11<600:51:26,  3.81s/it]
                                                           

  0%|          | 2334/569592 [1:56:11<600:51:26,  3.81s/it]
  0%|          | 2335/569592 [1:56:15<632:59:52,  4.02s/it]
                                                           

  0%|          | 2335/569592 [1:56:15<632:59:52,  4.02s/it]
  0%|          | 2336/569592 [1:56:19<596:13:48,  3.78s/it]
                                                           

  0%|          | 2336/569592 [1:56:19<596:13:48,  3.78s/it]
  0%|          | 2337/569592 [1:56:19<459:49:53,  2.92s/it]
                                                           

  0%|          | 2337/569592 [1:56:19<459:49:53,  2.92s/it]
  0%|          | 2338/569592 [1:56:23<486:13:47,  3.09s/it]
                                                           

  0%|          | 2338/569592 [1:56:23<486:13:47,  3.09s/it]
  0%|          | 2339/569592 [1:56:28<575:06:59,  3.65s/it]
                                                           

  0%|          | 2339/569592 [1:56:28<575:06:59,  3.65s/it]
  0%|          | 2340/569592 [1:56:31<546:58:24,  3.47s/it]
 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93913600 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                          

  0%|          | 2340/569592 [1:56:31<546:58:24,  3.47s/it]
  0%|          | 2341/569592 [1:56:32<425:24:07,  2.70s/it]
                                                           

  0%|          | 2341/569592 [1:56:32<425:24:07,  2.70s/it]
  0%|          | 2342/569592 [1:56:33<343:10:09,  2.18s/it]
                                                           

  0%|          | 2342/569592 [1:56:33<343:10:09,  2.18s/it]
  0%|          | 2343/569592 [1:56:34<285:52:59,  1.81s/it]
                                                           

  0%|          | 2343/569592 [1:56:34<285:52:59,  1.81s/it]
  0%|          | 2344/569592 [1:56:35<245:37:30,  1.56s/it]
                                                           

  0%|          | 2344/569592 [1:56:35<245:37:30,  1.56s/it]
  0%|          | 2345/569592 [1:56:36<217:11:03,  1.38s/it]
                                                           

  0%|          | 2345/569592 [1:56:36<217:11:03,  1.38s/it]
  0%|          | 2346/569592 [1:56:41<388:48:28,  2.47s/it]
                                                           

  0%|          | 2346/569592 [1:56:41<388:48:28,  2.47s/it]
  0%|          | 2347/569592 [1:56:44<447:53:58,  2.84s/it]
                                                           

  0%|          | 2347/569592 [1:56:44<447:53:58,  2.84s/it]
  0%|          | 2348/569592 [1:56:45<360:55:38,  2.29s/it]
                                                           

  0%|          | 2348/569592 [1:56:45<360:55:38,  2.29s/it]
  0%|          | 2349/569592 [1:56:46<296:53:59,  1.88s/it]
                                                           

  0%|          | 2349/569592 [1:56:46<296:53:59,  1.88s/it]
  0%|          | 2350/569592 [1:56:47<253:55:07,  1.61s/it]
                                                           

  0%|          | 2350/569592 [1:56:47<253:55:07,  1.61s/it]
  0%|          | 2351/569592 [1:56:48<222:43:51,  1.41s/it]
                                                           

  0%|          | 2351/569592 [1:56:48<222:43:51,  1.41s/it]
  0%|          | 2352/569592 [1:56:51<274:25:32,  1.74s/it]
                                                           

  0%|          | 2352/569592 [1:56:51<274:25:32,  1.74s/it]
  0%|          | 2353/569592 [1:56:55<404:36:38,  2.57s/it]
                                                           

  0%|          | 2353/569592 [1:56:55<404:36:38,  2.57s/it]
  0%|          | 2354/569592 [1:56:56<329:32:07,  2.09s/it]
                                                           

  0%|          | 2354/569592 [1:56:56<329:32:07,  2.09s/it]
  0%|          | 2355/569592 [1:56:57<276:18:35,  1.75s/it]
                                                           

  0%|          | 2355/569592 [1:56:57<276:18:35,  1.75s/it]
  0%|          | 2356/569592 [1:57:02<411:58:01,  2.61s/it]
                                                           

  0%|          | 2356/569592 [1:57:02<411:58:01,  2.61s/it]
  0%|          | 2357/569592 [1:57:05<438:16:01,  2.78s/it]
                                                           

  0%|          | 2357/569592 [1:57:05<438:16:01,  2.78s/it]
  0%|          | 2358/569592 [1:57:06<357:18:32,  2.27s/it]
                                                           

  0%|          | 2358/569592 [1:57:06<357:18:32,  2.27s/it]
  0%|          | 2359/569592 [1:57:07<295:16:38,  1.87s/it]
                                                           

  0%|          | 2359/569592 [1:57:07<295:16:38,  1.87s/it]
  0%|          | 2360/569592 [1:57:12<422:03:34,  2.68s/it]
                                                           

  0%|          | 2360/569592 [1:57:12<422:03:34,  2.68s/it]
  0%|          | 2361/569592 [1:57:15<459:19:42,  2.92s/it]
                                                           

  0%|          | 2361/569592 [1:57:15<459:19:42,  2.92s/it]
  0%|          | 2362/569592 [1:57:16<367:15:45,  2.33s/it]
                                                           

  0%|          | 2362/569592 [1:57:16<367:15:45,  2.33s/it]
  0%|          | 2363/569592 [1:57:17<309:50:13,  1.97s/it]
                                                           

  0%|          | 2363/569592 [1:57:17<309:50:13,  1.97s/it]
  0%|          | 2364/569592 [1:57:23<485:14:34,  3.08s/it]
                                                           

  0%|          | 2364/569592 [1:57:23<485:14:34,  3.08s/it]
  0%|          | 2365/569592 [1:57:25<454:31:30,  2.88s/it]
                                                           

  0%|          | 2365/569592 [1:57:25<454:31:30,  2.88s/it]
  0%|          | 2366/569592 [1:57:26<367:11:25,  2.33s/it]
                                                           

  0%|          | 2366/569592 [1:57:26<367:11:25,  2.33s/it]
  0%|          | 2367/569592 [1:57:27<303:59:36,  1.93s/it]
                                                           

  0%|          | 2367/569592 [1:57:27<303:59:36,  1.93s/it]
  0%|          | 2368/569592 [1:57:33<464:02:22,  2.95s/it]
                                                           

  0%|          | 2368/569592 [1:57:33<464:02:22,  2.95s/it]
  0%|          | 2369/569592 [1:57:35<457:50:05,  2.91s/it]
                                                           

  0%|          | 2369/569592 [1:57:35<457:50:05,  2.91s/it]
  0%|          | 2370/569592 [1:57:38<426:42:34,  2.71s/it]
                                                           

  0%|          | 2370/569592 [1:57:38<426:42:34,  2.71s/it]
  0%|          | 2371/569592 [1:57:39<344:00:29,  2.18s/it]
                                                           

  0%|          | 2371/569592 [1:57:39<344:00:29,  2.18s/it]
  0%|          | 2372/569592 [1:57:43<433:35:28,  2.75s/it]
                                                           

  0%|          | 2372/569592 [1:57:43<433:35:28,  2.75s/it]
  0%|          | 2373/569592 [1:57:46<449:14:18,  2.85s/it]
                                                           

  0%|          | 2373/569592 [1:57:46<449:14:18,  2.85s/it]
  0%|          | 2374/569592 [1:57:47<379:58:29,  2.41s/it]
                                                           

  0%|          | 2374/569592 [1:57:47<379:58:29,  2.41s/it]
  0%|          | 2375/569592 [1:57:48<314:54:15,  2.00s/it]
                                                           

  0%|          | 2375/569592 [1:57:48<314:54:15,  2.00s/it]
  0%|          | 2376/569592 [1:57:53<436:41:43,  2.77s/it]
                                                           

  0%|          | 2376/569592 [1:57:53<436:41:43,  2.77s/it]
  0%|          | 2377/569592 [1:57:56<441:51:47,  2.80s/it]
                                                           

  0%|          | 2377/569592 [1:57:56<441:51:47,  2.80s/it]
  0%|          | 2378/569592 [1:57:57<395:48:03,  2.51s/it]
                                                           

  0%|          | 2378/569592 [1:57:58<395:48:03,  2.51s/it]
  0%|          | 2379/569592 [1:57:59<327:32:58,  2.08s/it]
                                                           

  0%|          | 2379/569592 [1:57:59<327:32:58,  2.08s/it]
  0%|          | 2380/569592 [1:58:03<437:46:45,  2.78s/it]
                                                           

  0%|          | 2380/569592 [1:58:03<437:46:45,  2.78s/it]
  0%|          | 2381/569592 [1:58:07<476:29:22,  3.02s/it]
                                                           

  0%|          | 2381/569592 [1:58:07<476:29:22,  3.02s/it]
  0%|          | 2382/569592 [1:58:08<381:49:48,  2.42s/it]
                                                           

  0%|          | 2382/569592 [1:58:08<381:49:48,  2.42s/it]
  0%|          | 2383/569592 [1:58:09<316:10:03,  2.01s/it]
                                                           

  0%|          | 2383/569592 [1:58:09<316:10:03,  2.01s/it]
  0%|          | 2384/569592 [1:58:13<433:21:15,  2.75s/it]
                                                           

  0%|          | 2384/569592 [1:58:13<433:21:15,  2.75s/it]
  0%|          | 2385/569592 [1:58:17<471:47:18,  2.99s/it]
                                                /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
           

  0%|          | 2385/569592 [1:58:17<471:47:18,  2.99s/it]
  0%|          | 2386/569592 [1:58:18<378:30:35,  2.40s/it]
                                                           

  0%|          | 2386/569592 [1:58:18<378:30:35,  2.40s/it]
  0%|          | 2387/569592 [1:58:19<309:24:19,  1.96s/it]
                                                           

  0%|          | 2387/569592 [1:58:19<309:24:19,  1.96s/it]
  0%|          | 2388/569592 [1:58:23<428:46:44,  2.72s/it]
                                                           

  0%|          | 2388/569592 [1:58:23<428:46:44,  2.72s/it]
  0%|          | 2389/569592 [1:58:28<523:59:32,  3.33s/it]
                                                           

  0%|          | 2389/569592 [1:58:28<523:59:32,  3.33s/it]
  0%|          | 2390/569592 [1:58:29<412:12:15,  2.62s/it]
                                                           

  0%|          | 2390/569592 [1:58:29<412:12:15,  2.62s/it]
  0%|          | 2391/569592 [1:58:32<444:54:08,  2.82s/it]
                                                           

  0%|          | 2391/569592 [1:58:32<444:54:08,  2.82s/it]
  0%|          | 2392/569592 [1:58:33<356:56:03,  2.27s/it]
                                                           

  0%|          | 2392/569592 [1:58:33<356:56:03,  2.27s/it]
  0%|          | 2393/569592 [1:58:38<495:00:06,  3.14s/it]
                                                           

  0%|          | 2393/569592 [1:58:38<495:00:06,  3.14s/it]
  0%|          | 2394/569592 [1:58:39<390:02:33,  2.48s/it]
                                                           

  0%|          | 2394/569592 [1:58:39<390:02:33,  2.48s/it]
  0%|          | 2395/569592 [1:58:43<446:59:20,  2.84s/it]
                                                           

  0%|          | 2395/569592 [1:58:43<446:59:20,  2.84s/it]
  0%|          | 2396/569592 [1:58:44<361:32:24,  2.29s/it]
                                                           

  0%|          | 2396/569592 [1:58:44<361:32:24,  2.29s/it]
  0%|          | 2397/569592 [1:58:48<436:43:06,  2.77s/it]
                                                           

  0%|          | 2397/569592 [1:58:48<436:43:06,  2.77s/it]
  0%|          | 2398/569592 [1:58:49<374:09:59,  2.37s/it]
                                                           

  0%|          | 2398/569592 [1:58:49<374:09:59,  2.37s/it]
  0%|          | 2399/569592 [1:58:50<308:16:46,  1.96s/it]
                                                           

  0%|          | 2399/569592 [1:58:50<308:16:46,  1.96s/it]
  0%|          | 2400/569592 [1:58:52<302:34:24,  1.92s/it]
                                                           

  0%|          | 2400/569592 [1:58:52<302:34:24,  1.92s/it]
  0%|          | 2401/569592 [1:58:56<416:27:32,  2.64s/it]
                                                           

  0%|          | 2401/569592 [1:58:56<416:27:32,  2.64s/it]
  0%|          | 2402/569592 [1:58:59<434:49:19,  2.76s/it]
                                                           

  0%|          | 2402/569592 [1:58:59<434:49:19,  2.76s/it]
  0%|          | 2403/569592 [1:59:00<348:59:52,  2.22s/it]
                                                           

  0%|          | 2403/569592 [1:59:00<348:59:52,  2.22s/it]
  0%|          | 2404/569592 [1:59:04<410:53:05,  2.61s/it]
                                                           

  0%|          | 2404/569592 [1:59:04<410:53:05,  2.61s/it]
  0%|          | 2405/569592 [1:59:06<402:16:38,  2.55s/it]
                                                           

  0%|          | 2405/569592 [1:59:06<402:16:38,  2.55s/it]
  0%|          | 2406/569592 [1:59:10<455:29:23,  2.89s/it]
                                                           

  0%|          | 2406/569592 [1:59:10<455:29:23,  2.89s/it]
  0%|          | 2407/569592 [1:59:11<364:42:45,  2.31s/it]
                                                           

  0%|          | 2407/569592 [1:59:11<364:42:45,  2.31s/it]
  0%|          | 2408/569592 [1:59:16<488:11:00,  3.10s/it]
                                                           

  0%|          | 2408/569592 [1:59:16<488:11:00,  3.10s/it]
  0%|          | 2409/569592 [1:59:20<536:22:00,  3.40s/it]
                                                           

  0%|          | 2409/569592 [1:59:20<536:22:00,  3.40s/it]
  0%|          | 2410/569592 [1:59:21<418:25:29,  2.66s/it]
                                                           

  0%|          | 2410/569592 [1:59:21<418:25:29,  2.66s/it]
  0%|          | 2411/569592 [1:59:22<336:33:25,  2.14s/it]
                                                           

  0%|          | 2411/569592 [1:59:22<336:33:25,  2.14s/it]
  0%|          | 2412/569592 [1:59:26<418:52:16,  2.66s/it]
                                                           

  0%|          | 2412/569592 [1:59:26<418:52:16,  2.66s/it]
  0%|          | 2413/569592 [1:59:29<451:18:33,  2.86s/it]
                                                           

  0%|          | 2413/569592 [1:59:29<451:18:33,  2.86s/it]
  0%|          | 2414/569592 [1:59:30<361:44:31,  2.30s/it]
                                                           

  0%|          | 2414/569592 [1:59:30<361:44:31,  2.30s/it]
  0%|          | 2415/569592 [1:59:34<430:21:43,  2.73s/it]
                                                           

  0%|          | 2415/569592 [1:59:34<430:21:43,  2.73s/it]
  0%|          | 2416/569592 [1:59:37<475:58:22,  3.02s/it]
                                                           

  0%|          | 2416/569592 [1:59:39<475:58:22,  3.02s/it]
  0%|          | 2417/569592 [1:59:41<502:55:05,  3.19s/it]
                                                           

  0%|          | 2417/569592 [1:59:41<502:55:05,  3.19s/it]
  0%|          | 2418/569592 [1:59:42<395:06:38,  2.51s/it]
                                                           

  0%|          | 2418/569592 [1:59:42<395:06:38,  2.51s/it]
  0%|          | 2419/569592 [1:59:47<525:30:10,  3.34s/it]
                                                           

  0%|          | 2419/569592 [1:59:47<525:30:10,  3.34s/it]
  0%|          | 2420/569592 [1:59:52<594:03:55,  3.77s/it]
                                                           

  0%|          | 2420/569592 [1:59:52<594:03:55,  3.77s/it]
  0%|          | 2421/569592 [1:59:57<632:19:27,  4.01s/it]
                                                           

  0%|          | 2421/569592 [1:59:57<632:19:27,  4.01s/it]
  0%|          | 2422/569592 [2:00:01<665:25:58,  4.22s/it]
                                                           

  0%|          | 2422/569592 [2:00:01<665:25:58,  4.22s/it]
  0%|          | 2423/569592 [2:00:02<507:34:33,  3.22s/it]
                                                           

  0%|          | 2423/569592 [2:00:02<507:34:33,  3.22s/it]
  0%|          | 2424/569592 [2:00:05<500:24:16,  3.18s/it]
                                                           

  0%|          | 2424/569592 [2:00:05<500:24:16,  3.18s/it]
  0%|          | 2425/569592 [2:00:10<577:49:39,  3.67s/it]
                                                           

  0%|          | 2425/569592 [2:00:10<577:49:39,  3.67s/it]
  0%|          | 2426/569592 [2:00:15<628:10:48,  3.99s/it]
                                                           

  0%|          | 2426/569592 [2:00:15<628:10:48,  3.99s/it]
  0%|          | 2427/569592 [2:00:20<668:08:41,  4.24s/it]
                                                           

  0%|          | 2427/569592 [2:00:20<668:08:41,  4.24s/it]
  0%|          | 2428/569592 [2:00:24<689:39:40,  4.38s/it]
                                                           

  0%|          | 2428/569592 [2:00:24<689:39:40,  4.38s/it]
  0%|          | 2429/569592 [2:00:28<633:10:12,  4.02s/it]
                                                           

  0%|          | 2429/569592 [2:00:28<633:10:12,  4.02s/it]
  0%|          | 2430/569592 [2:00:32<667:33:34,  4.24s/it]
                                                           

  0%|          | 2430/569592 [2:00:32<667:33:34,  4.24s/it]
  0%|          | 2431/569592 [2:00:37<692:52:02,  4.40s/it]
                                                           

  0%|          | 2431/569592 [2:00:37<692:52:02,  4.40s/it]
  0%|          | 2432/569592 [2:00:42<717:58:40,  4.56s/it]
                                                           

  0%|          | 2432/569592 [2:00:42<717:58:40,  4.56s/it]
  0%|          | 2433/569592 [2:00:46<692:14:54,  4.39s/it]
                                                           

  0%|          | 2433/569592 [2:00:46<692:14:54,  4.39s/it]
  0%|          | 2434/569592 [2:00:51<707:26:36,  4.49s/it]
                                                           

  0%|          | 2434/569592 [2:00:51<707:26:36,  4.49s/it]
  0%|          | 2435/569592 [2:00:54<655:56:14,  4.16s/it]
                                                           

  0%|          | 2435/569592 [2:00:54<655:56:14,  4.16s/it]
  0%|          | 2436/569592 [2:00:59<687:00:34,  4.36s/it]
                                                           

  0%|          | 2436/569592 [2:00:59<687:00:34,  4.36s/it]
  0%|          | 2437/569592 [2:01:04<696:49:11,  4.42s/it]
                                                           

  0%|          | 2437/569592 [2:01:04<696:49:11,  4.42s/it]
  0%|          | 2438/569592 [2:01:08<717:32:45,  4.55s/it]
                                                           

  0%|          | 2438/569592 [2:01:08<717:32:45,  4.55s/it]
  0%|          | 2439/569592 [2:01:09<545:06:45,  3.46s/it]
                                                           

  0%|          | 2439/569592 [2:01:09<545:06:45,  3.46s/it]
  0%|          | 2440/569592 [2:01:14<618:48:59,  3.93s/it]
                                                           

  0%|          | 2440/569592 [2:01:14<618:48:59,  3.93s/it]
  0%|          | 2441/569592 [2:01:19<660:02:18,  4.19s/it]
                                                           

  0%|          | 2441/569592 [2:01:19<660:02:18,  4.19s/it]
  0%|          | 2442/569592 [2:01:24<692:20:57,  4.39s/it]
                                                           

  0%|          | 2442/569592 [2:01:24<692:20:57,  4.39s/it]
  0%|          | 2443/569592 [2:01:29<708:12:34,  4.50s/it]
                                                           

  0%|          | 2443/569592 [2:01:29<708:12:34,  4.50s/it]
  0%|          | 2444/569592 [2:01:32<671:45:55,  4.26s/it]
                                                           

  0%|          | 2444/569592 [2:01:32<671:45:55,  4.26s/it]
  0%|          | 2445/569592 [2:01:37<702:02:18,  4.46s/it]
                                                           

  0%|          | 2445/569592 [2:01:37<702:02:18,  4.46s/it]
  0%|          | 2446/569592 [2:01:40<634:28:15,  4.03s/it]
                                                           

  0%|          | 2446/569592 [2:01:40<634:28:15,  4.03s/it]
  0%|          | 2447/569592 [2:01:43<586:58:46,  3.73s/it]
                                                           

  0%|          | 2447/569592 [2:01:43<586:58:46,  3.73s/it]
  0%|          | 2448/569592 [2:01:44<453:37:02,  2.88s/it]
                                                           

  0%|          | 2448/569592 [2:01:44<453:37:02,  2.88s/it]
  0%|          | 2449/569592 [2:01:48<491:26:43,  3.12s/it]
                                                           

  0%|          | 2449/569592 [2:01:48<491:26:43,  3.12s/it]
  0%|          | 2450/569592 [2:01:49<388:58:18,  2.47s/it]
                                                           

  0%|          | 2450/569592 [2:01:49<388:58:18,  2.47s/it]
  0%|          | 2451/569592 [2:01:52<436:57:46,  2.77s/it]
                                                           

  0%|          | 2451/569592 [2:01:52<436:57:46,  2.77s/it]
  0%|          | 2452/569592 [2:01:56<454:24:45,  2.88s/it]
                                                           

  0%|          | 2452/569592 [2:01:56<454:24:45,  2.88s/it]
  0%|          | 2453/569592 [2:01:59<466:12:15,  2.96s/it]
                                                           

  0%|          | 2453/569592 [2:01:59<466:12:15,  2.96s/it]
  0%|          | 2454/569592 [2:02:03<541:48:50,  3.44s/it]
                                                           

  0%|          | 2454/569592 [2:02:03<541:48:50,  3.44s/it]
  0%|          | 2455/569592 [2:02:04<423:38:03,  2.69s/it]
                                                           

  0%|          | 2455/569592 [2:02:04<423:38:03,  2.69s/it]
  0%|          | 2456/569592 [2:02:08<458:44:33,  2.91s/it]
                                                           

  0%|          | 2456/569592 [2:02:08<458:44:33,  2.91s/it]
  0%|          | 2457/569592 [2:02:09<365:49:04,  2.32s/it]
                                                           

  0%|          | 2457/569592 [2:02:09<365:49:04,  2.32s/it]
  0%|          | 2458/569592 [2:02:12<416:03:55,  2.64s/it]
                                                           

  0%|          | 2458/569592 [2:02:12<416:03:55,  2.64s/it]
  0%|          | 2459/5695/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
92 [2:02:13<337:08:07,  2.14s/it]
                                                           

  0%|          | 2459/569592 [2:02:13<337:08:07,  2.14s/it]
  0%|          | 2460/569592 [2:02:14<287:54:23,  1.83s/it]
                                                           

  0%|          | 2460/569592 [2:02:14<287:54:23,  1.83s/it]
  0%|          | 2461/569592 [2:02:17<361:03:53,  2.29s/it]
                                                           

  0%|          | 2461/569592 [2:02:17<361:03:53,  2.29s/it]
  0%|          | 2462/569592 [2:02:18<302:20:36,  1.92s/it]
                                                           

  0%|          | 2462/569592 [2:02:18<302:20:36,  1.92s/it]
  0%|          | 2463/569592 [2:02:19<256:56:17,  1.63s/it]
                                                           

  0%|          | 2463/569592 [2:02:19<256:56:17,  1.63s/it]
  0%|          | 2464/569592 [2:02:24<421:03:00,  2.67s/it]
                                                           

  0%|          | 2464/569592 [2:02:25<421:03:00,  2.67s/it]
  0%|          | 2465/569592 [2:02:25<340:05:37,  2.16s/it]
                                                           

  0%|          | 2465/569592 [2:02:25<340:05:37,  2.16s/it]
  0%|          | 2466/569592 [2:02:26<282:19:51,  1.79s/it]
                                                           

  0%|          | 2466/569592 [2:02:26<282:19:51,  1.79s/it]
  0%|          | 2467/569592 [2:02:29<297:43:13,  1.89s/it]
                                                           

  0%|          | 2467/569592 [2:02:29<297:43:13,  1.89s/it]
  0%|          | 2468/569592 [2:02:29<252:40:28,  1.60s/it]
                                                           

  0%|          | 2468/569592 [2:02:29<252:40:28,  1.60s/it]
  0%|          | 2469/569592 [2:02:32<282:38:08,  1.79s/it]
                                                           

  0%|          | 2469/569592 [2:02:32<282:38:08,  1.79s/it]
  0%|          | 2470/569592 [2:02:33<251:47:35,  1.60s/it]
                                                           

  0%|          | 2470/569592 [2:02:33<251:47:35,  1.60s/it]
  0%|          | 2471/569592 [2:02:37<378:06:12,  2.40s/it]
                                                           

  0%|          | 2471/569592 [2:02:37<378:06:12,  2.40s/it]
  0%|          | 2472/569592 [2:02:39<348:06:58,  2.21s/it]
                                                           

  0%|          | 2472/569592 [2:02:39<348:06:58,  2.21s/it]
  0%|          | 2473/569592 [2:02:42<371:27:42,  2.36s/it]
                                                           

  0%|          | 2473/569592 [2:02:42<371:27:42,  2.36s/it]
  0%|          | 2474/569592 [2:02:43<332:30:44,  2.11s/it]
                                                           

  0%|          | 2474/569592 [2:02:43<332:30:44,  2.11s/it]
  0%|          | 2475/569592 [2:02:47<414:43:45,  2.63s/it]
                                                           

  0%|          | 2475/569592 [2:02:47<414:43:45,  2.63s/it]
  0%|          | 2476/569592 [2:02:50<414:05:20,  2.63s/it]
                                                           

  0%|          | 2476/569592 [2:02:50<414:05:20,  2.63s/it]
  0%|          | 2477/569592 [2:02:52<405:53:54,  2.58s/it]
                                                           

  0%|          | 2477/569592 [2:02:52<405:53:54,  2.58s/it]
  0%|          | 2478/569592 [2:02:54<361:58:28,  2.30s/it]
                                                           

  0%|          | 2478/569592 [2:02:54<361:58:28,  2.30s/it]
  0%|          | 2479/569592 [2:02:58<446:18:54,  2.83s/it]
                                                           

  0%|          | 2479/569592 [2:02:58<446:18:54,  2.83s/it]
  0%|          | 2480/569592 [2:03:00<435:19:43,  2.76s/it]
                                                           

  0%|          | 2480/569592 [2:03:00<435:19:43,  2.76s/it]
  0%|          | 2481/569592 [2:03:02<385:30:14,  2.45s/it]
                                                           

  0%|          | 2481/569592 [2:03:02<385:30:14,  2.45s/it]
  0%|          | 2482/569592 [2:03:04<353:08:09,  2.24s/it]
                                                           

  0%|          | 2482/569592 [2:03:04<353:08:09,  2.24s/it]
  0%|          | 2483/569592 [2:03:08<444:31:30,  2.82s/it]
                                                           

  0%|          | 2483/569592 [2:03:08<444:31:30,  2.82s/it]
  0%|          | 2484/569592 [2:03:11<463:21:47,  2.94s/it]
                                                           

  0%|          | 2484/569592 [2:03:11<463:21:47,  2.94s/it]
  0%|          | 2485/569592 [2:03:13<397:49:15,  2.53s/it]
                                                           

  0%|          | 2485/569592 [2:03:13<397:49:15,  2.53s/it]
  0%|          | 2486/569592 [2:03:16<409:57:29,  2.60s/it]
                                                           

  0%|          | 2486/569592 [2:03:16<409:57:29,  2.60s/it]
  0%|          | 2487/569592 [2:03:18<393:28:17,  2.50s/it]
                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96506930 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                         

  0%|          | 2487/569592 [2:03:18<393:28:17,  2.50s/it]
  0%|          | 2488/569592 [2:03:21<420:24:39,  2.67s/it]
                                                           

  0%|          | 2488/569592 [2:03:21<420:24:39,  2.67s/it]
  0%|          | 2489/569592 [2:03:23<407:22:11,  2.59s/it]
                                                           

  0%|          | 2489/569592 [2:03:23<407:22:11,  2.59s/it]
  0%|          | 2490/569592 [2:03:26<420:58:16,  2.67s/it]
                                                           

  0%|          | 2490/569592 [2:03:26<420:58:16,  2.67s/it]
  0%|          | 2491/569592 [2:03:28<401:48:46,  2.55s/it]
                                                           

  0%|          | 2491/569592 [2:03:28<401:48:46,  2.55s/it]
  0%|          | 2492/569592 [2:03:30<373:59:26,  2.37s/it]
                                                           

  0%|          | 2492/569592 [2:03:30<373:59:26,  2.37s/it]
  0%|          | 2493/569592 [2:03:35<468:42:40,  2.98s/it]
                                                           

  0%|          | 2493/569592 [2:03:35<468:42:40,  2.98s/it]
  0%|          | 2494/569592 [2:03:37<421:19:17,  2.67s/it]
                                                           

  0%|          | 2494/569592 [2:03:37<421:19:17,  2.67s/it]
  0%|          | 2495/569592 [2:03:38<346:56:17,  2.20s/it]
                                                           

  0%|          | 2495/569592 [2:03:38<346:56:17,  2.20s/it]
  0%|          | 2496/569592 [2:03:40<348:15:33,  2.21s/it]
                                                           

  0%|          | 2496/569592 [2:03:40<348:15:33,  2.21s/it]
  0%|          | 2497/569592 [2:03:44<418:15:27,  2.66s/it]
                                                           

  0%|          | 2497/569592 [2:03:44<418:15:27,  2.66s/it]
  0%|          | 2498/569592 [2:03:47<434:28:52,  2.76s/it]
                                                           

  0%|          | 2498/569592 [2:03:47<434:28:52,  2.76s/it]
  0%|          | 2499/569592 [2:03:49<421:38:53,  2.68s/it]
                                                           

  0%|          | 2499/569592 [2:03:49<421:38:53,  2.68s/it]
  0%|          | 2500/569592 [2:03:50<339:27:36,  2.15s/it]
                                                           

  0%|          | 2500/569592 [2:03:51<339:27:36,  2.15s/it]
  0%|          | 2501/569592 [2:03:54<432:43:11,  2.75s/it]
                                                           

  0%|          | 2501/569592 [2:03:54<432:43:11,  2.75s/it]
  0%|          | 2502/569592 [2:03:56<373:14:16,  2.37s/it]
                                                           

  0%|          | 2502/569592 [2:03:56<373:14:16,  2.37s/it]
  0%|          | 2503/569592 [2:03:58<361:06:03,  2.29s/it]
                                                           

  0%|          | 2503/569592 [2:03:58<361:06:03,  2.29s/it]
  0%|          | 2504/569592 [2:04:01<412:55:02,  2.62s/it]
                                                           

  0%|          | 2504/569592 [2:04:01<412:55:02,  2.62s/it]
  0%|          | 2505/569592 [2:04:05<441:16:54,  2.80s/it]
                                                           

  0%|          | 2505/569592 [2:04:05<441:16:54,  2.80s/it]
  0%|          | 2506/569592 [2:04:07<426:58:01,  2.71s/it]
                                                           

  0%|          | 2506/569592 [2:04:07<426:58:01,  2.71s/it]
  0%|          | 2507/569592 [2:04:08<342:57:26,  2.18s/it]
                                                           

  0%|          | 2507/569592 [2:04:08<342:57:26,  2.18s/it]
  0%|          | 2508/569592 [2:04:11<363:32:52,  2.31s/it]
                                                           

  0%|          | 2508/569592 [2:04:11<363:32:52,  2.31s/it]
  0%|          | 2509/569592 [2:04:15<459:30:51,  2.92s/it]
                                                           

  0%|          | 2509/569592 [2:04:15<459:30:51,  2.92s/it]
  0%|          | 2510/569592 [2:04:17<417:10:30,  2.65s/it]
                                                           

  0%|          | 2510/569592 [2:04:17<417:10:30,  2.65s/it]
  0%|          | 2511/569592 [2:04:18<341:45:56,  2.17s/it]
                                                           

  0%|          | 2511/569592 [2:04:18<341:45:56,  2.17s/it]
  0%|          | 2512/569592 [2:04:22<410:14:02,  2.60s/it]
                                                           

  0%|          | 2512/569592 [2:04:22<410:14:02,  2.60s/it]
  0%|          | 2513/569592 [2:04:25<453:04:51,  2.88s/it]
                                                           

  0%|          | 2513/569592 [2:04:25<453:04:51,  2.88s/it]
  0%|          | 2514/569592 [2:04:27<398:49:29,  2.53s/it]
                                                           

  0%|          | 2514/569592 [2:04:27<398:49:29,  2.53s/it]
  0%|          | 2515/569592 [2:04:28<323:20:01,  2.05s/it]
                                                           

  0%|          | 2515/569592 [2:04:28<323:20:01,  2.05s/it]
  0%|          | 2516/569592 [2:04:31<394:06:26,  2.50s/it]
                                                           

  0%|          | 2516/569592 [2:04:31<394:06:26,  2.50s/it]
  0%|          | 2517/569592 [2:04:35<455:16:25,  2.89s/it]
                                                           

  0%|          | 2517/569592 [2:04:35<455:16:25,  2.89s/it]
  0%|          | 2518/569592 [2:04:37<411:39:33,  2.61s/it]
                                                           

  0%|          | 2518/569592 [2:04:37<411:39:33,  2.61s/it]
  0%|          | 2519/569592 [2:04:38<337:14:14,  2.14s/it]
                                                           

  0%|          | 2519/569592 [2:04:38<337:14:14,  2.14s/it]
  0%|          | 2520/569592 [2:04:41<370:31:51,  2.35s/it]
                                                           

  0%|          | 2520/569592 [2:04:41<370:31:51,  2.35s/it]
  0%|          | 2521/569592 [2:04:46<520:09:37,  3.30s/it]
                                                           

  0%|          | 2521/569592 [2:04:46<520:09:37,  3.30s/it]
  0%|          | 2522/569592 [2:04:52<616:24:33,  3.91s/it]
                                                           

  0%|          | 2522/569592 [2:04:52<616:24:33,  3.91s/it]
  0%|          | 2523/569592 [2:04:53<475:10:55,  3.02s/it]
                                                           

  0%|          | 2523/569592 [2:04:53<475:10:55,  3.02s/it]
  0%|          | 2524/569592 [2:04:54<377:08:41,  2.39s/it]
                                                           

  0%|          | 2524/569592 [2:04:54<377:08:41,  2.39s/it]
  0%|          | 2525/569592 [2:04:57<437:14:36,  2.78s/it]
                                                           

  0%|          | 2525/569592 [2:04:57<437:14:36,  2.78s/it]
  0%|          | 2526/569592 [2:04:58<352:16:57,  2.24s/it]
                                                           

  0%|          | 2526/569592 [2:04:58<352:16:57,  2.24s/it]
  0%|          | 2527/569592 [2:05:03<488:42:48,  3.10s/it]
                                                           

  0%|          | 2527/569592 [2:05:03<488:42:48,  3.10s/it]
  0%|          | 2528/569592 [2:05:09<599:37:29,  3.81s/it]
                                                           

  0%|          | 2528/569592 [2:05:09<599:37:29,  3.81s/it]
  0%|          | 2529/569592 [2:05:13<611:32:21,  3.88s/it]
                                                           

  0%|          | 2529/569592 [2:05:13<611:32:21,  3.88s/it]
  0%|          | 2530/569592 [2:05:18<646:27:15,  4.10s/it]
                                                           

  0%|          | 2530/569592 [2:05:18<646:27:15,  4.10s/it]
  0%|          | 2531/569592 [2:05:18<493:49:13,  3.14s/it]
                                                           

  0%|          | 2531/569592 [2:05:18<493:49:13,  3.14s/it]
  0%|          | 2532/569592 [2:05:22<531:53:38,  3.38s/it]
                                                           

  0%|          | 2532/569592 [2:05:22<531:53:38,  3.38s/it]
  0%|          | 2533/569592 [2:05:26<534:32:15,  3.39s/it]
                                                           

  0%|          | 2533/569592 [2:05:26<534:32:15,  3.39s/it]
  0%|          | 2534/569592 [2:05:31<596:07:04,  3.78s/it]
                                                           

  0%|          | 2534/569592 [2:05:31<596:07:04,  3.78s/it]
  0%|          | 2535/569592 [2:05:31<460:13:38,  2.92s/it]
                                                           

  0%|          | 2535/569592 [2:05:31<460:13:38,  2.92s/it]
  0%|          | 2536/569592 [2:05:37<568:39:37,  3.61s/it]
                                                           

  0%|          | 2536/569592 [2:05:37<568:39:37,  3.61s/it]
  0%|          | 2537/569592 [2:05:38<442:33:35,  2.81s/it]
                                                           

  0%|          | 2537/569592 [2:05:38<442:33:35,  2.81s/it]
  0%|          | 2538/569592 [2:05:41<472:14:46,  3.00s/it]
                                                           

  0%|          | 2538/569592 [2:05:41<472:14:46,  3.00s/it]
  0%|          | 2539/569592 [2:05:46<570:19:16,  3.62s/it]
                                                           

  0%|          | 2539/569592 [2:05:46<570:19:16,  3.62s/it]
  0%|          | 2540/569592 [2:05:50<584:58:42,  3.71s/it]
                                                           

  0%|          | 2540/569592 [2:05:50<584:58:42,  3.71s/it]
  0%|          | 2541/569592 [2:05:54<579:19:17,  3.68s/it]
                                                           

  0%|          | 2541/569592 [2:05:54<579:19:17,  3.68s/it]
  0%|          | 2542/569592 [2:05:58<631:15:59,  4.01s/it]
                                                           

  0%|          | 2542/569592 [2:05:58<631:15:59,  4.01s/it]
  0%|          | 2543/569592 [2:06:03<664:03:15,  4.22s/it]
                                                           

  0%|          | 2543/569592 [2:06:03<664:03:15,  4.22s/it]
  0%|          | 2544/569592 [2:06:08<694:18:42,  4.41s/it]
                                                           

  0%|          | 2544/569592 [2:06:08<694:18:42,  4.41s/it]
  0%|          | 2545/569592 [2:06:13<704:29:10,  4.47s/it]
                                                           

  0%|          | 2545/569592 [2:06:13<704:29:10,  4.47s/it]
  0%|          | 2546/569592 [2:06:16<656:45:43,  4.17s/it]
                                                           

  0%|          | 2546/569592 [2:06:16<656:45:43,  4.17s/it]
  0%|          | 2547/569592 [2:06:21<680:39:21,  4.32s/it]
                                                           

  0%|          | 2547/569592 [2:06:21<680:39:21,  4.32s/it]
  0%|          | 2548/569592 [2:06:25<700:17:39,  4.45s/it]
                                                           

  0%|          | 2548/569592 [2:06:25<700:17:39,  4.45s/it]
  0%|          | 2549/569592 [2:06:30<710:21:39,  4.51s/it]
                                                           

  0%|          | 2549/569592 [2:06:30<710:21:39,  4.51s/it]
  0%|          | 2550/569592 [2:06:35<717:42:44,  4.56s/it]
                                                           

  0%|          | 2550/569592 [2:06:35<717:42:44,  4.56s/it]
  0%|          | 2551/569592 [2:06:41<798:20:25,  5.07s/it]
                                                           

  0%|          | 2551/569592 [2:06:41<798:20:25,  5.07s/it]
  0%|          | 2552/569592 [2:06:46<779:44:51,  4.95s/it]
                                                           

  0%|          | 2552/569592 [2:06:46<779:44:51,  4.95s/it]
  0%|          | 2553/569592 [2:06:50<761:07:26,  4.83s/it]
                                                           

  0%|          | 2553/569592 [2:06:50<761:07:26,  4.83s/it]
  0%|          | 2554/569592 [2:06:55<762:28:42,  4.84s/it]
                                                           

  0%|          | 2554/569592 [2:06:55<762:28:42,  4.84s/it]
  0%|          | 2555/569592 [2:06:58<675:14:42,  4.29s/it]
                                                           

  0%|          | 2555/569592 [2:06:58<675:14:42,  4.29s/it]
  0%|          | 2556/569592 [2:07:05<790:32:37,  5.02s/it]
                                                           

  0%|          | 2556/569592 [2:07:05<790:32:37,  5.02s/it]
  0%|          | 2557/569592 [2:07:08<711:01:13,  4.51s/it]
                                                           

  0%|          | 2557/569592 [2:07:08<711:01:13,  4.51s/it]
  0%|          | 2558/569592 [2:07:13<733:09:52,  4.65s/it]
                                                           

  0%|          | 2558/569592 [2:07:13<733:09:52,  4.65s/it]
  0%|          | 2559/569592 [2:07:18<730:50:32,  4.64s/it]
                                                           

  0%|          | 2559/569592 [2:07:18<730:50:32,  4.64s/it]
  0%|          | 2560/569592 [2:07:23<742:19:33,  4.71s/it]
                                                           

  0%|          | 2560/569592 [2:07:23<742:19:33,  4.71s/it]
  0%|          | 2561/569592 [2:07:26<699:59:56,  4.44s/it]
                                                           

  0%|          | 2561/569592 [2:07:26<699:59:56,  4.44s/it]
  0%|          | 2562/569592 [2:07:31<712:19:11,  4.52s/it]
                                                           

  0%|          | 2562/569592 [2:07:31<712:19:11,  4.52s/it]
  0%|          | 2563/569592 [2:07:36<722:25:02,  4.59s/it]
                                                           

  0%|          | 2563/569592 [2:07:36<722:25:02,  4.59s/it]
  0%|          | 2564/569592 [2:07:41<735:23:32,  4.67s/it]
                                                           

  0%|          | 2564/569592 [2:07:41<735:23:32,  4.67s/it]
  0%|          | 2565/569592 [2:07:42<557:34:58,  3.54s/it]
                                                           

  0%|          | 2565/569592 [2:07:42<557:34:58,  3.54s/it]
  0%|          | 2566/569592 [2:07:47<619:15:46,  3.93s/it]
                                                           

  0%|          | 2566/569592 [2:07:47<619:15:46,  3.93s/it]
  0%|          | 2567/569592 [2:07:51<666:49:25,  4.23s/it]
                                                           

  0%|          | 2567/569592 [2:07:51<666:49:25,  4.23s/it]
  0%|          | 2568/569592 [2:07:52<510:10:49,  3.24s/it]
                                                           

  0%|          | 2568/569592 [2:07:52<510:10:49,  3.24s/it]
  0%|          | 2569/569592 [2:07:56<531:11:52,  3.37s/it]
                                                           

  0%|          | 2569/569592 [2:07:56<531:11:52,  3.37s/it]
  0%|          | 2570/569592 [2:08:00<540:30:57,  3.43s/it]
                                                           

  0%|          | 2570/569592 [2:08:00<540:30:57,  3.43s/it]
  0%|          | 2571/569592 [2:08:04<598:47:58,  3.80s/it]
                                                           

  0%|          | 2571/569592 [2:08:04<598:47:58,  3.80s/it]
  0%|          | 2572/569592 [2:08:09<644:21:11,  4.09s/it]
                                                           

  0%|          | 2572/569592 [2:08:09<644:21:11,  4.09s/it]
  0%|          | 2573/569592 [2:08:10<497:33:11,  3.16s/it]
                                                           

  0%|          | 2573/569592 [2:08:10<497:33:11,  3.16s/it]
  0%|          | 2574/569592 [2:08:13<509:40:15,  3.24s/it]
                                                           

  0%|          | 2574/569592 [2:08:13<509:40:15,  3.24s/it]
  0%|          | 2575/569592 [2:08:14<400:35:54,  2.54s/it]
                                                           

  0%|          | 2575/569592 [2:08:14<400:35:54,  2.54s/it]
  0%|          | 2576/569592 [2:08:18<434:08:28,  2.76s/it]
                                                           

  0%|          | 2576/569592 [2:08:18<434:08:28,  2.76s/it]
  0%|          | 2577/569592 [2:08:19<352:53:35,  2.24s/it]
                                                           

  0%|          | 2577/569592 [2:08:19<352:53:35,  2/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
.24s/it]
  0%|          | 2578/569592 [2:08:20<293:03:17,  1.86s/it]
                                                           

  0%|          | 2578/569592 [2:08:20<293:03:17,  1.86s/it]
  0%|          | 2579/569592 [2:08:21<250:49:43,  1.59s/it]
                                                           

  0%|          | 2579/569592 [2:08:21<250:49:43,  1.59s/it]
  0%|          | 2580/569592 [2:08:22<221:27:18,  1.41s/it]
                                                           

  0%|          | 2580/569592 [2:08:22<221:27:18,  1.41s/it]
  0%|          | 2581/569592 [2:08:26<366:45:12,  2.33s/it]
                                                           

  0%|          | 2581/569592 [2:08:26<366:45:12,  2.33s/it]
  0%|          | 2582/569592 [2:08:27<310:24:19,  1.97s/it]
                                                           

  0%|          | 2582/569592 [2:08:28<310:24:19,  1.97s/it]
  0%|          | 2583/569592 [2:08:29<279:31:23,  1.77s/it]
                                                           

  0%|          | 2583/569592 [2:08:29<279:31:23,  1.77s/it]
  0%|          | 2584/569592 [2:08:29<240:19:42,  1.53s/it]
                                                           

  0%|          | 2584/569592 [2:08:30<240:19:42,  1.53s/it]
  0%|          | 2585/569592 [2:08:32<293:02:46,  1.86s/it]
                                                           

  0%|          | 2585/569592 [2:08:32<293:02:46,  1.86s/it]
  0%|          | 2586/569592 [2:08:34<293:30:09,  1.86s/it]
                                                           

  0%|          | 2586/569592 [2:08:34<293:30:09,  1.86s/it]
  0%|          | 2587/569592 [2:08:38<399:03:06,  2.53s/it]
                                                           

  0%|          | 2587/569592 [2:08:38<399:03:06,  2.53s/it]
  0%|          | 2588/569592 [2:08:39<327:05:47,  2.08s/it]
                                                           

  0%|          | 2588/569592 [2:08:39<327:05:47,  2.08s/it]
  0%|          | 2589/569592 [2:08:42<384:55:01,  2.44s/it]
                                                           

  0%|          | 2589/569592 [2:08:42<384:55:01,  2.44s/it]
  0%|          | 2590/569592 [2:08:44<354:59:57,  2.25s/it]
                                                           

  0%|          | 2590/569592 [2:08:44<354:59:57,  2.25s/it]
  0%|          | 2591/569592 [2:08:48<431:15:38,  2.74s/it]
                                                           

  0%|          | 2591/569592 [2:08:48<431:15:38,  2.74s/it]
  0%|          | 2592/569592 [2:08:49<351:54:47,  2.23s/it]
                                                           

  0%|          | 2592/569592 [2:08:49<351:54:47,  2.23s/it]
  0%|          | 2593/569592 [2:08:53<415:50:44,  2.64s/it]
                                                           

  0%|          | 2593/569592 [2:08:53<415:50:44,  2.64s/it]
  0%|          | 2594/569592 [2:08:55<393:29:18,  2.50s/it]
                                                           

  0%|          | 2594/569592 [2:08:55<393:29:18,  2.50s/it]
  0%|          | 2595/569592 [2:08:58<406:16:46,  2.58s/it]
                                                           

  0%|          | 2595/569592 [2:08:58<406:16:46,  2.58s/it]
  0%|          | 2596/569592 [2:09:00<394:44:14,  2.51s/it]
                                                           

  0%|          | 2596/569592 [2:09:00<394:44:14,  2.51s/it]
  0%|          | 2597/569592 [2:09:03<422:35:36,  2.68s/it]
                                                           

  0%|          | 2597/569592 [2:09:03<422:35:36,  2.68s/it]
  0%|          | 2598/569592 [2:09:05<393:17:05,  2.50s/it]
                                                           

  0%|          | 2598/569592 [2:09:05<393:17:05,  2.50s/it]
  0%|          | 2599/569592 [2:09:08<405:53:40,  2.58s/it]
                                                           

  0%|          | 2599/569592 [2:09:08<405:53:40,  2.58s/it]
  0%|          | 2600/569592 [2:09:10<396:03:04,  2.51s/it]
                                                           

  0%|          | 2600/569592 [2:09:10<396:03:04,  2.51s/it]
  0%|          | 2601/569592 [2:09:13<400:48:05,  2.54s/it]
                                                           

  0%|          | 2601/569592 [2:09:13<400:48:05,  2.54s/it]
  0%|          | 2602/569592 [2:09:15<400:12:07,  2.54s/it]
                                                           

  0%|          | 2602/569592 [2:09:15<400:12:07,  2.54s/it]
  0%|          | 2603/569592 [2:09:18<389:10:47,  2.47s/it]
                                                           

  0%|          | 2603/569592 [2:09:18<389:10:47,  2.47s/it]
  0%|          | 2604/569592 [2:09:19<352:39:42,  2.24s/it]
                                                           

  0%|          | 2604/569592 [2:09:19<352:39:42,  2.24s/it]
  0%|          | 2605/569592 [2:09:23<400:25:59,  2.54s/it]
                                                           

  0%|          | 2605/569592 [2:09:23<400:25:59,  2.54s/it]
  0%|          | 2606/569592 [2:09:26<433:44:31,  2.75s/it]
                                                           

  0%|          | 2606/569592 [2:09:26<433:44:31,  2.75s/it]
  0%|          | 2607/569592 [2:09:28<380:09:46,  2.41s/it]
                                                           

  0%|          | 2607/569592 [2:09:28<380:09:46,  2.41s/it]
  0%|          | 2608/569592 [2:09:30<395:10:31,  2.51s/it]
                                                           

  0%|          | 2608/569592 [2:09:30<395:10:31,  2.51s/it]
  0%|          | 2609/569592 [2:09:33<426:39:38,  2.71s/it]
                                                           

  0%|          | 2609/569592 [2:09:33<426:39:38,  2.71s/it]
  0%|          | 2610/569592 [2:09:36<424:35:03,  2.70s/it]
                                                           

  0%|          | 2610/569592 [2:09:36<424:35:03,  2.70s/it]
  0%|          | 2611/569592 [2:09:38<391:01:20,  2.48s/it]
                                                           

  0%|          | 2611/569592 [2:09:38<391:01:20,  2.48s/it]
  0%|          | 2612/569592 [2:09:40<376:02:49,  2.39s/it]
                                                           

  0%|          | 2612/569592 [2:09:40<376:02:49,  2.39s/it]
  0%|          | 2613/569592 [2:09:44<458:59:36,  2.91s/it]
                                                           

  0%|          | 2613/569592 [2:09:44<458:59:36,  2.91s/it]
  0%|          | 2614/569592 [2:09:46<404:45:59,  2.57s/it]
                                                           

  0%|          | 2614/569592 [2:09:46<404:45:59,  2.57s/it]
  0%|          | 2615/569592 [2:09:48<360:14:26,  2.29s/it]
                                                           

  0%|          | 2615/569592 [2:09:48<360:14:26,  2.29s/it]
  0%|          | 2616/569592 [2:09:50<371:39:31,  2.36s/it]
                                                           

  0%|          | 2616/569592 [2:09:50<371:39:31,  2.36s/it]
  0%|          | 2617/569592 [2:09:54<420:39:52,  2.67s/it]
                                                           

  0%|          | 2617/569592 [2:09:54<420:39:52,  2.67s/it]
  0%|          | 2618/569592 [2:09:56<401:09:25,  2.55s/it]
                                                           

  0%|          | 2618/569592 [2:09:56<401:09:25,  2.55s/it]
  0%|          | 2619/569592 [2:09:58<374:20:56,  2.38s/it]
                                                           

  0%|          | 2619/569592 [2:09:58<374:20:56,  2.38s/it]
  0%|          | 2620/569592 [2:10:00<362:11:35,  2.30s/it]
                                                           

  0%|          | 2620/569592 [2:10:00<362:11:35,  2.30s/it]
  0%|          | 2621/569592 [2:10:04<433:33:33,  2.75s/it]
                                                           

  0%|          | 2621/569592 [2:10:04<433:33:33,  2.75s/it]
  0%|          | 2622/569592 [2:10:06<388:15:16,  2.47s/it]
                                                           

  0%|          | 2622/569592 [2:10:06<388:15:16,  2.47s/it]
  0%|          | 2623/569592 [2:10:09</home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
429:28:50,  2.73s/it]
                                                           

  0%|          | 2623/569592 [2:10:09<429:28:50,  2.73s/it]
  0%|          | 2624/569592 [2:10:11<370:46:45,  2.35s/it]
                                                           

  0%|          | 2624/569592 [2:10:11<370:46:45,  2.35s/it]
  0%|          | 2625/569592 [2:10:14<408:25:14,  2.59s/it]
                                                           

  0%|          | 2625/569592 [2:10:14<408:25:14,  2.59s/it]
  0%|          | 2626/569592 [2:10:15<362:46:29,  2.30s/it]
                                                           

  0%|          | 2626/569592 [2:10:15<362:46:29,  2.30s/it]
  0%|          | 2627/569592 [2:10:19<430:05:27,  2.73s/it]
                                                           

  0%|          | 2627/569592 [2:10:19<430:05:27,  2.73s/it]
  0%|          | 2628/569592 [2:10:21<382:59:55,  2.43s/it]
                                                           

  0%|          | 2628/569592 [2:10:21<382:59:55,  2.43s/it]
  0%|          | 2629/569592 [2:10:24<428:41:47,  2.72s/it]
                                                           

  0%|          | 2629/569592 [2:10:24<428:41:47,  2.72s/it]
  0%|          | 2630/569592 [2:10:29<539:51:30,  3.43s/it]
                                                           

  0%|          | 2630/569592 [2:10:29<539:51:30,  3.43s/it]
  0%|          | 2631/569592 [2:10:30<424:34:27,  2.70s/it]
                                                           

  0%|          | 2631/569592 [2:10:30<424:34:27,  2.70s/it]
  0%|          | 2632/569592 [2:10:31<342:46:05,  2.18s/it]
                                                           

  0%|          | 2632/569592 [2:10:31<342:46:05,  2.18s/it]
  0%|          | 2633/569592 [2:10:34<354:12:01,  2.25s/it]
                                                           

  0%|          | 2633/569592 [2:10:34<354:12:01,  2.25s/it]
  0%|          | 2634/569592 [2:10:37<408:16:52,  2.59s/it]
                                   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                        

  0%|          | 2634/569592 [2:10:37<408:16:52,  2.59s/it]
  0%|          | 2635/569592 [2:10:42<524:58:13,  3.33s/it]
                                                           

  0%|          | 2635/569592 [2:10:42<524:58:13,  3.33s/it]
  0%|          | 2636/569592 [2:10:43<412:04:37,  2.62s/it]
                                                           

  0%|          | 2636/569592 [2:10:43<412:04:37,  2.62s/it]
  0%|          | 2637/569592 [2:10:47<498:32:46,  3.17s/it]
                                                           

  0%|          | 2637/569592 [2:10:47<498:32:46,  3.17s/it]
  0%|          | 2638/569592 [2:10:52<579:16:29,  3.68s/it]
                                                           

  0%|          | 2638/569592 [2:10:52<579:16:29,  3.68s/it]
  0%|          | 2639/569592 [2:10:53<447:33:18,  2.84s/it]
                                                           

  0%|          | 2639/569592 [2:10:53<447:33:18,  2.84s/it]
  0%|          | 2640/569592 [2:10:54<356:40:02,  2.26s/it]
                                                           

  0%|          | 2640/569592 [2:10:54<356:40:02,  2.26s/it]
  0%|          | 2641/569592 [2:10:55<295:52:28,  1.88s/it]
                                                           

  0%|          | 2641/569592 [2:10:55<295:52:28,  1.88s/it]
  0%|          | 2642/569592 [2:11:00<443:20:12,  2.82s/it]
                                                           

  0%|          | 2642/569592 [2:11:00<443:20:12,  2.82s/it]
  0%|          | 2643/569592 [2:11:01<355:55:48,  2.26s/it]
                                                           

  0%|          | 2643/569592 [2:11:01<355:55:48,  2.26s/it]
  0%|          | 2644/569592 [2:11:06<480:55:30,  3.05s/it]
                                                           

  0%|          | 2644/569592 [2:11:06<480:55:30,  3.05s/it]
  0%|          | 2645/569592 [2:11:07<380:22:52,  2.42s/it]
                                                           

  0%|          | 2645/569592 [2/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:11:07<380:22:52,  2.42s/it]
  0%|          | 2646/569592 [2:11:10<429:20:34,  2.73s/it]
                                                           

  0%|          | 2646/569592 [2:11:10<429:20:34,  2.73s/it]
  0%|          | 2647/569592 [2:11:15<532:02:57,  3.38s/it]
                                                           

  0%|          | 2647/569592 [2:11:15<532:02:57,  3.38s/it]
  0%|          | 2648/569592 [2:11:18<521:37:03,  3.31s/it]
                                                           

  0%|          | 2648/569592 [2:11:18<521:37:03,  3.31s/it]
  0%|          | 2649/569592 [2:11:22<541:33:44,  3.44s/it]
                                                           

  0%|          | 2649/569592 [2:11:22<541:33:44,  3.44s/it]
  0%|          | 2650/569592 [2:11:23<422:44:57,  2.68s/it]
                                                           

  0%|          | 2650/569592 [2:11:23<422:44:57,  2.68s/it]
  0%|          | 2651/569592 [2:11:27<460:07:16,  2.92s/it]
                                                           

  0%|          | 2651/569592 [2:11:27<460:07:16,  2.92s/it]
  0%|          | 2652/569592 [2:11:31<522:25:05,  3.32s/it]
                                                           

  0%|          | 2652/569592 [2:11:31<522:25:05,  3.32s/it]
  0%|          | 2653/569592 [2:11:36<587:53:21,  3.73s/it]
                                                           

  0%|          | 2653/569592 [2:11:36<587:53:21,  3.73s/it]
  0%|          | 2654/569592 [2:11:41<655:04:37,  4.16s/it]
                                                           

  0%|          | 2654/569592 [2:11:41<655:04:37,  4.16s/it]
  0%|          | 2655/569592 [2:11:46<689:28:19,  4.38s/it]
                                                           

  0%|          | 2655/569592 [2:11:46<689:28:19,  4.38s/it]
  0%|          | 2656/569592 [2:11:50<704:09:48,  4.47s/it]
                                                           

  0%|          | 2656/569592 [2:11:50<704:09:48,  4.47s/it]
  0%|          | 2657/569592 [2:11:56<746:07:27,  4.74s/it]
                                                           

  0%|          | 2657/569592 [2:11:56<746:07:27,  4.74s/it]
  0%|          | 2658/569592 [2:12:00<735:25:44,  4.67s/it]
                                                           

  0%|          | 2658/569592 [2:12:00<735:25:44,  4.67s/it]
  0%|          | 2659/569592 [2:12:05<746:31:18,  4.74s/it]
                                                           

  0%|          | 2659/569592 [2:12:05<746:31:18,  4.74s/it]
  0%|          | 2660/569592 [2:12:10<761:14:03,  4.83s/it]
                                                           

  0%|          | 2660/569592 [2:12:10<761:14:03,  4.83s/it]
  0%|          | 2661/569592 [2:12:13<680:20:12,  4.32s/it]
                                                           

  0%|          | 2661/569592 [2:12:13<680:20:12,  4.32s/it]
  0%|          | 2662/569592 [2:12:14<520:30:13,  3.31s/it]
                                                           

  0%|          | 2662/569592 [2:12:14<520:30:13,  3.31s/it]
  0%|          | 2663/569592 [2:12:19<599:07:56,  3.80s/it]
                                                           

  0%|          | 2663/569592 [2:12:19<599:07:56,  3.80s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  0%|          | 2664/569592 [2:12:23<612:54:05,  3.89s/it]
                                                           

  0%|          | 2664/569592 [2:12:23<612:54:05,  3.89s/it]
  0%|          | 2665/569592 [2:12:28<650:52:04,  4.13s/it]
                                                           

  0%|          | 2665/569592 [2:12:28<650:52:04,  4.13s/it]
  0%|          | 2666/569592 [2:12:33<678:17:17,  4.31s/it]
                                                           

  0%|          | 2666/569592 [2:12:33<678:17:17,  4.31s/it]
  0%|          | 2667/569592 [2:12:37<698:45:51,  4.44s/it]
                                                           

  0%|          | 2667/569592 [2:12:37<698:45:51,  4.44s/it]
  0%|          | 2668/569592 [2:12:42<722:05:46,  4.59s/it]
                                                           

  0%|          | 2668/569592 [2:12:42<722:05:46,  4.59s/it]
  0%|          | 2669/569592 [2:12:46<690:59:24,  4.39s/it]
                                                           

  0%|          | 2669/569592 [2:12:46<690:59:24,  4.39s/it]
  0%|          | 2670/569592 [2:12:50<672:13:39,  4.27s/it]
                                                           

  0%|          | 2670/569592 [2:12:50<672:13:39,  4.27s/it]
  0%|          | 2671/569592 [2:12:54<629:44:46,  4.00s/it]
                                                           

  0%|          | 2671/569592 [2:12:54<629:44:46,  4.00s/it]
  0%|          | 2672/569592 [2:12:58<672:11:00,  4.27s/it]
                                                           

  0%|          | 2672/569592 [2:12:58<672:11:00,  4.27s/it]
  0%|          | 2673/569592 [2:13:02<620:05:34,  3.94s/it]
                                                           

  0%|          | 2673/569592 [2:13:02<620:05:34,  3.94s/it]
  0%|          | 2674/569592 [2:13:05<580:58:21,  3.69s/it]
                                                           

  0%|          | 2674/569592 [2:13:05<580:58:21,  3.69s/it]
  0%|          | 2675/569592 [2:13:10<648:31:27,  4.12s/it]
                                                           

  0%|          | 2675/569592 [2:13:10<648:31:27,  4.12s/it]
  0%|          | 2676/569592 [2:13:15<675:12:44,  4.29s/it]
                                                           

  0%|          | 2676/569592 [2:13:15<675:12:44,  4.29s/it]
  0%|          | 2677/569592 [2:13:19<693:36:42,  4.40s/it]
                                                           

  0%|          | 2677/569592 [2:13:19<693:36:42,  4.40s/it]
  0%|          | 2678/569592 [2:13:23<655:26:45,  4.16s/it]
                                                           

  0%|          | 2678/569592 [2:13:23<655:26:45,  4.16s/it]
  0%|          | 2679/569592 [2:13:27<639:30:41,  4.06s/it]
                                                           

  0%|          | 2679/569592 [2:13:27<639:30:41,  4.06s/it]
  0%|          | 2680/569592 [2:13:30<598:36:10,  3.80s/it]
                                                           

  0%|          | 2680/569592 [2:13:30<598:36:10,  3.80s/it]
  0%|          | 2681/569592 [2:13:35<662:23:05,  4.21s/it]
                                                           

  0%|          | 2681/569592 [2:13:35<662:23:05,  4.21s/it]
  0%|          | 2682/569592 [2:13:36<505:03:54,  3.21s/it]
                                                           

  0%|          | 2682/569592 [2:13:36<505:03:54,  3.21s/it]
  0%|          | 2683/569592 [2:13:37<396:58:53,  2.52s/it]
                                                           

  0%|          | 2683/569592 [2:13:37<396:58:53,  2.52s/it]
  0%|          | 2684/569592 [2:13:42<507:11:33,  3.22s/it]
                                                           

  0%|          | 2684/569592 [2:13:42<507:11:33,  3.22s/it]
  0%|          | 2685/569592 [2:13:45<510:08:33,  3.24s/it]
                                                           

  0%|          | 2685/569592 [2:13:45<510:08:33,  3.24s/it]
  0%|          | 2686/569592 [2:13:49<537:13:46,  3.41s/it]
                                                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95476746 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
      

  0%|          | 2686/569592 [2:13:49<537:13:46,  3.41s/it]
  0%|          | 2687/569592 [2:13:52<552:21:55,  3.51s/it]
                                                           

  0%|          | 2687/569592 [2:13:52<552:21:55,  3.51s/it]
  0%|          | 2688/569592 [2:13:53<432:56:41,  2.75s/it]
                                                           

  0%|          | 2688/569592 [2:13:53<432:56:41,  2.75s/it]
  0%|          | 2689/569592 [2:13:54<348:04:47,  2.21s/it]
                                                           

  0%|          | 2689/569592 [2:13:54<348:04:47,  2.21s/it]
  0%|          | 2690/569592 [2:13:55<288:13:41,  1.83s/it]
                                                           

  0%|          | 2690/569592 [2:13:55<288:13:41,  1.83s/it]
  0%|          | 2691/569592 [2:13:59<369:28:06,  2.35s/it]
                                                           

  0%|          | 2691/569592 [2:13:59<369:28:06,  2.35s/it]
  0%|          | 2692/569592 [2:14:04<508:55:50,  3.23s/it]
                                                           

  0%|          | 2692/569592 [2:14:04<508:55:50,  3.23s/it]
  0%|          | 2693/569592 [2:14:05<400:10:45,  2.54s/it]
                                                           

  0%|          | 2693/569592 [2:14:05<400:10:45,  2.54s/it]
  0%|          | 2694/569592 [2:14:08<437:15:03,  2.78s/it]
                                                           

  0%|          | 2694/569592 [2:14:08<437:15:03,  2.78s/it]
  0%|          | 2695/569592 [2:14:12<474:02:47,  3.01s/it]
                                                           

  0%|          | 2695/569592 [2:14:12<474:02:47,  3.01s/it]
  0%|          | 2696/569592 [2:14:13<380:14:07,  2.41s/it]
                                                           

  0%|          | 2696/569592 [2:14:13<380:14:07,  2.41s/it]
  0%|          | 2697/569592 [2:14:14<312:29:07,  1.98s/it]
                                                           

  0%|          | 2697/569592 [2:14:14<312:29:07,  1.98s/it]
  0%|          | 2698/569592 [2:14:15<263:22:10,  1.67s/it]
                                                           

  0%|          | 2698/569592 [2:14:15<263:22:10,  1.67s/it]
  0%|          | 2699/569592 [2:14:16<228:13:15,  1.45s/it]
                                                           

  0%|          | 2699/569592 [2:14:16<228:13:15,  1.45s/it]
  0%|          | 2700/569592 [2:14:17<204:57:40,  1.30s/it]
                                                           

  0%|          | 2700/569592 [2:14:17<204:57:40,  1.30s/it]
  0%|          | 2701/569592 [2:14:18<189:57:09,  1.21s/it]
                                                           

  0%|          | 2701/569592 [2:14:18<189:57:09,  1.21s/it]
  0%|          | 2702/569592 [2:14:19<179:53:24,  1.14s/it]
                                                           

  0%|          | 2702/569592 [2:14:19<179:53:24,  1.14s/it]
  0%|          | 2703/569592 [2:14:22<261:58:57,  1.66s/it]
                                                           

  0%|          | 2703/569592 [2:14:22<261:58:57,  1.66s/it]
  0%|          | 2704/569592 [2:14:27<419:16:04,  2.66s/it]
                                                           

  0%|          | 2704/569592 [2:14:27<419:16:04,  2.66s/it]
  0%|          | 2705/569592 [2:14:28<367:19:45,  2.33s/it]
                                                           

  0%|          | 2705/569592 [2:14:28<367:19:45,  2.33s/it]
  0%|          | 2706/569592 [2:14:29<304:04:49,  1.93s/it]
                                                           

  0%|          | 2706/569592 [2:14:29<304:04:49,  1.93s/it]
  0%|          | 2707/569592 [2:14:33<383:40:01,  2.44s/it]
                                                           

  0%|          | 2707/569592 [2:14:33<383:40:01,  2.44s/it]
  0%|          | 2708/569592 [2:14:36<434:48:34,  2.76s/it]
                                                           

  0%|          | 2708/569592 [2:14:36<434:48:34,  2.76s/it]
  0%|          | 2709/569592 [2:14:38<394:37:36,  2.51s/it]
                                                           

  0%|          | 2709/569592 [2:14:38<394:37:36,  2.51s/it]
  0%|          | 2710/569592 [2:14:39<320:19:52,  2.03s/it]
                                                           

  0%|          | 2710/569592 [2:14:39<320:19:52,  2.03s/it]
  0%|          | 2711/569592 [2:14:43<388:19:25,  2.47s/it]
                                                           

  0%|          | 2711/569592 [2:14:43<388:19:25,  2.47s/it]
  0%|          | 2712/569592 [2:14:47<481:12:30,  3.06s/it]
                                                           

  0%|          | 2712/569592 [2:14:47<481:12:30,  3.06s/it]
  0%|          | 2713/569592 [2:14:48<394:07:07,  2.50s/it]
                                                           

  0%|          | 2713/569592 [2:14:48<394:07:07,  2.50s/it]
  0%|          | 2714/569592 [2:14:49<321:42:28,  2.04s/it]
                                                           

  0%|          | 2714/569592 [2:14:49<321:42/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:28,  2.04s/it]
  0%|          | 2715/569592 [2:14:54<426:39:51,  2.71s/it]
                                                           

  0%|          | 2715/569592 [2:14:54<426:39:51,  2.71s/it]
  0%|          | 2716/569592 [2:14:57<437:22:41,  2.78s/it]
                                                           

  0%|          | 2716/569592 [2:14:57<437:22:41,  2.78s/it]
  0%|          | 2717/569592 [2:14:59<405:17:32,  2.57s/it]
                                                           

  0%|          | 2717/569592 [2:14:59<405:17:32,  2.57s/it]
  0%|          | 2718/569592 [2:15:00<327:58:48,  2.08s/it]
                                                           

  0%|          | 2718/569592 [2:15:00<327:58:48,  2.08s/it]
  0%|          | 2719/569592 [2:15:03<376:28:03,  2.39s/it]
                                                           

  0%|          | 2719/569592 [2:15:03<376:28:03,  2.39s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102398576 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  0%|          | 2720/569592 [2:15:07<459:31:09,  2.92s/it]
                                                           

  0%|          | 2720/569592 [2:15:07<459:31:09,  2.92s/it]
  0%|          | 2721/569592 [2:15:10<456:34:43,  2.90s/it]
                                                           

  0%|          | 2721/569592 [2:15:10<456:34:43,  2.90s/it]
  0%|          | 2722/569592 [2:15:11<366:00:53,  2.32s/it]
                                                           

  0%|          | 2722/569592 [2:15:11<366:00:53,  2.32s/it]
  0%|          | 2723/569592 [2:15:13<386:06:43,  2.45s/it]
                                                           

  0%|          | 2723/569592 [2:15:13<386:06:43,  2.45s/it]
  0%|          | 2724/569592 [2:15:19<520:52:08,  3.31s/it]
                                                           

  0%|          | 2724/569592 [2:15:19<520:52:08,  3.31s/it]
  0%|          | 2725/569592 [2:15:20<448:39:42,  2.85s/it]
                                                           

  0%|          | 2725/569592 [2:15:21<448:39:42,  2.85s/it]
  0%|          | 2726/569592 [2:15:21<359:44:50,  2.28s/it]
                                                           

  0%|          | 2726/569592 [2:15:21<359:44:50,  2.28s/it]
  0%|          | 2727/569592 [2:15:23<343:37:13,  2.18s/it]
                                                           

  0%|          | 2727/569592 [2:15:23<343:37:13,  2.18s/it]
  0%|          | 2728/569592 [2:15:29<482:45:50,  3.07s/it]
                                                           

  0%|          | 2728/569592 [2:15:29<482:45:50,  3.07s/it]
  0%|          | 2729/569592 [2:15:30<385:09:26,  2.45s/it]
                                                           

  0%|          | 2729/569592 [2:15:30<385:09:26,  2.45s/it]
  0%|          | 2730/569592 [2:15:31<327:20:17,  2.08s/it]
                                                           

  0%|          | 2730/569592 [2:15:31<327:20:17,  2.08s/it]
  0%|          | 2731/569592 [2:15:33<353:36:15,  2.25s//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
it]
                                                           

  0%|          | 2731/569592 [2:15:33<353:36:15,  2.25s/it]
  0%|          | 2732/569592 [2:15:39<502:57:26,  3.19s/it]
                                                           

  0%|          | 2732/569592 [2:15:39<502:57:26,  3.19s/it]
  0%|          | 2733/569592 [2:15:40<396:54:48,  2.52s/it]
                                                           

  0%|          | 2733/569592 [2:15:40<396:54:48,  2.52s/it]
  0%|          | 2734/569592 [2:15:43<440:48:16,  2.80s/it]
                                                           

  0%|          | 2734/569592 [2:15:43<440:48:16,  2.80s/it]
  0%|          | 2735/569592 [2:15:44<353:28:39,  2.24s/it]
                                                           

  0%|          | 2735/569592 [2:15:44<353:28:39,  2.24s/it]
  0%|          | 2736/569592 [2:15:49<500:21:50,  3.18s/it]
                                                           

  0%|          | 2736/569592 [2:15:50<500:21:50,  3.18/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97555518 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
s/it]
  0%|          | 2737/569592 [2:15:50<394:58:13,  2.51s/it]
                                                           

  0%|          | 2737/569592 [2:15:50<394:58:13,  2.51s/it]
  0%|          | 2738/569592 [2:15:51<322:21:11,  2.05s/it]
                                                           

  0%|          | 2738/569592 [2:15:51<322:21:11,  2.05s/it]
  0%|          | 2739/569592 [2:15:54<334:15:08,  2.12s/it]
                                                           

  0%|          | 2739/569592 [2:15:54<334:15:08,  2.12s/it]
  0%|          | 2740/569592 [2:16:00<515:23:56,  3.27s/it]
                                                           

  0%|          | 2740/569592 [2:16:00<515:23:56,  3.27s/it]
  0%|          | 2741/569592 [2:16:01<407:49:37,  2.59s/it]
                                                           

  0%|          | 2741/569592 [2:16:01<407:49:37,  2.59s/it]
  0%|          | 2742/569592 [2:16:04<444:13:20,  2.82s/it]
                                                           

  0%|          | 2742/569592 [2:16:04<444:13:20,  2.82s/it]
  0%|          | 2743/569592 [2:16:08<475:48:23,  3.02s/it]
                                                           

  0%|          | 2743/569592 [2:16:08<475:48:23,  3.02s/it]
  0%|          | 2744/569592 [2:16:10<442:02:52,  2.81s/it]
                                                           

  0%|          | 2744/569592 [2:16:10<442:02:52,  2.81s/it]
  0%|          | 2745/569592 [2:16:11<353:44:33,  2.25s/it]
                                                           

  0%|          | 2745/569592 [2:16:11<353:44:33,  2.25s/it]
  0%|          | 2746/569592 [2:16:12<292:40:46,  1.86s/it]
                                                           

  0%|          | 2746/569592 [2:16:12<292:40:46,  1.86s/it]
  0%|          | 2747/569592 [2:16:14<304:06:23,  1.93s/it]
                                                           

  0%|          | 2747/569592 [2:16:14<304:06:23,  1.93s/it]
  0%|          | 2748/569592 [2:16:20<522:43:01,  3.32s/it]
                                                           

  0%|          | 2748/569592 [2:16:20<522:43:01,  3.32s/it]
  0%|          | 2749/569592 [2:16:21<411:39:53,  2.61s/it]
                                                           

  0%|          | 2749/569592 [2:16:21<411:39:53,  2.61s/it]
  0%|          | 2750/569592 [2:16:22<334:21:32,  2.12s/it]
                                                           

  0%|          | 2750/569592 [2:16:22<334:21:32,  2.12s/it]
  0%|          | 2751/569592 [2:16:25<340:08:48,  2.16s/it]
                                                           

  0%|          | 2751/569592 [2:16:25<340:08:48,  2.16s/it]
  0%|          | 2752/569592 [2:16:31<532:53:49,  3.38s/it]
                                                           

  0%|          | 2752/569592 [2:16:31<532:53:49,  3.38s/it]
  0%|          | 2753/569592 [2:16:32<418:04:49,  2.66s/it]
                                                           

  0%|          | 2753/569592 [2:16:32<418:04:49, /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 2.66s/it]
  0%|          | 2754/569592 [2:16:33<337:17:21,  2.14s/it]
                                                           

  0%|          | 2754/569592 [2:16:33<337:17:21,  2.14s/it]
  0%|          | 2755/569592 [2:16:36<395:02:22,  2.51s/it]
                                                           

  0%|          | 2755/569592 [2:16:36<395:02:22,  2.51s/it]
  0%|          | 2756/569592 [2:16:42<540:04:49,  3.43s/it]
                                                           

  0%|          | 2756/569592 [2:16:42<540:04:49,  3.43s/it]
  0%|          | 2757/569592 [2:16:43<422:56:03,  2.69s/it]
                                                           

  0%|          | 2757/569592 [2:16:43<422:56:03,  2.69s/it]
  0%|          | 2758/569592 [2:16:44<340:40:26,  2.16s/it]
                                                           

  0%|          | 2758/569592 [2:16:44<340:40:26,  2.16s/it]
  0%|          | 2759/569592 [2:16:46<339:17:51,  2.15s/it]
                                                           

  0%|          | 2759/569592 [2:16:46<339:17:51,  2.15s/it]
  0%|          | 2760/569592 [2:16:51<506:57:46,  3.22s/it]
                                                           

  0%|          | 2760/569592 [2:16:51<506:57:46,  3.22s/it]
  0%|          | 2761/569592 [2:16:55<505:02:04,  3.21s/it]
                                                           

  0%|          | 2761/569592 [2:16:55<505:02:04,  3.21s/it]
  0%|          | 2762/569592 [2:16:59<578:01:32,  3.67s/it]
                                                           

  0%|          | 2762/569592 [2:16:59<578:01:32,  3.67s/it]
  0%|          | 2763/569592 [2:17:03<555:46:37,  3.53s/it]
                                                           

  0%|          | 2763/569592 [2:17:03<555:46:37,  3.53s/it]
  0%|          | 2764/569592 [2:17:06<552:33:15,  3.51s/it]
                                                           

  0%|          | 2764/569592 [2:17:06<552:33:15,  3.51s/it]
  0%|          | 2765/569592 [2:17:07<431:03:16,  2.74s/it]
                                                           

  0%|          | 2765/569592 [2:17:07<431:03:16,  2.74s/it]
  0%|          | 2766/569592 [2:17:12<549:39:04,  3.49s/it]
                                                           

  0%|          | 2766/569592 [2:17:12<549:39:04,  3.49s/it]
  0%|          | 2767/569592 [2:17:16<551:40:52,  3.50s/it]
                                                           

  0%|          | 2767/569592 [2:17:16<551:40:52,  3.50s/it]
  0%|          | 2768/569592 [2:17:19<547:07:08,  3.47s/it]
                                                           

  0%|          | 2768/569592 [2:17:19<547:07:08,  3.47s/it]
  0%|          | 2769/569592 [2:17:24<606:13:48,  3.85s/it]
                                                           

  0%|          | 2769/569592 [2:17:24<606:13:48,  3.85s/it]
  0%|          | 2770/569592 [2:17:28<641:23:27,  4.07s/it]
                                                           

  0%|          | 2770/569592 [2:17:28<641:23:27,  4.07s/it]
  0%|          | 2771/569592 [2:17:29<492:01:56,  3.13s/it]
                                                           

  0%|          | 2771/569592 [2:17:29<492:01:56,  3.13s/it]
  0%|          | 2772/569592 [2:17:35<595:35:47,  3.78s/it]
                                                           

  0%|          | 2772/569592 [2:17:35<595:35:47,  3.78s/it]
  0%|          | 2773/569592 [2:17:40<650:27:40,  4.13s/it]
                                                           

  0%|          | 2773/569592 [2:17:40<650:27:40,  4.13s/it]
  0%|          | 2774/569592 [2:17:43<616:22:22,  3.91s/it]
                                                           

  0%|          | 2774/569592 [2:17:43<616:22:22,  3.91s/it]
  0%|          | 2775/569592 [2:17:44<474:49:30,  3.02s/it]
                                                           

  0%|          | 2775/569592 [2:17:44<474:49:30,  3.02s/it]
  0%|          | 2776/569592 [2:17:49<553:59:49,  3.52s/it]
                                           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                

  0%|          | 2776/569592 [2:17:49<553:59:49,  3.52s/it]
  0%|          | 2777/569592 [2:17:52<566:47:54,  3.60s/it]
                                                           

  0%|          | 2777/569592 [2:17:52<566:47:54,  3.60s/it]
  0%|          | 2778/569592 [2:17:57<616:14:04,  3.91s/it]
                                                           

  0%|          | 2778/569592 [2:17:57<616:14:04,  3.91s/it]
  0%|          | 2779/569592 [2:18:02<655:28:02,  4.16s/it]
                                                           

  0%|          | 2779/569592 [2:18:02<655:28:02,  4.16s/it]
  0%|          | 2780/569592 [2:18:05<603:22:03,  3.83s/it]
                                                           

  0%|          | 2780/569592 [2:18:05<603:22:03,  3.83s/it]
  0%|          | 2781/569592 [2:18:10<651:00:52,  4.13s/it]
                                                           

  0%|          | 2781/569592 [2:18:10<651:00:52,  4.13s/it]
  0%|          | 2782/569592 [2:18:14<675:52:56,  4.29s/it]
                                                           

  0%|          | 2782/569592 [2:18:14<675:52:56,  4.29s/it]
  0%|          | 2783/569592 [2:18:18<625:56:59,  3.98s/it]
                                                           

  0%|          | 2783/569592 [2:18:18<625:56:59,  3.98s/it]
  0%|          | 2784/569592 [2:18:21<579:20:50,  3.68s/it]
                                                           

  0%|          | 2784/569592 [2:18:21<579:20:50,  3.68s/it]
  0%|          | 2785/569592 [2:18:25<630:57:49,  4.01s/it]
                                                           

  0%|          | 2785/569592 [2:18:25<630:57:49,  4.01s/it]
  0%|          | 2786/569592 [2:18:30<664:18:22,  4.22s/it]
                                                           

  0%|          | 2786/569592 [2:18:30<664:18:22,  4.22s/it]
  0%|          | 2787/569592 [2:18:35<683:30:15,  4.34s/it]
                                                           

  0%|          | 2787/569592 [2:18:35<683:30:15,  4.34s/it]
  0%|          | 2788/569592 [2:18:38<647:40:33,  4.11s/it]
                                                           

  0%|          | 2788/569592 [2:18:38<647:40:33,  4.11s/it]
  0%|          | 2789/569592 [2:18:43<666:30:57,  4.23s/it]
                                                           

  0%|          | 2789/569592 [2:18:43<666:30:57,  4.23s/it]
  0%|          | 2790/569592 [2:18:47<688:50:21,  4.38s/it]
                                                           

  0%|          | 2790/569592 [2:18:48<688:50:21,  4.38s/it]
  0%|          | 2791/569592 [2:18:52<703:19:20,  4.47s/it]
                                                           

  0%|          | 2791/569592 [2:18:52<703:19:20,  4.47s/it]
  0%|          | 2792/569592 [2:18:55<634:09:30,  4.03s/it]
                                                           

  0%|          | 2792/569592 [2:18:55<634:09:30,  4.03s/it]
  0%|          | 2793/569592 [2:18:58<593:41:52,  3.77s/it]
                                                           

  0%|          | 2793/569592 [2:18:58<593:41:52,  3.77s/it]
  0%|          | 2794/569592 [2:19:01<559:45:49,  3.56s/it]
                                                           

  0%|          | 2794/569592 [2:19:01<559:45:49,  3.56s/it]
  0%|          | 2795/569592 [2:19:05<551:02:38,  3.50s/it]
                                                           

  0%|          | 2795/569592 [2:19:05<551:02:38,  3.50s/it]
  0%|          | 2796/569592 [2:19:09<576:03:25,  3.66s/it]
                                                           

  0%|          | 2796/569592 [2:19:09<576:03:25,  3.66s/it]
  0%|          | 2797/569592 [2:19:12<563:49:37,  3.58s/it]
                                                           

  0%|          | 2797/569592 [2:19:12<563:49:37,  3.58s/it]
  0%|          | 2798/569592 [2:19:16<556:11:51,  3.53s/it]
                                                           

  0%|          | 2798/569592 [2:19:16<556:11:51,  3.53s/it]
  0%|          | 2799/569592 [2:19:21<621:50:30,  3.95s/it]
                                                           

  0%|          | 2799/569592 [2:19:21<621:50:30,  3.95s/it]
  0%|          | 2800/569592 [2:19:21<480:19:17,  3.05s/it]
                                                           

  0%|          | 2800/569592 [2:19:22<480:19:17,  3.05s/it]
  0%|          | 2801/569592 [2:19:22<380:11:04,  2.41s/it]
                                                           

  0%|          | 2801/569592 [2:19:22<380:11:04,  2.41s/it]
  0%|          | 2802/569592 [2:19:26<431:07:59,  2.74s/it]
                                                           

  0%|          | 2802/569592 [2:19:26<431:07:59,  2.74s/it]
  0%|          | 2803/569592 [2:19:27<350:55:34,  2.23s/it]
                                                           

  0%|          | 2803/569592 [2:19:27<350:55:34,  2.23s/it]
  0%|          | 2804/569592 [2:19:31<415:14:33,  2.64s/it]
                                                           

  0%|          | 2804/569592 [2:19/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95807054 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:31<415:14:33,  2.64s/it]
  0%|          | 2805/569592 [2:19:35<514:48:23,  3.27s/it]
                                                           

  0%|          | 2805/569592 [2:19:35<514:48:23,  3.27s/it]
  0%|          | 2806/569592 [2:19:36<403:35:30,  2.56s/it]
                                                           

  0%|          | 2806/569592 [2:19:36<403:35:30,  2.56s/it]
  0%|          | 2807/569592 [2:19:37<329:30:30,  2.09s/it]
                                                           

  0%|          | 2807/569592 [2:19:37<329:30:30,  2.09s/it]
  0%|          | 2808/569592 [2:19:42<470:52:26,  2.99s/it]
                                                           

  0%|          | 2808/569592 [2:19:42<470:52:26,  2.99s/it]
  0%|          | 2809/569592 [2:19:46<497:39:23,  3.16s/it]
                                                           

  0%|          | 2809/569592 [2:19:46<497:39:23,  3.16s/it]
  0%|          | 2810/569592 [2:19:49<503:31:37,  3.20s/it]
                                                           

  0%|          | 2810/569592 [2:19:49<503:31:37,  3.20s/it]
  0%|          | 2811/569592 [2:19:53<519:16:15,  3.30s/it]
                                                           

  0%|          | 2811/569592 [2:19:53<519:16:15,  3.30s/it]
  0%|          | 2812/569592 [2:19:54<407:18:51,  2.59s/it]
                                                           

  0%|          | 2812/569592 [2:19:54<407:18:51,  2.59s/it]
  0%|          | 2813/569592 [2:19:55<329:43:35,  2.09s/it]
                                                           

  0%|          | 2813/569592 [2:19:55<329:43:35,  2.09s/it]
  0%|          | 2814/569592 [2:19:55<275:48:24,  1.75s/it]
                                                           

  0%|          | 2814/569592 [2:19:56<275:48:24,  1.75s/it]
  0%|          | 2815/569592 [2:19:56<238:33:09,  1.52s/it]
                                                           

  0%|          | 2815/569592 [2:19:56<238:33:09,  1.52s/it]
  0%|          | 2816/569592 [2:19:57<210:21:18,  1.34s/it]
                                                           

  0%|          | 2816/569592 [2:19:57<210:21:18,  1.34s/it]
  0%|          | 2817/569592 [2:19:58<192:03:04,  1.22s/it]
                                                           

  0%|          | 2817/569592 [2:19:58<192:03:04,  1.22s/it]
  0%|          | 2818/569592 [2:19:59<179:53:06,  1.14s/it]
                                                           

  0%|          | 2818/569592 [2:19:59<179:53:06,  1.14s/it]
  0%|          | 2819/569592 [2:20:03<304:01:52,  1.93s/it]
                                                           

  0%|          | 2819/569592 [2:20:03<304:01:52,  1.93s/it]
  0%|          | 2820/569592 [2:20:07<415:18:50,  2.64s/it]
                                                           

  0%|          | 2820/569592 [2:20:07<415:18:50,  2.64s/it]
  0%|          | 2821/569592 [2:20:08<338:26:01,  2.15s/it]
                                                           

  0%|          | 2821/569592 [2:20:08<338:26:01,  2.15s/it]
  0%|          | 2822/569592 [2:20:09<281:22:07,  1.79s/it]
                                                           

  0%|          | 2822/569592 [2:20:09<281:22:07,  1.79s/it]
  0%|          | 2823/569592 [2:20:12<322:05:01,  2.05s/it]
                                                           

  0%|          | 2823/569592 [2:20:12<322:05:01,  2.05s/it]
  0%|          | 2824/569592 [2:20:16<434:25:16,  2.76s/it]
                                                           

  0%|          | 2824/569592 [2:20:16<434:25:16,  2.76s/it]
  0%|          | 2825/569592 [2:20:18<386:39:38,  2.46s/it]
                                                           

  0%|          | 2825/569592 [2:20:18<386:39:38,  2.46s/it]
  0%|          | 2826/569592 [2:20:19<317:50:33,  2.02s/it]
                                                           

  0%|          | 2826/569592 [2:20:19<317:50:33,  2.02s/it]
  0%|          | 2827/569592 [2:20:23<422:55:05,  2.69s/it]
                                                           

  0%|          | 2827/569592 [2:20:23<422:55:05,  2.69s/it]
  0%|          | 2828/569592 [2:20:26<422:28:18,  2.68s/it]
                                                           

  0%|          | 2828/569592 [2:20:26<422:28:18,  2.68s/it]
  0%|          | 2829/569592 [2:20:29<417:54:14,  2.65s/it]
                                                           

  0%|          | 2829/569592 [2:20:29<417:54:14,  2.65s/it]
  0%|          | 2830/569592 [2:20:30<337:49:21,  2.15s/it]
                                                           

  0%|          | 2830/569592 [2:20:30<337:49:21,  2.15s/it]
  0%|          | 2831/569592 [2:20:33<395:50:32,  2.51s/it]
                                                           

  0%|          | 2831/569592 [2:20:33<395:50:32,  2.51s/it]
  0%|          | 2832/569592 [2:20:38<530:53:57,  3.37s/it]
                                                           

  0%|          | 2832/569592 [2:20:38<530:53:57,  3.37s/it]
  0%|          | 2833/569592 [2:20:39<417:59:19,  2.66s/it]
                                                           

  0%|          | 2833/569592 [2:20:39<417:59:19,  2.66s/it]
  0%|          | 2834/569592 [2:20:41<360:35:51,  2.29s/it]
                                                           

  0%|          | 2834/569592 [2:20:41<360:35:51,  2.29s/it]
  0%|          | 2835/569592 [2:20:43<338:01:12,  2.15s/it]
                                                           

  0%|          | 2835/569592 [2:20:43<338:01:12,  2.15s/it]
  0%|          | 2836/569592 [2:20:48<503:44:50,  3.20s/it]
                                                           

  0%|          | 2836/569592 [2:20:48<503:44:50,  3.20s/it]
  0%|          | 2837/569592 [2:20:49<398:41:55,  2.53s/it]
                                                           

  0%|          | 2837/569592 [2:20:49<398:41:55,  2.53s/it]
  0%|          | 2838/569592 [2:20:50<326:18:28,  2.07s/it]
                                                           

  0%|          | 2838/569592 [2:20:50<326:18:28,  2.07s/it]
  0%|          | 2839/569592 [2:20:52<328:09:49,  2.08s/it]
                                                           

  0%|          | 2839/569592 [2:20:52<328:09:49,  2.08s/it]
  0%|          | 2840/569592 [2:20:58<483:04:47,  3.07s/it]
                                                           

  0%|          | 2840/569592 [2:20:58<483:04:47,  3.07s/it]
  0%|          | 2841/569592 [2:20:59<398:03:37,  2.53s/it]
                                                           

  0%|          | 2841/569592 [2:20:59<398:03:37,  2.53s/it]
  0%|          | 2842/569592 [2:21:02<425:49:22,  2.70s/it]
                                                           

  0%|          | 2842/569592 [2:21:02<425:49:22,  2.70s/it]
  0%|          | 2843/569592 [2:21:03<342:29:38,  2.18s/it]
                                                           

  0%|          | 2843/569592 [2:21:03<342:29:38,  2.18s/it]
  0%|          | 2844/569592 [2:21:09<514:26:01,  3.27s/it]
                                                           

  0%|          | 2844/569592 [2:21:09<514:26:01,  3.27s/it]
  0%|          | 2845/569592 [2:21:10<408:59:06,  2.60s/it]
                                                           

  0%|          | 2845/569592 [2:21:10<408:59:06,  2.60s/it]
  0%|          | 2846/569592 [2:21:11<331:51:33,  2.11s/it]
                                                           

  0%|          | 2846/569592 [2:21:11<331:51:33,  2.11s/it]
  0%|          | 2847/569592 [2:21:13<315:03:14,  2.00s/it]
                                                           

  0%|          | 2847/569592 [2:21:13<315:03:14,  2.00s/it]
  1%|          | 2848/569592 [2:21:17<450:23:25,  2.86s/it]
                                                           

  1%|          | 2848/569592 [2:21:17<450:23:25,  2.86s/it]
  1%|          | 2849/569592 [2:21:19<392:57:58,  2.50s/it]
                                                           

  1%|          | 2849/569592 [2:21:19<392:57:58,  2.50s/it]
  1%|          | 2850/569592 [2:21:22<399:16:33,  2.54s/it]
                                                           

  1%|          | 2850/569592 [2:21:22<399:16:33,  2.54s/it]
  1%|          | 2851/569592 [2:21:23<331:39:52,  2.11s/it]
                                                           

  1%|          | 2851/569592 [2:21:23<331:39:52,  2.11s/it]
  1%|          | 2852/569592 [2:21:28<479:35:04,  3.05s/it]
                                                           

  1%|          | 2852/569592 [2:21:28<479:35:04,  3.05s/it]
  1%|          | 2853/569592 [2:21:29<385:44:46,  2.45s/it]
                                                           

  1%|          | 2853/569592 [2:21:29<385:44:46,  2.45s/it]
  1%|          | 2854/569592 [2:21:31<380:09:37,  2.41s/it]
                                                           

  1%|          | 2854/569592 [2:21:31<380:09:37,  2.41s/it]
  1%|          | 2855/569592 [2:21:35<427:00:47,  2.71s/it]
                                                           

  1%|          | 2855/569592 [2:21:35<427:00:47,  2.71s/it]
  1%|          | 2856/569592 [2:21:39<472:32:27,  3.00s/it]
                                                           

  1%|          | 2856/569592 [2:21:39<472:32:27,  3.00s/it]
  1%|          | 2857/569592 [2:21:40<377:27:41,  2.40s/it]
                                                           

  1%|          | 2857/569592 [2:21:40<377:27:41,  2.40s/it]
  1%|          | 2858/569592 [2:21:42<383:34:27,  2.44s/it]
                                                           

  1%|          | 2858/569592 [2:21:42<383:34:27,  2.44s/it]
  1%|          | 2859/569592 [2:21:43<313:41:19,  1.99s/it]
                                                           

  1%|          | 2859/569592 [2:21:43<313:41:19,  1.99s/it]
  1%|          | 2860/569592 [2:21:50<534:56:30,  3.40s/it]
                                                           

  1%|          | 2860/569592 [2:21:50<534:56:30,  3.40s/it]
  1%|          | 2861/569592 [2:21:51<419:08:34,  2.66s/it]
                                                           

  1%|          | 2861/569592 [2:21:51<419:08:34,  2.66s/it]
  1%|          | 2862/569592 [2:21:53<387:35:18,  2.46s/it]
                                                           

  1%|          | 2862/569592 [2:21:53<387:35:18,  2.46s/it]
  1%|          | 2863/569592 [2:21:54<315:40:45,  2.01s/it]
                                                           

  1%|          | 2863/569592 [2:21:54<315:40:45,  2.01s/it]
  1%|          | 2864/569592 [2:21:58<434:39:16,  2.76s/it]
                                                           

  1%|          | 2864/569592 [2:21:58<434:39:16,  2.76s/it]
  1%|          | 2865/569592 [2:22:00<371:37:43,  2.36s/it]
                                                           

  1%|          | 2865/569592 [2:22:00<371:37:43,  2.36s/it]
  1%|          | 2866/569592 [2:22:03<424:49:38,  2.70s/it]
                                                           

  1%|          | 2866/569592 [2:22:03<424:49:38,  2.70s/it]
  1%|          |/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 2867/569592 [2:22:04<344:17:01,  2.19s/it]
                                                           

  1%|          | 2867/569592 [2:22:04<344:17:01,  2.19s/it]
  1%|          | 2868/569592 [2:22:10<548:32:05,  3.48s/it]
                                                           

  1%|          | 2868/569592 [2:22:11<548:32:05,  3.48s/it]
  1%|          | 2869/569592 [2:22:11<427:22:02,  2.71s/it]
                                                           

  1%|          | 2869/569592 [2:22:11<427:22:02,  2.71s/it]
  1%|          | 2870/569592 [2:22:15<470:23:17,  2.99s/it]
                                                           

  1%|          | 2870/569592 [2:22:15<470:23:17,  2.99s/it]
  1%|          | 2871/569592 [2:22:17<401:56:07,  2.55s/it]
                                                           

  1%|          | 2871/569592 [2:22:17<401:56:07,  2.55s/it]
  1%|          | 2872/569592 [2:22:18<347:35:49,  2.21s/it]
                                                           

  1%|          | 2872/569592 [2:22:18<347:35:49,  2.21s/it]
  1%|          | 2873/569592 [2:22:19<290:41:31,  1.85s/it]
                                                           

  1%|          | 2873/569592 [2:22:19<290:41:31,  1.85s/it]
  1%|          | 2874/569592 [2:22:25<509:30:23,  3.24s/it]
                                                           

  1%|          | 2874/569592 [2:22:25<509:30:23,  3.24s/it]
  1%|          | 2875/569592 [2:22:26<402:49:25,  2.56s/it]
                                                           

  1%|          | 2875/569592 [2:22:26<402:49:25,  2.56s/it]
  1%|          | 2876/569592 [2:22:29<419:26:11,  2.66s/it]
                                                           

  1%|          | 2876/569592 [2:22:29<419:26:11,  2.66s/it]
  1%|          | 2877/569592 [2:22:30<341:02:58,  2.17s/it]
                                                           

  1%|          | 2877/569592 [2:22:30<341:02:58,  2.17s/it]
  1%|          | 2878/569592 [2:22:33<361:33:56,  2.30s/it]
                                                           

  1%|          | 2878/569592 [2:22:33<361:33:56,  2.30s/it]
  1%|          | 2879/569592 [2:22:37<446:01:32,  2.83s/it]
                                                           

  1%|          | 2879/569592 [2:22:37<446:01:32,  2.83s/it]
  1%|          | 2880/569592 [2:22:42<558:01:15,  3.54s/it]
                                                           

  1%|          | 2880/569592 [2:22:42<558:01:15,  3.54s/it]
  1%|          | 2881/569592 [2:22:47<628:43:27,  3.99s/it]
                                                           

  1%|          | 2881/569592 [2:22:47<628:43:27,  3.99s/it]
  1%|          | 2882/569592 [2:22:54<773:19:24,  4.91s/it]
                                                           

  1%|          | 2882/569592 [2:22:54<773:19:24,  4.91s/it]
  1%|          | 2883/569592 [2:22:57<681:33:21,  4.33s/it]
                                                           

  1%|          | 2883/569592 [2:22:57<681:33:21,  4.33s/it]
  1%|          | 2884/569592 [2:22:58<521:03:09,  3.31s/it]
                                                           

  1%|          | 2884/569592 [2:22:58<521:03:09,  3.31s/it]
  1%|          | 2885/569592 [2:23:03<595:42:08,  3.78s/it]
                                                           

  1%|          | 2885/569592 [2:23:03<595:42:08,  3.78s/it]
  1%|          | 2886/569592 [2:23:08<647:02:13,  4.11s/it]
                                                           

  1%|          | 2886/569592 [2:23:08<647:02:13,  4.11s/it]
  1%|          | 2887/569592 [2:23:12<647:47:03,  4.12s/it]
                                                           

  1%|          | 2887/569592 [2:23:12<647:47:03,  4.12s/it]
  1%|          | 2888/569592 [2:23:16<632:08:40,  4.02s/it]
                                                           

  1%|          | 2888/569592 [2:23:16<632:08:40,  4.02s/it]
  1%|          | 2889/569592 [2:23:21<696:04:36,  4.42s/it]
                                                           

  1%|          | 2889/569592 [2:23:21<696:04:36,  4.42s/it]
  1%|          | 2890/569592 [2:23:26<707:36:00,  4.50s/it]
                                                           

  1%|          | 2890/569592 [2:23:26<707:36:00,  4.50s/it]
  1%|          | 2891/569592 [2:23:31<718:06:29,  4.56s/it]
                                                           

  1%|          | 2891/569592 [2:23:31<718:06:29,  4.56s/it]
  1%|          | 2892/569592 [2:23:36<738:13:51,  4.69s/it]
                                                           

  1%|          | 2892/569592 [2:23:36<738:13:51,  4.69s/it]
  1%|          | 2893/569592 [2:23:40<708:09:08,  4.50s/it]
                                                           

  1%|          | 2893/569592 [2:23:40<708:09:08,  4.50s/it]
  1%|          | 2894/569592 [2:23:44<712:18:07,  4.52s/it]
                                                           

  1%|          | 2894/569592 [2:23:44<712:18:07,  4.52s/it]
  1%|          | 2895/569592 [2:23:49<716:59:17,  4.55s/it]
                                                           

  1%|          | 2895/569592 [2:23:49<716:59:17,  4.55s/it]
  1%|          | 2896/569592 [2:23:54<719:07:27,  4.57s/it]
                                                           

  1%|          | 2896/569592 [2:23:54<719:07:27,  4.57s/it]
  1%|          | 2897/569592 [2:23:58<735:36:01,  4.67s/it]
                                                           

  1%|          | 2897/569592 [2:23:58<735:36:01,  4.67s/it]
  1%|          | 2898/569592 [2:24:01<657:48:31,  4.18s/it]
                                                           

  1%|          | 2898/569592 [2:24:01<657:48:31,  4.18s/it]
  1%|          | 2899/569592 [2:24:06<678:29:58,  4.31s/it]
                                                           

  1%|          | 2899/569592 [2:24:06<678:29:58,  4.31s/it]
  1%|          | 2900/569592 [2:24:11<708:53:35,  4.50s/it]
                                                           

  1%|          | 2900/569592 [2:24:11<708:53:35,  4.50s/it]
  1%|          | 2901/569592 [2:24:15<676:10:01,  4.30s/it]
                                                           

  1%|          | 2901/569592 [2:24:15<676:10:01,  4.30s/it]
  1%|          | 2902/569592 [2:24:16<517:09:26,  3.29s/it]
                                                           

  1%|          | 2902/569592 [2:24:16<517:09:26,  3.29s/it]
  1%|          | 2903/569592 [2:24:21<609:08:11,  3.87s/it]
                                                           

  1%|          | 2903/569592 [2:24:21<609:08:11,  3.87s/it]
  1%|          | 2904/569592 [2:24:26<643:14:45,  4.09s/it]
                                                           

  1%|          | 2904/569592 [2:24:26<643:14:45,  4.09s/it]
  1%|          | 2905/569592 [2:24:30<670:44:05,  4.26s/it]
                                                           

  1%|          | 2905/569592 [2:24:30<670:44:05,  4.26s/it]
  1%|          | 2906/569592 [2:24:35<687:26:54,  4.37s/it]
                                                           

  1%|          | 2906/569592 [2:24:35<687:26:54,  4.37s/it]
  1%|          | 2907/569592 [2:24:40<710:54:18,  4.52s/it]
                                                           

  1%|          | 2907/569592 [2:24:40<710:54:18,  4.52s/it]
  1%|          | 2908/569592 [2:24:44<692:22:10,  4.40s/it]
                                                           

  1%|          | 2908/569592 [2:24:44<692:22:10,  4.40s/it]
  1%|          | 2909/569592 [2:24:49<704:45:04,  4.48s/it]
                                                           

  1%|          | 2909/569592 [2:24:49<704:45:04,  4.48s/it]
  1%|          | 2910/569592 [2:24:49<535:13:49,  3.40s/it]
                                                           

  1%|          | 2910/569592 [2:24:49<535:13:49,  3.40s/it]
  1%|          | 2911/569592 [2:24:53<532:25:09,  3.38s/it]
                                                           

  1%|          | 2911/569592 [2:24:53<532:25:09,  3.38s/it]
  1%|          | 2912/569592 [2:24:56<541:24:38,  3.44s/it]
                                                           

  1%|          | 2912/569592 [2:24:56<541:24:38,  3.44s/it]
  1%|          | 2913/569592 [2:25:02<623:49:16,  3.96s/it]
                                                           

  1%|          | 2913/569592 [2:25:02<623:49:16,  3.96s/it]
  1%|          | 2914/569592 [2:25:06<651:50:06,  4.14s/it]
                                                           

  1%|          | 2914/569592 [2:25:06<651:50:06,  4.14s/it]
  1%|          | 2915/569592 [2:25:10<652:08:06,  4.14s/it]
                                                           

  1%|          | 2915/569592 [2:25:10<652:08:06,  4.14s/it]
  1%|          | 2916/569592 [2:25:14<622:25:20,  3.95s/it]
                                                           

  1%|          | 2916/569592 [2:25:14<622:25:20,  3.95s/it]
  1%|          | 2917/569592 [2:25:19<677:06:57,  4.30s/it]
                                                           

  1%|          | 2917/569592 [2:25:19<677:06:57,  4.30s/it]
  1%|          | 2918/569592 [2:25:20<530:36:36,  3.37s/it]
                                                           

  1%|          | 2918/569592 [2:25:20<530:36:36,  3.37s/it]
  1%|          | 2919/569592 [2:25:21<414:10:14,  2.63s/it]
                                                           

  1%|          | 2919/569592 [2:25:21<414:10:14,  2.63s/it]
  1%|          | 2920/569592 [2:25:25<476:52:11,  3.03s/it]
                                                           

  1%|          | 2920/569592 [2:25:25<476:52:11,  3.03s/it]
  1%|          | 2921/569592 [2:25:30<571:55:13,  3.63s/it]
                                                           

  1%|          | 2921/569592 [2:25:30<571:55:13,  3.63s/it]
  1%|          | 2922/569592 [2:25:34<571:38:16,  3.63s/it]
                                                           

  1%|          | 2922/569592 [2:25:34<571:38:16,  3.63s/it]
  1%|          | 2923/569592 [2:25:39<636:42:35,  4.04s/it]
                                                           

  1%|          | 2923/569592 [2:25:39<636:42:35,  4.04s/it]
  1%|          | 2924/569592 [2:25:40<491:25:32,  3.12s/it]
                                                           

  1%|          | 2924/569592 [2:25:40<491:25:32,  3.12s/it]
  1%|          | 2925/569592 [2:25:40<387:18:32,  2.46s/it]
                                                           

  1%|          | 2925/569592 [2:25:41<387:18:32,  2.46s/it]
  1%|          | 2926/569592 [2:25:42<319:38:26,  2.03s/it]
                                                           

  1%|          | 2926/569592 [2:25:42<319:38:26,  2.03s/it]
  1%|          | 2927/569592 [2:25:43<270:43:31,  1.72s/it]
                                                           

  1%|          | 2927/569592 [2:25:43<270:43:31,  1.72s/it]
  1%|          | 2928/569592 [2:25:46<371:08:24,  2.36s/it]
                                                           

  1%|          | 2928/569592 [2:25:46<371:08:24,  2.36s/it]
  1%|          | 2929/569592 [2:25:51<462:25:15,  2.94s/it]
                                                           

  1%|          | 2929/569592 [2:25:51<462:25:15,  2.94s/it]
  1%|          | 2930/569592 [2:25:52<368:42:06,  2.34s/it]
                                                           

  1%|          | 2930/569592 [2:25:52<368:42:06,  2.34s/it]
  1%|          | 2931/569592 [2:25:53<304:51:44,  1.94s/it]
                                                           

  1%|          | 2931/569592 [2:25:53<304:51:44,  1.94s/it]
  1%|          | 2932/569592 [2:25:54<261:00:30,  1.66s/it]
                                                           

  1%|          | 2932/569592 [2:25:54<261:00:30,  1.66s/it]
  1%|          | 2933/569592 [2:25:55<227:20:50,  1.44s/it]
                                                           

  1%|          | 2933/569592 [2:25:55<227:20:50,  1.44s/it]
  1%|          | 2934/569592 [2:25:56<204:45:48,  1.30s/it]
                                                           

  1%|          | 2934/569592 [2:25:56<204:45:48,  1.30s/it]
  1%|          | 2935/569592 [2:25:56<188:00:43,  1.19s/it]
                                                           

  1%|          | 2935/569592 [2:25:56<188:00:43,  1.19s/it]
  1%|          | 2936/569592 [2:26:02<410:44:30,  2.61s/it]
                                                           

  1%|          | 2936/569592 [2:26:02<410:44:30,  2.61s/it]
  1%|          | 2937/569592 [2:26:04<350:23:05,  2.23s/it]
                                                           

  1%|          | 2937/569592 [2:26:04<350:23:05,  2.23s/it]
  1%|          | 2938/569592 [2:26:05<291:41:03,  1.85s/it]
                                                           

  1%|          | 2938/569592 [2:26:05<291:41:03,  1.85s/it]
  1%|          | 2939/569592 [2:26:06<271:20:43,  1.72s/it]
                                                           

  1%|          | 2939/569592 [2:26:06<271:20:43,  1.72s/it]
  1%|          | 2940/569592 [2:26:13<496:54:41,  3.16s/it]
                                                           

  1%|          | 2940/569592 [2:26:13<496:54:41,  3.16s/it]
  1%|          | 2941/569592 [2:26:14<395:00:42,  2.51s/it]
                                                           

  1%|          | 2941/569592 [2:26:14<395:00:42,  2.51s/it]
  1%|          | 2942/569592 [2:26:15<332:00:03,  2.11s/it]
                                                           

  1%|          | 2942/569592 [2:26:15<332:00:03,  2.11s/it]
  1%|          | 2943/569592 [2:26:16<313:58:30,  1.99s/it]
                                                           

  1%|          | 2943/569592 [2:26:17<313:58:30,  1.99s/it]
  1%|          | 2944/569592 [2:26:22<495:47:40,  3.15s/it]
                                                           

  1%|          | 2944/569592 [2:26:22<495:47:40,  3.15s/it]
  1%|          | 2945/569592 [2:26:24<413:41:56,  2.63s/it]
                                                           

  1%|          | 2945/569592 [2:26:24<413:41:56,  2.63s/it]
  1%|          | 2946/569592 [2:26:25<339:44:19,  2.16s/it]
                                                           

  1%|          | 2946/569592 [2:26:25<339:44:19,  2.16s/it]
  1%|          | 2947/569592 [2:26:28<392:43:25,  2.50s/it]
                                                           

  1%|          | 2947/569592 [2:26:28<392:43:25,  2.50s/it]
  1%|          | 2948/569592 [2:26:33<511:49:00,  3.25s/it]
                                                           

  1%|          | 2948/569592 [2:26:33<511:49:00,  3.25s/it]
  1%|          | 2949/569592 [2:26:34<406:19:23,  2.58s/it]
                                                           

  1%|          | 2949/569592 [2:26:34<406:19:23,  2.58s/it]
  1%|          | 2950/569592 [2:26:35<328:19:18,  2.09s/it]
                                                           

  1%|          | 2950/569592 [2:26:35<328:19:18,  2.09s/it]
  1%|          | 2951/569592 [2:26:38<389:04:24,  2.47s/it]
                                                           

  1%|          | 2951/569592 [2:26:38<389:04:24,  2.47s/it]
  1%|          | 2952/569592 [2:26:42<446:35:36,  2.84s/it]
                                                           

  1%|          | 2952/569592 [2:26:42<446:35:36,  2.84s/it]
  1%|          | 2953/569592 [2:26:44<403:18:41,  2.56s/it]
                                                           

  1%|          | 2953/569592 [2:26:44<403:18:41,  2.56s/it]
  1%|          | 2954/569592 [2:26:46<352:35:24,  2.24s/it]
                                                           

  1%|          | 2954/569592 [2:26:46<352:35:24,  2.24s/it]
  1%|          | 2955/569592 [2:26:48<371:41:36,  2.36s/it]
                                                           

  1%|          | 2955/569592 [2:26:48<371:41:36,  2.36s/it]
  1%|          | 2956/569592 [2:26:52<459:16:24,  2.92s/it]
                                                           

  1%|          | 2956/569592 [2:26:52<459:16:24,  2.92s/it]
  1%|          | 2957/569592 [2:26:55<427:51:30,  2.72s/it]
                                                           

  1%|          | 2957/569592 [2:26:55<427:51:30,  2.72s/it]
  1%|          | 2958/569592 [2:26:56<365:51:06,  2.32s/it]
                                                           

  1%|          | 2958/569592 [2:26:56<365:51:06,  2.32s/it]
  1%|          | 2959/569592 [2:26:57<321:38:37,  2.04s/it]
                                                           

  1%|          | 2959/569592 [2:26:57<321:38:37,  2.04s/it]
  1%|          | 2960/569592 [2:27:03<485:57:08,  3.09s/it]
                                                           

  1%|          | 2960/569592 [2:27:03<485:57:08,  3.09s/it]
  1%|          | 2961/569592 [2:27:05<432:06:40,  2.75s/it]
                                                           

  1%|          | 2961/569592 [2:27:05<432:06:40,  2.75s/it]
  1%|          | 2962/569592 [2:27:06<365:07:51,  2.32s/it]
                                                           

  1%|          | 2962/569592 [2:27:06<365:07:51,  2.32s/it]
  1%|          | 2963/569592 [2:27:09<395:43:23,  2.51s/it]
                                                           

  1%|          | 2963/569592 [2:27:09<395:43:23,  2.51s/it]
  1%|          | 2964/569592 [2:27:13<469:09:25,  2.98s/it]
                                                           

  1%|          | 2964/569592 [2:27:13<469:09:25,  2.98s/it]
  1%|          | 2965/569592 [2:27:15<423:56:01,  2.69s/it]
                                                           

  1%|          | 2965/569592 [2:27:15<423:56:01,  2.69s/it]
  1%|          | 2966/569592 [2:27:16<341:47:08,  2.17s/it]
                                                           

  1%|          | 2966/569592 [2:27:16<341:47:08,  2.17s/it]
  1%|          | 2967/569592 [2:27:18<323:21:31,  2.05s/it]
                                                           

  1%|          | 2967/569592 [2:27:18<323:21:31,  2.05s/it]
  1%|          | 2968/569592 [2:27:23<483:43:44,  3.07s/it]
                                                           

  1%|          | 2968/569592 [2:27:23<483:43:44,  3.07s/it]
  1%|          | 2969/569592 [2:27:25<426:48:40,  2.71s/it]
                                                           

  1%|          | 2969/569592 [2:27:25<426:48:40,  2.71s/it]
  1%|          | 2970/569592 [2:27:29<462:35:47,  2.94s/it]
                                                           

  1%|          | 2970/569592 [2:27:29<462:35:47,  2.94s/it]
  1%|          | 2971/569592 [2:27:30<371:52:47,  2.36s/it]
                                                           

  1%|          | 2971/569592 [2:27:30<371:52:47,  2.36s/it]
  1%|          | 2972/569592 [2:27:34<441:05:57,  2.80s/it]
                                                           

  1%|          | 2972/569592 [2:27:34<441:05:57,  2.80s/it]
  1%|          | 2973/569592 [2:27:35<386:22:57,  2.45s/it]
                                                           

  1%|          | 2973/569592 [2:27:35<386:22:57,  2.45s/it]
  1%|          | 2974/569592 [2:27:38<377:35:28,  2.40s/it]
                                                           

  1%|          | 2974/569592 [2:27:38<377:35:28,  2.40s/it]
  1%|          | 2975/569592 [2:27:39<309:37:37,  1.97s/it]
                                                           

  1%|          | 2975/569592 [2:27:39<309:37:37,  1.97s/it]
  1%|          | 2976/569592 [2:27:44<460:33:47,  2.93s/it]
                                                           

  1%|          | 2976/569592 [2:27:44<460:33:47,  2.93s/it]
  1%|          | 2977/569592 [2:27:46<419:36:35,  2.67s/it]
                                                           

  1%|          | 2977/569592 [2:27:46<419:36:35,  2.67s/it]
  1%|          | 2978/569592 [2:27:50<477:47:30,  3.04s/it]
                                                           

  1%|          | 2978/569592 [2:27:50<477:47:30,  3.04s/it]
  1%|          | 2979/569592 [2:27:51<382:48:48,  2.43s/it]
                                                           

  1%|          | 2979/569592 [2:27:51<382:48:48,  2.43s/it]
  1%|          | 2980/569592 [2:27:54<432:02:30,  2.75s/it]
                                                           

  1%|          | 2980/569592 [2:27:54<432:02:30,  2.75s/it]
  1%|          | 2981/569592 [2:27:56<398:38:38,  2.53s/it]
                                                           

  1%|          | 2981/569592 [2:27:56<398:38:38,  2.53s/it]
  1%|          | 2982/569592 [2:27:58<372:17:51,  2.37s/it]
                                                           

  1%|          | 2982/569592 [2:27:58<372:17:51,  2.37s/it]
  1%|          | 2983/569592 [2:27:59<315:40:39,  2.01s/it]
                                                           

  1%|          | 2983/569592 [2:27:59<315:40:39,  2.01s/it]
  1%|          | 2984/569592 [2:28:04<438:45:52,  2.79s/it]
                                                           

  1%|          | 2984/569592 [2:28:04<438:45:52,  2.79s/it]
  1%|          | 2985/569592 [2:28:07<474:14:25,  3.01s/it]
                                                           

  1%|          | 2985/569592 [2:28:08<474/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95767500 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:14:25,  3.01s/it]
  1%|          | 2986/569592 [2:28:09<383:32:00,  2.44s/it]
                                                           

  1%|          | 2986/569592 [2:28:09<383:32:00,  2.44s/it]
  1%|          | 2987/569592 [2:28:10<313:50:01,  1.99s/it]
                                                           

  1%|          | 2987/569592 [2:28:10<313:50:01,  1.99s/it]
  1%|          | 2988/569592 [2:28:15<457:17:06,  2.91s/it]
                                                           

  1%|          | 2988/569592 [2:28:15<457:17:06,  2.91s/it]
  1%|          | 2989/569592 [2:28:16<382:07:10,  2.43s/it]
                                                           

  1%|          | 2989/569592 [2:28:16<382:07:10,  2.43s/it]
  1%|          | 2990/569592 [2:28:18<353:31:15,  2.25s/it]
                                                           

  1%|          | 2990/569592 [2:28:18<353:31:15,  2.25s/it]
  1%|          | 2991/569592 [2:28:21<418:45:39,  2.66s/it]
                                                           

  1%|          | 2991/569592 [2:28:21<418:45:39,  2.66s/it]
  1%|          | 2992/569592 [2:28:25<471:04:04,  2.99s/it]
                                                           

  1%|          | 2992/569592 [2:28:25<471:04:04,  2.99s/it]
  1%|          | 2993/569592 [2:28:26<380:11:23,  2.42s/it]
                                                           

  1%|          | 2993/569592 [2:28:26<380:11:23,  2.42s/it]
  1%|          | 2994/569592 [2:28:29<402:57:07,  2.56s/it]
                                                           

  1%|          | 2994/569592 [2:28:29<402:57:07,  2.56s/it]
  1%|          | 2995/569592 [2:28:34<504:00:32,  3.20s/it]
                                                           

  1%|          | 2995/569592 [2:28:34<504:00:32,  3.20s/it]
  1%|          | 2996/569592 [2:28:39<595:04:54,  3.78s/it]
                                                           

  1%|          | 2996/569592 [2:28:39<595:04:54,  3.78s/it]
  1%|          | 2997/569592 [2:28:44<635:53:50,  4.04s/it]
                                                           

  1%|          | 2997/569592 [2:28:44<635:53:50,  4.04s/it]
  1%|          | 2998/569592 [2:28:48<651:00:10,  4.14s/it]
                                                           

  1%|          | 2998/569592 [2:28:48<651:00:10,  4.14s/it]
  1%|          | 2999/569592 [2:28:51<607:00:21,  3.86s/it]
                                                           

  1%|          | 2999/569592 [2:28:51<607:00:21,  3.86s/it]
  1%|          | 3000/569592 [2:28:54<575:23:39,  3.66s/it]
                                                           

  1%|          | 3000/569592 [2:28:54<575:23:39,  3.66s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-3000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-3000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-3000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-3000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-3000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-3000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-2000] due to args.save_total_limit

  1%|          | 3001/569592 [2:30:55<6103:34:36, 38.78s/it]
                                                            

  1%|          | 3001/569592 [2:30:55<6103:34:36, 38.78s/it]
  1%|          | 3002/569592 [2:30:59<4458:31:43, 28.33s/it]
                                                            

  1%|          | 3002/569592 [2:30:59<4458:31:43, 28.33s/it]
  1%|          | 3003/569592 [2:31:03<3304:45:03, 21.00s/it]
                                                            

  1%|          | 3003/569592 [2:31:03<3304:45:03, 21.00s/it]
  1%|          | 3004/569592 [2:31:06<2478:17:47, 15.75s/it]
                                                            

  1%|          | 3004/569592 [2:31:06<2478:17:47, 15.75s/it]
  1%|          | 3005/569592 [2:31:11<1965:12:45, 12.49s/it]
                                                            

  1%|          | 3005/569592 [2:31:11<1965:12:45, 12.49s/it]
  1%|          | 3006/569592 [2:31:14<1527:59:13,  9.71s/it]
                                                            

  1%|          | 3006/569592 [2:31:14<1527:59:13,  9.71s/it]
  1%|          | 3007/569592 [2:31:20<1310:28:33,  8.33s/it]
                                                            

  1%|          | 3007/569592 [2:31:20<1310:28:33,  8.33s/it]
  1%|          | 3008/569592 [2:31:24<1133:44:59,  7.20s/it]
                                                            

  1%|          | 3008/569592 [2:31:24<1133:44:59,  7.20s/it]
  1%|          | 3009/569592 [2:31:29<1006:19:23,  6.39s/it]
                                                            

  1%|          | 3009/569592 [2:31:29<1006:19:23,  6.39s/it]
  1%|          | 3010/569592 [2:31:33<924:11:46,  5.87s/it] 
                                                           

  1%|          | 3010/569592 [2:31:33<924:11:46,  5.87s/it]
  1%|          | 3011/569592 [2:31:38<846:20:47,  5.38s/it]
                                                           

  1%|          | 3011/569592 [2:31:38<846:20:47,  5.38s/it]
  1%|          | 3012/569592 [2:31:41<751:57:30,  4.78s/it]
                                                           

  1%|          | 3012/569592 [2:31:41<751:57:30,  4.78s/it]
  1%|          | 3013/569592 [2:31:46<754:28:30,  4.79s/it]
                                                           

  1%|          | 3013/569592 [2:31:46<754:28:30,  4.79s/it]
  1%|          | 3014/569592 [2:31:49<695:31:22,  4.42s/it]
                                                           

  1%|          | 3014/569592 [2:31:49<695:31:22,  4.42s/it]
  1%|          | 3015/569592 [2:31:50<529:42:41,  3.37s/it]
                                                           

  1%|          | 3015/569592 [2:31:50<529:42:41,  3.37s/it]
  1%|          | 3016/569592 [2:31:55<619:52:18,  3.94s/it]
                                                           

  1%|          | 3016/569592 [2:31:55<619:52:18,  3.94s/it]
  1%|          | 3017/569592 [2:31:59<607:43:03,  3.86s/it]
                                                           

  1%|          | 3017/569592 [2:31:59<607:43:03,  3.86s/it]
  1%|          | 3018/569592 [2:32:04<649:26:37,  4.13s/it]
                                                           

  1%|          | 3018/569592 [2:32:04<649:26:37,  4.13s/it]
  1%|          | 3019/569592 [2:32:08<670:27:25,  4.26s/it]
                                                           

  1%|          | 3019/569592 [2:32:08<670:27:25,  4.26s/it]
  1%|          | 3020/569592 [2:32:12<643:20:41,  4.09s/it]
                                                           

  1%|          | 3020/569592 [2:32:12<643:20:41,  4.09s/it]
  1%|          | 3021/569592 [2:32:18<713:51:04,  4.54s/it]
                                                           

  1%|          | 3021/569592 [2:32:18<713:51:04,  4.54s/it]
  1%|          | 3022/569592 [2:32:19<542:39:31,  3.45s/it]
                                                           

  1%|          | 3022/569592 [2:32:19<542:39:31,  3.45s/it]
  1%|          | 3023/569592 [2:32:23<577:15:03,  3.67s/it]
                                                           

  1%|          | 3023/569592 [2:32:23<577:15:03,  3.67s/it]
  1%|          | 3024/569592 [2:32:28<645:01:19,  4.10s/it]
                                                           

  1%|          | 3024/569592 [2:32:28<645:01:19,  4.10s/it]
  1%|          | 3025/569592 [2:32:31<603:45:20,  3.84s/it]
                                                           

  1%|          | 3025/569592 [2:32:31<603:45:20,  3.84s/it]
  1%|          | 3026/569592 [2:32:36<645:22:28,  4.10s/it]
                                                           

  1%|          | 3026/569592 [2:32:36<645:22:28,  4.10s/it]
  1%|          | 3027/569592 [2:32:37<505:10:30,  3.21s/it]
                                                           

  1%|          | 3027/569592 [2:32:37<505:10:30,  3.21s/it]
  1%|          | 3028/569592 [2:32:42<573:38:22,  3.64s/it]
                                                           

  1%|          | 3028/569592 [2:32:42<573:38:22,  3.64s/it]
  1%|          | 3029/569592 [2:32:46<597:31:35,  3.80s/it]
                                                           

  1%|          | 3029/569592 [2:32:46<597:31:35,  3.80s/it]
  1%|          | 3030/569592 [2:32:51<646:30:57,  4.11s/it]
                                                           

  1%|          | 3030/569592 [2:32:51<646:30:57,  4.11s/it]
  1%|          | 3031/569592 [2:32:55<666:29:00,  4.23s/it]
                                                           

  1%|          | 3031/569592 [2:32:55<666:29:00,  4.23s/it]
  1%|          | 3032/569592 [2:33:00<698:18:57,  4.44s/it]
                                                           

  1%|          | 3032/569592 [2:33:00<698:18:57,  4.44s/it]
  1%|          | 3033/569592 [2:33:05<715:14:26,  4.54s/it]
                                                           

  1%|          | 3033/569592 [2:33:05<715:14:26,  4.54s/it]
  1%|          | 3034/569592 [2:33:06<542:25:03,  3.45s/it]
                                                           

  1%|          | 3034/569592 [2:33:06<542:25:03,  3.45s/it]
  1%|          | 3035/569592 [2:33:11<606:33:55,  3.85s/it]
                                                           

  1%|          | 3035/569592 [2:33:11<606:33:55,  3.85s/it]
  1%|          | 3036/569592 [2:33:15<613:26:28,  3.90s/it]
                                                           

  1%|          | 3036/569592 [2:33:15<613:26:28,  3.90s/it]
  1%|          | 3037/569592 [2:33:20<672:09:01,  4.27s/it]
                                                           

  1%|          | 3037/569592 [2:33:20<672:09:01,  4.27s/it]
  1%|          | 3038/569592 [2:33:24<677:43:05,  4.31s/it]
                                                           

  1%|          | 3038/569592 [2:33:24<677:43:05,  4.31s/it]
  1%|          | 3039/569592 [2:33:29<695:09:46,  4.42s/it]
                                                           

  1%|          | 3039/569592 [2:33:29<695:09:46,  4.42s/it]
  1%|          | 3040/569592 [2:33:30<528:36:58,  3.36s/it]
                                                           

  1%|          | 3040/569592 [2:33:30<528:36:58,  3.36s/it]
  1%|          | 3041/569592 [2:33:31<413:01:25,  2.62s/it]
                                                           

  1%|          | 3041/569592 [2:33:31<413:01:25,  2.62s/it]
  1%|          | 3042/569592 [2:33:34<446:59:14,  2.84s/it]
                                                           

  1%|          | 3042/569592 [2:33:34<446:59:14,  2.84s/it]
  1%|          | 3043/569592 [2:33:38<524:00:09,  3.33s/it]
                                                           

  1%|          | 3043/569592 [2:33:38<524:00:09,  3.33s/it]
  1%|          | 3044/569592 [2:33:44<620:34:25,  3.94s/it]
                                                           

  1%|          | 3044/569592 [2:33:44<620:34:25,  3.94s/it]
  1%|          | 3045/569592 [2:33:45<478:35:31,  3.04s/it]
                                                           

  1%|          | 3045/569592 [2:33:45<478:35:31,  3.04s/it]
  1%|          | 3046/569592 [2:33:46<377:30:02,  2.40s/it]
                                                           

  1%|          | 3046/569592 [2:33:46<377:30:02,  2.40s/it]
  1%|          | 3047/569592 [2:33:47<308:41:24,  1.96s/it]
                                                           

  1%|          | 3047/569592 [2:33:47<308:41:24,  1.96s/it]
  1%|          | 3048/569592 [2:33:48<262:11:22,  1.67s/it]
                                                           

  1%|          | 3048/569592 [2:33:48<262:11:22,  1.67s/it]
  1%|          | 3049/569592 [2:33:49<233:06:53,  1.48s/it]
                                                           

  1%|          | 3049/569592 [2:33:49<233:06:53,  1.48s/it]
  1%|          | 3050/569592 [2:33:50<209:52:55,  1.33s/it]
                                                           

  1%|          | 3050/569592 [2:33:50<209:52:55,  1.33s/it]
  1%|          | 3051/569592 [2:33:51<195:01:43,  1.24s/it]
                                                           

  1%|          | 3051/569592 [2:33:51<195:01:43,  1.24s/it]
  1%|          | 3052/569592 [2:33:52<202:36:20,  1.29s/it]
                                                           

  1%|          | 3052/569592 [2:33:52<202:36:20,  1.29s/it]
  1%|          | 3053/569592 [2:33:58<412:26:53,  2.62s/it]
                                                           

  1%|          | 3053/569592 [2:33:58<412:26:53,  2.62s/it]
  1%|          | 3054/569592 [2:33:59<338:53:33,  2.15s/it]
                                                           

  1%|          | 3054/569592 [2:33:59<338:53:33,  2.15s/it]
  1%|          | 3055/569592 [2:34:00<283:01:05,  1.80s/it]
                                                           

  1%|          | 3055/569592 [2:34:00<283:01:05,  1.80s/it]
  1%|          | 3056/569592 [2:34:02<287:46:20,  1.83s/it]
                                                           

  1%|          | 3056/569592 [2:34:02<287:46:20,  1.83s/it]
  1%|          | 3057/569592 [2:34:08<517:51:11,  3.29s/it]
               /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95727954 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                            

  1%|          | 3057/569592 [2:34:08<517:51:11,  3.29s/it]
  1%|          | 3058/569592 [2:34:10<447:20:48,  2.84s/it]
                                                           

  1%|          | 3058/569592 [2:34:10<447:20:48,  2.84s/it]
  1%|          | 3059/569592 [2:34:11<357:46:48,  2.27s/it]
                                                           

  1%|          | 3059/569592 [2:34:11<357:46:48,  2.27s/it]
  1%|          | 3060/569592 [2:34:12<297:06:16,  1.89s/it]
                                                           

  1%|          | 3060/569592 [2:34:12<297:06:16,  1.89s/it]
  1%|          | 3061/569592 [2:34:18<505:59:41,  3.22s/it]
                                                           

  1%|          | 3061/569592 [2:34:18<505:59:41,  3.22s/it]
  1%|          | 3062/569592 [2:34:20<446:55:14,  2.84s/it]
                                                           

  1%|          | 3062/569592 [2:34:20<446:55:14,  2.84s/it]
  1%|        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97382000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  | 3063/569592 [2:34:21<360:45:33,  2.29s/it]
                                                           

  1%|          | 3063/569592 [2:34:21<360:45:33,  2.29s/it]
  1%|          | 3064/569592 [2:34:22<296:29:51,  1.88s/it]
                                                           

  1%|          | 3064/569592 [2:34:22<296:29:51,  1.88s/it]
  1%|          | 3065/569592 [2:34:29<508:51:44,  3.23s/it]
                                                           

  1%|          | 3065/569592 [2:34:29<508:51:44,  3.23s/it]
  1%|          | 3066/569592 [2:34:31<456:36:53,  2.90s/it]
                                                           

  1%|          | 3066/569592 [2:34:31<456:36:53,  2.90s/it]
  1%|          | 3067/569592 [2:34:32<363:39:01,  2.31s/it]
                                                           

  1%|          | 3067/569592 [2:34:32<363:39:01,  2.31s/it]
  1%|          | 3068/569592 [2:34:33<299:18:30,  1.90s/it]
                                                           

  1%|      /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
    | 3068/569592 [2:34:33<299:18:30,  1.90s/it]
  1%|          | 3069/569592 [2:34:38<478:27:52,  3.04s/it]
                                                           

  1%|          | 3069/569592 [2:34:38<478:27:52,  3.04s/it]
  1%|          | 3070/569592 [2:34:41<452:09:21,  2.87s/it]
                                                           

  1%|          | 3070/569592 [2:34:41<452:09:21,  2.87s/it]
  1%|          | 3071/569592 [2:34:42<362:10:16,  2.30s/it]
                                                           

  1%|          | 3071/569592 [2:34:42<362:10:16,  2.30s/it]
  1%|          | 3072/569592 [2:34:43<300:39:26,  1.91s/it]
                                                           

  1%|          | 3072/569592 [2:34:43<300:39:26,  1.91s/it]
  1%|          | 3073/569592 [2:34:49<496:07:02,  3.15s/it]
                                                           

  1%|          | 3073/569592 [2:34:49<496:07:02,  3.15s/it]
  1%|          | 3074/569592 [2:34:51<439:42:22,  2.79s/it]
          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                 

  1%|          | 3074/569592 [2:34:51<439:42:22,  2.79s/it]
  1%|          | 3075/569592 [2:34:52<352:11:30,  2.24s/it]
                                                           

  1%|          | 3075/569592 [2:34:52<352:11:30,  2.24s/it]
  1%|          | 3076/569592 [2:34:54<340:05:21,  2.16s/it]
                                                           

  1%|          | 3076/569592 [2:34:54<340:05:21,  2.16s/it]
  1%|          | 3077/569592 [2:35:00<512:20:40,  3.26s/it]
                                                           

  1%|          | 3077/569592 [2:35:00<512:20:40,  3.26s/it]
  1%|          | 3078/569592 [2:35:01<430:32:48,  2.74s/it]
                                                           

  1%|          | 3078/569592 [2:35:01<430:32:48,  2.74s/it]
  1%|          | 3079/569592 [2:35:02<345:15:42,  2.19s/it]
                                                           

  1%|          | 3079/569592 [2:35:02<345:15:42,  2.19s/it]
  1%|          | 3080/569592 [2:35:03<285:54:41,  1.82s/it]
                                                           

  1%|          | 3080/569592 [2:35:04<285:54:41,  1.82s/it]
  1%|          | 3081/569592 [2:35:09<505:57:53,  3.22s/it]
                                                           

  1%|          | 3081/569592 [2:35:09<505:57:53,  3.22s/it]
  1%|          | 3082/569592 [2:35:11<411:34:03,  2.62s/it]
                                                           

  1%|          | 3082/569592 [2:35:11<411:34:03,  2.62s/it]
  1%|          | 3083/569592 [2:35:15<474:11:06,  3.01s/it]
                                                           

  1%|          | 3083/569592 [2:35:15<474:11:06,  3.01s/it]
  1%|          | 3084/569592 [2:35:18<492:01:13,  3.13s/it]
                                                           

  1%|          | 3084/569592 [2:35:18<492:01:13,  3.13s/it]
  1%|          | 3085/569592 [2:35:19<390:55:33,  2.48s/it]
                                                           

  1%|          | 3085/569592 [2:35:19<390:55:33,  2.48s/it]
  1%|          | 3086/569592 [2:35:20<317:33:46,  2.02s/it]
                                                           

  1%|          | 3086/569592 [2:35:20<317:33:46,  2.02s/it]
  1%|          | 3087/569592 [2:35:21<267:24:07,  1.70s/it]
                                                           

  1%|          | 3087/569592 [2:35:21<267:24:07,  1.70s/it]
  1%|          | 3088/569592 [2:35:24<317:05:45,  2.02s/it]
                                                           

  1%|          | 3088/569592 [2:35:24<317:05:45,  2.02s/it]
  1%|          | 3089/569592 [2:35:29<460:09:49,  2.92s/it]
                                                           

  1%|          | 3089/569592 [2:35:29<460:09:49,  2.92s/it]
  1%|          | 3090/569592 [2:35:31<426:41:43,  2.71s/it]
                                                           

  1%|          | 3090/569592 [2:35:31<426:41:43,  2.71s/it]
  1%|          | 3091/569592 [2:35:32<343:07:17,  2.18s/it]
                                                           

  1%|          | 3091/569592 [2:35:32<343:07:17,  2.18s/it]
  1%|          | 3092/569592 [2:35:35<400:47:47,  2.55s/it]
                                                           

  1%|          | 3092/569592 [2:35:35<400:47:47,  2.55s/it]
  1%|          | 3093/569592 [2:35:39<476:25:21,  3.03s/it]
                                                           

  1%|          | 3093/569592 [2:35:39<476:25:21,  3.03s/it]
  1%|          | 3094/569592 [2:35:42<445:28:45,  2.83s/it]
                                                           

  1%|          | 3094/569592 [2:35:42<445:28:45,  2.83s/it]
  1%|          | 3095/569592 [2:35:43<356:22:56,  2.26s/it]
                                                           

  1%|          | 3095/569592 [2:35:43<356:22:56,  2.26s/it]
  1%|          | 3096/569592 [2:35:44<307:54:02,  1.96s/it]
                                                           

  1%|          | 3096/569592 [2:35:44<307:54:02,  1.96s/it]
  1%|          | 3097/569592 [2:35:49<431:33:38,  2.74s/it]
                                                           

  1%|          | 3097/569592 [2:35:49<431:33:38,  2.74s/it]
  1%|          | 3098/569592 [2:35:52<485:52:46,  3.09s/it]
                                                           

  1%|          | 3098/569592 [2:35:52<485:52:46,  3.09s/it]
  1%|          | 3099/569592 [2:35:56<496:34:14,  3.16s/it]
                                                           

  1%|          | 3099/569592 [2:35:56<496:34:14,  3.16s/it]
  1%|          | 3100/569592 [2:35:57<391:44:50,  2.49s/it]
                                                           

  1%|          | 3100/569592 [2:35:57<391:44:50,  2.49s/it]
  1%|          | 3101/569592 [2:36:00<436:20:25,  2.77s/it]
                                                           

  1%|          | 3101/569592 [2:36:00<436:20:25,  2.77s/it]
  1%|          | 3102/569592 [2:36:05<518:17:24,  3.29s/it]
                                                           

  1%|          | 3102/569592 [2:36:05<518:17:24,  3.29s/it]
  1%|          | 3103/569592 [2:36:06<407:54:31,  2.59s/it]
                                                           

  1%|          | 3103/569592 [2:36:06<407:54:31,  2.59s/it]
  1%|          | 3104/569592 [2:36:07<330:38:03,  2.10s/it]
                                                           

  1%|          | 3104/569592 [2:36:07<330:38:03,  2.10s/it]
  1%|          | 3105/569592 [2:36:08<317:38:56,  2.02s/it]
                                                           

  1%|          | 3105/569592 [2:36:08<317:38:56,  2.02s/it]
  1%|          | 3106/569592 [2:36:11<368:17:00,  2.34s/it]
                                                           

  1%|          | 3106/569592 [2:36:11<368:17:00,  2.34s/it]
  1%|          | 3107/569592 [2:36:15<437:12:24,  2.78s/it]
                                                           

  1%|          | 3107/569592 [2:36:15<437:12:24,  2.78s/it]
  1%|          | 3108/569592 [2:36:20<526:02:54,  3.34s/it]
                                                           

  1%|          | 3108/569592 [2:36:20<526:02:54,  3.34s/it]
  1%|          | 3109/569592 [2:36:24<565:55:26,  3.60s/it]
                                                           

  1%|          | 3109/569592 [2:36:24<565:55:26,  3.60s/it]
  1%|          | 3110/569592 [2:36:28<563:47:09,  3.58s/it]
                                                           

  1%|          | 3110/569592 [2:36:28<563:47:09,  3.58s/it]
  1%|          | 3111/569592 [2:36:33<639:02:51,  4.06s/it]
                                                           

  1%|          | 3111/569592 [2:36:33<639:02:51,  4.06s/it]
  1%|          | 3112/569592 [2:36:36<599:42:20,  3.81s/it]
                                                           

  1%|          | 3112/569592 [2:36:36<599:42:20,  3.81s/it]
  1%|          | 3113/569592 [2:36:41<631:59:37,  4.02s/it]
                                                           

  1%|          | 3113/569592 [2:36:41<631:59:37,  4.02s/it]
  1%|          | 3114/569592 [2:36:41<484:06:37,  3.08s/it]
                                                           

  1%|          | 3114/569592 [2:36:41<484:06:37,  3.08s/it]
  1%|          | 3115/569592 [2:36:46<533:38:16,  3.39s/it]
                                                           

  1%|          | 3115/569592 [2:36:46<533:38:16,  3.39s/it]
  1%|          | 3116/569592 [2:36:49<557:44:53,  3.54s/it]
                                                           

  1%|          | 3116/569592 [2:36:49<557:44:53,  3.54s/it]
  1%|          | 3117/569592 [2:36:53<559:36:36,  3.56s/it]
                                                           

  1%|          | 3117/569592 [2:36:53<559:36:36,  3.56s/it]
  1%|          | 3118/569592 [2:36:58<628:08:24,  3.99s/it]
                                                           

  1%|          | 3118/569592 [2:36:58<628:08:24,  3.99s/it]
  1%|          | 3119/569592 [2:37:01<593:03:51,  3.77s/it]
                                                           

  1%|          | 3119/569592 [2:37:01<593:03:51,  3.77s/it]
  1%|          | 3120/569592 [2:37:06<657:48:08,  4.18s/it]
                                                           

  1%|          | 3120/569592 [2:37:06<657:48:08,  4.18s/it]
  1%|          | 3121/569592 [2:37:11<681:41:41,  4.33s/it]
                                                           

  1%|          | 3121/569592 [2:37:11<681:41:41,  4.33s/it]
  1%|          | 3122/569592 [2:37:16<711:14:45,  4.52s/it]
                                                           

  1%|          | 3122/569592 [2:37:16<711:14:45,  4.52s/it]
  1%|          | 3123/569592 [2:37:19<650:32:01,  4.13s/it]
                                                           

  1%|          | 3123/569592 [2:37:19<650:32:01,  4.13s/it]
  1%|          | 3124/569592 [2:37:24<681:27:54,  4.33s/it]
                                                           

  1%|          | 3124/569592 [2:37:24<681:27:54,  4.33s/it]
  1%|          | 3125/569592 [2:37:29<699:03:37,  4.44s/it]
                                                           

  1%|          | 3125/569592 [2:37:29<699:03:37,  4.44s/it]
  1%|          | 3126/569592 [2:37:33<711:31:18,  4.52s/it]
                                                           

  1%|          | 3126/569592 [2:37:34<711:31:18,  4.52s/it]
  1%|          | 3127/569592 [2:37:34<541:23:51,  3.44s/it]
                                                           

  1%|          | 3127/569592 [2:37:34<541:23:51,  3.44s/it]
  1%|          | 3128/569592 [2:37:38<563:45:37,  3.58s/it]
                                                           

  1%|          | 3128/569592 [2:37:38<563:45:37,  3.58s/it]
  1%|          | 3129/569592 [2:37:43<621:27:04,  3.95s/it]
                                                           

  1%|          | 3129/569592 [2:37:43<621:27:04,  3.95s/it]
  1%|          | 3130/569592 [2:37:48<673:37:10,  4.28s/it]
                                                           

  1%|          | 3130/569592 [2:37:48<673:37:10,  4.28s/it]
  1%|          | 3131/569592 [2:37:51<627:02:42,  3.99s/it]
                                                           

  1%|          | 3131/569592 [2:37:51<627:02:42,  3.99s/it]
  1%|          | 3132/569592 [2:37:55<605:23:55,  3.85s/it]
                                                           

  1%|          | 3132/569592 [2:37:55<605:23:55,  3.85s/it]
  1%|          | 3133/569592 [2:38:00<649:16:41,  4.13s/it]
                                                           

  1%|          | 3133/569592 [2:38:00<649:16:41,  4.13s/it]
  1%|          | 3134/569592 [2:38:05<681:52:09,  4.33s/it]
                                                           

  1%|          | 3134/569592 [2:38:05<681:52:09,  4.33s/it]
  1%|          | 3135/569592 [2:38:05<519:35:50,  3.30s/it]
                                                           

  1%|          | 3135/569592 [2:38:06<519:35:50,  3.30s/it]
  1%|          | 3136/569592 [2:38:09<514:51:41,  3.27s/it]
                                                           

  1%|          | 3136/569592 [2:38:09<514:51:41,  3.27s/it]
  1%|          | 3137/569592 [2:38:14<610:43:34,  3.88s/it]
                                                           

  1%|          | 3137/569592 [2:38:14<610:43:34,  3.88s/it]
  1%|          | 3138/569592 [2:38:19<644:13:27,  4.09s/it]
                                                           

  1%|          | 3138/569592 [2:38:19<644:13:27,  4.09s/it]
  1%|          | 3139/569592 [2:38:22<601:06:47,  3.82s/it]
                                                           

  1%|          | 3139/569592 [2:38:22<601:06:47,  3.82s/it]
  1%|          | 3140/569592 [2:38:25<594:40:33,  3.78s/it]
                                                           

  1%|          | 3140/569592 [2:38:25<594:40:33,  3.78s/it]
  1%|          | 3141/569592 [2:38:31<654:45:27,  4.16s/it]
                                                           

  1%|          | 3141/569592 [2:38:31<654:45:27,  4.16s/it]
  1%|          | 3142/569592 [2:38:35<676:47:16,  4.30s/it]
                                                           

  1%|          | 3142/569592 [2:38:35<676:47:16,  4.30s/it]
  1%|          | 3143/569592 [2:38:38<614:58:29,  3.91s/it]
                                                           

  1%|          | 3143/569592 [2:38:38<614:58:29,  3.91s/it]
  1%|          | 3144/569592 [2:38:41<578:22:01,  3.68s/it]
                                                           

  1%|          | 3144/569592 [2:38:41<578:22:01,  3.68s/it]
  1%|          | 3145/569592 [2:38:45<574:56:40,  3.65s/it]
                                                           

  1%|          | 3145/569592 [2:38:45<574:56:40,  3.65s/it]
  1%|          | 3146/569592 [2:38:46<444:48:15,  2.83s/it]
                                                           

  1%|          | 3146/569592 [2:38:46<444:48:15,  2.83s/it]
  1%|          | 3147/569592 [2:38:49<485:23:28,  3.08s/it]
                                                           

  1%|          | 3147/569592 [2:38:49<485:23:28,  3.08s/it]
  1%|          | 3148/569592 [2:38:53<485:24:30,  3.08s/it]
                                                           

  1%|          | 3148/569592 [2:38:53<485:24:30,  3.08s/it]
  1%|          | 3149/569592 [2:38:56<508:18:40,  3.23s/it]
                                                           

  1%|          | 3149/569592 [2:38:56<508:18:40,  3.23s/it]
  1%|          | 3150/569592 [2:39:00<529:27:55,  3.36s/it]
                                                           

  1%|          | 3150/569592 [2:39:00<529:27:55,  3.36s/it]
  1%|          | 3151/569592 [2:39:03<519:57:42,  3.30s/it]
                                                           

  1%|          | 3151/569592 [2:39:03<519:57:42,  3.30s/it]
  1%|          | 3152/569592 [2:39:08<585:32:17,  3.72s/it]
                                                           

  1%|          | 3152/569592 [2:39:08<585:32:17,  3.72s/it]
  1%|          | 3153/569592 [2:39:09<452:55:46,  2.88s/it]
                                                           

  1%|          | 3153/569592 [2:39:09<452:55:46,  2.88s/it]
  1%|          | 3154/569592 [2:39:13<540:11:44,  3.43s/it]
                                                           

  1%|          | 3154/569592 [2:39:13<540:11:44,  3.43s/it]
  1%|          | 3155/569592 [2:39:19<626:30:10,  3.98s/it]
                                                           

  1%|          | 3155/569592 [2:39:19<626:30:10,  3.98s/it]
  1%|          | 3156/569592 [2:39:19<480:04:30,  3.05s/it]
                                                           

  1%|          | 3156/569592 [2:39:19<480:04:30,  3.05s/it]
  1%|          | 3157/569592 [2:39:20<379:22:33,  2.41s/it]
                                                           

  1%|          | 3157/569592 [2:39:20<379:22:33,  2.41s/it]
  1%|          | 3158/569592 [2:39:21<310:03:58,  1.97s/it]
                                                           

  1%|          | 3158/569592 [2:39:21<310:03:58,  1.97s/it]
  1%|          | 3159/569592 [2:39:26<455:43:41,  2.90s/it]
                                                           

  1%|          | 3159/569592 [2:39:26<455:43:41,  2.90s/it]
  1%|          | 3160/569592 [2:39:27<364:11:16,  2.31s/it]
                                                           

  1%|          | 3160/569592 [2:39:27<364:11:16,  2.31s/it]
  1%|          | 3161/569592 [2:39:31<446:28:35,  2.84s/it]
                                                           

  1%|          | 3161/569592 [2:39:31<446:28:35,  2.84s/it]
  1%|          | 3162/569592 [2:39:32<356:33:33,  2.27s/it]
                                                           

  1%|          | 3162/569592 [2:39:33<356:33:33,  2.27s/it]
  1%|          | 3163/569592 [2:39:34<311:35:35,  1.98s/it]
                                                           

  1%|          | 3163/569592 [2:39:34<311:35:35,  1.98s/it]
  1%|          | 3164/569592 [2:39:35<262:43:47,  1.67s/it]
                                                           

  1%|          | 3164/569592 [2:39:35<262:43:47,  1.67s/it]
  1%|          | 3165/569592 [2:39:36<230:14:59,  1.46s/it]
                                                           

  1%|          | 3165/569592 [2:39:36<230:14:59,  1.46s/it]
  1%|          | 3166/569592 [2:39:36<204:47:28,  1.30s/it]
                                                           

  1%|          | 3166/569592 [2:39:36<204:47:28,  1.30s/it]
  1%|          | 3167/569592 [2:39:37<186:56:56,  1.19s/it]
                                                           

  1%|          | 3167/569592 [2:39:37<186:56:56,  1.19s/it]
  1%|          | 3168/569592 [2:39:42<350:22:50,  2.23s/it]
                                                           

  1%|          | 3168/569592 [2:39:42<350:22:50,  2.23s/it]
  1%|          | 3169/569592 [2:39:43<294:42:10,  1.87s/it]
                                                           

  1%|          | 3169/569592 [2:39:43<294:42:10,  1.87s/it]
  1%|          | 3170/569592 [2:39:45<308:47:31,  1.96s/it]
                                                           

  1%|          | 3170/569592 [2:39:45<308:47:31,  1.96s/it]
  1%|          | 3171/569592 [2:39:46<269:21:09,  1.71s/it]
                                                           

  1%|          | 3171/569592 [2:39:46<269:21:09,  1.71s/it]
  1%|          | 3172/569592 [2:39:53<497:51:45,  3.16s/it]
                                                           

  1%|          | 3172/569592 [2:39:53<497:51:45,  3.16s/it]
  1%|          | 3173/569592 [2:39:54<420:39:42,  2.67s/it]
                                                           

  1%|          | 3173/569592 [2:39:54<420:39:42,  2.67s/it]
  1%|          | 3174/569592 [2:39:56<349:36:40,  2.22s/it]
                                                           

  1%|          | 3174/569592 [2:39:56<349:36:40,  2.22s/it]
  1%|          | 3175/569592 [2:39:57<288:12:25,  1.83s/it]
                                                           

  1%|          | 3175/569592 [2:39:57<288:12:25,  1.83s/it]
  1%|          | 3176/569592 [2:40:03<525:03:05,  3.34s/it]
                                                           

  1%|          | 3176/569592 [2:40:03<525:03:05,  3.34s/it]
  1%|          | 3177/569592 [2:40:05<436:41:20,  2.78s/it]
                                                           

  1%|          | 3177/569592 [2:40:05<436:41:20,  2.78s/it]
  1%|          | 3178/569592 [2:40:06<349:55:49,  2.22s/it]
                                                           

  1%|          | 3178/569592 [2:40:06<349:55:49,  2.22s/it]
  1%|          | 3179/569592 [2:40:07<289:12:48,  1.84s/it]
                                                           

  1%|          | 3179/569592 [2:40:07<289:12:48,  1.84s/it]
  1%|          | 3180/569592 [2:40:12<455:35:23,  2.90s/it]
                                                           

  1%|          | 3180/569592 [2:40:12<455:35:23,  2.90s/it]
  1%|          | 3181/569592 [2:40:16<520:16:13,  3.31s/it]
                                                           

  1%|          | 3181/569592 [2:40:16</home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
520:16:13,  3.31s/it]
  1%|          | 3182/569592 [2:40:17<409:43:49,  2.60s/it]
                                                           

  1%|          | 3182/569592 [2:40:17<409:43:49,  2.60s/it]
  1%|          | 3183/569592 [2:40:18<332:08:54,  2.11s/it]
                                                           

  1%|          | 3183/569592 [2:40:18<332:08:54,  2.11s/it]
  1%|          | 3184/569592 [2:40:22<407:49:05,  2.59s/it]
                                                           

  1%|          | 3184/569592 [2:40:22<407:49:05,  2.59s/it]
  1%|          | 3185/569592 [2:40:28<547:40:15,  3.48s/it]
                                                           

  1%|          | 3185/569592 [2:40:28<547:40:15,  3.48s/it]
  1%|          | 3186/569592 [2:40:29<429:54:51,  2.73s/it]
                                                           

  1%|          | 3186/569592 [2:40:29<429:54:51,  2.73s/it]
  1%|          | 3187/569592 [2:40:29<344:53:28,  2.19s/it]
                                                           

  1%|          | 3187/569592 [2:40:29<344:53:28,  2.19s/it]
  1%|          | 3188/569592 [2:40:33<400:24:00,  2.54s/it]
                                                           

  1%|          | 3188/569592 [2:40:33<400:24:00,  2.54s/it]
  1%|          | 3189/569592 [2:40:38<502:42:20,  3.20s/it]
                                                           

  1%|          | 3189/569592 [2:40:38<502:42:20,  3.20s/it]
  1%|          | 3190/569592 [2:40:39<396:35:05,  2.52s/it]
                                                           

  1%|          | 3190/569592 [2:40:39<396:35:05,  2.52s/it]
  1%|          | 3191/569592 [2:40:39<323:37:49,  2.06s/it]
                                                           

  1%|          | 3191/569592 [2:40:40<323:37:49,  2.06s/it]
  1%|          | 3192/569592 [2:40:43<377:19:17,  2.40s/it]
                                                           

  1%|          | 3192/569592 [2:40:43<377:19:17,  2.40s/it]
  1%|          | 3193/569592 [2:40:48<524:08:39,  3.33s/it]
                                                           

  1%|          | 3193/569592 [2:40:48<524:08:39,  3.33s/it]
  1%|          | 3194/569592 [2:40:49<410:56:43,  2.61s/it]
                                                           

  1%|          | 3194/569592 [2:40:49<410:56:43,  2.61s/it]
  1%|          | 3195/569592 [2:40:50<334:29:12,  2.13s/it]
                                                           

  1%|          | 3195/569592 [2:40:50<334:29:12,  2.13s/it]
  1%|          | 3196/569592 [2:40:52<318:56:01,  2.03s/it]
                                                           

  1%|          | 3196/569592 [2:40:52<318:56:01,  2.03s/it]
  1%|          | 3197/569592 [2:40:58<507:26:44,  3.23s/it]
                                                           

  1%|          | 3197/569592 [2:40:58<507:26:44,  3.23s/it]
  1%|          | 3198/569592 [2:40:59<401:07:35,  2.55s/it]
                                                           

  1%|          | 3198/569592 [2:4/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102267072 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
0:59<401:07:35,  2.55s/it]
  1%|          | 3199/569592 [2:41:00<325:11:47,  2.07s/it]
                                                           

  1%|          | 3199/569592 [2:41:00<325:11:47,  2.07s/it]
  1%|          | 3200/569592 [2:41:02<337:16:18,  2.14s/it]
                                                           

  1%|          | 3200/569592 [2:41:02<337:16:18,  2.14s/it]
  1%|          | 3201/569592 [2:41:07<447:03:06,  2.84s/it]
                                                           

  1%|          | 3201/569592 [2:41:07<447:03:06,  2.84s/it]
  1%|          | 3202/569592 [2:41:08<390:37:00,  2.48s/it]
                                                           

  1%|          | 3202/569592 [2:41:08<390:37:00,  2.48s/it]
  1%|          | 3203/569592 [2:41:09<320:39:25,  2.04s/it]
                                                           

  1%|          | 3203/569592 [2:41:09<320:39:25,  2.04s/it]
  1%|          | 3204/569592 [2:41:12<375:21:23,  2.39s/it]
                                                           

  1%|          | 3204/569592 [2:41:12<375:21:23,  2.39s/it]
  1%|          | 3205/569592 [2:41:16<452:19:22,  2.88s/it]
                                                           

  1%|          | 3205/569592 [2:41:17<452:19:22,  2.88s/it]
  1%|          | 3206/569592 [2:41:17<364:12:23,  2.31s/it]
                                                           

  1%|          | 3206/569592 [2:41:18<364:12:23,  2.31s/it]
  1%|          | 3207/569592 [2:41:19<302:51:47,  1.93s/it]
                                                           

  1%|          | 3207/569592 [2:41:19<302:51:47,  1.93s/it]
  1%|          | 3208/569592 [2:41:23<412:55:46,  2.62s/it]
                                                           

  1%|          | 3208/569592 [2:41:23<412:55:46,  2.62s/it]
  1%|          | 3209/569592 [2:41:28<529:47:48,  3.37s/it]
                                                           

  1%|          | 3209/569592 [2:41:28<529:47:48,  3.37s/it]
  1%|          | 3210/569592 [2:41:33<620:53:31,  3.95s/it]
                                                           

  1%|          | 3210/569592 [2:41:33<620:53:31,  3.95s/it]
  1%|          | 3211/569592 [2:41:34<477:18:36,  3.03s/it]
                                                           

  1%|          | 3211/569592 [2:41:34<477:18:36,  3.03s/it]
  1%|          | 3212/569592 [2:41:39<566:22:32,  3.60s/it]
                                                           

  1%|          | 3212/569592 [2:41:39<566:22:32,  3.60s/it]
  1%|          | 3213/569592 [2:41:40<444:02:05,  2.82s/it]
                                                           

  1%|          | 3213/569592 [2:41:40<444:02:05,  2.82s/it]
  1%|          | 3214/569592 [2:41:45<541:48:43,  3.44s/it]
                                                           

  1%|          | 3214/569592 [2:41:45<541:48:43,  3.44s/it]
  1%|          | 3215/569592 [2:41:48<532:47:39,  3.39s/it]
                                                           

  1%|          | 3215/569592 [2:41:48<532:47:39,  3.39s/it]
  1%|          | 3216/569592 [2:41:49<416:17:54,  2.65s/it]
                                                           

  1%|          | 3216/569592 [2:41:49<416:17:54,  2.65s/it]
  1%|          | 3217/569592 [2:41:50<335:43:29,  2.13s/it]
                                                           

  1%|          | 3217/569592 [2:41:50<335:43:29,  2.13s/it]
  1%|          | 3218/569592 [2:41:51<279:52:33,  1.78s/it]
                                                           

  1%|          | 3218/569592 [2:41:51<279:52:33,  1.78s/it]
  1%|          | 3219/569592 [2:41:52<239:51:55,  1.52s/it]
                                                           

  1%|          | 3219/569592 [2:41:52<239:51:55,  1.52s/it]
  1%|          | 3220/569592 [2:41:57<419:05:37,  2.66s/it]
                                                           

  1%|          | 3220/569592 [2:41:57<419:05:37,  2.66s/it]
  1%|          | 3221/569592 [2:42:02<523:09:59,  3.33s/it]
                                                           

  1%|          | 3221/569592 [2:42:02<523:09:59,  3.33s/it]
  1%|          | 3222/569592 [2:42:06<531:44:16,  3.38s/it]
                                                           

  1%|          | 3222/569592 [2:42:06<531:44:16,  3.38s/it]
  1%|          | 3223/569592 [2:42:09<539:10:12,  3.43s/it]
                                                           

  1%|          | 3223/569592 [2:42:09<539:10:12,  3.43s/it]
  1%|          | 3224/569592 [2:42:10<420:22:29,  2.67s/it]
                                                           

  1%|          | 3224/569592 [2:42:10<420:22:29,  2.67s/it]
  1%|          | 3225/569592 [2:42:14<470:17:40,  2.99s/it]
                                                           

  1%|          | 3225/569592 [2:42:14<470:17:40,  2.99s/it]
  1%|          | 3226/569592 [2:42:19<564:41:22,  3.59s/it]
                                                           

  1%|          | 3226/569592 [2:42:19<564:41:22,  3.59s/it]
  1%|          | 3227/569/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
592 [2:42:23<583:29:46,  3.71s/it]
                                                           

  1%|          | 3227/569592 [2:42:23<583:29:46,  3.71s/it]
  1%|          | 3228/569592 [2:42:26<554:09:21,  3.52s/it]
                                                           

  1%|          | 3228/569592 [2:42:26<554:09:21,  3.52s/it]
  1%|          | 3229/569592 [2:42:29<531:20:52,  3.38s/it]
                                                           

  1%|          | 3229/569592 [2:42:29<531:20:52,  3.38s/it]
  1%|          | 3230/569592 [2:42:32<540:12:55,  3.43s/it]
                                                           

  1%|          | 3230/569592 [2:42:32<540:12:55,  3.43s/it]
  1%|          | 3231/569592 [2:42:38<620:33:25,  3.94s/it]
                                                           

  1%|          | 3231/569592 [2:42:38<620:33:25,  3.94s/it]
  1%|          | 3232/569592 [2:42:38<476:33:29,  3.03s/it]
                                                           

  1%|          | 3232/5/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96078502 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
69592 [2:42:38<476:33:29,  3.03s/it]
  1%|          | 3233/569592 [2:42:44<589:00:35,  3.74s/it]
                                                           

  1%|          | 3233/569592 [2:42:44<589:00:35,  3.74s/it]
  1%|          | 3234/569592 [2:42:49<637:03:26,  4.05s/it]
                                                           

  1%|          | 3234/569592 [2:42:49<637:03:26,  4.05s/it]
  1%|          | 3235/569592 [2:42:53<673:24:47,  4.28s/it]
                                                           

  1%|          | 3235/569592 [2:42:53<673:24:47,  4.28s/it]
  1%|          | 3236/569592 [2:42:54<513:22:31,  3.26s/it]
                                                           

  1%|          | 3236/569592 [2:42:54<513:22:31,  3.26s/it]
  1%|          | 3237/569592 [2:42:58<525:31:26,  3.34s/it]
                                                           

  1%|          | 3237/569592 [2:42:58<525:31:26,  3.34s/it]
  1%|          | 3238/569592 [2:43:01<537:22:33,  3.42s/it]
                                                           

  1%|          | 3238/569592 [2:43:01<537:22:33,  3.42s/it]
  1%|          | 3239/569592 [2:43:06<568:16:40,  3.61s/it]
                                                           

  1%|          | 3239/569592 [2:43:06<568:16:40,  3.61s/it]
  1%|          | 3240/569592 [2:43:07<446:34:02,  2.84s/it]
                                                           

  1%|          | 3240/569592 [2:43:07<446:34:02,  2.84s/it]
  1%|          | 3241/569592 [2:43:10<478:21:52,  3.04s/it]
                                                           

  1%|          | 3241/569592 [2:43:10<478:21:52,  3.04s/it]
  1%|          | 3242/569592 [2:43:15<568:08:45,  3.61s/it]
                                                           

  1%|          | 3242/569592 [2:43:15<568:08:45,  3.61s/it]
  1%|          | 3243/569592 [2:43:20<639:39:35,  4.07s/it]
                                                           

  1%|          | 3243/569592 [2:43:20<639:39:35,  4.07s/it]
  1%|          | 3244/569592 [2:43:25<665:31:25,  4.23s/it]
                                                           

  1%|          | 3244/569592 [2:43:25<665:31:25,  4.23s/it]
  1%|          | 3245/569592 [2:43:26<507:22:19,  3.23s/it]
                                                           

  1%|          | 3245/569592 [2:43:26<507:22:19,  3.23s/it]
  1%|          | 3246/569592 [2:43:31<599:55:43,  3.81s/it]
                                                           

  1%|          | 3246/569592 [2:43:31<599:55:43,  3.81s/it]
  1%|          | 3247/569592 [2:43:36<640:52:02,  4.07s/it]
                                                           

  1%|          | 3247/569592 [2:43:36<640:52:02,  4.07s/it]
  1%|          | 3248/569592 [2:43:36<490:26:12,  3.12s/it]
                                                           

  1%|          | 3248/569592 [2:43:36<490:26:12,  3.12s/it]
  1%|          | 3249/569592 [2:43:40<501:14:53,  3.19s/it]
                                                           

  1%|          | 3249/569592 [2:43:40<501:14:53,  3.19s/it]
  1%|          | 3250/569592 [2:43:45<581:34:16,  3.70s/it]
                                                           

  1%|          | 3250/569592 [2:43:45<581:34:16,  3.70s/it]
  1%|          | 3251/569592 [2:43:49<634:15:50,  4.03s/it]
                                                           

  1%|          | 3251/569592 [2:43:49<634:15:50,  4.03s/it]
  1%|          | 3252/569592 [2:43:54<661:39:30,  4.21s/it]
                                                           

  1%|          | 3252/569592 [2:43:54<661:39:30,  4.21s/it]
  1%|          | 3253/569592 [2:43:58<659:54:14,  4.19s/it]
                                                           

  1%|          | 3253/569592 [2:43:58<659:54:14,  4.19s/it]
  1%|          | 3254/569592 [2:44:03<680:23:01,  4.32s/it]
                                                           

  1%|          | 3254/569592 [2:44:03<680:23:01,  4.32s/it]
  1%|          | 3255/569592 [2:44:06<626:00:11,  3.98s/it]
                                                           

  1%|          | 3255/569592 [2:44:06<626:00:11,  3.98s/it]
  1%|          | 3256/569592 [2:44:09<599:36:42,  3.81s/it]
                                                           

  1%|          | 3256/569592 [2:44:09<599:36:42,  3.81s/it]
  1%|          | 3257/569592 [2:44:14<640:44:50,  4.07s/it]
                                                           

  1%|          | 3257/569592 [2:44:14<640:44:50,  4.07s/it]
  1%|          | 3258/569592 [2:44:19<685:49:44,  4.36s/it]
                                                           

  1%|          | 3258/569592 [2:44:19<685:49:44,  4.36s/it]
  1%|          | 3259/569592 [2:44:20<525:34:33,  3.34s/it]
                                                           

  1%|          | 3259/569592 [2:44:20<525:34:33,  3.34s/it]
  1%|          | 3260/569592 [2:44:23<525:35:30,  3.34s/it]
                                                           

  1%|          | 3260/569592 [2:44:23<525:35:30,  3.34s/it]
  1%|          | 3261/569592 [2:44:26<510:28:40,  3.24s/it]
                                                           

  1%|          | 3261/569592 [2:44:26<510:28:40,  3.24s/it]
  1%|          | 3262/569592 [2:44:31<549:41:10,  3.49s/it]
                                                           

  1%|          | 3262/569592 [2:44:31<549:41:10,  3.49s/it]
  1%|          | 3263/569592 [2:44:32<430:09:08,  2.73s/it]
                                                           

  1%|          | 3263/569592 [2:44:32<430:09:08,  2.73s/it]
  1%|          | 3264/569592 [2:44:33<349:58:15,  2.22s/it]
                                                           

  1%|          | 3264/569592 [2:44:33<349:58:15,  2.22s/it]
  1%|          | 3265/569592 [2:44:34<291:45:12,  1.85s/it]
                                                           

  1%|          | 3265/569592 [2:44:34<291:45:12,  1.85s/it]
  1%|          | 3266/569592 [2:44:39<460:02:44,  2.92s/it]
                                                           

  1%|          | 3266/569592 [2:44:39<460:02:44,  2.92s/it]
  1%|          | 3267/569592 [2:44:44<548:24:27,  3.49s/it]
                                                           

  1%|          | 3267/569592 [2:44:44<548:24:27,  3.49s/it]
  1%|          | 3268/569592 [2:44:47<556:33:53,  3.54s/it]
                                                           

  1%|          | 3268/569592 [2:44:47<556:33:53,  3.54s/it]
  1%|          | 3269/569592 [2:44:48<434:21:58,  2.76s/it]
                                                           

  1%|          | 3269/569592 [2:44:48<434:21:58,  2.76s/it]
  1%|          | 3270/569592 [2:44:52<471:33:31,  3.00s/it]
                                                           

  1%|          | 3270/569592 [2:44:52<471:33:31,  3.00s/it]
  1%|          | 3271/569592 [2:44:53<376:38:11,  2.39s/it]
                                                           

  1%|          | 3271/569592 [2:44:53<376:38:11,  2.39s/it]
  1%|          | 3272/569592 [2:44:54<309:38:21,  1.97s/it]
                                                           

  1%|          | 3272/569592 [2:44:54<309:38:21,  1.97s/it]
  1%|          | 3273/569592 [2:44:57<376:11:23,  2.39s/it]
                                                           

  1%|          | 3273/569592 [2:44:57<376:11:23,  2.39s/it]
  1%|          | 3274/569592 [2:44:58<309:46:34,  1.97s/it]
                                                           

  1%|          | 3274/569592 [2:44:58<309:46:34,  1.97s/it]
  1%|          | 3275/569592 [2:44:59<262:12:32,  1.67s/it]
                                                           

  1%|          | 3275/569592 [2:44:59<262:12:32,  1.67s/it]
  1%|          | 3276/569592 [2:45:03<343:59:45,  2.19s/it]
                                                           

  1%|          | 3276/569592 [2:45:03<343:59:45,  2.19s/it]
  1%|          | 3277/569592 [2:45:04<285:21:51,  1.81s/it]
                                                           

  1%|          | 3277/569592 [2:45:04<285:21:51,  1.81s/it]
  1%|     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102135840 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
     | 3278/569592 [2:45:05<245:10:52,  1.56s/it]
                                                           

  1%|          | 3278/569592 [2:45:05<245:10:52,  1.56s/it]
  1%|          | 3279/569592 [2:45:09<377:11:50,  2.40s/it]
                                                           

  1%|          | 3279/569592 [2:45:09<377:11:50,  2.40s/it]
  1%|          | 3280/569592 [2:45:10<308:33:19,  1.96s/it]
                                                           

  1%|          | 3280/569592 [2:45:10<308:33:19,  1.96s/it]
  1%|          | 3281/569592 [2:45:11<260:28:29,  1.66s/it]
                                                           

  1%|          | 3281/569592 [2:45:11<260:28:29,  1.66s/it]
  1%|          | 3282/569592 [2:45:12<255:31:24,  1.62s/it]
                                                           

  1%|          | 3282/569592 [2:45:12<255:31:24,  1.62s/it]
  1%|          | 3283/569592 [2:45:16<338:42:56,  2.15s/it]
                                                           

  1%|          | 3283/569592 [2:45:16<338:42:56,  2.15s/it]
  1%|          | 3284/569592 [2:45:17<298:18:04,  1.90s/it]
                                                           

  1%|          | 3284/569592 [2:45:17<298:18:04,  1.90s/it]
  1%|          | 3285/569592 [2:45:21<414:46:06,  2.64s/it]
                                                           

  1%|          | 3285/569592 [2:45:21<414:46:06,  2.64s/it]
  1%|          | 3286/569592 [2:45:24<395:06:01,  2.51s/it]
                                                           

  1%|          | 3286/569592 [2:45:24<395:06:01,  2.51s/it]
  1%|          | 3287/569592 [2:45:26<409:52:42,  2.61s/it]
                                                           

  1%|          | 3287/569592 [2:45:26<409:52:42,  2.61s/it]
  1%|          | 3288/569592 [2:45:27<333:15:53,  2.12s/it]
                                                           

  1%|          | 3288/569592 [2:45:27<333:15:53,  2.12s/it]
  1%|          | 3289/569592 [2:45:32<433:58:21,  2.76s/it]
                                                           

  1%|          | 3289/569592 [2:45:32<433:58:21,  2.76s/it]
  1%|          | 3290/569592 [2:45:34<395:00:38,  2.51s/it]
                                                           

  1%|          | 3290/569592 [2:45:34<395:00:38,  2.51s/it]
  1%|          | 3291/569592 [2:45:36<405:05:21,  2.58s/it]
                                                           

  1%|          | 3291/569592 [2:45:36<405:05:21,  2.58s/it]
  1%|          | 3292/569592 [2:45:39<404:43:44,  2.57s/it]
                                                           

  1%|          | 3292/569592 [2:45:39<404:43:44,  2.57s/it]
  1%|          | 3293/569592 [2:45:42<422:29:10,  2.69s/it]
                                                           

  1%|          | 3293/569592 [2:45:42<422:29:10,  2.69s/it]
  1%|          | 3294/569592 [2:45:44<404:12:01,  2.57s/it]
                                                           

  1%|          | 3294/569592 [2:45:44<404:12:01,  2.57s/it]
  1%|          | 3295/569592 [2:45:47<417:06:04,  2.65s/it]
                                                           

  1%|          | 3295/569592 [2:45:47<417:06:04,  2.65s/it]
  1%|          | 3296/569592 [2:45:50<456:47:13,  2.90s/it]
                                                           

  1%|          | 3296/569592 [2:45:50<456:47:13,  2.90s/it]
  1%|          | 3297/569592 [2:45:52<385:52:35,  2.45s/it]
                                                           

  1%|          | 3297/569592 [2:45:52<385:52:35,  2.45s/it]
  1%|          | 3298/569592 [2:45:54<363:21:51,  2.31s/it]
                                                           

  1%|          | 3298/569592 [2:45:54<363:21:51,  2.31s/it]
  1%|          | 3299/569592 [2:45:56<375:03:49,  2.38s/it]
                                                           

  1%|          | 3299/569592 [2:45:56<375:03:49,  2.38s/it]
  1%|          | 3300/569592 [2:46:00<434:10:28,  2.76s/it]
                                                           

  1%|          | 3300/569592 [2:46:00<434:10:28,  2.76s/it]
  1%|          | 3301/569592 [2:46:02<380:31:30,  2.42s/it]
                                                           

  1%|          | 3301/569592 [2:46:02<380:31:30,  2.42s/it]
  1%|          | 3302/569592 [2:46:04<377:51:44,  2.40s/it]
                                                           

  1%|          | 3302/569592 [2:46:04<377:51:44,  2.40s/it]
  1%|          | 3303/569592 [2:46:07<400:05:57,  2.54s/it]
                                                           

  1%|          | 3303/569592 [2:46:07<400:05:57,  2.54s/it]
  1%|          | 3304/569592 [2:46:11<452:40:19,  2.88s/it]
                                                           

  1%|          | 3304/569592 [2:46:11<452:40:19,  2.88s/it]
  1%|          | 3305/569592 [2:46:13<448:04:24,  2.85s/it]
                                                           

  1%|          | 3305/569592 [2:46:13<448:04:24,  2.85s/it]
  1%|          | 3306/569592 [2:46:14<366:40:59,  2.33s/it]
                                                           

  1%|          | 3306/569592 [2:46:14<366:40:59,  2.33s/it]
  1%|          | 3307/569592 [2:46:17<354:41:42,  2.25s/it]
                                                           

  1%|          | 3307/569592 [2:46:17<354:41:42,  2.25s/it]
  1%|          | 3308/569592 [2:46:21<454:26:54,  2.89s/it]
                                                           

  1%|          | 3308/569592 [2:46:21<454:26:54,  2.89s/it]
  1%|          | 3309/569592 [2:46:23<433:49:08,  2.76s/it]
                                                           

  1%|          | 3309/569592 [2:46:23<433:49:08,  2.76s/it]
  1%|          | 3310/569592 [2:46:27<463:30:31,  2.95s/it]
                                                           

  1%|          | 3310/569592 [2:46:27<463:30:31,  2.95s/it]
  1%|          | 3311/569592 [2:46:28<368:07:33,  2.34s/it]
                                                           

  1%|          | 3311/569592 [2:46:28<368:07:33,  2.34s/it]
  1%|          | 3312/569592 [2:46:31<437:45:39,  2.78s/it]
                                                           

  1%|          | 3312/569592 [2:46:31<437:45:39,  2.78s/it]
  1%|          | 3313/569592 [2:46:34<406:15:22,  2.58s/it]
                                                           

  1%|          | 3313/569592 [2:46:34<406:15:22,  2.58s/it]
  1%|          | 3314/569592 [2:46:35<353:17:45,  2.25s/it]
                                                           

  1%|          | 3314/569592 [2:46:35<353:17:45,  2.25s/it]
  1%|          | 3315/569592 [2:46:37<351:55:57,  2.24s/it]
                                                           

  1%|          | 3315/569592 [2:46:37<351:55:57,  2.24s/it]
  1%|          | 3316/569592 [2:46:42<450:45:15,  2.87s/it]
                                                           

  1%|          | 3316/569592 [2:46:42<450:45:15,  2.87s/it]
  1%|          | 3317/569592 [2:46:43<397:29:13,  2.53s/it]
                                                           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(


  1%|          | 3317/569592 [2:46:43<397:29:13,  2.53s/it]
  1%|          | 3318/569592 [2:46:46<416:36:56,  2.65s/it]
                                                           

  1%|          | 3318/569592 [2:46:46<416:36:56,  2.65s/it]
  1%|          | 3319/569592 [2:46:50<453:31:58,  2.88s/it]
                                                           

  1%|          | 3319/569592 [2:46:50<453:31:58,  2.88s/it]
  1%|          | 3320/569592 [2:46:51<393:46:15,  2.50s/it]
                                                           

  1%|          | 3320/569592 [2:46:51<393:46:15,  2.50s/it]
  1%|          | 3321/569592 [2:46:53<368:42:13,  2.34s/it]
                                                           

  1%|          | 3321/569592 [2:46:53<368:42:13,  2.34s/it]
  1%|          | 3322/569592 [2:46:55<347:26:46,  2.21s/it]
                                                           

  1%|          | 3322/569592 [2:46:55<347:26:46,  2.21s/it]
  1%|          | 3323/569592 [2:46:59<406:22:55,  2.58s/it]
                                                           

  1%|          | 3323/569592 [2:46:59<406:22:55,  2.58s/it]
  1%|          | 3324/569592 [2:47:01<408:16:19,  2.60s/it]
                                                           

  1%|          | 3324/569592 [2:47:01<408:16:19,  2.60s/it]
  1%|          | 3325/569592 [2:47:05<445:07:58,  2.83s/it]
                                                           

  1%|          | 3325/569592 [2:47:05<445:07:58,  2.83s/it]
  1%|          | 3326/569592 [2:47:07<436:33:53,  2.78s/it]
                                                           

  1%|          | 3326/569592 [2:47:07<436:33:53,  2.78s/it]
  1%|          | 3327/569592 [2:47:10<457:44:29,  2.91s/it]
                                                           

  1%|          | 3327/569592 [2:47:11<457:44:29,  2.91s/it]
  1%|          | 3328/569592 [2:47:15<524:09:43,  3.33s/it]
                                                           

  1%|          | 3328/569592 [2:47:15<524:09:43,  3.33s/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/it]
  1%|          | 3329/569592 [2:47:16<411:53:48,  2.62s/it]
                                                           

  1%|          | 3329/569592 [2:47:16<411:53:48,  2.62s/it]
  1%|          | 3330/569592 [2:47:21<522:07:13,  3.32s/it]
                                                           

  1%|          | 3330/569592 [2:47:21<522:07:13,  3.32s/it]
  1%|          | 3331/569592 [2:47:22<420:08:17,  2.67s/it]
                                                           

  1%|          | 3331/569592 [2:47:22<420:08:17,  2.67s/it]
  1%|          | 3332/569592 [2:47:23<342:28:34,  2.18s/it]
                                                           

  1%|          | 3332/569592 [2:47:23<342:28:34,  2.18s/it]
  1%|          | 3333/569592 [2:47:28<493:42:18,  3.14s/it]
                                                           

  1%|          | 3333/569592 [2:47:28<493:42:18,  3.14s/it]
  1%|          | 3334/569592 [2:47:32<502:20:42,  3.19s/it]
                                                           

  1%|          | 3334/569592 [2:47:32<502:20:42,  3.19s/it]
  1%|          | 3335/569592 [2:47:36<572:29:08,  3.64s/it]
                                                           

  1%|          | 3335/569592 [2:47:36<572:29:08,  3.64s/it]
  1%|          | 3336/569592 [2:47:37<443:04:23,  2.82s/it]
                                                           

  1%|          | 3336/569592 [2:47:37<443:04:23,  2.82s/it]
  1%|          | 3337/569592 [2:47:38<354:23:02,  2.25s/it]
                                                           

  1%|          | 3337/569592 [2:47:38<354:23:02,  2.25s/it]
  1%|          | 3338/569592 [2:47:39<293:35:33,  1.87s/it]
                                                           

  1%|          | 3338/569592 [2:47:39<293:35:33,  1.87s/it]
  1%|          | 3339/569592 [2:47:44<445:45:21,  2.83s/it]
                                                           

  1%|          | 3339/569592 [2:47:44<445:45:21,  2.83s/it]
  1%|          | 3340/569592 [2:47:48<469:13:54,  2.98s/it]
                                                           

  1%|          | 3340/569592 [2:47:48<469:13:54,  2.98s/it]
  1%|          | 3341/569592 [2:47:51<497:08:01,  3.16s/it]
                                                           

  1%|          | 3341/569592 [2:47:51<497:08:01,  3.16s/it]
  1%|          | 3342/569592 [2:47:56<572:46:32,  3.64s/it]
                                                           

  1%|          | 3342/569592 [2:47:56<572:46:32,  3.64s/it]
  1%|          | 3343/569592 [2:47:57<444:12:50,  2.82s/it]
                                                           

  1%|          | 3343/569592 [2:47:57<444:12:50,  2.82s/it]
  1%|          | 3344/569592 [2:48:00<473:21:14,  3.01s/it]
                                                           

  1%|          | 3344/569592 [2:48:00<473:21:14,  3.01s/it]
  1%|          | 3345/569592 [2:48:01<376:50:07,  2.40s/it]
                                                           

  1%|          | 3345/569592 [2:48:01<376:50:07,  2.40s/it]
  1%|          | 3346/569592 [2:48:07<528:44:29,  3.36s/it]
                                                           

  1%|          | 3346/569592 [2:48:07<528:44:29,  3.36s/it]
  1%|          | 3347/569592 [2:48:10<520:02:00,  3.31s/it]
                                                           

  1%|          | 3347/569592 [2:48:10<520:02:00,  3.31s/it]
  1%|          | 3348/569592 [2:48:14<534:33:08,  3.40s/it]
                                                           

  1%|          | 3348/569592 [2:48:14<534:33:08,  3.40s/it]
  1%|          | 3349/569592 [2:48:17<523:21:20,  3.33s/it]
                                                           

  1%|          | 3349/569592 [2:48:17<523:21:20,  3.33s/it]
  1%|          | 3350/569592 [2:48:22<591:50:33,  3.76s/it]
                                                           

  1%|          | 3350/569592 [2:48:22<591:50:33,  3.76s/it]
  1%|          | 3351/569592 [2:48:26<627:59:36,  3.99s/it]
                                                           

  1%|          | 3351/569592 [2:48:26<627:59:36,  3.99s/it]
  1%|          | 3352/569592 [2:48:33<769:08:08,  4.89s/it]
                                                           

  1%|          | 3352/569592 [2:48:33<769:08:08,  4.89s/it]
  1%|          | 3353/569592 [2:48:36<698:11:09,  4.44s/it]
                                                           

  1%|          | 3353/569592 [2:48:36<698:11:09,  4.44s/it]
  1%|          | 3354/569592 [2:48:38<541:10:26,  3.44s/it]
                                                           

  1%|          | 3354/569592 [2:48:38<541:10:26,  3.44s/it]
  1%|          | 3355/569592 [2:48:43<622:01:33,  3.95s/it]
                                                           

  1%|          | 3355/569592 [2:48:43<622:01:33,  3.95s/it]
  1%|          | 3356/569592 [2:48:46<591:46:48,  3.76s/it]
                                                           

  1%|          | 3356/569592 [2:48:46<591:46:48,  3.76s/it]
  1%|          | 3357/569592 [2:48:51<628:11:37,  3.99s/it]
                                                           

  1%|          | 3357/569592 [2:48:51<628:11:37,  3.99s/it]
  1%|          | 3358/569592 [2:48:54<587:09:28,  3.73s/it]
                                                           

  1%|          | 3358/569592 [2:48:54<587:09:28,  3.73s/it]
  1%|          | 3359/569592 [2:48:58<630:54:14,  4.01s/it]
                                                           

  1%|          | 3359/569592 [2:48:58<630:54:14,  4.01s/it]
  1%|          | 3360/569592 [2:49:02<593:46:42,  3.78s/it]
                                                           

  1%|          | 3360/569592 [2:49:02<593:46:42,  3.78s/it]
  1%|          | 3361/569592 [2:49:05<560:18:57,  3.56s/it]
                                                           

  1%|          | 3361/569592 [2:49:05<560:18:57,  3.56s/it]
  1%|          | 3362/569592 [2:49:08<537:35:02,  3.42s/it]
                                                           

  1%|          | 3362/569592 [2:49:08<537:35:02,  3.42s/it]
  1%|          | 3363/569592 [2:49:12<592:07:59,  3.76s/it]
                                                           

  1%|          | 3363/569592 [2:49:12<592:07:59,  3.76s/it]
  1%|          | 3364/569592 [2:49:16<612:40:12,  3.90s/it]
                                                           

  1%|          | 3364/569592 [2:49:16<612:40:12,  3.90s/it]
  1%|          | 3365/569592 [2:49:21<646:39:42,  4.11s/it]
                                                           

  1%|          | 3365/569592 [2:49:21<646:39:42,  4.11s/it]
  1%|          | 3366/569592 [2:49:24<607:21:27,  3.86s/it]
                                                           

  1%|          | 3366/569592 [2:49:24<607:21:27,  3.86s/it]
  1%|          | 3367/569592 [2:49:28<581:06:11,  3.69s/it]
                                                           

  1%|          | 3367/569592 [2:49:28<581:06:11,  3.69s/it]
  1%|          | 3368/569592 [2:49:32<603:19:22,  3.84s/it]
                                                           

  1%|          | 3368/569592 [2:49:32<603:19:22,  3.84s/it]
  1%|          | 3369/569592 [2:49:37<647:14:18,  4.12s/it]
                                                           

  1%|          | 3369/569592 [2:49:37<647:14:18,  4.12s/it]
  1%|          | 3370/569592 [2:49:41<661:05:09,  4.20s/it]
                                                           

  1%|          | 3370/569592 [2:49:41<661:05:09,  4.20s/it]
  1%|          | 3371/569592 [2:49:44<603:53:53,  3.84s/it]
                                                           

  1%|          | 3371/569592 [2:49:44<603:53:53,  3.84s/it]
  1%|          | 3372/569592 [2:49:45<465:59:20,  2.96s/it]
                                                           

  1%|          | 3372/569592 [2:49:45<465:59:20,  2.96s/it]
  1%|          | 3373/569592 [2:49:48<479:02:40,  3.05s/it]
                                                           

  1%|          | 3373/569592 [2:49:48<479:02:40,  3.05s/it]
  1%|          | 3374/569592 [2:49:53<564:04:33,  3.59s/it]
                                                           

  1%|          | 3374/569592 [2:49:53<564:04:33,  3.59s/it]
  1%|          | 3375/569592 [2:49:57<589:34:53,  3.75s/it]
                                                           

  1%|          | 3375/569592 [2:49:57<589:34:53,  3.75s/it]
  1%|          | 3376/569592 [2:50:01<573:55:52,  3.65s/it]
                                                           

  1%|          | 3376/569592 [2:50:01<573:55:52,  3.65s/it]
  1%|          | 3377/569592 [2:50:01<443:36:40,  2.82s/it]
                                                           

  1%|          | 3377/569592 [2:50:01<443:36:40,  2.82s/it]
  1%|          | 3378/569592 [2:50:06<547:43:51,  3.48s/it]
                                                           

  1%|          | 3378/569592 [2:50:06<547:43:51,  3.48s/it]
  1%|          | 3379/569592 [2:50:07<426:10:23,  2.71s/it]
                                                           

  1%|          | 3379/569592 [2:50:07<426:10:23,  2.71s/it]
  1%|          | 3380/569592 [2:50:11<463:26:59,  2.95s/it]
                                                           

  1%|          | 3380/569592 [2:50:11<463:26:59,  2.95s/it]
  1%|          | 3381/569592 [2:50:12<369:08:37,  2.35s/it]
                                                           

  1%|          | 3381/569592 [2:50:12<369:08:37,  2.35s/it]
  1%|          | 3382/569592 [2:50:13<304:26:49,  1.94s/it]
                                                           

  1%|          | 3382/569592 [2:50:13<304:26:49,  1.94s/it]
  1%|          | 3383/569592 [2:50:16<372:03:58,  2.37s/it]
                                                           

  1%|          | 3383/569592 [2:50:16<372:03:58,  2.37s/it]
  1%|          | 3384/569592 [2:50:20<422:34:26,  2.69s/it]
                                                           

  1%|          | 3384/569592 [2:50:20<422:34:26,  2.69s/it]
  1%|          | 3385/569592 [2:50:24<525:59:18,  3.34s/it]
                                                           

  1%|          | 3385/569592 [2:50:24<525:59:18,  3.34s/it]
  1%|          | 3386/569592 [2:50:28<518:32:17,  3.30s/it]
                                                           

  1%|          | 3386/569592 [2:50:28<518:32:17,  3.30s/it]
  1%|          | 3387/569592 [2:50:29<407:21:21,  2.59s/it]
                                                           

  1%|          | 3387/569592 [2:50:29<407:21:21,  2.59s/it]
  1%|          | 3388/569592 [2:50:32<437:00:48,  2.78s/it]
                                                           

  1%|          | 3388/569592 [2:50:32<437:00:48,  2.78s/it]
  1%|          | 3389/569592 [2:50:33<352:41:12,  2.24s/it]
                                                           

  1%|          | 3389/569592 [2:50:33<352:41:12,  2.24s/it]
  1%|          | 3390/569592 [2:50:37<425:29:46,  2.71s/it]
                                                           

  1%|          | 3390/569592 [2:50:37<425:29:46,  2.71s/it]
  1%|          | 3391/569592 [2:50:40<450:12:12,  2.86s/it]
                                                           

  1%|          | 3391/569592 [2:50:40<450:12:12,  2.86s/it]
  1%|          | 3392/569592 [2:50:41<361:11:06,  2.30s/it]
                                                           

  1%|          | 3392/569592 [2:50:41<361:11:06,  2.30s/it]
  1%|          | 3393/569592 [2:50:42<296:39:16,  1.89s/it]
                                                           

  1%|          | 3393/569592 [2:50:42<296:39:16,  1.89s/it]
  1%|          | 3394/569592 [2:50:43<252:52:06,  1.61s/it]
                                                           

  1%|          | 3394/569592 [2:50:43<252:52:06,  1.61s/it]
  1%|          | 3395/569592 [2:50:44<221:38:16,  1.41s/it]
                                                           

  1%|          | 3395/569592 [2:50:44<221:38:16,  1.41s/it]
  1%|          | 3396/569592 [2:50:47<327:03:20,  2.08s/it]
                                                           

  1%|          | 3396/569592 [2:50:47<327:03:20,  2.08s/it]
  1%|          | 3397/569592 [2:50:48<273:34:03,  1.74s/it]
                                                           

  1%|          | 3397/569592 [2:50:48<273:34:03,  1.74s/it]
  1%|          | 3398/569592 [2:50:49<237:12:20,  1.51s/it]
                                                           

  1%|          | 3398/569592 [2:50:49<237:12:20,  1.51s/it]
  1%|          | 3399/569592 [2:50:52<300:10:10,  1.91s/it]
                                                           

  1%|          | 3399/569592 [2:50:52<300:10:10,  1.91s/it]
  1%|          | 3400/569592 [2:50:54<289:55:30,  1.84s/it]
                                                           

  1%|          | 3400/569592 [2:50:54<289:55:30,  1.84s/it]
  1%|          | 3401/569592 [2:50:56<322:47:56,  2.05s/it]
                                                           

  1%|          | 3401/569592 [2:50:56<322:47:56,  2.05s/it]
  1%|          | 3402/569592 [2:50:57<271:42:30,  1.73s/it]
                                                           

  1%|          | 3402/569592 [2:50:57<271:42:30,  1.73s/it]
  1%|          | 3403/569592 [2:51:01<381:25:40,  2.43s/it]
                                                           

  1%|          | 3403/569592 [2:51:01<381:25:40,  2.43s/it]
  1%|          | 3404/569592 [2:51:04<376:04:11,  2.39s/it]
                                                           

  1%|          | 3404/569592 [2:51:04<376:04:11,  2.39s/it]
  1%|          | 3405/569592 [2:51:06<373:37:20,  2.38s/it]
                                                           

  1%|          | 3405/569592 [2:51:06<373:37:20,  2.38s/it]
  1%|          | 3406/569592 [2:51:09<396:56:53,  2.52s/it]
                                                           

  1%|          | 3406/569592 [2:51:09<396:56:53,  2.52s/it]
  1%|          | 3407/569592 [2:51:13<477:27:45,  3.04s/it]
                                                           

  1%|          | 3407/569592 [2:51:13<477:27:45,  3.04s/it]
  1%|          | 3408/569592 [2:51:14<384:03:03,  2.44s/it]
                                                           

  1%|          | 3408/569592 [2:51:14<384:03:03,  2.44s/it]
  1%|          | 3409/569592 [2:51:17<420:54:23,  2.68s/it]
                                                           

  1%|          | 3409/569592 [2:51:17<420:54:23,  2.68s/it]
  1%|          | 3410/569592 [2:51:18<346:57:49,  2.21s/it]
                                                           

  1%|          | 3410/569592 [2:51:18<346:57:49,  2.21s/it]
  1%|          | 3411/569592 [2:51:22<401:08:30,  2.55s/it]
                                                           

  1%|          | 3411/569592 [2:51:22<401:08:30,  2.55s/it]
  1%|          | 3412/569592 [2:51:24<384:26:39,  2.44s/it]
                                                           

  1%|          | 3412/569592 [2:51:24<384:26:39,  2.44s/it]
  1%|          | 3413/569592 [2:51:26<353:41:05,  2.25s/it]
                                                           

  1%|          | 3413/569592 [2:51:26<353:41:05,  2.25s/it]
  1%|          | 3414/569592 [2:51:29<383:21:37,  2.44s/it]
                                                           

  1%|          | 3414/569592 [2:51:29<383:21:37,  2.44s/it]
  1%|          | 3415/569592 [2:51:32<441:27:40,  2.81s/it]
                                                           

  1%|          | 3415/569592 [2:51:32<441:27:40,  2.81s/it]
  1%|          | 3416/569592 [2:51:34<390:47:17,  2.48s/it]
                                                           

  1%|          | 3416/569592 [2:51:34<390:47:17,  2.48s/it]
  1%|          | 3417/569592 [2:51:36<372:44:33,  2.37s/it]
                                                           

  1%|          | 3417/569592 [2:51:36<372:44:33,  2.37s/it]
  1%|          | 3418/569592 [2:51:39<373:53:36,  2.38s/it]
                                                           

  1%|          | 3418/569592 [2:51:39<373:53:36,  2.38s/it]
  1%|          | 3419/569592 [2:51:42<423:40:46,  2.69s/it]
                                                           

  1%|          | 3419/569592 [2:51:42<423:40:46,  2.69s/it]
  1%|          | 3420/569592 [2:51:44<395:35:04,  2.52s/it]
                                                           

  1%|          | 3420/569592 [2:51:44<395:35:04,  2.52s/it]
  1%|          | 3421/569592 [2:51:46<379:13:45,  2.41s/it]
                                                           

  1%|          | 3421/569592 [2:51:46<379:13:45,  2.41s/it]
  1%|          | 3422/569592 [2:51:49<381:53:03,  2.43s/it]
                                                           

  1%|          | 3422/569592 [2:51:49<381:53:03,  2.43s/it]
  1%|          | 3423/569592 [2:51:52<403:57:51,  2.57s/it]
                                                           

  1%|          | 3423/569592 [2:51:52<403:57:51,  2.57s/it]
  1%|          | 3424/569592 [2:51:55<442:47:42,  2.82s/it]
                                                           

  1%|          | 3424/569592 [2:51:55<442:47:42,  2.82s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (109712830 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  1%|          | 3425/569592 [2:51:57<401:07:34,  2.55s/it]
                                                           

  1%|          | 3425/569592 [2:51:57<401:07:34,  2.55s/it]
  1%|          | 3426/569592 [2:51:58<342:02:26,  2.17s/it]
                                                           

  1%|          | 3426/569592 [2:51:58<342:02:26,  2.17s/it]
  1%|          | 3427/569592 [2:52:03<442:37:14,  2.81s/it]
                                                           

  1%|          | 3427/569592 [2:52:03<442:37:14,  2.81s/it]
  1%|          | 3428/569592 [2:52:06<489:41:20,  3.11s/it]
                                                           

  1%|          | 3428/569592 [2:52:06<489:41:20,  3.11s/it]
  1%|          | 3429/569592 [2:52:07<390:00:14,  2.48s/it]
                                                           

  1%|          | 3429/569592 [2:52:07<390:00:14,  2.48s/it]
  1%|          | 3430/569592 [2:52:09<343:21:35,  2.18s/it]
                                                           

  1%|          | 3430/569592 [2:52:09<343:21:35,  2.18s/it]
  1%|          | 3431/569592 [2:52:13<428:46:10,  2.73s/it]
                                                           

  1%|          | 3431/569592 [2:52:13<428:46:10,  2.73s/it]
  1%|          | 3432/569592 [2:52:16<445:28:14,  2.83s/it]
                                                           

  1%|          | 3432/569592 [2:52:16<445:28:14,  2.83s/it]
  1%|          | 3433/569592 [2:52:17<358:32:25,  2.28s/it]
                                                           

  1%|          | 3433/569592 [2:52:17<358:32:25,  2.28s/it]
  1%|          | 3434/569592 [2:52:20<374:57:44,  2.38s/it]
                                                           

  1%|          | 3434/569592 [2:52:20<374:57:44,  2.38s/it]
  1%|          | 3435/569592 [2:52:22<389:38:56,  2.48s/it]
                                                           

  1%|          | 3435/569592 [2:52:22<389:38:56,  2.48s/it]
  1%|          | 3436/569592 [2:52:27<513:24:01,  3.26s/it]
                                                           

  1%|          | 3436/569592 [2:52:27<513:24:01,  3.26s/it]
  1%|          | 3437/569592 [2:52:31<527:53:04,  3.36s/it]
                                                           

  1%|          | 3437/569592 [2:52:31<527:53:04,  3.36s/it]
  1%|          | 3438/569592 [2:52:32<414:53:44,  2.64s/it]
                                                           

  1%|          | 3438/569592 [2:52:32<414:53:44,  2.64s/it]
  1%|          | 3439/569592 [2:52:34<384:48:16,  2.45s/it]
                                                           

  1%|          | 3439/569592 [2:52:34<384:48:16,  2.45s/it]
  1%|          | 3440/569592 [2:52:36<366:35:32,  2.33s/it]
                                                           

  1%|          | 3440/569592 [2:52:36<366:35:32,  2.33s/it]
  1%|          | 3441/569592 [2:52:41<499:38:13,  3.18s/it]
                                                           

  1%|          | 3441/569592 [2:52:41<499:38:13,  3.18s/it]
  1%|          | 3442/569592 [2:52:42<397:01:49,  2.52s/it]
                                                           

  1%|          | 3442/569592 [2:52:42<397:01:49,  2.52s/it]
  1%|          | 3443/569592 [2:52:45<435:35:21,  2.77s/it]
                                                           

  1%|          | 3443/569592 [2:52:45<435:35:21,  2.77s/it]
  1%|          | 3444/569592 [2:52:46<350:39:01,  2.23s/it]
                                                           

  1%|          | 3444/569592 [2:52:46<350:39:01,  2.23s/it]
  1%|          | 3445/569592 [2:52:50<406:41:42,  2.59s/it]
                                                           

  1%|          | 3445/569592 [2:52:50<406:41:42,  2.59s/it]
  1%|          | 3446/569592 [2:52:54<469:14:18,  2.98s/it]
                                                           

  1%|          | 3446/569592 [2:52:54<469:14:18,  2.98s/it]
  1%|          | 3447/569592 [2:52:56<428:16:39,  2.72s/it]
                                                           

  1%|          | 3447/569592 [2:52:56<428:16:39,  2.72s/it]
  1%|          | 3448/569592 [2:52:57<351:40:45,  2.24s/it]
                                                           

  1%|          | 3448/569592 [2:52:57<351:40:45,  2.24s/it]
  1%|          | 3449/569592 [2:53:02<468:57:31,  2.98s/it]
                                                           

  1%|          | 3449/569592 [2:53:02<468:57:31,  2.98s/it]
  1%|          | 3450/569592 [2:53:03<375:52:46,  2.39s/it]
                                                           

  1%|          | 3450/569592 [2:53:03<375:52:46,  2.39s/it]
  1%|          | 3451/569592 [2:53:08<501:41:58,  3.19s/it]
                                                           

  1%|          | 3451/569592 [2:53:08<501:41:58,  3.19s/it]
  1%|          | 3452/569592 [2:53:13<584:17:59,  3.72s/it]
                                                           

  1%|          | 3452/569592 [2:53:13<584:17:59,  3.72s/it]
  1%|          | 3453/569592 [2:53:14<453:50:18,  2.89s/it]
                                                           

  1%|          | 3453/569592 [2:53:14<453:50:18,  2.89s/it]
  1%|          | 3454/569592 [2:53:18<541:49:57,  3.45s/it]
                                                           

  1%|          | 3454/569592 [2:53:18<541:49:57,  3.45s/it]
  1%|          | 3455/569592 [2:53:22<538:02:58,  3.42s/it]
                                                           

  1%|          | 3455/569592 [2:53:22<538:02:58,  3.42s/it]
  1%|          | 3456/569592 [2:53:26<581:18:20,  3.70s/it]
                                                           

  1%|          | 3456/569592 [2:53:26<581:18:20,  3.70s/it]
  1%|          | 3457/569592 [2:53:29<546:34:27,  3.48s/it]
                                                           

  1%|          | 3457/569592 [2:53:29<546:34:27,  3.48s/it]
  1%|          | 3458/569592 [2:53:33<560:13:49,  3.56s/it]
                                                           

  1%|          | 3458/569592 [2:53:33<560:13:49,  3.56s/it]
  1%|          | 3459/569592 [2:53:38<625:51:51,  3.98s/it]
                                                           

  1%|          | 3459/569592 [2:53:38<625:51:51,  3.98s/it]
  1%|          | 3460/569592 [2:53:42<651:16:52,  4.14s/it]
                                                           

  1%|          | 3460/569592 [2:53:42<651:16:52,  4.14s/it]
  1%|          | 3461/569592 [2:53:45<599:27:36,  3.81s/it]
                                                           

  1%|          | 3461/569592 [2:53:45<599:27:36,  3.81s/it]
  1%|          | 3462/569592 [2:53:49<586:34:38,  3.73s/it]
                                                           

  1%|          | 3462/569592 [2:53:49<586:34:38,  3.73s/it]
  1%|          | 3463/569592 [2:53:50<461:59:22,  2.94s/it]
                                                           

  1%|          | 3463/569592 [2:53:50<461:59:22,  2.94s/it]
  1%|          | 3464/569592 [2:53:55<555:37:50,  3.53s/it]
                                                           

  1%|          | 3464/569592 [2:53:55<555:37:50,  3.53s/it]
  1%|          | 3465/569592 [2:53:58<550:51:21,  3.50s/it]
                                                           

  1%|          | 3465/569592 [2:53:58<550:51:21,  3.50s/it]
  1%|          | 3466/569592 [2:54:02<582:56:00,  3.71s/it]
                                                           

  1%|          | 3466/569592 [2:54:02<582:56:00,  3.71s/it]
  1%|          | 3467/569592 [2:54:07<631:23:43,  4.02s/it]
                                                           

  1%|          | 3467/569592 [2:54:07<631:23:43,  4.02s/it]
  1%|          | 3468/569592 [2:54:12<685:37:01,  4.36s/it]
                                                           

  1%|          | 3468/569592 [2:54:12<685:37:01,  4.36s/it]
  1%|          | 3469/569592 [2:54:17<704:22:05,  4.48s/it]
                                                           

  1%|          | 3469/569592 [2:54:17<704:22:05,  4.48s/it]
  1%|          | 3470/569592 [2:54:21<696:45:07,  4.43s/it]
                                                           

  1%|          | 3470/569592 [2:54:21<696:45:07,  4.43s/it]
  1%|          | 3471/569592 [2:54:26<712:26:56,  4.53s/it]
                                                           

  1%|          | 3471/569592 [2:54:26<712:26:56,  4.53s/it]
  1%|          | 3472/569592 [2:54:31<703:00:29,  4.47s/it]
                                                           

  1%|          | 3472/569592 [2:54:31<703:00:29,  4.47s/it]
  1%|          | 3473/569592 [2:54:35<710:38:20,  4.52s/it]
                                                           

  1%|          | 3473/569592 [2:54:35<710:38:20,  4.52s/it]
  1%|          | 3474/569592 [2:54:39<658:19:38,  4.19s/it]
                                                           

  1%|          | 3474/569592 [2:54:39<658:19:38,  4.19s/it]
  1%|          | 3475/569592 [2:54:43<692:39:23,  4.40s/it]
                                                           

  1%|          | 3475/569592 [2:54:44<692:39/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:23,  4.40s/it]
  1%|          | 3476/569592 [2:54:48<702:27:31,  4.47s/it]
                                                           

  1%|          | 3476/569592 [2:54:48<702:27:31,  4.47s/it]
  1%|          | 3477/569592 [2:54:53<705:11:56,  4.48s/it]
                                                           

  1%|          | 3477/569592 [2:54:53<705:11:56,  4.48s/it]
  1%|          | 3478/569592 [2:54:57<719:22:11,  4.57s/it]
                                                           

  1%|          | 3478/569592 [2:54:57<719:22:11,  4.57s/it]
  1%|          | 3479/569592 [2:55:01<652:27:13,  4.15s/it]
                                                           

  1%|          | 3479/569592 [2:55:01<652:27:13,  4.15s/it]
  1%|          | 3480/569592 [2:55:05<659:53:24,  4.20s/it]
                                                           

  1%|          | 3480/569592 [2:55:05<659:53:24,  4.20s/it]
  1%|          | 3481/569592 [2:55:10<694:43:24,  4.42s/it]
                                                           

  1%|          | 3481/569592 [2:55:10<694:43:24,  4.42s/it]
  1%|          | 3482/569592 [2:55:13<633:08:18,  4.03s/it]
                                                           

  1%|          | 3482/569592 [2:55:13<633:08:18,  4.03s/it]
  1%|          | 3483/569592 [2:55:17<642:08:17,  4.08s/it]
                                                           

  1%|          | 3483/569592 [2:55:17<642:08:17,  4.08s/it]
  1%|          | 3484/569592 [2:55:22<665:04:08,  4.23s/it]
                                                           

  1%|          | 3484/569592 [2:55:22<665:04:08,  4.23s/it]
  1%|          | 3485/569592 [2:55:26<645:04:03,  4.10s/it]
                                                           

  1%|          | 3485/569592 [2:55:26<645:04:03,  4.10s/it]
  1%|          | 3486/569592 [2:55:29<622:11:49,  3.96s/it]
                                                           

  1%|          | 3486/569592 [2:55:29<622:11:49,  3.96s/it]
  1%|          | 3487/569592 [2:55:34<657:16:11,  4.18s/it]
                                                           

  1%|          | 3487/569592 [2:55:34<657:16:11,  4.18s/it]
  1%|          | 3488/569592 [2:55:37<616:18:47,  3.92s/it]
                                                           

  1%|          | 3488/569592 [2:55:37<616:18:47,  3.92s/it]
  1%|          | 3489/569592 [2:55:41<618:32:58,  3.93s/it]
                                                           

  1%|          | 3489/569592 [2:55:41<618:32:58,  3.93s/it]
  1%|          | 3490/569592 [2:55:42<477:15:20,  3.04s/it]
                                                           

  1%|          | 3490/569592 [2:55:42<477:15:20,  3.04s/it]
  1%|          | 3491/569592 [2:55:47<558:00:45,  3.55s/it]
                                                           

  1%|          | 3491/569592 [2:55:47<558:00:45,  3.55s/it]
  1%|          | 3492/569592 [2:55:51<606:23:45,  3.86s/it]
                                                           

  1%|          | 3492/569592 [2:55:51<606:23:45,  3.86s/it]
  1%|          | 3493/569592 [2:55:56<648:08:30,  4.12s/it]
                                                           

  1%|          | 3493/569592 [2:55:56<648:08:30,  4.12s/it]
  1%|          | 3494/569592 [2:56:00<632:01:19,  4.02s/it]
                                                           

  1%|          | 3494/569592 [2:56:00<632:01:19,  4.02s/it]
  1%|          | 3495/569592 [2:56:04<659:21:57,  4.19s/it]
                                                           

  1%|          | 3495/569592 [2:56:05<659:21:57,  4.19s/it]
  1%|          | 3496/569592 [2:56:09<677:13:27,  4.31s/it]
                                                           

  1%|          | 3496/569592 [2:56:09<677:13:27,  4.31s/it]
  1%|          | 3497/569592 [2:56:10<528:31:25,  3.36s/it]
                                                           

  1%|          | 3497/569592 [2:56:10<528:31:25,  3.36s/it]
  1%|          | 3498/569592 [2:56:15<600:05:52,  3.82s/it]
                                                           

  1%|          | 3498/569592 [2:56:15<600:05:52,  3.82s/it]
  1%|          | 3499/569592 [2:56:16<475:45:27,  3.03s/it]
                                                           

  1%|          | 3499/569592 [2:56:16<475:45:27,  3.03s/it]
  1%|          | 3500/569592 [2:56:21<553:19:01,  3.52s/it]
                                                           

  1%|          | 3500/569592 [2:56:21<553:19:01,  3.52s/it]
  1%|          | 3501/569592 [2:56:22<430:52:38,  2.74s/it]
                                                           

  1%|          | 3501/569592 [2:56:22<430:52:38,  2.74s/it]
  1%|          | 3502/569592 [2:56:26<484:50:30,  3.08s/it]
                                                           

  1%|          | 3502/569592 [2:56:26<484:50:30,  3.08s/it]
  1%|          | 3503/569592 [2:56:31<564:34:00,  3.59s/it]
                                                           

  1%|          | 3503/569592 [2:56:31<564:34:00,  3.59s/it]
  1%|          | 3504/569592 [2:56:35<585:55:24,  3.73s/it]
                                                           

  1%|          | 3504/569592 [2:56:35<585:55:24,  3.73s/it]
  1%|          | 3505/569592 [2:56:35<453:24:29,  2.88s/it]
                                                           

  1%|          | 3505/569592 [2:56:35<453:24:29,  2.88s/it]
  1%|          | 3506/569592 [2:56:40<541:23:25,  3.44s/it]
                                                           

  1%|          | 3506/569592 [2:56:40<541:23:25,  3.44s/it]
  1%|          | 3507/569592 [2:56:41<422:00:23,  2.68s/it]
                                                           

  1%|          | 3507/569592 [2:56:41<422:00:23,  2.68s/it]
  1%|          | 3508/569592 [2:56:42<343:35:13,  2.19s/it]
                                                           

  1%|          | 3508/569592 [2:56:42<343:35:13,  2.19s/it]
  1%|          | 3509/569592 [2:56:45<395:09:13,  2.51s/it]
                                                           

  1%|          | 3509/569592 [2:56:45<395:09:13,  2.51s/it]
  1%|          | 3510/569592 [2:56:46<322:15:30,  2.05s/it]
                                                           

  1%|          | 3510/569592 [2:56:46<322:15:30,  2.05s/it]
  1%|          | 3511/569592 [2:56:47<269:25:50,  1.71s/it]
                                                           

  1%|          | 3511/569592 [2:56:47<269:25:50,  1.71s/it]
  1%|          | 3512/569592 [2:56:48<231:49:01,  1.47s/it]
                                                           

  1%|          | 3512/569592 [2:56:48<231:49:01,  1.47s/it]
  1%|          | 3513/569592 [2:56:49<205:50:47,  1.31s/it]
                                                           

  1%|          | 3513/569592 [2:56:49<205:50:47,  1.31s/it]
  1%|          | 3514/569592 [2:56:53<317:18:44,  2.02s/it]
                                                           

  1%|          | 3514/569592 [2:56:53<317:18:44,  2.02s/it]
  1%|          | 3515/569592 [2:56:54<267:46:18,  1.70s/it]
                                                           

  1%|          | 3515/569592 [2:56:54<267:46:18,  1.70s/it]
  1%|          | 3516/569592 [2:56:55<238:29:48,  1.52s/it]
                                                           

  1%|          | 3516/569592 [2:56:55<238:29:48,  1.52s/it]
  1%|          | 3517/569592 [2:56:58<294:49:35,  1.87s/it]
                                                           

  1%|          | 3517/569592 [2:56:58<294:49:35,  1.87s/it]
  1%|          | 3518/569592 [2:56:59<275:05:53,  1.75s/it]
                                                           

  1%|          | 3518/569592 [2:56:59<275:05:53,  1.75s/it]
  1%|          | 3519/569592 [2:57:04<426:44:03,  2.71s/it]
                                                           

  1%|          | 3519/569592 [2:57:04<426:44:03,  2.71s/it]
  1%|          | 3520/569592 [2:57:06<368:09:38,  2.34s/it]
                                                           

  1%|          | 3520/569592 [2:57:06<368:09:38,  2.34s/it]
  1%|          | 3521/569592 [2:57:08<360:44:26,  2.29s/it]
                                                           

  1%|          | 3521/569592 [2:57:08<360:44:26,  2.29s/it]
  1%|          | 3522/569592 [2:57:10<362:31:38,  2.31s/it]
                                                           

  1%|          | 3522/569592 [2:57:10<362:31:38,  2.31s/it]
  1%|          | 3523/569592 [2:57:15<480:54:12,  3.06s/it]
                                                           

  1%|          | 3523/569592 [2:57:15<480:54:12,  3.06s/it]
  1%|          | 3524/569592 [2:57:16<389:03:01,  2.47s/it]
                                                           

  1%|          | 3524/569592 [2:57:16<389:03:01,  2.47s/it]
  1%|          | 3525/569592 [2:57:18<362:07:37,  2.30s/it]
                                                           

  1%|          | 3525/569592 [2:57:18<362:07:37,  2.30s/it]
  1%|          | 3526/569592 [2:57:20<376:54:36,  2.40s/it]
                                                           

  1%|          | 3526/569592 [2:57:20<376:54:36,  2.40s/it]
  1%|          | 3527/569592 [2:57:24<439:35:20,  2.80s/it]
                                                           

  1%|          | 3527/569592 [2:57:24<439:35:20,  2.80s/it]
  1%|          | 3528/569592 [2:57:26<405:21:17,  2.58s/it]
                                                           

  1%|          | 3528/569592 [2:57:26<405:21:17,  2.58s/it]
  1%|          | 3529/569592 [2:57:28<346:54:52,  2.21s/it]
                                                           

  1%|          | 3529/569592 [2:57:28<346:54:52,  2.21s/it]
  1%|          | 3530/569592 [2:57:32<448:13:29,  2.85s/it]
                                                           

  1%|          | 3530/569592 [2:57:32<448:13:29,  2.85s/it]
  1%|          | 3531/569592 [2:57:34<428:29:38,  2.73s/it]
                                                           

  1%|          | 3531/569592 [2:57:34<428:29:38,  2.73s/it]
  1%|          | 3532/569592 [2:57:37<423:00:26,  2.69s/it]
                                                           

  1%|          | 3532/569592 [2:57:37<423:00:26,  2.69s/it]
  1%|          | 3533/569592 [2:57:39<367:02:57,  2.33s/it]
                                                           

  1%|          | 3533/569592 [2:57:39<367:02:57,  2.33s/it]
  1%|          | 3534/569592 [2:57:41<352:03:41,  2.24s/it]
                                                           

  1%|          | 3534/569592 [2:57:41<352:03:41,  2.24s/it]
  1%|          | 3535/569592 [2:57:44<413:05:03,  2.63s/it]
                                                           

  1%|          | 3535/569592 [2:57:44<413:05:03,  2.63s/it]
  1%|          | 3536/569592 [2:57:46<386:32:54,  2.46s/it]
                                                           

  1%|          | 3536/569592 [2:57:46<386:32:54,  2.46s/it]
  1%|          | 3537/569592 [2:57:48<366:24:42,  2.33s/it]
                                                           

  1%|          | 3537/569592 [2:57:48<366:24:42,  2.33s/it]
  1%|          | 3538/569592 [2:57:52<442:38:52,  2.82s/it]
                                                           

  1%|          | 3538/569592 [2:57:52<442:38:52,  2.82s/it]
  1%|          | 3539/569592 [2:57:54<402:52:35,  2.56s/it]
                                                           

  1%|          | 3539/569592 [2:57:54<402:52:35,  2.56s/it]
  1%|          | 3540/569592 [2:57:57<415:06:33,  2.64s/it]
                                                           

  1%|          | 3540/569592 [2:57:57<415:06:33,  2.64s/it]
  1%|          | 3541/569592 [2:58:00<444:35:16,  2.83s/it]
                                                           

  1%|          | 3541/569592 [2:58:00<444:35:16,  2.83s/it]
  1%|          | 3542/569592 [2:58:01<357:57:58,  2.28s/it]
                                                           

  1%|          | 3542/569592 [2:58:01<357:57:58,  2.28s/it]
  1%|          | 3543/569592 [2:58:05<421:59:03,  2.68s/it]
                                                           

  1%|          | 3543/569592 [2:58:05<421:59:03,  2.68s/it]
  1%|          | 3544/569592 [2:58:07<420:52:08,  2.68s/it]
                                                           

  1%|          | 3544/569592 [2:58:07<420:52:08,  2.68s/it]
  1%|          | 3545/569592 [2:58:11<452:03:43,  2.88s/it]
                                                           

  1%|          | 3545/569592 [2:58:11<452:03:43,  2.88s/it]
  1%|          | 3546/569592 [2:58:12<361:18:51,  2.30s/it]
                                                           

  1%|          | 3546/569592 [2:58:12<361:18:51,  2.30s/it]
  1%|          | 3547/569592 [2:58:15<393:31:18,  2.50s/it]
                                                           

  1%|          | 3547/569592 [2:58:15<393:31:18,  2.50s/it]
  1%|          | 3548/569592 [2:58:18<416:59:03,  2.65s/it]
                                                           

  1%|          | 3548/569592 [2:58:18<416:59:03,  2.65s/it]
  1%|          | 3549/569592 [2:58:21<466:14:02,  2.97s/it]
                                                           

  1%|          | 3549/569592 [2:58:21<466:14:02,  2.97s/it]
  1%|          | 3550/569592 [2:58:25<511:03:21,  3.25s/it]
                                                           

  1%|          | 3550/569592 [2:58:25<511:03:21,  3.25s/it]
  1%|          | 3551/569592 [2:58:26<401:29:49,  2.55s/it]
                                                           

  1%|          | 3551/569592 [2:58:26<401:29:49,  2.55s/it]
  1%|          | 3552/569592 [2:58:28<369:23:34,  2.35s/it]
                                                           

  1%|          | 3552/569592 [2:58:28<369:23:34,  2.35s/it]
  1%|          | 3553/569592 [2:58:32<424:43:26,  2.70s/it]
                                                           

  1%|          | 3553/569592 [2:58:32<424:43:26,  2.70s/it]
  1%|          | 3554/569592 [2:58:36<489:18:37,  3.11s/it]
                                                           

  1%|          | 3554/569592 [2:58:36<489:18:37,  3.11s/it]
  1%|          | 3555/569592 [2:58:39<498:04:39,  3.17s/it]
                                                           

  1%|          | 3555/569592 [2:58:39<498:04:39,  3.17s/it]
  1%|          | 3556/569592 [2:58:44<573:52:44,  3.65s/it]
                                                           

  1%|          | 3556/569592 [2:58:44<573:52:44,  3.65s/it]
  1%|          | 3557/569592 [2:58:45<444:34:17,  2.83s/it]
                                                           

  1%|          | 3557/569592 [2:58:45<444:34:17,  2.83s/it]
  1%|          | 3558/569592 [2:58:50<557:23:30,  3.55s/it]
                                                           

  1%|          | 3558/569592 [2:58:50<557:23:30,  3.55s/it]
  1%|          | 3559/569592 [2:58:51<436:53:42,  2.78s/it]
                                                           

  1%|          | 3559/569592 [2:58:51<436:53:42,  2.78s/it]
  1%|          | 3560/569592 [2:58:52<353:11:58,  2.25s/it]
                                                           

  1%|          | 35/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
60/569592 [2:58:52<353:11:58,  2.25s/it]
  1%|          | 3561/569592 [2:58:53<292:07:42,  1.86s/it]
                                                           

  1%|          | 3561/569592 [2:58:53<292:07:42,  1.86s/it]
  1%|          | 3562/569592 [2:58:54<248:55:43,  1.58s/it]
                                                           

  1%|          | 3562/569592 [2:58:54<248:55:43,  1.58s/it]
  1%|          | 3563/569592 [2:58:57<339:53:21,  2.16s/it]
                                                           

  1%|          | 3563/569592 [2:58:57<339:53:21,  2.16s/it]
  1%|          | 3564/569592 [2:59:01<395:59:19,  2.52s/it]
                                                           

  1%|          | 3564/569592 [2:59:01<395:59:19,  2.52s/it]
  1%|          | 3565/569592 [2:59:02<325:10:38,  2.07s/it]
                                                           

  1%|          | 3565/569592 [2:59:02<325:10:38,  2.07s/it]
  1%|          | 3566/569592 [2:59:03<272:53:22,  1.74s/it]
                                                           

  1%|          | 3566/569592 [2:59:03<272:53:22,  1.74s/it]
  1%|          | 3567/569592 [2:59:08<447:28:40,  2.85s/it]
                                                           

  1%|          | 3567/569592 [2:59:08<447:28:40,  2.85s/it]
  1%|          | 3568/569592 [2:59:11<469:30:44,  2.99s/it]
                                                           

  1%|          | 3568/569592 [2:59:11<469:30:44,  2.99s/it]
  1%|          | 3569/569592 [2:59:17<575:06:53,  3.66s/it]
                                                           

  1%|          | 3569/569592 [2:59:17<575:06:53,  3.66s/it]
  1%|          | 3570/569592 [2:59:20<557:13:15,  3.54s/it]
                                                           

  1%|          | 3570/569592 [2:59:20<557:13:15,  3.54s/it]
  1%|          | 3571/569592 [2:59:21<432:36:11,  2.75s/it]
                                                           

  1%|          | 3571/569592 [2:59:21<432:36:11,  2.75s/it]
  1%|          | 3572/569592 [2:59:26<535:31:14,  3.41s/it]
                                                           

  1%|          | 3572/569592 [2:59:26<535:31:14,  3.41s/it]
  1%|          | 3573/569592 [2:59:29<524:43:39,  3.34s/it]
                                                           

  1%|          | 3573/569592 [2:59:29<524:43:39,  3.34s/it]
  1%|          | 3574/569592 [2:59:34<594:57:48,  3.78s/it]
                                                           

  1%|          | 3574/569592 [2:59:34<594:57:48,  3.78s/it]
  1%|          | 3575/569592 [2:59:38<631:08:48,  4.01s/it]
                                                           

  1%|          | 3575/569592 [2:59:38<631:08:48,  4.01s/it]
  1%|          | 3576/569592 [2:59:43<684:26:47,  4.35s/it]
                                                           

  1%|          | 3576/569592 [2:59:43<684:26:47,  4.35s/it]
  1%|          | 3577/569592 [2:59:47<648:59:41,  4.13s/it]
                                                           

  1%|          | 3577/569592 [2:59:47<648:59:41,  4.13s/it]
  1%|          | 3578/569592 [2:59:51<636:33:55,  4.05s/it]
                                                           

  1%|          | 3578/569592 [2:59:51<636:33:55,  4.05s/it]
  1%|          | 3579/569592 [2:59:52<487:09:06,  3.10s/it]
                                                           

  1%|          | 3579/569592 [2:59:52<487:09:06,  3.10s/it]
  1%|          | 3580/569592 [2:59:57<565:19:07,  3.60s/it]
                                                           

  1%|          | 3580/569592 [2:59:57<565:19:07,  3.60s/it]
  1%|          | 3581/569592 [3:00:02<632:29:55,  4.02s/it]
                                                           

  1%|          | 3581/569592 [3:00:02<632:29:55,  4.02s/it]
  1%|          | 3582/569592 [3:00:05<599:43:40,  3.81s/it]
                                                           

  1%|          | 3582/569592 [3:00:05<599:43:40,  3.81s/it]
  1%|          | 3583/569592 [3:00:10<661:06:54,  4.20s/it]
                                                           

  1%|          | 3583/569592 [3:00:10<661:06:54,  4.20s/it]
  1%|          | 3584/569592 [3:00:15<703:24:47,  4.47s/it]
                                                           

  1%|          | 3584/569592 [3:00:15<703:24:47,  4.47s/it]
  1%|          | 3585/569592 [3:00:20<734:24:05,  4.67s/it]
                                                           

  1%|          | 3585/569592 [3:00:20<734:24:05,  4.67s/it]
  1%|          | 3586/569592 [3:00:24<673:15:57,  4.28s/it]
                                                           

  1%|          | 3586/569592 [3:00:24<673:15:57,  4.28s/it]
  1%|          | 3587/569592 [3:00:28<671:41:33,  4.27s/it]
                                                           

  1%|          | 3587/569592 [3:00:28<671:41:33,  4.27s/it]
  1%|          | 3588/569592 [3:00:31<639:26:32,  4.07s/it]
                                                           

  1%|          | 3588/569592 [3:00:31<639:26:32,  4.07s/it]
  1%|          | 3589/569592 [3:00:34<585:33:53,  3.72s/it]
                                                           

  1%|          | 3589/569592 [3:00:34<585:33:53,  3.72s/it]
  1%|          | 3590/569592 [3:00:39<631:30:57,  4.02s/it]
                                                           

  1%|          | 3590/569592 [3:00:39<631:30:57,  4.02s/it]
  1%|          | 3591/569592 [3:00:44<671:17:02,  4.27s/it]
                                                           

  1%|          | 3591/569592 [3:00:44<671:17:02,  4.27s/it]
  1%|          | 3592/569592 [3:00:48<683:37:34,  4.35s/it]
                                                           

  1%|          | 3592/569592 [3:00:48<683:37:34,  4.35s/it]
  1%|          | 3593/569592 [3:00:52<666:30:24,  4.24s/it]
                                                           

  1%|          | 3593/569592 [3:00:52<666:30:24,  4.24s/it]
  1%|          | 3594/569592 [3:00:57<689:32:57,  4.39s/it]
                                                           

  1%|          | 3594/569592 [3:00:57<689:32:57,  4.39s/it]
  1%|          | 3595/569592 [3:01:01<670:02:54,  4.26s/it]
                                                           

  1%|          | 3595/569592 [3:01:01<670:02:54,  4.26s/it]
  1%|          | 3596/569592 [3:01:05<672:23:09,  4.28s/it]
                                                           

  1%|          | 3596/569592 [3:01:05<672:23:09,  4.28s/it]
  1%|          | 3597/569592 [3:01:10<695:48:56,  4.43s/it]
                                                           

  1%|          | 3597/569592 [3:01:10<695:48:56,  4.43s/it]
  1%|          | 3598/569592 [3:01:15<700:43:09,  4.46s/it]
                                                           

  1%|          | 3598/569592 [3:01:15<700:43:09,  4.46s/it]
  1%|          | 3599/569592 [3:01:19<706:36:12,  4.49s/it]
                                                           

  1%|          | 3599/569592 [3:01:19<706:36:12,  4.49s/it]
  1%|          | 3600/569592 [3:01:24<692:22:39,  4.40s/it]
                                                           

  1%|          | 3600/569592 [3:01:24<692:22:39,  4.40s/it]
  1%|          | 3601/569592 [3:01:27<640:01:53,  4.07s/it]
                                                           

  1%|          | 3601/569592 [3:01:27<640:01:53,  4.07s/it]
  1%|          | 3602/569592 [3:01:28<497:28:18,  3.16s/it]
                                                           

  1%|          | 3602/569592 [3:01:28<497:28:18,  3.16s/it]
  1%|          | 3603/569592 [3:01:31<510:13:45,  3.25s/it]
                                                           

  1%|          | 3603/569592 [3:01:31<510:13:45,  3.25s/it]
  1%|          | 3604/569592 [3:01:35<511:50:55,  3.26s/it]
                                                           

  1%|          | 3604/569592 [3:01:35<511:50:55,  3.26s/it]
  1%|          | 3605/569592 [3:01:39<582:43:59,  3.71s/it]
                                                           

  1%|          | 3605/569592 [3:01:39<582:43:59,  3.71s/it]
  1%|          | 3606/569592 [3:01:40<454:32:57,  2.89s/it]
                                                           

  1%|          | 3606/569592 [3:01:40<454:32:57,  2.89s/it]
  1%|          | 3607/569592 [3:01:45<531:43:47,  3.38s/it]
                                                           

  1%|          | 3607/569592 [3:01:45<531:43:47,  3.38s/it]
  1%|          | 3608/569592 [3:01:46<417:18:02,  2.65s/it]
                                                           

  1%|          | 3608/569592 [3:01:46<417:18:02,  2.65s/it]
  1%|          | 3609/569592 [3:01:49<452:38:46,  2.88s/it]
                                                           

  1%|          | 3609/569592 [3:01:49<452:38:46,  2.88s/it]
  1%|          | 3610/569592 [3:01:54<554:43:58,  3.53s/it]
                                                           

  1%|          | 3610/569592 [3:01:54<554:43:58,  3.53s/it]
  1%|          | 3611/569592 [3:01:59<619:36:29,  3.94s/it]
                                                           

  1%|          | 3611/569592 [3:01:59<619:36:29,  3.94s/it]
  1%|          | 3612/569592 [3:02:04<651:06:52,  4.14s/it]
                                                           

  1%|          | 3612/569592 [3:02:04<651:06:52,  4.14s/it]
  1%|          | 3613/569592 [3:02:05<497:05:56,  3.16s/it]
                                                           

  1%|          | 3613/569592 [3:02:05<497:05:56,  3.16s/it]
  1%|          | 3614/569592 [3:02:08<499:34:20,  3.18s/it]
                                                           

  1%|          | 3614/569592 [3:02:08<499:34:20,  3.18s/it]
  1%|          | 3615/569592 [3:02:09<397:05:30,  2.53s/it]
                                                           

  1%|          | 3615/569592 [3:02:09<397:05:30,  2.53s/it]
  1%|          | 3616/569592 [3:02:14<516:23:46,  3.28s/it]
                                                           

  1%|          | 3616/569592 [3:02:14<516:23:46,  3.28s/it]
  1%|          | 3617/569592 [3:02:17<512:11:14,  3.26s/it]
                                                           

  1%|          | 3617/569592 [3:02:17<512:11:14,  3.26s/it]
  1%|          | 3618/569592 [3:02:21<546:01:03,  3.47s/it]
                                                           

  1%|          | 3618/569592 [3:02:21<546:01:03,  3.47s/it]
  1%|          | 3619/569592 [3:02:24<521:06:02,  3.31s/it]
                                                           

  1%|          | 3619/569592 [3:02:24<521:06:02,  3.31s/it]
  1%|          | 3620/569592 [3:02:29<590:54:50,  3.76s/it]
                                                           

  1%|          | 3620/569592 [3:02:29<590:54:50,  3.76s/it]
  1%|          | 3621/569592 [3:02:34<637:24:10,  4.05s/it]
                                                           

  1%|          | 3621/569592 [3:02:34<637:24:10,  4.05s/it]
  1%|          | 3622/569592 [3:02:38<670:04:05,  4.26s/it]
                                                           

  1%|          | 3622/569592 [3:02:38<670:04:05,  4.26s/it]
  1%|          | 3623/569592 [3:02:43<694:07:25,  4.42s/it]
                                                           

  1%|          | 3623/569592 [3:02:43<694:07:25,  4.42s/it]
  1%|          | 3624/569592 [3:02:44<530:43:11,  3.38s/it]
                                                           

  1%|          | 3624/569592 [3:02:44<530:43:11,  3.38s/it]
  1%|          | 3625/569592 [3:02:45<414:07:36,  2.63s/it]
                                                           

  1%|          | 3625/569592 [3:02:45<414:07:36,  2.63s/it]
  1%|          | 3626/569592 [3:02:50<521:20:29,  3.32s/it]
                                                           

  1%|          | 3626/569592 [3:02:50<521:20:29,  3.32s/it]
  1%|          | 3627/569592 [3:02:51<414:56:13,  2.64s/it]
                                                           

  1%|          | 3627/569592 [3:02:51<414:56:13,  2.64s/it]
  1%|          | 3628/569592 [3:02:52<335:00:44,  2.13s/it]
                                                           

  1%|          | 3628/569592 [3:02:52<335:00:44,  2.13s/it]
  1%|          | 3629/569592 [3:02:53<280:23:46,  1.78s/it]
                                                           

  1%|          | 3629/569592 [3:02:53<280:23:46,  1.78s/it]
  1%|          | 3630/569592 [3:02:54<244:03:35,  1.55s/it]
                                                           

  1%|          | 3630/569592 [3:02:54<244:03:35,  1.55s/it]
  1%|          | 3631/569592 [3:02:55<215:39:05,  1.37s/it]
                                                           

  1%|          | 3631/569592 [3:02:55<215:39:05,  1.37s/it]
  1%|          | 3632/569592 [3:02:58<320:38:41,  2.04s/it]
                                                           

  1%|          | 3632/569592 [3:02:58<320:38:41,  2.04s/it]
  1%|          | 3633/569592 [3:02:59<270:32:49,  1.72s/it]
                                                           

  1%|          | 3633/569592 [3:02:59<270:32:49,  1.72s/it]
  1%|          | 3634/569592 [3:03:00<236:09:37,  1.50s/it]
                                                           

  1%|          | 3634/569592 [3:03:00<236:09:37,  1.50s/it]
  1%|          | 3635/569592 [3:03:04<331:30:30,  2.11s/it]
                                                           

  1%|          | 3635/569592 [3:03:04<331:30:30,  2.11s/it]
  1%|          | 3636/569592 [3:03:07<356:04:43,  2.26s/it]
                                                           

  1%|          | 3636/569592 [3:03:07<356:04:43,  2.26s/it]
  1%|          | 3637/569592 [3:03:07<294:44:32,  1.87s/it]
                                                           

  1%|          | 3637/569592 [3:03:08<294:44:32,  1.87s/it]
  1%|          | 3638/569592 [3:03:08<250:40:52,  1.59s/it]
                                                           

  1%|          | 3638/569592 [3:03:08<250:40:52,  1.59s/it]
  1%|          | 3639/569592 [3:03:14<445:06:12,  2.83s/it]
                                                           

  1%|          | 3639/569592 [3:03:14<445:06:12,  2.83s/it]
  1%|          | 3640/569592 [3:03:17<436:08:57,  2.77s/it]
                                                           

  1%|          | 3640/569592 [3:03:17<436:08:57,  2.77s/it]
  1%|          | 3641/569592 [3:03:18<350:43:32,  2.23s/it]
                                                           

  1%|          | 3641/569592 [3:03:18<350:43:32,  2.23s/it]
  1%|          | 3642/569592 [3:03:19<291:00:09,  1.85s/it]
                                                           

  1%|          | 3642/569592 [3:03:19<291:00:09,  1.85s/it]
  1%|          | 3643/569592 [3:03:23<422:03:00,  2.68s/it]
                                                           

  1%|          | 3643/569592 [3:03:23<422:03:00,  2.68s/it]
  1%|          | 3644/569592 [3:03:28<525:10:12,  3.34s/it]
                                                           

  1%|          | 3644/569592 [3:03:28<525:10:12,  3.34s/it]
  1%|          | 3645/569592 [3:03:29<419:13:09,  2.67s/it]
                                                           

  1%|          | 3645/569592 [3:03:29<419:13:09,  2.67s/it]
  1%|          | 3646/569592 [3:03:30<337:43:28,  2.15s/it]
                                                           

  1%|          | 3646/569592 [3:03:30<337:43:28,  2.15s/it]
  1%|          | 3647/569592 [3:03:35<449:32:53,  2.86s/it]
                                                           

  1%|          | 3647/569592 [3:03:35<449:32:53,  2.86s/it]
  1%|          | 3648/569592 [3:03:38<449:02:20,  2.86s/it]
                                                           

  1%|          | 3648/569592 [3:03:38<449:02:20,  2.86s/it]
  1%|          | 3649/569592 [3:03:39<385:07:47,  2.45s/it]
                                                           

  1%|          | 3649/569592 [3:03:39<385:07:47,  2.45s/it]
  1%|          | 3650/569592 [3:03:40<314:06:42,  2.00s/it]
                                                           

  1%|          | 3650/569592 [3:03:40<314:06:42,  2.00s/it]
  1%|          | 3651/569592 [3:03:46<522:22:36,  3.32s/it]
                                                           

  1%|          | 3651/569592 [3:03:47<522:22:36,  3.32s/it]
  1%|          | 3652/569592 [3:03:48<422:19:08,  2.69s/it]
                                                           

  1%|          | 3652/569592 [3:03:48<422:19:08,  2.69s/it]
  1%|          | 3653/569592 [3:03:50<385:03:56,  2.45s/it]
                                                           

  1%|          | 3653/569592 [3:03:50<385:03:56,  2.45s/it]
  1%|          | 3654/569592 [3:03:51<315:11:57,  2.01s/it]
                                                           

  1%|          | 3654/569592 [3:03:51<315:11:57,  2.01s/it]
  1%|          | 3655/569592 [3:03:57<511:17:27,  3.25s/it]
                                                           

  1%|          | 3655/569592 [3:03:57<511:17:27,  3.25s/it]
  1%|          | 3656/569592 [3:03:58<416:03:32,  2.65s/it]
                                                           

  1%|          | 3656/569592 [3:03:58<416:03:32,  2.65s/it]
  1%|          | 3657/569592 [3:03:59<357:50:22,  2.28s/it]
                                                           

  1%|          | 3657/569592 [3:03:59<357:50:22,  2.28s/it]
  1%|          | 3658/569592 [3:04:00<300:19:18,  1.91s/it]
                                                           

  1%|          | 3658/569592 [3:04:00<300:19:18,  1.91s/it]
  1%|          | 3659/569592 [3:04:06<488:36:05,  3.11s/it]
                                                           

  1%|          | 3659/569592 [3:04:06<488:36:05,  3.11s/it]
  1%|          | 3660/569592 [3:04:09<491:21:23,  3.13s/it]
                                                           

  1%|          | 3660/569592 [3:04:10<491:21:23,  3.13s/it]
  1%|          | 3661/569592 [3:04:11<402:35:00,  2.56s/it]
                                                           

  1%|          | 3661/569592 [3:04:11<402:35:00,  2.56s/it]
  1%|          | 3662/569592 [3:04:14<441:00:06,  2.81s/it]
                                                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (114256065 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
         

  1%|          | 3662/569592 [3:04:14<441:00:06,  2.81s/it]
  1%|          | 3663/569592 [3:04:19<539:23:13,  3.43s/it]
                                                           

  1%|          | 3663/569592 [3:04:19<539:23:13,  3.43s/it]
  1%|          | 3664/569592 [3:04:20<422:46:50,  2.69s/it]
                                                           

  1%|          | 3664/569592 [3:04:20<422:46:50,  2.69s/it]
  1%|          | 3665/569592 [3:04:21<342:06:57,  2.18s/it]
                                                           

  1%|          | 3665/569592 [3:04:21<342:06:57,  2.18s/it]
  1%|          | 3666/569592 [3:04:25<416:05:07,  2.65s/it]
                                                           

  1%|          | 3666/569592 [3:04:25<416:05:07,  2.65s/it]
  1%|          | 3667/569592 [3:04:26<339:51:54,  2.16s/it]
                                                           

  1%|          | 3667/569592 [3:04:26<339:51:54,  2.16s/it]
  1%|          | 3668/569592 [3:04:29<386:37:22,  2.46s/it]
                                                           

  1%|          | 3668/569592 [3:04:29<386:37:22,  2.46s/it]
  1%|          | 3669/569592 [3:04:32<439:37:43,  2.80s/it]
                                                           

  1%|          | 3669/569592 [3:04:32<439:37:43,  2.80s/it]
  1%|          | 3670/569592 [3:04:33<352:25:46,  2.24s/it]
                                                           

  1%|          | 3670/569592 [3:04:33<352:25:46,  2.24s/it]
  1%|          | 3671/569592 [3:04:39<501:33:25,  3.19s/it]
                                                           

  1%|          | 3671/569592 [3:04:39<501:33:25,  3.19s/it]
  1%|          | 3672/569592 [3:04:42<509:27:21,  3.24s/it]
                                                           

  1%|          | 3672/569592 [3:04:42<509:27:21,  3.24s/it]
  1%|          | 3673/569592 [3:04:43<401:29:28,  2.55s/it]
                                                           

  1%|          | 3673/569592 [3:04:43<401:29:28,  2.55s/it]
  1%|          | 3674/569592 [3:04:44<326:25:38,  2.08s/it]
                                                           

  1%|          | 3674/569592 [3:04:44<326:25:38,  2.08s/it]
  1%|          | 3675/569592 [3:04:45<274:55:41,  1.75s/it]
                                                           

  1%|          | 3675/569592 [3:04:45<274:55:41,  1.75s/it]
  1%|          | 3676/569592 [3:04:49<381:14:23,  2.43s/it]
                                                           

  1%|          | 3676/569592 [3:04:49<381:14:23,  2.43s/it]
  1%|          | 3677/569592 [3:04:53<432:07:13,  2.75s/it]
                                                           

  1%|          | 3677/569592 [3:04:53<432:07:13,  2.75s/it]
  1%|          | 3678/569592 [3:04:54<348:19:11,  2.22s/it]
                                                           

  1%|          | 3678/569592 [3:04:54<348:19:11,  2.22s/it]
  1%|          | 3679/569592 [3:04:57<393:23:33,  2.50s/it]
                                                           

  1%|          | 3679/569592 [3:04:57<393:23:33,  2.50s/it]
  1%|          | 3680/569592 [3:05:01<465:18:05,  2.96s/it]
                                                           

  1%|          | 3680/569592 [3:05:01<465:18:05,  2.96s/it]
  1%|          | 3681/569592 [3:05:04<472:06:52,  3.00s/it]
                                                           

  1%|          | 3681/569592 [3:05:04<472:06:52,  3.00s/it]
  1%|          | 3682/569592 [3:05:07<500:09:07,  3.18s/it]
                                                           

  1%|          | 3682/569592 [3:05:07<500:09:07,  3.18s/it]
  1%|          | 3683/569592 [3:05:08<393:56:22,  2.51s/it]
                                                           

  1%|          | 3683/569592 [3:05:08<393:56:22,  2.51s/it]
  1%|          | 3684/569592 [3:05:12<448:13:27,  2.85s/it]
                                                           

  1%|          | 3684/569592 [3:05:12<448:13:27,  2.85s/it]
  1%|          | 3685/569592 [3:05:15<466:57:03,  2.97s/it]
                                                           

  1%|          | 3685/569592 [3:05:15<466:57:03,  2.97s/it]
  1%|          | 3686/569592 [3:05:16<372:21:29,  2.37s/it]
                                                           

  1%|          | 3686/569592 [3:05:16<372:21:29,  2.37s/it]
  1%|          | 3687/569592 [3:05:21<506:16:19,  3.22s/it]
                                                           

  1%|          | 3687/569592 [3:05:21<506:16:19,  3.22s/it]
  1%|          | 3688/569592 [3:05:26<562:36:40,  3.58s/it]
                                                           

  1%|          | 3688/569592 [3:05:26<562:36:40,  3.58s/it]
  1%|          | 3689/569592 [3:05:30<598:09:01,  3.81s/it]
                                                           

  1%|          | 3689/569592 [3:05:30<598:09:01,  3.81s/it]
  1%|          | 3690/569592 [3:05:35<658:13:30,  4.19s/it]
                                                           

  1%|          | 3690/569592 [3:05:35<658:13:30,  4.19s/it]
  1%|          | 3691/569592 [3:05:38<611:45:17,  3.89s/it]
                                                           

  1%|          | 3691/569592 [3:05:38<611:45:17,  3.89s/it]
  1%|          | 3692/569592 [3:05:43<639:47:24,  4.07s/it]
                                                           

  1%|          | 3692/569592 [3:05:43<639:47:24,  4.07s/it]
  1%|          | 3693/569592 [3:05:46<587:45:52,  3.74s/it]
                                                           

  1%|          | 3693/569592 [3:05:46<587:45:52,  3.74s/it]
  1%|          | 3694/569592 [3:05:51<655:22:07,  4.17s/it]
                                                           

  1%|          | 3694/569592 [3:05:51<655:22:07,  4.17s/it]
  1%|          | 3695/569592 [3:05:54<603:19:41,  3.84s/it]
                                                           

  1%|          | 3695/569592 [3:05:54<603:19:41,  3.84s/it]
  1%|          | 3696/569592 [3:05:57<565:06:55,  3.60s/it]
                                                           

  1%|          | 3696/569592 [3:05:57<565:06:55,  3.60s/it]
  1%|          | 3697/569592 [3:06:02<626:02:25,  3.98s/it]
                                                           

  1%|          | 3697/569592 [3:06:02<626:02:25,  3.98s/it]
  1%|          | 3698/569592 [3:06:06<621:42:37,  3.96s/it]
                                                           

  1%|          | 3698/569592 [3:06:06<621:42:37,  3.96s/it]
  1%|          | 3699/569592 [3:06:11<655:46:06,  4.17s/it]
                                                           

  1%|          | 3699/569592 [3:06:11<655:46:06,  4.17s/it]
  1%|          | 3700/569592 [3:06:15<682:46:39,  4.34s/it]
                                                           

  1%|          | 3700/569592 [3:06:15<682:46:39,  4.34s/it]
  1%|          | 3701/569592 [3:06:19<641:21:13,  4.08s/it]
                                                           

  1%|          | 3701/569592 [3:06:19<641:21:13,  4.08s/it]
  1%|          | 3702/569592 [3:06:24<685:42:54,  4.36s/it]
                                                           

  1%|          | 3702/569592 [3:06:24<685:42:54,  4.36s/it]
  1%|          | 3703/569592 [3:06:27<649:18:56,  4.13s/it]
                                                           

  1%|          | 3703/569592 [3:06:27<649:18:56,  4.13s/it]
  1%|          | 3704/569592 [3:06:32<675:55:37,  4.30s/it]
                                                           

  1%|          | 3704/569592 [3:06:32<675:55:37,  4.30s/it]
  1%|          | 3705/569592 [3:06:37<701:10:55,  4.46s/it]
                                                           

  1%|          | 3705/569592 [3:06:37<701:10:55,  4.46s/it]
  1%|          | 3706/569592 [3:06:42<706:44:24,  4.50s/it]
                                                           

  1%|          | 3706/569592 [3:06:42<706:44:24,  4.50s/it]
  1%|          | 3707/569592 [3:06:45<659:50:48,  4.20s/it]
                                                           

  1%|          | 3707/569592 [3:06:4/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101412842 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
5<659:50:48,  4.20s/it]
  1%|          | 3708/569592 [3:06:46<503:57:03,  3.21s/it]
                                                           

  1%|          | 3708/569592 [3:06:46<503:57:03,  3.21s/it]
  1%|          | 3709/569592 [3:06:50<544:33:13,  3.46s/it]
                                                           

  1%|          | 3709/569592 [3:06:50<544:33:13,  3.46s/it]
  1%|          | 3710/569592 [3:06:53<533:58:29,  3.40s/it]
                                                           

  1%|          | 3710/569592 [3:06:53<533:58:29,  3.40s/it]
  1%|          | 3711/569592 [3:06:57<535:00:05,  3.40s/it]
                                                           

  1%|          | 3711/569592 [3:06:57<535:00:05,  3.40s/it]
  1%|          | 3712/569592 [3:07:02<617:55:06,  3.93s/it]
                                                           

  1%|          | 3712/569592 [3:07:02<617:55:06,  3.93s/it]
  1%|          | 3713/569592 [3:07:06<647:19:35,  4.12s/it]
                                   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                        

  1%|          | 3713/569592 [3:07:06<647:19:35,  4.12s/it]
  1%|          | 3714/569592 [3:07:11<676:50:02,  4.31s/it]
                                                           

  1%|          | 3714/569592 [3:07:11<676:50:02,  4.31s/it]
  1%|          | 3715/569592 [3:07:14<617:16:16,  3.93s/it]
                                                           

  1%|          | 3715/569592 [3:07:14<617:16:16,  3.93s/it]
  1%|          | 3716/569592 [3:07:19<657:41:32,  4.18s/it]
                                                           

  1%|          | 3716/569592 [3:07:19<657:41:32,  4.18s/it]
  1%|          | 3717/569592 [3:07:22<614:23:12,  3.91s/it]
                                                           

  1%|          | 3717/569592 [3:07:22<614:23:12,  3.91s/it]
  1%|          | 3718/569592 [3:07:25<580:58:59,  3.70s/it]
                                                           

  1%|          | 3718/569592 [3:07:25<580:58:59,  3.70s/it]
  1%|          | 3719/569592 [3:07:30<602:05:18,  3.83s/it]
                                                           

  1%|          | 3719/569592 [3:07:30<602:05:18,  3.83s/it]
  1%|          | 3720/569592 [3:07:33<581:38:59,  3.70s/it]
                                                           

  1%|          | 3720/569592 [3:07:33<581:38:59,  3.70s/it]
  1%|          | 3721/569592 [3:07:38<626:42:12,  3.99s/it]
                                                           

  1%|          | 3721/569592 [3:07:38<626:42:12,  3.99s/it]
  1%|          | 3722/569592 [3:07:42<625:05:31,  3.98s/it]
                                                           

  1%|          | 3722/569592 [3:07:42<625:05:31,  3.98s/it]
  1%|          | 3723/569592 [3:07:47<679:07:35,  4.32s/it]
                                                           

  1%|          | 3723/569592 [3:07:47<679:07:35,  4.32s/it]
  1%|          | 3724/569592 [3:07:50<612:43:45,  3.90s/it]
                                                           

  1%|          | 3724/569592 [3:07:50<612:43:45,  3.90s/it]
  1%|          | 3725/569592 [3:07:55<665:43:41,  4.24s/it]
                                                           

  1%|          | 3725/569592 [3:07:55<665:43:41,  4.24s/it]
  1%|          | 3726/569592 [3:08:00<705:39:00,  4.49s/it]
                                                           

  1%|          | 3726/569592 [3:08:00<705:39:00,  4.49s/it]
  1%|          | 3727/569592 [3:08:04<675:22:22,  4.30s/it]
                                                           

  1%|          | 3727/569592 [3:08:04<675:22:22,  4.30s/it]
  1%|          | 3728/569592 [3:08:04<513:56:38,  3.27s/it]
                                                           

  1%|          | 3728/569592 [3:08:04<513:56:38,  3.27s/it]
  1%|          | 3729/569592 [3:08:09<585:51:36,  3.73s/it]
                                                           

  1%|          | 3729/569592 [3:08:09<585:51:36,  3.73s/it]
  1%|          | 3730/569592 [3:08:12<558:31:27,  3.55s/it]
                                                           

  1%|          | 3730/569592 [3:08:12<558:31:27,  3.55s/it]
  1%|          | 3731/569592 [3:08:16<550:14:21,  3.50s/it]
                                                           

  1%|          | 3731/569592 [3:08:16<550:14:21,  3.50s/it]
  1%|          | 3732/569592 [3:08:17<429:16:15,  2.73s/it]
                                                           

  1%|          | 3732/569592 [3:08:17<429:16:15,  2.73s/it]
  1%|          | 3733/569592 [3:08:18<348:35:07,  2.22s/it]
                                                           

  1%|          | 3733/569592 [3:08:18<348:35:07,  2.22s/it]
  1%|          | 3734/569592 [3:08:19<290:25:08,  1.85s/it]
                                                           

  1%|          | 3734/569592 [3:08:19<290:25:08,  1.85s/it]
  1%|          | 3735/569592 [3:08:20<252:37:31,  1.61s/it]
                                                           

  1%|          | 3735/569592 [3:08:20<252:37:31,  1.61s/it]
  1%|          | 3736/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91118874 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [3:08:25<413:58:15,  2.63s/it]
                                                           

  1%|          | 3736/569592 [3:08:25<413:58:15,  2.63s/it]
  1%|          | 3737/569592 [3:08:29<474:03:34,  3.02s/it]
                                                           

  1%|          | 3737/569592 [3:08:29<474:03:34,  3.02s/it]
  1%|          | 3738/569592 [3:08:32<502:49:37,  3.20s/it]
                                                           

  1%|          | 3738/569592 [3:08:32<502:49:37,  3.20s/it]
  1%|          | 3739/569592 [3:08:36<517:53:00,  3.29s/it]
                                                           

  1%|          | 3739/569592 [3:08:36<517:53:00,  3.29s/it]
  1%|          | 3740/569592 [3:08:37<411:58:34,  2.62s/it]
                                                           

  1%|          | 3740/569592 [3:08:37<411:58:34,  2.62s/it]
  1%|          | 3741/569592 [3:08:40<441:36:44,  2.81s/it]
                                                           

  1%|          | 3741/569592 [3:08:40<441:36:44,  2.81s/it]
  1%|          | 3742/569592 [3:08:41<353:18:45,  2.25s/it]
                                                           

  1%|          | 3742/569592 [3:08:41<353:18:45,  2.25s/it]
  1%|          | 3743/569592 [3:08:42<293:01:15,  1.86s/it]
                                                           

  1%|          | 3743/569592 [3:08:42<293:01:15,  1.86s/it]
  1%|          | 3744/569592 [3:08:43<249:48:32,  1.59s/it]
                                                           

  1%|          | 3744/569592 [3:08:43<249:48:32,  1.59s/it]
  1%|          | 3745/569592 [3:08:44<220:40:23,  1.40s/it]
                                                           

  1%|          | 3745/569592 [3:08:44<220:40:23,  1.40s/it]
  1%|          | 3746/569592 [3:08:45<216:45:09,  1.38s/it]
                                                           

  1%|          | 3746/569592 [3:08:45<216:45:09,  1.38s/it]
  1%|          | 3747/569592 [3:08:47<220:06:57,  1.40s/it]
                                                           

  1%|          | 3747/569592 [3:08:47<220:06:57,  1.40s/it]
  1%|          | 3748/569592 [3:08:49<277:44:49,  1.77s/it]
                                                           

  1%|          | 3748/569592 [3:08:49<277:44:49,  1.77s/it]
  1%|          | 3749/569592 [3:08:53<385:31:26,  2.45s/it]
                                                           

  1%|          | 3749/569592 [3:08:53<385:31:26,  2.45s/it]
  1%|          | 3750/569592 [3:08:55<341:20:44,  2.17s/it]
                                                           

  1%|          | 3750/569592 [3:08:55<341:20:44,  2.17s/it]
  1%|          | 3751/569592 [3:08:56<294:45:22,  1.88s/it]
                                                           

  1%|          | 3751/569592 [3:08:56<294:45:22,  1.88s/it]
  1%|          | 3752/569592 [3:08:59<358:34:42,  2.28s/it]
                                                           

  1%|          | 3752/569592 [3:08:59<358:34:42,  2.28s/it]
  1%|          | 3753/569592 [3:09:00<302:14:31,  1.92s/it]
                                                           

  1%|          | 3753/569592 [3:09:00<302:14:31,  1.92s/it]
  1%|          | 3754/569592 [3:09:05<406:21:44,  2.59s/it]
                                                           

  1%|          | 3754/569592 [3:09:05<406:21:44,  2.59s/it]
  1%|          | 3755/569592 [3:09:06<331:28:21,  2.11s/it]
                                                           

  1%|          | 3755/569592 [3:09:06<331:28:21,  2.11s/it]
  1%|          | 3756/569592 [3:09:10<424:50:00,  2.70s/it]
                                                           

  1%|          | 3756/569592 [3:09:10<424:50:00,  2.70s/it]
  1%|          | 3757/569592 [3:09:11<344:54:15,  2.19s/it]
                                                           

  1%|          | 3757/569592 [3:09:11<344:54:15,  2.19s/it]
  1%|          | 3758/569592 [3:09:16<481:19:05,  3.06s/it]
                                                           

  1%|          | 3758/569592 [3:09:16<481:19:05,  3.06s/it]
  1%|          | 3759/569592 [3:09:17<390:05:40,  2.48s/it]
                                                           

  1%|          | 3759/569592 [3:09:17<390:05:40,  2.48s/it]
  1%|          | 3760/569592 [3:09:20<425:24:27,  2.71s/it]
                                                           

  1%|          | 3760/569592 [3:09:20<425:24:27,  2.71s/it]
  1%|          | 3761/569592 [3:09:21<349:08:07,  2.22s/it]
                                                           

  1%|          | 3761/569592 [3:09:21<349:08:07,  2.22s/it]
  1%|          | 3762/569592 [3:09:25<434:45:13,  2.77s/it]
                                                           

  1%|          | 3762/569592 [3:09:25<434:45:13,  2.77s/it]
  1%|          | 3763/569592 [3:09:27<364:41:17,  2.32s/it]
                                                           

  1%|          | 3763/569592 [3:09:27<364:41:17,  2.32s/it]
  1%|          | 3764/569592 [3:09:31<451:20:41,  2.87s/it]
                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                       

  1%|          | 3764/569592 [3:09:31<451:20:41,  2.87s/it]
  1%|          | 3765/569592 [3:09:32<361:18:29,  2.30s/it]
                                                           

  1%|          | 3765/569592 [3:09:32<361:18:29,  2.30s/it]
  1%|          | 3766/569592 [3:09:34<385:57:16,  2.46s/it]
                                                           

  1%|          | 3766/569592 [3:09:34<385:57:16,  2.46s/it]
  1%|          | 3767/569592 [3:09:38<427:19:06,  2.72s/it]
                                                           

  1%|          | 3767/569592 [3:09:38<427:19:06,  2.72s/it]
  1%|          | 3768/569592 [3:09:41<432:37:18,  2.75s/it]
                                                           

  1%|          | 3768/569592 [3:09:41<432:37:18,  2.75s/it]
  1%|          | 3769/569592 [3:09:42<357:50:51,  2.28s/it]
                                                           

  1%|          | 3769/569592 [3:09:42<357:50:51,  2.28s/it]
  1%|          | 3770/569592 [3:09:45<404:58:44,  2.58s/it]
                                                           

  1%|          | 3770/569592 [3:09:45<404:58:44,  2.58s/it]
  1%|          | 3771/569592 [3:09:46<349:04:26,  2.22s/it]
                                                           

  1%|          | 3771/569592 [3:09:46<349:04:26,  2.22s/it]
  1%|          | 3772/569592 [3:09:51<444:15:05,  2.83s/it]
                                                           

  1%|          | 3772/569592 [3:09:51<444:15:05,  2.83s/it]
  1%|          | 3773/569592 [3:09:52<374:16:12,  2.38s/it]
                                                           

  1%|          | 3773/569592 [3:09:52<374:16:12,  2.38s/it]
  1%|          | 3774/569592 [3:09:55<406:21:17,  2.59s/it]
                                                           

  1%|          | 3774/569592 [3:09:55<406:21:17,  2.59s/it]
  1%|          | 3775/569592 [3:09:58<442:50:12,  2.82s/it]
                                                           

  1%|          | 3775/569592 [3:09:58<442:50:12,  2.82s/it]
  1%|          | 3776/569592 [3:10:01<417:39:24,  2.66s/it]
                                                           

  1%|          | 3776/569592 [3:10:01<417:39:24,  2.66s/it]
  1%|          | 3777/569592 [3:10:02<361:27:07,  2.30s/it]
                                                           

  1%|          | 3777/569592 [3:10:02<361:27:07,  2.30s/it]
  1%|          | 3778/569592 [3:10:06<450:47:33,  2.87s/it]
                                                           

  1%|          | 3778/569592 [3:10:06<450:47:33,  2.87s/it]
  1%|          | 3779/569592 [3:10:10<491:05:32,  3.12s/it]
                                                           

  1%|          | 3779/569592 [3:10:10<491:05:32,  3.12s/it]
  1%|          | 3780/569592 [3:10:13<500:15:12,  3.18s/it]
                                                           

  1%|          | 3780/569592 [3:10:13<500:15:12,  3.18s/it]
  1%|          | 3781/569592 [3:10:14<399:32:07,  2.54s/it]
                                                           

  1%|          | 3781/569592 [3:10:14<399:32:07,  2.54s/it]
  1%|          | 3782/569592 [3:10:18<432:46:45,  2.75s/it]
                                                           

  1%|          | 3782/569592 [3:10:18<432:46:45,  2.75s/it]
  1%|          | 3783/569592 [3:10:19<351:46:40,  2.24s/it]
                                                           

  1%|          | 3783/569592 [3:10:19<351:46:40,  2.24s/it]
  1%|          | 3784/569592 [3:10:25<522:17:55,  3.32s/it]
                                                           

  1%|          | 3784/569592 [3:10:25<522:17:55,  3.32s/it]
  1%|          | 3785/569592 [3:10:26<409:24:45,  2.60s/it]
                                                           

  1%|          | 3785/569592 [3:10:26<409:24:45,  2.60s/it]
  1%|          | 3786/569592 [3:10:31<521:23:15,  3.32s/it]
                                                           

  1%|          | 3786/569592 [3:10:31<521:23:15,  3.32s/it]
  1%|          | 3787/569592 [3:10:31<409:19:28,  2.60s/it]
                                                           

  1%|          | 3787/569592 [3:10:31<409:19:28,  2.60s/it]
  1%|          | 3788/569592 [3:10:35<443:14:21,  2.82s/it]
                                                           

  1%|          | 3788/569592 [3:10:35<443:14:21,  2.82s/it]
  1%|          | 3789/569592 [3:10:38<470:29:58,  2.99s/it]
                                                           

  1%|          | 3789/569592 [3:10:38<470:29:58,  2.99s/it]
  1%|          | 3790/569592 [3:10:42<486:58:07,  3.10s/it]
                                                           

  1%|          | 3790/569592 [3:10:42<486:58:07,  3.10s/it]
  1%|          | 3791/569592 [3:10:42<384:34:43,  2.45s/it]
                                                           

  1%|          | 3791/569592 [3:10:42<384:34:43,  2.45s/it]
  1%|          | 3792/569592 [3:10:43<317:15:11,  2.02s/it]
                                                           

  1%|          | 3792/569592 [3:10:43<317:15:11,  2.02s/it]
  1%|          | 3793/569592 [3:10:44<267:12:35,  1.70s/it]
                                                           

  1%|          | 3793/569592 [3:10:44<267:12:35,  1.70s/it]
  1%|          | 3794/569592 [3:10:49<422:02:53,  2.69s/it]
                                                           

  1%|          | 3794/569592 [3:10:49<422:02:53,  2.69s/it]
  1%|          | 3795/569592 [3:10:50<341:58:09,  2.18s/it]
                                                           

  1%|          | 3795/569592 [3:10:50<341:58:09,  2.18s/it]
  1%|          | 3796/569592 [3:10:51<283:09:46,  1.80s/it]
                                                           

  1%|          | 3796/569592 [3:10:51<283:09:46,  1.80s/it]
  1%|          | 3797/569592 [3:10:53<294:38:04,  1.87s/it]
                                                           

  1%|          | 3797/569592 [3:10:53<294:38:04,  1.87s/it]
  1%|          | 3798/569592 [3:10:59<470:51:22,  3.00s/it]
                                                           

  1%|          | 3798/569592 [3:10:59<470:51:22,  3.00s/it]
  1%|          | 3799/569592 [3:11:04<572:23:14,  3.64s/it]
                                                           

  1%|          | 3799/569592 [3:11:04<572:23:14,  3.64s/it]
  1%|          | 3800/569592 [3:11:08<581:23:11,  3.70s/it]
                                                           

  1%|          | 3800/569592 [3:11:08<581:23:11,  3.70s/it]
  1%|          | 3801/569592 [3:11:09<452:12:52,  2.88s/it]
                                                           

  1%|          | 3801/569592 [3:11:09<452:12:52,  2.88s/it]
  1%|          | 3802/569592 [3:11:13<519:45:49,  3.31s/it]
                                                           

  1%|          | 3802/569592 [3:11:13<519:45:49,  3.31s/it]
  1%|          | 3803/569592 [3:11:17<528:55:34,  3.37s/it]
                                                           

  1%|          | 3803/569592 [3:11:17<528:55:34,  3.37s/it]
  1%|          | 3804/569592 [3:11:18<422:27:37,  2.69s/it]
                                                           

  1%|          | 3804/569592 [3:11:18<422:27:37,  2.69s/it]
  1%|          | 3805/569592 [3:11:21<453:56:18,  2.89s/it]
                                                           

  1%|          | 3805/569592 [3:11:21<453:56:18,  2.89s/it]
  1%|          | 3806/569592 [3:11:22<363:36:52,  2.31s/it]
                                                           

  1%|          | 3806/569592 [3:11:22<363:36:52,  2.31s/it]
  1%|          | 3807/569592 [3:11:26<422:19:29,  2.69s/it]
                                                           

  1%|          | 3807/569592 [3:11:26<422:19:29,  2.69s/it]
  1%|          | 3808/569592 [3:11:29<456:00:34,  2.90s/it]
                                                           

  1%|          | 3808/569592 [3:11:29<456:00:34,  2.90s/it]
  1%|          | 3809/569592 [3:11:32<473:14:02,  3.01s/it]
                                                           

  1%| /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
         | 3809/569592 [3:11:32<473:14:02,  3.01s/it]
  1%|          | 3810/569592 [3:11:37<557:25:34,  3.55s/it]
                                                           

  1%|          | 3810/569592 [3:11:37<557:25:34,  3.55s/it]
  1%|          | 3811/569592 [3:11:40<536:07:20,  3.41s/it]
                                                           

  1%|          | 3811/569592 [3:11:40<536:07:20,  3.41s/it]
  1%|          | 3812/569592 [3:11:45<619:41:52,  3.94s/it]
                                                           

  1%|          | 3812/569592 [3:11:46<619:41:52,  3.94s/it]
  1%|          | 3813/569592 [3:11:49<595:13:35,  3.79s/it]
                                                           

  1%|          | 3813/569592 [3:11:49<595:13:35,  3.79s/it]
  1%|          | 3814/569592 [3:11:56<728:22:07,  4.63s/it]
                                                           

  1%|          | 3814/569592 [3:11:56<728:22:07,  4.63s/it]
  1%|          | 3815/569592 [3:12:00<728:51:03,  4.64s/it]
                                                           

  1%|          | 3815/569592 [3:12:00<728:51:03,  4.64s/it]
  1%|          | 3816/569592 [3:12:07<825:16:07,  5.25s/it]
                                                           

  1%|          | 3816/569592 [3:12:07<825:16:07,  5.25s/it]
  1%|          | 3817/569592 [3:12:10<719:49:14,  4.58s/it]
                                                           

  1%|          | 3817/569592 [3:12:10<719:49:14,  4.58s/it]
  1%|          | 3818/569592 [3:12:13<659:41:18,  4.20s/it]
                                                           

  1%|          | 3818/569592 [3:12:13<659:41:18,  4.20s/it]
  1%|          | 3819/569592 [3:12:16<610:32:01,  3.88s/it]
                                                           

  1%|          | 3819/569592 [3:12:16<610:32:01,  3.88s/it]
  1%|          | 3820/569592 [3:12:21<653:15:00,  4.16s/it]
                                                           

  1%|          | 3820/569592 [3:12:21<653:15:00,  4.16s/it]
  1%|          | 3821/569592 [3:12:26<673:43:09,  4.29s/it]
                                                           

  1%|          | 3821/569592 [3:12:26<673:43:09,  4.29s/it]
  1%|          | 3822/569592 [3:12:30<691:32:23,  4.40s/it]
                                                           

  1%|          | 3822/569592 [3:12:30<691:32:23,  4.40s/it]
  1%|          | 3823/569592 [3:12:35<703:46:23,  4.48s/it]
                                                           

  1%|          | 3823/569592 [3:12:35<703:46:23,  4.48s/it]
  1%|          | 3824/569592 [3:12:40<716:22:28,  4.56s/it]
                                                           

  1%|          | 3824/569592 [3:12:40<716:22:28,  4.56s/it]
  1%|          | 3825/569592 [3:12:43<644:08:20,  4.10s/it]
                                                           

  1%|          | 3825/569592 [3:12:43<644:08:20,  4.10s/it]
  1%|          | 3826/569592 [3:12:44<493:01:20,  3.14s/it]
                                                           

  1%|          | 3826/569592 [3:12:44<493:01:20,  3.14s/it]
  1%|          | 3827/569592 [3:12:49<585:02:51,  3.72s/it]
                                                           

  1%|          | 3827/569592 [3:12:49<585:02:51,  3.72s/it]
  1%|          | 3828/569592 [3:12:54<632:14:42,  4.02s/it]
                                                           

  1%|          | 3828/569592 [3:12:54<632:14:42,  4.02s/it]
  1%|          | 3829/569592 [3:12:58<662:02:01,  4.21s/it]
                                                           

  1%|          | 3829/569592 [3:12:58<662:02:01,  4.21s/it]
  1%|          | 3830/569592 [3:13:02<653:25:29,  4.16s/it]
                                                           

  1%|          | 3830/569592 [3:13:02<653:25:29,  4.16s/it]
  1%|          | 3831/569592 [3:13:07<688:46:16,  4.38s/it]
                                                           

  1%|          | 3831/569592 [3:13:07<688:46:16,  4.38s/it]
  1%|          | 3832/569592 [3:13:10<635:36:37,  4.04s/it]
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                           

  1%|          | 3832/569592 [3:13:10<635:36:37,  4.04s/it]
  1%|          | 3833/569592 [3:13:15<681:03:29,  4.33s/it]
                                                           

  1%|          | 3833/569592 [3:13:15<681:03:29,  4.33s/it]
  1%|          | 3834/569592 [3:13:19<656:59:55,  4.18s/it]
                                                           

  1%|          | 3834/569592 [3:13:19<656:59:55,  4.18s/it]
  1%|          | 3835/569592 [3:13:24<675:15:54,  4.30s/it]
                                                           

  1%|          | 3835/569592 [3:13:24<675:15:54,  4.30s/it]
  1%|          | 3836/569592 [3:13:28<694:11:07,  4.42s/it]
                                                           

  1%|          | 3836/569592 [3:13:28<694:11:07,  4.42s/it]
  1%|          | 3837/569592 [3:13:32<661:44:00,  4.21s/it]
                                                           

  1%|          | 3837/569592 [3:13:32<661:44:00,  4.21s/it]
  1%|          | 3838/569592 [3:13:36<620:55:24,  3.95s/it]
                                                           

  1%|          | 3838/569592 [3:13:36<620:55:24,  3.95s/it]
  1%|          | 3839/569592 [3:13:41<672:21:23,  4.28s/it]
                                                           

  1%|          | 3839/569592 [3:13:41<672:21:23,  4.28s/it]
  1%|          | 3840/569592 [3:13:45<691:58:08,  4.40s/it]
                                                           

  1%|          | 3840/569592 [3:13:45<691:58:08,  4.40s/it]
  1%|          | 3841/569592 [3:13:50<702:02:41,  4.47s/it]
                                                           

  1%|          | 3841/569592 [3:13:50<702:02:41,  4.47s/it]
  1%|          | 3842/569592 [3:13:53<643:30:56,  4.09s/it]
                                                           

  1%|          | 3842/569592 [3:13:53<643:30:56,  4.09s/it]
  1%|          | 3843/569592 [3:13:54<492:42:21,  3.14s/it]
                                                           

  1%|          | 3843/569592 [3:13:54<492:42:21,  3.14s/it]
  1%|          | 3844/569592 [3:13:57<506:32:58,  3.22s/it]
                                                           

  1%|          | 3844/569592 [3:13:57<506:32:58,  3.22s/it]
  1%|          | 3845/569592 [3:14:02<582:45:37,  3.71s/it]
                                                           

  1%|          | 3845/569592 [3:14:02<582:45:37,  3.71s/it]
  1%|          | 3846/569592 [3:14:05<555:25:30,  3.53s/it]
                                                           

  1%|          | 3846/569592 [3:14:05<555:25:30,  3.53s/it]
  1%|          | 3847/569592 [3:14:09<544:57:34,  3.47s/it]
                                                           

  1%|          | 3847/569592 [3:14:09<544:57:34,  3.47s/it]
  1%|          | 3848/569592 [3:14:10<428:51:56,  2.73s/it]
                                                           

  1%|          | 3848/569592 [3:14:10<428:51:56,  2.73s/it]
  1%|          | 3849/569592 [3:14:13<457:37:37,  2.91s/it]
                                                           

  1%|          | 3849/569592 [3:14:13<457:37:37,  2.91s/it]
  1%|          | 3850/569592 [3:14:16<471:05:15,  3.00s/it]
                                                           

  1%|          | 3850/569592 [3:14:16<471:05:15,  3.00s/it]
  1%|          | 3851/569592 [3:14:19<479:54:10,  3.05s/it]
                                                           

  1%|          | 3851/569592 [3:14:19<479:54:10,  3.05s/it]
  1%|          | 3852/569592 [3:14:20<379:22:06,  2.41s/it]
                                                           

  1%|          | 3852/569592 [3:14:20<379:22:06,  2.41s/it]
  1%|          | 3853/569592 [3:14:21<310:31:06,  1.98s/it]
                                                           

  1%|          | 3853/569592 [3:14:21<310:31:06,  1.98s/it]
  1%|          | 3854/569592 [3:14:25<387:03:23,  2.46s/it]
                                                           

  1%|          | 3854/569592 [3:14:25<387:03:23,  2.46s/it]
  1%|          | 3855/569592 [3:14:29<451:06:04,  2.87s/it]
                                                           

  1%|          | 3855/569592 [3:14:29<451:06:04,  2.87s/it]
  1%|          | 3856/569592 [3:14:32<477:12:28,  3.04s/it]
                                                           

  1%|          | 3856/569592 [3:14:32<477:12:28,  3.04s/it]
  1%|          | 3857/569592 [3:14:36<506:53:09,  3.23s/it]
                                                           

  1%|          | 3857/569592 [3:14:36<506:53:09,  3.23s/it]
  1%|          | 3858/569592 [3:14:37<400:21:51,  2.55s/it]
                                                           

  1%|          | 3858/569592 [3:14:37<400:21:51,  2.55s/it]
  1%|          | 3859/569592 [3:14:42<517:24:12,  3.29s/it]
                                                           

  1%|          | 3859/569592 [3:14:42<517:24:12,  3.29s/it]
  1%|          | 3860/569592 [3:14:43<407:56:23,  2.60s/it]
                                                           

  1%|          | 3860/569592 [3:14:43<407:56:23,  2.60s/it]
  1%|          | 3861/569592 [3:14:44<331:01:31,  2.11s/it]
                                                           

  1%|          | 3861/569592 [3:14:44<331:01:31,  2.11s/it]
  1%|          | 3862/569592 [3:14:45<278:24:25,  1.77s/it]
                                                           

  1%|          | 3862/569592 [3:14:45<278:24:25,  1.77s/it]
  1%|          | 3863/569592 [3:14:46<239:37:53,  1.52s/it]
                                                           

  1%|          | 3863/569592 [3:14:46<239:37:53,  1.52s/it]
  1%|          | 3864/569592 [3:14:47<212:25:38,  1.35s/it]
                                                           

  1%|          | 3864/569592 [3:14:47<212:25:38,  1.35s/it]
  1%|          | 3865/569592 [3:14:48<198:42:01,  1.26s/it]
                                                           

  1%|          | 3865/569592 [3:14:48<198:42:01,  1.26s/it]
  1%|          | 3866/569592 [3:14:49<190:48:05,  1.21s/it]
                                                           

  1%|          | 3866/569592 [3:14:49<190:48:05,  1.21s/it]
  1%|          | 3867/569592 [3:14:53<313:23:35,  1.99s/it]
                                                           

  1%|          | 3867/569592 [3:14:53<313:23:35,  1.99s/it]
  1%|          | 3868/569592 [3:14:56<373:41:50,  2.38s/it]
                                                           

  1%|          | 3868/569592 [3:14:56<373:41:50,  2.38s/it]
  1%|          | 3869/569592 [3:14:57<313:52:16,  2.00s/it]
                                                           

  1%|          | 3869/569592 [3:14:57<313:52:16,  2.00s/it]
  1%|          | 3870/569592 [3:14:59<299:43:56,  1.91s/it]
                                                           

  1%|          | 3870/569592 [3:14:59<299:43:56,  1.91s/it]
  1%|          | 3871/569592 [3:15:01<299:21:01,  1.90s/it]
                                                           

  1%|          | 3871/569592 [3:15:01<299:21:01,  1.90s/it]
  1%|          | 3872/569592 [3:15:06<471:26:41,  3.00s/it]
                                                           

  1%|          | 3872/569592 [3:15:06<471:26:41,  3.00s/it]
  1%|          | 3873/569592 [3:15:07<375:35:38,  2.39s/it]
                                                           

  1%|          | 3873/569592 [3:15:07<375:35:38,  2.39s/it]
  1%|          | 3874/569592 [3:15:09<355:17:13,  2.26s/it]
                                                           

  1%|          | 3874/569592 [3:15:09<355:17:13,  2.26s/it]
  1%|          | 3875/569592 [3:15:11<323:25:34,  2.06s/it]
                                                           

  1%|          | 3875/569592 [3:15:11<323:25:34,  2.06s/it]
  1%|          | 3876/569592 [3:15:16<461:18:03,  2.94s/it]
                                                           

  1%|          | 3876/569592 [3:15:16<461:18:03,  2.94s/it]
  1%|          | 3877/569592 [3:15:18<422:53:49,  2.69s/it]
                                                           

  1%|          | 3877/569592 [3:15:18<422:53:49,  2.69s/it]
  1%|          | 3878/569592 [3:15:19<374:03:54,  2.38s/it]
                                                           

  1%|          | 3878/569592 [3:15:19<374:03:54,  2.38s/it]
  1%|          | 3879/569592 [3:15:21<317:30:02,  2.02s/it]
                                                           

  1%|          | 3879/569592 [3:15:21<317:30:02,  2.02s/it]
  1%|          | 3880/569592 [3:15:26<470:55:02,  3.00s/it]
                                                           

  1%|          | 3880/569592 [3:15:26<470:55:02,  3.00s/it]
  1%|          | 3881/569592 [3:15:29<457:28:45,  2.91s/it]
                                                           

  1%|          | 3881/569592 [3:15:29<457:28:45,  2.91s/it]
  1%|          | 3882/569592 [3:15:30<371:11:32,  2.36s/it]
                                                           

  1%|          | 3882/569592 [3:15:30<371:11:32,  2.36s/it]
  1%|          | 3883/569592 [3:15:31<308:37:08,  1.96s/it]
                                                           

  1%|          | 3883/569592 [3:15:31<308:37:08,  1.96s/it]
  1%|          | 3884/569592 [3:15:36<482:12:17,  3.07s/it]
                                                           

  1%|          | 3884/569592 [3:15:36<482:12:17,  3.07s/it]
  1%|          | 3885/569592 [3:15:38<429:06:46,  2.73s/it]
                                                           

  1%|          | 3885/569592 [3:15:38<429:06:46,  2.73s/it]
  1%|          | 3886/569592 [3:15:40<393:03:19,  2.50s/it]
                                                           

  1%|          | 3886/569592 [3:15:40<393:03:19,  2.50s/it]
  1%|          | 3887/569592 [3:15:41<320:13:50,  2.04s/it]
                                                           

  1%|          | 3887/569592 [3:15:41<320:13:50,  2.04s/it]
  1%|          | 3888/569592 [3:15:47<497:31:32,  3.17s/it]
                                                           

  1%|          | 3888/569592 [3:15:47<497:31:32,  3.17s/it]
  1%|          | 3889/569592 [3:15:49<435:27:56,  2.77s/it]
                                                           

  1%|          | 3889/569592 [3:15:49<435:27:56,  2.77s/it]
  1%|          | 3890/569592 [3:15:50<373:25:50,  2.38s/it]
                                                           

  1%|          | 3890/569592 [3:15:50<373:25:50,  2.38s/it]
  1%|          | 3891/569592 [3:15:51<305:32:32,  1.94s/it]
                                                           

  1%|          | 3891/569592 [3:15:51<305:32:32,  1.94s/it]
  1%|          | 3892/569592 [3:15:59<562:56:10,  3.58s/it]
                                                           

  1%|          | 3892/569592 [3:15:59<562:56:10,  3.58s/it]
  1%|          | 3893/569592 [3:16:00<440:29:35,  2.80s/it]
                                                           

  1%|          | 3893/569592 [3:16:00<440:29:35,  2.80s/it]
  1%|          | 3894/569592 [3:16:01<353:17:53,  2.25s/it]
                                                           

  1%|          | 3894/569592 [3:16:01<353:17:53,  2.25s/it]
  1%|          | 3895/569592 [3:16:02<332:08:14,  2.11s/it]
                                                           

  1%|          | 3895/569592 [3:16:02<332:08:14,  2.11s/it]
  1%|          | 3896/569592 [3:16:08<486:43:17,  3.10s/it]
                                                           

  1%|          | 3896/569592 [3:16:08<486:43:17,  3.10s/it]
  1%|          | 3897/569592 [3:16:09<420:54:06,  2.68s/it]
                                                           

  1%|          | 3897/569592 [3:16:10<420:54:06,  2.68s/it]
  1%|          | 3898/569592 [3:16:14<525:58:15,  3.35s/it]
                                                           

  1%|          | 3898/569592 [3:16:14<525:58:15,  3.35s/it]
  1%|          | 3899/569592 [3:16:15<414:02:48,  2.63s/it]
                                                           

  1%|          | 3899/569592 [3:16:15<414:02:48,  2.63s/it]
  1%|          | 3900/569592 [3:16:17<376:22:48,  2.40s/it]
                                                           

  1%|          | 3900/569592 [3:16:17<376:22:48,  2.40s/it]
  1%|          | 3901/569592 [3:16:21<428:56:08,  2.73s/it]
                                                           

  1%|          | 3901/569592 [3:16:21<428:56:08,  2.73s/it]
  1%|          | 3902/569592 [3:16:22<345:07:05,  2.20s/it]
                                                           

  1%|          | 3902/569592 [3:16:22<345:07:05,  2.20s/it]
  1%|          | 3903/569592 [3:16:26<423:07:40,  2.69s/it]
                                                           

  1%|          | 3903/569592 [3:16:26<423:07:40,  2.69s/it]
  1%|          | 3904/569592 [3:16:29<451:21:33,  2.87s/it]
                                                           

  1%|          | 3904/569592 [3:16:29<451:21:33,  2.87s/it]
  1%|          | 3905/569592 [3:16:30<360:10:26,  2.29s/it]
                                                           

  1%|          | 3905/569592 [3:16:30<360:10:26,  2.29s/it]
  1%|          | 3906/569592 [3:16:34<428:52:07,  2.73s/it]
                                                           

  1%|          | 3906/569592 [3:16:34<428:52:07,  2.73s/it]
  1%|          | 3907/569592 [3:16:39<562:20:45,  3.58s/it]
                                                           

  1%|          | 3907/569592 [3:16:39<562:20:45,  3.58s/it]
  1%|          | 3908/569592 [3:16:43<564:02:26,  3.59s/it]
                                                           

  1%|          | 3908/569592 [3:16:43<564:02:26,  3.59s/it]
  1%|          | 3909/569592 [3:16:44<438:01:53,  2.79s/it]
                                                           

  1%|          | 3909/569592 [3:16:44<438:01:53,  2.79s/it]
  1%|          | 3910/569592 [3:16:45<349:58:08,  2.23s/it]
                                                           

  1%|          | 3910/569592 [3:16:45<349:58:08,  2.23s/it]
  1%|          | 3911/569592 [3:16:45<291:04:07,  1.85s/it]
                                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                      

  1%|          | 3911/569592 [3:16:46<291:04:07,  1.85s/it]
  1%|          | 3912/569592 [3:16:49<378:43:42,  2.41s/it]
                                                           

  1%|          | 3912/569592 [3:16:50<378:43:42,  2.41s/it]
  1%|          | 3913/569592 [3:16:55<522:47:50,  3.33s/it]
                                                           

  1%|          | 3913/569592 [3:16:55<522:47:50,  3.33s/it]
  1%|          | 3914/569592 [3:16:56<409:51:25,  2.61s/it]
                                                           

  1%|          | 3914/569592 [3:16:56<409:51:25,  2.61s/it]
  1%|          | 3915/569592 [3:16:57<333:27:39,  2.12s/it]
                                                           

  1%|          | 3915/569592 [3:16:57<333:27:39,  2.12s/it]
  1%|          | 3916/569592 [3:17:00<390:33:41,  2.49s/it]
                                                           

  1%|          | 3916/569592 [3:17:00<390:33:41,  2.49s/it]
  1%|          | 3917/569592 [3:17:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
04<442:53:45,  2.82s/it]
                                                           

  1%|          | 3917/569592 [3:17:04<442:53:45,  2.82s/it]
  1%|          | 3918/569592 [3:17:04<355:35:00,  2.26s/it]
                                                           

  1%|          | 3918/569592 [3:17:05<355:35:00,  2.26s/it]
  1%|          | 3919/569592 [3:17:05<292:54:11,  1.86s/it]
                                                           

  1%|          | 3919/569592 [3:17:05<292:54:11,  1.86s/it]
  1%|          | 3920/569592 [3:17:10<434:54:51,  2.77s/it]
                                                           

  1%|          | 3920/569592 [3:17:10<434:54:51,  2.77s/it]
  1%|          | 3921/569592 [3:17:15<536:28:36,  3.41s/it]
                                                           

  1%|          | 3921/569592 [3:17:15<536:28:36,  3.41s/it]
  1%|          | 3922/569592 [3:17:16<418:14:16,  2.66s/it]
                                                           

  1%|          | 3922/569592 [3:1/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
7:16<418:14:16,  2.66s/it]
  1%|          | 3923/569592 [3:17:21<529:35:54,  3.37s/it]
                                                           

  1%|          | 3923/569592 [3:17:21<529:35:54,  3.37s/it]
  1%|          | 3924/569592 [3:17:22<413:49:39,  2.63s/it]
                                                           

  1%|          | 3924/569592 [3:17:22<413:49:39,  2.63s/it]
  1%|          | 3925/569592 [3:17:27<521:44:36,  3.32s/it]
                                                           

  1%|          | 3925/569592 [3:17:27<521:44:36,  3.32s/it]
  1%|          | 3926/569592 [3:17:30<513:08:16,  3.27s/it]
                                                           

  1%|          | 3926/569592 [3:17:30<513:08:16,  3.27s/it]
  1%|          | 3927/569592 [3:17:33<508:43:37,  3.24s/it]
                                                           

  1%|          | 3927/569592 [3:17:33<508:43:37,  3.24s/it]
  1%|          | 3928/569592 [3:17:37<514:37:40,  3.28s/it]
                                                           

  1%|          | 3928/569592 [3:17:37<514:37:40,  3.28s/it]
  1%|          | 3929/569592 [3:17:40<505:24:50,  3.22s/it]
                                                           

  1%|          | 3929/569592 [3:17:40<505:24:50,  3.22s/it]
  1%|          | 3930/569592 [3:17:45<601:23:17,  3.83s/it]
                                                           

  1%|          | 3930/569592 [3:17:45<601:23:17,  3.83s/it]
  1%|          | 3931/569592 [3:17:50<639:27:39,  4.07s/it]
                                                           

  1%|          | 3931/569592 [3:17:50<639:27:39,  4.07s/it]
  1%|          | 3932/569592 [3:17:53<593:34:23,  3.78s/it]
                                                           

  1%|          | 3932/569592 [3:17:53<593:34:23,  3.78s/it]
  1%|          | 3933/569592 [3:17:56<583:25:23,  3.71s/it]
                                                           

  1%|          | 3933/569592 [3:17:56<583:25:23,  3.71s/it]
  1%|          | 3934/569592 [3:18:00<606:32:57,  3.86s/it]
                                                           

  1%|          | 3934/569592 [3:18:01<606:32:57,  3.86s/it]
  1%|          | 3935/569592 [3:18:05<647:45:28,  4.12s/it]
                                                           

  1%|          | 3935/569592 [3:18:05<647:45:28,  4.12s/it]
  1%|          | 3936/569592 [3:18:10<678:59:14,  4.32s/it]
                                                           

  1%|          | 3936/569592 [3:18:10<678:59:14,  4.32s/it]
  1%|          | 3937/569592 [3:18:13<631:47:23,  4.02s/it]
                                                           

  1%|          | 3937/569592 [3:18:13<631:47:23,  4.02s/it]
  1%|          | 3938/569592 [3:18:17<622:55:22,  3.96s/it]
                                                           

  1%|          | 3938/569592 [3:18:17<622:55:22,  3.96s/it]
  1%|          | 3939/569592 [3:18:21<611:46:10,  3.89s/it]
                                                           

  1%|          | 3939/569592 [3:18:21<611:46:10,  3.89s/it]
  1%|          | 3940/569592 [3:18:25<645:22:06,  4.11s/it]
                                                           

  1%|          | 3940/569592 [3:18:26<645:22:06,  4.11s/it]
  1%|          | 3941/569592 [3:18:30<667:42:57,  4.25s/it]
                                                           

  1%|          | 3941/569592 [3:18:30<667:42:57,  4.25s/it]
  1%|          | 3942/569592 [3:18:35<681:41:21,  4.34s/it]
                                                           

  1%|          | 3942/569592 [3:18:35<681:41:21,  4.34s/it]
  1%|          | 3943/569592 [3:18:39<664:06:34,  4.23s/it]
                                                           

  1%|          | 3943/569592 [3:18:39<664:06:34,  4.23s/it]
  1%|          | 3944/569592 [3:18:43<663:55:38,  4.23s/it]
                                                           

  1%|          | 3944/569592 [3:18:43<663:55:38,  4.23s/it]
  1%|          | 3945/569592 [3:18:44<508:15:55,  3.23s/it]
                                                           

  1%|          | 3945/569592 [3:18:44<508:15:55,  3.23s/it]
  1%|          | 3946/569592 [3:18:48<570:01:33,  3.63s/it]
                                                           

  1%|          | 3946/569592 [3:18:48<570:01:33,  3.63s/it]
  1%|          | 3947/569592 [3:18:53<626:43:09,  3.99s/it]
                                                           

  1%|          | 3947/569592 [3:18:53<626:43:09,  3.99s/it]
  1%|          | 3948/569592 [3:18:58<667:01:19,  4.25s/it]
                                                           

  1%|          | 3948/569592 [3:18:58<667:01:19,  4.25s/it]
  1%|          | 3949/569592 [3:19:02<648:00:44,  4.12s/it]
                                                           

  1%|          | 3949/569592 [3:19:02<648:00:44,  4.12s/it]
  1%|          | 3950/569592 [3:19:03<494:52:17,  3.15s/it]
                                                           

  1%|          | 3950/569592 [3:19:03<494:52:17,  3.15s/it]
  1%|          | 3951/569592 [3:19:08<590:17:08,  3.76s/it]
                                                           

  1%|          | 3951/569592 [3:19:08<590:17:08,  3.76s/it]
  1%|          | 3952/569592 [3:19:11<574:36:45,  3.66s/it]
                                                           

  1%|          | 3952/569592 [3:19:11<574:36:45,  3.66s/it]
  1%|          | 3953/569592 [3:19:14<542:28:00,  3.45s/it]
                                                           

  1%|          | 3953/569592 [3:19:14<542:28:00,  3.45s/it]
  1%|          | 3954/569592 [3:19:17<527:20:27,  3.36s/it]
                                                           

  1%|          | 3954/569592 [3:19:17<527:20:27,  3.36s/it]
  1%|          | 3955/569592 [3:19:22<602:40:16,  3.84s/it]
                                                           

  1%|          | 3955/569592 [3:19:22<602:40:16,  3.84s/it]
  1%|          | 3956/569592 [3:19:26<572:50:19,  3.65s/it]
                                                           

  1%|          | 3956/5/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94605504 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
69592 [3:19:26<572:50:19,  3.65s/it]
  1%|          | 3957/569592 [3:19:29<543:42:09,  3.46s/it]
                                                           

  1%|          | 3957/569592 [3:19:29<543:42:09,  3.46s/it]
  1%|          | 3958/569592 [3:19:32<551:02:58,  3.51s/it]
                                                           

  1%|          | 3958/569592 [3:19:32<551:02:58,  3.51s/it]
  1%|          | 3959/569592 [3:19:35<537:46:39,  3.42s/it]
                                                           

  1%|          | 3959/569592 [3:19:35<537:46:39,  3.42s/it]
  1%|          | 3960/569592 [3:19:39<534:44:01,  3.40s/it]
                                                           

  1%|          | 3960/569592 [3:19:39<534:44:01,  3.40s/it]
  1%|          | 3961/569592 [3:19:40<416:55:27,  2.65s/it]
                                                           

  1%|          | 3961/569592 [3:19:40<416:55:27,  2.65s/it]
  1%|          | 3962/569592 [3:19:44<502:38:35,  3.20s/it]
                                                           

  1%|          | 3962/569592 [3:19:44<502:38:35,  3.20s/it]
  1%|          | 3963/569592 [3:19:47<495:49:06,  3.16s/it]
                                                           

  1%|          | 3963/569592 [3:19:47<495:49:06,  3.16s/it]
  1%|          | 3964/569592 [3:19:52<571:20:26,  3.64s/it]
                                                           

  1%|          | 3964/569592 [3:19:52<571:20:26,  3.64s/it]
  1%|          | 3965/569592 [3:19:56<573:29:11,  3.65s/it]
                                                           

  1%|          | 3965/569592 [3:19:56<573:29:11,  3.65s/it]
  1%|          | 3966/569592 [3:19:57<442:57:18,  2.82s/it]
                                                           

  1%|          | 3966/569592 [3:19:57<442:57:18,  2.82s/it]
  1%|          | 3967/569592 [3:20:01<539:41:25,  3.43s/it]
                                                           

  1%|          | 3967/569592 [3:20:01<539:41:25,  3.43s/it]
  1%|          | 396/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94547712 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
8/569592 [3:20:02<420:05:30,  2.67s/it]
                                                           

  1%|          | 3968/569592 [3:20:02<420:05:30,  2.67s/it]
  1%|          | 3969/569592 [3:20:03<339:51:03,  2.16s/it]
                                                           

  1%|          | 3969/569592 [3:20:03<339:51:03,  2.16s/it]
  1%|          | 3970/569592 [3:20:07<416:01:57,  2.65s/it]
                                                           

  1%|          | 3970/569592 [3:20:07<416:01:57,  2.65s/it]
  1%|          | 3971/569592 [3:20:08<335:46:22,  2.14s/it]
                                                           

  1%|          | 3971/569592 [3:20:08<335:46:22,  2.14s/it]
  1%|          | 3972/569592 [3:20:11<396:11:50,  2.52s/it]
                                                           

  1%|          | 3972/569592 [3:20:11<396:11:50,  2.52s/it]
  1%|          | 3973/569592 [3:20:15<462:36:36,  2.94s/it]
                                                           

  1%|          | 3973/569592 [3:20:15<462:36:36,  2.94s/it]
  1%|          | 3974/569592 [3:20:16<372:06:23,  2.37s/it]
                                                           

  1%|          | 3974/569592 [3:20:16<372:06:23,  2.37s/it]
  1%|          | 3975/569592 [3:20:17<305:58:27,  1.95s/it]
                                                           

  1%|          | 3975/569592 [3:20:17<305:58:27,  1.95s/it]
  1%|          | 3976/569592 [3:20:21<400:20:48,  2.55s/it]
                                                           

  1%|          | 3976/569592 [3:20:21<400:20:48,  2.55s/it]
  1%|          | 3977/569592 [3:20:22<329:26:11,  2.10s/it]
                                                           

  1%|          | 3977/569592 [3:20:22<329:26:11,  2.10s/it]
  1%|          | 3978/569592 [3:20:23<278:11:37,  1.77s/it]
                                                           

  1%|          | 3978/569592 [3:20:23<278:11:37,  1.77s/it]
  1%|          | 3979/569592 [3:20:24<240:08:46,  1.53s/it]
                                                           

  1%|          | 3979/569592 [3:20:24<240:08:46,  1.53s/it]
  1%|          | 3980/569592 [3:20:26<238:00:53,  1.51s/it]
                                                           

  1%|          | 3980/569592 [3:20:26<238:00:53,  1.51s/it]
  1%|          | 3981/569592 [3:20:27<213:07:39,  1.36s/it]
                                                           

  1%|          | 3981/569592 [3:20:27<213:07:39,  1.36s/it]
  1%|          | 3982/569592 [3:20:30<279:17:51,  1.78s/it]
                                                           

  1%|          | 3982/569592 [3:20:30<279:17:51,  1.78s/it]
  1%|          | 3983/569592 [3:20:30<240:27:47,  1.53s/it]
                                                           

  1%|          | 3983/569592 [3:20:30<240:27:47,  1.53s/it]
  1%|          | 3984/569592 [3:20:35<394:02:04,  2.51s/it]
                                                           

  1%|          | 3984/569592 [3:20:35<394:02:04,  2.51s/it]
  1%|          | 3985/569592 [3:20:39<455:33:28,  2.90s/it]
                                                           

  1%|          | 3985/569592 [3:20:39<455:33:28,  2.90s/it]
  1%|          | 3986/569592 [3:20:40<376:04:00,  2.39s/it]
                                                           

  1%|          | 3986/569592 [3:20:40<376:04:00,  2.39s/it]
  1%|          | 3987/569592 [3:20:41<320:06:59,  2.04s/it]
                                                           

  1%|          | 3987/569592 [3:20:42<320:06:59,  2.04s/it]
  1%|          | 3988/569592 [3:20:45<413:06:01,  2.63s/it]
                                                           

  1%|          | 3988/569592 [3:20:46<413:06:01,  2.63s/it]
  1%|          | 3989/569592 [3:20:47<362:07:39,  2.30s/it]
                                                           

  1%|          | 3989/569592 [3:20:47<362:07:39,  2.30s/it]
  1%|          | 3990/569592 [3:20:49<364:16:41,  2.32s/it]
                                                           

  1%|          | 3990/569592 [3:20:49<364:16:41,  2.32s/it]
  1%|          | 3991/569592 [3:20:52<363:57:06,  2.32s/it]
                                                           

  1%|          | 3991/569592 [3:20:52<363:57:06,  2.32s/it]
  1%|          | 3992/569592 [3:20:56<465:19:38,  2.96s/it]
                                                           

  1%|          | 3992/569592 [3:20:56<465:19:38,  2.96s/it]
  1%|          | 3993/569592 [3:20:57<371:30:43,  2.36s/it]
                                                           

  1%|          | 3993/569592 [3:20:57<371:30:43,  2.36s/it]
  1%|          | 3994/569592 [3:21:00<374:57:08,  2.39s/it]
                                                           

  1%|          | 3994/569592 [3:21:00<374:57:08,  2.39s/it]
  1%|          | 3995/569592 [3:21:02<376:36:35,  2.40s/it]
                                                           

  1%|          | 3995/569592 [3:21:02<376:36:35,  2.40s/it]
  1%|          | 3996/569592 [3:21:08<533:20:50,  3.39s/it]
                                                           

  1%|          | 3996/569592 [3:21:08<533:20:50,  3.39s/it]
  1%|          | 3997/569592 [3:21:09<423:48:26,  2.70s/it]
                                                           

  1%|          | 3997/569592 [3:21:09<423:48:26,  2.70s/it]
  1%|          | 3998/569592 [3:21:11<382:34:12,  2.44s/it]
                                                           

  1%|          | 3998/569592 [3:21:11<382:34:12,  2.44s/it]
  1%|          | 3999/569592 [3:21:12<353:25:08,  2.25s/it]
                                                           

  1%|          | 3999/569592 [3:21:12<353:25:08,  2.25s/it]
  1%|          | 4000/569592 [3:21:16<428:53:07,  2.73s/it]
                                                           

  1%|          | 4000/569592 [3:21:16<428:53:07,  2.73s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-4000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-4000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-4000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-4000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-4000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-4000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-3000] due to args.save_total_limit

  1%|          | 4001/569592 [3:23:16<5943:44:24, 37.83s/it]
                                                            

  1%|          | 4001/569592 [3:23:16<5943:44:24, 37.83s/it]
  1%|          | 4002/569592 [3:23:19<4305:34:28, 27.41s/it]
                                                            

  1%|          | 4002/569592 [3:23:19<4305:34:28, 27.41s/it]
  1%|          | 4003/569592 [3:23:20<3057:29:54, 19.46s/it]
                                                            

  1%|          | 4003/569592 [3:23:20<3057:29:54, 19.46s/it]
  1%|          | 4004/569592 [3:23:21<2185:01:32, 13.91s/it]
                                                            

  1%|          | 4004/569592 [3:23:21<2185:01:32, 13.91s/it]
  1%|          | 4005/569592 [3:23:22<1579:05:30, 10.05s/it]
                                                            

  1%|          | 4005/569592 [3:23:22<1579:05:30, 10.05s/it]
  1%|          | 4006/569592 [3:23:23<1149:43:07,  7.32s/it]
                                                            

  1%|          | 4006/569592 [3:23:23<1149:43:07,  7.32s/it]
  1%|          | 4007/569592 [3:23:24<854:08:26,  5.44s/it] 
                                                           

  1%|          | 4007/569592 [3:23:24<854:08:26,  5.44s/it]
  1%|          | 4008/569592 [3:23:25<642:10:04,  4.09s/it]
                                                           

  1%|          | 4008/569592 [3:23:25<642:10:04,  4.09s/it]
  1%|          | 4009/569592 [3:23:29<647:53:11,  4.12s/it]
                                                           

  1%|          | 4009/569592 [3:23:29<647:53:11,  4.12s/it]
  1%|          | 4010/569592 [3:23:31<522:33:30,  3.33s/it]
                                                           

  1%|          | 4010/569592 [3:23:31<522:33:30,  3.33s/it]
  1%|          | 4011/569592 [3:23:33<464:31:11,  2.96s/it]
                                                           

  1%|          | 4011/569592 [3:23:33<464:31:11,  2.96s/it]
  1%|          | 4012/569592 [3:23:34<404:49:05,  2.58s/it]
                                                           

  1%|          | 4012/569592 [3:23:34<404:49:05,  2.58s/it]
  1%|          | 4013/569592 [3:23:35<330:42:22,  2.10s/it]
                                                           

  1%|          | 4013/569592 [3:23:35<330:42:22,  2.10s/it]
  1%|          | 4014/569592 [3:23:38<375:56:56,  2.39s/it]
                                                           

  1%|          | 4014/569592 [3:23:38<375:56:56,  2.39s/it]
  1%|          | 4015/569592 [3:23:45<554:12:12,  3.53s/it]
                                                           

  1%|          | 4015/569592 [3:23:45<554:12:12,  3.53s/it]
  1%|          | 4016/569592 [3:23:48<550:09:11,  3.50s/it]
                                                           

  1%|          | 4016/569592 [3:23:48<550:09:11,  3.50s/it]
  1%|          | 4017/569592 [3:23:49<435:03:00,  2.77s/it]
                                                           

  1%|          | 4017/569592 [3:23:49<435:03:00,  2.77s/it]
  1%|          | 4018/569592 [3:23:50<352:20:45,  2.24s/it]
                                                           

  1%|          | 4018/569592 [3:23:50<352:20:45,  2.24s/it]
  1%|          | 4019/569592 [3:23:56<502:54:34,  3.20s/it]
                                                           

  1%|          | 4019/569592 [3:23:56<502:54:34,  3.20s/it]
  1%|          | 4020/569592 [3:24:01<592:38:22,  3.77s/it]
                                                           

  1%|          | 4020/569592 [3:24:01<592:38:22,  3.77s/it]
  1%|          | 4021/569592 [3:24:02<464:17:53,  2.96s/it]
                                                           

  1%|          | 4021/569592 [3:24:02<464:17:53,  2.96s/it]
  1%|          | 4022/569592 [3:24:03<369:11:37,  2.35s/it]
                                                           

  1%|          | 4022/569592 [3:24:03<369:11:37,  2.35s/it]
  1%|          | 4023/569592 [3:24:08<497:52:47,  3.17s/it]
                                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101756928 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                         

  1%|          | 4023/569592 [3:24:08<497:52:47,  3.17s/it]
  1%|          | 4024/569592 [3:24:13<605:24:00,  3.85s/it]
                                                           

  1%|          | 4024/569592 [3:24:13<605:24:00,  3.85s/it]
  1%|          | 4025/569592 [3:24:14<467:57:40,  2.98s/it]
                                                           

  1%|          | 4025/569592 [3:24:14<467:57:40,  2.98s/it]
  1%|          | 4026/569592 [3:24:15<381:37:23,  2.43s/it]
                                                           

  1%|          | 4026/569592 [3:24:15<381:37:23,  2.43s/it]
  1%|          | 4027/569592 [3:24:16<314:52:31,  2.00s/it]
                                                           

  1%|          | 4027/569592 [3:24:16<314:52:31,  2.00s/it]
  1%|          | 4028/569592 [3:24:17<264:57:15,  1.69s/it]
                                                           

  1%|          | 4028/569592 [3:24:17<264:57:15,  1.69s/it]
  1%|          | 4029/569592 [3:24:21<349:53:33,  2.23s/it]
                                                           

  1%|          | 4029/569592 [3:24:21<349:53:33,  2.23s/it]
  1%|          | 4030/569592 [3:24:23<339:32:18,  2.16s/it]
                                                           

  1%|          | 4030/569592 [3:24:23<339:32:18,  2.16s/it]
  1%|          | 4031/569592 [3:24:24<283:30:11,  1.80s/it]
                                                           

  1%|          | 4031/569592 [3:24:24<283:30:11,  1.80s/it]
  1%|          | 4032/569592 [3:24:25<260:27:41,  1.66s/it]
                                                           

  1%|          | 4032/569592 [3:24:25<260:27:41,  1.66s/it]
  1%|          | 4033/569592 [3:24:31<445:42:04,  2.84s/it]
                                                           

  1%|          | 4033/569592 [3:24:31<445:42:04,  2.84s/it]
  1%|          | 4034/569592 [3:24:36<568:17:01,  3.62s/it]
                                                           

  1%|          | 4034/569592 [3:24:36<568:17:01,  3.62s/it]
  1%|          | 4035/569592 [3:24:40<584:49:05,  3.72s/it]
                                                           

  1%|          | 4035/569592 [3:24:40<584:49:05,  3.72s/it]
  1%|          | 4036/569592 [3:24:45<651:41:19,  4.15s/it]
                                                           

  1%|          | 4036/569592 [3:24:45<651:41:19,  4.15s/it]
  1%|          | 4037/569592 [3:24:49<611:52:02,  3.89s/it]
                                                           

  1%|          | 4037/569592 [3:24:49<611:52:02,  3.89s/it]
  1%|          | 4038/569592 [3:24:52<597:34:35,  3.80s/it]
                                                           

  1%|          | 4038/569592 [3:24:52<597:34:35,  3.80s/it]
  1%|          | 4039/569592 [3:24:56<590:38:34,  3.76s/it]
                                                           

  1%|          | 4039/569592 [3:24:56<590:38:34,  3.76s/it]
  1%|          | 4040/569592 [3:25:00<611:02:21,  3.89s/it]
                                                           

  1%|          | 4040/569592 [3:25:00<611:02:21,  3.89s/it]
  1%|          | 4041/569592 [3:25:05<642:39:50,  4.09s/it]
                                                           

  1%|          | 4041/569592 [3:25:05<642:39:50,  4.09s/it]
  1%|          | 4042/569592 [3:25:05<492:41:18,  3.14s/it]
                                                           

  1%|          | 4042/569592 [3:25:05<492:41:18,  3.14s/it]
  1%|          | 4043/569592 [3:25:11<585:43:39,  3.73s/it]
                                                           

  1%|          | 4043/569592 [3:25:11<585:43:39,  3.73s/it]
  1%|          | 4044/569592 [3:25:15<634:55:23,  4.04s/it]
                                                           

  1%|          | 4044/569592 [3:25:15<634:55:23,  4.04s/it]
  1%|          | 4045/569592 [3:25:20<684:48:13,  4.36s/it]
                                                           

  1%|          | 4045/569592 [3:25:20<684:48:13,  4.36s/it]
  1%|          | 4046/569592 [3:25:25<710:00:57,  4.52s/it]
                                                           

  1%|          | 4046/569592 [3:25:25<710:00:57,  4.52s/it]
  1%|          | 4047/569592 [3:25:30<730:52:19,  4.65s/it]
                                                           

  1%|          | 4047/569592 [3:25:30<730:52:19,  4.65s/it]
  1%|          | 4048/569592 [3:25:34<678:58:50,  4.32s/it]
                                                           

  1%|          | 4048/569592 [3:25:34<678:58:50,  4.32s/it]
  1%|          | 4049/569592 [3:25:38<665:36:02,  4.24s/it]
                                                           

  1%|          | 4049/569592 [3:25:38<665:36:02,  4.24s/it]
  1%|          | 4050/569592 [3:25:42<680:01:53,  4.33s/it]
                                                           

  1%|          | 4050/569592 [3:25:42<680:01:53,  4.33s/it]
  1%|          | 4051/569592 [3:25:47<709:38:16,  4.52s/it]
                                                           

  1%|          | 4051/569592 [3:25:47<709:38:16,  4.52s/it]
  1%|          | 4052/569592 [3:25:50<642:36:04,  4.09s/it]
                                                           

  1%|          | 4052/569592 [3:25:50<642:36:04,  4.09s/it]
  1%|          | 4053/569592 [3:25:55<673:04:56,  4.28s/it]
                                                           

  1%|          | 4053/569592 [3:25:55<673:04:56,  4.28s/it]
  1%|          | 4054/569592 [3:26:00<696:29:11,  4.43s/it]
                                                           

  1%|          | 4054/569592 [3:26:00<696:29:11,  4.43s/it]
  1%|          | 4055/569592 [3:26:07<842:04:24,  5.36s/it]
                                                           

  1%|          | 4055/569592 [3:26:07<842:04:24,  5.36s/it]
  1%|          | 4056/569592 [3:26:12<823:57:22,  5.25s/it]
                                                           

  1%|          | 4056/569592 [3:26:12<823:57:22,  5.25s/it]
  1%|          | 4057/569592 [3:26:16<760:21:53,  4.84s/it]
                                                           

  1%|          | 4057/569592 [3:26:16<760:21:53,  4.84s/it]
  1%|          | 4058/569592 [3:26:21<749:26:01,  4.77s/it]
                                                           

  1%|          | 4058/569592 [3:26:21<749:26:01,  4.77s/it]
  1%|          | 4059/569592 [3:26:25<707:40:06,  4.50s/it]
                                                           

  1%|          | 4059/569592 [3:26:25<707:40:06,  4.50s/it]
  1%|          | 4060/569592 [3:26:29<681:10:07,  4.34s/it]
                                                           

  1%|          | 4060/569592 [3:26:29<681:10:07,  4.34s/it]
  1%|          | 4061/569592 [3:26:32<646:15:05,  4.11s/it]
                                                           

  1%|          | 4061/569592 [3:26:32<646:15:05,  4.11s/it]
  1%|          | 4062/569592 [3:26:36<622:14:31,  3.96s/it]
                                                           

  1%|          | 4062/569592 [3:26:36<622:14:31,  3.96s/it]
  1%|          | 4063/569592 [3:26:41<652:11:17,  4.15s/it]
                                                           

  1%|          | 4063/569592 [3:26:41<652:11:17,  4.15s/it]
  1%|          | 4064/569592 [3:26:44<624:45:01,  3.98s/it]
                                                           

  1%|          | 4064/569592 [3:26:44<624:45:01,  3.98s/it]
  1%|          | 4065/569592 [3:26:49<676:02:46,  4.30s/it]
                                                           

  1%|          | 4065/569592 [3:26:49<676:02:46,  4.30s/it]
  1%|          | 4066/569592 [3:26:52<618:36:14,  3.94s/it]
                                                           

  1%|          | 4066/569592 [3:26:52<618:36:14,  3.94s/it]
  1%|          | 4067/569592 [3:26:57<647:22:47,  4.12s/it]
                                                           

  1%|          | 4067/569592 [3:26:57<647:22:47,  4.12s/it]
  1%|          | 4068/569592 [3:27:00<601:19:54,  3.83s/it]
                                                           

  1%|          | 406/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
8/569592 [3:27:00<601:19:54,  3.83s/it]
  1%|          | 4069/569592 [3:27:01<463:02:58,  2.95s/it]
                                                           

  1%|          | 4069/569592 [3:27:01<463:02:58,  2.95s/it]
  1%|          | 4070/569592 [3:27:06<550:30:26,  3.50s/it]
                                                           

  1%|          | 4070/569592 [3:27:06<550:30:26,  3.50s/it]
  1%|          | 4071/569592 [3:27:10<590:51:34,  3.76s/it]
                                                           

  1%|          | 4071/569592 [3:27:10<590:51:34,  3.76s/it]
  1%|          | 4072/569592 [3:27:13<559:36:22,  3.56s/it]
                                                           

  1%|          | 4072/569592 [3:27:13<559:36:22,  3.56s/it]
  1%|          | 4073/569592 [3:27:18<608:56:08,  3.88s/it]
                                                           

  1%|          | 4073/569592 [3:27:18<608:56:08,  3.88s/it]
  1%|          | 4074/569592 [3:27:21<581:30:59,  3.70s/it]
                                                           

  1%|          | 4074/569592 [3:27:21<581:30:59,  3.70s/it]
  1%|          | 4075/569592 [3:27:24<552:39:59,  3.52s/it]
                                                           

  1%|          | 4075/569592 [3:27:24<552:39:59,  3.52s/it]
  1%|          | 4076/569592 [3:27:27<536:42:01,  3.42s/it]
                                                           

  1%|          | 4076/569592 [3:27:27<536:42:01,  3.42s/it]
  1%|          | 4077/569592 [3:27:31<562:58:48,  3.58s/it]
                                                           

  1%|          | 4077/569592 [3:27:31<562:58:48,  3.58s/it]
  1%|          | 4078/569592 [3:27:35<587:27:03,  3.74s/it]
                                                           

  1%|          | 4078/569592 [3:27:35<587:27:03,  3.74s/it]
  1%|          | 4079/569592 [3:27:39<584:48:31,  3.72s/it]
                                                           

  1%|          | 4079/569592 [3:27:39<584:48:31,  3.72s/it]
  1%|          | /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
4080/569592 [3:27:43<571:30:28,  3.64s/it]
                                                           

  1%|          | 4080/569592 [3:27:43<571:30:28,  3.64s/it]
  1%|          | 4081/569592 [3:27:46<541:56:46,  3.45s/it]
                                                           

  1%|          | 4081/569592 [3:27:46<541:56:46,  3.45s/it]
  1%|          | 4082/569592 [3:27:46<423:31:19,  2.70s/it]
                                                           

  1%|          | 4082/569592 [3:27:46<423:31:19,  2.70s/it]
  1%|          | 4083/569592 [3:27:50<482:45:38,  3.07s/it]
                                                           

  1%|          | 4083/569592 [3:27:50<482:45:38,  3.07s/it]
  1%|          | 4084/569592 [3:27:55<530:57:26,  3.38s/it]
                                                           

  1%|          | 4084/569592 [3:27:55<530:57:26,  3.38s/it]
  1%|          | 4085/569592 [3:27:55<415:17:41,  2.64s/it]
                                                           

  1%|          | 4085/569592 [3:27:55<415:17:41,  2.64s/it]
  1%|          | 4086/569592 [3:27:59<446:51:55,  2.84s/it]
                                                           

  1%|          | 4086/569592 [3:27:59<446:51:55,  2.84s/it]
  1%|          | 4087/569592 [3:28:03<522:27:53,  3.33s/it]
                                                           

  1%|          | 4087/569592 [3:28:03<522:27:53,  3.33s/it]
  1%|          | 4088/569592 [3:28:07<539:48:11,  3.44s/it]
                                                           

  1%|          | 4088/569592 [3:28:07<539:48:11,  3.44s/it]
  1%|          | 4089/569592 [3:28:08<420:43:27,  2.68s/it]
                                                           

  1%|          | 4089/569592 [3:28:08<420:43:27,  2.68s/it]
  1%|          | 4090/569592 [3:28:12<472:46:23,  3.01s/it]
                                                           

  1%|          | 4090/569592 [3:28:12<472:46:23,  3.01s/it]
  1%|          | 4091/569592 [3:28:13<375:07:06,  2.39s/it]
                                                           

  1%|          | 4091/569592 [3:28:13<375:07:06,  2.39s/it]
  1%|          | 4092/569592 [3:28:14<311:15:41,  1.98s/it]
                                                           

  1%|          | 4092/569592 [3:28:14<311:15:41,  1.98s/it]
  1%|          | 4093/569592 [3:28:15<263:06:36,  1.67s/it]
                                                           

  1%|          | 4093/569592 [3:28:15<263:06:36,  1.67s/it]
  1%|          | 4094/569592 [3:28:15<227:58:47,  1.45s/it]
                                                           

  1%|          | 4094/569592 [3:28:15<227:58:47,  1.45s/it]
  1%|          | 4095/569592 [3:28:16<203:35:13,  1.30s/it]
                                                           

  1%|          | 4095/569592 [3:28:16<203:35:13,  1.30s/it]
  1%|          | 4096/569592 [3:28:17<186:35:42,  1.19s/it]
                                                           

  1%|          | 4096/569592 [3:28:17<186:35:42,  1.19s/it]
  1%|          | 4097/569592 [3:28:20<254:08:32,  1.62s/it]
                                                           

  1%|          | 4097/569592 [3:28:20<254:08:32,  1.62s/it]
  1%|          | 4098/569592 [3:28:24<357:18:10,  2.27s/it]
                                                           

  1%|          | 4098/569592 [3:28:24<357:18:10,  2.27s/it]
  1%|          | 4099/569592 [3:28:25<326:40:48,  2.08s/it]
                                                           

  1%|          | 4099/569592 [3:28:25<326:40:48,  2.08s/it]
  1%|          | 4100/569592 [3:28:26<272:50:52,  1.74s/it]
                                                           

  1%|          | 4100/569592 [3:28:26<272:50:52,  1.74s/it]
  1%|          | 4101/569592 [3:28:30<364:02:06,  2.32s/it]
                                                           

  1%|          | 4101/569592 [3:28:30<364:02:06,  2.32s/it]
  1%|          | 4102/569592 [3:28:31<300:37:42,  1.91s/it]
                                                           

  1%|          | 4102/569592 [3:28:31<300:37:42,  1.91s/it]
  1%|          | 4103/569592 [3:28:35<413:43:17,  2.63s/it]
                                                           

  1%|          | 4103/569592 [3:28:35<413:43:17,  2.63s/it]
  1%|          | 4104/569592 [3:28:37<348:35:20,  2.22s/it]
                                                           

  1%|          | 4104/569592 [3:28:37<348:35:20,  2.22s/it]
  1%|          | 4105/569592 [3:28:40<403:33:02,  2.57s/it]
                                                           

  1%|          | 4105/569592 [3:28:40<403:33:02,  2.57s/it]
  1%|          | 4106/569592 [3:28:41<338:06:54,  2.15s/it]
                                                           

  1%|          | 4106/569592 [3:28:41<338:06:54,  2.15s/it]
  1%|          | 4107/569592 [3:28:45<415:03:55,  2.64s/it]
                                                           

  1%|          | 4107/569592 [3:28:45<415:03:55,  2.64s/it]
  1%|          | 4108/569592 [3:28:48<417:29:59,  2.66s/it]
                                                           

  1%|          | 4108/569592 [3:28:48<417:29:59,  2.66s/it]
  1%|          | 4109/569592 [3:28:50<386:55:03,  2.46s/it]
                                                           

  1%|          | 4109/569592 [3:28:50<386:55:03,  2.46s/it]
  1%|          | 4110/569592 [3:28:51<333:45:53,  2.12s/it]
                                                           

  1%|          | 4110/569592 [3:28:51<333:45:53,  2.12s/it]
  1%|          | 4111/569592 [3:28:58<561:29:45,  3.57s/it]
                                                           

  1%|          | 4111/569592 [3:28:58<561:29:45,  3.57s/it]
  1%|          | 4112/569592 [3:28:59<440:37:58,  2.81s/it]
                                                           

  1%|          | 4112/569592 [3:28:59<440:37:58,  2.81s/it]
  1%|          | 4113/569592 [3:29:00<367:39:49,  2.34s/it]
                                                           

  1%|          | 4113/569592 [3:29:00<367:39:49,  2.34s/it]
  1%|          | 4114/569592 [3:29:01<302:08:54,  1.92s/it]
                                                           

  1%|          | 4114/569592 [3:29:01<302:08:54,  1.92s/it]
  1%|          | 4115/569592 [3:29:07<497:30:39,  3.17s/it]
                                                           

  1%|          | 4115/569592 [3:29:07<497:30:39,  3.17s/it]
  1%|          | 4116/569592 [3:29:09<446:26:48,  2.84s/it]
                                                           

  1%|          | 4116/569592 [3:29:09<446:26:48,  2.84s/it]
  1%|          | 4117/569592 [3:29:11<404:41:16,  2.58s/it]
                                                           

  1%|          | 4117/569592 [3:29:11<404:41:16,  2.58s/it]
  1%|          | 4118/569592 [3:29:12<328:53:05,  2.09s/it]
                                                           

  1%|          | 4118/569592 [3:29:12<328:53:05,  2.09s/it]
  1%|          | 4119/569592 [3:29:17<448:08:29,  2.85s/it]
                                                           

  1%|          | 4119/569592 [3:29:17<448:08:29,  2.85s/it]
  1%|          | 4120/569592 [3:29:19<409:35:10,  2.61s/it]
                                                           

  1%|          | 4120/569592 [3:29:19<409:35:10,  2.61s/it]
  1%|          | 4121/569592 [3:29:22<421:22:05,  2.68s/it]
                                                           

  1%|          | 4121/569592 [3:29:22<421:22:05,  2.68s/it]
  1%|          | 4122/569592 [3:29:26<491:50:53,  3.13s/it]
                                                           

  1%|          | 4122/569592 [3:29:26<491:50:53,  3.13s/it]
  1%|          | 4123/569592 [3:29:27<392:40:23,  2.50s/it]
                                                           

  1%|          | 4123/569592 [3:29:27<392:40:23,  2.50s/it]
  1%|          | 4124/569592 [3:29:29<376:11:05,  2.39s/it]
                                                           

  1%|          | 4124/569592 [3:29:29<376:11:05,  2.39s/it]
  1%|          | 4125/569592 [3:29:32<404:35:24,  2.58s/it]
                                                           

  1%|          | 4125/569592 [3:29:32<404:35:24,  2.58s/it]
  1%|          | 4126/569592 [3:29:33<327:50:27,  2.09s/it]
                                                           

  1%|          | 4126/569592 [3:29:33<327:50:27,  2.09s/it]
  1%|          | 4127/569592 [3:29:36<390:07:11,  2.48s/it]
                                                           

  1%|          | 4127/569592 [3:29:36<390:07:11,  2.48s/it]
  1%|          | 4128/569592 [3:29:40<432:19:41,  2.75s/it]
                                                           

  1%|          | 4128/569592 [3:29:40<432:19:41,  2.75s/it]
  1%|          | 4129/569592 [3:29:42<389:08:25,  2.48s/it]
                                                           

  1%|          | 4129/569592 [3:29:42<389:08:25,  2.48s/it]
  1%|          | 4130/569592 [3:29:43<318:50:22,  2.03s/it]
                                                           

  1%|          | 4130/569592 [3:29:43<318:50:22,  2.03s/it]
  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
1%|          | 4131/569592 [3:29:47<453:14:50,  2.89s/it]
                                                           

  1%|          | 4131/569592 [3:29:47<453:14:50,  2.89s/it]
  1%|          | 4132/569592 [3:29:49<400:15:15,  2.55s/it]
                                                           

  1%|          | 4132/569592 [3:29:49<400:15:15,  2.55s/it]
  1%|          | 4133/569592 [3:29:54<517:03:23,  3.29s/it]
                                                           

  1%|          | 4133/569592 [3:29:54<517:03:23,  3.29s/it]
  1%|          | 4134/569592 [3:29:59<604:29:56,  3.85s/it]
                                                           

  1%|          | 4134/569592 [3:29:59<604:29:56,  3.85s/it]
  1%|          | 4135/569592 [3:30:00<467:21:26,  2.98s/it]
                                                           

  1%|          | 4135/569592 [3:30:00<467:21:26,  2.98s/it]
  1%|          | 4136/569592 [3:30:04<493:45:02,  3.14s/it]
                                                           

  1%|          | 4136/569592 [3:30:04<493:45:02,  3.14s/it]
  1%|          | 4137/569592 [3:30:07<505:15:04,  3.22s/it]
                                                           

  1%|          | 4137/569592 [3:30:07<505:15:04,  3.22s/it]
  1%|          | 4138/569592 [3:30:08<399:03:00,  2.54s/it]
                                                           

  1%|          | 4138/569592 [3:30:08<399:03:00,  2.54s/it]
  1%|          | 4139/569592 [3:30:09<324:37:29,  2.07s/it]
                                                           

  1%|          | 4139/569592 [3:30:09<324:37:29,  2.07s/it]
  1%|          | 4140/569592 [3:30:10<271:48:02,  1.73s/it]
                                                           

  1%|          | 4140/569592 [3:30:10<271:48:02,  1.73s/it]
  1%|          | 4141/569592 [3:30:12<265:27:14,  1.69s/it]
                                                           

  1%|          | 4141/569592 [3:30:12<265:27:14,  1.69s/it]
  1%|          | 4142/569592 [3:30:17<426:23:02,  2.71s/it]
                                                           

  1%|          | 4142/569592 [3:30:17<426:23:02,  2.71s/it]
  1%|          | 4143/569592 [3:30:18<344:55:00,  2.20s/it]
                                                           

  1%|          | 4143/569592 [3:30:18<344:55:00,  2.20s/it]
  1%|          | 4144/569592 [3:30:20<329:50:13,  2.10s/it]
                                                           

  1%|          | 4144/569592 [3:30:20<329:50:13,  2.10s/it]
  1%|          | 4145/569592 [3:30:25<468:52:55,  2.99s/it]
                                                           

  1%|          | 4145/569592 [3:30:25<468:52:55,  2.99s/it]
  1%|          | 4146/569592 [3:30:26<372:13:18,  2.37s/it]
                                                           

  1%|          | 4146/569592 [3:30:26<372:13:18,  2.37s/it]
  1%|          | 4147/569592 [3:30:27<309:13:52,  1.97s/it]
                                                           

  1%|          | 4147/569592 [3:30:27<309:13:52,  1.97s/i/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97176671 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
t]
  1%|          | 4148/569592 [3:30:29<344:07:49,  2.19s/it]
                                                           

  1%|          | 4148/569592 [3:30:29<344:07:49,  2.19s/it]
  1%|          | 4149/569592 [3:30:35<504:46:01,  3.21s/it]
                                                           

  1%|          | 4149/569592 [3:30:35<504:46:01,  3.21s/it]
  1%|          | 4150/569592 [3:30:39<519:17:06,  3.31s/it]
                                                           

  1%|          | 4150/569592 [3:30:39<519:17:06,  3.31s/it]
  1%|          | 4151/569592 [3:30:39<407:25:08,  2.59s/it]
                                                           

  1%|          | 4151/569592 [3:30:40<407:25:08,  2.59s/it]
  1%|          | 4152/569592 [3:30:43<450:32:48,  2.87s/it]
                                                           

  1%|          | 4152/569592 [3:30:43<450:32:48,  2.87s/it]
  1%|          | 4153/569592 [3:30:48<551:57:25,  3.51s/it]
                                                           

  1%|          | 4153/569592 [3:30:48<551:57:25,  3.51s/it]
  1%|          | 4154/569592 [3:30:51<532:43:15,  3.39s/it]
                                                           

  1%|          | 4154/569592 [3:30:51<532:43:15,  3.39s/it]
  1%|          | 4155/569592 [3:30:52<416:00:22,  2.65s/it]
                                                           

  1%|          | 4155/569592 [3:30:52<416:00:22,  2.65s/it]
  1%|          | 4156/569592 [3:30:56<458:57:43,  2.92s/it]
                                                           

  1%|          | 4156/569592 [3:30:56<458:57:43,  2.92s/it]
  1%|          | 4157/569592 [3:30:59<505:13:45,  3.22s/it]
                                                           

  1%|          | 4157/569592 [3:31:00<505:13:45,  3.22s/it]
  1%|          | 4158/569592 [3:31:03<525:45:54,  3.35s/it]
                                                           

  1%|          | 4158/569592 [3:31:03<525:45:54,  3.35s/it]
  1%|          | 4159/569592 [3:31:06<517:19:32,  3.29s/it]
                                                           

  1%|          | 4159/569592 [3:31:06<517:19:32,  3.29s/it]
  1%|          | 4160/569592 [3:31:11<585:09:01,  3.73s/it]
                                                           

  1%|          | 4160/569592 [3:31:11<585:09:01,  3.73s/it]
  1%|          | 4161/569592 [3:31:14<565:55:52,  3.60s/it]
                                                           

  1%|          | 4161/569592 [3:31:14<565:55:52,  3.60s/it]
  1%|          | 4162/569592 [3:31:20<643:35:09,  4.10s/it]
                                                           

  1%|          | 4162/569592 [3:31:20<643:35:09,  4.10s/it]
  1%|          | 4163/569592 [3:31:24<664:10:43,  4.23s/it]
                                                           

  1%|          | 4163/569592 [3:31:24<664:10:43,  4.23s/it]
  1%|          | 4164/569592 [3:31:28<646:00:16,  4.11s/it]
                                                           

  1%|          | 4164/569592 [3:31:28<646:00:16,  4.11s/it]
  1%|          | 4165/569592 [3:31:29<493:23:16,  3.14s/it]
                                                           

  1%|          | 4165/569592 [3:31:29<493:23:16,  3.14s/it]
  1%|          | 4166/569592 [3:31:32<505:48:08,  3.22s/it]
                                                           

  1%|          | 4166/569592 [3:31:32<505:48:08,  3.22s/it]
  1%|          | 4167/569592 [3:31:37<596:29:43,  3.80s/it]
                                                           

  1%|          | 4167/569592 [3:31:37<596:29:43,  3.80s/it]
  1%|          | 4168/569592 [3:31:42<636:35:00,  4.05s/it]
                                                           

  1%|          | 4168/569592 [3:31:42<636:35:00,  4.05s/it]
  1%|          | 4169/569592 [3:31:48<712:48:50,  4.54s/it]
                                                           

  1%|          | 4169/569592 [3:31:48<712:48:50,  4.54s/it]
  1%|          | 4170/569592 [3:31:51<641:29:18,  4.08s/it]
                                                           

  1%|          | 4170/569592 [3:31:51<641:29:18,  4.08s/it]
  1%|          | 4171/569592 [3:31:55<639:53:18,  4.07s/it]
                                                           

  1%|          | 4171/569592 [3:31:55<639:53:18,  4.07s/it]
  1%|          | 4172/569592 [3:32:00<684:22:50,  4.36s/it]
                                                           

  1%|          | 4172/569592 [3:32:00<684:22:50,  4.36s/it]
  1%|          | 4173/569592 [3:32:04<692:34:12,  4.41s/it]
                                                           

  1%|          | 4173/569592 [3:32:04<692:34:12,  4.41s/it]
  1%|          | 4174/569592 [3:32:09<700:35:27,  4.46s/it]
                                                           

  1%|          | 4174/569592 [3:32:09<700:35:27,  4.46s/it]
  1%|          | 4175/569592 [3:32:13<668:31:47,  4.26s/it]
                                                           

  1%|          | 4175/569592 [3:32:13<668:31:47,  4.26s/it]
  1%|          | 4176/569592 [3:32:16<609:20:36,  3.88s/it]
                                                           

  1%|          | 4176/569592 [3:32:16<609:20:36,  3.88s/it]
  1%|          | 4177/569592 [3:32:20<611:23:56,  3.89s/it]
                                                           

  1%|          | 4177/569592 [3:32:20<611:23:56,  3.89s/it]
  1%|          | 4178/569592 [3:32:21<470:27:38,  3.00s/it]
                                                           

  1%|          | 4178/569592 [3:32:21<470:27:38,  3.00s/it]
  1%|          | 4179/569592 [3:32:26<572:28:30,  3.64s/it]
                                                           

  1%|          | 4179/569592 [3:32:26<572:28:30,  3.64s/it]
  1%|          | 4180/569592 [3:32:31<626:33:16,  3.99s/it]
                                                           

  1%|          | 4180/569592 [3:32:31<626:33:16,  3.99s/it]
  1%|          | 4181/569592 [3:32:34<617:01:03,  3.93s/it]
                                                           

  1%|          | 4181/569592 [3:32:34<617:01:03,  3.93s/it]
  1%|          | 4182/569592 [3:32:39<636:15:35,  4.05s/it]
                                                           

  1%|          | 4182/569592 [3:32:39<636:15:35,  4.05s/it]
  1%|          | 4183/569592 [3:32:43<660:38:39,  4.21s/it]
                                                           

  1%|          | 4183/569592 [3:32:43<660:38:39,  4.21s/it]
  1%|          | 4184/569592 [3:32:47<643:24:03,  4.10s/it]
                                                           

  1%|          | 4184/569592 [3:32:47<643:24:03,  4.10s/it]
  1%|          | 4185/569592 [3:32:50<612:12:57,  3.90s/it]
                                                           

  1%|          | 4185/569592 [3:32:50<612:12:57,  3.90s/it]
  1%|          | 4186/569592 [3:32:55<651:05:06,  4.15s/it]
                                                           

  1%|          | 4186/569592 [3:32:55<651:05:06,  4.15s/it]
  1%|          | 4187/569592 [3:33:00<674:06:58,  4.29s/it]
                                                           

  1%|          | 4187/569592 [3:33:00<674:06:58,  4.29s/it]
  1%|          | 4188/569592 [3:33:01<513:05:24,  3.27s/it]
                                                           

  1%|          | 4188/569592 [3:33:01<513:05:24,  3.27s/it]
  1%|          | 4189/569592 [3:33:04<509:34:43,  3.24s/it]
                                                           

  1%|          | 4189/569592 [3:33:04<509:34:43,  3.24s/it]
  1%|          | 4190/569592 [3:33:07<500:38:58,  3.19s/it]
                                                           

  1%|          | 4190/569592 [3:33:07<500:38:58,  3.19s/it]
  1%|          | 4191/569592 [3:33:10<499:41:28,  3.18s/it]
                                                           

  1%|          | 4191/569592 [3:33:10<499:41:28,  3.18s/it]
  1%|          | 4192/569592 [3:33:13<499:46:55,  3.18s/it]
                                                           

  1%|          | 4192/569592 [3:33:13<499:46:55,  3.18s/it]
  1%|          | 4193/569592 [3:33:14<393:52:31,  2.51s/it]
                                                           

  1%|          | 4193/569592 [3:33:14<393:52:31,  2.51s/it]
  1%|          | 4194/569592 [3:33:18<438:57:52,  2.79s/it]
                                                           

  1%|          | 4194/569592 [3:33:18<438:57:52,  2.79s/it]
  1%|          | 4195/569592 [3:33:23<550:45:49,  3.51s/it]
                                                           

  1%|          | 4195/569592 [3:33:23<550:45:49,  3.51s/it]
  1%|          | 4196/569592 [3:33:28<607:33:29,  3.87s/it]
                                                           

  1%|          | 4196/569592 [3:33:28<607:33:29,  3.87s/it]
  1%|          | 4197/569592 [3:33:31<568:50:45,  3.62s/it]
                                                           

  1%|          | 4197/569592 [3:33:31<568:50:45,  3.62s/it]
  1%|          | 4198/569592 [3:33:34<545:29:38,  3.47s/it]
                                                           

  1%|          | 4198/569592 [3:33:34<545:29:38,  3.47s/it]
  1%|          | 4199/569592 [3:33:35<424:21:43,  2.70s/it]
                                                           

  1%|          | 4199/569592 [3:33:35<424:21:43,  2.70s/it]
  1%|          | 4200/569592 [3:33:38<452:02:41,  2.88s/it]
                                                           

  1%|          | 4200/569592 [3:33:38<452:02:41,  2.88s/it]
  1%|          | 4201/569592 [3:33:42<504:07:31,  3.21s/it]
                                                           

  1%|          | 4201/569592 [3:33:42<504:07:31,  3.21s/it]
  1%|          | 4202/569592 [3:33:43<399:15:06,  2.54s/it]
                                                           

  1%|          | 4202/569592 [3:33:43<399:15:06,  2.54s/it]
  1%|          | 4203/569592 [3:33:48<534:11:33,  3.40s/it]
                                                           

  1%|          | 4203/569592 [3:33:48<534:11:33,  3.40s/it]
  1%|          | 4204/569592 [3:33:49<427:31:53,  2.72s/it]
                                                           

  1%|          | 4204/569592 [3:33:49<427:31:53,  2.72s/it]
  1%|          | 4205/569592 [3:33:50<347:38:57,  2.21s/it]
                                                           

  1%|          | 4205/569592 [3:33:51<347:38:57,  2.21s/it]
  1%|          | 4206/569592 [3:33:51<289:06:44,  1.84s/it]
                                                           

  1%|          | 4206/569592 [3:33:51<289:06:44,  1.84s/it]
  1%|          | 4207/569592 [3:33:53<253:04:47,  1.61s/it]
                                                           

  1%|          | 4207/569592 [3:33:53<253:04:47,  1.61s/it]
  1%|          | 4208/569592 [3:33:53<221:01:04,  1.41s/it]
                                                           

  1%|          | 4208/569592 [3:33:53<221:01:04,  1.41s/it]
  1%|          | 4209/569592 [3:33:54<200:36:18,  1.28s/it]
                                                           

  1%|          | 4209/569592 [3:33:54<200:36:18,  1.28s/it]
  1%|          | 4210/569592 [3:33:55<184:25:47,  1.17s/it]
                                                           

  1%|          | 4210/569592 [3:33:55<184:25:47,  1.17s/it]
  1%|          | 4211/569592 [3:33:59<309:09:05,  1.97s/it]
                                                           

  1%|          | 4211/569592 [3:33:59<309:09:05,  1.97s/it]
  1%|          | 4212/569592 [3:34:02<355:22:16,  2.26s/it]
                                                           

  1%|          | 4212/569592 [3:34:02<355:22:16,  2.26s/it]
  1%|          | 4213/569592 [3:34:04<318:51:09,  2.03s/it]
                                                           

  1%|          | 4213/569592 [3:34:04<318:51:09,  2.03s/it]
  1%|          | 4214/569592 [3:34:05<307:57:04,  1.96s/it]
                                                           

  1%|          | 4214/569592 [3:34:05<307:57:04,  1.96s/it]
  1%|          | 4215/569592 [3:34:07<307:14:24,  1.96s/it]
                                                           

  1%|          | 4215/569592 [3:34:07<307:14:24,  1.96s/it]
  1%|          | 4216/569592 [3:34:12<436:04:41,  2.78s/it]
                                                           

  1%|          | 4216/569592 [3:34:12<436:04:41,  2.78s/it]
  1%|          | 4217/569592 [3:34:15<422:16:28,  2.69s/it]
                                                           

  1%|          | 4217/569592 [3:34:15<422:16:28,  2.69s/it]
  1%|          | 4218/569592 [3:34:16<351:04:09,  2.24s/it]
                                                           

  1%|          | 4218/569592 [3:34:16<351:04:09,  2.24s/it]
  1%|          | 4219/569592 [3:34:17<315:44:38,  2.01s/it]
                                                           

  1%|          | 4219/569592 [3:34:17<315:44:38,  2.01s/it]
  1%|          | 4220/569592 [3:34:24<517:45:55,  3.30s/it]
                                                           

  1%|          | 4220/569592 [3:34:24<517:45:55,  3.30s/it]
  1%|          | 4221/569592 [3:34:25<411:53:50,  2.62s/it]
                                                           

  1%|          | 4221/569592 [3:34:25<411:53:50,  2.62s/it]
  1%|          | 4222/569592 [3:34:26<359:04:08,  2.29s/it]
                                                           

  1%|          | 4222/569592 [3:34:26<359:04:08,  2.29s/it]
  1%|          | 4223/569592 [3:34:27<310:23:08,  1.98s/it]
                                                           

  1%|          | 4223/569592 [3:34:27<310:23:08,  1.98s/it]
  1%|          | 4224/569592 [3:34:32<451:01:06,  2.87s/it]
                                                           

  1%|          | 4224/569592 [3:34:32<451:01:06,  2.87s/it]
  1%|          | 4225/569592 [3:34:33<366:06:52,  2.33s/it]
                                                           

  1%|          | 4225/569592 [3:34:33<366:06:52,  2.33s/it]
  1%|          | 4226/569592 [3:34:36<400:01:06,  2.55s/it]
                                                           

  1%|          | 4226/569592 [3:34:36<400:01:06,  2.55s/it]
  1%|          | 4227/569592 [3:34:37<328:53:28,  2.09s/it]
                                                           

  1%|          | 4227/569592 [3:34:37<328:53:28,  2.09s/it]
  1%|          | 4228/569592 [3:34:43<500:32:03,  3.19s/it]
                                                           

  1%|          | 4228/569592 [3:34:43<500:32:03,  3.19s/it]
  1%|          | 4229/569592 [3:34:44<396:38:22,  2.53s/it]
                                                           

  1%|          | 4229/569592 [3:34:44<396:38:22,  2.53s/it]
  1%|          | 4230/569592 [3:34:47<400:21:02,  2.55s/it]
                                                           

  1%|          | 4230/569592 [3:34:47<400:21:02,  2.55s/it]
  1%|          | 4231/569592 [3:34:48<329:36:33,  2.10s/it]
                                                           

  1%|          | 4231/569592 [3:34:48<329:36:33,  2.10s/it]
  1%|          | 4232/569592 [3:34:54<527:42:53,  3.36s/it]
                                                           

  1%|          | 4232/569592 [3:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
34:54<527:42:53,  3.36s/it]
  1%|          | 4233/569592 [3:34:55<413:47:41,  2.63s/it]
                                                           

  1%|          | 4233/569592 [3:34:55<413:47:41,  2.63s/it]
  1%|          | 4234/569592 [3:34:57<366:03:47,  2.33s/it]
                                                           

  1%|          | 4234/569592 [3:34:57<366:03:47,  2.33s/it]
  1%|          | 4235/569592 [3:35:00<435:59:58,  2.78s/it]
                                                           

  1%|          | 4235/569592 [3:35:01<435:59:58,  2.78s/it]
  1%|          | 4236/569592 [3:35:04<471:59:36,  3.01s/it]
                                                           

  1%|          | 4236/569592 [3:35:04<471:59:36,  3.01s/it]
  1%|          | 4237/569592 [3:35:07<491:14:27,  3.13s/it]
                                                           

  1%|          | 4237/569592 [3:35:07<491:14:27,  3.13s/it]
  1%|          | 4238/569592 [3:35:09<401:11:35,  2.55s/it]
                                                           

  1%|          | 4238/569592 [3:35:09<401:11:35,  2.55s/it]
  1%|          | 4239/569592 [3:35:10<325:26:26,  2.07s/it]
                                                           

  1%|          | 4239/569592 [3:35:10<325:26:26,  2.07s/it]
  1%|          | 4240/569592 [3:35:13<406:54:43,  2.59s/it]
                                                           

  1%|          | 4240/569592 [3:35:13<406:54:43,  2.59s/it]
  1%|          | 4241/569592 [3:35:18<523:06:47,  3.33s/it]
                                                           

  1%|          | 4241/569592 [3:35:18<523:06:47,  3.33s/it]
  1%|          | 4242/569592 [3:35:19<411:36:01,  2.62s/it]
                                                           

  1%|          | 4242/569592 [3:35:19<411:36:01,  2.62s/it]
  1%|          | 4243/569592 [3:35:20<332:50:40,  2.12s/it]
                                                           

  1%|          | 4243/569592 [3:35:20<332:50:40,  2.12s/it]
  1%|          | 4244/569592 [3:35:25<460:01:29,  2.93s/it]
                                                           

  1%|          | 4244/569592 [3:35:25<460:01:29,  2.93s/it]
  1%|          | 4245/569592 [3:35:26<368:51:38,  2.35s/it]
                                                           

  1%|          | 4245/569592 [3:35:26<368:51:38,  2.35s/it]
  1%|          | 4246/569592 [3:35:30<419:15:07,  2.67s/it]
                                                           

  1%|          | 4246/569592 [3:35:30<419:15:07,  2.67s/it]
  1%|          | 4247/569592 [3:35:31<339:02:41,  2.16s/it]
                                                           

  1%|          | 4247/569592 [3:35:31<339:02:41,  2.16s/it]
  1%|          | 4248/569592 [3:35:34<401:43:21,  2.56s/it]
                                                           

  1%|          | 4248/569592 [3:35:34<401:43:21,  2.56s/it]
  1%|          | 4249/569592 [3:35:39<520:08:28,  3.31s/it]
                                                           

  1%|          | 4249/569592 [3:35:39<520:08:28,  3.31s/it]
  1%|          | 4250/569592 [3:35:44<589:46:59,  3.76s/it]
                                                           

  1%|          | 4250/569592 [3:35:44<589:46:59,  3.76s/it]
  1%|          | 4251/569592 [3:35:45<454:45:08,  2.90s/it]
                                                           

  1%|          | 4251/569592 [3:35:45<454:45:08,  2.90s/it]
  1%|          | 4252/569592 [3:35:49<516:21:51,  3.29s/it]
                                                           

  1%|          | 4252/569592 [3:35:49<516:21:51,  3.29s/it]
  1%|          | 4253/569592 [3:35:53<527:35:34,  3.36s/it]
                                                           

  1%|          | 4253/569592 [3:35:53<527:35:34,  3.36s/it]
  1%|          | 4254/569592 [3:35:56<528:53:47,  3.37s/it]
                                                           

  1%|          | 4254/569592 [3:35:56<528:53:47,  3.37s/it]
  1%|          | 4255/569592 [3:36:01<590:00:17,  3.76s/it]
                                                           

  1%|          | 4255/569592 [3:36:01<590:00:17,  3.76s/it]
  1%|          | 4256/569592 [3:36:02<456:25:06,  2.91s/it]
                                                           

  1%|          | 4256/569592 [3:36:02<456:25:06,  2.91s/it]
  1%|          | 4257/569592 [3:36:02<362:38:14,  2.31s/it]
                                                           

  1%|          | 4257/569592 [3:36:02<362:38:14,  2.31s/it]
  1%|          | 4258/569592 [3:36:06<409:31:11,  2.61s/it]
                                                           

  1%|          | 4258/569592 [3:36:06<409:31:11,  2.61s/it]
  1%|          | 4259/569592 [3:36:07<331:56:57,  2.11s/it]
                                                           

  1%|          | 4259/569592 [3:36:07<331:56:57,  2.11s/it]
  1%|          | 4260/569592 [3:36:08<276:54:59,  1.76s/it]
                                                           

  1%|          | 4260/569592 [3:36:08<276:54:59,  1.76s/it]
  1%|          | 4261/56/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92779500 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
9592 [3:36:09<238:09:14,  1.52s/it]
                                                           

  1%|          | 4261/569592 [3:36:09<238:09:14,  1.52s/it]
  1%|          | 4262/569592 [3:36:12<346:44:28,  2.21s/it]
                                                           

  1%|          | 4262/569592 [3:36:12<346:44:28,  2.21s/it]
  1%|          | 4263/569592 [3:36:16<401:28:37,  2.56s/it]
                                                           

  1%|          | 4263/569592 [3:36:16<401:28:37,  2.56s/it]
  1%|          | 4264/569592 [3:36:19<443:26:16,  2.82s/it]
                                                           

  1%|          | 4264/569592 [3:36:19<443:26:16,  2.82s/it]
  1%|          | 4265/569592 [3:36:23<473:03:04,  3.01s/it]
                                                           

  1%|          | 4265/569592 [3:36:23<473:03:04,  3.01s/it]
  1%|          | 4266/569592 [3:36:27<512:35:27,  3.26s/it]
                                                           

  1%|          | 4266/569592 [3:36:27<512:35:27,  3.26s/it]
  1%|          | 4267/569592 [3:36:30<509:47:08,  3.25s/it]
                                                           

  1%|          | 4267/569592 [3:36:30<509:47:08,  3.25s/it]
  1%|          | 4268/569592 [3:36:31<402:03:00,  2.56s/it]
                                                           

  1%|          | 4268/569592 [3:36:31<402:03:00,  2.56s/it]
  1%|          | 4269/569592 [3:36:34<447:13:09,  2.85s/it]
                                                           

  1%|          | 4269/569592 [3:36:34<447:13:09,  2.85s/it]
  1%|          | 4270/569592 [3:36:38<495:43:37,  3.16s/it]
                                                           

  1%|          | 4270/569592 [3:36:38<495:43:37,  3.16s/it]
  1%|          | 4271/569592 [3:36:39<392:31:42,  2.50s/it]
                                                           

  1%|          | 4271/569592 [3:36:39<392:31:42,  2.50s/it]
  1%|          | 4272/569592 [3:36:40<320:08:14,  2.04s/it]
                                                           

  1%|          | 4272/569592 [3:36:40<320:08:14,  2.04s/it]
  1%|          | 4273/569592 [3:36:43<382:43:25,  2.44s/it]
                                                           

  1%|          | 4273/569592 [3:36:43<382:43:25,  2.44s/it]
  1%|          | 4274/569592 [3:36:47<425:25:09,  2.71s/it]
                                                           

  1%|          | 4274/569592 [3:36:47<425:25:09,  2.71s/it]
  1%|          | 4275/569592 [3:36:51<476:34:03,  3.03s/it]
                                                           

  1%|          | 4275/569592 [3:36:51<476:34:03,  3.03s/it]
  1%|          | 4276/569592 [3:36:54<511:06:22,  3.25s/it]
                                                           

  1%|          | 4276/569592 [3:36:54<511:06:22,  3.25s/it]
  1%|          | 4277/569592 [3:36:58<521:28:53,  3.32s/it]
                                                           

  1%|          | 4277/569592 [3:36:58<521:28:53,  3.32s/it]
  1%|          | 4278/569592 [3:37:01<507:39:06,  3.23s/it]
                                                           

  1%|          | 4278/569592 [3:37:01<507:39:06,  3.23s/it]
  1%|          | 4279/569592 [3:37:06<598:24:13,  3.81s/it]
                                                           

  1%|          | 4279/569592 [3:37:06<598:24:13,  3.81s/it]
  1%|          | 4280/569592 [3:37:11<632:45:47,  4.03s/it]
                                                           

  1%|          | 4280/569592 [3:37:11<632:45:47,  4.03s/it]
  1%|          | 4281/569592 [3:37:14<587:55:39,  3.74s/it]
                                                           

  1%|          | 4281/569592 [3:37:14<587:55:39,  3.74s/it]
  1%|          | 4282/569592 [3:37:14<454:45:52,  2.90s/it]
                                                           

  1%|          | 4282/569592 [3:37:15<454:45:52,  2.90s/it]
  1%|          | 4283/569592 [3:37:18<504:27:44,  3.21s/it]
                                                           

  1%|          | 4283/569592 [3:37:18<504:27:44,  3.21s/it]
  1%|          | 4284/569592 [3:37:22<514:33:29,  3.28s/it]
                                                           

  1%|          | 4284/569592 [3:37:22<514:33:29,  3.28s/it]
  1%|          | 4285/569592 [3:37:26<547:45:32,  3.49s/it]
                                                           

  1%|          | 4285/569592 [3:37:26<547:45:32,  3.49s/it]
  1%|          | 4286/569592 [3:37:30<599:34:53,  3.82s/it]
                                                           

  1%|          | 4286/569592 [3:37:30<599:34:53,  3.82s/it]
  1%|          | 4287/569592 [3:37:35<655:24:53,  4.17s/it]
                                                           

  1%|          | 4287/569592 [3:37:35<655:24:53,  4.17s/it]
  1%|          | 4288/569592 [3:37:40<651:33:16,  4.15s/it]
                                                           

  1%|          | 4288/569592 [3:37:40<651:33:16,  4.15s/it]
  1%|          | 4289/569592 [3:37:42<593:54:43,  3.78s/it]
                                                           

  1%|          | 4289/569592 [3:37:42<593:54:43,  3.78s/it]
  1%|          | 4290/569592 [3:37:47<635:38:19,  4.05s/it]
                                                           

  1%|          | 4290/569592 [3:37:47<635:38:19,  4.05s/it]
  1%|          | 4291/569592 [3:37:51<626:31:33,  3.99s/it]
                                                           

  1%|          | 4291/569592 [3:37:51<626:31:33,  3.99s/it]
  1%|          | 4292/569592 [3:37:56<657:27:31,  4.19s/it]
                                                           

  1%|          | 4292/569592 [3:37:56<657:27:31,  4.19s/it]
  1%|          | 4293/569592 [3:37:59<639:41:45,  4.07s/it]
                                                           

  1%|          | 4293/569592 [3:37:59<639:41:45,  4.07s/it]
  1%|          | 4294/569592 [3:38:03<599:32:31,  3.82s/it]
                                                           

  1%|          | 4294/569592 [3:38:03<599:32:31,  3.82s/it]
  1%|          | 4295/569592 [3:38:04<462:43:45,  2.95s/it]
                                                           

  1%|          | 4295/569592 [3:38:04<462:43:45,  2.95s/it]
  1%|          | 4296/569592 [3:38:07<486:06:17,  3.10s/it]
                                                           

  1%|          | 4296/569592 [3:38:07<486:06:17,  3.10s/it]
  1%|          | 4297/569592 [3:38:11<529:16:32,  3.37s/it]
                                                           

  1%|          | 4297/569592 [3:38:11<529:16:32,  3.37s/it]
  1%|          | 4298/569592 [3:38:16<596:34:47,  3.80s/it]
                                                           

  1%|          | 4298/569592 [3:38:16<596:34:47,  3.80s/it]
  1%|          | 4299/569592 [3:38:19<573:07:16,  3.65s/it]
                                                           

  1%|          | 4299/569592 [3:38:19<573:07:16,  3.65s/it]
  1%|          | 4300/569592 [3:38:23<573:03:34,  3.65s/it]
                                                           

  1%|          | 4300/569592 [3:38:23<573:03:34,  3.65s/it]
  1%|          | 4301/569592 [3:38:27<616:18:18,  3.92s/it]
                                                           

  1%|          | 4301/569592 [3:38:27<616:18:18,  3.92s/it]
  1%|          | 4302/569592 [3:38:34<749:59:00,  4.78s/it]
                                                           

  1%|          | 4302/569592 [3:38:34<749:59:00,  4.78s/it]
  1%|          | 4303/569592 [3:38:39<737:50:29,  4.70s/it]
                                                           

  1%|          | 4303/569592 [3:38:39<737:50:29,  4.70s/it]
  1%|          | 4304/569592 [3:38:44<750:46:10,  4.78s/it]
                                                           

  1%|          | 4304/569592 [3:38:44<750:46:10,  4.78s/it]
  1%|          | 4305/569592 [3:38:47<664:47:40,  4.23s/it]
                                                           

  1%|          | 4305/569592 [3:38:47<664:47:40,  4.23s/it]
  1%|          | 4306/569592 [3:38:47<507:33:33,  3.23s/it]
                                                           

  1%|          | 4306/569592 [3:38:47<507:33:33,  3.23s/it]
  1%|          | 4307/569592 [3:38:51<515:48:53,  3.28s/it]
                                                           

  1%|          | 4307/569592 [3:38:51<515:48:53,  3.28s/it]
  1%|          | 4308/569592 [3:38:52<407:38:37,  2.60s/it]
                                                           

  1%|          | 4308/569592 [3:38:52<407:38:37,  2.60s/it]
  1%|          | 4309/569592 [3:38:55<437:55:22,  2.79s/it]
                                                           

  1%|          | 4309/569592 [3:38:55<437:55:22,  2.79s/it]
  1%|          | 4310/569592 [3:38:59<471:22:38,  3.00s/it]
                                                           

  1%|          | 4310/569592 [3:38:59<471:22:38,  3.00s/it]
  1%|          | 4311/569592 [3:39:02<483:05:31,  3.08s/it]
                                                           

  1%|          | 4311/569592 [3:39:02<483:05:31,  3.08s/it]
  1%|          | 4312/569592 [3:39:05<498:22:56,  3.17s/it]
                                                           

  1%|          | 4312/569592 [3:39:05<498:22:56,  3.17s/it]
  1%|          | 4313/569592 [3:39:10<578:25:54,  3.68s/it]
                                                           

  1%|          | 4313/569592 [3:39:10<578:25:54,  3.68s/it]
  1%|          | 4314/569592 [3:39:14<580:53:36,  3.70s/it]
                                                           

  1%|          | 4314/569592 [3:39:14<580:53:36,  3.70s/it]
  1%|          | 4315/569592 [3:39:19<629:31:48,  4.01s/it]
                                                           

  1%|          | 4315/569592 [3:39:19<629:31:48,  4.01s/it]
  1%|          | 4316/569592 [3:39:22<584:16:29,  3.72s/it]
                                                           

  1%|          | 4316/569592 [3:39:22<584:16:29,  3.72s/it]
  1%|          | 4317/569592 [3:39:23<451:41:11,  2.88s/it]
                                                           

  1%|          | 4317/569592 [3:39:23<451:41:11,  2.88s/it]
  1%|          | 4318/569592 [3:39:23<361:00:33,  2.30s/it]
                                                           

  1%|          | 4318/569592 [3:39:24<361:00:33,  2.30s/it]
  1%|          | 4319/569592 [3:39:27<411:51:51,  2.62s/it]
                                                           

  1%|          | 4319/569592 [3:39:27<411:51:51,  2.62s/it]
  1%|          | 4320/569592 [3:39:28<337:10:50,  2.15s/it]
                                                           

  1%|          | 4320/569592 [3:39:28<337:10:50,  2.15s/it]
  1%|          | 4321/569592 [3:39:29<293:03:36,  1.87s/it]
                                                           

  1%|          | 4321/569592 [3:39:29<293:03:36,  1.87s/it]
  1%|          | 4322/569592 [3:39:30<251:34:07,  1.60s/it]
                                                           

  1%|          | 4322/569592 [3:39:30<251:34:07,  1.60s/it]
  1%|          | 4323/569592 [3:39:31<220:07:05,  1.40s/it]
                                                           

  1%|          | 4323/569592 [3:39:31<220:07:05,  1.40s/it]
  1%|          | 4324/569592 [3:39:35<322:10:32,  2.05s/it]
                                                           

  1%|          | 4324/569592 [3:39:35<322:10:32,  2.05s/it]
  1%|          | 4325/569592 [3:39:36<287:04:05,  1.83s/it]
                                                           

  1%|          | 4325/569592 [3:39:36<287:04:05,  1.83s/it]
  1%|          | 4326/569592 [3:39:37<245:19:28,  1.56s/it]
                                                           

  1%|          | 4326/569592 [3:39:37<245:19:28,  1.56s/it]
  1%|          | 4327/569592 [3:39:38<215:51:59,  1.37s/it]
                                                           

  1%|          | 4327/569592 [3:39:38<215:51:59,  1.37s/it]
  1%|          | 4328/569592 [3:39:42<347:42:50,  2.21s/it]
                                                           

  1%|          | 4328/569592 [3:39:42<347:42:50,  2.21s/it]
  1%|          | 4329/569592 [3:39:46<448:24:25,  2.86s/it]
                                                           

  1%|          | 4329/569592 [3:39:46<448:24:25,  2.86s/it]
  1%|          | 4330/569592 [3:39:47<359:44:11,  2.29s/it]
                                                           

  1%|          | 4330/569592 [3:39:47<359:44:11,  2.29s/it]
  1%|          | 4331/569592 [3:39:48<295:26:16,  1.88s/it]
                                                           

  1%|          | 4331/569592 [3:39:48<295:26:16,  1.88s/it]
  1%|          | 4332/569592 [3:39:52<386:51:12,  2.46s/it]
                                                           

  1%|          | 4332/569592 [3:39:52<386:51:12,  2.46s/it]
  1%|          | 4333/569592 [3:39:56<438:00:23,  2.79s/it]
                                                           

  1%|          | 4333/569592 [3:39:56<438:00:23,  2.79s/it]
  1%|          | 4334/569592 [3:39:57<373:00:58,  2.38s/it]
                                                           

  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
1%|          | 4334/569592 [3:39:57<373:00:58,  2.38s/it]
  1%|          | 4335/569592 [3:39:58<304:54:52,  1.94s/it]
                                                           

  1%|          | 4335/569592 [3:39:58<304:54:52,  1.94s/it]
  1%|          | 4336/569592 [3:40:03<448:01:09,  2.85s/it]
                                                           

  1%|          | 4336/569592 [3:40:03<448:01:09,  2.85s/it]
  1%|          | 4337/569592 [3:40:06<474:31:05,  3.02s/it]
                                                           

  1%|          | 4337/569592 [3:40:06<474:31:05,  3.02s/it]
  1%|          | 4338/569592 [3:40:07<375:49:27,  2.39s/it]
                                                           

  1%|          | 4338/569592 [3:40:07<375:49:27,  2.39s/it]
  1%|          | 4339/569592 [3:40:08<312:09:10,  1.99s/it]
                                                           

  1%|          | 4339/569592 [3:40:08<312:09:10,  1.99s/it]
  1%|          | 4340/569592 [3:40:14<478:20:42,  3.05s/it]
                                                           

  1%|          | 4340/569592 [3:40:14<478:20:42,  3.05s/it]
  1%|          | 4341/569592 [3:40:16<454:33:13,  2.89s/it]
                                                           

  1%|          | 4341/569592 [3:40:16<454:33:13,  2.89s/it]
  1%|          | 4342/569592 [3:40:17<367:59:48,  2.34s/it]
                                                           

  1%|          | 4342/569592 [3:40:17<367:59:48,  2.34s/it]
  1%|          | 4343/569592 [3:40:18<303:37:21,  1.93s/it]
                                                           

  1%|          | 4343/569592 [3:40:18<303:37:21,  1.93s/it]
  1%|          | 4344/569592 [3:40:22<382:35:05,  2.44s/it]
                                                           

  1%|          | 4344/569592 [3:40:22<382:35:05,  2.44s/it]
  1%|          | 4345/569592 [3:40:26<476:57:11,  3.04s/it]
                                                           

  1%|          | 4345/569592 [3:40:26<476:57:11,  3.04s/it]
  1%|          | 4346/569592 [3:40:28<397:01:43,  2.53s/it]
                                                           

  1%|          | 4346/569592 [3:40:28<397:01:43,  2.53s/it]
  1%|          | 4347/569592 [3:40:32<455:30:18,  2.90s/it]
                                                           

  1%|          | 4347/569592 [3:40:32<455:30:18,  2.90s/it]
  1%|          | 4348/569592 [3:40:33<391:54:50,  2.50s/it]
                                                           

  1%|          | 4348/569592 [3:40:33<391:54:50,  2.50s/it]
  1%|          | 4349/569592 [3:40:37<468:55:19,  2.99s/it]
                                                           

  1%|          | 4349/569592 [3:40:37<468:55:19,  2.99s/it]
  1%|          | 4350/569592 [3:40:38<374:41:33,  2.39s/it]
                                                           

  1%|          | 4350/569592 [3:40:38<374:41:33,  2.39s/it]
  1%|          | 4351/569592 [3:40:40<323:31:55,  2.06s/it]
                                                           

  1%|          | 4351/569592 [3:40:40<323:31:55,  2.06s/it]
  1%|          | 4352/569592 [3:40:43<374:24:46,  2.38s/it]
                                                           

  1%|          | 4352/569592 [3:40:43<374:24:46,  2.38s/it]
  1%|          | 4353/569592 [3:40:48<498:26:47,  3.17s/it]
                                                           

  1%|          | 4353/569592 [3:40:48<498:26:47,  3.17s/it]
  1%|          | 4354/569592 [3:40:51<513:11:26,  3.27s/it]
                                                           

  1%|          | 4354/569592 [3:40:51<513:11:26,  3.27s/it]
  1%|          | 4355/569592 [3:40:52<403:33:09,  2.57s/it]
                                                           

  1%|          | 4355/569592 [3:40:52<403:33:09,  2.57s/it]
  1%|          | 4356/569592 [3:40:53<327:13:31,  2.08s/it]
                                                           

  1%|          | 4356/569592 [3:40:53<327:13:31,  2.08s/it]
  1%|          | 4357/569592 [3:40:58<473:46:48,  3.02s/it]
                                                           

  1%|          | 4357/569592 [3:40:58<473:46:48,  3.02s/it]
  1%|          | 4358/569592 [3:41:00<402:59:48,  2.57s/it]
                                                           

  1%|          | 4358/569592 [3:41:00<402:59:48,  2.57s/it]
  1%|          | 4359/569592 [3:41:05<519:51:24,  3.31s/it]
                                                           

  1%|          | 4359/569592 [3:41:05<519:51:24,  3.31s/it]
  1%|          | 4360/569592 [3:41:06<408:28:08,  2.60s/it]
                                                           

  1%|          | 4360/569592 [3:41:06<408:28:08,  2.60s/it]
  1%|          | 4361/569592 [3:41:07<363:04:21,  2.31s/it]
                                                           

  1%|          | 4361/569592 [3:41:07<363:04:21,  2.31s/it]
  1%|          | 4362/569592 [3:41:12<487:52:45,  3.11s/it]
                                                           

  1%|          | 4362/569592 [3:41:12<487:52:45,  3.11s/it]
  1%|          | 4363/569592 [3:41:18<592:20:49,  3.77s/it]
                                                           

  1%|          | 4363/569592 [3:41:18<592:20:49,  3.77s/it]
  1%|          | 4364/569592 [3:41:19<457:51:23,  2.92s/it]
                                                           

  1%|          | 4364/569592 [3:41:19<457:51:23,  2.92s/it]
  1%|          | 4365/569592 [3:41:20<366:16:09,  2.33s/it]
                                                           

  1%|          | 4365/569592 [3:41:20<366:16:09,  2.33s/it]
  1%|          | 4366/569592 [3:41:23<414:13:23,  2.64s/it]
                                                           

  1%|          | 4366/569592 [3:41:23<414:13:23,  2.64s/it]
  1%|          | 4367/569592 [3:41:28<523:51:01,  3.34s/it]
                                                           

  1%|          | 4367/569592 [3:41:28<523:51:01,  3.34s/it]
  1%|          | 4368/569592 [3:41:29<409:48:05,  2.61s/it]
                                                           

  1%|          | 4368/569592 [3:41:29<409:48:05,  2.61s/it]
  1%|          | 4369/569592 [3:41:30<337:36:10,  2.15s/it]
                                                           

  1%|          | 4369/569592 [3:41:30<337:36:10,  2.15s/it]
  1%|          | 4370/569592 [3:41:34<443:25:29,  2.82s/it]
                                                           

  1%|          | 4370/569592 [3:41:34<443:25:29,  2.82s/it]
  1%|          | 4371/569592 [3:41:39<539:45:40,  3.44s/it]
                                                           

  1%|          | 4371/569592 [3:41:39<539:45:40,  3.44s/it]
  1%|          | 4372/569592 [3:41:40<421:35:28,  2.69s/it]
                                                           

  1%|          | 4372/569592 [3:41:40<421:35:28,  2.69s/it]
  1%|          | 4373/569592 [3:41:43<440:09:50,  2.80s/it]
                                                           

  1%|          | 4373/569592 [3:41:43<440:09:50,  2.80s/it]
  1%|          | 4374/569592 [3:41:44<353:39:04,  2.25s/it]
                                                           

  1%|          | 4374/569592 [3:41:44<353:39:04,  2.25s/it]
  1%|          | 4375/569592 [3:41:49<499:47:01,  3.18s/it]
                                                           

  1%|          | 4375/569592 [3:41:49<499:47:01,  3.18s/it]
  1%|          | 4376/569592 [3:41:53<531:29:21,  3.39s/it]
                                                           

  1%|          | 4376/569592 [3:41:53<531:29:21,  3.39s/it]
  1%|          | 4377/569592 [3:41:57<523:27:59,  3.33s/it]
                                                           

  1%|          | 4377/569592 [3:41:57<523:27:59,  3.33s/it]
  1%|          | 4378/569592 [3:42:01<582:02:40,  3.71s/it]
                                                           

  1%|          | 4378/569592 [3:42:01<582:02:40,  3.71s/it]
  1%|          | 4379/569592 [3:42:04<562:56:31,  3.59s/it]
                                                           

  1%|          | 4379/569592 [3:42:04<562:56:31,  3.59s/it]
  1%|          | 4380/569592 [3:42:09<630:10:10,  4.01s/it]
                                                           

  1%|          | 4380/569592 [3:42:09<630:10:10,  4.01s/it]
  1%|          | 4381/569592 [3:42:10<482:38:46,  3.07s/it]
                                                           

  1%|          | 4381/569592 [3:42:10<482:38:46,  3.07s/it]
  1%|          | 4382/569592 [3:42:14<493:42:09,  3.14s/it]
                                                           

  1%|          | 4382/569592 [3:42:14<493:42:09,  3.14s/it]
  1%|          | 4383/569592 [3:42:15<388:59:50,  2.48s/it]
                                                           

  1%|          | 4383/569592 [3:42:15<388:59:50,  2.48s/it]
  1%|          | 4384/569592 [3:42:16<318:20:46,  2.03s/it]
                                                           

  1%|          | 4384/569592 [3:42:16<318:20:46,  2.03s/it]
  1%|          | 4385/569592 [3:42:17<273:40:39,  1.74s/it]
                                                           

  1%|          | 4385/569592 [3:42:17<273:40:39,  1.74s/it]
  1%|          | 4386/569592 [3:42:20<346:26:21,  2.21s/it]
                                                           

  1%|          | 4386/569592 [3:42:20<346:26:21,  2.21s/it]
  1%|          | 4387/569592 [3:42:21<289:32:25,  1.84s/it]
                                                           

  1%|          | 4387/569592 [3:42:21<289:32:25,  1.84s/it]
  1%|          | 4388/569592 [3:42:26<438:39:52,  2.79s/it]
                                                           

  1%|          | 4388/569592 [3:42:26<438:39:52,  2.79s/it]
  1%|          | 4389/569592 [3:42:31<544:13:37,  3.47s/it]
                                                           

  1%|          | 4389/569592 [3:42:31<544:13:37,  3.47s/it]
  1%|          | 4390/569592 [3:42:36<607:14:00,  3.87s/it]
                                                           

  1%|          | 4390/569592 [3:42:36<607:14:00,  3.87s/it]
  1%|          | 4391/569592 [3:42:39<594:08:03,  3.78s/it]
                                                           

  1%|          | 4391/569592 [3:42:39<594:08:03,  3.78s/it]
  1%|          | 4392/569592 [3:42:44<639:53:07,  4.08s/it]
                                                           

  1%|          | 4392/569592 [3:42:44<639:53:07,  4.08s/it]
  1%|          | 4393/569592 [3:42:47<585:53:44,  3.73s/it]
                                                           

  1%|          | 4393/569592 [3:42:47<585:53:44,  3.73s/it]
  1%|          | 4394/569592 [3:42:52<634:49:06,  4.04s/it]
                                                           

  1%|          | 4394/569592 [3:42:52<634:49:06,  4.04s/it]
  1%|          | 4395/569592 [3:42:55<606:11:37,  3.86s/it]
                                                           

  1%|          | 4395/569592 [3:42:55<606:11:37,  3.86s/it]
  1%|          | 4396/569592 [3:43:00<648:49:24,  4.13s/it]
                                                           

  1%|          | 4396/569592 [3:43:00<648:49:24,  4.13s/it]
  1%|          | 4397/569592 [3:43:05<698:39:23,  4.45s/it]
                                                           

  1%|          | 4397/569592 [3:43:05<698:39:23,  4.45s/it]
  1%|          | 4398/569592 [3:43:06<530:52:45,  3.38s/it]
                                                           

  1%|          | 4398/569592 [3:43:06<530:52:45,  3.38s/it]
  1%|          | 4399/569592 [3:43:09<520:19:49,  3.31s/it]
                                                           

  1%|          | 4399/569592 [3:43:09<520:19:49,  3.31s/it]
  1%|          | 4400/569592 [3:43:14<588:40:55,  3.75s/it]
                                                           

  1%|          | 4400/569592 [3:43:14<588:40:55,  3.75s/it]
  1%|          | 4401/569592 [3:43:17<575:41:11,  3.67s/it]
                                                           

  1%|          | 4401/569592 [3:43:17<575:41:11,  3.67s/it]
  1%|          | 4402/569592 [3:43:22<627:55:03,  4.00s/it]
                                                           

  1%|          | 4402/569592 [3:43:22<627:55:03,  4.00s/it]
  1%|          | 4403/569592 [3:43:27<643:16:42,  4.10s/it]
                                                           

  1%|          | 4403/569592 [3:43:27<643:16:42,  4.10s/it]
  1%|          | 4404/569592 [3:43:31<664:21:10,  4.23s/it]
                                                           

  1%|          | 4404/569592 [3:43:31<664:21:10,  4.23s/it]
  1%|          | 4405/569592 [3:43:36<696:29:04,  4.44s/it]
                                                           

  1%|          | 4405/569592 [3:43:36<696:29:04,  4.44s/it]
  1%|          | 4406/569592 [3:43:41<701:36:30,  4.47s/it]
                                                           

  1%|          | 4406/569592 [3:43:41<701:36:30,  4.47s/it]
  1%|          | 4407/569592 [3:43:45<690:30:17,  4.40s/it]
                                                           

  1%|          | 4407/569592 [3:43:45<690:30:17,  4.40s/it]
  1%|          | 4408/569592 [3:43:48<643:54:56,  4.10s/it]
                                                           

  1%|          | 4408/569592 [3:43:48<643:54:56,  4.10s/it]
  1%|          | 4409/569592 [3:43:53<675:32:08,  4.30s/it]
                                                           

  1%|          | 4409/569592 [3:43:53<675:32:08,  4.30s/it]
  1%|          | 4410/569592 [3:43:57<658:32:41,  4.19s/it]
                                                           

  1%|          | 4410/569592 [3:43:57<658:32:41,  4.19s/it]
  1%|          | 4411/569592 [3:44:01<646:38:09,  4.12s/it]
                                                           

  1%|          | 4411/569592 [3:44:01<646:38:09,  4.12s/it]
  1%|          | 4412/569592 [3:44:06<674:26:11,  4.30s/it]
                                                           

  1%|          | 4412/569592 [3:44:06<674:26:11,  4.30s/it]
  1%|          | 4413/569592 [3:44:09<638:33:29,  4.07s/it]
                                                           

  1%|          | 4413/569592 [3:44:09<638:33:29,  4.07s/it]
  1%|          | 4414/569592 [3:44:12<602:40:47,  3.84s/it]
                                                           

  1%|          | 4414/569592 [3:44:12<602:40:47,  3.84s/it]
  1%|          | 4415/569592 [3:44:16<590:27:14,  3.76s/it]
                                                           

  1%|          | 4415/569592 [3:44:16<590:27:14,  3.76s/it]
  1%|          | 4416/569592 [3:44:17<455:57:03,  2.90s/it]
                                                           

  1%|          | 4416/569592 [3:44:17<455:57:03,  2.90s/it]
  1%|          | 4417/569592 [3:44:22<551:04:11,  3.51s/it]
                                                           

  1%|          | 4417/569592 [3:44:22<551:04:11,  3.51s/it]
  1%|          | 4418/569592 [3:44:25<549:47:00,  3.50s/it]
                                                           

  1%|          | 4418/569592 [3:44:25<549:47:00,  3.50s/it]
  1%|          | 4419/569592 [3:44:30<608:21:17,  3.88s/it]
                                                           

  1%|          | 4419/569592 [3:44:30<608:21:17,  3.88s/it]
  1%|          | 4420/569592 [3:44:34<598:57:27,  3.82s/it]
                                                           

  1%|          | 4420/569592 [3:44:34<598:57:27,  3.82s/it]
  1%|          | 4421/569592 [3:44:37<580:43:30,  3.70s/it]
                                                           

  1%|          | 4421/569592 [3:44:37<580:43:30,  3.70s/it]
  1%|          | 4422/569592 [3:44:42<621:27:04,  3.96s/it]
                                                           

  1%|          | 4422/569592 [3:44:42<621:27:04,  3.96s/it]
  1%|          | 4423/569592 [3:44:46<651:32:19,  4.15s/it]
                                                           

  1%|          | 4423/569592 [3:44:46<651:32:19,  4.15s/it]
  1%|          | 4424/569592 [3:44:51<678:13:38,  4.32s/it]
                                                           

  1%|          | 4424/569592 [3:44:51<678:13:38,  4.32s/it]
  1%|          | 4425/569592 [3:44:52<517:57:08,  3.30s/it]
                                                           

  1%|          | 4425/569592 [3:44:52<517:57:08,  3.30s/it]
  1%|          | 4426/569592 [3:44:55<510:20:14,  3.25s/it]
                                                           

  1%|          | 4426/569592 [3:44:55<510:20:14,  3.25s/it]
  1%|          | 4427/569592 [3:44:59<526:40:08,  3.35s/it]
                                                           

  1%|          | 4427/569592 [3:44:59<526:40:08,  3.35s/it]
  1%|          | 4428/569592 [3:45:03<579:37:01,  3.69s/it]
                                                           

  1%|          | 4428/569592 [3:45:03<579:37:01,  3.69s/it]
  1%|          | 4429/569592 [3:45:06<554:03:40,  3.53s/it]
                                                           

  1%|          | 4429/569592 [3:45:06<554:03:40,  3.53s/it]
  1%|          | 4430/569592 [3:45:10<567:58:01,  3.62s/it]
                                                           

  1%|          | 4430/569592 [3:45:10<567:58:01,  3.62s/it]
  1%|          | 4431/569592 [3:45:13<539:05:21,  3.43s/it]
                                                           

  1%|          | 4431/569592 [3:45:13<539:05:21,  3.43s/it]
  1%|          | 4432/569592 [3:45:14<420:18:39,  2.68s/it]
                                                           

  1%|          | 4432/569592 [3:45:14<420:18:39,  2.68s/it]
  1%|          | 4433/569592 [3:45:17<452:48:43,  2.88s/it]
                                                           

  1%|          | 4433/569592 [3:45:17<452:48:43,  2.88s/it]
  1%|          | 4434/569592 [3:45:18<363:22:30,  2.31s/it]
                                                           

  1%|          | 4434/569592 [3:45:18<363:22:30,  2.31s/it]
  1%|          | 4435/569592 [3:45:22<416:19:56,  2.65s/it]
                                                           

  1%|          | 4435/569592 [3:45:22<416:19:56,  2.65s/it]
  1%|          | 4436/569592 [3:45:23<336:34:03,  2.14s/it]
                                                           

  1%|          | 4436/569592 [3:45:23<336:34:03,  2.14s/it]
  1%|          | 4437/569592 [3:45:27<413:36:54,  2.63s/it]
                                                           

  1%|          | 4437/569592 [3:45:27<413:36:54,  2.63s/it]
  1%|          | 4438/569592 [3:45:28<334:56:56,  2.13s/it]
                                                           

  1%|          | 4438/569592 [3:45:28<334:56:56,  2.13s/it]
  1%|          | 4439/569592 [3:45:29<282:56:57,  1.80s/it]
                                                           

  1%|          | 4439/569592 [3:45:29<282:56:57,  1.80s/it]
  1%|          | 4440/569592 [3:45:30<242:37:30,  1.55s/it]
                                                           

  1%|          | 4440/569592 [3:45:30<242:37:30,  1.55s/it]
  1%|          | 4441/569592 [3:45:30<213:48:56,  1.36s/it]
                                                           

  1%|          | 4441/569592 [3:45:30<213:48:56,  1.36s/it]
  1%|          | 4442/569592 [3:45:31<195:01:05,  1.24s/it]
                                                           

  1%|          | 4442/569592 [3:45:31<195:01:05,  1.24s/it]
  1%|          | 4443/569592 [3:45:33<199:09:56,  1.27s/it]
                                                           

  1%|          | 4443/569592 [3:45:33<199:09:56,  1.27s/it]
  1%|          | 4444/569592 [3:45:37<341:12:38,  2.17s/it]
                                                           

  1%|          | 4444/569592 [3:45:37<341:12:38,  2.17s/it]
  1%|          | 4445/569592 [3:45:38<289:23:37,  1.84s/it]
                                                           

  1%|          | 4445/569592 [3:45:38<289:23:37,  1.84s/it]
  1%|          | 4446/569592 [3:45:41<328:43:30,  2.09s/it]
                                                           

  1%|          | 4446/569592 [3:45:41<328:43:30,  2.09s/it]
  1%|          | 4447/569592 [3:45:43<326:32:07,  2.08s/it]
                                                           

  1%|          | 4447/569592 [3:45:43<326:32:07,  2.08s/it]
  1%|          | 4448/569592 [3:45:48<448:38:57,  2.86s/it]
                                                           

  1%|          | 4448/569592 [3:45:48<448:38:57,  2.86s/it]
  1%|          | 4449/569592 [3:45:49<364:05:42,  2.32s/it]
                                                           

  1%|          | 4449/569592 [3:45:49<364:05:42,  2.32s/it]
  1%|          | 4450/569592 [3:45:52<395:36:00,  2.52s/it]
                                                           

  1%|          | 4450/569592 [3:45:52<395:36:00,  2.52s/it]
  1%|          | 4451/569592 [3:45:53<362:23:22,  2.31s/it]
                                                           

  1%|          | 4451/569592 [3:45:53<362:23:22,  2.31s/it]
  1%|          | 4452/569592 [3:45:57<431:19:17,  2.75s/it]
                                                           

  1%|          | 4452/569592 [3:45:57<431:19:17,  2.75s/it]
  1%|          | 4453/569592 [3:45:59<400:35:40,  2.55s/it]
                                                           

  1%|          | 4453/569592 [3:45:59<400:35:40,  2.55s/it]
  1%|          | 4454/569592 [3:46:02<399:38:09,  2.55s/it]
                                                           

  1%|          | 4454/569592 [3:46:02<399:38:09,  2.55s/it]
  1%|          | 4455/569592 [3:46:05<417:52:25,  2.66s/it]
                                                           

  1%|          | 4455/569592 [3:46:05<417:52:25,  2.66s/it]
  1%|          | 4456/569592 [3:46:07<418:50:40,  2.67s/it]
                                                           

  1%|          | 4456/569592 [3:46:07<418:50:40,  2.67s/it]
  1%|          | 4457/569592 [3:46:09<392:02:18,  2.50s/it]
                                                           

  1%|          | 4457/569592 [3:46:10<392:02:18,  2.50s/it]
  1%|          | 4458/569592 [3:46:12<395:10:02,  2.52s/it]
                                                           

  1%|          | 4458/569592 [3:46:12<395:10:02,  2.52s/it]
  1%|          | 4459/5695/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
92 [3:46:14<347:17:47,  2.21s/it]
                                                           

  1%|          | 4459/569592 [3:46:14<347:17:47,  2.21s/it]
  1%|          | 4460/569592 [3:46:19<516:31:34,  3.29s/it]
                                                           

  1%|          | 4460/569592 [3:46:19<516:31:34,  3.29s/it]
  1%|          | 4461/569592 [3:46:23<513:55:20,  3.27s/it]
                                                           

  1%|          | 4461/569592 [3:46:23<513:55:20,  3.27s/it]
  1%|          | 4462/569592 [3:46:24<404:20:04,  2.58s/it]
                                                           

  1%|          | 4462/569592 [3:46:24<404:20:04,  2.58s/it]
  1%|          | 4463/569592 [3:46:25<328:32:39,  2.09s/it]
                                                           

  1%|          | 4463/569592 [3:46:25<328:32:39,  2.09s/it]
  1%|          | 4464/569592 [3:46:28<415:27:51,  2.65s/it]
                                                           

  1%|          | 4464/569592 [3:46:28<415:27:51,  2.65s/it]
  1%|          | 4465/569592 [3:46:30<345:50:36,  2.20s/it]
                                                           

  1%|          | 4465/569592 [3:46:30<345:50:36,  2.20s/it]
  1%|          | 4466/569592 [3:46:33<418:56:39,  2.67s/it]
                                                           

  1%|          | 4466/569592 [3:46:33<418:56:39,  2.67s/it]
  1%|          | 4467/569592 [3:46:34<337:31:22,  2.15s/it]
                                                           

  1%|          | 4467/569592 [3:46:34<337:31:22,  2.15s/it]
  1%|          | 4468/569592 [3:46:40<483:09:54,  3.08s/it]
                                                           

  1%|          | 4468/569592 [3:46:40<483:09:54,  3.08s/it]
  1%|          | 4469/569592 [3:46:43<494:13:36,  3.15s/it]
                                                           

  1%|          | 4469/569592 [3:46:43<494:13:36,  3.15s/it]
  1%|          | 4470/569592 [3:46:44<404:55:47,  2.58s/it]
                                                           

  1%|          | 4470/569592 [3:46:44<404:55:47,  2.58s/it]
  1%|          | 4471/569592 [3:46:45<329:25:04,  2.10s/it]
                                                           

  1%|          | 4471/569592 [3:46:45<329:25:04,  2.10s/it]
  1%|          | 4472/569592 [3:46:51<514:49:25,  3.28s/it]
                                                           

  1%|          | 4472/569592 [3:46:51<514:49:25,  3.28s/it]
  1%|          | 4473/569592 [3:46:52<405:34:02,  2.58s/it]
                                                           

  1%|          | 4473/569592 [3:46:52<405:34:02,  2.58s/it]
  1%|          | 4474/569592 [3:46:55<410:58:17,  2.62s/it]
                                                           

  1%|          | 4474/569592 [3:46:55<410:58:17,  2.62s/it]
  1%|          | 4475/569592 [3:46:56<333:19:27,  2.12s/it]
                                                           

  1%|          | 4475/569592 [3:46:56<333:19:27,  2.12s/it]
  1%|          | 4476/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/569592 [3:46:58<318:33:01,  2.03s/it]
                                                           

  1%|          | 4476/569592 [3:46:58<318:33:01,  2.03s/it]
  1%|          | 4477/569592 [3:46:59<266:58:33,  1.70s/it]
                                                           

  1%|          | 4477/569592 [3:46:59<266:58:33,  1.70s/it]
  1%|          | 4478/569592 [3:47:05<489:26:19,  3.12s/it]
                                                           

  1%|          | 4478/569592 [3:47:05<489:26:19,  3.12s/it]
  1%|          | 4479/569592 [3:47:08<507:32:27,  3.23s/it]
                                                           

  1%|          | 4479/569592 [3:47:08<507:32:27,  3.23s/it]
  1%|          | 4480/569592 [3:47:12<517:28:44,  3.30s/it]
                                                           

  1%|          | 4480/569592 [3:47:12<517:28:44,  3.30s/it]
  1%|          | 4481/569592 [3:47:13<408:08:37,  2.60s/it]
                                                           

  1%|          | 4481/569592 [3:47:13<408:08:37,  2.60s/it]
  1%|          | 4482/569592 [3:47:15<379:40:47,  2.42s/it]
                                                           

  1%|          | 4482/569592 [3:47:15<379:40:47,  2.42s/it]
  1%|          | 4483/569592 [3:47:16<318:01:15,  2.03s/it]
                                                           

  1%|          | 4483/569592 [3:47:16<318:01:15,  2.03s/it]
  1%|          | 4484/569592 [3:47:21<478:41:42,  3.05s/it]
                                                           

  1%|          | 4484/569592 [3:47:21<478:41:42,  3.05s/it]
  1%|          | 4485/569592 [3:47:25<493:24:59,  3.14s/it]
                                                           

  1%|          | 4485/569592 [3:47:25<493:24:59,  3.14s/it]
  1%|          | 4486/569592 [3:47:26<391:56:41,  2.50s/it]
                                                           

  1%|          | 4486/569592 [3:47:26<391:56:41,  2.50s/it]
  1%|          | 4487/569592 [3:47:31<514:22:29,  3.28s/it]
                                                           

  1%|          | 4487/569592 [3:47:31<514:22:29,  3.28s/it]
  1%|          | 4488/569592 [3:47:34<507:20:47,  3.23s/it]
                                                           

  1%|          | 4488/569592 [3:47:34<507:20:47,  3.23s/it]
  1%|          | 4489/569592 [3:47:37<516:19:18,  3.29s/it]
                                                           

  1%|          | 4489/569592 [3:47:37<516:19:18,  3.29s/it]
  1%|          | 4490/569592 [3:47:38<405:09:36,  2.58s/it]
                                                           

  1%|          | 4490/569592 [3:47:39<405:09:36,  2.58s/it]
  1%|          | 4491/569592 [3:47:43<521:34:02,  3.32s/it]
                                                           

  1%|          | 4491/569592 [3:47:43<521:34:02,  3.32s/it]
  1%|          | 4492/569592 [3:47:48<585:49:52,  3.73s/it]
                                                           

  1%|          | 4492/569592 [3:47:48<585:49:52,  3.73s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  1%|          | 4493/569592 [3:47:51<565:26:31,  3.60s/it]
                                                           

  1%|          | 4493/569592 [3:47:51<565:26:31,  3.60s/it]
  1%|          | 4494/569592 [3:47:52<438:05:18,  2.79s/it]
                                                           

  1%|          | 4494/569592 [3:47:52<438:05:18,  2.79s/it]
  1%|          | 4495/569592 [3:47:57<547:04:27,  3.49s/it]
                                                           

  1%|          | 4495/569592 [3:47:57<547:04:27,  3.49s/it]
  1%|          | 4496/569592 [3:47:58<426:24:35,  2.72s/it]
                                                           

  1%|          | 4496/569592 [3:47:58<426:24:35,  2.72s/it]
  1%|          | 4497/569592 [3:48:02<462:05:51,  2.94s/it]
                                                           

  1%|          | 4497/569592 [3:48:02<462:05:51,  2.94s/it]
  1%|          | 4498/569592 [3:48:03<366:34:49,  2.34s/it]
                                                           

  1%|          | 4498/569592 [3:48:03<366:34:49,  2.34s/it]
  1%|          | 4499/569592 [3:48:06<416:12:37,  2.65s/it]
                                                           

  1%|          | 4499/569592 [3:48:06<416:12:37,  2.65s/it]
  1%|          | 4500/569592 [3:48:10<454:23:35,  2.89s/it]
                                                           

  1%|          | 4500/569592 [3:48:10<454:23:35,  2.89s/it]
  1%|          | 4501/569592 [3:48:13<475:01:44,  3.03s/it]
                                                           

  1%|          | 4501/569592 [3:48:13<475:01:44,  3.03s/it]
  1%|          | 4502/569592 [3:48:16<494:13:46,  3.15s/it]
                                                           

  1%|          | 4502/569592 [3:48:16<494:13:46,  3.15s/it]
  1%|          | 4503/569592 [3:48:20<505:46:26,  3.22s/it]
                                                           

  1%|          | 4503/569592 [3:48:20<505:46:26,  3.22s/it]
  1%|          | 4504/569592 [3:48:23<509:27:04,  3.25s/it]
                                                           

  1%|          | 4504/569592 [3:48:23<509:27:04,  3.25s/it]
  1%|          | 4505/569592 [3:48:27<554:22:23,  3.53s/it]
                                                           

  1%|          | 4505/569592 [3:48:27<554:22:23,  3.53s/it]
  1%|          | 4506/569592 [3:48:30<541:52:04,  3.45s/it]
                                                           

  1%|          | 4506/569592 [3:48:30<541:52:04,  3.45s/it]
  1%|          | 4507/569592 [3:48:34<560:03:55,  3.57s/it]
                                                           

  1%|          | 4507/569592 [3:48:34<560:03:55,  3.57s/it]
  1%|          | 4508/569592 [3:48:38<544:04:41,  3.47s/it]
                                                           

  1%|          | 4508/569592 [3:48:38<544:04:41,  3.47s/it]
  1%|          | 4509/569592 [3:48:42<602:01:35,  3.84s/it]
                                                           

  1%|          | 4509/569592 [3:48:42<602:01:35,  3.84s/it]
  1%|          | 4510/569592 [3:48:47<639:59:36,  4.08s/it]
                                                           

  1%|          | 4510/569592 [3:48:47<639:59:36,  4.08s/it]
  1%|          | 4511/569592 [3:48:51<660:22:57,  4.21s/it]
                                                           

  1%|          | 4511/569592 [3:48:51<660:22:57,  4.21s/it]
  1%|          | 4512/569592 [3:48:54<606:04:06,  3.86s/it]
                                                           

  1%|          | 4512/569592 [3:48:54<606:04:06,  3.86s/it]
  1%|          | 4513/569592 [3:48:58<576:51:59,  3.68s/it]
                                                           

  1%|          | 4513/569592 [3:48:58<576:51:59,  3.68s/it]
  1%|          | 4514/569592 [3:49:03<648:46:18,  4.13s/it]
                                                           

  1%|          | 4514/569592 [3:49:03<648:46:18,  4.13s/it]
  1%|          | 4515/569592 [3:49:07<667:30:35,  4.25s/it]
                                                           

  1%|          | 4515/569592 [3:49:07<667:30:35,  4.25s/it]
  1%|          | 4516/569592 [3:49:08<508:12:00,  3.24s/it]
                                                           

  1%|          | 4516/569592 [3:49:08<508:12:00,  3.24s/it]
  1%|          | 4517/569592 [3:49:12<541:17:14,  3.45s/it]
                                                           

  1%|          | 4517/569592 [3:49:12<541:17:14,  3.45s/it]
  1%|          | 4518/569592 [3:49:16<568:09:10,  3.62s/it]
                                                           

  1%|          | 4518/569592 [3:49:16<568:09:10,  3.62s/it]
  1%|          | 4519/569592 [3:49:20<558:35:04,  3.56s/it]
                                                           

  1%|          | 4519/569592 [3:49:20<558:35:04,  3.56s/it]
  1%|          | 4520/569592 [3:49:24<589:54:38,  3.76s/it]
                                                           

  1%|          | 4520/569592 [3:49:24<589:54:38,  3.76s/it]
  1%|          | 4521/569592 [3:49:29<637:01:04,  4.06s/it]
                                                           

  1%|          | 4521/569592 [3:49:29<637:01:04,  4.06s/it]
  1%|          | 4522/569592 [3:49:32<608:08:08,  3.87s/it]
                                                           

  1%|          | 4522/569592 [3:49:32<608:08:08,  3.87s/it]
  1%|          | 4523/569592 [3:49:35<563:57:49,  3.59s/it]
                                                           

  1%|          | 4523/569592 [3:49:35<563:57:49,  3.59s/it]
  1%|          | 4524/569592 [3:49:40<623:13:31,  3.97s/it]
                                                           

  1%|          | 4524/569592 [3:49:40<623:13:31,  3.97s/it]
  1%|          | 4525/569592 [3:49:45<657:10:23,  4.19s/it]
                                                           

  1%|          | 4525/569592 [3:49:45<657:10:23,  4.19s/it]
  1%|          | 4526/569592 [3:49:48<614:36:46,  3.92s/it]
                                                           

  1%|          | 4526/569592 [3:49:48<614:36:46,  3.92s/it]
  1%|          | 4527/569592 [3:49:49<472:28:15,  3.01s/it]
                                                           

  1%|          | 4527/569592 [3:49:49<472:28:15,  3.01s/it]
  1%|          | 4528/569592 [3:49:53<553:20:30,  3.53s/it]
                                                           

  1%|          | 4528/569592 [3:49:53<553:20:30,  3.53s/it]
  1%|          | 4529/569592 [3:49:58<606:56:31,  3.87s/it]
                                                           

  1%|          | 4529/569592 [3:49:58<606:56:31,  3.87s/it]
  1%|          | 4530/569592 [3:50:01<570:04:40,  3.63s/it]
                                                           

  1%|          | 4530/569592 [3:50:01<570:04:40,  3.63s/it]
  1%|          | 4531/569592 [3:50:04<551:09:34,  3.51s/it]
                                                           

  1%|          | 4531/569592 [3:50:04<551:09:34,  3.51s/it]
  1%|          | 4532/569592 [3:50:10<624:29:14,  3.98s/it]
                                                           

  1%|          | 4532/569592 [3:50:10<624:29:14,  3.98s/it]
  1%|          | 4533/569592 [3:50:10<481:30:25,  3.07s/it]
                                                           

  1%|          | 4533/569592 [3:50:10<481:30:25,  3.07s/it]
  1%|          | 4534/569592 [3:50:14<502:17:46,  3.20s/it]
                                                           

  1%|          | 4534/569592 [3:50:14<502:17:46,  3.20s/it]
  1%|          | 4535/569592 [3:50:17<501:29:32,  3.20s/it]
                                                           

  1%|          | 4535/569592 [3:50:17<501:29:32,  3.20s/it]
  1%|          | 4536/569592 [3:50:20<507:08:36,  3.23s/it]
                                                           

  1%|          | 4536/569592 [3:50:20<507:08:36,  3.23s/it]
  1%|          | 4537/569592 [3:50:24<511:53:47,  3.26s/it]
                                                           

  1%|          | 4537/569592 [3:50:24<511:53:47,  3.26s/it]
  1%|          | 4538/569592 [3:50:27<509:15:12,  3.24s/it]
                                                           

  1%|          | 4538/569592 [3:50:27<509:15:12,  3.24s/it]
  1%|          | 4539/569592 [3:50:31<543:36:11,  3.46s/it]
                                                           

  1%|          | 4539/569592 [3:50:31<543:36:11,  3.46s/it]
  1%|          | 4540/569592 [3:50:36<599:03:48,  3.82s/it]
                                                           

  1%|          | 4540/569592 [3:50:36<599:03:48,  3.82s/it]
  1%|          | 4541/569592 [3:50:40<629:13:11,  4.01s/it]
                                                           

  1%|          | 4541/569592 [3:50:40<629:13:11,  4.01s/it]
  1%|          | 4542/569592 [3:50:41<485:34:47,  3.09s/it]
                                                           

  1%|          | 4542/569592 [3:50:41<485:34:47,  3.09s/it]
  1%|          | 4543/569592 [3:50:44<495:55:11,  3.16s/it]
                                                           

  1%|          | 4543/569592 [3:50:44<495:55:11,  3.16s/it]
  1%|          | 4544/569592 [3:50:45<389:54:47,  2.48s/it]
                                                           

  1%|          | 4544/569592 [3:50:45<389:54:47,  2.48s/it]
  1%|          | 4545/569592 [3:50:50<507:42:06,  3.23s/it]
                                                           

  1%|          | 4545/569592 [3:50:50<507:42:06,  3.23s/it]
  1%|          | 4546/569592 [3:50:51<398:08:51,  2.54s/it]
                                                           

  1%|          | 4546/569592 [3:50:51<398:08:51,  2.54s/it]
  1%|          | 4547/569592 [3:50:54<434:20:14,  2.77s/it]
                                                           

  1%|          | 4547/569592 [3:50:54<434:20:14,  2.77s/it]
  1%|          | 4548/569592 [3:50:55<348:17:32,  2.22s/it]
                                                           

  1%|          | 4548/569592 [3:50:55<348:17:32,  2.22s/it]
  1%|          | 4549/569592 [3:51:01<487:05:36,  3.10s/it]
                                                           

  1%|          | 4549/569592 [3:51:01<487:05:36,  3.10s/it]
  1%|          | 4550/569592 [3:51:01<384:39:05,  2.45s/it]
                                                           

  1%|          | 4550/569592 [3:51:01<384:39:05,  2.45s/it]
  1%|          | 4551/569592 [3:51:02<314:09:34,  2.00s/it]
                                                           

  1%|          | 4551/569592 [3:51:02<314:09:34,  2.00s/it]
  1%|          | 4552/569592 [3:51:03<264:49:35,  1.69s/it]
                                                           

  1%|          | 4552/569592 [3:51:03<264:49:35,  1.69s/it]
  1%|          | 4553/569592 [3:51:04<229:00:47,  1.46s/it]
                                                           

  1%|          | 4553/569592 [3:51:04<229:00:47,  1.46s/it]
  1%|          | 4554/569592 [3:51:05<203:51:07,  1.30s/it]
                                                           

  1%|          | 4554/569592 [3:51:05<203:51:07,  1.30s/it]
  1%|          | 4555/569592 [3:51:06<187:45:10,  1.20s/it]
                                                           

  1%|          | 4555/569592 [3:51:06<187:45:10,  1.20s/it]
  1%|          | 4556/569592 [3:51:08<208:59:51,  1.33s/it]
                                                           

  1%|          | 4556/569592 [3:51:08<208:59:51,  1.33s/it]
  1%|          | 4557/569592 [3:51:09<214:44:15,  1.37s/it]
                                                           

  1%|          | 4557/569592 [3:51:09<214:44:15,  1.37s/it]
  1%|          | 4558/569592 [3:51:14<392:41:13,  2.50s/it]
                                                           

  1%|          | 4558/569592 [3:51:14<392:41:13,  2.50s/it]
  1%|          | 4559/569592 [3:51:15<319:32:38,  2.04s/it]
                                                           

  1%|          | 4559/569592 [3:51:15<319:32:38,  2.04s/it]
  1%|          | 4560/569592 [3:51:18<334:49:17,  2.13s/it]
                                                           

  1%|          | 4560/569592 [3:51:18<334:49:17,  2.13s/it]
  1%|          | 4561/569592 [3:51:19<309:50:33,  1.97s/it]
                                                           

  1%|          | 4561/569592 [3:51:19<309:50:33,  1.97s/it]
  1%|          | 4562/569592 [3:51:25<470:10:51,  3.00s/it]
                                                           

  1%|          | 4562/569592 [3:51:25<470:10:51,  3.00s/it]
  1%|          | 4563/569592 [3:51:26<383:20:10,  2.44s/it]
                                                           

  1%|          | 4563/569592 [3:51:26<383:20:10,  2.44s/it]
  1%|          | 4564/569592 [3:51:28<366:06:15,  2.33s/it]
                                                           

  1%|          | 4564/569592 [3:51:28<366:06:15,  2.33s/it]
  1%|          | 4565/569592 [3:51:29<299:49:13,  1.91s/it]
                                                           

  1%|          | 4565/569592 [3:51:29<299:49:13,  1.91s/it]
  1%|          | 4566/569592 [3:51:35<478:04:04,  3.05s/it]
                                                           

  1%|          | 4566/569592 [3:51:35<478:04:04,  3.05s/it]
  1%|          | 4567/569592 [3:51:36<382:38:04,  2.44s/it]
                                                           

  1%|          | 4567/569592 [3:51:36<382:38:04,  2.44s/it]
  1%|          | 4568/569592 [3:51:39<413:31:38,  2.63s/it]
                                                           

  1%|          | 4568/569592 [3:51:39<413:31:38,  2.63s/it]
  1%|          | 4569/569592 [3:51:40<338:32:34,  2.16s/it]
                                                           

  1%|          | 4569/569592 [3:51:40<338:32:34,  2.16s/it]
  1%|          | 4570/569592 [3:51:45<486:08:59,  3.10s/it]
                                                           

  1%|          | 4570/569592 [3:51:45<486:08:59,  3.10s/it]
  1%|          | 4571/569592 [3:51:46<392:34:25,  2.50s/it]
                                                           

  1%|          | 4571/569592 [3:51:46<392:34:25,  2.50s/it]
  1%|          | 4572/569592 [3:51:49<415:55:53,  2.65s/it]
                                                           

  1%|          | 4572/569592 [3:51:49<415:55:53,  2.65s/it]
  1%|          | 4573/569592 [3:51:53<450:28:49,  2.87s/it]
                                                           

  1%|          | 4573/569592 [3:51:53<450:28:49,  2.87s/it]
  1%|          | 4574/569592 [3:51:56<481:09:26,  3.07s/it]
                                                           

  1%|          | 4574/569592 [3:51:56<481:09:26,  3.07s/it]
  1%|          | 4575/569592 [3:51:57<384:59:08,  2.45s/it]
                                                           

  1%|          | 4575/569592 [3:51:57<384:59:08,  2.45s/it]
  1%|          | 4576/569592 [3:51:59<346:37:20,  2.21s/it]
                                                           

  1%|          | 4576/569592 [3:51:59<346:37:20,  2.21s/it]
  1%|          | 4577/569592 [3:52:00<286:36:50,  1.83s/it]
                                                           

  1%|          | 4577/569592 [3:52:00<286:36:50,  1.83s/it]
  1%|          | 4578/569592 [3:52:06<477:07:41,  3.04s/it]
                                                           

  1%|          | 4578/569592 [3:52:06<477:07:41,  3.04s/it]
  1%|          | 4579/569592 [3:52:07<387:34:10,  2.47s/it]
                                                           

  1%|          | 4579/569592 [3:52:07<387:34:10,  2.47s/it]
  1%|          | 4580/569592 [3:52:10<422:22:07,  2.69s/it]
                                                           

  1%|          | 4580/569592 [3:52:10<422:22:07,  2.69s/it]
  1%|          | 4581/569592 [3:52:13<453:30:44,  2.89s/it]
                                                           

  1%|          | 4581/569592 [3:52:13<453:30:44,  2.89s/it]
  1%|          | 4582/569592 [3:52:15<418:34:36,  2.67s/it]
                                                           

  1%|          | 4582/569592 [3:52:15<418:34:36,  2.67s/it]
  1%|          | 4583/569592 [3:52:16<341:37:09,  2.18s/it]
                                                           

  1%|          | 4583/569592 [3:52:16<341:37:09,  2.18s/it]
  1%|          | 4584/569592 [3:52:20<409:08:48,  2.61s/it]
                                                           

  1%|          | 4584/569592 [3:52:20<409:08:48,  2.61s/it]
  1%|          | 4585/569592 [3:52:21<332:58:32,  2.12s/it]
                                                           

  1%|          | 4585/569592 [3:52:21<332:58:32,  2.12s/it]
  1%|          | 4586/569592 [3:52:26<445:36:21,  2.84s/it]
                                                           

  1%|          | 4586/569592 [3:52:26<445:36:21,  2.84s/it]
  1%|          | 4587/569592 [3:52:29<466:15:45,  2.97s/it]
                                                           

  1%|          | 4587/569592 [3:52:29<466:15:45,  2.97s/it]
  1%|          | 4588/569592 [3:52:30<393:08:01,  2.50s/it]
                                                           

  1%|          | 4588/569592 [3:52:30<393:08:01,  2.50s/it]
  1%|          | 4589/569592 [3/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91391881 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:52:34<468:19:57,  2.98s/it]
                                                           

  1%|          | 4589/569592 [3:52:34<468:19:57,  2.98s/it]
  1%|          | 4590/569592 [3:52:36<397:12:03,  2.53s/it]
                                                           

  1%|          | 4590/569592 [3:52:36<397:12:03,  2.53s/it]
  1%|          | 4591/569592 [3:52:37<327:48:27,  2.09s/it]
                                                           

  1%|          | 4591/569592 [3:52:37<327:48:27,  2.09s/it]
  1%|          | 4592/569592 [3:52:40<388:27:30,  2.48s/it]
                                                           

  1%|          | 4592/569592 [3:52:40<388:27:30,  2.48s/it]
  1%|          | 4593/569592 [3:52:41<321:17:18,  2.05s/it]
                                                           

  1%|          | 4593/569592 [3:52:41<321:17:18,  2.05s/it]
  1%|          | 4594/569592 [3:52:46<464:57:20,  2.96s/it]
                                                           

  1%|          | 4594/569592 [3:52:46<464:57:20,  2.96s/it]
  1%|          | 4595/569592 [3:52:49<439:08:50,  2.80s/it]
                                                           

  1%|          | 4595/569592 [3:52:49<439:08:50,  2.80s/it]
  1%|          | 4596/569592 [3:52:52<461:53:34,  2.94s/it]
                                                           

  1%|          | 4596/569592 [3:52:52<461:53:34,  2.94s/it]
  1%|          | 4597/569592 [3:52:56<486:00:58,  3.10s/it]
                                                           

  1%|          | 4597/569592 [3:52:56<486:00:58,  3.10s/it]
  1%|          | 4598/569592 [3:52:57<388:34:18,  2.48s/it]
                                                           

  1%|          | 4598/569592 [3:52:57<388:34:18,  2.48s/it]
  1%|          | 4599/569592 [3:52:58<320:25:56,  2.04s/it]
                                                           

  1%|          | 4599/569592 [3:52:58<320:25:56,  2.04s/it]
  1%|          | 4600/569592 [3:53:01<389:36:26,  2.48s/it]
                                                           

  1%|          | 4600/569592 [3:53:01<389:36:26,  2.48s/it]
  1%|          | 4601/569592 [3:53:04<427:35:03,  2.72s/it]
                                                           

  1%|          | 4601/569592 [3:53:04<427:35:03,  2.72s/it]
  1%|          | 4602/569592 [3:53:08<457:30:45,  2.92s/it]
                                                           

  1%|          | 4602/569592 [3:53:08<457:30:45,  2.92s/it]
  1%|          | 4603/569592 [3:53:09<366:54:33,  2.34s/it]
                                                           

  1%|          | 4603/569592 [3:53:09<366:54:33,  2.34s/it]
  1%|          | 4604/569592 [3:53:13<444:11:48,  2.83s/it]
                                                           

  1%|          | 4604/569592 [3:53:13<444:11:48,  2.83s/it]
  1%|          | 4605/569592 [3:53:16<476:52:12,  3.04s/it]
                                                           

  1%|          | 4605/569592 [3:53:16<476:52:12,  3.04s/it]
  1%|          | 4606/569592 [3:53:20<496:55:55,  3.17s/it]
                                                           

  1%|          | 4606/569592 [3:53:20<496:55:55,  3.17s/it]
  1%|          | 4607/569592 [3:53:21<394:37:37,  2.51s/it]
                                                           

  1%|          | 4607/569592 [3:53:21<394:37:37,  2.51s/it]
  1%|          | 4608/569592 [3:53:24<434:44:16,  2.77s/it]
                                                           

  1%|          | 4608/569592 [3:53:24<434:44:16,  2.77s/it]
  1%|          | 4609/569592 [3:53:28<497:04:31,  3.17s/it]
                                                           

  1%|          | 4609/569592 [3:53:28<497:04:31,  3.17s/it]
  1%|          | 4610/569592 [3:53:33<573:10:31,  3.65s/it]
                                                           

  1%|          | 4610/569592 [3:53:33<573:10:31,  3.65s/it]
  1%|          | 4611/569592 [3:53:34<443:54:00,  2.83s/it]
                                                           

  1%|          | 4611/56/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
9592 [3:53:34<443:54:00,  2.83s/it]
  1%|          | 4612/569592 [3:53:37<462:46:20,  2.95s/it]
                                                           

  1%|          | 4612/569592 [3:53:37<462:46:20,  2.95s/it]
  1%|          | 4613/569592 [3:53:42<542:56:30,  3.46s/it]
                                                           

  1%|          | 4613/569592 [3:53:42<542:56:30,  3.46s/it]
  1%|          | 4614/569592 [3:53:45<524:47:59,  3.34s/it]
                                                           

  1%|          | 4614/569592 [3:53:45<524:47:59,  3.34s/it]
  1%|          | 4615/569592 [3:53:49<577:55:05,  3.68s/it]
                                                           

  1%|          | 4615/569592 [3:53:49<577:55:05,  3.68s/it]
  1%|          | 4616/569592 [3:53:52<551:13:46,  3.51s/it]
                                                           

  1%|          | 4616/569592 [3:53:52<551:13:46,  3.51s/it]
  1%|          | 4617/569592 [3:53:57<604:43:33,  3.85s/it]
                                                           

  1%|          | 4617/569592 [3:53:57<604:43:33,  3.85s/it]
  1%|          | 4618/569592 [3:54:02<638:44:54,  4.07s/it]
                                                           

  1%|          | 4618/569592 [3:54:02<638:44:54,  4.07s/it]
  1%|          | 4619/569592 [3:54:05<587:46:38,  3.75s/it]
                                                           

  1%|          | 4619/569592 [3:54:05<587:46:38,  3.75s/it]
  1%|          | 4620/569592 [3:54:08<590:19:41,  3.76s/it]
                                                           

  1%|          | 4620/569592 [3:54:08<590:19:41,  3.76s/it]
  1%|          | 4621/569592 [3:54:11<551:38:05,  3.52s/it]
                                                           

  1%|          | 4621/569592 [3:54:11<551:38:05,  3.52s/it]
  1%|          | 4622/569592 [3:54:12<429:36:48,  2.74s/it]
                                                           

  1%|          | 4622/569592 [3:54:12<429:36:48,  2.74s/it]
  1%|          | 4623/569592 [3:54:16<468:31:38,  2.99s/it]
                                                           

  1%|          | 4623/569592 [3:54:16<468:31:38,  2.99s/it]
  1%|          | 4624/569592 [3:54:19<500:27:30,  3.19s/it]
                                                           

  1%|          | 4624/569592 [3:54:19<500:27:30,  3.19s/it]
  1%|          | 4625/569592 [3:54:24<577:23:06,  3.68s/it]
                                                           

  1%|          | 4625/569592 [3:54:24<577:23:06,  3.68s/it]
  1%|          | 4626/569592 [3:54:27<544:02:51,  3.47s/it]
                                                           

  1%|          | 4626/569592 [3:54:27<544:02:51,  3.47s/it]
  1%|          | 4627/569592 [3:54:33<629:33:45,  4.01s/it]
                                                           

  1%|          | 4627/569592 [3:54:33<629:33:45,  4.01s/it]
  1%|          | 4628/569592 [3:54:37<636:31:50,  4.06s/it]
                                                           

  1%|          | 4628/569592 [3:54:37<636:31:50,  4.06s/it]
  1%|          | 4629/569592 [3:54:41<659:07:34,  4.20s/it]
                                                           

  1%|          | 4629/569592 [3:54:41<659:07:34,  4.20s/it]
  1%|          | 4630/569592 [3:54:44<606:49:13,  3.87s/it]
                                                           

  1%|          | 4630/569592 [3:54:44<606:49:13,  3.87s/it]
  1%|          | 4631/569592 [3:54:49<662:54:25,  4.22s/it]
                                                           

  1%|          | 4631/569592 [3:54:49<662:54:25,  4.22s/it]
  1%|          | 4632/569592 [3:54:53<625:59:22,  3.99s/it]
                                                           

  1%|          | 4632/569592 [3:54:53<625:59:22,  3.99s/it]
  1%|          | 4633/569592 [3:54:57<657:50:21,  4.19s/it]
                                                           

  1%|          | 4633/569592 [3:54:58<657:50:21,  4.19s/it]
  1%|          | 4634/569592 [3:55:01<606:08:12,  3.86s/it]
                                                           

  1%|          | 4634/569592 [3:55:01<606:08:12,  3.86s/it]
  1%|          | 4635/569592 [3:55:05<639:50:16,  4.08s/it]
                                                           

  1%|          | 4635/569592 [3:55:05<639:50:16,  4.08s/it]
  1%|          | 4636/569592 [3:55:09<612:16:09,  3.90s/it]
                                                           

  1%|          | 4636/569592 [3:55:09<612:16:09,  3.90s/it]
  1%|          | 4637/569592 [3:55:12<599:05:16,  3.82s/it]
                                                           

  1%|          | 4637/569592 [3:55:12<599:05:16,  3.82s/it]
  1%|          | 4638/569592 [3:55:17<640:04:29,  4.08s/it]
                                                           

  1%|          | 4638/569592 [3:55:17<640:04:29,  4.08s/it]
  1%|          | 4639/569592 [3:55:20<592:31:58,  3.78s/it]
                                                           

  1%|          | 4639/569592 [3:55:20<592:31:58,  3.78s/it]
  1%|          | 4640/569592 [3:55:24<618:06:45,  3.94s/it]
                                                           

  1%|          | 4640/569592 [3:55:24<618:06:45,  3.94s/it]
  1%|          | 4641/569592 [3:55:29<636:38:57,  4.06s/it]
                                                           

  1%|          | 4641/569592 [3:55:29<636:38:57,  4.06s/it]
  1%|          | 4642/569592 [3:55:33<664:46:32,  4.24s/it]
                                                           

  1%|          | 4642/569592 [3:55:33<664:46:32,  4.24s/it]
  1%|          | 4643/569592 [3:55:38<687:15:29,  4.38s/it]
                                                           

  1%|          | 4643/569592 [3:55:38<687:15:29,  4.38s/it]
  1%|          | 4644/569592 [3:55:41<631:56:29,  4.03s/it]
                                                           

  1%|          | 4644/569592 [3:55:41<631:56:29,  4.03s/it]
  1%|          | 4645/569592 [3:55:44<582:59:33,  3.71s/it]
                                                           

  1%|          | 4645/569592 [3:55:44<582:59:33,  3.71s/it]
  1%|          | 4646/569592 [3:55:49<637:04:19,  4.06s/it]
                                                           

  1%|          | 4646/569592 [3:55:49<637:04:19,  4.06s/it]
  1%|          | 4647/569592 [3:55:52<592:13:57,  3.77s/it]
                                                           

  1%|          | 4647/569592 [3:55:52<592:13:57,  3.77s/it]
  1%|          | 4648/569592 [3:55:55<561:02:18,  3.58s/it]
                                                           

  1%|          | 4648/569592 [3:55:55<561:02:18,  3.58s/it]
  1%|          | 4649/569592 [3:55:56<435:48:52,  2.78s/it]
                                                           

  1%|          | 4649/569592 [3:55:56<435:48:52,  2.78s/it]
  1%|          | 4650/569592 [3:56:00<470:00:05,  3.00s/it]
                                                           

  1%|          | 4650/569592 [3:56:00<470:00:05,  3.00s/it]
  1%|          | 4651/569592 [3:56:01<372:31:03,  2.37s/it]
                                                           

  1%|          | 4651/569592 [3:56:01<372:31:03,  2.37s/it]
  1%|          | 4652/569592 [3:56:04<430:43:05,  2.74s/it]
                                                           

  1%|          | 4652/569592 [3:56:04<430:43:05,  2.74s/it]
  1%|          | 4653/569592 [3:56:08<464:49:12,  2.96s/it]
                                                           

  1%|          | 4653/569592 [3:56:08<464:49:12,  2.96s/it]
  1%|          | 4654/569592 [3:56:11<498:10:41,  3.17s/it]
                                                           

  1%|          | 4654/569592 [3:56:11<498:10:41,  3.17s/it]
  1%|          | 4655/569592 [3:56:15<527:31:44,  3.36s/it]
                                                           

  1%|          | 4655/569592 [3:56:15<527:31:44,  3.36s/it]
  1%|          | 4656/569592 [3:56:20<602:21:08,  3.84s/it]
                                                           

  1%|          | 4656/569592 [3:56:20<602:21:08,  3.84s/it]
  1%|          | 4657/569592 [3:56:24<580:08:44,  3.70s/it]
                                                           

  1%|          | 4657/569592 [3:56:24<580:08:44,  3.70s/it]
  1%|          | 4658/569592 [3:56:28<625:36:15,  3.99s/it]
                                                           

  1%|          | 4658/569592 [3:56:28<625:36:15,  3.99s/it]
  1%|          | 4659/569592 [3:56:31<578:29:01,  3.69s/it]
                                                           

  1%|          | 4659/569592 [3:56:31<578:29:01,  3.69s/it]
  1%|          | 4660/569592 [3:56:32<449:17:19,  2.86s/it]
                                                           

  1%|          | 4660/569592 [3:56:32<449:17:19,  2.86s/it]
  1%|          | 4661/569592 [3:56:33<359:26:13,  2.29s/it]
                                                           

  1%|          | 4661/569592 [3:56:33<359:26:13,  2.29s/it]
  1%|          | 4662/569592 [3:56:37<426:27:30,  2.72s/it]
                                                           

  1%|          | 4662/569592 [3:56:37<426:27:30,  2.72s/it]
  1%|          | 4663/569592 [3:56:42<538:35:47,  3.43s/it]
                                                           

  1%|          | 4663/569592 [3:56:42<538:35:47,  3.43s/it]
  1%|          | 4664/569592 [3:56:45<518:56:54,  3.31s/it]
                                                           

  1%|          | 4664/569592 [3:56:45<518:56:54,  3.31s/it]
  1%|          | 4665/569592 [3:56:49<550:14:06,  3.51s/it]
                                                           

  1%|          | 4665/569592 [3:56:49<550:14:06,  3.51s/it]
  1%|          | 4666/569592 [3:56:52<550:38:03,  3.51s/it]
                                                           

  1%|          | 4666/569592 [3:56:52<550:38:03,  3.51s/it]
  1%|          | 4667/569592 [3:56:53<428:04:41,  2.73s/it]
                                                           

  1%|          | 4667/569592 [3:56:53<428:04:41,  2.73s/it]
  1%|          | 4668/569592 [3:56:54<344:50:43,  2.20s/it]
                                                           

  1%|          | 4668/569592 [3:56:54<344:50:43,  2.20s/it]
  1%|          | 4669/569592 [3:56:55<287:30:30,  1.83s/it]
                                                           

  1%|          | 4669/569592 [3:56:55<287:30:30,  1.83s/it]
  1%|          | 4670/569592 [3:56:56<246:39:11,  1.57s/it]
                                                           

  1%|          | 4670/569592 [3:56:56<246:39:11,  1.57s/it]
  1%|          | 4671/569592 [3:56:57<216:43:56,  1.38s/it]
                                                           

  1%|          | 4671/569592 [3:56:57<216:43:56,  1.38s/it]
  1%|          | 4672/569592 [3:56:58<195:59:04,  1.25s/it]
                                                           

  1%|          | 4672/569592 [3:56:58<195:59:04,  1.25s/it]
  1%|          | 4673/569592 [3:56:59<184:21:42,  1.17s/it]
                                                           

  1%|          | 4673/569592 [3:56:59<184:21:42,  1.17s/it]
  1%|          | 4674/569592 [3:57:02<245:48:10,  1.57s/it]
                                                           

  1%|          | 4674/569592 [3:57:02<245:48:10,  1.57s/it]
  1%|          | 4675/569592 [3:57:06<390:00:40,  2.49s/it]
                                                           

  1%|          | 4675/569592 [3:57:06<390:00:40,  2.49s/it]
  1%|          | 4676/569592 [3:57:07<320:54:13,  2.05s/it]
                                                           

  1%|          | 4676/569592 [3:57:07<320:54:13,  2.05s/it]
  1%|          | 4677/569592 [3:57:08<269:47:53,  1.72s/it]
                                                           

  1%|          | 4677/569592 [3:57:08<269:47:53,  1.72s/it]
  1%|          | 4678/569592 [3:57:12<352:17:10,  2.24s/it]
                                                           

  1%|          | 4678/569592 [3:57:12<352:17:10,  2.24s/it]
  1%|          | 4679/569592 [3:57:16<467:24:43,  2.98s/it]
                                                           

  1%|          | 4679/569592 [3:57:16<467:24:43,  2.98s/it]
  1%|          | 4680/569592 [3:57:17<375:19:56,  2.39s/it]
                                                           

  1%|          | 4680/569592 [3:57:17<375:19:56,  2.39s/it]
  1%|          | 4681/569592 [3:57:19<325:58:27,  2.08s/it]
                                                           

  1%|          | 4681/569592 [3:57:19<325:58:27,  2.08s/it]
  1%|          | 4682/569592 [3:57:22<404:14:38,  2.58s/it]
                                                           

  1%|          | 4682/569592 [3:57:22<404:14:38,  2.58s/it]
  1%|          | 4683/569592 [3:57:27<475:05:15,  3.03s/it]
                                                           

  1%|          | 4683/569592 [3:57:27<475:05:15,  3.03s/it]
  1%|          | 4684/569592 [3:57:28<387:40:24,  2.47s/it]
                                                           

  1%|          | 4684/569592 [3:57:28<387:40:24,  2.47s/it]
  1%|          | 4685/569592 [3:57:29<329:55:16,  2.10s/it]
                                                           

  1%|          | 4685/569592 [3:57:29<329:55:16,  2.10s/it]
  1%|          | 4686/569592 [3:57:33<409:41:39,  2.61s/it]
                                                           

  1%|          | 4686/569592 [3:57:33<409:41:39,  2.61s/it]
  1%|          | 4687/569592 [3:57:37<505:46:59,  3.22s/it]
                                                           

  1%|          | 4687/569592 [3:57:37<505:46:59,  3.22s/it]
  1%|          | 4688/569592 [3:57:38<401:46:23,  2.56s/it]
                                                           

  1%|          | 4688/569592 [3:57:38<401:46:23,  2.56s/it]
  1%|          | 4689/569592 [3:57:39<330:18:34,  2.10s/it]
                                                           

  1%|          | 4689/569592 [3:57:39<330:18:34,  2.10s/it]
  1%|          | 4690/569592 [3:57:44<446:56:36,  2.85s/it]
                                                           

  1%|          | 4690/569592 [3:57:44<446:56:36,  2.85s/it]
  1%|          | 4691/569592 [3:57:48<496:08:57,  3.16s/it]
                                                           

  1%|          | 4691/569592 [3:57:48<496:08:57,  3.16s/it]
  1%|          | 4692/569592 [3:57:49<393:43:55,  2.51s/it]
                                                           

  1%|          | 4692/569592 [3:57:49<393:43:55,  2.51s/it]
  1%|          | 4693/569592 [3:57:50<320:13:07,  2.04s/it]
                                                           

  1%|          | 4693/569592 [3:57:50<320:13:07,  2.04s/it]
  1%|          | 4694/569592 [3:57:53<387:23:58,  2.47s/it]
                                                           

  1%|          | 4694/569592 [3:57:53<387:23:58,  2.47s/it]
  1%|          | 4695/569592 [3:57:57<432:58:04,  2.76s/it]
                                                           

  1%|          | 4695/569592 [3:57:57<432:58:04,  2.76s/it]
  1%|          | 4696/569592 [3:57:58<347:34:06,  2.22s/it]
                                                           

  1%|          | 4696/569592 [3:57:58<347:34:06,  2.22s/it]
  1%|          | 4697/569592 [3:58:01<380:50:27,  2.43s/it]
                                                           

  1%|          | 4697/569592 [3:58:01<380:50:27,  2.43s/it]
  1%|          | 4698/569592 [3:58:04<425:38:08,  2.71s/it]
                                                           

  1%|          | 4698/569592 [3:58:04<425:38:08,  2.71s/it]
  1%|          | 4699/569592 [3:58:07<454:51:49,  2.90s/it]
                                                           

  1%|          | 4699/569592 [3:58:07<454:51:49,  2.90s/it]
  1%|          | 4700/569592 [3:58:08<367:23:27,  2.34s/it]
                                                           

  1%|          | 4700/569592 [3:58:08<367:23:27,  2.34s/it]
  1%|          | 4701/569592 [3:58:11<398:56:03,  2.54s/it]
                                                           

  1%|          | 4701/569592 [3:58:11<398:56:03,  2.54s/it]
  1%|          | 4702/569592 [3:58:17<523:14:27,  3.33s/it]
                                                           

  1%|          | 4702/569592 [3:58:17<523:14:27,  3.33s/it]
  1%|          | 4703/569592 [3:58:18<411:55:12,  2.63s/it]
                                                           

  1%|          | 4703/569592 [3:58:18<411:55:12,  2.63s/it]
  1%|          | 4704/569592 [3:58:21<445:05:36,  2.84s/it]
                                                           

  1%|          | 4704/569592 [3:58:21<445:05:36,  2.84s/it]
  1%|          | 4705/569592 [3:58:22<358:16:52,  2.28s/it]
                                                           

  1%|          | 4705/569592 [3:58:22<358:16:52,  2.28s/it]
  1%|          | 4706/569592 [3:58:26<429:44:57,  2.74s/it]
                                                           

  1%|          | 4706/569592 [3:58:26<429:44:57,  2.74s/it]
  1%|          | 4707/569592 [3:58:30<484:35:56,  3.09s/it]
                                                           

  1%|          | 4707/569592 [3:58:30<484:35:56,  3.09s//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94166820 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
it]
  1%|          | 4708/569592 [3:58:31<383:27:50,  2.44s/it]
                                                           

  1%|          | 4708/569592 [3:58:31<383:27:50,  2.44s/it]
  1%|          | 4709/569592 [3:58:32<317:21:57,  2.02s/it]
                                                           

  1%|          | 4709/569592 [3:58:32<317:21:57,  2.02s/it]
  1%|          | 4710/569592 [3:58:37<480:37:56,  3.06s/it]
                                                           

  1%|          | 4710/569592 [3:58:37<480:37:56,  3.06s/it]
  1%|          | 4711/569592 [3:58:39<426:39:22,  2.72s/it]
                                                           

  1%|          | 4711/569592 [3:58:39<426:39:22,  2.72s/it]
  1%|          | 4712/569592 [3:58:40<343:54:00,  2.19s/it]
                                                           

  1%|          | 4712/569592 [3:58:40<343:54:00,  2.19s/it]
  1%|          | 4713/569592 [3:58:43<390:14:07,  2.49s/it]
                                                           

  1%|          | 4713/569592 [3:58:43<390:14:07,  2.49s/it]
  1%|          | 4714/569592 [3:58:47<433:29:06,  2.76s/it]
                                                           

  1%|          | 4714/569592 [3:58:47<433:29:06,  2.76s/it]
  1%|          | 4715/569592 [3:58:51<497:36:17,  3.17s/it]
                                                           

  1%|          | 4715/569592 [3:58:51<497:36:17,  3.17s/it]
  1%|          | 4716/569592 [3:58:52<392:24:48,  2.50s/it]
                                                           

  1%|          | 4716/569592 [3:58:52<392:24:48,  2.50s/it]
  1%|          | 4717/569592 [3:58:53<320:32:31,  2.04s/it]
                                                           

  1%|          | 4717/569592 [3:58:53<320:32:31,  2.04s/it]
  1%|          | 4718/569592 [3:58:58<463:15:21,  2.95s/it]
                                                           

  1%|          | 4718/569592 [3:58:58<463:15:21,  2.95s/it]
  1%|          | 4719/569592 [3:59:02<510:07:26,  3.25s/it]
                                                           

  1%|          | 4719/569592 [3:59:02<510:07:26,  3.25s/it]
  1%|          | 4720/569592 [3:59:06<584:51:08,  3.73s/it]
                                                           

  1%|          | 4720/569592 [3:59:06<584:51:08,  3.73s/it]
  1%|          | 4721/569592 [3:59:11<639:45:59,  4.08s/it]
                                                           

  1%|          | 4721/569592 [3:59:11<639:45:59,  4.08s/it]
  1%|          | 4722/569592 [3:59:12<491:50:24,  3.13s/it]
                                                           

  1%|          | 4722/569592 [3:59:12<491:50:24,  3.13s/it]
  1%|          | 4723/569592 [3:59:16<502:31:34,  3.20s/it]
                                                           

  1%|          | 4723/569592 [3:59:16<502:31:34,  3.20s/it]
  1%|          | 4724/569592 [3:59:19<532:10:03,  3.39s/it]
                                                           

  1%|          | 4724/569592 [3:59:19<532:10:03,  3.39s/it]
  1%|          | 4725/569592 [3:59:23<526:38:44,  3.36s/it]
                                                           

  1%|          | 4725/569592 [3:59:23<526:38:44,  3.36s/it]
  1%|          | 4726/569592 [3:59:27<575:10:20,  3.67s/it]
                                                           

  1%|          | 4726/569592 [3:59:27<575:10:20,  3.67s/it]
  1%|          | 4727/569592 [3:59:30<550:38:21,  3.51s/it]
                                                           

  1%|          | 4727/569592 [3:59:30<550:38:21,  3.51s/it]
  1%|          | 4728/569592 [3:59:35<605:45:26,  3.86s/it]
                                                           

  1%|          | 4728/569592 [3:59:35<605:45:26,  3.86s/it]
  1%|          | 4729/569592 [3:59:36<468:07:26,  2.98s/it]
                                                           

  1%|          | 4729/569592 [3:59:36<468:07:26,  2.98s/it]
  1%|          | 4730/569592 [3:59:40<502:36:52,  3.20s/it]
                                                           

  1%|          | 4730/569592 [3:59:40<502:36:52,  3.20s/it]
  1%|          | 4731/569592 [3:59:44<575:50:08,  3.67s/it]
                                                           

  1%|          | 4731/569592 [3:59:44<575:50:08,  3.67s/it]
  1%|          | 4732/569592 [3:59:48<567:30:20,  3.62s/it]
                                                           

  1%|          | 4732/569592 [3:59:48<567:30:20,  3.62s/it]
  1%|          | 4733/569592 [3:59:51<555:41:40,  3.54s/it]
                                                           

  1%|          | 4733/569592 [3:59:51<555:41:40,  3.54s/it]
  1%|          | 4734/569592 [3:59:52<432:40:53,  2.76s/it]
                                                           

  1%|          | 4734/569592 [3:59:52<432:40:53,  2.76s/it]
  1%|          | 4735/569592 [3:59:55<452:46:55,  2.89s/it]
                                                           

  1%|          | 4735/569592 [3:59:55<452:46:55,  2.89s/it]
  1%|          | 4736/569592 [3:59:59<470:57:27,  3.00s/it]
                                                           

  1%|          | 4736/569592 [3:59:59<470:57:27,  3.00s/it]
  1%|          | 4737/569592 [4:00:02<499:11:05,  3.18s/it]
                                                           

  1%|          | 4737/569592 [4:00:02<499:11:05,  3.18s/it]
  1%|          | 4738/569592 [4:00:07<574:36:56,  3.66s/it]
                                                           

  1%|          | 4738/569592 [4:00:07<574:36:56,  3.66s/it]
  1%|          | 4739/569592 [4:00:08<444:24:23,  2.83s/it]
                                                           

  1%|          | 4739/569592 [4:00:08<444:24:23,  2.83s/it]
  1%|          | 4740/569592 [4:00:09<354:22:30,  2.26s/it]
                                                           

  1%|          | 4740/569592 [4:00:09<354:22:30,  2.26s/it]
  1%|          | 4741/569592 [4:00:14<487:37:01,  3.11s/it]
                                                           

  1%|          | 4741/569592 [4:00:14<487:37:01,  3.11s/it]
  1%|          | 4742/569592 [4:00:18<520:34:49,  3.32s/it]
                                                           

  1%|          | 4742/569592 [4:00:18<520:34:49,  3.32s/it]
  1%|          | 4743/569592 [4:00:21<510:01:21,  3.25s/it]
                                                           

  1%|          | 4743/569592 [4:00:21<510:01:21,  3.25s/it]
  1%|          | 4744/569592 [4:00:26<599:05:31,  3.82s/it]
                                                           

  1%|          | 4744/569592 [4:00:26<599:05:31,  3.82s/it]
  1%|          | 4745/569592 [4:00:30<602:25:11,  3.84s/it]
                                                           

  1%|          | 4745/569592 [4:00:30<602:25:11,  3.84s/it]
  1%|          | 4746/569592 [4:00:35<681:02:11,  4.34s/it]
                                                           

  1%|          | 4746/569592 [4:00:35<681:02:11,  4.34s/it]
  1%|          | 4747/569592 [4:00:40<699:01:02,  4.46s/it]
                                                           

  1%|          | 4747/569592 [4:00:40<699:01:02,  4.46s/it]
  1%|          | 4748/569592 [4:00:47<829:57:00,  5.29s/it]
                                                           

  1%|          | 4748/569592 [4:00:47<829:57:00,  5.29s/it]
  1%|          | 4749/569592 [4:00:52<796:40:58,  5.08s/it]
                                                           

  1%|          | 4749/569592 [4:00:52<796:40:58,  5.08s/it]
  1%|          | 4750/569592 [4:00:56<760:15:29,  4.85s/it]
                                                           

  1%|          | 4750/569592 [4:00:56<760:15:29,  4.85s/it]
  1%|          | 4751/569592 [4:00:57<579:57:01,  3.70s/it]
                                                           

  1%|          | 4751/569592 [4:00:57<579:57:01,  3.70s/it]
  1%|          | 4752/569592 [4:01:00<556:53:07,  3.55s/it]
                                                           

  1%|          | 4752/569592 [4:01:00<556:53:07,  3.55s/it]
  1%|          | 4753/569592 [4:01:06<631:48:34,  4.03s/it]
                                                           

  1%|          | 4753/569592 [4:01:06<631:48:34,  4.03s/it]
  1%|          | 4754/569592 [4:01:13<818:30:41,  5.22s/it]
                                                           

  1%|          | 4754/569592 [4:01:14<818:30:41,  5.22s/it]
  1%|          | 4755/569592 [4:01:18<769:20:40,  4.90s/it]
                                                           

  1%|          | 4755/569592 [4:01:18<769:20:40,  4.90s/it]
  1%|          | 4756/569592 [4:01:21<689:20:58,  4.39s/it]
                                                           

  1%|          | 4756/569592 [4:01:21<689:20:58,  4.39s/it]
  1%|          | 4757/569592 [4:01:25<676:13:54,  4.31s/it]
                                                           

  1%|          | 4757/569592 [4:01:25<676:13:54,  4.31s/it]
  1%|          | 4758/569592 [4:01:30<708:06:22,  4.51s/it]
                                                           

  1%|          | 4758/569592 [4:01:30<708:06:22,  4.51s/it]
  1%|          | 4759/569592 [4:01:35<717:01:29,  4.57s/it]
                                                           

  1%|          | 4759/569592 [4:01:35<717:01:29,  4.57s/it]
  1%|          | 4760/569592 [4:01:40<749:55:37,  4.78s/it]
                                                           

  1%|          | 4760/569592 [4:01:40<749:55:37,  4.78s/it]
  1%|          | 4761/569592 [4:01:43<678:15:38,  4.32s/it]
                                                           

  1%|          | 4761/569592 [4:01:43<678:15:38,  4.32s/it]
  1%|          | 4762/569592 [4:01:44<516:09:20,  3.29s/it]
                                                           

  1%|          | 4762/569592 [4:01:44<516:09:20,  3.29s/it]
  1%|          | 4763/569592 [4:01:47<510:10:39,  3.25s/it]
                                                           

  1%|          | 4763/569592 [4:01:47<510:10:39,  3.25s/it]
  1%|          | 4764/569592 [4:01:51<511:35:27,  3.26s/it]
                                                           

  1%|          | 4764/569592 [4:01:51<511:35:27,  3.26s/it]
  1%|          | 4765/569592 [4:01:54<514:16:11,  3.28s/it]
                                                           

  1%|          | 4765/569592 [4:01:54<514:16:11,  3.28s/it]
  1%|          | 4766/569592 [4:01:59<582:00:10,  3.71s/it]
                                                           

  1%|          | 4766/569592 [4:01:59<582:00:10,  3.71s/it]
  1%|          | 4767/569592 [4:02:02<592:28:51,  3.78s/it]
                                                           

  1%|          | 4767/569592 [4:02:03<592:28:51,  3.78s/it]
  1%|          | 4768/569592 [4:02:03<455:43:28,  2.90s/it]
                                                           

  1%|          | 4768/569592 [4:02:03<455:43:28,  2.90s/it]
  1%|          | 4769/569592 [4:02:07<470:25:21,  3.00s/it]
                                                           

  1%|          | 4769/569592 [4:02:07<470:25:21,  3.00s/it]
  1%|          | 4770/569592 [4:02:10<490:33:00,  3.13s/it]
                                                           

  1%|          | 4770/569592 [4:02:10<490:33:00,  3.13s/it]
  1%|          | 4771/569592 [4:02:15<565:31:41,  3.60s/it]
                                                           

  1%|          | 4771/569592 [4:02:15<565:31:41,  3.60s/it]
  1%|          | 4772/569592 [4:02:18<539:45:45,  3.44s/it]
                                                           

  1%|          | 4772/569592 [4:02:18<539:45:45,  3.44s/it]
  1%|          | 4773/569592 [4:02:23<601:05:24,  3.83s/it]
                                                           

  1%|          | 4773/569592 [4:02:23<601:05:24,  3.83s/it]
  1%|          | 4774/569592 [4:02:26<568:15:16,  3.62s/it]
                                                           

  1%|          | 4774/569592 [4:02:26<568:15:16,  3.62s/it]
  1%|          | 4775/569592 [4:02:30<621:01:49,  3.96s/it]
                                                           

  1%|          | 4775/569592 [4:02:30<621:01:49,  3.96s/it]
  1%|          | 4776/569592 [4:02:34<614:43:22,  3.92s/it]
                                                           

  1%|          | 4776/569592 [4:02:34<614:43:22,  3.92s/it]
  1%|          | 4777/569592 [4:02:39<649:06:29,  4.14s/it]
                                                           

  1%|          | 4777/569592 [4:02:39<649:06:29,  4.14s/it]
  1%|          | 4778/569592 [4:02:40<497:00:52,  3.17s/it]
                                                           

  1%|          | 4778/569592 [4:02:40<497:00:52,  3.17s/it]
  1%|          | 4779/569592 [4:02:41<391:44:52,  2.50s/it]
                                                           

  1%|          | 4779/569592 [4:02:41<391:44:52,  2.50s/it]
  1%|          | 4780/569592 [4:02:44<450:02:59,  2.87s/it]
                                                           

  1%|          | 4780/569592 [4:02:44<450:02:59,  2.87s/it]
  1%|          | 4781/569592 [4:02:45<359:06:03,  2.29s/it]
                                   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                        

  1%|          | 4781/569592 [4:02:45<359:06:03,  2.29s/it]
  1%|          | 4782/569592 [4:02:50<456:11:26,  2.91s/it]
                                                           

  1%|          | 4782/569592 [4:02:50<456:11:26,  2.91s/it]
  1%|          | 4783/569592 [4:02:55<550:48:27,  3.51s/it]
                                                           

  1%|          | 4783/569592 [4:02:55<550:48:27,  3.51s/it]
  1%|          | 4784/569592 [4:02:58<539:28:27,  3.44s/it]
                                                           

  1%|          | 4784/569592 [4:02:58<539:28:27,  3.44s/it]
  1%|          | 4785/569592 [4:02:59<425:40:20,  2.71s/it]
                                                           

  1%|          | 4785/569592 [4:02:59<425:40:20,  2.71s/it]
  1%|          | 4786/569592 [4:03:00<340:53:07,  2.17s/it]
                                                           

  1%|          | 4786/569592 [4:03:00<340:53:07,  2.17s/it]
  1%|          | 4787/569592 [4:03:01<284:01:05,  1.81s/it]
                                                           

  1%|          | 4787/569592 [4:03:01<284:01:05,  1.81s/it]
  1%|          | 4788/569592 [4:03:02<242:53:11,  1.55s/it]
                                                           

  1%|          | 4788/569592 [4:03:02<242:53:11,  1.55s/it]
  1%|          | 4789/569592 [4:03:03<213:39:33,  1.36s/it]
                                                           

  1%|          | 4789/569592 [4:03:03<213:39:33,  1.36s/it]
  1%|          | 4790/569592 [4:03:04<198:32:28,  1.27s/it]
                                                           

  1%|          | 4790/569592 [4:03:04<198:32:28,  1.27s/it]
  1%|          | 4791/569592 [4:03:05<183:01:49,  1.17s/it]
                                                           

  1%|          | 4791/569592 [4:03:05<183:01:49,  1.17s/it]
  1%|          | 4792/569592 [4:03:08<284:16:18,  1.81s/it]
                                                           

  1%|          | 4792/569592 [4:03:08<284:16:18,  1.81s/it]
  1%|          | 4793/569592 [4:03:11<354:15:58,  2.26s/it]
                                                           

  1%|          | 4793/569592 [4:03:11<354:15:58,  2.26s/it]
  1%|          | 4794/569592 [4:03:12<297:01:05,  1.89s/it]
                                                           

  1%|          | 4794/569592 [4:03:12<297:01:05,  1.89s/it]
  1%|          | 4795/569592 [4:03:13<262:51:54,  1.68s/it]
                                                           

  1%|          | 4795/569592 [4:03:14<262:51:54,  1.68s/it]
  1%|          | 4796/569592 [4:03:18<388:31:35,  2.48s/it]
                                                           

  1%|          | 4796/569592 [4:03:18<388:31:35,  2.48s/it]
  1%|          | 4797/569592 [4:03:22<453:32:01,  2.89s/it]
                                                           

  1%|          | 4797/569592 [4:03:22<453:32:01,  2.89s/it]
  1%|          | 4798/569592 [4:03:23<376:44:40,  2.40s/it]
                                                           

  1%|          | 4798/569592 [4:03:23<376:44:40,  2.40s/it]
  1%|          | 4799/569592 [4:03:24<307:31:36,  1.96s/it]
                                                           

  1%|          | 4799/569592 [4:03:24<307:31:36,  1.96s/it]
  1%|          | 4800/569592 [4:03:29<455:04:07,  2.90s/it]
                                                           

  1%|          | 4800/569592 [4:03:29<455:04:07,  2.90s/it]
  1%|          | 4801/569592 [4:03:32<449:33:44,  2.87s/it]
                                                           

  1%|          | 4801/569592 [4:03:32<449:33:44,  2.87s/it]
  1%|          | 4802/569592 [4:03:33<381:43:05,  2.43s/it]
                                                           

  1%|          | 4802/569592 [4:03:33<381:43:05,  2.43s/it]
  1%|          | 4803/569592 [4:03:34<312:19:10,  1.99s/it]
                                                           

  1%|          | 4803/569592 [4:03:34<312:19:10,  1.99s/it]
  1%|          | 4804/569592 [4:03:39<428:27:08,  2.73s/it]
                                                           

  1%|          | 4804/569592 [4:03:39<428:27:08,  2.73s/it]
  1%|          | 4805/569592 [4:03:42<467:34:20,  2.98s/it]
                                                           

  1%|          | 4805/569592 [4:03:42<467:34:20,  2.98s/it]
  1%|          | 4806/569592 [4:03:43<375:22:16,  2.39s/it]
                                                           

  1%|          | 4806/569592 [4:03:43<375:22:16,  2.39s/it]
  1%|          | 4807/569592 [4:03:46<416:29:31,  2.65s/it]
                                                           

  1%|          | 4807/569592 [4:03:46<416:29:31,  2.65s/it]
  1%|          | 4808/569592 [4:03:48<375:14:25,  2.39s/it]
                                                           

  1%|          | 4808/569592 [4:03:48<375:14:25,  2.39s/it]
  1%|          | 4809/569592 [4:03:52<442:20:28,  2.82s/it]
                                                           

  1%|          | 4809/569592 [4:03:52<442:20:28,  2.82s/it]
  1%|          | 4810/569592 [4:03:53<370:45:00,  2.36s/it]
                                                           

  1%|          | 4810/569592 [4:03:53<370:45:00,  2.36s/it]
  1%|          | 4811/569592 [4:03:55<341:25:52,  2.18s/it]
                                                           

  1%|          | 4811/569592 [4:03:55<341:25:52,  2.18s/it]
  1%|          | 4812/569592 [4:03:59<403:25:39,  2.57s/it]
                                                           

  1%|          | 4812/569592 [4:03:59<403:25:39,  2.57s/it]
  1%|          | 4813/569592 [4:04:04<552:20:11,  3.52s/it]
                                                           

  1%|          | 4813/569592 [4:04:04<552:20:11,  3.52s/it]
  1%|          | 4814/569592 [4:04:05<431:06:30,  2.75s/it]
                                                           

  1%|          | 4814/569592 [4:04:05<431:06:30,  2.75s/it]
  1%|          | 4815/569592 [4:04:06<349:00:22,  2.22s/it]
                         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95217417 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                  

  1%|          | 4815/569592 [4:04:06<349:00:22,  2.22s/it]
  1%|          | 4816/569592 [4:04:09<387:34:25,  2.47s/it]
                                                           

  1%|          | 4816/569592 [4:04:09<387:34:25,  2.47s/it]
  1%|          | 4817/569592 [4:04:14<495:25:58,  3.16s/it]
                                                           

  1%|          | 4817/569592 [4:04:14<495:25:58,  3.16s/it]
  1%|          | 4818/569592 [4:04:15<393:37:07,  2.51s/it]
                                                           

  1%|          | 4818/569592 [4:04:15<393:37:07,  2.51s/it]
  1%|          | 4819/569592 [4:04:16<327:01:41,  2.08s/it]
                                                           

  1%|          | 4819/569592 [4:04:16<327:01:41,  2.08s/it]
  1%|          | 4820/569592 [4:04:21<453:51:13,  2.89s/it]
                                                           

  1%|          | 4820/569592 [4:04:21<453:51:13,  2.89s/it]
  1%|          | 4821/569592 [4:04:25<530:46:54,  3.38s/it]
                                                           

  1%|          | 4821/569592 [4:04:25<530:46:54,  3.38s/it]
  1%|          | 4822/569592 [4:04:29<544:11:17,  3.47s/it]
                                                           

  1%|          | 4822/569592 [4:04:29<544:11:17,  3.47s/it]
  1%|          | 4823/569592 [4:04:30<425:56:13,  2.72s/it]
                                                           

  1%|          | 4823/569592 [4:04:30<425:56:13,  2.72s/it]
  1%|          | 4824/569592 [4:04:31<346:23:38,  2.21s/it]
                                                           

  1%|          | 4824/569592 [4:04:31<346:23:38,  2.21s/it]
  1%|          | 4825/569592 [4:04:35<402:50:39,  2.57s/it]
                                                           

  1%|          | 4825/569592 [4:04:35<402:50:39,  2.57s/it]
  1%|          | 4826/569592 [4:04:40<535:12:08,  3.41s/it]
                                                           

  1%|          | 4826/569592 [4:04:40<535:12:08,  3.41s/it]
  1%|          | 4827/569592 [4:04:41<419:01:46,  2.67s/it]
                                                           

  1%|          | 4827/569592 [4:04:41<419:01:46,  2.67s/it]
  1%|          | 4828/569592 [4:04:42<337:41:04,  2.15s/it]
                                                           

  1%|          | 4828/569592 [4:04:42<337:41:04,  2.15s/it]
  1%|          | 4829/569592 [4:04:44<345:08:38,  2.20s/it]
                                                           

  1%|          | 4829/569592 [4:04:44<345:08:38,  2.20s/it]
  1%|          | 4830/569592 [4:04:45<286:13:29,  1.82s/it]
                                                           

  1%|          | 4830/569592 [4:04:45<286:13:29,  1.82s/it]
  1%|          | 4831/569592 [4:04:49<367:26:33,  2.34s/it]
                                                           

  1%|          | 4831/569592 [4:04:49<367:26:33,  2.34s/it]
  1%|          | 4832/569592 [4:04:52<439:36:11,  2.80s/it]
                                                           

  1%|          | 4832/569592 [4:04:52<439:36:11,  2.80s/it]
  1%|          | 4833/569592 [4:04:57<543:01:53,  3.46s/it]
                                                           

  1%|          | 4833/569592 [4:04:57<543:01:53,  3.46s/it]
  1%|          | 4834/569592 [4:04:58<424:08:27,  2.70s/it]
                                                           

  1%|          | 4834/569592 [4:04:58<424:08:27,  2.70s/it]
  1%|          | 4835/569592 [4:05:02<451:25:39,  2.88s/it]
                                                           

  1%|          | 4835/569592 [4:05:02<451:25:39,  2.88s/it]
  1%|          | 4836/569592 [4:05:05<472:56:12,  3.01s/it]
                                                           

  1%|          | 4836/569592 [4:05:05<472:56:12,  3.01s/it]
  1%|          | 4837/569592 [4:05:10<561:12:50,  3.58s/it]
                                                           

  1%|          | 4837/569592 [4:05:10<561:12:50,  3.58s/it]
  1%|          | 4838/569592 [4:05:14<564:44:59,  3.60s/it]
                                                           

  1%|          | 4838/569592 [4:05:14<564:44:59,  3.60s/it]
  1%|          | 4839/569592 [4:05:18<618:04:55,  3.94s/it]
                                                           

  1%|          | 4839/569592 [4:05:18<618:04:55,  3.94s/it]
  1%|          | 4840/569592 [4:05:22<592:23:27,  3.78s/it]
                                                           

  1%|          | 4840/569592 [4:05:22<592:23:27,  3.78s/it]
  1%|          | 4841/569592 [4:05:26<620:15:36,  3.95s/it]
                                                           

  1%|          | 4841/569592 [4:05:26<620:15:36,  3.95s/it]
  1%|          | 4842/569592 [4:05:27<476:28:51,  3.04s/it]
                                                           

  1%|          | 4842/569592 [4:05:27<476:28:51,  3.04s/it]
  1%|          | 4843/569592 [4:05:30<494:59:07,  3.16s/it]
                                                           

  1%|          | 4843/569592 [4:05:30<494:59:07,  3.16s/it]
  1%|          | 4844/569592 [4:05:34<515:58:14,  3.29s/it]
                                                           

  1%|          | 4844/569592 [4:05:34<515:58:14,  3.29s/it]
  1%|          | 4845/569592 [4:05:37<518:28:30,  3.31s/it]
                                                           

  1%|          | 4845/569592 [4:05:37<518:28:30,  3.31s/it]
  1%|          | 4846/569592 [4:05:40<510:15:22,  3.25s/it]
                                                           

  1%|          | 4846/569592 [4:05:40<510:15:22,  3.25s/it]
  1%|          | 4847/569592 [4:05:46<596:53:12,  3.80s/it]
                                                           

  1%|          | 4847/569592 [4:05:46<596:53:12,  3.80s/it]
  1%|          | 4848/569592 [4:05:49<563:39:22,  3.59s/it]
                                                           

  1%|          | 4848/569592 [4:05:49<563:39:22,  3.59s/it]
  1%|          | 4849/569592 [4:05:54<632:58:14,  4.03s/it]
                                                           

  1%|          | 4849/569592 [4:05:54<632:58:14,  4.03s/it]
  1%|          | 4850/569592 [4:05:55<485:21:06,  3.09s/it]
                                                           

  1%|          | 4850/569592 [4:05:55<485:21:06,  3.09s/it]
  1%|          | 4851/569592 [4:05:59<564:20:56,  3.60s/it]
                                                           

  1%|          | 4851/569592 [4:05:59<564:20:56,  3.60s/it]
  1%|          | 4852/569592 [4:06:00<442:37:42,  2.82s/it]
                                                           

  1%|          | 4852/569592 [4:06:00<442:37:42,  2.82s/it]
  1%|          | 4853/569592 [4:06:04<480:29:34,  3.06s/it]
                                                           

  1%|          | 4853/569592 [4:06:04<480:29:34,  3.06s/it]
  1%|          | 4854/569592 [4:06:05<379:56:28,  2.42s/it]
                                                           

  1%|          | 4854/569592 [4:06:05<379:56:28,  2.42s/it]
  1%|          | 4855/569592 [4:06:09<439:50:07,  2.80s/it]
                                                           

  1%|          | 4855/569592 [4:06:09<439:50:07,  2.80s/it]
  1%|          | 4856/569592 [4:06:13<525:02:48,  3.35s/it]
                                                           

  1%|          | 4856/569592 [4:06:13<525:02:48,  3.35s/it]
  1%|          | 4857/569592 [4:06:17<527:49:25,  3.36s/it]
                                                           

  1%|          | 4857/569592 [4:06:17<527:49:25,  3.36s/it]
  1%|          | 4858/569592 [4:06:20<539:05:14,  3.44s/it]
                                                           

  1%|          | 4858/569592 [4:06:20<539:05:14,  3.44s/it]
  1%|          | 4859/569592 [4:06:25<592:07:23,  3.77s/it]
                                                           

  1%|          | 4859/569592 [4:06:25<592:07:23,  3.77s/it]
  1%|          | 4860/569592 [4:06:29<590:21:41,  3.76s/it]
                                                           

  1%|          | 4860/569592 [4:06:29<590:21:41,  3.76s/it]
  1%|          | 4861/569592 [4:06:32<559:29:29,  3.57s/it]
                                                           

  1%|          | 4861/569592 [4:06:32<559:29:29,  3.57s/it]
  1%|          | 4862/569592 [4:06:37<643:26:27,  4.10s/it]
                                                           

  1%|          | 4862/569592 [4:06:37<643:26:27,  4.10s/it]
  1%|          | 4863/569592 [4:06:42<693:56:22,  4.42s/it]
                                                           

  1%|          | 4863/569592 [4:06:42<693:56:22,  4.42s/it]
  1%|          | 4864/569592 [4:06:47<700:57:32,  4.47s/it]
                                                           

  1%|          | 4864/569592 [4:06:47<700:57:32,  4.47s/it]
  1%|          | 4865/569592 [4:06:50<634:46:18,  4.05s/it]
                                                           

  1%|          | 4865/569592 [4:06:50<634:46:18,  4.05s/it]
  1%|          | 4866/569592 [4:06:51<486:50:57,  3.10s/it]
          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91617764 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                 

  1%|          | 4866/569592 [4:06:51<486:50:57,  3.10s/it]
  1%|          | 4867/569592 [4:06:54<485:05:58,  3.09s/it]
                                                           

  1%|          | 4867/569592 [4:06:54<485:05:58,  3.09s/it]
  1%|          | 4868/569592 [4:06:57<501:31:18,  3.20s/it]
                                                           

  1%|          | 4868/569592 [4:06:57<501:31:18,  3.20s/it]
  1%|          | 4869/569592 [4:06:58<400:03:28,  2.55s/it]
                                                           

  1%|          | 4869/569592 [4:06:58<400:03:28,  2.55s/it]
  1%|          | 4870/569592 [4:07:03<509:22:17,  3.25s/it]
                                                           

  1%|          | 4870/569592 [4:07:03<509:22:17,  3.25s/it]
  1%|          | 4871/569592 [4:07:08<596:58:46,  3.81s/it]
                                                           

  1%|          | 4871/569592 [4:07:08<596:58:46,  3.81s/it]
  1%|          | 4872/569592 [4:07:13<633:24:03,  4.04s/it]
                                                           

  1%|          | 4872/569592 [4:07:13<633:24:03,  4.04s/it]
  1%|          | 4873/569592 [4:07:16<592:45:41,  3.78s/it]
                                                           

  1%|          | 4873/569592 [4:07:16<592:45:41,  3.78s/it]
  1%|          | 4874/569592 [4:07:20<579:56:38,  3.70s/it]
                                                           

  1%|          | 4874/569592 [4:07:20<579:56:38,  3.70s/it]
  1%|          | 4875/569592 [4:07:24<634:41:08,  4.05s/it]
                                                           

  1%|          | 4875/569592 [4:07:24<634:41:08,  4.05s/it]
  1%|          | 4876/569592 [4:07:27<587:13:09,  3.74s/it]
                                                           

  1%|          | 4876/569592 [4:07:27<587:13:09,  3.74s/it]
  1%|          | 4877/569592 [4:07:31<593:10:05,  3.78s/it]
                                                           

  1%|          | 4877/569592 [4:07:31<593:10:05,  3.78s/it]
  1%|          | 4878/569592 [4:07:36<617:45:03,  3.94s/it]
                                                           

  1%|          | 4878/569592 [4:07:36<617:45:03,  3.94s/it]
  1%|          | 4879/569592 [4:07:37<482:29:01,  3.08s/it]
                                                           

  1%|          | 4879/569592 [4:07:37<482:29:01,  3.08s/it]
  1%|          | 4880/569592 [4:07:38<385:13:47,  2.46s/it]
                                                           

  1%|          | 4880/569592 [4:07:38<385:13:47,  2.46s/it]
  1%|          | 4881/569592 [4:07:43<507:14:28,  3.23s/it]
                                                           

  1%|          | 4881/569592 [4:07:43<507:14:28,  3.23s/it]
  1%|          | 4882/569592 [4:07:48<586:32:44,  3.74s/it]
                                                           

  1%|          | 4882/569592 [4:07:48<586:32:44,  3.74s/it]
  1%|          | 4883/569592 [4:07:51<550:41:45,  3.51s/it]
                                                           

  1%|          | 4883/569592 [4:07:51<550:41:45,  3.51s/it]
  1%|          | 4884/569592 [4:07:55<601:57:11,  3.84s/it]
                                                           

  1%|          | 4884/569592 [4:07:55<601:57:11,  3.84s/it]
  1%|          | 4885/569592 [4:07:59<578:41:16,  3.69s/it]
                                                           

  1%|          | 4885/569592 [4:07:59<578:41:16,  3.69s/it]
  1%|          | 4886/569592 [4:08:02<554:11:02,  3.53s/it]
                                                           

  1%|          | 4886/569592 [4:08:02<554:11:02,  3.53s/it]
  1%|          | 4887/569592 [4:08:07<630:30:09,  4.02s/it]
                                                           

  1%|          | 4887/569592 [4:08:07<630:30:09,  4.02s/it]
  1%|          | 4888/569592 [4:08:12<663:24:22,  4.23s/it]
                                                           

  1%|          | 4888/569592 [4:08:12<663:24:22,  4.23s/it]
  1%|          | 4889/569592 [4:08:16<680:10:05,  4.34s/it]
                                                           

  1%|          | 4889/569592 [4:08:16<680:10:05,  4.34s/it]
  1%|          | 4890/569592 [4:08:19<621:44:59,  3.96s/it]
                                                           

  1%|          | 4890/569592 [4:08:19<621:44:59,  3.96s/it]
  1%|          | 4891/569592 [4:08:22<575:13:13,  3.67s/it]
                                                           

  1%|          | 4891/569592 [4:08:22<575:13:13,  3.67s/it]
  1%|          | 4892/569592 [4:08:26<563:20:44,  3.59s/it]
                                                           

  1%|          | 4892/569592 [4:08:26<563:20:44,  3.59s/it]
  1%|          | 4893/569592 [4:08:27<436:50:06,  2.78s/it]
                                                           

  1%|          | 4893/569592 [4:08:27<436:50:06,  2.78s/it]
  1%|          | 4894/569592 [4:08:30<477:27:01,  3.04s/it]
                                                           

  1%|          | 4894/569592 [4:08:30<477:27:01,  3.04s/it]
  1%|          | 4895/569592 [4:08:33<485:08:02,  3.09s/it]
                                                           

  1%|          | 4895/569592 [4:08:33<485:08:02,  3.09s/it]
  1%|          | 4896/569592 [4:08:35<391:25:42,  2.50s/it]
                                                           

  1%|          | 4896/569592 [4:08:35<391:25:42,  2.50s/it]
  1%|          | 4897/569592 [4:08:35<318:26:39,  2.03s/it]
                                                           

  1%|          | 4897/569592 [4:08:36<318:26:39,  2.03s/it]
  1%|          | 4898/569592 [4:08:39<383:42:58,  2.45s/it]
                                                           

  1%|          | 4898/569592 [4:08:39<383:42:58,  2.45s/it]
  1%|          | 4899/569592 [4:08:40<314:29:52,  2.00s/it]
                                                           

  1%|          | 4899/569592 [4:08:40<314:29:52,  2.00s/it]
  1%|          | 4900/569592 [4:08:45<462:17:16,  2.95s/it]
                                                           

  1%|          | 4900/569592 [4:08:45<462:17:16,  2.95s/it]
  1%|          | 4901/569592 [4:08:50<563:39:40,  3.59s/it]
                                                           

  1%|          | 4901/569592 [4:08:50<563:39:40,  3.59s/it]
  1%|          | 4902/569592 [4:08:53<545:37:30,  3.48s/it]
                                                           

  1%|          | 4902/569592 [4:08:53<545:37:30,  3.48s/it]
  1%|          | 4903/569592 [4:08:54<425:49:37,  2.71s/it]
                                                           

  1%|          | 4903/569592 [4:08:54<425:49:37,  2.71s/it]
  1%|          | 4904/569592 [4:08:55<342:12:59,  2.18s/it]
                                                           

  1%|          | 4904/569592 [4:08:55<342:12:59,  2.18s/it]
  1%|          | 4905/569592 [4:08:56<285:18:28,  1.82s/it]
                                                           

  1%|          | 4905/569592 [4:08:56<285:18:28,  1.82s/it/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
]
  1%|          | 4906/569592 [4:08:57<244:27:57,  1.56s/it]
                                                           

  1%|          | 4906/569592 [4:08:57<244:27:57,  1.56s/it]
  1%|          | 4907/569592 [4:08:58<214:25:56,  1.37s/it]
                                                           

  1%|          | 4907/569592 [4:08:58<214:25:56,  1.37s/it]
  1%|          | 4908/569592 [4:08:59<196:14:03,  1.25s/it]
                                                           

  1%|          | 4908/569592 [4:09:00<196:14:03,  1.25s/it]
  1%|          | 4909/569592 [4:09:00<198:04:20,  1.26s/it]
                                                           

  1%|          | 4909/569592 [4:09:00<198:04:20,  1.26s/it]
  1%|          | 4910/569592 [4:09:03<245:02:38,  1.56s/it]
                                                           

  1%|          | 4910/569592 [4:09:03<245:02:38,  1.56s/it]
  1%|          | 4911/569592 [4:09:07<369:54:25,  2.36s/it]
                                                           

  1%|          | 4911/569592 [4:09:07<369:54:25,  2.36s/it]
  1%|          | 4912/569592 [4:09:09<347:42:03,  2.22s/it]
                                                           

  1%|          | 4912/569592 [4:09:09<347:42:03,  2.22s/it]
  1%|          | 4913/569592 [4:09:10<287:33:24,  1.83s/it]
                                                           

  1%|          | 4913/569592 [4:09:10<287:33:24,  1.83s/it]
  1%|          | 4914/569592 [4:09:12<330:14:35,  2.11s/it]
                                                           

  1%|          | 4914/569592 [4:09:12<330:14:35,  2.11s/it]
  1%|          | 4915/569592 [4:09:17<434:09:33,  2.77s/it]
                                                           

  1%|          | 4915/569592 [4:09:17<434:09:33,  2.77s/it]
  1%|          | 4916/569592 [4:09:19<400:02:27,  2.55s/it]
                                                           

  1%|          | 4916/569592 [4:09:19<400:02:27,  2.55s/it]
  1%|          | 4917/569592 [4:09:20<326:37:55,  2.08s/it]
                                                           

  1%|          | 4917/569592 [4:09:20<326:37:55,  2.08s/it]
  1%|          | 4918/569592 [4:09:23<385:44:19,  2.46s/it]
                                                           

  1%|          | 4918/569592 [4:09:23<385:44:19,  2.46s/it]
  1%|          | 4919/569592 [4:09:27<440:33:18,  2.81s/it]
                                                           

  1%|          | 4919/569592 [4:09:27<440:33:18,  2.81s/it]
  1%|          | 4920/569592 [4:09:29<401:00:34,  2.56s/it]
                                                           

  1%|          | 4920/569592 [4:09:29<401:00:34,  2.56s/it]
  1%|          | 4921/569592 [4:09:30<330:59:38,  2.11s/it]
                                                           

  1%|          | 4921/569592 [4:09:30<330:59:38,  2.11s/it]
  1%|          | 4922/569592 [4:09:33<390:26:12,  2.49s/it]
                                                           

  1%|          | 4922/569592 [4:09:33<390:26:12,  2.49s/it]
  1%|          | 4923/569592 [4:09:37<438:09:45,  2.79s/it]
                                                           

  1%|          | 4923/569592 [4:09:37<438:09:45,  2.79s/it]
  1%|          | 4924/569592 [4:09:40<462:11:22,  2.95s/it]
                                                           

  1%|          | 4924/569592 [4:09:40<462:11:22,  2.95s/it]
  1%|          | 4925/569592 [4:09:41<370:35:10,  2.36s/it]
                                                           

  1%|          | 4925/569592 [4:09:41<370:35:10,  2.36s/it]
  1%|          | 4926/569592 [4:09:44<385:39:56,  2.46s/it]
                                                           

  1%|          | 4926/569592 [4:09:44<385:39:56,  2.46s/it]
  1%|          | 4927/569592 [4:09:49<516:54:52,  3.30s/it]
                                                           

  1%|          | 4927/569592 [4:09:49<516:54:52,  3.30s/it]
  1%|          | 4928/569592 [4:09:50<408:10:42,  2.60s/it]
                                                           

  1%|          | 4928/569592 [4:09:50<408:10:42,  2.60s/it]
  1%|          | 4929/569592 [4:09:51<329:24:34,  2.10s/it]
                                                           

  1%|          | 4929/569592 [4:09:51<329:24:34,  2.10s/it]
  1%|          | 4930/569592 [4:09:55<407:26:08,  2.60s/it]
                                                           

  1%|          | 4930/569592 [4:09:55<407:26:08,  2.60s/it]
  1%|          | 4931/569592 [4:09:58<432:26:56,  2.76s/it]
                                                           

  1%|          | 4931/569592 [4:09:58<432:26:56,  2.76s/it]
  1%|          | 4932/569592 [4:09:59<369:11:11,  2.35s/it]
                                                           

  1%|          | 4932/569592 [4:09:59<369:11:11,  2.35s/it]
  1%|          | 4933/569592 [4:10:00<303:36:11,  1.94s/it]
                                                           

  1%|          | 4933/569592 [4:10:00<303:36:11,  1.94s/it]
  1%|          | 4934/569592 [4:10:06<477:57:55,  3.05s/it]
                                                           

  1%|          | 4934/569592 [4:10:06<477:57:55,  3.05s/it]
  1%|          | 4935/569592 [4:10:09<504:20:04,  3.22s/it]
                                                           

  1%|          | 4935/569592 [4:10:09<504:20:04,  3.22s/it]
  1%|          | 4936/569592 [4:10:10<400:00:30,  2.55s/it]
                                                           

  1%|          | 4936/569592 [4:10:10<400:00:30,  2.55s/it]
  1%|          | 4937/569592 [4:10:11<323:44:26,  2.06s/it]
                                                           

  1%|          | 4937/569592 [4:10:11<323:44:26,  2.06s/it]
  1%|          | 4938/569592 [4:10:15<389:53:25,  2.49s/it]
                                                           

  1%|          | 4938/569592 [4:10:15<389:53:25,  2.49s/it]
  1%|          | 4939/569592 [4:10:20<512:02:54,  3.26s/it]
                                                           

  1%|          | 4939/569592 [4:10:20<512:02:54,  3.26s/it]
  1%|          | 4940/569592 [4:10:21<405:15:33,  2.58s/it]
                                                           

  1%|          | 4940/569592 [4:10:21<405:15:33,  2.58s/it]
  1%|          | 4941/569592 [4:10:22<330:06:52,  2.10s/it]
                                                           

  1%|          | 4941/569592 [4:10:22<330:06:52,  2.10s/it]
  1%|          | 4942/569592 [4:10:26<434:28:30,  2.77s/it]
                                                           

  1%|          | 4942/569592 [4:10:26<434:28:30,  2.77s/it]
  1%|          | 4943/569592 [4:10:30<490:01:05,  3.12s/it]
                                                           

  1%|          | 4943/569592 [4:10:30<490:01:05,  3.12s/it]
  1%|          | 4944/569592 [4:10:31<388:38:35,  2.48s/it]
                                                           

  1%|          | 4944/569592 [4:10:31<388:38:35,  2.48s/it]
  1%|          | 4945/569592 [4:10:36<520:59:16,  3.32s/it]
                                               /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92591040 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
            

  1%|          | 4945/569592 [4:10:36<520:59:16,  3.32s/it]
  1%|          | 4946/569592 [4:10:37<415:01:11,  2.65s/it]
                                                           

  1%|          | 4946/569592 [4:10:37<415:01:11,  2.65s/it]
  1%|          | 4947/569592 [4:10:38<338:59:39,  2.16s/it]
                                                           

  1%|          | 4947/569592 [4:10:38<338:59:39,  2.16s/it]
  1%|          | 4948/569592 [4:10:40<305:05:41,  1.95s/it]
                                                           

  1%|          | 4948/569592 [4:10:40<305:05:41,  1.95s/it]
  1%|          | 4949/569592 [4:10:45<452:27:25,  2.88s/it]
                                                           

  1%|          | 4949/569592 [4:10:45<452:27:25,  2.88s/it]
  1%|          | 4950/569592 [4:10:47<417:41:36,  2.66s/it]
                                                           

  1%|          | 4950/569592 [4:10:47<417:41:36,  2.66s/it]
  1%|          | 4951/569592 [4:10:50<450:41:15,  2.87s/it]
                                                           

  1%|          | 4951/569592 [4:10:50<450:41:15,  2.87s/it]
  1%|          | 4952/569592 [4:10:54<483:04:07,  3.08s/it]
                                                           

  1%|          | 4952/569592 [4:10:54<483:04:07,  3.08s/it]
  1%|          | 4953/569592 [4:10:57<498:03:49,  3.18s/it]
                                                           

  1%|          | 4953/569592 [4:10:57<498:03:49,  3.18s/it]
  1%|          | 4954/569592 [4:11:01<525:44:46,  3.35s/it]
                                                           

  1%|          | 4954/569592 [4:11:01<525:44:46,  3.35s/it]
  1%|          | 4955/569592 [4:11:06<590:00:10,  3.76s/it]
                                                           

  1%|          | 4955/569592 [4:11:06<590:00:10,  3.76s/it]
  1%|          | 4956/569592 [4:11:09<573:12:58,  3.65s/it]
                                                           

  1%|          | 4956/569592 [4:11:09<573:12:58,  3.65s/it]
  1%|          | 4957/569592 [4:11:12<547:12:52,  3.49s/it]
                                                           

  1%|          | 4957/569592 [4:11:12<547:12:52,  3.49s/it]
  1%|          | 4958/569592 [4:11:16<548:35:17,  3.50s/it]
                                                           

  1%|          | 4958/569592 [4:11:16<548:35:17,  3.50s/it]
  1%|          | 4959/569592 [4:11:20<566:31:45,  3.61s/it]
                                                           

  1%|          | 4959/569592 [4:11:20<566:31:45,  3.61s/it]
  1%|          | 4960/569592 [4:11:23<555:22:45,  3.54s/it]
                                                           

  1%|          | 4960/569592 [4:11:23<555:22:45,  3.54s/it]
  1%|          | 4961/569592 [4:11:26<536:10:25,  3.42s/it]
                                                           

  1%|          | 4961/569592 [4:11:26<536:10:25,  3.42s/it]
  1%|          | 4962/569592 [4:11:31<594:56:53,  3.79s/it]
                                          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                 

  1%|          | 4962/569592 [4:11:31<594:56:53,  3.79s/it]
  1%|          | 4963/569592 [4:11:35<610:58:07,  3.90s/it]
                                                           

  1%|          | 4963/569592 [4:11:35<610:58:07,  3.90s/it]
  1%|          | 4964/569592 [4:11:38<576:26:08,  3.68s/it]
                                                           

  1%|          | 4964/569592 [4:11:38<576:26:08,  3.68s/it]
  1%|          | 4965/569592 [4:11:43<628:53:25,  4.01s/it]
                                                           

  1%|          | 4965/569592 [4:11:43<628:53:25,  4.01s/it]
  1%|          | 4966/569592 [4:11:48<657:22:58,  4.19s/it]
                                                           

  1%|          | 4966/569592 [4:11:48<657:22:58,  4.19s/it]
  1%|          | 4967/569592 [4:11:51<634:40:03,  4.05s/it]
                                                           

  1%|          | 4967/569592 [4:11:51<634:40:03,  4.05s/it]
  1%|          | 4968/569592 [4:11:52<486:08:00,  3.10s/it]
                                                           

  1%|          | 4968/569592 [4:11:52<486:08:00,  3.10s/it]
  1%|          | 4969/569592 [4:11:56<525:27:14,  3.35s/it]
                                                           

  1%|          | 4969/569592 [4:11:56<525:27:14,  3.35s/it]
  1%|          | 4970/569592 [4:11:59<526:12:58,  3.36s/it]
                                                           

  1%|          | 4970/569592 [4:12:00<526:12:58,  3.36s/it]
  1%|          | 4971/569592 [4:12:03<544:16:01,  3.47s/it]
                                                           

  1%|          | 4971/569592 [4:12:03<544:16:01,  3.47s/it]
  1%|          | 4972/569592 [4:12:06<522:25:06,  3.33s/it]
                                                           

  1%|          | 4972/569592 [4:12:06<522:25:06,  3.33s/it]
  1%|          | 4973/569592 [4:12:11<585:59:41,  3.74s/it]
                                                           

  1%|          | 4973/569592 [4:12:11<585:59:41,  3.74s/it]
  1%|          | 4974/569592 [4:12:14<559:39:29,  3.57s/it]
                                                           

  1%|          | 4974/569592 [4:12:14<559:39:29,  3.57s/it]
  1%|          | 4975/569592 [4:12:17<543:53:41,  3.47s/it]
                                                           

  1%|          | 4975/569592 [4:12:17<543:53:41,  3.47s/it]
  1%|          | 4976/569592 [4:12:20<526:57:46,  3.36s/it]
                                                           

  1%|          | 4976/569592 [4:12:20<526:57:46,  3.36s/it]
  1%|          | 4977/569592 [4:12:26<613:20:30,  3.91s/it]
                                                           

  1%|          | 4977/569592 [4:12:26<613:20:30,  3.91s/it]
  1%|          | 4978/569592 [4:12:29<568:44:16,  3.63s/it]
                                                           

  1%|          | 4978/569592 [4:12:29<568:44:16,  3.63s/it]
  1%|          | 4979/569592 [4:12:33<592:33:37,  3.78s/it]
                                                           

  1%|          | 4979/569592 [4:12:33<592:33:37,  3.78s/it]
  1%|          | 4980/569592 [4:12:38<639:56:51,  4.08s/it]
                                                           

  1%|          | 4980/569592 [4:12:38<639:56:51,  4.08s/it]
  1%|          | 4981/569592 [4:12:42<666:58:06,  4.25s/it]
                                                           

  1%|          | 4981/569592 [4:12:42<666:58:06,  4.25s/it]
  1%|          | 4982/569592 [4:12:46<631:06:58,  4.02s/it]
                                                           

  1%|          | 4982/569592 [4:12:46<631:06:58,  4.02s/it]
  1%|          | 4983/569592 [4:12:50<656:22:58,  4.19s/it]
                                                           

  1%|          | 4983/569592 [4:12:50<656:22:58,  4.19s/it]
  1%|          | 4984/569592 [4:12:51<502:28:14,  3.20s/it]
                                                           

  1%|          | 4984/569592 [4:12:51<502:28:14,  3.20s/it]
  1%|          | 4985/569592 [4:12:54<509:05:03,  3.25s/it]
                                                           

  1%|          | 4985/569592 [4:12:55<509:05:03,  3.25s/it]
  1%|          | 4986/569592 [4:12:58<511:03:10,  3.26s/it]
                                                           

  1%|          | 4986/569592 [4:12:58<511:03:10,  3.26s/it]
  1%|          | 4987/569592 [4:13:01<515:10:33,  3.28s/it]
                                                           

  1%|          | 4987/569592 [4:13:01<515:10:33,  3.28s/it]
  1%|          | 4988/569592 [4:13:06<588:51:16,  3.75s/it]
                                                           

  1%|          | 4988/569592 [4:13:06<588:51:16,  3.75s/it]
  1%|          | 4989/569592 [4:13:10<602:40:42,  3.84s/it]
                                                           

  1%|          | 4989/569592 [4:13:10<602:40:42,  3.84s/it]
  1%|          | 4990/569592 [4:13:13<576:57:01,  3.68s/it]
                                                           

  1%|          | 4990/569592 [4:13:13<576:57:01,  3.68s/it]
  1%|          | 4991/569592 [4:13:18<601:36:41,  3.84s/it]
                                                           

  1%|          | 4991/569592 [4:13:18<601:36:41,  3.84s/it]
  1%|          | 4992/569592 [4:13:22<636:47:03,  4.06s/it]
                                                           

  1%|          | 4992/569592 [4:13:22<636:47:03,  4.06s/it]
  1%|          | 4993/569592 [4:13:26<650:22:00,  4.15s/it]
                                                           

  1%|          | 4993/569592 [4:13:26<650:22:00,  4.15s/it]
  1%|          | 4994/569592 [4:13:30<604:28:53,  3.85s/it]
                                                           

  1%|          | 4994/569592 [4:13:30<604:28:53,  3.85s/it]
  1%|          | 4995/569592 [4:13:34<650:23:05,  4.15s/it]
                                                           

  1%|          | 4995/569592 [4:13:34<650:23:05,  4.15s/it]
  1%|          | 4996/569592 [4:13:38<620:11:43,  3.95s/it]
                                                           

  1%|          | 4996/569592 [4:13:38<620:11:43,  3.95s/it]
  1%|          | 4997/569592 [4:13:41<569:54:53,  3.63s/it]
                                                           

  1%|          | 4997/569592 [4:13:41<569:54:53,  3.63s/it]
  1%|          | 4998/569592 [4:13:42<442:02:28,  2.82s/it]
                                                           

  1%|          | 4998/569592 [4:13:42<442:02:28,  2.82s/it]
  1%|          | 4999/569592 [4:13:47<539:34:45,  3.44s/it]
                                                           

  1%|          | 4999/569592 [4:13:47<539:34:45,  3.44s/it]
  1%|          | 5000/569592 [4:13:54<726:11:56,  4.63s/it]
                                                           

  1%|          | 5000/569592 [4:13:54<726:11:56,  4.63s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-5000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-5000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-5000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-5000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-5000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-5000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-4000] due to args.save_total_limit

  1%|          | 5001/569592 [4:15:54<6128:19:54, 39.08s/it]
                                                            

  1%|          | 5001/569592 [4:15:54<6128:19:54, 39.08s/it]
  1%|          | 5002/569592 [4:15:57<4444:18:08, 28.34s/it]
                                                            

  1%|          | 5002/569592 [4:15:57<4444:18:08, 28.34s/it]
  1%|          | 5003/569592 [4:15:58<3152:51:31, 20.10s/it]
                                                            

  1%|          | 5003/569592 [4:15:58<3152:51:31, 20.10s/it]
  1%|          | 5004/569592 [4:15:59<2252:27:17, 14.36s/it]
                                                            

  1%|          | 5004/569592 [4:15:59<2252:27:17, 14.36s/it]
  1%|          | 5005/569592 [4:16:02<1737:06:02, 11.08s/it]
                                                            

  1%|          | 5005/569592 [4:16:02<1737:06:02, 11.08s/it]
  1%|          | 5006/569592 [4:16:07<1425:51:40,  9.09s/it]
                                                            

  1%|          | 5006/569592 [4:16:07<1425:51:40,  9.09s/it]
  1%|          | 5007/569592 [4:16:11<1190:32:47,  7.59s/it]
                                                            

  1%|          | 5007/569592 [4:16:11<1190:32:47,  7.59s/it]
  1%|          | 5008/569592 [4:16:15<1050:33:06,  6.70s/it]
                                                            

  1%|          | 5008/569592 [4:16:15<1050:33:06,  6.70s/it]
  1%|          | 5009/569592 [4:16:16<777:24:39,  4.96s/it] 
                                                           

  1%|          | 5009/569592 [4:16:16<777:24:39,  4.96s/it]
  1%|          | 5010/569592 [4:16:20<723:10:23,  4.61s/it]
                                                           

  1%|          | 5010/569592 [4:16:20<723:10:23,  4.61s/it]
  1%|          | 5011/569592 [4:16:24<682:12:10,  4.35s/it]
                                                           

  1%|          | 5011/569592 [4:16:24<682:12:10,  4.35s/it]
  1%|          | 5012/569592 [4:16:27<628:24:52,  4.01s/it]
                                                           

  1%|          | 5012/569592 [4:16:27<628:24:52,  4.01s/it]
  1%|          | 5013/569592 [4:16:28<485:35:43,  3.10s/it]
                                                           

  1%|          | 5013/569592 [4:16:28<485:35:43,  3.10s/it]
  1%|          | 5014/569592 [4:16:29<383:54:57,  2.45s/it]
                                                           

  1%|          | 5014/569592 [4:16:29<383:54:57,  2.45s/it]
  1%|          | 5015/569592 [4:16:33<449:59:37,  2.87s/it]
                                                           

  1%|          | 5015/569592 [4:16:33<449:59:37,  2.87s/it]
  1%|          | 5016/569592 [4:16:38<565:16:49,  3.60s/it]
                                                           

  1%|          | 5016/569592 [4:16:38<565:16:49,  3.60s/it]
  1%|          | 5017/569592 [4:16:43<617:44:06,  3.94s/it]
                                                           

  1%|          | 5017/569592 [4:16:43<617:44:06,  3.94s/it]
  1%|          | 5018/569592 [4:16:46<574:48:19,  3.67s/it]
                                                           

  1%|          | 5018/569592 [4:16:46<574:48:19,  3.67s/it]
  1%|          | 5019/569592 [4:16:47<444:18:54,  2.83s/it]
                                                           

  1%|          | 5019/569592 [4:16:47<444:18:54,  2.83s/it]
  1%|          | 5020/569592 [4:16:48<355:15:11,  2.27s/it]
                                                           

  1%|          | 5020/569592 [4:16:48<355:15:11,  2.27s/it]
  1%|          | 5021/569592 [4:16:49<294:41:52,  1.88s/it]
                                                           

  1%|          | 5021/569592 [4:16:49<294:41:52,  1.88s/it]
  1%|          | 5022/569592 [4:16:49<251:22:57,  1.60s/it]
                                                           

  1%|          | 5022/569592 [4:16:49<251:22:57,  1.60s/it]
  1%|          | 5023/569592 [4:16:50<222:49:21,  1.42s/it]
                                                           

  1%|          | 5023/569592 [4:16:50<222:49:21,  1.42s/it]
  1%|          | 5024/569592 [4:16:51<204:29:48,  1.30s/it]
                                                           

  1%|          | 5024/569592 [4:16:51<204:29:48,  1.30s/it]
  1%|          | 5025/569592 [4:16:52<187:10:58,  1.19s/it]
                                                           

  1%|          | 5025/569592 [4:16:52<187:10:58,  1.19s/it]
  1%|          | 5026/569592 [4:16:56<293:20:37,  1.87s/it]
                                                           

  1%|          | 5026/569592 [4:16:56<293:20:37,  1.87s/it]
  1%|          | 5027/569592 [4:16:59<374:55:31,  2.39s/it]
                                                           

  1%|          | 5027/569592 [4:16:59<374:55:31,  2.39s/it]
  1%|          | 5028/569592 [4:17:01<313:06:00,  2.00s/it]
                                                           

  1%|          | 5028/569592 [4:17:01<313:06:00,  2.00s/it]
  1%|          | 5029/569592 [4:17:02<264:01:03,  1.68s/it]
                                                           

  1%|          | 5029/569592 [4:17:02<264:01:03,  1.68s/it]
  1%|          | 5030/569592 [4:17:06<390:02:26,  2.49s/it]
                                                           

  1%|          | 5030/569592 [4:17:06<390:02:26,  2.49s/it]
  1%|          | 5031/569592 [4:17:10<489:27:24,  3.12s/it]
                                                           

  1%|          | 5031/569592 [4:17:10<489:27:24,  3.12s/it]
  1%|          | 5032/569592 [4:17:12<392:20:57,  2.50s/it]
                                                           

  1%|          | 5032/569592 [4:17:12<392:20:57,  2.50s/it]
  1%|          | 5033/569592 [4:17:13<321:40:14,  2.05s/it]
                                                           

  1%|          | 5033/569592 [4:17:13<321:40:14,  2.05s/it]
  1%|          | 5034/569592 [4:17:17<437:06:53,  2.79s/it]
                                                           

  1%|          | 5034/569592 [4:17:17<437:06:53,  2.79s/it]
  1%|          | 5035/569592 [4:17:19<420:38:04,  2.68s/it]
                                                           

  1%|          | 5035/569592 [4:17:19<420:38:04,  2.68s/it]
  1%|          | 5036/569592 [4:17:21<347:46:48,  2.22s/it]
                                                           

  1%|          | 5036/569592 [4:17:21<347:46:48,  2.22s/it]
  1%|          | 5037/569592 [4:17:22<289:43:23,  1.85s/it]
                                                           

  1%|          | 5037/569592 [4:17:22<289:43:23,  1.85s/it]
  1%|          | 5038/569592 [4:17:27<473:25:10,  3.02s/it]
                                                           

  1%|          | 5038/569592 [4:17:27<473:25:10,  3.02s/it]
  1%|          | 5039/569592 [4:17:30<476:26:54,  3.04s/it]
                                                           

  1%|          | 5039/569592 [4:17:30<476:26:54,  3.04s/it]
  1%|          | 5040/569592 [4:17:35<530:38:27,  3.38s/it]
                                                           

  1%|          | 5040/569592 [4:17:35<530:38:27,  3.38s/it]
  1%|          | 5041/569592 [4:17:36<417:27:48,  2.66s/it]
                                                           

  1%|          | 5041/569592 [4:17:36<417:27:48,  2.66s/it]
  1%|          | 5042/569592 [4:17:37<336:42:23,  2.15s/it]
                                                           

  1%|          | 5042/569592 [4:17:37<336:42:23,  2.15s/it]
  1%|          | 5043/569592 [4:17:42<487:15:27,  3.11s/it]
                                                           

  1%|          | 5043/569592 [4:17:42<487:15:27,  3.11s/it]
  1%|          | 5044/569592 [4:17:43<387:29:38,  2.47s/it]
                                                           

  1%|          | 5044/569592 [4:17:43<387:29:38,  2.47s/it]
  1%|          | 5045/569592 [4:17:44<315:59:33,  2.02s/it]
                                                           

  1%|          | 5045/569592 [4:17:44<315:59:33,  2.02s/it]
  1%|          | 5046/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93236300 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/569592 [4:17:48<410:57:57,  2.62s/it]
                                                           

  1%|          | 5046/569592 [4:17:48<410:57:57,  2.62s/it]
  1%|          | 5047/569592 [4:17:51<421:48:09,  2.69s/it]
                                                           

  1%|          | 5047/569592 [4:17:51<421:48:09,  2.69s/it]
  1%|          | 5048/569592 [4:17:52<360:31:54,  2.30s/it]
                                                           

  1%|          | 5048/569592 [4:17:52<360:31:54,  2.30s/it]
  1%|          | 5049/569592 [4:17:56<423:45:36,  2.70s/it]
                                                           

  1%|          | 5049/569592 [4:17:56<423:45:36,  2.70s/it]
  1%|          | 5050/569592 [4:17:58<419:29:27,  2.68s/it]
                                                           

  1%|          | 5050/569592 [4:17:58<419:29:27,  2.68s/it]
  1%|          | 5051/569592 [4:18:01<413:58:28,  2.64s/it]
                                                           

  1%|          | 5051/569592 [4:18:01<413:58:28,  2.64s/it]
  1%|          | 5052/569592 [4:18:03<370:01:53,  2.36s/it]
                                                           

  1%|          | 5052/569592 [4:18:03<370:01:53,  2.36s/it]
  1%|          | 5053/569592 [4:18:04<304:59:05,  1.94s/it]
                                                           

  1%|          | 5053/569592 [4:18:04<304:59:05,  1.94s/it]
  1%|          | 5054/569592 [4:18:09<452:58:02,  2.89s/it]
                                                           

  1%|          | 5054/569592 [4:18:09<452:58:02,  2.89s/it]
  1%|          | 5055/569592 [4:18:11<422:53:39,  2.70s/it]
                                                           

  1%|          | 5055/569592 [4:18:11<422:53:39,  2.70s/it]
  1%|          | 5056/569592 [4:18:13<399:08:26,  2.55s/it]
                                                           

  1%|          | 5056/569592 [4:18:13<399:08:26,  2.55s/it]
  1%|          | 5057/569592 [4:18:14<326:50:09,  2.08s/it]
                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91867167 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                         

  1%|          | 5057/569592 [4:18:14<326:50:09,  2.08s/it]
  1%|          | 5058/569592 [4:18:19<460:50:37,  2.94s/it]
                                                           

  1%|          | 5058/569592 [4:18:19<460:50:37,  2.94s/it]
  1%|          | 5059/569592 [4:18:24<555:14:06,  3.54s/it]
                                                           

  1%|          | 5059/569592 [4:18:24<555:14:06,  3.54s/it]
  1%|          | 5060/569592 [4:18:29<619:46:33,  3.95s/it]
                                                           

  1%|          | 5060/569592 [4:18:29<619:46:33,  3.95s/it]
  1%|          | 5061/569592 [4:18:30<477:40:02,  3.05s/it]
                                                           

  1%|          | 5061/569592 [4:18:30<477:40:02,  3.05s/it]
  1%|          | 5062/569592 [4:18:31<379:04:56,  2.42s/it]
                                                           

  1%|          | 5062/569592 [4:18:31<379:04:56,  2.42s/it]
  1%|          | 5063/569592 [4:18:35<445:01:44,  2.84s/it]
                                                           

  1%|          | 5063/569592 [4:18:35<445:01:44,  2.84s/it]
  1%|          | 5064/569592 [4:18:36<356:23:38,  2.27s/it]
                                                           

  1%|          | 5064/569592 [4:18:36<356:23:38,  2.27s/it]
  1%|          | 5065/569592 [4:18:40<480:37:21,  3.06s/it]
                                                           

  1%|          | 5065/569592 [4:18:40<480:37:21,  3.06s/it]
  1%|          | 5066/569592 [4:18:41<380:18:29,  2.43s/it]
                                                           

  1%|          | 5066/569592 [4:18:41<380:18:29,  2.43s/it]
  1%|          | 5067/569592 [4:18:45<451:47:47,  2.88s/it]
                                                           

  1%|          | 5067/569592 [4:18:45<451:47:47,  2.88s/it]
  1%|          | 5068/569592 [4:18:49<480:04:02,  3.06s/it]
                                                           

  1%|          | 5068/569592 [4:18:49<480:04:02,  3.06s/it]
  1%|          | 5069/569592 [4:18:52<498:52:22,  3.18s/it]
                                                           

  1%|          | 5069/569592 [4:18:52<498:52:22,  3.18s/it]
  1%|          | 5070/569592 [4:18:57<592:19:30,  3.78s/it]
                                                           

  1%|          | 5070/569592 [4:18:57<592:19:30,  3.78s/it]
  1%|          | 5071/569592 [4:19:02<633:13:11,  4.04s/it]
                                                           

  1%|          | 5071/569592 [4:19:03<633:13:11,  4.04s/it]
  1%|          | 5072/569592 [4:19:04<523:33:53,  3.34s/it]
                                                           

  1%|          | 5072/569592 [4:19:04<523:33:53,  3.34s/it]
  1%|          | 5073/569592 [4:19:07<530:25:59,  3.38s/it]
                                                           

  1%|          | 5073/569592 [4:19:07<530:25:59,  3.38s/it]
  1%|          | 5074/569592 [4:19:11<565:52:17,  3.61s/it]
             /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                              

  1%|          | 5074/569592 [4:19:11<565:52:17,  3.61s/it]
  1%|          | 5075/569592 [4:19:15<578:00:50,  3.69s/it]
                                                           

  1%|          | 5075/569592 [4:19:15<578:00:50,  3.69s/it]
  1%|          | 5076/569592 [4:19:19<589:34:16,  3.76s/it]
                                                           

  1%|          | 5076/569592 [4:19:19<589:34:16,  3.76s/it]
  1%|          | 5077/569592 [4:19:24<623:56:18,  3.98s/it]
                                                           

  1%|          | 5077/569592 [4:19:24<623:56:18,  3.98s/it]
  1%|          | 5078/569592 [4:19:28<641:39:56,  4.09s/it]
                                                           

  1%|          | 5078/569592 [4:19:28<641:39:56,  4.09s/it]
  1%|          | 5079/569592 [4:19:29<490:35:55,  3.13s/it]
                                                           

  1%|          | 5079/569592 [4:19:29<490:35:55,  3.13s/it]
  1%|          | 5080/569592 [4:19:33<555:36:28,  3.54s/it]
                                                           

  1%|          | 5080/569592 [4:19:33<555:36:28,  3.54s/it]
  1%|          | 5081/569592 [4:19:38<610:01:02,  3.89s/it]
                                                           

  1%|          | 5081/569592 [4:19:38<610:01:02,  3.89s/it]
  1%|          | 5082/569592 [4:19:39<476:45:18,  3.04s/it]
                                                           

  1%|          | 5082/569592 [4:19:39<476:45:18,  3.04s/it]
  1%|          | 5083/569592 [4:19:40<376:51:11,  2.40s/it]
                                                           

  1%|          | 5083/569592 [4:19:40<376:51:11,  2.40s/it]
  1%|          | 5084/569592 [4:19:45<488:41:21,  3.12s/it]
                                                           

  1%|          | 5084/569592 [4:19:45<488:41:21,  3.12s/it]
  1%|          | 5085/569592 [4:19:46<386:36:16,  2.47s/it]
                                                           

  1%|          | 5085/569592 [4:19:46<386:36:16,  2.47s/it]
  1%|          | 5086/569592 [4:19:50<465:01:34,  2.97s/it]
                                                           

  1%|          | 5086/569592 [4:19:50<465:01:34,  2.97s/it]
  1%|          | 5087/569592 [4:19:54<524:31:48,  3.35s/it]
                                                           

  1%|          | 5087/569592 [4:19:54<524:31:48,  3.35s/it]
  1%|          | 5088/569592 [4:19:58<546:41:09,  3.49s/it]
                                                           

  1%|          | 5088/569592 [4:19:58<546:41:09,  3.49s/it]
  1%|          | 5089/569592 [4:20:01<542:09:12,  3.46s/it]
                                                           

  1%|          | 5089/569592 [4:20:01<542:09:12,  3.46s/it]
  1%|          | 5090/569592 [4:20:02<423:00:24,  2.70s/it]
                                                           

  1%|          | 5090/569592 [4:20:02<423:00:24,  2.70s/it]
  1%|          | 5091/569592 [4:20:06<479:53:50,  3.06s/it]
                                                           

  1%|          | 5091/569592 [4:20:06<479:53:50,  3.06s/it]
  1%|          | 5092/569592 [4:20:10<513:10:27,  3.27s/it]
                                                           

  1%|          | 5092/569592 [4:20:10<513:10:27,  3.27s/it]
  1%|          | 5093/569592 [4:20:15<599:06:40,  3.82s/it]
                                                           

  1%|          | 5093/569592 [4:20:15<599:06:40,  3.82s/it]
  1%|          | 5094/569592 [4:20:19<587:36:25,  3.75s/it]
                                                           

  1%|          | 5094/569592 [4:20:19<587:36:25,  3.75s/it]
  1%|          | 5095/569592 [4:20:24<639:28:06,  4.08s/it]
                                                           

  1%|          | 5095/569592 [4:20:24<639:28:06,  4.08s/it]
  1%|          | 5096/569592 [4:20:28<644:34:18,  4.11s/it]
                                                           

  1%|          | 5096/569592 [4:20:28<644:34:18,  4.11s/it]
  1%|          | 5097/569592 [4:20:32<637:35:30,  4.07s/it]
                                                           

  1%|          | 5097/569592 [4:20:32<637:35:30,  4.07s/it]
  1%|          | 5098/569592 [4:20:33<487:45:58,  3.11s/it]
                                                           

  1%|          | 5098/569592 [4:20:33<487:45:58,  3.11s/it]
  1%|          | 5099/569592 [4:20:36<516:19:56,  3.29s/it]
                                                           

  1%|          | 5099/569592 [4:20:36<516:19:56,  3.29s/it]
  1%|          | 5100/569592 [4:20:40<545:58:31,  3.48s/it]
                                                           

  1%|          | 5100/569592 [4:20:40<545:58:31,  3.48s/it]
  1%|          | 5101/569592 [4:20:41<426:37:07,  2.72s/it]
                                                           

  1%|          | 5101/569592 [4:20:41<426:37:07,  2.72s/it]
  1%|          | 5102/569592 [4:20:46<529:34:41,  3.38s/it]
                                                           

  1%|          | 5102/569592 [4:20:46<529:34:41,  3.38s/it]
  1%|          | 5103/569592 [4:20:50<559:02:38,  3.57s/it]
                                                           

  1%|          | 5103/569592 [4:20:50<559:02:38,  3.57s/it]
  1%|          | 5104/569592 [4:20:54<570:20:16,  3.64s/it]
                                                           

  1%|          | 5104/569592 [4:20:54<570:20:16,  3.64s/it]
  1%|          | 5105/569592 [4:20:57<558:50:01,  3.56s/it]
                                                           

  1%|          | 5105/569592 [4:20:57<558:50:01,  3.56s/it]
  1%|          | 5106/569592 [4:21:01<566:09:35,  3.61s/it]
                                                           

  1%|          | 5106/569592 [4:21:01<566:09:35,  3.61s/it]
  1%|          | 5107/569592 [4:21:04<547:25:50,  3.49s/it]
                                                           

  1%|          | 5107/569592 [4:21:04<547:25:50,  3.49s/it]
  1%|          | 5108/569592 [4:21:08<550:51:46,  3.51s/it]
                                                           

  1%|          | 5108/569592 [4:21:08<550:51:46,  3.51s/it]
  1%|          | 5109/569592 [4:21:09<430:48:02,  2.75s/it]
                                                           

  1%|          | 5109/569592 [4:21:09<430:48:02,  2.75s/it]
  1%|          | 5110/569592 [4:21:12<460:20:24,  2.94s/it]
                                                           

  1%|          | 5110/569592 [4:21:12<460:20:24,  2.94s/it]
  1%|          | 5111/569592 [4:21:17<554:22:52,  3.54s/it]
                                                           

  1%|          | 5111/569592 [4:21:17<554:22:52,  3.54s/it]
  1%|          | 5112/569592 [4:21:22<621:30:28,  3.96s/it]
                                                           

  1%|          | 5112/569592 [4:21:22<621:30:28,  3.96s/it]
  1%|          | 5113/569592 [4:21:26<598:22:00,  3.82s/it]
                                                           

  1%|          | 5113/569592 [4:21:26<598:22:00,  3.82s/it]
  1%|          | 5114/569592 [4:21:30<642:10:53,  4.10s/it]
                                                           

  1%|          | 5114/569592 [4:21:30<642:10:53,  4.10s/it]
  1%|          | 5115/569592 [4:21:33<598:05:34,  3.81s/it]
                                                           

  1%|          | 5115/569592 [4:21:33<598:05:34,  3.81s/it]
  1%|          | 5116/569592 [4:21:37<594:05:46,  3.79s/it]
                                                           

  1%|          | 5116/569592 [4:21:37<594:05:46,  3.79s/it]
  1%|          | 5117/569592 [4:21:42<648:19:40,  4.13s/it]
                                                           

  1%|          | 5117/569592 [4:21:42<648:19:40,  4.13s/it]
  1%|          | 5118/569592 [4:21:43<494:27:50,  3.15s/it]
                                                           

  1%|          | 5118/569592 [4:21:43<494:27:50,  3.15s/it]
  1%|          | 5119/569592 [4:21:46<490:21:59,  3.13s/it]
                                                           

  1%|          | 5119/569592 [4:21:46<490:21:59,  3.13s/it]
  1%|          | 5120/569592 [4:21:51<569:18:25,  3.63s/it]
                                                           

  1%|          | 5120/569592 [4:21:51<569:18:25,  3.63s/it]
  1%|          | 5121/569592 [4:21:55<580:55:14,  3.70s/it]
                                                           

  1%|          | 5121/569592 [4:21:55<580:55:14,  3.70s/it]
  1%|          | 5122/569592 [4:21:58<556:35:23,  3.55s/it]
                                                           

  1%|          | 5122/569592 [4:21:58<556:35:23,  3.55s/it]
  1%|          | 5123/569592 [4:22:01<545:52:48,  3.48s/it]
                                                           

  1%|          | 5123/569592 [4:22:01<545:52:48,  3.48s/it]
  1%|          | 5124/569592 [4:22:05<538:33:13,  3.43s/it]
                                                           

  1%|          | 5124/569592 [4:22:05<538:33:13,  3.43s/it]
  1%|          | 5125/569592 [4:22:08<537:24:10,  3.43s/it]
                                                           

  1%|          | 5125/569592 [4:22:08<537:24:10,  3.43s/it]
  1%|          | 5126/569592 [4:22:09<419:24:35,  2.67s/it]
                                                           

  1%|          | 5126/569592 [4:22:09<419:24:35,  2.67s/it]
  1%|          | 5127/569592 [4:22:10<337:38:05,  2.15s/it]
                                                           

  1%|          | 5127/569592 [4:22:10<337:38:05,  2.15s/it]
  1%|          | 5128/569592 [4:22:14<415:43:23,  2.65s/it]
                                                           

  1%|          | 5128/569592 [4:22:14<415:43:23,  2.65s/it]
  1%|          | 5129/569592 [4:22:15<337:34:37,  2.15s/it]
                                                           

  1%|          | 5129/569592 [4:22:15<337:34:37,  2.15s/it]
  1%|          | 5130/569592 [4:22:16<293:18:31,  1.87s/it]
                                                           

  1%|          | 5130/569592 [4:22:16<293:18:31,  1.87s//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
it]
  1%|          | 5131/569592 [4:22:19<367:07:42,  2.34s/it]
                                                           

  1%|          | 5131/569592 [4:22:19<367:07:42,  2.34s/it]
  1%|          | 5132/569592 [4:22:24<473:25:55,  3.02s/it]
                                                           

  1%|          | 5132/569592 [4:22:24<473:25:55,  3.02s/it]
  1%|          | 5133/569592 [4:22:25<375:48:04,  2.40s/it]
                                                           

  1%|          | 5133/569592 [4:22:25<375:48:04,  2.40s/it]
  1%|          | 5134/569592 [4:22:30<494:09:02,  3.15s/it]
                                                           

  1%|          | 5134/569592 [4:22:30<494:09:02,  3.15s/it]
  1%|          | 5135/569592 [4:22:31<389:08:21,  2.48s/it]
                                                           

  1%|          | 5135/569592 [4:22:31<389:08:21,  2.48s/it]
  1%|          | 5136/569592 [4:22:32<325:00:11,  2.07s/it]
                                                           

  1%|          | 5136/569592 [4:22:32<325:00:11,  2.07s/it]
  1%|          | 5137/569592 [4:22:33<271:24:58,  1.73s/it]
                                                           

  1%|          | 5137/569592 [4:22:33<271:24:58,  1.73s/it]
  1%|          | 5138/569592 [4:22:34<235:03:30,  1.50s/it]
                                                           

  1%|          | 5138/569592 [4:22:34<235:03:30,  1.50s/it]
  1%|          | 5139/569592 [4:22:35<208:14:06,  1.33s/it]
                                                           

  1%|          | 5139/569592 [4:22:35<208:14:06,  1.33s/it]
  1%|          | 5140/569592 [4:22:36<191:29:19,  1.22s/it]
                                                           

  1%|          | 5140/569592 [4:22:36<191:29:19,  1.22s/it]
  1%|          | 5141/569592 [4:22:38<232:24:11,  1.48s/it]
                                                           

  1%|          | 5141/569592 [4:22:38<232:24:11,  1.48s/it]
  1%|          | 5142/569592 [4:22:43<396:33:19,  2.53s/it]
                                                           

  1%|          | 5142/569592 [4:22:43<396:33:19,  2.53s/it]
  1%|          | 5143/569592 [4:22:45<371:28:37,  2.37s/it]
                                                           

  1%|          | 5143/569592 [4:22:45<371:28:37,  2.37s/it]
  1%|          | 5144/569592 [4:22:46<309:01:02,  1.97s/it]
                                                           

  1%|          | 5144/569592 [4:22:46<309:01:02,  1.97s/it]
  1%|          | 5145/569592 [4:22:48<316:55:55,  2.02s/it]
                                                           

  1%|          | 5145/569592 [4:22:48<316:55:55,  2.02s/it]
  1%|          | 5146/569592 [4:22:53<451:23:12,  2.88s/it]
                                                           

  1%|          | 5146/569592 [4:22:53<451:23:12,  2.88s/it]
  1%|          | 5147/569592 [4:22:54<360:57:04,  2.30s/it]
                                                           

  1%|          | 5147/569592 [4:22:54<360:57:04,  2.30s/it]
  1%|          | 5148/569592 [4:22:55<309:52:06,  1.98s/it]
                                                           

  1%|          | 5148/569592 [4:22:55<309:52:06,  1.98s/it]
  1%|          | 5149/569592 [4:22:59<403:14:11,  2.57s/it]
                                                           

  1%|          | 5149/569592 [4:22:59<403:14:11,  2.57s/it]
  1%|          | 5150/569592 [4:23:03<474:40:30,  3.03s/it]
                                                           

  1%|          | 5150/569592 [4:23:03<474:40:30,  3.03s/it]
  1%|          | 5151/569592 [4:23:04<403:49:42,  2.58s/it]
                                                           

  1%|          | 5151/569592 [4:23:04<403:49:42,  2.58s/it]
  1%|          | 5152/569592 [4:23:05<328:49:19,  2.10s/it]
                                                           

  1%|          | 5152/569592 [4:23:05<328:49:19,  2.10s/it]
  1%|          | 5153/569592 [4:23:09<405:20:50,  2.59s/it]
                                                           

  1%|          | 5153/569592 [4:23:09<405:20:50,  2.59s/it]
  1%|          | 5154/569592 [4:23:13<478:29:40,  3.05s/it]
                                                           

  1%|          | 5154/569592 [4:23:14<478:29:40,  3.05s/it]
  1%|          | 5155/569592 [4:23:15<395:03:17,  2.52s/it]
                                                           

  1%|          | 5155/569592 [4:23:15<395:03:17,  2.52s/it]
  1%|          | 5156/569592 [4:23:18<431:26:41,  2.75s/it]
                                                           

  1%|          | 5156/569592 [4:23:18<431:26:41,  2.75s/it]
  1%|          | 5157/569592 [4:23:19<362:40:03,  2.31s/it]
                                                           

  1%|          | 5157/569592 [4:23:19<362:40:03,  2.31s/it]
  1%|          | 5158/569592 [4:23:24<466:48:40,  2.98s/it]
                                                           

  1%|          | 5158/569592 [4:23:24<466:48:40,  2.98s/it]
  1%|          | 5159/569592 [4:23:26<417:04:41,  2.66s/it]
                                                           

  1%|          | 5159/569592 [4:23:26<417:04:41,  2.66s/it]
  1%|          | 5160/569592 [4:23:27<355:44:03,  2.27s/it]
                                                           

  1%|          | 5160/569592 [4:23:27<355:44:03,  2.27s/it]
  1%|          | 5161/569592 [4:23:32<495:29:52,  3.16s/it]
                                                           

  1%|          | 5161/569592 [4:23:32<495:29:52,  3.16s/it]
  1%|          | 5162/569592 [4:23:33<391:02:07,  2.49s/it]
                                                           

  1%|          | 5162/569592 [4:23:33<391:02:07,  2.49s/it]
  1%|          | 5163/569592 [4:23:34<323:28:52,  2.06s/it]
                                                           

  1%|          | 5163/569592 [4:23:34<323:28:52,  2.06s/it]
  1%|          | 5164/569592 [4:23:36<330:06:33,  2.11s/it]
                                                           

  1%|          | 5164/569592 [4:23:36<330:06:33,  2.11s/it]
  1%|          | 5165/569592 [4:23:40<402:52:25,  2.57s/it]
                                                           

  1%|          | 5165/569592 [4:23:40<402:52:25,  2.57s/it]
  1%|          | 5166/569592 [4:23:44<482:49:27,  3.08s/it]
                                                           

  1%|          | 5166/569592 [4:23:44<482:49:27,  3.08s/it]
  1%|          | 5167/569592 [4:23:48<521:06:58,  3.32s/it]
                                                           

  1%|          | 5167/569592 [4:23:48<521:06:58,  3.32s/it]
  1%|          | 5168/569592 [4:23:49<409:19:31,  2.61s/it]
                                                           

  1%|          | 5168/569592 [4:23:49<409:19:31,  2.61s/it]
  1%|          | 5169/569592 [4:23:50<331:35:41,  2.11s/it]
                                                           

  1%|          | 5169/569592 [4:23:50<331:35:41,  2.11s/it]
  1%|          | 5170/569592 [4:23:56<526:25:25,  3.36s/it]
                                             /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
              

  1%|          | 5170/569592 [4:23:56<526:25:25,  3.36s/it]
  1%|          | 5171/569592 [4:24:00<543:32:45,  3.47s/it]
                                                           

  1%|          | 5171/569592 [4:24:00<543:32:45,  3.47s/it]
  1%|          | 5172/569592 [4:24:01<428:26:47,  2.73s/it]
                                                           

  1%|          | 5172/569592 [4:24:01<428:26:47,  2.73s/it]
  1%|          | 5173/569592 [4:24:02<346:30:57,  2.21s/it]
                                                           

  1%|          | 5173/569592 [4:24:02<346:30:57,  2.21s/it]
  1%|          | 5174/569592 [4:24:07<458:38:22,  2.93s/it]
                                                           

  1%|          | 5174/569592 [4:24:07<458:38:22,  2.93s/it]
  1%|          | 5175/569592 [4:24:08<365:30:29,  2.33s/it]
                                                           

  1%|          | 5175/569592 [4:24:08<365:30:29,  2.33s/it]
  1%|          | 5176/569592 [4:24:12<483:51:37,  3.09s/it]
                                                           

  1%|          | 5176/569592 [4:24:12<483:51:37,  3.09s/it]
  1%|          | 5177/569592 [4:24:16<509:03:03,  3.25s/it]
                                                           

  1%|          | 5177/569592 [4:24:16<509:03:03,  3.25s/it]
  1%|          | 5178/569592 [4:24:19<510:48:03,  3.26s/it]
                                                           

  1%|          | 5178/569592 [4:24:19<510:48:03,  3.26s/it]
  1%|          | 5179/569592 [4:24:23<511:26:11,  3.26s/it]
                                                           

  1%|          | 5179/569592 [4:24:23<511:26:11,  3.26s/it]
  1%|          | 5180/569592 [4:24:26<527:17:14,  3.36s/it]
                                                           

  1%|          | 5180/569592 [4:24:26<527:17:14,  3.36s/it]
  1%|          | 5181/569592 [4:24:27<412:04:42,  2.63s/it]
                                                           

  1%|          | 5181/569592 [4:24:27<412:04:42,  2.63s/it]
  1%|          | 5182/569592 [4:24:32<513:43:08,  3.28s/it]
                                                           

  1%|          | 5182/569592 [4:24:32<513:43:08,  3.28s/it]
  1%|          | 5183/569592 [4:24:36<530:54:35,  3.39s/it]
                                                           

  1%|          | 5183/569592 [4:24:36<530:54:35,  3.39s/it]
  1%|          | 5184/569592 [4:24:40<594:10:55,  3.79s/it]
                                                           

  1%|          | 5184/569592 [4:24:40<594:10:55,  3.79s/it]
  1%|          | 5185/569592 [4:24:44<566:31:28,  3.61s/it]
                                                           

  1%|          | 5185/569592 [4:24:44<566:31:28,  3.61s/it]
  1%|          | 5186/569592 [4:24:48<620:34:51,  3.96s/it]
                                                           

  1%|          | 5186/569592 [4:24:48<620:34:51,  3.96s/it]
  1%|          | 5187/569592 [4:24:51<582:30:32,  3.72s/it]
                                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96323856 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                   

  1%|          | 5187/569592 [4:24:51<582:30:32,  3.72s/it]
  1%|          | 5188/569592 [4:24:56<603:08:43,  3.85s/it]
                                                           

  1%|          | 5188/569592 [4:24:56<603:08:43,  3.85s/it]
  1%|          | 5189/569592 [4:25:00<642:07:40,  4.10s/it]
                                                           

  1%|          | 5189/569592 [4:25:00<642:07:40,  4.10s/it]
  1%|          | 5190/569592 [4:25:04<631:39:57,  4.03s/it]
                                                           

  1%|          | 5190/569592 [4:25:04<631:39:57,  4.03s/it]
  1%|          | 5191/569592 [4:25:08<606:09:41,  3.87s/it]
                                                           

  1%|          | 5191/569592 [4:25:08<606:09:41,  3.87s/it]
  1%|          | 5192/569592 [4:25:09<467:22:55,  2.98s/it]
                                                           

  1%|          | 5192/569592 [4:25:09<467:22:55,  2.98s/it]
  1%|          | 5193/569592 [4:25:12<499:58:49,  3.19s/it]
                                                           

  1%|          | 5193/569592 [4:25:12<499:58:49,  3.19s/it]
  1%|          | 5194/569592 [4:25:17<582:59:43,  3.72s/it]
                                                           

  1%|          | 5194/569592 [4:25:17<582:59:43,  3.72s/it]
  1%|          | 5195/569592 [4:25:20<559:36:01,  3.57s/it]
                                                           

  1%|          | 5195/569592 [4:25:20<559:36:01,  3.57s/it]
  1%|          | 5196/569592 [4:25:24<582:30:14,  3.72s/it]
                                                           

  1%|          | 5196/569592 [4:25:24<582:30:14,  3.72s/it]
  1%|          | 5197/569592 [4:25:25<451:01:51,  2.88s/it]
                                                           

  1%|          | 5197/569592 [4:25:25<451:01:51,  2.88s/it]
  1%|          | 5198/569592 [4:25:29<466:52:41,  2.98s/it]
                                                           

  1%|          | 5198/569592 [4:25:29<466:52:41,  2.98s/it]
  1%|          | 5199/569592 [4:25:33<518:15:38,  3.31s/it]
                                                           

  1%|          | 5199/569592 [4:25:33<518:15:38,  3.31s/it]
  1%|          | 5200/569592 [4:25:36<540:08:52,  3.45s/it]
                                                           

  1%|          | 5200/569592 [4:25:36<540:08:52,  3.45s/it]
  1%|          | 5201/569592 [4:25:40<542:49:09,  3.46s/it]
                                                           

  1%|          | 5201/569592 [4:25:40<542:49:09,  3.46s/it]
  1%|          | 5202/569592 [4:25:43<542:24:22,  3.46s/it]
                                                           

  1%|          | 5202/569592 [4:25:43<542:24:22,  3.46s/it]
  1%|          | 5203/569592 [4:25:48<616:54:50,  3.94s/it]
                                                           

  1%|          | 5203/569592 [4:25:48<616:54:50,  3.94s/it]
  1%|          | 5204/569592 [4:25:53<644:46:21,  4.11s/it]
                                   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                        

  1%|          | 5204/569592 [4:25:53<644:46:21,  4.11s/it]
  1%|          | 5205/569592 [4:25:56<596:36:03,  3.81s/it]
                                                           

  1%|          | 5205/569592 [4:25:56<596:36:03,  3.81s/it]
  1%|          | 5206/569592 [4:26:00<587:37:58,  3.75s/it]
                                                           

  1%|          | 5206/569592 [4:26:00<587:37:58,  3.75s/it]
  1%|          | 5207/569592 [4:26:05<639:44:55,  4.08s/it]
                                                           

  1%|          | 5207/569592 [4:26:05<639:44:55,  4.08s/it]
  1%|          | 5208/569592 [4:26:09<667:50:17,  4.26s/it]
                                                           

  1%|          | 5208/569592 [4:26:09<667:50:17,  4.26s/it]
  1%|          | 5209/569592 [4:26:14<685:41:49,  4.37s/it]
                                                           

  1%|          | 5209/569592 [4:26:14<685:41:49,  4.37s/it]
  1%|          | 5210/569592 [4:26:15<521:24:40,  3.33s/it]
                                                           

  1%|          | 5210/569592 [4:26:15<521:24:40,  3.33s/it]
  1%|          | 5211/569592 [4:26:20<614:20:02,  3.92s/it]
                                                           

  1%|          | 5211/569592 [4:26:20<614:20:02,  3.92s/it]
  1%|          | 5212/569592 [4:26:23<581:43:54,  3.71s/it]
                                                           

  1%|          | 5212/569592 [4:26:23<581:43:54,  3.71s/it]
  1%|          | 5213/569592 [4:26:27<564:50:56,  3.60s/it]
                                                           

  1%|          | 5213/569592 [4:26:27<564:50:56,  3.60s/it]
  1%|          | 5214/569592 [4:26:30<548:23:50,  3.50s/it]
                                                           

  1%|          | 5214/569592 [4:26:30<548:23:50,  3.50s/it]
  1%|          | 5215/569592 [4:26:34<593:42:07,  3.79s/it]
                                                           

  1%|          | 5215/569592 [4:26:34<593:42:07,  3.79s/it]
  1%|          | 5216/569592 [4:26:39<660:08:29,  4.21s/it]
                                                           

  1%|          | 5216/569592 [4:26:40<660:08:29,  4.21s/it]
  1%|          | 5217/569592 [4:26:43<635:21:17,  4.05s/it]
                                                           

  1%|          | 5217/569592 [4:26:43<635:21:17,  4.05s/it]
  1%|          | 5218/569592 [4:26:44<487:13:18,  3.11s/it]
                                                           

  1%|          | 5218/569592 [4:26:44<487:13:18,  3.11s/it]
  1%|          | 5219/569592 [4:26:47<491:22:58,  3.13s/it]
                                                           

  1%|          | 5219/569592 [4:26:47<491:22:58,  3.13s/it]
  1%|          | 5220/569592 [4:26:51<503:57:48,  3.21s/it]
                                                           

  1%|          | 5220/569592 [4:26:51<503:57:48,  3.21s/it]
  1%|          | 5221/569592 [4:26:56<583:56:05,  3.72s/it]
                                                           

  1%|          | 5221/569592 [4:26:56<583:56:05,  3.72s/it]
  1%|          | 5222/569592 [4:26:56<450:11:47,  2.87s/it]
                                                           

  1%|          | 5222/569592 [4:26:56<450:11:47,  2.87s/it]
  1%|          | 5223/569592 [4:27:01<512:34:06,  3.27s/it]
                                                           

  1%|          | 5223/569592 [4:27:01<512:34:06,  3.27s/it]
  1%|          | 5224/569592 [4:27:06<599:44:29,  3.83s/it]
                                                           

  1%|          | 5224/569592 [4:27:06<599:44:29,  3.83s/it]
  1%|          | 5225/569592 [4:27:10<635:55:08,  4.06s/it]
                                                           

  1%|          | 5225/569592 [4:27:10<635:55:08,  4.06s/it]
  1%|          | 5226/569592 [4:27:15<654:44:36,  4.18s/it]
                                                           

  1%|          | 5226/569592 [4:27:15<654:44:36,  4.18s/it]
  1%|          | 5227/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [4:27:19<645:57:57,  4.12s/it]
                                                           

  1%|          | 5227/569592 [4:27:19<645:57:57,  4.12s/it]
  1%|          | 5228/569592 [4:27:22<600:28:30,  3.83s/it]
                                                           

  1%|          | 5228/569592 [4:27:22<600:28:30,  3.83s/it]
  1%|          | 5229/569592 [4:27:25<581:18:47,  3.71s/it]
                                                           

  1%|          | 5229/569592 [4:27:25<581:18:47,  3.71s/it]
  1%|          | 5230/569592 [4:27:29<556:34:48,  3.55s/it]
                                                           

  1%|          | 5230/569592 [4:27:29<556:34:48,  3.55s/it]
  1%|          | 5231/569592 [4:27:32<538:13:01,  3.43s/it]
                                                           

  1%|          | 5231/569592 [4:27:32<538:13:01,  3.43s/it]
  1%|          | 5232/569592 [4:27:33<419:29:03,  2.68s/it]
                                                           

  1%|          | 5232/569592 [4:27:33<419:29:03,  2.68s/it]
  1%|          | 5233/569592 [4:27:37<474:36:59,  3.03s/it]
                                                           

  1%|          | 5233/569592 [4:27:37<474:36:59,  3.03s/it]
  1%|          | 5234/569592 [4:27:40<489:37:36,  3.12s/it]
                                                           

  1%|          | 5234/569592 [4:27:40<489:37:36,  3.12s/it]
  1%|          | 5235/569592 [4:27:44<546:53:47,  3.49s/it]
                                                           

  1%|          | 5235/569592 [4:27:44<546:53:47,  3.49s/it]
  1%|          | 5236/569592 [4:27:47<525:01:35,  3.35s/it]
                                                           

  1%|          | 5236/569592 [4:27:47<525:01:35,  3.35s/it]
  1%|          | 5237/569592 [4:27:51<528:00:58,  3.37s/it]
                                                           

  1%|          | 5237/569592 [4:27:51<528:00:58,  3.37s/it]
  1%|          | 5238/569592 [4:27:55<552:20:18,  3.52s/it]
                                                           

  1%|          | 5238/569592 [4:27:55<552:20:18,  3.52s/it]
  1%|          | 5239/569592 [4:27:58<526:55:09,  3.36s/it]
                                                           

  1%|          | 5239/569592 [4:27:58<526:55:09,  3.36s/it]
  1%|          | 5240/569592 [4:27:58<411:31:41,  2.63s/it]
                                                           

  1%|          | 5240/569592 [4:27:58<411:31:41,  2.63s/it]
  1%|          | 5241/569592 [4:28:02<467:20:12,  2.98s/it]
                                                           

  1%|          | 5241/569592 [4:28:02<467:20:12,  2.98s/it]
  1%|          | 5242/569592 [4:28:06<481:50:31,  3.07s/it]
                                                           

  1%|          | 5242/569592 [4:28:06<481:50:31,  3.07s/it]
  1%|          | 5243/569592 [4:28:10<559:55:20,  3.57s/it]
                                                           

  1%|          | 5243/569592 [4:28:10<559:55:20,  3.57s/it]
  1%|          | 5244/569592 [4:28:13<531:32:59,  3.39s/it]
                                                           

  1%|          | 5244/569592 [4:28:13<531:32:59,  3.39s/it]
  1%|          | 5245/569592 [4:28:14<414:31:25,  2.64s/it]
                                                           

  1%|          | 5245/569592 [4:28:14<414:31:25,  2.64s/it]
  1%|          | 5246/569592 [4:28:15<334:04:39,  2.13s/it]
                                                           

  1%|          | 5246/569592 [4:28:15<334:04:39,  2.13s/it]
  1%|          | 5247/569592 [4:28:16<282:37:57,  1.80s/it]
                                                           

  1%|          | 5247/569592 [4:28:16<282:37:57,  1.80s/it]
  1%|          | 5248/569592 [4:28:17<245:11:25,  1.56s/it]
                                                           

  1%|          | 5248/569592 [4:28:17<245:11:25,  1.56s/it]
  1%|          | 5249/569592 [4:28:20<328:17:41,  2.09s/it]
                                                           

  1%|          | 5249/569592 [4:28:20<328:17:41,  2.09s/it]
  1%|          | 5250/569592 [4:28:21<276:13:42,  1.76s/it]
                                                           

  1%|          | 5250/569592 [4:28:21<276:13:42,  1.76s/it]
  1%|          | 5251/569592 [4:28:22<238:58:30,  1.52s/it]
                                                           

  1%|          | 5251/569592 [4:28:22<238:58:30,  1.52s/it]
  1%|          | 5252/569592 [4:28:28<438:22:42,  2.80s/it]
                                                           

  1%|          | 5252/569592 [4:28:28<438:22:42,  2.80s/it]
  1%|          | 5253/569592 [4:28:29<361:34:42,  2.31s/it]
                                                           

  1%|          | 5253/569592 [4:28:29<361:34:42,  2.31s/it]
  1%|          | 5254/569592 [4:28:30<304:40:08,  1.94s/it]
                                                           

  1%|          | 5254/569592 [4:28:30<304:40:08,  1.94s/it]
  1%|          | 5255/569592 [4:28:31<259:00:14,  1.65s/it]
                                                           

  1%|          | 5255/569592 [4:28:31<259:00:14,  1.65s/it]
  1%|          | 5256/569592 [4:28:35<343:51:56,  2.19s/it]
                                                           

  1%|          | 5256/569592 [4:28:35<343:51:56,  2.19s/it]
  1%|          | 5257/569592 [4:28:37<357:35:02,  2.28s/it]
                                                           

  1%|          | 5257/569592 [4:28:37<357:35:02,  2.28s/it]
  1%|          | 5258/569592 [4:28:38<299:10:10,  1.91s/it]
                                                           

  1%|          | 5258/569592 [4:28:38<299:10:10,  1.91s/it]
  1%|          | 5259/569592 [4:28:39<254:26:36,  1.62s/it]
                                                           

  1%|          | 5259/569592 [4:28:39<254:26:36,  1.62s/it]
  1%|          | 5260/569592 [4:28:44<404:52:46,  2.58s/it]
                                                           

  1%|          | 5260/569592 [4:28:44<404:52:46,  2.58s/it]
  1%|          | 5261/569592 [4:28:47<422:28:50,  2.70s/it]
                                                           

  1%|          | 5261/569592 [4:28:47<422:28:50,  2.70s/it]
  1%|          | 5262/569592 [4:28:48<341:38:56,  2.18s/it]
                                                           

  1%|          | 5262/569592 [4:28:48<341:38:56,  2.18s/it]
  1%|          | 5263/569592 [4:28:50<334:55:13,  2.14s/it]
                                                           

  1%|          | 5263/569592 [4:28:50<334:55:13,  2.14s/it]
  1%|          | 5264/569592 [4:28:54<426:43:56,  2.72s/it]
                                                           

  1%|          | 5264/569592 [4:28:54<426:43:56,  2.72s/it]
  1%|          | 5265/569592 [4:28:58<461:59:33,  2.95s/it]
                                                           

  1%|          | 5265/569592 [4:28:58<461:59:33,  2.95s/it]
  1%|          | 5266/569592 [4:29:01<484:31:35,  3.09s/it]
                                                           

  1%|          | 5266/569592 [4:29:01<484:31:35,  3.09s/it]
  1%|          | 5267/569592 [4:29:02<385:46:54,  2.46s/it]
                                                           

  1%|          | 5267/569592 [4:29:02<385:46:54,  2.46s/it]
  1%|          | 5268/569592 [4:29:07<483:26:20,  3.08s/it]
                                                           

  1%|          | 5268/569592 [4:29:07<483:26:20,  3.08s/it]
  1%|          | 5269/569592 [4:29:10<491:21:17,  3.13s/it]
                                                           

  1%|          | 5269/569592 [4:29:10<491:21:17,  3.13s/it]
  1%|          | 5270/569592 [4:29:11<393:47:45,  2.51s/it]
                                                           

  1%|          | 5270/569592 [4:29:11<393:47:45,  2.51s/it]
  1%|          | 5271/569592 [4:29:12<320:33:40,  2.04s/it]
                                                           

  1%|          | 5271/569592 [4:29:12<320:33:40,  2.04s/it]
  1%|          | 5272/569592 [4:29:16<423:16:15,  2.70s/it]
                                                           

  1%|          | 5272/569592 [4:29:16<423:16:15,  2.70s/it]
  1%|          | 5273/569592 [4:29:17<343:04:42,  2.19s/it]
                                                           

  1%|          | 5273/569592 [4:29:17<343:04:42,  2.19s/it]
  1%|          | 5274/569592 [4:29:21<412:10:42,  2.63s/it]
                                                           

  1%|          | 5274/569592 [4:29:21<412:10:42,  2.63s/it]
  1%|          | 5275/569592 [4:29:22<335:04:30,  2.14s/it]
                                                           

  1%|          | 5275/569592 [4:29:22<335:04:30,  2.14s/it]
  1%|          | 5276/569592 [4:29:25<366:08:16,  2.34s/it]
                                                           

  1%|          | 5276/569592 [4:29:25<366:08:16,  2.34s/it]
  1%|          | 5277/569592 [4:29:28<419:02:22,  2.67s/it]
                                                           

  1%|          | 5277/569592 [4:29:28<419:02:22,  2.67s/it]
  1%|          | 5278/569592 [4:29:30<387:48:45,  2.47s/it]
                                                           

  1%|          | 5278/569592 [4:29:30<387:48:45,  2.47s/it]
  1%|          | 5279/569592 [4:29:33<431:24:28,  2.75s/it]
                                                           

  1%|          | 5279/569592 [4:29:33<431:24:28,  2.75s/it]
  1%|          | 5280/569592 [4:29:36<435:59:26,  2.78s/it]
                                                           

  1%|          | 5280/569592 [4:29:36<435:59:26,  2.78s/it]
  1%|          | 5281/569592 [4:29:38<392:28:13,  2.50s/it]
                                                           

  1%|          | 5281/569592 [4:29:38<392:28:13,  2.50s/it]
  1%|          | 5282/569592 [4:29:40<360:38:47,  2.30s/it]
                                                           

  1%|          | 5282/569592 [4:29:40<360:38:47,  2.30s/it]
  1%|          | 5283/569592 [4:29:42<332:54:56,  2.12s/it]
                                                           

  1%|          | 5283/569592 [4:29:42<332:54:56,  2.12s/it]
  1%|          | 5284/569592 [4:29:45<406:31:03,  2.59s/it]
                                                           

  1%|          | 5284/569592 [4:29:45<406:31:03,  2.59s/it]
  1%|          | 5285/569592 [4:29:50<487:24:04,  3.11s/it]
                                                           

  1%|          | 5285/569592 [4:29:50<487:24:04,  3.11s/it]
  1%|          | 5286/569592 [4:29:51<396:27:42,  2.53s/it]
                                                           

  1%|          | 5286/569592 [4:29:51<396:27:42,  2.53s/it]
  1%|          | 5287/569592 [4:29:52<336:16:51,  2.15s/it]
                                                           

  1%|          | 5287/569592 [4:29:52<336:16:51,  2.15s/it]
  1%|          | 5288/569592 [4:29:56<401:26:07,  2.56s/it]
                                                           

  1%|          | 5288/569592 [4:29:56<401:26:07,  2.56s/it]
  1%|          | 5289/569592 [4:29:59<447:03:39,  2.85s/it]
          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                 

  1%|          | 5289/569592 [4:29:59<447:03:39,  2.85s/it]
  1%|          | 5290/569592 [4:30:01<415:55:16,  2.65s/it]
                                                           

  1%|          | 5290/569592 [4:30:01<415:55:16,  2.65s/it]
  1%|          | 5291/569592 [4:30:02<341:47:02,  2.18s/it]
                                                           

  1%|          | 5291/569592 [4:30:02<341:47:02,  2.18s/it]
  1%|          | 5292/569592 [4:30:06<403:53:49,  2.58s/it]
                                                           

  1%|          | 5292/569592 [4:30:06<403:53:49,  2.58s/it]
  1%|          | 5293/569592 [4:30:10<469:27:46,  2.99s/it]
                                                           

  1%|          | 5293/569592 [4:30:10<469:27:46,  2.99s/it]
  1%|          | 5294/569592 [4:30:12<437:03:27,  2.79s/it]
                                                           

  1%|          | 5294/569592 [4:30:12<437:03:27,  2.79s/it]
  1%|          | 5295/569592 [4:30:16<478:05:35,  3.05s/it]
                                                           

  1%|          | 5295/569592 [4:30:16<478:05:35,  3.05s/it]
  1%|          | 5296/569592 [4:30:19<503:09:40,  3.21s/it]
                                                           

  1%|          | 5296/569592 [4:30:19<503:09:40,  3.21s/it]
  1%|          | 5297/569592 [4:30:23<497:02:33,  3.17s/it]
                                                           

  1%|          | 5297/569592 [4:30:23<497:02:33,  3.17s/it]
  1%|          | 5298/569592 [4:30:26<508:04:13,  3.24s/it]
                                                           

  1%|          | 5298/569592 [4:30:26<508:04:13,  3.24s/it]
  1%|          | 5299/569592 [4:30:29<502:46:19,  3.21s/it]
                                                           

  1%|          | 5299/569592 [4:30:29<502:46:19,  3.21s/it]
  1%|          | 5300/569592 [4:30:30<396:37:25,  2.53s/it]
                                                           

  1%|          | 5300/569592 [4:30:30<396:37:25,  2.53s/it]
  1%|          | 5301/569592 [4:30:34<473:18:54,  3.02s/it]
                                                           

  1%|          | 5301/569592 [4:30:34<473:18:54,  3.02s/it]
  1%|          | 5302/569592 [4:30:38<489:25:24,  3.12s/it]
                                                           

  1%|          | 5302/569592 [4:30:38<489:25:24,  3.12s/it]
  1%|          | 5303/569592 [4:30:41<492:01:54,  3.14s/it]
                                                           

  1%|          | 5303/569592 [4:30:41<492:01:54,  3.14s/it]
  1%|          | 5304/569592 [4:30:45<562:28:06,  3.59s/it]
                                                           

  1%|          | 5304/569592 [4:30:45<562:28:06,  3.59s/it]
  1%|          | 5305/569592 [4:30:49<549:17:44,  3.50s/it]
                                                           

  1%|          | 5305/569592 [4:30:49<549:17:44,  3.50s/it]
  1%|          | 5306/569592 [4:30:52<555:12:26,  3.54s/it]
                                                           

  1%|          | 5306/569592 [4:30:52<555:12:26,  3.54s/it]
  1%|          | 5307/569592 [4:30:56<541:53:05,  3.46s/it]
                                                           

  1%|          | 5307/569592 [4:30:56<541:53:05,  3.46s/it]
  1%|          | 5308/569592 [4:30:59<542:58:55,  3.46s/it]
                                                           

  1%|          | 5308/569592 [4:30:59<542:58:55,  3.46s/it]
  1%|          | 5309/569592 [4:31:03<547:21:43,  3.49s/it]
                                                           

  1%|          | 5309/569592 [4:31:03<547:21:43,  3.49s/it]
  1%|          | 5310/569592 [4:31:06<526:06:22,  3.36s/it]
                                                           

  1%|          | 5310/569592 [4:31:06<526:06:22,  3.36s/it]
  1%|          | 5311/569592 [4:31:07<416:19:26,  2.66s/it]
                                                           

  1%|          | 5311/569592 [4:31:07<416:19:26,  2.66s/it]
  1%|          | 5312/569592 [4:31:10<458:45:34,  2.93s/it]
                                                           

  1%|          | 5312/569592 [4:31:10<458:45:34,  2.93s/it]
  1%|          | 5313/569592 [4:31:13<470:13:42,  3.00s/it]
                                                           

  1%|          | 5313/569592 [4:31:13<470:13:42,  3.00s/it]
  1%|          | 5314/569592 [4:31:17<479:36:06,  3.06s/it]
                                                           

  1%|          | 5314/569592 [4:31:17<479:36:06,  3.06s/it]
  1%|          | 5315/569592 [4:31:18<378:43:52,  2.42s/it]
                                                           

  1%|          | 5315/569592 [4:31:18<378:43:52,  2.42s/it]
  1%|          | 5316/569592 [4:31:21<449:06:17,  2.87s/it]
                                                           

  1%|          | 5316/569592 [4:31:21<449:06:17,  2.87s/it]
  1%|          | 5317/569592 [4:31:22<359:01:43,  2.29s/it]
                                                           

 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92063864 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 1%|          | 5317/569592 [4:31:22<359:01:43,  2.29s/it]
  1%|          | 5318/569592 [4:31:27<484:13:27,  3.09s/it]
                                                           

  1%|          | 5318/569592 [4:31:27<484:13:27,  3.09s/it]
  1%|          | 5319/569592 [4:31:32<538:15:27,  3.43s/it]
                                                           

  1%|          | 5319/569592 [4:31:32<538:15:27,  3.43s/it]
  1%|          | 5320/569592 [4:31:36<582:53:21,  3.72s/it]
                                                           

  1%|          | 5320/569592 [4:31:36<582:53:21,  3.72s/it]
  1%|          | 5321/569592 [4:31:40<589:17:45,  3.76s/it]
                                                           

  1%|          | 5321/569592 [4:31:40<589:17:45,  3.76s/it]
  1%|          | 5322/569592 [4:31:44<596:28:07,  3.81s/it]
                                                           

  1%|          | 5322/569592 [4:31:44<596:28:07,  3.81s/it]
  1%|          | 5323/569592 [4:31:47<565:52:36,  3.61s/it]
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                           

  1%|          | 5323/569592 [4:31:47<565:52:36,  3.61s/it]
  1%|          | 5324/569592 [4:31:51<570:56:38,  3.64s/it]
                                                           

  1%|          | 5324/569592 [4:31:51<570:56:38,  3.64s/it]
  1%|          | 5325/569592 [4:31:54<555:08:29,  3.54s/it]
                                                           

  1%|          | 5325/569592 [4:31:54<555:08:29,  3.54s/it]
  1%|          | 5326/569592 [4:31:57<546:12:24,  3.48s/it]
                                                           

  1%|          | 5326/569592 [4:31:57<546:12:24,  3.48s/it]
  1%|          | 5327/569592 [4:32:01<542:30:30,  3.46s/it]
                                                           

  1%|          | 5327/569592 [4:32:01<542:30:30,  3.46s/it]
  1%|          | 5328/569592 [4:32:04<554:26:22,  3.54s/it]
                                                           

  1%|          | 5328/569592 [4:32:04<554:26:22,  3.54s/it]
  1%|          | 5329/569592 [4:32:10<636:56:38,  4.06s/it]
                                                           

  1%|          | 5329/569592 [4:32:10<636:56:38,  4.06s/it]
  1%|          | 5330/569592 [4:32:13<610:39:33,  3.90s/it]
                                                           

  1%|          | 5330/569592 [4:32:13<610:39:33,  3.90s/it]
  1%|          | 5331/569592 [4:32:14<469:35:33,  3.00s/it]
                                                           

  1%|          | 5331/569592 [4:32:14<469:35:33,  3.00s/it]
  1%|          | 5332/569592 [4:32:18<533:38:21,  3.40s/it]
                                                           

  1%|          | 5332/569592 [4:32:18<533:38:21,  3.40s/it]
  1%|          | 5333/569592 [4:32:23<585:54:50,  3.74s/it]
                                                           

  1%|          | 5333/569592 [4:32:23<585:54:50,  3.74s/it]
  1%|          | 5334/569592 [4:32:27<598:27:56,  3.82s/it]
                                                           

  1%|          | 5334/569592 [4:32:27<598:27:56,  3.82s/it]
  1%|          | 5335/569592 [4:32:31<594:17:55,  3.79s/it]
                                                           

  1%|          | 5335/569592 [4:32:31<594:17:55,  3.79s/it]
  1%|          | 5336/569592 [4:32:34<564:18:48,  3.60s/it]
                                                           

  1%|          | 5336/569592 [4:32:34<564:18:48,  3.60s/it]
  1%|          | 5337/569592 [4:32:37<541:12:15,  3.45s/it]
                                                           

  1%|          | 5337/569592 [4:32:37<541:12:15,  3.45s/it]
  1%|          | 5338/569592 [4:32:40<538:20:43,  3.43s/it]
                                                           

  1%|          | 5338/569592 [4:32:40<538:20:43,  3.43s/it]
  1%|          | 5339/569592 [4:32:44<541:06:22,  3.45s/it]
                                                           

  1%|          | 5339/569592 [4:32:44<541:06:22,  3.45s/it]
  1%|          | 5340/569592 [4:32:48<576:59:35,  3.68s/it]
                                                           

  1%|          | 5340/569592 [4:32:48<576:59:35,  3.68s/it]
  1%|          | 5341/569592 [4:32:53<620:24:23,  3.96s/it]
                                                           

  1%|          | 5341/569592 [4:32:53<620:24:23,  3.96s/it]
  1%|          | 5342/569592 [4:32:57<645:34:46,  4.12s/it]
                                                           

  1%|          | 5342/569592 [4:32:57<645:34:46,  4.12s/it]
  1%|          | 5343/569592 [4:32:58<494:08:34,  3.15s/it]
                                                           

  1%|          | 5343/569592 [4:32:58<494:08:34,  3.15s/it]
  1%|          | 5344/569592 [4:33:01<502:18:44,  3.20s/it]
                                                           

  1%|          | 5344/569592 [4:33:01<502:18:44,  3.20s/it]
  1%|          | 5345/569592 [4:33:05<513:26:41,  3.28s/it]
                                                           

  1%|          | 5345/569592 [4:33:05<513:26:41,  3.28s/it]
  1%|          | 5346/569592 [4:33:09<580:13:01,  3.70s/it]
                                                           

  1%|          | 5346/569592 [4:33:09<580:13:01,  3.70s/it]
  1%|          | 5347/569592 [4:33:13<560:32:30,  3.58s/it]
                                                           

  1%|          | 5347/569592 [4:33:13<560:32:30,  3.58s/it]
  1%|          | 5348/569592 [4:33:17<609:18:38,  3.89s/it]
                                                           

  1%|          | 5348/569592 [4:33:17<609:18:38,  3.89s/it]
  1%|          | 5349/569592 [4:33:21<585:58:44,  3.74s/it]
                                                           

  1%|          | 5349/569592 [4:33:21<585:58:44,  3.74s/it]
  1%|          | 5350/569592 [4:33:24<574:03:04,  3.66s/it]
                                                           

  1%|          | 5350/569592 [4:33:24<574:03:04,  3.66s/it]
  1%|          | 5351/569592 [4:33:28<559:34:07,  3.57s/it]
                                                           

  1%|          | 5351/569592 [4:33:28<559:34:07,  3.57s/it]
  1%|          | 5352/569592 [4:33:31<548:15:29,  3.50s/it]
                                                           

  1%|          | 5352/569592 [4:33:31<548:15:29,  3.50s/it]
  1%|          | 5353/569592 [4:33:36<598:54:09,  3.82s/it]
                                                           

  1%|          | 5353/569592 [4:33:36<598:54:09,  3.82s/it]
  1%|          | 5354/569592 [4:33:39<575:40:26,  3.67s/it]
                                                           

  1%|          | 5354/569592 [4:33:39<575:40:26,  3.67s/it]
  1%|          | 5355/569592 [4:33:40<445:07:29,  2.84s/it]
                                                           

  1%|          | 5355/569592 [4:33:40<445:07:29,  2.84s/it]
  1%|          | 5356/569592 [4:33:45<540:49:26,  3.45s/it]
                                                           

  1%|          | 5356/569592 [4:33:45<540:49:26,  3.45s/it]
  1%|          | 5357/569592 [4:33:48<542:01:07,  3.46s/it]
                                                           

  1%|          | 5357/569592 [4:33:48<542:01:07,  3.46s/it]
  1%|          | 5358/569592 [4:33:51<533:17:54,  3.40s/it]
                                                           

  1%|          | 5358/569592 [4:33:51<533:17:54,  3.40s/it]
  1%|          | 5359/569592 [4:33:52<416:00:04,  2.65s/it]
                                                           

  1%|          | 5359/569592 [4:33:52<416:00:04,  2.65s/it]
  1%|          | 5360/569592 [4:33:57<522:31:13,  3.33s/it]
                                                           

  1%|          | 5360/569592 [4:33:57<522:31:13,  3.33s/it]
  1%|          | 5361/569592 [4:34:01<526:15:48,  3.36s/it]
                                                           

  1%|          | 5361/569592 [4:34:01<526:15:48,  3.36s/it]
  1%|          | 5362/569592 [4:34:04<507:06:43,  3.24s/it]
                                                           

  1%|          | 5362/569592 [4:34:04<507:06:43,  3.24s/it]
  1%|          | 5363/569592 [4:34:04<398:07:57,  2.54s/it]
                                                           

  1%|          | 5363/569592 [4:34:04<398:07:57,  2.54s/it]
  1%|          | 5364/569592 [4:34:10<526:13:19,  3.36s/it]
                                                           

  1%|          | 5364/569592 [4:34:10<526:13:19,  3.36s/it]
  1%|          | 5365/569592 [4:34:11<416:12:17,  2.66s/it]
                                                           

  1%|          | 5365/569592 [4:34:11<416:12:17,  2.66s/it]
  1%|          | 5366/569592 [4:34:12<338:18:18,  2.16s/it]
                                                           

  1%|          | 5366/569592 [4:34:12<338:18:18,  2.16s/it]
  1%|          | 5367/569592 [4:34:16<445:45:48,  2.84s/it]
                                                           

  1%|          | 5367/569592 [4:34:16<445:45:48,  2.84s/it]
  1%|          | 5368/569592 [4:34:17<356:01:33,  2.27s/it]
                                                           

  1%|          | 5368/569592 [4:34:17<356:01:33,  2.27s/it]
  1%|          | 5369/569592 [4:34:18<296:35:27,  1.89s/it]
                                                           

  1%|          | 5369/569592 [4:34:18<296:35:27,  1.89s/it]
  1%|          | 5370/569592 [4:34:19<252:05:12,  1.61s/it]
                                                           

  1%|          | 5370/569592 [4:34:19<252:05:12,  1.61s/it]
  1%|          | 5371/569592 [4:34:20<228:03:13,  1.46s/it]
                                                           

  1%|          | 5371/569592 [4:34:20<228:03:13,  1.46s/it]
  1%|          | 5372/569592 [4:34:21<203:58:30,  1.30s/it]
                                                           

  1%|          | 5372/569592 [4:34:21<203:58:30,  1.30s/it]
  1%|          | 5373/569592 [4:34:24<267:12:33,  1.70s/it]
                                                           

  1%|          | 5373/569592 [4:34:24<267:12:33,  1.70s/it]
  1%|          | 5374/569592 [4:34:25<232:03:08,  1.48s/it]
                                                           

  1%|          | 5374/569592 [4:34:25<232:03:08,  1.48s/it]
  1%|          | 5375/569592 [4:34:27<246:06:53,  1.57s/it]
                                                           

  1%|          | 5375/569592 [4:34:27<246:06:53,  1.57s/it]
  1%|          | 5376/569592 [4:34:32<416:37:48,  2.66s/it]
                                                           

  1%|          | 5376/569592 [4:34:32<416:37:48,  2.66s/it]
  1%|          | 5377/569592 [4:34:33<374:37:02,  2.39s/it]
                                                           

  1%|          | 5377/569592 [4:34:33<374:37:02,  2.39s/it]
  1%|          | 5378/569592 [4:34:35<341:05:36,  2.18s/it]
                                                           

  1%|          | 5378/569592 [4:34:35<341:05:36,  2.18s/it]
  1%|          | 5379/569592 [4:34:39<402:39:48,  2.57s/it]
                                                           

  1%|          | 5379/569592 [4:34:39<402:39:48,  2.57s/it]
  1%|          | 5380/569592 [4:34:41<399:34:11,  2.55s/it]
                                                           

  1%|          | 5380/569592 [4:34:41<399:34:11,  2.55s/it]
  1%|          | 5381/569592 [4:34:44<417:24:00,  2.66s/it]
                                                           

  1%|          | 5381/569592 [4:34:44<417:24:00,  2.66s/it]
  1%|          | 5382/569592 [4:34:48<474:50:50,  3.03s/it]
                                                           

  1%|          | 5382/569592 [4:34:48<474:50:50,  3.03s/it]
  1%|          | 5383/569592 [4:34:49<378:37:39,  2.42s/it]
                                                           

  1%|          | 5383/569592 [4:34:49<378:37:39,  2.42s/it]
  1%|          | 5384/569592 [4:34:50<326:16:57,  2.08s/it]
                                                           

  1%|          | 5384/569592 [4:34:50<326:16:57,  2.08s/it]
  1%|          | 5385/569592 [4:34:54<404:19:58,  2.58s/it]
                                                           

  1%|          | 5385/569592 [4:34:54<404:19:58,  2.58s/it]
  1%|          | 5386/569592 [4:34:55<340:21:00,  2.17s/it]
                                                           

  1%|          | 5386/569592 [4:34:55<340:21:00,  2.17s/it]
  1%|          | 5387/569592 [4:35:01<492:33:00,  3.14s/it]
                                                           

  1%|          | 5387/569592 [4:35:01<492:33:00,  3.14s/it]
  1%|          | 5388/569592 [4:35:02<420:44:06,  2.68s/it]
                                                           

  1%|          | 5388/569592 [4:35:02<420:44:06,  2.68s/it]
  1%|          | 5389/569592 [4:35:04<386:19:49,  2.47s/it]
                                                           

  1%|          | 5389/569592 [4:35:04<386:19:49,  2.47s/it]
  1%|          | 5390/569592 [4:35:06<371:50:09,  2.37s/it]
                                                           

  1%|          | 5390/569592 [4:35:06<371:50:09,  2.37s/it]
  1%|          | 5391/569592 [4:35:07<310:38:18,  1.98s/it]
                                                           

  1%|          | 5391/569592 [4:35:07<310:38:18,  1.98s/it]
  1%|          | 5392/569592 [4:35:12<414:58:26,  2.65s/it]
                                                           

  1%|          | 5392/569592 [4:35:12<414:58:26,  2.65s/it]
  1%|          | 5393/569592 [4:35:14<422:01:36,  2.69s/it]
                                                           

  1%|          | 5393/569592 [4:35:14<422:01:36,  2.69s/it]
  1%|          | 5394/569592 [4:35:17<406:41:44,  2.60s/it]
                                                           

  1%|          | 5394/569592 [4:35:17<406:41:44,  2.60s/it]
  1%|          | 5395/569592 [4:35:18<356:05:35,  2.27s/it]
                                                           

  1%|          | 5395/569592 [4:35:18<356:05:35,  2.27s/it]
  1%|          | 5396/569592 [4:35:22<406:54:44,  2.60s/it]
                                                           

  1%|          | 5396/569592 [4:35:22<406:54:44,  2.60s/it]
  1%|          | 5397/569592 [4:35:25<447:12:44,  2.85s/it]
                                                           

  1%|          | 5397/569592 [4:35:25<447:12:44,  2.85s/it]
  1%|          | 5398/569592 [4:35:27<422:20:03,  2.69s/it]
                                                           

  1%|          | 5398/569592 [4:35:27<422:20:03,  2.69s/it]
  1%|          | 5399/569592 [4:35:29<366:09:18,  2.34s/it]
                                                           

  1%|          | 5399/569592 [4:35:29<366:09:18,  2.34s/it]
  1%|          | 5400/569592 [4:35:32<382:21:59,  2.44s/it]
                                                           

  1%|          | 5400/569592 [4:35:32<382:21:59,  2.44s/it]
  1%|          | 5401/569592 [4:35:34<369:35:02,  2.36s/it]
                                                           

  1%|          | 5401/569592 [4:35:34<369:35:02,  2.36s/it]
  1%|          | 5402/569592 [4:35:39<491:55:23,  3.14s/it]
                                                           

  1%|          | 5402/569592 [4:35:39<491:55:23,  3.14s/it]
  1%|          | 5403/569592 [4:35:40<390:09:42,  2.49s/it]
                                                           

  1%|          | 5403/569592 [4:35:40<390:09:42,  2.49s/it]
  1%|          | 5404/569592 [4:35:42<358:05:25,  2.28s/it]
                                                           

  1%|          | 5404/569592 [4:35:42<358:05:25,  2.28s/it]
  1%|          | 5405/569592 [4:35:45<413:36:30,  2.64s/it]
                                                           

  1%|          | 5405/569592 [4:35:45<413:36:30,  2.64s/it]
  1%|          | 5406/569592 [4:35:49<456:07:47,  2.91s/it]
                                                           

  1%|          | 5406/569592 [4:35:49<456:07:47,  2.91s/it]
  1%|          | 5407/569592 [4:35:52<486:47:54,  3.11s/it]
                                                           

  1%|          | 5407/569592 [4:35:52<486:47:54,  3.11s/it]
  1%|          | 5408/569592 [4:35:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
53<386:20:07,  2.47s/it]
                                                           

  1%|          | 5408/569592 [4:35:53<386:20:07,  2.47s/it]
  1%|          | 5409/569592 [4:35:58<509:44:08,  3.25s/it]
                                                           

  1%|          | 5409/569592 [4:35:58<509:44:08,  3.25s/it]
  1%|          | 5410/569592 [4:36:03<566:40:46,  3.62s/it]
                                                           

  1%|          | 5410/569592 [4:36:03<566:40:46,  3.62s/it]
  1%|          | 5411/569592 [4:36:06<541:45:44,  3.46s/it]
                                                           

  1%|          | 5411/569592 [4:36:06<541:45:44,  3.46s/it]
  1%|          | 5412/569592 [4:36:09<542:26:18,  3.46s/it]
                                                           

  1%|          | 5412/569592 [4:36:09<542:26:18,  3.46s/it]
  1%|          | 5413/569592 [4:36:10<424:00:13,  2.71s/it]
                                                           

  1%|          | 5413/569592 [4:36:10<424:00:13,  2.71s/it]
  1%|          | 5414/569592 [4:36:13<448:32:32,  2.86s/it]
                                                           

  1%|          | 5414/569592 [4:36:13<448:32:32,  2.86s/it]
  1%|          | 5415/569592 [4:36:17<474:58:03,  3.03s/it]
                                                           

  1%|          | 5415/569592 [4:36:17<474:58:03,  3.03s/it]
  1%|          | 5416/569592 [4:36:20<495:42:33,  3.16s/it]
                                                           

  1%|          | 5416/569592 [4:36:20<495:42:33,  3.16s/it]
  1%|          | 5417/569592 [4:36:21<394:44:34,  2.52s/it]
                                                           

  1%|          | 5417/569592 [4:36:21<394:44:34,  2.52s/it]
  1%|          | 5418/569592 [4:36:25<445:17:55,  2.84s/it]
                                                           

  1%|          | 5418/569592 [4:36:25<445:17:55,  2.84s/it]
  1%|          | 5419/569592 [4:36:28<482:02:02,  3.08s/it]
                                                           

  1%|          | 5419/569592 [4:36:28<482:02:02,  3.08s/it]
  1%|          | 5420/569592 [4:36:30<386:12:02,  2.46s/it]
                                                           

  1%|          | 5420/569592 [4:36:30<386:12:02,  2.46s/it]
  1%|          | 5421/569592 [4:36:33<448:41:40,  2.86s/it]
                                                           

  1%|          | 5421/569592 [4:36:33<448:41:40,  2.86s/it]
  1%|          | 5422/569592 [4:36:34<359:51:53,  2.30s/it]
                                                           

  1%|          | 5422/569592 [4:36:34<359:51:53,  2.30s/it]
  1%|          | 5423/569592 [4:36:38<422:38:52,  2.70s/it]
                                                           

  1%|          | 5423/569592 [4:36:38<422:38:52,  2.70s/it]
  1%|          | 5424/569592 [4:36:39<350:46:57,  2.24s/it]
                                                           

  1%|          | 5424/569592 [4:36:39<350:46:57,  2.24s/it]
  1%|          | 5425/569592 [4:36:40<292:06:28,  1.86s/it]
                                                           

  1%|          | 5425/569592 [4:36:40<292:06:28,  1.86s/it]
  1%|          | 5426/569592 [4:36:44<392:05:23,  2.50s/it]
                                                           

  1%|          | 5426/569592 [4:36:44<392:05:23,  2.50s/it]
  1%|          | 5427/569592 [4:36:48<455:42:45,  2.91s/it]
                                                           

  1%|          | 5427/569592 [4:36:48<455:42:45,  2.91s/it]
  1%|          | 5428/569592 [4:36:51<481:00:20,  3.07s/it]
                                                           

  1%|          | 5428/569592 [4:36:51<481:00:20,  3.07s/it]
  1%|          | 5429/569592 [4:36:55<510:37:03,  3.26s/it]
                                                           

  1%|          | 5429/569592 [4:36:55<510:37:03,  3.26s/it]
  1%|          | 5430/569592 [4:36:58<515:32:53,  3.29s/it]
                                                           

  1%|          | 5430/569592 [4:36:58<515:32:53,  3.29s/it]
  1%|          | 5431/569592 [4:37:02<506:08:51,  3.23s/it]
                                                           

  1%|          | 5431/569592 [4:37:02<506:08:51,  3.23s/it]
  1%|          | 5432/569592 [4:37:05<507:55:52,  3.24s/it]
                                                           

  1%|          | 5432/569592 [4:37:05<507:55:52,  3.24s/it]
  1%|          | 5433/569592 [4:37:09<547:03:18,  3.49s/it]
                                                           

  1%|          | 5433/569592 [4:37:09<547:03:18,  3.49s/it]
  1%|          | 5434/569592 [4:37:15<672:45:42,  4.29s/it]
                                                           

  1%|          | 5434/569592 [4:37:15<672:45:42,  4.29s/it]
  1%|          | 5435/569592 [4:37:16<511:49:40,  3.27s/it]
                                                           

  1%|          | 5435/569592 [4:37:16<511:49:40,  3.27s/it]
  1%|          | 5436/569592 [4:37:20<557:09:10,  3.56s/it]
                                                           

  1%|          | 5436/569592 [4:37:20<557:09:10,  3.56s/it]
  1%|          | 5437/569592 [4:37:24<581:00:48,  3.71s/it]
                                                           

  1%|          | 5437/569592 [4:37:24<581:00:48,  3.71s/it]
  1%|          | 5438/569592 [4:37:28<577:04:23,  3.68s/it]
                                                           

  1%|          | 5438/569592 [4:37:28<577:04:23,  3.68s/it]
  1%|          | 5439/569592 [4:37:31<557:10:39,  3.56s/it]
                                                           

  1%|          | 5439/569592 [4:37:31<557:10:39,  3.56s/it]
  1%|          | 5440/569592 [4:37:36<612:24:22,  3.91s/it]
                                                           

  1%|          | 5440/569592 [4:37:36<612:24:22,  3.91s/it]
  1%|          | 5441/569592 [4:37:40<647:14:48,  4.13s/it]
                                                           

  1%|          | 5441/569592 [4:37:40<647:14:48,  4.13s/it]
  1%|          | 5442/569592 [4:37:44<605:11:42,  3.86s/it]
                                                           

  1%|          | 5442/569592 [4:37:44<605:11:42,  3.86s/it]
  1%|          | 5443/569592 [4:37:48<647:31:26,  4.13s/it]
                                                           

  1%|          | 5443/569592 [4:37:48<647:31:26,  4.13s/it]
  1%|          | 5444/569592 [4:37:52<616:50:34,  3.94s/it]
                                                           

  1%|          | 5444/569592 [4:37:52<616:50:34,  3.94s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  1%|          | 5445/569592 [4:37:56<627:44:21,  4.01s/it]
                                                           

  1%|          | 5445/569592 [4:37:56<627:44:21,  4.01s/it]
  1%|          | 5446/569592 [4:38:01<664:13:09,  4.24s/it]
                                                           

  1%|          | 5446/569592 [4:38:01<664:13:09,  4.24s/it]
  1%|          | 5447/569592 [4:38:06<702:35:12,  4.48s/it]
                                                           

  1%|          | 5447/569592 [4:38:06<702:35:12,  4.48s/it]
  1%|          | 5448/569592 [4:38:10<663:22:45,  4.23s/it]
                                                           

  1%|          | 5448/569592 [4:38:10<663:22:45,  4.23s/it]
  1%|          | 5449/569592 [4:38:14<684:32:55,  4.37s/it]
                                                           

  1%|          | 5449/569592 [4:38:14<684:32:55,  4.37s/it]
  1%|          | 5450/569592 [4:38:18<648:26:56,  4.14s/it]
                                                           

  1%|          | 5450/569592 [4:38:18<648:26:56,  4.14s/it]
  1%|          | 5451/569592 [4:38:21<604:14:55,  3.86s/it]
                                                           

  1%|          | 5451/569592 [4:38:21<604:14:55,  3.86s/it]
  1%|          | 5452/569592 [4:38:24<570:36:19,  3.64s/it]
                                                           

  1%|          | 5452/569592 [4:38:24<570:36:19,  3.64s/it]
  1%|          | 5453/569592 [4:38:27<554:20:33,  3.54s/it]
                                                           

  1%|          | 5453/569592 [4:38:27<554:20:33,  3.54s/it]
  1%|          | 5454/569592 [4:38:32<613:53:20,  3.92s/it]
                                                           

  1%|          | 5454/569592 [4:38:32<613:53:20,  3.92s/it]
  1%|          | 5455/569592 [4:38:36<584:10:32,  3.73s/it]
                                                           

  1%|          | 5455/569592 [4:38:36<584:10:32,  3.73s/it]
  1%|          | 5456/569592 [4:38:40<631:20:49,  4.03s/it]
                                                           

  1%|          | 5456/569592 [4:38:40<631:20:49,  4.03s/it]
  1%|          | 5457/569592 [4:38:44<593:31:12,  3.79s/it]
                                                           

  1%|          | 5457/569592 [4:38:44<593:31:12,  3.79s/it]
  1%|          | 5458/569592 [4:38:47<560:23:41,  3.58s/it]
                                                           

  1%|          | 5458/569592 [4:38:47<560:23:41,  3.58s/it]
  1%|          | 5459/569592 [4:38:52<630:44:36,  4.03s/it]
                                                           

  1%|          | 5459/569592 [4:38:52<630:44:36,  4.03s/it]
  1%|          | 5460/569592 [4:38:56<663:03:37,  4.23s/it]
                                                           

  1%|          | 5460/569592 [4:38:56<663:03:37,  4.23s/it]
  1%|          | 5461/569592 [4:39:00<618:28:07,  3.95s/it]
                                                           

  1%|          | 5461/569592 [4:39:00<618:28:07,  3.95s/it]
  1%|          | 5462/569592 [4:39:01<476:07:00,  3.04s/it]
                                                           

  1%|          | 5462/569592 [4:39:01<476:07:00,  3.04s/it]
  1%|          | 5463/569592 [4:39:02<376:21:16,  2.40s/it]
                                                           

  1%|          | 5463/569592 [4:39:02<376:21:16,  2.40s/it]
  1%|          | 5464/569592 [4:39:05<439:08:51,  2.80s/it]
                                                           

  1%|          | 5464/569592 [4:39:05<439:08:51,  2.80s/it]
  1%|          | 5465/569592 [4:39:09<490:14:16,  3.13s/it]
                                                           

  1%|          | 5465/569592 [4:39:09<490:14:16,  3.13s/it]
  1%|          | 5466/569592 [4:39:12<494:45:52,  3.16s/it]
                                                           

  1%|          | 5466/569592 [4:39:12<494:45:52,  3.16s/it]
  1%|          | 5467/569592 [4:39:17<549:03:33,  3.50s/it]
                                                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
      

  1%|          | 5467/569592 [4:39:17<549:03:33,  3.50s/it]
  1%|          | 5468/569592 [4:39:20<535:22:15,  3.42s/it]
                                                           

  1%|          | 5468/569592 [4:39:20<535:22:15,  3.42s/it]
  1%|          | 5469/569592 [4:39:23<525:09:50,  3.35s/it]
                                                           

  1%|          | 5469/569592 [4:39:23<525:09:50,  3.35s/it]
  1%|          | 5470/569592 [4:39:27<536:08:46,  3.42s/it]
                                                           

  1%|          | 5470/569592 [4:39:27<536:08:46,  3.42s/it]
  1%|          | 5471/569592 [4:39:30<531:33:10,  3.39s/it]
                                                           

  1%|          | 5471/569592 [4:39:30<531:33:10,  3.39s/it]
  1%|          | 5472/569592 [4:39:34<541:14:02,  3.45s/it]
                                                           

  1%|          | 5472/569592 [4:39:34<541:14:02,  3.45s/it]
  1%|          | 5473/569592 [4:39:37<542:34:56,  3.46s/it]
                                                           

  1%|          | 5473/569592 [4:39:37<542:34:56,  3.46s/it]
  1%|          | 5474/569592 [4:39:38<426:22:01,  2.72s/it]
                                                           

  1%|          | 5474/569592 [4:39:38<426:22:01,  2.72s/it]
  1%|          | 5475/569592 [4:39:42<460:13:44,  2.94s/it]
                                                           

  1%|          | 5475/569592 [4:39:42<460:13:44,  2.94s/it]
  1%|          | 5476/569592 [4:39:42<368:06:26,  2.35s/it]
                                                           

  1%|          | 5476/569592 [4:39:43<368:06:26,  2.35s/it]
  1%|          | 5477/569592 [4:39:46<419:40:05,  2.68s/it]
                                                           

  1%|          | 5477/569592 [4:39:46<419:40:05,  2.68s/it]
  1%|          | 5478/569592 [4:39:49<458:43:48,  2.93s/it]
                                                           

  1%|          | 5478/569592 [4:39:49<458:43:48,  2.93s/it]
  1%|          | 5479/569592 [4:39:53<476:01:14,  3.04s/it]
                                                           

  1%|          | 5479/569592 [4:39:53<476:01:14,  3.04s/it]
  1%|          | 5480/569592 [4:39:54<375:57:42,  2.40s/it]
                                                           

  1%|          | 5480/569592 [4:39:54<375:57:42,  2.40s/it]
  1%|          | 5481/569592 [4:39:55<308:34:13,  1.97s/it]
                                                           

  1%|          | 5481/569592 [4:39:55<308:34:13,  1.97s/it]
  1%|          | 5482/569592 [4:39:56<260:40:09,  1.66s/it]
                                                           

  1%|          | 5482/569592 [4:39:56<260:40:09,  1.66s/it]
  1%|          | 5483/569592 [4:39:56<225:18:20,  1.44s/it]
                                                           

  1%|          | 5483/569592 [4:39:56<225:18:20,  1.44s/it]
  1%|          | 5484/569592 [4:39:57<201:59:08,  1.29s/it]
                                                           

  1%|          | 5484/569592 [4:39:57<201:59:08,  1.29s/it]
  1%|          | 5485/569592 [4:40:01<319:55:52,  2.04s/it]
                                                           

  1%|          | 5485/569592 [4:40:01<319:55:52,  2.04s/it]
  1%|          | 5486/569592 [4:40:02<271:49:13,  1.73s/it]
                                                           

  1%|          | 5486/569592 [4:40:03<271:49:13,  1.73s/it]
  1%|          | 5487/569592 [4:40:03<246:37:29,  1.57s/it]
                                                           

  1%|          | 5487/569592 [4:40:03<246:37:29,  1.57s/it]
  1%|          | 5488/569592 [4:40:07<343:35:46,  2.19s/it]
                                                           

  1%|          | 5488/569592 [4:40:07<343:35:46,  2.19s/it]
  1%|          | 5489/569592 [4:40:08<288:27:23,  1.84s/it]
                                                           

  1%|          | 5489/569592 [4:40:08<288:27:23,  1.84s/it]
  1%|          | 5490/569592 [4:40:10<302:54:41,  1.93s/it]
                                                           

  1%|          | 5490/569592 [4:40:10<302:54:41,  1.93s/it]
  1%|          | 5491/569592 [4:40:14<371:40:47,  2.37s/it]
                                                           

  1%|          | 5491/569592 [4:40:14<371:40:47,  2.37s/it]
  1%|          | 5492/569592 [4:40:17<437:17:49,  2.79s/it]
                                                           

  1%|          | 5492/569592 [4:40:17<437:17:49,  2.79s/it]
  1%|          | 5493/569592 [4:40:18<351:53:38,  2.25s/it]
                                                           

  1%|          | 5493/569592 [4:40:18<351:53:38,  2.25s/it]
  1%|          | 5494/569592 [4:40:21<387:53:01,  2.48s/it]
                                                           

  1%|          | 5494/569592 [4:40:21<387:53:01,  2.48s/it]
  1%|          | 5495/569592 [4:40:22<320:02:03,  2.04s/it]
                                                           

  1%|          | 5495/569592 [4:40:22<320:02:03,  2.04s/it]
  1%|          | 5496/569592 [4:40:28<475:12:54,  3.03s/it]
                                                           

  1%|          | 5496/569592 [4:40:28<475:12:54,  3.03s/it]
  1%|          | 5497/569592 [4:40:29<381:17:01,  2.43s/it]
                                                           

  1%|          | 5497/569592 [4:40:29<381:17:01,  2.43s/it]
  1%|          | 5498/569592 [4:40:32<427:58:48,  2.73s/it]
                                                           

  1%|          | 5498/569592 [4:40:32<427:58:48,  2.73s/it]
  1%|          | 5499/569592 [4:40:36<456:22:32,  2.91s/it]
                                                           

  1%|          | 5499/569592 [4:40:36<456:22:32,  2.91s/it]
  1%|          | 5500/569592 [4:40:40<517:11:48,  3.30s/it]
                                                           

  1%|          | 5500/569592 [4:40:40<517:11:48,  3.30s/it]
  1%|          | 5501/569592 [4:40:41<413:37:29,  2.64s/it]
                                                           

  1%|          | 5501/569592 [4:40:41<413:37:29,  2.64s/it]
  1%|          | 5502/569592 [4:40:43<376:58:27,  2.41s/it]
                                                           

  1%|          | 5502/569592 [4:40:43<376:58:27,  2.41s/it]
  1%|          | 5503/569592 [4:40:46<416:14:34,  2.66s/it]
                                                           

  1%|          | 5503/569592 [4:40:46<416:14:34,  2.66s/it]
  1%|          | 5504/569592 [4:40:49<425:04:56,  2.71s/it]
                                                           

  1%|          | 5504/569592 [4:40:49<425:04:56,  2.71s/it]
  1%|          | 5505/569592 [4:40:54<539:24:10,  3.44s/it]
                                                           

  1%|          | 5505/569592 [4:40:54<539:24:10,  3.44s/it]
  1%|          | 5506/569592 [4:40:55<423:12:51,  2.70s/it]
                                                           

  1%|          | 5506/569592 [4:40:55<423:12:51,  2.70s/it]
  1%|          | 5507/569592 [4:40:56<340:39:11,  2.17s/it]
                                                           

  1%|          | 5507/569592 [4:40:56<340:39:11,  2.17s/it]
  1%|          | 5508/569592 [4:40:59<393:53:31,  2.51s/it]
                                                           

  1%|          | 5508/569592 [4:40:59<393:53:31,  2.51s/it]
  1%|          | 5509/569592 [4:41:00<321:07:09,  2.05s/it]
                                                           

  1%|          | 5509/569592 [4:41:00<321:07:09,  2.05s/it]
  1%|          | 5510/569592 [4:41:03<359:16:10,  2.29s/it]
                                                           

  1%|          | 5510/569592 [4:41:03<359:16:10,  2.29s/it]
  1%|          | 5511/569592 [4:41:04<298:23:19,  1.90s/it]
                                                           

  1%|          | 5511/569592 [4:41:04<298:23:19,  1.90s/it]
  1%|          | 5512/569592 [4:41:08<409:34:22,  2.61s/it]
                                                           

  1%|          | 5512/569592 [4:41:08<409:34:22,  2.61s/it]
  1%|          | 5513/569592 [4:41:10<383:56:07,  2.45s/it]
                                                           

  1%|          | 5513/569592 [4:41:10<383:56:07,  2.45s/it]
  1%|          | 5514/569592 [4:41:13<409:49:57,  2.62s/it]
                                                           

  1%|          | 5514/569592 [4:41:13<409:49:57,  2.62s/it]
  1%|          | 5515/569592 [4:41:14<332:38:52,  2.12s/it]
                                                           

  1%|          | 5515/569592 [4:41:14<332:38:52,  2.12s/it]
  1%|          | 5516/569592 [4:41:19<470:33:34,  3.00s/it]
                                                           

  1%|          | 5516/569592 [4:41:19<470:33:34,  3.00s/it]
  1%|          | 5517/569592 [4:41:21<423:05:44,  2.70s/it]
                                                           

  1%|          | 5517/569592 [4:41:21<423:05:44,  2.70s/it]
  1%|          | 5518/569592 [4:41:23<384:02:23,  2.45s/it]
                                                           

  1%|          | 5518/569592 [4:41:23<384:02:23,  2.45s/it]
  1%|          | 5519/569592 [4:41:28<489:48:01,  3.13s/it]
                                                           

  1%|          | 5519/569592 [4:41:28<489:48:01,  3.13s/it]
  1%|          | 5520/569592 [4:41:32<515:05:01,  3.29s/it]
                                                           

  1%|          | 5520/569592 [4:41:32<515:05:01,  3.29s/it]
  1%|          | 5521/569592 [4:41:35<509:30:30,  3.25s/it]
                                                           

  1%|          | 5521/569592 [4:41:35<509:30:30,  3.25s/it]
  1%|          | 5522/569592 [4:41:40<586:06:50,  3.74s/it]
                                                           

  1%|          | 5522/569592 [4:41:40<586:06:50,  3.74s/it]
  1%|          | 5523/569592 [4:41:41<452:58:03,  2.89s/it]
                                                           

  1%|          | 5523/569592 [4:41:41<452:58:03,  2.89s/it]
  1%|          | 5524/569592 [4:41:44<489:26:13,  3.12s/it]
                                                           

  1%|          | 5524/569592 [4:41:44<489:26:13,  3.12s/it]
  1%|          | 5525/569592 [4:41:48<509:05:41,  3.25s/it]
                                                           

  1%|          | 5525/569592 [4:41:48<509:05:41,  3.25s/it]
  1%|          | 5526/569592 [4:41:49<404:57:34,  2.58s/it]
                                                           

  1%|          | 5526/569592 [4:41:49<404:57:34,  2.58s/it]
  1%|          | 5527/569592 [4:41:50<327:48:18,  2.09s/it]
                                                           

  1%|          | 5527/569592 [4:41:50<327:48:18,  2.09s/it]
  1%|          | 5528/569592 [4:41:53<400:52:38,  2.56s/it]
                                                           

  1%|          | 5528/569592 [4:41:53<400:52:38,  2.56s/it]
  1%|          | 5529/569592 [4:41:57<449:18:43,  2.87s/it]
                                                           

  1%|          | 5529/569592 [4:41:57<449:18:43,  2.87s/it]
  1%|          | 5530/569592 [4:41:58<359:55:17,  2.30s/it]
                                                           

  1%|          | 5530/569592 [4:41:58<359:55:17,  2.30s/it]
  1%|          | 5531/569592 [4:42:03<484:27:03,  3.09s/it]
                                                           

  1%|          | 5531/569592 [4:42:03<484:27:03,  3.09s/it]
  1%|          | 5532/569592 [4:42:08<560:31:13,  3.58s/it]
                                                           

  1%|          | 5532/569592 [4:42:08<560:31:13,  3.58s/it]
  1%|          | 5533/569592 [4:42:12<584:35:54,  3.73s/it]
                                                           

  1%|          | 5533/569592 [4:42:12<584:35:54,  3.73s/it]
  1%|          | 5534/569592 [4:42:15<572:50:09,  3.66s/it]
                                                           

  1%|          | 5534/569592 [4:42:15<572:50:09,  3.66s/it]
  1%|          | 5535/569592 [4:42:16<447:02:49,  2.85s/it]
                                                           

  1%|          | 5535/569592 [4:42:16<447:02:49,  2.85s/it]
  1%|          | 5536/569592 [4:42:17<357:07:53,  2.28s/it]
                                                           

  1%|          | 5536/569592 [4:42:17<357:07:53,  2.28s/it]
  1%|          | 5537/569592 [4:42:21<420:11:01,  2.68s/it]
                                                           

  1%|          | 5537/569592 [4:42:21<420:11:01,  2.68s/it]
  1%|          | 5538/569592 [4:42:22<339:41:50,  2.17s/it]
                                                           

  1%|          | 5538/569592 [4:42:22<339:41:50,  2.17s/it]
  1%|          | 5539/569592 [4:42:27<473:23:47,  3.02s/it]
                                                           

  1%|          | 5539/569592 [4:42:27<473:23:47,  3.02s/it]
  1%|          | 5540/569592 [4:42:28<374:47:13,  2.39s/it]
                                                           

  1%|          | 5540/569592 [4:42:28<374:47:13,  2.39s/it]
  1%|          | 5541/569592 [4:42:32<466:42:31,  2.98s/it]
                                                           

  1%|          | 5541/569592 [4:42:32<466:42:31,  2.98s/it]
  1%|          | 5542/569592 [4:42:36<495:09:45,  3.16s/it]
                                                           

  1%|          | 5542/569592 [4:42:36<495:09:45,  3.16s/it]
  1%|          | 5543/569592 [4:42:39<493:40:12,  3.15s/it]
                                                           

  1%|          | 5543/569592 [4:42:39<493:40:12,  3.15s/it]
  1%|          | 5544/569592 [4:42:43<561:42:47,  3.59s/it]
                                                           

  1%|          | 5544/569592 [4:42:43<561:42:47,  3.59s/it]
  1%|          | 5545/569592 [4:42:48<617:48:08,  3.94s/it]
                                                           

  1%|          | 5545/569592 [4:42:48<617:48:08,  3.94s/it]
  1%|          | 5546/569592 [4:42:53<647:14:31,  4.13s/it]
                                                           

  1%|          | 5546/569592 [4:42:53<647:14:31,  4.13s/it]
  1%|          | 5547/569592 [4:42:57<661:45:28,  4.22s/it]
                                                           

  1%|          | 5547/569592 [4:42:57<661:45:28,  4.22s/it]
  1%|          | 5548/569592 [4:43:01<654:05:05,  4.17s/it]
                                                           

  1%|          | 5548/569592 [4:43:01<654:05:05,  4.17s/it]
  1%|          | 5549/569592 [4:43:04<599:47:55,  3.83s/it]
                                                           

  1%|          | 5549/569592 [4:43:04<599:47:55,  3.83s/it]
  1%|          | 5550/569592 [4:43:09<635:10:32,  4.05s/it]
                                                           

  1%|          | 5550/569592 [4:43:09<635:10:32,  4.05s/it]
  1%|          | 5551/569592 [4:43:12<611:09:37,  3.90s/it]
                                                           

  1%|          | 5551/569592 [4:43:12<611:09:37,  3.90s/it]
  1%|          | 5552/569592 [4:43:17<664:26:26,  4.24s/it]
                                                           

  1%|          | 5552/569592 [4:43:17<664:26:26,  4.24s/it]
  1%|          | 5553/569592 [4:43:21<615:42:11,  3.93s/it]
                                                           

  1%|          | 5553/569592 [4:43:21<615:42:11,  3.93s/it]
  1%|          | 5554/569592 [4:43:24<587:04:41,  3.75s/it]
                                                           

  1%|          | 5554/569592 [4:43:24<587:04:41,  3.75s/it]
  1%|          | 5555/569592 [4:43:29<643:51:25,  4.11s/it]
                                                           

  1%|          | 5555/569592 [4:43:29<643:51:25,  4.11s/it]
  1%|          | 5556/569592 [4:43:32<602:51:20,  3.85s/it]
                                                           

  1%|          | 5556/569592 [4:43:32<602:51:20,  3.85s/it]
  1%|          | 5557/569592 [4:43:36<599:32:19,  3.83s/it]
                                                           

  1%|          | 5557/569592 [4:43:36<599:32:19,  3.83s/it]
  1%|          | 5558/5695/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91249900 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
92 [4:43:39<567:06:02,  3.62s/it]
                                                           

  1%|          | 5558/569592 [4:43:39<567:06:02,  3.62s/it]
  1%|          | 5559/569592 [4:43:44<655:27:15,  4.18s/it]
                                                           

  1%|          | 5559/569592 [4:43:44<655:27:15,  4.18s/it]
  1%|          | 5560/569592 [4:43:45<499:33:33,  3.19s/it]
                                                           

  1%|          | 5560/569592 [4:43:45<499:33:33,  3.19s/it]
  1%|          | 5561/569592 [4:43:49<542:00:24,  3.46s/it]
                                                           

  1%|          | 5561/569592 [4:43:49<542:00:24,  3.46s/it]
  1%|          | 5562/569592 [4:43:53<554:30:40,  3.54s/it]
                                                           

  1%|          | 5562/569592 [4:43:53<554:30:40,  3.54s/it]
  1%|          | 5563/569592 [4:43:58<613:34:58,  3.92s/it]
                                                           

  1%|          | 5563/569592 [4:43:58<613:34:58,  3.92s/it]
  1%|          | 5564/569592 [4:44:03<662:07:20,  4.23s/it]
                                                           

  1%|          | 5564/569592 [4:44:03<662:07:20,  4.23s/it]
  1%|          | 5565/569592 [4:44:04<505:28:30,  3.23s/it]
                                                           

  1%|          | 5565/569592 [4:44:04<505:28:30,  3.23s/it]
  1%|          | 5566/569592 [4:44:07<499:29:18,  3.19s/it]
                                                           

  1%|          | 5566/569592 [4:44:07<499:29:18,  3.19s/it]
  1%|          | 5567/569592 [4:44:11<531:41:04,  3.39s/it]
                                                           

  1%|          | 5567/569592 [4:44:11<531:41:04,  3.39s/it]
  1%|          | 5568/569592 [4:44:15<569:25:43,  3.63s/it]
                                                           

  1%|          | 5568/569592 [4:44:15<569:25:43,  3.63s/it]
  1%|          | 5569/569592 [4:44:20<621:08:42,  3.96s/it]
                                                           

  1%|          | 5569/569592 [4:44:20<621:08:42,  3.96s/it]
  1%|          | 5570/569592 [4:44:23<582:20:49,  3.72s/it]
                                                           

  1%|          | 5570/569592 [4:44:23<582:20:49,  3.72s/it]
  1%|          | 5571/569592 [4:44:26<571:09:57,  3.65s/it]
                                                           

  1%|          | 5571/569592 [4:44:26<571:09:57,  3.65s/it]
  1%|          | 5572/569592 [4:44:29<549:29:23,  3.51s/it]
                                                           

  1%|          | 5572/569592 [4:44:29<549:29:23,  3.51s/it]
  1%|          | 5573/569592 [4:44:33<566:28:21,  3.62s/it]
                                                           

  1%|          | 5573/569592 [4:44:33<566:28:21,  3.62s/it]
  1%|          | 5574/569592 [4:44:37<587:53:55,  3.75s/it]
                                                           

  1%|          | 5574/569592 [4:44:37<587:53:55,  3.75s/it]
  1%|          | 5575/569592 [4:44:41<562:59:53,  3.59s/it]
                                                           

  1%|          | 5575/569592 [4:44:41<562:59:53,  3.59s/it]
  1%|          | 5576/569592 [4:44:42<438:04:29,  2.80s/it]
                                                           

  1%|          | 5576/569592 [4:44:42<438:04:29,  2.80s/it]
  1%|          | 5577/569592 [4:44:45<469:52:03,  3.00s/it]
                                                           

  1%|          | 5577/569592 [4:44:45<469:52:03,  3.00s/it]
  1%|          | 5578/569592 [4:44:46<377:57:05,  2.41s/it]
                                                           

  1%|          | 5578/569592 [4:44:46<377:57:05,  2.41s/it]
  1%|          | 5579/569592 [4:44:49<420:13:17,  2.68s/it]
                                                           

  1%|          | 5579/569592 [4:44:49<420:13:17,  2.68s/it]
  1%|          | 5580/569592 [4:44:50<340:48:42,  2.18s/it]
                                                           

  1%|          | 5580/569592 [4:44:50<340:48:42,  2.18s/it]
  1%|          | 5581/569592 [4:44:54<418:26:42,  2.67s/it]
                                                           

  1%|          | 5581/569592 [4:44:54<418:26:42,  2.67s/it]
  1%|          | 5582/569592 [4:44:58<449:33:19,  2.87s/it]
                                                           

  1%|          | 5582/569592 [4:44:58<449:33:19,  2.87s/it]
  1%|          | 5583/569592 [4:45:02<541:48:36,  3.46s/it]
                                                           

  1%|          | 5583/569592 [4:45:02<541:48:36,  3.46s/it]
  1%|          | 5584/569592 [4:45:06<534:23:35,  3.41s/it]
                                                           

  1%|          | 5584/569592 [4:45:06<534:23:35,  3.41s/it]
  1%|          | 5585/569592 [4:45:10<594:21:25,  3.79s/it]
                                                           

  1%|          | 5585/569592 [4:45:10<594:21:25,  3.79s/it]
  1%|          | 5586/569592 [4:45:14<568:02:29,  3.63s/it]
                                                           

  1%|          | 5586/569592 [4:45:14<568:02:29,  3.63s/it]
  1%|          | 5587/569592 [4:45:18<590:32:16,  3.77s/it]
                                                           

  1%|          | 5587/569592 [4:45:18<590:32:16,  3.77s/it]
  1%|          | 5588/569592 [4:45:21<579:04:03,  3.70s/it]
                                                           

  1%|          | 5588/569592 [4:45:21<579:04:03,  3.70s/it]
  1%|          | 5589/569592 [4:45:24<551:06:22,  3.52s/it]
                                                           

  1%|          | 5589/569592 [4:45:24<551:06:22,  3.52s/it]
  1%|          | 5590/569592 [4:45:29<604:51:43,  3.86s/it]
                                                           

  1%|          | 5590/569592 [4:45:29<604:51:43,  3.86s/it]
  1%|          | 5591/569592 [4:45:32<571:09:30,  3.65s/it]
                                                           

  1%|          | 5591/569592 [4:45:32<571:09:30,  3.65s/it]
  1%|          | 5592/569592 [4:45:36<571:24:42,  3.65s/it]
                                                           

  1%|          | 5592/569592 [4:45:36<571:24:42,  3.65s/it]
  1%|          | 5593/569592 [4:45:37<443:40:09,  2.83s/it]
                                                           

  1%|          | 5593/569592 [4:45:37<443:40:09,  2.83s/it]
  1%|          | 5594/569592 [4:45:38<355:19:49,  2.27s/it]
                                                           

  1%|          | 5594/569592 [4:45:38<355:19:49,  2.27s/it]
  1%|          | 5595/569592 [4:45:39<294:19:32,  1.88s/it]
                                                           

  1%|          | 5595/569592 [4:45:39<294:19:32,  1.88s/it]
  1%|          | 5596/569592 [4:45:43<398:29:11,  2.54s/it]
                                                           

  1%|          | 5596/569592 [4:45:43<398:29:11,  2.54s/it]
  1%|          | 5597/569592 [4:45:48<506:44:31,  3.23s/it]
                                                           

  1%|          | 5597/569592 [4:45:48<506:44:31,  3.23s/it]
  1%|          | 5598/569592 [4:45:49<399:53:50,  2.55s/it]
                                                           

  1%|          | 5598/569592 [4:45:49<399:53:50,  2.55s/it]
  1%|          | 5599/569592 [4:45:50<325:51:56,  2.08s/it]
                                                           

  1%|          | 5599/569592 [4:45:50<325:51:56,  2.08s/it]
  1%|          | 5600/569592 [4:45:50<274:19:32,  1.75s/it]
                                                           

  1%|          | 5600/569592 [4:45:51<274:19:32,  1.75s/it]
  1%|          | 5601/569592 [4:45:51<237:14:48,  1.51s/it]
                                                           

  1%|          | 5601/569592 [4:45:51<237:14:48,  1.51s/it]
  1%|          | 5602/569592 [4:45:57<410:38:25,  2.62s/it]
                                                           

  1%|          | 5602/569592 [4:45:57<410:38:25,  2.62s/it]
  1%|          | 5603/569592 [4:45:58<340:23:17,  2.17s/it]
                                                           

  1%|          | 5603/569592 [4:45:58<340:23:17,  2.17s/it]
  1%|          | 5604/569592 [4:46:01<405:16:24,  2.59s/it]
                                                           

  1%|          | 5604/569592 [4:46:01<405:16:24,  2.59s/it]
  1%|          | 5605/569592 [4:46:02<328:46:56,  2.10s/it]
                                                           

  1%|          | 5605/569592 [4:46:02<328:46:56,  2.10s/it]
  1%|          | 5606/569592 [4:46:03<275:37:45,  1.76s/it]
                                                           

  1%|          | 5606/569592 [4:46:03<275:37:45,  1.76s/it]
  1%|          | 5607/569592 [4:46:04<237:52:13,  1.52s/it]
                                                           

  1%|          | 5607/569592 [4:46:04<237:52:13,  1.52s/it]
  1%|          | 5608/569592 [4:46:07<284:06:09,  1.81s/it]
                                                           

  1%|          | 5608/569592 [4:46:07<284:06:09,  1.81s/it]
  1%|          | 5609/569592 [4:46:11<408:03:21,  2.60s/it]
                                                           

  1%|          | 5609/569592 [4:46:11<408:03:21,  2.60s/it]
  1%|          | 5610/569592 [4:46:12<332:08:08,  2.12s/it]
                                                           

  1%|          | 5610/569592 [4:46:12<332:08:08,  2.12s/it]
  1%|          | 5611/569592 [4:46:13<278:26:34,  1.78s/it]
                                                           

  1%|          | 5611/569592 [4:46:13<278:26:34,  1.78s/it]
  1%|          | 5612/569592 [4:46:17<395:17:08,  2.52s/it]
                                                           

  1%|          | 5612/569592 [4:46:17<395:17:08,  2.52s/it]
  1%|          | 5613/569592 [4:46:21<454:03:06,  2.90s/it]
                                                           

  1%|          | 5613/569592 [4:46:21<454:03:06,  2.90s/it]
  1%|          | 5614/569592 [4:46:24<472:30:43,  3.02s/it]
                                                           

  1%|          | 5614/569592 [4:46:25<472:30:43,  3.02s/it]
  1%|          | 5615/569592 [4:46:25<376:26:36,  2.40s/it]
                                                           

  1%|          | 5615/569592 [4:46:25<376:26:36,  2.40s/it]
  1%|          | 5616/569592 [4:46:27<329:17:54,  2.10s/it]
                                                           

  1%|          | 5616/569592 [4:46:27<329:17:54,  2.10s/it]
  1%|          | 5617/569592 [4:46:32<453:43:34,  2.90s/it]
                                                           

  1%|          | 5617/569592 [4:46:32<453:43:34,  2.90s/it]
  1%|          | 5618/569592 [4:46:33<362:49:57,  2.32s/it]
                                                           

  1%|          | 5618/569592 [4:46:33<362:49:57,  2.32s/it]
  1%|          | 5619/569592 [4:46:34<301:10:25,  1.92s/it]
                                                           

  1%|          | 5619/569592 [4:46:34<301:10:25,  1.92s/it]
  1%|          | 5620/569592 [4:46:37<349:49:38,  2.23s/it]
                                                           

  1%|          | 5620/569592 [4:46:37<349:49:38,  2.23s/it]
  1%|          | 5621/569592 [4:46:41<459:48:46,  2.94s/it]
                                                           

  1%|          | 5621/569592 [4:46:41<459:48:46,  2.94s/it]
  1%|          | 5622/569592 [4:46:45<483:12:34,  3.08s/it]
                                                           

  1%|          | 5622/569592 [4:46:45<483:12:34,  3.08s/it]
  1%|          | 5623/569592 [4:46:45<383:56:33,  2.45s/it]
                                                           

  1%|          | 5623/569592 [4:46:46<383:56:33,  2.45s/it]
  1%|          | 5624/569592 [4:46:47<318:19:46,  2.03s/it]
                                                           

  1%|          | 5624/569592 [4:46:47<318:19:46,  2.03s/it]
  1%|          | 5625/569592 [4:46:52<493:02:18,  3.15s/it]
                                                           

  1%|          | 5625/569592 [4:46:52<493:02:18,  3.15s/it]
  1%|          | 5626/569592 [4:46:53<392:56:49,  2.51s/it]
                                                           

  1%|          | 5626/569592 [4:46:53<392:56:49,  2.51s/it]
  1%|          | 5627/569592 [4:46:55<351:04:38,  2.24s/it]
                                                           

  1%|          | 5627/569592 [4:46:55<351:04:38,  2.24s/it]
  1%|          | 5628/569592 [4:46:57<365:19:17,  2.33s/it]
                                                           

  1%|          | 5628/569592 [4:46:57<365:19:17,  2.33s/it]
  1%|          | 5629/569592 [4:47:03<501:04:54,  3.20s/it]
                                                           

  1%|          | 5629/569592 [4:47:03<501:04:54,  3.20s/it]
  1%|          | 5630/569592 [4:47:04<394:20:12,  2.52s/it]
                                                           

  1%|          | 5630/569592 [4:47:04<394:20:12,  2.52s/it]
  1%|          | 5631/569592 [4:47:05<327:15:43,  2.09s/it]
                                                           

  1%|          | 5631/569592 [4:47:05<327:15:43,  2.09s/it]
  1%|          | 5632/569592 [4:47:08<365:04:00,  2.33s/it]
                                                           

  1%|          | 5632/569592 [4:47:08<365:04:00,  2.33s/it]
  1%|          | 5633/569592 [4:47:13<501:18:20,  3.20s/it]
                                                           

  1%|          | 5633/569592 [4:47:13<501:18:20,  3.20s/it]
  1%|          | 5634/569592 [4:47:16<504:49:24,  3.22s/it]
                                                           

  1%|          | 5634/569592 [4:47:16<504:49:24,  3.22s/it]
  1%|          | 5635/569592 [4:47:19<506:57:08,  3.24s/it]
                                                           

  1%|          | 5635/569592 [4:47:19<506:57:08,  3.24s/it]
  1%|          | 5636/569592 [4:47:24<555:30:45,  3.55s/it]
                                                           

  1%|          | 5636/569592 [4:47:24<555:30:45,  3.55s/it]
  1%|          | 5637/569592 [4:47:28<614:51:08,  3.92s/it]
                                                           

  1%|          | 5637/569592 [4:47:28<614:51:08,  3.92s/it]
  1%|          | 5638/569592 [4:47:32<577:32:05,  3.69s/it]
                                                           

  1%|          | 5638/569592 [4:47:32<577:32:05,  3.69s/it]
  1%|          | 5639/569592 [4:47:33<447:23:54,  2.86s/it]
                                                           

  1%|          | 5639/569592 [4:47:33<447:23:54,  2.86s/it]
  1%|          | 5640/569592 [4:47:33<355:36:10,  2.27s/it]
                                                           

  1%|          | 5640/569592 [4:47:33<355:36:10,  2.27s/it]
  1%|          | 5641/569592 [4:47:34<295:36:34,  1.89s/it]
                                                           

  1%|          | 5641/569592 [4:47:34<295:36:34,  1.89s/it]
  1%|          | 5642/569592 [4:47:35<250:51:29,  1.60s/it]
                                                           

  1%|          | 5642/569592 [4:47:35<250:51:29,  1.60s/it]
  1%|          | 5643/569592 [4:47:39<357:26:49,  2.28s/it]
                                                           

  1%|          | 5643/569592 [4:47:39<357:26:49,  2.28s/it]
  1%|          | 5644/569592 [4:47:43<444:21:27,  2.84s/it]
                                                           

  1%|          | 5644/569592 [4:47:43<444:21:27,  2.84s/it]
  1%|          | 5645/569592 [4:47:47<480:02:05,  3.06s/it]
                                                           

  1%|          | 5645/569592 [4:47:47<480:02:05,  3.06s/it]
  1%|          | 5646/569592 [4:47:50<497:47:43,  3.18s/it]
                                                           

  1%|          | 5646/569592 [4:47:50<497:47:43,  3.18s/it]
  1%|          | 5647/569592 [4:47:54<500:51:11,  3.20s/it]
                                                           

  1%|          | 5647/569592 [4:47:54<500:51:11,  3.20s/it]
  1%|          | 5648/569592 [4:47:55<392:54:45,  2.51s/it]
                                                           

  1%|          | 5648/569592 [4:47:55<392:54:45,  2.51s/it]
  1%|          | 5649/569592 [4:47:58<445:25:10,  2.84s/it]
                                                           

  1%|          | 5649/569592 [4:47:58<445:25:10,  2.84s/it]
  1%|          | 5650/569592 [4:47:59<359:32:59,  2.30s/it]
                                                           

  1%|          | 5650/569592 [4:47:59<359:32:59,  2.30s/it]
  1%|          | 5651/569592 [4:48:03<409:21:42,  2.61s/it]
                                                           

  1%|          | 5651/569592 [4:48:03<409:21:42,  2.61s/it]
  1%|          | 5652/569592 [4:48:06<462:43:29,  2.95s/it]
                                                           

  1%|          | 5652/569592 [4:48:06<462:43:29,  2.95s/it]
  1%|          | 5653/569592 [4:48:10<496:13:24,  3.17s/it]
                                                           

  1%|          | 5653/569592 [4:48:10<496:13:24,  3.17s/it]
  1%|          | 5654/569592 [4:48:11<407:46:37,  2.60s/it]
                                                           

  1%|          | 5654/569592 [4:48:11<407:46:37,  2.60s/it]
  1%|          | 5655/569592 [4:48:16<509:59:39,  3.26s/it]
                                                           

  1%|          | 5655/569592 [4:48:16<509:59:39,  3.26s/it]
  1%|          | 5656/569592 [4:48:19<515:00:58,  3.29s/it]
                                                           

  1%|          | 5656/569592 [4:48:19<515:00:58,  3.29s/it]
  1%|          | 5657/569592 [4:48:24<579:16:34,  3.70s/it]
                                                           

  1%|          | 5657/569592 [4:48:24<579:16:34,  3.70s/it]
  1%|          | 5658/569592 [4:48:25<447:16:19,  2.86s/it]
                                                           

  1%|          | 5658/569592 [4:48:25<447:16:19,  2.86s/it]
  1%|          | 5659/569592 [4:48:28<470:53:45,  3.01s/it]
                                                           

  1%|          | 5659/569592 [4:48:28<470:53:45,  3.01s/it]
  1%|          | 5660/569592 [4:48:33<537:45:35,  3.43s/it]
                                                           

  1%|          | 5660/569592 [4:48:33<537:45:35,  3.43s/it]
  1%|          | 5661/569592 [4:48:36<551:59:43,  3.52s/it]
                                                           

  1%|          | 5661/569592 [4:48:36<551:59:43,  3.52s/it]
  1%|          | 5662/569592 [4:48:39<528:24:18,  3.37s/it]
                                                           

  1%|          | 5662/569592 [4:48:39<528:24:18,  3.37s/it]
  1%|          | 5663/569592 [4:48:43<535:45:36,  3.42s/it]
                                                           

  1%|          | 5663/569592 [4:48:43<535:45:36,  3.42s/it]
  1%|          | 5664/569592 [4:48:48<594:13:48,  3.79s/it]
                                                           

  1%|          | 5664/569592 [4:48:48<594:13:48,  3.79s/it]
  1%|          | 5665/569592 [4:48:52<631:30:16,  4.03s/it]
                                                           

  1%|          | 5665/569592 [4:48:52<631:30:16,  4.03s/it]
  1%|          | 5666/569592 [4:48:57<659:13:25,  4.21s/it]
                                                           

  1%|          | 5666/569592 [4:48:57<659:13:25,  4.21s/it]
  1%|          | 5667/569592 [4:49:01<635:44:54,  4.06s/it]
                                                           

  1%|          | 5667/569592 [4:49:01<635:44:54,  4.06s/it]
  1%|          | 5668/569592 [4:49:05<662:29:52,  4.23s/it]
                                                           

  1%|          | 5668/569592 [4:49:05<662:29:52,  4.23s/it]
  1%|          | 5669/569592 [4:49:10<667:04:31,  4.26s/it]
                                                           

  1%|          | 5669/569592 [4:49:10<667:04:31,  4.26s/it]
  1%|          | 5670/569592 [4:49:13<613:43:25,  3.92s/it]
                                                           

  1%|          | 5670/569592 [4:49:13<613:43:25,  3.92s/it]
  1%|          | 5671/569592 [4:49:16<584:51:15,  3.73s/it]
                                                           

  1%|          | 5671/569592 [4:49:16<584:51:15,  3.73s/it]
  1%|          | 5672/569592 [4:49:19<569:17:37,  3.63s/it]
                                                           

  1%|          | 5672/569592 [4:49:19<569:17:37,  3.63s/it]
  1%|          | 5673/569592 [4:49:23<557:01:17,  3.56s/it]
                                                           

  1%|          | 5673/569592 [4:49:23<557:01:17,  3.56s/it]
  1%|          | 5674/569592 [4:49:26<552:18:44,  3.53s/it]
                                                           

  1%|          | 5674/569592 [4:49:26<552:18:44,  3.53s/it]
  1%|          | 5675/569592 [4:49:31<604:16:07,  3.86s/it]
                                                           

  1%|          | 5675/569592 [4:49:31<604:16:07,  3.86s/it]
  1%|          | 5676/569592 [4:49:35<605:41:35,  3.87s/it]
                                                           

  1%|          | 5676/569592 [4:49:35<605:41:35,  3/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
.87s/it]
  1%|          | 5677/569592 [4:49:39<641:05:35,  4.09s/it]
                                                           

  1%|          | 5677/569592 [4:49:39<641:05:35,  4.09s/it]
  1%|          | 5678/569592 [4:49:42<591:29:30,  3.78s/it]
                                                           

  1%|          | 5678/569592 [4:49:42<591:29:30,  3.78s/it]
  1%|          | 5679/569592 [4:49:46<606:48:16,  3.87s/it]
                                                           

  1%|          | 5679/569592 [4:49:46<606:48:16,  3.87s/it]
  1%|          | 5680/569592 [4:49:50<582:10:22,  3.72s/it]
                                                           

  1%|          | 5680/569592 [4:49:50<582:10:22,  3.72s/it]
  1%|          | 5681/569592 [4:49:53<552:20:24,  3.53s/it]
                                                           

  1%|          | 5681/569592 [4:49:53<552:20:24,  3.53s/it]
  1%|          | 5682/569592 [4:49:58<639:14:31,  4.08s/it]
                                                           

  1%|          | 5682/569592 [4:49:58<639:14:31,  4.08s/it]
  1%|          | 5683/569592 [4:49:59<488:44:00,  3.12s/it]
                                                           

  1%|          | 5683/569592 [4:49:59<488:44:00,  3.12s/it]
  1%|          | 5684/569592 [4:50:02<486:00:01,  3.10s/it]
                                                           

  1%|          | 5684/569592 [4:50:02<486:00:01,  3.10s/it]
  1%|          | 5685/569592 [4:50:07<553:04:18,  3.53s/it]
                                                           

  1%|          | 5685/569592 [4:50:07<553:04:18,  3.53s/it]
  1%|          | 5686/569592 [4:50:10<558:07:25,  3.56s/it]
                                                           

  1%|          | 5686/569592 [4:50:10<558:07:25,  3.56s/it]
  1%|          | 5687/569592 [4:50:15<612:11:31,  3.91s/it]
                                                           

  1%|          | 5687/569592 [4:50:15<612:11:31,  3.91s/it]
  1%|          | 5688/569592 [4:50:20<639:08:05,  4.08s/it]
                                                           

  1%|          | 5688/569592 [4:50:20<639:08:05,  4.08s/it]
  1%|          | 5689/569592 [4:50:23<600:16:16,  3.83s/it]
                                                           

  1%|          | 5689/569592 [4:50:23<600:16:16,  3.83s/it]
  1%|          | 5690/569592 [4:50:28<659:30:35,  4.21s/it]
                                                           

  1%|          | 5690/569592 [4:50:28<659:30:35,  4.21s/it]
  1%|          | 5691/569592 [4:50:31<621:55:11,  3.97s/it]
                                                           

  1%|          | 5691/569592 [4:50:31<621:55:11,  3.97s/it]
  1%|          | 5692/569592 [4:50:34<577:40:59,  3.69s/it]
                                                           

  1%|          | 5692/569592 [4:50:34<577:40:59,  3.69s/it]
  1%|          | 5693/569592 [4:50:35<446:52:04,  2.85s/it]
                                                           

  1%|          | 5693/569592 [4:50:35<446:52:04,  2.85s/it]
  1%|          | 5694/569592 [4:50:39<480:49:43,  3.07s/it]
                                                           

  1%|          | 5694/569592 [4:50:39<480:49:43,  3.07s/it]
  1%|          | 5695/569592 [4:50:42<489:39:56,  3.13s/it]
                                                           

  1%|          | 5695/569592 [4:50:42<489:39:56,  3.13s/it]
  1%|          | 5696/569592 [4:50:46<515:09:43,  3.29s/it]
                                                           

  1%|          | 5696/569592 [4:50:46<515:09:43,  3.29s/it]
  1%|          | 5697/569592 [4:50:49<509:13:38,  3.25s/it]
                                                           

  1%|          | 5697/569592 [4:50:49<509:13:38,  3.25s/it]
  1%|          | 5698/569592 [4:50:52<509:46:49,  3.25s/it]
                                                           

  1%|          | 5698/569592 [4:50:52<509:46:49,  3.25s/it]
  1%|          | 5699/569592 [4:50:57<587:04:55,  3.75s/it]
                                             /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90192960 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
              

  1%|          | 5699/569592 [4:50:57<587:04:55,  3.75s/it]
  1%|          | 5700/569592 [4:51:01<571:46:56,  3.65s/it]
                                                           

  1%|          | 5700/569592 [4:51:01<571:46:56,  3.65s/it]
  1%|          | 5701/569592 [4:51:01<441:57:03,  2.82s/it]
                                                           

  1%|          | 5701/569592 [4:51:01<441:57:03,  2.82s/it]
  1%|          | 5702/569592 [4:51:05<458:59:01,  2.93s/it]
                                                           

  1%|          | 5702/569592 [4:51:05<458:59:01,  2.93s/it]
  1%|          | 5703/569592 [4:51:08<487:17:50,  3.11s/it]
                                                           

  1%|          | 5703/569592 [4:51:08<487:17:50,  3.11s/it]
  1%|          | 5704/569592 [4:51:09<386:54:08,  2.47s/it]
                                                           

  1%|          | 5704/569592 [4:51:09<386:54:08,  2.47s/it]
  1%|          | 5705/569592 [4:51:13<458:59:15,  2.93s/it]
                                                           

  1%|          | 5705/569592 [4:51:13<458:59:15,  2.93s/it]
  1%|          | 5706/569592 [4:51:17<517:59:28,  3.31s/it]
                                                           

  1%|          | 5706/569592 [4:51:17<517:59:28,  3.31s/it]
  1%|          | 5707/569592 [4:51:21<529:46:46,  3.38s/it]
                                                           

  1%|          | 5707/569592 [4:51:21<529:46:46,  3.38s/it]
  1%|          | 5708/569592 [4:51:22<414:21:27,  2.65s/it]
                                                           

  1%|          | 5708/569592 [4:51:22<414:21:27,  2.65s/it]
  1%|          | 5709/569592 [4:51:26<499:14:33,  3.19s/it]
                                                           

  1%|          | 5709/569592 [4:51:26<499:14:33,  3.19s/it]
  1%|          | 5710/569592 [4:51:29<491:46:06,  3.14s/it]
                                                           

  1%|          | 5710/569592 [4:51:29<491:46:06,  3.14s/it]
  1%|          | 5711/569592 [4:51:30<387:27:42,  2.47s/it]
                                                           

  1%|          | 5711/569592 [4:51:30<387:27:42,  2.47s/it]
  1%|          | 5712/569592 [4:51:31<317:05:04,  2.02s/it]
                                                           

  1%|          | 5712/569592 [4:51:31<317:05:04,  2.02s/it]
  1%|          | 5713/569592 [4:51:36<470:12:50,  3.00s/it]
                                                           

  1%|          | 5713/569592 [4:51:36<470:12:50,  3.00s/it]
  1%|          | 5714/569592 [4:51:40<492:55:49,  3.15s/it]
                                                           

  1%|          | 5714/569592 [4:51:40<492:55:49,  3.15s/it]
  1%|          | 5715/569592 [4:51:41<387:34:38,  2.47s/it]
                                                           

  1%|          | 5715/569592 [4:51:41<387:34:38,  2.47s/it]
  1%|          | 5716/569592 [4:51:42<314:15:23,  2.01s/it]
                                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                   

  1%|          | 5716/569592 [4:51:42<314:15:23,  2.01s/it]
  1%|          | 5717/569592 [4:51:43<264:58:41,  1.69s/it]
                                                           

  1%|          | 5717/569592 [4:51:43<264:58:41,  1.69s/it]
  1%|          | 5718/569592 [4:51:46<358:45:27,  2.29s/it]
                                                           

  1%|          | 5718/569592 [4:51:46<358:45:27,  2.29s/it]
  1%|          | 5719/569592 [4:51:48<306:34:40,  1.96s/it]
                                                           

  1%|          | 5719/569592 [4:51:48<306:34:40,  1.96s/it]
  1%|          | 5720/569592 [4:51:53<453:26:38,  2.89s/it]
                                                           

  1%|          | 5720/569592 [4:51:53<453:26:38,  2.89s/it]
  1%|          | 5721/569592 [4:51:54<364:47:41,  2.33s/it]
                                                           

  1%|          | 5721/569592 [4:51:54<364:47:41,  2.33s/it]
  1%|          | 5722/569592 [4:51:55<301:13:19,  1.92s/it]
                                                           

  1%|          | 5722/569592 [4:51:55<301:13:19,  1.92s/it]
  1%|          | 5723/569592 [4:51:56<255:24:54,  1.63s/it]
                                                           

  1%|          | 5723/569592 [4:51:56<255:24:54,  1.63s/it]
  1%|          | 5724/569592 [4:51:57<224:25:10,  1.43s/it]
                                                           

  1%|          | 5724/569592 [4:51:57<224:25:10,  1.43s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (96000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  1%|          | 5725/569592 [4:52:00<324:23:30,  2.07s/it]
                                                           

  1%|          | 5725/569592 [4:52:00<324:23:30,  2.07s/it]
  1%|          | 5726/569592 [4:52:02<328:34:41,  2.10s/it]
                                                           

  1%|          | 5726/569592 [4:52:02<328:34:41,  2.10s/it]
  1%|          | 5727/569592 [4:52:03<279:43:04,  1.79s/it]
                                                           

  1%|          | 5727/569592 [4:52:03<279:43:04,  1.79s/it]
  1%|          | 5728/569592 [4:52:06<303:48:53,  1.94s/it]
                                                           

  1%|          | 5728/569592 [4:52:06<303:48:53,  1.94s/it]
  1%|          | 5729/569592 [4:52:07<261:55:53,  1.67s/it]
                                                           

  1%|          | 5729/569592 [4:52:07<261:55:53,  1.67s/it]
  1%|          | 5730/569592 [4:52:12<422:38:42,  2.70s/it]
                                                           

  1%|          | 5730/569592 [4:52:12<422:38:42,  2.70s/it]
  1%|          | 5731/569592 [4:52:14<422:47:56,  2.70s/it]
                                                           

  1%|          | 5731/569592 [4:52:14<422:47:56,  2.70s/it]
  1%|          | 5732/569592 [4:52:18<450:54:11,  2.88s/it]
                                                           

  1%|          | 5732/569592 [4:52:18<450:54:11,  2.88s/it]
  1%|          | 5733/569592 [4:52:19<362:14:06,  2.31s/it]
                                                           

  1%|          | 5733/569592 [4:52:19<362:14:06,  2.31s/it]
  1%|          | 5734/569592 [4:52:20<323:10:58,  2.06s/it]
                                                           

  1%|          | 5734/569592 [4:52:20<323:10:58,  2.06s/it]
  1%|          | 5735/569592 [4:52:25<441:21:38,  2.82s/it]
                                                           

  1%|          | 5735/569592 [4:52:25<441:21:38,  2.82s/it]
  1%|          | 5736/569592 [4:52:26<361:02:05,  2.31s/it]
                                                           

  1%|          | 5736/569592 [4:52:26<361:02:05,  2.31s/it]
  1%|          | 5737/569592 [4:52:28<332:17:52,  2.12s/it]
                                                           

  1%|          | 5737/569592 [4:52:28<332:17:52,  2.12s/it]
  1%|          | 5738/569592 [4:52:32<450:18:08,  2.88s/it]
                                                           

  1%|          | 5738/569592 [4:52:32<450:18:08,  2.88s/it]
  1%|          | 5739/569592 [4:52:34<410:47:00,  2.62s/it]
                                                           

  1%|          | 5739/569592 [4:52:34<410:47:00,  2.62s/it]
  1%|          | 5740/569592 [4:52:38<470:24:13,  3.00s/it]
                                                           

  1%|          | 5740/569592 [4:52:38<470:24:13,  3.00s/it]
  1%|          | 5741/569592 [4:52:39<375:04:39,  2.39s/it]
                                                           

  1%|          | 5741/569592 [4:52:39<375:04:39,  2.39s/it]
  1%|          | 5742/569592 [4:52:41<343:38:46,  2.19s/it]
                                                           

  1%|          | 5742/569592 [4:52:41<343:38:46,  2.19s/it]
  1%|          | 5743/569592 [4:52:45<432:03:07,  2.76s/it]
                                                           

  1%|          | 5743/569592 [4:52:45<432:03:07,  2.76s/it]
  1%|          | 5744/569592 [4:52:47<392:23:21,  2.51s/it]
                                                           

  1%|          | 5744/569592 [4:52:47<392:23:21,  2.51s/it]
  1%|          | 5745/569592 [4:52:49<356:59:11,  2.28s/it]
                                                           

  1%|          | 5745/569592 [4:52:49<356:59:11,  2.28s/it]
  1%|          | 5746/569592 [4:52:52<428:14:18,  2.73s/it]
                                                           

  1%|          | 5746/569592 [4:52:52<428:14:18,  2.73s/it]
  1%|          | 5747/569592 [4:52:56<461:46:38,  2.95s/it]
                                                           

  1%|          | 5747/569592 [4:52:56<461:46:38,  2.95s/it]
  1%|          | 5748/569592 [4:53:00<505:59:25,  3.23s/it]
                                                           

  1%|          | 5748/569592 [4:53:00<505:59:25,  3.23s/it]
  1%|          | 5749/569592 [4:53:03<507:40:48,  3.24s/it]
                                                           

  1%|          | 5749/569592 [4:53:03<507:40:48,  3.24s/it]
  1%|          | 5750/569592 [4:53:07<527:47:26,  3.37s/it]
                                                           

  1%|          | 5750/569592 [4:53:07<527:47:26,  3.37s/it]
  1%|          | 5751/569592 [4:53:08<422:56:38,  2.70s/it]
                                                           

  1%|          | 5751/569592 [4:53:08<422:56:38,  2.70s/it]
  1%|          | 5752/569592 [4:53:09<340:50:29,  2.18s/it]
                                                           

  1%|          | 5752/569592 [4:53:09<340:50:29,  2.18s/it]
  1%|          | 5753/569592 [4:53:10<283:41:10,  1.81s/it]
                                                           

  1%|          | 5753/569592 [4:53:10<283:41:10,  1.81s/it]
  1%|          | 5754/569592 [4:53:15<436:45:39,  2.79s/it]
                                                           

  1%|          | 5754/569592 [4:53:15<436:45:39,  2.79s/it]
  1%|          | 5755/569592 [4:53:18<459:12:27,  2.93s/it]
                                                           

  1%|          | 5755/569592 [4:53:18<459:12:27,  2.93s/it]
  1%|          | 5756/569592 [4:53:19<366:30:07,  2.34s/it]
                                                           

  1%|          | 5756/569592 [4:53:19<366:30:07,  2.34s/it]
  1%|          | 5757/569592 [4:53:20<303:33:19,  1.94s/it]
                                                           

  1%|          | 5757/569592 [4:53:20<303:33:19,  1.94s/it]
  1%|          | 5758/569592 [4:53:23<369:50:06,  2.36s/it]
                                                           

  1%|          | 5758/569592 [4:53:23<369:50:06, /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 2.36s/it]
  1%|          | 5759/569592 [4:53:28<488:24:14,  3.12s/it]
                                                           

  1%|          | 5759/569592 [4:53:28<488:24:14,  3.12s/it]
  1%|          | 5760/569592 [4:53:32<499:21:45,  3.19s/it]
                                                           

  1%|          | 5760/569592 [4:53:32<499:21:45,  3.19s/it]
  1%|          | 5761/569592 [4:53:35<531:49:17,  3.40s/it]
                                                           

  1%|          | 5761/569592 [4:53:35<531:49:17,  3.40s/it]
  1%|          | 5762/569592 [4:53:39<525:49:28,  3.36s/it]
                                                           

  1%|          | 5762/569592 [4:53:39<525:49:28,  3.36s/it]
  1%|          | 5763/569592 [4:53:40<416:32:00,  2.66s/it]
                                                           

  1%|          | 5763/569592 [4:53:40<416:32:00,  2.66s/it]
  1%|          | 5764/569592 [4:53:43<460:36:26,  2.94s/it]
                                                           

  1%|          | 5764/569592 [4:53:43<460:36:26,  2.94s/it]
  1%|          | 5765/569592 [4:53:44<366:31:11,  2.34s/it]
                                                           

  1%|          | 5765/569592 [4:53:44<366:31:11,  2.34s/it]
  1%|          | 5766/569592 [4:53:48<414:37:05,  2.65s/it]
                                                           

  1%|          | 5766/569592 [4:53:48<414:37:05,  2.65s/it]
  1%|          | 5767/569592 [4:53:49<336:39:44,  2.15s/it]
                                                           

  1%|          | 5767/569592 [4:53:49<336:39:44,  2.15s/it]
  1%|          | 5768/569592 [4:53:50<284:16:21,  1.82s/it]
                                                           

  1%|          | 5768/569592 [4:53:50<284:16:21,  1.82s/it]
  1%|          | 5769/569592 [4:53:53<366:33:00,  2.34s/it]
                                                           

  1%|          | 5769/569592 [4:53:53<366:33:00,  2.34s/it]
  1%|          | 5770/569592 [4:53:57<408:23:35,  2.61s/it]
                                                           

  1%|          | 5770/569592 [4:53:57<408:23:35,  2.61s/it]
  1%|          | 5771/569592 [4:53:58<337:08:24,  2.15s/it]
                                                           

  1%|          | 5771/569592 [4:53:58<337:08:24,  2.15s/it]
  1%|          | 5772/569592 [4:53:59<282:20:44,  1.80s/it]
                                                           

  1%|          | 5772/569592 [4:53:59<282:20:44,  1.80s/it]
  1%|          | 5773/569592 [4:54:02<358:20:34,  2.29s/it]
                                                           

  1%|          | 5773/569592 [4:54:02<358:20:34,  2.29s/it]
  1%|          | 5774/569592 [4:54:05<412:28:38,  2.63s/it]
                                                           

  1%|          | 5774/569592 [4:54:05<412:28:38,  2.63s/it]
  1%|          | 5775/569592 [4:54:09<470:58:37,  3.01s/it]
                                                           

  1%|          | 5775/569592 [4:54:09<470:58:37,  3.01s/it]
  1%|          | 5776/569592 [4:54:13<494:34:09,  3.16s/it]
                                                           

  1%|          | 5776/569592 [4:54:13<494:34:09,  3.16s/it]
  1%|          | 5777/569592 [4:54:16<500:16:31,  3.19s/it]
                                                           

  1%|          | 5777/569592 [4:54:16<500:16:31,  3.19s/it]
  1%|          | 5778/569592 [4:54:17<395:00:31,  2.52s/it]
                                                           

  1%|          | 5778/569592 [4:54:17<395:00:31,  2.52s/it]
  1%|          | 5779/569592 [4:54:22<510:56:02,  3.26s/it]
                                                           

  1%|          | 5779/569592 [4:54:22<510:56:02,  3.26s/it]
  1%|          | 5780/569592 [4:54:26<551:06:30,  3.52s/it]
                                                           

  1%|          | 5780/569592 [4:54:26<551:06:30,  3.52s/it]
  1%|          | 5781/569592 [4:54:30<544:58:52,  3.48s/it]
                                                           

  1%|          | 5781/569592 [4:54:30<544:58:52,  3.48s/it]
  1%|          | 5782/569592 [4:54:33<563:32:40,  3.60s/it]
                                                           

  1%|          | 5782/569592 [4:54:33<563:32:40,  3.60s/it]
  1%|          | 5783/569592 [4:54:37<544:00:00,  3.47s/it]
                                                           

  1%|          | 5783/569592 [4:54:37<544:00:00,  3.47s/it]
  1%|          | 5784/569592 [4:54:40<524:43:35,  3.35s/it]
                                                           

  1%|          | 5784/569592 [4:54:40<524:43:35,  3.35s/it]
  1%|          | 5785/569592 [4:54:45<594:06:09,  3.79s/it]
                                                           

  1%|          | 5785/569592 [4:54:45<594:06:09,  3.79s/it]
  1%|          | 5786/569592 [4:54:48<566:58:55,  3.62s/it]
                                                           

  1%|          | 5786/569592 [4:54:48<566:58:55,  3.62s/it]
  1%|          | 5787/569592 [4:54:51<543:32:25,  3.47s/it]
                                                           

  1%|          | 5787/569592 [4:54:51<543:32:25,  3.47s/it]
  1%|          | 5788/569592 [4:54:54<527:19:00,  3.37s/it]
                                                           

  1%|          | 5788/569592 [4:54:54<527:19:00,  3.37s/it]
  1%|          | 5789/569592 [4:54:58<535:44:41,  3.42s/it]
                                                           

  1%|          | 5789/569592 [4:54:58<535:44:41,  3.42s/it]
  1%|          | 5790/569592 [4:55:01<540:02:37,  3.45s/it]
                                                           

  1%|          | 5790/569592 [4:55:01<540:02:37,  3.45s/it]
  1%|          | 5791/569592 [4:55:04<530:38:38,  3.39s/it]
                                                           

  1%|          | 5791/569592 [4:55:04<530:38:38,  3.39s/it]
  1%|          | 5792/569592 [4:55:08<523:37:14,  3.34s/it]
                                                           

  1%|          | 5792/569592 [4:55:08<523:37:14,  3.34s/it]
  1%|          | 5793/569592 [4:55:11<553:34:33,  3.53s/it]
                                                           

  1%|          | 5793/569592 [4:55:12<553:34:33,  3.53s/it]
  1%|          | 5794/569592 [4:55:16<588:44:17,  3.76s/it]
                                                           

  1%|          | 5794/569592 [4:55:16<588:44:17,  3.76s/it]
  1%|          | 5795/569592 [4:55:20<610:33:35,  3.90s/it]
                                                           

  1%|          | 5795/569592 [4:55:20<610:33:35,  3.90s/it]
  1%|          | 5796/569592 [4:55:24<603:58:34,  3.86s/it]
                                                           

  1%|          | 5796/569592 [4:55:24<603:58:34,  3.86s/it]
  1%|          | 5797/569592 [4:55:27<564:18:28,  3.60s/it]
                                                           

  1%|          | 5797/569592 [4:55:27<564:18:28,  3.60s/it]
  1%|          | 5798/569592 [4:55:32<628:54:06,  4.02s/it]
                                                           

  1%|          | 5798/569592 [4:55:32<628:54:06,  4.02s/it]
  1%|          | 5799/569592 [4:55:33<483:01:04,  3.08s/it]
                                                           

  1%|          | 5799/569592 [4:55:33<483:01:04,  3.08s/it]
  1%|          | 5800/569592 [4:55:38<589:50:18,  3.77s/it]
                                                           

  1%|          | 5800/569592 [4:55:38<589:50:18,  3.77s/it]
  1%|          | 5801/569592 [4:55:42<580:54:45,  3.71s/it]
                                                           

  1%|          | 5801/569592 [4:55:42<580:54:45,  3.71s/it]
  1%|          | 5802/569592 [4:55:45<562:01:55,  3.59s/it]
                                                           

  1%|          | 5802/569592 [4:55:45<562:01:55,  3.59s/it]
  1%|          | 5803/569592 [4:55:48<548:47:37,  3.50s/it]
                                                           

  1%|          | 5803/569592 [4:55:48<548:47:37,  3.50s/it]
  1%|          | 5804/569592 [4:55:53<592:00:19,  3.78s/it]
                                                           

  1%|          | 5804/569592 [4:55:53<592:00:19,  3.78s/it]
  1%|          | 5805/569592 [4:55:57<598:39:01,  3.82s/it]
                                                           

  1%|          | 5805/569592 [4:55:57<598:39:01,  3.82s/it]
  1%|          | 5806/569592 [4:56:00<567:48:33,  3.63s/it]
                                                           

  1%|          | 5806/569592 [4:56:00<567:48:33,  3.63s/it]
  1%|          | 5807/569592 [4:56:05<634:27:59,  4.05s/it]
                                                           

  1%|          | 5807/569592 [4:56:05<634:27:59,  4.05s/it]
  1%|          | 5808/569592 [4:56:09<666:08:21,  4.25s/it]
                                                           

  1%|          | 5808/569592 [4:56:10<666:08:21,  4.25s/it]
  1%|          | 5809/569592 [4:56:14<692:30:51,  4.42s/it]
                                                           

  1%|          | 5809/569592 [4:56:14<692:30:51,  4.42s/it]
  1%|          | 5810/569592 [4:56:15<527:27:46,  3.37s/it]
                                                           

  1%|          | 5810/569592 [4:56:15<527:27:46,  3.37s/it]
  1%|          | 5811/569592 [4:56:20<572:42:20,  3.66s/it]
                                                           

  1%|          | 5811/569592 [4:56:20<572:42:20,  3.66s/it]
  1%|          | 5812/569592 [4:56:23<558:24:09,  3.57s/it]
                                                           

  1%|          | 5812/569592 [4:56:23<558:24:09,  3.57s/it]
  1%|          | 5813/569592 [4:56:26<559:03:43,  3.57s/it]
                                                           

  1%|          | 5813/569592 [4:56:26<559:03:43,  3.57s/it]
  1%|          | 5814/569592 [4:56:30<543:58:51,  3.47s/it]
                                                           

  1%|          | 5814/569592 [4:56:30<543:58:51,  3.47s/it]
  1%|          | 5815/569592 [4:56:33<523:23:31,  3.34s/it]
                                                           

  1%|          | 5815/569592 [4:56:33<523:23:31,  3.34s/it]
  1%|          | 5816/569592 [4:56:36<509:02:26,  3.25s/it]
                                                           

  1%|          | 5816/569592 [4:56:36<509:02:26,  3.25s/it]
  1%|          | 5817/569592 [4:56:39<517:56:10,  3.31s/it]
                                                           

  1%|          | 5817/569592 [4:56:39<517:56:10,  3.31s/it]
  1%|          | 5818/569592 [4:56:43<546:40:01,  3.49s/it]
                                                           

  1%|          | 5818/569592 [4:56:43<546:40:01,  3.49s/it]
  1%|          | 5819/569592 [4:56:47<556:54:10,  3.56s/it]
                                                           

  1%|          | 5819/569592 [4:56:47<556:54:10,  3.56s/it]
  1%|          | 5820/569592 [4:56:48<444:21:43,  2.84s/it]
                                                           

  1%|          | 5820/569592 [4:56:48<444:21:43,  2.84s/it]
  1%|          | 5821/569592 [4:56:51<461:50:35,  2.95s/it]
                                                           

  1%|          | 5821/569592 [4:56:51<461:50:35,  2.95s/it]
  1%|          | 5822/569592 [4:56:52<371:46:41,  2.37s/it]
                                                           

  1%|          | 5822/569592 [4:56:52<371:46:41,  2.37s/it]
  1%|          | 5823/569592 [4:56:57<497:26:17,  3.18s/it]
                                                           

  1%|          | 5823/569592 [4:56:57<497:26:17,  3.18s/it]
  1%|          | 5824/569592 [4:57:02<587:20:58,  3.75s/it]
                                                           

  1%|          | 5824/569592 [4:57:02<587:20:58,  3.75s/it]
  1%|          | 5825/569592 [4:57:07<631:46:49,  4.03s/it]
                                                           

  1%|          | 5825/569592 [4:57:07<631:46:49,  4.03s/it]
  1%|          | 5826/569592 [4:57:10<586:46:49,  3.75s/it]
                                                           

  1%|          | 5826/569592 [4:57:10<586:46:49,  3.75s/it]
  1%|          | 5827/569592 [4:57:11<453:30:37,  2.90s/it]
                                                           

  1%|          | 5827/569592 [4:57:11<453:30:37,  2.90s/it]
  1%|          | 5828/569592 [4:57:12<360:37:27,  2.30s/it]
                                                           

  1%|          | 5828/569592 [4:57:12<360:37:27,  2.30s/it]
  1%|          | 5829/569592 [4:57:13<298:56:36,  1.91s/it]
                                                           

  1%|          | 5829/569592 [4:57:13<298:56:36,  1.91s/it]
  1%|          | 5830/569592 [4:57:14<254:44:58,  1.63s/it]
                                                           

  1%|          | 5830/569592 [4:57:14<254:44:58,  1.63s/it]
  1%|          | 5831/569592 [4:57:18<346:35:40,  2.21s/it]
                                                           

  1%|          | 5831/569592 [4:57:18<346:35:40,  2.21s/it]
  1%|          | 5832/569592 [4:57:21<401:10:57,  2.56s/it]
                                                           

  1%|          | 5832/569592 [4:57:21<401:10:57,  2.56s/it]
  1%|          | 5833/569592 [4:57:22<331:15:47,  2.12s/it]
                                                           

  1%|          | 5833/569592 [4:57:22<331:15:47,  2.12s/it]
  1%|          | 5834/569592 [4:57:23<277:03:42,  1.77s/it]
                                                           

  1%|          | 5834/569592 [4:57:23<277:03:42,  1.77s/it]
  1%|          | 5835/569592 [4:57:24<239:45:10,  1.53s/it]
                                                           

  1%|          | 5835/569592 [4:57:24<239:45:10,  1.53s/it]
  1%|          | 5836/569592 [4:57:27<325:26:32,  2.08s/it]
                                                           

  1%|          | 5836/569592 [4:57:27<325:26:32,  2.08s/it]
  1%|          | 5837/569592 [4:57:28<271:31:57,  1.73s/it]
                                                           

  1%|          | 5837/569592 [4:57:28<271:31:57,  1.73s/it]
  1%|          | 5838/569592 [4:57:32<364:50:31,  2.33s/it]
                                                           

  1%|          | 5838/569592 [4:57:32<364:50:31,  2.33s/it]
  1%|          | 5839/569592 [4:57:34<352:32:47,  2.25s/it]
                                                           

  1%|          | 5839/569592 [4:57:34<352:32:47,  2.25s/it]
  1%|          | 5840/569592 [4:57:35<315:34:39,  2.02s/it]
                                                           

  1%|          | 5840/569592 [4:57:35<315:34:39,  2.02s/it]
  1%|          | 5841/569592 [4:57:38<355:20:18,  2.27s/it]
                                                           

  1%|          | 5841/569592 [4:57:38<355:20:18,  2.27s/it]
  1%|          | 5842/569592 [4:57:41<371:59:15,  2.38s/it]
                                                           

  1%|          | 5842/569592 [4:57:41<371:59:15,  2.38s/it]
  1%|          | 5843/569592 [4:57:44<410:48:43,  2.62s/it]
                                                           

  1%|          | 5843/569592 [4:57:44<410:48:43,  2.62s/it]
  1%|          | 5844/569592 [4:57:45<336:14:36,  2.15s/it]
                                                           

  1%|          | 5844/569592 [4:57:45<336:14:36,  2.15s/it]
  1%|          | 5845/569592 [4:57:46<282:18:06,  1.80s/it]
                                                           

  1%|          | 5845/569592 [4:57:46<282:18:06,  1.80s/it]
  1%|          | 5846/569592 [4:57:51<409:50:40,  2.62s/it]
                                                           

  1%|          | 5846/569592 [4:57:51<409:50:40,  2.62s/it]
  1%|          | 5847/569592 [4:57:54<458:51:29,  2.93s/it]
                                                           

  1%|          | 5847/569592 [4:57:54<458:51:29,  2.93s/it]
  1%|          | 5848/569592 [4:57:55<367:09:30,  2.34s/it]
                                                           

  1%|          | 5848/569592 [4:57:55<367:09:30,  2.34s/it]
  1%|          | 5849/569592 [4:57:57<357:48:51,  2.28s/it]
                                                           

  1%|          | 5849/569592 [4:57:58<357:48:51,  2.28s/it]
  1%|          | 5850/569592 [4:58:01<428:57:20,  2.74s/it]
                                                           

  1%|          | 5850/569592 [4:58:01<428:57:20,  2.74s/it]
  1%|          | 5851/569592 [4:58:04<416:51:07,  2.66s/it]
                                                           

  1%|          | 5851/569592 [4:58:04<416:51:07,  2.66s/it]
  1%|          | 5852/569592 [4:58:06<400:43:51,  2.56s/it]
                                                           

  1%|          | 5852/569592 [4:58:06<400:43:51,  2.56s/it]
  1%|          | 5853/569592 [4:58:08<347:48:51,  2.22s/it]
                                                           

  1%|          | 5853/569592 [4:58:08<347:48:51,  2.22s/it]
  1%|          | 5854/569592 [4:58:13<488:43:37,  3.12s/it]
                                                           

  1%|          | 5854/569592 [4:58:13<488:43:37,  3.12s/it]
  1%|          | 5855/569592 [4:58:16<471:37:36,  3.01s/it]
                                                           

  1%|          | 5855/569592 [4:58:16<471:37:36,  3.01s/it]
  1%|          | 5856/569592 [4:58:20<521:25:46,  3.33s/it]
                                                           

  1%|          | 5856/569592 [4:58:20<521:25:46,  3.33s/it]
  1%|          | 5857/569592 [4:58:21<413:46:09,  2.64s/it]
                                                           

  1%|          | 5857/569592 [4:58:21<413:46:09,  2.64s/it]
  1%|          | 5858/569592 [4:58:24<466:00:18,  2.98s/it]
                                                           

  1%|          | 5858/569592 [4:58:24<466:00:18,  2.98s/it]
  1%|          | 5859/569592 [4:58:25<371:49:46,  2.37s/it]
                                                           

  1%|          | 5859/569592 [4:58:25<371:49:46,  2.37s/it]
  1%|          | 5860/569592 [4:58:29<422:04:26,  2.70s/it]
                                                           

  1%|          | 5860/569592 [4:58:29<422:04:26,  2.70s/it]
  1%|          | 5861/569592 [4:58:30<340:15:00,  2.17s/it]
                                                           

  1%|          | 5861/569592 [4:58:30<340:15:00,  2.17s/it]
  1%|          | 5862/569592 [4:58:32<336:29:00,  2.15s/it]
                                                           

  1%|          | 5862/569592 [4:58:32<336:29:00,  2.15s/it]
  1%|          | 5863/569592 [4:58:36<408:28:38,  2.61s/it]
                                                           

  1%|          | 5863/569592 [4:58:36<408:28:38,  2.61s/it]
  1%|          | 5864/569592 [4:58:37<354:27:36,  2.26s/it]
                                                           

  1%|          | 5864/569592 [4:58:37<354:27:36,  2.26s/it]
  1%|          | 5865/569592 [4:58:40<411:10:35,  2.63s/it]
                                                           

  1%|          | 5865/569592 [4:58:40<411:10:35,  2.63s/it]
  1%|          | 5866/569592 [4:58:44<437:55:52,  2.80s/it]
                                                           

  1%|          | 5866/569592 [4:58:44<437:55:52,  2.80s/it]
  1%|          | 5867/569592 [4:58:47<469:05:29,  3.00s/it]
                                                           

  1%|          | 5867/569592 [4:58:47<469:05:29,  3.00s/it]
  1%|          | 5868/569592 [4:58:48<376:37:02,  2.41s/it]
                                                           

  1%|          | 5868/569592 [4:58:48<376:37:02,  2.41s/it]
  1%|          | 5869/569592 [4:58:49<311:27:44,  1.99s/it]
                                                           

  1%|          | 5869/569592 [4:58:49<311:27:44,  1.99s/it]
  1%|          | 5870/569592 [4:58:52<371:35:25,  2.37s/it]
                                                           

  1%|          | 5870/569592 [4:58:52<371:35:25,  2.37s/it]
  1%|          | 5871/569592 [4:58:55<370:10:38,  2.36s/it]
                                                           

  1%|          | 5871/569592 [4:58:55<370:10:38,  2.36s/it]
  1%|          | 5872/569592 [4:58:58<423:02:59,  2.70s/it]
                                                           

  1%|          | 5872/569592 [4:58:58<423:02:59,  2.70s/it]
  1%|          | 5873/569592 [4:59:03<520:02:02,  3.32s/it]
                                                           

  1%|          | 5873/569592 [4:59:03<520:02:02,  3.32s/it]
  1%|          | 5874/569592 [4:59:04<410:33:03,  2.62s/it]
                                                           

  1%|          | 5874/569592 [4:59:04<410:33:03,  2.62s/it]
  1%|          | 5875/569592 [4:59:05<349:04:51,  2.23s/it]
                                                           

  1%|          | 5875/569592 [4:59:05<349:04:51,  2.23s/it]
  1%|          | 5876/569592 [4:59:10<472:37:04,  3.02s/it]
                                                           

  1%|          | 5876/569592 [4:59:10<472:37:04,  3.02s/it]
  1%|          | 5877/569592 [4:59:11<377:52:14,  2.41s/it]
                                                           

  1%|          | 5877/569592 [4:59:11<377:52:14,  2.41s/it]
  1%|          | 5878/569592 [4:59:15<425:38:01,  2.72s/it]
                                                           

  1%|          | 5878/569592 [4:59:15<425:38:01,  2.72s/it]
  1%|          | 5879/569592 [4:59:18<452:11:43,  2.89s/it]
                                                           

  1%|          | 5879/569592 [4:59:18<452:11:43,  2.89s/it]
  1%|          | 5880/569592 [4:59:21<476:47:19,  3.04s/it]
                                                           

  1%|          | 5880/569592 [4:59:21<476:47:19,  3.04s/it]
  1%|          | 5881/569592 [4:59:22<379:08:08,  2.42s/it]
                                                           

  1%|          | 5881/569592 [4:59:22<379:08:08,  2.42s/it]
  1%|          | 5882/569592 [4:59:26<437:54:57,  2.80s/it]
                                                           

  1%|          | 5882/569592 [4:59:26<437:54:57,  2.80s/it]
  1%|          | 5883/569592 [4:59:27<351:55:30,  2.25s/it]
                                                           

  1%|          | 5883/569592 [4:59:27<351:55:30,  2.25s/it]
  1%|          | 5884/569592 [4:59:31<423:45:05,  2.71s/it]
                                                           

  1%|          | 5884/569592 [4:59:31<423:45:05,  2.71s/it]
  1%|          | 5885/569592 [4:59:32<341:56:50,  2.18s/it]
                                                           

  1%|          | 5885/569592 [4:59:32<341:56:50,  2.18s/it]
  1%|          | 5886/569592 [4:59:37<486:06:04,  3.10s/it]
                                                           

  1%|          | 5886/569592 [4:59:37<486:06:04,  3.10s/it]
  1%|          | 5887/569592 [4:59:41<538:38:57,  3.44s/it]
                                                           

  1%|          | 5887/569592 [4:59:41<538:38:57,  3.44s/it]
  1%|          | 5888/569592 [4:59:42<420:53:26,  2.69s/it]
                                                           

  1%|          | 5888/569592 [4:59:42<420:53:26,  2.69s/it]
  1%|          | 5889/569592 [4:59:43<339:44:07,  2.17s/it]
                                                           

  1%|          | 5889/569592 [4:59:43<339:44:07,  2.17s/it]
  1%|          | 5890/569592 [4:59:44<282:15:13,  1.80s/it]
                                                           

  1%|          | 5890/569592 [4:59:44<282:15:13,  1.80s/it]
  1%|          | 5891/569592 [4:59:48<368:41:09,  2.35s/it]
                                                           

  1%|          | 5891/569592 [4:59:48<368:41:09,  2.35s/it]
  1%|          | 5892/569592 [4:59:51<431:18:27,  2.75s/it]
                                                           

  1%|          | 5892/569592 [4:59:51<431:18:27,  2.75s/it]
  1%|          | 5893/569592 [4:59:56<521:35:02,  3.33s/it]
                                                           

  1%|          | 5893/569592 [4:59:56<521:35:02,  3.33s/it]
  1%|          | 5894/569592 [5:00:00<536:21:00,  3.43s/it]
                                                           

  1%|          | 5894/569592 [5:00:00<536:21:00,  3.43s/it]
  1%|          | 5895/569592 [5:00:03<528:35:24,  3.38s/it]
                                                           

  1%|          | 5895/569592 [5:00:03<528:35:24,  3.38s/it]
  1%|          | 5896/569592 [5:00:06<529:15:10,  3.38s/it]
                                                           

  1%|          | 5896/569592 [5:00:06<529:15:10,  3.38s/it]
  1%|          | 5897/569592 [5:00:10<541:08:08,  3.46s/it]
                                                           

  1%|          | 5897/569592 [5:00:10<541:08:08,  3.46s/it]
  1%|          | 5898/569592 [5:00:14<553:09:52,  3.53s/it]
                                                           

  1%|          | 5898/569592 [5:00:14<553:09:52,  3.53s/it]
  1%|          | 5899/569592 [5:00:18<571:24:31,  3.65s/it]
                                                           

  1%|          | 5899/569592 [5:00:18<571:24:31,  3.65s/it]
  1%|          | 5900/569592 [5:00:21<569:55:39,  3.64s/it]
                                                           

  1%|          | 5900/569592 [5:00:21<569:55:39,  3.64s/it]
  1%|          | 5901/569592 [5:00:24<548:33:24,  3.50s/it]
                                                           

  1%|          | 5901/569592 [5:00:24<548:33:24,  3.50s/it]
  1%|          | 5902/569592 [5:00:29<610:43:25,  3.90s/it]
                                                           

  1%|          | 5902/569592 [5:00:29<610:43:25,  3.90s/it]
  1%|          | 5903/569592 [5:00:33<598:49:55,  3.82s/it]
                                                           

  1%|          | 5903/569592 [5:00:33<598:49:55,  3.82s/it]
  1%|          | 5904/569592 [5:00:34<461:30:35,  2.95s/it]
                                                           

  1%|          | 5904/569592 [5:00:34<461:30:35,  2.95s/it]
  1%|          | 5905/569592 [5:00:38<544:54:09,  3.48s/it]
                                                           

  1%|          | 5905/569592 [5:00:38<544:54:09,  3.48s/it]
  1%|          | 5906/569592 [5:00:39<424:21:05,  2.71s/it]
                                                           

  1%|          | 5906/569592 [5:00:39<424:21:05,  2.71s/it]
  1%|          | 5907/569592 [5:00:43<461:24:15,  2.95s/it]
                                                           

  1%|          | 5907/569592 [5:00:43<461:24:15,  2.95s/it]
  1%|          | 5908/569592 [5:00:48<551:17:13,  3.52s/it]
                                                           

  1%|          | 5908/569592 [5:00:48<551:17:13,  3.52s/it]
  1%|          | 5909/569592 [5:00:51<542:04:23,  3.46s/it]
                                                           

  1%|          | 5909/569592 [5:00:51<542:04:23,  3.46s/it]
  1%|          | 5910/569592 [5:00:54<526:10:37,  3.36s/it]
                                                           

  1%|          | 5910/569592 [5:00:54<526:10:37,  3.36s/it]
  1%|          | 5911/569592 [5:00:59<594:19:00,  3.80s/it]
                                                           

  1%/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
|          | 5911/569592 [5:00:59<594:19:00,  3.80s/it]
  1%|          | 5912/569592 [5:01:02<552:58:40,  3.53s/it]
                                                           

  1%|          | 5912/569592 [5:01:02<552:58:40,  3.53s/it]
  1%|          | 5913/569592 [5:01:03<429:04:14,  2.74s/it]
                                                           

  1%|          | 5913/569592 [5:01:03<429:04:14,  2.74s/it]
  1%|          | 5914/569592 [5:01:07<488:17:22,  3.12s/it]
                                                           

  1%|          | 5914/569592 [5:01:07<488:17:22,  3.12s/it]
  1%|          | 5915/569592 [5:01:10<515:11:32,  3.29s/it]
                                                           

  1%|          | 5915/569592 [5:01:10<515:11:32,  3.29s/it]
  1%|          | 5916/569592 [5:01:14<545:35:27,  3.48s/it]
                                                           

  1%|          | 5916/569592 [5:01:14<545:35:27,  3.48s/it]
  1%|          | 5917/569592 [5:01:20<635:23:14,  4.06s/it]
                                                           

  1%|          | 5917/569592 [5:01:20<635:23:14,  4.06s/it]
  1%|          | 5918/569592 [5:01:21<490:20:06,  3.13s/it]
                                                           

  1%|          | 5918/569592 [5:01:21<490:20:06,  3.13s/it]
  1%|          | 5919/569592 [5:01:24<509:27:39,  3.25s/it]
                                                           

  1%|          | 5919/569592 [5:01:24<509:27:39,  3.25s/it]
  1%|          | 5920/569592 [5:01:25<400:14:22,  2.56s/it]
                                                           

  1%|          | 5920/569592 [5:01:25<400:14:22,  2.56s/it]
  1%|          | 5921/569592 [5:01:29<451:27:06,  2.88s/it]
                                                           

  1%|          | 5921/569592 [5:01:29<451:27:06,  2.88s/it]
  1%|          | 5922/569592 [5:01:33<527:56:21,  3.37s/it]
                                                           

  1%|          | 5922/569592 [5:01:33<527:56:21,  3.37s/it]
  1%|          | 5923/569592 [5:01:37<522:09:17,  3.33s/it]
                                                           

  1%|          | 5923/569592 [5:01:37<522:09:17,  3.33s/it]
  1%|          | 5924/569592 [5:01:41<592:50:02,  3.79s/it]
                                                           

  1%|          | 5924/569592 [5:01:41<592:50:02,  3.79s/it]
  1%|          | 5925/569592 [5:01:42<457:16:26,  2.92s/it]
                                                           

  1%|          | 5925/569592 [5:01:42<457:16:26,  2.92s/it]
  1%|          | 5926/569592 [5:01:46<491:25:50,  3.14s/it]
                                                           

  1%|          | 5926/569592 [5:01:46<491:25:50,  3.14s/it]
  1%|          | 5927/569592 [5:01:50<513:22:04,  3.28s/it]
                                                           

  1%|          | 5927/569592 [5:01:50<513:22:04,  3.28s/it]
  1%|          | 5928/569592 [5:01:53<516:42:56,  3.30s/it]
                                                           

  1%|          | 5928/569592 [5:01:53<516:42:56,  3.30s/it]
  1%|          | 5929/569592 [5:01:54<405:24:48,  2.59s/it]
                                                           

  1%|          | 5929/569592 [5:01:54<405:24:48,  2.59s/it]
  1%|          | 5930/569592 [5:01:57<437:33:22,  2.79s/it]
                                                           

  1%|          | 5930/569592 [5:01:57<437:33:22,  2.79s/it]
  1%|          | 5931/569592 [5:01:58<353:23:32,  2.26s/it]
                                                           

  1%|          | 5931/569592 [5:01:58<353:23:32,  2.26s/it]
  1%|          | 5932/569592 [5:02:02<422:13:25,  2.70s/it]
                                                           

  1%|          | 5932/569592 [5:02:02<422:13:25,  2.70s/it]
  1%|          | 5933/569592 [5:02:03<345:16:15,  2.21s/it]
                                                           

  1%|          | 5933/569592 [5:02:03<345:16:15,  2.21s/it]
  1%|          | 5934/569592 [5:02:04<290:07:43,  1.85s/it]
                                                           

  1%|          | 5934/569592 [5:02:04<290:07:43,  1.85s/it]
  1%|          | 5935/569592 [5:02:08<368:42:30,  2.35s/it]
                                                           

  1%|          | 5935/569592 [5:02:08<368:42:30,  2.35s/it]
  1%|          | 5936/569592 [5:02:11<436:06:21,  2.79s/it]
                                                           

  1%|          | 5936/569592 [5:02:11<436:06:21,  2.79s/it]
  1%|          | 5937/569592 [5:02:16<536:40:13,  3.43s/it]
                                                           

  1%|          | 5937/569592 [5:02:16<536:40:13,  3.43s/it]
  1%|          | 5938/569592 [5:02:17<423:29:40,  2.70s/it]
                                                           

  1%|          | 5938/569592 [5:02:17<423:29:40,  2.70s/it]
  1%|          | 5939/569592 [5:02:22<528:19:21,  3.37s/it]
                                                           

  1%|          | 5939/569592 [5:02:22<528:19:21,  3.37s/it]
  1%|          | 5940/569592 [5:02:25<517:06:42,  3.30s/it]
                                                           

  1%|          | 5940/569592 [5:02:25<517:06:42,  3.30s/it]
  1%|          | 5941/569592 [5:02:29<520:05:24,  3.32s/it]
                                                           

  1%|          | 5941/569592 [5:02:29<520:05:24,  3.32s/it]
  1%|          | 5942/569592 [5:02:32<512:11:46,  3.27s/it]
                                                           

  1%|          | 5942/569592 [5:02:32<512:11:46,  3.27s/it]
  1%|          | 5943/569592 [5:02:35<507:43:58,  3.24s/it]
                                                           

  1%|          | 5943/569592 [5:02:35<507:43:58,  3.24s/it]
  1%|          | 5944/569592 [5:02:39<535:04:41,  3.42s/it]
                                                           

  1%|          | 5944/569592 [5:02:39<535:04:41,  3.42s/it]
  1%|          | 5945/569592 [5:02:40<420:59:35,  2.69s/it]
                                                           

  1%|          | 5945/569592 [5:02:40<420:59:35,  2.69s/it]
  1%|          | 5946/569592 [5:02:41<339:16:08,  2.17s/it]
                                                           

  1%|          | 5946/569592 [5:02:41<339:16:08,  2.17s/it]
  1%|          | 5947/569592 [5:02:42<283:45:15,  1.81s/it]
                                                           

  1%|          | 5947/569592 [5:02:42<283:45:15,  1.81s/it]
  1%|          | 5948/569592 [5:02:47<454:09:30,  2.90s/it]
                                                           

  1%|          | 5948/569592 [5:02:47<454:09:30,  2.90s/it]
  1%|          | 5949/569592 [5:02:52<544:27:09,  3.48s/it]
                                                           

  1%|          | 5949/569592 [5:02:52<544:27:09,  3.48s/it]
  1%|          | 5950/569592 [5:02:55<531:25:02,  3.39s/it]
                                                           

  1%|          | 5950/569592 [5:02:55<531:25:02,  3.39s/it]
  1%|          | 5951/569592 [5:02:59<538:24:07,  3.44s/it]
                                                           

  1%|          | 5951/569592 [5:02:59<538:24:07,  3.44s/it]
  1%|          | 5952/569592 [5:03:00<423:23:42,  2.70s/it]
                                                           

  1%|          | 5952/569592 [5:03:00<423:23:42,  2.70s/it]
  1%|          | 5953/569592 [5:03:01<345:26:25,  2.21s/it]
                                                           

  1%|          | 5953/569592 [5:03:01<345:26:25,  2.21s/it]
  1%|          | 5954/569592 [5:03:04<398:12:52,  2.54s/it]
                                                           

  1%|          | 5954/569592 [5:03:04<398:12:52,  2.54s/it]
  1%|          | 5955/569592 [5:03:05<325:51:54,  2.08s/it]
                                                           

  1%|          | 5955/569592 [5:03:05<325:51:54,  2.08s/it]
  1%|          | 5956/569592 [5:03:09<411:06:53,  2.63s/it]
                                                           

  1%|          | 5956/569592 [5:03:09<411:06:53,  2.63s/it]
  1%|          | 5957/569592 [5:03:10<336:41:21,  2.15s/it]
                                                           

  1%|          | 5957/569592 [5:03:10<336:41:21,  2.15s/it]
  1%|          | 5958/569592 [5:03:11<280:07:56,  1.79s/it]
                                                           

  1%|          | 5958/569592 [5:03:11<280:07:56,  1.79s/it]
  1%|          | 5959/569592 [5:03:12<242:05:47,  1.55s/it]
                                                           

  1%|          | 5959/569592 [5:03:12<242:05:47,  1.55s/it]
  1%|          | 5960/569592 [5:03:13<216:41:52,  1.38s/it]
                                                           

  1%|          | 5960/569592 [5:03:13<216:41:52,  1.38s/it]
  1%|          | 5961/569592 [5:03:14<213:03:40,  1.36s/it]
                                                           

  1%|          | 5961/569592 [5:03:14<213:03:40,  1.36s/it]
  1%|          | 5962/569592 [5:03:15<194:51:05,  1.24s/it]
                                                           

  1%|          | 5962/569592 [5:03:15<194:51:05,  1.24s/it]
  1%|          | 5963/569592 [5:03:20<339:05:28,  2.17s/it]
                                                           

  1%|          | 5963/569592 [5:03:20<339:05:28,  2.17s/it]
  1%|          | 5964/569592 [5:03:23<417:41:20,  2.67s/it]
                                                           

  1%|          | 5964/569592 [5:03:23<417:41:20,  2.67s/it]
  1%|          | 5965/569592 [5:03:25<371:06:29,  2.37s/it]
                                                           

  1%|          | 5965/569592 [5:03:25<371:06:29,  2.37s/it]
  1%|          | 5966/569592 [5:03:26<304:06:03,  1.94s/it]
                                                           

  1%|          | 5966/569592 [5:03:26<304:06:03,  1.94s/it]
  1%|          | 5967/569592 [5:03:28<309:22:17,  1.98s/it]
                                                           

  1%|          | 5967/569592 [5:03:28<309:22:17,  1.98s/it]
  1%|          | 5968/569592 [5:03:32<420:47:08,  2.69s/it]
                                                           

  1%|          | 5968/569592 [5:03:33<420:47:08,  2.69s/it]
  1%|          | 5969/569592 [5:03:35<391:41:03,  2.50s/it]
                                                           

  1%|          | 5969/569592 [5:03:35<391:41:03,  2.50s/it]
  1%|          | 5970/569592 [5:03:36<323:29:15,  2.07s/it]
                                                           

  1%|          | 5970/569592 [5:03:36<323:29:15,  2.07s/it]
  1%|          | 5971/569592 [5:03:39<390:34:50,  2.49s/it]
                                                           

  1%|          | 5971/569592 [5:03:39<390:34:50,  2.49s/it]
  1%|          | 5972/569592 [5:03:43<443:05:04,  2.83s/it]
                                                           

  1%|          | 5972/569592 [5:03:43<443:05:04,  2.83s/it]
  1%|          | 5973/569592 [5:03:48<550:49:08,  3.52s/it]
                                                           

  1%|          | 5973/569592 [5:03:48<550:49:08,  3.52s/it]
  1%|          | 5974/569592 [5:03:51<543:01:40,  3.47s/it]
                                                           

  1%|          | 5974/569592 [5:03:51<543:01:40,  3.47s/it]
  1%|          | 5975/569592 [5:03:52<429:29:58,  2.74s/it]
                                                           

  1%|          | 5975/569592 [5:03:52<429:29:58,  2.74s/it]
  1%|          | 5976/569592 [5:03:56<485:55:43,  3.10s/it]
                                                           

  1%|          | 5976/569592 [5:03:56<485:55:43,  3.10s/it]
  1%|          | 5977/569592 [5:03:59<492:14:35,  3.14s/it]
                                                           

  1%|          | 5977/569592 [5:03:59<492:14:35,  3.14s/it]
  1%|          | 5978/569592 [5:04:00<393:03:00,  2.51s/it]
                                                           

  1%|          | 5978/569592 [5:04:00<393:03:00,  2.51s/it]
  1%|          | 5979/569592 [5:04:01<319:38:45,  2.04s/it]
                                                           

  1%|          | 5979/569592 [5:04:01<319:38:45,  2.04s/it]
  1%|          | 5980/569592 [5:04:03<321:39:43,  2.05s/it]
                                                           

  1%|          | 5980/569592 [5:04:03<321:39:43,  2.05s/it]
  1%|          | 5981/569592 [5:04:07<389:33:29,  2.49s/it]
                                                           

  1%|          | 5981/569592 [5:04:07<389:33:29,  2.49s/it]
  1%|          | 5982/569592 [5:04:08<321:23:19,  2.05s/it]
                                                           

  1%|          | 5982/569592 [5:04:08<321:23:19,  2.05s/it]
  1%|          | 5983/569592 [5:04:13<465:17:01,  2.97s/it]
                                                           

  1%|          | 5983/569592 [5:04:13<465:17:01,  2.97s/it]
  1%|          | 5984/569592 [5:04:16<479:01:50,  3.06s/it]
                                                           

  1%|          | 5984/569592 [5:04:16<479:01:50,  3.06s/it]
  1%|          | 5985/569592 [5:04:20<507:48:22,  3.24s/it]
                                                           

  1%|          | 5985/569592 [5:04:20<507:48:22,  3.24s/it]
  1%|          | 5986/569592 [5:04:21<412:15:53,  2.63s/it]
                                                           

  1%|          | 5986/569592 [5:04:21<412:15:53,  2.63s/it]
  1%|          | 5987/569592 [5:04:22<337:13:22,  2.15s/it]
                                                           

  1%|          | 5987/569592 [5:04:22<337:13:22,  2.15s/it]
  1%|          | 5988/569592 [5:04:24<331:08:59,  2.12s/it]
                                                           

  1%|          | 5988/569592 [5:04:25<331:08:59,  2.12s/it]
  1%|          | 5989/569592 [5:04:26<288:36:38,  1.84s/it]
                                                           

  1%|          | 5989/569592 [5:04:26<288:36:38,  1.84s/it]
  1%|          | 5990/569592 [5:04:29<369:22:44,  2.36s/it]
                                                           

  1%|          | 5990/569592 [5:04:29<369:22:44,  2.36s/it]
  1%|          | 5991/569592 [5:04:32<413:45:21,  2.64s/it]
                                                           

  1%|          | 5991/569592 [5:04:32<413:45:21,  2.64s/it]
  1%|          | 5992/569592 [5:04:36<444:09:35,  2.84s/it]
                                                           

  1%|          | 5992/569592 [5:04:36<444:09:35,  2.84s/it]
  1%|          | 5993/569592 [5:04:37<356:49:42,  2.28s/it]
                                                           

  1%|          | 5993/569592 [5:04:37<356:49:42,  2.28s/it]
  1%|          | 5994/569592 [5:04:41<463:16:28,  2.96s/it]
                                                           

  1%|          | 5994/569592 [5:04:41<463:16:28,  2.96s/it]
  1%|          | 5995/569592 [5:04:45<498:35:19,  3.18s/it]
                                                           

  1%|          | 5995/569592 [5:04:45<498:35:19,  3.18s/it]
  1%|          | 5996/569592 [5:04:46<393:21:02,  2.51s/it]
                                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                   

  1%|          | 5996/569592 [5:04:46<393:21:02,  2.51s/it]
  1%|          | 5997/569592 [5:04:49<431:19:10,  2.76s/it]
                                                           

  1%|          | 5997/569592 [5:04:49<431:19:10,  2.76s/it]
  1%|          | 5998/569592 [5:04:53<491:44:01,  3.14s/it]
                                                           

  1%|          | 5998/569592 [5:04:53<491:44:01,  3.14s/it]
  1%|          | 5999/569592 [5:04:59<596:47:54,  3.81s/it]
                                                           

  1%|          | 5999/569592 [5:04:59<596:47:54,  3.81s/it]
  1%|          | 6000/569592 [5:05:02<582:38:26,  3.72s/it]
                                                           

  1%|          | 6000/569592 [5:05:02<582:38:26,  3.72s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-6000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-6000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-6000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-6000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-6000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-6000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-5000] due to args.save_total_limit

  1%|          | 6001/569592 [5:07:01<5974:40:57, 38.16s/it]
                                                            

  1%|          | 6001/569592 [5:07:01<5974:40:57, 38.16s/it]
  1%|          | 6002/569592 [5:07:02<4224:41:00, 26.99s/it]
                                                            

  1%|          | 6002/569592 [5:07:02<4224:41:00, 26.99s/it]
  1%|          | 6003/569592 [5:07:03<3000:49:35, 19.17s/it]
                                                            

  1%|          | 6003/569592 [5:07:03<3000:49:35, 19.17s/it]
  1%|          | 6004/569592 [5:07:06<2267:14:36, 14.48s/it]
                                                            

  1%|          | 6004/569592 [5:07:06<2267:14:36, 14.48s/it]
  1%|          | 6005/569592 [5:07:07<1639:51:30, 10.47s/it]
                                                            

  1%|          | 6005/569592 [5:07:07<1639:51:30, 10.47s/it]
  1%|          | 6006/569592 [5:07:08<1194:34:37,  7.63s/it]
                                                            

  1%|          | 6006/569592 [5:07:08<1194:34:37,  7.63s/it]
  1%|          | 6007/569592 [5:07:12<1012:33:04,  6.47s/it]
                                                            

  1%|          | 6007/569592 [5:07:12<1012:33:04,  6.47s/it]
  1%|          | 6008/569592 [5:07:13<756:44:49,  4.83s/it] 
                                                           

  1%|          | 6008/569592 [5:07:13<756:44:49,  4.83s/it]
  1%|          | 6009/569592 [5:07:18<784:28:53,  5.01s/it]
                                                           

  1%|          | 6009/569592 [5:07:18<784:28:53,  5.01s/it]
  1%|          | 6010/569592 [5:07:23<747:55:22,  4.78s/it]
                                                           

  1%|          | 6010/569592 [5:07:23<747:55:22,  4.78s/it]
  1%|          | 6011/569592 [5:07:26<682:46:26,  4.36s/it]
                                                           

  1%|          | 6011/569592 [5:07:26<682:46:26,  4.36s/it]
  1%|          | 6012/569592 [5:07:31<705:10:09,  4.50s/it]
                                                           

  1%|          | 6012/569592 [5:07:31<705:10:09,  4.50s/it]
  1%|          | 6013/569592 [5:07:35<685:52:19,  4.38s/it]
                                                           

  1%|          | 6013/569592 [5:07:35<685:52:19,  4.38s/it]
  1%|          | 6014/569592 [5:07:42<796:25:19,  5.09s/it]
                                                           

  1%|          | 6014/569592 [5:07:42<796:25:19,  5.09s/it]
  1%|          | 6015/569592 [5:07:45<733:37:41,  4.69s/it]
                                                           

  1%|          | 6015/569592 [5:07:45<733:37:41,  4.69s/it]
  1%|          | 6016/569592 [5:07:50<732:43:33,  4.68s/it]
                                                           

  1%|          | 6016/569592 [5:07:50<732:43:33,  4.68s/it]
  1%|          | 6017/569592 [5:07:53<652:12:49,  4.17s/it]
                                                           

  1%|          | 6017/569592 [5:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101756928 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
07:53<652:12:49,  4.17s/it]
  1%|          | 6018/569592 [5:07:56<613:30:03,  3.92s/it]
                                                           

  1%|          | 6018/569592 [5:07:56<613:30:03,  3.92s/it]
  1%|          | 6019/569592 [5:08:01<654:05:27,  4.18s/it]
                                                           

  1%|          | 6019/569592 [5:08:01<654:05:27,  4.18s/it]
  1%|          | 6020/569592 [5:08:06<669:32:46,  4.28s/it]
                                                           

  1%|          | 6020/569592 [5:08:06<669:32:46,  4.28s/it]
  1%|          | 6021/569592 [5:08:09<614:26:05,  3.92s/it]
                                                           

  1%|          | 6021/569592 [5:08:09<614:26:05,  3.92s/it]
  1%|          | 6022/569592 [5:08:12<597:11:35,  3.81s/it]
                                                           

  1%|          | 6022/569592 [5:08:12<597:11:35,  3.81s/it]
  1%|          | 6023/569592 [5:08:16<587:49:50,  3.75s/it]
                               /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95109120 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                            

  1%|          | 6023/569592 [5:08:16<587:49:50,  3.75s/it]
  1%|          | 6024/569592 [5:08:21<636:21:12,  4.06s/it]
                                                           

  1%|          | 6024/569592 [5:08:21<636:21:12,  4.06s/it]
  1%|          | 6025/569592 [5:08:25<639:24:26,  4.08s/it]
                                                           

  1%|          | 6025/569592 [5:08:25<639:24:26,  4.08s/it]
  1%|          | 6026/569592 [5:08:28<596:05:29,  3.81s/it]
                                                           

  1%|          | 6026/569592 [5:08:28<596:05:29,  3.81s/it]
  1%|          | 6027/569592 [5:08:33<641:00:24,  4.09s/it]
                                                           

  1%|          | 6027/569592 [5:08:33<641:00:24,  4.09s/it]
  1%|          | 6028/569592 [5:08:36<621:01:57,  3.97s/it]
                                                           

  1%|          | 6028/569592 [5:08:36<621:01:57,  3.97s/it]
  1%|          | 6029/569592 [5:08:37<476:56:39,  3.05s/it]
                                                           

  1%|          | 6029/569592 [5:08:37<476:56:39,  3.05s/it]
  1%|          | 6030/569592 [5:08:41<496:34:42,  3.17s/it]
                                                           

  1%|          | 6030/569592 [5:08:41<496:34:42,  3.17s/it]
  1%|          | 6031/569592 [5:08:45<562:00:32,  3.59s/it]
                                                           

  1%|          | 6031/569592 [5:08:45<562:00:32,  3.59s/it]
  1%|          | 6032/569592 [5:08:49<579:10:50,  3.70s/it]
                                                           

  1%|          | 6032/569592 [5:08:49<579:10:50,  3.70s/it]
  1%|          | 6033/569592 [5:08:53<584:35:28,  3.73s/it]
                                                           

  1%|          | 6033/569592 [5:08:53<584:35:28,  3.73s/it]
  1%|          | 6034/569592 [5:08:58<624:43:09,  3.99s/it]
                                                           

  1%|          | 6034/569592 [5:08:58<624:43:09,  3.99s/it]
  1%|          | 6035/569592 [5:09:01<605:53:38,  3.87s/it]
                                                           

  1%|          | 6035/569592 [5:09:01<605:53:38,  3.87s/it]
  1%|          | 6036/569592 [5:09:05<604:07:31,  3.86s/it]
                                                           

  1%|          | 6036/569592 [5:09:05<604:07:31,  3.86s/it]
  1%|          | 6037/569592 [5:09:06<467:16:06,  2.98s/it]
                                                           

  1%|          | 6037/569592 [5:09:06<467:16:06,  2.98s/it]
  1%|          | 6038/569592 [5:09:11<574:51:55,  3.67s/it]
                                                           

  1%|          | 6038/569592 [5:09:11<574:51:55,  3.67s/it]
  1%|          | 6039/569592 [5:09:15<577:00:41,  3.69s/it]
                                                           

  1%|          | 6039/569592 [5:09:15<577:00:41,  3.69s/it]
  1%|          | 6040/569592 [5:09:19<586:47:20,  3.75s/it]
                                                           

  1%|          | 6040/569592 [5:09:19<586:47:20,  3.75s/it]
  1%|          | 6041/569592 [5:09:22<569:42:47,  3.64s/it]
                                                           

  1%|          | 6041/569592 [5:09:22<569:42:47,  3.64s/it]
  1%|          | 6042/569592 [5:09:26<552:24:45,  3.53s/it]
                                                           

  1%|          | 6042/569592 [5:09:26<552:24:45,  3.53s/it]
  1%|          | 6043/569592 [5:09:30<572:00:45,  3.65s/it]
                                                           

  1%|          | 6043/569592 [5:09:30<572:00:45,  3.65s/it]
  1%|          | 6044/569592 [5:09:31<444:33:16,  2.84s/it]
                                                           

  1%|          | 6044/569592 [5:09:31<444:33:16,  2.84s/it]
  1%|          | 6045/569592 [5:09:31<355:14:45,  2.27s/it]
                                                           

  1%|          | 6045/569592 [5:09:32<355:14:45,  2.27s/it]
  1%|          | 6046/569592 [5:09:35<401:37:24,  2.57s/it]
                                                           

  1%|          | 6046/569592 [5:09:35<401:37:24,  2.57s/it]
  1%|          | 6047/569592 [5:09:40<542:19:15,  3.46s/it]
                                                           

  1%|          | 6047/569592 [5:09:40<542:19:15,  3.46s/it]
  1%|          | 6048/569592 [5:09:44<552:18:21,  3.53s/it]
                                                           

  1%|          | 6048/569592 [5:09:44<552:18:21,  3.53s/it]
  1%|          | 6049/569592 [5:09:45<428:11:03,  2.74s/it]
                                                           

  1%|          | 6049/569592 [5:09:45<428:11:03,  2.74s/it]
  1%|          | 6050/569592 [5:09:46<342:41:54,  2.19s/it]
                                                           

  1%|          | 6050/569592 [5:09:46<342:41:54,  2.19s/it]
  1%|          | 6051/569592 [5:09:50<427:08:51,  2.73s/it]
                                                           

  1%|          | 6051/569592 [5:09:50<427:08:51,  2.73s/it]
  1%|          | 6052/569592 [5:09:53<453:39:14,  2.90s/it]
                                                           

  1%|          | 6052/569592 [5:09:53<453:39:14,  2.90s/it]
  1%|          | 6053/569592 [5:09:58<549:19:21,  3.51s/it]
                                                           

  1%|          | 6053/569592 [5:09:58<549:19:21,  3.51s/it]
  1%|          | 6054/569592 [5:09:59<427:15:48,  2.73s/it]
                                                           

  1%|          | 6054/569592 [5:09:59<427:15:48,  2.73s/it]
  1%|          | 6055/569592 [5:10:02<446:50:34,  2.85s/it]
                                                           

  1%|          | 6055/569592 [5:10:02<446:50:34,  2.85s/it]
  1%|          | 6056/569592 [5:10:06<479:03:52,  3.06s/it]
                                                           

  1%|          | 6056/569592 [5:10:06<479:03:52,  3.06s/it]
  1%|          | 6057/569592 [5:10:09<511:08:50,  3.27s/it]
                                                           

  1%|          | 6057/569592 [5:10:09<511:08:50,  3.27s/it]
  1%|          | 6058/569592 [5:10:10<401:00:01,  2.56s/it]
                                                           

  1%|          | 6058/569592 [5:10:10<401:00:01,  2.56s/it]
  1%|          | 6059/569592 [5:10:14<458:24:44,  2.93s/it]
                                                           

  1%|          | 6059/569592 [5:10:14<458:24:44,  2.93s/it]
  1%|          | 6060/569592 [5:10:15<365:46:30,  2.34s/it]
                                                           

  1%|          | 6060/569592 [5:10:15<365:46:30,  2.34s/it]
  1%|          | 6061/569592 [5:10:20<499:18:07,  3.19s/it]
                                                           

  1%|          | 6061/569592 [5:10:20<499:18:07,  3.19s/it]
  1%|          | 6062/569592 [5:10:21<393:51:03,  2.52s/it]
                                                           

  1%|          | 6062/569592 [5:10:21<393:51:03,  2.52s/it]
  1%|          | 6063/569592 [5:10:26<503:56:11,  3.22s/it]
                                                           

  1%|          | 6063/569592 [5:10:26<503:56:11,  3.22s/it]
  1%|          | 6064/569592 [5:10:29<503:04:43,  3.21s/it]
                                                           

  1%|          | 6064/569592 [5:10:29<503:04:43,  3.21s/it]
  1%|          | 6065/569592 [5:10:33<511:40:39,  3.27s/it]
                                                           

  1%|          | 6065/569592 [5:10:33<511:40:39,  3.27s/it]
  1%|          | 6066/569592 [5:10:34<401:12:36,  2.56s/it]
                                                           

  1%|          | 6066/569592 [5:10:34<401:12:36,  2.56s/it]
  1%|          | 6067/569592 [5:10:34<325:47:39,  2.08s/it]
                                                           

  1%|          | 6067/569592 [5:10:34<325:47:39,  2.08s/it]
  1%|          | 6068/569592 [5:10:38<388:08:52,  2.48s/it]
                                                           

  1%|          | 6068/569592 [5:10:38<388:08:52,  2.48s/it]
  1%|          | 6069/569592 [5:10:39<316:58:26,  2.02s/it]
                                                           

  1%|          | 6069/569592 [5:10:39<316:58:26,  2.02s/it]
  1%|          | 6070/569592 [5:10:43<394:27:36,  2.52s/it]
                                                           

  1%|          | 6070/569592 [5:10:43<394:27:36,  2.52s/it]
  1%|          | 6071/569592 [5:10:44<323:19:30,  2.07s/it]
                                                           

  1%|          | 6071/569592 [5:10:44<323:19:30,  2.07s/it]
  1%|          | 6072/569592 [5:10:44<272:27:07,  1.74s/it]
                                                           

  1%|          | 6072/569592 [5:10:45<272:27:07,  1.74s/it]
  1%|          | 6073/569592 [5:10:45<236:27:45,  1.51s/it]
                                                           

  1%|          | 6073/569592 [5:10:45<236:27:45,  1.51s/it]
  1%|          | 6074/569592 [5:10:46<212:39:38,  1.36s/it]
                                                           

  1%|          | 6074/569592 [5:10:46<212:39:38,  1.36s/it]
  1%|          | 6075/569592 [5:10:47<195:33:18,  1.25s/it]
                                                           

  1%|          | 6075/569592 [5:10:47<195:33:18,  1.25s/it]
  1%|          | 6076/569592 [5:10:49<186:43:11,  1.19s/it]
                                                           

  1%|          | 6076/569592 [5:10:49<186:43:11,  1.19s/it]
  1%|          | 6077/569592 [5:10:52<280:47:24,  1.79s/it]
                                                           

  1%|          | 6077/569592 [5:10:52<280:47:24,  1.79s/it]
  1%|          | 6078/569592 [5:10:57<452:54:51,  2.89s/it]
                                                           

  1%|          | 6078/569592 [5:10:57<452:54:51,  2.89s/it]
  1%|          | 6079/569592 [5:10:58<361:12:56,  2.31s/it]
                                                           

  1%|          | 6079/569592 [5:10:58<361:12:56,  2.31s/it]
  1%|          | 6080/569592 [5:11:00<318:20:56,  2.03s/it]
                                                           

  1%|          | 6080/569592 [5:11:00<318:20:56,  2.03s/it]
  1%|          | 6081/569592 [5:11:02<316:02:30,  2.02s/it]
                                                           

  1%|          | 6081/569592 [5:11:02<316:02:30,  2.02s/it]
  1%|          | 6082/569592 [5:11:07<480:40:23,  3.07s/it]
                                                           

  1%|          | 6082/569592 [5:11:07<480:40:23,  3.07s/it]
  1%|          | 6083/569592 [5:11:08<382:11:07,  2.44s/it]
                                                           

  1%|          | 6083/569592 [5:11:08<382:11:07,  2.44s/it]
  1%|          | 6084/569592 [5:11:09<324:06:41,  2.07s/it]
                                                           

  1%|          | 6084/569592 [5:11:09<324:06:41,  2.07s/it]
  1%|          | 6085/569592 [5:11:13<384:54:03,  2.46s/it]
                                                           

  1%|          | 6085/569592 [5:11:13<384:54:03,  2.46s/it]
  1%|          | 6086/569592 [5:11:16<449:48:41,  2.87s/it]
                                                           

  1%|          | 6086/569592 [5:11:16<449:48:41,  2.87s/it]
  1%|          | 6087/569592 [5:11:21<506:46:24,  3.24s/it]
                                                           

  1%|          | 6087/569592 [5:11:21<506:46:24,  3.24s/it]
  1%|          | 6088/569592 [5:11:26<611:20:26,  3.91s/it]
                                                           

  1%|          | 6088/569592 [5:11:26<611:20:26,  3.91s/it]
  1%|          | 6089/569592 [5:11:27<476:08:41,  3.04s/it]
                                                           

  1%|          | 6089/569592 [5:11:27<476:08:41,  3.04s/it]
  1%|          | 6090/569592 [5:11:31<516:34:24,  3.30s/it]
                                                           

  1%|          | 6090/569592 [5:11:31<516:34:24,  3.30s/it]
  1%|          | 6091/569592 [5:11:34<520:01:12,  3.32s/it]
                                                           

  1%|          | 6091/569592 [5:11:34<520:01:12,  3.32s/it]
  1%|          | 6092/569592 [5:11:35<411:02:38,  2.63s/it]
                                                           

  1%|          | 6092/569592 [5:11:35<411:02:38,  2.63s/it]
  1%|          | 6093/569592 [5:11:36<343:16:03,  2.19s/it]
                                                           

  1%|          | 6093/569592 [5:11:36<343:16:03,  2.19s/it]
  1%|          | 6094/569592 [5:11:39<371:41:02,  2.37s/it]
                                                           

  1%|          | 6094/569592 [5:11:39<371:41:02,  2.37s/it]
  1%|          | 6095/569592 [5:11:43<422:10:31,  2.70s/it]
                                                           

  1%|          | 6095/569592 [5:11:43<422:10:31,  2.70s/it]
  1%|          | 6096/569592 [5:11:44<339:41:14,  2.17s/it]
                                                           

  1%|          | 6096/569592 [5:11:44<339:41:14,  2.17s/it]
  1%|          | 6097/569592 [5:11:47<399:46:55,  2.55s/it]
                                                           

  1%|          | 6097/569592 [5:11:47<399:46:55,  2.55s/it]
  1%|          | 6098/569592 [5:11:51<464:53:42,  2.97s/it]
                                                           

  1%|          | 6098/569592 [5:11:51<464:53:42,  2.97s/it]
  1%|          | 6099/569592 [5:11:52<370:03:39,  2.36s/it]
                                                           

  1%|          | 6099/569592 [5:11:52<370:03:39,  2.36s/it]
  1%|          | 6100/569592 [5:11:53<304:04:27,  1.94s/it]
                                                           

  1%|          | 6100/569592 [5:11:53<304:04:27,  1.94s/it]
  1%|          | 6101/569592 [5:11:54<256:32:11,  1.64s/it]
                                                           

  1%|          | 6101/569592 [5:11:54<256:32:11,  1.64s/it]
  1%|          | 6102/569592 [5:12:01<498:58:24,  3.19s/it]
                                                           

  1%|          | 6102/569592 [5:12:01<498:58:24,  3.19s/it]
  1%|          | 6103/569592 [5:12:04<525:20:27,  3.36s/it]
                                                           

  1%|          | 6103/569592 [5:12:04<525:20:27,  3.36s/it]
  1%|          | 6104/569592 [5:12:05<412:11:36,  2.63s/it]
                                                           

  1%|          | 6104/569592 [5:12:05<412:11:36,  2.63s/it]
  1%|          | 6105/569592 [5:12:06<339:46:00,  2.17s/it]
                                                           

  1%|          | 6105/569592 [5:12:06<339:46:00,  2.17s/it]
  1%|          | 6106/569592 [5:12:11<458:46:09,  2.93s/it]
                                                           

  1%|          | 6106/569592 [5:12:11<458:46:09,  2.93s/it]
  1%|          | 6107/569592 [5:12:12<366:06:05,  2.34s/it]
                                                           

  1%|          | 6107/569592 [5:12:12<366:06:05,  2.34s/it]
  1%|          | 6108/569592 [5:12:16<446:42:15,  2.85s/it]
                                                           

  1%|          | 6108/569592 [5:12:16<446:42:15,  2.85s/it]
  1%|          | 6109/569592 [5:12:20<500:57:17,  3.20s/it]
                                                           

  1%|          | 6109/569592 [5:12:20<500:57:17,  3.20s/it]
  1%|          | 6110/569592 [5:12:24<534:09:07,  3.41s/it]
                                                           

  1%|          | 6110/569592 [5:12:24<534:09:07,  3.41s/it]
  1%|          | 6111/569592 [5:12:27<521:47:45,  3.33s/it]
                                                           

  1%|          | 6111/569592 [5:12:27<521:47:45,  3.33s/it]
  1%|          | 6112/569592 [5:12:33<613:35:43,  3.92s/it]
                                                           

  1%|          | 6112/569592 [5:12:33<613:35:43,  3.92s/it]
  1%|          | 6113/569592 [5:12:33<471:22:13,  3.01s/it]
                                                           

  1%|          | 6113/569592 [5:12:33<471:22:13,  3.01s/it]
  1%|          | 6114/569592 [5:12:37<500:26:42,  3.20s/it]
                                                           

  1%|          | 6114/569592 [5:12:37<500:26:42,  3.20s/it]
  1%|          | 6115/569592 [5:12:41<526:54:28,  3.37s/it]
                                                           

  1%|          | 6115/569592 [5:12:41<526:54:28,  3.37s/it]
  1%|          | 6116/569592 [5:12:45<556:00:05,  3.55s/it]
                                                           

  1%|          | 6116/569592 [5:12:45<556:00:05,  3.55s/it]
  1%|          | 6117/569592 [5:12:48<559:37:27,  3.58s/it]
                                                           

  1%|          | 6117/569592 [5:12:48<559:37:27,  3.58s/it]
  1%|          | 6118/569592 [5:12:49<438:23:00,  2.80s/it]
                                                           

  1%|          | 6118/569592 [5:12:49<438:23:00,  2.80s/it]
  1%|          | 6119/569592 [5:12:50<352:23:08,  2.25s/it]
                                                           

  1%|          | 6119/569592 [5:12:50<352:23:08,  2.25s/it]
  1%|          | 6120/569592 [5:12:51<295:29:22,  1.89s/it]
                                                           

  1%|          | 6120/569592 [5:12:51<295:29:22,  1.89s/it]
  1%|          | 6121/569592 [5:12:52<253:32:47,  1.62s/it]
                                                           

  1%|          | 6121/569592 [5:12:52<253:32:47,  1.62s/it]
  1%|          | 6122/569592 [5:12:53<223:27:20,  1.43s/it]
                                                           

  1%|          | 6122/569592 [5:12:53<223:27:20,  1.43s/it]
  1%|          | 6123/569592 [5:12:57<339:08:49,  2.17s/it]
                                                           

  1%|          | 6123/569592 [5:12:57<339:08:49,  2.17s/it]
  1%|          | 6124/569592 [5:13:01<405:31:58,  2.59s/it]
                                                           

  1%|          | 6124/569592 [5:13:01<405:31:58,  2.59s/it]
  1%|          | 6125/569592 [5:13:05<472:13:47,  3.02s/it]
                                                           

  1%|          | 6125/569592 [5:13:05<472:13:47,  3.02s/it]
  1%|          | 6126/569592 [5:13:08<491:46:06,  3.14s/it]
                                                           

  1%|          | 6126/569592 [5:13:08<491:46:06,  3.14s/it]
  1%|          | 6127/569592 [5:13:12<523:49:47,  3.35s/it]
                                                           

  1%|          | 6127/569592 [5:13:12<523:49:47,  3.35s/it]
  1%|          | 6128/569592 [5:13:16<556:30:28,  3.56s/it]
                                                           

  1%|          | 6128/569592 [5:13:16<556:30:28,  3.56s/it]
  1%|          | 6129/569592 [5:13:20<582:03:34,  3.72s/it]
                                                           

  1%|          | 6129/569592 [5:13:20<582:03:34,  3.72s/it]
  1%|          | 6130/569592 [5:13:24<562:25:52,  3.59s/it]
                                                           

  1%|          | 6130/569592 [5:13:24<562:25:52,  3.59s/it]
  1%|          | 6131/569592 [5:13:27<557:35:36,  3.56s/it]
                                                           

  1%|          | 6131/569592 [5:13:27<557:35:36,  3.56s/it]
  1%|          | 6132/569592 [5:13:28<433:28:22,  2.77s/it]
                                                           

  1%|          | 6132/569592 [5:13:28<433:28:22,  2.77s/it]
  1%|          | 6133/569592 [5:13:32<499:18:21,  3.19s/it]
                                                           

  1%|          | 6133/569592 [5:13:32<499:18:21,  3.19s/it]
  1%|          | 6134/569592 [5:13:36<545:28:33,  3.49s/it]
                                                           

  1%|          | 6134/569592 [5:13:36<545:28:33,  3.49s/it]
  1%|          | 6135/569592 [5:13:40<552:29:59,  3.53s/it]
                                                           

  1%|          | 6135/569592 [5:13:40<552:29:59,  3.53s/it]
  1%|          | 6136/569592 [5:13:43<537:06:54,  3.43s/it]
                                                           

  1%|          | 6136/569592 [5:13:43<537:06:54,  3.43s/it]
  1%|          | 6137/569592 [5:13:47<533:21:59,  3.41s/it]
                                                           

  1%|          | 6137/569592 [5:13:47<533:21:59,  3.41s/it]
  1%|          | 6138/569592 [5:13:51<574:40:49,  3.67s/it]
                                                           

  1%|          | 6138/569592 [5:13:51<574:40:49,  3.67s/it]
  1%|          | 6139/569592 [5:13:52<444:50:50,  2.84s/it]
                                                           

  1%|          | 6139/569592 [5:13:52<444:50:50,  2.84s/it]
  1%|          | 6140/569592 [5:13:55<481:47:43,  3.08s/it]
                                                           

  1%|          | 6140/569592 [5:13:55<481:47:43,  3.08s/it]
  1%|          | 6141/569592 [5:13:59<515:14:56,  3.29s/it]
                                                           

  1%|          | 6141/569592 [5:13:59<515:14:56,  3.29s/it]
  1%|          | 6142/569592 [5:14:02<511:42:16,  3.27s/it]
                                                           

  1%|          | 6142/569592 [5:14:02<511:42:16,  3.27s/it]
  1%|          | 6143/569592 [5:14:06<508:19:58,  3.25s/it]
                                                           

  1%|          | 6143/569592 [5:14:06<508:19:58,  3.25s/it]
  1%|          | 6144/569592 [5:14:10<572:45:09,  3.66s/it]
                                                           

  1%|          | 6144/569592 [5:14:10<572:45:09,  3.66s/it]
  1%|          | 6145/569592 [5:14:16<664:18:35,  4.24s/it]
                                                           

  1%|          | 6145/569592 [5:14:16<664:18:35,  4.24s/it]
  1%|          | 6146/569592 [5:14:19<632:41:27,  4.04s/it]
                                                           

  1%|          | 6146/569592 [5:14:19<632:41:27,  4.04s/it]
  1%|          | 6147/569592 [5:14:20<485:35:47,  3.10s/it]
                                                           

  1%|          | 6147/569592 [5:14:20<485:35:47,  3.10s/it]
  1%|          | 6148/569592 [5:14:23<487:58:31,  3.12s/it]
                                                           

  1%|          | 6148/569592 [5:14:23<487:58:31,  3.12s/it]
  1%|          | 6149/569592 [5:14:27<502:03:17,  3.21s/it]
                                                           

  1%|          | 6149/569592 [5:14:27<502:03:17,  3.21s/it]
  1%|          | 6150/569592 [5:14:28<397:38:30,  2.54s/it]
                                                           

  1%|          | 6150/569592 [5:14:28<397:38:30,  2.54s/it]
  1%|          | 6151/569592 [5:14:31<441:46:45,  2.82s/it]
                                                           

  1%|          | 6151/569592 [5:14:31<441:46:45,  2.82s/it]
  1%|          | 6152/569592 [5:14:36<513:18:34,  3.28s/it]
                                                           

  1%|          | 6152/569592 [5:14:36<513:18:34,  3.28s/it]
  1%|          | 6153/569592 [5:14:40<541:15:24,  3.46s/it]
                                                           

  1%|          | 6153/569592 [5:14:40<541:15:24,  3.46s/it]
  1%|          | 6154/569592 [5:14:44<611:18:22,  3.91s/it]
                                                           

  1%|          | 6154/569592 [5:14:44<611:18:22,  3.91s/it]
  1%|          | 6155/569592 [5:14:48<581:47:14,  3.72s/it]
                                                           

  1%|          | 6155/569592 [5:14:48<581:47:14,  3.72s/it]
  1%|          | 6156/569592 [5:14:51<571:22:46,  3.65s/it]
                                                           

  1%|          | 6156/569592 [5:14:51<571:22:46,  3.65s/it]
  1%|          | 6157/569592 [5:14:52<442:48:28,  2.83s/it]
                                                           

  1%|          | 6157/569592 [5:14:52<442:48:28,  2.83s/it]
  1%|          | 6158/569592 [5:14:53<354:45:30,  2.27s/it]
                                                           

  1%|          | 6158/569592 [5:14:53<354:45:30,  2.27s/it]
  1%|          | 6159/569592 [5:14:56<404:47:20,  2.59s/it]
                                                           

  1%|          | 6159/569592 [5:14:56<404:47:20,  2.59s/it]
  1%|          | 6160/569592 [5:15:00<472:14:43,  3.02s/it]
                                                           

  1%|          | 6160/569592 [5:15:01<472:14:43,  3.02s/it]
  1%|          | 6161/569592 [5:15:04<489:01:39,  3.12s/it]
                                                           

  1%|          | 6161/569592 [5:15:04<489:01:39,  3.12s/it]
  1%|          | 6162/569592 [5:15:05<385:26:09,  2.46s/it]
                                                           

  1%|          | 6162/569592 [5:15:05<385:26:09,  2.46s/it]
  1%|          | 6163/569592 [5:15:08<437:16:00,  2.79s/it]
                                                           

  1%|          | 6163/569592 [5:15:08<437:16:00,  2.79s/it]
  1%|          | 6164/569592 [5:15:12<478:23:44,  3.06s/it]
                                                           

  1%|          | 6164/569592 [5:15:12<478:23:44,  3.06s/it]
  1%|          | 6165/569592 [5:15:15<481:57:51,  3.08s/it]
                                                           

  1%|          | 6165/569592 [5:15:15<481:57:51,  3.08s/it]
  1%|          | 6166/569592 [5:15:19<510:45:50,  3.26s/it]
                                                           

  1%|          | 6166/569592 [5:15:19<510:45:50,  3.26s/it]
  1%|          | 6167/569592 [5:15:22<508:16:55,  3.25s/it]
                                                           

  1%|          | 6167/569592 [5:15:22<508:16:55,  3.25s/it]
  1%|          | 6168/569592 [5:15:25<496:24:47,  3.17s/it]
                                                           

  1%|          | 6168/569592 [5:15:25<496:24:47,  3.17s/it]
  1%|          | 6169/569592 [5:15:28<501:07:32,  3.20s/it]
                                                           

  1%|          | 6169/569592 [5:15:28<501:07:32,  3.20s/it]
  1%|          | 6170/569592 [5:15:32<522:42:25,  3.34s/it]
                                                           

  1%|          | 6170/569592 [5:15:32<522:42:25,  3.34s/it]
  1%|          | 6171/569592 [5:15:33<408:11:41,  2.61s/it]
                                                           

  1%|          | 6171/569592 [5:15:33<408:11:41,  2.61s/it]
  1%|          | 6172/569592 [5:15:36<448:36:55,  2.87s/it]
                                                           

  1%|          | 6172/569592 [5:15:36<448:36:55,  2.87s/it]
  1%|          | 6173/569592 [5:15:37<357:52:20,  2.29s/it]
                                                           

  1%|          | 6173/569592 [5:15:37<357:52:20,  2.29s/it]
  1%|          | 6174/569592 [5:15:43<498:32:44,  3.19s/it]
                                                           

  1%|          | 6174/569592 [5:15:43<498:32:44,  3.19s/it]
  1%|          | 6175/569592 [5:15:43<391:25:26,  2.50s/it]
                                                           

  1%|          | 6175/569592 [5:15:43<391:25:26,  2.50s/it]
  1%|          | 6176/569592 [5:15:47<441:22:07,  2.82s/it]
                                                           

  1%|          | 6176/569592 [5:15:47<441:22:07,  2.82s/it]
  1%|          | 6177/569592 [5:15:50<453:59:02,  2.90s/it]
                                                           

  1%|          | 6177/569592 [5:15:50<453:59:02,  2.90s/it]
  1%|          | 6178/569592 [5:15:54<486:13:27,  3.11s/it]
                                                           

  1%|          | 6178/569592 [5:15:54<486:13:27,  3.11s/it]
  1%|          | 6179/569592 [5:15:55<382:48:40,  2.45s/it]
                                                           

  1%|          | 6179/569592 [5:15:55<382:48:40,  2.45s/it]
  1%|          | 6180/569592 [5:15:56<314:20:30,  2.01s/it]
                                                           

  1%|          | 6180/569592 [5:15:56<314:20:30,  2.01s/it]
  1%|          | 6181/569592 [5:15:59<379:27:20,  2.42s/it]
                                                           

  1%|          | 6181/569592 [5:15:59<379:27:20,  2.42s/it]
  1%|          | 6182/569592 [5:16:00<312:17:52,  2.00s/it]
                                                           

  1%|          | 6182/569592 [5:16:00<312:17:52,  2.00s/it]
  1%|          | 6183/569592 [5:16:01<263:14:28,  1.68s/it]
                                                           

  1%|          | 6183/569592 [5:16:01<263:14:28,  1.68s/it]
  1%|          | 6184/569592 [5:16:02<228:48:12,  1.46s/it]
                                                           

  1%|          | 6184/569592 [5:16:02<228:48:12,  1.46s/it]
  1%|          | 6185/569592 [5:16:03<206:25:09,  1.32s/it]
                                                           

  1%|          | 6185/569592 [5:16:03<206:25:09,  1.32s/it]
  1%|          | 6186/569592 [5:16:04<189:34:35,  1.21s/it]
                                                           

  1%|          | 6186/569592 [5:16:04<189:34:35,  1.21s/it]
  1%|          | 6187/569592 [5:16:07<292:43:49,  1.87s/it]
                                                           

  1%|          | 6187/569592 [5:16:07<292:43:49,  1.87s/it]
  1%|          | 6188/569592 [5:16:08<258:12:01,  1.65s/it]
                                                           

  1%|          | 6188/569592 [5:16:08<258:12:01,  1.65s/it]
  1%|          | 6189/569592 [5:16:11<304:33:35,  1.95s/it]
                                                           

  1%|          | 6189/569592 [5:16:11<304:33:35,  1.95s/it]
  1%|          | 6190/569592 [5:16:13<319:46:12,  2.04s/it]
                                                           

  1%|          | 6190/569592 [5:16:13<319:46:12,  2.04s/it]
  1%|          | 6191/569592 [5:16:19<480:09:59,  3.07s/it]
                                                           

  1%|          | 6191/569592 [5:16:19<480:09:59,  3.07s/it]
  1%|          | 6192/569592 [5:16:20<386:08:02,  2.47s/it]
                                                           

  1%|          | 6192/569592 [5:16:20<386:08:02,  2.47s/it]
  1%|          | 6193/569592 [5:16:22<355:45:55,  2.27s/it]
                                                           

  1%|          | 6193/569592 [5:16:22<355:45:55,  2.27s/it]
  1%|          | 6194/569592 [5:16:24<342:41:45,  2.19s/it]
                                                           

  1%|          | 6194/569592 [5:16:24<342:41:45,  2.19s/it]
  1%|          | 6195/569592 [5:16:28<441:40:52,  2.82s/it]
                                                           

  1%|          | 6195/569592 [5:16:28<441:40:52,  2.82s/it]
  1%|          | 6196/569592 [5:16:29<353:22:39,  2.26s/it]
                                                           

  1%|          | 6196/569592 [5:16:29<353:22:39,  2.26s/it]
  1%|          | 6197/569592 [5:16:31<343:08:05,  2.19s/it]
                                                           

  1%|          | 6197/569592 [5:16:31<343:08:05,  2.19s/it]
  1%|          | 6198/569592 [5:16:35<416:30:14,  2.66s/it]
                                                           

  1%|          | 6198/569592 [5:16:35<4/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
16:30:14,  2.66s/it]
  1%|          | 6199/569592 [5:16:38<465:25:07,  2.97s/it]
                                                           

  1%|          | 6199/569592 [5:16:38<465:25:07,  2.97s/it]
  1%|          | 6200/569592 [5:16:39<369:36:15,  2.36s/it]
                                                           

  1%|          | 6200/569592 [5:16:39<369:36:15,  2.36s/it]
  1%|          | 6201/569592 [5:16:43<438:17:54,  2.80s/it]
                                                           

  1%|          | 6201/569592 [5:16:43<438:17:54,  2.80s/it]
  1%|          | 6202/569592 [5:16:47<481:08:01,  3.07s/it]
                                                           

  1%|          | 6202/569592 [5:16:47<481:08:01,  3.07s/it]
  1%|          | 6203/569592 [5:16:49<438:03:01,  2.80s/it]
                                                           

  1%|          | 6203/569592 [5:16:49<438:03:01,  2.80s/it]
  1%|          | 6204/569592 [5:16:52<466:15:37,  2.98s/it]
                                                           

  1%|          | 6204/569592 [5:16:52<466:15:37,  2.98s/it]
  1%|          | 6205/569592 [5:16:56<500:16:15,  3.20s/it]
                                                           

  1%|          | 6205/569592 [5:16:56<500:16:15,  3.20s/it]
  1%|          | 6206/569592 [5:17:00<511:43:13,  3.27s/it]
                                                           

  1%|          | 6206/569592 [5:17:00<511:43:13,  3.27s/it]
  1%|          | 6207/569592 [5:17:01<408:02:58,  2.61s/it]
                                                           

  1%|          | 6207/569592 [5:17:01<408:02:58,  2.61s/it]
  1%|          | 6208/569592 [5:17:04<446:49:03,  2.86s/it]
                                                           

  1%|          | 6208/569592 [5:17:04<446:49:03,  2.86s/it]
  1%|          | 6209/569592 [5:17:05<358:52:49,  2.29s/it]
                                                           

  1%|          | 6209/569592 [5:17:05<358:52:49,  2.29s/it]
  1%|          | 6210/569592 [5:17:09<423:31:47,  2.71s/it]
                                                           

  1%|          | 6210/569592 [5:17:09<423:31:47,  2.71s/it]
  1%|          | 6211/569592 [5:17:12<467:19:44,  2.99s/it]
                                                           

  1%|          | 6211/569592 [5:17:12<467:19:44,  2.99s/it]
  1%|          | 6212/569592 [5:17:13<376:31:00,  2.41s/it]
                                                           

  1%|          | 6212/569592 [5:17:13<376:31:00,  2.41s/it]
  1%|          | 6213/569592 [5:17:14<309:14:28,  1.98s/it]
                                                           

  1%|          | 6213/569592 [5:17:14<309:14:28,  1.98s/it]
  1%|          | 6214/569592 [5:17:17<323:00:11,  2.06s/it]
                                                           

  1%|          | 6214/569592 [5:17:17<323:00:11,  2.06s/it]
  1%|          | 6215/569592 [5:17:19<355:59:46,  2.27s/it]
                                                           

  1%|          | 6215/569592 [5:17:19<355:59:46,  2.27s/it]
  1%|          | 6216/569592 [5:17:23<404:10:00,  2.58s/it]
                                                           

  1%|          | 6216/569592 [5:17:23<404:10:00,  2.58s/it]
  1%|          | 6217/569592 [5:17:24<328:37:40,  2.10s/it]
                                                           

  1%|          | 6217/569592 [5:17:24<328:37:40,  2.10s/it]
  1%|          | 6218/569592 [5:17:28<430:31:14,  2.75s/it]
                                                           

  1%|          | 6218/569592 [5:17:28<430:31:14,  2.75s/it]
  1%|          | 6219/569592 [5:17:30<382:41:08,  2.45s/it]
                                                           

  1%|          | 6219/569592 [5:17:30<382:41:08,  2.45s/it]
  1%|          | 6220/569592 [5:17:33<444:15:31,  2.84s/it]
                                                           

  1%|          | 6220/569592 [5:17:33<444:15:31,  2.84s/it]
  1%|          | 6221/569592 [5:17:37<463:30:26,  2.96s/it]
                                                           

  1%|          | 6221/569592 [5:17:37<463:30:26,  2.96s/it]
  1%|          | 6222/569592 [5:17:42<559:47:35,  3.58s/it]
                                                           

  1%|          | 6222/569592 [5:17:42<559:47:35,  3.58s/it]
  1%|          | 6223/569592 [5:17:45<542:27:53,  3.47s/it]
                                                           

  1%|          | 6223/569592 [5:17:45<542:27:53,  3.47s/it]
  1%|          | 6224/569592 [5:17:46<424:01:49,  2.71s/it]
                                                           

  1%|          | 6224/569592 [5:17:46<424:01:49,  2.71s/it]
  1%|          | 6225/569592 [5:17:47<341:25:20,  2.18s/it]
                                                           

  1%|          | 6225/569592 [5:17:47<341:25:20,  2.18s/it]
  1%|          | 6226/569592 [5:17:51<422:38:58,  2.70s/it]
                                                           

  1%|          | 6226/569592 [5:17:51<422:38:58,  2.70s/it]
  1%|          | 6227/569592 [5:17:52<340:13:33,  2.17s/it]
                                                           

  1%|          | 6227/569592 [5:17:52<340:13:33,  2.17s/it]
  1%|          | 6228/569592 [5:17:53<287:14:54,  1.84s/it]
                                                           

  1%|          | 6228/569592 [5:17:53<287:14:54,  1.84s/it]
  1%|          | 6229/569592 [5:17:56<374:58:47,  2.40s/it]
                                                           

  1%|          | 6229/569592 [5:17:56<374:58:47,  2.40s/it]
  1%|          | 6230/569592 [5:18:00<427:50:18,  2.73s/it]
                                                           

  1%|          | 6230/569592 [5:18:00<427:50:18,  2.73s/it]
  1%|          | 6231/569592 [5:18:04<476:31:33,  3.05s/it]
                                                           

  1%|          | 6231/569592 [5:18:04<476:31:33,  3.05s/it]
  1%|          | 6232/569592 [5:18:07<481:04:50,  3.07s/it]
                                                           

  1%|          | 6232/569592 [5:18:07<481:04:50,  3.07s/it]
  1%|          | 6233/569592 [5:18:08<380:11:16,  2.43s/it]
                                                           

  1%|          | 6233/569592 [5:18:08<380:11:16,  2.43s/it]
  1%|          | 6234/569592 [5:18:12<449:26:23,  2.87s/it]
                                                           

  1%|          | 6234/569592 [5:18:12<449:26:23,  2.87s/it]
  1%|          | 6235/569592 [5:18:16<533:57:24,  3.41s/it]
                                                           

  1%|          | 6235/569592 [5:18:16<533:57:24,  3.41s/it]
  1%|          | 6236/569592 [5:18:20<531:25:30,  3.40s/it]
                                                           

  1%|          | 6236/569592 [5:18:20<531:25:30,  3.40s/it]
  1%|          | 6237/569592 [5:18:25<598:38:48,  3.83s/it]
                                                           

  1%|          | 6237/569592 [5:18:25<598:38:48,  3.83s/it]
  1%|          | 6238/569592 [5:18:28<590:28:16,  3.77s/it]
                                                           

  1%|          | 6238/569592 [5:18:28<590:28:16,  3.77s/it]
  1%|          | 6239/569592 [5:18:29<458:31:18,  2.93s/it]
                                                           

  1%|          | 6239/569592 [5:18:29<458:31:18,  2.93s/it]
  1%|          | 6240/569592 [5:18:33<489:33:32,  3.13s/it]
                                                           

  1%|          | 6240/569592 [5:18:33<489:33:32,  3.13s/it]
  1%|          | 6241/569592 [5:18:37<522:03:15,  3.34s/it]
                                                           

  1%|          | 6241/569592 [5:18:37<522:03:15,  3.34s/it]
  1%|          | 6242/569592 [5:18:40<526:03:23,  3.36s/it]
                                                           

  1%|          | 6242/569592 [5:18:40<526:03:23,  3.36s/it]
  1%|          | 6243/569592 [5:18:44<539:45:51,  3.45s/it]
                                                           

  1%|          | 6243/569592 [5:18:44<539:45:51,  3.45s/it]
  1%|          | 6244/569592 [5:18:47<534:25:25,  3.42s/it]
                                                           

  1%|          | 6244/569592 [5:18:47<534:25:25,  3.42s/it]
  1%|          | 6245/569592 [5:18:50<518:43:48,  3.31s/it]
                                                           

  1%|          | 6245/569592 [5:18:50<518:43:48,  3.31s/it]
  1%|          | 6246/569592 [5:18:54<535:53:45,  3.42s/it]
                                                           

  1%|          | 6246/569592 [5:18:54<535:53:45,  3.42s/it]
  1%|          | 6247/569592 [5:18:57<525:14:40,  3.36s/it]
                                                           

  1%|          | 6247/569592 [5:18:57<525:14:40,  3.36s/it]
  1%|          | 6248/569592 [5:19:00<523:43:54,  3.35s/it]
                                                           

  1%|          | 6248/569592 [5:19:00<523:43:54,  3.35s/it]
  1%|          | 6249/569592 [5:19:04<548:56:22,  3.51s/it]
                                                           

  1%|          | 6249/569592 [5:19:04<548:56:22,  3.51s/it]
  1%|          | 6250/569592 [5:19:07<539:31:29,  3.45s/it]
                                                           

  1%|          | 6250/569592 [5:19:07<539:31:29,  3.45s/it]
  1%|          | 6251/569592 [5:19:10<518:25:11,  3.31s/it]
                                                           

  1%|          | 6251/569592 [5:19:10<518:25:11,  3.31s/it]
  1%|          | 6252/569592 [5:19:11<406:30:51,  2.60s/it]
                                                           

  1%|          | 6252/569592 [5:19:11<406:30:51,  2.60s/it]
  1%|          | 6253/569592 [5:19:18<617:58:39,  3.95s/it]
                                                           

  1%|          | 6253/569592 [5:19:18<617:58:39,  3.95s/it]
  1%|          | 6254/569592 [5:19:22<589:38:48,  3.77s/it]
                                                           

  1%|          | 6254/569592 [5:19:22<589:38:48,  3.77s/it]
  1%|          | 6255/569592 [5:19:25<552:01:13,  3.53s/it]
                                                           

  1%|          | 6255/569592 [5:19:25<552:01:13,  3.53s/it]
  1%|          | 6256/569592 [5:19:29<563:02:13,  3.60s/it]
                                                           

  1%|          | 6256/569592 [5:19:29<563:02:13,  3.60s/it]
  1%|          | 6257/569592 [5:19:33<607:24:07,  3.88s/it]
                                                           

  1%|          | 6257/569592 [5:19:33<607:24:07,  3.88s/it]
  1%|          | 6258/569592 [5:19:36<570:15:29,  3.64s/it]
                                                           

  1%|          | 6258/569592 [5:19:36<570:15:29,  3.64s/it]
  1%|          | 6259/569592 [5:19:40<584:18:07,  3.73s/it]
                                                           

  1%|          | 6259/569592 [5:19:40<584:18:07,  3.73s/it]
  1%|          | 6260/569592 [5:19:45<632:31:45,  4.04s/it]
                                                           

  1%|          | 6260/569592 [5:19:45<632:31:45,  4.04s/it]
  1%|          | 6261/569592 [5:19:48<604:39:46,  3.86s/it]
                                                           

  1%|          | 6261/569592 [5:19:48<604:39:46,  3.86s/it]
  1%|          | 6262/569592 [5:19:51<562:52:11,  3.60s/it]
                                                           

  1%|          | 6262/569592 [5:19:51<562:52:11,  3.60s/it]
  1%|          | 6263/569592 [5:19:56<624:02:10,  3.99s/it]
                                                           

  1%|          | 6263/569592 [5:19:56<624:02:10,  3.99s/it]
  1%|          | 6264/569592 [5:20:00<604:51:47,  3.87s/it]
                                                           

  1%|          | 6264/569592 [5:20:00<604:51:47,  3.87s/it]
  1%|          | 6265/569592 [5:20:03<591:22:45,  3.78s/it]
                                                           

  1%|          | 6265/569592 [5:20:03<591:22:45,  3.78s/it]
  1%|          | 6266/569592 [5:20:07<583:34:03,  3.73s/it]
                                                           

  1%|          | 62/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (89507757 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
66/569592 [5:20:07<583:34:03,  3.73s/it]
  1%|          | 6267/569592 [5:20:12<636:34:41,  4.07s/it]
                                                           

  1%|          | 6267/569592 [5:20:12<636:34:41,  4.07s/it]
  1%|          | 6268/569592 [5:20:15<583:05:54,  3.73s/it]
                                                           

  1%|          | 6268/569592 [5:20:15<583:05:54,  3.73s/it]
  1%|          | 6269/569592 [5:20:18<570:01:03,  3.64s/it]
                                                           

  1%|          | 6269/569592 [5:20:18<570:01:03,  3.64s/it]
  1%|          | 6270/569592 [5:20:21<541:33:50,  3.46s/it]
                                                           

  1%|          | 6270/569592 [5:20:21<541:33:50,  3.46s/it]
  1%|          | 6271/569592 [5:20:24<531:37:09,  3.40s/it]
                                                           

  1%|          | 6271/569592 [5:20:24<531:37:09,  3.40s/it]
  1%|          | 6272/569592 [5:20:28<532:28:20,  3.40s/it]
                                                           

  1%|          | 6272/569592 [5:20:28<532:28:20,  3.40s/it]
  1%|          | 6273/569592 [5:20:32<544:43:28,  3.48s/it]
                                                           

  1%|          | 6273/569592 [5:20:32<544:43:28,  3.48s/it]
  1%|          | 6274/569592 [5:20:35<557:15:54,  3.56s/it]
                                                           

  1%|          | 6274/569592 [5:20:35<557:15:54,  3.56s/it]
  1%|          | 6275/569592 [5:20:36<436:56:30,  2.79s/it]
                                                           

  1%|          | 6275/569592 [5:20:36<436:56:30,  2.79s/it]
  1%|          | 6276/569592 [5:20:40<475:47:33,  3.04s/it]
                                                           

  1%|          | 6276/569592 [5:20:40<475:47:33,  3.04s/it]
  1%|          | 6277/569592 [5:20:44<505:17:50,  3.23s/it]
                                                           

  1%|          | 6277/569592 [5:20:44<505:17:50,  3.23s/it]
  1%|          |/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 6278/569592 [5:20:47<508:56:07,  3.25s/it]
                                                           

  1%|          | 6278/569592 [5:20:47<508:56:07,  3.25s/it]
  1%|          | 6279/569592 [5:20:50<510:46:50,  3.26s/it]
                                                           

  1%|          | 6279/569592 [5:20:50<510:46:50,  3.26s/it]
  1%|          | 6280/569592 [5:20:54<514:21:22,  3.29s/it]
                                                           

  1%|          | 6280/569592 [5:20:54<514:21:22,  3.29s/it]
  1%|          | 6281/569592 [5:20:57<517:28:28,  3.31s/it]
                                                           

  1%|          | 6281/569592 [5:20:57<517:28:28,  3.31s/it]
  1%|          | 6282/569592 [5:21:00<516:00:17,  3.30s/it]
                                                           

  1%|          | 6282/569592 [5:21:00<516:00:17,  3.30s/it]
  1%|          | 6283/569592 [5:21:05<582:37:03,  3.72s/it]
                                                           

  1%|          | 6283/569592 [5:21:05<582:37:03,  3.72s/it]
  1%|          | 6284/569592 [5:21:08<546:03:25,  3.49s/it]
                                                           

  1%|          | 6284/569592 [5:21:08<546:03:25,  3.49s/it]
  1%|          | 6285/569592 [5:21:09<426:08:58,  2.72s/it]
                                                           

  1%|          | 6285/569592 [5:21:09<426:08:58,  2.72s/it]
  1%|          | 6286/569592 [5:21:10<341:52:44,  2.18s/it]
                                                           

  1%|          | 6286/569592 [5:21:10<341:52:44,  2.18s/it]
  1%|          | 6287/569592 [5:21:13<409:18:10,  2.62s/it]
                                                           

  1%|          | 6287/569592 [5:21:13<409:18:10,  2.62s/it]
  1%|          | 6288/569592 [5:21:14<333:22:37,  2.13s/it]
                                                           

  1%|          | 6288/569592 [5:21:14<333:22:37,  2.13s/it]
  1%|          | 6289/569592 [5:21:15<277:54:29,  1.78s/it]
                                                           

  1%|          | 6289/569592 [5:21:15<277:54:29,  1.78s/it]
  1%|          | 6290/569592 [5:21:19<360:21:26,  2.30s/it]
                                                           

  1%|          | 6290/569592 [5:21:19<360:21:26,  2.30s/it]
  1%|          | 6291/569592 [5:21:22<418:22:56,  2.67s/it]
                                                           

  1%|          | 6291/569592 [5:21:22<418:22:56,  2.67s/it]
  1%|          | 6292/569592 [5:21:23<339:28:55,  2.17s/it]
                                                           

  1%|          | 6292/569592 [5:21:23<339:28:55,  2.17s/it]
  1%|          | 6293/569592 [5:21:24<281:34:55,  1.80s/it]
                                                           

  1%|          | 6293/569592 [5:21:24<281:34:55,  1.80s/it]
  1%|          | 6294/569592 [5:21:28<362:40:14,  2.32s/it]
                                                           

  1%|          | 6294/569592 [5:21:28<362:40:14,  2.32s/it]
  1%|          | 6295/569592 [5:21:29<299:52:45,  1.92s/it]
                                                           

  1%|          | 6295/569592 [5:21:29<299:52:45,  1.92s/it]
  1%|          | 6296/569592 [5:21:30<255:09:23,  1.63s/it]
                                                           

  1%|          | 6296/569592 [5:21:30<255:09:23,  1.63s/it]
  1%|          | 6297/569592 [5:21:32<279:32:48,  1.79s/it]
                                                           

  1%|          | 6297/569592 [5:21:32<279:32:48,  1.79s/it]
  1%|          | 6298/569592 [5:21:33<240:49:42,  1.54s/it]
                                                           

  1%|          | 6298/569592 [5:21:33<240:49:42,  1.54s/it]
  1%|          | 6299/569592 [5:21:34<213:30:19,  1.36s/it]
                                                           

  1%|          | 6299/569592 [5:21:34<213:30:19,  1.36s/it]
  1%|          | 6300/569592 [5:21:39<372:23:39,  2.38s/it]
                                                           

  1%|          | 6300/569592 [5:21:39<372:23:39,  2.38s/it]
  1%|          | 6301/569592 [5:21:42<412:58:02,  2.64s/it]
                                                           

  1%|          | 6301/569592 [5:21:42<412:58:02,  2.64s/it]
  1%|          | 6302/569592 [5:21:43<336:10:35,  2.15s/it]
                                                           

  1%|          | 6302/569592 [5:21:43<336:10:35,  2.15s/it]
  1%|          | 6303/569592 [5:21:44<314:13:05,  2.01s/it]
                                                           

  1%|          | 6303/569592 [5:21:44<314:13:05,  2.01s/it]
  1%|          | 6304/569592 [5:21:49<428:44:18,  2.74s/it]
                                                           

  1%|          | 6304/569592 [5:21:49<428:44:18,  2.74s/it]
  1%|          | 6305/569592 [5:21:52<461:16:21,  2.95s/it]
                                                           

  1%|          | 6305/569592 [5:21:52<461:16:21,  2.95s/it]
  1%|          | 6306/569592 [5:21:54<377:50:43,  2.41s/it]
                                                           

  1%|          | 6306/569592 [5:21:54<377:50:43,  2.41s/it]
  1%|          | 6307/569592 [5:21:55<329:33:43,  2.11s/it]
                                                           

  1%|          | 6307/569592 [5:21:55<329:33:43,  2.11s/it]
  1%|          | 6308/569592 [5:21:59<438:02:49,  2.80s/it]
                                                           

  1%|          | 6308/569592 [5:21:59<438:02:49,  2.80s/it]
  1%|          | 6309/569592 [5:22:02<451:25:19,  2.89s/it]
                                                           

  1%|          | 6309/569592 [5:22:02<451:25:19,  2.89s/it]
  1%|          | 6310/569592 [5:22:04<370:34:44,  2.37s/it]
                                                           

  1%|          | 6310/569592 [5:22:04<370:34:44,  2.37s/it]
  1%|          | 6311/569592 [5:22:05<309:47:26,  1.98s/it]
                                                           

  1%|          | 6311/569592 [5:22:05<309:47:26,  1.98s/it]
  1%|          | 6312/569592 [5:22:09<438:05:09,  2.80s/it]
                                                           

  1%|          | 6312/569592 [5:22:09<438:05:09,  2.80s/it]
  1%|          | 6313/569592 [5:22:13<458:48:01,  2.93s/it]
                                                           

  1%|          | 6313/569592 [5:22:13<458:48:01,  2.93s/it]
  1%|          | 6314/569592 [5:22:16<503:27:04,  3.22s/it]
                                                           

  1%|          | 6314/569592 [5:22:17<503:27:04,  3.22s/it]
  1%|          | 6315/569592 [5:22:21<553:37:44,  3.54s/it]
                                                           

  1%|          | 6315/569592 [5:22:21<553:37:44,  3.54s/it]
  1%|          | 6316/569592 [5:22:22<445:27:37,  2.85s/it]
                                                           

  1%|          | 6316/569592 [5:22:22<445:27:37,  2.85s/it]
  1%|          | 6317/569592 [5:22:23<356:46:04,  2.28s/it]
                                                           

  1%|          | 6317/569592 [5:22:23<356:46:04,  2.28s/it]
  1%|          | 6318/569592 [5:22:24<296:12:25,  1.89s/it]
                                                           

  1%|          | 6318/569592 [5:22:24<296:12:25,  1.89s/it]
  1%|          | 6319/569592 [5:22:25<258:16:23,  1.65s/it]
                                                           

  1%|          | 6319/569592 [5:22:25<258:16:23,  1.65s/it]
  1%|          | 6320/569592 [5:22:30<404:21:49,  2.58s/it]
                                                           

  1%|          | 6320/569592 [5:22:30<404:21:49,  2.58s/it]
  1%|          | 6321/569592 [5:22:35<510:56:50,  3.27s/it]
                                                           

  1%|          | 6321/569592 [5:22:35<510:56:50,  3.27s/it]
  1%|          | 6322/569592 [5:22:36<403:05:33,  2.58s/it]
                                                           

  1%|          | 6322/569592 [5:22:36<403:05:33,  2.58s/it]
  1%|          | 6323/569592 [5:22:39<448:52:05,  2.87s/it]
                                                           

  1%|          | 6323/569592 [5:22:39<448:52:05,  2.87s/it]
  1%|          | 6324/569592 [5:22:44<550:54:29,  3.52s/it]
                                                           

  1%|          | 6324/569592 [5:22:44<550:54:29,  3.52s/it]
  1%|          | 6325/569592 [5:22:45<431:27:21,  2.76s/it]
                                                           

  1%|          | 6325/569592 [5:22:45<431:27:21,  2.76s/it]
  1%|          | 6326/569592 [5:22:46<346:45:16,  2.22s/it]
                                                           

  1%|          | 6326/569592 [5:22:46<346:45:16,  2.22s/it]
  1%|          | 6327/569592 [5:22:47<289:04:22,  1.85s/it]
                                                           

  1%|          | 6327/569592 [5:22:47<289:04:22,  1.85s/it]
  1%|          | 6328/569592 [5:22:49<312:51:58,  2.00s/it]
                                                           

  1%|          | 6328/569592 [5:22:50<312:51:58,  2.00s/it]
  1%|          | 6329/569592 [5:22:54<415:01:22,  2.65s/it]
                                                           

  1%|          | 6329/569592 [5:22:54<415:01:22,  2.65s/it]
  1%|          | 6330/569592 [5:22:55<337:39:35,  2.16s/it]
                                                           

  1%|          | 6330/569592 [5:22:55<337:39:35,  2.16s/it]
  1%|          | 6331/569592 [5:22:58<389:40:45,  2.49s/it]
                                                           

  1%|          | 6331/569592 [5:22:58<389:40:45,  2.49s/it]
  1%|          | 6332/569592 [5:23:01<427:55:52,  2.74s/it]
                                                           

  1%|          | 6332/569592 [5:23:01<427:55:52,  2.74s/it]
  1%|          | 6333/569592 [5:23:03<374:46:15,  2.40s/it]
                                                           

  1%|          | 6333/569592 [5:23:03<374:46:15,  2.40s/it]
  1%|          | 6334/569592 [5:23:06<426:46:04,  2.73s/it]
                                                           

  1%|          | 6334/569592 [5:23:06<426:46:04,  2.73s/it]
  1%|          | 6335/569592 [5:23:10<483:17:40,  3.09s/it]
                                                           

  1%|          | 6335/569592 [5:23:10<483:17:40,  3.09s/it]
  1%|          | 6336/569592 [5:23:14<500:29:38,  3.20s/it]
                                                           

  1%|          | 6336/569592 [5:23:14<500:29:38,  3.20s/it]
  1%|          | 6337/569592 [5:23:15<400:33:19,  2.56s/it]
                                                           

  1%|          | 6337/569592 [5:23:15<400:33:19,  2.56s/it]
  1%|          | 6338/569592 [5:23:18<444:17:28,  2.84s/it]
                                                           

  1%|          | 6338/569592 [5:23:18<444:17:28,  2.84s/it]
  1%|          | 6339/569592 [5:23:19<360:38:44,  2.31s/it]
                                                           

  1%|          | 6339/569592 [5:23:19<360:38:44,  2.31s/it]
  1%|          | 6340/569592 [5:23:21<310:48:21,  1.99s/it]
                                                           

  1%|          | 6340/569592 [5:23:21<310:48:21,  1.99s/it]
  1%|          | 6341/569592 [5:23:24<379:52:08,  2.43s/it]
                                                           

  1%|          | 6341/569592 [5:23:24<379:52:08,  2.43s/it]
  1%|          | 6342/569592 [5:23:25<311:11:38,  1.99s/it]
                                                           

  1%|          | 6342/569592 [5:23:25<311:11:38,  1.99s/it]
  1%|          | 6343/569592 [5:23:28<380:16:53,  2.43s/it]
                                                           

  1%|          | 6343/569592 [5:23:28<380:16:53,  2.43s/it]
  1%|          | 6344/569592 [5:23:33<477:44:42,  3.05s/it]
                                                           

  1%|          | 6344/569592 [5:23:33<477:44:42,  3.05s/it]
  1%|          | 6345/569592 [5:23:34<393:48:14,  2.52s/it]
                                                           

  1%|          | 6345/569592 [5:23:34<393:48:14,  2.52s/it]
  1%|          | 6346/569592 [5:23:35<320:33:36,  2.05s/it]
                                                           

  1%|          | 6346/569592 [5:23:35<320:33:36,  2.05s/it]
  1%|          | 6347/569592 [5:23:39<396:57:12,  2.54s/it]
                                                           

  1%|          | 6347/569592 [5:23:39<396:57:12,  2.54s/it]
  1%|          | 6348/569592 [5:23:41<399:49:29,  2.56s/it]
                                                           

  1%|          | 6348/569592 [5:23:42<399:49:29,  2.56s/it]
  1%|          | 6349/569592 [5:23:46<506:29:29,  3.24s/it]
                                                           

  1%|          | 6349/569592 [5:23:46<506:29:29,  3.24s/it]
  1%|          | 6350/569592 [5:23:47<406:37:25,  2.60s/it]
                                                           

  1%|          | 6350/569592 [5:23:47<406:37:25,  2.60s/it]
  1%|          | 6351/569592 [5:23:51<460:31:15,  2.94s/it]
                                                           

  1%|          | 6351/569592 [5:23:51<460:31:15,  2.94s/it]
  1%|          | 6352/569592 [5:23:56<526:29:28,  3.37s/it]
                                                           

  1%|          | 6352/569592 [5:23:56<526:29:28,  3.37s/it]
  1%|          | 6353/569592 [5:23:56<411:18:33,  2.63s/it]
                                                           

  1%|          | 6353/569592 [5:23:56<411:18:33,  2.63s/it]
  1%|          | 6354/569592 [5:24:00<465:44:22,  2.98s/it]
                                                           

  1%|          | 6354/569592 [5:24:00<465:44:22,  2.98s/it]
  1%|          | 6355/569592 [5:24:04<509:50:20,  3.26s/it]
                                                           

  1%|          | 6355/569592 [5:24:04<509:50:20,  3.26s/it]
  1%|          | 6356/569592 [5:24:07<512:10:23,  3.27s/it]
                                                           

  1%|          | 6356/569592 [5:24:07<512:10:23,  3.27s/it]
  1%|          | 6357/569592 [5:24:12<550:53:16,  3.52s/it]
                                                           

  1%|          | 6357/569592 [5:24:12<550:53:16,  3.52s/it]
  1%|          | 6358/569592 [5:24:15<543:53:58,  3.48s/it]
                                                           

  1%|          | 6358/569592 [5:24:15<543:53:58,  3.48s/it]
  1%|          | 6359/569592 [5:24:18<529:48:06,  3.39s/it]
                                                           

  1%|          | 6359/569592 [5:24:18<529:48:06,  3.39s/it]
  1%|          | 6360/569592 [5:24:22<539:28:18,  3.45s/it]
                                                           

  1%|          | 6360/569592 [5:24:22<539:28:18,  3.45s/it]
  1%|          | 6361/569592 [5:24:25<556:00:35,  3.55s/it]
                                                           

  1%|          | 6361/569592 [5:24:25<556:00:35,  3.55s/it]
  1%|          | 6362/569592 [5:24:29<549:11:03,  3.51s/it]
                                                           

  1%|          | 6362/569592 [5:24:29<549:11:03,  3.51s/it]
  1%|          | 6363/569592 [5:24:32<535:26:01,  3.42s/it]
                                                           

  1%|          | 6363/569592 [5:24:32<535:26:01,  3.42s/it]
  1%|          | 6364/569592 [5:24:35<522:46:04,  3.34s/it]
                                                           

  1%|          | 6364/569592 [5:24:35<522:46:04,  3.34s/it]
  1%|          | 6365/569592 [5:24:39<557:33:55,  3.56s/it]
                                                           

  1%|          | 6365/569592 [5:24:39<557:33:55,  3.56s/it]
  1%|          | 6366/569592 [5:24:43<581:30:25,  3.72s/it]
                                                           

  1%|          | 6366/569592 [5:24:43<581:30:25,  3.72s/it]
  1%|          | 6367/569592 [5:24:47<585:22:42,  3.74s/it]
                                                           

  1%|          | 6367/569592 [5:24:47<585:22:42,  3.74s/it]
  1%|          | 6368/569592 [5:24:48<451:18:36,  2.88s/it]
                                                           

  1%|          | 6368/569592 [5:24:48<451:18:36,  2.88s/it]
  1%|          | 6369/569592 [5:24:52<501:47:45,  3.21s/it]
                                                           

  1%|          | 6369/569592 [5:24:52<501:47:45,  3.21s/it]
  1%|          | 6370/569592 [5:24:56<548:14:17,  3.50s/it]
                                                           

  1%|          | 6370/569592 [5:24:56<548:14:17,  3.50s/it]
  1%|          | 6371/569592 [5:24:59<523:48:03,  3.35s/it]
                                                           

  1%|          | 6371/569592 [5:24:59<523:48:03,  3.35s/it]
  1%|          | 6372/569592 [5:25:03<528:16:42,  3.38s/it]
                                                           

  1%|          | 6372/569592 [5:25:03<528:16:42,  3.38s/it]
  1%|          | 6373/569592 [5:25:04<411:47:51,  2.63s/it]
                                                           

  1%|          | 6373/569592 [5:25:04<411:47:51,  2.63s/it]
  1%|          | 6374/569592 [5:25:07<438:56:19,  2.81s/it]
                                                           

  1%|          | 6374/569592 [5:25:07<438:56:19,  2.81s/it]
  1%|          | 6375/569592 [5:25:10<469:41:41,  3.00s/it]
                                                           

  1%|          | 6375/569592 [5:25:10<469:41:41,  3.00s/it]
  1%|          | 6376/569592 [5:25:15<572:13:57,  3.66s/it]
                                                           

  1%|          | 6376/569592 [5:25:15<572:13:57,  3.66s/it]
  1%|          | 6377/569592 [5:25:18<544:08:38,  3.48s/it]
                                                           

  1%|          | 6377/569592 [5:25:19<544:08:38,  3.48s/it]
  1%|          | 6378/569592 [5:25:19<422:28:40,  2.70s/it]
                                                           

  1%|          | 6378/569592 [5:25:19<422:28:40,  2.70s/it]
  1%|          | 6379/569592 [5:25:23<451:02:39,  2.88s/it]
                                                           

  1%|          | 6379/569592 [5:25:23<451:02:39,  2.88s/it]
  1%|          | 6380/569592 [5:25:29<595:11:47,  3.80s/it]
                                                           

  1%|          | 6380/569592 [5:25:29<595:11:47,  3.80s/it]
  1%|          | 6381/569592 [5:25:32<562:55:54,  3.60s/it]
                                                           

  1%|          | 6381/569592 [5:25:32<562:55:54,  3.60s/it]
  1%|          | 6382/569592 [5:25:36<611:05:20,  3.91s/it]
                                                           

  1%|          | 6382/569592 [5:25:36<611:05:20,  3.91s/it]
  1%|          | 6383/569592 [5:25:40<574:29:09,  3.67s/it]
                                                           

  1%|          | 6383/569592 [5:25:40<574:29:09,  3.67s/it]
  1%|          | 6384/569592 [5:25:43<554:00:47,  3.54s/it]
                                                           

  1%|          | 6384/569592 [5:25:43<554:00:47,  3.54s/it]
  1%|          | 6385/569592 [5:25:44<430:01:45,  2.75s/it]
                                                           

  1%|          | 6385/569592 [5:25:44<430:01:45,  2.75s/it]
  1%|          | 6386/569592 [5:25:49<530:58:16,  3.39s/it]
                                                           

  1%|          | 6386/569592 [5:25:49<530:58:16,  3.39s/it]
  1%|          | 6387/569592 [5:25:52<529:26:10,  3.38s/it]
                                                           

  1%|          | 6387/569592 [5:25:52<529:26:10,  3.38s/it]
  1%|          | 6388/569592 [5:25:56<559:25:23,  3.58s/it]
                                                           

  1%|          | 6388/569592 [5:25:56<559:25:23,  3.58s/it]
  1%|          | 6389/569592 [5:25:59<538:59:43,  3.45s/it]
                                                           

  1%|          | 6389/569592 [5:25:59<538:59:43,  3.45s/it]
  1%|          | 6390/569592 [5:26:03<555:34:01,  3.55s/it]
                                                           

  1%|          | 6390/569592 [5:26:03<555:34:01,  3.55s/it]
  1%|          | 6391/569592 [5:26:07<562:36:07,  3.60s/it]
                                                           

  1%|          | 6391/569592 [5:26:07<562:36:07,  3.60s/it]
  1%|          | 6392/569592 [5:26:10<548:15:22,  3.50s/it]
                                                           

  1%|          | 6392/569592 [5:26:10<548:15:22,  3.50s/it]
  1%|          | 6393/569592 [5:26:13<543:14:33,  3.47s/it]
                                                           

  1%|          | 6393/569592 [5:26:13<543:14:33,  3.47s/it]
  1%|          | 6394/569592 [5:26:17<538:07:45,  3.44s/it]
                                                           

  1%|          | 6394/569592 [5:26:17<538:07:45,  3.44s/it]
  1%|          | 6395/569592 [5:26:20<516:19:59,  3.30s/it]
                                                           

  1%|          | 6395/569592 [5:26:20<516:19:59,  3.30s/it]
  1%|          | 6396/569592 [5:26:23<535:13:54,  3.42s/it]
                                                           

  1%|          | 6396/569592 [5:26:23<535:13:54,  3.42s/it]
  1%|          | 6397/569592 [5:26:27<527:35:15,  3.37s/it]
                                                           

  1%|          | 6397/569592 [5:26:27<527:35:15,  3.37s/it]
  1%|          | 6398/569592 [5:26:30<512:30:57,  3.28s/it]
                                                           

  1%|          | 6398/569592 [5:26:30<512:30:57,  3.28s/it]
  1%|          | 6399/569592 [5:26:33<517:49:47,  3.31s/it]
                                                           

  1%|          | 6399/569592 [5:26:33<517:49:47,  3.31s/it]
  1%|          | 6400/569592 [5:26:38<596:14:40,  3.81s/it]
                                                           

  1%|          | 6400/569592 [5:26:38<596:14:40,  3.81s/it]
  1%|          | 6401/569592 [5:26:39<460:42:36,  2.94s/it]
                                                           

  1%|          | 6401/569592 [5:26:39<460:42:36,  2.94s/it]
  1%|          | 6402/569592 [5:26:40<366:09:21,  2.34s/it]
                                                           

  1%|          | 6402/569592 [5:26:40<366:09:21,  2.34s/it]
  1%|          | 6403/569592 [5:26:43<412:28:40,  2.64s/it]
                                                           

  1%|          | 6403/569592 [5:26:43<412:28:40,  2.64s/it]
  1%|          | 6404/569592 [5:26:47<459:13:39,  2.94s/it]
                                                           

  1%|          | 6404/569592 [5:26:47<459:13:39,  2.94s/it]
  1%|          | 6405/569592 [5:26:50<471:19:43,  3.01s/it]
                                                           

  1%|          | 6405/569592 [5:26:50<471:19:43,  3.01s/it]
  1%|          | 6406/569592 [5:26:53<477:24:17,  3.05s/it]
                                                           

  1%|          | 6406/569592 [5:26:53<477:24:17,  3.05s/it]
  1%|          | 6407/569592 [5:26:54<376:27:42,  2.41s/it]
                                                           

  1%|          | 6407/569592 [5:26:54<376:27:42,  2.41s/it]
  1%|          | 6408/569592 [5:26:55<307:29:28,  1.97s/it]
                                                           

  1%|          | 6408/569592 [5:26:55<307:29:28,  1.97s/it]
  1%|          | 6409/569592 [5:26:56<259:34:44,  1.66s/it]
                                                           

  1%|          | 6409/569592 [5:26:56<259:34:44,  1.66s/it]
  1%|          | 6410/569592 [5:26:57<226:38:22,  1.45s/it]
                                                           

  1%|          | 6410/569592 [5:26:57<226:38:22,  1.45s/it]
  1%|          | 6411/569592 [5:26:58<203:09:56,  1.30s/it]
                                                           

  1%|          | 6411/569592 [5:26:58<203:09:56,  1.30s/it]
  1%|          | 6412/569592 [5:26:59<185:28:41,  1.19s/it]
                                                           

  1%|          | 6412/569592 [5:26:59<185:28:41,  1.19s/it]
  1%|          | 6413/569592 [5:27:01<218:40:59,  1.40s/it]
                                                           

  1%|          | 6413/569592 [5:27:01<218:40:59,  1.40s/it]
  1%|          | 6414/569592 [5:27:03<270:08:11,  1.73s/it]
                                                           

  1%|          | 6414/569592 [5:27:03<270:08:11,  1.73s/it]
  1%|          | 6415/569592 [5:27:07<348:02:26,  2.22s/it]
                                                           

  1%|          | 6415/569592 [5:27:07<348:02:26,  2.22s/it]
  1%|          | 6416/569592 [5:27:08<310:57:02,  1.99s/it]
                                                           

  1%|          | 6416/569592 [5:27:08<310:57:02,  1.99s/it]
  1%|          | 6417/569592 [5:27:11<373:15:59,  2.39s/it]
                                                           

  1%|          | 6417/569592 [5:27:11<373:15:59,  2.39s/it]
  1%|          | 6418/569592 [5:27:13<356:23:55,  2.28s/it]
                                                           

  1%|          | 6418/569592 [5:27:13<356:23:55,  2.28s/it]
  1%|          | 6419/569592 [5:27:17<431:49:58,  2.76s/it]
                                                           

  1%|          | 6419/569592 [5:27:17<431:49:58,  2.76s/it]
  1%|          | 6420/569592 [5:27:18<352:01:49,  2.25s/it]
                                                           

  1%|          | 6420/569592 [5:27:18<352:01:49,  2.25s/it]
  1%|          | 6421/569592 [5:27:21<357:11:01,  2.28s/it]
                                                           

  1%|          | 6421/569592 [5:27:21<357:11:01,  2.28s/it]
  1%|          | 6422/569592 [5:27:23<384:56:14,  2.46s/it]
                                                           

  1%|          | 6422/569592 [5:27:23<384:56:14,  2.46s/it]
  1%|          | 6423/569592 [5:27:30<578:19:22,  3.70s/it]
                                                           

  1%|          | 6423/569592 [5:27:30<578:19:22,  3.70s/it]
  1%|          | 6424/569592 [5:27:31<452:32:26,  2.89s/it]
                                                           

  1%|          | 6424/569592 [5:27:31<452:32:26,  2.89s/it]
  1%|          | 6425/569592 [5:27:32<367:08:01,  2.35s/it]
                                                           

  1%|          | 6425/569592 [5:27:32<367:08:01,  2.35s/it]
  1%|          | 6426/569592 [5:27:36<428:59:14,  2.74s/it]
                                                           

  1%|          | 6426/569592 [5:27:36<428:59:14,  2.74s/it]
  1%|          | 6427/569592 [5:27:40<484:17:37,  3.10s/it]
                                                           

  1%|          | 6427/569592 [5:27:40<484:17:37,  3.10s/it]
  1%|          | 6428/569592 [5:27:43<500:22:24,  3.20s/it]
                                                           

  1%|          | 6428/569592 [5:27:43<500:22:24,  3.20s/it]
  1%|          | 6429/569592 [5:27:44<396:14:27,  2.53s/it]
                                                           

  1%|          | 6429/569592 [5:27:44<396:14:27,  2.53s/it]
  1%|          | 6430/569592 [5:27:45<324:11:33,  2.07s/it]
                                                           

  1%|          | 6430/569592 [5:27:45<324:11:33,  2.07s/it]
  1%|          | 6431/569592 [5:27:48<358:06:39,  2.29s/it]
                                                           

  1%|          | 6431/569592 [5:27:48<358:06:39,  2.29s/it]
  1%|          | 6432/569592 [5:27:52<428:07:01,  2.74s/it]
                                                           

  1%|          | 6432/569592 [5:27:52<428:07:01,  2.74s/it]
  1%|          | 6433/569592 [5:27:53<375:00:26,  2.40s/it]
                                                           

  1%|          | 6433/569592 [5:27:53<375:00:26,  2.40s/it]
  1%|          | 6434/569592 [5:27:55<356:29:21,  2.28s/it]
                                                           

  1%|          | 6434/569592 [5:27:55<356:29:21,  2.28s/it]
  1%|          | 6435/569592 [5:28:00<457:32:39,  2.92s/it]
                                                           

  1%|          | 6435/569592 [5:28:00<457:32:39,  2.92s/it]
  1%|          | 6436/569592 [5:28:05<559:16:49,  3.58s/it]
                                                           

  1%|          | 6436/569592 [5:28:05<559:16:49,  3.58s/it]
  1%|          | 6437/569592 [5:28:06<436:31:46,  2.79s/it]
                                                           

  1%|          | 6437/569592 [5:28:06<436:31:46,  2.79s/it]
  1%|          | 6438/569592 [5:28:09<472:18:28,  3.02s/it]
                                                           

  1%|          | 6438/569592 [5:28:09<472:18:28,  3.02s/it]
  1%|          | 6439/569592 [5:28:13<487:01:28,  3.11s/it]
                                                           

  1%|          | 6439/569592 [5:28:13<487:01:28,  3.11s/it]
  1%|          | 6440/569592 [5:28:14<388:32:29,  2.48s/it]
                                                           

  1%|          | 6440/569592 [5:28:14<388:32:29,  2.48s/it]
  1%|          | 6441/569592 [5:28:17<435:55:15,  2.79s/it]
                                                           

  1%|          | 6441/569592 [5:28:17<435:55:15,  2.79s/it]
  1%|          | 6442/569592 [5:28:18<358:38:16,  2.29s/it]
                                                           

  1%|          | 6442/569592 [5:28:18<358:38:16,  2.29s/it]
  1%|          | 6443/569592 [5:28:19<296:21:20,  1.89s/it]
                                                           

  1%|          | 6443/569592 [5:28:19<296:21:20,  1.89s/it]
  1%|          | 6444/569592 [5:28:20<252:02:31,  1.61s/it]
                                                           

  1%|          | 6444/569592 [5:28:20<252:02:31,  1.61s/it]
  1%|          | 6445/569592 [5:28:25<377:18:03,  2.41s/it]
                                                           

  1%|          | 6445/569592 [5:28:25<377:18:03,  2.41s/it]
  1%|          | 6446/569592 [5:28:26<345:10:42,  2.21s/it]
                                                           

  1%|          | 6446/569592 [5:28:26<345:10:42,  2.21s/it]
  1%|          | 6447/569592 [5:28:30<409:38:30,  2.62s/it]
                                                           

  1%|          | 6447/569592 [5:28:30<409:38:30,  2.62s/it]
  1%|          | 6448/569592 [5:28:34<466:54:00,  2.98s/it]
                                                           

  1%|          | 6448/569592 [5:28:34<466:54:00,  2.98s/it]
  1%|          | 6449/569592 [5:28:38<514:00:20,  3.29s/it]
                                                           

  1%|          | 6449/569592 [5:28:38<514:00:20,  3.29s/it]
  1%|          | 6450/569592 [5:28:39<410:34:03,  2.62s/it]
                                                           

  1%|          | 6450/569592 [5:28:39<410:34:03,  2.62s/it]
  1%|          | 6451/569592 [5:28:40<331:33:19,  2.12s/it]
                                                           

  1%|          | 6451/569592 [5:28:40<331:33:19,  2.12s/it]
  1%|          | 6452/569592 [5:28:41<276:45:58,  1.77s/it]
                                                           

  1%|          | 6452/569592 [5:28:41<276:45:58,  1.77s/it]
  1%|          | 6453/569592 [5:28:45<410:57:51,  2.63s/it]
                                                           

  1%|          | 6453/569592 [5:28:45<410:57:51,  2.63s/it]
  1%|          | 6454/569592 [5:28:48<413:01:01,  2.64s/it]
                                                           

  1%|          | 6454/569592 [5:28:48<413:01:01,  2.64s/it]
  1%|          | 6455/569592 [5:28:50<379:50:30,  2.43s/it]
                                                           

  1%|          | 6455/569592 [5:28:50<379:50:30,  2.43s/it]
  1%|          | 6456/569592 [5:28:54<462:17:27,  2.96s/it]
                                                           

  1%|          | 6456/569592 [5:28:54<462:17:27,  2.96s/it]
  1%|          | 6457/569592 [5:28:58<499:53:03,  3.20s/it]
                                                           

  1%|          | 6457/569592 [5:28:58<499:53:03,  3.20s/it]
  1%|          | 6458/569592 [5:28:59<393:43:47,  2.52s/it]
                                                           

  1%|          | 6458/569592 [5:28:59<393:43:47,  2.52s/it]
  1%|          | 6459/569592 [5:29:00<356:07:32,  2.28s/it]
                                                           

  1%|          | 6459/569592 [5:29:00<356:07:32,  2.28s/it]
  1%|          | 6460/569592 [5:29:02<330:21:04,  2.11s/it]
                                                           

  1%|          | 6460/569592 [5:29:02<330:21:04,  2.11s/it]
  1%|          | 6461/569592 [5:29:06<401:50:15,  2.57s/it]
                                                           

  1%|          | 6461/569592 [5:29:06<401:50:15,  2.57s/it]
  1%|          | 6462/569592 [5:29:10<457:54:54,  2.93s/it]
                                                           

  1%|          | 6462/569592 [5:29:10<457:54:54,  2.93s/it]
  1%|          | 6463/569592 [5:29:11<366:05:37,  2.34s/it]
                                                           

  1%|          | 6463/569592 [5:29:11<366:05:37,  2.34s/it]
  1%|          | 6464/569592 [5:29:15<441:03:35,  2.82s/it]
                                                           

  1%|          | 6464/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/569592 [5:29:15<441:03:35,  2.82s/it]
  1%|          | 6465/569592 [5:29:19<499:37:54,  3.19s/it]
                                                           

  1%|          | 6465/569592 [5:29:19<499:37:54,  3.19s/it]
  1%|          | 6466/569592 [5:29:22<507:06:50,  3.24s/it]
                                                           

  1%|          | 6466/569592 [5:29:22<507:06:50,  3.24s/it]
  1%|          | 6467/569592 [5:29:25<510:46:48,  3.27s/it]
                                                           

  1%|          | 6467/569592 [5:29:25<510:46:48,  3.27s/it]
  1%|          | 6468/569592 [5:29:29<512:53:20,  3.28s/it]
                                                           

  1%|          | 6468/569592 [5:29:29<512:53:20,  3.28s/it]
  1%|          | 6469/569592 [5:29:33<586:05:34,  3.75s/it]
                                                           

  1%|          | 6469/569592 [5:29:33<586:05:34,  3.75s/it]
  1%|          | 6470/569592 [5:29:38<627:02:01,  4.01s/it]
                                                           

  1%|          | 6470/569592 [5:29:38<627:02:01,  4.01s/it]
  1%|          | 6471/569592 [5:29:41<580:57:47,  3.71s/it]
                                                           

  1%|          | 6471/569592 [5:29:41<580:57:47,  3.71s/it]
  1%|          | 6472/569592 [5:29:46<628:39:37,  4.02s/it]
                                                           

  1%|          | 6472/569592 [5:29:46<628:39:37,  4.02s/it]
  1%|          | 6473/569592 [5:29:50<645:43:55,  4.13s/it]
                                                           

  1%|          | 6473/569592 [5:29:50<645:43:55,  4.13s/it]
  1%|          | 6474/569592 [5:29:53<592:01:10,  3.78s/it]
                                                           

  1%|          | 6474/569592 [5:29:53<592:01:10,  3.78s/it]
  1%|          | 6475/569592 [5:29:58<636:55:30,  4.07s/it]
                                                           

  1%|          | 6475/569592 [5:29:58<636:55:30,  4.07s/it]
  1%|          | 6476/569592 [5:30:01<608:36:39,  3.89s/it]
                                                           

  1%|          | 6476/569592 [5:30:01<608:36:39,  3.89s/it]
  1%|          | 6477/569592 [5:30:04<566:27:01,  3.62s/it]
                                                           

  1%|          | 6477/569592 [5:30:04<566:27:01,  3.62s/it]
  1%|          | 6478/569592 [5:30:08<561:19:25,  3.59s/it]
                                                           

  1%|          | 6478/569592 [5:30:08<561:19:25,  3.59s/it]
  1%|          | 6479/569592 [5:30:12<595:38:29,  3.81s/it]
                                                           

  1%|          | 6479/569592 [5:30:12<595:38:29,  3.81s/it]
  1%|          | 6480/569592 [5:30:17<635:55:02,  4.07s/it]
                                                           

  1%|          | 6480/569592 [5:30:17<635:55:02,  4.07s/it]
  1%|          | 6481/569592 [5:30:20<587:44:55,  3.76s/it]
                                                           

  1%|          | 6481/569592 [5:30:20<587:44:55,  3.76s/it]
  1%|          | 6482/569592 [5:30:23<569:40:25,  3.64s/it]
                                                           

  1%|          | 6482/569592 [5:30:23<569:40:25,  3.64s/it]
  1%|          | 6483/569592 [5:30:27<558:02:32,  3.57s/it]
                                                           

  1%|          | 6483/569592 [5:30:27<558:02:32,  3.57s/it]
  1%|          | 6484/569592 [5:30:30<567:22:55,  3.63s/it]
                                                           

  1%|          | 6484/569592 [5:30:30<567:22:55,  3.63s/it]
  1%|          | 6485/569592 [5:30:33<541:08:31,  3.46s/it]
                                                           

  1%|          | 6485/569592 [5:30:33<541:08:31,  3.46s/it]
  1%|          | 6486/569592 [5:30:34<422:40:03,  2.70s/it]
                                                           

  1%|          | 6486/569592 [5:30:34<422:40:03,  2.70s/it]
  1%|          | 6487/569592 [5:30:38<451:13:56,  2.88s/it]
                                                           

  1%|          | 6487/569592 [5:30:38<451:13:56,  2.88s/it]
  1%|          | 6488/569592 [5:30:41<476:57:17,  3.05s/it]
                                                           

  1%|          | 6488/569592 [5:30:41<476:57:17,  3.05s/it]
  1%|          | 6489/569592 [5:30:45<492:48:55,  3.15s/it]
                                                           

  1%|          | 6489/569592 [5:30:45<492:48:55,  3.15s/it]
  1%|          | 6490/569592 [5:30:48<513:29:16,  3.28s/it]
                                                           

  1%|          | 6490/569592 [5:30:48<513:29:16,  3.28s/it]
  1%|          | 6491/569592 [5:30:49<403:31:58,  2.58s/it]
                                                           

  1%|          | 6491/569592 [5:30:49<403:31:58,  2.58s/it]
  1%|          | 6492/569592 [5:30:53<444:32:08,  2.84s/it]
                                                           

  1%|          | 6492/569592 [5:30:53<444:32:08,  2.84s/it]
  1%|          | 6493/569592 [5:30:56<471:53:09,  3.02s/it]
                                                           

  1%|          | 6493/569592 [5:30:56<471:53:09,  3.02s/it]
  1%|          | 6494/569592 [5:31:00<521:08:31,  3.33s/it]
                                                           

  1%|          | 6494/569592 [5:31:00<521:08:31,  3.33s/it]
  1%|          | 6495/569592 [5:31:03<520:05:35,  3.33s/it]
                                                           

  1%|          | 6495/569592 [5:31:03<520:05:35,  3.33s/it]
  1%|          | 6496/569592 [5:31:04<407:37:41,  2.61s/it]
                                                           

  1%|          | 6496/569592 [5:31:04<407:37:41,  2.61s/it]
  1%|          | 6497/569592 [5:31:08<465:43:45,  2.98s/it]
                                                           

  1%|          | 6497/569592 [5:31:08<465:43:45,  2.98s/it]
  1%|          | 6498/569592 [5:31:13<552:02:59,  3.53s/it]
                                                           

  1%|          | 6498/569592 [5:31:13<552:02:59,  3.53s/it]
  1%|          | 6499/569592 [5:31:16<534:21:52,  3.42s/it]
                                                           

  1%|          | 6499/569592 [5:31:16<534:21:52,  3.42s/it]
  1%|          | 6500/569592 [5:31:20<573:56:11,  3.67s/it]
                                                           

  1%|          | 6500/569592 [5:31:20<573:56:11,  3.67s/it]
  1%|          | 6501/569592 [5:31:23<546:55:47,  3.50s/it]
                                                           

  1%|          | 6501/569592 [5:31:23<546:55:47,  3.50s/it]
  1%|          | 6502/569592 [5:31:27<551:44:56,  3.53s/it]
                                                           

  1%|          | 6502/569592 [5:31:27<551:44:56,  3.53s/it]
  1%|          | 6503/569592 [5:31:32<613:14:20,  3.92s/it]
                                                           

  1%|          | 6503/569592 [5:31:32<613:14:20,  3.92s/it]
  1%|          | 6504/569592 [5:31:35<592:17:08,  3.79s/it]
                                                           

  1%|          | 6504/569592 [5:31:35<592:17:08,  3.79s/it]
  1%|          | 6505/569592 [5:31:40<610:52:58,  3.91s/it]
                                                           

  1%|          | 6505/569592 [5:31:40<610:52:58,  3.91s/it]
  1%|          | 6506/569592 [5:31:40<470:04:56,  3.01s/it]
                                                           

  1%|          | 6506/569592 [5:31:40<470:04:56,  3.01s/it]
  1%|          | 6507/569592 [5:31:44<475:25:38,  3.04s/it]
                                                           

  1%|          | 6507/569592 [5:31:44<475:25:38,  3.04s/it]
  1%|          | 6508/569592 [5:31:44<376:09:58,  2.40s/it]
                                                           

  1%|          | 6508/569592 [5:31:44<376:09:58,  2.40s/it]
  1%|          | 6509/569592 [5:31:48<438:07:14,  2.80s/it]
                                                           

  1%|          | 6509/569592 [5:31:48<438:07:14,  2.80s/it]
  1%|          | 6510/569592 [5:31:53<529:46:45,  3.39s/it]
                                                           

  1%|          | 6510/569592 [5:31:53<529:46:45,  3.39s/it]
  1%|          | 6511/569592 [5:31:56<527:39:04,  3.37s/it]
                                                           

  1%|          | 6511/569592 [5:31:56<527:39:04,  3.37s/it]
  1%|          | 6512/569592 [5:31:57<411:35:29,  2.63s/it]
                                                           

  1%|          | 6512/569592 [5:31:57<411:35:29,  2.63s/it]
  1%|          | 6513/569592 [5:32:02<516:06:46,  3.30s/it]
                                                           

  1%|          | 6513/569592 [5:32:02<516:06:46,  3.30s/it]
  1%|          | 6514/569592 [5:32:05<516:10:15,  3.30s/it]
                                                           

  1%|          | 6514/569592 [5:32:05<516:10:15,  3.30s/it]
  1%|          | 6515/569592 [5:32:06<405:11:54,  2.59s/it]
                                                           

  1%|          | 6515/569592 [5:32:06<405:11:54,  2.59s/it]
  1%|          | 6516/569592 [5:32:09<428:44:43,  2.74s/it]
                                                           

  1%|          | 6516/569592 [5:32:09<428:44:43,  2.74s/it]
  1%|          | 6517/569592 [5:32:13<485:27:04,  3.10s/it]
                                                           

  1%|          | 6517/569592 [5:32:13<485:27:04,  3.10s/it]
  1%|          | 6518/569592 [5:32:16<486:51:44,  3.11s/it]
                                                           

  1%|          | 6518/569592 [5:32:16<486:51:44,  3.11s/it]
  1%|          | 6519/569592 [5:32:20<487:45:18,  3.12s/it]
                                                           

  1%|          | 6519/569592 [5:32:20<487:45:18,  3.12s/it]
  1%|          | 6520/569592 [5:32:23<503:28:22,  3.22s/it]
                                                           

  1%|          | 6520/569592 [5:32:23<503:28:22,  3.22s/it]
  1%|          | 6521/569592 [5:32:27<518:21:44,  3.31s/it]
                                                           

  1%|          | 6521/569592 [5:32:27<518:21:44,  3.31s/it]
  1%|          | 6522/569592 [5:32:28<410:49:10,  2.63s/it]
                                                           

  1%|          | 6522/569592 [5:32:28<410:49:10,  2.63s/it]
  1%|          | 6523/569592 [5:32:29<331:16:56,  2.12s/it]
                                                           

  1%|          | 6523/569592 [5:32:29<331:16:56,  2.12s/it]
  1%|          | 6524/569592 [5:32:30<277:25:54,  1.77s/it]
                                                           

  1%|          | 6524/569592 [5:32:30<277:25:54,  1.77s/it]
  1%|          | 6525/569592 [5:32:30<238:47:04,  1.53s/it]
                                                           

  1%|          | 6525/569592 [5:32:30<238:47:04,  1.53s/it]
  1%|          | 6526/569592 [5:32:31<212:30:48,  1.36s/it]
                                                           

  1%|          | 6526/569592 [5:32:31<212:30:48,  1.36s/it]
  1%|          | 6527/569592 [5:32:32<192:57:46,  1.23s/it]
                                                           

  1%|          | 6527/569592 [5:32:32<192:57:46,  1.23s/it]
  1%|          | 6528/569592 [5:32:33<179:34:27,  1.15s/it]
                                                           

  1%|          | 6528/569592 [5:32:33<179:34:27,  1.15s/it]
  1%|          | 6529/569592 [5:32:36<248:13:52,  1.59s/it]
                                                           

  1%|          | 6529/569592 [5:32:36<248:13:52,  1.59s/it]
  1%|          | 6530/569592 [5:32:41<403:51:44,  2.58s/it]
                                                           

  1%|          | 6530/569592 [5:32:41<403:51:44,  2.58s/it]
  1%|          | 6531/569592 [5:32:42<334:55:59,  2.14s/it]
                                                           

  1%|          | 6531/569592 [5:32:42<334:55:59,  2.14s/it]
  1%|          | 6532/569592 [5:32:43<280:24:49,  1.79s/it]
                                                           

  1%|          | 6532/569592 [5:32:43<280:24:49,  1.79s/it]
  1%|          | 6533/569592 [5:32:46<328:22:06,  2.10s/it]
                                                           

  1%|          | 6533/569592 [5:32:46<328:22:06,  2.10s/it]
  1%|          | 6534/569592 [5:32:50<434:22:29,  2.78s/it]
                                                           

  1%|          | 6534/569592 [5:32:50<434:22:29,  2.78s/it]
  1%|          | 6535/569592 [5:32:51<349:24:26,  2.23s/it]
                                                           

  1%|          | 6535/569592 [5:32:51<349:24:26,  2.23s/it]
  1%|          | 6536/569592 [5:32:52<294:46:51,  1.88s/it]
                                                           

  1%|          | 6536/569592 [5:32:52<294:46:51,  1.88s/it]
  1%|          | 6537/569592 [5:32:57<437:20:08,  2.80s/it]
                                                           

  1%|          | 6537/569592 [5:32:57<437:20:08,  2.80s/it]
  1%|          | 6538/569592 [5:33:01<470:00:56,  3.01s/it]
                                                           

  1%|          | 6538/569592 [5:33:01<470:00:56,  3.01s/it]
  1%|          | 6539/569592 [5:33:02<378:20:12,  2.42s/it]
                                                           

  1%|          | 6539/569592 [5:33:02<378:20:12,  2.42s/it]
  1%|          | 6540/569592 [5:33:06<456:45:59,  2.92s/it]
                                                           

  1%|          | 6540/569592 [5:33:06<456:45:59,  2.92s/it]
  1%|          | 6541/569592 [5:33:09<483:22:52,  3.09s/it]
                                                           

  1%|          | 6541/569592 [5:33:09<483:22:52,  3.09s/it]
  1%|          | 6542/569592 [5:33:11<406:21:21,  2.60s/it]
                                                           

  1%|          | 6542/569592 [5:33:11<406:21:21,  2.60s/it]
  1%|          | 6543/569592 [5:33:12<333:48:53,  2.13s/it]
                                                           

  1%|          | 6543/569592 [5:33:12<333:48:53,  2.13s/it]
  1%|          | 6544/569592 [5:33:15<408:08:05,  2.61s/it]
                                                           

  1%|          | 6544/569592 [5:33:15<408:08:05,  2.61s/it]
  1%|          | 6545/569592 [5:33:18<407:51:41,  2.61s/it]
                                                           

  1%|          | 6545/569592 [5:33:18<407:51:41,  2.61s/it]
  1%|          | 6546/569592 [5:33:21<442:51:41,  2.83s/it]
                                                           

  1%|          | 6546/569592 [5:33:21<442:51:41,  2.83s/it]
  1%|          | 6547/569592 [5:33:22<355:25:22,  2.27s/it]
                                                           

  1%|          | 6547/569592 [5:33:22<355:25:22,  2.27s/it]
  1%|          | 6548/569592 [5:33:23<293:43:05,  1.88s/it]
                                                           

  1%|          | 6548/569592 [5:33:23<293:43:05,  1.88s/it]
  1%|          | 6549/569592 [5:33:30<516:09:11,  3.30s/it]
                                                           

  1%|          | 6549/569592 [5:33:30<516:09:11,  3.30s/it]
  1%|          | 6550/569592 [5:33:34<534:07:26,  3.42s/it]
                                                           

  1%|          | 6550/569592 [5:33:34<534:07:26,  3.42s/it]
  1%|          | 6551/569592 [5:33:35<418:19:00,  2.67s/it]
                                                           

  1%|          | 6551/569592 [5:33:35<418:19:00,  2.67s/it]
  1%|          | 6552/569592 [5:33:36<339:41:09,  2.17s/it]
                                                           

  1%|          | 6552/569592 [5:33:36<339:41:09,  2.17s/it]
  1%|          | 6553/569592 [5:33:40<469:33:29,  3.00s/it]
                                                           

  1%|          | 6553/569592 [5:33:40<469:33:29,  3.00s/it]
  1%|          | 6554/569592 [5:33:41<375:57:22,  2.40s/it]
                                                           

  1%|          | 6554/569592 [5:33:42<375:57:22,  2.40s/it]
  1%|          | 6555/569592 [5:33:43<334:52:24,  2.14s/it]
                                                           

  1%|          | 6555/569592 [5:33:43<334:52:24,  2.14s/it]
  1%|          | 6556/569592 [5:33:47<401:43:50,  2.57s/it]
                                                           

  1%|          | 6556/569592 [5:33:47<401:43:50,  2.57s/it]
  1%|          | 6557/569592 [5:33:51<500:29:44,  3.20s/it]
                                                           

  1%|          | 6557/569592 [5:33:51<500:29:44,  3.20s/it]
  1%|          | 6558/569592 [5:33:55<530:35:23,  3.39s/it]
                                                           

  1%|          | 6558/569592 [5:33:55<530:35:23,  3.39s/it]
  1%|          | 6559/569592 [5:33:59<555:03:21,  3.55s/it]
                                                           

  1%|          | 6559/569592 [5:33:59<555:03:21,  3.55s/it]
  1%|          | 6560/569592 [5:34:03<586:35:15,  3.75s/it]
                                                           

  1%|          | 6560/569592 [5:34:03<586:35:15,  3.75s/it]
  1%|          | 6561/569592 [5:34:06<553:17:59,  3.54s/it]
                                                           

  1%|          | 6561/569592 [5:34:06<553:17:59,  3.54s/it]
  1%|          | 6562/569592 [5:34:07<440:37:10,  2.82s/it]
                                                           

  1%|          | 6562/569592 [5:34:07<440:37:10,  2.82s/it]
  1%|          | 6563/569592 [5:34:08<357:31:02,  2.29s/it]
                                                           

  1%|          | 6563/569592 [5:34:08<357:31:02,  2.29s/it]
  1%|          | 6564/569592 [5:34:09<295:45:34,  1.89s/it]
                                                           

  1%|          | 6564/569592 [5:34:09<295:45:34,  1.89s/it]
  1%|          | 6565/569592 [5:34:14<402:54:14,  2.58s/it]
                                                           

  1%|          | 6565/569592 [5:34:14<402:54:14,  2.58s/it]
  1%|          | 6566/569592 [5:34:15<330:31:27,  2.11s/it]
                                                           

  1%|          | 6566/569592 [5:34:15<330:31:27,  2.11s/it]
  1%|          | 6567/569592 [5:34:20<484:09:49,  3.10s/it]
                                                           

  1%|          | 6567/569592 [5:34:20<484:09:49,  3.10s/it]
  1%|          | 6568/569592 [5:34:21<385:30:08,  2.46s/it]
                                                           

  1%|          | 6568/569592 [5:34:21<385:30:08,  2.46s/it]
  1%|          | 6569/569592 [5:34:23<340:06:03,  2.17s/it]
                                                           

  1%|          | 6569/569592 [5:34:23<340:06:03,  2.17s/it]
  1%|          | 6570/569592 [5:34:23<282:16:36,  1.80s/it]
                                                           

  1%|          | 6570/569592 [5:34:23<282:16:36,  1.80s/it]
  1%|          | 6571/569592 [5:34:25<246:59:07,  1.58s/it]
                                                           

  1%|          | 6571/569592 [5:34:25<246:59:07,  1.58s/it]
  1%|          | 6572/569592 [5:34:26<234:39:40,  1.50s/it]
                                                           

  1%|          | 6572/569592 [5:34:26<234:39:40,  1.50s/it]
  1%|          | 6573/569592 [5:34:32<463:43:19,  2.97s/it]
                                                           

  1%|          | 6573/569592 [5:34:32<463:43:19,  2.97s/it]
  1%|          | 6574/569592 [5:34:37<536:04:09,  3.43s/it]
                                                           

  1%|          | 6574/569592 [5:34:37<536:04:09,  3.43s/it]
  1%|          | 6575/569592 [5:34:40<534:18:56,  3.42s/it]
                                                           

  1%|          | 6575/569592 [5:34:40<534:18:56,  3.42s/it]
  1%|          | 6576/569592 [5:34:41<421:16:04,  2.69s/it]
                                                           

  1%|          | 6576/569592 [5:34:41<421:16:04,  2.69s/it]
  1%|          | 6577/569592 [5:34:42<340:23:07,  2.18s/it]
                                                           

  1%|          | 6577/569592 [5:34:42<340:23:07,/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  2.18s/it]
  1%|          | 6578/569592 [5:34:43<284:41:15,  1.82s/it]
                                                           

  1%|          | 6578/569592 [5:34:43<284:41:15,  1.82s/it]
  1%|          | 6579/569592 [5:34:47<361:29:02,  2.31s/it]
                                                           

  1%|          | 6579/569592 [5:34:47<361:29:02,  2.31s/it]
  1%|          | 6580/569592 [5:34:48<313:29:29,  2.00s/it]
                                                           

  1%|          | 6580/569592 [5:34:48<313:29:29,  2.00s/it]
  1%|          | 6581/569592 [5:34:52<426:58:07,  2.73s/it]
                                                           

  1%|          | 6581/569592 [5:34:52<426:58:07,  2.73s/it]
  1%|          | 6582/569592 [5:34:56<493:17:25,  3.15s/it]
                                                           

  1%|          | 6582/569592 [5:34:56<493:17:25,  3.15s/it]
  1%|          | 6583/569592 [5:35:00<506:28:58,  3.24s/it]
                                                           

  1%|          | 6583/569592 [5:35:00<506:28:58,  3.24s/it]
  1%|          | 6584/569592 [5:35:04<552:18:08,  3.53s/it]
                                                           

  1%|          | 6584/569592 [5:35:04<552:18:08,  3.53s/it]
  1%|          | 6585/569592 [5:35:07<544:24:28,  3.48s/it]
                                                           

  1%|          | 6585/569592 [5:35:07<544:24:28,  3.48s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91391881 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  1%|          | 6586/569592 [5:35:12<589:33:10,  3.77s/it]
                                                           

  1%|          | 6586/569592 [5:35:12<589:33:10,  3.77s/it]
  1%|          | 6587/569592 [5:35:16<598:24:55,  3.83s/it]
                                                           

  1%|          | 6587/569592 [5:35:16<598:24:55,  3.83s/it]
  1%|          | 6588/569592 [5:35:19<557:06:30,  3.56s/it]
                                                           

  1%|          | 6588/569592 [5:35:19<557:06:30,  3.56s/it]
  1%|          | 6589/569592 [5:35:22<530:54:05,  3.39s/it]
                                                           

  1%|          | 6589/569592 [5:35:22<530:54:05,  3.39s/it]
  1%|          | 6590/569592 [5:35:25<547:09:29,  3.50s/it]
                                                           

  1%|          | 6590/569592 [5:35:25<547:09:29,  3.50s/it]
  1%|          | 6591/569592 [5:35:30<603:27:21,  3.86s/it]
                                                           

  1%|          | 6591/569592 [5:35:30<603:27:21,  3.86s/it]
  1%|          | 6592/569592 [5:35:34<583:29:01,  3.73s/it]
                                                           

  1%|          | 6592/569592 [5:35:34<583:29:01,  3.73s/it]
  1%|          | 6593/569592 [5:35:37<588:24:44,  3.76s/it]
                                                           

  1%|          | 6593/569592 [5:35:37<588:24:44,  3.76s/it]
  1%|          | 6594/569592 [5:35:41<565:36:31,  3.62s/it]
                                                           

  1%|          | 6594/569592 [5:35:41<565:36:31,  3.62s/it]
  1%|          | 6595/569592 [5:35:44<551:13:04,  3.52s/it]
                                                           

  1%|          | 6595/569592 [5:35:44<551:13:04,  3.52s/it]
  1%|          | 6596/569592 [5:35:48<551:49:47,  3.53s/it]
                                                           

  1%|          | 6596/569592 [5:35:48<551:49:47,  3.53s/it]
  1%|          | 6597/569592 [5:35:51<558:41:45,  3.57s/it]
                                                           

  1%|          | 6597/569592 [5:35:51<558:41:45,  3.57s/it]
  1%|          | 6598/569592 [5:35:55<557:55:19,  3.57s/it]
                                                           

  1%|          | 6598/569592 [5:35:55<557:55:19,  3.57s/it]
  1%|          | 6599/569592 [5:35:58<549:54:08,  3.52s/it]
                                                           

  1%|          | 6599/569592 [5:35:58<549:54:08,  3.52s/it]
  1%|          | 6600/569592 [5:36:02<553:58:31,  3.54s/it]
                                                           

  1%|          | 6600/569592 [5:36:02<553:58:31,  3.54s/it]
  1%|          | 6601/569592 [5:36:05<546:51:49,  3.50s/it]
                                                           

  1%|          | 6601/569592 [5:36:05<546:51:49,  3.50s/it]
  1%|          | 6602/569592 [5:36:09<559:30:14,  3.58s/it]
                                                           

  1%|          | 6602/569592 [5:36:09<559:30:14,  3.58s/it]
  1%|          | 6603/569592 [5:36:13<580:36:30,  3.71s/it]
                                                           

  1%|          | 6603/569592 [5:36:13<580:36:30,  3.71s/it]
  1%|          | 6604/569592 [5:36:16<548:09:15,  3.51s/it]
                                                           

  1%|          | 6604/569592 [5:36:16<548:09:15,  3.51s/it]
  1%|          | 6605/569592 [5:36:17<428:25:57,  2.74s/it]
                                                           

  1%|          | 6605/569592 [5:36:17<428:25:57,  2.74s/it]
  1%|          | 6606/569592 [5:36:22<533:00:15,  3.41s/it]
                                                           

  1%|          | 6606/569592 [5:36:22<533:00:15,  3.41s/it]
  1%|          | 6607/569592 [5:36:27<596:49:58,  3.82s/it]
                                                           

  1%|          | 6607/569592 [5:36:27<596:49:58,  3.82s/it]
  1%|          | 6608/569592 [5:36:31<631:37:12,  4.04s/it]
                                                           

  1%|          | 6608/569592 [5:36:31<631:37:12,  4.04s/it]
  1%|          | 6609/569592 [5:36:32<484:56:02,  3.10s/it]
                                                           

  1%|          | 6609/569592 [5:36:32<484:56:02,  3.10s/it]
  1%|          | 6610/569592 [5:36:36<502:15:56,  3.21s/it]
                                                           

  1%|          | 6610/569592 [5:36:36<502:15:56,  3.21s/it]
  1%|          | 6611/569592 [5:36:37<395:10:28,  2.53s/it]
                                                           

  1%|          | 6611/569592 [5:36:37<395:10:28,  2.53s/it]
  1%|          | 6612/569592 [5:36:43<561:20:08,  3.59s/it]
                                                           

  1%|          | 6612/569592 [5:36:43<561:20:08,  3.59s/it]
  1%|          | 6613/569592 [5:36:47<608:43:33,  3.89s/it]
                                                           

  1%|          | 6613/569592 [5:36:47<608:43:33,  3.89s/it]
  1%|          | 6614/569592 [5:36:48<466:28:52,  2.98s/it]
                                                           

  1%|          | 6614/569592 [5:36:48<466:28:52,  2.98s/it]
  1%|          | 6615/569592 [5:36:52<520:37:08,  3.33s/it]
                                                           

  1%|          | 6615/569592 [5:36:52<520:37:08,  3.33s/it]
  1%|          | 6616/569592 [5:36:56<561:12:59,  3.59s/it]
                                                           

  1%|          | 6616/569592 [5:36:56<561:12:59,  3.59s/it]
  1%|          | 6617/569592 [5:37:00<541:47:11,  3.46s/it]
                                                           

  1%|          | 6617/569592 [5:37:00<541:47:11,  3.46s/it]
  1%|          | 6618/569592 [5:37:03<549:08:57,  3.51s/it]
                                                           

  1%|          | 6618/569592 [5:37:03<549:08:57,  3.51s/it]
  1%|          | 6619/569592 [5:37:06<535:19:00,  3.42s/it]
                                                           

  1%|          | 6619/569592 [5:37:06<535:19:00,  3.42s/it]
  1%|          | 6620/569592 [5:37:11<567:04:11,  3.63s/it]
                                                           

  1%|          | 6620/569592 [5:37:11<567:04:11,  3.63s/it]
  1%|          | 6621/569592 [5:37:15<595:13:26,  3.81s/it]
                                                           

  1%|          | 6621/569592 [5:37:15<595:13:26,  3.81s/it]
  1%|          | 6622/569592 [5:37:16<458:04:33,  2.93s/it]
                                                           

  1%|          | 6622/569592 [5:37:16<458:04:33,  2.93s/it]
  1%|          | 6623/569592 [5:37:20<505:05:02,  3.23s/it]
                                                           

  1%|          | 6623/569592 [5:37:20<505:05:02,  3.23s/it]
  1%|          | 6624/569592 [5:37:21<400:57:50,  2.56s/it]
                                                           

  1%|          | 6624/569592 [5:37:21<400:57:50,  2.56s/it]
  1%|          | 6625/569592 [5:37:24<435:57:22,  2.79s/it]
                                                           

  1%|          | 6625/569592 [5:37:24<435:57:22,  2.79s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  1%|          | 6626/569592 [5:37:29<531:44:52,  3.40s/it]
                                                           

  1%|          | 6626/569592 [5:37:29<531:44:52,  3.40s/it]
  1%|          | 6627/569592 [5:37:34<608:27:03,  3.89s/it]
                                                           

  1%|          | 6627/569592 [5:37:34<608:27:03,  3.89s/it]
  1%|          | 6628/569592 [5:37:37<580:30:52,  3.71s/it]
                                                           

  1%|          | 6628/569592 [5:37:37<580:30:52,  3.71s/it]
  1%|          | 6629/569592 [5:37:38<451:49:32,  2.89s/it]
                                                           

  1%|          | 6629/569592 [5:37:38<451:49:32,  2.89s/it]
  1%|          | 6630/569592 [5:37:39<359:21:27,  2.30s/it]
                                                           

  1%|          | 6630/569592 [5:37:39<359:21:27,  2.30s/it]
  1%|          | 6631/569592 [5:37:46<596:22:03,  3.81s/it]
                                                           

  1%|          | 6631/569592 [5:37:46<596:22:03,  3.81s/it]
  1%|          | 6632/569592 [5:37:50<577:51:14,  3.70s/it]
                                                           

  1%|          | 6632/569592 [5:37:50<577:51:14,  3.70s/it]
  1%|          | 6633/569592 [5:37:51<448:38:51,  2.87s/it]
                                                           

  1%|          | 6633/569592 [5:37:51<448:38:51,  2.87s/it]
  1%|          | 6634/569592 [5:37:54<458:14:43,  2.93s/it]
                                                           

  1%|          | 6634/569592 [5:37:54<458:14:43,  2.93s/it]
  1%|          | 6635/569592 [5:37:57<480:15:07,  3.07s/it]
                                                           

  1%|          | 6635/569592 [5:37:57<480:15:07,  3.07s/it]
  1%|          | 6636/569592 [5:37:58<381:19:19,  2.44s/it]
                                                           

  1%|          | 6636/569592 [5:37:58<381:19:19,  2.44s/it]
  1%|          | 6637/569592 [5:37:59<312:10:40,  2.00s/it]
                                                           

  1%|          | 6637/569592 [5:37:59<312:10:40,  2.00s/it]
  1%|          | 6638/569592 [5:38:03<381:37:17,  2.44s/it]
                                                           

  1%|          | 6638/569592 [5:38:03<381:37:17,  2.44s/it]
  1%|          | 6639/569592 [5:38:07<463:18:07,  2.96s/it]
                                                           

  1%|          | 6639/569592 [5:38:07<463:18:07,  2.96s/it]
  1%|          | 6640/569592 [5:38:08<372:45:34,  2.38s/it]
                                                           

  1%|          | 6640/569592 [5:38:08<372:45:34,  2.38s/it]
  1%|          | 6641/569592 [5:38:09<306:13:47,  1.96s/it]
                                                           

  1%|          | 6641/569592 [5:38:09<306:13:47,  1.96s/it]
  1%|          | 6642/569592 [5:38:10<268:29:57,  1.72s/it]
                                                           

  1%|          | 6642/569592 [5:38:10<268:29:57,  1.72/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
s/it]
  1%|          | 6643/569592 [5:38:11<232:46:48,  1.49s/it]
                                                           

  1%|          | 6643/569592 [5:38:11<232:46:48,  1.49s/it]
  1%|          | 6644/569592 [5:38:12<207:38:17,  1.33s/it]
                                                           

  1%|          | 6644/569592 [5:38:12<207:38:17,  1.33s/it]
  1%|          | 6645/569592 [5:38:13<208:27:08,  1.33s/it]
                                                           

  1%|          | 6645/569592 [5:38:13<208:27:08,  1.33s/it]
  1%|          | 6646/569592 [5:38:15<229:54:15,  1.47s/it]
                                                           

  1%|          | 6646/569592 [5:38:15<229:54:15,  1.47s/it]
  1%|          | 6647/569592 [5:38:17<258:34:16,  1.65s/it]
                                                           

  1%|          | 6647/569592 [5:38:17<258:34:16,  1.65s/it]
  1%|          | 6648/569592 [5:38:21<355:15:47,  2.27s/it]
                                                           

  1%|          | 6648/569592 [5:38:21<355:15:47,  2.27s/it]
  1%|          | 6649/569592 [5:38:24<393:24:32,  2.52s/it]
                                                           

  1%|          | 6649/569592 [5:38:24<393:24:32,  2.52s/it]
  1%|          | 6650/569592 [5:38:25<320:02:24,  2.05s/it]
                                                           

  1%|          | 6650/569592 [5:38:25<320:02:24,  2.05s/it]
  1%|          | 6651/569592 [5:38:27<322:00:47,  2.06s/it]
                                                           

  1%|          | 6651/569592 [5:38:27<322:00:47,  2.06s/it]
  1%|          | 6652/569592 [5:38:33<500:59:19,  3.20s/it]
                                                           

  1%|          | 6652/569592 [5:38:33<500:59:19,  3.20s/it]
  1%|          | 6653/569592 [5:38:36<503:09:48,  3.22s/it]
                                                           

  1%|          | 6653/569592 [5:38:36<503:09:48,  3.22s/it]
  1%|          | 6654/569592 [5:38:37<405:02:53,  2.59s/it]
                                                           

  1%|          | 6654/569592 [5:38:37<405:02:53,  2.59s/it]
  1%|          | 6655/569592 [5:38:38<348:49:15,  2.23s/it]
                                                           

  1%|          | 6655/569592 [5:38:39<348:49:15,  2.23s/it]
  1%|          | 6656/569592 [5:38:42<410:12:43,  2.62s/it]
                                                           

  1%|          | 6656/569592 [5:38:42<410:12:43,  2.62s/it]
  1%|          | 6657/569592 [5:38:43<335:48:11,  2.15s/it]
                                                           

  1%|          | 6657/569592 [5:38:43<335:48:11,  2.15s/it]
  1%|          | 6658/569592 [5:38:45<312:45:11,  2.00s/it]
                                                           

  1%|          | 6658/569592 [5:38:45<312:45:11,  2.00s/it]
  1%|          | 6659/569592 [5:38:48<376:52:29,  2.41s/it]
                                                           

  1%|          | 6659/569592 [5:38:48<376:52:29, /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91561458 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 2.41s/it]
  1%|          | 6660/569592 [5:38:51<407:28:23,  2.61s/it]
                                                           

  1%|          | 6660/569592 [5:38:51<407:28:23,  2.61s/it]
  1%|          | 6661/569592 [5:38:55<444:17:04,  2.84s/it]
                                                           

  1%|          | 6661/569592 [5:38:55<444:17:04,  2.84s/it]
  1%|          | 6662/569592 [5:38:58<494:31:54,  3.16s/it]
                                                           

  1%|          | 6662/569592 [5:38:58<494:31:54,  3.16s/it]
  1%|          | 6663/569592 [5:39:00<399:13:59,  2.55s/it]
                                                           

  1%|          | 6663/569592 [5:39:00<399:13:59,  2.55s/it]
  1%|          | 6664/569592 [5:39:03<454:04:56,  2.90s/it]
                                                           

  1%|          | 6664/569592 [5:39:03<454:04:56,  2.90s/it]
  1%|          | 6665/569592 [5:39:05<387:24:30,  2.48s/it]
                                                           

  1%|          | 6665/569592 [5:39:05<387:24:30,  2.48s/it]
  1%|          | 6666/569592 [5:39:08<444:21:34,  2.84s/it]
                                                           

  1%|          | 6666/569592 [5:39:08<444:21:34,  2.84s/it]
  1%|          | 6667/569592 [5:39:09<355:56:22,  2.28s/it]
                                                           

  1%|          | 6667/569592 [5:39:09<355:56:22,  2.28s/it]
  1%|          | 6668/569592 [5:39:14<449:48:02,  2.88s/it]
                                                           

  1%|          | 6668/569592 [5:39:14<449:48:02,  2.88s/it]
  1%|          | 6669/569592 [5:39:15<358:45:16,  2.29s/it]
                                                           

  1%|          | 6669/569592 [5:39:15<358:45:16,  2.29s/it]
  1%|          | 6670/569592 [5:39:16<299:51:31,  1.92s/it]
                                                           

  1%|          | 6670/569592 [5:39:16<299:51:31,  1.92s/it]
  1%|          | 6671/569592 [5:39:19<388:08:51,  2.48s/it]
                                                           

  1%|          | 6671/569592 [5:39:20<388:08:51,  2.48s/it]
  1%|          | 6672/569592 [5:39:24<486:54:17,  3.11s/it]
                                                           

  1%|          | 6672/569592 [5:39:24<486:54:17,  3.11s/it]
  1%|          | 6673/569592 [5:39:29<569:01:28,  3.64s/it]
                                                           

  1%|          | 6673/569592 [5:39:29<569:01:28,  3.64s/it]
  1%|          | 6674/569592 [5:39:32<553:50:49,  3.54s/it]
                                                           

  1%|          | 6674/569592 [5:39:32<553:50:49,  3.54s/it]
  1%|          | 6675/569592 [5:39:33<431:23:39,  2.76s/it]
                                                           

  1%|          | 6675/569592 [5:39:33<431:23:39,  2.76s/it]
  1%|          | 6676/569592 [5:39:36<454:34:02,  2.91s/it]
                                                           

  1%|          | 6676/569592 [5:39:36<454:34:02,  2.91s/it]
  1%|          | 6677/569592 [5:39:40<497:16:29,  3.18s/it]
                                                           

  1%|          | 6677/569592 [5:39:40<497:16:29,  3.18s/it]
  1%|          | 6678/569592 [5:39:41<395:17:08,  2.53s/it]
                                                           

  1%|          | 6678/569592 [5:39:41<395:17:08,  2.53s/it]
  1%|          | 6679/569592 [5:39:42<323:37:19,  2.07s/it]
                                                           

  1%|          | 6679/569592 [5:39:42<323:37:19,  2.07s/it]
  1%|          | 6680/569592 [5:39:43<271:32:00,  1.74s/it]
                                                           

  1%|          | 6680/569592 [5:39:43<271:32:00,  1.74s/it]
  1%|          | 6681/569592 [5:39:46<307:27:05,  1.97s/it]
                                                           

  1%|          | 6681/569592 [5:39:46<307:27:05,  1.97s/it]
  1%|          | 6682/569592 [5:39:47<263:51:40,  1.69s/it]
                                                           

  1%|          | 6682/569592 [5:39:47<263:51:40,  1.69s/it]
  1%|          | 6683/569592 [5:39:50<324:11:24,  2.07s/it]
                                                           

  1%|          | 6683/569592 [5:39:50<324:11:24,  2.07s/it]
  1%|          | 6684/569592 [5:39:53<388:46:41,  2.49s/it]
                                                           

  1%|          | 6684/569592 [5:39:53<388:46:41,  2.49s/it]
  1%|          | 6685/569592 [5:39:57<454:56:17,  2.91s/it]
                                                           

  1%|          | 6685/569592 [5:39:57<454:56:17,  2.91s/it]
  1%|          | 6686/569592 [5:39:58<363:19:09,  2.32s/it]
                                                           

  1%|          | 6686/569592 [5:39:58<363:19:09,  2.32s/it]
  1%|          | 6687/569592 [5:40:01<386:39:18,  2.47s/it]
                                                           

  1%|          | 6687/569592 [5:40:01<386:39:18,  2.47s/it]
  1%|          | 6688/569592 [5:40:02<322/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:18:02,  2.06s/it]
                                                           

  1%|          | 6688/569592 [5:40:02<322:18:02,  2.06s/it]
  1%|          | 6689/569592 [5:40:07<450:46:26,  2.88s/it]
                                                           

  1%|          | 6689/569592 [5:40:07<450:46:26,  2.88s/it]
  1%|          | 6690/569592 [5:40:08<361:17:48,  2.31s/it]
                                                           

  1%|          | 6690/569592 [5:40:08<361:17:48,  2.31s/it]
  1%|          | 6691/569592 [5:40:13<496:51:52,  3.18s/it]
                                                           

  1%|          | 6691/569592 [5:40:13<496:51:52,  3.18s/it]
  1%|          | 6692/569592 [5:40:17<536:25:09,  3.43s/it]
                                                           

  1%|          | 6692/569592 [5:40:17<536:25:09,  3.43s/it]
  1%|          | 6693/569592 [5:40:18<422:23:16,  2.70s/it]
                                                           

  1%|          | 6693/569592 [5:40:18<4/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
22:23:16,  2.70s/it]
  1%|          | 6694/569592 [5:40:19<340:28:52,  2.18s/it]
                                                           

  1%|          | 6694/569592 [5:40:19<340:28:52,  2.18s/it]
  1%|          | 6695/569592 [5:40:22<403:47:46,  2.58s/it]
                                                           

  1%|          | 6695/569592 [5:40:22<403:47:46,  2.58s/it]
  1%|          | 6696/569592 [5:40:23<327:55:55,  2.10s/it]
                                                           

  1%|          | 6696/569592 [5:40:23<327:55:55,  2.10s/it]
  1%|          | 6697/569592 [5:40:27<386:28:00,  2.47s/it]
                                                           

  1%|          | 6697/569592 [5:40:27<386:28:00,  2.47s/it]
  1%|          | 6698/569592 [5:40:30<435:21:30,  2.78s/it]
                                                           

  1%|          | 6698/569592 [5:40:30<435:21:30,  2.78s/it]
  1%|          | 6699/569592 [5:40:34<493:32:03,  3.16s/it]
                                                           

  1%|          | 6699/569592 [5:40:34<493:32:03,  3.16s/it]
  1%|          | 6700/569592 [5:40:40<593:21:51,  3.79s/it]
                                                           

  1%|          | 6700/569592 [5:40:40<593:21:51,  3.79s/it]
  1%|          | 6701/569592 [5:40:43<565:36:23,  3.62s/it]
                                                           

  1%|          | 6701/569592 [5:40:43<565:36:23,  3.62s/it]
  1%|          | 6702/569592 [5:40:46<542:49:42,  3.47s/it]
                                                           

  1%|          | 6702/569592 [5:40:46<542:49:42,  3.47s/it]
  1%|          | 6703/569592 [5:40:50<574:53:25,  3.68s/it]
                                                           

  1%|          | 6703/569592 [5:40:50<574:53:25,  3.68s/it]
  1%|          | 6704/569592 [5:40:55<610:54:12,  3.91s/it]
                                                           

  1%|          | 6704/569592 [5:40:55<610:54:12,  3.91s/it]
  1%|          | 6705/569592 [5:40:59<642:15:11,  4.11s/it]
                                                           

  1%|          | 6705/569592 [5:40:59<642:15:11,  4.11s/it]
  1%|          | 6706/569592 [5:41:02<607:51:04,  3.89s/it]
                                                           

  1%|          | 6706/569592 [5:41:02<607:51:04,  3.89s/it]
  1%|          | 6707/569592 [5:41:07<642:40:38,  4.11s/it]
                                                           

  1%|          | 6707/569592 [5:41:07<642:40:38,  4.11s/it]
  1%|          | 6708/569592 [5:41:11<641:58:19,  4.11s/it]
                                                           

  1%|          | 6708/569592 [5:41:11<641:58:19,  4.11s/it]
  1%|          | 6709/569592 [5:41:14<596:05:35,  3.81s/it]
                                                           

  1%|          | 6709/569592 [5:41:14<596:05:35,  3.81s/it]
  1%|          | 6710/569592 [5:41:18<573:41:01,  3.67s/it]
                                                           

  1%|          | 6710/569592 [5:41:18<573:41:01,  3.67s/it]
  1%|          | 6711/569592 [5:41:21<567:38:50,  3.63s/it]
                                                           

  1%|          | 6711/569592 [5:41:21<567:38:50,  3.63s/it]
  1%|          | 6712/569592 [5:41:25<560:53:17,  3.59s/it]
                                                           

  1%|          | 6712/569592 [5:41:25<560:53:17,  3.59s/it]
  1%|          | 6713/569592 [5:41:28<567:28:11,  3.63s/it]
                                                           

  1%|          | 6713/569592 [5:41:28<567:28:11,  3.63s/it]
  1%|          | 6714/569592 [5:41:33<631:14:39,  4.04s/it]
                                                           

  1%|          | 6714/569592 [5:41:33<631:14:39,  4.04s/it]
  1%|          | 6715/569592 [5:41:37<592:21:25,  3.79s/it]
                                                           

  1%|          | 6715/569592 [5:41:37<592:21:25,  3.79s/it]
  1%|          | 6716/569592 [5:41:40<554:57:19,  3.55s/it]
                                                           

  1%|          | 6716/569592 [5:41:40<554:57:19,  3.55s/it]
  1%|          | 6717/569592 [5:41:43<548:35:15,  3.51s/it]
                                                           

  1%|          | 6717/569592 [5:41:43<548:35:15,  3.51s/it]
  1%|          | 6718/569592 [5:41:47<557:33:49,  3.57s/it]
                                                           

  1%|          | 6718/569592 [5:41:47<557:33:49,  3.57s/it]
  1%|          | 6719/569592 [5:41:50<551:16:09,  3.53s/it]
                                                           

  1%|          | 6719/569592 [5:41:50<551:16:09,  3.53s/it]
  1%|          | 6720/569592 [5:41:53<535:38:26,  3.43s/it]
                                                           

  1%|          | 6720/569592 [5:41:53<535:38:26,  3.43s/it]
  1%|          | 6721/569592 [5:41:54<417:25:12,  2.67s/it]
                                                           

  1%|          | 6721/569592 [5:41:54<417:25:12,  2.67s/it]
  1%|          | 6722/569592 [5:41:55<336:50:00,  2.15s/it]
                                                           

  1%|          | 6722/569592 [5:41:55<336:50:00,  2.15s/it]
  1%|          | 6723/569592 [5:41:58<390:21:15,  2.50s/it]
                                                           

  1%|          | 6723/569592 [5:41:58<390:21:15,  2.50s/it]
  1%|          | 6724/569592 [5:42:02<441:13:11,  2.82s/it]
                                                           

  1%|          | 6724/569592 [5:42:02<441:13:11,  2.82s/it]
  1%|          | 6725/569592 [5:42:05<457:19:25,  2.92s/it]
                                                           

  1%|          | 6725/569592 [5:42:05<457:19:25,  2.92s/it]
  1%|          | 6726/569592 [5:42:09<491:21:29,  3.14s/it]
                                                           

  1%|          | 6726/569592 [5:42:09<491:21:29,  3.14s/it]
  1%|          | 6727/569592 [5:42:10<387:19:24,  2.48s/it]
                                                           

  1%|          | 6727/569592 [5:42:10<387:19:24,  2.48s/it]
  1%|          | 6728/569592 [5:42:14<454:11:06,  2.90s/it]
                                                           

  1%|          | 6728/569592 [5:42:14<454:11:06,  2.90s/it]
  1%|          | 6729/569592 [5:42:17<463:40:53,  2.97s/it]
                                                           

  1%|          | 6729/569592 [5:42:17<463:40:53,  2.97s/it]
  1%|          | 6730/569592 [5:42:21<507:20:06,  3.24s/it]
                                                           

  1%|          | 6730/569592 [5:42:21<507:20:06,  3.24s/it]
  1%|          | 6731/569592 [5:42:24<508:31:18,  3.25s/it]
                                                           

  1%|          | 6731/569592 [5:42:24<508:31:18,  3.25s/it]
  1%|          | 6732/569592 [5:42:27<519:18:49,  3.32s/it]
                                                           

  1%|          | 6732/569592 [5:42:27<519:18:49,  3.32s/it]
  1%|          | 6733/569592 [5:42:31<548:56:28,  3.51s/it]
                            /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                               

  1%|          | 6733/569592 [5:42:31<548:56:28,  3.51s/it]
  1%|          | 6734/569592 [5:42:36<609:44:54,  3.90s/it]
                                                           

  1%|          | 6734/569592 [5:42:36<609:44:54,  3.90s/it]
  1%|          | 6735/569592 [5:42:41<648:46:09,  4.15s/it]
                                                           

  1%|          | 6735/569592 [5:42:41<648:46:09,  4.15s/it]
  1%|          | 6736/569592 [5:42:44<597:09:12,  3.82s/it]
                                                           

  1%|          | 6736/569592 [5:42:44<597:09:12,  3.82s/it]
  1%|          | 6737/569592 [5:42:47<564:05:33,  3.61s/it]
                                                           

  1%|          | 6737/569592 [5:42:47<564:05:33,  3.61s/it]
  1%|          | 6738/569592 [5:42:50<545:00:35,  3.49s/it]
                                                           

  1%|          | 6738/569592 [5:42:50<545:00:35,  3.49s/it]
  1%|          | 6739/569592 [5:42:55<587:06:35,  3.76s/it]
                                                           

  1%|          | 6739/569592 [5:42:55<587:06:35,  3.76s/it]
  1%|          | 6740/569592 [5:42:58<564:55:06,  3.61s/it]
                                                           

  1%|          | 6740/569592 [5:42:58<564:55:06,  3.61s/it]
  1%|          | 6741/569592 [5:43:01<547:43:01,  3.50s/it]
                                                           

  1%|          | 6741/569592 [5:43:01<547:43:01,  3.50s/it]
  1%|          | 6742/569592 [5:43:02<426:06:04,  2.73s/it]
                                                           

  1%|          | 6742/569592 [5:43:02<426:06:04,  2.73s/it]
  1%|          | 6743/569592 [5:43:06<457:48:30,  2.93s/it]
                                                           

  1%|          | 6743/569592 [5:43:06<457:48:30,  2.93s/it]
  1%|          | 6744/569592 [5:43:09<492:01:13,  3.15s/it]
                                                           

  1%|          | 6744/569592 [5:43:09<492:01:13,  3.15s/it]
  1%|          | 6745/569592 [5:43:10<388:31:31,  2.49s/it]
                                                           

  1%|          | 6745/569592 [5:43:10<388:31:31,  2.49s/it]
  1%|          | 6746/569592 [5:43:13<423:06:44,  2.71s/it]
                                                           

  1%|          | 6746/569592 [5:43:13<423:06:44,  2.71s/it]
  1%|          | 6747/569592 [5:43:17<483:23:54,  3.09s/it]
                                                           

  1%|          | 6747/569592 [5:43:17<483:23:54,  3.09s/it]
  1%|          | 6748/569592 [5:43:21<521:07:00,  3.33s/it]
                                                           

  1%|          | 6748/569592 [5:43:21<521:07:00,  3.33s/it]
  1%|          | 6749/569592 [5:43:25<539:28:56,  3.45s/it]
                                                           

  1%|          | 6749/569592 [5:43:25<539:28:56,  3.45s/it]
  1%|          | 6750/569592 [5:43:26<420:04:41,  2.69s/it]
                                                           

  1%|          | 6750/569592 [5:43:26<420:04:41,  2.69s/it]
  1%|          | 6751/569592 [5:43:27<338:08:09,  2.16s/it]
                                                           

  1%|          | 6751/569592 [5:43:27<338:08:09,  2.16s/it]
  1%|          | 6752/569592 [5:43:30<388:27:37,  2.48s/it]
                                                           

  1%|          | 6752/569592 [5:43:30<388:27:37,  2.48s/it]
  1%|          | 6753/569592 [5:43:34<452:21:53,  2.89s/it]
                                                           

  1%|          | 6753/569592 [5:43:34<452:21:53,  2.89s/it]
  1%|          | 6754/569592 [5:43:35<363:21:58,  2.32s/it]
                                                           

  1%|          | 6754/569592 [5:43:35<363:21:58,  2.32s/it]
  1%|          | 6755/569592 [5:43:36<298:48:27,  1.91s/it]
                                                           

  1%|          | 6755/569592 [5:43:36<298:48:27,  1.91s/it]
  1%|          | 6756/569592 [5:43:40<382:51:04,  2.45s/it]
                                                           

  1%|          | 6756/569592 [5:43:40<382:51:04,  2.45s/it]
  1%|          | 6757/569592 [5:43:43<445:46:03,  2.85s/it]
                                                           

  1%|          | 6757/569592 [5:43:43<445:46:03,  2.85s/it]
  1%|          | 6758/569592 [5:43:44<357:06:16,  2.28s/it]
                                                           

  1%|          | 6758/569592 [5:43:44<357:06:16,  2.28s/it]
  1%|          | 6759/569592 [5:43:45<294:45:39,  1.89s/it]
                                                           

  1%|          | 6759/569592 [5:43:45<294:45:39,  1.89s/it]
  1%|          | 6760/569592 [5:43:46<249:55:19,  1.60s/it]
                                                           

  1%|          | 6760/569592 [5:43:46<249:55:19,  1.60s/it]
  1%|          | 6761/569592 [5:43:47<222:52:44,  1.43s/it]
                                                           

  1%|          | 6761/569592 [5:43:47<222:52:44,  1.43s/it]
  1%|          | 6762/569592 [5:43:49<245:16:52,  1.57s/it]
                                                           

  1%|          | 6762/569592 [5:43:49<245:16:52,  1.57s/it]
  1%|          | 6763/569592 [5:43:51<249:25:32,  1.60s/it]
                                                           

  1%|          | 6763/569592 [5:43:51<249:25:32,  1.60s/it]
  1%|          | 6764/569592 [5:43:52<224:38:05,  1.44s/it]
                                                           

  1%|          | 6764/569592 [5:43:52<224:38:05,  1.44s/it]
  1%|          | 6765/569592 [5:43:56<345:53:48,  2.21s/it]
                                                           

  1%|          | 6765/569592 [5:43:56<345:53:48,  2.21s/it]
  1%|          | 6766/569592 [5:44:00<415:24:55,  2.66s/it]
                                                           

  1%|          | 6766/569592 [5:44:00<415:24:55,  2.66s/it]
  1%|          | 6767/569592 [5:44:01<351:42:49,  2.25s/it]
                                                           

  1%|          | 6767/569592 [5:44:01<351:42:49,  2.25s/it]
  1%|          | 6768/569592 [5:44:02<291:12:23,  1.86s/it]
                                                           

  1%|          | 6768/569592 [5:44:02<291:12:23,  1.86s/it]
  1%|          | 6769/569592 [5:44:06<386:28:51,  2.47s/it]
                                                           

  1%|          | 6769/569592 [5:44:06<386:28:51,  2.47s/it]
  1%|          | 6770/569592 [5:44:09<441:46:01,  2.83s/it]
                                                           

  1%|          | 6770/569592 [5:44:09<441:46:01,  2.83s/it]
  1%|          | 6771/569592 [5:44:11<385:58:32,  2.47s/it]
                                                           

  1%|          | 6771/569592 [5:44:11<385:58:32,  2.47s/it]
  1%|          | 6772/569592 [5:44:12<316:47:26,  2.03s/it]
                                                           

  1%|          | 6772/569592 [5:44:12<316:47:26,  2.03s/it]
  1%|          | 6773/569592 [5:44:15<352:14:08,  2.25s/it]
                                                           

  1%|          | 6773/569592 [5:44:15<352:14:08,  2.25s/it]
  1%|          | 6774/569592 [5:44:20<478:49:36,  3.06s/it]
                                                           

  1%|          | 6774/569592 [5:44:20<478:49:36,  3.06s/it]
  1%|          | 6775/569592 [5:44:21<386:09:07,  2.47s/it]
                                                           

  1%|          | 6775/569592 [5:44:21<386:09:07,  2.47s/it]
  1%|          | 6776/569592 [5:44:25<466:13:43,  2.98s/it]
                                                           

  1%|          | 6776/569592 [5:44:25<466:13:43,  2.98s/it]
  1%|          | 6777/569592 [5:44:26<372:05:55,  2.38s/it]
                                                           

  1%|          | 6777/569592 [5:44:26<372:05:55,  2.38s/it]
  1%|          | 6778/569592 [5:44:29<414:07:01,  2.65s/it]
                                                           

  1%|          | 6778/569592 [5:44:29<414:07:01,  2.65s/it]
  1%|          | 6779/569592 [5:44:34<501:29:49,  3.21s/it]
                                                           

  1%|          | 6779/569592 [5:44:34<501:29:49,  3.21s/it]
  1%|          | 6780/569592 [5:44:38<538:54:52,  3.45s/it]
                                                           

  1%|          | 6780/569592 [5:44:38<538:54:52,  3.45s/it]
  1%|          | 6781/569592 [5:44:39<424:36:44,  2.72s/it]
                                                           

  1%|          | 6781/569592 [5:44:39<424:36:44,  2.72s/it]
  1%|          | 6782/569592 [5:44:40<375:15:10,  2.40s/it]
                                                           

  1%|          | 6782/569592 [5:44:40<375:15:10,  2.40s/it]
  1%|          | 6783/569592 [5:44:41<306:25:49,  1.96s/it]
                                                           

  1%|          | 6783/569592 [5:44:41<306:25:49,  1.96s/it]
  1%|          | 6784/569592 [5:44:46<427:17:30,  2.73s/it]
                                                           

  1%|          | 6784/569592 [5:44:46<427:17:30,  2.73s/it]
  1%|          | 6785/569592 [5:44:50<475:38:56,  3.04s/it]
                                                           

  1%|          | 6785/569592 [5:44:50<475:38:56,  3.04s/it]
  1%|          | 6786/569592 [5:44:54<522:59:28,  3.35s/it]
                                                           

  1%|          | 6786/569592 [5:44:54<522:59:28,  3.35s/it]
  1%|          | 6787/569592 [5:44:57<543:44:39,  3.48s/it]
                                                           

  1%|          | 6787/569592 [5:44:58<543:44:39,  3.48s/it]
  1%|          | 6788/569592 [5:44:58<425:21:08,  2.72s/it]
                                                           

  1%|          | 6788/569592 [5:44:58<425:21:08,  2.72s/it]
  1%|          | 6789/569592 [5:44:59<345:08:19,  2.21s/it]
                                                           

  1%|          | 6789/569592 [5:44:59<345:08:19,  2.21s/it]
  1%|          | 6790/569592 [5:45:00<288:38:16,  1.85s/it]
                                                           

  1%|          | 6790/569592 [5:45:00<288:38:16,  1.85s/it]
  1%|          | 6791/569592 [5:45:01<246:40:57,  1.58s/it]
                                                           

  1%|          | 6791/569592 [5:45:01<246:40:57,  1.58s/it]
  1%|          | 6792/569592 [5:45:05<332:32:26,  2.13s/it]
                                                           

  1%|          | 6792/569592 [5:45:05<332:32:26,  2.13s/it]
  1%|          | 6793/569592 [5:45:06<300:05:30,  1.92s/it]
                                                           

  1%|          | 6793/569592 [5:45:06<300:05:30,  1.92s/it]
  1%|          | 6794/569592 [5:45:10<387:14:07,  2.48s/it]
                                                           

  1%|          | 6794/569592 [5:45:10<387:14:07,  2.48s/it]
  1%|          | 6795/569592 [5:45:13<428:33:45,  2.74s/it]
                                                           

  1%|          | 6795/569592 [5:45:13<428:33:45,  2.74s/it]
  1%|          | 6796/569592 [5:45:14<344:31:14,  2.20s/it]
                                                           

  1%|          | 6796/569592 [5:45:14<344:31:14,  2.20s/it]
  1%|          | 6797/569592 [5:45:17<344:13:03,  2.20s/it]
                                                           

  1%|          | 6797/569592 [5:45:17<344:13:03,  2.20s/it]
  1%|          | 6798/569592 [5:45:21<438:36:14,  2.81s/it]
                                                           

  1%|          | 6798/569592 [5:45:21<438:36:14,  2.81s/it]
  1%|          | 6799/569592 [5:45:22<352:22:07,  2.25s/it]
                                                           

  1%|          | 6799/569592 [5:45:22<352:22:07,  2.25s/it]
  1%|          | 6800/569592 [5:45:23<291:56:48,  1.87s/it]
                                                           

  1%|          | 6800/569592 [5:45:23<291:56:48,  1.87s/it]
  1%|          | 6801/569592 [5:45:27<394:35:37,  2.52s/it]
                                                           

  1%|          | 6801/569592 [5:45:27<394:35:37,  2.52s/it]
  1%|          | 6802/569592 [5:45:31<477:13:52,  3.05s/it]
                                                           

  1%|          | 6802/569592 [5:45:31<477:13:52,  3.05s/it]
  1%|          | 6803/569592 [5:45:32<379:48:55,  2.43s/it]
                                                           

  1%|          | 6803/569592 [5:45:32<379:48:55,  2.43s/it]
  1%|          | 6804/569592 [5:45:33<310:22:10,  1.99s/it]
                                                           

  1%|          | 6804/569592 [5:45:33<310:22:10,  1.99s/it]
  1%|          | 6805/569592 [5:45:37<383:36:41,  2.45s/it]
                                                           

  1%|          | 6805/569592 [5:45:37<383:36:41,  2.45s/it]
  1%|          | 6806/569592 [5:45:41<474:25:43,  3.03s/it]
                                                           

  1%|          | 6806/569592 [5:45:41<474:25:43,  3.03s/it]
  1%|          | 6807/569592 [5:45:46<588:54:17,  3.77s/it]
                                                           

  1%|          | 6807/569592 [5:45:46<588:54:17,  3.77s/it]
  1%|          | 6808/569592 [5:45:47<457:10:55,  2.92s/it]
                                                           

  1%|          | 6808/569592 [5:45:47<457:10:55,  2.92s/it]
  1%|          | 6809/569592 [5:45:53<569:01:12,  3.64s/it]
                                                           

  1%|          | 6809/569592 [5:45:53<569:01:12,  3.64s/it]
  1%|          | 6810/569592 [5:45:56<568:26:45,  3.64s/it]
                                                           

  1%|          | 6810/569592 [5:45:56<568:26:45,  3.64s/it]
  1%|          | 6811/569592 [5:45:59<540:32:02,  3.46s/it]
                                                           

  1%|          | 6811/569592 [5:45:59<540:32:02,  3.46s/it]
  1%|          | 6812/569592 [5:46:03<531:20:33,  3.40s/it]
                                                           

  1%|          | 6812/569592 [5:46:03<531:20:33,  3.40s/it]
  1%|          | 6813/569592 [5:46:04<418:48:43,  2.68s/it]
                                                           

  1%|          | 6813/569592 [5:46:04<418:48:43,  2.68s/it]
  1%|          | 6814/569592 [5:46:05<337:52:45,  2.16s/it]
                                                           

  1%|          | 6814/569592 [5:46:05<337:52:45,  2.16s/it]
  1%|          | 6815/569592 [5:46:08<395:59:20,  2.53s/it]
                                                           

  1%|          | 6815/569592 [5:46:08<395:59:20,  2.53s/it]
  1%|          | 6816/569592 [5:46:12<457:22:35,  2.93s/it]
                                                           

  1%|          | 6816/569592 [5:46:12<457:22:35,  2.93s/it]
  1%|          | 6817/569592 [5:46:16<524:07:04,  3.35s/it]
                                                           

  1%|          | 6817/569592 [5:46:16<524:07:04,  3.35s/it]
  1%|          | 6818/569592 [5:46:20<526:44:08,  3.37s/it]
                                                           

  1%|          | 6818/569592 [5:46:20<526:44:08,  3.37s/it]
  1%|          | 6819/569592 [5:46:24<591:10:41,  3.78s/it]
                                                           

  1%|          | 6819/569592 [5:46:24<591:10:41,  3.78s/it]
  1%|          | 6820/569592 [5:46:27<553:42:39,  3.54s/it]
                                                           

  1%|          | 6820/569592 [5:46:27<553:42:39,  3.54s/it]
  1%|          | 6821/569592 [5:46:30<533:06:05,  3.41s/it]
                                                           

  1%|          | 6821/569592 [5:46:31<533:06:05,  3.41s/it]
  1%|          | 6822/569592 [5:46:35<603:48:23,  3.86s/it]
                                                           

  1%|          | 6822/569592 [5:46:35<603:48:23,  3.86s/it]
  1%|          | 6823/569592 [5:46:40<636:56:40,  4.07s/it]
                                                           

  1%|          | 6823/569592 [5:46:40<636:56:40,  4.07s/it]
  1%|          | 6824/569592 [5:46:43<593:52:16,  3.80s/it]
                                                           

  1%|          | 6824/569592 [5:46:43<593:52:16,  3.80s/it]
  1%|          | 6825/569592 [5:46:47<590:21:23,  3.78s/it]
                                                           

  1%|          | 6825/569592 [5:46:47<590:21:23,  3.78s/it]
  1%|          | 6826/569592 [5:46:51<631:58:07,  4.04s/it]
                                                           

  1%|          | 6826/569592 [5:46:51<631:58:07,  4.04s/it]
  1%|          | 6827/569592 [5:46:54<585:04:51,  3.74s/it]
                                                           

  1%|          | 6827/569592 [5:46:54<585:04:51,  3.74s/it]
  1%|          | 6828/569592 [5:46:58<564:40:55,  3.61s/it]
                                                           

  1%|          | 6828/569592 [5:46:58<564:40:55,  3.61s/it]
  1%|          | 6829/569592 [5:47:01<557:29:26,  3.57s/it]
                                                           

  1%|          | 6829/569592 [5:47:01<557:29:26,  3.57s/it]
  1%|          | 6830/569592 [5:47:05<590:00:27,  3.77s/it]
                                                           

  1%|          | 6830/569592 [5:47:05<590:00:27,  3.77s/it]
  1%|          | 6831/569592 [5:47:09<566:40:56,  3.63s/it]
                                                           

  1%|          | 6831/569592 [5:47:09<566:40:56,  3.63s/it]
  1%|          | 6832/569592 [5:47:12<555:22:21,  3.55s/it]
                                                           

  1%|          | 6832/569592 [5:47:12<555:22:21,  3.55s/it]
  1%|          | 6833/569592 [5:47:15<533:01:46,  3.41s/it]
                                                           

  1%|          | 6833/569592 [5:47:15<533:01:46,  3.41s/it]
  1%|          | 6834/569592 [5:47:18<523:43:04,  3.35s/it]
                                                           

  1%|          | 6834/569592 [5:47:18<523:43:04,  3.35s/it]
  1%|          | 6835/569592 [5:47:22<520:49:07,  3.33s/it]
                                                           

  1%|          | 6835/569592 [5:47:22<520:49:07,  3.33s/it]
  1%|          | 6836/569592 [5:47:25<533:00:09,  3.41s/it]
                                                           

  1%|          | 6836/569592 [5:47:25<533:00:09,  3.41s/it]
  1%|          | 6837/569592 [5:47:29<548:30:59,  3.51s/it]
                                                           

  1%|          | 6837/569592 [5:47:29<548:30:59,  3.51s/it]
  1%|          | 6838/569592 [5:47:32<527:24:24,  3.37s/it]
                                                           

  1%|          | 6838/569592 [5:47:32<527:24:24,  3.37s/it]
  1%|          | 6839/569592 [5:47:33<412:50:47,  2.64s/it]
                                                           

  1%|          | 6839/569592 [5:47:33<412:50:47,  2.64s/it]
  1%|          | 6840/569592 [5:47:34<333:45:56,  2.14s/it]
                                                           

  1%|          | 6840/569592 [5:47:34<333:45:56,  2.14s//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
it]
  1%|          | 6841/569592 [5:47:39<475:11:29,  3.04s/it]
                                                           

  1%|          | 6841/569592 [5:47:39<475:11:29,  3.04s/it]
  1%|          | 6842/569592 [5:47:43<504:34:31,  3.23s/it]
                                                           

  1%|          | 6842/569592 [5:47:43<504:34:31,  3.23s/it]
  1%|          | 6843/569592 [5:47:44<396:19:55,  2.54s/it]
                                                           

  1%|          | 6843/569592 [5:47:44<396:19:55,  2.54s/it]
  1%|          | 6844/569592 [5:47:48<481:55:10,  3.08s/it]
                                                           

  1%|          | 6844/569592 [5:47:48<481:55:10,  3.08s/it]
  1%|          | 6845/569592 [5:47:52<512:07:56,  3.28s/it]
                                                           

  1%|          | 6845/569592 [5:47:52<512:07:56,  3.28s/it]
  1%|          | 6846/569592 [5:47:55<514:25:39,  3.29s/it]
                                                           

  1%|          | 6846/569592 [5:47:55<514:25:39,  3.29s/it]
  1%|          | 6847/569592 [5:47:58<501:45:59,  3.21s/it]
                                                           

  1%|          | 6847/569592 [5:47:58<501:45:59,  3.21s/it]
  1%|          | 6848/569592 [5:48:03<566:56:55,  3.63s/it]
                                                           

  1%|          | 6848/569592 [5:48:03<566:56:55,  3.63s/it]
  1%|          | 6849/569592 [5:48:06<556:28:37,  3.56s/it]
                                                           

  1%|          | 6849/569592 [5:48:06<556:28:37,  3.56s/it]
  1%|          | 6850/569592 [5:48:10<561:38:18,  3.59s/it]
                                                           

  1%|          | 6850/569592 [5:48:10<561:38:18,  3.59s/it]
  1%|          | 6851/569592 [5:48:14<568:27:59,  3.64s/it]
                                                           

  1%|          | 6851/569592 [5:48:14<568:27:59,  3.64s/it]
  1%|          | 6852/569592 [5:48:18<623:46:43,  3.99s/it]
                                                           

  1%|          | 6852/569592 [5:48:18<623:46:43,  3.99s/it]
  1%|          | 6853/569592 [5:48:22<592:23:45,  3.79s/it]
                                                           

  1%|          | 6853/569592 [5:48:22<592:23:45,  3.79s/it]
  1%|          | 6854/569592 [5:48:25<570:06:27,  3.65s/it]
                                                           

  1%|          | 6854/569592 [5:48:25<570:06:27,  3.65s/it]
  1%|          | 6855/569592 [5:48:30<627:38:56,  4.02s/it]
                                                           

  1%|          | 6855/569592 [5:48:30<627:38:56,  4.02s/it]
  1%|          | 6856/569592 [5:48:34<639:35:39,  4.09s/it]
                                                           

  1%|          | 6856/569592 [5:48:34<639:35:39,  4.09s/it]
  1%|          | 6857/569592 [5:48:37<596:53:25,  3.82s/it]
                                                           

  1%|          | 6857/569592 [5:48:37<596:53:25,  3/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
.82s/it]
  1%|          | 6858/569592 [5:48:41<570:35:09,  3.65s/it]
                                                           

  1%|          | 6858/569592 [5:48:41<570:35:09,  3.65s/it]
  1%|          | 6859/569592 [5:48:44<558:18:32,  3.57s/it]
                                                           

  1%|          | 6859/569592 [5:48:44<558:18:32,  3.57s/it]
  1%|          | 6860/569592 [5:48:48<566:28:16,  3.62s/it]
                                                           

  1%|          | 6860/569592 [5:48:48<566:28:16,  3.62s/it]
  1%|          | 6861/569592 [5:48:51<545:31:36,  3.49s/it]
                                                           

  1%|          | 6861/569592 [5:48:51<545:31:36,  3.49s/it]
  1%|          | 6862/569592 [5:48:56<602:52:01,  3.86s/it]
                                                           

  1%|          | 6862/569592 [5:48:56<602:52:01,  3.86s/it]
  1%|          | 6863/569592 [5:48:59<573:22:45,  3.67s/it]
                                                           

  1%|          | 6863/569592 [5:48:59<573:22:45,  3.67s/it]
  1%|          | 6864/569592 [5:49:04<620:15:01,  3.97s/it]
                                                           

  1%|          | 6864/569592 [5:49:04<620:15:01,  3.97s/it]
  1%|          | 6865/569592 [5:49:04<475:48:54,  3.04s/it]
                                                           

  1%|          | 6865/569592 [5:49:04<475:48:54,  3.04s/it]
  1%|          | 6866/569592 [5:49:08<482:01:47,  3.08s/it]
                                                           

  1%|          | 6866/569592 [5:49:08<482:01:47,  3.08s/it]
  1%|          | 6867/569592 [5:49:12<523:57:07,  3.35s/it]
                                                           

  1%|          | 6867/569592 [5:49:12<523:57:07,  3.35s/it]
  1%|          | 6868/569592 [5:49:12<411:13:24,  2.63s/it]
                                                           

  1%|          | 6868/569592 [5:49:13<411:13:24,  2.63s/it]
  1%|          | 6869/569592 [5:49:13<331:40:09,  2.12s/it]
                                                           

  1%|          | 6869/569592 [5:49:13<331:40:09,  2.12s/it]
  1%|          | 6870/569592 [5:49:17<388:47:23,  2.49s/it]
                                                           

  1%|          | 6870/569592 [5:49:17<388:47:23,  2.49s/it]
  1%|          | 6871/569592 [5:49:21<455:18:35,  2.91s/it]
                                                           

  1%|          | 6871/569592 [5:49:21<455:18:35,  2.91s/it]
  1%|          | 6872/569592 [5:49:22<367:32:12,  2.35s/it]
                                                           

  1%|          | 6872/569592 [5:49:22<367:32:12,  2.35s/it]
  1%|          | 6873/569592 [5:49:23<304:05:29,  1.95s/it]
                                                           

  1%|          | 6873/569592 [5:49:23<304:05:29,  1.95s/it]
  1%|          | 6874/569592 [5:49:26<371:56:12,  2.38s/it]
                                                           

  1%|          | 6874/569592 [5:49:26<371:56:12,  2.38s/it]
  1%|          | 6875/569592 [5:49:30<431:00:46,  2.76s/it]
                                                           

  1%|          | 6875/569592 [5:49:30<431:00:46,  2.76s/it]
  1%|          | 6876/569592 [5:49:31<346:47:14,  2.22s/it]
                                                           

  1%|          | 6876/569592 [5:49:31<346:47:14,  2.22s/it]
  1%|          | 6877/569592 [5:49:32<287:14:48,  1.84s/it]
                                                           

  1%|          | 6877/569592 [5:49:32<287:14:48,  1.84s/it]
  1%|          | 6878/569592 [5:49:35<354:18:01,  2.27s/it]
                                                           

  1%|          | 6878/569592 [5:49:35<354:18:01,  2.27s/it]
  1%|          | 6879/569592 [5:49:36<293:46:59,  1.88s/it]
                                                           

  1%|          | 6879/569592 [5:49:36<293:46:59,  1.88s/it]
  1%|          | 6880/569592 [5:49:37<250:24:30,  1.60s/it]
                                                           

  1%|          | 6880/569592 [5:49:37<250:24:30,  1.60s/it]
  1%|          | 6881/569592 [5:49:40<328:23:37,  2.10s/it]
                                                           

  1%|          | 6881/569592 [5:49:40<328:23:37,  2.10s/it]
  1%|          | 6882/569592 [5:49:41<275:09:48,  1.76s/it]
                                                           

  1%|          | 6882/569592 [5:49:41<275:09:48,  1.76s/it]
  1%|          | 6883/569592 [5:49:42<237:58:18,  1.52s/it]
                                                           

  1%|          | 6883/569592 [5:49:42<237:58:18,  1.52s/it]
  1%|          | 6884/569592 [5:49:45<321:09:40,  2.05s/it]
                                                           

  1%|          | 6884/569592 [5:49:45<321:09:40,  2.05s/it]
  1%|          | 6885/569592 [5:49:47<298:35:59,  1.91s/it]
                                                           

  1%|          | 6885/569592 [5:49:47<298:35:59,  1.91s/it]
  1%|          | 6886/569592 [5:49:48<256:28:49,  1.64s/it]
                                                           

  1%|          | 6886/569592 [5:49:48<256:28:49,  1.64s/it]
  1%|          | 6887/569592 [5:49:52<354:31:57,  2.27s/it]
                                                           

  1%|          | 6887/569592 [5:49:52<354:31:57,  2.27s/it]
  1%|          | 6888/569592 [5:49:56<468:23:40,  3.00s/it]
                                                           

  1%|          | 6888/569592 [5:49:56<468:23:40,  3.00s/it]
  1%|          | 6889/569592 [5:49:58<390:35:23,  2.50s/it]
                                                           

  1%|          | 6889/569592 [5:49:58<390:35:23,  2.50s/it]
  1%|          | 6890/569592 [5:49:59<319:01:11,  2.04s/it]
                                                           

  1%|          | 6890/569592 [5:49:59<319:01:11,  2.04s/it]
  1%|          | 6891/569592 [5:50:01<320:16:10,  2.05s/it]
                                                           

  1%|          | 6891/569592 [5:50:01<320:16:10,  2.05s/it]
  1%|          | 6892/569592 [5:50:06<468:26:08,  3.00s/it]
                                                           

  1%|          | 6892/569592 [5:50:06<468:26:08,  3.00s/it]
  1%|          | 6893/569592 [5:50:07<384:24:24,  2.46s/it]
                                                           

  1%|          | 6893/569592 [5:50:07<384:24:24,  2.46s/it]
  1%|          | 6894/569592 [5:50:11<426:02:03,  2.73s/it]
                                                           

  1%|          | 6894/569592 [5:50:11<426:02:03,  2.73s/it]
  1%|          | 6895/569592 [5:50:14<480:18:15,  3.07s/it]
                                                           

  1%|          | 6895/569592 [5:50:14<480:18:15,  3.07s/it]
  1%|          | 6896/569592 [5:50:17<447:58:35,  2.87s/it]
                                                           

  1%|          | 6896/569592 [5:50:17<447:58:35,  2.87s/it]
  1%|          | 6897/569592 [5:50:19<413:02:29,  2.64s/it]
                                                           

  1%|          | 6897/569592 [5:50:19<413:02:29,  2.64s/it]
  1%|          | 6898/569592 [5:50:20<334:02:29,  2.14s/it]
                                                           

  1%|          | 6898/569592 [5:50:20<334:02:29,  2.14s/it]
  1%|          | 6899/569592 [5:50:22<312:11:45,  2.00s/it]
                                                           

  1%|          | 6899/569592 [5:50:22<312:11:45,  2.00s/it]
  1%|          | 6900/569592 [5:50:27<459:27:32,  2.94s/it]
                                                           

  1%|          | 6900/569592 [5:50:27<459:27:32,  2.94s/it]
  1%|          | 6901/569592 [5:50:31<525:55:04,  3.36s/it]
                                                           

  1%|          | 6901/569592 [5:50:31<525:55:04,  3.36s/it]
  1%|          | 6902/569592 [5:50:36<599:17:45,  3.83s/it]
                                                           

  1%|          | 6902/569592 [5:50:36<599:17:45,  3.83s/it]
  1%|          | 6903/569592 [5:50:37<465:51:37,  2.98s/it]
                                                           

  1%|          | 6903/569592 [5:50:37<465:51:37,  2.98s/it]
  1%|          | 6904/569592 [5:50:41<504:07:37,  3.23s/it]
                                                           

  1%|          | 6904/569592 [5:50:41<504:07:37,  3.23s/it]
  1%|          | 6905/569592 [5:50:42<414:02:16,  2.65s/it]
                                                           

  1%|          | 6905/569592 [5:50:42<414:02:16,  2.65s/it]
  1%|          | 6906/569592 [5:50:43<336:13:40,  2.15s/it]
                                                           

  1%|          | 6906/569592 [5:50:43<336:13:40,  2.15s/it]
  1%|          | 6907/569592 [5:50:44<280:29:39,  1.79s/it]
                                                           

  1%|          | 6907/569592 [5:50:44<280:29:39,  1.79s/it]
  1%|          | 6908/569592 [5:50:46<291:16:19,  1.86s/it]
                                                           

  1%|          | 6908/569592 [5:50:46<291:16:19,  1.86s/it]
  1%|          | 6909/569592 [5:50:51<442:45:51,  2.83s/it]
                                                           

  1%|          | 6909/569592 [5:50:51<442:45:51,  2.83s/it]
  1%|          | 6910/569592 [5:50:54<467:14:19,  2.99s/it]
                                                           

  1%|          | 6910/569592 [5:50:54<467:14:19,  2.99s/it]
  1%|          | 6911/569592 [5:50:58<482:51:38,  3.09s/it]
                                                           

  1%|          | 6911/569592 [5:50:58<482:51:38,  3.09s/it]
  1%|          | 6912/569592 [5:50:59<394:31:56,  2.52s/it]
                                                           

  1%|          | 6912/569592 [5:50:59<394:31:56,  2.52s/it]
  1%|          | 6913/569592 [5:51:02<427:53:16,  2.74s/it]
                                                           

  1%|          | 6913/569592 [5:51:02<427:53:16,  2.74s/it]
  1%|          | 6914/569592 [5:51:03<345:02:50,  2.21s/it]
                                                           

  1%|          | 6914/569592 [5:51:03<345:02:50,  2.21s/it]
  1%|          | 6915/569592 [5:51:04<285:52:45,  1.83s/it]
                                                           

  1%|          | 6915/569592 [5:51:04<285:52:45,  1.83s/it]
  1%|          | 6916/569592 [5:51:07<341:43:53,  2.19s/it]
                                                           

  1%|          | 6916/569592 [5:51:07<341:43:53,  2.19s/it]
  1%|          | 6917/569592 [5:51:10<388:41:35,  2.49s/it]
                                                           

  1%|          | 6917/569592 [5:51:10<388:41:35,  2.49s/it]
  1%|          | 6918/569592 [5:51:11<318:16:46,  2.04s/it]
                                                           

  1%|          | 6918/569592 [5:51:11<318:16:46,  2.04s/it]
  1%|          | 6919/569592 [5:51:12<269:01:10,  1.72s/it]
                                                           

  1%|          | 6919/569592 [5:51:12<269:01:10,  1.72s/it]
  1%|          | 6920/569592 [5:51:17<424:55:08,  2.72s/it]
                                                           

  1%|          | 6920/569592 [5:51:17<424:55:08,  2.72s/it]
  1%|          | 6921/569592 [5:51:21<453:09:53,  2.90s/it]
                                                           

  1%|          | 6921/569592 [5:51:21<453:09:53,  2.90s/it]
  1%|          | 6922/569592 [5:51:22<362:48:32,  2.32s/it]
                                                           

  1%|          | 6922/569592 [5:51:22<362:48:32,  2.32s/it]
  1%|          | 6923/569592 [5:51:23<299:50:57,  1.92s/it]
                                                           

  1%|          | 6923/569592 [5:51:23<299:50:57,  1.92s/it]
  1%|          | 6924/569592 [5:51:28<445:58:43,  2.85s/it]
                                                           

  1%|          | 6924/569592 [5:51:28<445:58:43,  2.85s/it]
  1%|          | 6925/569592 [5:51:32<497:38:35,  3.18s/it]
                                                           

  1%|          | 6925/569592 [5:51:32<497:38:35,  3.18s/it]
  1%|          | 6926/569592 [5:51:33<392:49:41,  2.51s/it]
                                                           

  1%|          | 6926/569592 [5:51:33<392:49:41,  2.51s/it]
  1%|          | 6927/569592 [5:51:37<461:14:07,  2.95s/it]
                                                           

  1%|          | 6927/569592 [5:51:37<461:14:07,  2.95s/it]
  1%|          | 6928/569592 [5:51:40<489:22:13,  3.13s/it]
                                                           

  1%|          | 6928/569592 [5:51:40<489:22:13,  3.13s/it]
  1%|          | 6929/569592 [5:51:44<531:59:41,  3.40s/it]
                                                           

  1%|          | 6929/569592 [5:51:44<531:59:41,  3.40s/it]
  1%|          | 6930/569592 [5:51:45<416:08:22,  2.66s/it]
                                                           

  1%|          | 6930/569592 [5:51:45<416:08:22,  2.66s/it]
  1%|          | 6931/569592 [5:51:46<341:12:00,  2.18s/it]
                                                           

  1%|          | 6931/569592 [5:51:46<341:12:00,  2.18s/it]
  1%|          | 6932/569592 [5:51:50<421:00:19,  2.69s/it]
                                                           

  1%|          | 6932/569592 [5:51:50<421:00:19,  2.69s/it]
  1%|          | 6933/569592 [5:51:53<445:45:02,  2.85s/it]
                                                           

  1%|          | 6933/569592 [5:51:53<445:45:02,  2.85s/it]
  1%|          | 6934/569592 [5:51:58<536:25:11,  3.43s/it]
                                                           

  1%|          | 6934/569592 [5:51:58<536:25:11,  3.43s/it]
  1%|          | 6935/569592 [5:52:02<550:08:59,  3.52s/it]
                                                           

  1%|          | 6935/569592 [5:52:02<550:08:59,  3.52s/it]
  1%|          | 6936/569592 [5:52:06<577:30:47,  3.70s/it]
                                                           

  1%|          | 6936/569592 [5:52:06<577:30:47,  3.70s/it]
  1%|          | 6937/569592/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 [5:52:10<610:56:14,  3.91s/it]
                                                           

  1%|          | 6937/569592 [5:52:10<610:56:14,  3.91s/it]
  1%|          | 6938/569592 [5:52:14<585:37:27,  3.75s/it]
                                                           

  1%|          | 6938/569592 [5:52:14<585:37:27,  3.75s/it]
  1%|          | 6939/569592 [5:52:15<453:02:50,  2.90s/it]
                                                           

  1%|          | 6939/569592 [5:52:15<453:02:50,  2.90s/it]
  1%|          | 6940/569592 [5:52:18<492:07:14,  3.15s/it]
                                                           

  1%|          | 6940/569592 [5:52:18<492:07:14,  3.15s/it]
  1%|          | 6941/569592 [5:52:23<576:40:44,  3.69s/it]
                                                           

  1%|          | 6941/569592 [5:52:23<576:40:44,  3.69s/it]
  1%|          | 6942/569592 [5:52:24<446:50:28,  2.86s/it]
                                                           

  1%|          | 6942/569592 [5:52:24<446:50:28,  2.86s/it]
  1%|          | 6943/569592 [5:52:28<486:31:38,  3.11s/it]
                                                           

  1%|          | 6943/569592 [5:52:28<486:31:38,  3.11s/it]
  1%|          | 6944/569592 [5:52:31<504:47:23,  3.23s/it]
                                                           

  1%|          | 6944/569592 [5:52:31<504:47:23,  3.23s/it]
  1%|          | 6945/569592 [5:52:36<551:17:24,  3.53s/it]
                                                           

  1%|          | 6945/569592 [5:52:36<551:17:24,  3.53s/it]
  1%|          | 6946/569592 [5:52:39<557:01:02,  3.56s/it]
                                                           

  1%|          | 6946/569592 [5:52:39<557:01:02,  3.56s/it]
  1%|          | 6947/569592 [5:52:43<574:54:01,  3.68s/it]
                                                           

  1%|          | 6947/569592 [5:52:43<574:54:01,  3.68s/it]
  1%|          | 6948/569592 [5:52:46<554:00:04,  3.54s/it]
                                                           

  1%|          | 6948/569592 [5:52:46<554:00:04,  3.54s/it]
  1%|          | 6949/569592 [5:52:50<541:41:42,  3.47s/it]
                                                           

  1%|          | 6949/569592 [5:52:50<541:41:42,  3.47s/it]
  1%|          | 6950/569592 [5:52:54<591:59:08,  3.79s/it]
                                                           

  1%|          | 6950/569592 [5:52:54<591:59:08,  3.79s/it]
  1%|          | 6951/569592 [5:52:59<639:07:27,  4.09s/it]
                                                           

  1%|          | 6951/569592 [5:52:59<639:07:27,  4.09s/it]
  1%|          | 6952/569592 [5:53:02<588:55:02,  3.77s/it]
                                                           

  1%|          | 6952/569592 [5:53:02<588:55:02,  3.77s/it]
  1%|          | 6953/569592 [5:53:06<609:06:02,  3.90s/it]
                                                           

  1%|          | 6953/569592 [5:53:06<609:06:02,  3.90s/it]
  1%|          | 6954/569592 [5:53:10<606:19:36,  3.88s/it]
                                                           

  1%|          | 6954/569592 [5:53:10<606:19:36,  3.88s/it]
  1%|          | 6955/569592 [5:53:13<572:09:34,  3.66s/it]
                                                           

  1%|          | 6955/569592 [5:53:13<572:09:34,  3.66s/it]
  1%|          | 6956/569592 [5:53:14<443:43:36,  2.84s/it]
                                                           

  1%|          | 6956/569592 [5:53:14<443:43:36,  2.84s/it]
  1%|          | 6957/569592 [5:53:18<488:14:43,  3.12s/it]
                                                           

  1%|          | 6957/569592 [5:53:18<488:14:43,  3.12s/it]
  1%|          | 6958/569592 [5:53:19<388:12:13,  2.48s/it]
                                                           

  1%|          | 6958/569592 [5:53:19<388:12:13,  2.48s/it]
  1%|          | 6959/569592 [5:53:23<444:30:45,  2.84s/it]
                                                           

  1%|          | 6959/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/569592 [5:53:23<444:30:45,  2.84s/it]
  1%|          | 6960/569592 [5:53:26<463:24:26,  2.97s/it]
                                                           

  1%|          | 6960/569592 [5:53:26<463:24:26,  2.97s/it]
  1%|          | 6961/569592 [5:53:29<487:29:29,  3.12s/it]
                                                           

  1%|          | 6961/569592 [5:53:29<487:29:29,  3.12s/it]
  1%|          | 6962/569592 [5:53:32<488:52:06,  3.13s/it]
                                                           

  1%|          | 6962/569592 [5:53:33<488:52:06,  3.13s/it]
  1%|          | 6963/569592 [5:53:37<565:15:03,  3.62s/it]
                                                           

  1%|          | 6963/569592 [5:53:37<565:15:03,  3.62s/it]
  1%|          | 6964/569592 [5:53:38<441:05:37,  2.82s/it]
                                                           

  1%|          | 6964/569592 [5:53:38<441:05:37,  2.82s/it]
  1%|          | 6965/569592 [5:53:42<487:25:44,  3.12s/it]
                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                       

  1%|          | 6965/569592 [5:53:42<487:25:44,  3.12s/it]
  1%|          | 6966/569592 [5:53:47<558:00:28,  3.57s/it]
                                                           

  1%|          | 6966/569592 [5:53:47<558:00:28,  3.57s/it]
  1%|          | 6967/569592 [5:53:50<549:47:32,  3.52s/it]
                                                           

  1%|          | 6967/569592 [5:53:50<549:47:32,  3.52s/it]
  1%|          | 6968/569592 [5:53:53<530:20:53,  3.39s/it]
                                                           

  1%|          | 6968/569592 [5:53:53<530:20:53,  3.39s/it]
  1%|          | 6969/569592 [5:53:57<570:12:51,  3.65s/it]
                                                           

  1%|          | 6969/569592 [5:53:57<570:12:51,  3.65s/it]
  1%|          | 6970/569592 [5:54:00<543:06:20,  3.48s/it]
                                                           

  1%|          | 6970/569592 [5:54:00<543:06:20,  3.48s/it]
  1%|          | 6971/569592 [5:54:05<612:29:14,  3.92s/it]
                                                           

  1%|          | 6971/569592 [5:54:05<612:29:14,  3.92s/it]
  1%|          | 6972/569592 [5:54:08<571:29:16,  3.66s/it]
                                                           

  1%|          | 6972/569592 [5:54:08<571:29:16,  3.66s/it]
  1%|          | 6973/569592 [5:54:12<570:03:58,  3.65s/it]
                                                           

  1%|          | 6973/569592 [5:54:12<570:03:58,  3.65s/it]
  1%|          | 6974/569592 [5:54:15<555:18:59,  3.55s/it]
                                                           

  1%|          | 6974/569592 [5:54:15<555:18:59,  3.55s/it]
  1%|          | 6975/569592 [5:54:20<582:57:33,  3.73s/it]
                                                           

  1%|          | 6975/569592 [5:54:20<582:57:33,  3.73s/it]
  1%|          | 6976/569592 [5:54:23<567:10:08,  3.63s/it]
                                                           

  1%|          | 6976/569592 [5:54:23<567:10:08,  3.63s/it]
  1%|          | 6977/569592 [5:54:26<537:58:46,  3.44s/it]
                                                           

  1%|          | 6977/569592 [5:54:26<537:58:46,  3.44s/it]
  1%|          | 6978/569592 [5:54:29<533:24:34,  3.41s/it]
                                                           

  1%|          | 6978/569592 [5:54:29<533:24:34,  3.41s/it]
  1%|          | 6979/569592 [5:54:30<417:33:39,  2.67s/it]
                                                           

  1%|          | 6979/569592 [5:54:30<417:33:39,  2.67s/it]
  1%|          | 6980/569592 [5:54:33<441:25:00,  2.82s/it]
                                                           

  1%|          | 6980/569592 [5:54:33<441:25:00,  2.82s/it]
  1%|          | 6981/569592 [5:54:37<466:38:36,  2.99s/it]
                                                           

  1%|          | 6981/569592 [5:54:37<466:38:36,  2.99s/it]
  1%|          | 6982/569592 [5:54:38<371:06:59,  2.37s/it]
                                                           

  1%|          | 6982/569592 [5:54:38<371:06:59,  2.37s/it]
  1%|          | 6983/569592 [5:54:39<304:29:47,  1.95s/it]
                                                           

  1%|          | 6983/569592 [5:54:39<304:29:47,  1.95s/it]
  1%|          | 6984/569592 [5:54:42<371:45:58,  2.38s/it]
                                                           

  1%|          | 6984/569592 [5:54:42<371:45:58,  2.38s/it]
  1%|          | 6985/569592 [5:54:46<446:15:21,  2.86s/it]
                                                           

  1%|          | 6985/569592 [5:54:46<446:15:21,  2.86s/it]
  1%|          | 6986/569592 [5:54:50<478:30:38,  3.06s/it]
                                                           

  1%|          | 6986/569592 [5:54:50<478:30:38,  3.06s/it]
  1%|          | 6987/569592 [5:54:51<380:14:02,  2.43s/it]
                                                           

  1%|          | 6987/569592 [5:54:51<380:14:02,  2.43s/it]
  1%|          | 6988/569592 [5:54:52<325:10:14,  2.08s/it]
                                                           

  1%|          | 6988/569592 [5:54:52<325:10:14,  2.08s/it]
  1%|          | 6989/569592 [5:54:53<272:51:59,  1.75s/it]
                                                           

  1%|          | 6989/569592 [5:54:53<272:51:59,  1.75s/it]
  1%|          | 6990/569592 [5:54:54<236:36:15,  1.51s/it]
                                                           

  1%|          | 6990/569592 [5:54:54<236:36:15,  1.51s/it]
  1%|          | 6991/569592 [5:54:55<211:14:24,  1.35s/it]
                                                           

  1%|          | 6991/569592 [5:54:55<211:14:24,  1.35s/it]
  1%|          | 6992/569592 [5:54:58<310:01:43,  1.98s/it]
                                                           

  1%|          | 6992/569592 [5:54:58<310:01:43,  1.98s/it]
  1%|          | 6993/569592 [5:55:04<471:05:26,  3.01s/it]
                                                           

  1%|          | 6993/569592 [5:55:04<471:05:26,  3.01s/it]
  1%|          | 6994/569592 [5:55:05<375:31:20,  2.40s/it]
                                                           

  1%|          | 6994/569592 [5:55:05<375:31:20,  2.40s/it]
  1%|          | 6995/569592 [5:55:08<429:29:19,  2.75s/it]
                                                           

  1%|          | 6995/569592 [5:55:08<429:29:19,  2.75s/it]
  1%|          | 6996/569592 [5:55:09<345:50:12,  2.21s/it]
                                                           

  1%|          | 6996/569592 [5:55:09<345:50:12,  2.21s/it]
  1%|          | 6997/569592 [5:55:10<287:23:36,  1.84s/it]
                                                           

  1%|          | 6997/569592 [5:55:10<287:23:36,  1.84s/it]
  1%|          | 6998/569592 [5:55:13<358:51:01,  2.30s/it]
                                                           

  1%|          | 6998/569592 [5:55:13<358:51:01,  2.30s/it]
  1%|          | 6999/569592 [5:55:14<296:14:50,  1.90s/it]
                                                           

  1%|          | 6999/569592 [5:55:14<296:14:50,  1.90s/it]
  1%|          | 7000/569592 [5:55:15<252:50:54,  1.62s/it]
                                                           

  1%|          | 7000/569592 [5:55:15<252:50:54,  1.62s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-7000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-7000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-7000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-7000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-7000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-7000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-6000] due to args.save_total_limit

  1%|          | 7001/569592 [5:57:15<5781:16:34, 36.99s/it]
                                                            

  1%|          | 7001/569592 [5:57:15<5781:16:34, 36.99s/it]
  1%|          | 7002/569592 [5:57:16<4090:12:14, 26.17s/it]
                                                            

  1%|          | 7002/569592 [5:57:16<4090:12:14, 26.17s/it]
  1%|          | 7003/569592 [5:57:17<2908:40:18, 18.61s/it]
                                                            

  1%|          | 7003/569592 [5:57:17<2908:40:18, 18.61s/it]
  1%|          | 7004/569592 [5:57:18<2087:21:36, 13.36s/it]
                                                            

  1%|          | 7004/569592 [5:57:18<2087:21:36, 13.36s/it]
  1%|          | 7005/569592 [5:57:19<1510:34:17,  9.67s/it]
                                                            

  1%|          | 7005/569592 [5:57:19<1510:34:17,  9.67s/it]
  1%|          | 7006/569592 [5:57:20<1104:37:10,  7.07s/it]
                                          /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                  

  1%|          | 7006/569592 [5:57:20<1104:37:10,  7.07s/it]
  1%|          | 7007/569592 [5:57:21<818:57:13,  5.24s/it] 
                                                           

  1%|          | 7007/569592 [5:57:21<818:57:13,  5.24s/it]
  1%|          | 7008/569592 [5:57:25<760:29:52,  4.87s/it]
                                                           

  1%|          | 7008/569592 [5:57:25<760:29:52,  4.87s/it]
  1%|          | 7009/569592 [5:57:26<586:30:10,  3.75s/it]
                                                           

  1%|          | 7009/569592 [5:57:26<586:30:10,  3.75s/it]
  1%|          | 7010/569592 [5:57:29<570:11:35,  3.65s/it]
                                                           

  1%|          | 7010/569592 [5:57:29<570:11:35,  3.65s/it]
  1%|          | 7011/569592 [5:57:33<563:06:01,  3.60s/it]
                                                           

  1%|          | 7011/569592 [5:57:33<563:06:01,  3.60s/it]
  1%|          | 7012/569592 [5:57:37<589:34:04,  3.77s/it]
                                                           

  1%|          | 7012/569592 [5:57:37<589:34:04,  3.77s/it]
  1%|          | 7013/569592 [5:57:38<474:16:25,  3.03s/it]
                                                           

  1%|          | 7013/569592 [5:57:38<474:16:25,  3.03s/it]
  1%|          | 7014/569592 [5:57:44<574:41:11,  3.68s/it]
                                                           

  1%|          | 7014/569592 [5:57:44<574:41:11,  3.68s/it]
  1%|          | 7015/569592 [5:57:45<450:00:48,  2.88s/it]
                                                           

  1%|          | 7015/569592 [5:57:45<450:00:48,  2.88s/it]
  1%|          | 7016/569592 [5:57:46<362:51:33,  2.32s/it]
                                                           

  1%|          | 7016/569592 [5:57:46<362:51:33,  2.32s/it]
  1%|          | 7017/569592 [5:57:47<298:32:59,  1.91s/it]
                                                           

  1%|          | 7017/569592 [5:57:47<298:32:59,  1.91s/it]
  1%|          | 7018/569592 [5:57:49<325:10:37,  2.08s/it]
                                                           

  1%|          | 7018/569592 [5:57:49<325:10:37,  2.08s/it]
  1%|          | 7019/569592 [5:57:53<397:54:59,  2.55s/it]
                                                           

  1%|          | 7019/569592 [5:57:53<397:54:59,  2.55s/it]
  1%|          | 7020/569592 [5:57:56<452:30:37,  2.90s/it]
                                                           

  1%|          | 7020/569592 [5:57:56<452:30:37,  2.90s/it]
  1%|          | 7021/569592 [5:58:00<502:14:39,  3.21s/it]
                                                           

  1%|          | 7021/569592 [5:58:00<502:14:39,  3.21s/it]
  1%|          | 7022/569592 [5:58:01<400:21:37,  2.56s/it]
                                                           

  1%|          | 7022/569592 [5:58:01<400:21:37,  2.56s/it]
  1%|          | 7023/569592 [5:58:02<325:37:56,  2.08s/it]
                                                           

  1%|          | 7023/569592 [5:58:02<325:37:56,  2.08s/it]
  1%|          | 7024/569592 [5:58:03<271:42:52,  1.74s/it]
                                                           

  1%|          | 7024/569592 [5:58:03<271:42:52,  1.74s/it]
  1%|          | 7025/569592 [5:58:05<276:16:03,  1.77s/it]
                                                           

  1%|          | 7025/569592 [5:58:05<276:16:03,  1.77s/it]
  1%|          | 7026/569592 [5:58:09<394:32:19,  2.52s/it]
                                                           

  1%|          | 7026/569592 [5:58:09<394:32:19,  2.52s/it]
  1%|          | 7027/569592 [5:58:14<468:20:47,  3.00s/it]
                                                           

  1%|          | 7027/569592 [5:58:14<468:20:47,  3.00s/it]
  1%|          | 7028/569592 [5:58:15<374:02:06,  2.39s/it]
                                                           

  1%|          | 7028/569592 [5:58:15<374:02:06,  2.39s/it]
  1%|          | 7029/569592 [5:58:19<447:43:06,  2.87s/it]
                                                           

  1%|          | 7029/569592 [5:58:19<447:43:06,  2.87s/it]
  1%|          | 7030/569592 [5:58:20<359:21:33,  2.30s/it]
                                                           

  1%|          | 7030/569592 [5:58:20<359:21:33,  2.30s/it]
  1%|          | 7031/569592 [5:58:20<295:41:18,  1.89s/it]
                                                           

  1%|          | 7031/569592 [5:58:20<295:41:18,  1.89s/it]
  1%|          | 7032/569592 [5:58:23<310:30:32,  1.99s/it]
                                                           

  1%|          | 7032/569592 [5:58:23<310:30:32,  1.99s/it]
  1%|          | 7033/569592 [5:58:26<353:08:25,  2.26s/it]
                                                           

  1%|          | 7033/569592 [5:58:26<353:08:25,  2.26s/it]
  1%|          | 7034/569592 [5:58:30<463:51:46,  2.97s/it]
                                                           

  1%|          | 7034/569592 [5:58:30<463:51:46,  2.97s/it]
  1%|          | 7035/569592 [5:58:34<510:07:39,  3.26s/it]
                                                           

  1%|          | 7035/569592 [5:58:34<510:07:39,  3.26s/it]
  1%|          | 7036/569592 [5:58:35<401:22:14,  2.57s/it]
                                                           

  1%|          | 7036/569592 [5:58:35<401:22:14,  2.57s/it]
  1%|          | 7037/569592 [5:58:36<328:25:26,  2.10s/it]
                                                           

  1%|          | 7037/569592 [5:58:36<328:25:26,  2.10s/it]
  1%|          | 7038/569592 [5:58:42<490:59:08,  3.14s/it]
                                                           

  1%|          | 7038/569592 [5:58:42<490:59:08,  3.14s/it]
  1%|          | 7039/569592 [5:58:43<390:14:53,  2.50s/it]
                                                           

  1%|          | 7039/569592 [5:58:43<390:14:53,  2.50s/it]
  1%|          | 7040/569592 [5:58:44<318:45:22,  2.04s/it]
                                                           

  1%|          | 7040/569592 [5:58:44<318:45:22,  2.04s/it]
  1%|          | 7041/569592 [5:58:48<413:17:47,  2.64s/it]
                                                           

  1%|          | 7041/569592 [5:58:48<413:17:47,  2.64s/it]
  1%|          | 7042/569592 [5:58:51<465:04:10,  2.98s/it]
                                                           

  1%|          | 7042/569592 [5:58:51<465:04:10,  2.98s/it]
  1%|          | 7043/569592 [5:58:56<537:29:13,  3.44s/it]
                                                           

  1%|          | 7043/569592 [5:58:56<537:29:13,  3.44s/it]
  1%|          | 7044/569592 [5:59:00<567:38:31,  3.63s/it]
                                                           

  1%|          | 7044/569592 [5:59:00<567:38:31,  3.63s/it]
  1%|          | 7045/569592 [5:59:04<592:53:09,  3.79s/it]
                                                           

  1%|          | 7045/569592 [5:59:04<592:53:09,  3.79s/it]
  1%|          | 7046/569592 [5:59:05<457:33:45,  2.93s/it]
                                                           

  1%|          | 7046/569592 [5:59:05<457:33:45,  2.93s/it]
  1%|          | 7047/569592 [5:59:09<489:10:15,  3.13s/it]
                                                           

  1%|          | 7047/569592 [5:59:09<489:10:15,  3.13s/it]
  1%|          | 7048/569592 [5:59:12<518:31:02,  3.32s/it]
                                                           

  1%|          | 7048/569592 [5:59:12<518:31:02,  3.32s/it]
  1%|          | 7049/569592 [5:59:16<537:45:40,  3.44s/it]
                                                           

  1%|          | 7049/569592 [5:59:16<537:45:40,  3.44s/it]
  1%|          | 7050/569592 [5:59:20<534:51:26,  3.42s/it]
                                                           

  1%|          | 7050/569592 [5:59:20<534:51:26,  3.42s/it]
  1%|          | 7051/569592 [5:59:24<583:16:12,  3.73s/it]
                                                           

  1%|          | 7051/569592 [5:59:24<583:16:12,  3.73s/it]
  1%|          | 7052/569592 [5:59:29<662:13:37,  4.24s/it]
                                                           

  1%|          | 7052/569592 [5:59:29<662:13:37,  4.24s/it]
  1%|          | 7053/569592 [5:59:33<611:00:17,  3.91s/it]
                                                           

  1%|          | 7053/569592 [5:59:33<611:00:17,  3.91s/it]
  1%|          | 7054/569592 [5:59:36<575:00:44,  3.68s/it]
                                                           

  1%|          | 7054/569592 [5:59:36<575:00:44,  3.68s/it]
  1%|          | 7055/569592 [5:59:40<603:58:47,  3.87s/it]
                                                           

  1%|          | 7055/569592 [5:59:40<603:58:47,  3.87s/it]
  1%|          | 7056/569592 [5:59:43<582:00:33,  3.72s/it]
                                                           

  1%|          | 7056/569592 [5:59:43<582:00:33,  3.72s/it]
  1%|          | 7057/569592 [5:59:46<546:47:47,  3.50s/it]
                                                           

  1%|          | 7057/569592 [5:59:46<546:47:47,  3.50s/it]
  1%|          | 7058/569592 [5:59:50<552:36:16,  3.54s/it]
                                                           

  1%|          | 7058/569592 [5:59:50<552:36:16,  3.54s/it]
  1%|          | 7059/569592 [5:59:53<534:18:39,  3.42s/it]
                                                           

  1%|          | 7059/569592 [5:59:53<534:18:39,  3.42s/it]
  1%|          | 7060/569592 [5:59:58<596:29:15,  3.82s/it]
                                                           

  1%|          | 7060/569592 [5:59:58<596:29:15,  3.82s/it]
  1%|          | 7061/569592 [6:00:01<582:03:24,  3.72s/it]
                                                           

  1%|          | 7061/569592 [6:00:01<582:03:24,  3.72s/it]
  1%|          | 7062/569592 [6:00:06<599:57:13,  3.84s/it]
                                                           

  1%|          | 7062/569592 [6:00:06<599:57:13,  3.84s/it]
  1%|          | 7063/569592 [6:00:09<593:11:19,  3.80s/it]
                                                           

  1%|          | 7063/569592 [6:00:09<593:11:19,  3.80s/it]
  1%|          | 7064/569592 [6:00:14<621:13:01,  3.98s/it]
                                                           

  1%|          | 7064/569592 [6:00:14<621:13:01,  3.98s/it]
  1%|          | 7065/569592 [6:00:18<661:13:20,  4.23s/it]
                                                           

  1%|          | 7065/569592 [6:00:18<661:13:20,  4.23s/it]
  1%|          | 7066/569592 [6:00:22<625:19:16,  4.00s/it]
                                                           

  1%|          | 7066/569592 [6:00:22<625:19:16,  4.00s/it]
  1%|          | 7067/569592 [6:00:26<612:13:40,  3.92s/it]
                                                           

  1%|          | 7067/569592 [6:00:26<612:13:40,  3.92s/it]
  1%|          | 7068/569592 [6:00:30<626:54:45,  4.01s/it]
                                                           

  1%|          | 7068/569592 [6:00:30<626:54:45,  4.01s/it]
  1%|          | 7069/569592 [6:00:31<481:08:54,  3.08s/it]
                                                           

  1%|          | 7069/569592 [6:00:31<481:08:54,  3.08s/it]
  1%|          | 7070/569592 [6:00:34<499:11:19,  3.19s/it]
                                                           

  1%|          | 7070/569592 [6:00:34<499:11:19,  3.19s/it]
  1%|          | 7071/569592 [6:00:38<507:19:02,  3.25s/it]
                                                           

  1%|          | 7071/569592 [6:00:38<507:19:02,  3.25s/it]
  1%|          | 7072/569592 [6:00:39<399:08:39,  2.55s/it]
                                                           

  1%|          | 7072/569592 [6:00:39<399:08:39,  2.55s/it]
  1%|          | 7073/569592 [6:00:42<441:48:10,  2.83s/it]
                                                           

  1%|          | 7073/569592 [6:00:42<441:48:10,  2.83s/it]
  1%|          | 7074/569592 [6:00:46<495:54:56,  3.17s/it]
                                                           

  1%|          | 7074/569592 [6:00:46<495:54:56,  3.17s/it]
  1%|          | 7075/569592 [6:00:49<505:17:44,  3.23s/it]
                                                           

  1%|          | 7075/569592 [6:00:49<505:17:44,  3.23s/it]
  1%|          | 7076/569592 [6:00:53<515:09:44,  3.30s/it]
                                                           

  1%|          | 7076/569592 [6:00:53<515:09:44,  3.30s/it]
  1%|          | 7077/569592 [6:00:56<514:52:36,  3.30s/it]
                                                           

  1%|          | 7077/569592 [6:00:56<514:52:36,  3.30s/it]
  1%|          | 7078/569592 [6:00:57<403:16:17,  2.58s/it]
                                                           

  1%|          | 7078/569592 [6:00:57<403:16:17,  2.58s/it]
  1%|          | 7079/569592 [6:01:01<469:10:09,  3.00s/it]
                                                           

  1%|          | 7079/569592 [6:01:01<469:10:09,  3.00s/it]
  1%|          | 7080/569592 [6:01:06<544:22:47,  3.48s/it]
                                                           

  1%|          | 7080/569592 [6:01:06<544:22:47,  3.48s/it]
  1%|          | 7081/569592 [6:01:09<551:58:27,  3.53s/it]
                                                           

  1%|          | 7081/569592 [6:01:09<551:58:27,  3.53s/it]
  1%|          | 7082/569592 [6:01:14<616:48:03,  3.95s/it]
                                                           

  1%|          | 7082/569592 [6:01:14<616:48:03,  3.95s/it]
  1%|          | 7083/569592 [6:01:17<583:56:16,  3.74s/it]
                                                           

  1%|          | 7083/569592 [6:01:17<583:56:16,  3.74s/it]
  1%|          | 7084/569592 [6:01:21<588:55:16,  3.77s/it]
                                                           

  1%|          | 7084/569592 [6:01:21<588:55:16,  3.77s/it]
  1%|          | 7085/569592 [6:01:25<569:00:28,  3.64s/it]
                                                           

  1%|          | 7085/569592 [6:01:25<569:00:28,  3.64s/it]
  1%|          | 7086/569592 [6:01:28<548:56:43,  3.51s/it]
                                                           

  1%|          | 7086/569592 [6:01:28<548:56:43,  3.51s/it]
  1%|          | 7087/569592 [6:01:31<546:50:39,  3.50s/it]
                                                           

  1%|          | 7087/569592 [6:01:31<546:50:39,  3.50s/it]
  1%|          | 7088/569592 [6:01:35<542:30:35,  3.47s/it]
                                                           

  1%|          | 7088/569592 [6:01:35<542:30:35,  3.47s/it]
  1%|          | 7089/569592 [6:01:36<421:56:38,  2.70s/it]
                                                           

  1%|          | 7089/569592 [6:01:36<421:56:38,  2.70s/it]
  1%|          | 7090/569592 [6:01:40<484:39:41,  3.10s/it]
                                                           

  1%|          | 7090/569592 [6:01:40<484:39:41,  3.10s/it]
  1%|          | 7091/569592 [6:01:43<485:26:57,  3.11s/it]
                                                           

  1%|          | 7091/569592 [6:01:43<485:26:57,  3.11s/it]
  1%|          | 7092/569592 [6:01:46<501:27:01,  3.21s/it]
                                                           

  1%|          | 7092/569592 [6:01:46<501:27:01,  3.21s/it]
  1%|          | 7093/569592 [6:01:50<512:16:26,  3.28s/it]
                                                           

  1%|          | 7093/569592 [6:01:50<512:16:26,  3.28s/it]
  1%|          | 7094/569592 [6:01:53<521:37:19,  3.34s/it]
                                                           

  1%|          | 7094/569592 [6:01:53<521:37:19,  3.34s/it]
  1%|          | 7095/569592 [6:01:54<407:57:02,  2.61s/it]
                                                           

  1%|          | 7095/569592 [6:01:54<407:57:02,  2.61s/it]
  1%|          | 7096/569592 [6:01:57<436:32:17,  2.79s/it]
                                                           

  1%|          | 7096/569592 [6:01:57<436:32:17,  2.79s/it]
  1%|          | 7097/569592 [6:02:01<461:21:35,  2.95s/it]
                                                           

  1%|          | 7097/569592 [6:02:01<461:21:35,  2.95s/it]
  1%|          | 7098/569592 [6:02:04<505:25:14,  3.23s/it]
                                                           

  1%|          | 7098/569592 [6:02:04<505:25:14,  3.23s/it]
  1%|          | 7099/569592 [6:02:05<396:17:32,  2.54s/it]
                                                           

  1%|          | 7099/569592 [6:02:05<396:17:32,  2.54s/it]
  1%|          | 7100/569592 [6:02:06<323:35:46,  2.07s/it]
                                                           

  1%|          | 7100/569592 [6:02:06<323:35:46,  2.07s/it]
  1%|          | 7101/569592 [6:02:07<273:54:03,  1.75s/it]
                                                           

  1%|          | 7101/569592 [6:02:07<273:54:03,  1.75s/it]
  1%|          | 7102/569592 [6:02:11<379:45:10,  2.43s/it]
                                                           

  1%|          | 7102/569592 [6:02:11<379:45:10,  2.43s/it]
  1%|          | 7103/569592 [6:02:12<310:37:28,  1.99s/it]
                                                           

  1%|          | 7103/569592 [6:02:12<310:37:28,  1.99s/it]
  1%|          | 7104/569592 [6:02:13<261:52:19,  1.68s/it]
                                                           

  1%|          | 7104/569592 [6:02:13<261:52:19,  1.68s/it]
  1%|          | 7105/569592 [6:02:14<227:23:09,  1.46s/it]
                                                           

  1%|          | 7105/569592 [6:02:14<227:23:09,  1.46s/it]
  1%|          | 7106/569592 [6:02:15<203:07:21,  1.30s/it]
                                                           

  1%|          | 7106/569592 [6:02:15<203:07:21,  1.30s/it]
  1%|          | 7107/569592 [6:02:19<324:31:38,  2.08s/it]
                                                           

  1%|          | 7107/569592 [6:02:19<324:31:38,  2.08s/it]
  1%|          | 7108/569592 [6:02:20<273:09:46,  1.75s/it]
                                                           

  1%|          | 7108/569592 [6:02:20<273:09:46,  1.75s/it]
  1%|          | 7109/569592 [6:02:25<443:09:52,  2.84s/it]
                                                           

  1%|          | 7109/569592 [6:02:25<443:09:52,  2.84s/it]
  1%|          | 7110/569592 [6:02:29<472:30:20,  3.02s/it]
                                                           

  1%|          | 7110/569592 [6:02:29<472:30:20,  3.02s/it]
  1%|          | 7111/569592 [6:02:30<376:11:18,  2.41s/it]
                                                           

  1%|          | 7111/569592 [6:02:30<376:11:18,  2.41s/it]
  1%|          | 7112/569592 [6:02:35<488:15:58,  3.13s/it]
                                                           

  1%|          | 7112/569592 [6:02:35<488:15:58,  3.13s/it]
  1%|          | 7113/569592 [6:02:36<387:11:34,  2.48s/it]
                                                           

  1%|          | 7113/569592 [6:02:36<387:11:34,  2.48s/it]
  1%|          | 7114/569592 [6:02:37<317:08:16,  2.03s/it]
                                                           

  1%|          | 7114/569592 [6:02:37<317:08:16,  2.03s/it]
  1%|          | 7115/569592 [6:02:38<308:37:12,  1.98s/it]
                                                           

  1%|          | 7115/569592 [6:02:38<308:37:12,  1.98s/it]
  1%|          | 7116/569592 [6:02:40<278:12:48,  1.78s/it]
                                                           

  1%|          | 7116/569592 [6:02:40<278:12:48,  1.78s/it]
  1%|          | 7117/569592 [6:02:43<336:16:33,  2.15s/it]
                                                           

  1%|          | 7117/569592 [6:02:43<336:16:33,  2.15s/it]
  1%|          | 7118/569592 [6:02:45<350:39:36,  2.24s/it]
                                                           

  1%|          | 7118/569592 [6:02:45<350:39:36,  2.24s/it]
  1%|          | 7119/569592 [6:02:49<399:53:52,  2.56s/it]
                                                           

  1%|          | 7119/569592 [6:02:49<399:53:52,  2.56s/it]
  1%|▏         | 7120/569592 [6:02:50<348:20:05,  2.23s/it]
                                                           

  1%|▏         | 7120/569592 [6:02:50<348:20:05,  2.23s/it]
  1%|▏         | 7121/569592 [6:02:53<385:19:23,  2.47s/it]
                                                           

  1%|▏         | 7121/569592 [6:02:53<385:19:23,  2.47s/it]
  1%|▏         | 7122/569592 [6:02:57<443:05:28,  2.84s/it]
                                                           

  1%|▏         | 7122/569592 [6:02:57<443:05:28,  2.84s/it]
  1%|▏         | 7123/569592 [6:03:00<472:54:32,  3.03s/it]
                                                           

  1%|▏         | 7123/569592 [6:03:00<472:54:32,  3.03s/it]
  1%|▏         | 7124/569592 [6:03:04<498:14:06,  3.19s/it]
                                                           

  1%|▏         | 7124/569592 [6:03:04<498:14:06,  3.19s/it]
  1%|▏         | 7125/569592 [6:03:05<394:01:55,  2.52s/it]
                                                           

  1%|▏         | 7125/569592 [6:03:05<394:01:55,  2.52s/it]
  1%|▏         | 7126/569592 [6:03:09<486:51:51,  3.12s/it]
                                                           

  1%|▏         | 7126/569592 [6:03:09<486:51:51,  3.12s/it]
  1%|▏         | 7127/569592 [6:03:10<385:02:02,  2.46s/it]
                                                           

  1%|▏         | 7127/569592 [6:03:10<385:02:02,  2.46s/it]
  1%|▏         | 7128/569592 [6:03:11<320:03:12,  2.05s/it]
                                                           

  1%|▏         | 7128/569592 [6:03:11<320:03:12,  2.05s/it]
  1%|▏         | 7129/569592 [6:03:12<267:51:21,  1.71s/it]
                                                           

  1%|▏         | 7129/569592 [6:03:12<267:51:21,  1.71s/it]
  1%|▏         | 7130/569592 [6:03:17<393:05:31,  2.52s/it]
                                                           

  1%|▏         | 7130/569592 [6:03:17<393:05:31,  2.52s/it]
  1%|▏         | 7131/569592 [6:03:21<461:54:35,  2.96s/it]
                                                           

  1%|▏         | 7131/569592 [6:03:21<461:54:35,  2.96s/it]
  1%|▏         | 7132/569592 [6:03:24<496:02:22,  3.17s/it]
                                                           

  1%|▏         | 7132/569592 [6:03:24<496:02:22,  3.17s/it]
  1%|▏         | 7133/569592 [6:03:28<537:20:55,  3.44s/it]
                                                           

  1%|▏         | 7133/569592 [6:03:28<537:20:55,  3.44s/it]
  1%|▏         | 7134/569592 [6:03:29<425:41:24,  2.72s/it]
                                                           

  1%|▏         | 7134/569592 [6:03:29<425:41:24,  2.72s/it]
  1%|▏         | 7135/569592 [6:03:33<461:44:48,  2.96s/it]
                                                           

  1%|▏         | 7135/569592 [6:03:33<461:44:48,  2.96s/it]
  1%|▏         | 7136/569592 [6:03:34<366:39:38,  2.35s/it]
                                                           

  1%|▏         | 7136/569592 [6:03:34<366:39:38,  2.35s/it]
  1%|▏         | 7137/569592 [6:03:35<303:52:13,  1.94s/it]
                                                           

  1%|▏         | 7137/569592 [6:03:35<303:52:13,  1.94s/it]
  1%|▏         | 7138/569592 [6:03:38<368:55:56,  2.36s/it]
                                                           

  1%|▏         | 7138/569592 [6:03:38<368:55:56,  2.36s/it]
  1%|▏         | 7139/569592 [6:03:42<421:30:59,  2.70s/it]
                                                           

  1%|▏         | 7139/569592 [6:03:42<421:30:59,  2.70s/it]
  1%|▏         | 7140/569592 [6:03:45<448:16:44,  2.87s/it]
                                                           

  1%|▏         | 7140/569592 [6:03:45<448:16:44,  2.87s/it]
  1%|▏         | 7141/569592 [6:03:46<358:24:24,  2.29s/it]
                                                           

  1%|▏         | 7141/569592 [6:03:46<358:24:24,  2.29s/it]
  1%|▏         | 7142/569592 [6:03:50<465:38:17,  2.98s/it]
                                                           

  1%|▏         | 7142/569592 [6:03:50<465:38:17,  2.98s/it]
  1%|▏         | 7143/569592 [6:03:51<372:46:40,  2.39s/it]
                                                           

  1%|▏         | 7143/569592 [6:03:51<372:46:40,  2.39s/it]
  1%|▏         | 7144/569592 [6:03:52<306:11:51,  1.96s/it]
                                                           

  1%|▏         | 7144/569592 [6:03:52<306:11:51,  1.96s/it]
  1%|▏         | 7145/569592 [6:03:54<290:41:19,  1.86s/it]
                                                           

  1%|▏         | 7145/569592 [6:03:54<290:41:19,  1.86s/it]
  1%|▏         | 7146/569592 [6:03:58<400:02:52,  2.56s/it]
                                                           

  1%|▏         | 7146/569592 [6:03:58<400:02:52,  2.56s/it]
  1%|▏         | 7147/569592 [6:04:03<494:32:38,  3.17s/it]
                                                           

  1%|▏         | 7147/569592 [6:04:03<494:32:38,  3.17s/it]
  1%|▏         | 7148/569592 [6:04:06<506:50:53,  3.24s/it]
                                                           

  1%|▏         | 7148/569592 [6:04:06<506:50:53,  3.24s/it]
  1%|▏         | 7149/569592 [6:04:07<398:16:03,  2.55s/it]
                                                           

  1%|▏         | 7149/569592 [6:04:07<398:16:03,  2.55s/it]
  1%|▏         | 7150/569592 [6:04:08<323:43:51,  2.07s/it]
                                                           

  1%|▏         | 7150/569592 [6:04:08<323:43:51,  2.07s/it]
  1%|▏         | 7151/569592 [6:04:13<448:18:44,  2.87s/it]
                                                           

  1%|▏         | 7151/569592 [6:04:13<448:18:44,  2.87s/it]
  1%|▏         | 7152/569592 [6:04:14<359:27:46,  2.30s/it]
                                                           

  1%|▏         | 7152/569592 [6:04:14<359:27/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90744918 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:46,  2.30s/it]
  1%|▏         | 7153/569592 [6:04:15<318:18:57,  2.04s/it]
                                                           

  1%|▏         | 7153/569592 [6:04:15<318:18:57,  2.04s/it]
  1%|▏         | 7154/569592 [6:04:19<381:50:28,  2.44s/it]
                                                           

  1%|▏         | 7154/569592 [6:04:19<381:50:28,  2.44s/it]
  1%|▏         | 7155/569592 [6:04:23<487:04:01,  3.12s/it]
                                                           

  1%|▏         | 7155/569592 [6:04:23<487:04:01,  3.12s/it]
  1%|▏         | 7156/569592 [6:04:27<510:23:20,  3.27s/it]
                                                           

  1%|▏         | 7156/569592 [6:04:27<510:23:20,  3.27s/it]
  1%|▏         | 7157/569592 [6:04:28<400:37:56,  2.56s/it]
                                                           

  1%|▏         | 7157/569592 [6:04:28<400:37:56,  2.56s/it]
  1%|▏         | 7158/569592 [6:04:32<461:41:00,  2.96s/it]
                     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                      

  1%|▏         | 7158/569592 [6:04:32<461:41:00,  2.96s/it]
  1%|▏         | 7159/569592 [6:04:35<481:02:57,  3.08s/it]
                                                           

  1%|▏         | 7159/569592 [6:04:35<481:02:57,  3.08s/it]
  1%|▏         | 7160/569592 [6:04:36<380:28:54,  2.44s/it]
                                                           

  1%|▏         | 7160/569592 [6:04:36<380:28:54,  2.44s/it]
  1%|▏         | 7161/569592 [6:04:40<458:19:21,  2.93s/it]
                                                           

  1%|▏         | 7161/569592 [6:04:40<458:19:21,  2.93s/it]
  1%|▏         | 7162/569592 [6:04:45<532:54:05,  3.41s/it]
                                                           

  1%|▏         | 7162/569592 [6:04:45<532:54:05,  3.41s/it]
  1%|▏         | 7163/569592 [6:04:48<546:44:46,  3.50s/it]
                                                           

  1%|▏         | 7163/569592 [6:04:48<546:44:46,  3.50s/it]
  1%|▏         | 7164/569592 [6:04:52<539:01:38,  3.45s/it]
                                                           

  1%|▏         | 7164/569592 [6:04:52<539:01:38,  3.45s/it]
  1%|▏         | 7165/569592 [6:04:55<533:28:34,  3.41s/it]
                                                           

  1%|▏         | 7165/569592 [6:04:55<533:28:34,  3.41s/it]
  1%|▏         | 7166/569592 [6:04:56<417:23:06,  2.67s/it]
                                                           

  1%|▏         | 7166/569592 [6:04:56<417:23:06,  2.67s/it]
  1%|▏         | 7167/569592 [6:04:59<452:42:47,  2.90s/it]
                                                           

  1%|▏         | 7167/569592 [6:04:59<452:42:47,  2.90s/it]
  1%|▏         | 7168/569592 [6:05:03<488:15:03,  3.13s/it]
                                                           

  1%|▏         | 7168/569592 [6:05:03<488:15:03,  3.13s/it]
  1%|▏         | 7169/569592 [6:05:07<517:55:01,  3.32s/it]
                                                           

  1%|▏         | 7169/569592 [6:05:07<517:55:01,  3.32s/it]
  1%|▏         | 7170/569592 [6:05:10<536:12:01,  3.43s/it]
                                                           

  1%|▏         | 7170/569592 [6:05:10<536:12:01,  3.43s/it]
  1%|▏         | 7171/569592 [6:05:11<417:29:47,  2.67s/it]
                                                           

  1%|▏         | 7171/569592 [6:05:11<417:29:47,  2.67s/it]
  1%|▏         | 7172/569592 [6:05:15<456:27:24,  2.92s/it]
                                                           

  1%|▏         | 7172/569592 [6:05:15<456:27:24,  2.92s/it]
  1%|▏         | 7173/569592 [6:05:16<362:53:56,  2.32s/it]
                                                           

  1%|▏         | 7173/569592 [6:05:16<362:53:56,  2.32s/it]
  1%|▏         | 7174/569592 [6:05:19<420:57:42,  2.69s/it]
                                                           

  1%|▏         | 7174/569592 [6:05:19<420:57:42,  2.69s/it]
  1%|▏         | 7175/569592 [6:05:24<524:48:21,  3.36s/it]
                                                           

  1%|▏         | 7175/569592 [6:05:24<524:48:21,  3.36s/it]
  1%|▏         | 7176/569592 [6:05:25<411:33:25,  2.63s/it]
                                                           

  1%|▏         | 7176/569592 [6:05:25<411:33:25,  2.63s/it]
  1%|▏         | 7177/569592 [6:05:29<461:36:31,  2.95s/it]
                                                           

  1%|▏         | 7177/569592 [6:05:29<461:36:31,  2.95s/it]
  1%|▏         | 7178/569592 [6:05:32<485:45:32,  3.11s/it]
                                                           

  1%|▏         | 7178/569592 [6:05:32<485:45:32,  3.11s/it]
  1%|▏         | 7179/569592 [6:05:36<509:28:02,  3.26s/it]
                                                           

  1%|▏         | 7179/569592 [6:05:36<509:28:02,  3.26s/it]
  1%|▏         | 7180/569592 [6:05:40<540:15:49,  3.46s/it]
                                                           

  1%|▏         | 7180/569592 [6:05:40<540:15:49,  3.46s/it]
  1%|▏         | 7181/569592 [6:05:45<639:26:24,  4.09s/it]
                                                           

  1%|▏         | 7181/569592 [6:05:46<639:26:24,  4.09s/it]
  1%|▏         | 7182/569592 [6:05:49<633:20:29,  4.05s/it]
                                                           

  1%|▏         | 7182/569592 [6:05:49<633:20:29,  4.05s/it]
  1%|▏         | 7183/569592 [6:05:53<588:49:53,  3.77s/it]
                                                           

  1%|▏         | 7183/569592 [6:05:53<588:49:53,  3.77s/it]
  1%|▏         | 7184/569592 [6:05:56<570:18:03,  3.65s/it]
                                                           

  1%|▏         | 7184/569592 [6:05:56<570:18:03,  3.65s/it]
  1%|▏         | 7185/569592 [6:05:59<557:23:34,  3.57s/it]
                                                           

  1%|▏         | 7185/569592 [6:05:59<557:23:34,  3.57s/it]
  1%|▏         | 7186/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95100928 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/569592 [6:06:03<544:10:37,  3.48s/it]
                                                           

  1%|▏         | 7186/569592 [6:06:03<544:10:37,  3.48s/it]
  1%|▏         | 7187/569592 [6:06:04<423:41:37,  2.71s/it]
                                                           

  1%|▏         | 7187/569592 [6:06:04<423:41:37,  2.71s/it]
  1%|▏         | 7188/569592 [6:06:07<475:40:19,  3.04s/it]
                                                           

  1%|▏         | 7188/569592 [6:06:07<475:40:19,  3.04s/it]
  1%|▏         | 7189/569592 [6:06:11<489:53:53,  3.14s/it]
                                                           

  1%|▏         | 7189/569592 [6:06:11<489:53:53,  3.14s/it]
  1%|▏         | 7190/569592 [6:06:12<392:30:59,  2.51s/it]
                                                           

  1%|▏         | 7190/569592 [6:06:12<392:30:59,  2.51s/it]
  1%|▏         | 7191/569592 [6:06:13<319:13:54,  2.04s/it]
                                                           
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  1%|▏         | 7191/569592 [6:06:13<319:13:54,  2.04s/it]
  1%|▏         | 7192/569592 [6:06:17<431:55:34,  2.76s/it]
                                                           

  1%|▏         | 7192/569592 [6:06:17<431:55:34,  2.76s/it]
  1%|▏         | 7193/569592 [6:06:22<530:50:55,  3.40s/it]
                                                           

  1%|▏         | 7193/569592 [6:06:22<530:50:55,  3.40s/it]
  1%|▏         | 7194/569592 [6:06:25<522:04:38,  3.34s/it]
                                                           

  1%|▏         | 7194/569592 [6:06:25<522:04:38,  3.34s/it]
  1%|▏         | 7195/569592 [6:06:29<545:13:32,  3.49s/it]
                                                           

  1%|▏         | 7195/569592 [6:06:29<545:13:32,  3.49s/it]
  1%|▏         | 7196/569592 [6:06:32<542:56:07,  3.48s/it]
                                                           

  1%|▏         | 7196/569592 [6:06:33<542:56:07,  3.48s/it]
  1%|▏         | 7197/569592 [6:06:36<524:36:51,  3.36s/it]
                                                           

  1%|▏         | 7197/569592 [6:06:36<524:36:51,  3.36s/it]
  1%|▏         | 7198/569592 [6:06:39<545:00:52,  3.49s/it]
                                                           

  1%|▏         | 7198/569592 [6:06:39<545:00:52,  3.49s/it]
  1%|▏         | 7199/569592 [6:06:43<542:27:58,  3.47s/it]
                                                           

  1%|▏         | 7199/569592 [6:06:43<542:27:58,  3.47s/it]
  1%|▏         | 7200/569592 [6:06:46<542:37:59,  3.47s/it]
                                                           

  1%|▏         | 7200/569592 [6:06:46<542:37:59,  3.47s/it]
  1%|▏         | 7201/569592 [6:06:50<534:00:29,  3.42s/it]
                                                           

  1%|▏         | 7201/569592 [6:06:50<534:00:29,  3.42s/it]
  1%|▏         | 7202/569592 [6:06:53<522:50:58,  3.35s/it]
                                                           

  1%|▏         | 7202/569592 [6:06:53<522:50:58,  3.35s/it]
  1%|▏         | 7203/569592 [6:06:56<523:24:50,  3.35s/it]
                                                           

  1%|▏         | 7203/569592 [6:06:56<523:24:50,  3.35s/it]
  1%|▏         | 7204/569592 [6:06:59<510:38:31,  3.27s/it]
                                                           

  1%|▏         | 7204/569592 [6:06:59<510:38:31,  3.27s/it]
  1%|▏         | 7205/569592 [6:07:02<500:35:46,  3.20s/it]
                                                           

  1%|▏         | 7205/569592 [6:07:02<500:35:46,  3.20s/it]
  1%|▏         | 7206/569592 [6:07:06<515:48:24,  3.30s/it]
                                                           

  1%|▏         | 7206/569592 [6:07:06<515:48:24,  3.30s/it]
  1%|▏         | 7207/569592 [6:07:09<526:42:40,  3.37s/it]
                                                           

  1%|▏         | 7207/569592 [6:07:09<526:42:40,  3.37s/it]
  1%|▏         | 7208/569592 [6:07:12<514:37:27,  3.29s/it]
                                                           

  1%|▏         | 7208/569592 [6:07:12<514:37:27,  3.29s/it]
  1%|▏         | 7209/569592 [6:07:16<506:34:00,  3.24s/it]
                                                           

  1%|▏         | 7209/569592 [6:07:16<506:34:00,  3.24s/it]
  1%|▏         | 7210/569592 [6:07:19<521:40:27,  3.34s/it]
                                                           

  1%|▏         | 7210/569592 [6:07:19<521:40:27,  3.34s/it]
  1%|▏         | 7211/569592 [6:07:22<522:26:54,  3.34s/it]
                                                           

  1%|▏         | 7211/569592 [6:07:22<522:26:54,  3.34s/it]
  1%|▏         | 7212/569592 [6:07:23<408:22:02,  2.61s/it]
                                                           

  1%|▏         | 7212/569592 [6:07:23<408:22:02,  2.61s/it]
  1%|▏         | 7213/569592 [6:07:27<448:18:04,  2.87s/it]
                                                           

  1%|▏         | 7213/569592 [6:07:27<448:18:04,  2.87s/it]
  1%|▏         | 7214/569592 [6:07:28<358:08:10,  2.29s/it]
                                                           

  1%|▏         | 7214/569592 [6:07:28<358:08:10,  2.29s/it]
  1%|▏         | 7215/569592 [6:07:29<296:49:32,  1.90s/it]
                                                           

  1%|▏         | 7215/569592 [6:07:29<296:49:32,  1.90s/it]
  1%|▏         | 7216/569592 [6:07:30<251:37:28,  1.61s/it]
                                                           

  1%|▏         | 7216/569592 [6:07:30<251:37:28,  1.61s/it]
  1%|▏         | 7217/569592 [6:07:31<221:03:19,  1.42s/it]
                                                           

  1%|▏         | 7217/569592 [6:07:31<221:03:19,  1.42s/it]
  1%|▏         | 7218/569592 [6:07:32<199:42:53,  1.28s/it]
                                                           

  1%|▏         | 7218/569592 [6:07:32<199:42:53,  1.28s/it]
  1%|▏         | 7219/569592 [6:07:36<367:27:10,  2.35s/it]
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (115022592 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                           

  1%|▏         | 7219/569592 [6:07:36<367:27:10,  2.35s/it]
  1%|▏         | 7220/569592 [6:07:40<433:46:18,  2.78s/it]
                                                           

  1%|▏         | 7220/569592 [6:07:40<433:46:18,  2.78s/it]
  1%|▏         | 7221/569592 [6:07:41<351:05:49,  2.25s/it]
                                                           

  1%|▏         | 7221/569592 [6:07:41<351:05:49,  2.25s/it]
  1%|▏         | 7222/569592 [6:07:42<290:10:39,  1.86s/it]
                                                           

  1%|▏         | 7222/569592 [6:07:42<290:10:39,  1.86s/it]
  1%|▏         | 7223/569592 [6:07:46<357:30:28,  2.29s/it]
                                                           

  1%|▏         | 7223/569592 [6:07:46<357:30:28,  2.29s/it]
  1%|▏         | 7224/569592 [6:07:47<306:36:12,  1.96s/it]
                                                           

  1%|▏         | 7224/569592 [6:07:47<306:36:12,  1.96s/it]
  1%|▏         | 7225/569592 [6:07:48<267:43:15,  1.71s/it]
                                                           

  1%|▏         | 7225/569592 [6:07:48<267:43:15,  1.71s/it]
  1%|▏         | 7226/569592 [6:07:51<344:24:27,  2.20s/it]
                                                           

  1%|▏         | 7226/569592 [6:07:51<344:24:27,  2.20s/it]
  1%|▏         | 7227/569592 [6:07:55<412:58:24,  2.64s/it]
                                                           

  1%|▏         | 7227/569592 [6:07:55<412:58:24,  2.64s/it]
  1%|▏         | 7228/569592 [6:07:56<363:59:52,  2.33s/it]
                                                           

  1%|▏         | 7228/569592 [6:07:56<363:59:52,  2.33s/it]
  1%|▏         | 7229/569592 [6:07:57<301:57:47,  1.93s/it]
                                                           

  1%|▏         | 7229/569592 [6:07:57<301:57:47,  1.93s/it]
  1%|▏         | 7230/569592 [6:08:02<436:32:26,  2.79s/it]
                                                           

  1%|▏         | 7230/569592 [6:08:02<436:32:26,  2.79s/it]
  1%|▏         | 7231/569592 [6:08:03<351:14:59,  2.25s/it]
                                                           

  1%|▏         | 7231/569592 [6:08:03<351:14:59,  2.25s/it]
  1%|▏         | 7232/569592 [6:08:07<415:30:39,  2.66s/it]
                                                           

  1%|▏         | 7232/569592 [6:08:07<415:30:39,  2.66s/it]
  1%|▏         | 7233/569592 [6:08:08<343:03:05,  2.20s/it]
                                                           

  1%|▏         | 7233/569592 [6:08:08<343:03:05,  2.20s/it]
  1%|▏         | 7234/569592 [6:08:11<392:11:04,  2.51s/it]
                                                           

  1%|▏         | 7234/569592 [6:08:12<392:11:04,  2.51s/it]
  1%|▏         | 7235/569592 [6:08:13<336:32:57,  2.15s/it]
                                                           

  1%|▏         | 7235/569592 [6:08:13<336:32:57,  2.15s/it]
  1%|▏         | 7236/569592 [6:08:17<439:02:17,  2.81s/it]
                                                           

  1%|▏         | 7236/569592 [6:08:17<439:02:17,  2.81s/it]
  1%|▏         | 7237/569592 [6:08:21<478:25:21,  3.06s/it]
                                                           

  1%|▏         | 7237/569592 [6:08:21<478:25:21,  3.06s/it]
  1%|▏         | 7238/569592 [6:08:23<449:45:13,  2.88s/it]
                                                           

  1%|▏         | 7238/569592 [6:08:23<449:45:13,  2.88s/it]
  1%|▏         | 7239/569592 [6:08:24<359:15:12,  2.30s/it]
                                                           

  1%|▏         | 7239/569592 [6:08:24<359:15:12,  2.30s/it]
  1%|▏         | 7240/569592 [6:08:28<444:11:43,  2.84s/it]
                                                           

  1%|▏         | 7240/569592 [6:08:28<444:11:43,  2.84s/it]
  1%|▏         | 7241/569592 [6:08:29<356:49:51,  2.28s/it]
                                                           

  1%|▏         | 7241/569592 [6:08:29<356:49:51,  2.28s/it]
  1%|▏         | 7242/569592 [6:08:32<392:11:22,  2.51s/it]
                                                           

  1%|▏         | 7242/569592 [6:08:32<392:11:22,  2.51s/it]
  1%|▏         | 7243/569592 [6:08:33<318:47:54,  2.04s/it]
                                                           

  1%|▏         | 7243/569592 [6:08:33<318:47:54,  2.04s/it]
  1%|▏         | 7244/569592 [6:08:39<487:31:05,  3.12s/it]
                                                           

  1%|▏         | 7244/569592 [6:08:39<487:31:05,  3.12s/it]
  1%|▏         | 7245/569592 [6:08:42<498:22:58,  3.19s/it]
                                                           

  1%|▏         | 7245/569592 [6:08:42<498:22:58,  3.19s/it]
  1%|▏         | 7246/569592 [6:08:46<528:30:54,  3.38s/it]
                                                           

  1%|▏         | 7246/569592 [6:08:46<528:30:54,  3.38s/it]
  1%|▏         | 7247/569592 [6:08:50<552:37:46,  3.54s/it]
                                                           

  1%|▏         | 7247/569592 [6:08:50<552:37:46,  3.54s/it]
  1%|▏         | 7248/569592 [6:08:53<558:00:31,  3.57s/it]
                                                           

  1%|▏         | 7248/569592 [6:08:53<558:00:31,  3.57s/it]
  1%|▏         | 7249/569592 [6:08:57<570:29:28,  3.65s/it]
                                                           

  1%|▏         | 7249/569592 [6:08:57<570:29:28,  3.65s/it]
  1%|▏         | 7250/569592 [6:08:58<447:20:50,  2.86s/it]
                                                           

  1%|▏         | 7250/569592 [6:08:58<447:20:50,  2.86s/it]
  1%|▏         | 7251/569592 [6:09:00<375:28:34,  2.40s/it]
                                                           

  1%|▏         | 7251/569592 [6:09:00<375:28:34,  2.40s/it]
  1%|▏         | 7252/569592 [6:09:04<484:21:26,  3.10s/it]
                                                           

  1%|▏         | 7252/569592 [6:09:04<484:21:26,  3.10s/it]
  1%|▏         | 7253/569592 [6:09:08<493:27:03,  3.16s/it]
                                                           

  1%|▏         | 7253/569592 [6:09:08<493:27:03,  3.16s/it]
  1%|▏         | 7254/569592 [6:09:09<390:58:39,  2.50s/it]
                                                           

  1%|▏         | 7254/569592 [6:09:09<390:58:39,  2.50s/it]
  1%|▏         | 7255/569592 [6:09:12<426:36:17,  2.73s/it]
                                                           

  1%|▏         | 7255/569592 [6:09:12<426:36:17,  2.73s/it]
  1%|▏         | 7256/569592 [6:09:13<345:02:01,  2.21s/it]
                                                           

  1%|▏         | 7256/569592 [6:09:13<345:02:01,  2.21s/it]
  1%|▏         | 7257/569592 [6:09:14<287:40:06,  1.84s/it]
                                                           

  1%|▏         | 7257/569592 [6:09:14<287:40:06,  1.84s/it]
  1%|▏       /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  | 7258/569592 [6:09:15<249:21:38,  1.60s/it]
                                                           

  1%|▏         | 7258/569592 [6:09:15<249:21:38,  1.60s/it]
  1%|▏         | 7259/569592 [6:09:16<219:20:08,  1.40s/it]
                                                           

  1%|▏         | 7259/569592 [6:09:16<219:20:08,  1.40s/it]
  1%|▏         | 7260/569592 [6:09:19<286:01:14,  1.83s/it]
                                                           

  1%|▏         | 7260/569592 [6:09:19<286:01:14,  1.83s/it]
  1%|▏         | 7261/569592 [6:09:22<363:45:47,  2.33s/it]
                                                           

  1%|▏         | 7261/569592 [6:09:22<363:45:47,  2.33s/it]
  1%|▏         | 7262/569592 [6:09:23<300:29:37,  1.92s/it]
                                                           

  1%|▏         | 7262/569592 [6:09:23<300:29:37,  1.92s/it]
  1%|▏         | 7263/569592 [6:09:25<277:16:22,  1.78s/it]
                                                           

  1%|▏         | 7263/569592 [6:09:25<277:16:22,  1.78s/it]
  1%|▏         | 7264/569592 [6:09:29<392:20:31,  2.51s/it]
                                                           

  1%|▏         | 7264/569592 [6:09:29<392:20:31,  2.51s/it]
  1%|▏         | 7265/569592 [6:09:30<320:09:39,  2.05s/it]
                                                           

  1%|▏         | 7265/569592 [6:09:30<320:09:39,  2.05s/it]
  1%|▏         | 7266/569592 [6:09:33<365:39:57,  2.34s/it]
                                                           

  1%|▏         | 7266/569592 [6:09:33<365:39:57,  2.34s/it]
  1%|▏         | 7267/569592 [6:09:36<428:32:02,  2.74s/it]
                                                           

  1%|▏         | 7267/569592 [6:09:36<428:32:02,  2.74s/it]
  1%|▏         | 7268/569592 [6:09:40<466:03:45,  2.98s/it]
                                                           

  1%|▏         | 7268/569592 [6:09:40<466:03:45,  2.98s/it]
  1%|▏         | 7269/569592 [6:09:44<502:46:54,  3.22s/it]
                                                           

  1%|▏         | 7269/569592 [6:09:44<502:46:54,  3.22s/it]
  1%|▏         | 7270/569592 [6:09:45<397:22:36,  2.54s/it]
                                                           

  1%|▏         | 7270/569592 [6:09:45<397:22:36,  2.54s/it]
  1%|▏         | 7271/569592 [6:09:48<439:09:24,  2.81s/it]
                                                           

  1%|▏         | 7271/569592 [6:09:48<439:09:24,  2.81s/it]
  1%|▏         | 7272/569592 [6:09:52<471:17:18,  3.02s/it]
                                                           

  1%|▏         | 7272/569592 [6:09:52<471:17:18,  3.02s/it]
  1%|▏         | 7273/569592 [6:09:55<491:51:46,  3.15s/it]
                                                           

  1%|▏         | 7273/569592 [6:09:55<491:51:46,  3.15s/it]
  1%|▏         | 7274/569592 [6:09:59<516:19:47,  3.31s/it]
                                                           

  1%|▏         | 7274/569592 [6:09:59<516:19:47,  3.31s/it]
  1%|▏         | 7275/569592 [6:10:00<406:02:33,  2.60s/it]
                                                           

  1%|▏         | 7275/569592 [6:10:00<406:02:33,  2.60s/it]
  1%|▏         | 7276/569592 [6:10:04<489:19:31,  3.13s/it]
                                                           

  1%|▏         | 7276/569592 [6:10:04<489:19:31,  3.13s/it]
  1%|▏         | 7277/569592 [6:10:07<497:45:59,  3.19s/it]
                                                           

  1%|▏         | 7277/569592 [6:10:07<497:45:59,  3.19s/it]
  1%|▏         | 7278/569592 [6:10:11<496:49:23,  3.18s/it]
                                                           

  1%|▏         | 7278/569592 [6:10:11<496:49:23,  3.18s/it]
  1%|▏         | 7279/569592 [6:10:14<521:22:36,  3.34s/it]
                                                           

  1%|▏         | 7279/569592 [6:10:14<521:22:36,  3.34s/it]
  1%|▏         | 7280/569592 [6:10:19<585:15:37,  3.75s/it]
                                                           

  1%|▏         | 7280/569592 [6:10:19<585:15:37,  3.75s/it]
  1%|▏         | 7281/569592 [6:10:22<574:19:50,  3.68s/it]
                                                           

  1%|▏         | 7281/569592 [6:10:23<574:19:50,  3.68s/it]
  1%|▏         | 7282/569592 [6:10:26<552:22:47,  3.54s/it]
                                                           

  1%|▏         | 7282/569592 [6:10:26<552:22:47,  3.54s/it]
  1%|▏         | 7283/569592 [6:10:29<535:38:31,  3.43s/it]
                                                           

  1%|▏         | 7283/569592 [6:10:29<535:38:31,  3.43s/it]
  1%|▏         | 7284/569592 [6:10:30<418:25:34,  2.68s/it]
                                                           

  1%|▏         | 7284/569592 [6:10:30<418:25:34,  2.68s/it]
  1%|▏         | 7285/569592 [6:10:36<559:33:01,  3.58s/it]
                                                           

  1%|▏         | 7285/569592 [6:10:36<559:33:01,  3.58s/it]
  1%|▏         | 7286/569592 [6:10:36<435:42:52,  2.79s/it]
                                                           

  1%|▏         | 7286/569592 [6:10:36<435:42:52,  2.79s/it]
  1%|▏         | 7287/569592 [6:10:40<474:06:06,  3.04s/it]
                                                           

  1%|▏         | 7287/569592 [6:10:40<474:06:06,  3.04s/it]
  1%|▏         | 7288/569592 [6:10:43<485:01:26,  3.11s/it]
                                                           

  1%|▏         | 7288/569592 [6:10:43<485:01:26,  3.11s/it]
  1%|▏         | 7289/569592 [6:10:44<384:47:20,  2.46s/it]
                                                           

  1%|▏         | 7289/569592 [6:10:44<384:47:20,  2.46s/it]
  1%|▏         | 7290/569592 [6:10:48<456:15:25,  2.92s/it]
                                                           

  1%|▏         | 7290/569592 [6:10:48<456:15:25,  2.92s/it]
  1%|▏         | 7291/569592 [6:10:54<595:22:27,  3.81s/it]
                                                           

  1%|▏         | 7291/569592 [6:10:54<595:22:27,  3.81s/it]
  1%|▏         | 7292/569592 [6:10:55<457:36:52,  2.93s/it]
                                                           

  1%|▏         | 7292/569592 [6:10:55<457:36:52,  2.93s/it]
  1%|▏         | 7293/569592 [6:10:59<496:20:51,  3.18s/it]
                                                           

  1%|▏         | 7293/569592 [6:10:59<496:20:51,  3.18s/it]
  1%|▏         | 7294/569592 [6:11:02<510:55:14,  3.27s/it]
                                                           

  1%|▏         | 7294/569592 [6:11:02<510:55:14,  3.27s/it]
  1%|▏         | 7295/569592 [6:11:05<507:54:23,  3.25s/it]
                                                           

  1%|▏         | 7295/569592 [6:11:06<507:54:23,  3.25s/it]
  1%|▏         | 7296/569592 [6:11:09<509:07:02,  3.26s/it]
                                                           

  1%|▏         | 7296/569592 [6:11:09<509:07:02,  3.26s/it]
  1%|▏         | 7297/569592 [6:11:12<505:01:22,  3.23s/it]
                                                           

  1%|▏         | 7297/569592 [6:11:12<505:01:22,  3.23s/it]
  1%|▏         | 7298/569592 [6:11:15<513:14:02,  3.29s/it]
                                                           

  1%|▏         | 7298/569592 [6:11:15<513:14:02,  3.29s/it]
  1%|▏         | 7299/569592 [6:11:19<509:46:57,  3.26s/it]
                                                           

  1%|▏         | 7299/569592 [6:11:19<509:46:57,  3.26s/it]
  1%|▏         | 7300/569592 [6:11:22<535:58:38,  3.43s/it]
                                                           

  1%|▏         | 7300/569592 [6:11:22<535:58:38,  3.43s/it]
  1%|▏         | 7301/569592 [6:11:26<529:04:35,  3.39s/it]
                                                           

  1%|▏         | 7301/569592 [6:11:26<529:04:35,  3.39s/it]
  1%|▏         | 7302/569592 [6:11:30<588:42:19,  3.77s/it]
                                                           

  1%|▏         | 7302/569592 [6:11:30<588:42:19,  3.77s/it]
  1%|▏         | 7303/569592 [6:11:34<570:55:50,  3.66s/it]
                                                           

  1%|▏         | 7303/569592 [6:11:34<570:55:50,  3.66s/it]
  1%|▏         | 7304/569592 [6:11:35<441:42:11,  2.83s/it]
                                                           

  1%|▏         | 7304/569592 [6:11:35<441:42:11,  2.83s/it]
  1%|▏         | 7305/569592 [6:11:38<464:52:05,  2.98s/it]
                                                           

  1%|▏         | 7305/569592 [6:11:38<464:52:05,  2.98s/it]
  1%|▏         | 7306/569592 [6:11:41<491:54:27,  3.15s/it]
                                                           

  1%|▏         | 7306/569592 [6:11:42<491:54:27,  3.15s/it]
  1%|▏         | 7307/569592 [6:11:42<389:40:10,  2.49s/it]
                                                           

  1%|▏         | 7307/569592 [6:11:42<389:40:10,  2.49s/it]
  1%|▏         | 7308/569592 [6:11:46<425:48:33,  2.73s/it]
                                                           

  1%|▏         | 7308/569592 [6:11:46<425:48:33,  2.73s/it]
  1%|▏         | 7309/569592 [6:11:50<494:11:38,  3.16s/it]
                                                           

  1%|▏         | 7309/569592 [6:11:50<494:11:38,  3.16s/it]
  1%|▏         | 7310/569592 [6:11:53<498:45:31,  3.19s/it]
                                                           

  1%|▏         | 7310/569592 [6:11:53<498:45:31,  3.19s/it]
  1%|▏         | 7311/569592 [6:11:57<548:17:02,  3.51s/it]
                                                           

  1%|▏         | 7311/569592 [6:11:57<548:17:02,  3.51s/it]
  1%|▏         | 7312/569592 [6:12:02<581:10:42,  3.72s/it]
                                                           

  1%|▏         | 7312/569592 [6:12:02<581:10:42,  3.72s/it]
  1%|▏         | 7313/569592 [6:12:07<676:07:36,  4.33s/it]
                                                           

  1%|▏         | 7313/569592 [6:12:07<676:07:36,  4.33s/it]
  1%|▏         | 7314/569592 [6:12:11<630:18:50,  4.04s/it]
                                                           

  1%|▏         | 7314/569592 [6:12:11<630:18:50,  4.04s/it]
  1%|▏         | 7315/569592 [6:12:14<590:49:13,  3.78s/it]
                                                           

  1%|▏         | 7315/569592 [6:12:14<590:49:13,  3.78s/it]
  1%|▏         | 7316/569592 [6:12:18<588:04:30,  3.77s/it]
                                                           

  1%|▏         | 7316/569592 [6:12:18<588:04:30,  3.77s/it]
  1%|▏         | 7317/569592 [6:12:21<576:33:13,  3.69s/it]
                                                           

  1%|▏         | 7317/569592 [6:12:21<576:33:13,  3.69s/it]
  1%|▏         | 7318/569592 [6:12:24<558:40:11,  3.58s/it]
                                                           

  1%|▏         | 7318/569592 [6:12:24<558:40:11,  3.58s/it]
  1%|▏         | 7319/569592 [6:12:28<554:05:39,  3.55s/it]
                                                           

  1%|▏         | 7319/569592 [6:12:28<554:05:39,  3.55s/it]
  1%|▏         | 7320/569592 [6:12:29<431:18:34,  2.76s/it]
                                                           

  1%|▏         | 7320/569592 [6:12:29<431:18:34,  2.76s/it]
  1%|▏         | 7321/569592 [6:12:32<446:28:00,  2.86s/it]
                                                           

  1%|▏         | 7321/569592 [6:12:32<446:28:00,  2.86s/it]
  1%|▏         | 7322/569592 [6:12:35<476:11:44,  3.05s/it]
                                                           

  1%|▏         | 7322/569592 [6:12:35<476:11:44,  3.05s/it]
  1%|▏         | 7323/569592 [6:12:36<377:42:15,  2.42s/it]
                                                           

  1%|▏         | 7323/569592 [6:12:36<377:42:15,  2.42s/it]
  1%|▏         | 7324/569592 [6:12:40<442:36:01,  2.83s/it]
                                                           

  1%|▏         | 7324/569592 [6:12:40<442:36:01,  2.83s/it]
  1%|▏         | 7325/569592 [6:12:44<464:51:31,  2.98s/it]
                                                           

  1%|▏         | 7325/569592 [6:12:44<464:51:31,  2.98s/it]
  1%|▏         | 7326/569592 [6:12:45<371:39:37,  2.38s/it]
                                                           

  1%|▏         | 7326/569592 [6:12:45<371:39:37,  2.38s/it]
  1%|▏         | 7327/569592 [6:12:49<455:01:58,  2.91s/it]
                                                           

  1%|▏         | 7327/569592 [6:12:49<455:01:58,  2.91s/it]
  1%|▏         | 7328/569592 [6:12:50<366:47:03,  2.35s/it]
                                                           

  1%|▏         | 7328/569592 [6:12:50<366:47:03,  2.35s/it]
  1%|▏         | 7329/569592 [6:12:53<431:29:11,  2.76s/it]
                                                           

  1%|▏         | 7329/569592 [6:12:53<431:29:11,  2.76s/it]
  1%|▏         | 7330/569592 [6:12:54<347:14:21,  2.22s/it]
                                                           

  1%|▏         | 7330/569592 [6:12:54<347:14:21,  2.22s/it]
  1%|▏         | 7331/569592 [6:12:58<430:49:14,  2.76s/it]
                                                           

  1%|▏         | 7331/569592 [6:12:58<430:49:14,  2.76s/it]
  1%|▏         | 7332/569592 [6:12:59<348:51:46,  2.23s/it]
                                                           

  1%|▏         | 7332/569592 [6:12:59<348:51:46,  2.23s/it]
  1%|▏         | 7333/569592 [6:13:00<289:39:44,  1.85s/it]
                                                           

  1%|▏         | 7333/569592 [6:13:00<289:39:44,  1.85s/it]
  1%|▏         | 7334/569592 [6:13:01<246:51:41,  1.58s/it]
                                                           

  1%|▏         | 7334/569592 [6:13:01<246:51:41,  1.58s/it]
  1%|▏         | 7335/569592 [6:13:02<219:07:37,  1.40s/it]
                                                           

  1%|▏         | 7335/569592 [6:13:02<219:07:37,  1.40s/it]
  1%|▏         | 7336/569592 [6:13:03<196:22:51,  1.26s/it]
                                                           

  1%|▏         | 7336/569592 [6:13:03<196:22:51,  1.26s/it]
  1%|▏         | 7337/569592 [6:13:07<305:19:25,  1.95s/it]
                                                           

  1%|▏         | 7337/569592 [6:13:07<305:19:25,  1.95s/it]
  1%|▏         | 7338/569592 [6:13:08<266:37:55,  1.71s/it]
                                                           

  1%|▏         | 7338/569592 [6:13:08<266:37:55,  1.71s/it]
  1%|▏         | 7339/569592 [6:13:10<286:42:53,  1.84s/it]
                                                           

  1%|▏         | 7339/569592 [6:13:10<286:42:53,  1.84s/it]
  1%|▏         | 7340/569592 [6:13:14<380:04:21,  2.43s/it]
                                                           

  1%|▏         | 7340/569592 [6:13:14<380:04:21,  2.43s/it]
  1%|▏         | 7341/569592 [6:13:16<355:08:16,  2.27s/it]
                                                           

  1%|▏         | 7341/569592 [6:13:16<355:08:16,  2.27s/it]
  1%|▏         | 7342/569592 [6:13:17<315:03:15,  2.02s/it]
                                                           

  1%|▏         | 7342/569592 [6:13:17<315:03:15,  2.02s/it]
  1%|▏         | 7343/569592 [6:13:20<358:15:08,  2.29s/it]
                                                           

  1%|▏         | 7343/569592 [6:13:20<358:15:08,  2.29s/it]
  1%|▏         | 7344/569592 [6:13:24<414:27:03,  2.65s/it]
                                                           

  1%|▏         | 7344/569592 [6:13:24<414:27:03,  2.65s/it]
  1%|▏         | 7345/569592 [6:13:27<469:14:22,  3.00s/it]
                                                           

  1%|▏         | 7345/569592 [6:13:27<469:14:22,  3.00s/it]
  1%|▏         | 7346/569592 [6:13:28<374:37:24,  2.40s/it]
                                                         /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93035714 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  

  1%|▏         | 7346/569592 [6:13:28<374:37:24,  2.40s/it]
  1%|▏         | 7347/569592 [6:13:30<354:22:57,  2.27s/it]
                                                           

  1%|▏         | 7347/569592 [6:13:30<354:22:57,  2.27s/it]
  1%|▏         | 7348/569592 [6:13:34<429:10:30,  2.75s/it]
                                                           

  1%|▏         | 7348/569592 [6:13:34<429:10:30,  2.75s/it]
  1%|▏         | 7349/569592 [6:13:35<350:38:33,  2.25s/it]
                                                           

  1%|▏         | 7349/569592 [6:13:35<350:38:33,  2.25s/it]
  1%|▏         | 7350/569592 [6:13:39<400:10:03,  2.56s/it]
                                                           

  1%|▏         | 7350/569592 [6:13:39<400:10:03,  2.56s/it]
  1%|▏         | 7351/569592 [6:13:40<326:17:21,  2.09s/it]
                                                           

  1%|▏         | 7351/569592 [6:13:40<326:17:21,  2.09s/it]
  1%|▏         | 7352/569592 [6:13:44<419:22:06,  2.69s/it]
                                                           

  1%|▏         | 7352/569592 [6:13:44<419:22:06,  2.69s/it]
  1%|▏         | 7353/569592 [6:13:47<451:18:13,  2.89s/it]
                                                           

  1%|▏         | 7353/569592 [6:13:47<451:18:13,  2.89s/it]
  1%|▏         | 7354/569592 [6:13:48<362:56:23,  2.32s/it]
                                                           

  1%|▏         | 7354/569592 [6:13:48<362:56:23,  2.32s/it]
  1%|▏         | 7355/569592 [6:13:51<377:48:20,  2.42s/it]
                                                           

  1%|▏         | 7355/569592 [6:13:51<377:48:20,  2.42s/it]
  1%|▏         | 7356/569592 [6:13:54<417:39:45,  2.67s/it]
                                                           

  1%|▏         | 7356/569592 [6:13:54<417:39:45,  2.67s/it]
  1%|▏         | 7357/569592 [6:13:57<445:24:18,  2.85s/it]
                                                           

  1%|▏ /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
        | 7357/569592 [6:13:57<445:24:18,  2.85s/it]
  1%|▏         | 7358/569592 [6:14:02<520:15:04,  3.33s/it]
                                                           

  1%|▏         | 7358/569592 [6:14:02<520:15:04,  3.33s/it]
  1%|▏         | 7359/569592 [6:14:03<409:35:04,  2.62s/it]
                                                           

  1%|▏         | 7359/569592 [6:14:03<409:35:04,  2.62s/it]
  1%|▏         | 7360/569592 [6:14:05<381:33:05,  2.44s/it]
                                                           

  1%|▏         | 7360/569592 [6:14:05<381:33:05,  2.44s/it]
  1%|▏         | 7361/569592 [6:14:08<421:41:51,  2.70s/it]
                                                           

  1%|▏         | 7361/569592 [6:14:08<421:41:51,  2.70s/it]
  1%|▏         | 7362/569592 [6:14:09<358:58:54,  2.30s/it]
                                                           

  1%|▏         | 7362/569592 [6:14:09<358:58:54,  2.30s/it]
  1%|▏         | 7363/569592 [6:14:13<432:11:12,  2.77s/it]
                                                           

  1%|▏         | 7363/569592 [6:14:13<432:11:12,  2.77s/it]
  1%|▏         | 7364/569592 [6:14:18<538:34:21,  3.45s/it]
                                                           

  1%|▏         | 7364/569592 [6:14:18<538:34:21,  3.45s/it]
  1%|▏         | 7365/569592 [6:14:22<547:41:18,  3.51s/it]
                                                           

  1%|▏         | 7365/569592 [6:14:22<547:41:18,  3.51s/it]
  1%|▏         | 7366/569592 [6:14:25<541:47:42,  3.47s/it]
                                                           

  1%|▏         | 7366/569592 [6:14:25<541:47:42,  3.47s/it]
  1%|▏         | 7367/569592 [6:14:30<608:11:22,  3.89s/it]
                                                           

  1%|▏         | 7367/569592 [6:14:30<608:11:22,  3.89s/it]
  1%|▏         | 7368/569592 [6:14:33<571:45:36,  3.66s/it]
                                                           

  1%|▏         | 7368/569592 [6:14:33<571:45:36,  3.66s/it]
  1%|▏         | 7369/569592 [6:14:34<444:02:04,  2.84s/it]
                                                           

  1%|▏         | 7369/569592 [6:14:34<444:02:04,  2.84s/it]
  1%|▏         | 7370/569592 [6:14:35<357:44:55,  2.29s/it]
                                                           

  1%|▏         | 7370/569592 [6:14:35<357:44:55,  2.29s/it]
  1%|▏         | 7371/569592 [6:14:36<296:15:05,  1.90s/it]
                                                           

  1%|▏         | 7371/569592 [6:14:36<296:15:05,  1.90s/it]
  1%|▏         | 7372/569592 [6:14:37<251:04:54,  1.61s/it]
                                                           

  1%|▏         | 7372/569592 [6:14:37<251:04:54,  1.61s/it]
  1%|▏         | 7373/569592 [6:14:38<221:28:11,  1.42s/it]
                                                           

  1%|▏         | 7373/569592 [6:14:38<221:28:11,  1.42s/it]
  1%|▏         | 7374/569592 [6:14:42<316:30:58,  2.03s/it]
                                                           

  1%|▏         | 7374/569592 [6:14:42<316:30:58,  2.03s/it]
  1%|▏         | 7375/569592 [6:14:43<267:28:26,  1.71s/it]
                                                           

  1%|▏         | 7375/569592 [6:14:43<267:28:26,  1.71s/it]
  1%|▏         | 7376/569592 [6:14:45<292:22:45,  1.87s/it]
                                                           

  1%|▏         | 7376/569592 [6:14:45<292:22:45,  1.87s/it]
  1%|▏         | 7377/569592 [6:14:47<317:20:02,  2.03s/it]
                                                           

  1%|▏         | 7377/569592 [6:14:47<317:20:02,  2.03s/it]
  1%|▏         | 7378/569592 [6:14:49<320:22:41,  2.05s/it]
                                                           

  1%|▏         | 7378/569592 [6:14:49<320:22:41,  2.05s/it]
  1%|▏         | 7379/569592 [6:14:50<267:47:31,  1.71s/it]
                                                           

  1%|▏         | 7379/569592 [6:14:50<267:47:31,  1.71s/it]
  1%|▏         | 7380/569592 [6:14:55<431:20:31,  2.76s/it]
                                                           

  1%|▏         | 7380/569592 [6:14:55<431:20:31,  2.76s/it]
  1%|▏         | 7381/569592 [6:14:59<462:27:08,  2.96s/it]
                                                           

  1%|▏         | 7381/569592 [6:14:59<462:27:08,  2.96s/it]
  1%|▏         | 7382/569592 [6:15:03<495:42:45,  3.17s/it]
                                                           

  1%|▏         | 7382/569592 [6:15:03<495:42:45,  3.17s/it]
  1%|▏         | 7383/569592 [6:15:03<391:50:00,  2.51s/it]
                                                           

  1%|▏         | 7383/569592 [6:15:04<391:50:00,  2.51s/it]
  1%|▏         | 7384/569592 [6:15:08<478:45:24,  3.07s/it]
                                                           

  1%|▏         | 7384/569592 [6:15:08<478:45:24,  3.07s/it]
  1%|▏         | 7385/569592 [6:15:11<490:56:24,  3.14s/it]
                                                           

  1%|▏         | 7385/569592 [6:15:11<490:56:24,  3.14s/it]
  1%|▏         | 7386/569592 [6:15:12<391:15:33,  2.51s/it]
                                                           

  1%|▏         | 7386/569592 [6:15:12<391:15:33,  2.51s/it]
  1%|▏         | 7387/569592 [6:15:13<323:56:44,  2.07s/it]
                                                           

  1%|▏         | 7387/569592 [6:15:13<323:56:44,  2.07s/it]
  1%|▏         | 7388/569592 [6:15:17<403:41:32,  2.58s/it]
                                                           

  1%|▏         | 7388/569592 [6:15:17<403:41:32,  2.58s/it]
  1%|▏         | 7389/569592 [6:15:18<328:16:07,  2.10s/it]
                                                           

  1%|▏         | 7389/569592 [6:15:18<328:16:07,  2.10s/it]
  1%|▏         | 7390/569592 [6:15:23<462:13:10,  2.96s/it]
                                                           

  1%|▏         | 7390/569592 [6:15:23<462:13:10,  2.96s/it]
  1%|▏         | 7391/569592 [6:15:27<507:41:37,  3.25s/it]
                                                           

  1%|▏         | 7391/569592 [6:15:27<507:41:37,  3.25s/it]
  1%|▏         | 7392/569592 [6:15:28<409:54:34,  2.62s/it]
                                                           

  1%|▏         | 7392/569592 [6:15:28<409:54:34,  2.62s/it]
  1%|▏         | 7393/569592 [6:15:31<446:00:05,  2.86s/it]
                                                           

  1%|▏         | 7393/569592 [6:15:31<446:00:05,  2.86s/it]
  1%|▏         | 7394/569592 [6:15:35<479:11:27,  3.07s/it]
                                                           

  1%|▏         | 7394/569592 [6:15:35<479:11:27,  3.07s/it]
  1%|▏         | 7395/569592 [6:15:39<504:10:17,  3.23s/it]
                                                           

  1%|▏         | 7395/569592 [6:15:39<504:10:17,  3.23s/it]
  1%|▏         | 7396/569592 [6:15:42<504:12:48,  3.23s/it]
                                                           

  1%|▏         | 7396/569592 [6:15:42<504:12:48,  3.23s/it]
  1%|▏         | 7397/569592 [6:15:46<544:06:02,  3.48s/it]
                                                           

  1%|▏         | 7397/569592 [6:15:46<544:06:02,  3.48s/it]
  1%|▏         | 7398/569592 [6:15:51<602:09:11,  3.86s/it]
                                                           

  1%|▏         | 7398/569592 [6:15:51<602:09:11,  3.86s/it]
  1%|▏         | 7399/569592 [6:15:54<578:02:46,  3.70s/it]
                                                           

  1%|▏         | 7399/569592 [6:15:54<578:02:46,  3.70s/it]
  1%|▏         | 7400/569592 [6:15:57<557:31:55,  3.57s/it]
                                                           

  1%|▏         | 7400/569592 [6:15:57<557:31:55,  3.57s/it]
  1%|▏         | 7401/569592 [6:15:58<446:40:52,  2.86s/it]
                                                           

  1%|▏         | 7401/569592 [6:15:58<446:40:52,  2.86s/it]
  1%|▏         | 7402/569592 [6:16:02<470:14:47,  3.01s/it]
                                                           

  1%|▏         | 7402/569592 [6:16:02<470:14:47,  3.01s/it]
  1%|▏         | 7403/569592 [6:16:07<547:34:32,  3.51s/it]
                                                           

  1%|▏         | 7403/569592 [6:16:07<547:34:32,  3.51s/it]
  1%|▏         | 7404/569592 [6:16:10<557:52:29,  3.57s/it]
                                                           

  1%|▏         | 7404/569592 [6:16:10<557:52:29,  3.57s/it]
  1%|▏         | 7405/569592 [6:16:13<540:52:24,  3.46s/it]
                                                           

  1%|▏         | 7405/569592 [6:16:13<540:52:24,  3.46s/it]
  1%|▏         | 7406/569592 [6:16:14<423:18:58,  2.71s/it]
                                                           

  1%|▏         | 7406/569592 [6:16:14<423:18:58,  2.71s/it]
  1%|▏         | 7407/569592 [6:16:18<457:54:31,  2.93s/it]
                                                           

  1%|▏         | 7407/569592 [6:16:18<457:54:31,  2.93s/it]
  1%|▏         | 7408/569592 [6:16:22<526:34:11,  3.37s/it]
                                                           

  1%|▏         | 7408/569592 [6:16:22<526:34:11,  3.37s/it]
  1%|▏         | 7409/569592 [6:16:25<517:06:07,  3.31s/it]
                                                           

  1%|▏         | 7409/569592 [6:16:25<517:06:07,  3.31s/it]
  1%|▏         | 7410/569592 [6:16:26<404:15:55,  2.59s/it]
                                                           

  1%|▏         | 7410/569592 [6:16:26<404:15:55,  2.59s/it]
  1%|▏         | 7411/569592 [6:16:30<446:37:15,  2.86s/it]
                                                           

  1%|▏         | 7411/569592 [6:16:30<446:37:15,  2.86s/it]
  1%|▏         | 7412/569592 [6:16:31<360:12:22,  2.31s/it]
                                                           

  1%|▏         | 7412/569592 [6:16:31<360:12:22,  2.31s/it]
  1%|▏         | 7413/569592 [6:16:34<417:10:20,  2.67s/it]
                                                           

  1%|▏         | 7413/569592 [6:16:34<417:10:20,  2.67s/it]
  1%|▏         | 7414/569592 [6:16:38<474:56:00,  3.04s/it]
                                                           

  1%|▏         | 7414/569592 [6:16:38<474:56:00,  3.04s/it]
  1%|▏         | 7415/569592 [6:16:42<529:13:15,  3.39s/it]
                                                           

  1%|▏         | 7415/569592 [6:16:42<529:13:15,  3.39s/it]
  1%|▏         | 7416/569592 [6:16:46<525:04:30,  3.36s/it]
                                                           

  1%|▏         | 7416/569592 [6:16:46<525:04:30,  3.36s/it]
  1%|▏         | 7417/569592 [6:16:50<544:03:38,  3.48s/it]
                                                           

  1%|▏         | 7417/569592 [6:16:50<544:03:38,  3.48s/it]
  1%|▏         | 7418/569592 [6:16:53<537:12:01,  3.44s/it]
                                                           

  1%|▏         | 7418/569592 [6:16:53<537:12:01,  3.44s/it]
  1%|▏         | 7419/569592 [6:16:57<570:21:09,  3.65s/it]
                                                           

  1%|▏         | 7419/569592 [6:16:57<570:21:09,  3.65s/it]
  1%|▏         | 7420/569592 [6:16:58<446:30:50,  2.86s/it]
                                                           

  1%|▏         | 7420/569592 [6:16:58<446:30:50,  2.86s/it]
  1%|▏         | 7421/569592 [6:17:01<472:57:58,  3.03s/it]
                                                           

  1%|▏         | 7421/569592 [6:17:01<472:57:58,  3.03s/it]
  1%|▏         | 7422/569592 [6:17:05<479:37:41,  3.07s/it]
                                                           

  1%|▏         | 7422/569592 [6:17:05<479:37:41,  3.07s/it]
  1%|▏         | 7423/569592 [6:17:08<513:41:51,  3.29s/it]
                                                           

  1%|▏         | 7423/569592 [6:17:08<513:41:51,  3.29s/it]
  1%|▏         | 7424/569592 [6:17:09<402:22:07,  2.58s/it]
                                                           

  1%|▏         | 7424/569592 [6:17:09<402:22:07,  2.58s/it]
  1%|▏         | 7425/569592 [6:17:12<428:55:18,  2.75s/it]
                                                           

  1%|▏         | 7425/569592 [6:17:12<428:55:18,  2.75s/it]
  1%|▏         | 7426/569592 [6:17:16<450:33:02,  2.89s/it]
                                                           

  1%|▏         | 7426/569592 [6:17:16<450:33:02,  2.89s/it]
  1%|▏         | 7427/569592 [6:17:20<505:57:53,  3.24s/it]
                                                           

  1%|▏         | 7427/569592 [6:17:20<505:57:53,  3.24s/it]
  1%|▏         | 7428/569592 [6:17:23<501:54:57,  3.21s/it]
                                                           

  1%|▏         | 7428/569592 [6:17:23<501:54:57,  3.21s/it]
  1%|▏         | 7429/569592 [6:17:28<586:50:00,  3.76s/it]
                                                           

  1%|▏         | 7429/569592 [6:17:28<586:50:00,  3.76s/it]
  1%|▏         | 7430/569592 [6:17:31<569:33:51,  3.65s/it]
                                                           

  1%|▏         | 7430/569592 [6:17:31<569:33:51,  3.65s/it]
  1%|▏         | 7431/569592 [6:17:35<556:44:02,  3.57s/it]
                                                           

  1%|▏         | 7431/569592 [6:17:35<556:44:02,  3.57s/it]
  1%|▏         | 7432/569592 [6:17:39<612:06:21,  3.92s/it]
                                                           

  1%|▏         | 7432/569592 [6:17:39<612:06:21,  3.92s/it]
  1%|▏         | 7433/569592 [6:17:43<612:40:42,  3.92s/it]
                                                           

  1%|▏         | 7433/569592 [6:17:43<612:40:42,  3.92s/it]
  1%|▏         | 7434/569592 [6:17:47<613:42:34,  3.93s/it]
                                                           

  1%|▏         | 7434/569592 [6:17:47<613:42:34,  3.93s/it]
  1%|▏         | 7435/569592 [6:17:51<617:55:05,  3.96s/it]
                                                           

  1%|▏         | 7435/569592 [6:17:51<617:55:05,  3.96s/it]
  1%|▏         | 7436/569592 [6:17:55<588:07:23,  3.77s/it]
                                                           

  1%|▏         | 7436/569592 [6:17:55<588:07:23,  3.77s/it]
  1%|▏         | 7437/569592 [6:17:59<594:06:54,  3.80s/it]
                                                           

  1%|▏         | 7437/569592 [6:17:59<594:06:54,  3.80s/it]
  1%|▏         | 7438/569592 [6:18:00<462:32:17,  2.96s/it]
                                                           

  1%|▏         | 7438/569592 [6:18:00<462:32:17,  2.96s/it]
  1%|▏         | 7439/569592 [6:18:03<486:49:24,  3.12s/it]
                                                           

  1%|▏         | 7439/569592 [6:18:03<486:49:24,  3.12s/it]
  1%|▏         | 7440/569592 [6:18:04<385:16:51,  2.47s/it]
                                                           

  1%|▏         | 7440/569592 [6:18:04<385:16:51,  2.47s/it]
  1%|▏         | 7441/569592 [6:18:05<315:10:59,  2.02s/it]
                                                           

  1%|▏         | 7441/569592 [6:18:05<315:10:59,  2.02s/it]
  1%|▏         | 7442/569592 [6:18:08<378:33:30,  2.42s/it]
                                                           

  1%|▏         | 7442/569592 [6:18:08<378:33:30,  2.42s/it]
  1%|▏         | 7443/569592 [6:18:12<431:04:18,  2.76s/it]
                                                           

  1%|▏         | 7443/569592 [6:18:12<431:04:18,  2.76s/it]
  1%|▏         | 7444/569592 [6:18:13<348:28:44,  2.23s/it]
                                                           

  1%|▏         | 7444/569592 [6:18:13<348:28:44,  2.23s/it]
  1%|▏         | 7445/569592 [6:18:16<401:38:11,  2.57s/it]
                                                           

  1%|▏         | 7445/569592 [6:18:16<401:38:11,  2.57s/it]
  1%|▏         | 7446/569592 [6:18:20<452:27:00,  2.90s/it]
                                                           

  1%|▏         | 7446/569592 [6:18:20<452:27:00,  2.90s/it]
  1%|▏         | 7447/569592 [6:18:21<361:53:15,  2.32s/it]
                                                           

  1%|▏         | 7447/569592 [6:18:21<361:53:15,  2.32s/it]/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(

  1%|▏         | 7448/569592 [6:18:22<297:01:18,  1.90s/it]
                                                           

  1%|▏         | 7448/569592 [6:18:22<297:01:18,  1.90s/it]
  1%|▏         | 7449/569592 [6:18:26<402:22:39,  2.58s/it]
                                                           

  1%|▏         | 7449/569592 [6:18:26<402:22:39,  2.58s/it]
  1%|▏         | 7450/569592 [6:18:27<327:45:01,  2.10s/it]
                                                           

  1%|▏         | 7450/569592 [6:18:27<327:45:01,  2.10s/it]
  1%|▏         | 7451/569592 [6:18:30<381:00:00,  2.44s/it]
                                                           

  1%|▏         | 7451/569592 [6:18:30<381:00:00,  2.44s/it]
  1%|▏         | 7452/569592 [6:18:31<311:34:33,  2.00s/it]
                                                           

  1%|▏         | 7452/569592 [6:18:31<311:34:33,  2.00s/it]
  1%|▏         | 7453/569592 [6:18:32<263:04:47,  1.68s/it]
                                                           

  1%|▏         | 7453/569592 [6:18:32<263:04:47,  1.68s/it]
  1%|▏         | 7454/569592 [6:18:36<361:55:39,  2.32s/it]
                                                           

  1%|▏         | 7454/569592 [6:18:36<361:55:39,  2.32s/it]
  1%|▏         | 7455/569592 [6:18:37<301:12:22,  1.93s/it]
                                                           

  1%|▏         | 7455/569592 [6:18:37<301:12:22,  1.93s/it]
  1%|▏         | 7456/569592 [6:18:38<270:30:04,  1.73s/it]
                                                           

  1%|▏         | 7456/569592 [6:18:38<270:30:04,  1.73s/it]
  1%|▏         | 7457/569592 [6:18:39<236:33:01,  1.51s/it]
                                                           

  1%|▏         | 7457/569592 [6:18:39<236:33:01,  1.51s/it]
  1%|▏         | 7458/569592 [6:18:44<408:16:15,  2.61s/it]
                                                           

  1%|▏         | 7458/569592 [6:18:44<408:16:15,  2.61s/it]
  1%|▏         | 7459/569592 [6:18:45<335:11:53,  2.15s/it]
                                                           

  1%|▏         | 7459/569592 [6:18:45<335:11:53,  2.15s/it]
  1%|▏         | 7460/569592 [6:18:47<296:19:54,  1.90s/it]
                                                           

  1%|▏         | 7460/569592 [6:18:47<296:19:54,  1.90s/it]
  1%|▏         | 7461/569592 [6:18:49<309:57:57,  1.99s/it]
                                                           

  1%|▏         | 7461/569592 [6:18:49<309:57:57,  1.99s/it]
  1%|▏         | 7462/569592 [6:18:54<462:25:31,  2.96s/it]
                                                           

  1%|▏         | 7462/569592 [6:18:54<462:25:31,  2.96s/it]
  1%|▏         | 7463/569592 [6:18:59<555:40:46,  3.56s/it]
                                                           

  1%|▏         | 7463/569592 [6:18:59<555:40:46,  3.56s/it]
  1%|▏         | 7464/569592 [6:19:00<437:55:34,  2.80s/it]
                                                           

  1%|▏         | 7464/569592 [6:19:00<437:55:34,  2.80s/it]
  1%|▏         | 7465/569592 [6:19:04<479:59:04,  3.07s/it]
                                                           

  1%|▏         | 7465/569592 [6:19:04<479:59:04,  3.07s/it]
  1%|▏         | 7466/569592 [6:19:05<382:01:29,  2.45s/it]
                                                           

  1%|▏         | 7466/569592 [6:19:05<382:01:29,  2.45s/it]
  1%|▏         | 7467/569592 [6:19:08<435:05:52,  2.79s/it]
                                                           

  1%|▏         | 7467/569592 [6:19:08<435:05:52,  2.79s/it]
  1%|▏         | 7468/569592 [6:19:10<356:20:02,  2.28s/it]
                                                           

  1%|▏         | 7468/569592 [6:19:10<356:20:02,  2.28s/it]
  1%|▏         | 7469/569592 [6:19:10<294:22:14,  1.89s/it]
                                                           

  1%|▏         | 7469/569592 [6:19:10<294:22:14,  1.89s/it]
  1%|▏         | 7470/569592 [6:19:14<366:39:26,  2.35s/it]
                                                           

  1%|▏         | 7470/569592 [6:19:14<366:39:26,  2.35s/it]
  1%|▏         | 7471/569592 [6:19:19<490:05:32,  3.14s/it]
                                                           

  1%|▏         | 7471/569592 [6:19:19<490:05:32,  3.14s/it]
  1%|▏         | 7472/569592 [6:19:20<387:37:33,  2.48s/it]
                                                           

  1%|▏         | 7472/569592 [6:19:20<387:37:33,  2.48s/it]
  1%|▏         | 7473/569592 [6:19:21<315:26:58,  2.02s/it]
                                                           

  1%|▏         | 7473/569592 [6:19:21<315:26:58,  2.02s/it]
  1%|▏         | 7474/569592 [6:19:26<444:32:07,  2.85s/it]
                                                           

  1%|▏         | 7474/569592 [6:19:26<444:32:07,  2.85s/it]
  1%|▏         | 7475/569592 [6:19:27<357:26:14,  2.29s/it]
                                                           

  1%|▏         | 7475/569592 [6:19:27<357:26:14,  2.29s/it]
  1%|▏         | 7476/569592 [6:19:29<350:20:08,  2.24s/it]
                                                           

  1%|▏         | 7476/569592 [6:19:29<350:20:08,  2.24s/it]
  1%|▏         | 7477/569592 [6:19:32<401:18:03,  2.57s/it]
                                                           

  1%|▏         | 7477/569592 [6:19:32<401:18:03,  2.57s/it]
  1%|▏         | 7478/569592 [6:19:35<444:10:16,  2.84s/it]
                                                           

  1%|▏         | 7478/569592 [6:19:36<444:10:16,  2.84s/it]
  1%|▏         | 7479/569592 [6:19:39<459:54:27,  2.95s/it]
                                                           

  1%|▏         | 7479/569592 [6:19:39<459:54:27,  2.95s/it]
  1%|▏         | 7480/569592 [6:19:42<493:00:02,  3.16s/it]
                                                           

  1%|▏         | 7480/569592 [6:19:42<493:00:02,  3.16s/it]
  1%|▏         | 7481/569592 [6:19:46<522:33:34,  3.35s/it]
                                                           

  1%|▏         | 7481/569592 [6:19:46<522:33:34,  3.35s/it]
  1%|▏         | 7482/569592 [6:19:47<413:13:53,  2.65s/it]
                                                           

  1%|▏         | 7482/569592 [6:19:47<413:13:53,  2.65s/it]
  1%|▏         | 7483/569592 [6:19:51<477:18:16,  3.06s/it]
                                                           

  1%|▏         | 7483/569592 [6:19:51<477:18:16,  3.06s/it]
  1%|▏         | 7484/569592 [6:19:55<496:20:04,  3.18s/it]
                                                           

  1%|▏         | 7484/569592 [6:19:55<496:20:04,  3.18s/it]
  1%|▏         | 7485/569592 [6:19:58<513:57:20,  3.29s/it]
                                                           

  1%|▏         | 7485/569592 [6:19:59<513:57:20,  3.29s/it]
  1%|▏         | 7486/569592 [6:19:59<415:47:45,  2.66s/it]
                                                           

  1%|▏         | 7486/569592 [6:19:59<415:47:45,  2.66s/it]
  1%|▏         | 7487/569592 [6:20:03<454:40:41,  2.91s/it]
                                                           

  1%|▏         | 7487/569592 [6:20:03<454:40:41,  2.91s/it]
  1%|▏         | 7488/569592 [6:20:04<363:43:38,  2.33s/it]
                                                           

  1%|▏         | 7488/569592 [6:20:04<363:43:38,  2.33s/it]
  1%|▏         | 7489/569592 [6:20:05<298:52:55,  1.91s/it]
                                                           

  1%|▏         | 7489/569592 [6:20:05<298:52:55,  1.91s/it]
  1%|▏         | 7490/569592 [6:20:06<269:50:40,  1.73s/it]
                                                           

  1%|▏         | 7490/569592 [6:20:06<269:50:40,  1.73s/it]
  1%|▏         | 7491/569592 [6:20:07<243:43:30,  1.56s/it]
                                                           

  1%|▏         | 7491/569592 [6:20:07<243:43:30,  1.56s/it]
  1%|▏         | 7492/569592 [6:20:08<218:57:52,  1.40s/it]
                                                           

  1%|▏         | 7492/569592 [6:20:08<218:57:52,  1.40s/it]
  1%|▏         | 7493/569592 [6:20:12<324:48:55,  2.08s/it]
                                                           

  1%|▏         | 7493/569592 [6:20:12<324:48:55,  2.08s/it]
  1%|▏         | 7494/569592 [6:20:16<401:42:33,  2.57s/it]
                                                           

  1%|▏         | 7494/569592 [6:20:16<401:42:33,  2.57s/it]
  1%|▏         | 7495/569592 [6:20:17<326:51:49,  2.09s/it]
                                                           

  1%|▏         | 7495/569592 [6:20:17<326:51:49,  2.09s/it]
  1%|▏         | 7496/569592 [6:20:19<328:00:57,  2.10s/it]
                                                           

  1%|▏         | 7496/569592 [6:20:19<328:00:57,  2.10s/it]
  1%|▏         | 7497/569592 [6:20:22<386:53:52,  2.48s/it]
                                                           

  1%|▏         | 7497/569592 [6:20:22<386:53:52,  2.48s/it]
  1%|▏         | 7498/569592 [6:20:25<424:10:18,  2.72s/it]
                                                           

  1%|▏         | 7498/569592 [6:20:25<424:10:18,  2.72s/it]
  1%|▏         | 7499/569592 [6:20:27<350:56:51,  2.25s/it]
                                                           

  1%|▏         | 7499/569592 [6:20:27<350:56:51,  2.25s/it]
  1%|▏         | 7500/569592 [6:20:29<382:06:44,  2.45s/it]
                                                           

  1%|▏         | 7500/569592 [6:20:29<382:06:44,  2.45s/it]
  1%|▏         | 7501/569592 [6:20:31<329:35:31,  2.11s/it]
                                                           

  1%|▏         | 7501/569592 [6:20:31<329:35:31,  2.11s/it]
  1%|▏         | 7502/569592 [6:20:35<428:16:01,  2.74s/it]
                                                           

  1%|▏         | 7502/569592 [6:20:35<428:16:01,  2.74s/it]
  1%|▏         | 7503/569592 [6:20:36<367:47:07,  2.36s/it]
  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                         

  1%|▏         | 7503/569592 [6:20:36<367:47:07,  2.36s/it]
  1%|▏         | 7504/569592 [6:20:40<411:29:30,  2.64s/it]
                                                           

  1%|▏         | 7504/569592 [6:20:40<411:29:30,  2.64s/it]
  1%|▏         | 7505/569592 [6:20:41<335:24:37,  2.15s/it]
                                                           

  1%|▏         | 7505/569592 [6:20:41<335:24:37,  2.15s/it]
  1%|▏         | 7506/569592 [6:20:48<569:48:59,  3.65s/it]
                                                           

  1%|▏         | 7506/569592 [6:20:48<569:48:59,  3.65s/it]
  1%|▏         | 7507/569592 [6:20:51<555:06:09,  3.56s/it]
                                                           

  1%|▏         | 7507/569592 [6:20:51<555:06:09,  3.56s/it]
  1%|▏         | 7508/569592 [6:20:56<613:03:32,  3.93s/it]
                                                           

  1%|▏         | 7508/569592 [6:20:56</home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93370144 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
613:03:32,  3.93s/it]
  1%|▏         | 7509/569592 [6:21:00<635:43:57,  4.07s/it]
                                                           

  1%|▏         | 7509/569592 [6:21:00<635:43:57,  4.07s/it]
  1%|▏         | 7510/569592 [6:21:04<595:05:36,  3.81s/it]
                                                           

  1%|▏         | 7510/569592 [6:21:04<595:05:36,  3.81s/it]
  1%|▏         | 7511/569592 [6:21:07<555:28:51,  3.56s/it]
                                                           

  1%|▏         | 7511/569592 [6:21:07<555:28:51,  3.56s/it]
  1%|▏         | 7512/569592 [6:21:10<556:26:47,  3.56s/it]
                                                           

  1%|▏         | 7512/569592 [6:21:10<556:26:47,  3.56s/it]
  1%|▏         | 7513/569592 [6:21:14<546:47:45,  3.50s/it]
                                                           

  1%|▏         | 7513/569592 [6:21:14<546:47:45,  3.50s/it]
  1%|▏         | 7514/569592 [6:21:17<550:18:10,  3.52s/it]
                                                           

  1%|▏         | 7514/569592 [6:21:17<550:18:10,  3.52s/it]
  1%|▏         | 7515/569592 [6:21:18<433:24:54,  2.78s/it]
                                                           

  1%|▏         | 7515/569592 [6:21:18<433:24:54,  2.78s/it]
  1%|▏         | 7516/569592 [6:21:22<461:31:40,  2.96s/it]
                                                           

  1%|▏         | 7516/569592 [6:21:22<461:31:40,  2.96s/it]
  1%|▏         | 7517/569592 [6:21:25<484:00:27,  3.10s/it]
                                                           

  1%|▏         | 7517/569592 [6:21:25<484:00:27,  3.10s/it]
  1%|▏         | 7518/569592 [6:21:29<538:29:55,  3.45s/it]
                                                           

  1%|▏         | 7518/569592 [6:21:29<538:29:55,  3.45s/it]
  1%|▏         | 7519/569592 [6:21:32<517:14:06,  3.31s/it]
                                                           

  1%|▏         | 7519/569592 [6:21:32<517:14:06,  3/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
.31s/it]
  1%|▏         | 7520/569592 [6:21:37<581:51:18,  3.73s/it]
                                                           

  1%|▏         | 7520/569592 [6:21:37<581:51:18,  3.73s/it]
  1%|▏         | 7521/569592 [6:21:40<575:39:49,  3.69s/it]
                                                           

  1%|▏         | 7521/569592 [6:21:41<575:39:49,  3.69s/it]
  1%|▏         | 7522/569592 [6:21:44<589:04:48,  3.77s/it]
                                                           

  1%|▏         | 7522/569592 [6:21:44<589:04:48,  3.77s/it]
  1%|▏         | 7523/569592 [6:21:48<566:25:47,  3.63s/it]
                                                           

  1%|▏         | 7523/569592 [6:21:48<566:25:47,  3.63s/it]
  1%|▏         | 7524/569592 [6:21:51<544:55:33,  3.49s/it]
                                                           

  1%|▏         | 7524/569592 [6:21:51<544:55:33,  3.49s/it]
  1%|▏         | 7525/569592 [6:21:54<523:44:08,  3.35s/it]
                                                           

  1%|▏         | 7525/569592 [6:21:54<523:44:08,  3.35s/it]
  1%|▏         | 7526/569592 [6:21:58<539:36:48,  3.46s/it]
                                                           

  1%|▏         | 7526/569592 [6:21:58<539:36:48,  3.46s/it]
  1%|▏         | 7527/569592 [6:21:59<422:21:12,  2.71s/it]
                                                           

  1%|▏         | 7527/569592 [6:21:59<422:21:12,  2.71s/it]
  1%|▏         | 7528/569592 [6:22:03<497:07:49,  3.18s/it]
                                                           

  1%|▏         | 7528/569592 [6:22:03<497:07:49,  3.18s/it]
  1%|▏         | 7529/569592 [6:22:07<531:14:27,  3.40s/it]
                                                           

  1%|▏         | 7529/569592 [6:22:07<531:14:27,  3.40s/it]
  1%|▏         | 7530/569592 [6:22:10<510:51:20,  3.27s/it]
                                                           

  1%|▏         | 7530/569592 [6:22:10<510:51:20,  3.27s/it]
  1%|▏         | 7531/569592 [6:22:14<556:49:04,  3.57s/it]
                                                           

  1%|▏         | 7531/569592 [6:22:14<556:49:04,  3.57s/it]
  1%|▏         | 7532/569592 [6:22:18<560:42:39,  3.59s/it]
                                                           

  1%|▏         | 7532/569592 [6:22:18<560:42:39,  3.59s/it]
  1%|▏         | 7533/569592 [6:22:19<434:15:48,  2.78s/it]
                                                           

  1%|▏         | 7533/569592 [6:22:19<434:15:48,  2.78s/it]
  1%|▏         | 7534/569592 [6:22:22<449:35:17,  2.88s/it]
                                                           

  1%|▏         | 7534/569592 [6:22:22<449:35:17,  2.88s/it]
  1%|▏         | 7535/569592 [6:22:25<490:28:51,  3.14s/it]
                                                           

  1%|▏         | 7535/569592 [6:22:25<490:28:51,  3.14s/it]
  1%|▏         | 7536/569592 [6:22:29<496:09:11,  3.18s/it]
                                                           

  1%|▏         | 7536/569592 [6:22:29<496:09:11,  3.18s/it]
  1%|▏         | 7537/569592 [6:22:33<549:17:54,  3.52s/it]
                                                           

  1%|▏         | 7537/569592 [6:22:33<549:17:54,  3.52s/it]
  1%|▏         | 7538/569592 [6:22:34<430:42:50,  2.76s/it]
                                                           

  1%|▏         | 7538/569592 [6:22:34<430:42:50,  2.76s/it]
  1%|▏         | 7539/569592 [6:22:35<344:45:48,  2.21s/it]
                                                           

  1%|▏         | 7539/569592 [6:22:35<344:45:48,  2.21s/it]
  1%|▏         | 7540/569592 [6:22:38<392:34:28,  2.51s/it]
                                                           

  1%|▏         | 7540/569592 [6:22:38<392:34:28,  2.51s/it]
  1%|▏         | 7541/569592 [6:22:43<483:57:49,  3.10s/it]
                                                           

  1%|▏         | 7541/569592 [6:22:43<483:57:49,  3.10s/it]
  1%|▏         | 7542/569592 [6:22:44<384:49:06,  2.46s/it]
                                                           

  1%|▏         | 7542/569592 [6:22:44<384:49:06,  2.46s/it]
  1%|▏         | 7543/569592 [6:22:47<417:40:37,  2.68s/it]
                                                           

  1%|▏         | 7543/569592 [6:22:47<417:40:37,  2.68s/it]
  1%|▏         | 7544/569592 [6:22:50<454:59:33,  2.91s/it]
                                                           

  1%|▏         | 7544/569592 [6:22:50<454:59:33,  2.91s/it]
  1%|▏         | 7545/569592 [6:22:54<517:29:42,  3.31s/it]
                                                           

  1%|▏         | 7545/569592 [6:22:55<517:29:42,  3.31s/it]
  1%|▏         | 7546/569592 [6:22:58<516:57:31,  3.31s/it]
                                                           

  1%|▏         | 7546/569592 [6:22:58<516:57:31,  3.31s/it]
  1%|▏         | 7547/569592 [6:23:01<526:51:32,  3.37s/it]
                                                           

  1%|▏         | 7547/569592 [6:23:01<526:51:32,  3.37s/it]
  1%|▏         | 7548/569592 [6:23:05<541:42:11,  3.47s/it]
                                                           

  1%|▏         | 7548/569592 [6:23:05<541:42:11,  3.47s/it]
  1%|▏         | 7549/569592 [6:23:09<544:25:02,  3.49s/it]
                                                           

  1%|▏         | 7549/569592 [6:23:09<544:25:02,  3.49s/it]
  1%|▏         | 7550/569592 [6:23:12<543:48:09,  3.48s/it]
                                                           

  1%|▏         | 7550/569592 [6:23:12<543:48:09,  3.48s/it]
  1%|▏         | 7551/569592 [6:23:17<600:01:39,  3.84s/it]
                                                           

  1%|▏         | 7551/569592 [6:23:17<600:01:39,  3.84s/it]
  1%|▏         | 7552/569592 [6:23:21<635:44:56,  4.07s/it]
                                                           

  1%|▏         | 7552/569592 [6:23:21<635:44:56,  4.07s/it]
  1%|▏         | 7553/569592 [6:23:25<597:40:17,  3.83s/it]
                                                           

  1%|▏         | 7553/569592 [6:23:25<597:40:17,  3.83s/it]
  1%|▏         | 7554/569592 [6:23:28<582:59:25,  3.73s/it]
                                                           

  1%|▏         | 7554/569592 [6:23:28<582:59:25,  3.73s/it]
  1%|▏         | 7555/569592 [6:23:29<451:00:55,  2.89s/it]
                                                           

  1%|▏         | 7555/569592 [6:23:29<451:00:55,  2.89s/it]
  1%|▏         | 7556/569592 [6:23:30<359:43:47,  2.30s/it]
                                                           

  1%|▏         | 7556/569592 [6:23:30<359:43:47,  2.30s/it]
  1%|▏         | 7557/569592 [6:23:34<419:47:42,  2.69s/it]
                                                           

  1%|▏         | 7557/569592 [6:23:34<419:47:42,  2.69s/it]
  1%|▏         | 7558/569592 [6:23:35<340:22:00,  2.18s/it]
                                                           

  1%|▏         | 7558/569592 [6:23:35<340:22:00,  2.18s/it]
  1%|▏         | 7559/569592 [6:23:38<403:04:28,  2.58s/it]
                                                           

  1%|▏         | 7559/569592 [6:23:38<403:04:28,  2.58s/it]
  1%|▏         | 7560/569592 [6:23:41<431:28:53,  2.76s/it]
                                                           

  1%|▏         | 7560/569592 [6:23:41<431:28:53,  2.76s/it]
  1%|▏         | 7561/569592 [6:23:45<455:52:36,  2.92s/it]
                                                           

  1%|▏         | 7561/569592 [6:23:45<455:52:36,  2.92s/it]
  1%|▏         | 7562/569592 [6:23:45<362:50:31,  2.32s/it]
                                                           

  1%|▏         | 7562/569592 [6:23:45<362:50:31,  2.32s/it]
  1%|▏         | 7563/569592 [6:23:49<411:47:39,  2.64s/it]
                                                           

  1%|▏         | 7563/569592 [6:23:49<411:47:39,  2.64s/it]
  1%|▏         | 7564/569592 [6:23:52<459:19:09,  2.94s/it]
                                                           

  1%|▏         | 7564/569592 [6:23:52<459:19:09,  2.94s/it]
  1%|▏         | 7565/569592 [6:23:53<366:03:28,  2.34s/it]
                                                           

  1%|▏         | 7565/569592 [6:23:53<366:03:28,  2.34s/it]
  1%|▏         | 7566/569592 [6:23:54<301:10:01,  1.93s/it]
                                                           

  1%|▏         | 7566/569592 [6:23:54<301:10:01,  1.93s/it]
  1%|▏         | 7567/569592 [6:23:59<406:10:16,  2.60s/it]
                                                           

  1%|▏         | 7567/569592 [6:23:59<406:10:16,  2.60s/it]
  1%|▏         | 7568/569592 [6:24:00<333:08:27,  2.13s/it]
                                                           

  1%|▏         | 7568/569592 [6:24:00<333:08:27,  2.13s/it]
  1%|▏         | 7569/569592 [6:24:01<293:01:44,  1.88s/it]
                                                           

  1%|▏         | /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100663296 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
7569/569592 [6:24:01<293:01:44,  1.88s/it]
  1%|▏         | 7570/569592 [6:24:02<249:33:34,  1.60s/it]
                                                           

  1%|▏         | 7570/569592 [6:24:02<249:33:34,  1.60s/it]
  1%|▏         | 7571/569592 [6:24:03<221:00:56,  1.42s/it]
                                                           

  1%|▏         | 7571/569592 [6:24:03<221:00:56,  1.42s/it]
  1%|▏         | 7572/569592 [6:24:07<334:21:17,  2.14s/it]
                                                           

  1%|▏         | 7572/569592 [6:24:07<334:21:17,  2.14s/it]
  1%|▏         | 7573/569592 [6:24:08<283:01:41,  1.81s/it]
                                                           

  1%|▏         | 7573/569592 [6:24:08<283:01:41,  1.81s/it]
  1%|▏         | 7574/569592 [6:24:09<244:08:00,  1.56s/it]
                                                           

  1%|▏         | 7574/569592 [6:24:09<244:08:00,  1.56s/it]
  1%|▏         | 7575/569592 [6:24:12<330:55:32,  2.12s/it]
                                                           

  1%|▏         | 7575/569592 [6:24:12<330:55:32,  2.12s/it]
  1%|▏         | 7576/569592 [6:24:15<390:35:22,  2.50s/it]
                                                           

  1%|▏         | 7576/569592 [6:24:15<390:35:22,  2.50s/it]
  1%|▏         | 7577/569592 [6:24:17<345:22:47,  2.21s/it]
                                                           

  1%|▏         | 7577/569592 [6:24:17<345:22:47,  2.21s/it]
  1%|▏         | 7578/569592 [6:24:19<325:25:52,  2.08s/it]
                                                           

  1%|▏         | 7578/569592 [6:24:19<325:25:52,  2.08s/it]
  1%|▏         | 7579/569592 [6:24:22<393:56:42,  2.52s/it]
                                                           

  1%|▏         | 7579/569592 [6:24:22<393:56:42,  2.52s/it]
  1%|▏         | 7580/569592 [6:24:26<467:11:55,  2.99s/it]
                                                           

  1%|▏         | 7580/569592 [6:24:26<467:11:55,  2.99s/it]
  1%|▏         | 7581/569592 [6:24:27<373:28:14,  2.39s/it]
                                                           

  1%|▏         | 7581/569592 [6:24:27<373:28:14,  2.39s/it]
  1%|▏         | 7582/569592 [6:24:29<349:49:55,  2.24s/it]
                                                           

  1%|▏         | 7582/569592 [6:24:29<349:49:55,  2.24s/it]
  1%|▏         | 7583/569592 [6:24:32<355:33:43,  2.28s/it]
                                                           

  1%|▏         | 7583/569592 [6:24:32<355:33:43,  2.28s/it]
  1%|▏         | 7584/569592 [6:24:35<415:24:33,  2.66s/it]
                                                           

  1%|▏         | 7584/569592 [6:24:35<415:24:33,  2.66s/it]
  1%|▏         | 7585/569592 [6:24:37<392:09:39,  2.51s/it]
                                                           

  1%|▏         | 7585/569592 [6:24:37<392:09:39,  2.51s/it]
  1%|▏         | 7586/569592 [6:24:39<357:11:12,  2.29s/it]
                                                           

  1%|▏         | 7586/569592 [6:24:39<357:11:12,  2.29s/it]
  1%|▏         | 7587/569592 [6:24:43<416:08:31,  2.67s/it]
                                                           

  1%|▏         | 7587/569592 [6:24:43<416:08:31,  2.67s/it]
  1%|▏         | 7588/569592 [6:24:45<383:38:05,  2.46s/it]
                                                           

  1%|▏         | 7588/569592 [6:24:45<383:38:05,  2.46s/it]
  1%|▏         | 7589/569592 [6:24:48<444:07:23,  2.84s/it]
                                                           

  1%|▏         | 7589/569592 [6:24:48<444:07:23,  2.84s/it]
  1%|▏         | 7590/569592 [6:24:53<507:13:17,  3.25s/it]
                                                           

  1%|▏         | 7590/569592 [6:24:53<507:13:17,  3.25s/it]
  1%|▏         | 7591/569592 [6:24:54<401:29:37,  2.57s/it]
                                                           

  1%|▏         | 7591/569592 [6:24:54<401:29:37,  2.57s/it]
  1%|▏         | 7592/569592 [6:24:55<342:48:17,  2.20s/it]
                                                           

  1%|▏         | 7592/569592 [6:24:55<342:48:17,  2.20s/it]
  1%|▏         | 7593/569592 [6:24:59<426:38:22,  2.73s/it]
                                                           

  1%|▏         | 7593/569592 [6:24:59<426:38:22,  2.73s/it]
  1%|▏         | 7594/569592 [6:25:04<526:36:30,  3.37s/it]
                                                           

  1%|▏         | 7594/569592 [6:25:04<526:36:30,  3.37s/it]
  1%|▏         | 7595/569592 [6:25:05<413:33:11,  2.65s/it]
                                                           

  1%|▏         | 7595/569592 [6:25:05<413:33:11,  2.65s/it]
  1%|▏         | 7596/569592 [6:25:08<453:59:20,  2.91s/it]
                                                           

  1%|▏         | 7596/569592 [6:25:08<453:59:20,  2.91s/it]
  1%|▏         | 7597/569592 [6:25:12<473:31:22,  3.03s/it]
                                                           

  1%|▏         | 7597/569592 [6:25:12<473:31:22,  3.03s/it]
  1%|▏         | 7598/569592 [6:25:13<388:27:24,  2.49s/it]
                                                           

  1%|▏         | 7598/569592 [6:25:13<388:27:24,  2.49s/it]
  1%|▏         | 7599/569592 [6:25:14<318:25:00,  2.04s/it]
                                                           

  1%|▏         | 7599/569592 [6:25:14<318:25:00,  2.04s/it]
  1%|▏         | 7600/569592 [6:25:17<360:11:31,  2.31s/it]
                                                           

  1%|▏         | 7600/569592 [6:25:17<360:11:31,  2.31s/it]
  1%|▏         | 7601/569592 [6:25:20<427:14:00,  2.74s/it]
                                                           

  1%|▏         | 7601/569592 [6:25:20<427:14:00,  2.74s/it]
  1%|▏         | 7602/569592 [6:25:24<461:52:24,  2.96s/it]
                                                           

  1%|▏         | 7602/569592 [6:25:24<461:52:24,  2.96s/it]
  1%|▏         | 7603/569592 [6:25:25<370:02:41,  2.37s/it]
                                                           

  1%|▏         | 7603/569592 [6:25:25<370:02:41,  2.37s/it]
  1%|▏         | 7604/569592 [6:25:28<419:36:32,  2.69s/it]
                                                           

  1%|▏         | 7604/569592 [6:25:28<419:36:32,  2.69s/it]
  1%|▏         | 7605/569592 [6:25:32<449:42:42,  2.88s/it]
                                                           

  1%|▏         | 7605/569592 [6:25:32<449:42:42,  2.88s/it]
  1%|▏         | 7606/569592 [6:25:34<420:33:27,  2.69s/it]
                                                           

  1%|▏         | 7606/569592 [6:25:34<420:33:27,  2.69s/it]
  1%|▏         | 7607/569592 [6:25:38<472:27:00,  3.03s/it]
                                                           

  1%|▏         | 7607/569592 [6:25:38<472:27:00,  3.03s/it]
  1%|▏         | 7608/569592 [6:25:39<376:23:07,  2.41s/it]
                                                           

  1%|▏         | 7608/569592 [6:25:39<376:23:07,  2.41s/it]
  1%|▏         | 7609/569592 [6:25:42<420:43:51,  2.70s/it]
                                                           

  1%|▏         | 7609/569592 [6:25:42<420:43:51,  2.70s/it]
  1%|▏         | 7610/569592 [6:25:44<371:11:46,  2.38s/it]
                                                           

  1%|▏         | 7610/569592 [6:25:44<371:11:46,  2.38s/it]
  1%|▏         | 7611/569592 [6:25:47<425:06:13,  2.72s/it]
                                                           

  1%|▏         | 7611/569592 [6:25:47<425:06:13,  2.72s/it]
  1%|▏         | 7612/569592 [6:25:48<344:32:10,  2.21s/it]
                                                           

  1%|▏         | 7612/569592 [6:25:48<344:32:10,  2.21s/it]
  1%|▏         | 7613/569592 [6:25:49<286:59:35,  1.84s/it]
                                                           

  1%|▏         | 7613/569592 [6:25:49<286:59:35,  1.84s/it]
  1%|▏         | 7614/569592 [6:25:54<402:01:53,  2.58s/it]
                                                           

  1%|▏         | 7614/569592 [6:25:54<402:01:53,  2.58s/it]
  1%|▏         | 7615/569592 [6:25:55<372:18:14,  2.38s/it]
                                                           

  1%|▏         | 7615/569592 [6:25:55<372:18:14,  2.38s/it]
  1%|▏         | 7616/569592 [6:25:56<304:16:13,  1.95s/it]
                                                           

  1%|▏         | 7616/569592 [6:25:56<304:16:13,  1.95s/it]
  1%|▏         | 7617/569592 [6:25:59<356:50:42,  2.29s/it]
                                                           

  1%|▏         | 7617/569592 [6:25:59<356:50:42,  2.29s/it]
  1%|▏         | 7618/569592 [6:26:03<406:19:17,  2.60s/it]
                                                           

  1%|▏         | 7618/569592 [6:26:03<406:19:17,  2.60s/it]
  1%|▏         | 7619/569592 [6:26:06<441:37:32,  2.83s/it]
                                                           

  1%|▏         | 7619/569592 [6:26:06<441:37:32,  2.83s/it]
  1%|▏         | 7620/569592 [6:26:07<369:48:08,  2.37s/it]
                                                           

  1%|▏         | 7620/569592 [6:26:07<369:48:08,  2.37s/it]
  1%|▏         | 7621/569592 [6:26:11<437:22:41,  2.80s/it]
                                                           

  1%|▏         | 7621/569592 [6:26:11<437:22:41,  2.80s/it]
  1%|▏         | 7622/569592 [6:26:13<376:44:02,  2.41s/it]
                                                           

  1%|▏         | 7622/569592 [6:26:13<376:44:02,  2.41s/it]
  1%|▏         | 7623/569592 [6:26:16<429:19:44,  2.75s/it]
                                                           

  1%|▏         | 7623/569592 [6:26:16<429:19:44,  2.75s/it]
  1%|▏         | 7624/569592 [6:26:17<351:28:13,  2.25s/it]
                                                           

  1%|▏         | 7624/569592 [6:26:17<351:28:13,  2.25s/it]
  1%|▏         | 7625/569592 [6:26:22<468:06:53,  3.00s/it]
                                                           

  1%|▏         | 7625/569592 [6:26:22<468:06:53,  3.00s/it]
  1%|▏         | 7626/569592 [6:26:26<491:14:51,  3.15s/it]
                                                           

  1%|▏         | 7626/569592 [6:26:26<491:14:51,  3.15s/it]
  1%|▏         | 7627/569592 [6:26:29<519:59:04,  3.33s/it]
                                                           

  1%|▏         | 7627/569592 [6:26:29<519:59:04,  3.33s/it]
  1%|▏         | 7628/569592 [6:26:30<406:17:32,  2.60s/it]
                                                           

  1%|▏         | 7628/569592 [6:26:30<406:17:32,  2.60s/it]
  1%|▏         | 7629/569592 [6:26:34<465:00:21,  2.98s/it]
                                                           

  1%|▏         | 7629/569592 [6:26:34<465:00:21,  2.98s/it]
  1%|▏         | 7630/569592 [6:26:38<508:50:23,  3.26s/it]
                                                           

  1%|▏         | 7630/569592 [6:26:38<508:50:23,  3.26s/it]
  1%|▏         | 7631/569592 [6:26:41<497:25:52,  3.19s/it]
                                                           

  1%|▏         | 7631/569592 [6:26:41<497:25:52,  3.19s/it]
  1%|▏         | 7632/569592 [6:26:45<524:24:41,  3.36s/it]
                                                           

  1%|▏         | 7632/569592 [6:26:45<524:24:41,  3.36s/it]
  1%|▏         | 7633/569592 [6:26:48<521:04:34,  3.34s/it]
                                                           

  1%|▏         | 7633/569592 [6:26:48<521:04:34,  3.34s/it]
  1%|▏         | 7634/569592 [6:26:52<529:01:31,  3.39s/it]
                                                           

  1%|▏         | 7634/569592 [6:26:52<529:01:31,  3.39s/it]
  1%|▏         | 7635/569592 [6:26:53<413:04:52,  2.65s/it]
                                                           

  1%|▏         | 7635/569592 [6:26:53<413:04:52,  2.65s/it]
  1%|▏         | 7636/569592 [6:26:56<457:59:13,  2.93s/it]
                                                           

  1%|▏         | 7636/569592 [6:26:56<457:59:13,  2.93s/it]
  1%|▏         | 7637/569592 [6:26:57<365:29:04,  2.34s/it]
                                                           

  1%|▏         | 7637/569592 [6:26:57<365:29:04,  2.34s/it]
  1%|▏         | 7638/569592 [6:27:01<433:00:59,  2.77s/it]
                                                           

  1%|▏         | 7638/569592 [6:27:01<433:00:59,  2.77s/it]
  1%|▏         | 7639/569592 [6:27:04<459:05:34,  2.94s/it]
                                                           

  1%|▏         | 7639/569592 [6:27:04<459:05:34,  2.94s/it]
  1%|▏         | 7640/569592 [6:27:08<502:36:20,  3.22s/it]
                                                           

  1%|▏         | 7640/569592 [6:27:08<502:36:20,  3.22s/it]
  1%|▏         | 7641/569592 [6:27:11<496:31:35,  3.18s/it]
                                                           

  1%|▏         | 7641/569592 [6:27:11<496:31:35,  3.18s/it]
  1%|▏         | 7642/569592 [6:27:12<391:38:12,  2.51s/it]
                                                           

  1%|▏         | 7642/569592 [6:27:12<391:38:12,  2.51s/it]
  1%|▏         | 7643/569592 [6:27:16<448:47:42,  2.88s/it]
                                                           

  1%|▏         | 7643/569592 [6:27:16<448:47:42,  2.88s/it]
  1%|▏         | 7644/569592 [6:27:21<543:29:08,  3.48s/it]
                                                           

  1%|▏         | 7644/569592 [6:27:21<543:29:08,  3.48s/it]
  1%|▏         | 7645/569592 [6:27:22<423:07:17,  2.71s/it]
                                                           

  1%|▏         | 7645/569592 [6:27:22<423:07:17,  2.71s/it]
  1%|▏         | 7646/569592 [6:27:25<467:07:47,  2.99s/it]
                                                           

  1%|▏         | 7646/569592 [6:27:25<467:07:47,  2.99s/it]
  1%|▏         | 7647/569592 [6:27:29<479:26:33,  3.07s/it]
                                                           

  1%|▏         | 7647/569592 [6:27:29<479:26:33,  3.07s/it]
  1%|▏         | 7648/569592 [6:27:30<381:28:45,  2.44s/it]
                                                           

  1%|▏         | 7648/569592 [6:27:30<381:28:45,  2.44s/it]
  1%|▏         | 7649/569592 [6:27:33<431:32:11,  2.76s/it]
                                                           

  1%|▏         | 7649/569592 [6:27:33<431:32:11,  2.76s/it]
  1%|▏         | 7650/569592 [6:27:37<492:40:31,  3.16s/it]
                                                           

  1%|▏         | 7650/569592 [6:27:37<492:40:31,  3.16s/it]
  1%|▏         | 7651/569592 [6:27:38<389:30:38,  2.50s/it]
                                                           

  1%|▏         | 7651/569592 [6:27:38<389:30:38,  2.50s/it]
  1%|▏         | 7652/569592 [6:27:41<427:22:16,  2.74s/it]
                                                           

  1%|▏         | 7652//home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (102611072 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
569592 [6:27:41<427:22:16,  2.74s/it]
  1%|▏         | 7653/569592 [6:27:45<475:28:17,  3.05s/it]
                                                           

  1%|▏         | 7653/569592 [6:27:45<475:28:17,  3.05s/it]
  1%|▏         | 7654/569592 [6:27:49<489:31:09,  3.14s/it]
                                                           

  1%|▏         | 7654/569592 [6:27:49<489:31:09,  3.14s/it]
  1%|▏         | 7655/569592 [6:27:52<493:05:28,  3.16s/it]
                                                           

  1%|▏         | 7655/569592 [6:27:52<493:05:28,  3.16s/it]
  1%|▏         | 7656/569592 [6:27:55<504:35:11,  3.23s/it]
                                                           

  1%|▏         | 7656/569592 [6:27:55<504:35:11,  3.23s/it]
  1%|▏         | 7657/569592 [6:27:59<541:45:30,  3.47s/it]
                                                           

  1%|▏         | 7657/569592 [6:27:59<541:45:30,  3.47s/it]
  1%|▏         | 7658/569592 [6:28:03<537:15:06,  3.44s/it]
                                                           

  1%|▏         | 7658/569592 [6:28:03<537:15:06,  3.44s/it]
  1%|▏         | 7659/569592 [6:28:06<550:54:37,  3.53s/it]
                                                           

  1%|▏         | 7659/569592 [6:28:06<550:54:37,  3.53s/it]
  1%|▏         | 7660/569592 [6:28:10<536:48:54,  3.44s/it]
                                                           

  1%|▏         | 7660/569592 [6:28:10<536:48:54,  3.44s/it]
  1%|▏         | 7661/569592 [6:28:13<516:18:59,  3.31s/it]
                                                           

  1%|▏         | 7661/569592 [6:28:13<516:18:59,  3.31s/it]
  1%|▏         | 7662/569592 [6:28:16<534:22:11,  3.42s/it]
                                                           

  1%|▏         | 7662/569592 [6:28:16<534:22:11,  3.42s/it]
  1%|▏         | 7663/569592 [6:28:20<554:32:27,  3.55s/it]
                                                           

  1%|▏         | 7663/569592 [6:28:20<554:32:27,  3.55s/it]
  1%|▏         | 7664/569592 [6:28:23<541:28:35,  3.47s/it]
                                                           

  1%|▏         | 7664/569592 [6:28:23<541:28:35,  3.47s/it]
  1%|▏         | 7665/569592 [6:28:28<584:02:38,  3.74s/it]
                                                           

  1%|▏         | 7665/569592 [6:28:28<584:02:38,  3.74s/it]
  1%|▏         | 7666/569592 [6:28:31<566:37:31,  3.63s/it]
                                                           

  1%|▏         | 7666/569592 [6:28:31<566:37:31,  3.63s/it]
  1%|▏         | 7667/569592 [6:28:34<549:39:31,  3.52s/it]
                                                           

  1%|▏         | 7667/569592 [6:28:34<549:39:31,  3.52s/it]
  1%|▏         | 7668/569592 [6:28:35<427:14:23,  2.74s/it]
                                                           

  1%|▏         | 7668/569592 [6:28:35<427:14:23,  2.74s/it]
  1%|▏         | 7669/569592 [6:28:39<478:23:04,  3.06s/it]
                                                           

  1%|▏         | 7669/569592 [6:28:39<478:23:04,  3.06s/it]
  1%|▏         | 7670/569592 [6:28:43<506:05:36,  3.24s/it]
                                                           

  1%|▏         | 7670/569592 [6:28:43<506:05:36,  3.24s/it]
  1%|▏         | 7671/569592 [6:28:46<501:46:29,  3.21s/it]
                                                           

  1%|▏         | 7671/569592 [6:28:46<501:46:29,  3.21s/it]
  1%|▏         | 7672/569592 [6:28:49<498:41:23,  3.19s/it]
                                                           

  1%|▏         | 7672/569592 [6:28:49<498:41:23,  3.19s/it]
  1%|▏         | 7673/569592 [6:28:50<393:32:04,  2.52s/it]
                                                           

  1%|▏         | 7673/569592 [6:28:50<393:32:04,  2.52s/it]
  1%|▏         | 7674/569592 [6:28:51<320:00:50,  2.05s/it]
                                                           

  1%|▏         | 7674/569592 [6:28:51<320:00:50,  2.05s/it]
  1%|▏         | 7675/569592 [6:28:55<391:59:03,  2.51s/it]
                                                           

  1%|▏         | 7675/569592 [6:28:55<391:59:03,  2.51s/it]
  1%|▏         | 7676/569592 [6:28:58<438:27:39,  2.81s/it]
                                                           

  1%|▏         | 7676/569592 [6:28:58<438:27:39,  2.81s/it]
  1%|▏         | 7677/569592 [6:28:59<357:46:51,  2.29s/it]
                                                           

  1%|▏         | 7677/569592 [6:28:59<357:46:51,  2.29s/it]
  1%|▏         | 7678/569592 [6:29:03<416:02:24,  2.67s/it]
                                                           

  1%|▏         | 7678/569592 [6:29:03<416:02:24,  2.67s/it]
  1%|▏         | 7679/569592 [6:29:04<337:55:38,  2.16s/it]
                                                           

  1%|▏         | 7679/569592 [6:29:04<337:55:38,  2.16s/it]
  1%|▏         | 7680/569592 [6:29:05<281:11:10,  1.80s/it]
                                                           

  1%|▏         | 7680/569592 [6:29:05<281:11:10,  1.80s/it]
  1%|▏         | 7681/569592 [6:29:08<371:57:24,  2.38s/it]
                                                           

  1%|▏         | 7681/569592 [6:29:08<371:57:24,  2.38s/it]
  1%|▏         | 7682/569592 [6:29:12<438:22:00,  2.81s/it]
                                                           

  1%|▏         | 7682/569592 [6:29:12<438:22:00,  2.81s/it]
  1%|▏         | 7683/569592 [6:29:13<351:47:11,  2.25s/it]
                                                           

  1%|▏         | 7683/569592 [6:29:13<351:47:11,  2.25s/it]
  1%|▏         | 7684/569592 [6:29:14<290:43:54,  1.86s/it]
                                                           

  1%|▏         | 7684/569592 [6:29:14<290:43:54,  1.86s/it]
  1%|▏         | 7685/569592 [6:29:17<362:40:56,  2.32s/it]
                                                           

  1%|▏         | 7685/569592 [6:29:17<362:40:56,  2.32s/it]
  1%|▏         | 7686/569592 [6:29:19<311:10:56,  1.99s/it]
                                                           

  1%|▏         | 7686/569592 [6:29:19<311:10:56,  1.99s/it]
  1%|▏         | 7687/569592 [6:29:20<262:36:25,  1.68s/it]
                                                           

  1%|▏         | 7687/569592 [6:29:20<262:36:25,  1.68s/it]
  1%|▏         | 7688/569592 [6:29:21<227:06:55,  1.46s/it]
                                                           

  1%|▏         | 7688/569592 [6:29:21<227:06:55,  1.46s/it]
  1%|▏         | 7689/569592 [6:29:24<320:29:26,  2.05s/it]
                                                           

  1%|▏         | 7689/569592 [6:29:24<320:29:26,  2.05s/it]
  1%|▏         | 7690/569592 [6:29:28<394:35:42,  2.53s/it]
                                                           

  1%|▏         | 7690/569592 [6:29:28<394:35:42,  2.53s/it]
  1%|▏         | 7691/569592 [6:29:29<321:34:45,  2.06s/it]
                                                           

  1%|▏         | 7691/569592 [6:29:29<321:34:45,  2.06s/it]
  1%|▏         | 7692/569592 [6:29:30<270:07:02,  1.73s/it]
                                                           

  1%|▏         | 7692/569592 [6:29:30<270:07:02,  1.73s/it]
  1%|▏         | 7693/569592 [6:29:33<368:38:57,  2.36s/it]
                                                           

  1%|▏         | 7693/569592 [6:29:33<368:38:57,  2.36s/it]
  1%|▏         | 7694/569592 [6:29:37<420:39:24,  2.70s/it]
                                                           

  1%|▏         | 7694/569592 [6:29:37<420:39:24,  2.70s/it]
  1%|▏         | 7695/569592 [6:29:38<339:48:30,  2.18s/it]
                                                           

  1%|▏         | 7695/569592 [6:29:38<339:48:30,  2.18s/it]
  1%|▏         | 7696/569592 [6:29:42<409:55:49,  2.63s/it]
                                                           

  1%|▏         | 7696/569592 [6:29:42<409:55:49,  2.63s/it]
  1%|▏         | 7697/569592 [6:29:45<441:45:48,  2.83s/it]
                                                           

  1%|▏         | 7697/569592 [6:29:45<441:45:48,  2.83s/it]
  1%|▏         | 7698/569592 [6:29:48<477:27:48,  3.06s/it]
                                                           

  1%|▏         | 7698/569592 [6:29:48<477:27:48,  3.06s/it]
  1%|▏         | 7699/569592 [6:29:49<380:41:11,  2.44s/it]
                                                           

  1%|▏         | 7699/569592 [6:29:49<380:41:11,  2.44s/it]
  1%|▏         | 7700/569592 [6:29:51<356:06:03,  2.28s/it]
                                                           

  1%|▏         | 7700/569592 [6:29:51<356:06:03,  2.28s/it]
  1%|▏         | 7701/569592 [6:29:54<381:26:47,  2.44s/it]
                                                           

  1%|▏         | 7701/569592 [6:29:54<381:26:47,  2.44s/it]
  1%|▏         | 7702/569592 [6:29:55<311:03:16,  1.99s/it]
                                                           

  1%|▏         | 7702/569592 [6:29:55<311:03:16,  1.99s/it]
  1%|▏         | 7703/569592 [6:29:58<376:04:50,  2.41s/it]
                                                           

  1%|▏         | 7703/569592 [6:29:58<376:04:50,  2.41s/it]
  1%|▏         | 7704/569592 [6:30:02<418:18:46,  2.68s/it]
                                                           

  1%|▏         | 7704/569592 [6:30:02<418:18:46,  2.68s/it]
  1%|▏         | 7705/569592 [6:30:05<444:44:54,  2.85s/it]
                                                           

  1%|▏         | 7705/569592 [6:30:05<444:44:54,  2.85s/it]
  1%|▏         | 7706/569592 [6:30:09<500:49:40,  3.21s/it]
                                                           

  1%|▏         | 7706/569592 [6:30:09<500:49:40,  3.21s/it]
  1%|▏         | 7707/569592 [6:30:13<522:14:42,  3.35s/it]
                                                           

  1%|▏         | 7707/569592 [6:30:13<522:14:42,  3.35s/it]
  1%|▏         | 7708/569592 [6:30:14<411:58:41,  2.64s/it]
                                                           

  1%|▏         | 7708/569592 [6:30:14<411:58:41,  2.64s/it]
  1%|▏         | 7709/569592 [6:30:17<450:59:54,  2.89s/it]
                                                           

  1%|▏         | 7709/569592 [6:30:17<450:59:54,  2.89s/it]
  1%|▏         | 7710/569592 [6:30:18<362:07:56,  2.32s/it]
                                                           

  1%|▏         | 7710/569592 [6:30:18<362:07:56,  2.32s/it]
  1%|▏         | 7711/569592 [6:30:19<297:53:22,  1.91s/it]
                                                           

  1%|▏         | 7711/569592 [6:30:19<297:53:22,  1.91s/it]
  1%|▏         | 7712/569592 [6:30:22<365:37:04,  2.34s/it]
                                                           

  1%|▏         | 7712/569592 [6:30:23<365:37:04,  2.34s/it]
  1%|▏         | 7713/569592 [6:30:24<326:59:25,  2.10s/it]
                                                           

  1%|▏         | 7713/569592 [6:30:24<326:59:25,  2.10s/it]
  1%|▏         | 7714/569592 [6:30:27<378:22:01,  2.42s/it]
                                                           

  1%|▏         | 7714/569592 [6:30:27<378:22:01,  2.42s/it]
  1%|▏         | 7715/569592 [6:30:31<430:07:32,  2.76s/it]
                                                           

  1%|▏         | 7715/569592 [6:30:31<430:07:32,  2.76s/it]
  1%|▏         | 7716/569592 [6:30:33<406:05:54,  2.60s/it]
                                                           

  1%|▏         | 7716/569592 [6:30:33<406:05:54,  2.60s/it]
  1%|▏         | 7717/569592 [6:30:36<442:57:44,  2.84s/it]
                                                           

  1%|▏         | 7717/569592 [6:30:36<442:57:44,  2.84s/it]
  1%|▏         | 7718/569592 [6:30:40<501:08:54,  3.21s/it]
                                                           

  1%|▏         | 7718/569592 [6:30:40<501:08:54,  3.21s/it]
  1%|▏         | 7719/569592 [6:30:44<527:55:19,  3.38s/it]
                                                           

  1%|▏         | 7719/569592 [6:30:44<527:55:19,  3.38s/it]
  1%|▏         | 7720/569592 [6:30:48<551:28:38,  3.53s/it]
                                                           

  1%|▏         | 7720/569592 [6:30:48<551:28:38,  3.53s/it]
  1%|▏         | 7721/569592 [6:30:49<430:35:44,  2.76s/it]
                                                           

  1%|▏         | 7721/569592 [6:30:49<430:35:44,  2.76s/it]
  1%|▏         | 7722/569592 [6:30:53<465:33:29,  2.98s/it]
                                                           

  1%|▏         | 7722/569592 [6:30:53<465:33:29,  2.98s/it]
  1%|▏         | 7723/569592 [6:30:54<371:04:43,  2.38s/it]
                                                           

  1%|▏         | 7723/569592 [6:30:54<371:04:43,  2.38s/it]
  1%|▏         | 7724/569592 [6:30:55<307:01:25,  1.97s/it]
                                                           

  1%|▏         | 7724/569592 [6:30:55<307:01:25,  1.97s/it]
  1%|▏         | 7725/569592 [6:30:56<260:14:10,  1.67s/it]
                                                           

  1%|▏         | 7725/569592 [6:30:56<260:14:10,  1.67s/it]
  1%|▏         | 7726/569592 [6:30:59<336:25:08,  2.16s/it]
                                                           

  1%|▏         | 7726/569592 [6:30:59<336:25:08,  2.16s/it]
  1%|▏         | 7727/569592 [6:31:00<285:14:47,  1.83s/it]
                                                           

  1%|▏         | 7727/569592 [6:31:00<285:14:47,  1.83s/it]
  1%|▏         | 7728/569592 [6:31:05<419:18:08,  2.69s/it]
                                                           

  1%|▏         | 7728/569592 [6:31:05<419:18:08,  2.69s/it]
  1%|▏         | 7729/569592 [6:31:08<471:10:56,  3.02s/it]
                                                           

  1%|▏         | 7729/569592 [6:31:08<471:10:56,  3.02s/it]
  1%|▏         | 7730/569592 [6:31:09<377:00:25,  2.42s/it]
                                                           

  1%|▏         | 7730/569592 [6:31:09<377:00:25,  2.42s/it]
  1%|▏         | 7731/569592 [6:31:14<465:27:45,  2.98s/it]
                                                           

  1%|▏         | 7731/569592 [6:31:14<465:27:45,  2.98s/it]
  1%|▏         | 7732/569592 [6:31:17<479:15:03,  3.07s/it]
                                                           

  1%|▏         | 7732/569592 [6:31:17<479:15:03,  3.07s/it]
  1%|▏         | 7733/569592 [6:31:18<379:58:05,  2.43s/it]
                                                           

  1%|▏         | 7733/569592 [6:31:18<379:58:05,  2.43s/it]
  1%|▏         | 7734/569592 [6:31:21<429:55:19,  2.75s/it]
                                                           

  1%|▏         | 7734/569592 [6:31:21<429:55:19,  2.75s/it]
  1%|▏         | 7735/569592 [6:31:22<347:04:55,  2.22s/it]
                                                           

  1%|▏         | 7735/56959/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
2 [6:31:22<347:04:55,  2.22s/it]
  1%|▏         | 7736/569592 [6:31:26<399:47:07,  2.56s/it]
                                                           

  1%|▏         | 7736/569592 [6:31:26<399:47:07,  2.56s/it]
  1%|▏         | 7737/569592 [6:31:27<346:07:40,  2.22s/it]
                                                           

  1%|▏         | 7737/569592 [6:31:27<346:07:40,  2.22s/it]
  1%|▏         | 7738/569592 [6:31:32<449:39:21,  2.88s/it]
                                                           

  1%|▏         | 7738/569592 [6:31:32<449:39:21,  2.88s/it]
  1%|▏         | 7739/569592 [6:31:35<485:25:54,  3.11s/it]
                                                           

  1%|▏         | 7739/569592 [6:31:35<485:25:54,  3.11s/it]
  1%|▏         | 7740/569592 [6:31:39<495:27:41,  3.17s/it]
                                                           

  1%|▏         | 7740/569592 [6:31:39<495:27:41,  3.17s/it]
  1%|▏         | 7741/569592 [6:31:39<390:58:27,  2.51s/it]
                                                           

  1%|▏         | 7741/569592 [6:31:40<390:58:27,  2.51s/it]
  1%|▏         | 7742/569592 [6:31:43<435:53:16,  2.79s/it]
                                                           

  1%|▏         | 7742/569592 [6:31:43<435:53:16,  2.79s/it]
  1%|▏         | 7743/569592 [6:31:46<460:46:40,  2.95s/it]
                                                           

  1%|▏         | 7743/569592 [6:31:46<460:46:40,  2.95s/it]
  1%|▏         | 7744/569592 [6:31:50<501:27:47,  3.21s/it]
                                                           

  1%|▏         | 7744/569592 [6:31:50<501:27:47,  3.21s/it]
  1%|▏         | 7745/569592 [6:31:53<502:45:22,  3.22s/it]
                                                           

  1%|▏         | 7745/569592 [6:31:53<502:45:22,  3.22s/it]
  1%|▏         | 7746/569592 [6:31:54<393:54:36,  2.52s/it]
                                                           

  1%|▏         | 7746/569592 [6:31:54<393:54:36,  2.52s/it]
  1%|▏         | 7747/569592 [6:31:58<435:33:48,  2.79s/it]
                                                           

  1%|▏         | 7747/569592 [6:31:58<435:33:48,  2.79s/it]
  1%|▏         | 7748/569592 [6:32:01<457:16:21,  2.93s/it]
                                                           

  1%|▏         | 7748/569592 [6:32:01<457:16:21,  2.93s/it]
  1%|▏         | 7749/569592 [6:32:04<485:28:08,  3.11s/it]
                                                           

  1%|▏         | 7749/569592 [6:32:04<485:28:08,  3.11s/it]
  1%|▏         | 7750/569592 [6:32:08<503:53:39,  3.23s/it]
                                                           

  1%|▏         | 7750/569592 [6:32:08<503:53:39,  3.23s/it]
  1%|▏         | 7751/569592 [6:32:09<396:56:00,  2.54s/it]
                                                           

  1%|▏         | 7751/569592 [6:32:09<396:56:00,  2.54s/it]
  1%|▏         | 7752/569592 [6:32:12<444:12:04,  2.85s/it]
                                                           

  1%|▏         | 7752/569592 [6:32:12<444:12:04,  2.85s/it]
  1%|▏         | 7753/569592 [6:32:16<481:13:16,  3.08s/it]
                                                           

  1%|▏         | 7753/569592 [6:32:16<481:13:16,  3.08s/it]
  1%|▏         | 7754/569592 [6:32:21<562:39:36,  3.61s/it]
                                                           

  1%|▏         | 7754/569592 [6:32:21<562:39:36,  3.61s/it]
  1%|▏         | 7755/569592 [6:32:22<435:26:14,  2.79s/it]
                                                           

  1%|▏         | 7755/569592 [6:32:22<435:26:14,  2.79s/it]
  1%|▏         | 7756/569592 [6:32:27<555:32:54,  3.56s/it]
                                                           

  1%|▏         | 7756/569592 [6:32:27<555:32:54,  3.56s/it]
  1%|▏         | 7757/569592 [6:32:31<575:45:48,  3.69s/it]
                                                           

  1%|▏         | 7757/569592 [6:32:31<575:45:48,  3.69s/it]
  1%|▏         | 7758/569592 [6:32:34<553:37:15,  3.55s/it]
                                                           

  1%|▏         | 7758/569592 [6:32:34<553:37:15,  3.55s/it]
  1%|▏         | 7759/569592 [6:32:38<543:27:56,  3.48s/it]
                                                           

  1%|▏         | 7759/569592 [6:32:38<543:27:56,  3.48s/it]
  1%|▏         | 7760/569592 [6:32:39<423:56:54,  2.72s/it]
                                                           

  1%|▏         | 7760/569592 [6:32:39<423:56:54,  2.72s/it]
  1%|▏         | 7761/569592 [6:32:42<450:38:50,  2.89s/it]
                                                           

  1%|▏         | 7761/569592 [6:32:42<450:38:50,  2.89s/it]
  1%|▏         | 7762/569592 [6:32:45<469:03:18,  3.01s/it]
                                                           

  1%|▏         | 7762/569592 [6:32:45<469:03:18,  3.01s/it]
  1%|▏         | 7763/569592 [6:32:51<617:14:16,  3.96s/it]
                                                           

  1%|▏         | 7763/569592 [6:32:51<617:14:16,  3.96s/it]
  1%|▏         | 7764/569592 [6:32:54<567:39:55,  3.64s/it]
                                                           

  1%|▏         | 7764/569592 [6:32:54<567:39:55,  3.64s/it]
  1%|▏         | 7765/569592 [6:32:57<542:48:25,  3.48s/it]
                                                           

  1%|▏         | 7765/569592 [6:32:57<542:48:25,  3.48s/it]
  1%|▏         | 7766/569592 [6:33:01<529:02:25,  3.39s/it]
                                                           

  1%|▏         | 7766/569592 [6:33:01<529:02:25,  3.39s/it]
  1%|▏         | 7767/569592 [6:33:01<413:14:46,  2.65s/it]
                                                           

  1%|▏         | 7767/569592 [6:33:01<413:14:46,  2.65s/it]
  1%|▏         | 7768/569592 [6:33:05<468:40:56,  3.00s/it]
                                                           

  1%|▏         | 7768/569592 [6:33:05<468:40:56,  3.00s/it]
  1%|▏         | 7769/569592 [6:33:09<498:56:46,  3.20s/it]
                                                           

  1%|▏         | 7769/569592 [6:33:09<498:56:46,  3.20s/it]
  1%|▏         | 7770/569592 [6:33:13<540:53:53,  3.47s/it]
                                                           

  1%|▏         | 7770/569592 [6:33:13<540:53:53,  3.47s/it]
  1%|▏         | 7771/569592 [6:33:16<531:47:06,  3.41s/it]
                                                           

  1%|▏         | 7771/569592 [6:33:16<531:47:06,  3.41s/it]
  1%|▏         | 7772/569592 [6:33:19<519:27:04,  3.33s/it]
                                                           

  1%|▏         | 7772/569592 [6:33:19<519:27:04,  3.33s/it]
  1%|▏         | 7773/569592 [6:33:20<406:31:55,  2.60s/it]
                                                           

  1%|▏         | 7773/569592 [6:33:20<406:31:55,  2.60s/it]
  1%|▏         | 7774/569592 [6:33:21<328:42:32,  2.11s/it]
                                           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                

  1%|▏         | 7774/569592 [6:33:21<328:42:32,  2.11s/it]
  1%|▏         | 7775/569592 [6:33:25<415:36:43,  2.66s/it]
                                                           

  1%|▏         | 7775/569592 [6:33:25<415:36:43,  2.66s/it]
  1%|▏         | 7776/569592 [6:33:31<542:21:30,  3.48s/it]
                                                           

  1%|▏         | 7776/569592 [6:33:31<542:21:30,  3.48s/it]
  1%|▏         | 7777/569592 [6:33:34<528:29:41,  3.39s/it]
                                                           

  1%|▏         | 7777/569592 [6:33:34<528:29:41,  3.39s/it]
  1%|▏         | 7778/569592 [6:33:35<411:53:09,  2.64s/it]
                                                           

  1%|▏         | 7778/569592 [6:33:35<411:53:09,  2.64s/it]
  1%|▏         | 7779/569592 [6:33:38<449:39:51,  2.88s/it]
                                                           

  1%|▏         | 7779/569592 [6:33:38<449:39:51,  2.88s/it]
  1%|▏         | 7780/569592 [6:33:42<475:53:16,  3.05s/it]
                                                           

  1%|▏         | 7780/569592 [6:33:42<475:53:16,  3.05s/it]
  1%|▏         | 7781/569592 [6:33:45<512:28:43,  3.28s/it]
                                                           

  1%|▏         | 7781/569592 [6:33:45<512:28:43,  3.28s/it]
  1%|▏         | 7782/569592 [6:33:49<518:34:51,  3.32s/it]
                                                           

  1%|▏         | 7782/569592 [6:33:49<518:34:51,  3.32s/it]
  1%|▏         | 7783/569592 [6:33:52<509:03:23,  3.26s/it]
                                                           

  1%|▏         | 7783/569592 [6:33:52<509:03:23,  3.26s/it]
  1%|▏         | 7784/569592 [6:33:55<505:07:11,  3.24s/it]
                                                           

  1%|▏         | 7784/569592 [6:33:55<505:07:11,  3.24s/it]
  1%|▏         | 7785/569592 [6:33:56<397:02:50,  2.54s/it]
                                                           

  1%|▏         | 7785/569592 [6:33:56<397:02:50,  2.54s/it]
  1%|▏         | 7786/569592 [6:33:59<434:18:12,  2.78s/it]
                                                           

  1%|▏         | 7786/569592 [6:33:59<434:18:12,  2.78s/it]
  1%|▏         | 7787/569592 [6:34:04<504:10:02,  3.23s/it]
                                                           

  1%|▏         | 7787/569592 [6:34:04<504:10:02,  3.23s/it]
  1%|▏         | 7788/569592 [6:34:07<520:50:16,  3.34s/it]
                                                           

  1%|▏         | 7788/569592 [6:34:07<520:50:16,  3.34s/it]
  1%|▏         | 7789/569592 [6:34:08<409:10:57,  2.62s/it]
                                                           

  1%|▏         | 7789/569592 [6:34:08<409:10:57,  2.62s/it]
  1%|▏         | 7790/569592 [6:34:12<441:42:02,  2.83s/it]
                                                           

  1%|▏         | 7790/569592 [6:34:12<441:42:02,  2.83s/it]
  1%|▏         | 7791/569592 [6:34:13<354:30:35,  2.27s/it]
                                                           

  1%|▏         | 7791/569592 [6:34:13<354:30:35,  2.27s/it]
  1%|▏         | 7792/569592 [6:34:13<293:08:17,  1.88s/it]
                                                           

  1%|▏         | 7792/569592 [6:34:13<293:08:17,  1.88s/it]
  1%|▏         | 7793/569592 [6:34:17<362:15:43,  2.32s/it]
                                                           

  1%|▏         | 7793/569592 [6:34:17<362:15:43,  2.32s/it]
  1%|▏         | 7794/569592 [6:34:20<408:38:36,  2.62s/it]
                                                           

  1%|▏         | 7794/569592 [6:34:20<408:38:36,  2.62s/it]
  1%|▏         | 7795/569592 [6:34:23<435:27:59,  2.79s/it]
                                                           

  1%|▏         | 7795/569592 [6:34:23<435:27:59,  2.79s/it]
  1%|▏         | 7796/569592 [6:34:27<459:43:29,  2.95s/it]
                                                           

  1%|▏         | 7796/569592 [6:34:27<459:43:29,  2.95s/it]
  1%|▏         | 7797/569592 [6:34:28<365:36:45,  2.34s/it]
                                                           

  1%|▏         | 7797/569592 [6:34:28<365:36:45,  2.34s/it]
  1%|▏         | 7798/569592 [6:34:31<415:42:15,  2.66s/it]
                                                           

  1%|▏         | 7798/569592 [6:34:31<415:42:15,  2.66s/it]
  1%|▏         | 7799/569592 [6:34:32<336:30:36,  2.16s/it]
                                                           

  1%|▏         | 7799/569592 [6:34:32<336:30:36,  2.16s/it]
  1%|▏         | 7800/569592 [6:34:36<409:30:56,  2.62s/it]
                                                           

  1%|▏         | 7800/569592 [6:34:36<409:30:56,  2.62s/it]
  1%|▏         | 7801/569592 [6:34:37<333:28:34,  2.14s/it]
                                                           

  1%|▏         | 7801/569592 [6:34:37<333:28:34,  2.14s/it]
  1%|▏         | 7802/569592 [6:34:40<407:5/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
6:17,  2.61s/it]
                                                           

  1%|▏         | 7802/569592 [6:34:40<407:56:17,  2.61s/it]
  1%|▏         | 7803/569592 [6:34:41<329:42:40,  2.11s/it]
                                                           

  1%|▏         | 7803/569592 [6:34:41<329:42:40,  2.11s/it]
  1%|▏         | 7804/569592 [6:34:42<274:50:36,  1.76s/it]
                                                           

  1%|▏         | 7804/569592 [6:34:42<274:50:36,  1.76s/it]
  1%|▏         | 7805/569592 [6:34:43<236:50:23,  1.52s/it]
                                                           

  1%|▏         | 7805/569592 [6:34:43<236:50:23,  1.52s/it]
  1%|▏         | 7806/569592 [6:34:47<328:18:56,  2.10s/it]
                                                           

  1%|▏         | 7806/569592 [6:34:47<328:18:56,  2.10s/it]
  1%|▏         | 7807/569592 [6:34:51<432:23:49,  2.77s/it]
                                                           

  1%|▏         | 7807/569592 [6:34:51<432:23:49,  2.77s/it]
  1%|▏         | 7808/569592 [6:34:52<350:13:37,  2.24s/it]
                                                           

  1%|▏         | 7808/569592 [6:34:52<350:13:37,  2.24s/it]
  1%|▏         | 7809/569592 [6:34:56<409:09:16,  2.62s/it]
                                                           

  1%|▏         | 7809/569592 [6:34:56<409:09:16,  2.62s/it]
  1%|▏         | 7810/569592 [6:34:57<330:53:00,  2.12s/it]
                                                           

  1%|▏         | 7810/569592 [6:34:57<330:53:00,  2.12s/it]
  1%|▏         | 7811/569592 [6:35:00<392:48:12,  2.52s/it]
                                                           

  1%|▏         | 7811/569592 [6:35:00<392:48:12,  2.52s/it]
  1%|▏         | 7812/569592 [6:35:03<429:01:47,  2.75s/it]
                                                           

  1%|▏         | 7812/569592 [6:35:03<429:01:47,  2.75s/it]
  1%|▏         | 7813/569592 [6:35:04<345:55:13,  2.22s/it]
                                                           

  1%|▏         | 7813/569592 [6:35:04<345:55:13,  2.22s/it]
  1%|▏         | 7814/569592 [6:35:05<287:42:05,  1.84s/it]
                                                           

  1%|▏         | 7814/569592 [6:35:05<287:42:05,  1.84s/it]
  1%|▏         | 7815/569592 [6:35:10<440:55:24,  2.83s/it]
                                                           

  1%|▏         | 7815/569592 [6:35:10<440:55:24,  2.83s/it]
  1%|▏         | 7816/569592 [6:35:14<487:48:29,  3.13s/it]
                                                           

  1%|▏         | 7816/569592 [6:35:14<487:48:29,  3.13s/it]
  1%|▏         | 7817/569592 [6:35:15<387:19:02,  2.48s/it]
                                                           

  1%|▏         | 7817/569592 [6:35:15<387:19:02,  2.48s/it]
  1%|▏         | 7818/569592 [6:35:19<434:06:46,  2.78s/it]
                                                           

  1%|▏         | 7818/569592 [6:35:19<434:06:46,  2.78s/it]
  1%|▏         | 7819/569592 [6:35:24<540:16:21,  3.46s/it]
                                                           

  1%|▏         | 7819/569592 [6:35:24<540:16:21,  3.46s/it]
  1%|▏         | 7820/569592 [6:35:25<436:36:22,  2.80s/it]
                                                           

  1%|▏         | 7820/569592 [6:35:25<436:36:22,  2.80s/it]
  1%|▏         | 7821/569592 [6:35:26<350:53:53,  2.25s/it]
                                                           

  1%|▏         | 7821/569592 [6:35:26<350:53:53,  2.25s/it]
  1%|▏         | 7822/569592 [6:35:27<297:15:44,  1.90s/it]
                                                           

  1%|▏         | 7822/569592 [6:35:27<297:15:44,  1.90s/it]
  1%|▏         | 7823/569592 [6:35:30<367:47:13,  2.36s/it]
                                                           

  1%|▏         | 7823/569592 [6:35:30<367:47:13,  2.36s/it]
  1%|▏         | 7824/569592 [6:35:31<303:37:17,  1.95s/it]
                                                           

  1%|▏         | 7824/569592 [6:35:31<303:37:17,  1.95s/it]
  1%|▏         | 7825/569592 [6:35:35<372:48:23,  2.39s/it]
                                                           

  1%|▏         | 7825/569592 [6:35:35<372:48:23,  2.39s/it]
  1%|▏         | 7826/569592 [6:35:38<420:22:08,  2.69s/it]
                                                           

  1%|▏         | 7826/569592 [6:35:38<420:22:08,  2.69s/it]
  1%|▏         | 7827/569592 [6:35:39<340:20:45,  2.18s/it]
                                                           

  1%|▏         | 7827/569592 [6:35:39<340:20:45,  2.18s/it]
  1%|▏         | 7828/569592 [6:35:40<292:57:50,  1.88s/it]
                                                           

  1%|▏         | 7828/569592 [6:35:40<292:57:50,  1.88s/it]
  1%|▏         | 7829/569592 [6:35:42<263:57:50,  1.69s/it]
                                                           

  1%|▏         | 7829/569592 [6:35:42<263:57:50,  1.69s/it]
  1%|▏         | 7830/569592 [6:35:46<377:57:56,  2.42s/it]
                                                           

  1%|▏         | 7830/569592 [6:35:46<377:57:56,  2.42s/it]
  1%|▏         | 7831/569592 [6:35:49<420:26:29,  2.69s/it]
                                                           

  1%|▏         | 7831/569592 [6:35:49<420:26:29,  2.69s/it]
  1%|▏         | 7832/569592 [6:35:50<344:34:22,  2.21s/it]
                                                           

  1%|▏         | 7832/569592 [6:35:50<344:34:22,  2.21s/it]
  1%|▏         | 7833/569592 [6:35:54<416:32:28,  2.67s/it]
                                                           

  1%|▏         | 7833/569592 [6:35:54<416:32:28,  2.67s/it]
  1%|▏         | 7834/569592 [6:35:55<356:09:34,  2.28s/it]
                                                           

  1%|▏         | 7834/569592 [6:35:55<356:09:34,  2.28s/it]
  1%|▏         | 7835/569592 [6:35:59<402:18:22,  2.58s/it]
                                                           

  1%|▏         | 7835/569592 [6:35:59<402:18:22,  2.58s/it]
  1%|▏         | 7836/569592 [6:36:00<355:29:10,  2.28s/it]
                                                           

  1%|▏         | 7836/569592 [6:36:00<355:29:10,  2.28s/it]
  1%|▏         | 7837/569592 [6:36:04<423:08:43,  2.71s/it]
                                                           

  1%|▏         | 7837/569592 [6:36:04<423:08:43,  2.71s/it]
  1%|▏         | 7838/569592 [6:36:07<461:06:42,  2.96s/it]
                                                           

  1%|▏         | 7838/569592 [6:36:07<461:06:42,  2.96s/it]
  1%|▏         | 7839/569592 [6:36:08<372:07:15,  2.38s/it]
                                                           

  1%|▏         | 7839/569592 [6:36:08<372:07:15,  2.38s/it]
  1%|▏         | 7840/569592 [6:36:12<424:04:22,  2.72s/it]
                                                           

  1%|▏         | 7840/569592 [6:36:12<424:04:22,  2.72s/it/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
]
  1%|▏         | 7841/569592 [6:36:13<354:01:30,  2.27s/it]
                                                           

  1%|▏         | 7841/569592 [6:36:13<354:01:30,  2.27s/it]
  1%|▏         | 7842/569592 [6:36:16<370:17:12,  2.37s/it]
                                                           

  1%|▏         | 7842/569592 [6:36:16<370:17:12,  2.37s/it]
  1%|▏         | 7843/569592 [6:36:20<481:26:47,  3.09s/it]
                                                           

  1%|▏         | 7843/569592 [6:36:20<481:26:47,  3.09s/it]
  1%|▏         | 7844/569592 [6:36:24<492:49:42,  3.16s/it]
                                                           

  1%|▏         | 7844/569592 [6:36:24<492:49:42,  3.16s/it]
  1%|▏         | 7845/569592 [6:36:25<395:09:44,  2.53s/it]
                                                           

  1%|▏         | 7845/569592 [6:36:25<395:09:44,  2.53s/it]
  1%|▏         | 7846/569592 [6:36:26<322:18:40,  2.07s/it]
                                                           

  1%|▏         | 7846/569592 [6:36:26<322:18:40,  2.07s/it]
  1%|▏         | 7847/569592 [6:36:29<391:45:50,  2.51s/it]
                                                           

  1%|▏         | 7847/569592 [6:36:29<391:45:50,  2.51s/it]
  1%|▏         | 7848/569592 [6:36:33<434:17:55,  2.78s/it]
                                                           

  1%|▏         | 7848/569592 [6:36:33<434:17:55,  2.78s/it]
  1%|▏         | 7849/569592 [6:36:36<452:47:28,  2.90s/it]
                                                           

  1%|▏         | 7849/569592 [6:36:36<452:47:28,  2.90s/it]
  1%|▏         | 7850/569592 [6:36:39<467:21:32,  3.00s/it]
                                                           

  1%|▏         | 7850/569592 [6:36:39<467:21:32,  3.00s/it]
  1%|▏         | 7851/569592 [6:36:43<487:43:24,  3.13s/it]
                                                           

  1%|▏         | 7851/569592 [6:36:43<487:43:24,  3.13s/it]
  1%|▏         | 7852/569592 [6:36:44<385:56:17,  2.47s/it]
                                                           

  1%|▏         | 7852/569592 [6:36:44<385:56:17,  2.47s/it]
  1%|▏         | 7853/569592 [6:36:45<315:21:03,  2.02s/it]
                                                           

  1%|▏         | 7853/569592 [6:36:45<315:21:03,  2.02s/it]
  1%|▏         | 7854/569592 [6:36:46<277:34:29,  1.78s/it]
                                                           

  1%|▏         | 7854/569592 [6:36:46<277:34:29,  1.78s/it]
  1%|▏         | 7855/569592 [6:36:50<371:31:09,  2.38s/it]
                                                           

  1%|▏         | 7855/569592 [6:36:50<371:31:09,  2.38s/it]
  1%|▏         | 7856/569592 [6:36:51<306:31:50,  1.96s/it]
                                                           

  1%|▏         | 7856/569592 [6:36:51<306:31:50,  1.96s/it]
  1%|▏         | 7857/569592 [6:36:54<367:31:55,  2.36s/it]
                                                           

  1%|▏         | 7857/569592 [6:36:54<367:31:55,  2.36s/it]
  1%|▏         | 7858/569592 [6:36:58<459:26:20,  2.94s/it]
                                                           

  1%|▏         | 7858/569592 [6:36:58<459:26:20,  2.94s/it]
  1%|▏         | 7859/569592 [6:36:59<366:46:00,  2.35s/it]
                                                           

  1%|▏         | 7859/569592 [6:36:59<366:46:00,  2.35s/it]
  1%|▏         | 7860/569592 [6:37:03<430:37:03,  2.76s/it]
                                                           

  1%|▏         | 7860/569592 [6:37:03<430:37:03,  2.76s/it]
  1%|▏         | 7861/569592 [6:37:06<452:55:04,  2.90s/it]
                                                           

  1%|▏         | 7861/569592 [6:37:06<452:55:04,  2.90s/it]
  1%|▏         | 7862/569592 [6:37:10<504:53:45,  3.24s/it]
                                                           

  1%|▏         | 7862/569592 [6:37:10<504:53:45,  3.24s/it]
  1%|▏         | 7863/569592 [6:37:13<510:51:10,  3.27s/it]
                                                           

  1%|▏         | 7863/569592 [6:37:13<510:51:10,  3.27s/it]
  1%|▏         | 7864/569592 [6:37:17<526:58:51,  3.38s/it]
                                                           

  1%|▏         | 7864/569592 [6:37:17<526:58:51,  3.38s/it]
  1%|▏         | 7865/569592 [6:37:20<516:59:08,  3.31s/it]
                                                           

  1%|▏         | 7865/569592 [6:37:20<516:59:08,  3.31s/it]
  1%|▏         | 7866/569592 [6:37:23<507:04:15,  3.25s/it]
                                                           

  1%|▏         | 7866/569592 [6:37:23<507:04:15,  3.25s/it]
  1%|▏         | 7867/569592 [6:37:27<531:07:22,  3.40s/it]
                                                           

  1%|▏         | 7867/569592 [6:37:27<531:07:22,  3.40s/it]
  1%|▏         | 7868/569592 [6:37:31<543:00:08,  3.48s/it]
                                                           

  1%|▏         | 7868/569592 [6:37:31<543:00:08,  3.48s/it]
  1%|▏         | 7869/569592 [6:37:35<571:16:37,  3.66s/it]
                                                           

  1%|▏         | 7869/569592 [6:37:35<571:16:37,  3.66s/it]
  1%|▏         | 7870/569592 [6:37:38<565:33:30,  3.62s/it]
                                                           

  1%|▏         | 7870/569592 [6:37:38<565:33:30,  3.62s/it]
  1%|▏         | 7871/569592 [6:37:41<542:13:58,  3.48s/it]
                                                           

  1%|▏         | 7871/569592 [6:37:42<542:13:58,  3.48s/it]
  1%|▏         | 7872/569592 [6:37:45<535:00:05,  3.43s/it]
                                                           

  1%|▏         | 7872/569592 [6:37:45<535:00:05,  3.43s/it]
  1%|▏         | 7873/569592 [6:37:48<529:40:09,  3.39s/it]
                                                           

  1%|▏         | 7873/569592 [6:37:48<529:40:09,  3.39s/it]
  1%|▏         | 7874/569592 [6:37:52<551:33:10,  3.53s/it]
                                                           

  1%|▏         | 7874/569592 [6:37:52<551:33:10,  3.53s/it]
  1%|▏         | 7875/569592 [6:37:56<562:34:48,  3.61s/it]
                                                           

  1%|▏         | 7875/569592 [6:37:56<562:34:48,  3.61s/it]
  1%|▏         | 7876/569592 [6:37:59<557:55:21,  3.58s/it]
                                                           

  1%|▏         | 7876/569592 [6:37:59<557:55:21,  3.58s/it]
  1%|▏         | 7877/569592 [6:38:03<542:46:55,  3.48s/it]
                                                           

  1%|▏         | 7877/569592 [6:38:03<542:46:55,  3.48s/it]
  1%|▏         | 7878/569592 [6:38:06<522:31:31,  3.35s/it]
                                                           

  1%|▏         | 7878/569592 [6:38:06<522:31:31,  3.35s/it]
  1%|▏         | 7879/569592 [6:38:09<527:02:52,  3.38s/it]
                                                           

  1%|▏         | 7879/569592 [6:38:09<527:02:52,  3.38s/it]
  1%|▏         | 7880/569592 [6:38:12<518:45:12,  3.32s/it]
                                                           

  1%|▏         | 7880/569592 [6:38:12<518:45:12,  3.32s/it]
  1%|▏         | 7881/569592 [6:38:17<587:20:53,  3.76s/it]
                                                           

  1%|▏         | 7881/569592 [6:38:17<587:20:53,  3.76s/it]
  1%|▏         | 7882/569592 [6:38:22<629:25:46,  4.03s/it]
                                                           

  1%|▏         | 7882/569592 [6:38:22<629:25:46,  4.03s/it]
  1%|▏         | 7883/569592 [6:38:26<656:12:36,  4.21s/it]
                                                           

  1%|▏         | 7883/569592 [6:38:26<656:12:36,  4.21s/it]
  1%|▏         | 7884/569592 [6:38:30<626:02:32,  4.01s/it]
                                                           

  1%|▏         | 7884/569592 [6:38:30<626:02:32,  4.01s/it]
  1%|▏         | 7885/569592 [6:38:31<480:10:29,  3.08s/it]
                                                           

  1%|▏         | 7885/569592 [6:38:31<480:10:29,  3.08s/it]
  1%|▏         | 7886/569592 [6:38:34<508:03:47,  3.26s/it]
                                                           

  1%|▏         | 7886/569592 [6:38:34<508:03:47,  3.26s/it]
  1%|▏         | 7887/569592 [6:38:35<401:23:48,  2.57s/it]
                                                           

  1%|▏         | 7887/569592 [6:38:35<401:23:48,  2.57s/it]
  1%|▏         | 7888/569592 [6:38:41<558:13:45,  3.58s/it]
                                                           

  1%|▏         | 7888/569592 [6:38:41<558:13:45,  3.58s/it]
  1%|▏         | 7889/569592 [6:38:45<562:15:47,  3.60s/it]
                                                           

  1%|▏         | 7889/569592 [6:38:45<562:15:47,  3.60s/it]
  1%|▏         | 7890/569592 [6:38:48<549:17:48,  3.52s/it]
                                                           

  1%|▏         | 7890/569592 [6:38:48<549:17:48,  3.52s/it]
  1%|▏         | 7891/569592 [6:38:49<428:08:01,  2.74s/it]
                                                           

  1%|▏         | 7891/569592 [6:38:49<428:08:01,  2.74s/it]
  1%|▏         | 7892/569592 [6:38:52<448:21:04,  2.87s/it]
                                                           

  1%|▏         | 7892/569592 [6:38:52<448:21:04,  2.87s/it]
  1%|▏         | 7893/569592 [6:38:56<487:14:27,  3.12s/it]
                                                           

  1%|▏         | 7893/569592 [6:38:56<487:14:27,  3.12s/it]
  1%|▏         | 7894/569592 [6:39:00<511:49:18,  3.28s/it]
                                                           

  1%|▏         | 7894/569592 [6:39:00<511:49:18,  3.28s/it]
  1%|▏         | 7895/569592 [6:39:04<538:54:53,  3.45s/it]
                                                           

  1%|▏         | 7895/569592 [6:39:04<538:54:53,  3.45s/it]
  1%|▏         | 7896/569592 [6:39:07<542:23:42,  3.48s/it]
 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                          

  1%|▏         | 7896/569592 [6:39:07<542:23:42,  3.48s/it]
  1%|▏         | 7897/569592 [6:39:08<422:13:13,  2.71s/it]
                                                           

  1%|▏         | 7897/569592 [6:39:08<422:13:13,  2.71s/it]
  1%|▏         | 7898/569592 [6:39:12<481:15:18,  3.08s/it]
                                                           

  1%|▏         | 7898/569592 [6:39:12<481:15:18,  3.08s/it]
  1%|▏         | 7899/569592 [6:39:15<494:01:09,  3.17s/it]
                                                           

  1%|▏         | 7899/569592 [6:39:15<494:01:09,  3.17s/it]
  1%|▏         | 7900/569592 [6:39:19<498:05:47,  3.19s/it]
                                                           

  1%|▏         | 7900/569592 [6:39:19<498:05:47,  3.19s/it]
  1%|▏         | 7901/569592 [6:39:23<537:23:04,  3.44s/it]
                                                           

  1%|▏         | 7901/569592 [6:39:23<537:23:04,  3.44s/it]
  1%|▏         | 7902/569592 [6:39:24<422:39:05,  2.71s/it]
                                                           

  1%|▏         | 7902/569592 [6:39:24<422:39:05,  2.71s/it]
  1%|▏         | 7903/569592 [6:39:25<339:09:17,  2.17s/it]
                                                           

  1%|▏         | 7903/569592 [6:39:25<339:09:17,  2.17s/it]
  1%|▏         | 7904/569592 [6:39:28<400:13:14,  2.57s/it]
                                                           

  1%|▏         | 7904/569592 [6:39:28<400:13:14,  2.57s/it]
  1%|▏         | 7905/569592 [6:39:32<458:56:36,  2.94s/it]
                                                           

  1%|▏         | 7905/569592 [6:39:32<458:56:36,  2.94s/it]
  1%|▏         | 7906/569592 [6:39:35<486:44:22,  3.12s/it]
                                                           

  1%|▏         | 7906/569592 [6:39:35<486:44:22,  3.12s/it]
  1%|▏         | 7907/569592 [6:39:39<491:59:04,  3.15s/it]
                                                           

  1%|▏         | 7907/569592 [6:39:39<491:59:04,  3.15s/it]
  1%|▏         | 7908/569592 [6:39:40<388:27:04,  2.49s/it]
                                                           

  1%|▏         | 7908/569592 [6:39:40<388:27:04,  2.49s/it]
  1%|▏         | 7909/569592 [6:39:41<316:47:18,  2.03s/it]
                                                           

  1%|▏         | 7909/569592 [6:39:41<316:47:18,  2.03s/it]
  1%|▏         | 7910/569592 [6:39:41<266:49:48,  1.71s/it]
                                                           

  1%|▏         | 7910/569592 [6:39:42<266:49:48,  1.71s/it]
  1%|▏         | 7911/569592 [6:39:45<340:25:05,  2.18s/it]
                                                           

  1%|▏         | 7911/569592 [6:39:45<340:25:05,  2.18s/it]
  1%|▏         | 7912/569592 [6:39:48<397:00:44,  2.54s/it]
                                                           

  1%|▏         | 7912/569592 [6:39:48<397:00:44,  2.54s/it]
  1%|▏         | 7913/569592 [6:39:51<433:17:50,  2.78s/it]
                                                           

  1%|▏         | 7913/569592 [6:39:52<433:17:50,  2.78s/it]
  1%|▏         | 7914/569592 [6:39:55<468:23:32,  3.00s/it]
                                                           

  1%|▏         | 7914/569592 [6:39:55<468:23:32,  3.00s/it]
  1%|▏         | 7915/569592 [6:39:56<373:12:17,  2.39s/it]
                                                           

  1%|▏         | 7915/569592 [6:39:56<373:12:17,  2.39s/it]
  1%|▏         | 7916/569592 [6:40:01<489:11:05,  3.14s/it]
                                                           

  1%|▏         | 7916/569592 [6:40:01<489:11:05,  3.14s/it]
  1%|▏         | 7917/569592 [6:40:02<388:18:23,  2.49s/it]
                                                           

  1%|▏         | 7917/569592 [6:40:02<388:18:23,  2.49s/it]
  1%|▏         | 7918/569592 [6:40:06<455:10:48,  2.92s/it]
                           /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90750000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                

  1%|▏         | 7918/569592 [6:40:06<455:10:48,  2.92s/it]
  1%|▏         | 7919/569592 [6:40:10<500:55:05,  3.21s/it]
                                                           

  1%|▏         | 7919/569592 [6:40:10<500:55:05,  3.21s/it]
  1%|▏         | 7920/569592 [6:40:14<570:10:08,  3.65s/it]
                                                           

  1%|▏         | 7920/569592 [6:40:14<570:10:08,  3.65s/it]
  1%|▏         | 7921/569592 [6:40:15<442:39:25,  2.84s/it]
                                                           

  1%|▏         | 7921/569592 [6:40:15<442:39:25,  2.84s/it]
  1%|▏         | 7922/569592 [6:40:19<467:03:55,  2.99s/it]
                                                           

  1%|▏         | 7922/569592 [6:40:19<467:03:55,  2.99s/it]
  1%|▏         | 7923/569592 [6:40:20<371:13:44,  2.38s/it]
                                                           

  1%|▏         | 7923/569592 [6:40:20<371:13:44,  2.38s/it]
  1%|▏         | 7924/569592 [6:40:23<442:40:12,  2.84s/it]
                                                           

  1%|▏         | 7924/569592 [6:40:23<442:40:12,  2.84s/it]
  1%|▏         | 7925/569592 [6:40:27<477:25:52,  3.06s/it]
                                                           

  1%|▏         | 7925/569592 [6:40:27<477:25:52,  3.06s/it]
  1%|▏         | 7926/569592 [6:40:28<378:49:02,  2.43s/it]
                                                           

  1%|▏         | 7926/569592 [6:40:28<378:49:02,  2.43s/it]
  1%|▏         | 7927/569592 [6:40:29<309:35:38,  1.98s/it]
                                                           

  1%|▏         | 7927/569592 [6:40:29<309:35:38,  1.98s/it]
  1%|▏         | 7928/569592 [6:40:30<263:52:02,  1.69s/it]
                                                           

  1%|▏         | 7928/569592 [6:40:30<263:52:02,  1.69s/it]
  1%|▏         | 7929/569592 [6:40:33<343:01:36,  2.20s/it]
                                                           

  1%|▏         | 7929/569592 [6:40:33<343:01:36,  2.20s/it]
  1%|▏         | 7930/569592 [6:40:34<283:09:41,  1.81s/it]
                                                           

  1%|▏         | 7930/569592 [6:40:34<283:09:41,  1.81s/it]
  1%|▏         | 7931/569592 [6:40:38<359:06:17,  2.30s/it]
                                                           

  1%|▏         | 7931/569592 [6:40:38<359:06:17,  2.30s/it]
  1%|▏         | 7932/569592 [6:40:42<433:08:38,  2.78s/it]
                                                           

  1%|▏         | 7932/569592 [6:40:42<433:08:38,  2.78s/it]
  1%|▏         | 7933/569592 [6:40:45<481:40:17,  3.09s/it]
                                                           

  1%|▏         | 7933/569592 [6:40:45<481:40:17,  3.09s/it]
  1%|▏         | 7934/569592 [6:40:46<383:11:07,  2.46s/it]
                                                           

  1%|▏         | 7934/569592 [6:40:46<383:11:07,  2.46s/it]
  1%|▏         | 7935/569592 [6:40:47<315:48:29,  2.02s/it]
                                                           

  1%|▏         | 7935/569592 [6:40:47<315:48:29,  2.02s/it]
  1%|▏         | 7936/569592 [6:40:51<389:44:56,  2.50s/it]
                                                           

  1%|▏         | 7936/569592 [6:40:51<389:44:56,  2.50s/it]
  1%|▏         | 7937/569592 [6:40:52<317:47:47,  2.04s/it]
                                                           

  1%|▏         | 7937/569592 [6:40:52<317:47:47,  2.04s/it]
  1%|▏         | 7938/569592 [6:40:53<268:07:23,  1.72s/it]
                                                           

  1%|▏         | 7938/569592 [6:40:53<268:07:23,  1.72s/it]
  1%|▏         | 7939/569592 [6:40:54<231:43:05,  1.49s/it]
                                                           

  1%|▏         | 7939/569592 [6:40:54<231:43:05,  1.49s/it]
  1%|▏         | 7940/569592 [6:40:57<320:33:37,  2.05s/it]
                                                           

  1%|▏         | 7940/569592 [6:40:57<320:33:37,  2.05s/it]
  1%|▏         | 7941/569592 [6:40:59<289:41:49,  1.86s/it]
                                                           

  1%|▏         | 7941/569592 [6:40:59<289:41:49,  1.86s/it]
  1%|▏         | 7942/569592 [6:41:02<366:32:53,  2.35s/it]
                                                           

  1%|▏         | 7942/569592 [6:41:02<366:32:53,  2.35s/it]
  1%|▏         | 7943/569592 [6:41:03<301:14:24,  1.93s/it]
                                                           

  1%|▏         | 7943/569592 [6:41:03<301:14:24,  1.93s/it]
  1%|▏         | 7944/569592 [6:41:07<383:49:43,  2.46s/it]
                                                           

  1%|▏         | 7944/569592 [6:41:07<383:49:43,  2.46s/it]
  1%|▏         | 7945/569592 [6:41:08<341:22:02,  2.19s/it]
                                                           

  1%|▏         | 7945/569592 [6:41:08<341:22:02,  2.19s/it]
  1%|▏         | 7946/569592 [6:41:12<416:56:45,  2.67s/it]
                                                           

  1%|▏         | 7946/569592 [6:41:12<416:56:45,  2.67s/it]
  1%|▏         | 7947/569592 [6:41:14<365:42:37,  2.34s/it]
                                                           

  1%|▏         | 7947/569592 [6:41:14<365:42:37,  2.34s/it]
  1%|▏         | 7948/569592 [6:41:17<418:21:39,  2.68s/it]
                                                           

  1%|▏         | 7948/569592 [6:41:17<418:21:39,  2.68s/it]
  1%|▏         | 7949/569592 [6:41:18<342:11:25,  2.19s/it]
                                                           

  1%|▏         | 7949/569592 [6:41:18<342:11:25,  2.19s/it]
  1%|▏         | 7950/569592 [6:41:22<424:47:34,  2.72s/it]
                                                           

  1%|▏         | 7950/569592 [6:41:22<424:47:34,  2.72s/it]
  1%|▏         | 7951/569592 [6:41:23<343:09:01,  2.20s/it]
                                                           

  1%|▏         | 7951/569592 [6:41:23<343:09:01,  2.20s/it]
  1%|▏         | 7952/569592 [6:41:26<392:16:31,  2.51s/it]
                                                           

  1%|▏         | 7952/569592 [6:41:26<392:16:31,  2.51s/it]
  1%|▏         | 7953/569592 [6:41:29<393:39:16,  2.52s/it]
                                                           

  1%|▏         | 7953/569592 [6:41:29<393:39:16,  2.52s/it]
  1%|▏         | 7954/569592 [6:41:34<491:27:28,  3.15s/it]
                                                           

  1%|▏         | 7954/569592 [6:41:34<491:27:28,  3.15s/it]
  1%|▏         | 7955/569592 [6:41:37<506:41:06,  3.25s/it]
                                                           

  1%|▏         | 7955/569592 [6:41:37<506:41:06,  3.25s/it]
  1%|▏         | 7956/569592 [6:41:41<528:04:03,  3.38s/it]
                                                           

  1%|▏         | 7956/569592 [6:41:41<528:04:03,  3.38s/it]
  1%|▏         | 7957/569592 [6:41:44<540:18:09,  3.46s/it]
                                                           

  1%|▏         | 7957/569592 [6:41:44<540:18:09,  3.46s/it]
  1%|▏         | 7958/569592 [6:41:48<537:51:49,  3.45s/it]
                                                           

  1%|▏         | 7958/569592 [6:41:48<537:51:49,  3.45s/it]
  1%|▏         | 7959/569592 [6:41:49<420:35:33,  2.70s/it]
                                                           

  1%|▏         | 7959/569592 [6:41:49<420:35:33,  2.70s/it]
  1%|▏         | 7960/569592 [6:41:50<340:51:48,  2.18s/it]
                                                           

  1%|▏         | 7960/569592 [6:41:50<340:51:48,  2.18s/it]
  1%|▏         | 7961/569592 [6:41:53<411:32:49,  2.64s/it]
                                                           

  1%|▏         | 7961/569592 [6:41:54<411:32:49,  2.64s/it]
  1%|▏         | 7962/569592 [6:41:57<456:34:10,  2.93s/it]
                                                           

  1%|▏         | 7962/569592 [6:41:57<456:34:10,  2.93s/it]
  1%|▏         | 7963/569592 [6:42:01<484:52:20,  3.11s/it]
                                                           

  1%|▏         | 7963/569592 [6:42:01<484:52:20,  3.11s/it]
  1%|▏         | 7964/569592 [6:42:02<382:59:31,  2.45s/it]
                                                           

  1%|▏         | 7964/569592 [6:42:02<382:59:31,  2.45s/it]
  1%|▏         | 7965/569592 [6:42:05<424:33:45,  2.72s/it]
                                                           

  1%|▏         | 7965/569592 [6:42:05<424:33:45,  2.72s/it]
  1%|▏         | 7966/569592 [6:42:06<344:24:28,  2.21s/it]
                                                           

  1%|▏         | 7966/569592 [6:42:06<344:24:28,  2.21s/it]
  1%|▏         | 7967/569592 [6:42:09<406:30:35,  2.61s/it]
                                                           

  1%|▏         | 7967/569592 [6:42:09<406:30:35,  2.61s/it]
  1%|▏         | 7968/569592 [6:42:13<461:01:05,  2.96s/it]
                                                           

  1%|▏         | 7968/569592 [6:42:13<461:01:05,  2.96s/it]
  1%|▏         | 7969/569592 [6:42:17<477:33:30,  3.06s/it]
                                                           

  1%|▏         | 7969/569592 [6:42:17<477:33:30,  3.06s/it]
  1%|▏         | 7970/569592 [6:42:18<381:13:33,  2.44s/it]
                                                           

  1%|▏         | 7970/569592 [6:42:18<381:13:33,  2.44s/it]
  1%|▏         | 7971/569592 [6:42:18<311:49:51,  2.00s/it]
                                                           

  1%|▏         | 7971/569592 [6:42:18<311:49:51,  2.00s/it]
  1%|▏         | 7972/569592 [6:42:19<263:31:29,  1.69s/it]
                                                           

  1%|▏         | 7972/569592 [6:42:19<263:31:29,  1.69s/it]
  1%|▏         | 7973/569592 [6:42:21<246:22:21,  1.58s/it]
                                                           

  1%|▏         | 7973/569592 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (93641436 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
[6:42:21<246:22:21,  1.58s/it]
  1%|▏         | 7974/569592 [6:42:24<331:56:47,  2.13s/it]
                                                           

  1%|▏         | 7974/569592 [6:42:24<331:56:47,  2.13s/it]
  1%|▏         | 7975/569592 [6:42:27<354:45:42,  2.27s/it]
                                                           

  1%|▏         | 7975/569592 [6:42:27<354:45:42,  2.27s/it]
  1%|▏         | 7976/569592 [6:42:30<414:40:07,  2.66s/it]
                                                           

  1%|▏         | 7976/569592 [6:42:30<414:40:07,  2.66s/it]
  1%|▏         | 7977/569592 [6:42:31<335:41:13,  2.15s/it]
                                                           

  1%|▏         | 7977/569592 [6:42:31<335:41:13,  2.15s/it]
  1%|▏         | 7978/569592 [6:42:36<438:57:20,  2.81s/it]
                                                           

  1%|▏         | 7978/569592 [6:42:36<438:57:20,  2.81s/it]
  1%|▏         | 7979/569592 [6:42:40<493:57:55,  3.17s/it]
                                                           

  1%|▏         | 7979/569592 [6:42:40<493:57:55,  3.17s/it]
  1%|▏         | 7980/569592 [6:42:43<509:44:03,  3.27s/it]
                                                           

  1%|▏         | 7980/569592 [6:42:43<509:44:03,  3.27s/it]
  1%|▏         | 7981/569592 [6:42:44<400:56:04,  2.57s/it]
                                                           

  1%|▏         | 7981/569592 [6:42:44<400:56:04,  2.57s/it]
  1%|▏         | 7982/569592 [6:42:48<476:43:45,  3.06s/it]
                                                           

  1%|▏         | 7982/569592 [6:42:48<476:43:45,  3.06s/it]
  1%|▏         | 7983/569592 [6:42:53<561:20:47,  3.60s/it]
                                                           

  1%|▏         | 7983/569592 [6:42:53<561:20:47,  3.60s/it]
  1%|▏         | 7984/569592 [6:42:56<539:41:06,  3.46s/it]
                                                           

  1%|▏         | 7984/569592 [6:42:56<539:41:06,  3.46s/it]
  1%|▏         | 7985/569592 [6:43:00<533:35:10,  3.42s/it]
                                                           

  1%|▏         | 7985/569592 [6:43:00<533:35:10,  3.42s/it]
  1%|▏         | 7986/569592 [6:43:03<547:24:12,  3.51s/it]
                                                           

  1%|▏         | 7986/569592 [6:43:03<547:24:12,  3.51s/it]
  1%|▏         | 7987/569592 [6:43:10<673:23:39,  4.32s/it]
                                                           

  1%|▏         | 7987/569592 [6:43:10<673:23:39,  4.32s/it]
  1%|▏         | 7988/569592 [6:43:13<640:36:57,  4.11s/it]
                                                           

  1%|▏         | 7988/569592 [6:43:13<640:36:57,  4.11s/it]
  1%|▏         | 7989/569592 [6:43:17<630:20:32,  4.04s/it]
                                                           

  1%|▏         | 7989/569592 [6:43:17<630:20:32,  4.04s/it]
  1%|▏         | 7990/569592 [6:43:18<483:43:01,  3.10s/it]
                                                           

  1%|▏         | 7990/569592 [6:43:18<483:43:01,  3.10s/it]
  1%|▏         | 7991/569592 [6:43:21<503:29:25,  3.23s/it]
                                                           

  1%|▏         | 7991/569592 [6:43:21<503:29:25,  3.23s/it]
  1%|▏         | 7992/569592 [6:43:25<507:57:59,  3.26s/it]
                                                           

  1%|▏         | 7992/569592 [6:43:25<507:57:59,  3.26s/it]
  1%|▏         | 7993/569592 [6:43:28<518:00:56,  3.32s/it]
                                                           

  1%|▏         | 7993/569592 [6:43:28<518:00:56,  3.32s/it]
  1%|▏         | 7994/569592 [6:43:33<581:17:26,  3.73s/it]
                                                           

  1%|▏         | 7994/569592 [6:43:33<581:17:26,  3.73s/it]
  1%|▏         | 7995/569592 [6:43:36<552:22:30,  3.54s/it]
                                                           

  1%|▏         | 7995/569592 [6:43:36<552:22:30,  3.54s/it]
  1%|▏         | 7996/569592 [6:43:41<625:13:17,  4.01s/it]
                                                           

  1%|▏         | 7996/569592 [6:43:41<625:13:17,  4.01s/it]
  1%|▏         | 7997/569592 [6:43:44<589:49:02,  3.78s/it]
                                                           

  1%|▏         | 7997/569592 [6:43:44<589:49:02,  3.78s/it]
  1%|▏         | 7998/569592 [6:43:48<567:37:44,  3.64s/it]
                                                           

  1%|▏         | 7998/569592 [6:43:48<567:37:44,  3.64s/it]
  1%|▏         | 7999/569592 [6:43:51<544:17:18,  3.49s/it]
                                                           

  1%|▏         | 7999/569592 [6:43:51<544:17:18,  3.49s/it]
  1%|▏         | 8000/569592 [6:43:52<425:41:22,  2.73s/it]
                                                           

  1%|▏         | 8000/569592 [6:43:52<425:41:22,  2.73s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-8000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-8000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-8000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-8000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-8000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-8000/special_tokens_map.json
Deleting older checkpoint [/fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-7000] due to args.save_total_limit

  1%|▏         | 8001/569592 [6:45:51<5873:17:33, 37.65s/it]
                                                            

  1%|▏         | 8001/569592 [6:45:51<5873:17:33, 37.65s/it]
  1%|▏         | 8002/569592 [6:45:54<4271:50:39, 27.38s/it]
                                                            

  1%|▏         | 8002/569592 [6:45:54<4271:50:39, 27.38s/it]
  1%|▏         | 8003/569592 [6:45:58<3169:52:30, 20.32s/it]
                                                            

  1%|▏         | 8003/569592 [6:45:58<3169:52:30, 20.32s/it]
  1%|▏         | 8004/569592 [6:45:59<2261:40:46, 14.50s/it]
                                                            

  1%|▏         | 8004/569592 [6:45:59<2261:40:46, 14.50s/it]
  1%|▏         | 8005/569592 [6:46:03<1756:24:34, 11.26s/it]
                                                            

  1%|▏         | 8005/569592 [6:46:03<1756:24:34, 11.26s/it]
  1%|▏         | 8006/569592 [6:46:07<1429:00:59,  9.16s/it]
                    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (95835312 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                        

  1%|▏         | 8006/569592 [6:46:07<1429:00:59,  9.16s/it]
  1%|▏         | 8007/569592 [6:46:08<1044:15:22,  6.69s/it]
                                                            

  1%|▏         | 8007/569592 [6:46:08<1044:15:22,  6.69s/it]
  1%|▏         | 8008/569592 [6:46:09<776:13:24,  4.98s/it] 
                                                           

  1%|▏         | 8008/569592 [6:46:09<776:13:24,  4.98s/it]
  1%|▏         | 8009/569592 [6:46:12<704:02:02,  4.51s/it]
                                                           

  1%|▏         | 8009/569592 [6:46:12<704:02:02,  4.51s/it]
  1%|▏         | 8010/569592 [6:46:16<680:17:28,  4.36s/it]
                                                           

  1%|▏         | 8010/569592 [6:46:16<680:17:28,  4.36s/it]
  1%|▏         | 8011/569592 [6:46:20<632:24:35,  4.05s/it]
                                                           

  1%|▏         | 8011/569592 [6:46:20<632:24:35,  4.05s/it]
  1%|▏         | 8012/569592 [6:46:24<621:37:45,  3.98s/it]
                                                           

  1%|▏         | 8012/569592 [6:46:24<621:37:45,  3.98s/it]
  1%|▏         | 8013/569592 [6:46:28<621:05:26,  3.98s/it]
                                                           

  1%|▏         | 8013/569592 [6:46:28<621:05:26,  3.98s/it]
  1%|▏         | 8014/569592 [6:46:32<643:12:00,  4.12s/it]
                                                           

  1%|▏         | 8014/569592 [6:46:32<643:12:00,  4.12s/it]
  1%|▏         | 8015/569592 [6:46:33<491:15:30,  3.15s/it]
                                                           

  1%|▏         | 8015/569592 [6:46:33<491:15:30,  3.15s/it]
  1%|▏         | 8016/569592 [6:46:34<386:50:09,  2.48s/it]
                                                           

  1%|▏         | 8016/569592 [6:46:34<386:50:09,  2.48s/it]
  1%|▏         | 8017/569592 [6:46:38<468:24:52,  3.00s/it]
                                                           

  1%|▏         | 8017/569592 [6:46:38<468:24:52,  3.00s/it]
  1%|▏         | 8018/569592 [6:46:41<481:54:42,  3.09s/it]
                                                           

  1%|▏         | 8018/569592 [6:46:41<481:54:42,  3.09s/it]
  1%|▏         | 8019/569592 [6:46:42<383:22:45,  2.46s/it]
                                                           

  1%|▏         | 8019/569592 [6:46:42<383:22:45,  2.46s/it]
  1%|▏         | 8020/569592 [6:46:46<446:33:19,  2.86s/it]
                                                           

  1%|▏         | 8020/569592 [6:46:46<446:33:19,  2.86s/it]
  1%|▏         | 8021/569592 [6:46:47<357:02:10,  2.29s/it]
                                                           

  1%|▏         | 8021/569592 [6:46:47<357:02:10,  2.29s/it]
  1%|▏         | 8022/569592 [6:46:52<482:25:43,  3.09s/it]
                                                           

  1%|▏         | 8022/569592 [6:46:52<482:25:43,  3.09s/it]
  1%|▏         | 8023/569592 [6:46:56<523:22:19,  3.36s/it]
                                                           

  1%|▏         | 8023/569592 [6:46:56<523:22:19,  3.36s/it]
  1%|▏         | 8024/569592 [6:46:59<520:21:17,  3.34s/it]
                                                           

  1%|▏         | 8024/569592 [6:46:59<520:21:17,  3.34s/it]
  1%|▏         | 8025/569592 [6:47:00<407:00:45,  2.61s/it]
                                                           

  1%|▏         | 8025/569592 [6:47:00<407:00:45,  2.61s/it]
  1%|▏         | 8026/569592 [6:47:01<328:47:43,  2.11s/it]
                                                           

  1%|▏         | 8026/569592 [6:47:01<328:47:43,  2.11s/it]
  1%|▏         | 8027/569592 [6:47:05<409:26:12,  2.62s/it]
                                                           

  1%|▏         | 8027/569592 [6:47:05<409:26:12,  2.62s/it]
  1%|▏         | 8028/569592 [6:47:09<459:38:36,  2.95s/it]
                                                           

  1%|▏         | 8028/569592 [6:47:09<459:38:36,  2.95s/it]
  1%|▏         | 8029/569592 [6:47:10<368:15:09,  2.36s/it]
                                                           

  1%|▏         | 8029/569592 [6:47:10<368:15:09,  2.36s/it]
  1%|▏         | 8030/569592 [6:47:13<431:12:27,  2.76s/it]
                                                           

  1%|▏         | 8030/569592 [6:47:13<431:12:27,  2.76s/it]
  1%|▏         | 8031/569592 [6:47:14<348:53:56,  2.24s/it]
                                                           

  1%|▏         | 8031/569592 [6:47:14<348:53:56,  2.24s/it]
  1%|▏         | 8032/569592 [6:47:19<468:16:39,  3.00s/it]
                                                           

  1%|▏         | 8032/569592 [6:47:19<468:16:39,  3.00s/it]
  1%|▏         | 8033/569592 [6:47:20<373:17:01,  2.39s/it]
                                                           

  1%|▏         | 8033/569592 [6:47:20<373:17:01,  2.39s/it]
  1%|▏         | 8034/569592 [6:47:24<431:28:32,  2.77s/it]
                                                           

  1%|▏         | 8034/569592 [6:47:24<431:28:32,  2.77s/it]
  1%|▏         | 8035/569592 [6:47:28<489:59:12,  3.14s/it]
                                                           

  1%|▏         | 8035/569592 [6:47:28<489:59:12,  3.14s/it]
  1%|▏         | 8036/569592 [6:47:31<500:05:33,  3.21s/it]
                                                           

  1%|▏         | 8036/569592 [6:47:31<500:05:33,  3.21s/it]
  1%|▏         | 8037/569592 [6:47:32<393:04:43,  2.52s/it]
                                                           

  1%|▏         | 8037/569592 [6:47:32<393:04:43,  2.52s/it]
  1%|▏         | 8038/569592 [6:47:33<319:55:29,  2.05s/it]
                                                           

  1%|▏         | 8038/569592 [6:47:33<319:55:29,  2.05s/it]
  1%|▏         | 8039/569592 [6:47:36<385:36:51,  2.47s/it]
                                                           

  1%|▏         | 8039/569592 [6:47:36<385:36:51,  2.47s/it]
  1%|▏         | 8040/569592 [6:47:37<314:34:03,  2.02s/it]
                                                           

  1%|▏         | 8040/569592 [6:47:37<314:34:03,  2.02s/it]
  1%|▏         | 8041/569592 [6:47:41<389:59:54,  2.50s/it]
                                                           

  1%|▏         | 8041/569592 [6:47:41<389:59:54,  2.50s/it]
  1%|▏         | 8042/569592 [6:47:42<318:44:58,  2.04s/it]
                                                           

  1%|▏         | 8042/569592 [6:47:42<318:44:58,  2.04s/it]
  1%|▏         | 8043/569592 [6:47:46<390:32:59,  2.50s/it]
                                                           

  1%|▏         | 8043/569592 [6:47:46<390:32:59,  2.50s/it]
  1%|▏         | 8044/569592 [6:47:47<317:52:12,  2.04s/it]
                                                           

  1%|▏         | 8044/569592 [6:47:47<317:52:12,  2.04s/it]
  1%|▏         | 8045/569592 [6:47:52<454:26:49,  2.91s/it]
                                                           

  1%|▏         | 8045/569592 [6:47:52<454:26:49,  2.91s/it]
  1%|▏         | 8046/569592 [6:47:55<475:51:17,  3.05s/it]
                                                           

  1%|▏         | 8046/569592 [6:47:55<475:51:17,  3.05s/it]
  1%|▏         | 8047/569592 [6:47:59<512:54:38,  3.29s/it]
                                                           

  1%|▏         | 8047/569592 [6:47:59<512:54:38,  3.29s/it]
  1%|▏         | 8048/569592 [6:48:04<583:49:59,  3.74s/it]
                                                           

  1%|▏         | 8048/569592 [6:48:04<583:49:59,  3.74s/it]
  1%|▏         | 8049/569592 [6:48:07<573:06:34,  3.67s/it]
                                                           

  1%|▏         | 8049/569592 [6:48:07<573:06:34,  3.67s/it]
  1%|▏         | 8050/569592 [6:48:08<443:59:56,  2.85s/it]
                                                           

  1%|▏         | 8050/569592 [6:48:08<443:59:56,  2.85s/it]
  1%|▏         | 8051/569592 [6:48:11<462:36:43,  2.97s/it]
                                                           

  1%|▏         | 8051/569592 [6:48:11<462:36:43,  2.97s/it]
  1%|▏         | 8052/569592 [6:48:12<368:55:04,  2.37s/it]
                                                           

  1%|▏         | 8052/569592 [6:48:12<368:55:04,  2.37s/it]
  1%|▏         | 8053/569592 [6:48:13<302:38:50,  1.94s/it]
                                                           

  1%|▏         | 8053/569592 [6:48:13<302:38:50,  1.94s/it]
  1%|▏         | 8054/569592 [6:48:14<257:48:49,  1.65s/it]
                                                           

  1%|▏         | 8054/569592 [6:48:14<257:48:49,  1.65s/it]
  1%|▏         | 8055/569592 [6:48:18<378:55:09,  2.43s/it]
                                                           

  1%|▏         | 8055/569592 [6:48:18<378:55:09,  2.43s/it]
  1%|▏         | 8056/569592 [6:48:19<315:11:01,  2.02s/it]
                                                           

  1%|▏         | 8056/569592 [6:48:19<315:11:01,  2.02s/it]
  1%|▏         | 8057/569592 [6:48:23<386:23:29,  2.48s/it]
                                                           

  1%|▏         | 8057/569592 [6:48:23<386:23:29,  2.48s/it]
  1%|▏         | 8058/569592 [6:48:24<316:38:37,  2.03s/it]
                                                           

  1%|▏         | 8058/569592 [6:48:24<316:38:37,  2.03s/it]
  1%|▏         | 8059/569592 [6:48:28<394:18:02,  2.53s/it]
                                                           

  1%|▏         | 8059/569592 [6:48:28<394:18:02,  2.53s/it]
  1%|▏         | 8060/569592 [6:48:29<321:23:50,  2.06s/it]
                                                           

  1%|▏         | 8060/569592 [6:48:29<321:23:50,  2.06s/it]
  1%|▏         | 8061/569592 [6:48:32<379:37:45,  2.43s/it]
                                                           

  1%|▏         | 8061/569592 [6:48:32<379:37:45,  2.43s/it]
  1%|▏         | 8062/569592 [6:48:33<308:11:16,  1.98s/it]
                                                           

  1%|▏         | 8062/569592 [6:48:33<308:11:16,  1.98s/it]
  1%|▏         | 8063/569592 [6:48:37<403:52:40,  2.59s/it]
                                                           

  1%|▏         | 8063/569592 [6:48:37<403:52:40,  2.59s/it]
  1%|▏         | 8064/569592 [6:48:38<327:52:42,  2.10s/it]
                                                           

  1%|▏         | 8064/569592 [6:48:38<327:52:42,  2.10s/it]
  1%|▏         | 8065/569592 [6:48:42<411:30:38,  2.64s/it]
                                                           

  1%|▏         | 8065/569592 [6:48:42<411:30:38,  2.64s/it]
  1%|▏         | 8066/569592 [6:48:43<335:03:42,  2.15s/it]
                                                           

  1%|▏         | 8066/569592 [6:48:44<335:03:42,  2.15s/it]
  1%|▏         | 8067/569592 [6:48:47<414:00:43,  2.65s/it]
                                                           

  1%|▏         | 8067/569592 [6:48:47<414:00:43,  2.65s/it]
  1%|▏         | 8068/569592 [6:48:48<337:47:53,  2.17s/it]
                                                           

  1%|▏         | 8068/569592 [6:48:48<337:47:53,  2.17s/it]
  1%|▏         | 8069/569592 [6:48:52<436:41:44,  2.80s/it]
                                                           

  1%|▏         | 8069/569592 [6:48:52<436:41:44,  2.80s/it]
  1%|▏         | 8070/569592 [6:48:56<482:06:38,  3.09s/it]
                                                           

  1%|▏         | 8070/569592 [6:48:56<482:06:38,  3.09s/it]
  1%|▏         | 8071/569592 [6:48:59<506:42:29,  3.25s/it]
                                                           

  1%|▏         | 8071/569592 [6:48:59<506:42:29,  3.25s/it]
  1%|▏         | 8072/569592 [6:49:03<552:35:09,  3.54s/it]
                                                           

  1%|▏         | 8072/569592 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (103117440 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
[6:49:03<552:35:09,  3.54s/it]
  1%|▏         | 8073/569592 [6:49:07<571:39:22,  3.66s/it]
                                                           

  1%|▏         | 8073/569592 [6:49:07<571:39:22,  3.66s/it]
  1%|▏         | 8074/569592 [6:49:08<442:04:31,  2.83s/it]
                                                           

  1%|▏         | 8074/569592 [6:49:08<442:04:31,  2.83s/it]
  1%|▏         | 8075/569592 [6:49:13<530:41:59,  3.40s/it]
                                                           

  1%|▏         | 8075/569592 [6:49:13<530:41:59,  3.40s/it]
  1%|▏         | 8076/569592 [6:49:16<530:23:19,  3.40s/it]
                                                           

  1%|▏         | 8076/569592 [6:49:16<530:23:19,  3.40s/it]
  1%|▏         | 8077/569592 [6:49:17<414:31:32,  2.66s/it]
                                                           

  1%|▏         | 8077/569592 [6:49:17<414:31:32,  2.66s/it]
  1%|▏         | 8078/569592 [6:49:18<338:11:54,  2.17s/it]
                                                           

  1%|▏         | 8078/569592 [6:49:18<338:11:54,  2.17s/it]
  1%|▏         | 8079/569592 [6:49:22<402:36:03,  2.58s/it]
                                                           

  1%|▏         | 8079/569592 [6:49:22<402:36:03,  2.58s/it]
  1%|▏         | 8080/569592 [6:49:25<440:29:42,  2.82s/it]
                                                           

  1%|▏         | 8080/569592 [6:49:25<440:29:42,  2.82s/it]
  1%|▏         | 8081/569592 [6:49:29<465:50:41,  2.99s/it]
                                                           

  1%|▏         | 8081/569592 [6:49:29<465:50:41,  2.99s/it]
  1%|▏         | 8082/569592 [6:49:30<373:21:45,  2.39s/it]
                                                           

  1%|▏         | 8082/569592 [6:49:30<373:21:45,  2.39s/it]
  1%|▏         | 8083/569592 [6:49:31<310:35:42,  1.99s/it]
                                                           

  1%|▏         | 8083/569592 [6:49:31<310:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (94638025 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
35:42,  1.99s/it]
  1%|▏         | 8084/569592 [6:49:35<406:37:30,  2.61s/it]
                                                           

  1%|▏         | 8084/569592 [6:49:35<406:37:30,  2.61s/it]
  1%|▏         | 8085/569592 [6:49:39<474:31:21,  3.04s/it]
                                                           

  1%|▏         | 8085/569592 [6:49:39<474:31:21,  3.04s/it]
  1%|▏         | 8086/569592 [6:49:40<376:31:26,  2.41s/it]
                                                           

  1%|▏         | 8086/569592 [6:49:40<376:31:26,  2.41s/it]
  1%|▏         | 8087/569592 [6:49:41<310:10:22,  1.99s/it]
                                                           

  1%|▏         | 8087/569592 [6:49:41<310:10:22,  1.99s/it]
  1%|▏         | 8088/569592 [6:49:42<262:48:40,  1.68s/it]
                                                           

  1%|▏         | 8088/569592 [6:49:42<262:48:40,  1.68s/it]
  1%|▏         | 8089/569592 [6:49:43<230:19:04,  1.48s/it]
                                                           

  1%|▏         | 8089/569592 [6:49:43<230:19:04,  1.48s/it]
  1%|▏         | 8090/569592 [6:49:46<320:16:59,  2.05s/it]
                                                           

  1%|▏         | 8090/569592 [6:49:46<320:16:59,  2.05s/it]
  1%|▏         | 8091/569592 [6:49:50<415:48:52,  2.67s/it]
                                                           

  1%|▏         | 8091/569592 [6:49:50<415:48:52,  2.67s/it]
  1%|▏         | 8092/569592 [6:49:51<335:02:28,  2.15s/it]
                                                           

  1%|▏         | 8092/569592 [6:49:51<335:02:28,  2.15s/it]
  1%|▏         | 8093/569592 [6:49:55<429:05:45,  2.75s/it]
                                                           

  1%|▏         | 8093/569592 [6:49:55<429:05:45,  2.75s/it]
  1%|▏         | 8094/569592 [6:50:00<503:14:25,  3.23s/it]
                                                           

  1%|▏         | 8094/569592 [6:50:00<503:14:25,  3.23s/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98085130 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
/it]
  1%|▏         | 8095/569592 [6:50:03<508:16:34,  3.26s/it]
                                                           

  1%|▏         | 8095/569592 [6:50:03<508:16:34,  3.26s/it]
  1%|▏         | 8096/569592 [6:50:07<525:44:58,  3.37s/it]
                                                           

  1%|▏         | 8096/569592 [6:50:07<525:44:58,  3.37s/it]
  1%|▏         | 8097/569592 [6:50:13<661:46:24,  4.24s/it]
                                                           

  1%|▏         | 8097/569592 [6:50:13<661:46:24,  4.24s/it]
  1%|▏         | 8098/569592 [6:50:16<628:13:34,  4.03s/it]
                                                           

  1%|▏         | 8098/569592 [6:50:16<628:13:34,  4.03s/it]
  1%|▏         | 8099/569592 [6:50:20<598:47:13,  3.84s/it]
                                                           

  1%|▏         | 8099/569592 [6:50:20<598:47:13,  3.84s/it]
  1%|▏         | 8100/569592 [6:50:24<598:15:01,  3.84s/it]
                                                           

  1%|▏         | 8100/569592 [6:50:24<598:15:01,  3.84s/it]
  1%|▏         | 8101/569592 [6:50:28<620:16:04,  3.98s/it]
                                                           

  1%|▏         | 8101/569592 [6:50:28<620:16:04,  3.98s/it]
  1%|▏         | 8102/569592 [6:50:32<631:02:52,  4.05s/it]
                                                           

  1%|▏         | 8102/569592 [6:50:32<631:02:52,  4.05s/it]
  1%|▏         | 8103/569592 [6:50:36<613:29:11,  3.93s/it]
                                                           

  1%|▏         | 8103/569592 [6:50:36<613:29:11,  3.93s/it]
  1%|▏         | 8104/569592 [6:50:39<593:43:44,  3.81s/it]
                                                           

  1%|▏         | 8104/569592 [6:50:39<593:43:44,  3.81s/it]
  1%|▏         | 8105/569592 [6:50:43<596:59:18,  3.83s/it]
                                                           

  1%|▏         | 8105/569592 [6:50:43<596:59:18,  3.83s/it]
  1%|▏/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91375000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
         | 8106/569592 [6:50:47<583:30:54,  3.74s/it]
                                                           

  1%|▏         | 8106/569592 [6:50:47<583:30:54,  3.74s/it]
  1%|▏         | 8107/569592 [6:50:48<454:03:57,  2.91s/it]
                                                           

  1%|▏         | 8107/569592 [6:50:48<454:03:57,  2.91s/it]
  1%|▏         | 8108/569592 [6:50:52<500:28:17,  3.21s/it]
                                                           

  1%|▏         | 8108/569592 [6:50:52<500:28:17,  3.21s/it]
  1%|▏         | 8109/569592 [6:50:55<512:28:14,  3.29s/it]
                                                           

  1%|▏         | 8109/569592 [6:50:55<512:28:14,  3.29s/it]
  1%|▏         | 8110/569592 [6:50:58<514:06:29,  3.30s/it]
                                                           

  1%|▏         | 8110/569592 [6:50:58<514:06:29,  3.30s/it]
  1%|▏         | 8111/569592 [6:51:02<543:36:23,  3.49s/it]
                                                           

  1%|▏         | 8111/569592 [6:51:02<543:36:23,  3.49s/it]
  1%|▏         | 8112/569592 [6:51:08<640:07:10,  4.10s/it]
                                                           

  1%|▏         | 8112/569592 [6:51:08<640:07:10,  4.10s/it]
  1%|▏         | 8113/569592 [6:51:11<589:16:26,  3.78s/it]
                                                           

  1%|▏         | 8113/569592 [6:51:11<589:16:26,  3.78s/it]
  1%|▏         | 8114/569592 [6:51:14<550:23:32,  3.53s/it]
                                                           

  1%|▏         | 8114/569592 [6:51:14<550:23:32,  3.53s/it]
  1%|▏         | 8115/569592 [6:51:18<560:46:28,  3.60s/it]
                                                           

  1%|▏         | 8115/569592 [6:51:18<560:46:28,  3.60s/it]
  1%|▏         | 8116/569592 [6:51:19<436:25:41,  2.80s/it]
                                                           

  1%|▏         | 8116/569592 [6:51:19<436:25:41,  2.80s/it]
  1%|▏         | 8117/569592 [6:51:20<350:32:07,  2.25s/it]
                                                           

  1%|▏         | 8117/569592 [6:51:20<350:32:07,  2.25s/it]
  1%|▏         | 8118/569592 [6:51:21<290:36:49,  1.86s/it]
                                                           

  1%|▏         | 8118/569592 [6:51:21<290:36:49,  1.86s/it]
  1%|▏         | 8119/569592 [6:51:25<406:11:43,  2.60s/it]
                                                           

  1%|▏         | 8119/569592 [6:51:25<406:11:43,  2.60s/it]
  1%|▏         | 8120/569592 [6:51:28<439:46:45,  2.82s/it]
                                                           

  1%|▏         | 8120/569592 [6:51:28<439:46:45,  2.82s/it]
  1%|▏         | 8121/569592 [6:51:29<351:01:15,  2.25s/it]
                                                           

  1%|▏         | 8121/569592 [6:51:29<351:01:15,  2.25s/it]
  1%|▏         | 8122/569592 [6:51:33<417:08:38,  2.67s/it]
                                                           

  1%|▏         | 8122/569592 [6:51:33<417:08:38,  2.67s/it]
  1%|▏         | 8123/569592 [6:51:37<478:27:55,  3.07s/it]
                                                           

  1%|▏         | 8123/569592 [6:51:37<478:27:55,  3.07s/it]
  1%|▏         | 8124/569592 [6:51:40<505:33:39,  3.24s/it]
                                                           

  1%|▏         | 8124/569592 [6:51:40<505:33:39,  3.24s/it]
  1%|▏         | 8125/569592 [6:51:44<531:09:49,  3.41s/it]
                                                           

  1%|▏         | 8125/569592 [6:51:44<531:09:49,  3.41s/it]
  1%|▏         | 8126/569592 [6:51:47<518:17:04,  3.32s/it]
                                                           

  1%|▏         | 8126/569592 [6:51:47<518:17:04,  3.32s/it]
  1%|▏         | 8127/569592 [6:51:51<521:42:40,  3.35s/it]
                                                           

  1%|▏         | 8127/569592 [6:51:51<521:42:40,  3.35s/it]
  1%|▏         | 8128/569592 [6:/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (97128300 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
51:52<407:22:33,  2.61s/it]
                                                           

  1%|▏         | 8128/569592 [6:51:52<407:22:33,  2.61s/it]
  1%|▏         | 8129/569592 [6:51:55<448:53:03,  2.88s/it]
                                                           

  1%|▏         | 8129/569592 [6:51:55<448:53:03,  2.88s/it]
  1%|▏         | 8130/569592 [6:51:58<469:11:39,  3.01s/it]
                                                           

  1%|▏         | 8130/569592 [6:51:58<469:11:39,  3.01s/it]
  1%|▏         | 8131/569592 [6:52:02<498:45:09,  3.20s/it]
                                                           

  1%|▏         | 8131/569592 [6:52:02<498:45:09,  3.20s/it]
  1%|▏         | 8132/569592 [6:52:05<495:42:20,  3.18s/it]
                                                           

  1%|▏         | 8132/569592 [6:52:05<495:42:20,  3.18s/it]
  1%|▏         | 8133/569592 [6:52:08<499:35:11,  3.20s/it]
                                                           

  1%|▏         | 8133/569592 [6:52:08<499:35:11,  3.20s/it]
  1%|▏         | 8134/569592 [6:52:12<504:22:47,  3.23s/it]
                                                           

  1%|▏         | 8134/569592 [6:52:12<504:22:47,  3.23s/it]
  1%|▏         | 8135/569592 [6:52:13<397:01:16,  2.55s/it]
                                                           

  1%|▏         | 8135/569592 [6:52:13<397:01:16,  2.55s/it]
  1%|▏         | 8136/569592 [6:52:16<440:56:21,  2.83s/it]
                                                           

  1%|▏         | 8136/569592 [6:52:16<440:56:21,  2.83s/it]
  1%|▏         | 8137/569592 [6:52:17<358:27:13,  2.30s/it]
                                                           

  1%|▏         | 8137/569592 [6:52:17<358:27:13,  2.30s/it]
  1%|▏         | 8138/569592 [6:52:21<420:57:03,  2.70s/it]
                                                           

  1%|▏         | 8138/569592 [6:52:21<420:57:03,  2.70s/it]
  1%|▏         | 8139/569592 [6:52:25<466:42:17,  2.99s/it]
                                                           

  1%|▏         | 8139/569592 [6:52:25<466:42:17,  2.99s/it]
  1%|▏         | 8140/569592 [6:52:26<372:49:13,  2.39s/it]
                                                           

  1%|▏         | 8140/569592 [6:52:26<372:49:13,  2.39s/it]
  1%|▏         | 8141/569592 [6:52:27<306:22:59,  1.96s/it]
                                                           

  1%|▏         | 8141/569592 [6:52:27<306:22:59,  1.96s/it]
  1%|▏         | 8142/569592 [6:52:28<261:35:25,  1.68s/it]
                                                           

  1%|▏         | 8142/569592 [6:52:28<261:35:25,  1.68s/it]
  1%|▏         | 8143/569592 [6:52:31<336:43:59,  2.16s/it]
                                                           

  1%|▏         | 8143/569592 [6:52:31<336:43:59,  2.16s/it]
  1%|▏         | 8144/569592 [6:52:34<404:26:12,  2.59s/it]
                                                           

  1%|▏         | 8144/569592 [6:52:34<404:26:12,  2.59s/it]
  1%|▏         | 8145/569592 [6:52:38<446:17:15,  2.86s/it]
                                                           

  1%|▏         | 8145/569592 [6:52:38<446:17:15,  2.86s/it]
  1%|▏         | 8146/569592 [6:52:39<357:55:23,  2.30s/it]
                                                           

  1%|▏         | 8146/569592 [6:52:39<357:55:23,  2.30s/it]
  1%|▏         | 8147/569592 [6:52:42<420:13:06,  2.69s/it]
                                                           

  1%|▏         | 8147/569592 [6:52:43<420:13:06,  2.69s/it]
  1%|▏         | 8148/569592 [6:52:43<338:36:02,  2.17s/it]
                                                           

  1%|▏         | 8148/569592 [6:52:43<338:36:02,  2.17s/it]
  1%|▏         | 8149/569592 [6:52:47<402:31:55,  2.58s/it]
                                                           

  1%|▏         | 8149/569592 [6:52:47<402:31:55,  2.58s/it]
  1%|▏         | 8150/569592 [6:52:48<339:09:16,  2.17s/it]
                                                           

  1%|▏         | 8150/569592 [6:52:48<339:09:16,  2.17s/it]
  1%|▏         | 8151/569592 [6:52:52<404:56:22,  2.60s/it]
                                                           

  1%|▏         | 8151/569592 [6:52:52<404:56:22,  2.60s/it]
  1%|▏         | 8152/569592 [6:52:53<327:02:25,  2.10s/it]
                                                           

  1%|▏         | 8152/569592 [6:52:53<327:02:25,  2.10s/it]
  1%|▏         | 8153/569592 [6:52:56<392:58:34,  2.52s/it]
                                                           

  1%|▏         | 8153/569592 [6:52:56<392:58:34,  2.52s/it]
  1%|▏         | 8154/569592 [6:52:57<319:09:00,  2.05s/it]
                                                           

  1%|▏         | 8154/569592 [6:52:57<319:09:00,  2.05s/it]
  1%|▏         | 8155/569592 [6:53:00<377:43:19,  2.42s/it]
                                                           

  1%|▏         | 8155/569592 [6:53:00<377:43:19,  2.42s/it]
  1%|▏         | 8156/569592 [6:53:01<311:15:45,  2.00s/it]
                                                           

  1%|▏         | 8156/569592 [6:53:01<311:15:45,  2.00s/it]
  1%|▏         | 8157/569592 [6:53:02<262:29:15,  1.68s/it]
                                                           

  1%|▏         | 8157/569592 [6:53:02<262:29:15,  1.68s/it]
  1%|▏         | 8158/569592 [6:53:06<360:12:16,  2.31s/it]
                                                           

  1%|▏         | 8158/569592 [6:53:06<360:12:16,  2.31s/it]
  1%|▏         | 8159/569592 [6:53:07<298:13:13,  1.91s/it]
                                                           

  1%|▏         | 8159/569592 [6:53:07<298:13:13,  1.91s/it]
  1%|▏         | 8160/569592 [6:53:11<376:37:44,  2.42s/it]
                                                           

  1%|▏         | 8160/569592 [6:53:11<376:37:44,  2.42s/it]
  1%|▏         | 8161/569592 [6:53:13<351:31:51,  2.25s/it]
                                                           

  1%|▏         | 8161/569592 [6:53:13<351:31:51,  2.25s/it]
  1%|▏         | 8162/569592 [6:53:16<418:17:32,  2.68s/it]
                                                           

  1%|▏         | 8162/569592 [6:53:16<418:17:32,  2.68s/it]
  1%|▏         | 8163/569592 [6:53:20<478:27:45,  3.07s/it]
                                                           

  1%|▏         | 8163/569592 [6:53:20<478:27:45,  3.07s/it]
  1%|▏         | 8164/569592 [6:53:24<497:37:44,  3.19s/it]
                                                           

  1%|▏         | 8164/569592 [6:53:24<497:37:44,  3.19s/it]
  1%|▏         | 8165/569592 [6:53:25<393:20:56,  2.52s/it]
                                                           

  1%|▏         | 8165/569592 [6:53:25<393:20:56,  2.52s/it]
  1%|▏         | 8166/569592 [6:53:26<319:20:28,  2.05s/it]
                                                           

  1%|▏         | 8166/569592 [6:53:26<319:20:28,  2.05s/it]
  1%|▏         | 8167/569592 [6:53:27<308:47:05,  1.98s/it]
                                                           

  1%|▏         | 8167/569592 [6:53:28<308:47:05,  1.98s/it]
  1%|▏         | 8168/569592 [6:53:30<324:27:08,  2.08s/it]
                                                           

  1%|▏         | 8168/569592 [6:53:30<324:27:08,  2.08s/it]
  1%|▏         | 8169/569592 [6:53:31<290:28:14,  1.86s/it]
                                                           

  1%|▏         | 8169/569592 [6:53:31<290:28:14,  1.86s/it]
  1%|▏         | 8170/569592 [6:53:33<278:37:16,  1.79s/it]
                                                           

  1%|▏         | 8170/569592 [6:53:33<278:37:16,  1.79s/it]
  1%|▏         | 8171/569592 [6:53:36<355:02:50,  2.28s/it]
                                                           

  1%|▏         | 8171/569592 [6:53:36<355:02:50,  2.28s/it]
  1%|▏         | 8172/569592 [6:53:40<435:53:47,  2.80s/it]
                        /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91595708 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                   

  1%|▏         | 8172/569592 [6:53:40<435:53:47,  2.80s/it]
  1%|▏         | 8173/569592 [6:53:44<464:26:58,  2.98s/it]
                                                           

  1%|▏         | 8173/569592 [6:53:44<464:26:58,  2.98s/it]
  1%|▏         | 8174/569592 [6:53:47<504:21:51,  3.23s/it]
                                                           

  1%|▏         | 8174/569592 [6:53:47<504:21:51,  3.23s/it]
  1%|▏         | 8175/569592 [6:53:48<400:45:57,  2.57s/it]
                                                           

  1%|▏         | 8175/569592 [6:53:48<400:45:57,  2.57s/it]
  1%|▏         | 8176/569592 [6:53:53<486:22:54,  3.12s/it]
                                                           

  1%|▏         | 8176/569592 [6:53:53<486:22:54,  3.12s/it]
  1%|▏         | 8177/569592 [6:53:54<387:51:11,  2.49s/it]
                                                           

  1%|▏         | 8177/569592 [6:53:54<387:51:11,  2.49s/it]
  1%|▏         | 8178/569592 [6:53:58<447:04:43,  2.87s/it]
                                                           

  1%|▏         | 8178/569592 [6:53:58<447:04:43,  2.87s/it]
  1%|▏         | 8179/569592 [6:53:59<356:18:26,  2.28s/it]
                                                           

  1%|▏         | 8179/569592 [6:53:59<356:18:26,  2.28s/it]
  1%|▏         | 8180/569592 [6:54:03<460:14:12,  2.95s/it]
                                                           

  1%|▏         | 8180/569592 [6:54:03<460:14:12,  2.95s/it]
  1%|▏         | 8181/569592 [6:54:04<368:02:18,  2.36s/it]
                                                           

  1%|▏         | 8181/569592 [6:54:04<368:02:18,  2.36s/it]
  1%|▏         | 8182/569592 [6:54:05<302:20:24,  1.94s/it]
                                                           

  1%|▏         | 8182/569592 [6:54:05<302:20:24,  1.94s/it]
  1%|▏         | 8183/569592 [6:54:08<375:16:14,  2.41s/it]
                                                           

  1%|▏         | 8183/569592 [6:54:08<375:16:14,  2.41s/it]
  1%|▏         | 8184/569592 [6:54:12<424:22:36,  2.72s/it]
                                                           

  1%|▏         | 8184/569592 [6:54:12<424:22:36,  2.72s/it]
  1%|▏         | 8185/569592 [6:54:16<464:14:55,  2.98s/it]
                                                           

  1%|▏         | 8185/569592 [6:54:16<464:14:55,  2.98s/it]
  1%|▏         | 8186/569592 [6:54:16<368:47:12,  2.36s/it]
                                                           

  1%|▏         | 8186/569592 [6:54:16<368:47:12,  2.36s/it]
  1%|▏         | 8187/569592 [6:54:21<448:38:11,  2.88s/it]
                                                           

  1%|▏         | 8187/569592 [6:54:21<448:38:11,  2.88s/it]
  1%|▏         | 8188/569592 [6:54:22<378:04:42,  2.42s/it]
                                                           

  1%|▏         | 8188/569592 [6:54:22<378:04:42,  2.42s/it]
  1%|▏         | 8189/569592 [6:54:26<459:49:25,  2.95s/it]
                                                           

  1%|▏         | 8189/569592 [6:54:26<459:49:25,  2.95s/it]
  1%|▏         | 8190/569592 [6:54:29<472:03:33,  3.03s/it]
                                                           

  1%|▏         | 8190/569592 [6:54:29<472:03:33,  3.03s/it]
  1%|▏         | 8191/569592 [6:54:30<378:18:20,  2.43s/it]
                                                           

  1%|▏         | 8191/569592 [6:54:30<378:18:20,  2.43s/it]
  1%|▏         | 8192/569592 [6:54:35<464:15:42,  2.98s/it]
                                                           

  1%|▏         | 8192/569592 [6:54:35<464:15:42,  2.98s/it]
  1%|▏         | 8193/569592 [6:54:38<485:58:28,  3.12s/it]
                                                           

  1%|▏         | 8193/569592 [6:54:38<485:58:28,  3.12s/it]
  1%|▏         | 8194/569592 [6:54:41<494:02:00,  3.17s/it]
                                                           

  1%|▏         | 8194/569592 [6:54:41<494:02:00,  3.17s/it]
  1%|▏         | 8195/569592 [6:54:42<390:12:30,  2.50s/it]
                                                           

  1%|▏         | 8195/569592 [6:54:42<390:12:30,  2.50s/it]
  1%|▏         | 8196/569592 [6:54:43<318:56:13,  2.05s/it]
                                                           

  1%|▏         | 8196/569592 [6:54:43<318:56:13,  2.05s/it]
  1%|▏         | 8197/569592 [6:54:47<415:19:56,  2.66s/it]
                                                           

  1%|▏         | 8197/569592 [6:54:47<415:19:56,  2.66s/it]
  1%|▏         | 8198/569592 [6:54:48<338:31:51,  2.17s/it]
                                                           

  1%|▏         | 8198/569592 [6:54:48<338:31:51,  2.17s/it]
  1%|▏         | 8199/569592 [6:54:49<290:36:43,  1.86s/it]
                                                           

  1%|▏         | 8199/569592 [6:54:50<290:36:43,  1.86s/it]
  1%|▏         | 8200/569592 [6:54:51<294:26:15,  1.89s/it]
                                                           

  1%|▏         | 8200/569592 [6:54:51<294:26:15,  1.89s/it]
  1%|▏         | 8201/569592 [6:54:53<274:03:20,  1.76s/it]
                                                           

  1%|▏         | 8201/569592 [6:54:53<274:03:20,  1.76s/it]
  1%|▏         | 8202/569592 [6:54:57<361:38:07,  2.32s/it]
                                                           

  1%|▏         | 8202/569592 [6:54:57<361:38:07,  2.32s/it]
  1%|▏         | 8203/569592 [6:55:00<436:14:47,  2.80s/it]
                                                           

  1%|▏         | 8203/569592 [6:55:00<436:14:47,  2.80s/it]
  1%|▏         | 8204/569592 [6:55:04<477:15:31,  3.06s/it]
                                                           

  1%|▏         | 8204/569592 [6:55:04<477:15:31,  3.06s/it]
  1%|▏         | 8205/569592 [6:55:05<378:47:39,  2.43s/it]
                                                           

  1%|▏         | 8205/569592 [6:55:05<378:47:39,  2.43s/it]
  1%|▏         | 8206/569592 [6:55:09<432:29:02,  2.77s/it]
                                                           

  1%|▏         | 8206/569592 [6:55:09<432:29:02,  2.77s/it]
  1%|▏         | 8207/569592 [6:55:10<346:03:13,  2.22s/it]
                                                           

  1%|▏         | 8207/569592 [6:55:10<346:03:13,  2.22s/it]
  1%|▏         | 8208/569592 [6:55:13<409:23:29,  2.63s/it]
                                                           

  1%|▏         | 8208/569592 [6:55:13<409:23:29,  2.63s/it]
  1%|▏         | 8209/569592 [6:55:14<333:18:49,  2.14s/it]
                                                           

  1%|▏         | 8209/569592 [6:55:14<333:18:49,  2.14s/it]
  1%|▏         | 8210/569592 [6:55:17<390:23:57,  2.50s/it]
                                                           

  1%|▏         | 8210/569592 [6:55:18<390:23:57,  2.50s/it]
  1%|▏         | 8211/569592 [6:55:21<456:52:15,  2.93s/it]
                                                           

  1%|▏         | 8211/569592 [6:55:21<456:52:15,  2.93s/it]
  1%|▏         | 8212/569592 [6:55:25<506:26:41,  3.25s/it]
                                                           

  1%|▏         | 8212/569592 [6:55:25<506:26:41,  3.25s/it]
  1%|▏         | 8213/569592 [6:55:29<531:45:18,  3.41s/it]
                                                           

  1%|▏         | 8213/569592 [6:55:29<531:45:18,  3.41s/it]
  1%|▏         | 8214/569592 [6:55:33<538:19:39,  3.45s/it]
                                                           

  1%|▏         | 8214/569592 [6:55:33<538:19:39,  3.45s/it]
  1%|▏         | 8215/569592 [6:55:36<547:53:20,  3.51s/it]
                                                           

  1%|▏         | 8215/569592 [6:55:36<547:53:20,  3.51s/it]
  1%|▏         | 8216/569592 [6:55:40<553:20:55,  3.55s/it]
                                                           

  1%|▏         | 8216/569592 [6:55:40<553:20:55,  3.55s/it]
  1%|▏         | 8217/569592 [6:55:44<561:25:18,  3.60s/it]
                                                           

  1%|▏         | 8217/569592 [6:55:44<561:25:18,  3.60s/it]
  1%|▏         | 8218/569592 [6:55:45<435:47:50,  2.79s/it]
                                                           

  1%|▏         | 8218/569592 [6:55:45<435:47:50,  2.79s/it]
  1%|▏         | 8219/569592 [6:55:49<484:33:13,  3.11s/it]
                                                           

  1%|▏         | 8219/569592 [6:55:49<484:33:13,  3.11s/it]
  1%|▏         | 8220/569592 [6:55:52<494:55:18,  3.17s/it]
                                                           

  1%|▏         | 8220/569592 [6:55:52<494:55:18,  3.17s/it]
  1%|▏         | 8221/569592 [6:55:56<548:06:15,  3.51s/it]
                                                           

  1%|▏         | 8221/569592 [6:55:56<548:06:15,  3.51s/it]
  1%|▏         | 8222/569592 [6:56:00<563:03:22,  3.61s/it]
                                                           

  1%|▏         | 8222/569592 [6:56:00<563:03:22,  3.61s/it]
  1%|▏         | 8223/569592 [6:56:04<564:45:46,  3.62s/it]
                                                           

  1%|▏         | 8223/569592 [6:56:04<564:45:46,  3.62s/it]
  1%|▏         | 8224/569592 [6:56:07<557:19:54,  3.57s/it]
                                                           

  1%|▏         | 8224/569592 [6:56:07<557:19:54,  3.57s/it]
  1%|▏         | 8225/569592 [6:56:10<542:10:03,  3.48s/it]
                                                           

  1%|▏         | 8225/569592 [6:56:10<542:10:03,  3.48s/it]
  1%|▏         | 8226/569592 [6:56:11<422:35:53,  2.71s/it]
                                                           

  1%|▏         | 8226/569592 [6:56:11<422:35:53,  2.71s/it]
  1%|▏         | 8227/569592 [6:56:15<472:10:21,  3.03s/it]
                                                           

  1%|▏         | 8227/569592 [6:56:15<472:10:21,  3.03s/it]
  1%|▏         | 8228/569592 [6:56:18<492:20:12,  3.16s/it]
                                                           

  1%|▏         | 8228/569592 [6:56:19<492:20:12,  3.16s/it]
  1%|▏         | 8229/569592 [6:56:22<513:13:23,  3.29s/it]
                                                           

  1%|▏         | 8229/569592 [6:56:22<513:13:23,  3.29s/it]
  1%|▏         | 8230/569592 [6:56:25<518:22:34,  3.32s/it]
                                                           

  1%|▏         | 8230/569592 [6:56:26<518:22:34,  3.32s/it]
  1%|▏         | 8231/569592 [6:56:26<405:18:45,  2.60s/it]
                                                           

  1%|▏         | 8231/569592 [6:56:26<405:18:45,  2.60s/it]
  1%|▏         | 8232/569592 [6:56:30<469:59:43,  3.01s/it]
                                                           

  1%|▏         | 8232/569592 [6:56:30<469:59:43,  3.01s/it]
  1%|▏         | 8233/569592 [6:56:31<372:31:41,  2.39s/it]
                                                           

  1%|▏         | 8233/569592 [6:56:32<372:31:41,  2.39s/it]
  1%|▏         | 8234/569592 [6:56:33<321:48:31,  2.06s/it]
                                                           

  1%|▏         | 8234/569592 [6:56:33<321:48:31,  2.06s/it]
  1%|▏         | 8235/569592 [6:56:36<380:12:44,  2.44s/it]
                                                           

  1%|▏         | 8235/569592 [6:56:36<380:12:44,  2.44s/it]
  1%|▏         | 8236/569592 [6:56:40<453:43:37,  2.91s/it]
                                                           

  1%|▏         | 8236/569592 [6:56:40<453:43:37,  2.91s/it]
  1%|▏         | 8237/569592 [6:56:43<466:36:54,  2.99s/it]
                                                           

  1%|▏         | 8237/569592 [6:56:43<466:36:54,  2.99s/it]
  1%|▏         | 8238/569592 [6:56:47<516:33:46,  3.31s/it]
                                                           

  1%|▏         | 8238/569592 [6:56:47<516:33:46,  3.31s/it]
  1%|▏         | 8239/569592 [6:56:51<524:16:34,  3.36s/it]
                                                           

  1%|▏         | 8239/569592 [6:56:51<524:16:34,  3.36s/it]
  1%|▏         | 8240/569592 [6:56:54<535:19:54,  3.43s/it]
                                                           

  1%|▏         | 8240/569592 [6:56:54<535:19:54,  3.43s/it]
  1%|▏         | 8241/569592 [6:56:59<593:30:52,  3.81s/it]
                                                           

  1%|▏         | 8241/569592 [6:56:59<593:30:52,  3.81s/it]
  1%|▏         | 8242/569592 [6:57:02<568:02:13,  3.64s/it]
                                                           

  1%|▏         | 8242/569592 [6:57:02<568:02:13,  3.64s/it]
  1%|▏         | 8243/569592 [6:57:06<552:45:25,  3.54s/it]
                                                           

  1%|▏         | 8243/569592 [6:57:06<552:45:25,  3.54s/it]
  1%|▏         | 8244/569592 [6:57:09<539:07:13,  3.46s/it]
                                                           

  1%|▏         | 8244/569592 [6:57:09<539:07:13,  3.46s/it]
  1%|▏         | 8245/569592 [6:57:10<422:36:17,  2.71s/it]
                                                           

  1%|▏         | 8245/569592 [6:57:10<422:36:17,  2.71s/it]
  1%|▏         | 8246/569592 [6:57:11<341:19:48,  2.19s/it]
                                                           

  1%|▏         | 8246/569592 [6:57:11<341:19:48,  2.19s/it]
  1%|▏         | 8247/569592 [6:57:14<404:19:10,  2.59s/it]
                                                           

  1%|▏         | 8247/569592 [6:57:14<404:19:10,  2.59s/it]
  1%|▏         | 8248/569592 [6:57:18<450:48:46,  2.89s/it]
                                                           

  1%|▏         | 8248/569592 [6:57:18<450:48:46,  2.89s/it]
  1%|▏         | 8249/569592 [6:57:19<364:52:33,  2.34s/it]
                                                           

  1%|▏         | 8249/569592 [6:57:19<364:52:33,  2.34s/it]
  1%|▏         | 8250/569592 [6:57:24<474:32:29,  3.04s/it]
                                                           

  1%|▏         | 8250/569592 [6:57:24<474:32:29,  3.04s/it]
  1%|▏         | 8251/569592 [6:57:27<496:33:41,  3.18s/it]
                                                           

  1%|▏         | 8251/569592 [6:57:27<496:33:41,  3.18s/it]
  1%|▏         | 8252/569592 [6:57:30<500:54:40,  3.21s/it]
                                                           

  1%|▏         | 8252/569592 [6:57:30<500:54:40,  3.21s/it]
  1%|▏         | 8253/569592 [6:57:31<393:25:28,  2.52s/it]
                                                           

  1%|▏         | 8253/569592 [6:57:31<393:25:28,  2.52s/it]
  1%|▏         | 8254/569592 [6:57:34<425:24:47,  2.73s/it]
                                                           

  1%|▏         | 8254/569592 [6:57:34<425:24:47,  2.73s/it]
  1%|▏         | 8255/569592 [6:57:39<494:32:57,  3.17s/it]
                                                           

  1%|▏         | 8255/569592 [6:57:39<494:32:57,  3.17s/it]
  1%|▏         | 8256/569592 [6:57:42<492:57:09,  3.16s/it]
                                                           

  1%|▏         | 8256/569592 [6:57:42<492:57:09,  3.16s/it]
  1%|▏         | 8257/569592 [6:57:45<513:03:27,  3.29s/it]
                                                           

  1%|▏         | 8257/569592 [6:57:45<513:03:27,  3.29s/it]
  1%|▏         | 8258/569592 [6:57:46<401:59:08,  2.58s/it]
                                                           

  1%|▏         | 8258/569592 [6:57:46<401:59:08,  2.58s/it]
  1%|▏         | 8259/569592 [6:57:47<325:52:57,  2.09s/it]
                                                           

  1%|▏         | 8259/569592 [6:57:47<325:52:57,  2.09s/it]
  1%|▏         | 8260/569592 [6:57:51<390:02:06,  2.50s/it]
                                                           

  1%|▏         | 8260/569592 [6:57:51<390:02:06,  2.50s/it]
  1%|▏         | 8261/569592 [6:57:54<433:02:26,  2.78s/it]
                                                           

  1%|▏         | 8261/569592 [6:57:54<433:02:26,  2.78s/it]
  1%|▏         | 8262/569592 [6:57:58<467:32:56,  3.00s/it]
                                                           

  1%|▏         | 8262/569592 [6:57:58<467:32:56,  3.00s/it]
  1%|▏         | 8263/569592 [6:58:01<479:37:03,  3.08s/it]
                                                           

  1%|▏         | 8263/569592 [6:58:01<479:37:03,  3.08s/it]
  1%|▏         | 8264/569592 [6:58:04<490:53:31,  3.15s/it]
                                                           

  1%|▏         | 8264/569592 [6:58:04<490:53:31,  3.15s/it]
  1%|▏         | 8265/569592 [6:58:08<496:30:06,  3.18s/it]
                                                           

  1%|▏         | 8265/569592 [6:58:08<496:30:06,  3.18s/it]
  1%|▏         | 8266/569592 [6:58:11<496:32:54,  3.18s/it]
                                                           

  1%|▏         | 8266/569592 [6:58:11<496:32:54,  3.18s/it]
  1%|▏         | 8267/569592 [6:58:12<392:38:24,  2.52s/it]
                                                           

  1%|▏         | 8267/569592 [6:58:12<392:38:24,  2.52s/it]
  1%|▏         | 8268/569592 [6:58:13<320:01:44,  2.05s/it]
                                                           

  1%|▏         | 8268/569592 [6:58:13<320:01:44,  2.05s/it]
  1%|▏         | 8269/569592 [6:58:16<395:43:12,  2.54s/it]
                                                           

  1%|▏         | 8269/569592 [6:58:16<395:43:12,  2.54s/it]
  1%|▏         | 8270/569592 [6:58:17<323:58:08,  2.08s/it]
                                                           

  1%|▏         | 8270/569592 [6:58:17<323:58:08,  2.08s/it]
  1%|▏         | 8271/569592 [6:58:21<394:10:50,  2.53s/it]
                                                           

  1%|▏         | 8271/569592 [6:58:21<394:10:50,  2.53s/it]
  1%|▏         |/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (89543531 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 8272/569592 [6:58:22<322:09:33,  2.07s/it]
                                                           

  1%|▏         | 8272/569592 [6:58:22<322:09:33,  2.07s/it]
  1%|▏         | 8273/569592 [6:58:25<384:48:10,  2.47s/it]
                                                           

  1%|▏         | 8273/569592 [6:58:25<384:48:10,  2.47s/it]
  1%|▏         | 8274/569592 [6:58:27<331:08:39,  2.12s/it]
                                                           

  1%|▏         | 8274/569592 [6:58:27<331:08:39,  2.12s/it]
  1%|▏         | 8275/569592 [6:58:31<421:15:39,  2.70s/it]
                                                           

  1%|▏         | 8275/569592 [6:58:31<421:15:39,  2.70s/it]
  1%|▏         | 8276/569592 [6:58:34<469:53:33,  3.01s/it]
                                                           

  1%|▏         | 8276/569592 [6:58:34<469:53:33,  3.01s/it]
  1%|▏         | 8277/569592 [6:58:38<494:34:47,  3.17s/it]
                                                           

  1%|▏         | 8277/569592 [6:58:38<494:34:47,  3.17s/it]
  1%|▏         | 8278/569592 [6:58:39<392:45:14,  2.52s/it]
                                                           

  1%|▏         | 8278/569592 [6:58:39<392:45:14,  2.52s/it]
  1%|▏         | 8279/569592 [6:58:40<319:51:48,  2.05s/it]
                                                           

  1%|▏         | 8279/569592 [6:58:40<319:51:48,  2.05s/it]
  1%|▏         | 8280/569592 [6:58:41<270:46:47,  1.74s/it]
                                                           

  1%|▏         | 8280/569592 [6:58:41<270:46:47,  1.74s/it]
  1%|▏         | 8281/569592 [6:58:45<360:13:56,  2.31s/it]
                                                           

  1%|▏         | 8281/569592 [6:58:45<360:13:56,  2.31s/it]
  1%|▏         | 8282/569592 [6:58:49<445:08:15,  2.85s/it]
                                                           

  1%|▏         | 8282/569592 [6:58:49<445:08:15,  2.85s/it]
  1%|▏         | 8283/569592 [6:58:50<357:58:15,  2.30s/it]
                                                           

  1%|▏         | 8283/569592 [6:58:50<357:58:15,  2.30s/it]
  1%|▏         | 8284/569592 [6:58:55<482:22:38,  3.09s/it]
                                                           

  1%|▏         | 8284/569592 [6:58:55<482:22:38,  3.09s/it]
  1%|▏         | 8285/569592 [6:58:58<496:08:31,  3.18s/it]
                                                           

  1%|▏         | 8285/569592 [6:58:58<496:08:31,  3.18s/it]
  1%|▏         | 8286/569592 [6:58:59<394:03:54,  2.53s/it]
                                                           

  1%|▏         | 8286/569592 [6:58:59<394:03:54,  2.53s/it]
  1%|▏         | 8287/569592 [6:59:02<433:53:59,  2.78s/it]
                                                           

  1%|▏         | 8287/569592 [6:59:02<433:53:59,  2.78s/it]
  1%|▏         | 8288/569592 [6:59:03<351:08:13,  2.25s/it]
                                                           

  1%|▏         | 8288/569592 [6:59:03<351:08:13,  2.25s/it]
  1%|▏         | 8289/569592 [6:59:04<295:09:02,  1.89s/it]
                                                           

  1%|▏         | 8289/569592 [6:59:04<295:09:02,  1.89s/it]
  1%|▏         | 8290/569592 [6:59:08<371:32:22,  2.38s/it]
                                                           

  1%|▏         | 8290/569592 [6:59:08<371:32:22,  2.38s/it]
  1%|▏         | 8291/569592 [6:59:12<434:44:30,  2.79s/it]
                                                           

  1%|▏         | 8291/569592 [6:59:12<434:44:30,  2.79s/it]
  1%|▏         | 8292/569592 [6:59:13<349:27:59,  2.24s/it]
                                                           

  1%|▏         | 8292/569592 [6:59:13<349:27:59,  2.24s/it]
  1%|▏         | 8293/569592 [6:59:16<411:28:52,  2.64s/it]
                                                           

  1%|▏         | 8293/569592 [6:59:16<411:28:52,  2.64s/it]
  1%|▏         | 8294/569592 [6:59:20<452:07:53,  2.90s/it]
                                                           

  1%|▏         | 8294/569592 [6:59:20<452:07:53,  2.90s/it]
  1%|▏         | 8295/569592 [6:59:23<473:00:13,  3.03s/it]
                                                           

  1%|▏         | 8295/569592 [6:59:23<473:00:13,  3.03s/it]
  1%|▏         | 8296/569592 [6:59:24<376:58:46,  2.42s/it]
                                                           

  1%|▏         | 8296/569592 [6:59:24<376:58:46,  2.42s/it]
  1%|▏         | 8297/569592 [6:59:27<423:04:52,  2.71s/it]
                                                           

  1%|▏         | 8297/569592 [6:59:28<423:04:52,  2.71s/it]
  1%|▏         | 8298/569592 [6:59:31<464:27:45,  2.98s/it]
                                                           

  1%|▏         | 8298/569592 [6:59:31<464:27:45,  2.98s/it]
  1%|▏         | 8299/569592 [6:59:32<369:38:11,  2.37s/it]
                                                           

  1%|▏         | 8299/569592 [6:59:32<369:38:11,  2.37s/it]
  1%|▏         | 8300/569592 [6:59:36<459:36:38,  2.95s/it]
                                                           

  1%|▏         | 8300/569592 [6:59:36<459:36:38,  2.95s/it]
  1%|▏         | 8301/569592 [6:59:37<370:14:23,  2.37s/it]
                                                           

  1%|▏         | 8301/569592 [6:59:37<370:14:23,  2.37s/it]
  1%|▏         | 8302/569592 [6:59:41<449:25:21,  2.88s/it]
                                                           

  1%|▏         | 8302/569592 [6:59:41<449:25:21,  2.88s/it]
  1%|▏         | 8303/569592 [6:59:42<359:57:11,  2.31s/it]
                                                           

  1%|▏         | 8303/569592 [6:59:42<359:57:11,  2.31s/it]
  1%|▏         | 8304/569592 [6:59:43<299:09:24,  1.92s/it]
                                                           

  1%|▏         | 8304/569592 [6:59:43<299:09:24,  1.92s/it]
  1%|▏         | 8305/569592 [6:59:47<381:03:49,  2.44s/it]
                                                           

  1%|▏         | 8305/569592 [6:59:47<381:03:49,  2.44s/it]
  1%|▏         | 8306/569592 [6:59:48<312:58:01,  2.01s/it]
                                                           

  1%|▏         | 8306/569592 [6:59:48<312:58:01,  2.01s/it]
  1%|▏         | 8307/569592 [6:59:49<266:46:18,  1.71s/it]
                                                           

  1%|▏         | 8307/569592 [6:59:49<266:46:18,  1.71s/it]
  1%|▏         | 8308/569592 [6:59:52<345:33:13,  2.22s/it]
                                                           

  1%|▏         | 8308/569592 [6:59:53<345:33:13,  2.22s/it]
  1%|▏         | 8309/569592 [6:59:56<397:31:17,  2.55s/it]
                                                           

  1%|▏         | 8309/569592 [6:59:56<397:31:17,  2.55s/it]
  1%|▏         | 8310/569592 [6:59:59<441:52:24,  2.83s/it]
                                                           

  1%|▏         | 8310/569592 [6/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
:59:59<441:52:24,  2.83s/it]
  1%|▏         | 8311/569592 [7:00:00<354:29:22,  2.27s/it]
                                                           

  1%|▏         | 8311/569592 [7:00:00<354:29:22,  2.27s/it]
  1%|▏         | 8312/569592 [7:00:01<291:56:07,  1.87s/it]
                                                           

  1%|▏         | 8312/569592 [7:00:01<291:56:07,  1.87s/it]
  1%|▏         | 8313/569592 [7:00:05<368:15:44,  2.36s/it]
                                                           

  1%|▏         | 8313/569592 [7:00:05<368:15:44,  2.36s/it]
  1%|▏         | 8314/569592 [7:00:06<312:46:34,  2.01s/it]
                                                           

  1%|▏         | 8314/569592 [7:00:06<312:46:34,  2.01s/it]
  1%|▏         | 8315/569592 [7:00:07<265:35:10,  1.70s/it]
                                                           

  1%|▏         | 8315/569592 [7:00:07<265:35:10,  1.70s/it]
  1%|▏         | 8316/569592 [7:00:11<371:42:42,  2.38s/it]
                                                           

  1%|▏         | 8316/569592 [7:00:11<371:42:42,  2.38s/it]
  1%|▏         | 8317/569592 [7:00:12<304:57:53,  1.96s/it]
                                                           

  1%|▏         | 8317/569592 [7:00:12<304:57:53,  1.96s/it]
  1%|▏         | 8318/569592 [7:00:16<413:44:00,  2.65s/it]
                                                           

  1%|▏         | 8318/569592 [7:00:16<413:44:00,  2.65s/it]
  1%|▏         | 8319/569592 [7:00:20<456:48:32,  2.93s/it]
                                                           

  1%|▏         | 8319/569592 [7:00:20<456:48:32,  2.93s/it]
  1%|▏         | 8320/569592 [7:00:25<548:37:48,  3.52s/it]
                                                           

  1%|▏         | 8320/569592 [7:00:25<548:37:48,  3.52s/it]
  1%|▏         | 8321/569592 [7:00:28<549:51:56,  3.53s/it]
                                                           

  1%|▏         | 8321/569592 [7:00:28<549:51:56,  3.53s/it]
  1%|▏         | 8322/569592 [7:00:29<431:45:14,  2.77s/it]
                                                           

  1%|▏         | 8322/569592 [7:00:29<431:45:14,  2.77s/it]
  1%|▏         | 8323/569592 [7:00:32<452:30:01,  2.90s/it]
                                                           

  1%|▏         | 8323/569592 [7:00:32<452:30:01,  2.90s/it]
  1%|▏         | 8324/569592 [7:00:36<473:37:32,  3.04s/it]
                                                           

  1%|▏         | 8324/569592 [7:00:36<473:37:32,  3.04s/it]
  1%|▏         | 8325/569592 [7:00:37<377:22:20,  2.42s/it]
                                                           

  1%|▏         | 8325/569592 [7:00:37<377:22:20,  2.42s/it]
  1%|▏         | 8326/569592 [7:00:40<433:37:57,  2.78s/it]
                                                           

  1%|▏         | 8326/569592 [7:00:40<433:37:57,  2.78s/it]
  1%|▏         | 8327/569592 [7:00:45<500:51:05,  3.21s/it]
                                                           

  1%|▏         | 8327/569592 [7:00:45<500:51:05,  3.21s/it]
  1%|▏         | 8328/569592 [7:00:48<502:47:33,  3.22s/it]
                                                           

  1%|▏         | 8328/569592 [7:00:48<502:47:33,  3.22s/it]
  1%|▏         | 8329/569592 [7:00:51<500:58:16,  3.21s/it]
                                                           

  1%|▏         | 8329/569592 [7:00:51<500:58:16,  3.21s/it]
  1%|▏         | 8330/569592 [7:00:55<539:13:49,  3.46s/it]
                                                           

  1%|▏         | 8330/569592 [7:00:55<539:13:49,  3.46s/it]
  1%|▏         | 8331/569592 [7:00:59<555:26:42,  3.56s/it]
                                                           

  1%|▏         | 8331/569592 [7:00:59<555:26:42,  3.56s/it]
  1%|▏         | 8332/569592 [7:01:02<538:12:55,  3.45s/it]
                                                           

  1%|▏         | 8332/569592 [7:01:02<538:12:55,  3.45s/it]
  1%|▏         | 8333/569592 [7:01:05<527:17:26,  3.38s/it]
                                                           

  1%|▏         | 8333/569592 [7:01:05<527:17:26,  3.38s/it]
  1%|▏         | 8334/569592 [7:01:09<547:39:59,  3.51s/it]
                                                           

  1%|▏         | 8334/569592 [7:01:09<547:39:59,  3.51s/it]
  1%|▏         | 8335/569592 [7:01:13<558:18:22,  3.58s/it]
                                                           

  1%|▏         | 8335/569592 [7:01:13<558:18:22,  3.58s/it]
  1%|▏         | 8336/569592 [7:01:16<556:19:18,  3.57s/it]
                                                           

  1%|▏         | 8336/569592 [7:01:16<556:19:18,  3.57s/it]
  1%|▏         | 8337/569592 [7:01:20<570:27:25,  3.66s/it]
                                                           

  1%|▏         | 8337/569592 [7:01:20<570:27:25,  3.66s/it]
  1%|▏         | 8338/569592 [7:01:21<442:00:05,  2.84s/it]
                                                           

  1%|▏         | 8338/569592 [7:01:21<442:00:05,  2.84s/it]
  1%|▏         | 8339/569592 [7:01:24<458:38:48,  2.94s/it]
                                                           

  1%|▏         | 8339/569592 [7:01:24<458:38:48,  2.94s/it]
  1%|▏         | 8340/569592 [7:01:28<491:03:58,  3.15s/it]
                                                           

  1%|▏         | 8340/569592 [7:01:28<491:03:58,  3.15s/it]
  1%|▏         | 8341/569592 [7:01:31<492:40:29,  3.16s/it]
                                                           

  1%|▏         | 8341/569592 [7:01:31<492:40:29,  3.16s/it]
  1%|▏         | 8342/569592 [7:01:34<493:39:50,  3.17s/it]
                                                           

  1%|▏         | 8342/569592 [7:01:34<493:39:50,  3.17s/it]
  1%|▏         | 8343/569592 [7:01:38<497:36:55,  3.19s/it]
                                                           

  1%|▏         | 8343/569592 [7:01:38<497:36:55,  3.19s/it]
  1%|▏         | 8344/569592 [7:01:41<530:47:03,  3.40s/it]
                                                           

  1%|▏         | 8344/569592 [7:01:41<530:47:03,  3.40s/it]
  1%|▏         | 8345/569592 [7:01:45<554:07:46,  3.55s/it]
                                                           

  1%|▏         | 8345/569592 [7:01:45<554:07:46,  3.55s/it]
  1%|▏         | 8346/569592 [7:01:50<622:04:47,  3.99s/it]
                                                           

  1%|▏         | 8346/569592 [7:01:50<622:04:47,  3.99s/it]
  1%|▏         | 8347/569592 [7:01:54<599:06:44,  3.84s/it]
                                                           

  1%|▏         | 8347/569592 [7:01:54<599:06:44,  3.84s/it]
  1%|▏         | 8348/569592 [7:01:59<670:27:34,  4.30s/it]
                                                           

  1%|▏         | 8348/569592 [7:01:59<670:27:34,  4.30s/it]
  1%|▏         | 8349/569592 [7:02:00<512:09:11,  3.29s/it]
                                                           

  1%|▏         | 8349/569592 [7:02:00<512:09:11,  3.29s/it]
  1%|▏         | 8350/569592 [7:02:04<536:45:16,  3.44s/it]
                                                           

  1%|▏         | 8350/569592 [7:02:04<536:45:16,  3.44s/it]
  1%|▏         | 8351/569592 [7:02:07<536:52:48,  3.44s/it]
                                                           

  1%|▏         | 8351/569592 [7:02:07<536:52:48,  3.44s/it]
  1%|▏         | 8352/569592 [7:02:10<517:33:26,  3.32s/it]
                                                           

  1%|▏         | 8352/569592 [7:02:10<517:33:26,  3.32s/it]
  1%|▏         | 8353/569592 [7:02:11<405:02:34,  2.60s/it]
                                                           

  1%|▏         | 8353/569592 [7:02:11<405:02:34,  2.60s/it]
  1%|▏         | 8354/569592 [7:02:15<459:40:51,  2.95s/it]
                                                           

  1%|▏         | 8354/569592 [7:02:15<459:40:51,  2.95s/it]
  1%|▏         | 8355/569592 [7:02:16<373:14:13,  2.39s/it]
                                                           

  1%|▏         | 8355/569592 [7:02:16<373:14:13,  2.39s/it]
  1%|▏         | 8356/569592 [7:02:20<423:32:25,  2.72s/it]
                                                           

  1%|▏         | 8356/569592 [7:02:20<423:32:25,  2.72s/it]
  1%|▏         | 8357/569592 [7:02:24<489:26:14,  3.14s/it]
                                                           

  1%|▏         | 8357/569592 [7:02:24<489:26:14,  3.14s/it]
  1%|▏         | 8358/569592 [7:02:28<517:56:27,  3.32s/it]
                                                           

  1%|▏         | 8358/569592 [7:02:28<517:56:27,  3.32s/it]
  1%|▏         | 8359/569592 [7:02:31<526:43:41,  3.38s/it]
                                                           

  1%|▏         | 8359/569592 [7:02:31<526:43:41,  3.38s/it]
  1%|▏         | 8360/569592 [7:02:34<510:44:21,  3.28s/it]
                                                           

  1%|▏         | 8360/569592 [7:02:34<510:44:21,  3.28s/it]
  1%|▏         | 8361/569592 [7:02:37<502:27:41,  3.22s/it]
                                                           

  1%|▏         | 8361/569592 [7:02:37<502:27:41,  3.22s/it]
  1%|▏         | 8362/569592 [7:02:38<394:36:31,  2.53s/it]
                                                           

  1%|▏         | 8362/569592 [7:02:38<394:36:31,  2.53s/it]
  1%|▏         | 8363/569592 [7:02:39<322:51:01,  2.07s/it]
                                                           

  1%|▏         | 8363/569592 [7:02:39<322:51:01,  2.07s/it]
  1%|▏         | 8364/569592 [7:02:40<269:29:25,  1.73s/it]
                                                           

  1%|▏         | 8364/569592 [7:02:40<269:29:25,  1.73s/it]
  1%|▏         | 8365/569592 [7:02:43<348:42:28,  2.24s/it]
                                                           

  1%|▏         | 8365/569592 [7:02:43<348:42:28,  2.24s/it]
  1%|▏         | 8366/569592 [7:02:47<427:02:29,  2.74s/it]
                                                           

  1%|▏         | 8366/569592 [7:02:47<427:02:29,  2.74s/it]
  1%|▏         | 8367/569592 [7:02:51<454:48:51,  2.92s/it]
                                                           

  1%|▏         | 8367/569592 [7:02:51<454:48:51,  2.92s/it]
  1%|▏         | 8368/569592 [7:02:54<477:17:45,  3.06s/it]
                                                           

  1%|▏         | 8368/569592 [7:02:54<477:17:45,  3.06s/it]
  1%|▏         | 8369/569592 [7:02:58<498:04:45,  3.19s/it]
                                                           

  1%|▏         | 8369/569592 [7:02:58<498:04:45,  3.19s/it]
  1%|▏         | 8370/569592 [7:03:01<526:57:22,  3.38s/it]
                                                           

  1%|▏         | 8370/569592 [7:03:01<526:57:22,  3.38s/it]
  1%|▏         | 8371/569592 [7:03:02<413:25:08,  2.65s/it]
                                                           

  1%|▏    /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (98911692 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
     | 8371/569592 [7:03:02<413:25:08,  2.65s/it]
  1%|▏         | 8372/569592 [7:03:06<450:13:49,  2.89s/it]
                                                           

  1%|▏         | 8372/569592 [7:03:06<450:13:49,  2.89s/it]
  1%|▏         | 8373/569592 [7:03:09<479:13:46,  3.07s/it]
                                                           

  1%|▏         | 8373/569592 [7:03:09<479:13:46,  3.07s/it]
  1%|▏         | 8374/569592 [7:03:10<379:54:39,  2.44s/it]
                                                           

  1%|▏         | 8374/569592 [7:03:10<379:54:39,  2.44s/it]
  1%|▏         | 8375/569592 [7:03:14<446:46:42,  2.87s/it]
                                                           

  1%|▏         | 8375/569592 [7:03:14<446:46:42,  2.87s/it]
  1%|▏         | 8376/569592 [7:03:15<358:29:40,  2.30s/it]
                                                           

  1%|▏         | 8376/569592 [7:03:15<358:29:40,  2.30s/it]
  1%|▏         | 8377/569592 [7:03:19<422:01:34,  2.71s/it]
                                                           

  1%|▏         | 8377/569592 [7:03:19<422:01:34,  2.71s/it]
  1%|▏         | 8378/569592 [7:03:23<478:01:48,  3.07s/it]
                                                           

  1%|▏         | 8378/569592 [7:03:23<478:01:48,  3.07s/it]
  1%|▏         | 8379/569592 [7:03:26<490:33:30,  3.15s/it]
                                                           

  1%|▏         | 8379/569592 [7:03:26<490:33:30,  3.15s/it]
  1%|▏         | 8380/569592 [7:03:29<490:39:11,  3.15s/it]
                                                           

  1%|▏         | 8380/569592 [7:03:29<490:39:11,  3.15s/it]
  1%|▏         | 8381/569592 [7:03:33<519:04:23,  3.33s/it]
                                                           

  1%|▏         | 8381/569592 [7:03:33<519:04:23,  3.33s/it]
  1%|▏         | 8382/569592 [7:03:34<405:28:37,  2.60s/it]
                                                           

  1%|▏         | 8382/569592 [7:03:34<405:28:37,  2.60s/it]
  1%|▏         | 8383/569592 [7:03:35<327:05:08,  2.10s/it]
                                                           

  1%|▏         | 8383/569592 [7:03:35<327:05:08,  2.10s/it]
  1%|▏         | 8384/569592 [7:03:39<418:33:34,  2.68s/it]
                                                           

  1%|▏         | 8384/569592 [7:03:39<418:33:34,  2.68s/it]
  1%|▏         | 8385/569592 [7:03:40<338:37:11,  2.17s/it]
                                                           

  1%|▏         | 8385/569592 [7:03:40<338:37:11,  2.17s/it]
  1%|▏         | 8386/569592 [7:03:43<397:58:25,  2.55s/it]
                                                           

  1%|▏         | 8386/569592 [7:03:43<397:58:25,  2.55s/it]
  1%|▏         | 8387/569592 [7:03:47<479:49:03,  3.08s/it]
                                                           

  1%|▏         | 8387/569592 [7:03:48<479:49:03,  3.08s/it]
  1%|▏         | 8388/569592 [7:03:51<500:45:39,  3.21s/it]
                                                           

  1%|▏         | 8388/569592 [7:03:51<500:45:39,  3.21s/it]
  1%|▏         | 8389/569592 [7:03:52<394:10:19,  2.53s/it]
                                                           

  1%|▏         | 8389/569592 [7:03:52<394:10:19,  2.53s/it]
  1%|▏         | 8390/569592 [7:03:55<434:12:38,  2.79s/it]
                                                           

  1%|▏         | 8390/569592 [7:03:55<434:12:38,  2.79s/it]
  1%|▏         | 8391/569592 [7:03:56<348:19:08,  2.23s/it]
                                                           

  1%|▏         | 8391/569592 [7:03:56<348:19:08,  2.23s/it]
  1%|▏         | 8392/569592 [7:03:57<291:01:47,  1.87s/it]
                                                           

  1%|▏         | 8392/569592 [7:03:57<291:01:47,  1.87s/it]
  1%|▏         | 8393/569592 [7:03:58<255:32:11,  1.64s/it]
                                                           

  1%|▏         | 8393/569592 [7:03:58<255:32:11,  1.64s/it]
  1%|▏         | 8394/569592 [7:04:02<345:11:54,  2.21s/it]
                                                           

  1%|▏         | 8394/569592 [7:04:02<345:11:54,  2.21s/it]
  1%|▏         | 8395/569592 [7:04:03<288:37:01,  1.85s/it]
                                                           

  1%|▏         | 8395/569592 [7:04:03<288:37:01,  1.85s/it]
  1%|▏         | 8396/569592 [7:04:04<246:22:42,  1.58s/it]
                                                           

  1%|▏         | 8396/569592 [7:04:04<246:22:42,  1.58s/it]
  1%|▏         | 8397/569592 [7:04:08<343:31:06,  2.20s/it]
                                                           

  1%|▏         | 8397/569592 [7:04:08<343:31:06,  2.20s/it]
  1%|▏         | 8398/569592 [7:04:11<404:40:01,  2.60s/it]
                                                           

  1%|▏         | 8398/569592 [7:04:11<404:40:01,  2.60s/it]
  1%|▏         | 8399/569592 [7:04:14<440:32:19,  2.83s/it]
                                                           

  1%|▏         | 8399/569592 [7:04:14<440:32:19,  2.83s/it]
  1%|▏         | 8400/569592 [7:04:18<490:53:12,  3.15s/it]
                                                           

  1%|▏         | 8400/569592 [7:04:18<490:53:12,  3.15s/it]
  1%|▏         | 8401/569592 [7:04:20<401:26:38,  2.58s/it]
                                                           

  1%|▏         | 8401/569592 [7:04:20<401:26:38,  2.58s/it]
  1%|▏         | 8402/569592 [7:04:21<325:25:23,  2.09s/it]
                                                           

  1%|▏         | 8402/569592 [7:04:21<325:25:23,  2.09s/it]
  1%|▏         | 8403/569592 [7:04:22<274:28:38,  1.76s/it]
                                                           

  1%|▏         | 8403/569592 [7:04:22<274:28:38,  1.76s/it]
  1%|▏         | 8404/569592 [7:04:23<239:13:56,  1.53s/it]
                                                           

  1%|▏         | 8404/569592 [7:04:23<239:13:56,  1.53s/it]
  1%|▏         | 8405/569592 [7:04:26<311:01:17,  2.00s/it]
                                                           

  1%|▏         | 8405/569592 [7:04:26<311:01:17,  2.00s/it]
  1%|▏         | 8406/569592 [7:04:29<354:26:23,  2.27s/it]
                                                           

  1%|▏         | 8406/569592 [7:04:29<354:26:23,  2.27s/it]
  1%|▏         | 8407/569592 [7:04:29<292:20:21,  1.88s/it]
                                                           

  1%|▏         | 8407/569592 [7:04:30<292:20:21,  1.88s/it]
  1%|▏         | 8408/569592 [7:04:33<375:15:30,  2.41s/it]
                                                           

  1%|▏         | 8408/569592 [7:04:33<375:15:30,  2.41s/it]
  1%|▏         | 8409/569592 [7:04:35<369:34:55,  2.37s/it]
                                                           

  1%|▏         | 8409/569592 [7:04:35<369:34:55,  2.37s/it]
  1%|▏         | 8410/569592 [7:04:39<436:56:34,  2.80s/it]
                                                           

  1%|▏         | 8410/569592 [7:04:39<436:56:34,  2.80s/it]
  1%|▏         | 8411/569592 [7:04:44<509:38:08,  3.27s/it]
                                                           

  1%|▏         | 8411/569592 [7:04:44<509:38:08,  3.27s/it]
  1%|▏         | 8412/569592 [7:04:45<400:46:01,  2.57s/it]
                                                           

  1%|▏         | 8412/569592 [7:04:45<400:46:01,  2.57s/it]
  1%|▏         | 8413/569592 [7:04:48<438:36:16,  2.81s/it]
                                                           

  1%|▏         | 8413/569592 [7:04:48<438:36:16,  2.81s/it]
  1%|▏         | 8414/569592 [7:04:49<352:44:34,  2.26s/it]
                                                           

  1%|▏         | 8414/569592 [7:04:49<352:44:34,  2.26s/it]
  1%|▏         | 8415/569592 [7:04:53<419:06:23,  2.69s/it]
                                                           

  1%|▏         | 8415/569592 [7:04:53<419:06:23,  2.69s/it]
  1%|▏         | 8416/569592 [7:04:54<338:15:26,  2.17s/it]
                                                           

  1%|▏         | 8416/569592 [7:04:54<338:15:26,  2.17s/it]
  1%|▏         | 8417/569592 [7:04:57<401:14:09,  2.57s/it]
                                                           

  1%|▏         | 8417/569592 [7:04:57<401:14:09,  2.57s/it]
  1%|▏         | 8418/569592 [7:05:01<446:28:40,  2.86s/it]
                                                           

  1%|▏         | 8418/569592 [7:05:01<446:28:40,  2.86s/it]
  1%|▏         | 8419/569592 [7:05:04<480:21:06,  3.08s/it]
                                                           

  1%|▏         | 8419/569592 [7:05:04<480:21:06,  3.08s/it]
  1%|▏         | 8420/569592 [7:05:05<381:21:01,  2.45s/it]
                                                           

  1%|▏         | 8420/569592 [7:05:05<381:21:01,  2.45s/it]
  1%|▏         | 8421/569592 [7:05:06<311:01:11,  2.00s/it]
                                                           

  1%|▏         | 8421/569592 [7:05:06<311:01:11,  2.00s/it]
  1%|▏         | 8422/569592 [7:05:11<429:09:35,  2.75s/it]
                                                           

  1%|▏         | 8422/569592 [7:05:11<429:09:35,  2.75s/it]
  1%|▏         | 8423/569592 [7:05:12<346:30:57,  2.22s/it]
                                                           

  1%|▏         | 8423/569592 [7:05:12<346:30:57,  2.22s/it]
  1%|▏         | 8424/569592 [7:05:13<326:32:32,  2.09s/it]
                                                           

  1%|▏         | 8424/569592 [7:05:13<326:32:32,  2.09s/it]
  1%|▏         | 8425/569592 [7:05:15<297:39:12,  1.91s/it]
                                                           

  1%|▏         | 8425/569592 [7:05:15<297:39:12,  1.91s/it]
  1%|▏         | 8426/569592 [7:05:21<488:29:18,  3.13s/it]
                                                           

  1%|▏         | 8426/569592 [7:05:21<488:29:18,  3.13s/it]
  1%|▏         | 8427/569592 [7:05:22<385:54:46,  2.48s/it]
                                                           

  1%|▏         | 8427/569592 [7:05:22<385:54:46,  2.48s/it]
  1%|▏         | 8428/569592 [7:05:25<428:54:39,  2.75s/it]
                                                           

  1%|▏         | 8428/569592 [7:05:25<428:54:39,  2.75s/it]
  1%|▏         | 8429/569592 [7:05:26<344:59:50,  2.21s/it]
                                                           

  1%|▏         | 8429/569592 [7:05:26<344:59:50,  2.21s/it]
  1%|▏         | 8430/569592 [7:05:31<470:24:20,  3.02s/it]
                                                           

  1%|▏         | 8430/569592 [7:05:31<470:24:20,  3.02s/it]
  1%|▏         | 8431/569592 [7:05:34<490:01:07,  3.14s/it]
                                                           

  1%|▏         | 8431/569592 [7:05:34<490:01:07,  3.14s/it]
  1%|▏         | 8432/569592 [7:05:38<493:50:17,  3.17s/it]
                                                           

  1%|▏         | 8432/569592 [7:05:38<493:50:17,  3.17s/it]
  1%|▏         | 8433/569592 [7:05:42<554:15:22,  3.56s/it]
                                                           

  1%|▏         | 8433/569592 [7:05:42<554:15:22,  3.56s/it]
  1%|▏         | 8434/569592 [7:05:45<540:42:01,  3.47s/it]
                                                           

  1%|▏         | 8434/569592 [7:05:45<540:42:01,  3.47s/it]
  1%|▏         | 8435/569592 [7:05:49<526:32:45,  3.38s/it]
                                                           

  1%|▏         | 8435/569592 [7:05:49<526:32:45,  3.38s/it]
  1%|▏         | 8436/569592 [7:05:52<524:48:58,  3.37s/it]
                                                           

  1%|▏         | 8436/569592 [7:05:52<524:48:58,  3.37s/it]
  1%|▏         | 8437/569592 [7:05:55<528:31:01,  3.39s/it]
                                                           

  1%|▏         | 8437/569592 [7:05:55<528:31:01,  3.39s/it]
  1%|▏         | 8438/569592 [7:05:59<534:46:13,  3.43s/it]
                                                           

  1%|▏         | 8438/569592 [7:05:59<534:46:13,  3.43s/it]
  1%|▏         | 8439/569592 [7:06:04<600:17:44,  3.85s/it]
                                                           

  1%|▏         | 8439/569592 [7:06:04<600:17:44,  3.85s/it]
  1%|▏         | 8440/569592 [7:06:07<591:42:58,  3.80s/it]
                                                           

  1%|▏         | 8440/569592 [7:06:07<591:42:58,  3.80s/it]
  1%|▏         | 8441/569592 [7:06:08<462:56:37,  2.97s/it]
                                                           

  1%|▏         | 8441/569592 [7:06:08<462:56:37,  2.97s/it]
  1%|▏         | 8442/569592 [7:06:12<472:35:35,  3.03s/it]
                                                           

  1%|▏         | 8442/569592 [7:06:12<472:35:35,  3.03s/it]
  1%|▏         | 8443/569592 [7:06:13<376:17:20,  2.41s/it]
                                                           

  1%|▏         | 8443/569592 [7:06:13<376:17:20,  2.41s/it]
  1%|▏         | 8444/569592 [7:06:14<308:59:11,  1.98s/it]
                                                           

  1%|▏         | 8444/569592 [7:06:14<308:59:11,  1.98s/it]
  1%|▏         | 8445/569592 [7:06:18<408:33:00,  2.62s/it]
                                                           

  1%|▏         | 8445/569592 [7:06:18<408:33:00,  2.62s/it]
  1%|▏         | 8446/569592 [7:06:21<456:55:32,  2.93s/it]
                                                           

  1%|▏         | 8446/569592 [7:06:21<456:55:32,  2.93s/it]
  1%|▏         | 8447/569592 [7:06:24<467:19:00,  3.00s/it]
                                                           

  1%|▏         | 8447/569592 [7:06:25<467:19:00,  3.00s/it]
  1%|▏         | 8448/569592 [7:06:28<478:31:17,  3.07s/it]
                                                           

  1%|▏         | 8448/569592 [7:06:28<478:31:17,  3.07s/it]
  1%|▏         | 8449/569592 [7:06:32<512:32:22,  3.29s/it]
                                                           

  1%|▏         | 8449/569592 [7:06:32<512:32:22,  3.29s/it]
  1%|▏         | 8450/569592 [7:06:35<532:43:59,  3.42s/it]
                                                           

  1%|▏         | 8450/569592 [7:06:35<532:43:59,  3.42s/it]
  1%|▏         | 8451/569592 [7:06:39<538:52:44,  3.46s/it]
                                                           

  1%|▏         | 8451/569592 [7:06:39<538:52:44,  3.46s/it]
  1%|▏         | 8452/569592 [7:06:40<423:26:50,  2.72s/it]
                                                           

  1%|▏         | 8452/569592 [7:06:40<423:26:50,  2.72s/it]
  1%|▏         | 8453/569592 [7:06:43<468:29:03,  3.01s/it]
                                                           

  1%|▏         | 8453/569592 [7:06:43<468:29:03,  3.01s/it]
  1%|▏         | 8454/569592 [7:06:47<478:05:45,  3.07s/it]
                                                           

  1%|▏         | 8454/569592 [7:06:47<478:05:45,  3.07s/it]
  1%|▏         | 8455/569592 [7:06:50<504:24:36,  3.24s/it]
                                                           

  1%|▏         | 8455/569592 [7:06:50<504:24:36,  3.24s/it]
  1%|▏         | 8456/569592 [7:06:51<396:25:11,  2.54s/it]
                                                           

  1%|▏         | 8456/569592 [7:06:51<396:25:11,  2.54s/it]
  1%|▏         | 8457/569592 [7:06:56<477:27:10,  3.06s/it]
                                                           

  1%|▏         | 8457/569592 [7:06:56<477:27:10,  3.06s/it]
  1%|▏         | 8458/569592 [7:06:59<500:31:18,  3.21s/it]
                                                           

  1%|▏         | 8458/569592 [7:06:59<500:31:18,  3.21s/it]
  1%|▏         | 8459/569592 [7:07:00<394:19:27,  2.53s/it]
                                                           

  1%|▏         | 8459/569592 [7:07:00<394:19:27,  2.53s/it]
  1%|▏         | 8460/569592 [7:07:03<424:22:48,  2.72s/it]
                                                           

  1%|▏         | 8460/569592 [7:07:03<424:22:48,  2.72s/it]
  1%|▏         | 8461/569592 [7:07:08<531:46:04,  3.41s/it]
                                                           

  1%|▏         | 8461/569592 [7:07:08<531:46:04,  3.41s/it]
  1%|▏         | 8462/569592 [7:07:12<529:57:28,  3.40s/it]
                                                           

  1%|▏         | 8462/569592 [7:07:12<529:57:28,  3.40s/it]
  1%|▏         | 8463/569592 [7:07:15<543:05:53,  3.48s/it]
                                                           

  1%|▏         | 8463/569592 [7:07:15<543:05:53,  3.48s/it]
  1%|▏         | 8464/569592 [7:07:19<543:05:56,  3.48s/it]
                                                           

  1%|▏         | 8464/569592 [7:07:19<543:05:56,  3.48s/it]
  1%|▏         | 8465/569592 [7:07:22<526:08:58,  3.38s/it]
                                                           

  1%|▏         | 8465/569592 [7:07:22<526:08:58,  3.38s/it]
  1%|▏         | 8466/569592 [7:07:25<519:51:47,  3.34s/it]
                                                           

  1%|▏         | 8466/569592 [7:07:25<519:51:47,  3.34s/it]
  1%|▏         | 8467/569592 [7:07:26<405:50:48,  2.60s/it]
                                                           

  1%|▏         | 8467/569592 [7:07:26<405:50:48,  2.60s/it]
  1%|▏         | 8468/569592 [7:07:27<330:37:48,  2.12s/it]
                                                           

  1%|▏         | 8468/569592 [7:07:27<330:37:48,  2.12s/it]
  1%|▏         | 8469/569592 [7:07:30<382:05:14,  2.45s/it]
                                                           

  1%|▏         | 8469/569592 [7:07:30<382:05:14,  2.45s/it]
  1%|▏         | 8470/569592 [7:07:34<432:26:43,  2.77s/it]
                                                           

  1%|▏         | 8470/569592 [7:07:34<432:26:43,  2.77s/it]
  1%|▏         | 8471/569592 [7:07:37<451:08:40,  2.89s/it]
     /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (99387746 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                                      

  1%|▏         | 8471/569592 [7:07:37<451:08:40,  2.89s/it]
  1%|▏         | 8472/569592 [7:07:41<492:21:18,  3.16s/it]
                                                           

  1%|▏         | 8472/569592 [7:07:41<492:21:18,  3.16s/it]
  1%|▏         | 8473/569592 [7:07:42<388:06:57,  2.49s/it]
                                                           

  1%|▏         | 8473/569592 [7:07:42<388:06:57,  2.49s/it]
  1%|▏         | 8474/569592 [7:07:45<425:44:35,  2.73s/it]
                                                           

  1%|▏         | 8474/569592 [7:07:45<425:44:35,  2.73s/it]
  1%|▏         | 8475/569592 [7:07:49<479:44:54,  3.08s/it]
                                                           

  1%|▏         | 8475/569592 [7:07:49<479:44:54,  3.08s/it]
  1%|▏         | 8476/569592 [7:07:52<497:55:28,  3.19s/it]
                                                           

  1%|▏         | 8476/569592 [7:07:52<497:55:28,  3.19s/it]
  1%|▏         | 8477/569592 [7:07:55<495:37:07,  3.18s/it]
                                                           

  1%|▏         | 8477/569592 [7:07:55<495:37:07,  3.18s/it]
  1%|▏         | 8478/569592 [7:07:59<495:29:07,  3.18s/it]
                                                           

  1%|▏         | 8478/569592 [7:07:59<495:29:07,  3.18s/it]
  1%|▏         | 8479/569592 [7:08:00<390:29:22,  2.51s/it]
                                                           

  1%|▏         | 8479/569592 [7:08:00<390:29:22,  2.51s/it]
  1%|▏         | 8480/569592 [7:08:01<319:00:25,  2.05s/it]
                                                           

  1%|▏         | 8480/569592 [7:08:01<319:00:25,  2.05s/it]
  1%|▏         | 8481/569592 [7:08:04<384:13:13,  2.47s/it]
                                                           

  1%|▏         | 8481/569592 [7:08:04<384:13:13,  2.47s/it]
  1%|▏         | 8482/569592 [7:08:08<444:14:23,  2.85s/it]
                  /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                         

  1%|▏         | 8482/569592 [7:08:08<444:14:23,  2.85s/it]
  1%|▏         | 8483/569592 [7:08:09<357:26:51,  2.29s/it]
                                                           

  1%|▏         | 8483/569592 [7:08:09<357:26:51,  2.29s/it]
  1%|▏         | 8484/569592 [7:08:12<427:55:20,  2.75s/it]
                                                           

  1%|▏         | 8484/569592 [7:08:13<427:55:20,  2.75s/it]
  1%|▏         | 8485/569592 [7:08:16<483:03:27,  3.10s/it]
                                                           

  1%|▏         | 8485/569592 [7:08:16<483:03:27,  3.10s/it]
  1%|▏         | 8486/569592 [7:08:17<382:47:35,  2.46s/it]
                                                           

  1%|▏         | 8486/569592 [7:08:17<382:47:35,  2.46s/it]
  1%|▏         | 8487/569592 [7:08:21<426:06:12,  2.73s/it]
                                                           

  1%|▏         | 8487/569592 [7:08:21<426:06:12,  2.73s/it]
  1%|▏         | 8488/569592 [7:08:24<452:19:57,  2.90s/it]
                                                           

  1%|▏         | 8488/569592 [7:08:24<452:19:57,  2.90s/it]
  1%|▏         | 8489/569592 [7:08:27<462:06:20,  2.96s/it]
                                                           

  1%|▏         | 8489/569592 [7:08:27<462:06:20,  2.96s/it]
  1%|▏         | 8490/569592 [7:08:32<548:08:43,  3.52s/it]
                                                           

  1%|▏         | 8490/569592 [7:08:32<548:08:43,  3.52s/it]
  1%|▏         | 8491/569592 [7:08:35<539:38:24,  3.46s/it]
                                                           

  1%|▏         | 8491/569592 [7:08:35<539:38:24,  3.46s/it]
  1%|▏         | 8492/569592 [7:08:36<421:58:26,  2.71s/it]
                                                           

  1%|▏         | 8492/569592 [7:08:36<421:58:26,  2.71s/it]
  1%|▏         | 8493/569592 [7:08:40<467:12:13,  3.00s/it]
                                                           

  1%|▏         | 8493/569592 [7:08:40<467:12:13,  3.00s/it]
  1%|▏         | 8494/569592 [7:08:41<373:44:23,  2.40s/it]
                                                           

  1%|▏         | 8494/569592 [7:08:41<373:44:23,  2.40s/it]
  1%|▏         | 8495/569592 [7:08:45<446:43:04,  2.87s/it]
                                                           

  1%|▏         | 8495/569592 [7:08:45<446:43:04,  2.87s/it]
  1%|▏         | 8496/569592 [7:08:48<466:41:23,  2.99s/it]
                                                           

  1%|▏         | 8496/569592 [7:08:48<466:41:23,  2.99s/it]
  1%|▏         | 8497/569592 [7:08:49<375:37:18,  2.41s/it]
                                                           

  1%|▏         | 8497/569592 [7:08:49<375:37:18,  2.41s/it]
  1%|▏         | 8498/569592 [7:08:52<412:52:50,  2.65s/it]
                                                           

  1%|▏         | 8498/569592 [7:08:52<412:52:50,  2.65s/it]
  1%|▏         | 8499/569592 [7:08:57<509:04:35,  3.27s/it]
                                                           

  1%|▏         | 8499/569592 [7:08:57<509:04:35,  3.27s/it]
  1%|▏         | 8500/569592 [7:09:00<502:24:35,  3.22s/it]
                                                           

  1%|▏         | 8500/569592 [7:09:00<502:24:35,  3.22s/it]
  1%|▏         | 8501/569592 [7:09:03<503:39:15,  3.23s/it]
                                                           

  1%|▏         | 8501/569592 [7:09:04<503:39:15,  3.23s/it]
  1%|▏         | 8502/569592 [7:09:07<503:07:51,  3.23s/it]
                                                           

  1%|▏         | 8502/569592 [7:09:07<503:07:51,  3.23s/it]
  1%|▏         | 8503/569592 [7:09:10<510:32:25,  3.28s/it]
                                                           

  1%|▏         | 8503/569592 [7:09:10<510:32:25,  3.28s/it]
  1%|▏         | 8504/569592 [7:09:13<503:01:35,  3.23s/it]
                                                           

  1%|▏         | 8504/569592 [7:09:13<503:01:35,  3.23s/it]
  1%|▏         | 8505/569592 [7:09:17<508:36:47,  3.26s/it]
                                                           

  1%|▏         | 8505/569592 [7:09:17<508:36:47,  3.26s/it]
  1%|▏         | 8506/569592 [7:09:18<404:07:55,  2.59s/it]
                                                           

  1%|▏         | 8506/569592 [7:09:18<404:07:55,  2.59s/it]
  1%|▏         | 8507/569592 [7:09:19<327:53:41,  2.10s/it]
                                                           

  1%|▏         | 8507/569592 [7:09:19<327:53:41,  2.10s/it]
  1%|▏         | 8508/569592 [7:09:20<275:46:46,  1.77s/it]
                                                           

  1%|▏         | 8508/569592 [7:09:20<275:46:46,  1.77s/it]
  1%|▏         | 8509/569592 [7:09:23<367:13:42,  2.36s/it]
                                                           

  1%|▏         | 8509/569592 [7:09:23<367:13:42,  2.36s/it]
  1%|▏         | 8510/569592 [7:09:27<424:32:08,  2.72s/it]
                                                           

  1%|▏         | 8510/569592 [7:09:27<424:32:08,  2.72s/it]
  1%|▏         | 8511/569592 [7:09:28<341:20:47,  2.19s/it]
                                                           

  1%|▏         | 8511/569592 [7:09:28<341:20:47,  2.19s/it]
  1%|▏         | 8512/569592 [7:09:32<419:13:23,  2.69s/it]
                                                           

  1%|▏         | 8512/569592 [7:09:32<419:13:23,  2.69s/it]
  1%|▏         | 8513/569592 [7:09:33<338:31:34,  2.17s/it]
                                                           

  1%|▏         | 8513/569592 [7:09:33<338:31:34,  2.17s/it]
  1%|▏         | 8514/569592 [7:09:34<280:51:56,  1.80s/it]
                                                           

  1%|▏         | 8514/569592 [7:09:34<280:51:56,  1.80s/it]
  1%|▏         | 8515/569592 [7:09:37<370:19:15,  2.38s/it]
                                                           

  1%|▏         | 8515/569592 [7:09:37<370:19:15,  2.38s/it]
  1%|▏         | 8516/569592 [7:09:38<306:35:49,  1.97s/it]
                                                           

  1%|▏         | 8516/569592 [7:09:38<306:35:49,  1.97s/it]
  1%|▏         | 8517/569592 [7:09:42<402:43:28,  2.58s/it]
                                                           

  1%|▏         | 8517/569592 [7:09:42<402:43:28,  2.58s/it]
  1%|▏         | 8518/569592 [7:09:43<325:35:47,  2.09s/it]
                                                           

  1%|▏         | 8518/569592 [7:09:43<325:35:47,  2.09s/it]
  1%|▏         | 8519/569592 [7:09:44<271:37:54,  1.74s/it]
                                                           

  1%|▏         | 8519/569592 [7:09:44<271:37:54,  1.74s/it]
  1%|▏         | 8520/569592 [7:09:45<234:39:38,  1.51s/it]
                                                           

  1%|▏         | 8520/569592 [7:09:45<234:39:38,  1.51s/it]
  1%|▏         | 8521/569592 [7:09:49<322:25:32,  2.07s/it]
                                                           

  1%|▏         | 8521/569592 [7:09:49<322:25:32,  2.07s/it]
  1%|▏         | 8522/569592 [7:09:50<314:55:49,  2.02s/it]
                                                           

  1%|▏         | 8522/569592 [7:09:50<314:55:49,  2.02s/it]
  1%|▏         | 8523/569592 [7:09:54<406:56:10,  2.61s/it]
                                                           

  1%|▏         | 8523/569592 [7:09:54<406:56:10,  2.61s/it]
  1%|▏         | 8524/569592 [7:09:59<487:20:19,  3.13s/it]
                                                           

  1%|▏         | 8524/569592 [7:09:59<487:20:19,  3.13s/it]
  1%|▏         | 8525/569592 [7:10:03<522:00:23,  3.35s/it]
                                                           

  1%|▏         | 8525/569592 [7:10:03<522:00:23,  3.35s/it]
  1%|▏         | 8526/569592 [7:10:06<528:02:44,  3.39s/it]
                                                           

  1%|▏         | 8526/569592 [7:10:06<528:02:44,  3.39s/it]
  1%|▏         | 8527/569592 [7:10:07<414:31:03,  2.66s/it]
                                                           

  1%|▏         | 8527/569592 [7:10:07<414:31:03,  2.66s/it]
  1%|▏         | 8528/569592 [7:10:11<479:58:26,  3.08s/it]
                                                           

  1%|▏         | 8528/569592 [7:10:11<479:58:26,  3.08s/it]
  1%|▏         | 8529/569592 [7:10:15<500:33:15,  3.21s/it]
                                                           

  1%|▏         | 8529/569592 [7:10:15<500:33:15,  3.21s/it]
  1%|▏         | 8530/569592 [7:10:18<519:48:33,  3.34s/it]
                                                           

  1%|▏         | 8530/569592 [7:10:18<519:48:33,  3.34s/it]
  1%|▏         | 8531/569592 [7:10:19<407:35:02,  2.62s/it]
                                                           

  1%|▏         | 8531/569592 [7:10:19<407:35:02,  2.62s/it]
  1%|▏         | 8532/569592 [7:10:20<332:20:13,  2.13s/it]
                                                           

  1%|▏         | 8532/569592 [7:10:20<332:20:13,  2.13s/it]
  1%|▏         | 8533/569592 [7:10:21<282:05:50,  1.81s/it]
                                                           

  1%|▏         | 8533/569592 [7:10:21<282:05:50,  1.81s/it]
  1%|▏         | 8534/569592 [7:10:22<242:43:14,  1.56s/it]
                                                           

  1%|▏         | 8534/569592 [7:10:22<242:43:14,  1.56s/it]
  1%|▏         | 8535/569592 [7:10:26<332:36:32,  2.13s/it]
                                                           

  1%|▏         | 8535/569592 [7:10:26<332:36:32,  2.13s/it]
  1%|▏         | 8536/569592 [7:10:27<278:03:12,  1.78s/it]
                                                           

  1%|▏         | 8536/569592 [7:10:27<278:03:12,  1.78s/it]
  1%|▏         | 8537/569592 [7:10:30<359:31:14,  2.31s/it]
                                                           

  1%|▏         | 8537/569592 [7:10:30<359:31:14,  2.31s/it]
  1%|▏         | 8538/569592 [7:10:32<322:55:30,  2.07s/it]
                                                           

  1%|▏         | 8538/569592 [7:10:32<322:55:30,  2.07s/it]
  1%|▏         | 8539/569592 [7:10:36<406:41:13,  2.61s/it]
                                                           

  1%|▏         | 8539/569592 [7:10:36<406:41:13,  2.61s/it]
  1%|▏         | 8540/569592 [7:10:37<328:55:13,  2.11s/it]
                                                           

  1%|▏         | 8540/569592 [7:10:37<328:55:13,  2.11s/it]
  1%|▏         | 8541/569592 [7:10:37<273:45:53,  1.76s/it]
                                                           

  1%|▏         | 8541/569592 [7:10:37<273:45:53,  1.76s/it]
  1%|▏         | 8542/569592 [7:10:42<408:38:17,  2.62s/it]
                                                           

  1%|▏         | 8542/569592 [7:10:42<408:38:17,  2.62s/it]
  1%|▏         | 8543/569592 [7:10:45<438:50:42,  2.82s/it]
                                                           

  1%|▏         | 8543/569592 [7:10:45<438:50:42,  2.82s/it]
  2%|▏         | 8544/569592 [7:10:49<473:51:46,  3.04s/it]
                                                           

  2%|▏         | 8544/569592 [7:10:49<473:51:46,  3.04s/it]
  2%|▏         | 8545/569592 [7:10:52<497:34:38,  3.19s/it]
                                                           

  2%|▏         | 8545/569592 [7:10:52<497:34:38,  3.19s/it]
  2%|▏         | 8546/569592 [7:10:54<396:11:02,  2.54s/it]
                                                           

  2%|▏         | 8546/569592 [7:10:54<396:11:02,  2.54s/it]
  2%|▏         | 8547/569592 [7:10:54<320:38:59,  2.06s/it]
                                                           

  2%|▏         | 8547/569592 [7:10:54<320:38:59,  2.06s/it]
  2%|▏         | 8548/569592 [7:10:58<390:26:39,  2.51s/it]
                                                           

  2%|▏         | 8548/569592 [7:10:58<390:26:39,  2.51s/it]
  2%|▏         | 8549/569592 [7:11:01<426:00:41,  2.73s/it]
                                                           

  2%|▏         | 8549/569592 [7:11:01<426:00:41,  2.73s/it]
  2%|▏         | 8550/569592 [7:11:03<370:25:08,  2.38s/it]
                                                           

  2%|▏         | 8550/569592 [7:11:03<370:25:08,  2.38s/it]
  2%|▏         | 8551/569592 [7:11:06<425:17:10,  2.73s/it]
                                                           

  2%|▏         | 8551/569592 [7:11:06<425:17:10,  2.73s/it]
  2%|▏         | 8552/569592 [7:11:10<489:38:24,  3.14s/it]
                                                           

  2%|▏         | 8552/569592 [7:11:10<489:38:24,  3.14s/it]
  2%|▏         | 8553/569592 [7:11:14<510:11:51,  3.27s/it]
                                                           

  2%|▏         | 8553/569592 [7:11:14<510:11:51,  3.27s/it]
  2%|▏         | 8554/569592 [7:11:17<514:53:11,  3.30s/it]
                                                           

  2%|▏         | 8554/569592 [7:11:17<514:53:11,  3.30s/it]
  2%|▏         | 8555/569592 [7:11:22<563:24:22,  3.62s/it]
                                                           

  2%|▏         | 8555/569592 [7:11:22<563:24:22,  3.62s/it]
  2%|▏         | 8556/569592 [7:11:25<540:28:25,  3.47s/it]
                                                           

  2%|▏         | 8556/569592 [7:11:25<540:28:25,  3.47s/it]
  2%|▏         | 8557/569592 [7:11:28<528:24:19,  3.39s/it]
                                                           

  2%|▏         | 8557/569592 [7:11:28<528:24:19,  3.39s/it]
  2%|▏         | 8558/569592 [7:11:29<412:05:02,  2.64s/it]
                                                           

  2%|▏         | 8558/569592 [7:11:29<412:05:02,  2.64s/it]
  2%|▏         | 8559/569592 [7:11:33<457:33:33,  2.94s/it]
                                                           

  2%|▏         | 8559/569592 [7:11:33<457:33:33,  2.94s/it]
  2%|▏         | 8560/569592 [7:11:36<465:43:55,  2.99s/it]
                                                           

  2%|▏         | 8560/569592 [7:11:36<465:43:55,  2.99s/it]
  2%|▏         | 8561/569592 [7:11:37<371:32:46,  2.38s/it]
                                                           

  2%|▏         | 8561/569592 [7:11:37<371:32:46,  2.38s/it]
  2%|▏         | 8562/569592 [7:11:41<452:42:11,  2.90s/it]
                                                           

  2%|▏         | 8562/569592 [7:11:41<452:42:11,  2.90s/it]
  2%|▏         | 8563/569592 [7:11:44<488:18:25,  3.13s/it]
                                                           

  2%|▏         | 8563/569592 [7:11:44<488:18:25,  3.13s/it]
  2%|▏         | 8564/569592 [7:11:48<497:11:43,  3.19s/it]
                                                           

  2%|▏         | 8564/569592 [7:11:48<497:11:43,  3.19s/it]
  2%|▏         | 8565/569592 [7:11:52<524:43:22,  3.37s/it]
                                                           

  2%|▏         | 8565/569592 [7:11:52<524:43:22,  3.37s/it]
  2%|▏         | 8566/569592 [7:11:52<409:16:45,  2.63s/it]
                                                           

  2%|▏         | 8566/569592 [7:11:52<409:16:45,  2.63s/it]
  2%|▏         | 8567/569592 [7:11:57<479:33:23,  3.08s/it]
                                                           

  2%|▏         | 8567/569592 [7:11:57<479:33:23,  3.08s/it]
  2%|▏         | 8568/569592 [7:12:00<503:05:56,  3.23s/it]
                                                           

  2%|▏         | 8568/569592 [7:12:01<503:05:56,  3.23s/it]
  2%|▏         | 8569/569592 [7:12:04<536:48:23,  3.44s/it]
                                                           

  2%|▏         | 8569/569592 [7:12:04<536:48:23,  3.44s/it]
  2%|▏         | 8570/569592 [7:12:08<548:46:14,  3.52s/it]
                                                           

  2%|▏         | 8570/569592 [7:12:08<548:46:14,  3.52s/it]
  2%|▏         | 8571/569592 [7:12:11<526:04:20,  3.38s/it]
                                                           

  2%|▏         | 8571/569592 [7:12:11<526:04:20,  3.38s/it]
  2%|▏         | 8572/569592 [7:12:15<558:04:03,  3.58s/it]
                                                           

  2%|▏         | 8572/569592 [7:12:15<558:04:03,  3.58s/it]
  2%|▏         | 8573/569592 [7:12:18<549:05:44,  3.52s/it]
                                                           

  2%|▏         | 8573/569592 [7:12:18<549:05:44,  3.52s/it]
  2%|▏         | 8574/569592 [7:12:22<551:52:53,  3.54s/it]
                                                           

  2%|▏         | 8574/569592 [7:12:22<551:52:53,  3.54s/it]
  2%|▏         | 8575/569592 [7:12:25<538:16:55,  3.45s/it]
                                                           

  2%|▏         | 8575/569592 [7:12:25<538:16:55,  3.45s/it]
  2%|▏         | 8576/569592 [7:12:29<576:32:43,  3.70s/it]
                                                           

  2%|▏         | 8576/569592 [7:12:29<576:32:43,  3.70s/it]
  2%|▏         | 8577/569592 [7:12:33<577:39:15,  3.71s/it]
                                                           

  2%|▏         | 8577/569592 [7:12:33<577:39:15,  3.71s/it]
  2%|▏         | 8578/569592 [7:12:34<446:57:17,  2.87s/it]
                                                           

  2%|▏         | 8578/569592 [7:12:34<446:57:17,  2.87s/it]
  2%|▏         | 8579/569592 [7:12:38<484:52:33,  3.11s/it]
                                                           

  2%|▏         | 8579/569592 [7:12:38<484:52:33,  3.11s/it]
  2%|▏         | 8580/569592 [7:12:41<498:48:30,  3.20s/it]
                                                           

  2%|▏         | 8580/569592 [7:12:41<498:48:30,  3.20s/it]
  2%|▏         | 8581/569592 [7:12:45<536:27:30,  3.44s/it]
                                                           

  2%|▏         | 8581/569592 [7:12:45<536:27:30,  3.44s/it]
  2%|▏         | 8582/569592 [7:12:46<418:17:39,  2.68s/it]
                                                           

  2%|▏         | 8582/569592 [7:12:46<418:17:39,  2.68s/it]
  2%|▏         | 8583/569592 [7:12:50<468:53:34,  3.01s/it]
                                                           

  2%|▏         | 8583/569592 [7:12:50<468:53:34,  3.01s/it]
  2%|▏         | 8584/569592 [7:12:53<480:01:40,  3.08s/it]
                                                           

  2%|▏         | 8584/569592 [7:12:53<480:01:40,  3.08s/it]
  2%|▏         | 8585/569592 [7:12:54<381:13:02,  2.45s/it]
                                                           

  2%|▏         | 8585/569592 [7:12:54<381:13:02,  2.45s/it]
  2%|▏         | 8586/569592 [7:12:55<314:23:05,  2.02s/it]
                                                           

  2%|▏         | 8586/569592 [7:12:55<314:23:05,  2.02s/it]
  2%|▏         | 8587/569592 [7:12:59<382:28:35,  2.45s/it]
                                                           

  2%|▏         | 8587/569592 [7:12:59<382:28:35,  2.45s/it]
  2%|▏         | 8588/569592 [7:13:00<313:18:00,  2.01s/it]
                                                           

  2%|▏         | 8588/569592 [7:13:00<313:18:00,  2.01s/it]
  2%|▏         | 8589/569592 [7:13:04<436:36:10,  2.80s/it]
                                                           

  2%|▏         | 8589/569592 [7:13:04<436:36:10,  2.80s/it]
  2%|▏         | 8590/569592 [7:13:05<351:25:57,  2.26s/it]
                                                           

  2%|▏         | 8590/569592 [7:13:05<351:25:57,  2.26s/it]
  2%|▏         | 8591/569592 [7:13:09<413:12:54,  2.65s/it]
                                                           

  2%|▏         | 8591/569592 [7:13:09<413:12:54,  2.65s/it]
  2%|▏         | 8592/569592 [7:13:12<450:50:20,  2.89s/it]
                                                           

  2%|▏         | 8592/569592 [7:13:12<450:50:20,  2.89s/it]
  2%|▏         | 8593/569592 [7:13:16<490:04:23,  3.14s/it]
                                                           

  2%|▏         | 8593/569592 [7:13:16<490:04:23,  3.14s/it]
  2%|▏         | 8594/569592 [7:13:20<528:21:05,  3.39s/it]
                                                           

  2%|▏         | 8594/569592 [7:13:20<528:21:05,  3.39s/it]
  2%|▏         | 8595/569592 [7:13:23<511:35:15,  3.28s/it]
                                                           

  2%|▏         | 8595/569592 [7:13:23<511:35:15,  3.28s/it]
  2%|▏         | 8596/569592 [7:13:26<514:53:28,  3.30s/it]
                                                           

  2%|▏         | 8596/569592 [7:13:26<514:53:28,  3.30s/it]
  2%|▏         | 8597/569592 [7:13:27<416:29:46,  2.67s/it]
                                                           

  2%|▏         | 8597/569592 [7:13:27<416:29:46,  2.67s/it]
  2%|▏         | 8598/569592 [7:13:28<336:39:30,  2.16s/it]
                                                           

 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (101518284 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
 2%|▏         | 8598/569592 [7:13:28<336:39:30,  2.16s/it]
  2%|▏         | 8599/569592 [7:13:32<394:44:36,  2.53s/it]
                                                           

  2%|▏         | 8599/569592 [7:13:32<394:44:36,  2.53s/it]
  2%|▏         | 8600/569592 [7:13:35<439:36:11,  2.82s/it]
                                                           

  2%|▏         | 8600/569592 [7:13:35<439:36:11,  2.82s/it]
  2%|▏         | 8601/569592 [7:13:36<352:20:23,  2.26s/it]
                                                           

  2%|▏         | 8601/569592 [7:13:36<352:20:23,  2.26s/it]
  2%|▏         | 8602/569592 [7:13:40<413:27:08,  2.65s/it]
                                                           

  2%|▏         | 8602/569592 [7:13:40<413:27:08,  2.65s/it]
  2%|▏         | 8603/569592 [7:13:44<471:53:15,  3.03s/it]
                                                           

  2%|▏         | 8603/569592 [7:13:44<471:53:15,  3.03s/it]
  2%|▏         | 8604/569592 [7:13:47<491:00:39,  3.15s/it]
                                                           

  2%|▏         | 8604/569592 [7:13:47<491:00:39,  3.15s/it]
  2%|▏         | 8605/569592 [7:13:51<499:41:29,  3.21s/it]
                                                           

  2%|▏         | 8605/569592 [7:13:51<499:41:29,  3.21s/it]
  2%|▏         | 8606/569592 [7:13:54<526:14:30,  3.38s/it]
                                                           

  2%|▏         | 8606/569592 [7:13:54<526:14:30,  3.38s/it]
  2%|▏         | 8607/569592 [7:13:57<509:59:45,  3.27s/it]
                                                           

  2%|▏         | 8607/569592 [7:13:57<509:59:45,  3.27s/it]
  2%|▏         | 8608/569592 [7:14:01<545:11:37,  3.50s/it]
                                                           

  2%|▏         | 8608/569592 [7:14:01<545:11:37,  3.50s/it]
  2%|▏         | 8609/569592 [7:14:02<424:40:16,  2.73s/it]
                                                           

  2%|▏         | 8609/569592 [7:14:02<424:40:16,  2.73s/it]
  2%|▏         | 8610/569592 [7:14:03<341:13:33,  2.19s/it]
                                                           

  2%|▏         | 8610/569592 [7:14:03<341:13:33,  2.19s/it]
  2%|▏         | 8611/569592 [7:14:07<423:10:11,  2.72s/it]
                                                           

  2%|▏         | 8611/569592 [7:14:07<423:10:11,  2.72s/it]
  2%|▏         | 8612/569592 [7:14:08<346:33:49,  2.22s/it]
                                                           

  2%|▏         | 8612/569592 [7:14:08<346:33:49,  2.22s/it]
  2%|▏         | 8613/569592 [7:14:12<424:47:25,  2.73s/it]
                                                           

  2%|▏         | 8613/569592 [7:14:12<424:47:25,  2.73s/it]
  2%|▏         | 8614/569592 [7:14:16<479:04:52,  3.07s/it]
                                                           

  2%|▏         | 8614/569592 [7:14:16<479:04:52,  3.07s/it]
  2%|▏         | 8615/569592 [7:14:20<509:04:51,  3.27s/it]
                                                           

  2%|▏         | 8615/569592 [7:14:20<509:04:51,  3.27s/it]
  2%|▏         | 8616/569592 [7:14:21<402:08:39,  2.58s/it]
                                                           

  2%|▏         | 8616/569592 [7:14:21<402:08:39,  2.58s/it]
  2%|▏         | 8617/569592 [7:14:22<325:56:10,  2.09s/it]
                                                           

  2%|▏         | 8617/569592 [7:14:22<325:56:10,  2.09s/it]
  2%|▏         | 8618/569592 [7:14:23<272:28:46,  1.75s/it]
                                                           

  2%|▏         | 8618/569592 [7:14:23<272:28:46,  1.75s/it]
  2%|▏         | 8619/569592 [7:14:24<235:38:41,  1.51s/it]
                                                           

  2%|▏         | 8619/569592 [7:14:24<235:38:41,  1.51s/it]
  2%|▏         | 8620/569592 [7:14:27<341:27:57,  2.19s/it]
                                                           

  2%|▏         | 8620/569592 [7:14:27<341:27:57,  2.19s/it]
  2%|▏         | 8621/569592 [7:14:28<283:07:15,  1.82s/it]
                                                           

  2%|▏         | 8621/569592 [7:14:28<283:07:15,  1.82s/it]
  2%|▏         | 8622/569592 [7:14:32<382:19:22,  2.45s/it]
                                                           

  2%|▏         | 8622/569592 [7:14:32<382:19:22,  2.45s/it]
  2%|▏         | 8623/569592 [7:14:37<495:17:59,  3.18s/it]
                                                           

  2%|▏         | 8623/569592 [7:14:37<495:17:59,  3.18s/it]
  2%|▏         | 8624/569592 [7:14:38<391:00:08,  2.51s/it]
                                                           

  2%|▏         | 8624/569592 [7:14:38<391:00:08,  2.51s/it]
  2%|▏         | 8625/569592 [7:14:39<318:06:13,  2.04s/it]
                                                           

  2%|▏         | 8625/569592 [7:14:39<318:06:13,  2.04s/it]
  2%|▏         | 8626/569592 [7:14:40<268:25:19,  1.72s/it]
                                                           

  2%|▏         | 8626/569592 [7:14:40<268:25:19,  1.72s/it]
  2%|▏         | 8627/569592 [7:14:43<351:07:54,  2.25s/it]
                                                           

  2%|▏         | 8627/569592 [7:14:44<351:07:54,  2.25s/it]
  2%|▏         | 8628/569592 [7:14:47<404:24:13,  2.60s/it]
                                                           

  2%|▏         | 8628/569592 [7:14:47<404:24:13,  2.60s/it]
  2%|▏         | 8629/569592 [7:14:48<328:16:21,  2.11s/it]
                                                           

  2%|▏         | 8629/569592 [7:14:48<328:16:21,  2.11s/it]
  2%|▏         | 8630/569592 [7:14:49<275:23:10,  1.77s/it]
                                                           

  2%|▏         | 8630/569592 [7:14:49<275:23:10,  1.77s/it]
  2%|▏         | 8631/569592 [7:14:50<236:57:04,  1.52s/it]
                                                           

  2%|▏         | 8631/569592 [7:14:50<236:57:04,  1.52s/it]
  2%|▏         | 8632/569592 [7:14:55<391:42:27,  2.51s/it]
                                                           

  2%|▏         | 8632/569592 [7:14:55<391:42:27,  2.51s/it]
  2%|▏         | 8633/569592 [7:14:58<434:01:09,  2.79s/it]
                                                           

  2%|▏         | 8633/569592 [7:14:58<434:01:09,  2.79s/it]
  2%|▏         | 8634/569592 [7:15:02<474:12:58,  3.04s/it]
                                                           

  2%|▏         | 8634/569592 [7:15:02<474:12:58,  3.04s/it]
  2%|▏         | 8635/569592 [7:15:06<516:22:45,  3.31s/it]
                                                           

  2%|▏         | 8635/569592 [7:15:06<516:22:45,  3.31s/it]
  2%|▏         | 8636/569592 [7:15:09<523:35:18,  3.36s/it]
                                                           

  2%|▏         | 8636/569592 [7:15:09<523:35:18,  3.36s/it]
  2%|▏         | 8637/569592 [7:15:13<528:04:11,  3.39s/it]
                                                           

  2%|▏         | 8637/569592 [7:15:13<528:04:11,  3.39s/it]
  2%|▏         | 8638/569592 [7:15:16<522:15:51,  3.35s/it]
                                                           

  2%|▏         | 8638/569592 [7:15:16<522:15:51,  3.35s/it]
  2%|▏         | 8639/569592 [7:15:17<409:27:28,  2.63s/it]
                                                           

  2%|▏         | 8639/569592 [7:15:17<409:27:28,  2.63s/it]
  2%|▏         | 8640/569592 [7:15:18<331:04:51,  2.12s/it]
                                                           

  2%|▏         | 8640/569592 [7:15:18<331:04:51,  2.12s/it]
  2%|▏         | 8641/569592 [7:15:22<414:10:50,  2.66s/it]
                                                           

  2%|▏         | 8641/569592 [7:15:22<414:10:50,  2.66s/it]
  2%|▏         | 8642/569592 [7:15:23<340:18:46,  2.18s/it]
                                                           

  2%|▏         | 8642/569592 [7:15:23<340:18:46,  2.18s/it]
  2%|▏         | 8643/569592 [7:15:26<411:22:49,  2.64s/it]
                                                           

  2%|▏         | 8643/569592 [7:15:26<411:22:49,  2.64s/it]
  2%|▏         | 8644/569592 [7:15:30<440:27:33,  2.83s/it]
                                                           

  2%|▏         | 8644/569592 [7:15:30<440:27:33,  2.83s/it]
  2%|▏         | 8645/569592 [7:15:31<352:03:57,  2.26s/it]
                                                           

  2%|▏         | 8645/569592 [7:15:31<352:03:57,  2.26s/it]
  2%|▏         | 8646/569592 [7:15:34<406:14:22,  2.61s/it]
                                                           

  2%|▏         | 8646/569592 [7:15:34<406:14:22,  2.61s/it]
  2%|▏         | 8647/569592 [7:15:38<467:36:00,  3.00s/it]
                                                           

  2%|▏         | 8647/569592 [7:15:38<467:36:00,  3.00s/it]
  2%|▏         | 8648/569592 [7:15:39<372:47:28,  2.39s/it]
                                                           

  2%|▏         | 8648/569592 [7:15:39<372:47:28,  2.39s/it]
  2%|▏         | 8649/569592 [7:15:40<305:36:42,  1.96s/it]
                                                           

  2%|▏         | 8649/569592 [7:15:40<305:36:42,  1.96s/it]
  2%|▏         | 8650/569592 [7:15:41<265:51:39,  1.71s/it]
                                                           

  2%|▏         | 8650/569592 [7:15:41<265:51:39,  1.71s/it]
  2%|▏         | 8651/569592 [7:15:42<230:22:01,  1.48s/it]
                                                           

  2%|▏         | 8651/569592 [7:15:42<230:22:01,  1.48s/it]
  2%|▏         | 8652/569592 [7:15:46<338:31:16,  2.17s/it]
                                                           

  2%|▏         | 8652/569592 [7:15:46<338:31:16,  2.17s/it]
  2%|▏         | 8653/569592 [7:15:47<283:02:02,  1.82s/it]
                                                           

  2%|▏         | 8653/569592 [7:15:47<283:02:02,  1.82s/it]
  2%|▏         | 8654/569592 [7:15:50<341:31:55,  2.19s/it]
                                                           

  2%|▏         | 8654/569592 [7:15:50<341:31:55,  2.19s/it]
  2%|▏         | 8655/569592 [7:15:53<411:30:00,  2.64s/it]
                                                           

  2%|▏         | 8655/569592 [7:15:53<411:30:00,  2.64s/it]
  2%|▏         | 8656/569592 [7:15:56<391:38:41,  2.51s/it]
                                                           

  2%|▏         | 8656/569592 [7:15:56<391:38:41,  2.51s/it]
  2%|▏         | 8657/569592 [7:15:57<321:49:07,  2.07s/it]
                                                           

  2%|▏         | 8657/569592 [7:15:57<321:49:07,  2.07s/it]
  2%|▏         | 8658/569592 [7:16:00<378:52:19,  2.43s/it]
                                                           

  2%|▏         | 8658/569592 [7:16:00<378:52:19,  2.43s/it]
  2%|▏         | 8659/569592 [7:16:03<428:44:42,  2.75s/it]
                                                           

  2%|▏         | 8659/569592 [7:16:03<428:44:42,  2.75s/it]
  2%|▏         | 8660/569592 [7:16:05<383:14:27,  2.46s/it]
                                                           

  2%|▏         | 8660/569592 [7:16:05<383:14:27,  2.46s/it]
  2%|▏         | 8661/569592 [7:16:09<430:38:22,  2.76s/it]
                                                           

  2%|▏         | 8661/569592 [7:16:09<430:38:22,  2.76s/it]
  2%|▏         | 8662/569592 [7:16:12<473:34:47,  3.04s/it]
                                                           

  2%|▏         | 8662/569592 [7:16:12<473:34:47,  3.04s/it]
  2%|▏         | 8663/569592 [7:16:13<379:53:59,  2.44s/it]
                                                           

  2%|▏         | 8663/569592 [7:16:13<379:53:59,  2.44s/it]
  2%|▏         | 8664/569592 [7:16:17<435:43:11,  2.80s/it]
                                                           

  2%|▏         | 8664/569592 [7:16:17<435:43:11,  2.80s/it]
  2%|▏         | 8665/569592 [7:16:21<475:15:24,  3.05s/it]
                                                           

  2%|▏         | 8665/569592 [7:16:21<475:15:24,  3.05s/it]
  2%|▏         | 8666/569592 [7:16:22<379:40:47,  2.44s/it]
                                                           

  2%|▏         | 8666/569592 [7:16:22<379:40:47,  2.44s/it]
  2%|▏         | 8667/569592 [7:16:23<309:31:47,  1.99s/it]
                                                           

  2%|▏         | 8667/569592 [7:16:23<309:31:47,  1.99s/it]
  2%|▏         | 8668/569592 [7:16:26<383:02:05,  2.46s/it]
                                                           

  2%|▏         | 8668/569592 [7:16:26<383:02:05,  2.46s/it]
  2%|▏         | 8669/569592 [7:16:30<451:42:35,  2.90s/it]
                                                           

  2%|▏         | 8669/569592 [7:16:30<451:42:35,  2.90s/it]
  2%|▏         | 8670/569592 [7:16:35<549:34:35,  3.53s/it]
                                                           

  2%|▏         | 8670/569592 [7:16:35<549:34:35,  3.53s/it]
  2%|▏         | 8671/569592 [7:16:39<558:27:08,  3.58s/it]
                                                           

  2%|▏         | 8671/569592 [7:16:39<558:27:08,  3.58s/it]
  2%|▏         | 8672/569592 [7:16:40<433:58:15,  2.79s/it]
                                                           

  2%|▏         | 8672/569592 [7:16:40<433:58:15,  2.79s/it]
  2%|▏         | 8673/569592 [7:16:43<474:24:05,  3.04s/it]
                                                           

  2%|▏         | 8673/569592 [7:16:43<474:24:05,  3.04s/it]
  2%|▏         | 8674/569592 [7:16:47<497:19:13,  3.19s/it]
                                                           

  2%|▏         | 8674/569592 [7:16:47<497:19:13,  3.19s/it]
  2%|▏         | 8675/569592 [7:16:51<519:53:13,  3.34s/it]
                                                           

  2%|▏         | 8675/569592 [7:16:51<519:53:13,  3.34s/it]
  2%|▏         | 8676/569592 [7:16:54<510:55:45,  3.28s/it]
                                                           

  2%|▏         | 8676/569592 [7:16:54<510:55:45,  3.28s/it]
  2%|▏         | 8677/569592 [7:16:57<515:58:58,  3.31s/it]
                                                           

  2%|▏         | 8677/569592 [7:16:57<515:58:58,  3.31s/it]
  2%|▏         | 8678/569592 [7:17:00<514:01:59,  3.30s/it]
                                                           

  2%|▏         | 8678/569592 [7:17:00<514:01:59,  3.30s/it]
  2%|▏         | 8679/569592 [7:17:01<403:00:56,  2.59s/it]
                                                           

  2%|▏         | 8679/569592 [7:17:01<403:00:56,  2.59s/it]
  2%|▏         | 8680/569592 [7:17:06<494:02:24,  3.17s/it]
                                                           

  2%|▏         | 8680/569592 [7:17:06<494:02:24,  3.17s/it]
  2%|▏         | 8681/569592 [7:17:09<508:53:52,  3.27s/it]
                                                           

  2%|▏         | 8681/569592 [7:17:09<508:53:52,  3.27s/it]
  2%|▏         | 8682/569592 [7:17:10<400:57:25,  2.57s/it]
                                                           

  2%|▏         | 8682/569592 [7:17:10<400:57:25,  2.57s/it]
  2%|▏         | 8683/569592 [7:17:16<554:40:15,  3.56s/it]
                                                           

  2%|▏         | 8683/569592 [7:17:16<554:40:15,  3.56s/it]
  2%|▏         | 8684/569592 [7:17:20<566:45:27,  3.64s/it]
                                                           

  2%|▏         | 8684/569592 [7:17:20<566:45:27,  3.64s/it]
  2%|▏         | 8685/569592 [7:17:23<548:42:49,  3.52s/it]
                                                           

  2%|▏         | 8685/569592 [7:17:23<548:42:49,  3.52s/it]
  2%|▏         | 8686/569592 [7:17:27<547:28:26,  3.51s/it]
                                                           

  2%|▏         | 8686/569592 [7:17:27<547:28:26,  3.51s/it]
  2%|▏         | 8687/569592 [7:17:30<542:30:49,  3.48s/it]
                                                           

  2%|▏         | 8687/569592 [7:17:30<542:30:49,  3.48s/it]
  2%|▏         | 8688/569592 [7:17:34<546:11:27,  3.51s/it]
                                                           

  2%|▏         | 8688/569592 [7:17:34<546:11:27,  3.51s/it]
  2%|▏         | 8689/569592 [7:17:37<531:00:50,  3.41s/it]
                                                           

  2%|▏         | 8689/569592 [7:17:37<531:00:50,  3.41s/it]
  2%|▏         | 8690/569592 [7:17:40<518:21:42,  3.33s/it]
                                                           

  2%|▏         | 8690/569592 [7:17:40<518:21:42,  3.33s/it]
  2%|▏         | 8691/569592 [7:17:43<518:37:49,  3.33s/it]
                                                           

  2%|▏         | 8691/569592 [7:17:43<518:37:49,  3.33s/it]
  2%|▏         | 8692/569592 [7:17:48<566:31:40,  3.64s/it]
                                                           

  2%|▏         | 8692/569592 [7:17:48<566:31:40,  3.64s/it]
  2%|▏         | 8693/569592 [7:17:52<616:19:19,  3.96s/it]
                                                           

  2%|▏         | 8693/569592 [7:17:52<616:19:19,  3.96s/it]
  2%|▏         | 8694/569592 [7:17:57<637:50:21,  4.09s/it]
                                                           

  2%|▏         | 8694/569592 [7:17:57<637:50:21,  4.09s/it]
  2%|▏         | 8695/569592 [7:18:01<623:11:57,  4.00s/it]
                                                           

  2%|▏         | 8695/569592 [7:18:01<623:11:57,  4.00s/it]
  2%|▏         | 8696/569592 [7:18:04<599:48:19,  3.85s/it]
                                                           

  2%|▏         | 8696/569592 [7:18:04<599:48:19,  3.85s/it]
  2%|▏         | 8697/569592 [7:18:07<563:26:25,  3.62s/it]
                                                           

  2%|▏         | 8697/569592 [7:18:07<563:26:25,  3.62s/it]
  2%|▏         | 8698/569592 [7:18:11<551:44:23,  3.54s/it]
                                                           

  2%|▏         | 8698/569592 [7:18:11<551:44:23,  3.54s/it]
  2%|▏         | 8699/569592 [7:18:15<573:14:57,  3.68s/it]
                                                           

  2%|▏         | 8699/569592 [7:18:15<573:14:57,  3.68s/it]
  2%|▏         | 8700/569592 [7:18:18<568:11:43,  3.65s/it]
                                                           

  2%|▏         | 8700/569592 [7:18:18<568:11:43,  3.65s/it]
  2%|▏         | 8701/569592 [7:18:21<542:01:13,  3.48s/it]
                                                           

  2%|▏         | 8701/569592 [7:18:21<542:01:13,  3.48s/it]
  2%|▏         | 8702/569592 [7:18:25<554:46:14,  3.56s/it]
                                                           

  2%|▏         | 8702/569592 [7:18:25<554:46:14,  3.56s/it]
  2%|▏         | 8703/569592 [7:18:26<430:29:20,  2.76s/it]
                                                           

  2%|▏         | 8703/569592 [7:18:26<430:29:20,  2.76s/it]
  2%|▏         | 8704/569592 [7:18:27<345:51:45,  2.22s/it]
                                                           

  2%|▏         | 8704/569592 [7:18:27<345:51:45,  2.22s/it]
  2%|▏         | 8705/569592 [7:18:30<399:54:06,  2.57s/it]
                                                           

  2%|▏         | 8705/569592 [7:18:30<399:54:06,  2.57s/it]
  2%|▏         | 8706/569592 [7:18:31<325:25:22,  2.09s/it]
                                                           

  2%|▏         | 8706/569592 [7:18:31<325:25:22,  2.09s/it]
  2%|▏         | 8707/569592 [7:18:35<399:20:34,  2.56s/it]
                                                           

  2%|▏         | 8707/569592 [7:18:35<399:20:34,  2.56s/it]
  2%|▏         | 8708/569592 [7:18:36<323:31:59,  2.08s/it]
                                                           

  2%|▏         | 8708/569592 [7:18:36<323:31:59,  2.08s/it]
  2%|▏         | 8709/569592 [7:18:40<406:21:54,  2.61s/it]
                                                           

  2%|▏         | 8709/569592 [7:18:40<406:21:54,  2.61s/it]
  2%|▏         | 8710/569592 [7:18:41<330:30:49,  2.12s/it]
                                                           

  2%|▏         | 8710/569592 [7:18:41<330:30:49,  2.12s/it]
  2%|▏         | 8711/569592 [7:18:44<406:35:55,  2.61s/it]
                                                           

  2%|▏         | 8711/569592 [7:18:44<406:35:55,  2.61s/it]
  2%|▏         | 8712/569592 [7:18:48<440:15:56,  2.83s/it]
                                                           

  2%|▏         | 8712/569592 [7:18:48<440:15:56,  2.83s/it]
  2%|▏         | 8713/569592 [7:18:49<354:20:35,  2.27s/it]
                                                           

  2%|▏         | 8713/569592 [7:18:49<354:20:35,  2.27s/it]
  2%|▏         | 8714/569592 [7:18:52<399:49:09,  2.57s/it]
                                                           

  2%|▏         | 8714/569592 [7:18:52<399:4/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (90481664 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
9:09,  2.57s/it]
  2%|▏         | 8715/569592 [7:18:53<324:19:59,  2.08s/it]
                                                           

  2%|▏         | 8715/569592 [7:18:53<324:19:59,  2.08s/it]
  2%|▏         | 8716/569592 [7:18:56<397:18:44,  2.55s/it]
                                                           

  2%|▏         | 8716/569592 [7:18:57<397:18:44,  2.55s/it]
  2%|▏         | 8717/569592 [7:19:00<434:41:43,  2.79s/it]
                                                           

  2%|▏         | 8717/569592 [7:19:00<434:41:43,  2.79s/it]
  2%|▏         | 8718/569592 [7:19:03<457:05:42,  2.93s/it]
                                                           

  2%|▏         | 8718/569592 [7:19:03<457:05:42,  2.93s/it]
  2%|▏         | 8719/569592 [7:19:04<364:19:13,  2.34s/it]
                                                           

  2%|▏         | 8719/569592 [7:19:04<364:19:13,  2.34s/it]
  2%|▏         | 8720/569592 [7:19:08<428:57:25,  2.75s/it]
                                                           

  2%|▏         | 8720/569592 [7:19:08<428:57:25,  2.75s/it]
  2%|▏         | 8721/569592 [7:19:11<469:56:45,  3.02s/it]
                                                           

  2%|▏         | 8721/569592 [7:19:11<469:56:45,  3.02s/it]
  2%|▏         | 8722/569592 [7:19:12<373:52:36,  2.40s/it]
                                                           

  2%|▏         | 8722/569592 [7:19:12<373:52:36,  2.40s/it]
  2%|▏         | 8723/569592 [7:19:17<496:36:48,  3.19s/it]
                                                           

  2%|▏         | 8723/569592 [7:19:17<496:36:48,  3.19s/it]
  2%|▏         | 8724/569592 [7:19:18<392:15:59,  2.52s/it]
                                                           

  2%|▏         | 8724/569592 [7:19:18<392:15:59,  2.52s/it]
  2%|▏         | 8725/569592 [7:19:22<459:23:03,  2.95s/it]
                                                           

  2%|▏         | 8725/569592 [7:19:22<459:23:03,  2.95s/it]
  2%|▏         | 8726/569592 [7:19:27<545:24:39,  3.50s/it]
                                                           

  2%|▏         | 8726/569592 [7:19:27<545:24:39,  3.50s/it]
  2%|▏         | 8727/569592 [7:19:28<423:32:16,  2.72s/it]
                                                           

  2%|▏         | 8727/569592 [7:19:28<423:32:16,  2.72s/it]
  2%|▏         | 8728/569592 [7:19:32<468:37:42,  3.01s/it]
                                                           

  2%|▏         | 8728/569592 [7:19:32<468:37:42,  3.01s/it]
  2%|▏         | 8729/569592 [7:19:35<491:49:10,  3.16s/it]
                                                           

  2%|▏         | 8729/569592 [7:19:35<491:49:10,  3.16s/it]
  2%|▏         | 8730/569592 [7:19:38<488:09:57,  3.13s/it]
                                                           

  2%|▏         | 8730/569592 [7:19:38<488:09:57,  3.13s/it]
  2%|▏         | 8731/569592 [7:19:42<498:15:09,  3.20s/it]
                                                           

  2%|▏         | 8731/569592 [7:19:42<498:15:09,  3.20s/it]
  2%|▏         | 8732/569592 [7:19:45<505:02:36,  3.24s/it]
                                                           

  2%|▏         | 8732/569592 [7:19:45<505:02:36,  3.24s/it]
  2%|▏         | 8733/569592 [7:19:48<501:19:25,  3.22s/it]
                                                           

  2%|▏         | 8733/569592 [7:19:48<501:19:25,  3.22s/it]
  2%|▏         | 8734/569592 [7:19:51<505:53:31,  3.25s/it]
                                                           

  2%|▏         | 8734/569592 [7:19:51<505:53:31,  3.25s/it]
  2%|▏         | 8735/569592 [7:19:53<411:01:45,  2.64s/it]
                                                           

  2%|▏         | 8735/569592 [7:19:53<411:01:45,  2.64s/it]
  2%|▏         | 8736/569592 [7:19:54<331:30:27,  2.13s/it]
                                                           

  2%|▏         | 8736/569592 [7:19:54<331:30:27,  2.13s/it]
  2%|▏         | 8737/569592 [7:19:55<279:00:07,  1.79s/it]
                                                           

  2%|▏         | 8737/569592 [7:19:55<279:00:07,  1.79s/it]
  2%|▏         | 8738/569592 [7:19:58<364:30:42,  2.34s/it]
                                                           

  2%|▏         | 8738/569592 [7:19:58<364:30:42,  2.34s/it]
  2%|▏         | 8739/569592 [7:19:59<298:52:13,  1.92s/it]
                                                           

  2%|▏         | 8739/569592 [7:19:59<298:52:13,  1.92s/it]
  2%|▏         | 8740/569592 [7:20:03<377:43:40,  2.42s/it]
                                                           

  2%|▏         | 8740/569592 [7:20:03<377:43:40,  2.42s/it]
  2%|▏         | 8741/569592 [7:20:04<311:14:27,  2.00s/it]
                                                           

  2%|▏         | 8741/569592 [7:20:04<311:14:27,  2.00s/it]
  2%|▏         | 8742/569592 [7:20:05<261:59:22,  1.68s/it]
                                                           

  2%|▏         | 8742/569592 [7:20:05<261:59:22,  1.68s/it]
  2%|▏         | 8743/569592 [7:20:06<227:48:00,  1.46s/it]
                                                           

  2%|▏         | 8743/569592 [7:20:06<227:48:00,  1.46s/it]
  2%|▏         | 8744/569592 [7:20:07<204:19:37,  1.31s/it]
                                                           

  2%|▏         | 8744/569592 [7:20:07<204:19:37,  1.31s/it]
  2%|▏         | 8745/569592 [7:20:11<331:27:56,  2.13s/it]
                                                           

  2%|▏         | 8745/569592 [7:20:11<331:27:56,  2.13s/it]
  2%|▏         | 8746/569592 [7:20:12<279:04:19,  1.79s/it]
                                                           

  2%|▏         | 8746/569592 [7:20:12<279:04:19,  1.79s/it]
  2%|▏         | 8747/569592 [7:20:16<410:23:50,  2.63s/it]
                                                           

  2%|▏         | 8747/569592 [7:20:16<410:23:50,  2.63s/it]
  2%|▏         | 8748/569592 [7:20:17<332:50:30,  2.14s/it]
                                                           

  2%|▏         | 8748/569592 [7:20:17<332:50:30,  2.14s/it]
  2%|▏         | 8749/569592 [7:20:21<408:13:55,  2.62s/it]
                                                           

  2%|▏         | 8749/569592 [7:20:21<408:13:55,  2.62s/it]
  2%|▏         | 8750/569592 [7:20:22<332:21:51,  2.13s/it]
                                                           

  2%|▏         | 8750/569592 [7:20:22<332:21:51,  2.13s/it]
  2%|▏         | 8751/569592 [7:20:27<457:36:51,  2.94s/it]
                                                           

  2%|▏         | 8751/569592 [7:20:27<457:36:51,  2.94s/it]
  2%|▏         | 8752/569592 [7:20:30<471:44:05,  3.03s/it]
                                                           

  2%|▏         | 8752/569592 [7:20:30<471:44:05,  3.03s/it]
  2%|▏         | 8753/569592 [7:20:33<487:53:24,  3.13s/it]
                                                           

  2%|▏         | 8753/569592 [7:20:33<487:53:24,  3.13s/it]
  2%|▏         | 8754/569592 [7:20:37<505:14:25,  3.24s/it]
                                                           

  2%|▏         | 8754/569592 [7:20:37<505:14:25,  3.24s/it]
  2%|▏         | 8755/569592 [7:20:38<402:17:33,  2.58s/it]
                                                           

  2%|▏         | 8755/569592 [7:20:38<402:17:33,  2.58s/it]
  2%|▏         | 8756/569592 [7:20:41<444:30:19,  2.85s/it]
                                                           

  2%|▏         | 8756/569592 [7:20:41<444:30:19,  2.85s/it]
  2%|▏         | 8757/569592 [7:20:43<362:14:29,  2.33s/it]
                                                           

  2%|▏         | 8757/569592 [7:20:43<362:14:29,  2.33s/it]
  2%|▏         | 8758/569592 [7:20:44<299:52:06,  1.92s/it]
                                                           

  2%|▏         | 8758/569592 [7:20:44<299:52:06,  1.92s/it]
  2%|▏         | 8759/569592 [7:20:46<317:25:55,  2.04s/it]
                                                           

  2%|▏         | 8759/569592 [7:20:46<317:25:55,  2.04s/it]
  2%|▏         | 8760/569592 [7:20:49<375:19:52,  2.41s/it]
                                                           

  2%|▏         | 8760/569592 [7:20:49<375:19:52,  2.41s/it]
  2%|▏         | 8761/569592 [7:20:53<425:43:19,  2.73s/it]
                                                           

  2%|▏         | 8761/569592 [7:20:53<425:43:19,  2.73s/it]
  2%|▏         | 8762/569592 [7:20:56<449:41:21,  2.89s/it]
                                                           

  2%|▏         | 8762/569592 [7:20:56<449:41:21,  2.89s/it]
  2%|▏         | 8763/569592 [7:20:59<474:29:47,  3.05s/it]
                                                           

  2%|▏         | 8763/569592 [7:20:59<474:29:47,  3.05s/it]
  2%|▏         | 8764/569592 [7:21:03<485:28:54,  3.12s/it]
                                                           

  2%|▏         | 8764/569592 [7:21:03<485:28:54,  3.12s/it]
  2%|▏         | 8765/569592 [7:21:06<501:34:00,  3.22s/it]
                                                           

  2%|▏         | 8765/569592 [7:21:06<501:34:00,  3.22s/it]
  2%|▏         | 8766/569592 [7:21:07<396:00:00,  2.54s/it]
                                                           

  2%|▏         | 8766/569592 [7:21:07<396:00:00,  2.54s/it]
  2%|▏         | 8767/569592 [7:21:08<331:44:50,  2.13s/it]
                                                           

  2%|▏         | 8767/569592 [7:21:08<331:44:50,  2.13s/it]
  2%|▏         | 8768/569592 [7:21:09<277:12:26,  1.78s/it]
                                                           

  2%|▏         | 8768/569592 [7:21:09<277:12:26,  1.78s/it]
  2%|▏         | 8769/569592 [7:21:12<345:54:45,  2.22s/it]
                                                           

  2%|▏         | 8769/569592 [7:21:12<345:54:45,  2.22s/it]
  2%|▏         | 8770/569592 [7:21:14<312:27:31,  2.01s/it]
                                                           

  2%|▏         | 8770/569592 [7:21:14<312:27:31,  2.01s/it]
  2%|▏         | 8771/569592 [7:21:16<329:37:39,  2.12s/it]
                                                           

  2%|▏         | 8771/569592 [7:21:16<329:37:39,  2.12s/it]
  2%|▏         | 8772/569592 [7:21:18<324:52:10,  2.09s/it]
                                                           

  2%|▏         | 8772/569592 [7:21:18<324:52:10,  2.09s/it]
  2%|▏         | 8773/569592 [7:21:22<385:08:45,  2.47s/it]
                                                           

  2%|▏         | 8773/569592 [7:21:22<385:08:45,  2.47s/it]
  2%|▏         | 8774/569592 [7:21:24<383:35:49,  2.46s/it]
                                                           

  2%|▏         | 8774/569592 [7:21:24<383:35:49,  2.46s/it]
  2%|▏         | 8775/569592 [7:21:28<443:37:03,  2.85s/it]
                                                           

  2%|▏         | 8775/569592 [7:21:28<443:37:03,  2.85s/it]
  2%|▏         | 8776/569592 [7:21:30<424:52:31,  2.73s/it]
                                                           

  2%|▏         | 8776/569592 [7:21:30<424:52:31,  2.73s/it]
  2%|▏         | 8777/569592 [7:21:34<478:17:14,  3.07s/it]
                                                           

  2%|▏         | 8777/569592 [7:21:34<478:17:14,  3.07s/it]
  2%|▏         | 8778/569592 [7:21:38<511:24:46,  3.28s/it]
                                                           

  2%|▏         | 8778/569592 [7:21:38<511:24:46,  3.28s/it]
  2%|▏         | 8779/569592 [7:21:41<514:10:27,  3.30s/it]
                                                           

  2%|▏         | 8779/569592 [7:21:41<514:10:27,  3.30s/it]
  2%|▏         | 8780/569592 [7:21:45<516:05:41,  3.31s/it]
                                                           

  2%|▏         | 8780/569592 [7:21:45<516:05:41,  3.31s/it]
  2%|▏         | 8781/569592 [7:21:45<405:34:50,  2.60s/it]
                                                           

  2%|▏         | 8781/569592 [7:21:46<405:34:50,  2.60s/it]
  2%|▏         | 8782/569592 [7:21:49<459:00:01,  2.95s/it]
                                                           

  2%|▏         | 8782/569592 [7:21:49<459:00:01,  2.95s/it]
  2%|▏         | 8783/569592 [7:21:50<366:40:35,  2.35s/it]
                                                           

  2%|▏         | 8783/569592 [7:21:50<366:40:35,  2.35s/it]
  2%|▏         | 8784/569592 [7:21:51<300:51:33,  1.93s/it]
                                                           

  2%|▏         | 8784/569592 [7:21:51<300:51:33,  1.93s/it]
  2%|▏         | 8785/569592 [7:21:55<379:11:34,  2.43s/it]
                                                           

  2%|▏         | 8785/569592 [7:21:55<379:11:34,  2.43s/it]
  2%|▏         | 8786/569592 [7:21:58<439:07:44,  2.82s/it]
                                                           

  2%|▏         | 8786/569592 [7:21:59<439:07:44,  2.82s/it]
  2%|▏         | 8787/569592 [7:22:02<470:52:04,  3.02s/it]
                                                           

  2%|▏         | 8787/569592 [7:22:02<470:52:04,  3.02s/it]
  2%|▏         | 8788/569592 [7:22:06<500:47:16,  3.21s/it]
                                                           

  2%|▏         | 8788/569592 [7:22:06<500:47:16,  3.21s/it]
  2%|▏         | 8789/569592 [7:22:09<502:00:06,  3.22s/it]
                                                           

  2%|▏         | 8789/569592 [7:22:09<502:00:06,  3.22s/it]
  2%|▏         | 8790/569592 [7:22:12<493:31:41,  3.17s/it]
                                                           

  2%|▏         | 8790/569592 [7:22:12<493:31:41,  3.17s/it]
  2%|▏         | 8791/569592 [7:22:16<512:35:54,  3.29s/it]
                                                           

  2%|▏         | 8791/569592 [7:22:16<512:35:54,  3.29s/it]
  2%|▏         | 8792/569592 [7:22:19<519:33:50,  3.34s/it]
                                                           

  2%|▏         | 8792/569592 [7:22:19<519:33:50,  3.34s/it]
  2%|▏         | 8793/569592 [7:22:22<526:03:55,  3.38s/it]
                                                           

  2%|▏         | 8793/569592 [7:22:22<526:03:55,  3.38s/it]
  2%|▏         | 8794/569592 [7:22:26<515:27:07,  3.31s/it]
                                                           

  2%|▏         | 8794/569592 [7:22:26<515:27:07,  3.31s/it]
  2%|▏         | 8795/569592 [7:22:29<514:59:58,  3.31s/it]
                                                           

  2%|▏         | 8795/569592 [7:22:29<514:59:58,  3.31s/it]
  2%|▏         | 8796/569592 [7:22:32<528:40:07,  3.39s/it]
                                                           

  2%|▏         | 8796/569592 [7:22:32<528:40:07,  3.39s/it]
  2%|▏         | 8797/569592 [7:22:33<412:46:38,  2.65s/it]
                                                           

  2%|▏         | 8797/569592 [7:22:33<412:46:38,  2.65s/it]
  2%|▏         | 8798/569592 [7:22:38<482:45:33,  3.10s/it]
                                                           

  2%|▏         | 8798/569592 [7:22:38<482:45:33,  3.10s/it]
  2%|▏         | 8799/569592 [7:22:41<499:11:51,  3.20s/it]
                                                           

  2%|▏         | 8799/569592 [7:22:41<499:11:51,  3.20s/it]
  2%|▏         | 8800/569592 [7:22:45<528:08:31,  3.39s/it]
                                                           

  2%|▏         | 8800/569592 [7:22:45<528:08:31,  3.39s/it]
  2%|▏         | 8801/569592 [7:22:48<520:14:24,  3.34s/it]
                                                           

  2%|▏         | 8801/569592 [7:22:48<520:14:24,  3.34s/it]
  2%|▏         | 8802/569592 [7:22:51<519:11:01,  3.33s/it]
                                                           

  2%|▏         | 8802/569592 [7:22:51<519:11:01,  3.33s/it]
  2%|▏         | 8803/569592 [7:22:56<590:42:32,  3.79s/it]
                                                           

  2%|▏         | 8803/569592 [7:22:56<590:42:32,  3.79s/it]
  2%|▏         | 8804/569592 [7:22:59<561:35:22,  3.61s/it]
                                                           

  2%|▏         | 8804/569592 [7:22:59<561:35:22,  3.61s/it]
  2%|▏         | 8805/569592 [7:23:03<557:03:51,  3.58s/it]
                                                           

  2%|▏         | 8805/569592 [7:23:03<557:03:51,  3.58s/it]
  2%|▏         | 8806/569592 [7:23:07<563:10:57,  3.62s/it]
                                                           

  2%|▏         | 8806/569592 [7:23:07<563:10:57,  3.62s/it]
  2%|▏         | 8807/569592 [7:23:10<552:12:37,  3.54s/it]
                                                           

  2%|▏         | 8807/569592 [7:23:10<552:12:37,  3.54s/it]
  2%|▏         | 8808/569592 [7:23:14<562:55:48,  3.61s/it]
                                                           

  2%|▏         | 8808/569592 [7:23:14<562:55:48,  3.61s/it]
  2%|▏         | 8809/569592 [7:23:15<437:16:49,  2.81s/it]
                                                           

  2%|▏         | 8809/569592 [7:23:15<437:16:49,  2.81s/it]
  2%|▏         | 8810/569592 [7:23:21<584:35:45,  3.75s/it]
                                                           

  2%|▏         | 8810/569592 [7:23:21<584:35:45,  3.75s/it]
  2%|▏         | 8811/569592 [7:23:24<550:29:58,  3.53s/it]
                                                           

  2%|▏         | 8811/569592 [7:23:24<550:29:58,  3.53s/it]
  2%|▏         | 8812/569592 [7:23:27<551:49:47,  3.54s/it]
                                                           

  2%|▏         | 8812/569592 [7:23:27<551:49:47,  3.54s/it]
  2%|▏         | 8813/569592 [7:23:31<563:59:10,  3.62s/it]
                                                           

  2%|▏         | 8813/569592 [7:23:31<563:59:10,  3.62s/it]
  2%|▏         | 8814/569592 [7:23:35<571:21:34,  3.67s/it]
                                                           

  2%|▏         | 8814/569592 [7:23:35<571:21:34,  3.67s/it]
  2%|▏         | 8815/569592 [7:23:38<553:50:10,  3.56s/it]
                                                           

  2%|▏         | 8815/569592 [7:23:38<553:50:10,  3.56s/it]
  2%|▏         | 8816/569592 [7:23:41<538:54:54,  3.46s/it]
                                                           

  2%|▏         | 8816/569592 [7:23:41<538:54:54,  3.46s/it]
  2%|▏         | 8817/569592 [7:23:46<606:06:28,  3.89s/it]
                                                           

  2%|▏         | 8817/569592 [7:23:46<606:06:28,  3.89s/it]
  2%|▏         | 8818/569592 [7:23:52<674:29:41,  4.33s/it]
                                                           

  2%|▏         | 8818/569592 [7:23:52<674:29:41,  4.33s/it]
  2%|▏         | 8819/569592 [7:23:55<636:20:18,  4.09s/it]
                                                           

  2%|▏         | 8819/569592 [7:23:55<636:20:18,  4.09s/it]
  2%|▏         | 8820/569592 [7:23:58<590:23:14,  3.79s/it]
                                                           

  2%|▏         | 8820/569592 [7:23:58<590:23:14,  3.79s/it]
  2%|▏         | 8821/569592 [7:23:59<455:30:52,  2.92s/it]
                                                           

  2%|▏         | 8821/569592 [7:23:59<455:30:52,  2.92s/it]
  2%|▏         | 8822/569592 [7:24:00<362:06:28,  2.32s/it]
                                                           

  2%|▏         | 8822/569592 [7:24:00<362:06:28,  2.32s/it]
  2%|▏         | 8823/569592 [7:24:03<405:30:26,  2.60s/it]
                                                           

  2%|▏         | 8823/569592 [7:24:03<405:30:26,  2.60s/it]
  2%|▏         | 8824/569592 [7:24:07<443:37:54,  2.85s/it]
                                                           

  2%|▏         | 8824/569592 [7:24:07<443:37:54,  2.85s/it]
  2%|▏         | 8825/569592 [7:24:08<355:17:55,  2.28s/it]
                                                           

  2%|▏         | 8825/569592 [7:24:08<355:17:55,  2.28s/it]
  2%|▏         | 8826/569592 [7:24:09<292:42:09,  1.88s/it]
                                                           

  2%|▏         | 8826/569592 [7:24:09<292:42:09,  1.88s/it]
  2%|▏         | 8827/569592 [7:24:12<384:25:40,  2.47s/it]
                                                           

  2%|▏         | 8827/569592 [7:24:12<384:25:40,  2.47s/it]
  2%|▏         | 8828/569592 [7:24:13<317:23:38,  2.04s/it]
                                                           

  2%|▏         | 8828/569592 [7:24:13<317:23:38,  2.04s/it]
  2%|▏         | 8829/569592 [7:24:19<459:10:58,  2.95s/it]
                                                           

  2%|▏         | 8829/569592 [7:24:19<459:10:58,  2.95s/it]
  2%|▏         | 8830/569592 [7:24:20<369:23:17,  2.37s/it]
                                                           

  2%|▏         | 8830/569592 [7:24:20<369:23:17,  2.37s/it]
  2%|▏         | 8831/569592 [7:24:21<308:50:59,  1.98s/it]
                                                           

  2%|▏         | 8831/569592 [7:24:21<308:50:59,  1.98s/it]
  2%|▏         | 8832/569592 [7:24:24<384:11:24,  2.47s/it]
                                                           

  2%|▏         | 8832/569592 [7:24:24<384:11:24,  2.47s/it]
  2%|▏         | 8833/569592 [7:24:25<315:28:33,  2.03s/it]
                                                           

  2%|▏         | 8833/569592 [7:24:25<315:28:33,  2.03s/it]
  2%|▏         | 8834/569592 [7:24:29<389:45:50,  2.50s/it]
                                                           

  2%|▏         | 8834/569592 [7:24:29<389:45:50,  2.50s/it]
  2%|▏         | 8835/569592 [7:24:32<433:34:48,  2.78s/it]
                                                           

  2%|▏         | 8835/569592 [7:24:32<433:34:48,  2.78s/it]
  2%|▏         | 8836/569592 [7:24:33<348:12:14,  2.24s/it]
                                                           

  2%|▏         | 8836/569592 [7:24:33<348:12:14,  2.24s/it]
  2%|▏         | 8837/569592 [7:24:37<411:56:25,  2.64s/it]
                                                           

  2%|▏         | 8837/569592 [7:24:37<411:56:25,  2.64s/it]
  2%|▏         | 8838/569592 [7:24:40<448:37:59,  2.88s/it]
                                                           

  2%|▏         | 8838/569592 [7:24:40<448:37:59,  2.88s/it]
  2%|▏         | 8839/569592 [7:24:44<490:31:59,  3.15s/it]
                                                           

  2%|▏         | 8839/569592 [7:24:44<490:31:59,  3.15s/it]
  2%|▏         | 8840/569592 [7:24:48<504:47:29,  3.24s/it]
                                                           

  2%|▏         | 8840/569592 [7:24:48<504:47:29,  3.24s/it]
  2%|▏         | 8841/569592 [7:24:51<509:16:55,  3.27s/it]
                                                           

  2%|▏         | 8841/569592 [7:24:51<509:16:55,  3.27s/it]
  2%|▏         | 8842/569592 [7:24:54<516:23:03,  3.32s/it]
                                                           

  2%|▏         | 8842/569592 [7:24:54<516:23:03,  3.32s/it]
  2%|▏         | 8843/569592 [7:24:55<403:29:19,  2.59s/it]
                                                           

  2%|▏         | 8843/569592 [7:24:55<403:29:19,  2.59s/it]
  2%|▏         | 8844/569592 [7:24:59<444:46:27,  2.86s/it]
                                                           

  2%|▏         | 8844/569592 [7:24:59<444:46:27,  2.86s/it]
  2%|▏         | 8845/569592 [7:25:00<356:09:06,  2.29s/it]
                                                           

  2%|▏         | 8845/569592 [7:25:00<356:09:06,  2.29s/it]
  2%|▏         | 8846/569592 [7:25:03<409:26:33,  2.63s/it]
                                                           

  2%|▏         | 8846/569592 [7:25:03<409:26:33,  2.63s/it]
  2%|▏         | 8847/569592 [7:25:07<464:25:57,  2.98s/it]
                                                           

  2%|▏         | 8847/569592 [7:25:07<464:25:57,  2.98s/it]
  2%|▏         | 8848/569592 [7:25:10<475:04:25,  3.05s/it]
                                                           

  2%|▏         | 8848/569592 [7:25:10<475:04:25,  3.05s/it]
  2%|▏         | 8849/569592 [7:25:14<507:24:45,  3.26s/it]
                                                           

  2%|▏         | 8849/569592 [7:25:14<507:24:45,  3.26s/it]
  2%|▏         | 8850/569592 [7:25:17<500:09:43,  3.21s/it]
                                                           

  2%|▏         | 8850/569592 [7:25:17<500:09:43,  3.21s/it]
  2%|▏         | 8851/569592 [7:25:20<494:55:11,  3.18s/it]
                                                           

  2%|▏         | 8851/569592 [7:25:20<494:55:11,  3.18s/it]
  2%|▏         | 8852/569592 [7:25:21<388:53:17,  2.50s/it]
                                                           

  2%|▏         | 8852/569592 [7:25:21<388:53:17,  2.50s/it]
  2%|▏         | 8853/569592 [7:25:24<423:15:57,  2.72s/it]
                                                           

  2%|▏         | 8853/569592 [7:25:24<423:15:57,  2.72s/it]
  2%|▏         | 8854/569592 [7:25:25<345:06:38,  2.22s/it]
                                                           

  2%|▏         | 8854/569592 [7:25:25<345:06:38,  2.22s/it]
  2%|▏         | 8855/569592 [7:25:26<287:48:15,  1.85s/it]
                                                           

  2%|▏         | 8855/569592 [7:25:26<287:48:15,  1.85s/it]
  2%|▏         | 8856/569592 [7:25:31<432:20:57,  2.78s/it]
                                                           

  2%|▏         | 8856/569592 [7:25:31<432:20:57,  2.78s/it]
  2%|▏         | 8857/569592 [7:25:34<458:03:10,  2.94s/it]
                                                           

  2%|▏         | 8857/569592 [7:25:34<458:03:10,  2.94s/it]
  2%|▏         | 8858/569592 [7:25:38<502:46:00,  3.23s/it]
                                                           

  2%|▏         | 8858/569592 [7:25:38<502:46:00,  3.23s/it]
  2%|▏         | 8859/569592 [7:25:39<395:15:27,  2.54s/it]
                                                           

  2%|▏         | 8859/569592 [7:25:39<395:15:27,  2.54s/it]
  2%|▏         | 8860/569592 [7:25:40<321:18:10,  2.06s/it]
                                                           

  2%|▏         | 8860/569592 [7:25:40<321:18:10,  2.06s/it]
  2%|▏         | 8861/569592 [7:25:41<269:48:56,  1.73s/it]
                                                           

  2%|▏         | 8861/569592 [7:25:41<269:48:56,  1.73s/it]
  2%|▏         | 8862/569592 [7:25:42<239:22:40,  1.54s/it]
                                                           

  2%|▏         | 8862/569592 [7:25:42<239:22:40,  1.54s/it]
  2%|▏         | 8863/569592 [7:25:46<334:53:50,  2.15s/it]
                                                           

  2%|▏         | 8863/569592 [7:25:46<334:53:50,  2.15s/it]
  2%|▏         | 8864/569592 [7:25:47<280:13:39,  1.80s/it]
                                                           

  2%|▏         | 8864/569592 [7:25:47<280:13:39,  1.80s/it]
  2%|▏         | 8865/569592 [7:25:50<351:16:33,  2.26s/it]
                                                           

  2%|▏         | 8865/569592 [7:25:50<351:16:33,  2.26s/it]
  2%|▏         | 8866/569592 [7:25:54<416:57:57,  2.68s/it]
                                                           

  2%|▏         | 8866/569592 [7:25:54<416:57:57,  2.68s/it]
  2%|▏         | 8867/569592 [7:25:55<338:06:02,  2.17s/it]
                                                           

  2%|▏         | 8867/569592 [7:25:55<338:06:02,  2.17s/it]
  2%|▏         | 8868/569592 [7:25:58<396:49:36,  2.55s/it]
                                                           

  2%|▏         | 8868/569592 [7:25:58<396:49:36,  2.55s/it]
  2%|▏         | 8869/569592 [7:26:02<464:10:15,  2.98s/it]
                                                           

  2%|▏         | 8869/569592 [7:26:02<464:10:15,  2.98s/it]
  2%|▏         | 8870/569592 [7:26:06<515:37:02,  3.31s/it]
                                                           

  2%|▏         | 8870/569592 [7:26:06<515:37:02,  3.31s/it]
  2%|▏         | 8871/569592 [7:26:07<410:48:25,  2.64s/it]
                                                           

  2%|▏         | 8871/569592 [7:26:07<410:48:25,  2.64s/it]
  2%|▏         | 8872/569592 [7:26:08<333:17:02,  2.14s/it]
                                                           

  2%|▏         | 8872/569592 [7:26:08<333:17:02,  2.14s/it]
  2%|▏         | 8873/569592 [7:26:09<280:10:58,  1.80s/it]
                                                           

  2%|▏         | 8873/569592 [7:26:09<280:10:58,  1.80s/it]
  2%|▏         | 8874/569592 [7:26:13<363:33:45,  2.33s/it]
                                                           

  2%|▏         | 8874/569592 [7:26:13<363:33:45,  2.33s/it]
  2%|▏         | 8875/569592 [7:26:14<316:03:00,  2.03s/it]
                 /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (91927968 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                                          

  2%|▏         | 8875/569592 [7:26:14<316:03:00,  2.03s/it]
  2%|▏         | 8876/569592 [7:26:15<266:35:53,  1.71s/it]
                                                           

  2%|▏         | 8876/569592 [7:26:15<266:35:53,  1.71s/it]
  2%|▏         | 8877/569592 [7:26:19<365:56:10,  2.35s/it]
                                                           

  2%|▏         | 8877/569592 [7:26:19<365:56:10,  2.35s/it]
  2%|▏         | 8878/569592 [7:26:20<301:14:05,  1.93s/it]
                                                           

  2%|▏         | 8878/569592 [7:26:20<301:14:05,  1.93s/it]
  2%|▏         | 8879/569592 [7:26:23<364:25:29,  2.34s/it]
                                                           

  2%|▏         | 8879/569592 [7:26:23<364:25:29,  2.34s/it]
  2%|▏         | 8880/569592 [7:26:27<448:30:29,  2.88s/it]
                                                           

  2%|▏         | 8880/569592 [7:26:27<448:30:29,  2.88s/it]
  2%|▏         | 8881/569592 [7:26:31<484:21:14,  3.11s/it]
                                                           

  2%|▏         | 8881/569592 [7:26:31<484:21:14,  3.11s/it]
  2%|▏         | 8882/569592 [7:26:34<495:58:39,  3.18s/it]
                                                           

  2%|▏         | 8882/569592 [7:26:34<495:58:39,  3.18s/it]
  2%|▏         | 8883/569592 [7:26:35<392:09:09,  2.52s/it]
                                                           

  2%|▏         | 8883/569592 [7:26:35<392:09:09,  2.52s/it]
  2%|▏         | 8884/569592 [7:26:36<318:01:25,  2.04s/it]
                                                           

  2%|▏         | 8884/569592 [7:26:36<318:01:25,  2.04s/it]
  2%|▏         | 8885/569592 [7:26:37<266:09:21,  1.71s/it]
                                                           

  2%|▏         | 8885/569592 [7:26:37<266:09:21,  1.71s/it]
  2%|▏         | 8886/569592 [7:26:40<318:12:24,  2.04s/it]
                              /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
                             

  2%|▏         | 8886/569592 [7:26:40<318:12:24,  2.04s/it]
  2%|▏         | 8887/569592 [7:26:44<389:12:28,  2.50s/it]
                                                           

  2%|▏         | 8887/569592 [7:26:44<389:12:28,  2.50s/it]
  2%|▏         | 8888/569592 [7:26:45<321:13:25,  2.06s/it]
                                                           

  2%|▏         | 8888/569592 [7:26:45<321:13:25,  2.06s/it]
  2%|▏         | 8889/569592 [7:26:48<366:15:58,  2.35s/it]
                                                           

  2%|▏         | 8889/569592 [7:26:48<366:15:58,  2.35s/it]
  2%|▏         | 8890/569592 [7:26:51<411:38:05,  2.64s/it]
                                                           

  2%|▏         | 8890/569592 [7:26:51<411:38:05,  2.64s/it]
  2%|▏         | 8891/569592 [7:26:55<456:35:43,  2.93s/it]
                                                           

  2%|▏         | 8891/569592 [7:26:55<456:35:43,  2.93s/it]
  2%|▏         | 8892/569592 [7:26:58<486:07:26,  3.12s/it]
                                                           

  2%|▏         | 8892/569592 [7:26:58<486:07:26,  3.12s/it]
  2%|▏         | 8893/569592 [7:26:59<394:08:03,  2.53s/it]
                                                           

  2%|▏         | 8893/569592 [7:26:59<394:08:03,  2.53s/it]
  2%|▏         | 8894/569592 [7:27:03<460:11:03,  2.95s/it]
                                                           

  2%|▏         | 8894/569592 [7:27:03<460:11:03,  2.95s/it]
  2%|▏         | 8895/569592 [7:27:07<477:00:19,  3.06s/it]
                                                           

  2%|▏         | 8895/569592 [7:27:07<477:00:19,  3.06s/it]
  2%|▏         | 8896/569592 [7:27:08<379:03:05,  2.43s/it]
                                                           

  2%|▏         | 8896/569592 [7:27:08<379:03:05,  2.43s/it]
  2%|▏         | 8897/569592 [7:27:11<425:05:36,  2.73s/it]
                                                           

  2%|▏         | 8897/569592 [7:27:11<425:05:36,  2.73s/it]
  2%|▏         | 8898/569592 [7:27:15<467:21:43,  3.00s/it]
                                                           

  2%|▏         | 8898/569592 [7:27:15<467:21:43,  3.00s/it]
  2%|▏         | 8899/569592 [7:27:16<371:41:43,  2.39s/it]
                                                           

  2%|▏         | 8899/569592 [7:27:16<371:41:43,  2.39s/it]
  2%|▏         | 8900/569592 [7:27:19<427:24:29,  2.74s/it]
                                                           

  2%|▏         | 8900/569592 [7:27:19<427:24:29,  2.74s/it]
  2%|▏         | 8901/569592 [7:27:20<344:37:14,  2.21s/it]
                                                           

  2%|▏         | 8901/569592 [7:27:20<344:37:14,  2.21s/it]
  2%|▏         | 8902/569592 [7:27:23<353:22:21,  2.27s/it]
                                                           

  2%|▏         | 8902/569592 [7:27:23<353:22:21,  2.27s/it]
  2%|▏         | 8903/569592 [7:27:27<437:51:19,  2.81s/it]
                                                           

  2%|▏         | 8903/569592 [7:27:27<437:51:19,  2.81s/it]
  2%|▏         | 8904/569592 [7:27:30<460:05:23,  2.95s/it]
                                                           

  2%|▏         | 8904/569592 [7:27:30<460:05:23,  2.95s/it]
  2%|▏         | 8905/569592 [7:27:34<503:26:16,  3.23s/it]
                                                           

  2%|▏         | 8905/569592 [7:27:34<503:26:16,  3.23s/it]
  2%|▏         | 8906/569592 [7:27:38<530:01:24,  3.40s/it]
                                                           

  2%|▏         | 8906/569592 [7:27:38<530:01:24,  3.40s/it]
  2%|▏         | 8907/569592 [7:27:41<527:39:05,  3.39s/it]
                                                           

  2%|▏         | 8907/569592 [7:27:41<527:39:05,  3.39s/it]
  2%|▏         | 8908/569592 [7:27:44<533:17:29,  3.42s/it]
                                                           

  2%|▏         | 8908/569592 [7:27:44<533:17:29,  3.42s/it]
  2%|▏         | 8909/569592 [7:27:48<534:07:30,  3.43s/it]
                                                           

  2%|▏         | 8909/569592 [7:27:48<534:07:30,  3.43s/it]
  2%|▏         | 8910/569592 [7:27:51<523:53:35,  3.36s/it]
                                                           

  2%|▏         | 8910/569592 [7:27:51<523:53:35,  3.36s/it]
  2%|▏         | 8911/569592 [7:27:52<410:07:23,  2.63s/it]
                                                           

  2%|▏         | 8911/569592 [7:27:52<410:07:23,  2.63s/it]
  2%|▏         | 8912/569592 [7:27:56<461:37:53,  2.96s/it]
                                                           

  2%|▏         | 8912/569592 [7:27:56<461:37:53,  2.96s/it]
  2%|▏         | 8913/569592 [7:27:59<496:39:48,  3.19s/it]
                                                           

  2%|▏         | 8913/569592 [7:27:59<496:39:48,  3.19s/it]
  2%|▏         | 8914/569592 [7:28:03<528:48:12,  3.40s/it]
                                                           

  2%|▏         | 8914/569592 [7:28:03<528:48:12,  3.40s/it]
  2%|▏         | 8915/569592 [7:28:04<412:48:07,  2.65s/it]
                                                           

  2%|▏         | 8915/569592 [7:28:04<412:48:07,  2.65s/it]
  2%|▏         | 8916/569592 [7:28:08<467:11:29,  3.00s/it]
                                                           

  2%|▏         | 8916/569592 [7:28:08<467:11:29,  3.00s/it]
  2%|▏         | 8917/569592 [7:28:09<374:42:07,  2.41s/it]
                                                           

  2%|▏         | 8917/569592 [7:28:09<374:42:07,  2.41s/it]
  2%|▏         | 8918/569592 [7:28:13<428:28:22,  2.75s/it]
                                                           

  2%|▏         | 8918/569592 [7:28:13<428:28:22,  2.75s/it]
  2%|▏         | 8919/569592 [7:28:17<483:45:02,  3.11s/it]
                                                           

  2%|▏         | 8919/569592 [7:28:17<483:45:02,  3.11s/it]
  2%|▏         | 8920/569592 [7:28:20<512:11:21,  3.29s/it]
                                                           

  2%|▏         | 8920/569592 [7:28:20<512:11:21,  3.29s/it]
  2%|▏         | 8921/569592 [7:28:24<511:55:42,  3.29s/it]
                                                           

  2%|▏         | 8921/569592 [7:28:24<511:55:42,  3.29s/it]
  2%|▏         | 8922/569592 [7:28:27<532:33:33,  3.42s/it]
                                                           

  2%|▏         | 8922/569592 [7:28:27<532:33:33,  3.42s/it]
  2%|▏         | 8923/569592 [7:28:30<521:22:28,  3.35s/it]
                                                           

  2%|▏         | 8923/569592 [7:28:31<521:22:28,  3.35s/it]
  2%|▏         | 8924/569592 [7:28:31<408:07:44,  2.62s/it]
                                                           

  2%|▏         | 8924/569592 [7:28:31<408:07:44,  2.62s/it]
  2%|▏         | 8925/569592 [7:28:35<460:09:37,  2.95s/it]
                                                           

  2%|▏         | 8925/569592 [7:28:35<460:09:37,  2.95s/it]
  2%|▏         | 8926/569592 [7:28:39<481:43:39,  3.09s/it]
                                                           

  2%|▏         | 8926/569592 [7:28:39<481:43:39,  3.09s/it]
  2%|▏         | 8927/569592 [7:28:42<505:55:10,  3.25s/it]
                                                           

  2%|▏         | 8927/569592 [7:28:42<505:55:10,  3.25s/it]
  2%|▏         | 8928/569592 [7:28:46<537:00:11,  3.45s/it]
                                                           

  2%|▏         | 8928/569592 [7:28:46<537:00:11,  3.45s/it]
  2%|▏         | 8929/569592 [7:28:50<541:33:06,  3.48s/it]
                                                           

  2%|▏         | 8929/569592 [7:28:50<541:33:06,  3.48s/it]
  2%|▏         | 8930/569592 [7:28:53<530:25:58,  3.41s/it]
                                                           

  2%|▏         | 8930/569592 [7:28:53<530:25:58,  3.41s/it]
  2%|▏         | 8931/569592 [7:28:57<556:24:16,  3.57s/it]
                                                           

  2%|▏         | 8931/569592 [7:28:57<556:24:16,  3.57s/it]
  2%|▏         | 8932/569592 [7:29:00<536:41:59,  3.45s/it]
                                                           

  2%|▏         | 8932/569592 [7:29:00<536:41:59,  3.45s/it]
  2%|▏         | 8933/569592 [7:29:03<528:54:41,  3.40s/it]
                                                           

  2%|▏         | 8933/569592 [7:29:03<528:54:41,  3.40s/it]
  2%|▏         | 8934/569592 [7:29:07<524:40:07,  3.37s/it]
                                                           

  2%|▏         | 8934/569592 [7:29:07<524:40:07,  3.37s/it]
  2%|▏         | 8935/569592 [7:29:10<528:22:02,  3.39s/it]
                                                           

  2%|▏         | 8935/569592 [7:29:10<528:22:02,  3.39s/it]
  2%|▏         | 8936/569592 [7:29:13<526:19:58,  3.38s/it]
                                                           

  2%|▏         | 8936/569592 [7:29:13<526:19:58,  3.38s/it]
  2%|▏         | 8937/569592 [7:29:17<537:55:23,  3.45s/it]
                                                           

  2%|▏         | 8937/569592 [7:29:17<537:55:23,  3.45s/it]
  2%|▏         | 8938/569592 [7:29:18<433:13:21,  2.78s/it]
                                                           

  2%|▏         | 8938/569592 [7:29:18<433:13:21,  2.78s/it]
  2%|▏         | 8939/569592 [7:29:21<448:54:22,  2.88s/it]
                                                           

  2%|▏         | 8939/569592 [7:29:21<448:54:22,  2.88s/it]
  2%|▏         | 8940/569592 [7:29:22<358:00:15,  2.30s/it]
                                                           

  2%|▏         | 8940/569592 [7:29:22<358:00:15,  2.30s/it]
  2%|▏         | 8941/569592 [7:29:26<404:30:58,  2.60s/it]
                                                           

  2%|▏         | 8941/569592 [7:29:26<404:30:58,  2.60s/it]
  2%|▏         | 8942/569592 [7:29:29<466:56:47,  3.00s/it]
                                                           

  2%|▏         | 8942/569592 [7:29:30<466:56:47,  3.00s/it]
  2%|▏         | 8943/569592 [7:29:30<371:33:06,  2.39s/it]
                                                           

  2%|▏         | 8943/569592 [7:29:30<371:33:06,  2.39s/it]
  2%|▏         | 8944/569592 [7:29:34<424:56:07,  2.73s/it]
                                                           

  2%|▏         | 8944/569592 [7:29:34<424:56:07,  2.73s/it]
  2%|▏         | 8945/569592 [7:29:37<449:08:02,  2.88s/it]
                                                           

  2%|▏         | 8945/569592 [7:29:37<449:08:02,  2.88s/it]
  2%|▏         | 8946/569592 [7:29:41<478:08:51,  3.07s/it]
                                                           

  2%|▏         | 8946/569592 [7:29:41<478:08:51,  3.07s/it]
  2%|▏         | 8947/569592 [7:29:45<511:44:04,  3.29s/it]
                                                           

  2%|▏         | 8947/569592 [7:29:45<511:44:04,  3.29s/it]
  2%|▏         | 8948/569592 [7:29:45<400:41:49,  2.57s/it]
                                                           

  2%|▏         | 8948/569592 [7:29:45<400:41:49,  2.57s/it]
  2%|▏         | 8949/569592 [7:29:46<325:24:04,  2.09s/it]
                                                           

  2%|▏         | 8949/569592 [7:29:46<325:24:04,  2.09s/it]
  2%|▏         | 8950/569592 [7:29:47<276:34:48,  1.78s/it]
                                                           

  2%|▏         | 8950/569592 [7:29:48<276:34:48,  1.78s/it]
  2%|▏         | 8951/569592 [7:29:49<246:07:49,  1.58s/it]
                                                           

  2%|▏         | 8951/569592 [7:29:49<246:07:49,  1.58s/it]
  2%|▏         | 8952/569592 [7:29:52<336:56:42,  2.16s/it]
                                                           

  2%|▏         | 8952/569592 [7:29:52<336:56:42,  2.16s/it]
  2%|▏         | 8953/569592 [7:29:55<386:51:44,  2.48s/it]
                                                           

  2%|▏         | 8953/569592 [7:29:55<386:51:44,  2.48s/it]
  2%|▏         | 8954/569592 [7:29:59<433:25:32,  2.78s/it]
                                                           

  2%|▏         | 8954/569592 [7:29:59<433:25:32,  2.78s/it]
  2%|▏         | 8955/569592 [7:30:02<473:42:26,  3.04s/it]
                                                           

  2%|▏         | 8955/569592 [7:30:02<473:42:26,  3.04s/it]
  2%|▏         | 8956/569592 [7:30:06<506:36:23,  3.25s/it]
                                                           

  2%|▏         | 8956/569592 [7:30:06<506:36:23,  3.25s/it]
  2%|▏         | 8957/569592 [7:30:09<502:10:32,  3.22s/it]
                                                           

  2%|▏         | 8957/569592 [7:30:09<502:10:32,  3.22s/it]
  2%|▏         | 8958/569592 [7:30:13<505:39:24,  3.25s/it]
                                                           

  2%|▏         | 8958/569592 [7:30:13<505:39:24,  3.25s/it]
  2%|▏         | 8959/569592 [7:30:14<397:02:52,  2.55s/it]
                                                           

  2%|▏         | 8959/569592 [7:30:14<397:02:52,  2.55s/it]
  2%|▏         | 8960/569592 [7:30:17<447:06:14,  2.87s/it]
                                                           

  2%|▏         | 8960/569592 [7:30:17<447:06:14,  2.87s/it]
  2%|▏         | 8961/569592 [7:30:18<358:45:58,  2.30s/it]
                                                           

  2%|▏         | 8961/569592 [7:30:18<358:45:58,  2.30s/it]
  2%|▏         | 8962/569592 [7:30:22<418:17:16,  2.69s/it]
                                                           

  2%|▏         | 8962/569592 [7:30:22<418:17:16,  2.69s/it]
  2%|▏         | 8963/569592 [7:30:23<337:33:13,  2.17s/it]
                                                           

  2%|▏         | 8963/569592 [7:30:23<337:33:13,  2.17s/it/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (92113584 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
]
  2%|▏         | 8964/569592 [7:30:27<421:26:04,  2.71s/it]
                                                           

  2%|▏         | 8964/569592 [7:30:27<421:26:04,  2.71s/it]
  2%|▏         | 8965/569592 [7:30:28<338:48:44,  2.18s/it]
                                                           

  2%|▏         | 8965/569592 [7:30:28<338:48:44,  2.18s/it]
  2%|▏         | 8966/569592 [7:30:31<390:22:36,  2.51s/it]
                                                           

  2%|▏         | 8966/569592 [7:30:31<390:22:36,  2.51s/it]
  2%|▏         | 8967/569592 [7:30:34<428:09:35,  2.75s/it]
                                                           

  2%|▏         | 8967/569592 [7:30:34<428:09:35,  2.75s/it]
  2%|▏         | 8968/569592 [7:30:38<459:37:08,  2.95s/it]
                                                           

  2%|▏         | 8968/569592 [7:30:38<459:37:08,  2.95s/it]
  2%|▏         | 8969/569592 [7:30:41<493:12:13,  3.17s/it]
                                                           

  2%|▏         | 8969/569592 [7:30:41<493:12:13,  3.17s/it]
  2%|▏         | 8970/569592 [7:30:42<389:17:56,  2.50s/it]
                                                           

  2%|▏         | 8970/569592 [7:30:42<389:17:56,  2.50s/it]
  2%|▏         | 8971/569592 [7:30:43<320:00:22,  2.05s/it]
                                                           

  2%|▏         | 8971/569592 [7:30:43<320:00:22,  2.05s/it]
  2%|▏         | 8972/569592 [7:30:44<267:48:08,  1.72s/it]
                                                           

  2%|▏         | 8972/569592 [7:30:44<267:48:08,  1.72s/it]
  2%|▏         | 8973/569592 [7:30:45<232:42:06,  1.49s/it]
                                                           

  2%|▏         | 8973/569592 [7:30:45<232:42:06,  1.49s/it]
  2%|▏         | 8974/569592 [7:30:49<337:34:24,  2.17s/it]
                                                           

  2%|▏         | 8974/569592 [7:30:49<337:34:24,  2.17s/it]
  2%|▏   /home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100000000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
      | 8975/569592 [7:30:53<404:53:43,  2.60s/it]
                                                           

  2%|▏         | 8975/569592 [7:30:53<404:53:43,  2.60s/it]
  2%|▏         | 8976/569592 [7:30:54<331:38:45,  2.13s/it]
                                                           

  2%|▏         | 8976/569592 [7:30:54<331:38:45,  2.13s/it]
  2%|▏         | 8977/569592 [7:30:55<277:13:45,  1.78s/it]
                                                           

  2%|▏         | 8977/569592 [7:30:55<277:13:45,  1.78s/it]
  2%|▏         | 8978/569592 [7:30:58<350:13:40,  2.25s/it]
                                                           

  2%|▏         | 8978/569592 [7:30:58<350:13:40,  2.25s/it]
  2%|▏         | 8979/569592 [7:31:02<431:26:36,  2.77s/it]
                                                           

  2%|▏         | 8979/569592 [7:31:02<431:26:36,  2.77s/it]
  2%|▏         | 8980/569592 [7:31:05<463:17:17,  2.98s/it]
                                                           

  2%|▏         | 8980/569592 [7:31:05<463:17:17,  2.98s/it]
  2%|▏         | 8981/569592 [7:31:09<517:21:21,  3.32s/it]
                                                           

  2%|▏         | 8981/569592 [7:31:09<517:21:21,  3.32s/it]
  2%|▏         | 8982/569592 [7:31:10<406:48:20,  2.61s/it]
                                                           

  2%|▏         | 8982/569592 [7:31:10<406:48:20,  2.61s/it]
  2%|▏         | 8983/569592 [7:31:11<329:06:21,  2.11s/it]
                                                           

  2%|▏         | 8983/569592 [7:31:11<329:06:21,  2.11s/it]
  2%|▏         | 8984/569592 [7:31:15<408:25:53,  2.62s/it]
                                                           

  2%|▏         | 8984/569592 [7:31:15<408:25:53,  2.62s/it]
  2%|▏         | 8985/569592 [7:31:16<333:21:44,  2.14s/it]
                                                           

  2%|▏         | 8985/569592 [7:31:16<333:21:44,  2.14s/it]
  2%|▏         | 8986/569592 [7:31:20<403:45:46,  2.59s/it]
                                                           

  2%|▏         | 8986/569592 [7:31:20<403:45:46,  2.59s/it]
  2%|▏         | 8987/569592 [7:31:23<454:29:45,  2.92s/it]
                                                           

  2%|▏         | 8987/569592 [7:31:24<454:29:45,  2.92s/it]
  2%|▏         | 8988/569592 [7:31:27<470:22:52,  3.02s/it]
                                                           

  2%|▏         | 8988/569592 [7:31:27<470:22:52,  3.02s/it]
  2%|▏         | 8989/569592 [7:31:28<377:07:02,  2.42s/it]
                                                           

  2%|▏         | 8989/569592 [7:31:28<377:07:02,  2.42s/it]
  2%|▏         | 8990/569592 [7:31:29<319:50:55,  2.05s/it]
                                                           

  2%|▏         | 8990/569592 [7:31:29<319:50:55,  2.05s/it]
  2%|▏         | 8991/569592 [7:31:30<271:08:10,  1.74s/it]
                                                           

/home/zhaojiang/.local/lib/python3.10/site-packages/PIL/Image.py:3368: DecompressionBombWarning: Image size (100920000 pixels) exceeds limit of 89478485 pixels, could be decompression bomb DOS attack.
  warnings.warn(
  2%|▏         | 8991/569592 [7:31:30<271:08:10,  1.74s/it]
  2%|▏         | 8992/569592 [7:31:33<349:40:10,  2.25s/it]
                                                           

  2%|▏         | 8992/569592 [7:31:33<349:40:10,  2.25s/it]
  2%|▏         | 8993/569592 [7:31:34<290:08:01,  1.86s/it]
                                                           

  2%|▏         | 8993/569592 [7:31:34<290:08:01,  1.86s/it]
  2%|▏         | 8994/569592 [7:31:36<293:58:26,  1.89s/it]
                                                           

  2%|▏         | 8994/569592 [7:31:36<293:58:26,  1.89s/it]
  2%|▏         | 8995/569592 [7:31:40<367:00:57,  2.36s/it]
                                                           

  2%|▏         | 8995/569592 [7:31:40<367:00:57,  2.36s/it]
  2%|▏         | 8996/569592 [7:31:41<301:47:26,  1.94s/it]
                                                           

  2%|▏         | 8996/569592 [7:31:41<301:47:26,  1.94s/it]
  2%|▏         | 8997/569592 [7:31:44<382:40:47,  2.46s/it]
                                                           

  2%|▏         | 8997/569592 [7:31:44<382:40:47,  2.46s/it]
  2%|▏         | 8998/569592 [7:31:47<382:47:27,  2.46s/it]
                                                           

  2%|▏         | 8998/569592 [7:31:47<382:47:27,  2.46s/it]
  2%|▏         | 8999/569592 [7:31:50<431:19:42,  2.77s/it]
                                                           

  2%|▏         | 8999/569592 [7:31:50<431:19:42,  2.77s/it]
  2%|▏         | 9000/569592 [7:31:51<346:12:46,  2.22s/it]
                                                           

  2%|▏         | 9000/569592 [7:31:51<346:12:46,  2.22s/it]Saving model checkpoint to /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-9000
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-9000/config.json
Configuration saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-9000/generation_config.json
The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 6 checkpoint shards. You can find where each parameters has been saved in the index located at /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-9000/model.safetensors.index.json.
tokenizer config file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-9000/tokenizer_config.json
Special tokens file saved in /fsx_0/user/zhaojiang/models/qwen-vl-gen/checkpoint-9000/special_tokens_map.json
Traceback (most recent call last):
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/serialization.py", line 850, in save
    _save(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/serialization.py", line 1114, in _save
    zip_file.write_record(name, storage, num_bytes)
RuntimeError: [enforce fail at inline_container.cc:778] . PytorchStreamWriter failed writing file data/723: file write failed

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
    train(attn_implementation="flash_attention_2")
  File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
    trainer.train()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
    return inner_training_loop(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
    self._maybe_log_save_evaluate(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
    self._save_checkpoint(model, trial)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
    self._save_optimizer_and_scheduler(output_dir)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
    self.model_wrapped.save_checkpoint(output_dir)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3199, in save_checkpoint
    self._save_checkpoint(save_dir,
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3421, in _save_checkpoint
    self.checkpoint_engine.save(state, save_path)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/checkpoint_engine/torch_checkpoint_engine.py", line 22, in save
    torch.save(state_dict, path)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/serialization.py", line 849, in save
    with _open_zipfile_writer(f) as opened_zipfile:
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/serialization.py", line 690, in __exit__
    self.file_like.write_end_of_file()
RuntimeError: [enforce fail at inline_container.cc:603] . unexpected pos 27282028288 vs 27282028184
[rank0]: Traceback (most recent call last):
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/serialization.py", line 850, in save
[rank0]:     _save(
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/serialization.py", line 1114, in _save
[rank0]:     zip_file.write_record(name, storage, num_bytes)
[rank0]: RuntimeError: [enforce fail at inline_container.cc:778] . PytorchStreamWriter failed writing file data/723: file write failed

[rank0]: During handling of the above exception, another exception occurred:

[rank0]: Traceback (most recent call last):
[rank0]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank0]:     train(attn_implementation="flash_attention_2")
[rank0]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank0]:     trainer.train()
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank0]:     return inner_training_loop(
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank0]:     self._maybe_log_save_evaluate(
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank0]:     self._save_checkpoint(model, trial)
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank0]:     self._save_optimizer_and_scheduler(output_dir)
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank0]:     self.model_wrapped.save_checkpoint(output_dir)
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3199, in save_checkpoint
[rank0]:     self._save_checkpoint(save_dir,
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3421, in _save_checkpoint
[rank0]:     self.checkpoint_engine.save(state, save_path)
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/checkpoint_engine/torch_checkpoint_engine.py", line 22, in save
[rank0]:     torch.save(state_dict, path)
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/serialization.py", line 849, in save
[rank0]:     with _open_zipfile_writer(f) as opened_zipfile:
[rank0]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/serialization.py", line 690, in __exit__
[rank0]:     self.file_like.write_end_of_file()
[rank0]: RuntimeError: [enforce fail at inline_container.cc:603] . unexpected pos 27282028288 vs 27282028184
[rank0]:[W217 14:56:40.817564534 ProcessGroupNCCL.cpp:1250] Warning: WARNING: process group has NOT been destroyed before we destruct ProcessGroupNCCL. On normal program exit, the application should call destroy_process_group to ensure that any pending NCCL operations have finished in this process. In rare cases this process can exit before this point and block the progress of another member of the process group. This constraint has always been present,  but this warning has only been added since PyTorch 2.4 (function operator())
[rank35]:[E217 15:05:47.754221661 ProcessGroupNCCL.cpp:616] [Rank 35] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600058 milliseconds before timing out.
[rank18]:[E217 15:05:47.992305383 ProcessGroupNCCL.cpp:616] [Rank 18] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600003 milliseconds before timing out.
[rank10]:[E217 15:05:47.687980560 ProcessGroupNCCL.cpp:616] [Rank 10] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600049 milliseconds before timing out.
[rank63]:[E217 15:05:47.426428481 ProcessGroupNCCL.cpp:616] [Rank 63] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600061 milliseconds before timing out.
[rank81]:[E217 15:05:47.905351523 ProcessGroupNCCL.cpp:616] [Rank 81] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
[rank85]:[E217 15:05:47.905339943 ProcessGroupNCCL.cpp:616] [Rank 85] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600044 milliseconds before timing out.
[rank60]:[E217 15:05:47.448301694 ProcessGroupNCCL.cpp:616] [Rank 60] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600039 milliseconds before timing out.
[rank78]:[E217 15:05:47.771998388 ProcessGroupNCCL.cpp:616] [Rank 78] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
[rank124]:[E217 15:05:47.531169090 ProcessGroupNCCL.cpp:616] [Rank 124] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600072 milliseconds before timing out.
[rank85]:[E217 15:05:47.918440673 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 85] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank117]:[E217 15:05:47.719825730 ProcessGroupNCCL.cpp:616] [Rank 117] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600069 milliseconds before timing out.
[rank60]:[E217 15:05:47.462816917 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 60] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank126]:[E217 15:05:47.542745052 ProcessGroupNCCL.cpp:616] [Rank 126] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600096 milliseconds before timing out.
[rank48]:[E217 15:05:47.537742492 ProcessGroupNCCL.cpp:616] [Rank 48] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
[rank119]:[E217 15:05:47.727916678 ProcessGroupNCCL.cpp:616] [Rank 119] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600062 milliseconds before timing out.
[rank115]:[E217 15:05:47.732946367 ProcessGroupNCCL.cpp:616] [Rank 115] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
[rank68]:[E217 15:05:47.455795810 ProcessGroupNCCL.cpp:616] [Rank 68] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600001 milliseconds before timing out.
[rank61]:[E217 15:05:47.414182646 ProcessGroupNCCL.cpp:616] [Rank 61] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600045 milliseconds before timing out.
[rank90]:[E217 15:05:47.964278117 ProcessGroupNCCL.cpp:616] [Rank 90] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
[rank119]:[E217 15:05:47.741088566 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 119] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank115]:[E217 15:05:47.741093137 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 115] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank94]:[E217 15:05:47.956313507 ProcessGroupNCCL.cpp:616] [Rank 94] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600018 milliseconds before timing out.
[rank66]:[E217 15:05:47.611075242 ProcessGroupNCCL.cpp:616] [Rank 66] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600084 milliseconds before timing out.
[rank43]:[E217 15:05:47.888693855 ProcessGroupNCCL.cpp:616] [Rank 43] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
[rank75]:[E217 15:05:47.743035778 ProcessGroupNCCL.cpp:616] [Rank 75] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600057 milliseconds before timing out.
[rank68]:[E217 15:05:47.613283446 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 68] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank63]:[E217 15:05:47.492407420 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 63] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank35]:[E217 15:05:47.850879614 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 35] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank100]:[E217 15:05:47.393054465 ProcessGroupNCCL.cpp:616] [Rank 100] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600003 milliseconds before timing out.
[rank51]:[E217 15:05:47.495929377 ProcessGroupNCCL.cpp:616] [Rank 51] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600029 milliseconds before timing out.
[rank18]:[E217 15:05:47.088676806 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 18] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank22]:[E217 15:05:47.027333699 ProcessGroupNCCL.cpp:616] [Rank 22] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
[rank50]:[E217 15:05:47.502270663 ProcessGroupNCCL.cpp:616] [Rank 50] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
[rank100]:[E217 15:05:47.490455639 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 100] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank13]:[E217 15:05:47.766437134 ProcessGroupNCCL.cpp:616] [Rank 13] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
[rank113]:[E217 15:05:47.775973405 ProcessGroupNCCL.cpp:616] [Rank 113] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600099 milliseconds before timing out.
[rank46]:[E217 15:05:47.853078542 ProcessGroupNCCL.cpp:616] [Rank 46] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
[rank28]:[E217 15:05:47.627885408 ProcessGroupNCCL.cpp:616] [Rank 28] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
[rank15]:[E217 15:05:47.692931654 ProcessGroupNCCL.cpp:616] [Rank 15] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600039 milliseconds before timing out.
[rank95]:[E217 15:05:47.990952407 ProcessGroupNCCL.cpp:616] [Rank 95] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600039 milliseconds before timing out.
[rank34]:[E217 15:05:47.798737792 ProcessGroupNCCL.cpp:616] [Rank 34] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
[rank58]:[E217 15:05:47.445570533 ProcessGroupNCCL.cpp:616] [Rank 58] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600048 milliseconds before timing out.
[rank83]:[E217 15:05:47.907946838 ProcessGroupNCCL.cpp:616] [Rank 83] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600047 milliseconds before timing out.
[rank82]:[E217 15:05:47.906878935 ProcessGroupNCCL.cpp:616] [Rank 82] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600043 milliseconds before timing out.
[rank81]:[E217 15:05:47.989741370 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 81] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank69]:[E217 15:05:47.529268793 ProcessGroupNCCL.cpp:616] [Rank 69] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600042 milliseconds before timing out.
[rank123]:[E217 15:05:47.541197630 ProcessGroupNCCL.cpp:616] [Rank 123] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
[rank79]:[E217 15:05:47.773330847 ProcessGroupNCCL.cpp:616] [Rank 79] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
[rank39]:[E217 15:05:47.805921710 ProcessGroupNCCL.cpp:616] [Rank 39] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600057 milliseconds before timing out.
[rank126]:[E217 15:05:47.608672691 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 126] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank124]:[E217 15:05:47.608670751 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 124] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank23]:[E217 15:05:47.958314930 ProcessGroupNCCL.cpp:616] [Rank 23] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600097 milliseconds before timing out.
[rank38]:[E217 15:05:47.802804236 ProcessGroupNCCL.cpp:616] [Rank 38] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600027 milliseconds before timing out.
[rank77]:[E217 15:05:47.776712447 ProcessGroupNCCL.cpp:616] [Rank 77] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600063 milliseconds before timing out.
[rank70]:[E217 15:05:47.601030618 ProcessGroupNCCL.cpp:616] [Rank 70] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600085 milliseconds before timing out.
[rank49]:[E217 15:05:47.526834529 ProcessGroupNCCL.cpp:616] [Rank 49] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
[rank40]:[E217 15:05:47.938122073 ProcessGroupNCCL.cpp:616] [Rank 40] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600085 milliseconds before timing out.
[rank117]:[E217 15:05:47.799923070 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 117] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank86]:[E217 15:05:47.922250177 ProcessGroupNCCL.cpp:616] [Rank 86] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600061 milliseconds before timing out.
[rank78]:[E217 15:05:47.863068346 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 78] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank71]:[E217 15:05:47.612132798 ProcessGroupNCCL.cpp:616] [Rank 71] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
[rank61]:[E217 15:05:47.478680209 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 61] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank106]:[E217 15:05:47.039017391 ProcessGroupNCCL.cpp:616] [Rank 106] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600047 milliseconds before timing out.
[rank8]:[E217 15:05:47.782079724 ProcessGroupNCCL.cpp:616] [Rank 8] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600006 milliseconds before timing out.
[rank17]:[E217 15:05:47.054123414 ProcessGroupNCCL.cpp:616] [Rank 17] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
[rank62]:[E217 15:05:47.384332099 ProcessGroupNCCL.cpp:616] [Rank 62] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
[rank11]:[E217 15:05:47.804105480 ProcessGroupNCCL.cpp:616] [Rank 11] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600065 milliseconds before timing out.
[rank7]:[E217 15:05:47.797753950 ProcessGroupNCCL.cpp:616] [Rank 7] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600084 milliseconds before timing out.
[rank107]:[E217 15:05:47.960527942 ProcessGroupNCCL.cpp:616] [Rank 107] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600043 milliseconds before timing out.
[rank14]:[E217 15:05:47.802775570 ProcessGroupNCCL.cpp:616] [Rank 14] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600063 milliseconds before timing out.
[rank76]:[E217 15:05:47.743032578 ProcessGroupNCCL.cpp:616] [Rank 76] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600053 milliseconds before timing out.
[rank65]:[E217 15:05:47.596100133 ProcessGroupNCCL.cpp:616] [Rank 65] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
[rank42]:[E217 15:05:47.874844460 ProcessGroupNCCL.cpp:616] [Rank 42] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
[rank44]:[E217 15:05:47.877322269 ProcessGroupNCCL.cpp:616] [Rank 44] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
[rank116]:[E217 15:05:47.735749261 ProcessGroupNCCL.cpp:616] [Rank 116] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
[rank89]:[E217 15:05:47.025105336 ProcessGroupNCCL.cpp:616] [Rank 89] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
[rank90]:[E217 15:05:47.106598579 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 90] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank36]:[E217 15:05:47.780186377 ProcessGroupNCCL.cpp:616] [Rank 36] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600026 milliseconds before timing out.
[rank27]:[E217 15:05:47.657278716 ProcessGroupNCCL.cpp:616] [Rank 27] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
[rank10]:[E217 15:05:47.833906926 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 10] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank45]:[E217 15:05:47.800975455 ProcessGroupNCCL.cpp:616] [Rank 45] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
[rank66]:[E217 15:05:47.689060633 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 66] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank37]:[E217 15:05:47.784044950 ProcessGroupNCCL.cpp:616] [Rank 37] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600027 milliseconds before timing out.
[rank92]:[E217 15:05:47.956325497 ProcessGroupNCCL.cpp:616] [Rank 92] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600007 milliseconds before timing out.
[rank108]:[E217 15:05:47.981190102 ProcessGroupNCCL.cpp:616] [Rank 108] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600072 milliseconds before timing out.
[rank4]:[E217 15:05:47.812356983 ProcessGroupNCCL.cpp:616] [Rank 4] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600088 milliseconds before timing out.
[rank48]:[E217 15:05:47.637803363 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 48] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank99]:[E217 15:05:47.468480588 ProcessGroupNCCL.cpp:616] [Rank 99] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600093 milliseconds before timing out.
[rank53]:[E217 15:05:47.564487954 ProcessGroupNCCL.cpp:616] [Rank 53] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
[rank15]:[E217 15:05:47.905803269 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 15] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank98]:[E217 15:05:47.471090538 ProcessGroupNCCL.cpp:616] [Rank 98] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600093 milliseconds before timing out.
[rank93]:[E217 15:05:47.038609831 ProcessGroupNCCL.cpp:616] [Rank 93] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
[rank103]:[E217 15:05:47.473245789 ProcessGroupNCCL.cpp:616] [Rank 103] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600097 milliseconds before timing out.
[rank1]:[E217 15:05:47.773883507 ProcessGroupNCCL.cpp:616] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
[rank43]:[E217 15:05:47.976089928 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 43] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank21]:[E217 15:05:47.080598424 ProcessGroupNCCL.cpp:616] [Rank 21] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600097 milliseconds before timing out.
[rank101]:[E217 15:05:47.393047785 ProcessGroupNCCL.cpp:616] [Rank 101] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600002 milliseconds before timing out.
[rank38]:[E217 15:05:47.887905931 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 38] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank55]:[E217 15:05:47.495935997 ProcessGroupNCCL.cpp:616] [Rank 55] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600028 milliseconds before timing out.
[rank102]:[E217 15:05:47.480550659 ProcessGroupNCCL.cpp:616] [Rank 102] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600094 milliseconds before timing out.
[rank19]:[E217 15:05:47.040987245 ProcessGroupNCCL.cpp:616] [Rank 19] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
[rank47]:[E217 15:05:47.920268233 ProcessGroupNCCL.cpp:616] [Rank 47] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600089 milliseconds before timing out.
[rank79]:[E217 15:05:47.863073406 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 79] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank97]:[E217 15:05:47.483963905 ProcessGroupNCCL.cpp:616] [Rank 97] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600095 milliseconds before timing out.
[rank29]:[E217 15:05:47.596031075 ProcessGroupNCCL.cpp:616] [Rank 29] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
[rank118]:[E217 15:05:47.716473687 ProcessGroupNCCL.cpp:616] [Rank 118] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600046 milliseconds before timing out.
[rank74]:[E217 15:05:47.744479293 ProcessGroupNCCL.cpp:616] [Rank 74] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600018 milliseconds before timing out.
[rank111]:[E217 15:05:47.998258493 ProcessGroupNCCL.cpp:616] [Rank 111] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
[rank109]:[E217 15:05:47.998175171 ProcessGroupNCCL.cpp:616] [Rank 109] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600086 milliseconds before timing out.
[rank116]:[E217 15:05:47.852370344 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 116] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank51]:[E217 15:05:47.587489267 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 51] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank69]:[E217 15:05:47.687872665 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 69] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank113]:[E217 15:05:47.856520118 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 113] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank122]:[E217 15:05:47.517999853 ProcessGroupNCCL.cpp:616] [Rank 122] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600031 milliseconds before timing out.
[rank83]:[E217 15:05:47.059782167 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 83] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank87]:[E217 15:05:47.915353278 ProcessGroupNCCL.cpp:616] [Rank 87] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600059 milliseconds before timing out.
[rank59]:[E217 15:05:47.442803300 ProcessGroupNCCL.cpp:616] [Rank 59] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600049 milliseconds before timing out.
[rank32]:[E217 15:05:47.854434051 ProcessGroupNCCL.cpp:616] [Rank 32] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600064 milliseconds before timing out.
[rank54]:[E217 15:05:47.523633850 ProcessGroupNCCL.cpp:616] [Rank 54] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
[rank86]:[E217 15:05:47.003158524 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 86] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank33]:[E217 15:05:47.793744830 ProcessGroupNCCL.cpp:616] [Rank 33] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600031 milliseconds before timing out.
[rank56]:[E217 15:05:47.505120649 ProcessGroupNCCL.cpp:616] [Rank 56] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
[rank84]:[E217 15:05:47.924177066 ProcessGroupNCCL.cpp:616] [Rank 84] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600059 milliseconds before timing out.
[rank70]:[E217 15:05:47.695873627 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 70] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank127]:[E217 15:05:47.549356772 ProcessGroupNCCL.cpp:616] [Rank 127] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600071 milliseconds before timing out.
[rank57]:[E217 15:05:47.450052895 ProcessGroupNCCL.cpp:616] [Rank 57] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600050 milliseconds before timing out.
[rank39]:[E217 15:05:47.931856603 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 39] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank71]:[E217 15:05:47.703303601 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 71] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank75]:[E217 15:05:47.874644470 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 75] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank24]:[E217 15:05:47.596027685 ProcessGroupNCCL.cpp:616] [Rank 24] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
[rank12]:[E217 15:05:47.798301137 ProcessGroupNCCL.cpp:616] [Rank 12] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
[rank73]:[E217 15:05:47.779021273 ProcessGroupNCCL.cpp:616] [Rank 73] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600060 milliseconds before timing out.
[rank102]:[E217 15:05:47.598885464 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 102] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank72]:[E217 15:05:47.836379880 ProcessGroupNCCL.cpp:616] [Rank 72] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
[rank114]:[E217 15:05:47.716459707 ProcessGroupNCCL.cpp:616] [Rank 114] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600049 milliseconds before timing out.
[rank118]:[E217 15:05:47.847739005 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 118] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank30]:[E217 15:05:47.647180872 ProcessGroupNCCL.cpp:616] [Rank 30] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
[rank3]:[E217 15:05:47.874550342 ProcessGroupNCCL.cpp:616] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600069 milliseconds before timing out.
[rank67]:[E217 15:05:47.595132779 ProcessGroupNCCL.cpp:616] [Rank 67] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
[rank50]:[E217 15:05:47.659865215 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 50] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank26]:[E217 15:05:47.649369097 ProcessGroupNCCL.cpp:616] [Rank 26] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
[rank36]:[E217 15:05:47.955081404 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 36] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank62]:[E217 15:05:47.597303827 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 62] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank37]:[E217 15:05:47.957429598 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 37] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank82]:[E217 15:05:47.059367330 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 82] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank110]:[E217 15:05:47.960520252 ProcessGroupNCCL.cpp:616] [Rank 110] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600048 milliseconds before timing out.
[rank91]:[E217 15:05:47.022828250 ProcessGroupNCCL.cpp:616] [Rank 91] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
[rank22]:[E217 15:05:47.155346145 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 22] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank65]:[E217 15:05:47.676477921 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 65] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank52]:[E217 15:05:47.593769451 ProcessGroupNCCL.cpp:616] [Rank 52] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600037 milliseconds before timing out.
[rank87]:[E217 15:05:47.060650022 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 87] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank104]:[E217 15:05:47.016455605 ProcessGroupNCCL.cpp:616] [Rank 104] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600043 milliseconds before timing out.
[rank44]:[E217 15:05:47.036600186 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 44] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank54]:[E217 15:05:47.671509845 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 54] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank20]:[E217 15:05:47.058946180 ProcessGroupNCCL.cpp:616] [Rank 20] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600075 milliseconds before timing out.
[rank6]:[E217 15:05:47.804753912 ProcessGroupNCCL.cpp:616] [Rank 6] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
[rank40]:[E217 15:05:47.038675512 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 40] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank25]:[E217 15:05:47.734972099 ProcessGroupNCCL.cpp:616] [Rank 25] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
[rank45]:[E217 15:05:47.976088228 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 45] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank49]:[E217 15:05:47.675350627 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 49] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank94]:[E217 15:05:47.112315406 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 94] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank5]:[E217 15:05:47.806264441 ProcessGroupNCCL.cpp:616] [Rank 5] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
[rank106]:[E217 15:05:47.137938626 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 106] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank121]:[E217 15:05:47.641550071 ProcessGroupNCCL.cpp:616] [Rank 121] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600086 milliseconds before timing out.
[rank101]:[E217 15:05:47.594636363 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 101] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank46]:[E217 15:05:47.982396521 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 46] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank53]:[E217 15:05:47.687703771 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 53] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank105]:[E217 15:05:47.978467050 ProcessGroupNCCL.cpp:616] [Rank 105] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600072 milliseconds before timing out.
[rank112]:[E217 15:05:47.799546651 ProcessGroupNCCL.cpp:616] [Rank 112] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600061 milliseconds before timing out.
[rank28]:[E217 15:05:47.759080651 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 28] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank2]:[E217 15:05:47.810395603 ProcessGroupNCCL.cpp:616] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
[rank31]:[E217 15:05:47.660546944 ProcessGroupNCCL.cpp:616] [Rank 31] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
[rank103]:[E217 15:05:47.592921470 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 103] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank55]:[E217 15:05:47.692620466 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 55] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank123]:[E217 15:05:47.667906286 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 123] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank29]:[E217 15:05:47.761809477 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 29] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank27]:[E217 15:05:47.752648219 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 27] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank41]:[E217 15:05:47.896291981 ProcessGroupNCCL.cpp:616] [Rank 41] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600082 milliseconds before timing out.
[rank52]:[E217 15:05:47.705787368 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 52] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank13]:[E217 15:05:47.925842360 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 13] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank84]:[E217 15:05:47.104648894 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 84] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank127]:[E217 15:05:47.720087917 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 127] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank23]:[E217 15:05:47.198369088 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 23] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank76]:[E217 15:05:47.937313860 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 76] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank64]:[E217 15:05:47.683020671 ProcessGroupNCCL.cpp:616] [Rank 64] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
[rank96]:[E217 15:05:47.545973701 ProcessGroupNCCL.cpp:616] [Rank 96] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600090 milliseconds before timing out.
[rank95]:[E217 15:05:47.149474917 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 95] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank58]:[E217 15:05:47.601961569 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 58] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank125]:[E217 15:05:47.641518529 ProcessGroupNCCL.cpp:616] [Rank 125] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
[rank34]:[E217 15:05:47.958973059 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 34] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank80]:[E217 15:05:47.942988777 ProcessGroupNCCL.cpp:616] [Rank 80] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600002 milliseconds before timing out.
[rank47]:[E217 15:05:47.048459490 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 47] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank19]:[E217 15:05:47.231809133 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 19] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank77]:[E217 15:05:47.933044288 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 77] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank120]:[E217 15:05:47.578497154 ProcessGroupNCCL.cpp:616] [Rank 120] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
[rank11]:[E217 15:05:47.962180715 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 11] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank14]:[E217 15:05:47.966751710 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 14] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank21]:[E217 15:05:47.241568610 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 21] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank17]:[E217 15:05:47.207104333 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 17] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank32]:[E217 15:05:47.051922977 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 32] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank73]:[E217 15:05:47.940656768 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 73] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank1]:[E217 15:05:47.966756540 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 1] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank9]:[E217 15:05:47.880302862 ProcessGroupNCCL.cpp:616] [Rank 9] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600064 milliseconds before timing out.
[rank42]:[E217 15:05:47.032881778 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 42] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank92]:[E217 15:05:47.192306102 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 92] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank91]:[E217 15:05:47.181221842 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 91] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank72]:[E217 15:05:47.941713840 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 72] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank74]:[E217 15:05:47.984153466 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 74] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank7]:[E217 15:05:47.966751389 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 7] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank110]:[E217 15:05:47.137939815 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 110] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank20]:[E217 15:05:47.273603743 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 20] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank107]:[E217 15:05:47.137945576 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 107] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank24]:[E217 15:05:47.795671059 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 24] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank125]:[E217 15:05:47.784579320 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 125] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank89]:[E217 15:05:47.187381257 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 89] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank108]:[E217 15:05:47.147142344 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 108] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank12]:[E217 15:05:47.024761854 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 12] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank30]:[E217 15:05:47.872635644 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 30] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank67]:[E217 15:05:47.822461981 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 67] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank99]:[E217 15:05:47.627673385 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 99] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank4]:[E217 15:05:47.975661807 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 4] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank111]:[E217 15:05:47.167662281 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 111] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank109]:[E217 15:05:47.167475387 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 109] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank98]:[E217 15:05:47.631478818 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 98] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank93]:[E217 15:05:47.204099738 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 93] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank31]:[E217 15:05:47.884725186 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 31] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank8]:[E217 15:05:47.977186360 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 8] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank59]:[E217 15:05:47.675988266 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 59] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank97]:[E217 15:05:47.643183372 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 97] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank114]:[E217 15:05:47.963080163 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 114] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank41]:[E217 15:05:47.125032277 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 41] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank33]:[E217 15:05:47.040465034 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 33] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank57]:[E217 15:05:47.690272686 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 57] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank122]:[E217 15:05:47.751202014 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 122] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank26]:[E217 15:05:47.879487972 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 26] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank16]:[E217 15:05:47.139761730 ProcessGroupNCCL.cpp:616] [Rank 16] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
[rank3]:[E217 15:05:47.030407065 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 3] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank25]:[E217 15:05:47.895399593 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 25] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank6]:[E217 15:05:47.044157261 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 6] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank5]:[E217 15:05:47.049090786 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 5] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank121]:[E217 15:05:47.799622126 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 121] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank2]:[E217 15:05:47.058446403 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 2] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank105]:[E217 15:05:47.220218828 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 105] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank9]:[E217 15:05:47.105912081 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 9] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank56]:[E217 15:05:47.706476786 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 56] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank104]:[E217 15:05:47.239854618 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 104] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank120]:[E217 15:05:47.859221740 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 120] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank112]:[E217 15:05:47.013610438 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 112] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank80]:[E217 15:05:47.244566420 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 80] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank88]:[E217 15:05:47.219879040 ProcessGroupNCCL.cpp:616] [Rank 88] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
[rank96]:[E217 15:05:47.764996433 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 96] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank64]:[E217 15:05:47.909325308 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 64] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank16]:[E217 15:05:47.460077230 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 16] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank88]:[E217 15:05:47.428671962 ProcessGroupNCCL.cpp:1785] [PG ID 1 PG GUID 1 Rank 88] Exception (either an error or timeout) detected by watchdog at work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank48]:[E217 15:05:47.230204390 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 48] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank48]:[E217 15:05:47.230242041 ProcessGroupNCCL.cpp:630] [Rank 48] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank48]:[E217 15:05:47.230250341 ProcessGroupNCCL.cpp:636] [Rank 48] To avoid data inconsistency, we are taking the entire process down.
[rank24]:[E217 15:05:47.445165617 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 24] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank24]:[E217 15:05:47.445190688 ProcessGroupNCCL.cpp:630] [Rank 24] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank24]:[E217 15:05:47.445195318 ProcessGroupNCCL.cpp:636] [Rank 24] To avoid data inconsistency, we are taking the entire process down.
[rank48]: Traceback (most recent call last):
[rank48]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank48]:     train(attn_implementation="flash_attention_2")
[rank48]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank48]:     trainer.train()
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank48]:     return inner_training_loop(
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank48]:     self._maybe_log_save_evaluate(
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank48]:     self._save_checkpoint(model, trial)
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank48]:     self._save_optimizer_and_scheduler(output_dir)
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank48]:     self.model_wrapped.save_checkpoint(output_dir)
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank48]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank48]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank48]:     return func(*args, **kwargs)
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank48]:     return cdb.barrier(group=group, async_op=async_op)
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank48]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank48]:     return func(*args, **kwargs)
[rank48]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank48]:     work = group.barrier(opts=opts)
[rank48]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 48. 
[rank24]: Traceback (most recent call last):
[rank24]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank24]:     train(attn_implementation="flash_attention_2")
[rank24]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank24]:     trainer.train()
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank24]:     return inner_training_loop(
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank24]:     self._maybe_log_save_evaluate(
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank24]:     self._save_checkpoint(model, trial)
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank24]:     self._save_optimizer_and_scheduler(output_dir)
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank24]:     self.model_wrapped.save_checkpoint(output_dir)
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank24]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank24]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank24]:     return func(*args, **kwargs)
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank24]:     return cdb.barrier(group=group, async_op=async_op)
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank24]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank24]:     return func(*args, **kwargs)
[rank24]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank24]:     work = group.barrier(opts=opts)
[rank24]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 24. 
[rank40]:[E217 15:05:48.838832847 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 40] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank40]:[E217 15:05:48.838859529 ProcessGroupNCCL.cpp:630] [Rank 40] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank40]:[E217 15:05:48.838865579 ProcessGroupNCCL.cpp:636] [Rank 40] To avoid data inconsistency, we are taking the entire process down.
[rank24]:[E217 15:05:48.619520994 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 24] Process group watchdog thread terminated with exception: [Rank 24] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7141a42e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x71415962a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x714159631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x71415963361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7141a4a735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7141a8c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7141a8d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 24] Process group watchdog thread terminated with exception: [Rank 24] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7141a42e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x71415962a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x714159631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x71415963361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7141a4a735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7141a8c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7141a8d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7141a42e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7141592a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7141a4a735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7141a8c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7141a8d26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank32]:[E217 15:05:48.806799725 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 32] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank32]:[E217 15:05:48.806831227 ProcessGroupNCCL.cpp:630] [Rank 32] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank32]:[E217 15:05:48.806837927 ProcessGroupNCCL.cpp:636] [Rank 32] To avoid data inconsistency, we are taking the entire process down.
[rank48]:[E217 15:05:48.526981651 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 48] Process group watchdog thread terminated with exception: [Rank 48] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75a35036c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75a305a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75a305a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75a305a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75a3514635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75a355094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75a355126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 48] Process group watchdog thread terminated with exception: [Rank 48] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75a35036c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75a305a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75a305a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75a305a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75a3514635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75a355094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75a355126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75a35036c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x75a3056a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x75a3514635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x75a355094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x75a355126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank8]:[E217 15:05:48.804262059 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 8] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank8]:[E217 15:05:48.804282770 ProcessGroupNCCL.cpp:630] [Rank 8] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank8]:[E217 15:05:48.804288930 ProcessGroupNCCL.cpp:636] [Rank 8] To avoid data inconsistency, we are taking the entire process down.
[rank72]:[E217 15:05:48.854738694 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 72] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank72]:[E217 15:05:48.854765866 ProcessGroupNCCL.cpp:630] [Rank 72] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank72]:[E217 15:05:48.854770856 ProcessGroupNCCL.cpp:636] [Rank 72] To avoid data inconsistency, we are taking the entire process down.
[rank32]: Traceback (most recent call last):
[rank32]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank32]:     train(attn_implementation="flash_attention_2")
[rank32]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank32]:     trainer.train()
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank32]:     return inner_training_loop(
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank32]:     self._maybe_log_save_evaluate(
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank32]:     self._save_checkpoint(model, trial)
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank32]:     self._save_optimizer_and_scheduler(output_dir)
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank32]:     self.model_wrapped.save_checkpoint(output_dir)
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank32]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank32]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank32]:     return func(*args, **kwargs)
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank32]:     return cdb.barrier(group=group, async_op=async_op)
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank32]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank32]:     return func(*args, **kwargs)
[rank32]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank32]:     work = group.barrier(opts=opts)
[rank32]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 32. 
[rank8]:[E217 15:05:48.961748511 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 8] Process group watchdog thread terminated with exception: [Rank 8] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600006 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7208ae56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x720863c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x720863c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x720863c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7208af25c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7208b3294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7208b3326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 8] Process group watchdog thread terminated with exception: [Rank 8] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600006 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7208ae56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x720863c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x720863c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x720863c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7208af25c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7208b3294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7208b3326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7208ae56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7208638a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7208af25c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7208b3294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7208b3326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank40]: Traceback (most recent call last):
[rank40]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank40]:     train(attn_implementation="flash_attention_2")
[rank40]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank40]:     trainer.train()
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank40]:     return inner_training_loop(
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank40]:     self._maybe_log_save_evaluate(
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank40]:     self._save_checkpoint(model, trial)
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank40]:     self._save_optimizer_and_scheduler(output_dir)
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank40]:     self.model_wrapped.save_checkpoint(output_dir)
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank40]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank40]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank40]:     return func(*args, **kwargs)
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank40]:     return cdb.barrier(group=group, async_op=async_op)
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank40]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank40]:     return func(*args, **kwargs)
[rank40]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank40]:     work = group.barrier(opts=opts)
[rank40]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 40. 
[rank32]:[E217 15:05:48.022969103 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 32] Process group watchdog thread terminated with exception: [Rank 32] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600064 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f2d44393446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f2cf962a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f2cf9631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f2cf963361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f2d444ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f2d48c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f2d48d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 32] Process group watchdog thread terminated with exception: [Rank 32] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600064 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f2d44393446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f2cf962a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f2cf9631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f2cf963361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f2d444ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f2d48c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f2d48d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f2d44393446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7f2cf92a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f2d444ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f2d48c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7f2d48d26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank72]: Traceback (most recent call last):
[rank72]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank72]:     train(attn_implementation="flash_attention_2")
[rank72]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank72]:     trainer.train()
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank72]:     return inner_training_loop(
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank72]:     self._maybe_log_save_evaluate(
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank72]:     self._save_checkpoint(model, trial)
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank72]:     self._save_optimizer_and_scheduler(output_dir)
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank72]:     self.model_wrapped.save_checkpoint(output_dir)
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank72]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank72]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank72]:     return func(*args, **kwargs)
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank72]:     return cdb.barrier(group=group, async_op=async_op)
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank72]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank72]:     return func(*args, **kwargs)
[rank72]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank72]:     work = group.barrier(opts=opts)
[rank72]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 72. 
[rank40]:[E217 15:05:48.118995402 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 40] Process group watchdog thread terminated with exception: [Rank 40] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600085 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71d9d50c1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x71d98a42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x71d98a431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x71d98a43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x71d9d521c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x71d9d9a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x71d9d9b26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 40] Process group watchdog thread terminated with exception: [Rank 40] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600085 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71d9d50c1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x71d98a42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x71d98a431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x71d98a43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x71d9d521c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x71d9d9a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x71d9d9b26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71d9d50c1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x71d98a0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x71d9d521c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x71d9d9a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x71d9d9b26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank72]:[E217 15:05:48.048195288 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 72] Process group watchdog thread terminated with exception: [Rank 72] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75cc2092a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75cbd5c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75cbd5c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75cbd5c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75cc210735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75cc25294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75cc25326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 72] Process group watchdog thread terminated with exception: [Rank 72] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75cc2092a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75cbd5c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75cbd5c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75cbd5c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75cc210735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75cc25294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75cc25326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75cc2092a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x75cbd58a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x75cc210735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x75cc25294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x75cc25326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank120]:[E217 15:05:48.864758082 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 120] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank120]:[E217 15:05:48.864777813 ProcessGroupNCCL.cpp:630] [Rank 120] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank120]:[E217 15:05:48.864783113 ProcessGroupNCCL.cpp:636] [Rank 120] To avoid data inconsistency, we are taking the entire process down.
[rank120]:[E217 15:05:48.002628528 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 120] Process group watchdog thread terminated with exception: [Rank 120] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x784cd396c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x784c8902a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x784c89031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x784c8903361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x784cd4a565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x784cd8694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x784cd8726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 120] Process group watchdog thread terminated with exception: [Rank 120] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x784cd396c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x784c8902a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x784c89031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x784c8903361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x784cd4a565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x784cd8694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x784cd8726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x784cd396c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x784c88ca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x784cd4a565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x784cd8694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x784cd8726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank56]:[E217 15:05:48.930671946 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 56] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank56]:[E217 15:05:48.930697597 ProcessGroupNCCL.cpp:630] [Rank 56] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank56]:[E217 15:05:48.930702388 ProcessGroupNCCL.cpp:636] [Rank 56] To avoid data inconsistency, we are taking the entire process down.
[rank112]:[E217 15:05:48.245114046 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 112] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank112]:[E217 15:05:48.245141457 ProcessGroupNCCL.cpp:630] [Rank 112] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank112]:[E217 15:05:48.245147417 ProcessGroupNCCL.cpp:636] [Rank 112] To avoid data inconsistency, we are taking the entire process down.
[rank80]:[E217 15:05:48.466045132 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 80] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank80]:[E217 15:05:48.466070283 ProcessGroupNCCL.cpp:630] [Rank 80] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank80]:[E217 15:05:48.466076053 ProcessGroupNCCL.cpp:636] [Rank 80] To avoid data inconsistency, we are taking the entire process down.
[rank88]:[E217 15:05:48.606635382 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 88] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank88]:[E217 15:05:48.606653724 ProcessGroupNCCL.cpp:630] [Rank 88] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank88]:[E217 15:05:48.606659594 ProcessGroupNCCL.cpp:636] [Rank 88] To avoid data inconsistency, we are taking the entire process down.
[rank64]:[E217 15:05:48.235277801 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 64] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank64]:[E217 15:05:48.235300771 ProcessGroupNCCL.cpp:630] [Rank 64] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank64]:[E217 15:05:48.235305681 ProcessGroupNCCL.cpp:636] [Rank 64] To avoid data inconsistency, we are taking the entire process down.
[rank56]: Traceback (most recent call last):
[rank56]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank56]:     train(attn_implementation="flash_attention_2")
[rank56]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank56]:     trainer.train()
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank56]:     return inner_training_loop(
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank56]:     self._maybe_log_save_evaluate(
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank56]:     self._save_checkpoint(model, trial)
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank56]:     self._save_optimizer_and_scheduler(output_dir)
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank56]:     self.model_wrapped.save_checkpoint(output_dir)
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank56]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank56]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank56]:     return func(*args, **kwargs)
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank56]:     return cdb.barrier(group=group, async_op=async_op)
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank56]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank56]:     return func(*args, **kwargs)
[rank56]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank56]:     work = group.barrier(opts=opts)
[rank56]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 56. 
[rank16]:[E217 15:05:48.701743049 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 16] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank16]:[E217 15:05:48.701769410 ProcessGroupNCCL.cpp:630] [Rank 16] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank16]:[E217 15:05:48.701776101 ProcessGroupNCCL.cpp:636] [Rank 16] To avoid data inconsistency, we are taking the entire process down.
[rank104]:[E217 15:05:48.612340256 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 104] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank104]:[E217 15:05:48.612367157 ProcessGroupNCCL.cpp:630] [Rank 104] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank104]:[E217 15:05:48.612372637 ProcessGroupNCCL.cpp:636] [Rank 104] To avoid data inconsistency, we are taking the entire process down.
[rank56]:[E217 15:05:48.119184057 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 56] Process group watchdog thread terminated with exception: [Rank 56] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f6e216db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f6dd6a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f6dd6a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f6dd6a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f6e222585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f6e26094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f6e26126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 56] Process group watchdog thread terminated with exception: [Rank 56] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f6e216db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f6dd6a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f6dd6a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f6dd6a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f6e222585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f6e26094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f6e26126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f6e216db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7f6dd66a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f6e222585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f6e26094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7f6e26126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank96]:[E217 15:05:48.121686028 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 96] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank96]:[E217 15:05:48.121714948 ProcessGroupNCCL.cpp:630] [Rank 96] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank96]:[E217 15:05:48.121721038 ProcessGroupNCCL.cpp:636] [Rank 96] To avoid data inconsistency, we are taking the entire process down.
[rank80]:[E217 15:05:48.606676057 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 80] Process group watchdog thread terminated with exception: [Rank 80] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600002 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7aa3887b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7aa33da2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7aa33da31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7aa33da3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7aa3892555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7aa38d094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7aa38d126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 80] Process group watchdog thread terminated with exception: [Rank 80] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600002 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7aa3887b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7aa33da2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7aa33da31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7aa33da3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7aa3892555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7aa38d094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7aa38d126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7aa3887b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7aa33d6a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7aa3892555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7aa38d094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7aa38d126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank112]: Traceback (most recent call last):
[rank112]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank112]:     train(attn_implementation="flash_attention_2")
[rank112]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank112]:     trainer.train()
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank112]:     return inner_training_loop(
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank112]:     self._maybe_log_save_evaluate(
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank112]:     self._save_checkpoint(model, trial)
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank112]:     self._save_optimizer_and_scheduler(output_dir)
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank112]:     self.model_wrapped.save_checkpoint(output_dir)
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank112]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank112]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank112]:     return func(*args, **kwargs)
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank112]:     return cdb.barrier(group=group, async_op=async_op)
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank112]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank112]:     return func(*args, **kwargs)
[rank112]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank112]:     work = group.barrier(opts=opts)
[rank112]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 112. 
[rank112]:[E217 15:05:48.455478162 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 112] Process group watchdog thread terminated with exception: [Rank 112] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600061 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e0bd916c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e0b8e82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e0b8e831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e0b8e83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e0bd9e5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e0bdde94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e0bddf26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 112] Process group watchdog thread terminated with exception: [Rank 112] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600061 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e0bd916c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e0b8e82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e0b8e831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e0b8e83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e0bd9e5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e0bdde94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e0bddf26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e0bd916c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7e0b8e4a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7e0bd9e5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7e0bdde94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7e0bddf26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank88]:[E217 15:05:48.782304822 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 88] Process group watchdog thread terminated with exception: [Rank 88] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70801f4e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x707fd482a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x707fd4831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x707fd483361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x70801fc735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x708023e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x708023f26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 88] Process group watchdog thread terminated with exception: [Rank 88] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70801f4e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x707fd482a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x707fd4831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x707fd483361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x70801fc735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x708023e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x708023f26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70801f4e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x707fd44a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x70801fc735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x708023e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x708023f26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank16]:[E217 15:05:48.841509044 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 16] Process group watchdog thread terminated with exception: [Rank 16] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b40464e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b3ffb82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b3ffb831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b3ffb83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b4046c735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b404ae94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b404af26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 16] Process group watchdog thread terminated with exception: [Rank 16] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b40464e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b3ffb82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b3ffb831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b3ffb83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b4046c735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b404ae94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b404af26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b40464e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7b3ffb4a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7b4046c735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7b404ae94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7b404af26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank64]: Traceback (most recent call last):
[rank64]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank64]:     train(attn_implementation="flash_attention_2")
[rank64]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank64]:     trainer.train()
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank64]:     return inner_training_loop(
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank64]:     self._maybe_log_save_evaluate(
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank64]:     self._save_checkpoint(model, trial)
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank64]:     self._save_optimizer_and_scheduler(output_dir)
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank64]:     self.model_wrapped.save_checkpoint(output_dir)
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank64]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank64]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank64]:     return func(*args, **kwargs)
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank64]:     return cdb.barrier(group=group, async_op=async_op)
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank64]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank64]:     return func(*args, **kwargs)
[rank64]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank64]:     work = group.barrier(opts=opts)
[rank64]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 64. 
[rank64]:[E217 15:05:48.393129452 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 64] Process group watchdog thread terminated with exception: [Rank 64] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b596fee7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b592522a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b5925231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b592523361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b5970a585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b5974894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b5974926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 64] Process group watchdog thread terminated with exception: [Rank 64] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b596fee7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b592522a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b5925231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b592523361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b5970a585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b5974894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b5974926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b596fee7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7b5924ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7b5970a585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7b5974894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7b5974926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank104]: Traceback (most recent call last):
[rank104]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank104]:     train(attn_implementation="flash_attention_2")
[rank104]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank104]:     trainer.train()
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank104]:     return inner_training_loop(
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank104]:     self._maybe_log_save_evaluate(
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank104]:     self._save_checkpoint(model, trial)
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank104]:     self._save_optimizer_and_scheduler(output_dir)
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank104]:     self.model_wrapped.save_checkpoint(output_dir)
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank104]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank104]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank104]:     return func(*args, **kwargs)
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank104]:     return cdb.barrier(group=group, async_op=async_op)
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank104]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank104]:     return func(*args, **kwargs)
[rank104]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank104]:     work = group.barrier(opts=opts)
[rank104]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 104. 
[rank104]:[E217 15:05:48.773793060 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 104] Process group watchdog thread terminated with exception: [Rank 104] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600043 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7845dcee7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78459222a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x784592231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78459223361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7845dda515c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7845e1894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7845e1926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 104] Process group watchdog thread terminated with exception: [Rank 104] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600043 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7845dcee7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78459222a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x784592231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78459223361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7845dda515c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7845e1894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7845e1926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7845dcee7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x784591ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7845dda515c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7845e1894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7845e1926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank96]: Traceback (most recent call last):
[rank96]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank96]:     train(attn_implementation="flash_attention_2")
[rank96]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank96]:     trainer.train()
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank96]:     return inner_training_loop(
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank96]:     self._maybe_log_save_evaluate(
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank96]:     self._save_checkpoint(model, trial)
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank96]:     self._save_optimizer_and_scheduler(output_dir)
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank96]:     self.model_wrapped.save_checkpoint(output_dir)
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank96]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank96]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank96]:     return func(*args, **kwargs)
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank96]:     return cdb.barrier(group=group, async_op=async_op)
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank96]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank96]:     return func(*args, **kwargs)
[rank96]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank96]:     work = group.barrier(opts=opts)
[rank96]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 96. 
[rank96]:[E217 15:05:49.313744813 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 96] Process group watchdog thread terminated with exception: [Rank 96] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600090 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78087e56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x780833c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x780833c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x780833c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78087f65d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x780883294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x780883326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 96] Process group watchdog thread terminated with exception: [Rank 96] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600090 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78087e56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x780833c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x780833c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x780833c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78087f65d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x780883294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x780883326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78087e56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7808338a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x78087f65d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x780883294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x780883326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank121]:[E217 15:05:49.616541336 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 121] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank121]:[E217 15:05:49.616569268 ProcessGroupNCCL.cpp:630] [Rank 121] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank121]:[E217 15:05:49.616574758 ProcessGroupNCCL.cpp:636] [Rank 121] To avoid data inconsistency, we are taking the entire process down.
[rank121]:[E217 15:05:49.663825838 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 121] Process group watchdog thread terminated with exception: [Rank 121] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600086 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x785b31ae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x785ae6e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x785ae6e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x785ae6e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x785b322735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x785b36494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x785b36526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 121] Process group watchdog thread terminated with exception: [Rank 121] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600086 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x785b31ae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x785ae6e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x785ae6e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x785ae6e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x785b322735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x785b36494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x785b36526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x785b31ae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x785ae6aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x785b322735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x785b36494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x785b36526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank125]:[E217 15:05:49.771462504 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 125] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank125]:[E217 15:05:49.771487295 ProcessGroupNCCL.cpp:630] [Rank 125] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank125]:[E217 15:05:49.771493156 ProcessGroupNCCL.cpp:636] [Rank 125] To avoid data inconsistency, we are taking the entire process down.
[rank127]:[E217 15:05:49.781307445 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 127] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank127]:[E217 15:05:49.781335537 ProcessGroupNCCL.cpp:630] [Rank 127] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank127]:[E217 15:05:49.781340977 ProcessGroupNCCL.cpp:636] [Rank 127] To avoid data inconsistency, we are taking the entire process down.
[rank125]:[E217 15:05:49.790567595 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 125] Process group watchdog thread terminated with exception: [Rank 125] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b143d96c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b13f302a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b13f3031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b13f303361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b143ea535c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b1442494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b1442526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 125] Process group watchdog thread terminated with exception: [Rank 125] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b143d96c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b13f302a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b13f3031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b13f303361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b143ea535c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b1442494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b1442526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b143d96c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7b13f2ca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7b143ea535c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7b1442494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7b1442526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank123]:[E217 15:05:49.808532966 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 123] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank123]:[E217 15:05:49.808550547 ProcessGroupNCCL.cpp:630] [Rank 123] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank123]:[E217 15:05:49.808555307 ProcessGroupNCCL.cpp:636] [Rank 123] To avoid data inconsistency, we are taking the entire process down.
[rank127]:[E217 15:05:49.829710927 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 127] Process group watchdog thread terminated with exception: [Rank 127] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600071 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x724d11b2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x724cc6e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x724cc6e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x724cc6e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x724d122735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x724d16494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x724d16526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 127] Process group watchdog thread terminated with exception: [Rank 127] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600071 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x724d11b2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x724cc6e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x724cc6e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x724cc6e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x724d122735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x724d16494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x724d16526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x724d11b2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x724cc6aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x724d122735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x724d16494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x724d16526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank122]:[E217 15:05:49.846946499 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 122] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank122]:[E217 15:05:49.846970150 ProcessGroupNCCL.cpp:630] [Rank 122] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank122]:[E217 15:05:49.846975440 ProcessGroupNCCL.cpp:636] [Rank 122] To avoid data inconsistency, we are taking the entire process down.
[rank124]:[E217 15:05:49.847958553 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 124] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank124]:[E217 15:05:49.847971023 ProcessGroupNCCL.cpp:630] [Rank 124] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank124]:[E217 15:05:49.847974963 ProcessGroupNCCL.cpp:636] [Rank 124] To avoid data inconsistency, we are taking the entire process down.
[rank126]:[E217 15:05:49.855208236 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 126] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank126]:[E217 15:05:49.855224787 ProcessGroupNCCL.cpp:630] [Rank 126] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank126]:[E217 15:05:49.855229127 ProcessGroupNCCL.cpp:636] [Rank 126] To avoid data inconsistency, we are taking the entire process down.
[rank122]:[E217 15:05:49.865188994 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 122] Process group watchdog thread terminated with exception: [Rank 122] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600031 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x763a2a4e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7639df82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7639df831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7639df83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x763a2ac735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x763a2ee94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x763a2ef26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 122] Process group watchdog thread terminated with exception: [Rank 122] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600031 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x763a2a4e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7639df82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7639df831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7639df83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x763a2ac735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x763a2ee94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x763a2ef26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x763a2a4e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7639df4a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x763a2ac735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x763a2ee94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x763a2ef26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank123]: Traceback (most recent call last):
[rank123]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank123]:     train(attn_implementation="flash_attention_2")
[rank123]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank123]:     trainer.train()
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank123]:     return inner_training_loop(
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank123]:     self._maybe_log_save_evaluate(
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank123]:     self._save_checkpoint(model, trial)
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank123]:     self._save_optimizer_and_scheduler(output_dir)
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank123]:     self.model_wrapped.save_checkpoint(output_dir)
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank123]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank123]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank123]:     return func(*args, **kwargs)
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank123]:     return cdb.barrier(group=group, async_op=async_op)
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank123]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank123]:     return func(*args, **kwargs)
[rank123]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank123]:     work = group.barrier(opts=opts)
[rank123]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 123. 
[rank123]:[E217 15:05:49.870975420 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 123] Process group watchdog thread terminated with exception: [Rank 123] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7c7eddae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7c7e92e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7c7e92e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7c7e92e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7c7ede6585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7c7ee2494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7c7ee2526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 123] Process group watchdog thread terminated with exception: [Rank 123] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7c7eddae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7c7e92e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7c7e92e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7c7e92e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7c7ede6585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7c7ee2494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7c7ee2526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7c7eddae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7c7e92aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7c7ede6585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7c7ee2494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7c7ee2526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank126]: Traceback (most recent call last):
[rank126]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank126]:     train(attn_implementation="flash_attention_2")
[rank126]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank126]:     trainer.train()
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank126]:     return inner_training_loop(
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank126]:     self._maybe_log_save_evaluate(
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank126]:     self._save_checkpoint(model, trial)
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank126]:     self._save_optimizer_and_scheduler(output_dir)
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank126]:     self.model_wrapped.save_checkpoint(output_dir)
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank126]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank126]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank126]:     return func(*args, **kwargs)
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank126]:     return cdb.barrier(group=group, async_op=async_op)
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank126]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank126]:     return func(*args, **kwargs)
[rank126]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank126]:     work = group.barrier(opts=opts)
[rank126]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 126. 
[rank124]: Traceback (most recent call last):
[rank124]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank124]:     train(attn_implementation="flash_attention_2")
[rank124]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank124]:     trainer.train()
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank124]:     return inner_training_loop(
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank124]:     self._maybe_log_save_evaluate(
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank124]:     self._save_checkpoint(model, trial)
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank124]:     self._save_optimizer_and_scheduler(output_dir)
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank124]:     self.model_wrapped.save_checkpoint(output_dir)
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank124]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank124]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank124]:     return func(*args, **kwargs)
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank124]:     return cdb.barrier(group=group, async_op=async_op)
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank124]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank124]:     return func(*args, **kwargs)
[rank124]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank124]:     work = group.barrier(opts=opts)
[rank124]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 124. 
[rank126]:[E217 15:05:49.983926478 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 126] Process group watchdog thread terminated with exception: [Rank 126] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600096 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x727514f2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7274ca22a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7274ca231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7274ca23361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72751566d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x727519894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x727519926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 126] Process group watchdog thread terminated with exception: [Rank 126] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600096 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x727514f2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7274ca22a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7274ca231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7274ca23361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72751566d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x727519894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x727519926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x727514f2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7274c9ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x72751566d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x727519894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x727519926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank124]:[E217 15:05:49.987759051 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 124] Process group watchdog thread terminated with exception: [Rank 124] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600072 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x794c77176446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x794c2c42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x794c2c431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x794c2c43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x794c778585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x794c7ba94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x794c7bb26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 124] Process group watchdog thread terminated with exception: [Rank 124] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600072 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x794c77176446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x794c2c42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x794c2c431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x794c2c43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x794c778585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x794c7ba94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x794c7bb26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x794c77176446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x794c2c0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x794c778585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x794c7ba94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x794c7bb26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank54]:[E217 15:05:50.939275523 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 54] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank54]:[E217 15:05:50.939301004 ProcessGroupNCCL.cpp:630] [Rank 54] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank54]:[E217 15:05:50.939306064 ProcessGroupNCCL.cpp:636] [Rank 54] To avoid data inconsistency, we are taking the entire process down.
[rank50]:[E217 15:05:50.940455878 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 50] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank50]:[E217 15:05:50.940485299 ProcessGroupNCCL.cpp:630] [Rank 50] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank50]:[E217 15:05:50.940490869 ProcessGroupNCCL.cpp:636] [Rank 50] To avoid data inconsistency, we are taking the entire process down.
[rank54]: Traceback (most recent call last):
[rank54]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank54]:     train(attn_implementation="flash_attention_2")
[rank54]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank54]:     trainer.train()
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank54]:     return inner_training_loop(
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank54]:     self._maybe_log_save_evaluate(
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank54]:     self._save_checkpoint(model, trial)
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank54]:     self._save_optimizer_and_scheduler(output_dir)
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank54]:     self.model_wrapped.save_checkpoint(output_dir)
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank54]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank54]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank54]:     return func(*args, **kwargs)
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank54]:     return cdb.barrier(group=group, async_op=async_op)
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank54]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank54]:     return func(*args, **kwargs)
[rank54]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank54]:     work = group.barrier(opts=opts)
[rank54]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 54. 
[rank50]: Traceback (most recent call last):
[rank50]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank50]:     train(attn_implementation="flash_attention_2")
[rank50]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank50]:     trainer.train()
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank50]:     return inner_training_loop(
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank50]:     self._maybe_log_save_evaluate(
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank50]:     self._save_checkpoint(model, trial)
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank50]:     self._save_optimizer_and_scheduler(output_dir)
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank50]:     self.model_wrapped.save_checkpoint(output_dir)
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank50]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank50]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank50]:     return func(*args, **kwargs)
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank50]:     return cdb.barrier(group=group, async_op=async_op)
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank50]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank50]:     return func(*args, **kwargs)
[rank50]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank50]:     work = group.barrier(opts=opts)
[rank50]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 50. 
[rank50]:[E217 15:05:50.007388741 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 50] Process group watchdog thread terminated with exception: [Rank 50] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x797406b76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7973bbe2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7973bbe31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7973bbe3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7974072585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x79740b494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x79740b526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 50] Process group watchdog thread terminated with exception: [Rank 50] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x797406b76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7973bbe2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7973bbe31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7973bbe3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7974072585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x79740b494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x79740b526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x797406b76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7973bbaa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7974072585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x79740b494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x79740b526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank54]:[E217 15:05:50.014136695 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 54] Process group watchdog thread terminated with exception: [Rank 54] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x731920993446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7318d5c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7318d5c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7318d5c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x731920aee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x731925294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x731925326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 54] Process group watchdog thread terminated with exception: [Rank 54] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x731920993446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7318d5c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7318d5c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7318d5c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x731920aee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x731925294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x731925326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x731920993446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7318d58a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x731920aee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x731925294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x731925326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank45]:[E217 15:05:50.350120678 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 45] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank45]:[E217 15:05:50.350152039 ProcessGroupNCCL.cpp:630] [Rank 45] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank45]:[E217 15:05:50.350157860 ProcessGroupNCCL.cpp:636] [Rank 45] To avoid data inconsistency, we are taking the entire process down.
[rank45]:[E217 15:05:50.352133030 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 45] Process group watchdog thread terminated with exception: [Rank 45] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75838416c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75833982a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x758339831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75833983361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7583852565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x758388e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x758388f26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 45] Process group watchdog thread terminated with exception: [Rank 45] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75838416c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75833982a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x758339831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75833983361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7583852565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x758388e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x758388f26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75838416c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7583394a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7583852565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x758388e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x758388f26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank11]:[E217 15:05:50.354109204 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 11] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank11]:[E217 15:05:50.354139124 ProcessGroupNCCL.cpp:630] [Rank 11] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank11]:[E217 15:05:50.354144375 ProcessGroupNCCL.cpp:636] [Rank 11] To avoid data inconsistency, we are taking the entire process down.
[rank11]: Traceback (most recent call last):
[rank11]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank11]:     train(attn_implementation="flash_attention_2")
[rank11]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank11]:     trainer.train()
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank11]:     return inner_training_loop(
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank11]:     self._maybe_log_save_evaluate(
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank11]:     self._save_checkpoint(model, trial)
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank11]:     self._save_optimizer_and_scheduler(output_dir)
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank11]:     self.model_wrapped.save_checkpoint(output_dir)
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank11]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank11]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank11]:     return func(*args, **kwargs)
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank11]:     return cdb.barrier(group=group, async_op=async_op)
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank11]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank11]:     return func(*args, **kwargs)
[rank11]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank11]:     work = group.barrier(opts=opts)
[rank11]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 11. 
[rank11]:[E217 15:05:50.416926478 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 11] Process group watchdog thread terminated with exception: [Rank 11] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600065 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7764ed36c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7764a2a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7764a2a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7764a2a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7764ee4565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7764f2094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7764f2126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 11] Process group watchdog thread terminated with exception: [Rank 11] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600065 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7764ed36c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7764a2a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7764a2a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7764a2a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7764ee4565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7764f2094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7764f2126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7764ed36c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7764a26a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7764ee4565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7764f2094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7764f2126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank49]:[E217 15:05:50.162111452 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 49] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank49]:[E217 15:05:50.162134632 ProcessGroupNCCL.cpp:630] [Rank 49] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank49]:[E217 15:05:50.162139572 ProcessGroupNCCL.cpp:636] [Rank 49] To avoid data inconsistency, we are taking the entire process down.
[rank29]:[E217 15:05:50.270130809 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 29] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank29]:[E217 15:05:50.270161051 ProcessGroupNCCL.cpp:630] [Rank 29] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank29]:[E217 15:05:50.270166171 ProcessGroupNCCL.cpp:636] [Rank 29] To avoid data inconsistency, we are taking the entire process down.
[rank51]:[E217 15:05:50.167679351 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 51] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank51]:[E217 15:05:50.167705771 ProcessGroupNCCL.cpp:630] [Rank 51] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank51]:[E217 15:05:50.167711071 ProcessGroupNCCL.cpp:636] [Rank 51] To avoid data inconsistency, we are taking the entire process down.
[rank53]:[E217 15:05:50.171777069 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 53] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank53]:[E217 15:05:50.171792359 ProcessGroupNCCL.cpp:630] [Rank 53] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank53]:[E217 15:05:50.171798889 ProcessGroupNCCL.cpp:636] [Rank 53] To avoid data inconsistency, we are taking the entire process down.
[rank55]:[E217 15:05:50.174823244 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 55] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank55]:[E217 15:05:50.174849124 ProcessGroupNCCL.cpp:630] [Rank 55] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank55]:[E217 15:05:50.174854454 ProcessGroupNCCL.cpp:636] [Rank 55] To avoid data inconsistency, we are taking the entire process down.
[rank47]:[E217 15:05:50.536505122 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 47] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank47]:[E217 15:05:50.536530633 ProcessGroupNCCL.cpp:630] [Rank 47] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank47]:[E217 15:05:50.536535824 ProcessGroupNCCL.cpp:636] [Rank 47] To avoid data inconsistency, we are taking the entire process down.
[rank29]:[E217 15:05:50.318020759 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 29] Process group watchdog thread terminated with exception: [Rank 29] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71f8fa56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x71f8afc2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x71f8afc31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x71f8afc3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x71f8fa9635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x71f8ff094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x71f8ff126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 29] Process group watchdog thread terminated with exception: [Rank 29] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71f8fa56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x71f8afc2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x71f8afc31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x71f8afc3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x71f8fa9635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x71f8ff094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x71f8ff126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71f8fa56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x71f8af8a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x71f8fa9635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x71f8ff094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x71f8ff126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank49]: Traceback (most recent call last):
[rank49]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank49]:     train(attn_implementation="flash_attention_2")
[rank49]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank49]:     trainer.train()
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank49]:     return inner_training_loop(
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank49]:     self._maybe_log_save_evaluate(
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank49]:     self._save_checkpoint(model, trial)
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank49]:     self._save_optimizer_and_scheduler(output_dir)
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank49]:     self.model_wrapped.save_checkpoint(output_dir)
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank49]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank49]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank49]:     return func(*args, **kwargs)
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank49]:     return cdb.barrier(group=group, async_op=async_op)
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank49]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank49]:     return func(*args, **kwargs)
[rank49]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank49]:     work = group.barrier(opts=opts)
[rank49]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 49. 
[rank43]:[E217 15:05:50.547030661 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 43] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank43]:[E217 15:05:50.547061303 ProcessGroupNCCL.cpp:630] [Rank 43] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank43]:[E217 15:05:50.547070534 ProcessGroupNCCL.cpp:636] [Rank 43] To avoid data inconsistency, we are taking the entire process down.
[rank53]:[E217 15:05:50.219256025 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 53] Process group watchdog thread terminated with exception: [Rank 53] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ff0eabb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7ff09fe2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7ff09fe31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7ff09fe3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7ff0eb66c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7ff0ef494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7ff0ef526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 53] Process group watchdog thread terminated with exception: [Rank 53] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ff0eabb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7ff09fe2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7ff09fe31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7ff09fe3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7ff0eb66c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7ff0ef494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7ff0ef526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ff0eabb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7ff09faa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7ff0eb66c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7ff0ef494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7ff0ef526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank51]: Traceback (most recent call last):
[rank51]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank51]:     train(attn_implementation="flash_attention_2")
[rank51]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank51]:     trainer.train()
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank51]:     return inner_training_loop(
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank51]:     self._maybe_log_save_evaluate(
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank51]:     self._save_checkpoint(model, trial)
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank51]:     self._save_optimizer_and_scheduler(output_dir)
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank51]:     self.model_wrapped.save_checkpoint(output_dir)
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank51]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank51]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank51]:     return func(*args, **kwargs)
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank51]:     return cdb.barrier(group=group, async_op=async_op)
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank51]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank51]:     return func(*args, **kwargs)
[rank51]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank51]:     work = group.barrier(opts=opts)
[rank51]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 51. 
[rank55]:[E217 15:05:50.223267890 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 55] Process group watchdog thread terminated with exception: [Rank 55] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600028 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75f245d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75f1fb42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75f1fb431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75f1fb43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75f2461635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75f24a894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75f24a926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 55] Process group watchdog thread terminated with exception: [Rank 55] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600028 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75f245d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75f1fb42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75f1fb431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75f1fb43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75f2461635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75f24a894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75f24a926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75f245d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x75f1fb0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x75f2461635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x75f24a894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x75f24a926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank49]:[E217 15:05:50.228990103 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 49] Process group watchdog thread terminated with exception: [Rank 49] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x728d03993446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x728cb8c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x728cb8c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x728cb8c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x728d03aee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x728d08294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x728d08326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 49] Process group watchdog thread terminated with exception: [Rank 49] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x728d03993446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x728cb8c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x728cb8c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x728cb8c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x728d03aee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x728d08294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x728d08326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x728d03993446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x728cb88a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x728d03aee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x728d08294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x728d08326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank13]:[E217 15:05:50.507117162 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 13] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank13]:[E217 15:05:50.507140423 ProcessGroupNCCL.cpp:630] [Rank 13] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank13]:[E217 15:05:50.507145923 ProcessGroupNCCL.cpp:636] [Rank 13] To avoid data inconsistency, we are taking the entire process down.
[rank51]:[E217 15:05:50.245178979 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 51] Process group watchdog thread terminated with exception: [Rank 51] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600029 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a467fdb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a463502a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a4635031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a463503361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a46808665c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a4684694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a4684726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 51] Process group watchdog thread terminated with exception: [Rank 51] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600029 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a467fdb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a463502a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a4635031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a463503361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a46808665c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a4684694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a4684726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a467fdb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7a4634ca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7a46808665c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7a4684694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7a4684726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank47]:[E217 15:05:50.585317595 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 47] Process group watchdog thread terminated with exception: [Rank 47] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600089 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d572ad93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7d56e002a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7d56e0031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7d56e003361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7d572aeee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7d572f694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7d572f726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 47] Process group watchdog thread terminated with exception: [Rank 47] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600089 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d572ad93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7d56e002a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7d56e0031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7d56e003361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7d572aeee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7d572f694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7d572f726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d572ad93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7d56dfca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7d572aeee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7d572f694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7d572f726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank77]:[E217 15:05:50.511493526 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 77] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank77]:[E217 15:05:50.511522407 ProcessGroupNCCL.cpp:630] [Rank 77] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank77]:[E217 15:05:50.511527428 ProcessGroupNCCL.cpp:636] [Rank 77] To avoid data inconsistency, we are taking the entire process down.
[rank52]:[E217 15:05:50.265712229 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 52] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank52]:[E217 15:05:50.265738389 ProcessGroupNCCL.cpp:630] [Rank 52] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank52]:[E217 15:05:50.265744460 ProcessGroupNCCL.cpp:636] [Rank 52] To avoid data inconsistency, we are taking the entire process down.
[rank43]: Traceback (most recent call last):
[rank43]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank43]:     train(attn_implementation="flash_attention_2")
[rank43]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank43]:     trainer.train()
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank43]:     return inner_training_loop(
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank43]:     self._maybe_log_save_evaluate(
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank43]:     self._save_checkpoint(model, trial)
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank43]:     self._save_optimizer_and_scheduler(output_dir)
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank43]:     self.model_wrapped.save_checkpoint(output_dir)
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank43]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank43]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank43]:     return func(*args, **kwargs)
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank43]:     return cdb.barrier(group=group, async_op=async_op)
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank43]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank43]:     return func(*args, **kwargs)
[rank43]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank43]:     work = group.barrier(opts=opts)
[rank43]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 43. 
[rank36]:[E217 15:05:50.555780320 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 36] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank36]:[E217 15:05:50.555808982 ProcessGroupNCCL.cpp:630] [Rank 36] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank36]:[E217 15:05:50.555813732 ProcessGroupNCCL.cpp:636] [Rank 36] To avoid data inconsistency, we are taking the entire process down.
[rank15]:[E217 15:05:50.536058068 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 15] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank15]:[E217 15:05:50.536086708 ProcessGroupNCCL.cpp:630] [Rank 15] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank15]:[E217 15:05:50.536092248 ProcessGroupNCCL.cpp:636] [Rank 15] To avoid data inconsistency, we are taking the entire process down.
[rank42]:[E217 15:05:50.603828111 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 42] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank42]:[E217 15:05:50.603850762 ProcessGroupNCCL.cpp:630] [Rank 42] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank42]:[E217 15:05:50.603855783 ProcessGroupNCCL.cpp:636] [Rank 42] To avoid data inconsistency, we are taking the entire process down.
[rank15]:[E217 15:05:50.537982222 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 15] Process group watchdog thread terminated with exception: [Rank 15] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600039 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x79df81376446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x79df3662a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x79df36631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x79df3663361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x79df81e555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x79df85c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x79df85d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 15] Process group watchdog thread terminated with exception: [Rank 15] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600039 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x79df81376446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x79df3662a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x79df36631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x79df3663361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x79df81e555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x79df85c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x79df85d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x79df81376446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x79df362a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x79df81e555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x79df85c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x79df85d26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank44]:[E217 15:05:50.608104020 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 44] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank44]:[E217 15:05:50.608127002 ProcessGroupNCCL.cpp:630] [Rank 44] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank44]:[E217 15:05:50.608131812 ProcessGroupNCCL.cpp:636] [Rank 44] To avoid data inconsistency, we are taking the entire process down.
[rank116]:[E217 15:05:50.467713374 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 116] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank116]:[E217 15:05:50.467743826 ProcessGroupNCCL.cpp:630] [Rank 116] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank116]:[E217 15:05:50.467749446 ProcessGroupNCCL.cpp:636] [Rank 116] To avoid data inconsistency, we are taking the entire process down.
[rank41]:[E217 15:05:50.608249319 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 41] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank41]:[E217 15:05:50.608265409 ProcessGroupNCCL.cpp:630] [Rank 41] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank41]:[E217 15:05:50.608269570 ProcessGroupNCCL.cpp:636] [Rank 41] To avoid data inconsistency, we are taking the entire process down.
[rank10]:[E217 15:05:50.541953533 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 10] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank10]:[E217 15:05:50.541975684 ProcessGroupNCCL.cpp:630] [Rank 10] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank10]:[E217 15:05:50.541980664 ProcessGroupNCCL.cpp:636] [Rank 10] To avoid data inconsistency, we are taking the entire process down.
[rank46]:[E217 15:05:50.616151641 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 46] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank46]:[E217 15:05:50.616166072 ProcessGroupNCCL.cpp:630] [Rank 46] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank46]:[E217 15:05:50.616172482 ProcessGroupNCCL.cpp:636] [Rank 46] To avoid data inconsistency, we are taking the entire process down.
[rank13]: Traceback (most recent call last):
[rank13]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank13]:     train(attn_implementation="flash_attention_2")
[rank13]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank13]:     trainer.train()
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank13]:     return inner_training_loop(
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank13]:     self._maybe_log_save_evaluate(
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank13]:     self._save_checkpoint(model, trial)
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank13]:     self._save_optimizer_and_scheduler(output_dir)
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank13]:     self.model_wrapped.save_checkpoint(output_dir)
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank13]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank13]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank13]:     return func(*args, **kwargs)
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank13]:     return cdb.barrier(group=group, async_op=async_op)
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank13]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank13]:     return func(*args, **kwargs)
[rank13]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank13]:     work = group.barrier(opts=opts)
[rank13]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 13. 
[rank38]:[E217 15:05:50.584538853 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 38] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank38]:[E217 15:05:50.584568604 ProcessGroupNCCL.cpp:630] [Rank 38] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank38]:[E217 15:05:50.584573835 ProcessGroupNCCL.cpp:636] [Rank 38] To avoid data inconsistency, we are taking the entire process down.
[rank13]:[E217 15:05:50.570693914 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 13] Process group watchdog thread terminated with exception: [Rank 13] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7cb05016c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7cb00582a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7cb005831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7cb00583361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7cb0505e45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7cb054e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7cb054f26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 13] Process group watchdog thread terminated with exception: [Rank 13] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7cb05016c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7cb00582a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7cb005831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7cb00583361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7cb0505e45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7cb054e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7cb054f26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7cb05016c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7cb0054a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7cb0505e45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7cb054e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7cb054f26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank74]:[E217 15:05:50.559858902 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 74] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank74]:[E217 15:05:50.559883203 ProcessGroupNCCL.cpp:630] [Rank 74] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank74]:[E217 15:05:50.559888753 ProcessGroupNCCL.cpp:636] [Rank 74] To avoid data inconsistency, we are taking the entire process down.
[rank75]:[E217 15:05:50.559880213 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 75] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank75]:[E217 15:05:50.559900974 ProcessGroupNCCL.cpp:630] [Rank 75] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank75]:[E217 15:05:50.559907625 ProcessGroupNCCL.cpp:636] [Rank 75] To avoid data inconsistency, we are taking the entire process down.
[rank52]:[E217 15:05:50.312042130 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 52] Process group watchdog thread terminated with exception: [Rank 52] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600037 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d8302576446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7d82b782a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7d82b7831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7d82b783361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7d8302c585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7d8306e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7d8306f26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 52] Process group watchdog thread terminated with exception: [Rank 52] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600037 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d8302576446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7d82b782a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7d82b7831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7d82b783361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7d8302c585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7d8306e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7d8306f26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d8302576446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7d82b74a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7d8302c585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7d8306e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7d8306f26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank27]:[E217 15:05:50.421170456 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 27] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank27]:[E217 15:05:50.421200528 ProcessGroupNCCL.cpp:630] [Rank 27] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank27]:[E217 15:05:50.421206088 ProcessGroupNCCL.cpp:636] [Rank 27] To avoid data inconsistency, we are taking the entire process down.
[rank36]:[E217 15:05:50.600186696 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 36] Process group watchdog thread terminated with exception: [Rank 36] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600026 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7665e0ae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x766595e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x766595e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x766595e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7665e12735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7665e5494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7665e5526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 36] Process group watchdog thread terminated with exception: [Rank 36] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600026 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7665e0ae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x766595e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x766595e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x766595e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7665e12735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7665e5494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7665e5526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7665e0ae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x766595aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7665e12735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7665e5494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7665e5526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank77]: Traceback (most recent call last):
[rank77]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank77]:     train(attn_implementation="flash_attention_2")
[rank77]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank77]:     trainer.train()
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank77]:     return inner_training_loop(
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank77]:     self._maybe_log_save_evaluate(
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank77]:     self._save_checkpoint(model, trial)
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank77]:     self._save_optimizer_and_scheduler(output_dir)
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank77]:     self.model_wrapped.save_checkpoint(output_dir)
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank77]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank77]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank77]:     return func(*args, **kwargs)
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank77]:     return cdb.barrier(group=group, async_op=async_op)
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank77]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank77]:     return func(*args, **kwargs)
[rank77]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank77]:     work = group.barrier(opts=opts)
[rank77]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 77. 
[rank31]:[E217 15:05:50.423836360 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 31] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank31]:[E217 15:05:50.423863411 ProcessGroupNCCL.cpp:630] [Rank 31] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank31]:[E217 15:05:50.423868621 ProcessGroupNCCL.cpp:636] [Rank 31] To avoid data inconsistency, we are taking the entire process down.
[rank25]:[E217 15:05:50.425285537 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 25] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank25]:[E217 15:05:50.425309798 ProcessGroupNCCL.cpp:630] [Rank 25] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank25]:[E217 15:05:50.425316088 ProcessGroupNCCL.cpp:636] [Rank 25] To avoid data inconsistency, we are taking the entire process down.
[rank9]:[E217 15:05:50.584546423 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 9] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank9]:[E217 15:05:50.584569643 ProcessGroupNCCL.cpp:630] [Rank 9] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank9]:[E217 15:05:50.584574473 ProcessGroupNCCL.cpp:636] [Rank 9] To avoid data inconsistency, we are taking the entire process down.
[rank44]: Traceback (most recent call last):
[rank44]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank44]:     train(attn_implementation="flash_attention_2")
[rank44]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank44]:     trainer.train()
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank44]:     return inner_training_loop(
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank44]:     self._maybe_log_save_evaluate(
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank44]:     self._save_checkpoint(model, trial)
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank44]:     self._save_optimizer_and_scheduler(output_dir)
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank44]:     self.model_wrapped.save_checkpoint(output_dir)
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank44]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank44]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank44]:     return func(*args, **kwargs)
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank44]:     return cdb.barrier(group=group, async_op=async_op)
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank44]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank44]:     return func(*args, **kwargs)
[rank44]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank44]:     work = group.barrier(opts=opts)
[rank44]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 44. 
[rank41]: Traceback (most recent call last):
[rank41]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank41]:     train(attn_implementation="flash_attention_2")
[rank41]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank41]:     trainer.train()
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank41]:     return inner_training_loop(
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank41]:     self._maybe_log_save_evaluate(
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank41]:     self._save_checkpoint(model, trial)
[rank10]: Traceback (most recent call last):
[rank10]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank10]:     train(attn_implementation="flash_attention_2")
[rank10]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank10]:     trainer.train()
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank10]:     return inner_training_loop(
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank10]:     self._maybe_log_save_evaluate(
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank10]:     self._save_checkpoint(model, trial)
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank41]:     self._save_optimizer_and_scheduler(output_dir)
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank41]:     self.model_wrapped.save_checkpoint(output_dir)
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank41]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank41]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank41]:     return func(*args, **kwargs)
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank10]:     self._save_optimizer_and_scheduler(output_dir)
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank10]:     self.model_wrapped.save_checkpoint(output_dir)
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank10]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank10]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank10]:     return func(*args, **kwargs)
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank41]:     return cdb.barrier(group=group, async_op=async_op)
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank41]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank41]:     return func(*args, **kwargs)
[rank41]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank41]:     work = group.barrier(opts=opts)
[rank41]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 41. 
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank10]:     return cdb.barrier(group=group, async_op=async_op)
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank10]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank10]:     return func(*args, **kwargs)
[rank10]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank10]:     work = group.barrier(opts=opts)
[rank10]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 10. 
[rank12]:[E217 15:05:50.590041769 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 12] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank12]:[E217 15:05:50.590061910 ProcessGroupNCCL.cpp:630] [Rank 12] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank12]:[E217 15:05:50.590066550 ProcessGroupNCCL.cpp:636] [Rank 12] To avoid data inconsistency, we are taking the entire process down.
[rank77]:[E217 15:05:50.576300892 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 77] Process group watchdog thread terminated with exception: [Rank 77] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600063 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f2a4c6b5446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f2a01a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f2a01a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f2a01a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f2a4c81c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f2a51094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f2a51126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 77] Process group watchdog thread terminated with exception: [Rank 77] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600063 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f2a4c6b5446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f2a01a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f2a01a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f2a01a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f2a4c81c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f2a51094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f2a51126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f2a4c6b5446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7f2a016a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f2a4c81c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f2a51094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7f2a51126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank105]:[E217 15:05:50.751659399 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 105] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank105]:[E217 15:05:50.751686379 ProcessGroupNCCL.cpp:630] [Rank 105] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank105]:[E217 15:05:50.751691369 ProcessGroupNCCL.cpp:636] [Rank 105] To avoid data inconsistency, we are taking the entire process down.
[rank14]:[E217 15:05:50.591725408 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 14] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank14]:[E217 15:05:50.591746308 ProcessGroupNCCL.cpp:630] [Rank 14] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank14]:[E217 15:05:50.591750619 ProcessGroupNCCL.cpp:636] [Rank 14] To avoid data inconsistency, we are taking the entire process down.
[rank41]:[E217 15:05:50.658260528 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 41] Process group watchdog thread terminated with exception: [Rank 41] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600082 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75bfbc350446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75bf7162a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75bf71631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75bf7163361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75bfbc4ab5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75bfc0c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75bfc0d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank42]: Traceback (most recent call last):
[rank42]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank42]:     train(attn_implementation="flash_attention_2")
[rank42]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank42]:     trainer.train()
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank42]:     return inner_training_loop(
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank42]:     self._maybe_log_save_evaluate(
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank42]:     self._save_checkpoint(model, trial)
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank42]:     self._save_optimizer_and_scheduler(output_dir)
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank42]:     self.model_wrapped.save_checkpoint(output_dir)
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank42]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank42]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank42]:     return func(*args, **kwargs)
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank42]:     return cdb.barrier(group=group, async_op=async_op)
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank42]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank42]:     return func(*args, **kwargs)
[rank42]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank42]:     work = group.barrier(opts=opts)
[rank42]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 42. 
  what():  [PG ID 1 PG GUID 1 Rank 41] Process group watchdog thread terminated with exception: [Rank 41] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600082 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75bfbc350446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75bf7162a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75bf71631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75bf7163361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75bfbc4ab5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75bfc0c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75bfc0d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75bfbc350446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x75bf712a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x75bfbc4ab5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x75bfc0c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x75bfc0d26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank34]:[E217 15:05:50.613489285 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 34] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank34]:[E217 15:05:50.613506766 ProcessGroupNCCL.cpp:630] [Rank 34] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank34]:[E217 15:05:50.613511687 ProcessGroupNCCL.cpp:636] [Rank 34] To avoid data inconsistency, we are taking the entire process down.
[rank116]: Traceback (most recent call last):
[rank116]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank116]:     train(attn_implementation="flash_attention_2")
[rank116]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank116]:     trainer.train()
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank116]:     return inner_training_loop(
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank116]:     self._maybe_log_save_evaluate(
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank116]:     self._save_checkpoint(model, trial)
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank116]:     self._save_optimizer_and_scheduler(output_dir)
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank116]:     self.model_wrapped.save_checkpoint(output_dir)
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank116]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank116]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank116]:     return func(*args, **kwargs)
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank116]:     return cdb.barrier(group=group, async_op=async_op)
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank116]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank116]:     return func(*args, **kwargs)
[rank116]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank116]:     work = group.barrier(opts=opts)
[rank116]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 116. 
[rank46]: Traceback (most recent call last):
[rank46]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank46]:     train(attn_implementation="flash_attention_2")
[rank46]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank46]:     trainer.train()
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank46]:     return inner_training_loop(
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank46]:     self._maybe_log_save_evaluate(
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank46]:     self._save_checkpoint(model, trial)
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank46]:     self._save_optimizer_and_scheduler(output_dir)
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank46]:     self.model_wrapped.save_checkpoint(output_dir)
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank46]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank46]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank46]:     return func(*args, **kwargs)
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank46]:     return cdb.barrier(group=group, async_op=async_op)
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank46]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank46]:     return func(*args, **kwargs)
[rank46]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank46]:     work = group.barrier(opts=opts)
[rank46]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 46. 
[rank42]:[E217 15:05:50.669161569 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 42] Process group watchdog thread terminated with exception: [Rank 42] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e9ebbb6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e9e7122a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e9e71231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e9e7123361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e9ebc85c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e9ec0894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e9ec0926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 42] Process group watchdog thread terminated with exception: [Rank 42] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e9ebbb6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e9e7122a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e9e71231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank9]:[E217 15:05:50.603028568 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 9] Process group watchdog thread terminated with exception: [Rank 9] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600064 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x77b675d2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x77b62b02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x77b62b031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e9e7123361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e9ebc85c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e9ec0894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e9ec0926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e9ebbb6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7e9e70ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x77b62b03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x77b6764735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x77b67a694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x77b67a726850 in /lib/x86_64-linux-gnu/libc.so.6)

frame #2: <unknown function> + 0x145c0 (0x7e9ebc85c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7e9ec0894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7e9ec0926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 9] Process group watchdog thread terminated with exception: [Rank 9] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600064 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x77b675d2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x77b62b02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x77b62b031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x77b62b03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x77b6764735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x77b67a694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x77b67a726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x77b675d2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x77b62aca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x77b6764735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x77b67a694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x77b67a726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank74]:[E217 15:05:50.596256581 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 74] Process group watchdog thread terminated with exception: [Rank 74] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600018 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f1c63ce7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f1c1902a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f1c19031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f1c1903361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f1c644735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f1c68694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f1c68726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 74] Process group watchdog thread terminated with exception: [Rank 74] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600018 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f1c63ce7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f1c1902a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f1c19031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f1c1903361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f1c644735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f1c68694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f1c68726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f1c63ce7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7f1c18ca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f1c644735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f1c68694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7f1c68726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank46]:[E217 15:05:50.677628613 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 46] Process group watchdog thread terminated with exception: [Rank 46] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75467856c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75462dc2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75462dc31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75462dc3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7546789e45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75467d294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75467d326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 46] Process group watchdog thread terminated with exception: [Rank 46] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75467856c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75462dc2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75462dc31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75462dc3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7546789e45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75467d294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75467d326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75467856c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x75462d8a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7546789e45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x75467d294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x75467d326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank10]:[E217 15:05:50.614104772 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 10] Process group watchdog thread terminated with exception: [Rank 10] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600049 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70209416c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x70204982a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x702049831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x70204983361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x702094e5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x702098e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x702098f26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 10] Process group watchdog thread terminated with exception: [Rank 10] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600049 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70209416c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x70204982a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x702049831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x70204983361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x702094e5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x702098e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x702098f26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70209416c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7020494a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank43]:[E217 15:05:50.681119608 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 43] Process group watchdog thread terminated with exception: [Rank 43] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x720c30f6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x720be662a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x720be6631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x702094e5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x702098e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x702098f26850 in /lib/x86_64-linux-gnu/libc.so.6)

frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x720be663361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x720c31c5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x720c35a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x720c35b26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 43] Process group watchdog thread terminated with exception: [Rank 43] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x720c30f6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x720be662a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x720be6631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x720be663361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x720c31c5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x720c35a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x720c35b26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x720c30f6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x720be62a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x720c31c5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x720c35a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x720c35b26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank75]: Traceback (most recent call last):
[rank75]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank75]:     train(attn_implementation="flash_attention_2")
[rank75]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank75]:     trainer.train()
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank75]:     return inner_training_loop(
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank75]:     self._maybe_log_save_evaluate(
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank75]:     self._save_checkpoint(model, trial)
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank75]:     self._save_optimizer_and_scheduler(output_dir)
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank75]:     self.model_wrapped.save_checkpoint(output_dir)
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank75]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank75]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank75]:     return func(*args, **kwargs)
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank75]:     return cdb.barrier(group=group, async_op=async_op)
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank75]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank75]:     return func(*args, **kwargs)
[rank75]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank75]:     work = group.barrier(opts=opts)
[rank75]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 75. 
[rank38]: Traceback (most recent call last):
[rank38]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank38]:     train(attn_implementation="flash_attention_2")
[rank38]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank38]:     trainer.train()
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank38]:     return inner_training_loop(
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank38]:     self._maybe_log_save_evaluate(
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank38]:     self._save_checkpoint(model, trial)
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank38]:     self._save_optimizer_and_scheduler(output_dir)
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank38]:     self.model_wrapped.save_checkpoint(output_dir)
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank38]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank38]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank38]:     return func(*args, **kwargs)
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank38]:     return cdb.barrier(group=group, async_op=async_op)
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank38]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank38]:     return func(*args, **kwargs)
[rank38]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank38]:     work = group.barrier(opts=opts)
[rank38]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 38. 
[rank75]:[E217 15:05:51.614654767 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 75] Process group watchdog thread terminated with exception: [Rank 75] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600057 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e629af76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e625022a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e6250231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e625023361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e629ba555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e629f894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e629f926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 75] Process group watchdog thread terminated with exception: [Rank 75] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600057 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e629af76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e625022a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e6250231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e625023361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e629ba555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e629f894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e629f926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e629af76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7e624fea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank59]:[E217 15:05:51.294302454 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 59] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank59]:[E217 15:05:51.294328485 ProcessGroupNCCL.cpp:630] [Rank 59] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank59]:[E217 15:05:51.294336105 ProcessGroupNCCL.cpp:636] [Rank 59] To avoid data inconsistency, we are taking the entire process down.
frame #2: <unknown function> + 0x145c0 (0x7e629ba555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7e629f894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7e629f926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank31]:[E217 15:05:51.470930399 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 31] Process group watchdog thread terminated with exception: [Rank 31] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b1b61776446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b1b16a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b1b16a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b1b16a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b1b61e585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b1b66094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b1b66126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 31] Process group watchdog thread terminated with exception: [Rank 31] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b1b61776446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b1b16a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b1b16a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b1b16a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b1b61e585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b1b66094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b1b66126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b1b61776446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7b1b166a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7b1b61e585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7b1b66094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7b1b66126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank12]:[E217 15:05:51.633715173 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 12] Process group watchdog thread terminated with exception: [Rank 12] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73c1f0776446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73c1a5a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73c1a5a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73c1a5a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x73c1f0e585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73c1f5094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73c1f5126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank25]:[E217 15:05:51.475274719 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 25] Process group watchdog thread terminated with exception: [Rank 25] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78f895b76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78f84ae2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x78f84ae31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78f84ae3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78f8962585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x78f89a494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x78f89a526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 12] Process group watchdog thread terminated with exception: [Rank 12] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600067 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73c1f0776446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73c1a5a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73c1a5a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73c1a5a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x73c1f0e585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73c1f5094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73c1f5126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73c1f0776446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x73c1a56a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x73c1f0e585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x73c1f5094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x73c1f5126850 in /lib/x86_64-linux-gnu/libc.so.6)

  what():  [PG ID 1 PG GUID 1 Rank 25] Process group watchdog thread terminated with exception: [Rank 25] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78f895b76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78f84ae2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x78f84ae31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78f84ae3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78f8962585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x78f89a494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x78f89a526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78f895b76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x78f84aaa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x78f8962585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x78f89a494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x78f89a526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank105]:[E217 15:05:51.799228265 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 105] Process group watchdog thread terminated with exception: [Rank 105] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600072 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7cf83796c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7cf7ed02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7cf7ed031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7cf7ed03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7cf838a5d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7cf83c694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7cf83c726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 105] Process group watchdog thread terminated with exception: [Rank 105] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600072 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7cf83796c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7cf7ed02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7cf7ed031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7cf7ed03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7cf838a5d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7cf83c694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7cf83c726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7cf83796c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7cf7ecca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7cf838a5d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7cf83c694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7cf83c726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank14]: Traceback (most recent call last):
[rank14]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank14]:     train(attn_implementation="flash_attention_2")
[rank14]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank14]:     trainer.train()
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank14]:     return inner_training_loop(
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank14]:     self._maybe_log_save_evaluate(
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank14]:     self._save_checkpoint(model, trial)
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank14]:     self._save_optimizer_and_scheduler(output_dir)
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank14]:     self.model_wrapped.save_checkpoint(output_dir)
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank14]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank14]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank14]:     return func(*args, **kwargs)
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank14]:     return cdb.barrier(group=group, async_op=async_op)
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank14]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank14]:     return func(*args, **kwargs)
[rank14]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank14]:     work = group.barrier(opts=opts)
[rank14]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 14. 
[rank79]:[E217 15:05:51.629360166 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 79] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank79]:[E217 15:05:51.629382587 ProcessGroupNCCL.cpp:630] [Rank 79] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank79]:[E217 15:05:51.629387687 ProcessGroupNCCL.cpp:636] [Rank 79] To avoid data inconsistency, we are taking the entire process down.
[rank44]:[E217 15:05:51.710326853 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 44] Process group watchdog thread terminated with exception: [Rank 44] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b70c436c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b7079a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b7079a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b7079a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b70c505c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b70c9094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b70c9126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank73]:[E217 15:05:51.629950410 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 73] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank73]:[E217 15:05:51.629970962 ProcessGroupNCCL.cpp:630] [Rank 73] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank73]:[E217 15:05:51.629975132 ProcessGroupNCCL.cpp:636] [Rank 73] To avoid data inconsistency, we are taking the entire process down.
  what():  [PG ID 1 PG GUID 1 Rank 44] Process group watchdog thread terminated with exception: [Rank 44] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b70c436c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b7079a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b7079a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b7079a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b70c505c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b70c9094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b70c9126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b70c436c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7b70796a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7b70c505c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7b70c9094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7b70c9126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank34]: Traceback (most recent call last):
[rank34]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank34]:     train(attn_implementation="flash_attention_2")
[rank34]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank34]:     trainer.train()
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank34]:     return inner_training_loop(
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank34]:     self._maybe_log_save_evaluate(
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank34]:     self._save_checkpoint(model, trial)
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank34]:     self._save_optimizer_and_scheduler(output_dir)
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank34]:     self.model_wrapped.save_checkpoint(output_dir)
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank34]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank34]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank34]:     return func(*args, **kwargs)
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank34]:     return cdb.barrier(group=group, async_op=async_op)
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank34]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank34]:     return func(*args, **kwargs)
[rank34]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank34]:     work = group.barrier(opts=opts)
[rank34]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 34. 
[rank38]:[E217 15:05:51.667241322 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 38] Process group watchdog thread terminated with exception: [Rank 38] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600027 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f8980b93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f8935e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f8935e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f8935e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f8980cee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f8985494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f8985526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 38] Process group watchdog thread terminated with exception: [Rank 38] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600027 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f8980b93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f8935e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f8935e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f8935e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f8980cee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f8985494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f8985526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f8980b93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7f8935aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f8980cee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f8985494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7f8985526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank27]: Traceback (most recent call last):
[rank27]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank27]:     train(attn_implementation="flash_attention_2")
[rank27]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank27]:     trainer.train()
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank27]:     return inner_training_loop(
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank27]:     self._maybe_log_save_evaluate(
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank27]:     self._save_checkpoint(model, trial)
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank27]:     self._save_optimizer_and_scheduler(output_dir)
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank27]:     self.model_wrapped.save_checkpoint(output_dir)
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank27]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank27]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank27]:     return func(*args, **kwargs)
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank27]:     return cdb.barrier(group=group, async_op=async_op)
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank27]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank27]:     return func(*args, **kwargs)
[rank27]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank27]:     work = group.barrier(opts=opts)
[rank27]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 27. 
[rank76]:[E217 15:05:51.636521969 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 76] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank76]:[E217 15:05:51.636543130 ProcessGroupNCCL.cpp:630] [Rank 76] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank76]:[E217 15:05:51.636549840 ProcessGroupNCCL.cpp:636] [Rank 76] To avoid data inconsistency, we are taking the entire process down.
[rank86]:[E217 15:05:51.778304765 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 86] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank86]:[E217 15:05:51.778331866 ProcessGroupNCCL.cpp:630] [Rank 86] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank86]:[E217 15:05:51.778337317 ProcessGroupNCCL.cpp:636] [Rank 86] To avoid data inconsistency, we are taking the entire process down.
[rank116]:[E217 15:05:51.578326348 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 116] Process group watchdog thread terminated with exception: [Rank 116] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7c30900c1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7c304542a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7c3045431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7c304543361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7c309021c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7c3094a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7c3094b26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 116] Process group watchdog thread terminated with exception: [Rank 116] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600076 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7c30900c1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7c304542a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7c3045431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank78]:[E217 15:05:51.638718168 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 78] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank78]:[E217 15:05:51.638739369 ProcessGroupNCCL.cpp:630] [Rank 78] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7c304543361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7c309021c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7c3094a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7c3094b26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7c30900c1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7c30450a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank78]:[E217 15:05:51.638744780 ProcessGroupNCCL.cpp:636] [Rank 78] To avoid data inconsistency, we are taking the entire process down.
frame #2: <unknown function> + 0x145c0 (0x7c309021c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7c3094a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7c3094b26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank14]:[E217 15:05:51.655732980 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 14] Process group watchdog thread terminated with exception: [Rank 14] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600063 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72f75bd2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72f71102a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72f711031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72f71103361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72f75c4735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72f760694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72f760726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 14] Process group watchdog thread terminated with exception: [Rank 14] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600063 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72f75bd2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72f71102a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72f711031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72f71103361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72f75c4735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72f760694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72f760726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72f75bd2a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x72f710ca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x72f75c4735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x72f760694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x72f760726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank111]:[E217 15:05:51.817696845 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 111] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank111]:[E217 15:05:51.817729576 ProcessGroupNCCL.cpp:630] [Rank 111] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank111]:[E217 15:05:51.817735626 ProcessGroupNCCL.cpp:636] [Rank 111] To avoid data inconsistency, we are taking the entire process down.
[rank34]:[E217 15:05:51.680211644 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 34] Process group watchdog thread terminated with exception: [Rank 34] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72d0f516c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72d0aa82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72d0aa831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72d0aa83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72d0f5e5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72d0f9e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72d0f9f26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 34] Process group watchdog thread terminated with exception: [Rank 34] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72d0f516c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72d0aa82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72d0aa831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72d0aa83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72d0f5e5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72d0f9e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72d0f9f26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72d0f516c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x72d0aa4a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x72d0f5e5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x72d0f9e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x72d0f9f26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank109]:[E217 15:05:51.828771591 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 109] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank109]:[E217 15:05:51.828790561 ProcessGroupNCCL.cpp:630] [Rank 109] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank109]:[E217 15:05:51.828795071 ProcessGroupNCCL.cpp:636] [Rank 109] To avoid data inconsistency, we are taking the entire process down.
[rank27]:[E217 15:05:51.511299245 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 27] Process group watchdog thread terminated with exception: [Rank 27] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d79292bc446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7d78de62a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7d78de631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7d78de63361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7d79294175c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7d792dc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7d792dd26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 27] Process group watchdog thread terminated with exception: [Rank 27] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d79292bc446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7d78de62a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7d78de631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7d78de63361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7d79294175c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7d792dc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7d792dd26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d79292bc446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7d78de2a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7d79294175c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7d792dc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7d792dd26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank59]:[E217 15:05:51.341367263 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 59] Process group watchdog thread terminated with exception: [Rank 59] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600049 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x769a010e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7699b642a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7699b6431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7699b643361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x769a018735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x769a05a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x769a05b26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 59] Process group watchdog thread terminated with exception: [Rank 59] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600049 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x769a010e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7699b642a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7699b6431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7699b643361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x769a018735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x769a05a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x769a05b26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x769a010e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7699b60a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x769a018735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x769a05a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x769a05b26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank76]:[E217 15:05:51.676154809 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 76] Process group watchdog thread terminated with exception: [Rank 76] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600053 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ebbe3193446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7ebb9842a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7ebb98431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7ebb9843361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7ebbe32ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7ebbe7a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7ebbe7b26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 76] Process group watchdog thread terminated with exception: [Rank 76] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600053 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ebbe3193446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7ebb9842a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7ebb98431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7ebb9843361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7ebbe32ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7ebbe7a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7ebbe7b26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ebbe3193446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7ebb980a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7ebbe32ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7ebbe7a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7ebbe7b26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank73]: Traceback (most recent call last):
[rank73]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank73]:     train(attn_implementation="flash_attention_2")
[rank73]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank73]:     trainer.train()
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank73]:     return inner_training_loop(
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank73]:     self._maybe_log_save_evaluate(
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank73]:     self._save_checkpoint(model, trial)
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank73]:     self._save_optimizer_and_scheduler(output_dir)
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank73]:     self.model_wrapped.save_checkpoint(output_dir)
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank73]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank73]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank73]:     return func(*args, **kwargs)
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank73]:     return cdb.barrier(group=group, async_op=async_op)
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank73]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank73]:     return func(*args, **kwargs)
[rank73]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank73]:     work = group.barrier(opts=opts)
[rank73]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 73. 
[rank33]:[E217 15:05:51.717907617 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 33] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank33]:[E217 15:05:51.717934208 ProcessGroupNCCL.cpp:630] [Rank 33] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank33]:[E217 15:05:51.717939768 ProcessGroupNCCL.cpp:636] [Rank 33] To avoid data inconsistency, we are taking the entire process down.
[rank79]: Traceback (most recent call last):
[rank79]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank79]:     train(attn_implementation="flash_attention_2")
[rank79]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank79]:     trainer.train()
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank79]:     return inner_training_loop(
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank79]:     self._maybe_log_save_evaluate(
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank79]:     self._save_checkpoint(model, trial)
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank79]:     self._save_optimizer_and_scheduler(output_dir)
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank79]:     self.model_wrapped.save_checkpoint(output_dir)
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank79]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank79]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank79]:     return func(*args, **kwargs)
[rank35]:[E217 15:05:51.718880928 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 35] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank35]:[E217 15:05:51.718900769 ProcessGroupNCCL.cpp:630] [Rank 35] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank35]:[E217 15:05:51.718905829 ProcessGroupNCCL.cpp:636] [Rank 35] To avoid data inconsistency, we are taking the entire process down.
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank79]:     return cdb.barrier(group=group, async_op=async_op)
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank79]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank79]:     return func(*args, **kwargs)
[rank79]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank79]:     work = group.barrier(opts=opts)
[rank79]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 79. 
[rank73]:[E217 15:05:51.694557376 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 73] Process group watchdog thread terminated with exception: [Rank 73] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600060 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x76765096a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x767605c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x767605c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x767605c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7676510585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x767655294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x767655326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 73] Process group watchdog thread terminated with exception: [Rank 73] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600060 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x76765096a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x767605c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x767605c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x767605c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7676510585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x767655294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x767655326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x76765096a446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7676058a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7676510585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x767655294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x767655326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank106]:[E217 15:05:51.869899372 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 106] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank106]:[E217 15:05:51.869925943 ProcessGroupNCCL.cpp:630] [Rank 106] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank106]:[E217 15:05:51.869933323 ProcessGroupNCCL.cpp:636] [Rank 106] To avoid data inconsistency, we are taking the entire process down.
[rank78]: Traceback (most recent call last):
[rank78]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank78]:     train(attn_implementation="flash_attention_2")
[rank78]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank78]:     trainer.train()
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank78]:     return inner_training_loop(
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank78]:     self._maybe_log_save_evaluate(
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank78]:     self._save_checkpoint(model, trial)
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank78]:     self._save_optimizer_and_scheduler(output_dir)
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank78]:     self.model_wrapped.save_checkpoint(output_dir)
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank78]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank78]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank78]:     return func(*args, **kwargs)
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank78]:     return cdb.barrier(group=group, async_op=async_op)
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank78]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank78]:     return func(*args, **kwargs)
[rank78]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank78]:     work = group.barrier(opts=opts)
[rank78]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 78. 
[rank86]: Traceback (most recent call last):
[rank86]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank86]:     train(attn_implementation="flash_attention_2")
[rank86]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank86]:     trainer.train()
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank86]:     return inner_training_loop(
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank86]:     self._maybe_log_save_evaluate(
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank86]:     self._save_checkpoint(model, trial)
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank86]:     self._save_optimizer_and_scheduler(output_dir)
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank86]:     self.model_wrapped.save_checkpoint(output_dir)
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank86]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank86]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank86]:     return func(*args, **kwargs)
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank86]:     return cdb.barrier(group=group, async_op=async_op)
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank86]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank86]:     return func(*args, **kwargs)
[rank86]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank86]:     work = group.barrier(opts=opts)
[rank86]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 86. 
[rank111]: Traceback (most recent call last):
[rank111]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank111]:     train(attn_implementation="flash_attention_2")
[rank111]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank111]:     trainer.train()
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank111]:     return inner_training_loop(
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank111]:     self._maybe_log_save_evaluate(
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank111]:     self._save_checkpoint(model, trial)
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank111]:     self._save_optimizer_and_scheduler(output_dir)
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank111]:     self.model_wrapped.save_checkpoint(output_dir)
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank111]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank111]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank111]:     return func(*args, **kwargs)
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank111]:     return cdb.barrier(group=group, async_op=async_op)
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank111]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank111]:     return func(*args, **kwargs)
[rank111]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank111]:     work = group.barrier(opts=opts)
[rank111]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 111. 
[rank109]: Traceback (most recent call last):
[rank109]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank109]:     train(attn_implementation="flash_attention_2")
[rank109]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank109]:     trainer.train()
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank109]:     return inner_training_loop(
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank109]:     self._maybe_log_save_evaluate(
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank109]:     self._save_checkpoint(model, trial)
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank109]:     self._save_optimizer_and_scheduler(output_dir)
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank109]:     self.model_wrapped.save_checkpoint(output_dir)
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank109]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank109]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank109]:     return func(*args, **kwargs)
[rank79]:[E217 15:05:51.708376481 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 79] Process group watchdog thread terminated with exception: [Rank 79] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x722418f93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7223ce22a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7223ce231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank109]:     return cdb.barrier(group=group, async_op=async_op)
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank109]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank109]:     return func(*args, **kwargs)
[rank109]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank109]:     work = group.barrier(opts=opts)
[rank109]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 109. 
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7223ce23361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7224190ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72241d894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72241d926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 79] Process group watchdog thread terminated with exception: [Rank 79] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600055 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x722418f93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7223ce22a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7223ce231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7223ce23361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7224190ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72241d894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72241d926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x722418f93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7223cdea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7224190ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x72241d894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x72241d926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank111]:[E217 15:05:51.883704901 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 111] Process group watchdog thread terminated with exception: [Rank 111] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x74aa80d76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x74aa3602a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x74aa36031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x74aa3603361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x74aa818555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x74aa85694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x74aa85726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 111] Process group watchdog thread terminated with exception: [Rank 111] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x74aa80d76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x74aa3602a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x74aa36031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x74aa3603361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x74aa818555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x74aa85694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x74aa85726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x74aa80d76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x74aa35ca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x74aa818555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x74aa85694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x74aa85726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank86]:[E217 15:05:51.855812304 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 86] Process group watchdog thread terminated with exception: [Rank 86] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600061 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d1da82db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7d1d5d62a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7d1d5d631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7d1d5d63361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7d1da8e525c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7d1dacc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7d1dacd26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 86] Process group watchdog thread terminated with exception: [Rank 86] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600061 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d1da82db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7d1d5d62a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7d1d5d631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7d1d5d63361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7d1da8e525c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7d1dacc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7d1dacd26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7d1da82db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7d1d5d2a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7d1da8e525c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7d1dacc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7d1dacd26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank26]:[E217 15:05:51.576825283 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 26] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank26]:[E217 15:05:51.576849444 ProcessGroupNCCL.cpp:630] [Rank 26] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank26]:[E217 15:05:51.576856165 ProcessGroupNCCL.cpp:636] [Rank 26] To avoid data inconsistency, we are taking the entire process down.
[rank30]:[E217 15:05:51.577057602 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 30] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank30]:[E217 15:05:51.577087963 ProcessGroupNCCL.cpp:630] [Rank 30] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank30]:[E217 15:05:51.577094604 ProcessGroupNCCL.cpp:636] [Rank 30] To avoid data inconsistency, we are taking the entire process down.
[rank28]:[E217 15:05:51.578532650 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 28] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank28]:[E217 15:05:51.578545871 ProcessGroupNCCL.cpp:630] [Rank 28] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank28]:[E217 15:05:51.578549641 ProcessGroupNCCL.cpp:636] [Rank 28] To avoid data inconsistency, we are taking the entire process down.
[rank109]:[E217 15:05:51.898153343 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 109] Process group watchdog thread terminated with exception: [Rank 109] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600086 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72e9792e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72e92e62a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72e92e631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72e92e63361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72e979a6d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72e97dc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72e97dd26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 109] Process group watchdog thread terminated with exception: [Rank 109] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600086 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72e9792e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72e92e62a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72e92e631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72e92e63361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72e979a6d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72e97dc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72e97dd26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72e9792e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x72e92e2a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x72e979a6d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x72e97dc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x72e97dd26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank33]: Traceback (most recent call last):
[rank33]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank33]:     train(attn_implementation="flash_attention_2")
[rank33]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank33]:     trainer.train()
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank33]:     return inner_training_loop(
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank33]:     self._maybe_log_save_evaluate(
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank33]:     self._save_checkpoint(model, trial)
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank33]:     self._save_optimizer_and_scheduler(output_dir)
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank33]:     self.model_wrapped.save_checkpoint(output_dir)
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank33]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank33]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank33]:     return func(*args, **kwargs)
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank33]:     return cdb.barrier(group=group, async_op=async_op)
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank33]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank33]:     return func(*args, **kwargs)
[rank33]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank33]:     work = group.barrier(opts=opts)
[rank33]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 33. 
[rank118]:[E217 15:05:51.671968456 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 118] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank118]:[E217 15:05:51.671990017 ProcessGroupNCCL.cpp:630] [Rank 118] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank118]:[E217 15:05:51.671995077 ProcessGroupNCCL.cpp:636] [Rank 118] To avoid data inconsistency, we are taking the entire process down.
[rank114]:[E217 15:05:51.672088432 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 114] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank114]:[E217 15:05:51.672107353 ProcessGroupNCCL.cpp:630] [Rank 114] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank114]:[E217 15:05:51.672112103 ProcessGroupNCCL.cpp:636] [Rank 114] To avoid data inconsistency, we are taking the entire process down.
[rank33]:[E217 15:05:51.767034830 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 33] Process group watchdog thread terminated with exception: [Rank 33] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600031 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fce09d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7fcdbf42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7fcdbf431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7fcdbf43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7fce0a1635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7fce0e894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7fce0e926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 33] Process group watchdog thread terminated with exception: [Rank 33] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600031 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fce09d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7fcdbf42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7fcdbf431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7fcdbf43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7fce0a1635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7fce0e894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7fce0e926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fce09d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7fcdbf0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7fce0a1635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7fce0e894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7fce0e926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank98]:[E217 15:05:51.395227108 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 98] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank98]:[E217 15:05:51.395257909 ProcessGroupNCCL.cpp:630] [Rank 98] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank98]:[E217 15:05:51.395265849 ProcessGroupNCCL.cpp:636] [Rank 98] To avoid data inconsistency, we are taking the entire process down.
[rank100]:[E217 15:05:51.397555973 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 100] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank100]:[E217 15:05:51.397574793 ProcessGroupNCCL.cpp:630] [Rank 100] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank100]:[E217 15:05:51.397580273 ProcessGroupNCCL.cpp:636] [Rank 100] To avoid data inconsistency, we are taking the entire process down.
[rank22]:[E217 15:05:51.004420757 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 22] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank22]:[E217 15:05:51.004441309 ProcessGroupNCCL.cpp:630] [Rank 22] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank22]:[E217 15:05:51.004445959 ProcessGroupNCCL.cpp:636] [Rank 22] To avoid data inconsistency, we are taking the entire process down.
[rank35]: Traceback (most recent call last):
[rank35]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank35]:     train(attn_implementation="flash_attention_2")
[rank35]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank35]:     trainer.train()
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank35]:     return inner_training_loop(
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank35]:     self._maybe_log_save_evaluate(
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank35]:     self._save_checkpoint(model, trial)
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank35]:     self._save_optimizer_and_scheduler(output_dir)
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank35]:     self.model_wrapped.save_checkpoint(output_dir)
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank35]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank35]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank35]:     return func(*args, **kwargs)
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank35]:     return cdb.barrier(group=group, async_op=async_op)
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank35]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank35]:     return func(*args, **kwargs)
[rank35]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank35]:     work = group.barrier(opts=opts)
[rank35]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 35. 
[rank106]: Traceback (most recent call last):
[rank106]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank106]:     train(attn_implementation="flash_attention_2")
[rank106]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank106]:     trainer.train()
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank106]:     return inner_training_loop(
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank106]:     self._maybe_log_save_evaluate(
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank106]:     self._save_checkpoint(model, trial)
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank106]:     self._save_optimizer_and_scheduler(output_dir)
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank106]:     self.model_wrapped.save_checkpoint(output_dir)
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank106]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank106]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank106]:     return func(*args, **kwargs)
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank106]:     return cdb.barrier(group=group, async_op=async_op)
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank106]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank106]:     return func(*args, **kwargs)
[rank106]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank106]:     work = group.barrier(opts=opts)
[rank106]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 106. 
[rank107]:[E217 15:05:51.921060869 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 107] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank107]:[E217 15:05:51.921084640 ProcessGroupNCCL.cpp:630] [Rank 107] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank107]:[E217 15:05:51.921090500 ProcessGroupNCCL.cpp:636] [Rank 107] To avoid data inconsistency, we are taking the entire process down.
[rank57]:[E217 15:05:51.426302725 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 57] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank57]:[E217 15:05:51.426332337 ProcessGroupNCCL.cpp:630] [Rank 57] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank57]:[E217 15:05:51.426337897 ProcessGroupNCCL.cpp:636] [Rank 57] To avoid data inconsistency, we are taking the entire process down.
[rank108]:[E217 15:05:51.927524675 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 108] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank108]:[E217 15:05:51.927544666 ProcessGroupNCCL.cpp:630] [Rank 108] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank108]:[E217 15:05:51.927549716 ProcessGroupNCCL.cpp:636] [Rank 108] To avoid data inconsistency, we are taking the entire process down.
[rank110]:[E217 15:05:51.929655007 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 110] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank110]:[E217 15:05:51.929679997 ProcessGroupNCCL.cpp:630] [Rank 110] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank110]:[E217 15:05:51.929685137 ProcessGroupNCCL.cpp:636] [Rank 110] To avoid data inconsistency, we are taking the entire process down.
[rank66]:[E217 15:05:51.563264139 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 66] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank66]:[E217 15:05:51.563292910 ProcessGroupNCCL.cpp:630] [Rank 66] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank66]:[E217 15:05:51.563300410 ProcessGroupNCCL.cpp:636] [Rank 66] To avoid data inconsistency, we are taking the entire process down.
[rank61]:[E217 15:05:51.443038563 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 61] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank61]:[E217 15:05:51.443059194 ProcessGroupNCCL.cpp:630] [Rank 61] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank61]:[E217 15:05:51.443064304 ProcessGroupNCCL.cpp:636] [Rank 61] To avoid data inconsistency, we are taking the entire process down.
[rank30]: Traceback (most recent call last):
[rank30]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank30]:     train(attn_implementation="flash_attention_2")
[rank30]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank30]:     trainer.train()
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank30]:     return inner_training_loop(
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank30]:     self._maybe_log_save_evaluate(
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank30]:     self._save_checkpoint(model, trial)
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank30]:     self._save_optimizer_and_scheduler(output_dir)
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank30]:     self.model_wrapped.save_checkpoint(output_dir)
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank30]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank30]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank30]:     return func(*args, **kwargs)
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank30]:     return cdb.barrier(group=group, async_op=async_op)
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank30]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank30]:     return func(*args, **kwargs)
[rank30]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank30]:     work = group.barrier(opts=opts)
[rank30]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 30. 
[rank26]:[E217 15:05:51.623675553 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 26] Process group watchdog thread terminated with exception: [Rank 26] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7096a29b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x709657c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x709657c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x709657c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7096a346c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7096a7294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7096a7326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank26]: Traceback (most recent call last):
[rank26]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank26]:     train(attn_implementation="flash_attention_2")
[rank26]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank26]:     trainer.train()
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank26]:     return inner_training_loop(
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank26]:     self._maybe_log_save_evaluate(
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank26]:     self._save_checkpoint(model, trial)
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank26]:     self._save_optimizer_and_scheduler(output_dir)
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank26]:     self.model_wrapped.save_checkpoint(output_dir)
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank26]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank26]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank26]:     return func(*args, **kwargs)
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank26]:     return cdb.barrier(group=group, async_op=async_op)
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank26]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank26]:     return func(*args, **kwargs)
[rank26]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank26]:     work = group.barrier(opts=opts)
[rank26]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 26. 
  what():  [PG ID 1 PG GUID 1 Rank 26] Process group watchdog thread terminated with exception: [Rank 26] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7096a29b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x709657c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x709657c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x709657c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7096a346c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7096a7294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7096a7326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7096a29b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7096578a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7096a346c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7096a7294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7096a7326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank117]:[E217 15:05:51.711539236 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 117] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank117]:[E217 15:05:51.711571388 ProcessGroupNCCL.cpp:630] [Rank 117] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank117]:[E217 15:05:51.711577498 ProcessGroupNCCL.cpp:636] [Rank 117] To avoid data inconsistency, we are taking the entire process down.
[rank28]: Traceback (most recent call last):
[rank28]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank28]:     train(attn_implementation="flash_attention_2")
[rank28]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank28]:     trainer.train()
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank28]:     return inner_training_loop(
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank28]:     self._maybe_log_save_evaluate(
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank28]:     self._save_checkpoint(model, trial)
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank28]:     self._save_optimizer_and_scheduler(output_dir)
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank28]:     self.model_wrapped.save_checkpoint(output_dir)
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank28]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank28]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank28]:     return func(*args, **kwargs)
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank28]:     return cdb.barrier(group=group, async_op=async_op)
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank28]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank28]:     return func(*args, **kwargs)
[rank28]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank28]:     work = group.barrier(opts=opts)
[rank28]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 28. 
[rank78]:[E217 15:05:51.775798273 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 78] Process group watchdog thread terminated with exception: [Rank 78] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ac798d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7ac74e42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7ac74e431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7ac74e43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7ac799a5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7ac79d894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7ac79d926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 78] Process group watchdog thread terminated with exception: [Rank 78] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ac798d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7ac74e42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7ac74e431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7ac74e43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7ac799a5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7ac79d894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7ac79d926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ac798d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7ac74e0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7ac799a5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7ac79d894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7ac79d926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank102]:[E217 15:05:51.439382244 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 102] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank102]:[E217 15:05:51.439406184 ProcessGroupNCCL.cpp:630] [Rank 102] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank102]:[E217 15:05:51.439410814 ProcessGroupNCCL.cpp:636] [Rank 102] To avoid data inconsistency, we are taking the entire process down.
[rank28]:[E217 15:05:51.639180268 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 28] Process group watchdog thread terminated with exception: [Rank 28] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x786ef42af446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x786ea962a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x786ea9631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x786ea963361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x786ef44165c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x786ef8c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x786ef8d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 28] Process group watchdog thread terminated with exception: [Rank 28] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x786ef42af446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x786ea962a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x786ea9631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x786ea963361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x786ef44165c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x786ef8c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x786ef8d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x786ef42af446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x786ea92a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x786ef44165c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x786ef8c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x786ef8d26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank98]: Traceback (most recent call last):
[rank98]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank98]:     train(attn_implementation="flash_attention_2")
[rank98]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank98]:     trainer.train()
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank98]:     return inner_training_loop(
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank98]:     self._maybe_log_save_evaluate(
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank98]:     self._save_checkpoint(model, trial)
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank98]:     self._save_optimizer_and_scheduler(output_dir)
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank98]:     self.model_wrapped.save_checkpoint(output_dir)
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank98]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank98]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank98]:     return func(*args, **kwargs)
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank98]:     return cdb.barrier(group=group, async_op=async_op)
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank98]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank98]:     return func(*args, **kwargs)
[rank98]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank98]:     work = group.barrier(opts=opts)
[rank98]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 98. 
[rank68]:[E217 15:05:51.589893116 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 68] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank68]:[E217 15:05:51.589923377 ProcessGroupNCCL.cpp:630] [Rank 68] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank68]:[E217 15:05:51.589928617 ProcessGroupNCCL.cpp:636] [Rank 68] To avoid data inconsistency, we are taking the entire process down.
[rank30]:[E217 15:05:51.643109861 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 30] Process group watchdog thread terminated with exception: [Rank 30] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x737f95ae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x737f4ae2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x737f4ae31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x737f4ae3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x737f962735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x737f9a494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x737f9a526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 30] Process group watchdog thread terminated with exception: [Rank 30] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600079 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x737f95ae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x737f4ae2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x737f4ae31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x737f4ae3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x737f962735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x737f9a494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x737f9a526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x737f95ae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x737f4aaa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x737f962735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x737f9a494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x737f9a526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank68]:[E217 15:05:51.591952948 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 68] Process group watchdog thread terminated with exception: [Rank 68] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600001 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72a717176446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72a6cc42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72a6cc431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72a6cc43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72a717c555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72a71ba94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72a71bb26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank37]:[E217 15:05:51.823322130 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 37] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank37]:[E217 15:05:51.823346862 ProcessGroupNCCL.cpp:630] [Rank 37] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank37]:[E217 15:05:51.823353082 ProcessGroupNCCL.cpp:636] [Rank 37] To avoid data inconsistency, we are taking the entire process down.
  what():  [PG ID 1 PG GUID 1 Rank 68] Process group watchdog thread terminated with exception: [Rank 68] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600001 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72a717176446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72a6cc42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72a6cc431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72a6cc43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72a717c555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72a71ba94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72a71bb26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72a717176446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x72a6cc0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x72a717c555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x72a71ba94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x72a71bb26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank118]: Traceback (most recent call last):
[rank118]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank118]:     train(attn_implementation="flash_attention_2")
[rank118]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank118]:     trainer.train()
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank118]:     return inner_training_loop(
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank118]:     self._maybe_log_save_evaluate(
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank118]:     self._save_checkpoint(model, trial)
[rank100]: Traceback (most recent call last):
[rank100]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank100]:     train(attn_implementation="flash_attention_2")
[rank100]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank100]:     trainer.train()
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank100]:     return inner_training_loop(
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank100]:     self._maybe_log_save_evaluate(
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank100]:     self._save_checkpoint(model, trial)
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank118]:     self._save_optimizer_and_scheduler(output_dir)
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank118]:     self.model_wrapped.save_checkpoint(output_dir)
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank118]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank118]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank118]:     return func(*args, **kwargs)
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank100]:     self._save_optimizer_and_scheduler(output_dir)
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank100]:     self.model_wrapped.save_checkpoint(output_dir)
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank100]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank100]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank100]:     return func(*args, **kwargs)
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank118]:     return cdb.barrier(group=group, async_op=async_op)
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank118]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank118]:     return func(*args, **kwargs)
[rank118]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank118]:     work = group.barrier(opts=opts)
[rank118]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 118. 
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank100]:     return cdb.barrier(group=group, async_op=async_op)
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank100]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank100]:     return func(*args, **kwargs)
[rank100]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank100]:     work = group.barrier(opts=opts)
[rank100]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 100. 
[rank39]:[E217 15:05:51.825110344 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 39] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank39]:[E217 15:05:51.825128285 ProcessGroupNCCL.cpp:630] [Rank 39] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank39]:[E217 15:05:51.825132536 ProcessGroupNCCL.cpp:636] [Rank 39] To avoid data inconsistency, we are taking the entire process down.
[rank22]:[E217 15:05:51.058076533 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 22] Process group watchdog thread terminated with exception: [Rank 22] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e9af71b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e9aac42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e9aac431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e9aac43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e9af7c6c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e9afba94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e9afbb26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 22] Process group watchdog thread terminated with exception: [Rank 22] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e9af71b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e9aac42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e9aac431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e9aac43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e9af7c6c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e9afba94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e9afbb26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e9af71b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7e9aac0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7e9af7c6c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7e9afba94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7e9afbb26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank114]: Traceback (most recent call last):
[rank114]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank114]:     train(attn_implementation="flash_attention_2")
[rank114]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank114]:     trainer.train()
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank114]:     return inner_training_loop(
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank114]:     self._maybe_log_save_evaluate(
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank114]:     self._save_checkpoint(model, trial)
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank114]:     self._save_optimizer_and_scheduler(output_dir)
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank114]:     self.model_wrapped.save_checkpoint(output_dir)
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank114]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank114]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank114]:     return func(*args, **kwargs)
[rank57]:[E217 15:05:51.474625440 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 57] Process group watchdog thread terminated with exception: [Rank 57] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600050 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x737ed5d76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x737e8b02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x737e8b031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank114]:     return cdb.barrier(group=group, async_op=async_op)
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank114]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank114]:     return func(*args, **kwargs)
[rank114]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank114]:     work = group.barrier(opts=opts)
[rank114]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 114. 
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x737e8b03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x737ed68555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x737eda694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x737eda726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 57] Process group watchdog thread terminated with exception: [Rank 57] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600050 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x737ed5d76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x737e8b02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x737e8b031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x737e8b03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x737ed68555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x737eda694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x737eda726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x737ed5d76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x737e8aca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x737ed68555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x737eda694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x737eda726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank118]:[E217 15:05:51.738942979 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 118] Process group watchdog thread terminated with exception: [Rank 118] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600046 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78342ceb5446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7833e222a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7833e2231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7833e223361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78342d01c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x783431894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x783431926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 118] Process group watchdog thread terminated with exception: [Rank 118] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600046 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78342ceb5446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7833e222a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7833e2231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7833e223361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78342d01c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x783431894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x783431926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78342ceb5446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7833e1ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x78342d01c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x783431894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x783431926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank114]:[E217 15:05:51.739954381 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 114] Process group watchdog thread terminated with exception: [Rank 114] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600049 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x787965eaf446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78791b22a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x78791b231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78791b23361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7879660165c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x78796a894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x78796a926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank108]: Traceback (most recent call last):
[rank108]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank108]:     train(attn_implementation="flash_attention_2")
[rank108]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank108]:     trainer.train()
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank108]:     return inner_training_loop(
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank108]:     self._maybe_log_save_evaluate(
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank108]:     self._save_checkpoint(model, trial)
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank108]:     self._save_optimizer_and_scheduler(output_dir)
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank108]:     self.model_wrapped.save_checkpoint(output_dir)
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank108]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank108]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank108]:     return func(*args, **kwargs)
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank108]:     return cdb.barrier(group=group, async_op=async_op)
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank108]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank108]:     return func(*args, **kwargs)
[rank108]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank108]:     work = group.barrier(opts=opts)
[rank108]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 108. 
  what():  [PG ID 1 PG GUID 1 Rank 114] Process group watchdog thread terminated with exception: [Rank 114] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600049 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x787965eaf446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78791b22a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x78791b231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78791b23361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7879660165c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x78796a894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x78796a926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x787965eaf446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x78791aea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7879660165c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x78796a894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x78796a926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank106]:[E217 15:05:51.974982470 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 106] Process group watchdog thread terminated with exception: [Rank 106] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600047 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73c43cae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73c3f1e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73c3f1e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73c3f1e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x73c43d65e5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73c441494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73c441526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank107]: Traceback (most recent call last):
[rank107]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank107]:     train(attn_implementation="flash_attention_2")
[rank107]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank107]:     trainer.train()
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank107]:     return inner_training_loop(
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank107]:     self._maybe_log_save_evaluate(
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank107]:     self._save_checkpoint(model, trial)
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank107]:     self._save_optimizer_and_scheduler(output_dir)
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank107]:     self.model_wrapped.save_checkpoint(output_dir)
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank107]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank107]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank107]:     return func(*args, **kwargs)
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank107]:     return cdb.barrier(group=group, async_op=async_op)
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank107]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank107]:     return func(*args, **kwargs)
[rank107]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank107]:     work = group.barrier(opts=opts)
[rank107]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 107. 
terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 106] Process group watchdog thread terminated with exception: [Rank 106] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600047 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73c43cae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73c3f1e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73c3f1e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73c3f1e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x73c43d65e5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73c441494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73c441526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73c43cae7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x73c3f1aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x73c43d65e5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x73c441494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x73c441526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank98]:[E217 15:05:51.463781871 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 98] Process group watchdog thread terminated with exception: [Rank 98] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600093 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ab953b50446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7ab908e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7ab908e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7ab908e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7ab953cab5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7ab958494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7ab958526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 98] Process group watchdog thread terminated with exception: [Rank 98] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600093 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ab953b50446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7ab908e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7ab908e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7ab908e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7ab953cab5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7ab958494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7ab958526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7ab953b50446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7ab908aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7ab953cab5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7ab958494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7ab958526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank110]: Traceback (most recent call last):
[rank110]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank110]:     train(attn_implementation="flash_attention_2")
[rank110]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank110]:     trainer.train()
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank110]:     return inner_training_loop(
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank110]:     self._maybe_log_save_evaluate(
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank110]:     self._save_checkpoint(model, trial)
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank110]:     self._save_optimizer_and_scheduler(output_dir)
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank110]:     self.model_wrapped.save_checkpoint(output_dir)
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank110]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank110]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank110]:     return func(*args, **kwargs)
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank110]:     return cdb.barrier(group=group, async_op=async_op)
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank110]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank110]:     return func(*args, **kwargs)
[rank110]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank110]:     work = group.barrier(opts=opts)
[rank110]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 110. 
[rank63]:[E217 15:05:51.492301276 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 63] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank63]:[E217 15:05:51.492321667 ProcessGroupNCCL.cpp:630] [Rank 63] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank63]:[E217 15:05:51.492326777 ProcessGroupNCCL.cpp:636] [Rank 63] To avoid data inconsistency, we are taking the entire process down.
[rank107]:[E217 15:05:51.987940792 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 107] Process group watchdog thread terminated with exception: [Rank 107] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600043 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78f58816c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78f53d82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x78f53d831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78f53d83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78f5892565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x78f58ce94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x78f58cf26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 107] Process group watchdog thread terminated with exception: [Rank 107] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600043 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78f58816c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78f53d82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x78f53d831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78f53d83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78f5892565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x78f58ce94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x78f58cf26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78f58816c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x78f53d4a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x78f5892565c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x78f58ce94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x78f58cf26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank91]:[E217 15:05:51.042513107 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 91] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank91]:[E217 15:05:51.042539089 ProcessGroupNCCL.cpp:630] [Rank 91] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank91]:[E217 15:05:51.042544039 ProcessGroupNCCL.cpp:636] [Rank 91] To avoid data inconsistency, we are taking the entire process down.
[rank61]: Traceback (most recent call last):
[rank61]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank61]:     train(attn_implementation="flash_attention_2")
[rank61]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank61]:     trainer.train()
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank61]:     return inner_training_loop(
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank61]:     self._maybe_log_save_evaluate(
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank61]:     self._save_checkpoint(model, trial)
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank61]:     self._save_optimizer_and_scheduler(output_dir)
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank61]:     self.model_wrapped.save_checkpoint(output_dir)
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank61]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank61]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank61]:     return func(*args, **kwargs)
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank61]:     return cdb.barrier(group=group, async_op=async_op)
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank61]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank61]:     return func(*args, **kwargs)
[rank61]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank61]:     work = group.barrier(opts=opts)
[rank61]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 61. 
[rank66]: Traceback (most recent call last):
[rank66]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank66]:     train(attn_implementation="flash_attention_2")
[rank66]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank66]:     trainer.train()
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank66]:     return inner_training_loop(
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank66]:     self._maybe_log_save_evaluate(
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank66]:     self._save_checkpoint(model, trial)
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank66]:     self._save_optimizer_and_scheduler(output_dir)
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank66]:     self.model_wrapped.save_checkpoint(output_dir)
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank66]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank66]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank66]:     return func(*args, **kwargs)
[rank119]:[E217 15:05:51.756584689 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 119] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank119]:[E217 15:05:51.756602440 ProcessGroupNCCL.cpp:630] [Rank 119] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank66]:     return cdb.barrier(group=group, async_op=async_op)
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank66]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank66]:     return func(*args, **kwargs)
[rank66]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank66]:     work = group.barrier(opts=opts)
[rank66]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 66. 
[rank119]:[E217 15:05:51.756607160 ProcessGroupNCCL.cpp:636] [Rank 119] To avoid data inconsistency, we are taking the entire process down.
[rank108]:[E217 15:05:51.992478171 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 108] Process group watchdog thread terminated with exception: [Rank 108] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600072 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7cc293750446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7cc248a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7cc248a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7cc248a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7cc2938ab5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7cc298094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7cc298126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank113]:[E217 15:05:51.758325008 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 113] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank113]:[E217 15:05:51.758344610 ProcessGroupNCCL.cpp:630] [Rank 113] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank113]:[E217 15:05:51.758349330 ProcessGroupNCCL.cpp:636] [Rank 113] To avoid data inconsistency, we are taking the entire process down.
  what():  [PG ID 1 PG GUID 1 Rank 108] Process group watchdog thread terminated with exception: [Rank 108] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600072 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7cc293750446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7cc248a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7cc248a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7cc248a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7cc2938ab5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7cc298094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7cc298126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7cc293750446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7cc2486a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7cc2938ab5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7cc298094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7cc298126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank82]:[E217 15:05:51.960329046 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 82] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank82]:[E217 15:05:51.960353467 ProcessGroupNCCL.cpp:630] [Rank 82] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank82]:[E217 15:05:51.960358148 ProcessGroupNCCL.cpp:636] [Rank 82] To avoid data inconsistency, we are taking the entire process down.
[rank89]:[E217 15:05:51.046882047 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 89] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank89]:[E217 15:05:51.046909009 ProcessGroupNCCL.cpp:630] [Rank 89] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank89]:[E217 15:05:51.046915949 ProcessGroupNCCL.cpp:636] [Rank 89] To avoid data inconsistency, we are taking the entire process down.
[rank115]:[E217 15:05:51.761056729 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 115] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank115]:[E217 15:05:51.761090321 ProcessGroupNCCL.cpp:630] [Rank 115] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank115]:[E217 15:05:51.761094741 ProcessGroupNCCL.cpp:636] [Rank 115] To avoid data inconsistency, we are taking the entire process down.
[rank110]:[E217 15:05:51.998867925 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 110] Process group watchdog thread terminated with exception: [Rank 110] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600048 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75ccbf56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75cc74c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75cc74c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75cc74c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75ccc025c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75ccc4294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75ccc4326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 110] Process group watchdog thread terminated with exception: [Rank 110] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600048 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75ccbf56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x75cc74c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x75cc74c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x75cc74c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75ccc025c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x75ccc4294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x75ccc4326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75ccbf56c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x75cc748a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x75ccc025c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x75ccc4294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x75ccc4326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank117]: Traceback (most recent call last):
[rank117]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank117]:     train(attn_implementation="flash_attention_2")
[rank117]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank117]:     trainer.train()
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank117]:     return inner_training_loop(
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank117]:     self._maybe_log_save_evaluate(
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank117]:     self._save_checkpoint(model, trial)
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank117]:     self._save_optimizer_and_scheduler(output_dir)
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank117]:     self.model_wrapped.save_checkpoint(output_dir)
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank117]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank117]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank117]:     return func(*args, **kwargs)
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank117]:     return cdb.barrier(group=group, async_op=async_op)
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank117]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank117]:     return func(*args, **kwargs)
[rank117]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank117]:     work = group.barrier(opts=opts)
[rank117]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 117. 
[rank102]: Traceback (most recent call last):
[rank102]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank102]:     train(attn_implementation="flash_attention_2")
[rank102]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank102]:     trainer.train()
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank102]:     return inner_training_loop(
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank102]:     self._maybe_log_save_evaluate(
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank102]:     self._save_checkpoint(model, trial)
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank102]:     self._save_optimizer_and_scheduler(output_dir)
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank102]:     self.model_wrapped.save_checkpoint(output_dir)
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank102]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank102]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank102]:     return func(*args, **kwargs)
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank102]:     return cdb.barrier(group=group, async_op=async_op)
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank102]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank102]:     return func(*args, **kwargs)
[rank102]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank102]:     work = group.barrier(opts=opts)
[rank102]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 102. 
[rank35]:[E217 15:05:51.867103823 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 35] Process group watchdog thread terminated with exception: [Rank 35] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600058 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e7807776446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e77bca2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e77bca31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e77bca3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e78082555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e780c094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e780c126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 35] Process group watchdog thread terminated with exception: [Rank 35] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600058 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e7807776446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e77bca2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e77bca31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e77bca3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e78082555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e780c094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e780c126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e7807776446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7e77bc6a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7e78082555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7e780c094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7e780c126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank37]:[E217 15:05:51.870246888 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 37] Process group watchdog thread terminated with exception: [Rank 37] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600027 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f88c58db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f887ac2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f887ac31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f887ac3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f88c64585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f88ca294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f88ca326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 37] Process group watchdog thread terminated with exception: [Rank 37] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600027 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f88c58db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f887ac2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f887ac31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f887ac3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f88c64585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f88ca294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f88ca326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f88c58db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7f887a8a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f88c64585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f88ca294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7f88ca326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank39]: Traceback (most recent call last):
[rank39]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank39]:     train(attn_implementation="flash_attention_2")
[rank39]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank39]:     trainer.train()
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank39]:     return inner_training_loop(
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank39]:     self._maybe_log_save_evaluate(
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank39]:     self._save_checkpoint(model, trial)
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank39]:     self._save_optimizer_and_scheduler(output_dir)
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank39]:     self.model_wrapped.save_checkpoint(output_dir)
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank39]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank39]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank39]:     return func(*args, **kwargs)
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank39]:     return cdb.barrier(group=group, async_op=async_op)
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank39]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank39]:     return func(*args, **kwargs)
[rank39]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank39]:     work = group.barrier(opts=opts)
[rank39]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 39. 
[rank70]:[E217 15:05:51.644721394 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 70] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank70]:[E217 15:05:51.644746824 ProcessGroupNCCL.cpp:630] [Rank 70] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank70]:[E217 15:05:51.644752074 ProcessGroupNCCL.cpp:636] [Rank 70] To avoid data inconsistency, we are taking the entire process down.
[rank61]:[E217 15:05:51.523113963 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 61] Process group watchdog thread terminated with exception: [Rank 61] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600045 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fba526bc446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7fba07a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7fba07a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7fba07a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7fba528175c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7fba57094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7fba57126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 61] Process group watchdog thread terminated with exception: [Rank 61] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600045 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fba526bc446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7fba07a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7fba07a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7fba07a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7fba528175c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7fba57094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7fba57126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fba526bc446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7fba076a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7fba528175c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7fba57094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7fba57126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank84]:[E217 15:05:51.992959808 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 84] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank84]:[E217 15:05:51.992980609 ProcessGroupNCCL.cpp:630] [Rank 84] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank84]:[E217 15:05:51.992987149 ProcessGroupNCCL.cpp:636] [Rank 84] To avoid data inconsistency, we are taking the entire process down.
[rank39]:[E217 15:05:51.889783655 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 39] Process group watchdog thread terminated with exception: [Rank 39] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600057 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f3b4fd6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f3b0542a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f3b05431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f3b0543361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f3b50a5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f3b54894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f3b54926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 39] Process group watchdog thread terminated with exception: [Rank 39] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600057 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f3b4fd6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f3b0542a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f3b05431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f3b0543361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f3b50a5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f3b54894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f3b54926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f3b4fd6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7f3b050a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f3b50a5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f3b54894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7f3b54926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank18]:[E217 15:05:51.127083181 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 18] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank18]:[E217 15:05:51.127110792 ProcessGroupNCCL.cpp:630] [Rank 18] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank18]:[E217 15:05:51.127116132 ProcessGroupNCCL.cpp:636] [Rank 18] To avoid data inconsistency, we are taking the entire process down.
[rank113]: Traceback (most recent call last):
[rank113]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank113]:     train(attn_implementation="flash_attention_2")
[rank113]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank113]:     trainer.train()
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank113]:     return inner_training_loop(
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank113]:     self._maybe_log_save_evaluate(
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank113]:     self._save_checkpoint(model, trial)
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank113]:     self._save_optimizer_and_scheduler(output_dir)
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank113]:     self.model_wrapped.save_checkpoint(output_dir)
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank113]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank113]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank113]:     return func(*args, **kwargs)
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank113]:     return cdb.barrier(group=group, async_op=async_op)
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank113]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank113]:     return func(*args, **kwargs)
[rank113]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank113]:     work = group.barrier(opts=opts)
[rank113]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 113. 
[rank63]: Traceback (most recent call last):
[rank63]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank63]:     train(attn_implementation="flash_attention_2")
[rank63]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank63]:     trainer.train()
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank63]:     return inner_training_loop(
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank63]:     self._maybe_log_save_evaluate(
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank63]:     self._save_checkpoint(model, trial)
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank63]:     self._save_optimizer_and_scheduler(output_dir)
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank63]:     self.model_wrapped.save_checkpoint(output_dir)
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank63]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank63]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank63]:     return func(*args, **kwargs)
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank63]:     return cdb.barrier(group=group, async_op=async_op)
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank63]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank63]:     return func(*args, **kwargs)
[rank63]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank63]:     work = group.barrier(opts=opts)
[rank63]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 63. 
[rank89]: Traceback (most recent call last):
[rank89]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank89]:     train(attn_implementation="flash_attention_2")
[rank89]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank89]:     trainer.train()
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank89]:     return inner_training_loop(
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank89]:     self._maybe_log_save_evaluate(
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank89]:     self._save_checkpoint(model, trial)
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank89]:     self._save_optimizer_and_scheduler(output_dir)
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank89]:     self.model_wrapped.save_checkpoint(output_dir)
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank89]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank89]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank89]:     return func(*args, **kwargs)
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank89]:     return cdb.barrier(group=group, async_op=async_op)
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank89]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank89]:     return func(*args, **kwargs)
[rank89]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank89]:     work = group.barrier(opts=opts)
[rank89]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 89. 
[rank91]: Traceback (most recent call last):
[rank91]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank91]:     train(attn_implementation="flash_attention_2")
[rank91]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank91]:     trainer.train()
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank91]:     return inner_training_loop(
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank91]:     self._maybe_log_save_evaluate(
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank91]:     self._save_checkpoint(model, trial)
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank91]:     self._save_optimizer_and_scheduler(output_dir)
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank91]:     self.model_wrapped.save_checkpoint(output_dir)
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank91]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank91]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank91]:     return func(*args, **kwargs)
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank91]:     return cdb.barrier(group=group, async_op=async_op)
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank91]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank91]:     return func(*args, **kwargs)
[rank91]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank91]:     work = group.barrier(opts=opts)
[rank91]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 91. 
[rank115]: Traceback (most recent call last):
[rank115]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank115]:     train(attn_implementation="flash_attention_2")
[rank115]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank115]:     trainer.train()
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank115]:     return inner_training_loop(
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank115]:     self._maybe_log_save_evaluate(
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank115]:     self._save_checkpoint(model, trial)
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank115]:     self._save_optimizer_and_scheduler(output_dir)
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank115]:     self.model_wrapped.save_checkpoint(output_dir)
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank115]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank115]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank115]:     return func(*args, **kwargs)
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank115]:     return cdb.barrier(group=group, async_op=async_op)
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank115]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank115]:     return func(*args, **kwargs)
[rank115]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank115]:     work = group.barrier(opts=opts)
[rank115]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 115. 
[rank91]:[E217 15:05:51.103151394 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 91] Process group watchdog thread terminated with exception: [Rank 91] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75002276c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x74ffd7e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x74ffd7e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank87]:[E217 15:05:51.016877066 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 87] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank87]:[E217 15:05:51.016902517 ProcessGroupNCCL.cpp:630] [Rank 87] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank87]:[E217 15:05:51.016907507 ProcessGroupNCCL.cpp:636] [Rank 87] To avoid data inconsistency, we are taking the entire process down.
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x74ffd7e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75002345c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x750027294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x750027326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank119]: Traceback (most recent call last):
[rank119]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank119]:     train(attn_implementation="flash_attention_2")
[rank119]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank119]:     trainer.train()
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank119]:     return inner_training_loop(
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank119]:     self._maybe_log_save_evaluate(
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank119]:     self._save_checkpoint(model, trial)
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank119]:     self._save_optimizer_and_scheduler(output_dir)
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank119]:     self.model_wrapped.save_checkpoint(output_dir)
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank119]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank119]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank119]:     return func(*args, **kwargs)
  what():  [PG ID 1 PG GUID 1 Rank 91] Process group watchdog thread terminated with exception: [Rank 91] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75002276c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x74ffd7e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x74ffd7e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank119]:     return cdb.barrier(group=group, async_op=async_op)
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank119]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank119]:     return func(*args, **kwargs)
[rank119]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank119]:     work = group.barrier(opts=opts)
[rank119]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 119. 
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x74ffd7e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x75002345c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x750027294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x750027326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x75002276c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x74ffd7aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x75002345c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x750027294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x750027326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank100]:[E217 15:05:51.535606555 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 100] Process group watchdog thread terminated with exception: [Rank 100] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600003 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b9334f76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b92ea22a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b92ea231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b92ea23361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b93356585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b9339894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b9339926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 100] Process group watchdog thread terminated with exception: [Rank 100] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600003 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b9334f76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7b92ea22a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7b92ea231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7b92ea23361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7b93356585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7b9339894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7b9339926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7b9334f76446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7b92e9ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7b93356585c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7b9339894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7b9339926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank89]:[E217 15:05:51.106382131 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 89] Process group watchdog thread terminated with exception: [Rank 89] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71818bac1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x718140e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x718140e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x718140e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x71818bc1c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x718190494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x718190526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 89] Process group watchdog thread terminated with exception: [Rank 89] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71818bac1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x718140e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x718140e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x718140e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x71818bc1c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x718190494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x718190526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71818bac1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x718140aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x71818bc1c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x718190494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x718190526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank82]: Traceback (most recent call last):
[rank82]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank82]:     train(attn_implementation="flash_attention_2")
[rank82]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank82]:     trainer.train()
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank82]:     return inner_training_loop(
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank82]:     self._maybe_log_save_evaluate(
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank82]:     self._save_checkpoint(model, trial)
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank82]:     self._save_optimizer_and_scheduler(output_dir)
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank82]:     self.model_wrapped.save_checkpoint(output_dir)
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank82]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank82]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank82]:     return func(*args, **kwargs)
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank82]:     return cdb.barrier(group=group, async_op=async_op)
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank82]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank82]:     return func(*args, **kwargs)
[rank82]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank82]:     work = group.barrier(opts=opts)
[rank82]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 82. 
[rank102]:[E217 15:05:51.539777715 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 102] Process group watchdog thread terminated with exception: [Rank 102] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600094 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a32f13b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a32a662a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a32a6631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a32a663361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a32f1e675c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a32f5c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a32f5d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 102] Process group watchdog thread terminated with exception: [Rank 102] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600094 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a32f13b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a32a662a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a32a6631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a32a663361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a32f1e675c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a32f5c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a32f5d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a32f13b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7a32a62a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7a32f1e675c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7a32f5c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7a32f5d26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank82]:[E217 15:05:51.029524889 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 82] Process group watchdog thread terminated with exception: [Rank 82] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600043 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73e30d6c1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73e2c2a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73e2c2a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73e2c2a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x73e30d81c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73e312094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73e312126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 82] Process group watchdog thread terminated with exception: [Rank 82] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600043 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73e30d6c1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73e2c2a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73e2c2a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73e2c2a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x73e30d81c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73e312094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73e312126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73e30d6c1446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x73e2c26a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x73e30d81c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x73e312094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x73e312126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank84]:[E217 15:05:51.040188320 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 84] Process group watchdog thread terminated with exception: [Rank 84] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600059 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7da417d93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7da3cd02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7da3cd031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7da3cd03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7da417eee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7da41c694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7da41c726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank66]:[E217 15:05:51.702188591 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 66] Process group watchdog thread terminated with exception: [Rank 66] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600084 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a02781b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a022d42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a022d431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a022d43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a0278c665c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a027ca94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a027cb26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank70]: Traceback (most recent call last):
[rank70]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank70]:     train(attn_implementation="flash_attention_2")
[rank70]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank70]:     trainer.train()
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank70]:     return inner_training_loop(
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank70]:     self._maybe_log_save_evaluate(
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank70]:     self._save_checkpoint(model, trial)
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank70]:     self._save_optimizer_and_scheduler(output_dir)
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank70]:     self.model_wrapped.save_checkpoint(output_dir)
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank70]:     self._create_zero_checkpoint_files(save_dir, tag)
  what():  [PG ID 1 PG GUID 1 Rank 84] Process group watchdog thread terminated with exception: [Rank 84] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600059 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7da417d93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7da3cd02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7da3cd031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank70]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank70]:     return func(*args, **kwargs)
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank70]:     return cdb.barrier(group=group, async_op=async_op)
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank70]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank70]:     return func(*args, **kwargs)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7da3cd03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7da417eee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7da41c694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7da41c726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7da417d93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7da3ccca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank70]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
frame #2: <unknown function> + 0x145c0 (0x7da417eee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7da41c694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7da41c726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank70]:     work = group.barrier(opts=opts)
[rank70]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 70. 
terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 66] Process group watchdog thread terminated with exception: [Rank 66] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600084 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a02781b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a022d42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a022d431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a022d43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a0278c665c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a027ca94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a027cb26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a02781b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7a022d0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7a0278c665c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7a027ca94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7a027cb26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank97]:[E217 15:05:51.563789994 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 97] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank97]:[E217 15:05:51.563814775 ProcessGroupNCCL.cpp:630] [Rank 97] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank97]:[E217 15:05:51.563819745 ProcessGroupNCCL.cpp:636] [Rank 97] To avoid data inconsistency, we are taking the entire process down.
[rank117]:[E217 15:05:51.848712099 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 117] Process group watchdog thread terminated with exception: [Rank 117] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600069 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x702eead6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x702ea042a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x702ea0431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x702ea043361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x702eebe5d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x702eefa94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x702eefb26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 117] Process group watchdog thread terminated with exception: [Rank 117] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600069 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x702eead6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x702ea042a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x702ea0431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x702ea043361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x702eebe5d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x702eefa94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x702eefb26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x702eead6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x702ea00a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x702eebe5d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x702eefa94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x702eefb26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank70]:[E217 15:05:51.713929521 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 70] Process group watchdog thread terminated with exception: [Rank 70] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600085 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x741a0c393446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7419c162a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7419c1631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7419c163361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x741a0c4ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x741a10c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x741a10d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 70] Process group watchdog thread terminated with exception: [Rank 70] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600085 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x741a0c393446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7419c162a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7419c1631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7419c163361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x741a0c4ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x741a10c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x741a10d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x741a0c393446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7419c12a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x741a0c4ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x741a10c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x741a10d26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank81]:[E217 15:05:51.061476222 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 81] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank81]:[E217 15:05:51.061501213 ProcessGroupNCCL.cpp:630] [Rank 81] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank81]:[E217 15:05:51.061507113 ProcessGroupNCCL.cpp:636] [Rank 81] To avoid data inconsistency, we are taking the entire process down.
[rank85]:[E217 15:05:51.062097877 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 85] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank85]:[E217 15:05:51.062118088 ProcessGroupNCCL.cpp:630] [Rank 85] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank85]:[E217 15:05:51.062122969 ProcessGroupNCCL.cpp:636] [Rank 85] To avoid data inconsistency, we are taking the entire process down.
[rank18]: Traceback (most recent call last):
[rank18]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank18]:     train(attn_implementation="flash_attention_2")
[rank18]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank18]:     trainer.train()
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank18]:     return inner_training_loop(
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank18]:     self._maybe_log_save_evaluate(
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank18]:     self._save_checkpoint(model, trial)
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank18]:     self._save_optimizer_and_scheduler(output_dir)
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank18]:     self.model_wrapped.save_checkpoint(output_dir)
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank18]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank18]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank18]:     return func(*args, **kwargs)
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank18]:     return cdb.barrier(group=group, async_op=async_op)
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank18]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank18]:     return func(*args, **kwargs)
[rank18]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank18]:     work = group.barrier(opts=opts)
[rank18]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 18. 
[rank83]:[E217 15:05:51.067077669 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 83] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank83]:[E217 15:05:51.067108640 ProcessGroupNCCL.cpp:630] [Rank 83] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank83]:[E217 15:05:51.067113131 ProcessGroupNCCL.cpp:636] [Rank 83] To avoid data inconsistency, we are taking the entire process down.
[rank87]: Traceback (most recent call last):
[rank87]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank87]:     train(attn_implementation="flash_attention_2")
[rank87]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank87]:     trainer.train()
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank87]:     return inner_training_loop(
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank87]:     self._maybe_log_save_evaluate(
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank87]:     self._save_checkpoint(model, trial)
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank87]:     self._save_optimizer_and_scheduler(output_dir)
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank87]:     self.model_wrapped.save_checkpoint(output_dir)
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank87]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank87]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank87]:     return func(*args, **kwargs)
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank87]:     return cdb.barrier(group=group, async_op=async_op)
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank87]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank87]:     return func(*args, **kwargs)
[rank87]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank87]:     work = group.barrier(opts=opts)
[rank87]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 87. 
[rank95]:[E217 15:05:51.156200164 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 95] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank95]:[E217 15:05:51.156229316 ProcessGroupNCCL.cpp:630] [Rank 95] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank95]:[E217 15:05:51.156234286 ProcessGroupNCCL.cpp:636] [Rank 95] To avoid data inconsistency, we are taking the entire process down.
[rank93]:[E217 15:05:51.167348658 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 93] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank93]:[E217 15:05:51.167371400 ProcessGroupNCCL.cpp:630] [Rank 93] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank93]:[E217 15:05:51.167376090 ProcessGroupNCCL.cpp:636] [Rank 93] To avoid data inconsistency, we are taking the entire process down.
[rank87]:[E217 15:05:51.081113747 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 87] Process group watchdog thread terminated with exception: [Rank 87] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600059 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70fddf76c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x70fd94e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x70fd94e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x70fd94e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x70fde045c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x70fde4294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x70fde4326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 87] Process group watchdog thread terminated with exception: [Rank 87] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600059 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70fddf76c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x70fd94e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x70fd94e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x70fd94e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x70fde045c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x70fde4294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x70fde4326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70fddf76c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x70fd94aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x70fde045c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x70fde4294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x70fde4326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank113]:[E217 15:05:51.895403226 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 113] Process group watchdog thread terminated with exception: [Rank 113] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600099 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x705c3556c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x705beac2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x705beac31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x705beac3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x705c366635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x705c3a294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x705c3a326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank63]:[E217 15:05:51.634781591 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 63] Process group watchdog thread terminated with exception: [Rank 63] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600061 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7517effb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7517a522a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7517a5231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
  what():  [PG ID 1 PG GUID 1 Rank 113] Process group watchdog thread terminated with exception: [Rank 113] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600099 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x705c3556c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x705beac2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x705beac31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7517a523361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7517f0a555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7517f4894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7517f4926850 in /lib/x86_64-linux-gnu/libc.so.6)

frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x705beac3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x705c366635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x705c3a294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x705c3a326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x705c3556c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x705bea8a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
terminate called after throwing an instance of 'c10::DistBackendError'
frame #2: <unknown function> + 0x145c0 (0x705c366635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x705c3a294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x705c3a326850 in /lib/x86_64-linux-gnu/libc.so.6)

  what():  [PG ID 1 PG GUID 1 Rank 63] Process group watchdog thread terminated with exception: [Rank 63] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600061 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7517effb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7517a522a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7517a5231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7517a523361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7517f0a555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7517f4894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7517f4926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7517effb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7517a4ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7517f0a555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7517f4894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7517f4926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank97]: Traceback (most recent call last):
[rank97]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank97]:     train(attn_implementation="flash_attention_2")
[rank97]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank97]:     trainer.train()
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank97]:     return inner_training_loop(
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank97]:     self._maybe_log_save_evaluate(
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank97]:     self._save_checkpoint(model, trial)
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank97]:     self._save_optimizer_and_scheduler(output_dir)
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank97]:     self.model_wrapped.save_checkpoint(output_dir)
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank97]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank97]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank97]:     return func(*args, **kwargs)
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank97]:     return cdb.barrier(group=group, async_op=async_op)
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank97]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank97]:     return func(*args, **kwargs)
[rank97]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank97]:     work = group.barrier(opts=opts)
[rank97]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 97. 
[rank85]: Traceback (most recent call last):
[rank85]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank85]:     train(attn_implementation="flash_attention_2")
[rank85]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank85]:     trainer.train()
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank85]:     return inner_training_loop(
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank85]:     self._maybe_log_save_evaluate(
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank85]:     self._save_checkpoint(model, trial)
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank85]:     self._save_optimizer_and_scheduler(output_dir)
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank85]:     self.model_wrapped.save_checkpoint(output_dir)
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank85]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank85]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank85]:     return func(*args, **kwargs)
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank85]:     return cdb.barrier(group=group, async_op=async_op)
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank85]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank85]:     return func(*args, **kwargs)
[rank85]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank85]:     work = group.barrier(opts=opts)
[rank85]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 85. 
[rank81]: Traceback (most recent call last):
[rank81]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank81]:     train(attn_implementation="flash_attention_2")
[rank81]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank81]:     trainer.train()
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank81]:     return inner_training_loop(
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank81]:     self._maybe_log_save_evaluate(
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank81]:     self._save_checkpoint(model, trial)
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank81]:     self._save_optimizer_and_scheduler(output_dir)
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank81]:     self.model_wrapped.save_checkpoint(output_dir)
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank81]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank81]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank81]:     return func(*args, **kwargs)
[rank97]:[E217 15:05:51.632442228 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 97] Process group watchdog thread terminated with exception: [Rank 97] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600095 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7717c3b6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x77177922a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x771779231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank81]:     return cdb.barrier(group=group, async_op=async_op)
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank81]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank81]:     return func(*args, **kwargs)
[rank81]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank81]:     work = group.barrier(opts=opts)
[rank81]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 81. 
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x77177923361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7717c485c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7717c8894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7717c8926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 97] Process group watchdog thread terminated with exception: [Rank 97] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600095 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7717c3b6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x77177922a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x771779231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x77177923361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7717c485c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7717c8894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7717c8926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7717c3b6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x771778ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7717c485c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7717c8894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7717c8926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank95]: Traceback (most recent call last):
[rank95]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank95]:     train(attn_implementation="flash_attention_2")
[rank95]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank95]:     trainer.train()
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank95]:     return inner_training_loop(
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank95]:     self._maybe_log_save_evaluate(
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank95]:     self._save_checkpoint(model, trial)
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank95]:     self._save_optimizer_and_scheduler(output_dir)
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank95]:     self.model_wrapped.save_checkpoint(output_dir)
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank95]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank95]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank95]:     return func(*args, **kwargs)
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank95]:     return cdb.barrier(group=group, async_op=async_op)
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank95]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank95]:     return func(*args, **kwargs)
[rank95]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank95]:     work = group.barrier(opts=opts)
[rank95]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 95. 
[rank83]: Traceback (most recent call last):
[rank83]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank83]:     train(attn_implementation="flash_attention_2")
[rank83]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank83]:     trainer.train()
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank83]:     return inner_training_loop(
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank83]:     self._maybe_log_save_evaluate(
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank83]:     self._save_checkpoint(model, trial)
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank83]:     self._save_optimizer_and_scheduler(output_dir)
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank83]:     self.model_wrapped.save_checkpoint(output_dir)
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank83]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank83]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank83]:     return func(*args, **kwargs)
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank83]:     return cdb.barrier(group=group, async_op=async_op)
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank83]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank83]:     return func(*args, **kwargs)
[rank83]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank83]:     work = group.barrier(opts=opts)
[rank83]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 83. 
[rank93]: Traceback (most recent call last):
[rank93]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank93]:     train(attn_implementation="flash_attention_2")
[rank93]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank93]:     trainer.train()
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank93]:     return inner_training_loop(
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank93]:     self._maybe_log_save_evaluate(
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank93]:     self._save_checkpoint(model, trial)
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank93]:     self._save_optimizer_and_scheduler(output_dir)
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank93]:     self.model_wrapped.save_checkpoint(output_dir)
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank93]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank93]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank93]:     return func(*args, **kwargs)
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank93]:     return cdb.barrier(group=group, async_op=async_op)
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank93]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank93]:     return func(*args, **kwargs)
[rank93]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank93]:     work = group.barrier(opts=opts)
[rank93]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 93. 
[rank20]:[E217 15:05:51.251401111 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 20] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank20]:[E217 15:05:51.251423612 ProcessGroupNCCL.cpp:630] [Rank 20] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank20]:[E217 15:05:51.251428762 ProcessGroupNCCL.cpp:636] [Rank 20] To avoid data inconsistency, we are taking the entire process down.
[rank95]:[E217 15:05:51.216566733 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 95] Process group watchdog thread terminated with exception: [Rank 95] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600039 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x77840b8af446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7783c0c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7783c0c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7783c0c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x77840ba165c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x778410294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x778410326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 95] Process group watchdog thread terminated with exception: [Rank 95] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600039 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x77840b8af446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7783c0c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7783c0c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7783c0c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x77840ba165c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x778410294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x778410326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x77840b8af446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7783c08a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x77840ba165c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x778410294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x778410326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank115]:[E217 15:05:51.933336282 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 115] Process group watchdog thread terminated with exception: [Rank 115] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x738869193446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73881e42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73881e431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73881e43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7388692ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73886da94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73886db26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 115] Process group watchdog thread terminated with exception: [Rank 115] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x738869193446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73881e42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73881e431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73881e43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7388692ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73886da94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73886db26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x738869193446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x73881e0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7388692ee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x73886da94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x73886db26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank93]:[E217 15:05:51.222047464 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 93] Process group watchdog thread terminated with exception: [Rank 93] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73eb04b93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73eab9e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73eab9e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73eab9e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x73eb04cee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73eb09494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73eb09526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 93] Process group watchdog thread terminated with exception: [Rank 93] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73eb04b93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x73eab9e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x73eab9e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x73eab9e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x73eb04cee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x73eb09494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x73eb09526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x73eb04b93446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x73eab9aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x73eb04cee5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x73eb09494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x73eb09526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank17]:[E217 15:05:51.259894064 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 17] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank17]:[E217 15:05:51.259915275 ProcessGroupNCCL.cpp:630] [Rank 17] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank17]:[E217 15:05:51.259921415 ProcessGroupNCCL.cpp:636] [Rank 17] To avoid data inconsistency, we are taking the entire process down.
[rank119]:[E217 15:05:51.935934166 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 119] Process group watchdog thread terminated with exception: [Rank 119] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600062 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72b05c3b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72b01162a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72b011631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72b01163361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72b05ce555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72b060c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72b060d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 119] Process group watchdog thread terminated with exception: [Rank 119] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600062 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72b05c3b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72b01162a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72b011631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank19]:[E217 15:05:51.260950298 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 19] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank19]:[E217 15:05:51.260971849 ProcessGroupNCCL.cpp:630] [Rank 19] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank19]:[E217 15:05:51.260979019 ProcessGroupNCCL.cpp:636] [Rank 19] To avoid data inconsistency, we are taking the entire process down.
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72b01163361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72b05ce555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72b060c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72b060d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72b05c3b9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x72b0112a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x72b05ce555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x72b060c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x72b060d26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank21]:[E217 15:05:51.263763971 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 21] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank21]:[E217 15:05:51.263790113 ProcessGroupNCCL.cpp:630] [Rank 21] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank21]:[E217 15:05:51.263796873 ProcessGroupNCCL.cpp:636] [Rank 21] To avoid data inconsistency, we are taking the entire process down.
[rank18]:[E217 15:05:51.265142142 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 18] Process group watchdog thread terminated with exception: [Rank 18] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600003 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e26ca96c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e268002a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e2680031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e268003361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e26cade25c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e26cf694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e26cf726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 18] Process group watchdog thread terminated with exception: [Rank 18] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600003 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e26ca96c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e268002a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e2680031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e268003361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e26cade25c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e26cf694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e26cf726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e26ca96c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7e267fca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7e26cade25c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7e26cf694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7e26cf726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank23]:[E217 15:05:51.265801765 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 23] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank23]:[E217 15:05:51.265820006 ProcessGroupNCCL.cpp:630] [Rank 23] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank23]:[E217 15:05:51.265824246 ProcessGroupNCCL.cpp:636] [Rank 23] To avoid data inconsistency, we are taking the entire process down.
[rank58]:[E217 15:05:51.713300281 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 58] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank58]:[E217 15:05:51.713322431 ProcessGroupNCCL.cpp:630] [Rank 58] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank58]:[E217 15:05:51.713327272 ProcessGroupNCCL.cpp:636] [Rank 58] To avoid data inconsistency, we are taking the entire process down.
[rank20]:[E217 15:05:51.299848702 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 20] Process group watchdog thread terminated with exception: [Rank 20] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600075 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x762bb356c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x762b68c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x762b68c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x762b68c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x762bb39635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x762bb8094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x762bb8126850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 20] Process group watchdog thread terminated with exception: [Rank 20] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600075 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x762bb356c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x762b68c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x762b68c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x762b68c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x762bb39635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x762bb8094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x762bb8126850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x762bb356c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x762b688a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x762bb39635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x762bb8094ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x762bb8126850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank60]:[E217 15:05:51.715158197 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 60] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank60]:[E217 15:05:51.715181778 ProcessGroupNCCL.cpp:630] [Rank 60] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank60]:[E217 15:05:51.715186788 ProcessGroupNCCL.cpp:636] [Rank 60] To avoid data inconsistency, we are taking the entire process down.
[rank62]:[E217 15:05:51.715316875 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 62] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank62]:[E217 15:05:51.715337196 ProcessGroupNCCL.cpp:630] [Rank 62] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank62]:[E217 15:05:51.715342056 ProcessGroupNCCL.cpp:636] [Rank 62] To avoid data inconsistency, we are taking the entire process down.
[rank83]:[E217 15:05:51.177641496 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 83] Process group watchdog thread terminated with exception: [Rank 83] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600047 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70b3a5bb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x70b35ae2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x70b35ae31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x70b35ae3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x70b3a666c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x70b3aa494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x70b3aa526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank19]:[E217 15:05:51.301220452 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 19] Process group watchdog thread terminated with exception: [Rank 19] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x779380ea3446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x77933622a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x779336231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x77933623361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x77938185c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x779385894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x779385926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 83] Process group watchdog thread terminated with exception: [Rank 83] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600047 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70b3a5bb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x70b35ae2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x70b35ae31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x70b35ae3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x70b3a666c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x70b3aa494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x70b3aa526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70b3a5bb9446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x70b35aaa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x70b3a666c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x70b3aa494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x70b3aa526850 in /lib/x86_64-linux-gnu/libc.so.6)

  what():  [PG ID 1 PG GUID 1 Rank 19] Process group watchdog thread terminated with exception: [Rank 19] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600080 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x779380ea3446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x77933622a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x779336231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x77933623361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x77938185c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x779385894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x779385926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x779380ea3446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x779335ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x77938185c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x779385894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x779385926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank17]: Traceback (most recent call last):
[rank17]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank17]:     train(attn_implementation="flash_attention_2")
[rank17]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank17]:     trainer.train()
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank17]:     return inner_training_loop(
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank17]:     self._maybe_log_save_evaluate(
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank17]:     self._save_checkpoint(model, trial)
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank17]:     self._save_optimizer_and_scheduler(output_dir)
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank17]:     self.model_wrapped.save_checkpoint(output_dir)
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank17]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank17]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank17]:     return func(*args, **kwargs)
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank17]:     return cdb.barrier(group=group, async_op=async_op)
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank17]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank17]:     return func(*args, **kwargs)
[rank17]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank17]:     work = group.barrier(opts=opts)
[rank17]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 17. 
[rank23]:[E217 15:05:51.311368580 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 23] Process group watchdog thread terminated with exception: [Rank 23] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600097 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e86d0f6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e868662a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e8686631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e868663361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e86d1c5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e86d5c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e86d5d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 23] Process group watchdog thread terminated with exception: [Rank 23] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600097 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e86d0f6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e868662a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e8686631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e868663361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e86d1c5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e86d5c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e86d5d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e86d0f6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7e86862a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7e86d1c5c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7e86d5c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7e86d5d26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank67]:[E217 15:05:51.852244073 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 67] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank67]:[E217 15:05:51.852270834 ProcessGroupNCCL.cpp:630] [Rank 67] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank67]:[E217 15:05:51.852276954 ProcessGroupNCCL.cpp:636] [Rank 67] To avoid data inconsistency, we are taking the entire process down.
[rank71]:[E217 15:05:51.852949854 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 71] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank71]:[E217 15:05:51.852967564 ProcessGroupNCCL.cpp:630] [Rank 71] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank71]:[E217 15:05:51.852973035 ProcessGroupNCCL.cpp:636] [Rank 71] To avoid data inconsistency, we are taking the entire process down.
[rank65]:[E217 15:05:51.853056416 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 65] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank65]:[E217 15:05:51.853084626 ProcessGroupNCCL.cpp:630] [Rank 65] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank65]:[E217 15:05:51.853091066 ProcessGroupNCCL.cpp:636] [Rank 65] To avoid data inconsistency, we are taking the entire process down.
[rank21]: Traceback (most recent call last):
[rank21]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank21]:     train(attn_implementation="flash_attention_2")
[rank21]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank21]:     trainer.train()
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank21]:     return inner_training_loop(
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank21]:     self._maybe_log_save_evaluate(
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank21]:     self._save_checkpoint(model, trial)
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank21]:     self._save_optimizer_and_scheduler(output_dir)
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank21]:     self.model_wrapped.save_checkpoint(output_dir)
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank21]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank21]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank21]:     return func(*args, **kwargs)
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank21]:     return cdb.barrier(group=group, async_op=async_op)
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank21]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank21]:     return func(*args, **kwargs)
[rank21]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank21]:     work = group.barrier(opts=opts)
[rank21]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 21. 
[rank69]:[E217 15:05:51.853675765 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 69] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank69]:[E217 15:05:51.853690435 ProcessGroupNCCL.cpp:630] [Rank 69] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank69]:[E217 15:05:51.853694575 ProcessGroupNCCL.cpp:636] [Rank 69] To avoid data inconsistency, we are taking the entire process down.
[rank17]:[E217 15:05:51.321478525 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 17] Process group watchdog thread terminated with exception: [Rank 17] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78f4b596c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78f46b02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x78f46b031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78f46b03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78f4b665c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x78f4ba694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x78f4ba726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 17] Process group watchdog thread terminated with exception: [Rank 17] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78f4b596c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x78f46b02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x78f46b031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x78f46b03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78f4b665c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x78f4ba694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x78f4ba726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78f4b596c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x78f46aca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x78f4b665c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x78f4ba694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x78f4ba726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank81]:[E217 15:05:51.200441290 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 81] Process group watchdog thread terminated with exception: [Rank 81] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a01fcea3446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a01b222a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a01b2231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a01b223361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a01fd85c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a0201894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a0201926850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 81] Process group watchdog thread terminated with exception: [Rank 81] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a01fcea3446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a01b222a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a01b2231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a01b223361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a01fd85c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a0201894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a0201926850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a01fcea3446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7a01b1ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7a01fd85c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7a0201894ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7a0201926850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank21]:[E217 15:05:51.326847209 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 21] Process group watchdog thread terminated with exception: [Rank 21] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600097 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7c788209f446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7c783742a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7c7837431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7c783743361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7c78821fa5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7c7886a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7c7886b26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 21] Process group watchdog thread terminated with exception: [Rank 21] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600097 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7c788209f446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7c783742a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7c7837431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7c783743361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7c78821fa5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7c7886a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7c7886b26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7c788209f446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7c78370a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7c78821fa5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7c7886a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7c7886b26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank99]:[E217 15:05:51.724580182 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 99] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank99]:[E217 15:05:51.724604502 ProcessGroupNCCL.cpp:630] [Rank 99] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank99]:[E217 15:05:51.724609632 ProcessGroupNCCL.cpp:636] [Rank 99] To avoid data inconsistency, we are taking the entire process down.
[rank101]:[E217 15:05:51.728156270 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 101] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank101]:[E217 15:05:51.728177480 ProcessGroupNCCL.cpp:630] [Rank 101] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank101]:[E217 15:05:51.728183931 ProcessGroupNCCL.cpp:636] [Rank 101] To avoid data inconsistency, we are taking the entire process down.
[rank103]:[E217 15:05:51.729726070 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 103] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank103]:[E217 15:05:51.729745681 ProcessGroupNCCL.cpp:630] [Rank 103] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank103]:[E217 15:05:51.729750601 ProcessGroupNCCL.cpp:636] [Rank 103] To avoid data inconsistency, we are taking the entire process down.
[rank92]:[E217 15:05:51.308973766 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 92] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank92]:[E217 15:05:51.308995117 ProcessGroupNCCL.cpp:630] [Rank 92] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank92]:[E217 15:05:51.309022689 ProcessGroupNCCL.cpp:636] [Rank 92] To avoid data inconsistency, we are taking the entire process down.
[rank94]:[E217 15:05:51.309902645 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 94] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank94]:[E217 15:05:51.309924967 ProcessGroupNCCL.cpp:630] [Rank 94] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank94]:[E217 15:05:51.309929487 ProcessGroupNCCL.cpp:636] [Rank 94] To avoid data inconsistency, we are taking the entire process down.
[rank90]:[E217 15:05:51.311131664 ProcessGroupNCCL.cpp:1834] [PG ID 1 PG GUID 1 Rank 90] Timeout at NCCL work: 66413, last enqueued NCCL work: 66413, last completed NCCL work: 66412.
[rank90]:[E217 15:05:51.311150415 ProcessGroupNCCL.cpp:630] [Rank 90] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank90]:[E217 15:05:51.311154725 ProcessGroupNCCL.cpp:636] [Rank 90] To avoid data inconsistency, we are taking the entire process down.
[rank58]: Traceback (most recent call last):
[rank58]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank58]:     train(attn_implementation="flash_attention_2")
[rank58]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank58]:     trainer.train()
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank58]:     return inner_training_loop(
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank58]:     self._maybe_log_save_evaluate(
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank58]:     self._save_checkpoint(model, trial)
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank58]:     self._save_optimizer_and_scheduler(output_dir)
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank58]:     self.model_wrapped.save_checkpoint(output_dir)
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank58]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank58]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank58]:     return func(*args, **kwargs)
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank58]:     return cdb.barrier(group=group, async_op=async_op)
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank58]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank58]:     return func(*args, **kwargs)
[rank58]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank58]:     work = group.barrier(opts=opts)
[rank58]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 58. 
[rank67]:[E217 15:05:51.893238699 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 67] Process group watchdog thread terminated with exception: [Rank 67] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e204f2db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e200462a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e2004631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e200463361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e204fe525c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e2053c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e2053d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [rank69]:[E217 15:05:51.893745967 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 69] Process group watchdog thread terminated with exception: [Rank 69] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600042 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f1c9596c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f1c4b02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f1c4b031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f1c4b03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f1c95de45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f1c9a694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f1c9a726850 in /lib/x86_64-linux-gnu/libc.so.6)

[PG ID 1 PG GUID 1 Rank 67] Process group watchdog thread terminated with exception: [Rank 67] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600081 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e204f2db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7e200462a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7e2004631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7e200463361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7e204fe525c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7e2053c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7e2053d26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e204f2db446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7e20042a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7e204fe525c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7e2053c94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7e2053d26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 69] Process group watchdog thread terminated with exception: [Rank 69] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600042 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f1c9596c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7f1c4b02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7f1c4b031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f1c4b03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f1c95de45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f1c9a694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7f1c9a726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f1c9596c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7f1c4aca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f1c95de45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f1c9a694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7f1c9a726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank85]:[E217 15:05:51.232897044 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 85] Process group watchdog thread terminated with exception: [Rank 85] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600044 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a869396c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a864902a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a8649031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a864903361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a8694a595c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a8698494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a8698526850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 85] Process group watchdog thread terminated with exception: [Rank 85] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600044 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a869396c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a864902a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a8649031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a864903361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a8694a595c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a8698494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a8698526850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a869396c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7a8648ca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank60]: Traceback (most recent call last):
[rank60]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank60]:     train(attn_implementation="flash_attention_2")
[rank60]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank60]:     trainer.train()
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank60]:     return inner_training_loop(
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank60]:     self._maybe_log_save_evaluate(
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank60]:     self._save_checkpoint(model, trial)
frame #2: <unknown function> + 0x145c0 (0x7a8694a595c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7a8698494ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7a8698526850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank60]:     self._save_optimizer_and_scheduler(output_dir)
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank60]:     self.model_wrapped.save_checkpoint(output_dir)
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank60]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank60]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank60]:     return func(*args, **kwargs)
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank60]:     return cdb.barrier(group=group, async_op=async_op)
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank60]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank60]:     return func(*args, **kwargs)
[rank60]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank60]:     work = group.barrier(opts=opts)
[rank60]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 60. 
[rank62]: Traceback (most recent call last):
[rank62]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank62]:     train(attn_implementation="flash_attention_2")
[rank62]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank62]:     trainer.train()
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank62]:     return inner_training_loop(
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank62]:     self._maybe_log_save_evaluate(
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank62]:     self._save_checkpoint(model, trial)
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank62]:     self._save_optimizer_and_scheduler(output_dir)
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank62]:     self.model_wrapped.save_checkpoint(output_dir)
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank62]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank62]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank62]:     return func(*args, **kwargs)
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank62]:     return cdb.barrier(group=group, async_op=async_op)
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank62]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank62]:     return func(*args, **kwargs)
[rank62]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank62]:     work = group.barrier(opts=opts)
[rank62]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 62. 
[rank65]: Traceback (most recent call last):
[rank65]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank65]:     train(attn_implementation="flash_attention_2")
[rank65]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank65]:     trainer.train()
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank65]:     return inner_training_loop(
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank65]:     self._maybe_log_save_evaluate(
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank65]:     self._save_checkpoint(model, trial)
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank65]:     self._save_optimizer_and_scheduler(output_dir)
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank65]:     self.model_wrapped.save_checkpoint(output_dir)
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank65]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank65]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank65]:     return func(*args, **kwargs)
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank65]:     return cdb.barrier(group=group, async_op=async_op)
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank65]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank65]:     return func(*args, **kwargs)
[rank65]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank65]:     work = group.barrier(opts=opts)
[rank65]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 65. 
[rank58]:[E217 15:05:51.779930214 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 58] Process group watchdog thread terminated with exception: [Rank 58] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600048 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78504136c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x784ff6a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x784ff6a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x784ff6a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78504205c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x785045e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x785045f26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 58] Process group watchdog thread terminated with exception: [Rank 58] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600048 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78504136c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x784ff6a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x784ff6a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x784ff6a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x78504205c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x785045e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x785045f26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x78504136c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x784ff66a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x78504205c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x785045e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x785045f26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank62]:[E217 15:05:51.782397182 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 62] Process group watchdog thread terminated with exception: [Rank 62] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x79e32eb6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x79e2e422a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x79e2e4231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x79e2e423361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x79e32f85c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x79e333694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x79e333726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 62] Process group watchdog thread terminated with exception: [Rank 62] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600066 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x79e32eb6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x79e2e422a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x79e2e4231bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x79e2e423361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x79e32f85c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x79e333694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x79e333726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x79e32eb6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x79e2e3ea071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x79e32f85c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x79e333694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x79e333726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank71]: Traceback (most recent call last):
[rank71]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank71]:     train(attn_implementation="flash_attention_2")
[rank71]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank71]:     trainer.train()
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank71]:     return inner_training_loop(
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank71]:     self._maybe_log_save_evaluate(
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank71]:     self._save_checkpoint(model, trial)
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank71]:     self._save_optimizer_and_scheduler(output_dir)
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank71]:     self.model_wrapped.save_checkpoint(output_dir)
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank71]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank71]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank71]:     return func(*args, **kwargs)
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank71]:     return cdb.barrier(group=group, async_op=async_op)
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank71]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank71]:     return func(*args, **kwargs)
[rank71]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank71]:     work = group.barrier(opts=opts)
[rank71]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 71. 
[rank101]:[E217 15:05:51.767115106 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 101] Process group watchdog thread terminated with exception: [Rank 101] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600002 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x76850716c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7684bc82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7684bc831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7684bc83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7685075635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x76850bc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x76850bd26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 101] Process group watchdog thread terminated with exception: [Rank 101] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600002 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x76850716c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7684bc82a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7684bc831bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7684bc83361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7685075635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x76850bc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x76850bd26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x76850716c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7684bc4a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7685075635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x76850bc94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x76850bd26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank71]:[E217 15:05:51.919296297 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 71] Process group watchdog thread terminated with exception: [Rank 71] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72f5b236c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72f567a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72f567a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72f567a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72f5b27635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72f5b6e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72f5b6f26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
[rank99]: Traceback (most recent call last):
[rank99]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank99]:     train(attn_implementation="flash_attention_2")
[rank99]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank99]:     trainer.train()
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank99]:     return inner_training_loop(
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank99]:     self._maybe_log_save_evaluate(
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank99]:     self._save_checkpoint(model, trial)
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank99]:     self._save_optimizer_and_scheduler(output_dir)
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank99]:     self.model_wrapped.save_checkpoint(output_dir)
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank99]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank99]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank99]:     return func(*args, **kwargs)
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank99]:     return cdb.barrier(group=group, async_op=async_op)
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank99]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank99]:     return func(*args, **kwargs)
[rank99]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank99]:     work = group.barrier(opts=opts)
[rank99]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 99. 
  what():  [PG ID 1 PG GUID 1 Rank 71] Process group watchdog thread terminated with exception: [Rank 71] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72f5b236c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72f567a2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72f567a31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72f567a3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72f5b27635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72f5b6e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72f5b6f26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72f5b236c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x72f5676a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x72f5b27635c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x72f5b6e94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x72f5b6f26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank92]: Traceback (most recent call last):
[rank92]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank92]:     train(attn_implementation="flash_attention_2")
[rank92]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank92]:     trainer.train()
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank92]:     return inner_training_loop(
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank92]:     self._maybe_log_save_evaluate(
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank92]:     self._save_checkpoint(model, trial)
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank92]:     self._save_optimizer_and_scheduler(output_dir)
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank92]:     self.model_wrapped.save_checkpoint(output_dir)
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank92]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank92]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank92]:     return func(*args, **kwargs)
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank92]:     return cdb.barrier(group=group, async_op=async_op)
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank92]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank92]:     return func(*args, **kwargs)
[rank92]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank92]:     work = group.barrier(opts=opts)
[rank92]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 92. 
[rank103]: Traceback (most recent call last):
[rank103]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank103]:     train(attn_implementation="flash_attention_2")
[rank103]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank103]:     trainer.train()
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank103]:     return inner_training_loop(
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank103]:     self._maybe_log_save_evaluate(
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank103]:     self._save_checkpoint(model, trial)
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank103]:     self._save_optimizer_and_scheduler(output_dir)
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank103]:     self.model_wrapped.save_checkpoint(output_dir)
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank103]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank103]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank103]:     return func(*args, **kwargs)
[rank92]:[E217 15:05:51.355687720 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 92] Process group watchdog thread terminated with exception: [Rank 92] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600007 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x74acb50e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x74ac6a42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x74ac6a431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank103]:     return cdb.barrier(group=group, async_op=async_op)
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank103]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank103]:     return func(*args, **kwargs)
[rank103]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank103]:     work = group.barrier(opts=opts)
[rank103]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 103. 
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x74ac6a43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x74acb58735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x74acb9a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x74acb9b26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 92] Process group watchdog thread terminated with exception: [Rank 92] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600007 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x74acb50e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x74ac6a42a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x74ac6a431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x74ac6a43361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x74acb58735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x74acb9a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x74acb9b26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x74acb50e7446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x74ac6a0a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x74acb58735c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x74acb9a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x74acb9b26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank65]:[E217 15:05:51.931992981 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 65] Process group watchdog thread terminated with exception: [Rank 65] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72c57176c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72c526e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72c526e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72c526e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72c57245c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72c576294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72c576326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 65] Process group watchdog thread terminated with exception: [Rank 65] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600078 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72c57176c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x72c526e2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x72c526e31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x72c526e3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x72c57245c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x72c576294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x72c576326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x72c57176c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x72c526aa071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x72c57245c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x72c576294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x72c576326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank94]: Traceback (most recent call last):
[rank94]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank94]:     train(attn_implementation="flash_attention_2")
[rank94]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank94]:     trainer.train()
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank94]:     return inner_training_loop(
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank94]:     self._maybe_log_save_evaluate(
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank94]:     self._save_checkpoint(model, trial)
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank94]:     self._save_optimizer_and_scheduler(output_dir)
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank94]:     self.model_wrapped.save_checkpoint(output_dir)
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank94]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank94]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank94]:     return func(*args, **kwargs)
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank94]:     return cdb.barrier(group=group, async_op=async_op)
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank94]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank94]:     return func(*args, **kwargs)
[rank94]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank94]:     work = group.barrier(opts=opts)
[rank94]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 94. 
[rank99]:[E217 15:05:51.791683256 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 99] Process group watchdog thread terminated with exception: [Rank 99] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600093 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x76f6b6376446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x76f66b62a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x76f66b631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x76f66b63361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x76f6b6e555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x76f6bac94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x76f6bad26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 99] Process group watchdog thread terminated with exception: [Rank 99] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600093 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x76f6b6376446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x76f66b62a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x76f66b631bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x76f66b63361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x76f6b6e555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x76f6bac94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x76f6bad26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x76f6b6376446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x76f66b2a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x76f6b6e555c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x76f6bac94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x76f6bad26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank90]: Traceback (most recent call last):
[rank90]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train_mem.py", line 4, in <module>
[rank90]:     train(attn_implementation="flash_attention_2")
[rank90]:   File "/opt/hpcaas/.mounts/fs-036153e63d56f4dc2/home/zhaojiang/interleaved-llava/llava/train/train.py", line 1633, in train
[rank90]:     trainer.train()
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2241, in train
[rank90]:     return inner_training_loop(
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 2612, in _inner_training_loop
[rank90]:     self._maybe_log_save_evaluate(
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3092, in _maybe_log_save_evaluate
[rank90]:     self._save_checkpoint(model, trial)
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3194, in _save_checkpoint
[rank90]:     self._save_optimizer_and_scheduler(output_dir)
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/transformers/trainer.py", line 3305, in _save_optimizer_and_scheduler
[rank90]:     self.model_wrapped.save_checkpoint(output_dir)
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3205, in save_checkpoint
[rank90]:     self._create_zero_checkpoint_files(save_dir, tag)
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/runtime/engine.py", line 3376, in _create_zero_checkpoint_files
[rank90]:     dist.barrier(group=self.optimizer.dp_process_group)
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 117, in log_wrapper
[rank90]:     return func(*args, **kwargs)
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/comm.py", line 408, in barrier
[rank90]:     return cdb.barrier(group=group, async_op=async_op)
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/deepspeed/comm/torch.py", line 336, in barrier
[rank90]:     return torch.distributed.barrier(group=group, async_op=async_op, device_ids=device_ids)
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 83, in wrapper
[rank90]:     return func(*args, **kwargs)
[rank90]:   File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 4159, in barrier
[rank90]:     work = group.barrier(opts=opts)
[rank90]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 90. 
[rank103]:[E217 15:05:51.801994813 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 103] Process group watchdog thread terminated with exception: [Rank 103] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600097 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70205056c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x702005c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x702005c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x702005c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x70205125c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x702055294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x702055326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 103] Process group watchdog thread terminated with exception: [Rank 103] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600097 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70205056c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x702005c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x702005c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x702005c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x70205125c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x702055294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x702055326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x70205056c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7020058a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x70205125c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x702055294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x702055326850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank94]:[E217 15:05:51.373932509 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 94] Process group watchdog thread terminated with exception: [Rank 94] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600018 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a3b93d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a3b4942a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a3b49431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a3b4943361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a3b94e5d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a3b98a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a3b98b26850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 94] Process group watchdog thread terminated with exception: [Rank 94] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600018 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a3b93d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7a3b4942a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7a3b49431bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7a3b4943361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7a3b94e5d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7a3b98a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7a3b98b26850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7a3b93d6c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7a3b490a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7a3b94e5d5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7a3b98a94ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7a3b98b26850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank90]:[E217 15:05:51.419199340 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 90] Process group watchdog thread terminated with exception: [Rank 90] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7997f996c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7997af02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7997af031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7997af03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7997fa65c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7997fe694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7997fe726850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 90] Process group watchdog thread terminated with exception: [Rank 90] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600052 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7997f996c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x7997af02a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x7997af031bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7997af03361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7997fa65c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7997fe694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x7997fe726850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7997f996c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x7997aeca071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7997fa65c5c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7997fe694ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x7997fe726850 in /lib/x86_64-linux-gnu/libc.so.6)

[rank60]:[E217 15:05:51.883075470 ProcessGroupNCCL.cpp:1595] [PG ID 1 PG GUID 1 Rank 60] Process group watchdog thread terminated with exception: [Rank 60] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600039 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x751c4256c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x751bf7c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x751bf7c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x751bf7c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x751c429e45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x751c47294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x751c47326850 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 60] Process group watchdog thread terminated with exception: [Rank 60] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=66413, OpType=ALLREDUCE, NumelIn=1, NumelOut=1, Timeout(ms)=600000) ran for 600039 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:618 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x751c4256c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x282 (0x751bf7c2a772 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x233 (0x751bf7c31bb3 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x751bf7c3361d in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x751c429e45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x751c47294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: <unknown function> + 0x126850 (0x751c47326850 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1601 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x751c4256c446 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe4271b (0x751bf78a071b in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x751c429e45c0 in /home/zhaojiang/.local/lib/python3.10/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x751c47294ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: <unknown function> + 0x126850 (0x751c47326850 in /lib/x86_64-linux-gnu/libc.so.6)

W0217 15:06:22.676000 237666 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 237822 closing signal SIGTERM
W0217 15:06:22.686000 2598810 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2599571 closing signal SIGTERM
W0217 15:06:22.689000 2578773 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2580234 closing signal SIGTERM
W0217 15:06:22.694000 2629720 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2630496 closing signal SIGTERM
W0217 15:06:22.699000 2598122 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2598255 closing signal SIGTERM
W0217 15:06:22.705000 1019786 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1020157 closing signal SIGTERM
W0217 15:06:22.712000 2614682 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2614815 closing signal SIGTERM
W0217 15:06:22.713000 2608625 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2610225 closing signal SIGTERM
W0217 15:06:22.726000 233265 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 234570 closing signal SIGTERM
W0217 15:06:22.730000 2598250 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2598933 closing signal SIGTERM
W0217 15:06:22.731000 2570963 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2572601 closing signal SIGTERM
W0217 15:06:22.731000 262236 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 262370 closing signal SIGTERM
W0217 15:06:22.733000 262147 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 262272 closing signal SIGTERM
W0217 15:06:22.734000 2621360 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2622122 closing signal SIGTERM
W0217 15:06:22.768000 4078901 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 4079622 closing signal SIGTERM
[rank0]:[E217 15:06:27.739914174 ProcessGroupNCCL.cpp:1484] [PG ID 0 PG GUID 0(default_pg) Rank 0] ProcessGroupNCCL's watchdog got stuck for 480 seconds without making progress in monitoring enqueued collectives. This typically indicates a NCCL/CUDA API (e.g., CudaEventDestroy) hang blocking the watchdog, and could be triggered by another thread holding the GIL inside a CUDA api (for example, CudaEventDestroy), or other deadlock-prone behaviors.If you suspect the watchdog is not actually stuck and a longer timeout would help, you can either increase the timeout (TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC) to a larger value or disable the heartbeat monitor (TORCH_NCCL_ENABLE_MONITORING=0).If either of aforementioned helps, feel free to file an issue to PyTorch about the short timeout or false positive abort; otherwise, please attempt to debug the hang. 
W0217 15:06:52.682000 237666 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 237822 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.690000 2598810 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 2599571 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.693000 2578773 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 2580234 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.699000 2629720 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 2630496 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.703000 2598122 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 2598255 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.709000 1019786 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 1020157 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.717000 2614682 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 2614815 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.717000 2608625 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 2610225 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.730000 233265 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 234570 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.734000 2598250 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 2598933 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.735000 2570963 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 2572601 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.736000 262236 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 262370 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.737000 262147 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 262272 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.738000 2621360 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 2622122 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
W0217 15:06:52.772000 4078901 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:916] Unable to shutdown process 4079622 via Signals.SIGTERM, forcefully exiting via Signals.SIGKILL
E0217 15:07:18.101000 2608625 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:869] failed (exitcode: -6) local_rank: 1 (pid: 2610226) of binary: /usr/bin/python3.10
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 269, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
========================================================
llava/train/train_mem.py FAILED
--------------------------------------------------------
Failures:
[1]:
  time      : 2025-02-17_15:06:22
  host      : h100-st-p548xlarge-421.ar-ai-use2.hpcaas
  rank      : 122 (local_rank: 2)
  exitcode  : -6 (pid: 2610227)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2610227
[2]:
  time      : 2025-02-17_15:06:22
  host      : h100-st-p548xlarge-421.ar-ai-use2.hpcaas
  rank      : 123 (local_rank: 3)
  exitcode  : -6 (pid: 2610228)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2610228
[3]:
  time      : 2025-02-17_15:06:22
  host      : h100-st-p548xlarge-421.ar-ai-use2.hpcaas
  rank      : 124 (local_rank: 4)
  exitcode  : -6 (pid: 2610229)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2610229
[4]:
  time      : 2025-02-17_15:06:22
  host      : h100-st-p548xlarge-421.ar-ai-use2.hpcaas
  rank      : 125 (local_rank: 5)
  exitcode  : -6 (pid: 2610230)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2610230
[5]:
  time      : 2025-02-17_15:06:22
  host      : h100-st-p548xlarge-421.ar-ai-use2.hpcaas
  rank      : 126 (local_rank: 6)
  exitcode  : -6 (pid: 2610231)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2610231
[6]:
  time      : 2025-02-17_15:06:22
  host      : h100-st-p548xlarge-421.ar-ai-use2.hpcaas
  rank      : 127 (local_rank: 7)
  exitcode  : -6 (pid: 2610232)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2610232
--------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2025-02-17_15:06:22
  host      : h100-st-p548xlarge-421.ar-ai-use2.hpcaas
  rank      : 121 (local_rank: 1)
  exitcode  : -6 (pid: 2610226)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 2610226
========================================================
srun: error: h100-st-p548xlarge-421: task 15: Exited with exit code 1
srun: Terminating StepId=335933.0
slurmstepd: error: *** STEP 335933.0 ON h100-st-p548xlarge-10 CANCELLED AT 2025-02-17T15:07:19 ***
W0217 15:07:19.214000 262147 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 233265 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 1019786 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 2598122 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 2621360 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 2598250 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 262236 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 2614682 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 2570963 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 4078901 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 237666 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 2578773 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 2598810 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.214000 2629720 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.220000 262147 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 262272 closing signal SIGTERM
W0217 15:07:19.220000 233265 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 234570 closing signal SIGTERM
W0217 15:07:19.221000 2598122 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2598255 closing signal SIGTERM
W0217 15:07:19.220000 2598250 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2598933 closing signal SIGTERM
W0217 15:07:19.221000 2621360 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2622122 closing signal SIGTERM
W0217 15:07:19.220000 2614682 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2614815 closing signal SIGTERM
W0217 15:07:19.221000 2570963 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2572601 closing signal SIGTERM
W0217 15:07:19.214000 1533179 .local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py:704] Received Signals.SIGTERM death signal, shutting down workers
W0217 15:07:19.220000 1019786 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1020157 closing signal SIGTERM
W0217 15:07:19.220000 237666 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 237822 closing signal SIGTERM
W0217 15:07:19.220000 4078901 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 4079622 closing signal SIGTERM
W0217 15:07:19.221000 2578773 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2580234 closing signal SIGTERM
W0217 15:07:19.221000 262236 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 262370 closing signal SIGTERM
W0217 15:07:19.221000 2598810 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2599571 closing signal SIGTERM
W0217 15:07:19.221000 2629720 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 2630496 closing signal SIGTERM
W0217 15:07:19.221000 1533179 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1533945 closing signal SIGTERM
W0217 15:07:19.222000 1533179 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1533946 closing signal SIGTERM
W0217 15:07:19.223000 1533179 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1533947 closing signal SIGTERM
W0217 15:07:19.223000 1533179 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1533948 closing signal SIGTERM
W0217 15:07:19.225000 1533179 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1533949 closing signal SIGTERM
W0217 15:07:19.226000 1533179 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1533950 closing signal SIGTERM
W0217 15:07:19.227000 1533179 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1533951 closing signal SIGTERM
W0217 15:07:19.228000 1533179 .local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 1533952 closing signal SIGTERM
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2578773 got signal: 15
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2598810 got signal: 15
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 4078901 got signal: 15
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2598122 got signal: 15
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 237666 got signal: 15
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2614682 got signal: 15
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2570963 got signal: 15
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2629720 got signal: 15
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1019786 got signal: 15
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 262147 got signal: 15
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2598250 got signal: 15
srun: error: h100-st-p548xlarge-414: task 11: Exited with exit code 1
srun: error: h100-st-p548xlarge-420: task 14: Exited with exit code 1
srun: error: h100-st-p548xlarge-40: task 2: Exited with exit code 1
srun: error: h100-st-p548xlarge-409: task 7: Exited with exit code 1
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 262236 got signal: 15
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 233265 got signal: 15
srun: error: h100-st-p548xlarge-43: task 3: Exited with exit code 1
srun: error: h100-st-p548xlarge-412: task 10: Exited with exit code 1
srun: error: h100-st-p548xlarge-411: task 9: Exited with exit code 1
srun: error: h100-st-p548xlarge-419: task 13: Exited with exit code 1
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 856, in _invoke_run
    run_result = self._monitor_workers(self._worker_group)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/local_elastic_agent.py", line 387, in _monitor_workers
    result = self._pcontext.wait(0)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 531, in wait
    return self._poll()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 861, in _poll
    self.close()  # terminate all running procs
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 572, in close
    self._close(death_sig=death_sig, timeout=timeout)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 923, in _close
    handler.proc.wait()
  File "/usr/lib/python3.10/subprocess.py", line 1209, in wait
    return self._wait(timeout=timeout)
  File "/usr/lib/python3.10/subprocess.py", line 1959, in _wait
    (pid, sts) = self._try_wait(0)
  File "/usr/lib/python3.10/subprocess.py", line 1917, in _try_wait
    (pid, sts) = os.waitpid(self.pid, wait_flags)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 2621360 got signal: 15
srun: error: h100-st-p548xlarge-185: task 6: Exited with exit code 1
srun: error: h100-st-p548xlarge-46: task 4: Exited with exit code 1
srun: error: h100-st-p548xlarge-415: task 12: Exited with exit code 1
srun: error: h100-st-p548xlarge-39: task 1: Exited with exit code 1
srun: error: h100-st-p548xlarge-184: task 5: Exited with exit code 1
srun: error: h100-st-p548xlarge-410: task 8: Exited with exit code 1
Traceback (most recent call last):
  File "/home/zhaojiang/.local/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 260, in launch_agent
    result = agent.run()
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 137, in wrapper
    result = f(*args, **kwargs)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 696, in run
    result = self._invoke_run(role)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 855, in _invoke_run
    time.sleep(monitor_interval)
  File "/home/zhaojiang/.local/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 84, in _terminate_process_handler
    raise SignalException(f"Process {os.getpid()} got signal: {sigval}", sigval=sigval)
torch.distributed.elastic.multiprocessing.api.SignalException: Process 1533179 got signal: 15
srun: error: h100-st-p548xlarge-10: task 0: Exited with exit code 1