| [2025-01-29 08:39:12,791][00651] Saving configuration to /content/train_dir/default_experiment/config.json... | |
| [2025-01-29 08:39:12,795][00651] Rollout worker 0 uses device cpu | |
| [2025-01-29 08:39:12,797][00651] Rollout worker 1 uses device cpu | |
| [2025-01-29 08:39:12,798][00651] Rollout worker 2 uses device cpu | |
| [2025-01-29 08:39:12,799][00651] Rollout worker 3 uses device cpu | |
| [2025-01-29 08:39:12,801][00651] Rollout worker 4 uses device cpu | |
| [2025-01-29 08:39:12,802][00651] Rollout worker 5 uses device cpu | |
| [2025-01-29 08:39:12,804][00651] Rollout worker 6 uses device cpu | |
| [2025-01-29 08:39:12,805][00651] Rollout worker 7 uses device cpu | |
| [2025-01-29 08:39:12,953][00651] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-01-29 08:39:12,955][00651] InferenceWorker_p0-w0: min num requests: 2 | |
| [2025-01-29 08:39:12,989][00651] Starting all processes... | |
| [2025-01-29 08:39:12,990][00651] Starting process learner_proc0 | |
| [2025-01-29 08:39:13,045][00651] Starting all processes... | |
| [2025-01-29 08:39:13,053][00651] Starting process inference_proc0-0 | |
| [2025-01-29 08:39:13,055][00651] Starting process rollout_proc0 | |
| [2025-01-29 08:39:13,056][00651] Starting process rollout_proc1 | |
| [2025-01-29 08:39:13,056][00651] Starting process rollout_proc2 | |
| [2025-01-29 08:39:13,056][00651] Starting process rollout_proc3 | |
| [2025-01-29 08:39:13,058][00651] Starting process rollout_proc5 | |
| [2025-01-29 08:39:13,058][00651] Starting process rollout_proc6 | |
| [2025-01-29 08:39:13,058][00651] Starting process rollout_proc7 | |
| [2025-01-29 08:39:13,058][00651] Starting process rollout_proc4 | |
| [2025-01-29 08:39:29,811][02619] Worker 0 uses CPU cores [0] | |
| [2025-01-29 08:39:29,928][02605] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-01-29 08:39:29,934][02605] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0 | |
| [2025-01-29 08:39:29,957][02628] Worker 4 uses CPU cores [0] | |
| [2025-01-29 08:39:29,986][02621] Worker 2 uses CPU cores [0] | |
| [2025-01-29 08:39:29,991][02605] Num visible devices: 1 | |
| [2025-01-29 08:39:30,023][02605] Starting seed is not provided | |
| [2025-01-29 08:39:30,024][02605] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-01-29 08:39:30,024][02605] Initializing actor-critic model on device cuda:0 | |
| [2025-01-29 08:39:30,026][02605] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-01-29 08:39:30,028][02605] RunningMeanStd input shape: (1,) | |
| [2025-01-29 08:39:30,041][02627] Worker 7 uses CPU cores [1] | |
| [2025-01-29 08:39:30,069][02626] Worker 6 uses CPU cores [0] | |
| [2025-01-29 08:39:30,079][02605] ConvEncoder: input_channels=3 | |
| [2025-01-29 08:39:30,089][02620] Worker 1 uses CPU cores [1] | |
| [2025-01-29 08:39:30,146][02623] Worker 5 uses CPU cores [1] | |
| [2025-01-29 08:39:30,164][02622] Worker 3 uses CPU cores [1] | |
| [2025-01-29 08:39:30,182][02618] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-01-29 08:39:30,182][02618] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0 | |
| [2025-01-29 08:39:30,199][02618] Num visible devices: 1 | |
| [2025-01-29 08:39:30,351][02605] Conv encoder output size: 512 | |
| [2025-01-29 08:39:30,351][02605] Policy head output size: 512 | |
| [2025-01-29 08:39:30,403][02605] Created Actor Critic model with architecture: | |
| [2025-01-29 08:39:30,403][02605] ActorCriticSharedWeights( | |
| (obs_normalizer): ObservationNormalizer( | |
| (running_mean_std): RunningMeanStdDictInPlace( | |
| (running_mean_std): ModuleDict( | |
| (obs): RunningMeanStdInPlace() | |
| ) | |
| ) | |
| ) | |
| (returns_normalizer): RecursiveScriptModule(original_name=RunningMeanStdInPlace) | |
| (encoder): VizdoomEncoder( | |
| (basic_encoder): ConvEncoder( | |
| (enc): RecursiveScriptModule( | |
| original_name=ConvEncoderImpl | |
| (conv_head): RecursiveScriptModule( | |
| original_name=Sequential | |
| (0): RecursiveScriptModule(original_name=Conv2d) | |
| (1): RecursiveScriptModule(original_name=ELU) | |
| (2): RecursiveScriptModule(original_name=Conv2d) | |
| (3): RecursiveScriptModule(original_name=ELU) | |
| (4): RecursiveScriptModule(original_name=Conv2d) | |
| (5): RecursiveScriptModule(original_name=ELU) | |
| ) | |
| (mlp_layers): RecursiveScriptModule( | |
| original_name=Sequential | |
| (0): RecursiveScriptModule(original_name=Linear) | |
| (1): RecursiveScriptModule(original_name=ELU) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (core): ModelCoreRNN( | |
| (core): GRU(512, 512) | |
| ) | |
| (decoder): MlpDecoder( | |
| (mlp): Identity() | |
| ) | |
| (critic_linear): Linear(in_features=512, out_features=1, bias=True) | |
| (action_parameterization): ActionParameterizationDefault( | |
| (distribution_linear): Linear(in_features=512, out_features=5, bias=True) | |
| ) | |
| ) | |
| [2025-01-29 08:39:30,666][02605] Using optimizer <class 'torch.optim.adam.Adam'> | |
| [2025-01-29 08:39:32,950][00651] Heartbeat connected on Batcher_0 | |
| [2025-01-29 08:39:32,954][00651] Heartbeat connected on InferenceWorker_p0-w0 | |
| [2025-01-29 08:39:32,963][00651] Heartbeat connected on RolloutWorker_w0 | |
| [2025-01-29 08:39:32,968][00651] Heartbeat connected on RolloutWorker_w1 | |
| [2025-01-29 08:39:32,970][00651] Heartbeat connected on RolloutWorker_w2 | |
| [2025-01-29 08:39:32,973][00651] Heartbeat connected on RolloutWorker_w3 | |
| [2025-01-29 08:39:32,984][00651] Heartbeat connected on RolloutWorker_w4 | |
| [2025-01-29 08:39:32,985][00651] Heartbeat connected on RolloutWorker_w5 | |
| [2025-01-29 08:39:32,986][00651] Heartbeat connected on RolloutWorker_w6 | |
| [2025-01-29 08:39:32,998][00651] Heartbeat connected on RolloutWorker_w7 | |
| [2025-01-29 08:39:35,871][02605] No checkpoints found | |
| [2025-01-29 08:39:35,872][02605] Did not load from checkpoint, starting from scratch! | |
| [2025-01-29 08:39:35,883][02605] Initialized policy 0 weights for model version 0 | |
| [2025-01-29 08:39:35,902][02605] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-01-29 08:39:35,919][02605] LearnerWorker_p0 finished initialization! | |
| [2025-01-29 08:39:35,920][00651] Heartbeat connected on LearnerWorker_p0 | |
| [2025-01-29 08:39:36,269][02618] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-01-29 08:39:36,272][02618] RunningMeanStd input shape: (1,) | |
| [2025-01-29 08:39:36,290][02618] ConvEncoder: input_channels=3 | |
| [2025-01-29 08:39:36,558][02618] Conv encoder output size: 512 | |
| [2025-01-29 08:39:36,559][02618] Policy head output size: 512 | |
| [2025-01-29 08:39:36,614][00651] Inference worker 0-0 is ready! | |
| [2025-01-29 08:39:36,615][00651] All inference workers are ready! Signal rollout workers to start! | |
| [2025-01-29 08:39:36,837][02621] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-01-29 08:39:36,839][02626] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-01-29 08:39:36,841][02628] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-01-29 08:39:36,847][02619] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-01-29 08:39:36,866][02627] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-01-29 08:39:36,870][02622] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-01-29 08:39:36,875][02623] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-01-29 08:39:36,872][02620] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-01-29 08:39:37,768][00651] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 0. Throughput: 0: nan. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-01-29 08:39:38,240][02628] Decorrelating experience for 0 frames... | |
| [2025-01-29 08:39:38,241][02626] Decorrelating experience for 0 frames... | |
| [2025-01-29 08:39:38,239][02621] Decorrelating experience for 0 frames... | |
| [2025-01-29 08:39:38,636][02623] Decorrelating experience for 0 frames... | |
| [2025-01-29 08:39:38,638][02627] Decorrelating experience for 0 frames... | |
| [2025-01-29 08:39:38,640][02620] Decorrelating experience for 0 frames... | |
| [2025-01-29 08:39:38,650][02622] Decorrelating experience for 0 frames... | |
| [2025-01-29 08:39:38,982][02626] Decorrelating experience for 32 frames... | |
| [2025-01-29 08:39:38,984][02619] Decorrelating experience for 0 frames... | |
| [2025-01-29 08:39:39,497][02628] Decorrelating experience for 32 frames... | |
| [2025-01-29 08:39:39,792][02622] Decorrelating experience for 32 frames... | |
| [2025-01-29 08:39:39,803][02623] Decorrelating experience for 32 frames... | |
| [2025-01-29 08:39:39,805][02627] Decorrelating experience for 32 frames... | |
| [2025-01-29 08:39:40,821][02621] Decorrelating experience for 32 frames... | |
| [2025-01-29 08:39:40,861][02620] Decorrelating experience for 32 frames... | |
| [2025-01-29 08:39:41,090][02627] Decorrelating experience for 64 frames... | |
| [2025-01-29 08:39:41,256][02628] Decorrelating experience for 64 frames... | |
| [2025-01-29 08:39:41,422][02626] Decorrelating experience for 64 frames... | |
| [2025-01-29 08:39:41,436][02619] Decorrelating experience for 32 frames... | |
| [2025-01-29 08:39:41,960][02621] Decorrelating experience for 64 frames... | |
| [2025-01-29 08:39:41,990][02627] Decorrelating experience for 96 frames... | |
| [2025-01-29 08:39:42,460][02622] Decorrelating experience for 64 frames... | |
| [2025-01-29 08:39:42,670][02623] Decorrelating experience for 64 frames... | |
| [2025-01-29 08:39:42,768][00651] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-01-29 08:39:43,396][02626] Decorrelating experience for 96 frames... | |
| [2025-01-29 08:39:43,440][02623] Decorrelating experience for 96 frames... | |
| [2025-01-29 08:39:43,518][02619] Decorrelating experience for 64 frames... | |
| [2025-01-29 08:39:43,590][02621] Decorrelating experience for 96 frames... | |
| [2025-01-29 08:39:44,246][02622] Decorrelating experience for 96 frames... | |
| [2025-01-29 08:39:44,575][02628] Decorrelating experience for 96 frames... | |
| [2025-01-29 08:39:47,394][02619] Decorrelating experience for 96 frames... | |
| [2025-01-29 08:39:47,768][00651] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 59.4. Samples: 594. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-01-29 08:39:47,774][00651] Avg episode reward: [(0, '2.047')] | |
| [2025-01-29 08:39:49,903][02605] Signal inference workers to stop experience collection... | |
| [2025-01-29 08:39:49,929][02618] InferenceWorker_p0-w0: stopping experience collection | |
| [2025-01-29 08:39:49,983][02620] Decorrelating experience for 64 frames... | |
| [2025-01-29 08:39:51,189][02620] Decorrelating experience for 96 frames... | |
| [2025-01-29 08:39:52,768][00651] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 153.6. Samples: 2304. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-01-29 08:39:52,773][00651] Avg episode reward: [(0, '2.487')] | |
| [2025-01-29 08:39:53,205][02605] Signal inference workers to resume experience collection... | |
| [2025-01-29 08:39:53,206][02618] InferenceWorker_p0-w0: resuming experience collection | |
| [2025-01-29 08:39:57,768][00651] Fps is (10 sec: 2457.5, 60 sec: 1228.8, 300 sec: 1228.8). Total num frames: 24576. Throughput: 0: 350.5. Samples: 7010. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:39:57,771][00651] Avg episode reward: [(0, '3.574')] | |
| [2025-01-29 08:40:01,149][02618] Updated weights for policy 0, policy_version 10 (0.0024) | |
| [2025-01-29 08:40:02,768][00651] Fps is (10 sec: 4505.6, 60 sec: 1802.2, 300 sec: 1802.2). Total num frames: 45056. Throughput: 0: 413.0. Samples: 10324. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:40:02,771][00651] Avg episode reward: [(0, '4.299')] | |
| [2025-01-29 08:40:07,771][00651] Fps is (10 sec: 3685.6, 60 sec: 2047.8, 300 sec: 2047.8). Total num frames: 61440. Throughput: 0: 503.3. Samples: 15100. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:40:07,773][00651] Avg episode reward: [(0, '4.484')] | |
| [2025-01-29 08:40:12,768][00651] Fps is (10 sec: 3276.8, 60 sec: 2223.5, 300 sec: 2223.5). Total num frames: 77824. Throughput: 0: 593.9. Samples: 20788. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:40:12,774][00651] Avg episode reward: [(0, '4.379')] | |
| [2025-01-29 08:40:12,985][02618] Updated weights for policy 0, policy_version 20 (0.0033) | |
| [2025-01-29 08:40:17,768][00651] Fps is (10 sec: 3687.4, 60 sec: 2457.6, 300 sec: 2457.6). Total num frames: 98304. Throughput: 0: 605.4. Samples: 24214. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:40:17,774][00651] Avg episode reward: [(0, '4.320')] | |
| [2025-01-29 08:40:22,770][00651] Fps is (10 sec: 3685.8, 60 sec: 2548.5, 300 sec: 2548.5). Total num frames: 114688. Throughput: 0: 650.3. Samples: 29266. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:40:22,774][00651] Avg episode reward: [(0, '4.439')] | |
| [2025-01-29 08:40:22,777][02605] Saving new best policy, reward=4.439! | |
| [2025-01-29 08:40:25,128][02618] Updated weights for policy 0, policy_version 30 (0.0014) | |
| [2025-01-29 08:40:27,768][00651] Fps is (10 sec: 3276.8, 60 sec: 2621.4, 300 sec: 2621.4). Total num frames: 131072. Throughput: 0: 744.4. Samples: 33500. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:40:27,771][00651] Avg episode reward: [(0, '4.460')] | |
| [2025-01-29 08:40:27,778][02605] Saving new best policy, reward=4.460! | |
| [2025-01-29 08:40:32,768][00651] Fps is (10 sec: 3687.0, 60 sec: 2755.5, 300 sec: 2755.5). Total num frames: 151552. Throughput: 0: 801.4. Samples: 36656. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:40:32,774][00651] Avg episode reward: [(0, '4.565')] | |
| [2025-01-29 08:40:32,778][02605] Saving new best policy, reward=4.565! | |
| [2025-01-29 08:40:35,403][02618] Updated weights for policy 0, policy_version 40 (0.0016) | |
| [2025-01-29 08:40:37,768][00651] Fps is (10 sec: 3686.4, 60 sec: 2798.9, 300 sec: 2798.9). Total num frames: 167936. Throughput: 0: 900.5. Samples: 42828. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:40:37,772][00651] Avg episode reward: [(0, '4.607')] | |
| [2025-01-29 08:40:37,780][02605] Saving new best policy, reward=4.607! | |
| [2025-01-29 08:40:42,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3072.0, 300 sec: 2835.7). Total num frames: 184320. Throughput: 0: 879.7. Samples: 46596. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:40:42,772][00651] Avg episode reward: [(0, '4.509')] | |
| [2025-01-29 08:40:47,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3345.1, 300 sec: 2867.2). Total num frames: 200704. Throughput: 0: 857.4. Samples: 48906. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:40:47,773][00651] Avg episode reward: [(0, '4.353')] | |
| [2025-01-29 08:40:48,576][02618] Updated weights for policy 0, policy_version 50 (0.0036) | |
| [2025-01-29 08:40:52,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 2949.1). Total num frames: 221184. Throughput: 0: 888.5. Samples: 55082. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:40:52,773][00651] Avg episode reward: [(0, '4.246')] | |
| [2025-01-29 08:40:57,770][00651] Fps is (10 sec: 3685.8, 60 sec: 3549.8, 300 sec: 2969.5). Total num frames: 237568. Throughput: 0: 885.8. Samples: 60652. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:40:57,772][00651] Avg episode reward: [(0, '4.426')] | |
| [2025-01-29 08:40:59,502][02618] Updated weights for policy 0, policy_version 60 (0.0022) | |
| [2025-01-29 08:41:02,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 2987.7). Total num frames: 253952. Throughput: 0: 856.7. Samples: 62766. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:41:02,775][00651] Avg episode reward: [(0, '4.634')] | |
| [2025-01-29 08:41:02,778][02605] Saving new best policy, reward=4.634! | |
| [2025-01-29 08:41:07,768][00651] Fps is (10 sec: 4096.6, 60 sec: 3618.3, 300 sec: 3094.8). Total num frames: 278528. Throughput: 0: 882.3. Samples: 68968. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:41:07,771][00651] Avg episode reward: [(0, '4.573')] | |
| [2025-01-29 08:41:07,780][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000068_278528.pth... | |
| [2025-01-29 08:41:09,425][02618] Updated weights for policy 0, policy_version 70 (0.0012) | |
| [2025-01-29 08:41:12,771][00651] Fps is (10 sec: 4504.3, 60 sec: 3686.2, 300 sec: 3147.4). Total num frames: 299008. Throughput: 0: 944.7. Samples: 76012. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:41:12,777][00651] Avg episode reward: [(0, '4.387')] | |
| [2025-01-29 08:41:17,768][00651] Fps is (10 sec: 3686.3, 60 sec: 3618.1, 300 sec: 3153.9). Total num frames: 315392. Throughput: 0: 922.5. Samples: 78170. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-01-29 08:41:17,771][00651] Avg episode reward: [(0, '4.418')] | |
| [2025-01-29 08:41:20,964][02618] Updated weights for policy 0, policy_version 80 (0.0016) | |
| [2025-01-29 08:41:22,768][00651] Fps is (10 sec: 3277.7, 60 sec: 3618.2, 300 sec: 3159.8). Total num frames: 331776. Throughput: 0: 899.0. Samples: 83282. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:41:22,773][00651] Avg episode reward: [(0, '4.407')] | |
| [2025-01-29 08:41:27,768][00651] Fps is (10 sec: 4096.1, 60 sec: 3754.7, 300 sec: 3239.6). Total num frames: 356352. Throughput: 0: 974.4. Samples: 90446. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:41:27,773][00651] Avg episode reward: [(0, '4.363')] | |
| [2025-01-29 08:41:29,611][02618] Updated weights for policy 0, policy_version 90 (0.0032) | |
| [2025-01-29 08:41:32,768][00651] Fps is (10 sec: 4505.6, 60 sec: 3754.7, 300 sec: 3276.8). Total num frames: 376832. Throughput: 0: 992.9. Samples: 93588. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:41:32,771][00651] Avg episode reward: [(0, '4.498')] | |
| [2025-01-29 08:41:37,768][00651] Fps is (10 sec: 3686.3, 60 sec: 3754.7, 300 sec: 3276.8). Total num frames: 393216. Throughput: 0: 952.5. Samples: 97946. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:41:37,771][00651] Avg episode reward: [(0, '4.734')] | |
| [2025-01-29 08:41:37,780][02605] Saving new best policy, reward=4.734! | |
| [2025-01-29 08:41:41,221][02618] Updated weights for policy 0, policy_version 100 (0.0024) | |
| [2025-01-29 08:41:42,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3309.6). Total num frames: 413696. Throughput: 0: 973.1. Samples: 104440. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:41:42,776][00651] Avg episode reward: [(0, '4.693')] | |
| [2025-01-29 08:41:47,771][00651] Fps is (10 sec: 4095.0, 60 sec: 3891.0, 300 sec: 3339.7). Total num frames: 434176. Throughput: 0: 1002.6. Samples: 107886. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:41:47,788][00651] Avg episode reward: [(0, '4.544')] | |
| [2025-01-29 08:41:52,410][02618] Updated weights for policy 0, policy_version 110 (0.0017) | |
| [2025-01-29 08:41:52,770][00651] Fps is (10 sec: 3685.7, 60 sec: 3822.8, 300 sec: 3337.4). Total num frames: 450560. Throughput: 0: 972.1. Samples: 112716. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:41:52,773][00651] Avg episode reward: [(0, '4.553')] | |
| [2025-01-29 08:41:57,768][00651] Fps is (10 sec: 3687.4, 60 sec: 3891.3, 300 sec: 3364.6). Total num frames: 471040. Throughput: 0: 941.3. Samples: 118366. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:41:57,773][00651] Avg episode reward: [(0, '4.535')] | |
| [2025-01-29 08:42:02,067][02618] Updated weights for policy 0, policy_version 120 (0.0042) | |
| [2025-01-29 08:42:02,768][00651] Fps is (10 sec: 4096.8, 60 sec: 3959.5, 300 sec: 3389.8). Total num frames: 491520. Throughput: 0: 971.3. Samples: 121880. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:42:02,775][00651] Avg episode reward: [(0, '4.568')] | |
| [2025-01-29 08:42:07,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3413.3). Total num frames: 512000. Throughput: 0: 991.8. Samples: 127914. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:42:07,773][00651] Avg episode reward: [(0, '4.717')] | |
| [2025-01-29 08:42:12,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3823.1, 300 sec: 3408.9). Total num frames: 528384. Throughput: 0: 937.1. Samples: 132614. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:42:12,770][00651] Avg episode reward: [(0, '4.945')] | |
| [2025-01-29 08:42:12,789][02605] Saving new best policy, reward=4.945! | |
| [2025-01-29 08:42:13,697][02618] Updated weights for policy 0, policy_version 130 (0.0015) | |
| [2025-01-29 08:42:17,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3430.4). Total num frames: 548864. Throughput: 0: 941.7. Samples: 135964. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:42:17,771][00651] Avg episode reward: [(0, '4.817')] | |
| [2025-01-29 08:42:22,770][00651] Fps is (10 sec: 4095.3, 60 sec: 3959.4, 300 sec: 3450.5). Total num frames: 569344. Throughput: 0: 998.0. Samples: 142856. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:42:22,777][00651] Avg episode reward: [(0, '4.863')] | |
| [2025-01-29 08:42:22,860][02618] Updated weights for policy 0, policy_version 140 (0.0015) | |
| [2025-01-29 08:42:27,771][00651] Fps is (10 sec: 3685.5, 60 sec: 3822.8, 300 sec: 3445.4). Total num frames: 585728. Throughput: 0: 952.8. Samples: 147318. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:42:27,773][00651] Avg episode reward: [(0, '4.840')] | |
| [2025-01-29 08:42:32,768][00651] Fps is (10 sec: 3687.0, 60 sec: 3822.9, 300 sec: 3464.0). Total num frames: 606208. Throughput: 0: 937.8. Samples: 150086. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-01-29 08:42:32,770][00651] Avg episode reward: [(0, '4.756')] | |
| [2025-01-29 08:42:34,162][02618] Updated weights for policy 0, policy_version 150 (0.0022) | |
| [2025-01-29 08:42:37,768][00651] Fps is (10 sec: 4506.7, 60 sec: 3959.5, 300 sec: 3504.4). Total num frames: 630784. Throughput: 0: 989.1. Samples: 157222. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:42:37,771][00651] Avg episode reward: [(0, '4.626')] | |
| [2025-01-29 08:42:42,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3498.2). Total num frames: 647168. Throughput: 0: 987.6. Samples: 162810. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:42:42,773][00651] Avg episode reward: [(0, '4.641')] | |
| [2025-01-29 08:42:44,798][02618] Updated weights for policy 0, policy_version 160 (0.0017) | |
| [2025-01-29 08:42:47,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3823.1, 300 sec: 3492.4). Total num frames: 663552. Throughput: 0: 959.6. Samples: 165060. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:42:47,770][00651] Avg episode reward: [(0, '4.874')] | |
| [2025-01-29 08:42:52,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.6, 300 sec: 3528.9). Total num frames: 688128. Throughput: 0: 972.4. Samples: 171670. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:42:52,771][00651] Avg episode reward: [(0, '4.789')] | |
| [2025-01-29 08:42:54,194][02618] Updated weights for policy 0, policy_version 170 (0.0025) | |
| [2025-01-29 08:42:57,768][00651] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3543.0). Total num frames: 708608. Throughput: 0: 1008.1. Samples: 177978. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:42:57,772][00651] Avg episode reward: [(0, '4.869')] | |
| [2025-01-29 08:43:02,771][00651] Fps is (10 sec: 3275.9, 60 sec: 3822.8, 300 sec: 3516.5). Total num frames: 720896. Throughput: 0: 980.6. Samples: 180094. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:43:02,777][00651] Avg episode reward: [(0, '5.023')] | |
| [2025-01-29 08:43:02,780][02605] Saving new best policy, reward=5.023! | |
| [2025-01-29 08:43:05,800][02618] Updated weights for policy 0, policy_version 180 (0.0021) | |
| [2025-01-29 08:43:07,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3549.9). Total num frames: 745472. Throughput: 0: 955.9. Samples: 185868. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:43:07,771][00651] Avg episode reward: [(0, '4.975')] | |
| [2025-01-29 08:43:07,783][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000182_745472.pth... | |
| [2025-01-29 08:43:12,768][00651] Fps is (10 sec: 4506.8, 60 sec: 3959.4, 300 sec: 3562.6). Total num frames: 765952. Throughput: 0: 1008.6. Samples: 192702. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:43:12,771][00651] Avg episode reward: [(0, '5.011')] | |
| [2025-01-29 08:43:15,491][02618] Updated weights for policy 0, policy_version 190 (0.0018) | |
| [2025-01-29 08:43:17,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3556.1). Total num frames: 782336. Throughput: 0: 1002.6. Samples: 195204. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:43:17,771][00651] Avg episode reward: [(0, '4.959')] | |
| [2025-01-29 08:43:22,768][00651] Fps is (10 sec: 3276.9, 60 sec: 3823.0, 300 sec: 3549.9). Total num frames: 798720. Throughput: 0: 944.2. Samples: 199712. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:43:22,772][00651] Avg episode reward: [(0, '5.299')] | |
| [2025-01-29 08:43:22,776][02605] Saving new best policy, reward=5.299! | |
| [2025-01-29 08:43:26,702][02618] Updated weights for policy 0, policy_version 200 (0.0024) | |
| [2025-01-29 08:43:27,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.6, 300 sec: 3579.5). Total num frames: 823296. Throughput: 0: 973.0. Samples: 206594. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-01-29 08:43:27,770][00651] Avg episode reward: [(0, '5.269')] | |
| [2025-01-29 08:43:32,768][00651] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3590.5). Total num frames: 843776. Throughput: 0: 1000.5. Samples: 210082. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:43:32,775][00651] Avg episode reward: [(0, '5.223')] | |
| [2025-01-29 08:43:37,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3566.9). Total num frames: 856064. Throughput: 0: 950.9. Samples: 214462. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:43:37,771][00651] Avg episode reward: [(0, '5.292')] | |
| [2025-01-29 08:43:38,154][02618] Updated weights for policy 0, policy_version 210 (0.0026) | |
| [2025-01-29 08:43:42,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3594.4). Total num frames: 880640. Throughput: 0: 952.0. Samples: 220816. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:43:42,773][00651] Avg episode reward: [(0, '5.650')] | |
| [2025-01-29 08:43:42,776][02605] Saving new best policy, reward=5.650! | |
| [2025-01-29 08:43:46,988][02618] Updated weights for policy 0, policy_version 220 (0.0024) | |
| [2025-01-29 08:43:47,768][00651] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3604.5). Total num frames: 901120. Throughput: 0: 980.9. Samples: 224234. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:43:47,773][00651] Avg episode reward: [(0, '5.588')] | |
| [2025-01-29 08:43:52,770][00651] Fps is (10 sec: 3685.8, 60 sec: 3822.8, 300 sec: 3598.0). Total num frames: 917504. Throughput: 0: 975.3. Samples: 229756. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:43:52,772][00651] Avg episode reward: [(0, '5.476')] | |
| [2025-01-29 08:43:57,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3607.6). Total num frames: 937984. Throughput: 0: 941.5. Samples: 235068. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:43:57,772][00651] Avg episode reward: [(0, '5.610')] | |
| [2025-01-29 08:43:58,595][02618] Updated weights for policy 0, policy_version 230 (0.0034) | |
| [2025-01-29 08:44:02,768][00651] Fps is (10 sec: 4096.6, 60 sec: 3959.6, 300 sec: 3616.8). Total num frames: 958464. Throughput: 0: 961.0. Samples: 238450. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:44:02,772][00651] Avg episode reward: [(0, '5.781')] | |
| [2025-01-29 08:44:02,774][02605] Saving new best policy, reward=5.781! | |
| [2025-01-29 08:44:07,769][00651] Fps is (10 sec: 4095.8, 60 sec: 3891.2, 300 sec: 3625.7). Total num frames: 978944. Throughput: 0: 1011.6. Samples: 245234. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:44:07,771][00651] Avg episode reward: [(0, '6.119')] | |
| [2025-01-29 08:44:07,786][02605] Saving new best policy, reward=6.119! | |
| [2025-01-29 08:44:08,377][02618] Updated weights for policy 0, policy_version 240 (0.0029) | |
| [2025-01-29 08:44:12,771][00651] Fps is (10 sec: 3685.6, 60 sec: 3822.8, 300 sec: 3619.3). Total num frames: 995328. Throughput: 0: 949.5. Samples: 249324. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:44:12,776][00651] Avg episode reward: [(0, '6.496')] | |
| [2025-01-29 08:44:12,780][02605] Saving new best policy, reward=6.496! | |
| [2025-01-29 08:44:17,768][00651] Fps is (10 sec: 3686.6, 60 sec: 3891.2, 300 sec: 3627.9). Total num frames: 1015808. Throughput: 0: 944.3. Samples: 252574. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:44:17,772][00651] Avg episode reward: [(0, '6.585')] | |
| [2025-01-29 08:44:17,779][02605] Saving new best policy, reward=6.585! | |
| [2025-01-29 08:44:19,225][02618] Updated weights for policy 0, policy_version 250 (0.0014) | |
| [2025-01-29 08:44:22,768][00651] Fps is (10 sec: 4506.7, 60 sec: 4027.7, 300 sec: 3650.5). Total num frames: 1040384. Throughput: 0: 996.7. Samples: 259312. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:44:22,770][00651] Avg episode reward: [(0, '6.268')] | |
| [2025-01-29 08:44:27,771][00651] Fps is (10 sec: 3685.4, 60 sec: 3822.8, 300 sec: 3629.9). Total num frames: 1052672. Throughput: 0: 963.4. Samples: 264170. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:44:27,773][00651] Avg episode reward: [(0, '6.022')] | |
| [2025-01-29 08:44:30,887][02618] Updated weights for policy 0, policy_version 260 (0.0018) | |
| [2025-01-29 08:44:32,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3637.8). Total num frames: 1073152. Throughput: 0: 940.7. Samples: 266566. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:44:32,770][00651] Avg episode reward: [(0, '5.799')] | |
| [2025-01-29 08:44:37,768][00651] Fps is (10 sec: 4097.1, 60 sec: 3959.5, 300 sec: 3707.2). Total num frames: 1093632. Throughput: 0: 972.1. Samples: 273498. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:44:37,773][00651] Avg episode reward: [(0, '5.893')] | |
| [2025-01-29 08:44:39,725][02618] Updated weights for policy 0, policy_version 270 (0.0016) | |
| [2025-01-29 08:44:42,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3776.7). Total num frames: 1114112. Throughput: 0: 988.8. Samples: 279564. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:44:42,774][00651] Avg episode reward: [(0, '6.401')] | |
| [2025-01-29 08:44:47,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 1130496. Throughput: 0: 960.6. Samples: 281678. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:44:47,775][00651] Avg episode reward: [(0, '6.380')] | |
| [2025-01-29 08:44:51,084][02618] Updated weights for policy 0, policy_version 280 (0.0013) | |
| [2025-01-29 08:44:52,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.3, 300 sec: 3818.3). Total num frames: 1150976. Throughput: 0: 948.9. Samples: 287932. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:44:52,771][00651] Avg episode reward: [(0, '7.271')] | |
| [2025-01-29 08:44:52,776][02605] Saving new best policy, reward=7.271! | |
| [2025-01-29 08:44:57,774][00651] Fps is (10 sec: 4503.1, 60 sec: 3959.1, 300 sec: 3832.1). Total num frames: 1175552. Throughput: 0: 1010.5. Samples: 294798. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:44:57,786][00651] Avg episode reward: [(0, '7.326')] | |
| [2025-01-29 08:44:57,797][02605] Saving new best policy, reward=7.326! | |
| [2025-01-29 08:45:01,361][02618] Updated weights for policy 0, policy_version 290 (0.0024) | |
| [2025-01-29 08:45:02,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3818.3). Total num frames: 1187840. Throughput: 0: 986.0. Samples: 296946. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:45:02,773][00651] Avg episode reward: [(0, '7.798')] | |
| [2025-01-29 08:45:02,789][02605] Saving new best policy, reward=7.798! | |
| [2025-01-29 08:45:07,768][00651] Fps is (10 sec: 3278.6, 60 sec: 3823.0, 300 sec: 3832.2). Total num frames: 1208320. Throughput: 0: 953.1. Samples: 302200. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:45:07,774][00651] Avg episode reward: [(0, '7.791')] | |
| [2025-01-29 08:45:07,782][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000296_1212416.pth... | |
| [2025-01-29 08:45:07,907][02605] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000068_278528.pth | |
| [2025-01-29 08:45:11,357][02618] Updated weights for policy 0, policy_version 300 (0.0017) | |
| [2025-01-29 08:45:12,768][00651] Fps is (10 sec: 4505.6, 60 sec: 3959.6, 300 sec: 3846.1). Total num frames: 1232896. Throughput: 0: 1004.0. Samples: 309346. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:45:12,774][00651] Avg episode reward: [(0, '8.232')] | |
| [2025-01-29 08:45:12,776][02605] Saving new best policy, reward=8.232! | |
| [2025-01-29 08:45:17,768][00651] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3860.0). Total num frames: 1253376. Throughput: 0: 1019.6. Samples: 312450. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:45:17,774][00651] Avg episode reward: [(0, '7.987')] | |
| [2025-01-29 08:45:22,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3846.1). Total num frames: 1265664. Throughput: 0: 966.1. Samples: 316974. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:45:22,771][00651] Avg episode reward: [(0, '8.079')] | |
| [2025-01-29 08:45:22,803][02618] Updated weights for policy 0, policy_version 310 (0.0040) | |
| [2025-01-29 08:45:27,768][00651] Fps is (10 sec: 3686.3, 60 sec: 3959.6, 300 sec: 3860.0). Total num frames: 1290240. Throughput: 0: 980.8. Samples: 323700. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:45:27,771][00651] Avg episode reward: [(0, '8.440')] | |
| [2025-01-29 08:45:27,780][02605] Saving new best policy, reward=8.440! | |
| [2025-01-29 08:45:31,703][02618] Updated weights for policy 0, policy_version 320 (0.0021) | |
| [2025-01-29 08:45:32,774][00651] Fps is (10 sec: 4503.0, 60 sec: 3959.1, 300 sec: 3873.8). Total num frames: 1310720. Throughput: 0: 1007.9. Samples: 327040. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:45:32,782][00651] Avg episode reward: [(0, '8.839')] | |
| [2025-01-29 08:45:32,785][02605] Saving new best policy, reward=8.839! | |
| [2025-01-29 08:45:37,768][00651] Fps is (10 sec: 3686.5, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 1327104. Throughput: 0: 976.1. Samples: 331858. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:45:37,771][00651] Avg episode reward: [(0, '9.213')] | |
| [2025-01-29 08:45:37,781][02605] Saving new best policy, reward=9.213! | |
| [2025-01-29 08:45:42,774][00651] Fps is (10 sec: 3686.5, 60 sec: 3890.8, 300 sec: 3887.7). Total num frames: 1347584. Throughput: 0: 948.8. Samples: 337492. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:45:42,777][00651] Avg episode reward: [(0, '9.110')] | |
| [2025-01-29 08:45:43,626][02618] Updated weights for policy 0, policy_version 330 (0.0031) | |
| [2025-01-29 08:45:47,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 1368064. Throughput: 0: 975.6. Samples: 340846. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:45:47,773][00651] Avg episode reward: [(0, '8.593')] | |
| [2025-01-29 08:45:52,768][00651] Fps is (10 sec: 3688.4, 60 sec: 3891.2, 300 sec: 3887.8). Total num frames: 1384448. Throughput: 0: 994.4. Samples: 346948. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:45:52,775][00651] Avg episode reward: [(0, '8.779')] | |
| [2025-01-29 08:45:54,312][02618] Updated weights for policy 0, policy_version 340 (0.0013) | |
| [2025-01-29 08:45:57,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3755.0, 300 sec: 3887.7). Total num frames: 1400832. Throughput: 0: 939.6. Samples: 351626. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:45:57,772][00651] Avg episode reward: [(0, '9.764')] | |
| [2025-01-29 08:45:57,786][02605] Saving new best policy, reward=9.764! | |
| [2025-01-29 08:46:02,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 1425408. Throughput: 0: 945.9. Samples: 355014. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:46:02,771][00651] Avg episode reward: [(0, '10.708')] | |
| [2025-01-29 08:46:02,776][02605] Saving new best policy, reward=10.708! | |
| [2025-01-29 08:46:03,961][02618] Updated weights for policy 0, policy_version 350 (0.0017) | |
| [2025-01-29 08:46:07,768][00651] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3887.8). Total num frames: 1445888. Throughput: 0: 999.3. Samples: 361944. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:46:07,774][00651] Avg episode reward: [(0, '10.777')] | |
| [2025-01-29 08:46:07,791][02605] Saving new best policy, reward=10.777! | |
| [2025-01-29 08:46:12,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3887.7). Total num frames: 1462272. Throughput: 0: 945.1. Samples: 366230. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:46:12,775][00651] Avg episode reward: [(0, '10.229')] | |
| [2025-01-29 08:46:15,652][02618] Updated weights for policy 0, policy_version 360 (0.0025) | |
| [2025-01-29 08:46:17,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3901.6). Total num frames: 1482752. Throughput: 0: 934.5. Samples: 369086. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-01-29 08:46:17,773][00651] Avg episode reward: [(0, '10.685')] | |
| [2025-01-29 08:46:22,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 1503232. Throughput: 0: 980.8. Samples: 375994. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:46:22,772][00651] Avg episode reward: [(0, '10.423')] | |
| [2025-01-29 08:46:25,118][02618] Updated weights for policy 0, policy_version 370 (0.0014) | |
| [2025-01-29 08:46:27,770][00651] Fps is (10 sec: 3685.8, 60 sec: 3822.8, 300 sec: 3873.8). Total num frames: 1519616. Throughput: 0: 976.1. Samples: 381412. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:46:27,775][00651] Avg episode reward: [(0, '10.530')] | |
| [2025-01-29 08:46:32,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3823.3, 300 sec: 3887.7). Total num frames: 1540096. Throughput: 0: 950.7. Samples: 383626. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:46:32,775][00651] Avg episode reward: [(0, '9.359')] | |
| [2025-01-29 08:46:36,055][02618] Updated weights for policy 0, policy_version 380 (0.0033) | |
| [2025-01-29 08:46:37,768][00651] Fps is (10 sec: 4506.3, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 1564672. Throughput: 0: 968.5. Samples: 390530. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:46:37,775][00651] Avg episode reward: [(0, '10.652')] | |
| [2025-01-29 08:46:42,768][00651] Fps is (10 sec: 4505.5, 60 sec: 3959.8, 300 sec: 3901.6). Total num frames: 1585152. Throughput: 0: 1012.1. Samples: 397170. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:46:42,779][00651] Avg episode reward: [(0, '11.199')] | |
| [2025-01-29 08:46:42,789][02605] Saving new best policy, reward=11.199! | |
| [2025-01-29 08:46:46,486][02618] Updated weights for policy 0, policy_version 390 (0.0021) | |
| [2025-01-29 08:46:47,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 1601536. Throughput: 0: 983.1. Samples: 399254. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:46:47,775][00651] Avg episode reward: [(0, '12.154')] | |
| [2025-01-29 08:46:47,782][02605] Saving new best policy, reward=12.154! | |
| [2025-01-29 08:46:52,768][00651] Fps is (10 sec: 3686.5, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 1622016. Throughput: 0: 958.1. Samples: 405058. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:46:52,771][00651] Avg episode reward: [(0, '12.392')] | |
| [2025-01-29 08:46:52,774][02605] Saving new best policy, reward=12.392! | |
| [2025-01-29 08:46:56,182][02618] Updated weights for policy 0, policy_version 400 (0.0017) | |
| [2025-01-29 08:46:57,768][00651] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 3901.6). Total num frames: 1642496. Throughput: 0: 1017.2. Samples: 412002. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:46:57,770][00651] Avg episode reward: [(0, '13.229')] | |
| [2025-01-29 08:46:57,831][02605] Saving new best policy, reward=13.229! | |
| [2025-01-29 08:47:02,770][00651] Fps is (10 sec: 3685.8, 60 sec: 3891.1, 300 sec: 3887.7). Total num frames: 1658880. Throughput: 0: 1008.9. Samples: 414490. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:47:02,772][00651] Avg episode reward: [(0, '12.796')] | |
| [2025-01-29 08:47:07,726][02618] Updated weights for policy 0, policy_version 410 (0.0021) | |
| [2025-01-29 08:47:07,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 1679360. Throughput: 0: 958.4. Samples: 419120. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:47:07,778][00651] Avg episode reward: [(0, '12.540')] | |
| [2025-01-29 08:47:07,786][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000410_1679360.pth... | |
| [2025-01-29 08:47:07,917][02605] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000182_745472.pth | |
| [2025-01-29 08:47:12,768][00651] Fps is (10 sec: 4096.6, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 1699840. Throughput: 0: 989.5. Samples: 425938. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:47:12,774][00651] Avg episode reward: [(0, '13.498')] | |
| [2025-01-29 08:47:12,780][02605] Saving new best policy, reward=13.498! | |
| [2025-01-29 08:47:17,201][02618] Updated weights for policy 0, policy_version 420 (0.0013) | |
| [2025-01-29 08:47:17,771][00651] Fps is (10 sec: 4095.0, 60 sec: 3959.3, 300 sec: 3901.6). Total num frames: 1720320. Throughput: 0: 1019.3. Samples: 429498. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:47:17,774][00651] Avg episode reward: [(0, '13.575')] | |
| [2025-01-29 08:47:17,793][02605] Saving new best policy, reward=13.575! | |
| [2025-01-29 08:47:22,769][00651] Fps is (10 sec: 3276.6, 60 sec: 3822.9, 300 sec: 3887.8). Total num frames: 1732608. Throughput: 0: 959.0. Samples: 433686. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:47:22,775][00651] Avg episode reward: [(0, '14.769')] | |
| [2025-01-29 08:47:22,779][02605] Saving new best policy, reward=14.769! | |
| [2025-01-29 08:47:27,768][00651] Fps is (10 sec: 3687.3, 60 sec: 3959.6, 300 sec: 3901.6). Total num frames: 1757184. Throughput: 0: 951.7. Samples: 439996. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:47:27,775][00651] Avg episode reward: [(0, '14.712')] | |
| [2025-01-29 08:47:28,316][02618] Updated weights for policy 0, policy_version 430 (0.0038) | |
| [2025-01-29 08:47:32,768][00651] Fps is (10 sec: 4915.6, 60 sec: 4027.7, 300 sec: 3901.6). Total num frames: 1781760. Throughput: 0: 985.1. Samples: 443582. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:47:32,771][00651] Avg episode reward: [(0, '15.951')] | |
| [2025-01-29 08:47:32,776][02605] Saving new best policy, reward=15.951! | |
| [2025-01-29 08:47:37,772][00651] Fps is (10 sec: 3685.2, 60 sec: 3822.7, 300 sec: 3887.7). Total num frames: 1794048. Throughput: 0: 974.7. Samples: 448922. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:47:37,774][00651] Avg episode reward: [(0, '16.174')] | |
| [2025-01-29 08:47:37,787][02605] Saving new best policy, reward=16.174! | |
| [2025-01-29 08:47:39,800][02618] Updated weights for policy 0, policy_version 440 (0.0015) | |
| [2025-01-29 08:47:42,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3823.0, 300 sec: 3901.6). Total num frames: 1814528. Throughput: 0: 938.8. Samples: 454248. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:47:42,773][00651] Avg episode reward: [(0, '16.038')] | |
| [2025-01-29 08:47:47,768][00651] Fps is (10 sec: 4507.1, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 1839104. Throughput: 0: 961.6. Samples: 457762. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:47:47,770][00651] Avg episode reward: [(0, '16.736')] | |
| [2025-01-29 08:47:47,780][02605] Saving new best policy, reward=16.736! | |
| [2025-01-29 08:47:48,574][02618] Updated weights for policy 0, policy_version 450 (0.0014) | |
| [2025-01-29 08:47:52,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 1855488. Throughput: 0: 1005.7. Samples: 464376. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-01-29 08:47:52,773][00651] Avg episode reward: [(0, '15.771')] | |
| [2025-01-29 08:47:57,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3901.6). Total num frames: 1871872. Throughput: 0: 948.9. Samples: 468638. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:47:57,774][00651] Avg episode reward: [(0, '15.116')] | |
| [2025-01-29 08:48:00,251][02618] Updated weights for policy 0, policy_version 460 (0.0017) | |
| [2025-01-29 08:48:02,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.6, 300 sec: 3901.6). Total num frames: 1896448. Throughput: 0: 943.0. Samples: 471932. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-01-29 08:48:02,776][00651] Avg episode reward: [(0, '14.411')] | |
| [2025-01-29 08:48:07,770][00651] Fps is (10 sec: 4504.9, 60 sec: 3959.4, 300 sec: 3901.6). Total num frames: 1916928. Throughput: 0: 1011.0. Samples: 479182. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:48:07,775][00651] Avg episode reward: [(0, '14.906')] | |
| [2025-01-29 08:48:09,338][02618] Updated weights for policy 0, policy_version 470 (0.0019) | |
| [2025-01-29 08:48:12,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 1933312. Throughput: 0: 977.5. Samples: 483982. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:48:12,773][00651] Avg episode reward: [(0, '15.554')] | |
| [2025-01-29 08:48:17,769][00651] Fps is (10 sec: 3277.2, 60 sec: 3823.1, 300 sec: 3901.6). Total num frames: 1949696. Throughput: 0: 948.6. Samples: 486270. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:48:17,776][00651] Avg episode reward: [(0, '16.803')] | |
| [2025-01-29 08:48:17,783][02605] Saving new best policy, reward=16.803! | |
| [2025-01-29 08:48:20,862][02618] Updated weights for policy 0, policy_version 480 (0.0016) | |
| [2025-01-29 08:48:22,768][00651] Fps is (10 sec: 4095.9, 60 sec: 4027.8, 300 sec: 3901.6). Total num frames: 1974272. Throughput: 0: 982.2. Samples: 493120. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:48:22,774][00651] Avg episode reward: [(0, '16.968')] | |
| [2025-01-29 08:48:22,780][02605] Saving new best policy, reward=16.968! | |
| [2025-01-29 08:48:27,768][00651] Fps is (10 sec: 4096.1, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 1990656. Throughput: 0: 990.7. Samples: 498828. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:48:27,774][00651] Avg episode reward: [(0, '16.178')] | |
| [2025-01-29 08:48:32,500][02618] Updated weights for policy 0, policy_version 490 (0.0012) | |
| [2025-01-29 08:48:32,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3754.6, 300 sec: 3901.6). Total num frames: 2007040. Throughput: 0: 960.0. Samples: 500964. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:48:32,775][00651] Avg episode reward: [(0, '16.549')] | |
| [2025-01-29 08:48:37,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.7, 300 sec: 3901.6). Total num frames: 2031616. Throughput: 0: 951.8. Samples: 507206. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:48:37,774][00651] Avg episode reward: [(0, '15.286')] | |
| [2025-01-29 08:48:41,156][02618] Updated weights for policy 0, policy_version 500 (0.0017) | |
| [2025-01-29 08:48:42,768][00651] Fps is (10 sec: 4505.7, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 2052096. Throughput: 0: 1014.1. Samples: 514272. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:48:42,771][00651] Avg episode reward: [(0, '14.871')] | |
| [2025-01-29 08:48:47,770][00651] Fps is (10 sec: 3685.8, 60 sec: 3822.8, 300 sec: 3901.6). Total num frames: 2068480. Throughput: 0: 988.7. Samples: 516426. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:48:47,775][00651] Avg episode reward: [(0, '15.304')] | |
| [2025-01-29 08:48:52,742][02618] Updated weights for policy 0, policy_version 510 (0.0020) | |
| [2025-01-29 08:48:52,768][00651] Fps is (10 sec: 3686.5, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 2088960. Throughput: 0: 941.6. Samples: 521554. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:48:52,770][00651] Avg episode reward: [(0, '14.900')] | |
| [2025-01-29 08:48:57,768][00651] Fps is (10 sec: 4096.6, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 2109440. Throughput: 0: 988.5. Samples: 528466. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:48:57,771][00651] Avg episode reward: [(0, '15.161')] | |
| [2025-01-29 08:49:02,440][02618] Updated weights for policy 0, policy_version 520 (0.0027) | |
| [2025-01-29 08:49:02,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 2129920. Throughput: 0: 1010.4. Samples: 531736. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:49:02,774][00651] Avg episode reward: [(0, '16.141')] | |
| [2025-01-29 08:49:07,768][00651] Fps is (10 sec: 3686.3, 60 sec: 3823.0, 300 sec: 3901.6). Total num frames: 2146304. Throughput: 0: 954.8. Samples: 536088. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:49:07,774][00651] Avg episode reward: [(0, '18.192')] | |
| [2025-01-29 08:49:07,784][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000524_2146304.pth... | |
| [2025-01-29 08:49:07,924][02605] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000296_1212416.pth | |
| [2025-01-29 08:49:07,933][02605] Saving new best policy, reward=18.192! | |
| [2025-01-29 08:49:12,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 2166784. Throughput: 0: 979.4. Samples: 542902. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:49:12,771][00651] Avg episode reward: [(0, '18.803')] | |
| [2025-01-29 08:49:12,776][02605] Saving new best policy, reward=18.803! | |
| [2025-01-29 08:49:13,074][02618] Updated weights for policy 0, policy_version 530 (0.0020) | |
| [2025-01-29 08:49:17,768][00651] Fps is (10 sec: 4505.7, 60 sec: 4027.7, 300 sec: 3901.6). Total num frames: 2191360. Throughput: 0: 1008.6. Samples: 546350. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:49:17,773][00651] Avg episode reward: [(0, '18.205')] | |
| [2025-01-29 08:49:22,775][00651] Fps is (10 sec: 3684.0, 60 sec: 3822.5, 300 sec: 3901.6). Total num frames: 2203648. Throughput: 0: 980.5. Samples: 551334. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:49:22,777][00651] Avg episode reward: [(0, '19.057')] | |
| [2025-01-29 08:49:22,780][02605] Saving new best policy, reward=19.057! | |
| [2025-01-29 08:49:24,550][02618] Updated weights for policy 0, policy_version 540 (0.0030) | |
| [2025-01-29 08:49:27,768][00651] Fps is (10 sec: 3276.9, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 2224128. Throughput: 0: 948.2. Samples: 556942. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:49:27,774][00651] Avg episode reward: [(0, '18.629')] | |
| [2025-01-29 08:49:32,768][00651] Fps is (10 sec: 4508.6, 60 sec: 4027.8, 300 sec: 3915.5). Total num frames: 2248704. Throughput: 0: 977.0. Samples: 560388. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:49:32,771][00651] Avg episode reward: [(0, '18.753')] | |
| [2025-01-29 08:49:33,552][02618] Updated weights for policy 0, policy_version 550 (0.0015) | |
| [2025-01-29 08:49:37,768][00651] Fps is (10 sec: 4095.9, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 2265088. Throughput: 0: 995.9. Samples: 566370. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:49:37,771][00651] Avg episode reward: [(0, '17.750')] | |
| [2025-01-29 08:49:42,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3901.6). Total num frames: 2281472. Throughput: 0: 946.8. Samples: 571072. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:49:42,770][00651] Avg episode reward: [(0, '18.220')] | |
| [2025-01-29 08:49:45,137][02618] Updated weights for policy 0, policy_version 560 (0.0020) | |
| [2025-01-29 08:49:47,768][00651] Fps is (10 sec: 4096.1, 60 sec: 3959.6, 300 sec: 3915.5). Total num frames: 2306048. Throughput: 0: 952.8. Samples: 574610. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:49:47,774][00651] Avg episode reward: [(0, '18.271')] | |
| [2025-01-29 08:49:52,773][00651] Fps is (10 sec: 4503.5, 60 sec: 3959.2, 300 sec: 3901.6). Total num frames: 2326528. Throughput: 0: 1014.3. Samples: 581734. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:49:52,775][00651] Avg episode reward: [(0, '17.801')] | |
| [2025-01-29 08:49:55,118][02618] Updated weights for policy 0, policy_version 570 (0.0020) | |
| [2025-01-29 08:49:57,776][00651] Fps is (10 sec: 3274.3, 60 sec: 3822.5, 300 sec: 3901.5). Total num frames: 2338816. Throughput: 0: 958.3. Samples: 586032. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:49:57,778][00651] Avg episode reward: [(0, '17.462')] | |
| [2025-01-29 08:50:02,768][00651] Fps is (10 sec: 3688.1, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 2363392. Throughput: 0: 947.2. Samples: 588972. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:50:02,773][00651] Avg episode reward: [(0, '17.646')] | |
| [2025-01-29 08:50:05,316][02618] Updated weights for policy 0, policy_version 580 (0.0042) | |
| [2025-01-29 08:50:07,768][00651] Fps is (10 sec: 4509.0, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 2383872. Throughput: 0: 992.4. Samples: 595986. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:50:07,772][00651] Avg episode reward: [(0, '17.049')] | |
| [2025-01-29 08:50:12,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 2400256. Throughput: 0: 989.4. Samples: 601464. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:50:12,777][00651] Avg episode reward: [(0, '15.921')] | |
| [2025-01-29 08:50:16,790][02618] Updated weights for policy 0, policy_version 590 (0.0018) | |
| [2025-01-29 08:50:17,768][00651] Fps is (10 sec: 3686.3, 60 sec: 3822.9, 300 sec: 3915.5). Total num frames: 2420736. Throughput: 0: 961.4. Samples: 603652. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:50:17,770][00651] Avg episode reward: [(0, '16.701')] | |
| [2025-01-29 08:50:22,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.9, 300 sec: 3901.6). Total num frames: 2441216. Throughput: 0: 981.0. Samples: 610514. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:50:22,775][00651] Avg episode reward: [(0, '17.580')] | |
| [2025-01-29 08:50:25,494][02618] Updated weights for policy 0, policy_version 600 (0.0020) | |
| [2025-01-29 08:50:27,768][00651] Fps is (10 sec: 4505.8, 60 sec: 4027.7, 300 sec: 3915.6). Total num frames: 2465792. Throughput: 0: 1020.3. Samples: 616986. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-01-29 08:50:27,770][00651] Avg episode reward: [(0, '17.243')] | |
| [2025-01-29 08:50:32,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3901.6). Total num frames: 2478080. Throughput: 0: 989.4. Samples: 619134. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:50:32,772][00651] Avg episode reward: [(0, '18.478')] | |
| [2025-01-29 08:50:36,830][02618] Updated weights for policy 0, policy_version 610 (0.0043) | |
| [2025-01-29 08:50:37,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.7). Total num frames: 2498560. Throughput: 0: 959.9. Samples: 624924. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:50:37,775][00651] Avg episode reward: [(0, '19.062')] | |
| [2025-01-29 08:50:37,785][02605] Saving new best policy, reward=19.062! | |
| [2025-01-29 08:50:42,768][00651] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 3915.5). Total num frames: 2523136. Throughput: 0: 1025.0. Samples: 632150. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:50:42,773][00651] Avg episode reward: [(0, '19.096')] | |
| [2025-01-29 08:50:42,777][02605] Saving new best policy, reward=19.096! | |
| [2025-01-29 08:50:46,805][02618] Updated weights for policy 0, policy_version 620 (0.0020) | |
| [2025-01-29 08:50:47,772][00651] Fps is (10 sec: 4094.5, 60 sec: 3891.0, 300 sec: 3915.5). Total num frames: 2539520. Throughput: 0: 1015.6. Samples: 634678. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-01-29 08:50:47,774][00651] Avg episode reward: [(0, '18.590')] | |
| [2025-01-29 08:50:52,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.5, 300 sec: 3929.4). Total num frames: 2560000. Throughput: 0: 968.9. Samples: 639588. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:50:52,771][00651] Avg episode reward: [(0, '17.461')] | |
| [2025-01-29 08:50:56,783][02618] Updated weights for policy 0, policy_version 630 (0.0022) | |
| [2025-01-29 08:50:57,768][00651] Fps is (10 sec: 4507.2, 60 sec: 4096.5, 300 sec: 3929.4). Total num frames: 2584576. Throughput: 0: 1006.8. Samples: 646770. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:50:57,770][00651] Avg episode reward: [(0, '18.426')] | |
| [2025-01-29 08:51:02,770][00651] Fps is (10 sec: 4504.6, 60 sec: 4027.6, 300 sec: 3929.4). Total num frames: 2605056. Throughput: 0: 1037.4. Samples: 650338. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:51:02,773][00651] Avg episode reward: [(0, '17.462')] | |
| [2025-01-29 08:51:07,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 2617344. Throughput: 0: 984.9. Samples: 654834. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:51:07,771][00651] Avg episode reward: [(0, '18.439')] | |
| [2025-01-29 08:51:07,790][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000639_2617344.pth... | |
| [2025-01-29 08:51:07,935][02605] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000410_1679360.pth | |
| [2025-01-29 08:51:08,079][02618] Updated weights for policy 0, policy_version 640 (0.0033) | |
| [2025-01-29 08:51:12,768][00651] Fps is (10 sec: 3687.2, 60 sec: 4027.7, 300 sec: 3929.4). Total num frames: 2641920. Throughput: 0: 985.6. Samples: 661336. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:51:12,772][00651] Avg episode reward: [(0, '19.283')] | |
| [2025-01-29 08:51:12,777][02605] Saving new best policy, reward=19.283! | |
| [2025-01-29 08:51:16,776][02618] Updated weights for policy 0, policy_version 650 (0.0019) | |
| [2025-01-29 08:51:17,768][00651] Fps is (10 sec: 4915.2, 60 sec: 4096.0, 300 sec: 3943.3). Total num frames: 2666496. Throughput: 0: 1014.3. Samples: 664776. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:51:17,774][00651] Avg episode reward: [(0, '19.441')] | |
| [2025-01-29 08:51:17,786][02605] Saving new best policy, reward=19.441! | |
| [2025-01-29 08:51:22,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3929.4). Total num frames: 2678784. Throughput: 0: 1002.8. Samples: 670050. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:51:22,771][00651] Avg episode reward: [(0, '19.445')] | |
| [2025-01-29 08:51:22,773][02605] Saving new best policy, reward=19.445! | |
| [2025-01-29 08:51:27,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3929.4). Total num frames: 2699264. Throughput: 0: 963.6. Samples: 675510. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:51:27,770][00651] Avg episode reward: [(0, '19.427')] | |
| [2025-01-29 08:51:28,447][02618] Updated weights for policy 0, policy_version 660 (0.0013) | |
| [2025-01-29 08:51:32,768][00651] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 3929.4). Total num frames: 2723840. Throughput: 0: 985.9. Samples: 679038. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:51:32,775][00651] Avg episode reward: [(0, '18.746')] | |
| [2025-01-29 08:51:37,769][00651] Fps is (10 sec: 4095.8, 60 sec: 4027.7, 300 sec: 3915.5). Total num frames: 2740224. Throughput: 0: 1021.2. Samples: 685544. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:51:37,772][00651] Avg episode reward: [(0, '17.800')] | |
| [2025-01-29 08:51:38,114][02618] Updated weights for policy 0, policy_version 670 (0.0017) | |
| [2025-01-29 08:51:42,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 2756608. Throughput: 0: 964.9. Samples: 690190. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:51:42,771][00651] Avg episode reward: [(0, '16.966')] | |
| [2025-01-29 08:51:47,768][00651] Fps is (10 sec: 4096.2, 60 sec: 4028.0, 300 sec: 3929.4). Total num frames: 2781184. Throughput: 0: 964.3. Samples: 693728. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:51:47,771][00651] Avg episode reward: [(0, '17.963')] | |
| [2025-01-29 08:51:48,440][02618] Updated weights for policy 0, policy_version 680 (0.0025) | |
| [2025-01-29 08:51:52,769][00651] Fps is (10 sec: 4914.7, 60 sec: 4095.9, 300 sec: 3943.3). Total num frames: 2805760. Throughput: 0: 1023.9. Samples: 700912. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:51:52,773][00651] Avg episode reward: [(0, '17.269')] | |
| [2025-01-29 08:51:57,772][00651] Fps is (10 sec: 3685.1, 60 sec: 3891.0, 300 sec: 3929.4). Total num frames: 2818048. Throughput: 0: 985.1. Samples: 705670. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:51:57,774][00651] Avg episode reward: [(0, '17.453')] | |
| [2025-01-29 08:51:59,525][02618] Updated weights for policy 0, policy_version 690 (0.0036) | |
| [2025-01-29 08:52:02,768][00651] Fps is (10 sec: 3277.1, 60 sec: 3891.3, 300 sec: 3929.4). Total num frames: 2838528. Throughput: 0: 963.8. Samples: 708146. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:52:02,771][00651] Avg episode reward: [(0, '18.369')] | |
| [2025-01-29 08:52:07,768][00651] Fps is (10 sec: 4507.1, 60 sec: 4096.0, 300 sec: 3943.3). Total num frames: 2863104. Throughput: 0: 1007.3. Samples: 715380. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:52:07,775][00651] Avg episode reward: [(0, '18.486')] | |
| [2025-01-29 08:52:08,319][02618] Updated weights for policy 0, policy_version 700 (0.0023) | |
| [2025-01-29 08:52:12,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3929.4). Total num frames: 2879488. Throughput: 0: 1015.9. Samples: 721224. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:52:12,771][00651] Avg episode reward: [(0, '19.836')] | |
| [2025-01-29 08:52:12,862][02605] Saving new best policy, reward=19.836! | |
| [2025-01-29 08:52:17,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3943.3). Total num frames: 2895872. Throughput: 0: 983.9. Samples: 723312. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:52:17,771][00651] Avg episode reward: [(0, '20.955')] | |
| [2025-01-29 08:52:17,780][02605] Saving new best policy, reward=20.955! | |
| [2025-01-29 08:52:19,809][02618] Updated weights for policy 0, policy_version 710 (0.0028) | |
| [2025-01-29 08:52:22,768][00651] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 3943.3). Total num frames: 2920448. Throughput: 0: 979.5. Samples: 729620. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:52:22,774][00651] Avg episode reward: [(0, '22.211')] | |
| [2025-01-29 08:52:22,777][02605] Saving new best policy, reward=22.211! | |
| [2025-01-29 08:52:27,771][00651] Fps is (10 sec: 4504.4, 60 sec: 4027.6, 300 sec: 3929.3). Total num frames: 2940928. Throughput: 0: 1028.2. Samples: 736462. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:52:27,784][00651] Avg episode reward: [(0, '22.502')] | |
| [2025-01-29 08:52:27,796][02605] Saving new best policy, reward=22.502! | |
| [2025-01-29 08:52:29,568][02618] Updated weights for policy 0, policy_version 720 (0.0018) | |
| [2025-01-29 08:52:32,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3943.3). Total num frames: 2957312. Throughput: 0: 996.0. Samples: 738550. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:52:32,772][00651] Avg episode reward: [(0, '23.051')] | |
| [2025-01-29 08:52:32,773][02605] Saving new best policy, reward=23.051! | |
| [2025-01-29 08:52:37,768][00651] Fps is (10 sec: 3687.4, 60 sec: 3959.5, 300 sec: 3943.3). Total num frames: 2977792. Throughput: 0: 955.5. Samples: 743908. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:52:37,771][00651] Avg episode reward: [(0, '23.149')] | |
| [2025-01-29 08:52:37,785][02605] Saving new best policy, reward=23.149! | |
| [2025-01-29 08:52:40,189][02618] Updated weights for policy 0, policy_version 730 (0.0012) | |
| [2025-01-29 08:52:42,768][00651] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 3943.3). Total num frames: 3002368. Throughput: 0: 1007.1. Samples: 750986. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:52:42,771][00651] Avg episode reward: [(0, '21.979')] | |
| [2025-01-29 08:52:47,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3943.3). Total num frames: 3018752. Throughput: 0: 1018.7. Samples: 753986. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-01-29 08:52:47,771][00651] Avg episode reward: [(0, '22.945')] | |
| [2025-01-29 08:52:51,299][02618] Updated weights for policy 0, policy_version 740 (0.0022) | |
| [2025-01-29 08:52:52,768][00651] Fps is (10 sec: 3276.7, 60 sec: 3823.0, 300 sec: 3943.3). Total num frames: 3035136. Throughput: 0: 957.7. Samples: 758478. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-01-29 08:52:52,773][00651] Avg episode reward: [(0, '23.089')] | |
| [2025-01-29 08:52:57,768][00651] Fps is (10 sec: 4096.0, 60 sec: 4028.0, 300 sec: 3943.3). Total num frames: 3059712. Throughput: 0: 985.6. Samples: 765574. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:52:57,772][00651] Avg episode reward: [(0, '23.370')] | |
| [2025-01-29 08:52:57,778][02605] Saving new best policy, reward=23.370! | |
| [2025-01-29 08:53:00,259][02618] Updated weights for policy 0, policy_version 750 (0.0035) | |
| [2025-01-29 08:53:02,768][00651] Fps is (10 sec: 4505.7, 60 sec: 4027.7, 300 sec: 3943.3). Total num frames: 3080192. Throughput: 0: 1015.6. Samples: 769012. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:53:02,770][00651] Avg episode reward: [(0, '23.985')] | |
| [2025-01-29 08:53:02,775][02605] Saving new best policy, reward=23.985! | |
| [2025-01-29 08:53:07,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3929.4). Total num frames: 3092480. Throughput: 0: 979.6. Samples: 773700. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:53:07,775][00651] Avg episode reward: [(0, '24.109')] | |
| [2025-01-29 08:53:07,853][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000756_3096576.pth... | |
| [2025-01-29 08:53:08,009][02605] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000524_2146304.pth | |
| [2025-01-29 08:53:08,024][02605] Saving new best policy, reward=24.109! | |
| [2025-01-29 08:53:11,712][02618] Updated weights for policy 0, policy_version 760 (0.0018) | |
| [2025-01-29 08:53:12,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 3117056. Throughput: 0: 963.4. Samples: 779812. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:53:12,773][00651] Avg episode reward: [(0, '22.765')] | |
| [2025-01-29 08:53:17,768][00651] Fps is (10 sec: 4915.2, 60 sec: 4096.0, 300 sec: 3957.2). Total num frames: 3141632. Throughput: 0: 995.2. Samples: 783332. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:53:17,775][00651] Avg episode reward: [(0, '21.875')] | |
| [2025-01-29 08:53:21,121][02618] Updated weights for policy 0, policy_version 770 (0.0019) | |
| [2025-01-29 08:53:22,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 3158016. Throughput: 0: 1007.6. Samples: 789250. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-01-29 08:53:22,771][00651] Avg episode reward: [(0, '22.981')] | |
| [2025-01-29 08:53:27,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3891.4, 300 sec: 3957.2). Total num frames: 3174400. Throughput: 0: 963.2. Samples: 794328. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:53:27,771][00651] Avg episode reward: [(0, '22.993')] | |
| [2025-01-29 08:53:32,001][02618] Updated weights for policy 0, policy_version 780 (0.0047) | |
| [2025-01-29 08:53:32,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3943.3). Total num frames: 3194880. Throughput: 0: 971.6. Samples: 797706. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-01-29 08:53:32,773][00651] Avg episode reward: [(0, '22.544')] | |
| [2025-01-29 08:53:37,770][00651] Fps is (10 sec: 4504.8, 60 sec: 4027.6, 300 sec: 3957.1). Total num frames: 3219456. Throughput: 0: 1024.3. Samples: 804572. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:53:37,777][00651] Avg episode reward: [(0, '22.509')] | |
| [2025-01-29 08:53:42,773][00651] Fps is (10 sec: 3684.7, 60 sec: 3822.6, 300 sec: 3943.2). Total num frames: 3231744. Throughput: 0: 961.7. Samples: 808856. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-01-29 08:53:42,780][00651] Avg episode reward: [(0, '21.877')] | |
| [2025-01-29 08:53:43,298][02618] Updated weights for policy 0, policy_version 790 (0.0025) | |
| [2025-01-29 08:53:47,768][00651] Fps is (10 sec: 3687.1, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 3256320. Throughput: 0: 957.6. Samples: 812104. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:53:47,772][00651] Avg episode reward: [(0, '20.607')] | |
| [2025-01-29 08:53:52,106][02618] Updated weights for policy 0, policy_version 800 (0.0014) | |
| [2025-01-29 08:53:52,768][00651] Fps is (10 sec: 4507.7, 60 sec: 4027.8, 300 sec: 3957.2). Total num frames: 3276800. Throughput: 0: 1013.4. Samples: 819304. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:53:52,772][00651] Avg episode reward: [(0, '20.460')] | |
| [2025-01-29 08:53:57,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3943.3). Total num frames: 3293184. Throughput: 0: 989.5. Samples: 824340. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:53:57,771][00651] Avg episode reward: [(0, '20.005')] | |
| [2025-01-29 08:54:02,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3943.3). Total num frames: 3309568. Throughput: 0: 960.1. Samples: 826536. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:54:02,770][00651] Avg episode reward: [(0, '20.319')] | |
| [2025-01-29 08:54:03,679][02618] Updated weights for policy 0, policy_version 810 (0.0023) | |
| [2025-01-29 08:54:07,768][00651] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 3957.2). Total num frames: 3334144. Throughput: 0: 985.1. Samples: 833580. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:54:07,780][00651] Avg episode reward: [(0, '22.268')] | |
| [2025-01-29 08:54:12,768][00651] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3943.3). Total num frames: 3354624. Throughput: 0: 1010.7. Samples: 839808. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:54:12,773][00651] Avg episode reward: [(0, '22.057')] | |
| [2025-01-29 08:54:13,174][02618] Updated weights for policy 0, policy_version 820 (0.0014) | |
| [2025-01-29 08:54:17,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3957.2). Total num frames: 3371008. Throughput: 0: 983.6. Samples: 841966. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:54:17,771][00651] Avg episode reward: [(0, '21.151')] | |
| [2025-01-29 08:54:22,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3957.2). Total num frames: 3391488. Throughput: 0: 961.2. Samples: 847826. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:54:22,770][00651] Avg episode reward: [(0, '21.758')] | |
| [2025-01-29 08:54:23,763][02618] Updated weights for policy 0, policy_version 830 (0.0022) | |
| [2025-01-29 08:54:27,768][00651] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 3957.2). Total num frames: 3416064. Throughput: 0: 1027.0. Samples: 855068. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:54:27,771][00651] Avg episode reward: [(0, '23.609')] | |
| [2025-01-29 08:54:32,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 3432448. Throughput: 0: 1007.8. Samples: 857454. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:54:32,771][00651] Avg episode reward: [(0, '23.636')] | |
| [2025-01-29 08:54:35,132][02618] Updated weights for policy 0, policy_version 840 (0.0027) | |
| [2025-01-29 08:54:37,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3823.1, 300 sec: 3957.2). Total num frames: 3448832. Throughput: 0: 955.5. Samples: 862302. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:54:37,772][00651] Avg episode reward: [(0, '22.932')] | |
| [2025-01-29 08:54:42,768][00651] Fps is (10 sec: 4096.0, 60 sec: 4028.0, 300 sec: 3957.2). Total num frames: 3473408. Throughput: 0: 1002.2. Samples: 869440. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:54:42,771][00651] Avg episode reward: [(0, '24.397')] | |
| [2025-01-29 08:54:42,777][02605] Saving new best policy, reward=24.397! | |
| [2025-01-29 08:54:44,166][02618] Updated weights for policy 0, policy_version 850 (0.0014) | |
| [2025-01-29 08:54:47,768][00651] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 3493888. Throughput: 0: 1027.4. Samples: 872768. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:54:47,771][00651] Avg episode reward: [(0, '25.210')] | |
| [2025-01-29 08:54:47,779][02605] Saving new best policy, reward=25.210! | |
| [2025-01-29 08:54:52,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3957.3). Total num frames: 3506176. Throughput: 0: 966.5. Samples: 877072. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-01-29 08:54:52,779][00651] Avg episode reward: [(0, '26.540')] | |
| [2025-01-29 08:54:52,781][02605] Saving new best policy, reward=26.540! | |
| [2025-01-29 08:54:55,643][02618] Updated weights for policy 0, policy_version 860 (0.0026) | |
| [2025-01-29 08:54:57,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 3530752. Throughput: 0: 974.0. Samples: 883640. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-01-29 08:54:57,770][00651] Avg episode reward: [(0, '24.321')] | |
| [2025-01-29 08:55:02,768][00651] Fps is (10 sec: 4915.2, 60 sec: 4096.0, 300 sec: 3971.0). Total num frames: 3555328. Throughput: 0: 1006.2. Samples: 887246. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:55:02,772][00651] Avg episode reward: [(0, '25.112')] | |
| [2025-01-29 08:55:05,133][02618] Updated weights for policy 0, policy_version 870 (0.0013) | |
| [2025-01-29 08:55:07,771][00651] Fps is (10 sec: 3685.4, 60 sec: 3891.0, 300 sec: 3957.1). Total num frames: 3567616. Throughput: 0: 992.5. Samples: 892490. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:55:07,779][00651] Avg episode reward: [(0, '25.440')] | |
| [2025-01-29 08:55:07,836][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000872_3571712.pth... | |
| [2025-01-29 08:55:08,027][02605] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000639_2617344.pth | |
| [2025-01-29 08:55:12,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3957.2). Total num frames: 3588096. Throughput: 0: 954.4. Samples: 898018. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:55:12,773][00651] Avg episode reward: [(0, '25.699')] | |
| [2025-01-29 08:55:15,631][02618] Updated weights for policy 0, policy_version 880 (0.0037) | |
| [2025-01-29 08:55:17,768][00651] Fps is (10 sec: 4506.8, 60 sec: 4027.7, 300 sec: 3971.0). Total num frames: 3612672. Throughput: 0: 982.7. Samples: 901674. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:55:17,774][00651] Avg episode reward: [(0, '23.517')] | |
| [2025-01-29 08:55:22,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3943.3). Total num frames: 3629056. Throughput: 0: 1018.0. Samples: 908114. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:55:22,771][00651] Avg episode reward: [(0, '23.400')] | |
| [2025-01-29 08:55:26,987][02618] Updated weights for policy 0, policy_version 890 (0.0019) | |
| [2025-01-29 08:55:27,768][00651] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3957.2). Total num frames: 3645440. Throughput: 0: 960.2. Samples: 912650. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:55:27,771][00651] Avg episode reward: [(0, '24.265')] | |
| [2025-01-29 08:55:32,768][00651] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3971.0). Total num frames: 3670016. Throughput: 0: 963.9. Samples: 916142. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:55:32,771][00651] Avg episode reward: [(0, '21.804')] | |
| [2025-01-29 08:55:36,007][02618] Updated weights for policy 0, policy_version 900 (0.0017) | |
| [2025-01-29 08:55:37,770][00651] Fps is (10 sec: 4504.9, 60 sec: 4027.6, 300 sec: 3957.1). Total num frames: 3690496. Throughput: 0: 1019.0. Samples: 922928. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-01-29 08:55:37,776][00651] Avg episode reward: [(0, '19.918')] | |
| [2025-01-29 08:55:42,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3957.2). Total num frames: 3706880. Throughput: 0: 976.4. Samples: 927576. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:55:42,772][00651] Avg episode reward: [(0, '21.385')] | |
| [2025-01-29 08:55:47,575][02618] Updated weights for policy 0, policy_version 910 (0.0023) | |
| [2025-01-29 08:55:47,768][00651] Fps is (10 sec: 3686.9, 60 sec: 3891.2, 300 sec: 3957.2). Total num frames: 3727360. Throughput: 0: 952.3. Samples: 930100. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:55:47,774][00651] Avg episode reward: [(0, '20.928')] | |
| [2025-01-29 08:55:52,769][00651] Fps is (10 sec: 4505.5, 60 sec: 4096.0, 300 sec: 3957.1). Total num frames: 3751936. Throughput: 0: 994.6. Samples: 937246. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:55:52,776][00651] Avg episode reward: [(0, '20.176')] | |
| [2025-01-29 08:55:56,985][02618] Updated weights for policy 0, policy_version 920 (0.0024) | |
| [2025-01-29 08:55:57,771][00651] Fps is (10 sec: 4094.7, 60 sec: 3959.3, 300 sec: 3943.3). Total num frames: 3768320. Throughput: 0: 1000.7. Samples: 943054. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:55:57,774][00651] Avg episode reward: [(0, '20.065')] | |
| [2025-01-29 08:56:02,768][00651] Fps is (10 sec: 3276.9, 60 sec: 3822.9, 300 sec: 3957.2). Total num frames: 3784704. Throughput: 0: 966.8. Samples: 945180. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:56:02,775][00651] Avg episode reward: [(0, '20.740')] | |
| [2025-01-29 08:56:07,768][02618] Updated weights for policy 0, policy_version 930 (0.0012) | |
| [2025-01-29 08:56:07,770][00651] Fps is (10 sec: 4096.5, 60 sec: 4027.8, 300 sec: 3957.1). Total num frames: 3809280. Throughput: 0: 966.5. Samples: 951610. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:56:07,773][00651] Avg episode reward: [(0, '21.386')] | |
| [2025-01-29 08:56:12,768][00651] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 3943.3). Total num frames: 3829760. Throughput: 0: 1016.2. Samples: 958378. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:56:12,770][00651] Avg episode reward: [(0, '21.842')] | |
| [2025-01-29 08:56:17,768][00651] Fps is (10 sec: 3277.4, 60 sec: 3822.9, 300 sec: 3943.3). Total num frames: 3842048. Throughput: 0: 986.0. Samples: 960514. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-01-29 08:56:17,771][00651] Avg episode reward: [(0, '21.669')] | |
| [2025-01-29 08:56:19,233][02618] Updated weights for policy 0, policy_version 940 (0.0022) | |
| [2025-01-29 08:56:22,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 3866624. Throughput: 0: 956.8. Samples: 965984. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:56:22,773][00651] Avg episode reward: [(0, '21.866')] | |
| [2025-01-29 08:56:27,768][00651] Fps is (10 sec: 4505.7, 60 sec: 4027.7, 300 sec: 3943.3). Total num frames: 3887104. Throughput: 0: 1009.5. Samples: 973002. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:56:27,772][00651] Avg episode reward: [(0, '21.083')] | |
| [2025-01-29 08:56:27,988][02618] Updated weights for policy 0, policy_version 950 (0.0027) | |
| [2025-01-29 08:56:32,768][00651] Fps is (10 sec: 4095.9, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 3907584. Throughput: 0: 1021.0. Samples: 976046. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-01-29 08:56:32,774][00651] Avg episode reward: [(0, '20.478')] | |
| [2025-01-29 08:56:37,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3891.3, 300 sec: 3957.2). Total num frames: 3923968. Throughput: 0: 960.8. Samples: 980482. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:56:37,770][00651] Avg episode reward: [(0, '19.919')] | |
| [2025-01-29 08:56:39,371][02618] Updated weights for policy 0, policy_version 960 (0.0032) | |
| [2025-01-29 08:56:42,768][00651] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3943.3). Total num frames: 3944448. Throughput: 0: 989.1. Samples: 987562. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-01-29 08:56:42,775][00651] Avg episode reward: [(0, '19.418')] | |
| [2025-01-29 08:56:47,768][00651] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 3943.3). Total num frames: 3969024. Throughput: 0: 1021.5. Samples: 991148. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-01-29 08:56:47,773][00651] Avg episode reward: [(0, '20.849')] | |
| [2025-01-29 08:56:48,435][02618] Updated weights for policy 0, policy_version 970 (0.0015) | |
| [2025-01-29 08:56:52,768][00651] Fps is (10 sec: 4095.9, 60 sec: 3891.2, 300 sec: 3957.2). Total num frames: 3985408. Throughput: 0: 985.7. Samples: 995964. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-01-29 08:56:52,770][00651] Avg episode reward: [(0, '21.431')] | |
| [2025-01-29 08:56:57,652][02605] Stopping Batcher_0... | |
| [2025-01-29 08:56:57,653][02605] Loop batcher_evt_loop terminating... | |
| [2025-01-29 08:56:57,654][00651] Component Batcher_0 stopped! | |
| [2025-01-29 08:56:57,665][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-01-29 08:56:57,714][02618] Weights refcount: 2 0 | |
| [2025-01-29 08:56:57,716][02618] Stopping InferenceWorker_p0-w0... | |
| [2025-01-29 08:56:57,718][02618] Loop inference_proc0-0_evt_loop terminating... | |
| [2025-01-29 08:56:57,716][00651] Component InferenceWorker_p0-w0 stopped! | |
| [2025-01-29 08:56:57,802][02605] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000756_3096576.pth | |
| [2025-01-29 08:56:57,825][02605] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-01-29 08:56:57,934][00651] Component RolloutWorker_w6 stopped! | |
| [2025-01-29 08:56:57,936][02626] Stopping RolloutWorker_w6... | |
| [2025-01-29 08:56:57,944][02626] Loop rollout_proc6_evt_loop terminating... | |
| [2025-01-29 08:56:57,966][00651] Component RolloutWorker_w4 stopped! | |
| [2025-01-29 08:56:57,974][02628] Stopping RolloutWorker_w4... | |
| [2025-01-29 08:56:57,975][02628] Loop rollout_proc4_evt_loop terminating... | |
| [2025-01-29 08:56:57,993][00651] Component RolloutWorker_w2 stopped! | |
| [2025-01-29 08:56:57,999][02621] Stopping RolloutWorker_w2... | |
| [2025-01-29 08:56:58,002][00651] Component RolloutWorker_w0 stopped! | |
| [2025-01-29 08:56:58,008][02619] Stopping RolloutWorker_w0... | |
| [2025-01-29 08:56:58,000][02621] Loop rollout_proc2_evt_loop terminating... | |
| [2025-01-29 08:56:58,010][02619] Loop rollout_proc0_evt_loop terminating... | |
| [2025-01-29 08:56:58,023][02605] Stopping LearnerWorker_p0... | |
| [2025-01-29 08:56:58,025][02605] Loop learner_proc0_evt_loop terminating... | |
| [2025-01-29 08:56:58,023][00651] Component LearnerWorker_p0 stopped! | |
| [2025-01-29 08:56:58,127][02623] Stopping RolloutWorker_w5... | |
| [2025-01-29 08:56:58,131][02623] Loop rollout_proc5_evt_loop terminating... | |
| [2025-01-29 08:56:58,127][00651] Component RolloutWorker_w5 stopped! | |
| [2025-01-29 08:56:58,151][02622] Stopping RolloutWorker_w3... | |
| [2025-01-29 08:56:58,151][00651] Component RolloutWorker_w3 stopped! | |
| [2025-01-29 08:56:58,154][02622] Loop rollout_proc3_evt_loop terminating... | |
| [2025-01-29 08:56:58,183][02627] Stopping RolloutWorker_w7... | |
| [2025-01-29 08:56:58,183][00651] Component RolloutWorker_w7 stopped! | |
| [2025-01-29 08:56:58,189][02627] Loop rollout_proc7_evt_loop terminating... | |
| [2025-01-29 08:56:58,221][02620] Stopping RolloutWorker_w1... | |
| [2025-01-29 08:56:58,220][00651] Component RolloutWorker_w1 stopped! | |
| [2025-01-29 08:56:58,222][02620] Loop rollout_proc1_evt_loop terminating... | |
| [2025-01-29 08:56:58,227][00651] Waiting for process learner_proc0 to stop... | |
| [2025-01-29 08:56:59,684][00651] Waiting for process inference_proc0-0 to join... | |
| [2025-01-29 08:56:59,692][00651] Waiting for process rollout_proc0 to join... | |
| [2025-01-29 08:57:01,665][00651] Waiting for process rollout_proc1 to join... | |
| [2025-01-29 08:57:01,669][00651] Waiting for process rollout_proc2 to join... | |
| [2025-01-29 08:57:01,673][00651] Waiting for process rollout_proc3 to join... | |
| [2025-01-29 08:57:01,675][00651] Waiting for process rollout_proc4 to join... | |
| [2025-01-29 08:57:01,678][00651] Waiting for process rollout_proc5 to join... | |
| [2025-01-29 08:57:01,681][00651] Waiting for process rollout_proc6 to join... | |
| [2025-01-29 08:57:01,684][00651] Waiting for process rollout_proc7 to join... | |
| [2025-01-29 08:57:01,686][00651] Batcher 0 profile tree view: | |
| batching: 26.7923, releasing_batches: 0.0259 | |
| [2025-01-29 08:57:01,687][00651] InferenceWorker_p0-w0 profile tree view: | |
| wait_policy: 0.0000 | |
| wait_policy_total: 442.5107 | |
| update_model: 8.0882 | |
| weight_update: 0.0027 | |
| one_step: 0.0071 | |
| handle_policy_step: 551.8484 | |
| deserialize: 13.5782, stack: 2.9701, obs_to_device_normalize: 117.4222, forward: 282.8342, send_messages: 27.1902 | |
| prepare_outputs: 83.8513 | |
| to_cpu: 51.9100 | |
| [2025-01-29 08:57:01,689][00651] Learner 0 profile tree view: | |
| misc: 0.0035, prepare_batch: 14.5887 | |
| train: 73.1159 | |
| epoch_init: 0.0116, minibatch_init: 0.0061, losses_postprocess: 0.6405, kl_divergence: 0.6319, after_optimizer: 33.5056 | |
| calculate_losses: 26.0761 | |
| losses_init: 0.0039, forward_head: 1.2641, bptt_initial: 17.5653, tail: 1.0275, advantages_returns: 0.2565, losses: 3.8971 | |
| bptt: 1.8668 | |
| bptt_forward_core: 1.7742 | |
| update: 11.6707 | |
| clip: 0.8298 | |
| [2025-01-29 08:57:01,693][00651] RolloutWorker_w0 profile tree view: | |
| wait_for_trajectories: 0.2621, enqueue_policy_requests: 112.7649, env_step: 808.4728, overhead: 11.4668, complete_rollouts: 7.2940 | |
| save_policy_outputs: 18.9420 | |
| split_output_tensors: 7.2818 | |
| [2025-01-29 08:57:01,694][00651] RolloutWorker_w7 profile tree view: | |
| wait_for_trajectories: 0.3846, enqueue_policy_requests: 118.8723, env_step: 804.5749, overhead: 12.0656, complete_rollouts: 6.4974 | |
| save_policy_outputs: 18.6956 | |
| split_output_tensors: 7.4016 | |
| [2025-01-29 08:57:01,695][00651] Loop Runner_EvtLoop terminating... | |
| [2025-01-29 08:57:01,697][00651] Runner profile tree view: | |
| main_loop: 1068.7079 | |
| [2025-01-29 08:57:01,700][00651] Collected {0: 4005888}, FPS: 3748.3 | |
| [2025-01-29 08:57:02,089][00651] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-01-29 08:57:02,090][00651] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-01-29 08:57:02,093][00651] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-01-29 08:57:02,096][00651] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-01-29 08:57:02,099][00651] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-01-29 08:57:02,102][00651] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-01-29 08:57:02,104][00651] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-01-29 08:57:02,105][00651] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-01-29 08:57:02,106][00651] Adding new argument 'push_to_hub'=False that is not in the saved config file! | |
| [2025-01-29 08:57:02,107][00651] Adding new argument 'hf_repository'=None that is not in the saved config file! | |
| [2025-01-29 08:57:02,108][00651] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-01-29 08:57:02,109][00651] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-01-29 08:57:02,110][00651] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-01-29 08:57:02,111][00651] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-01-29 08:57:02,112][00651] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-01-29 08:57:02,149][00651] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-01-29 08:57:02,153][00651] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-01-29 08:57:02,154][00651] RunningMeanStd input shape: (1,) | |
| [2025-01-29 08:57:02,171][00651] ConvEncoder: input_channels=3 | |
| [2025-01-29 08:57:02,289][00651] Conv encoder output size: 512 | |
| [2025-01-29 08:57:02,291][00651] Policy head output size: 512 | |
| [2025-01-29 08:57:02,469][00651] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-01-29 08:57:03,273][00651] Num frames 100... | |
| [2025-01-29 08:57:03,431][00651] Num frames 200... | |
| [2025-01-29 08:57:03,569][00651] Num frames 300... | |
| [2025-01-29 08:57:03,700][00651] Num frames 400... | |
| [2025-01-29 08:57:03,826][00651] Num frames 500... | |
| [2025-01-29 08:57:03,952][00651] Num frames 600... | |
| [2025-01-29 08:57:04,076][00651] Num frames 700... | |
| [2025-01-29 08:57:04,215][00651] Num frames 800... | |
| [2025-01-29 08:57:04,394][00651] Num frames 900... | |
| [2025-01-29 08:57:04,574][00651] Num frames 1000... | |
| [2025-01-29 08:57:04,737][00651] Num frames 1100... | |
| [2025-01-29 08:57:04,901][00651] Num frames 1200... | |
| [2025-01-29 08:57:05,075][00651] Num frames 1300... | |
| [2025-01-29 08:57:05,273][00651] Avg episode rewards: #0: 30.810, true rewards: #0: 13.810 | |
| [2025-01-29 08:57:05,278][00651] Avg episode reward: 30.810, avg true_objective: 13.810 | |
| [2025-01-29 08:57:05,309][00651] Num frames 1400... | |
| [2025-01-29 08:57:05,471][00651] Num frames 1500... | |
| [2025-01-29 08:57:05,658][00651] Num frames 1600... | |
| [2025-01-29 08:57:05,830][00651] Num frames 1700... | |
| [2025-01-29 08:57:06,000][00651] Num frames 1800... | |
| [2025-01-29 08:57:06,217][00651] Avg episode rewards: #0: 20.465, true rewards: #0: 9.465 | |
| [2025-01-29 08:57:06,219][00651] Avg episode reward: 20.465, avg true_objective: 9.465 | |
| [2025-01-29 08:57:06,235][00651] Num frames 1900... | |
| [2025-01-29 08:57:06,405][00651] Num frames 2000... | |
| [2025-01-29 08:57:06,590][00651] Num frames 2100... | |
| [2025-01-29 08:57:06,749][00651] Num frames 2200... | |
| [2025-01-29 08:57:06,878][00651] Num frames 2300... | |
| [2025-01-29 08:57:07,002][00651] Num frames 2400... | |
| [2025-01-29 08:57:07,126][00651] Num frames 2500... | |
| [2025-01-29 08:57:07,257][00651] Num frames 2600... | |
| [2025-01-29 08:57:07,382][00651] Num frames 2700... | |
| [2025-01-29 08:57:07,509][00651] Num frames 2800... | |
| [2025-01-29 08:57:07,638][00651] Num frames 2900... | |
| [2025-01-29 08:57:07,773][00651] Num frames 3000... | |
| [2025-01-29 08:57:07,901][00651] Num frames 3100... | |
| [2025-01-29 08:57:08,028][00651] Num frames 3200... | |
| [2025-01-29 08:57:08,170][00651] Avg episode rewards: #0: 23.230, true rewards: #0: 10.897 | |
| [2025-01-29 08:57:08,172][00651] Avg episode reward: 23.230, avg true_objective: 10.897 | |
| [2025-01-29 08:57:08,217][00651] Num frames 3300... | |
| [2025-01-29 08:57:08,344][00651] Num frames 3400... | |
| [2025-01-29 08:57:08,474][00651] Num frames 3500... | |
| [2025-01-29 08:57:08,600][00651] Num frames 3600... | |
| [2025-01-29 08:57:08,735][00651] Num frames 3700... | |
| [2025-01-29 08:57:08,864][00651] Num frames 3800... | |
| [2025-01-29 08:57:08,988][00651] Avg episode rewards: #0: 20.885, true rewards: #0: 9.635 | |
| [2025-01-29 08:57:08,990][00651] Avg episode reward: 20.885, avg true_objective: 9.635 | |
| [2025-01-29 08:57:09,050][00651] Num frames 3900... | |
| [2025-01-29 08:57:09,177][00651] Num frames 4000... | |
| [2025-01-29 08:57:09,312][00651] Num frames 4100... | |
| [2025-01-29 08:57:09,436][00651] Num frames 4200... | |
| [2025-01-29 08:57:09,565][00651] Num frames 4300... | |
| [2025-01-29 08:57:09,698][00651] Num frames 4400... | |
| [2025-01-29 08:57:09,829][00651] Num frames 4500... | |
| [2025-01-29 08:57:09,956][00651] Num frames 4600... | |
| [2025-01-29 08:57:10,086][00651] Num frames 4700... | |
| [2025-01-29 08:57:10,246][00651] Avg episode rewards: #0: 21.564, true rewards: #0: 9.564 | |
| [2025-01-29 08:57:10,248][00651] Avg episode reward: 21.564, avg true_objective: 9.564 | |
| [2025-01-29 08:57:10,272][00651] Num frames 4800... | |
| [2025-01-29 08:57:10,396][00651] Num frames 4900... | |
| [2025-01-29 08:57:10,526][00651] Num frames 5000... | |
| [2025-01-29 08:57:10,650][00651] Num frames 5100... | |
| [2025-01-29 08:57:10,786][00651] Num frames 5200... | |
| [2025-01-29 08:57:10,916][00651] Num frames 5300... | |
| [2025-01-29 08:57:11,041][00651] Num frames 5400... | |
| [2025-01-29 08:57:11,165][00651] Num frames 5500... | |
| [2025-01-29 08:57:11,301][00651] Num frames 5600... | |
| [2025-01-29 08:57:11,428][00651] Num frames 5700... | |
| [2025-01-29 08:57:11,553][00651] Num frames 5800... | |
| [2025-01-29 08:57:11,687][00651] Num frames 5900... | |
| [2025-01-29 08:57:11,828][00651] Num frames 6000... | |
| [2025-01-29 08:57:11,956][00651] Num frames 6100... | |
| [2025-01-29 08:57:12,083][00651] Num frames 6200... | |
| [2025-01-29 08:57:12,216][00651] Num frames 6300... | |
| [2025-01-29 08:57:12,346][00651] Num frames 6400... | |
| [2025-01-29 08:57:12,472][00651] Num frames 6500... | |
| [2025-01-29 08:57:12,598][00651] Num frames 6600... | |
| [2025-01-29 08:57:12,727][00651] Num frames 6700... | |
| [2025-01-29 08:57:12,864][00651] Num frames 6800... | |
| [2025-01-29 08:57:13,023][00651] Avg episode rewards: #0: 27.970, true rewards: #0: 11.470 | |
| [2025-01-29 08:57:13,025][00651] Avg episode reward: 27.970, avg true_objective: 11.470 | |
| [2025-01-29 08:57:13,050][00651] Num frames 6900... | |
| [2025-01-29 08:57:13,173][00651] Num frames 7000... | |
| [2025-01-29 08:57:13,303][00651] Num frames 7100... | |
| [2025-01-29 08:57:13,441][00651] Num frames 7200... | |
| [2025-01-29 08:57:13,568][00651] Num frames 7300... | |
| [2025-01-29 08:57:13,696][00651] Num frames 7400... | |
| [2025-01-29 08:57:13,832][00651] Num frames 7500... | |
| [2025-01-29 08:57:13,958][00651] Avg episode rewards: #0: 26.077, true rewards: #0: 10.791 | |
| [2025-01-29 08:57:13,959][00651] Avg episode reward: 26.077, avg true_objective: 10.791 | |
| [2025-01-29 08:57:14,023][00651] Num frames 7600... | |
| [2025-01-29 08:57:14,153][00651] Num frames 7700... | |
| [2025-01-29 08:57:14,285][00651] Num frames 7800... | |
| [2025-01-29 08:57:14,415][00651] Num frames 7900... | |
| [2025-01-29 08:57:14,539][00651] Num frames 8000... | |
| [2025-01-29 08:57:14,599][00651] Avg episode rewards: #0: 23.877, true rewards: #0: 10.002 | |
| [2025-01-29 08:57:14,600][00651] Avg episode reward: 23.877, avg true_objective: 10.002 | |
| [2025-01-29 08:57:14,723][00651] Num frames 8100... | |
| [2025-01-29 08:57:14,859][00651] Num frames 8200... | |
| [2025-01-29 08:57:14,984][00651] Num frames 8300... | |
| [2025-01-29 08:57:15,110][00651] Num frames 8400... | |
| [2025-01-29 08:57:15,246][00651] Num frames 8500... | |
| [2025-01-29 08:57:15,370][00651] Num frames 8600... | |
| [2025-01-29 08:57:15,498][00651] Num frames 8700... | |
| [2025-01-29 08:57:15,563][00651] Avg episode rewards: #0: 22.784, true rewards: #0: 9.673 | |
| [2025-01-29 08:57:15,565][00651] Avg episode reward: 22.784, avg true_objective: 9.673 | |
| [2025-01-29 08:57:15,685][00651] Num frames 8800... | |
| [2025-01-29 08:57:15,814][00651] Num frames 8900... | |
| [2025-01-29 08:57:15,948][00651] Num frames 9000... | |
| [2025-01-29 08:57:16,074][00651] Num frames 9100... | |
| [2025-01-29 08:57:16,207][00651] Num frames 9200... | |
| [2025-01-29 08:57:16,334][00651] Num frames 9300... | |
| [2025-01-29 08:57:16,462][00651] Num frames 9400... | |
| [2025-01-29 08:57:16,589][00651] Num frames 9500... | |
| [2025-01-29 08:57:16,743][00651] Num frames 9600... | |
| [2025-01-29 08:57:16,923][00651] Num frames 9700... | |
| [2025-01-29 08:57:17,088][00651] Num frames 9800... | |
| [2025-01-29 08:57:17,257][00651] Num frames 9900... | |
| [2025-01-29 08:57:17,406][00651] Avg episode rewards: #0: 23.354, true rewards: #0: 9.954 | |
| [2025-01-29 08:57:17,408][00651] Avg episode reward: 23.354, avg true_objective: 9.954 | |
| [2025-01-29 08:58:17,510][00651] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |
| [2025-01-29 09:06:35,035][00651] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-01-29 09:06:35,042][00651] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-01-29 09:06:35,046][00651] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-01-29 09:06:35,047][00651] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-01-29 09:06:35,049][00651] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-01-29 09:06:35,051][00651] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-01-29 09:06:35,053][00651] Adding new argument 'max_num_frames'=100000 that is not in the saved config file! | |
| [2025-01-29 09:06:35,054][00651] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-01-29 09:06:35,057][00651] Adding new argument 'push_to_hub'=True that is not in the saved config file! | |
| [2025-01-29 09:06:35,058][00651] Adding new argument 'hf_repository'='hwting/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file! | |
| [2025-01-29 09:06:35,059][00651] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-01-29 09:06:35,061][00651] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-01-29 09:06:35,062][00651] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-01-29 09:06:35,063][00651] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-01-29 09:06:35,064][00651] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-01-29 09:06:35,122][00651] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-01-29 09:06:35,124][00651] RunningMeanStd input shape: (1,) | |
| [2025-01-29 09:06:35,147][00651] ConvEncoder: input_channels=3 | |
| [2025-01-29 09:06:35,201][00651] Conv encoder output size: 512 | |
| [2025-01-29 09:06:35,204][00651] Policy head output size: 512 | |
| [2025-01-29 09:06:35,232][00651] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-01-29 09:06:35,885][00651] Num frames 100... | |
| [2025-01-29 09:06:36,070][00651] Num frames 200... | |
| [2025-01-29 09:06:36,247][00651] Num frames 300... | |
| [2025-01-29 09:06:36,422][00651] Num frames 400... | |
| [2025-01-29 09:06:36,581][00651] Num frames 500... | |
| [2025-01-29 09:06:36,708][00651] Num frames 600... | |
| [2025-01-29 09:06:36,835][00651] Num frames 700... | |
| [2025-01-29 09:06:36,964][00651] Num frames 800... | |
| [2025-01-29 09:06:37,092][00651] Num frames 900... | |
| [2025-01-29 09:06:37,217][00651] Num frames 1000... | |
| [2025-01-29 09:06:37,368][00651] Num frames 1100... | |
| [2025-01-29 09:06:37,524][00651] Avg episode rewards: #0: 25.840, true rewards: #0: 11.840 | |
| [2025-01-29 09:06:37,526][00651] Avg episode reward: 25.840, avg true_objective: 11.840 | |
| [2025-01-29 09:06:37,550][00651] Num frames 1200... | |
| [2025-01-29 09:06:37,673][00651] Num frames 1300... | |
| [2025-01-29 09:06:37,801][00651] Num frames 1400... | |
| [2025-01-29 09:06:37,928][00651] Num frames 1500... | |
| [2025-01-29 09:06:38,055][00651] Num frames 1600... | |
| [2025-01-29 09:06:38,180][00651] Num frames 1700... | |
| [2025-01-29 09:06:38,325][00651] Num frames 1800... | |
| [2025-01-29 09:06:38,454][00651] Num frames 1900... | |
| [2025-01-29 09:06:38,583][00651] Num frames 2000... | |
| [2025-01-29 09:06:38,710][00651] Num frames 2100... | |
| [2025-01-29 09:06:38,874][00651] Avg episode rewards: #0: 23.935, true rewards: #0: 10.935 | |
| [2025-01-29 09:06:38,877][00651] Avg episode reward: 23.935, avg true_objective: 10.935 | |
| [2025-01-29 09:06:38,896][00651] Num frames 2200... | |
| [2025-01-29 09:06:39,020][00651] Num frames 2300... | |
| [2025-01-29 09:06:39,148][00651] Num frames 2400... | |
| [2025-01-29 09:06:39,272][00651] Num frames 2500... | |
| [2025-01-29 09:06:39,416][00651] Num frames 2600... | |
| [2025-01-29 09:06:39,553][00651] Num frames 2700... | |
| [2025-01-29 09:06:39,699][00651] Num frames 2800... | |
| [2025-01-29 09:06:39,825][00651] Num frames 2900... | |
| [2025-01-29 09:06:39,952][00651] Num frames 3000... | |
| [2025-01-29 09:06:40,077][00651] Num frames 3100... | |
| [2025-01-29 09:06:40,233][00651] Avg episode rewards: #0: 24.597, true rewards: #0: 10.597 | |
| [2025-01-29 09:06:40,234][00651] Avg episode reward: 24.597, avg true_objective: 10.597 | |
| [2025-01-29 09:06:40,265][00651] Num frames 3200... | |
| [2025-01-29 09:06:40,417][00651] Num frames 3300... | |
| [2025-01-29 09:06:40,539][00651] Num frames 3400... | |
| [2025-01-29 09:06:40,669][00651] Num frames 3500... | |
| [2025-01-29 09:06:40,784][00651] Avg episode rewards: #0: 19.613, true rewards: #0: 8.862 | |
| [2025-01-29 09:06:40,786][00651] Avg episode reward: 19.613, avg true_objective: 8.862 | |
| [2025-01-29 09:06:40,856][00651] Num frames 3600... | |
| [2025-01-29 09:06:40,981][00651] Num frames 3700... | |
| [2025-01-29 09:06:41,106][00651] Num frames 3800... | |
| [2025-01-29 09:06:41,241][00651] Num frames 3900... | |
| [2025-01-29 09:06:41,387][00651] Num frames 4000... | |
| [2025-01-29 09:06:41,519][00651] Num frames 4100... | |
| [2025-01-29 09:06:41,650][00651] Num frames 4200... | |
| [2025-01-29 09:06:41,781][00651] Num frames 4300... | |
| [2025-01-29 09:06:41,908][00651] Num frames 4400... | |
| [2025-01-29 09:06:42,036][00651] Num frames 4500... | |
| [2025-01-29 09:06:42,167][00651] Num frames 4600... | |
| [2025-01-29 09:06:42,296][00651] Num frames 4700... | |
| [2025-01-29 09:06:42,479][00651] Avg episode rewards: #0: 21.986, true rewards: #0: 9.586 | |
| [2025-01-29 09:06:42,482][00651] Avg episode reward: 21.986, avg true_objective: 9.586 | |
| [2025-01-29 09:06:42,494][00651] Num frames 4800... | |
| [2025-01-29 09:06:42,619][00651] Num frames 4900... | |
| [2025-01-29 09:06:42,751][00651] Num frames 5000... | |
| [2025-01-29 09:06:42,878][00651] Num frames 5100... | |
| [2025-01-29 09:06:43,009][00651] Num frames 5200... | |
| [2025-01-29 09:06:43,133][00651] Num frames 5300... | |
| [2025-01-29 09:06:43,265][00651] Num frames 5400... | |
| [2025-01-29 09:06:43,412][00651] Num frames 5500... | |
| [2025-01-29 09:06:43,554][00651] Num frames 5600... | |
| [2025-01-29 09:06:43,643][00651] Avg episode rewards: #0: 21.708, true rewards: #0: 9.375 | |
| [2025-01-29 09:06:43,647][00651] Avg episode reward: 21.708, avg true_objective: 9.375 | |
| [2025-01-29 09:06:43,746][00651] Num frames 5700... | |
| [2025-01-29 09:06:43,877][00651] Num frames 5800... | |
| [2025-01-29 09:06:44,005][00651] Num frames 5900... | |
| [2025-01-29 09:06:44,131][00651] Num frames 6000... | |
| [2025-01-29 09:06:44,259][00651] Num frames 6100... | |
| [2025-01-29 09:06:44,397][00651] Num frames 6200... | |
| [2025-01-29 09:06:44,536][00651] Num frames 6300... | |
| [2025-01-29 09:06:44,709][00651] Avg episode rewards: #0: 20.847, true rewards: #0: 9.133 | |
| [2025-01-29 09:06:44,711][00651] Avg episode reward: 20.847, avg true_objective: 9.133 | |
| [2025-01-29 09:06:44,723][00651] Num frames 6400... | |
| [2025-01-29 09:06:44,847][00651] Num frames 6500... | |
| [2025-01-29 09:06:44,973][00651] Num frames 6600... | |
| [2025-01-29 09:06:45,101][00651] Num frames 6700... | |
| [2025-01-29 09:06:45,230][00651] Num frames 6800... | |
| [2025-01-29 09:06:45,367][00651] Num frames 6900... | |
| [2025-01-29 09:06:45,500][00651] Num frames 7000... | |
| [2025-01-29 09:06:45,625][00651] Num frames 7100... | |
| [2025-01-29 09:06:45,757][00651] Num frames 7200... | |
| [2025-01-29 09:06:45,884][00651] Num frames 7300... | |
| [2025-01-29 09:06:46,013][00651] Num frames 7400... | |
| [2025-01-29 09:06:46,141][00651] Num frames 7500... | |
| [2025-01-29 09:06:46,273][00651] Num frames 7600... | |
| [2025-01-29 09:06:46,423][00651] Num frames 7700... | |
| [2025-01-29 09:06:46,570][00651] Num frames 7800... | |
| [2025-01-29 09:06:46,751][00651] Num frames 7900... | |
| [2025-01-29 09:06:46,919][00651] Num frames 8000... | |
| [2025-01-29 09:06:47,086][00651] Num frames 8100... | |
| [2025-01-29 09:06:47,259][00651] Num frames 8200... | |
| [2025-01-29 09:06:47,442][00651] Num frames 8300... | |
| [2025-01-29 09:06:47,624][00651] Num frames 8400... | |
| [2025-01-29 09:06:47,841][00651] Avg episode rewards: #0: 24.866, true rewards: #0: 10.616 | |
| [2025-01-29 09:06:47,844][00651] Avg episode reward: 24.866, avg true_objective: 10.616 | |
| [2025-01-29 09:06:47,859][00651] Num frames 8500... | |
| [2025-01-29 09:06:48,031][00651] Num frames 8600... | |
| [2025-01-29 09:06:48,207][00651] Num frames 8700... | |
| [2025-01-29 09:06:48,384][00651] Num frames 8800... | |
| [2025-01-29 09:06:48,562][00651] Num frames 8900... | |
| [2025-01-29 09:06:48,742][00651] Num frames 9000... | |
| [2025-01-29 09:06:48,917][00651] Num frames 9100... | |
| [2025-01-29 09:06:49,099][00651] Num frames 9200... | |
| [2025-01-29 09:06:49,197][00651] Avg episode rewards: #0: 23.810, true rewards: #0: 10.254 | |
| [2025-01-29 09:06:49,199][00651] Avg episode reward: 23.810, avg true_objective: 10.254 | |
| [2025-01-29 09:06:49,291][00651] Num frames 9300... | |
| [2025-01-29 09:06:49,424][00651] Num frames 9400... | |
| [2025-01-29 09:06:49,550][00651] Num frames 9500... | |
| [2025-01-29 09:06:49,681][00651] Num frames 9600... | |
| [2025-01-29 09:06:49,808][00651] Num frames 9700... | |
| [2025-01-29 09:06:49,931][00651] Num frames 9800... | |
| [2025-01-29 09:06:50,058][00651] Num frames 9900... | |
| [2025-01-29 09:06:50,221][00651] Avg episode rewards: #0: 22.988, true rewards: #0: 9.988 | |
| [2025-01-29 09:06:50,223][00651] Avg episode reward: 22.988, avg true_objective: 9.988 | |
| [2025-01-29 09:07:50,528][00651] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |