|
{ |
|
"results": { |
|
"gat": { |
|
"acc,none": 0.2664618086040386, |
|
"acc_stderr,none": 0.003495353970358859, |
|
"alias": "gat" |
|
}, |
|
"gat_algebra": { |
|
"alias": " - gat_algebra", |
|
"acc,none": 0.24935064935064935, |
|
"acc_stderr,none": 0.008335372497778036 |
|
}, |
|
"gat_analogy": { |
|
"alias": " - gat_analogy", |
|
"acc,none": 0.2983606557377049, |
|
"acc_stderr,none": 0.00873445255221157 |
|
}, |
|
"gat_arithmetic": { |
|
"alias": " - gat_arithmetic", |
|
"acc,none": 0.25874125874125875, |
|
"acc_stderr,none": 0.008403358167147365 |
|
}, |
|
"gat_association": { |
|
"alias": " - gat_association", |
|
"acc,none": 0.19138755980861244, |
|
"acc_stderr,none": 0.012175219862346352 |
|
}, |
|
"gat_comparisons": { |
|
"alias": " - gat_comparisons", |
|
"acc,none": 0.30573770491803276, |
|
"acc_stderr,none": 0.013195760894549713 |
|
}, |
|
"gat_completion": { |
|
"alias": " - gat_completion", |
|
"acc,none": 0.27603305785123966, |
|
"acc_stderr,none": 0.012856618756239491 |
|
}, |
|
"gat_contextual": { |
|
"alias": " - gat_contextual", |
|
"acc,none": 0.2561349693251534, |
|
"acc_stderr,none": 0.012092310807729188 |
|
}, |
|
"gat_geometry": { |
|
"alias": " - gat_geometry", |
|
"acc,none": 0.25205479452054796, |
|
"acc_stderr,none": 0.022757873597035808 |
|
}, |
|
"gat_reading": { |
|
"alias": " - gat_reading", |
|
"acc,none": 0.2729678638941399, |
|
"acc_stderr,none": 0.008663668753419975 |
|
} |
|
}, |
|
"groups": { |
|
"gat": { |
|
"acc,none": 0.2664618086040386, |
|
"acc_stderr,none": 0.003495353970358859, |
|
"alias": "gat" |
|
} |
|
}, |
|
"group_subtasks": { |
|
"gat": [ |
|
"gat_analogy", |
|
"gat_association", |
|
"gat_completion", |
|
"gat_reading", |
|
"gat_algebra", |
|
"gat_arithmetic", |
|
"gat_comparisons", |
|
"gat_contextual", |
|
"gat_geometry" |
|
] |
|
}, |
|
"configs": { |
|
"gat_algebra": { |
|
"task": "gat_algebra", |
|
"dataset_path": "lm_eval/tasks/gat/gat_data/gat.py", |
|
"dataset_name": "algebra", |
|
"dataset_kwargs": { |
|
"trust_remote_code": true |
|
}, |
|
"test_split": "test", |
|
"fewshot_split": "validation", |
|
"process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n # def _process_doc(doc):\n \n # subject = doc['id'].split(\"-\")[0]\n # subject_ar = subtasks_ar[subtasks.index(subject)]\n # out_doc = {**doc, 'subject_ar': subject_ar}\n # print(subject_ar)\n # print(out_doc)\n # return out_doc\n\n return dataset\n", |
|
"doc_to_text": "{{question}}\n\u0623. {{choices[0]}}\n\u0628. {{choices[1]}}\n\u062c. {{choices[2]}}\n\u062f. {{choices[3]}}\n\u0627\u0644\u0627\u062c\u0627\u0628\u0629:", |
|
"doc_to_target": "{{label}}", |
|
"doc_to_choice": [ |
|
"\u0623", |
|
"\u0628", |
|
"\u062c", |
|
"\u062f" |
|
], |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"gat_analogy": { |
|
"task": "gat_analogy", |
|
"dataset_path": "lm_eval/tasks/gat/gat_data/gat.py", |
|
"dataset_name": "analogy", |
|
"dataset_kwargs": { |
|
"trust_remote_code": true |
|
}, |
|
"test_split": "test", |
|
"fewshot_split": "validation", |
|
"process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n # def _process_doc(doc):\n \n # subject = doc['id'].split(\"-\")[0]\n # subject_ar = subtasks_ar[subtasks.index(subject)]\n # out_doc = {**doc, 'subject_ar': subject_ar}\n # print(subject_ar)\n # print(out_doc)\n # return out_doc\n\n return dataset\n", |
|
"doc_to_text": "{{question}}\n\u0623. {{choices[0]}}\n\u0628. {{choices[1]}}\n\u062c. {{choices[2]}}\n\u062f. {{choices[3]}}\n\u0627\u0644\u0627\u062c\u0627\u0628\u0629:", |
|
"doc_to_target": "{{label}}", |
|
"doc_to_choice": [ |
|
"\u0623", |
|
"\u0628", |
|
"\u062c", |
|
"\u062f" |
|
], |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"gat_arithmetic": { |
|
"task": "gat_arithmetic", |
|
"dataset_path": "lm_eval/tasks/gat/gat_data/gat.py", |
|
"dataset_name": "arithmetic", |
|
"dataset_kwargs": { |
|
"trust_remote_code": true |
|
}, |
|
"test_split": "test", |
|
"fewshot_split": "validation", |
|
"process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n # def _process_doc(doc):\n \n # subject = doc['id'].split(\"-\")[0]\n # subject_ar = subtasks_ar[subtasks.index(subject)]\n # out_doc = {**doc, 'subject_ar': subject_ar}\n # print(subject_ar)\n # print(out_doc)\n # return out_doc\n\n return dataset\n", |
|
"doc_to_text": "{{question}}\n\u0623. {{choices[0]}}\n\u0628. {{choices[1]}}\n\u062c. {{choices[2]}}\n\u062f. {{choices[3]}}\n\u0627\u0644\u0627\u062c\u0627\u0628\u0629:", |
|
"doc_to_target": "{{label}}", |
|
"doc_to_choice": [ |
|
"\u0623", |
|
"\u0628", |
|
"\u062c", |
|
"\u062f" |
|
], |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"gat_association": { |
|
"task": "gat_association", |
|
"dataset_path": "lm_eval/tasks/gat/gat_data/gat.py", |
|
"dataset_name": "association", |
|
"dataset_kwargs": { |
|
"trust_remote_code": true |
|
}, |
|
"test_split": "test", |
|
"fewshot_split": "validation", |
|
"process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n # def _process_doc(doc):\n \n # subject = doc['id'].split(\"-\")[0]\n # subject_ar = subtasks_ar[subtasks.index(subject)]\n # out_doc = {**doc, 'subject_ar': subject_ar}\n # print(subject_ar)\n # print(out_doc)\n # return out_doc\n\n return dataset\n", |
|
"doc_to_text": "{{question}}\n\u0623. {{choices[0]}}\n\u0628. {{choices[1]}}\n\u062c. {{choices[2]}}\n\u062f. {{choices[3]}}\n\u0627\u0644\u0627\u062c\u0627\u0628\u0629:", |
|
"doc_to_target": "{{label}}", |
|
"doc_to_choice": [ |
|
"\u0623", |
|
"\u0628", |
|
"\u062c", |
|
"\u062f" |
|
], |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"gat_comparisons": { |
|
"task": "gat_comparisons", |
|
"dataset_path": "lm_eval/tasks/gat/gat_data/gat.py", |
|
"dataset_name": "comparisons", |
|
"dataset_kwargs": { |
|
"trust_remote_code": true |
|
}, |
|
"test_split": "test", |
|
"fewshot_split": "validation", |
|
"process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n # def _process_doc(doc):\n \n # subject = doc['id'].split(\"-\")[0]\n # subject_ar = subtasks_ar[subtasks.index(subject)]\n # out_doc = {**doc, 'subject_ar': subject_ar}\n # print(subject_ar)\n # print(out_doc)\n # return out_doc\n\n return dataset\n", |
|
"doc_to_text": "{{question}}\n\u0623. {{choices[0]}}\n\u0628. {{choices[1]}}\n\u062c. {{choices[2]}}\n\u062f. {{choices[3]}}\n\u0627\u0644\u0627\u062c\u0627\u0628\u0629:", |
|
"doc_to_target": "{{label}}", |
|
"doc_to_choice": [ |
|
"\u0623", |
|
"\u0628", |
|
"\u062c", |
|
"\u062f" |
|
], |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"gat_completion": { |
|
"task": "gat_completion", |
|
"dataset_path": "lm_eval/tasks/gat/gat_data/gat.py", |
|
"dataset_name": "completion", |
|
"dataset_kwargs": { |
|
"trust_remote_code": true |
|
}, |
|
"test_split": "test", |
|
"fewshot_split": "validation", |
|
"process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n # def _process_doc(doc):\n \n # subject = doc['id'].split(\"-\")[0]\n # subject_ar = subtasks_ar[subtasks.index(subject)]\n # out_doc = {**doc, 'subject_ar': subject_ar}\n # print(subject_ar)\n # print(out_doc)\n # return out_doc\n\n return dataset\n", |
|
"doc_to_text": "{{question}}\n\u0623. {{choices[0]}}\n\u0628. {{choices[1]}}\n\u062c. {{choices[2]}}\n\u062f. {{choices[3]}}\n\u0627\u0644\u0627\u062c\u0627\u0628\u0629:", |
|
"doc_to_target": "{{label}}", |
|
"doc_to_choice": [ |
|
"\u0623", |
|
"\u0628", |
|
"\u062c", |
|
"\u062f" |
|
], |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"gat_contextual": { |
|
"task": "gat_contextual", |
|
"dataset_path": "lm_eval/tasks/gat/gat_data/gat.py", |
|
"dataset_name": "contextual", |
|
"dataset_kwargs": { |
|
"trust_remote_code": true |
|
}, |
|
"test_split": "test", |
|
"fewshot_split": "validation", |
|
"process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n # def _process_doc(doc):\n \n # subject = doc['id'].split(\"-\")[0]\n # subject_ar = subtasks_ar[subtasks.index(subject)]\n # out_doc = {**doc, 'subject_ar': subject_ar}\n # print(subject_ar)\n # print(out_doc)\n # return out_doc\n\n return dataset\n", |
|
"doc_to_text": "{{question}}\n\u0623. {{choices[0]}}\n\u0628. {{choices[1]}}\n\u062c. {{choices[2]}}\n\u062f. {{choices[3]}}\n\u0627\u0644\u0627\u062c\u0627\u0628\u0629:", |
|
"doc_to_target": "{{label}}", |
|
"doc_to_choice": [ |
|
"\u0623", |
|
"\u0628", |
|
"\u062c", |
|
"\u062f" |
|
], |
|
"description": "\u0627\u0648\u062c\u062f \u0627\u0644\u062e\u0637\u0623 \u0627\u0644\u0633\u064a\u0627\u0642\u064a \u0641\u064a \u0627\u0644\u0639\u0628\u0627\u0631\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0645\u0646 \u0628\u064a\u0646 \u0627\u0644\u062e\u064a\u0627\u0631\u0627\u062a:", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"gat_geometry": { |
|
"task": "gat_geometry", |
|
"dataset_path": "lm_eval/tasks/gat/gat_data/gat.py", |
|
"dataset_name": "geometry", |
|
"dataset_kwargs": { |
|
"trust_remote_code": true |
|
}, |
|
"test_split": "test", |
|
"fewshot_split": "validation", |
|
"process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n # def _process_doc(doc):\n \n # subject = doc['id'].split(\"-\")[0]\n # subject_ar = subtasks_ar[subtasks.index(subject)]\n # out_doc = {**doc, 'subject_ar': subject_ar}\n # print(subject_ar)\n # print(out_doc)\n # return out_doc\n\n return dataset\n", |
|
"doc_to_text": "{{question}}\n\u0623. {{choices[0]}}\n\u0628. {{choices[1]}}\n\u062c. {{choices[2]}}\n\u062f. {{choices[3]}}\n\u0627\u0644\u0627\u062c\u0627\u0628\u0629:", |
|
"doc_to_target": "{{label}}", |
|
"doc_to_choice": [ |
|
"\u0623", |
|
"\u0628", |
|
"\u062c", |
|
"\u062f" |
|
], |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
}, |
|
"gat_reading": { |
|
"task": "gat_reading", |
|
"dataset_path": "lm_eval/tasks/gat/gat_data/gat.py", |
|
"dataset_name": "reading", |
|
"dataset_kwargs": { |
|
"trust_remote_code": true |
|
}, |
|
"test_split": "test", |
|
"fewshot_split": "validation", |
|
"process_docs": "def process_docs(dataset: datasets.Dataset) -> datasets.Dataset:\n # def _process_doc(doc):\n \n # subject = doc['id'].split(\"-\")[0]\n # subject_ar = subtasks_ar[subtasks.index(subject)]\n # out_doc = {**doc, 'subject_ar': subject_ar}\n # print(subject_ar)\n # print(out_doc)\n # return out_doc\n\n return dataset\n", |
|
"doc_to_text": "{{question}}\n\u0623. {{choices[0]}}\n\u0628. {{choices[1]}}\n\u062c. {{choices[2]}}\n\u062f. {{choices[3]}}\n\u0627\u0644\u0627\u062c\u0627\u0628\u0629:", |
|
"doc_to_target": "{{label}}", |
|
"doc_to_choice": [ |
|
"\u0623", |
|
"\u0628", |
|
"\u062c", |
|
"\u062f" |
|
], |
|
"description": "", |
|
"target_delimiter": " ", |
|
"fewshot_delimiter": "\n\n", |
|
"num_fewshot": 0, |
|
"metric_list": [ |
|
{ |
|
"metric": "acc", |
|
"aggregation": "mean", |
|
"higher_is_better": true |
|
} |
|
], |
|
"output_type": "multiple_choice", |
|
"repeats": 1, |
|
"should_decontaminate": false, |
|
"metadata": { |
|
"version": 0.0 |
|
} |
|
} |
|
}, |
|
"versions": { |
|
"gat": 0, |
|
"gat_algebra": 0.0, |
|
"gat_analogy": 0.0, |
|
"gat_arithmetic": 0.0, |
|
"gat_association": 0.0, |
|
"gat_comparisons": 0.0, |
|
"gat_completion": 0.0, |
|
"gat_contextual": 0.0, |
|
"gat_geometry": 0.0, |
|
"gat_reading": 0.0 |
|
}, |
|
"n-shot": { |
|
"gat_algebra": 0, |
|
"gat_analogy": 0, |
|
"gat_arithmetic": 0, |
|
"gat_association": 0, |
|
"gat_comparisons": 0, |
|
"gat_completion": 0, |
|
"gat_contextual": 0, |
|
"gat_geometry": 0, |
|
"gat_reading": 0 |
|
}, |
|
"higher_is_better": { |
|
"gat": { |
|
"acc": true |
|
}, |
|
"gat_algebra": { |
|
"acc": true |
|
}, |
|
"gat_analogy": { |
|
"acc": true |
|
}, |
|
"gat_arithmetic": { |
|
"acc": true |
|
}, |
|
"gat_association": { |
|
"acc": true |
|
}, |
|
"gat_comparisons": { |
|
"acc": true |
|
}, |
|
"gat_completion": { |
|
"acc": true |
|
}, |
|
"gat_contextual": { |
|
"acc": true |
|
}, |
|
"gat_geometry": { |
|
"acc": true |
|
}, |
|
"gat_reading": { |
|
"acc": true |
|
} |
|
}, |
|
"n-samples": { |
|
"gat_analogy": { |
|
"original": 2745, |
|
"effective": 2745 |
|
}, |
|
"gat_association": { |
|
"original": 1045, |
|
"effective": 1045 |
|
}, |
|
"gat_completion": { |
|
"original": 1210, |
|
"effective": 1210 |
|
}, |
|
"gat_reading": { |
|
"original": 2645, |
|
"effective": 2645 |
|
}, |
|
"gat_algebra": { |
|
"original": 2695, |
|
"effective": 2695 |
|
}, |
|
"gat_arithmetic": { |
|
"original": 2717, |
|
"effective": 2717 |
|
}, |
|
"gat_comparisons": { |
|
"original": 1220, |
|
"effective": 1220 |
|
}, |
|
"gat_contextual": { |
|
"original": 1304, |
|
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"pretty_env_info": "PyTorch version: 2.4.0+cu121\nIs debug build: False\nCUDA used to build PyTorch: 12.1\nROCM used to build PyTorch: N/A\n\nOS: Ubuntu 22.04.3 LTS (x86_64)\nGCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0\nClang version: Could not collect\nCMake version: version 3.27.1\nLibc version: glibc-2.35\n\nPython version: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] (64-bit runtime)\nPython platform: Linux-5.15.0-1064-azure-x86_64-with-glibc2.35\nIs CUDA available: True\nCUDA runtime version: 12.2.128\nCUDA_MODULE_LOADING set to: LAZY\nGPU models and configuration: \nGPU 0: NVIDIA A100-SXM4-80GB\nGPU 1: NVIDIA A100-SXM4-80GB\nGPU 2: NVIDIA A100-SXM4-80GB\nGPU 3: NVIDIA A100-SXM4-80GB\nGPU 4: NVIDIA A100-SXM4-80GB\nGPU 5: NVIDIA A100-SXM4-80GB\nGPU 6: NVIDIA A100-SXM4-80GB\nGPU 7: NVIDIA A100-SXM4-80GB\n\nNvidia driver version: 535.161.08\ncuDNN version: Probably one of the following:\n/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.4\n/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.4\nHIP runtime version: N/A\nMIOpen runtime version: N/A\nIs XNNPACK available: True\n\nCPU:\nArchitecture: x86_64\nCPU op-mode(s): 32-bit, 64-bit\nAddress sizes: 48 bits physical, 48 bits virtual\nByte Order: Little Endian\nCPU(s): 96\nOn-line CPU(s) list: 0-95\nVendor ID: AuthenticAMD\nModel name: AMD EPYC 7V12 64-Core Processor\nCPU family: 23\nModel: 49\nThread(s) per core: 1\nCore(s) per socket: 48\nSocket(s): 2\nStepping: 0\nBogoMIPS: 4890.88\nFlags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl tsc_reliable nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm cmp_legacy cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw topoext perfctr_core ssbd vmmcall fsgsbase bmi1 avx2 smep bmi2 rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 clzero xsaveerptr rdpru arat umip rdpid\nHypervisor vendor: Microsoft\nVirtualization type: full\nL1d cache: 3 MiB (96 instances)\nL1i cache: 3 MiB (96 instances)\nL2 cache: 48 MiB (96 instances)\nL3 cache: 384 MiB (24 instances)\nNUMA node(s): 4\nNUMA node0 CPU(s): 0-23\nNUMA node1 CPU(s): 24-47\nNUMA node2 CPU(s): 48-71\nNUMA node3 CPU(s): 72-95\nVulnerability Gather data sampling: Not affected\nVulnerability Itlb multihit: Not affected\nVulnerability L1tf: Not affected\nVulnerability Mds: Not affected\nVulnerability Meltdown: Not affected\nVulnerability Mmio stale data: Not affected\nVulnerability Retbleed: Mitigation; untrained return thunk; SMT disabled\nVulnerability Spec rstack overflow: Mitigation; safe RET, no microcode\nVulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp\nVulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization\nVulnerability Spectre v2: Mitigation; Retpolines; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected\nVulnerability Srbds: Not affected\nVulnerability Tsx async abort: Not affected\n\nVersions of relevant libraries:\n[pip3] numpy==1.26.4\n[pip3] onnx==1.14.0\n[pip3] pytorch-lightning==2.0.7\n[pip3] pytorch-quantization==2.1.2\n[pip3] torch==2.4.0\n[pip3] torch-tensorrt==2.0.0.dev0\n[pip3] torchaudio==2.1.0\n[pip3] torchdata==0.7.0a0\n[pip3] torchmetrics==1.2.0\n[pip3] torchvision==0.19.0\n[pip3] triton==3.0.0\n[conda] Could not collect", |
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