| nohup: ignoring input | |
| + CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 | |
| + DATA_ROOT=/jizhicfs/bojoli | |
| + VISION_TOWER_NAME=clip-vit-large-patch14-336 | |
| + MODEL_NAME=vicuna-7b-1.5 | |
| + VISION_TOWER=/jizhicfs/bojoli/clip-vit-large-patch14-336 | |
| + MODEL_PATH=/jizhicfs/bojoli/vicuna-7b-1.5 | |
| + BASE_RUN_NAME=mmpe_vicuna-7b-1.5_clip-vit-large-patch14-336 | |
| + RUN_NAME=final_mmpe_finetune_vicuna-7b-1.5_clip-vit-large-patch14-336 | |
| + PROMPT_VERSION=v1 | |
| + EVAL_MODEL=../checkpoints/final_mmpe_finetune_vicuna-7b-1.5_clip-vit-large-patch14-336 | |
| + BENCHMARKS=mmbench_en | |
| + python3 -m accelerate.commands.launch --num_processes=8 --main_process_port 12899 -m lmms_eval --model llava --model_args pretrained=../checkpoints/final_mmpe_finetune_vicuna-7b-1.5_clip-vit-large-patch14-336,conv_template=v1 --tasks mmbench_en --batch_size 1 --log_samples --log_samples_suffix final_mmpe_finetune_vicuna-7b-1.5_clip-vit-large-patch14-336 --output_path ./logs/ | |
| The following values were not passed to `accelerate launch` and had defaults used instead: | |
| More than one GPU was found, enabling multi-GPU training. | |
| If this was unintended please pass in `--num_processes=1`. | |
| `--num_machines` was set to a value of `1` | |
| `--mixed_precision` was set to a value of `'no'` | |
| `--dynamo_backend` was set to a value of `'no'` | |
| To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`. | |
| [32m2025-05-19 01:44:28.140[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate[0m:[36m294[0m - [1mVerbosity set to INFO[0m | |
| [32m2025-05-19 01:44:28.206[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate[0m:[36m294[0m - [1mVerbosity set to INFO[0m | |
| [32m2025-05-19 01:44:28.914[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate[0m:[36m294[0m - [1mVerbosity set to INFO[0m | |
| [32m2025-05-19 01:44:28.916[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate[0m:[36m294[0m - [1mVerbosity set to INFO[0m | |
| [32m2025-05-19 01:44:28.922[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate[0m:[36m294[0m - [1mVerbosity set to INFO[0m | |
| [32m2025-05-19 01:44:28.923[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate[0m:[36m294[0m - [1mVerbosity set to INFO[0m | |
| [32m2025-05-19 01:44:28.931[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate[0m:[36m294[0m - [1mVerbosity set to INFO[0m | |
| [32m2025-05-19 01:44:28.941[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate[0m:[36m294[0m - [1mVerbosity set to INFO[0m | |
| Detected kernel version 5.4.119, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher. | |
| [32m2025-05-19 01:44:31.949[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m377[0m - [1mEvaluation tracker args: {'output_path': './logs/'}[0m | |
| [32m2025-05-19 01:44:31.950[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m466[0m - [1mSelected Tasks: ['mmbench_en'][0m | |
| [32m2025-05-19 01:44:31.955[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36msimple_evaluate[0m:[36m155[0m - [1mSetting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234[0m | |
| [32m2025-05-19 01:44:32.253[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m377[0m - [1mEvaluation tracker args: {'output_path': './logs/'}[0m | |
| [32m2025-05-19 01:44:32.253[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m466[0m - [1mSelected Tasks: ['mmbench_en'][0m | |
| [32m2025-05-19 01:44:32.260[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36msimple_evaluate[0m:[36m155[0m - [1mSetting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234[0m | |
| [32m2025-05-19 01:44:32.902[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m377[0m - [1mEvaluation tracker args: {'output_path': './logs/'}[0m | |
| [32m2025-05-19 01:44:32.902[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m466[0m - [1mSelected Tasks: ['mmbench_en'][0m | |
| [32m2025-05-19 01:44:32.907[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36msimple_evaluate[0m:[36m155[0m - [1mSetting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234[0m | |
| [32m2025-05-19 01:44:32.960[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m377[0m - [1mEvaluation tracker args: {'output_path': './logs/'}[0m | |
| [32m2025-05-19 01:44:32.960[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m466[0m - [1mSelected Tasks: ['mmbench_en'][0m | |
| [32m2025-05-19 01:44:32.964[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m377[0m - [1mEvaluation tracker args: {'output_path': './logs/'}[0m | |
| [32m2025-05-19 01:44:32.965[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m466[0m - [1mSelected Tasks: ['mmbench_en'][0m | |
| [32m2025-05-19 01:44:32.966[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36msimple_evaluate[0m:[36m155[0m - [1mSetting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234[0m | |
| [32m2025-05-19 01:44:32.969[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m377[0m - [1mEvaluation tracker args: {'output_path': './logs/'}[0m | |
| [32m2025-05-19 01:44:32.970[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m466[0m - [1mSelected Tasks: ['mmbench_en'][0m | |
| [32m2025-05-19 01:44:32.971[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36msimple_evaluate[0m:[36m155[0m - [1mSetting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234[0m | |
| [32m2025-05-19 01:44:32.972[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m377[0m - [1mEvaluation tracker args: {'output_path': './logs/'}[0m | |
| [32m2025-05-19 01:44:32.972[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m377[0m - [1mEvaluation tracker args: {'output_path': './logs/'}[0m | |
| [32m2025-05-19 01:44:32.973[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m466[0m - [1mSelected Tasks: ['mmbench_en'][0m | |
| [32m2025-05-19 01:44:32.973[0m | [1mINFO [0m | [36m__main__[0m:[36mcli_evaluate_single[0m:[36m466[0m - [1mSelected Tasks: ['mmbench_en'][0m | |
| [32m2025-05-19 01:44:32.977[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36msimple_evaluate[0m:[36m155[0m - [1mSetting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234[0m | |
| [32m2025-05-19 01:44:32.982[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36msimple_evaluate[0m:[36m155[0m - [1mSetting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234[0m | |
| [32m2025-05-19 01:44:32.982[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36msimple_evaluate[0m:[36m155[0m - [1mSetting random seed to 0 | Setting numpy seed to 1234 | Setting torch manual seed to 1234[0m | |
| You are using a model of type llama to instantiate a model of type llava_llama. This is not supported for all configurations of models and can yield errors. | |
| Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s]You are using a model of type llama to instantiate a model of type llava_llama. This is not supported for all configurations of models and can yield errors. | |
| Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s]Detected kernel version 5.4.119, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher. | |
| Rank 0: Loaded LLaVA model: ../checkpoints/final_mmpe_finetune_vicuna-7b-1.5_clip-vit-large-patch14-336 | |
| You are using a model of type llama to instantiate a model of type llava_llama. This is not supported for all configurations of models and can yield errors. | |
| You are using a model of type llama to instantiate a model of type llava_llama. This is not supported for all configurations of models and can yield errors. | |
| You are using a model of type llama to instantiate a model of type llava_llama. This is not supported for all configurations of models and can yield errors. | |
| You are using a model of type llama to instantiate a model of type llava_llama. This is not supported for all configurations of models and can yield errors. | |
| You are using a model of type llama to instantiate a model of type llava_llama. This is not supported for all configurations of models and can yield errors. | |
| Rank 0: Loading vision tower: /jizhicfs/bojoli/clip-vit-large-patch14-336 | |
| Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s] Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s] Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s] Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s] Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s]You are using a model of type llama to instantiate a model of type llava_llama. This is not supported for all configurations of models and can yield errors. | |
| Loading checkpoint shards: 0%| | 0/3 [00:00<?, ?it/s] Loading checkpoint shards: 33%|███▎ | 1/3 [00:04<00:09, 4.86s/it] Loading checkpoint shards: 33%|███▎ | 1/3 [00:04<00:09, 4.87s/it] Loading checkpoint shards: 33%|███▎ | 1/3 [00:04<00:09, 4.96s/it] Loading checkpoint shards: 33%|███▎ | 1/3 [00:04<00:09, 4.91s/it] Loading checkpoint shards: 33%|███▎ | 1/3 [00:04<00:09, 4.95s/it] Loading checkpoint shards: 33%|███▎ | 1/3 [00:05<00:10, 5.02s/it] Loading checkpoint shards: 33%|███▎ | 1/3 [00:05<00:10, 5.19s/it] Loading checkpoint shards: 33%|███▎ | 1/3 [00:05<00:10, 5.01s/it] Loading checkpoint shards: 67%|██████▋ | 2/3 [00:09<00:04, 4.97s/it] Loading checkpoint shards: 67%|██████▋ | 2/3 [00:09<00:04, 4.93s/it] Loading checkpoint shards: 67%|██████▋ | 2/3 [00:10<00:05, 5.02s/it] Loading checkpoint shards: 67%|██████▋ | 2/3 [00:09<00:04, 5.00s/it] Loading checkpoint shards: 67%|██████▋ | 2/3 [00:10<00:05, 5.02s/it] Loading checkpoint shards: 67%|██████▋ | 2/3 [00:10<00:05, 5.10s/it] Loading checkpoint shards: 67%|██████▋ | 2/3 [00:10<00:05, 5.11s/it] Loading checkpoint shards: 67%|██████▋ | 2/3 [00:10<00:05, 5.13s/it] Loading checkpoint shards: 100%|██████████| 3/3 [00:14<00:00, 4.62s/it] Loading checkpoint shards: 100%|██████████| 3/3 [00:14<00:00, 4.70s/it] | |
| [2025-05-19 01:45:00,372] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) | |
| [93m [WARNING] [0m async_io requires the dev libaio .so object and headers but these were not found. | |
| [93m [WARNING] [0m async_io: please install the libaio-dev package with apt | |
| [93m [WARNING] [0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. | |
| [93m [WARNING] [0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH | |
| [93m [WARNING] [0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 | |
| [93m [WARNING] [0m using untested triton version (2.3.1), only 1.0.0 is known to be compatible | |
| Loading checkpoint shards: 100%|██████████| 3/3 [00:14<00:00, 4.62s/it] Loading checkpoint shards: 100%|██████████| 3/3 [00:14<00:00, 4.70s/it] | |
| [2025-05-19 01:45:01,621] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) | |
| [93m [WARNING] [0m async_io requires the dev libaio .so object and headers but these were not found. | |
| [93m [WARNING] [0m async_io: please install the libaio-dev package with apt | |
| [93m [WARNING] [0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. | |
| [93m [WARNING] [0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH | |
| [32m2025-05-19 01:45:02.002[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_dev on rank 2...[0m | |
| [93m [WARNING] [0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 | |
| [93m [WARNING] [0m using untested triton version (2.3.1), only 1.0.0 is known to be compatible | |
| [32m2025-05-19 01:45:03.150[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_dev on rank 6...[0m | |
| Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.11s/it] Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.08s/it] | |
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| Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.13s/it] Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.10s/it] | |
| Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.15s/it] Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.13s/it] | |
| Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.16s/it] Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.15s/it] | |
| [2025-05-19 01:45:03,657] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) | |
| [2025-05-19 01:45:03,662] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) | |
| [2025-05-19 01:45:03,670] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) | |
| Rank 0: Model Class: LlavaLlamaForCausalLM | |
| [2025-05-19 01:45:03,857] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) | |
| [2025-05-19 01:45:03,970] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) | |
| [93m [WARNING] [0m async_io requires the dev libaio .so object and headers but these were not found. | |
| [93m [WARNING] [0m async_io requires the dev libaio .so object and headers but these were not found. | |
| [93m [WARNING] [0m async_io requires the dev libaio .so object and headers but these were not found. | |
| [93m [WARNING] [0m async_io: please install the libaio-dev package with apt | |
| [93m [WARNING] [0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. | |
| [93m [WARNING] [0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH | |
| [93m [WARNING] [0m async_io: please install the libaio-dev package with apt | |
| [93m [WARNING] [0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. | |
| [93m [WARNING] [0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH | |
| [93m [WARNING] [0m async_io: please install the libaio-dev package with apt | |
| [93m [WARNING] [0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. | |
| [93m [WARNING] [0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH | |
| [93m [WARNING] [0m async_io requires the dev libaio .so object and headers but these were not found. | |
| [93m [WARNING] [0m async_io: please install the libaio-dev package with apt | |
| [93m [WARNING] [0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. | |
| [93m [WARNING] [0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH | |
| [93m [WARNING] [0m async_io requires the dev libaio .so object and headers but these were not found. | |
| [93m [WARNING] [0m async_io: please install the libaio-dev package with apt | |
| [93m [WARNING] [0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. | |
| [93m [WARNING] [0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH | |
| [93m [WARNING] [0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 | |
| [93m [WARNING] [0m using untested triton version (2.3.1), only 1.0.0 is known to be compatible | |
| [93m [WARNING] [0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 | |
| [93m [WARNING] [0m using untested triton version (2.3.1), only 1.0.0 is known to be compatible | |
| [93m [WARNING] [0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 | |
| [93m [WARNING] [0m using untested triton version (2.3.1), only 1.0.0 is known to be compatible | |
| [93m [WARNING] [0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 | |
| [93m [WARNING] [0m using untested triton version (2.3.1), only 1.0.0 is known to be compatible | |
| [93m [WARNING] [0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 | |
| [93m [WARNING] [0m using untested triton version (2.3.1), only 1.0.0 is known to be compatible | |
| Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.11s/it] Loading checkpoint shards: 100%|██████████| 3/3 [00:15<00:00, 5.10s/it] | |
| [2025-05-19 01:45:05,606] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) | |
| 0%| | 0/541 [00:00<?, ?it/s] 100%|██████████| 541/541 [00:00<00:00, 46768.59it/s] | |
| [93m [WARNING] [0m async_io requires the dev libaio .so object and headers but these were not found. | |
| [93m [WARNING] [0m async_io: please install the libaio-dev package with apt | |
| [93m [WARNING] [0m If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found. | |
| [93m [WARNING] [0m Please specify the CUTLASS repo directory as environment variable $CUTLASS_PATH | |
| [32m2025-05-19 01:45:06.189[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_dev on rank 4...[0m | |
| [32m2025-05-19 01:45:06.198[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_dev on rank 3...[0m | |
| [32m2025-05-19 01:45:06.199[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_dev on rank 5...[0m | |
| [32m2025-05-19 01:45:06.286[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_dev on rank 1...[0m | |
| [32m2025-05-19 01:45:06.341[0m | [1mINFO [0m | [36mlmms_eval.models.llava[0m:[36m__init__[0m:[36m134[0m - [1mUsing 8 devices with data parallelism[0m | |
| [32m2025-05-19 01:45:06.342[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_dev on rank 0...[0m | |
| [93m [WARNING] [0m sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.3 | |
| [93m [WARNING] [0m using untested triton version (2.3.1), only 1.0.0 is known to be compatible | |
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| [32m2025-05-19 01:45:07.288[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_dev on rank 7...[0m | |
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| TENCENT64:79954:80270 [1] NCCL INFO Channel 01/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 01/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 02/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 02/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 02/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 02/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 02/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 02/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 02/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 02/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 03/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 03/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 03/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 03/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 03/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 03/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 03/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 03/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 04/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 04/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 04/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 04/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 04/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 04/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 04/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 04/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 05/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 05/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 05/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 05/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 05/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 05/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 05/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 05/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 06/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 06/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 06/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 06/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 06/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 06/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 06/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 06/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 07/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 07/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 07/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 07/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 07/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 07/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 07/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 07/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 08/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 08/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 08/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 08/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 08/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 08/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 08/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 08/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 09/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 09/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 09/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 09/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 09/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 09/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 09/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 09/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 10/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 10/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 10/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 10/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 10/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 10/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 10/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 10/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 11/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 11/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 11/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 11/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 11/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 11/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 11/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 11/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 12/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 12/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 12/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 12/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 12/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 12/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 12/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 12/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 13/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 13/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 13/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 13/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 13/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 13/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 13/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 13/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 14/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 14/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 14/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 14/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 14/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 14/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 14/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 14/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 15/0 : 3[3] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 15/0 : 5[5] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 15/0 : 2[2] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 15/0 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 15/0 : 4[4] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 15/0 : 6[6] -> 7[7] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 15/0 : 1[1] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79953:80265 [0] NCCL INFO Channel 15/0 : 0[0] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Connected all rings | |
| TENCENT64:79954:80270 [1] NCCL INFO Connected all rings | |
| TENCENT64:79953:80265 [0] NCCL INFO Connected all rings | |
| TENCENT64:79956:80269 [3] NCCL INFO Connected all rings | |
| TENCENT64:79957:80271 [4] NCCL INFO Connected all rings | |
| TENCENT64:79960:80336 [7] NCCL INFO Connected all rings | |
| TENCENT64:79958:80267 [5] NCCL INFO Connected all rings | |
| TENCENT64:79959:80266 [6] NCCL INFO Connected all rings | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 00/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 01/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 02/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 03/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 04/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 05/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 06/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 07/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 00/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 08/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 01/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 09/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 02/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 10/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 03/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 11/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 04/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 12/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 05/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 00/0 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 13/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 06/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 01/0 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 00/0 : 3[3] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 14/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 07/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 02/0 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 01/0 : 3[3] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 00/0 : 4[4] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79960:80336 [7] NCCL INFO Channel 15/0 : 7[7] -> 6[6] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 08/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 00/0 : 5[5] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 00/0 : 6[6] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 03/0 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 02/0 : 3[3] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 01/0 : 4[4] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 09/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 01/0 : 5[5] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 01/0 : 6[6] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 04/0 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 03/0 : 3[3] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 02/0 : 4[4] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 10/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 02/0 : 5[5] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 02/0 : 6[6] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 05/0 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 04/0 : 3[3] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 03/0 : 4[4] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 11/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
| TENCENT64:79958:80267 [5] NCCL INFO Channel 03/0 : 5[5] -> 4[4] via P2P/CUMEM/read | |
| TENCENT64:79959:80266 [6] NCCL INFO Channel 03/0 : 6[6] -> 5[5] via P2P/CUMEM/read | |
| TENCENT64:79954:80270 [1] NCCL INFO Channel 06/0 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80269 [3] NCCL INFO Channel 05/0 : 3[3] -> 2[2] via P2P/CUMEM/read | |
| TENCENT64:79957:80271 [4] NCCL INFO Channel 04/0 : 4[4] -> 3[3] via P2P/CUMEM/read | |
| TENCENT64:79955:80268 [2] NCCL INFO Channel 12/0 : 2[2] -> 1[1] via P2P/CUMEM/read | |
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| TENCENT64:79953:80265 [0] NCCL INFO Connected all trees | |
| TENCENT64:79953:80265 [0] NCCL INFO threadThresholds 8/8/64 | 64/8/64 | 512 | 512 | |
| TENCENT64:79953:80265 [0] NCCL INFO 16 coll channels, 0 collnet channels, 0 nvls channels, 16 p2p channels, 16 p2p channels per peer | |
| TENCENT64:79954:80270 [1] NCCL INFO Connected all trees | |
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| TENCENT64:79954:80270 [1] NCCL INFO 16 coll channels, 0 collnet channels, 0 nvls channels, 16 p2p channels, 16 p2p channels per peer | |
| TENCENT64:79955:80268 [2] NCCL INFO Connected all trees | |
| TENCENT64:79955:80268 [2] NCCL INFO threadThresholds 8/8/64 | 64/8/64 | 512 | 512 | |
| TENCENT64:79955:80268 [2] NCCL INFO 16 coll channels, 0 collnet channels, 0 nvls channels, 16 p2p channels, 16 p2p channels per peer | |
| TENCENT64:79956:80269 [3] NCCL INFO Connected all trees | |
| TENCENT64:79956:80269 [3] NCCL INFO threadThresholds 8/8/64 | 64/8/64 | 512 | 512 | |
| TENCENT64:79956:80269 [3] NCCL INFO 16 coll channels, 0 collnet channels, 0 nvls channels, 16 p2p channels, 16 p2p channels per peer | |
| TENCENT64:79957:80271 [4] NCCL INFO Connected all trees | |
| TENCENT64:79957:80271 [4] NCCL INFO threadThresholds 8/8/64 | 64/8/64 | 512 | 512 | |
| TENCENT64:79957:80271 [4] NCCL INFO 16 coll channels, 0 collnet channels, 0 nvls channels, 16 p2p channels, 16 p2p channels per peer | |
| TENCENT64:79958:80267 [5] NCCL INFO Connected all trees | |
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| TENCENT64:79958:80267 [5] NCCL INFO threadThresholds 8/8/64 | 64/8/64 | 512 | 512 | |
| TENCENT64:79958:80267 [5] NCCL INFO 16 coll channels, 0 collnet channels, 0 nvls channels, 16 p2p channels, 16 p2p channels per peer | |
| TENCENT64:79959:80266 [6] NCCL INFO threadThresholds 8/8/64 | 64/8/64 | 512 | 512 | |
| TENCENT64:79960:80336 [7] NCCL INFO threadThresholds 8/8/64 | 64/8/64 | 512 | 512 | |
| TENCENT64:79959:80266 [6] NCCL INFO 16 coll channels, 0 collnet channels, 0 nvls channels, 16 p2p channels, 16 p2p channels per peer | |
| TENCENT64:79960:80336 [7] NCCL INFO 16 coll channels, 0 collnet channels, 0 nvls channels, 16 p2p channels, 16 p2p channels per peer | |
| TENCENT64:79957:80271 [4] NCCL INFO comm 0xf018850 rank 4 nranks 8 cudaDev 4 nvmlDev 4 busId 89000 commId 0x402b4d0350a71a1b - Init COMPLETE | |
| TENCENT64:79960:80336 [7] NCCL INFO comm 0xe630280 rank 7 nranks 8 cudaDev 7 nvmlDev 7 busId c9000 commId 0x402b4d0350a71a1b - Init COMPLETE | |
| TENCENT64:79958:80267 [5] NCCL INFO comm 0x11e9ea30 rank 5 nranks 8 cudaDev 5 nvmlDev 5 busId 8e000 commId 0x402b4d0350a71a1b - Init COMPLETE | |
| TENCENT64:79956:80269 [3] NCCL INFO comm 0xcd6dc30 rank 3 nranks 8 cudaDev 3 nvmlDev 3 busId 4d000 commId 0x402b4d0350a71a1b - Init COMPLETE | |
| TENCENT64:79959:80266 [6] NCCL INFO comm 0xf3037b0 rank 6 nranks 8 cudaDev 6 nvmlDev 6 busId c5000 commId 0x402b4d0350a71a1b - Init COMPLETE | |
| TENCENT64:79955:80268 [2] NCCL INFO comm 0xb2ff1f0 rank 2 nranks 8 cudaDev 2 nvmlDev 2 busId 49000 commId 0x402b4d0350a71a1b - Init COMPLETE | |
| TENCENT64:79953:80265 [0] NCCL INFO comm 0xd3ff140 rank 0 nranks 8 cudaDev 0 nvmlDev 0 busId 10000 commId 0x402b4d0350a71a1b - Init COMPLETE | |
| TENCENT64:79954:80270 [1] NCCL INFO comm 0x1d2d43f0 rank 1 nranks 8 cudaDev 1 nvmlDev 1 busId 16000 commId 0x402b4d0350a71a1b - Init COMPLETE | |
| [32m2025-05-19 01:45:13.639[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_test on rank 0...[0m | |
| [32m2025-05-19 01:45:13.640[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_test on rank 7...[0m | |
| [32m2025-05-19 01:45:13.640[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_test on rank 2...[0m | |
| [32m2025-05-19 01:45:13.640[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_test on rank 6...[0m | |
| [32m2025-05-19 01:45:13.640[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_test on rank 3...[0m | |
| [32m2025-05-19 01:45:13.640[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_test on rank 4...[0m | |
| [32m2025-05-19 01:45:13.640[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_test on rank 1...[0m | |
| [32m2025-05-19 01:45:13.640[0m | [1mINFO [0m | [36mlmms_eval.api.task[0m:[36mbuild_all_requests[0m:[36m425[0m - [1mBuilding contexts for mmbench_en_test on rank 5...[0m | |
| 0%| | 0/833 [00:00<?, ?it/s] 0%| | 0/833 [00:00<?, ?it/s] 0%| | 0/833 [00:00<?, ?it/s] 0%| | 0/833 [00:00<?, ?it/s] 0%| | 0/834 [00:00<?, ?it/s] 0%| | 0/833 [00:00<?, ?it/s] 76%|███████▌ | 634/833 [00:00<00:00, 2825.12it/s] 100%|██████████| 833/833 [00:00<00:00, 3641.91it/s] | |
| 0%| | 0/833 [00:00<?, ?it/s] 0%| | 0/834 [00:00<?, ?it/s] 76%|███████▌ | 634/833 [00:00<00:00, 2577.54it/s] 100%|██████████| 833/833 [00:00<00:00, 3328.33it/s] | |
| 76%|███████▌ | 634/833 [00:00<00:00, 2494.36it/s] 100%|██████████| 833/833 [00:00<00:00, 3223.39it/s] | |
| 76%|███████▌ | 631/833 [00:00<00:00, 2451.51it/s] 100%|██████████| 833/833 [00:00<00:00, 3181.34it/s] | |
| 76%|███████▌ | 631/833 [00:00<00:00, 2722.81it/s] 100%|██████████| 833/833 [00:00<00:00, 3527.31it/s] | |
| 76%|███████▌ | 631/834 [00:00<00:00, 2613.76it/s] 100%|██████████| 834/834 [00:00<00:00, 3394.76it/s] | |
| 76%|███████▌ | 634/833 [00:00<00:00, 2736.93it/s] 100%|██████████| 833/833 [00:00<00:00, 3532.22it/s] | |
| 76%|███████▌ | 630/834 [00:00<00:00, 2640.00it/s] 100%|██████████| 834/834 [00:00<00:00, 3433.64it/s] | |
| [32m2025-05-19 01:45:19.562[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36mevaluate[0m:[36m446[0m - [1mRunning generate_until requests[0m | |
| [32m2025-05-19 01:45:19.562[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36mevaluate[0m:[36m446[0m - [1mRunning generate_until requests[0m | |
| [32m2025-05-19 01:45:19.562[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36mevaluate[0m:[36m446[0m - [1mRunning generate_until requests[0m | |
| [32m2025-05-19 01:45:19.562[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36mevaluate[0m:[36m446[0m - [1mRunning generate_until requests[0m | |
| [32m2025-05-19 01:45:19.562[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36mevaluate[0m:[36m446[0m - [1mRunning generate_until requests[0m | |
| [32m2025-05-19 01:45:19.562[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36mevaluate[0m:[36m446[0m - [1mRunning generate_until requests[0m | |
| [32m2025-05-19 01:45:19.562[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36mevaluate[0m:[36m446[0m - [1mRunning generate_until requests[0m | |
| [32m2025-05-19 01:45:19.562[0m | [1mINFO [0m | [36mlmms_eval.evaluator[0m:[36mevaluate[0m:[36m446[0m - [1mRunning generate_until requests[0m | |
| Model Responding: 0%| | 0/1376 [00:00<?, ?it/s] Model Responding: 0%| | 1/1376 [00:01<35:46, 1.56s/it] Model Responding: 0%| | 2/1376 [00:01<17:17, 1.32it/s] Model Responding: 0%| | 3/1376 [00:01<11:36, 1.97it/s] Model Responding: 0%| | 4/1376 [00:02<08:39, 2.64it/s] Model Responding: 0%| | 5/1376 [00:02<07:59, 2.86it/s] Model Responding: 0%| | 6/1376 [00:02<07:35, 3.01it/s] Model Responding: 1%| | 7/1376 [00:03<07:19, 3.12it/s] Model Responding: 1%| | 8/1376 [00:03<06:30, 3.50it/s] Model Responding: 1%| | 9/1376 [00:03<05:47, 3.93it/s] Model Responding: 1%| | 10/1376 [00:03<05:17, 4.30it/s] Model Responding: 1%| | 11/1376 [00:03<04:56, 4.60it/s] Model Responding: 1%| | 12/1376 [00:03<04:36, 4.92it/s] Model Responding: 1%| | 13/1376 [00:04<04:23, 5.18it/s] Model Responding: 1%| | 14/1376 [00:04<04:30, 5.03it/s] Model Responding: 1%| | 15/1376 [00:04<04:23, 5.16it/s] Model Responding: 1%| | 16/1376 [00:04<04:18, 5.26it/s] Model Responding: 1%| | 17/1376 [00:04<04:15, 5.31it/s] Model Responding: 1%|▏ | 18/1376 [00:05<05:19, 4.25it/s] Model Responding: 1%|▏ | 19/1376 [00:05<04:53, 4.62it/s] Model Responding: 1%|▏ | 20/1376 [00:05<04:36, 4.91it/s] Model Responding: 2%|▏ | 21/1376 [00:05<04:22, 5.16it/s] Model Responding: 2%|▏ | 22/1376 [00:05<04:02, 5.57it/s] Model Responding: 2%|▏ | 23/1376 [00:06<03:52, 5.83it/s] Model Responding: 2%|▏ | 24/1376 [00:06<03:43, 6.04it/s] Model Responding: 2%|▏ | 25/1376 [00:06<03:38, 6.20it/s] Model Responding: 2%|▏ | 26/1376 [00:06<03:43, 6.04it/s] Model Responding: 2%|▏ | 27/1376 [00:06<03:45, 5.98it/s] Model Responding: 2%|▏ | 28/1376 [00:06<03:46, 5.95it/s] Model Responding: 2%|▏ | 29/1376 [00:07<03:46, 5.94it/s] Model Responding: 2%|▏ | 30/1376 [00:07<03:47, 5.92it/s] Model Responding: 2%|▏ | 31/1376 [00:07<03:47, 5.91it/s] Model Responding: 2%|▏ | 32/1376 [00:07<03:47, 5.91it/s] Model Responding: 2%|▏ | 33/1376 [00:07<03:47, 5.90it/s] Model Responding: 2%|▏ | 34/1376 [00:07<03:47, 5.90it/s] Model Responding: 3%|▎ | 35/1376 [00:08<03:47, 5.89it/s] Model Responding: 3%|▎ | 36/1376 [00:08<04:07, 5.42it/s] Model Responding: 3%|▎ | 37/1376 [00:08<04:21, 5.12it/s] Model Responding: 3%|▎ | 38/1376 [00:08<04:25, 5.03it/s] Model Responding: 3%|▎ | 39/1376 [00:08<04:29, 4.96it/s] Model Responding: 3%|▎ | 40/1376 [00:09<04:19, 5.15it/s] Model Responding: 3%|▎ | 41/1376 [00:09<04:12, 5.29it/s] Model Responding: 3%|▎ | 42/1376 [00:09<04:56, 4.50it/s] Model Responding: 3%|▎ | 43/1376 [00:09<04:29, 4.94it/s] Model Responding: 3%|▎ | 44/1376 [00:09<04:12, 5.28it/s] Model Responding: 3%|▎ | 45/1376 [00:10<03:58, 5.59it/s] Model Responding: 3%|▎ | 46/1376 [00:10<04:09, 5.33it/s] Model Responding: 3%|▎ | 47/1376 [00:10<04:04, 5.42it/s] Model Responding: 3%|▎ | 48/1376 [00:10<04:16, 5.19it/s] Model Responding: 4%|▎ | 49/1376 [00:10<04:23, 5.03it/s] Model Responding: 4%|▎ | 50/1376 [00:11<04:29, 4.93it/s] Model Responding: 4%|▎ | 51/1376 [00:11<04:15, 5.19it/s] Model Responding: 4%|▍ | 52/1376 [00:11<04:05, 5.40it/s] Model Responding: 4%|▍ | 53/1376 [00:11<04:12, 5.23it/s] Model Responding: 4%|▍ | 54/1376 [00:11<04:07, 5.34it/s] Model Responding: 4%|▍ | 55/1376 [00:11<04:02, 5.44it/s] Model Responding: 4%|▍ | 56/1376 [00:12<03:59, 5.51it/s] Model Responding: 4%|▍ | 57/1376 [00:12<03:57, 5.55it/s] Model Responding: 4%|▍ | 58/1376 [00:12<03:52, 5.67it/s] Model Responding: 4%|▍ | 59/1376 [00:12<03:57, 5.56it/s] Model Responding: 4%|▍ | 60/1376 [00:12<04:06, 5.34it/s] Model Responding: 4%|▍ | 61/1376 [00:13<04:01, 5.44it/s] Model Responding: 5%|▍ | 62/1376 [00:13<04:09, 5.27it/s] Model Responding: 5%|▍ | 63/1376 [00:13<04:01, 5.43it/s] Model Responding: 5%|▍ | 64/1376 [00:13<04:35, 4.75it/s] Model Responding: 5%|▍ | 65/1376 [00:13<04:59, 4.38it/s] Model Responding: 5%|▍ | 66/1376 [00:14<05:15, 4.15it/s] Model Responding: 5%|▍ | 67/1376 [00:14<04:49, 4.53it/s] Model Responding: 5%|▍ | 68/1376 [00:14<04:29, 4.86it/s] Model Responding: 5%|▌ | 69/1376 [00:14<04:15, 5.12it/s] Model Responding: 5%|▌ | 70/1376 [00:14<04:22, 4.98it/s] Model Responding: 5%|▌ | 71/1376 [00:15<04:03, 5.35it/s] Model Responding: 5%|▌ | 72/1376 [00:15<03:56, 5.51it/s] Model Responding: 5%|▌ | 73/1376 [00:15<03:58, 5.47it/s] Model Responding: 5%|▌ | 74/1376 [00:15<03:58, 5.45it/s] Model Responding: 5%|▌ | 75/1376 [00:15<03:59, 5.43it/s] Model Responding: 6%|▌ | 76/1376 [00:16<03:47, 5.71it/s] Model Responding: 6%|▌ | 77/1376 [00:16<03:45, 5.77it/s] Model Responding: 6%|▌ | 78/1376 [00:16<03:43, 5.80it/s] Model Responding: 6%|▌ | 79/1376 [00:16<03:42, 5.83it/s] Model Responding: 6%|▌ | 80/1376 [00:16<03:32, 6.09it/s] Model Responding: 6%|▌ | 81/1376 [00:16<03:28, 6.22it/s] Model Responding: 6%|▌ | 82/1376 [00:16<03:25, 6.30it/s] Model Responding: 6%|▌ | 83/1376 [00:17<03:37, 5.94it/s] Model Responding: 6%|▌ | 84/1376 [00:17<03:51, 5.59it/s] Model Responding: 6%|▌ | 85/1376 [00:17<04:03, 5.29it/s] Model Responding: 6%|▋ | 86/1376 [00:17<04:04, 5.29it/s] Model Responding: 6%|▋ | 87/1376 [00:17<03:50, 5.59it/s] Model Responding: 6%|▋ | 88/1376 [00:18<03:46, 5.70it/s] Model Responding: 6%|▋ | 89/1376 [00:18<03:42, 5.78it/s] Model Responding: 7%|▋ | 90/1376 [00:18<03:29, 6.14it/s] Model Responding: 7%|▋ | 91/1376 [00:18<03:45, 5.69it/s] Model Responding: 7%|▋ | 92/1376 [00:18<04:43, 4.53it/s] Model Responding: 7%|▋ | 93/1376 [00:19<04:23, 4.87it/s] Model Responding: 7%|▋ | 94/1376 [00:19<04:12, 5.08it/s] Model Responding: 7%|▋ | 95/1376 [00:19<04:01, 5.31it/s] Model Responding: 7%|▋ | 96/1376 [00:19<03:53, 5.49it/s] Model Responding: 7%|▋ | 97/1376 [00:19<04:33, 4.68it/s] Model Responding: 7%|▋ | 98/1376 [00:20<05:18, 4.02it/s] Model Responding: 7%|▋ | 99/1376 [00:20<05:00, 4.25it/s] Model Responding: 7%|▋ | 100/1376 [00:20<04:49, 4.41it/s] Model Responding: 7%|▋ | 101/1376 [00:20<04:39, 4.56it/s] Model Responding: 7%|▋ | 102/1376 [00:21<04:37, 4.59it/s] Model Responding: 7%|▋ | 103/1376 [00:21<05:05, 4.17it/s] Model Responding: 8%|▊ | 104/1376 [00:21<05:13, 4.05it/s] Model Responding: 8%|▊ | 105/1376 [00:21<05:22, 3.95it/s] Model Responding: 8%|▊ | 106/1376 [00:22<05:25, 3.91it/s] Model Responding: 8%|▊ | 107/1376 [00:22<05:11, 4.07it/s] Model Responding: 8%|▊ | 108/1376 [00:22<05:02, 4.19it/s] Model Responding: 8%|▊ | 109/1376 [00:22<04:57, 4.26it/s] Model Responding: 8%|▊ | 110/1376 [00:22<04:33, 4.63it/s] Model Responding: 8%|▊ | 111/1376 [00:23<04:33, 4.63it/s] Model Responding: 8%|▊ | 112/1376 [00:23<04:35, 4.60it/s] Model Responding: 8%|▊ | 113/1376 [00:23<04:55, 4.28it/s] Model Responding: 8%|▊ | 114/1376 [00:23<04:47, 4.39it/s] Model Responding: 8%|▊ | 115/1376 [00:24<04:32, 4.62it/s] Model Responding: 8%|▊ | 116/1376 [00:24<04:20, 4.83it/s] Model Responding: 9%|▊ | 117/1376 [00:24<04:12, 4.98it/s] Model Responding: 9%|▊ | 118/1376 [00:24<04:38, 4.52it/s] Model Responding: 9%|▊ | 119/1376 [00:25<05:16, 3.97it/s] Model Responding: 9%|▊ | 120/1376 [00:25<05:31, 3.79it/s] Model Responding: 9%|▉ | 121/1376 [00:25<05:45, 3.64it/s] Model Responding: 9%|▉ | 122/1376 [00:25<05:19, 3.92it/s] Model Responding: 9%|▉ | 123/1376 [00:26<05:34, 3.75it/s] Model Responding: 9%|▉ | 124/1376 [00:26<04:52, 4.28it/s] Model Responding: 9%|▉ | 125/1376 [00:26<05:22, 3.88it/s] Model Responding: 9%|▉ | 126/1376 [00:26<05:37, 3.70it/s] Model Responding: 9%|▉ | 127/1376 [00:27<05:02, 4.13it/s] Model Responding: 9%|▉ | 128/1376 [00:27<05:29, 3.79it/s] Model Responding: 9%|▉ | 129/1376 [00:27<05:38, 3.68it/s] Model Responding: 9%|▉ | 130/1376 [00:27<05:01, 4.14it/s] Model Responding: 10%|▉ | 131/1376 [00:28<04:29, 4.62it/s] Model Responding: 10%|▉ | 132/1376 [00:28<04:12, 4.93it/s] Model Responding: 10%|▉ | 133/1376 [00:28<03:59, 5.19it/s] Model Responding: 10%|▉ | 134/1376 [00:28<03:58, 5.21it/s] Model Responding: 10%|▉ | 135/1376 [00:28<03:44, 5.53it/s] Model Responding: 10%|▉ | 136/1376 [00:28<03:34, 5.78it/s] Model Responding: 10%|▉ | 137/1376 [00:29<03:27, 5.98it/s] Model Responding: 10%|█ | 138/1376 [00:29<03:35, 5.75it/s] Model Responding: 10%|█ | 139/1376 [00:29<04:08, 4.98it/s] Model Responding: 10%|█ | 140/1376 [00:29<03:51, 5.34it/s] Model Responding: 10%|█ | 141/1376 [00:29<03:52, 5.31it/s] Model Responding: 10%|█ | 142/1376 [00:29<03:46, 5.45it/s] Model Responding: 10%|█ | 143/1376 [00:30<03:46, 5.45it/s] Model Responding: 10%|█ | 144/1376 [00:30<04:38, 4.42it/s] Model Responding: 11%|█ | 145/1376 [00:30<05:05, 4.03it/s] Model Responding: 11%|█ | 146/1376 [00:31<05:16, 3.89it/s] Model Responding: 11%|█ | 147/1376 [00:31<05:22, 3.82it/s] Model Responding: 11%|█ | 148/1376 [00:31<05:28, 3.74it/s] Model Responding: 11%|█ | 149/1376 [00:31<05:06, 4.00it/s] Model Responding: 11%|█ | 150/1376 [00:32<04:42, 4.34it/s] Model Responding: 11%|█ | 151/1376 [00:32<04:10, 4.88it/s] Model Responding: 11%|█ | 152/1376 [00:32<04:32, 4.50it/s] Model Responding: 11%|█ | 153/1376 [00:32<04:57, 4.12it/s] Model Responding: 11%|█ | 154/1376 [00:33<05:07, 3.98it/s] Model Responding: 11%|█▏ | 155/1376 [00:33<05:14, 3.88it/s] Model Responding: 11%|█▏ | 156/1376 [00:33<05:21, 3.80it/s] Model Responding: 11%|█▏ | 157/1376 [00:33<05:25, 3.74it/s] Model Responding: 11%|█▏ | 158/1376 [00:34<05:27, 3.72it/s] Model Responding: 12%|█▏ | 159/1376 [00:34<05:26, 3.73it/s] Model Responding: 12%|█▏ | 160/1376 [00:34<05:23, 3.75it/s] Model Responding: 12%|█▏ | 161/1376 [00:34<05:22, 3.77it/s] Model Responding: 12%|█▏ | 162/1376 [00:35<04:39, 4.35it/s] Model Responding: 12%|█▏ | 163/1376 [00:35<04:08, 4.89it/s] Model Responding: 12%|█▏ | 164/1376 [00:35<03:45, 5.36it/s] Model Responding: 12%|█▏ | 165/1376 [00:35<03:53, 5.18it/s] Model Responding: 12%|█▏ | 166/1376 [00:35<04:22, 4.61it/s] Model Responding: 12%|█▏ | 167/1376 [00:36<04:41, 4.29it/s] Model Responding: 12%|█▏ | 168/1376 [00:36<04:13, 4.76it/s] Model Responding: 12%|█▏ | 169/1376 [00:36<03:59, 5.03it/s] Model Responding: 12%|█▏ | 170/1376 [00:36<03:48, 5.27it/s] Model Responding: 12%|█▏ | 171/1376 [00:36<03:42, 5.42it/s] Model Responding: 12%|█▎ | 172/1376 [00:37<04:13, 4.75it/s] Model Responding: 13%|█▎ | 173/1376 [00:37<04:33, 4.39it/s] Model Responding: 13%|█▎ | 174/1376 [00:37<04:26, 4.52it/s] Model Responding: 13%|█▎ | 175/1376 [00:37<04:19, 4.62it/s] Model Responding: 13%|█▎ | 176/1376 [00:37<04:15, 4.69it/s] Model Responding: 13%|█▎ | 177/1376 [00:38<04:13, 4.74it/s] Model Responding: 13%|█▎ | 178/1376 [00:38<04:10, 4.78it/s] Model Responding: 13%|█▎ | 179/1376 [00:38<04:29, 4.45it/s] Model Responding: 13%|█▎ | 180/1376 [00:38<04:42, 4.23it/s] Model Responding: 13%|█▎ | 181/1376 [00:39<04:52, 4.09it/s] Model Responding: 13%|█▎ | 182/1376 [00:39<05:03, 3.94it/s] Model Responding: 13%|█▎ | 183/1376 [00:39<05:04, 3.92it/s] Model Responding: 13%|█▎ | 184/1376 [00:39<04:46, 4.16it/s] Model Responding: 13%|█▎ | 185/1376 [00:40<04:27, 4.46it/s] Model Responding: 14%|█▎ | 186/1376 [00:40<04:21, 4.55it/s] Model Responding: 14%|█▎ | 187/1376 [00:40<04:17, 4.62it/s] Model Responding: 14%|█▎ | 188/1376 [00:40<04:14, 4.67it/s] Model Responding: 14%|█▎ | 189/1376 [00:40<04:03, 4.87it/s] Model Responding: 14%|█▍ | 190/1376 [00:41<04:38, 4.26it/s] Model Responding: 14%|█▍ | 191/1376 [00:41<05:01, 3.92it/s] Model Responding: 14%|█▍ | 192/1376 [00:41<05:18, 3.72it/s] Model Responding: 14%|█▍ | 193/1376 [00:42<05:15, 3.75it/s] Model Responding: 14%|█▍ | 194/1376 [00:42<05:20, 3.69it/s] Model Responding: 14%|█▍ | 195/1376 [00:42<04:38, 4.24it/s] Model Responding: 14%|█▍ | 196/1376 [00:42<04:27, 4.41it/s] Model Responding: 14%|█▍ | 197/1376 [00:42<04:42, 4.17it/s] Model Responding: 14%|█▍ | 198/1376 [00:43<04:50, 4.06it/s] Model Responding: 14%|█▍ | 199/1376 [00:43<04:13, 4.65it/s] Model Responding: 15%|█▍ | 200/1376 [00:43<04:05, 4.78it/s] Model Responding: 15%|█▍ | 201/1376 [00:43<04:28, 4.37it/s] Model Responding: 15%|█▍ | 202/1376 [00:44<04:21, 4.48it/s] Model Responding: 15%|█▍ | 203/1376 [00:44<04:35, 4.26it/s] Model Responding: 15%|█▍ | 204/1376 [00:44<05:06, 3.82it/s] Model Responding: 15%|█▍ | 205/1376 [00:44<05:29, 3.55it/s] Model Responding: 15%|█▍ | 206/1376 [00:45<05:46, 3.37it/s] Model Responding: 15%|█▌ | 207/1376 [00:45<05:37, 3.46it/s] Model Responding: 15%|█▌ | 208/1376 [00:45<05:32, 3.51it/s] Model Responding: 15%|█▌ | 209/1376 [00:46<05:27, 3.56it/s] Model Responding: 15%|█▌ | 210/1376 [00:46<05:23, 3.60it/s] Model Responding: 15%|█▌ | 211/1376 [00:46<05:16, 3.68it/s] Model Responding: 15%|█▌ | 212/1376 [00:46<04:31, 4.29it/s] Model Responding: 15%|█▌ | 213/1376 [00:46<04:09, 4.66it/s] Model Responding: 16%|█▌ | 214/1376 [00:47<04:26, 4.36it/s] Model Responding: 16%|█▌ | 215/1376 [00:47<04:36, 4.19it/s] Model Responding: 16%|█▌ | 216/1376 [00:47<04:45, 4.07it/s] Model Responding: 16%|█▌ | 217/1376 [00:48<05:14, 3.69it/s] Model Responding: 16%|█▌ | 218/1376 [00:48<05:11, 3.72it/s] Model Responding: 16%|█▌ | 219/1376 [00:48<05:34, 3.46it/s] Model Responding: 16%|█▌ | 220/1376 [00:48<05:48, 3.32it/s] Model Responding: 16%|█▌ | 221/1376 [00:49<05:59, 3.21it/s] Model Responding: 16%|█▌ | 222/1376 [00:49<05:42, 3.37it/s] Model Responding: 16%|█▌ | 223/1376 [00:49<05:35, 3.44it/s] Model Responding: 16%|█▋ | 224/1376 [00:50<05:28, 3.50it/s] Model Responding: 16%|█▋ | 225/1376 [00:50<05:23, 3.56it/s] Model Responding: 16%|█▋ | 226/1376 [00:50<05:20, 3.59it/s] Model Responding: 16%|█▋ | 227/1376 [00:50<05:15, 3.64it/s] Model Responding: 17%|█▋ | 228/1376 [00:51<05:32, 3.45it/s] Model Responding: 17%|█▋ | 229/1376 [00:51<04:59, 3.83it/s] Model Responding: 17%|█▋ | 230/1376 [00:51<05:04, 3.76it/s] Model Responding: 17%|█▋ | 231/1376 [00:51<05:06, 3.74it/s] Model Responding: 17%|█▋ | 232/1376 [00:52<05:18, 3.59it/s] Model Responding: 17%|█▋ | 233/1376 [00:52<05:16, 3.61it/s] Model Responding: 17%|█▋ | 234/1376 [00:52<04:53, 3.89it/s] Model Responding: 17%|█▋ | 235/1376 [00:53<05:06, 3.72it/s] Model Responding: 17%|█▋ | 236/1376 [00:53<05:14, 3.63it/s] Model Responding: 17%|█▋ | 237/1376 [00:53<05:21, 3.54it/s] Model Responding: 17%|█▋ | 238/1376 [00:53<05:14, 3.62it/s] Model Responding: 17%|█▋ | 239/1376 [00:54<05:14, 3.62it/s] Model Responding: 17%|█▋ | 240/1376 [00:54<05:12, 3.64it/s] Model Responding: 18%|█▊ | 241/1376 [00:54<05:11, 3.65it/s] Model Responding: 18%|█▊ | 242/1376 [00:55<05:11, 3.64it/s] Model Responding: 18%|█▊ | 243/1376 [00:55<04:44, 3.98it/s] Model Responding: 18%|█▊ | 244/1376 [00:55<04:53, 3.86it/s] Model Responding: 18%|█▊ | 245/1376 [00:55<04:57, 3.80it/s] Model Responding: 18%|█▊ | 246/1376 [00:56<04:56, 3.81it/s] Model Responding: 18%|█▊ | 247/1376 [00:56<04:20, 4.33it/s] Model Responding: 18%|█▊ | 248/1376 [00:56<03:58, 4.72it/s] Model Responding: 18%|█▊ | 249/1376 [00:56<04:19, 4.35it/s] Model Responding: 18%|█▊ | 250/1376 [00:56<04:29, 4.18it/s] Model Responding: 18%|█▊ | 251/1376 [00:57<04:41, 3.99it/s] Model Responding: 18%|█▊ | 252/1376 [00:57<04:48, 3.90it/s] Model Responding: 18%|█▊ | 253/1376 [00:57<04:53, 3.82it/s] Model Responding: 18%|█▊ | 254/1376 [00:57<04:57, 3.77it/s] Model Responding: 19%|█▊ | 255/1376 [00:58<04:25, 4.22it/s] Model Responding: 19%|█▊ | 256/1376 [00:58<04:02, 4.62it/s] Model Responding: 19%|█▊ | 257/1376 [00:58<04:16, 4.36it/s] Model Responding: 19%|█▉ | 258/1376 [00:58<04:30, 4.13it/s] Model Responding: 19%|█▉ | 259/1376 [00:59<04:13, 4.41it/s] Model Responding: 19%|█▉ | 260/1376 [00:59<04:30, 4.13it/s] Model Responding: 19%|█▉ | 261/1376 [00:59<04:37, 4.02it/s] Model Responding: 19%|█▉ | 262/1376 [00:59<04:11, 4.44it/s] Model Responding: 19%|█▉ | 263/1376 [00:59<03:48, 4.87it/s] Model Responding: 19%|█▉ | 264/1376 [01:00<03:36, 5.14it/s] Model Responding: 19%|█▉ | 265/1376 [01:00<03:27, 5.35it/s] Model Responding: 19%|█▉ | 266/1376 [01:00<03:52, 4.78it/s] Model Responding: 19%|█▉ | 267/1376 [01:00<04:09, 4.45it/s] Model Responding: 19%|█▉ | 268/1376 [01:01<04:22, 4.22it/s] Model Responding: 20%|█▉ | 269/1376 [01:01<04:29, 4.11it/s] Model Responding: 20%|█▉ | 270/1376 [01:01<04:57, 3.72it/s] Model Responding: 20%|█▉ | 271/1376 [01:01<05:14, 3.51it/s] Model 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| TENCENT64:79959:80373 [6] NCCL INFO Channel 00/1 : 6[6] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80374 [3] NCCL INFO Channel 00/1 : 3[3] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79958:80375 [5] NCCL INFO Channel 00/1 : 5[5] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80377 [4] NCCL INFO Channel 00/1 : 4[4] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79955:80376 [2] NCCL INFO Channel 00/1 : 2[2] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79960:80378 [7] NCCL INFO Channel 00/1 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79954:80380 [1] NCCL INFO Channel 00/1 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79959:80373 [6] NCCL INFO Channel 01/1 : 6[6] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80374 [3] NCCL INFO Channel 01/1 : 3[3] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79958:80375 [5] NCCL INFO Channel 01/1 : 5[5] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80377 [4] NCCL INFO Channel 01/1 : 4[4] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79955:80376 [2] NCCL INFO Channel 01/1 : 2[2] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79960:80378 [7] NCCL INFO Channel 01/1 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79954:80380 [1] NCCL INFO Channel 01/1 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79959:80373 [6] NCCL INFO Channel 02/1 : 6[6] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80374 [3] NCCL INFO Channel 02/1 : 3[3] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79958:80375 [5] NCCL INFO Channel 02/1 : 5[5] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80377 [4] NCCL INFO Channel 02/1 : 4[4] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79955:80376 [2] NCCL INFO Channel 02/1 : 2[2] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79960:80378 [7] NCCL INFO Channel 02/1 : 7[7] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79954:80380 [1] NCCL INFO Channel 02/1 : 1[1] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79959:80373 [6] NCCL INFO Channel 03/1 : 6[6] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79956:80374 [3] NCCL INFO Channel 03/1 : 3[3] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79958:80375 [5] NCCL INFO Channel 03/1 : 5[5] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79957:80377 [4] NCCL INFO Channel 03/1 : 4[4] -> 0[0] via P2P/CUMEM/read | |
| TENCENT64:79955:80376 [2] NCCL INFO Channel 03/1 : 2[2] -> 0[0] via P2P/CUMEM/read | |
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| ============= MMBench-EN(Dev) Detailed Results ============= | |
| Category Acc. (dev): | |
| action_recognition: 88.889 | |
| attribute_comparison: 63.636 | |
| attribute_recognition: 89.189 | |
| celebrity_recognition: 80.808 | |
| function_reasoning: 73.418 | |
| future_prediction: 42.500 | |
| identity_reasoning: 97.778 | |
| image_emotion: 80.000 | |
| image_quality: 52.830 | |
| image_scene: 96.154 | |
| image_style: 86.792 | |
| image_topic: 77.778 | |
| nature_relation: 56.250 | |
| object_localization: 46.914 | |
| ocr: 66.667 | |
| physical_property_reasoning: 49.333 | |
| physical_relation: 41.667 | |
| social_relation: 93.023 | |
| spatial_relationship: 20.000 | |
| structuralized_imagetext_understanding: 30.769 | |
| L2-category Acc. (dev): | |
| attribute_reasoning: 69.849 | |
| coarse_perception: 81.757 | |
| finegrained_perception (cross-instance): 59.441 | |
| finegrained_perception (instance-level): 71.672 | |
| logic_reasoning: 34.746 | |
| relation_reasoning: 66.957 | |
| [32m2025-05-19 01:50:54.491[0m | [1mINFO [0m | [36men_utils[0m:[36mmmbench_aggregate_dev_results_submission[0m:[36m121[0m - [1mSaved results to /jizhicfs/bojoli/mmpe/mmpe-main/eval/logs/submissions/mmbench_en_dev_results.xlsx[0m | |
| [32m2025-05-19 01:50:55.933[0m | [1mINFO [0m | [36men_utils[0m:[36mmmbench_aggregate_test_results[0m:[36m129[0m - [1mSaved results to /jizhicfs/bojoli/mmpe/mmpe-main/eval/logs/submissions/mmbench_en_test_results.xlsx[0m | |
| fatal: not a git repository (or any parent up to mount point /) | |
| Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set). | |
| [32m2025-05-19 01:50:56.096[0m | [1mINFO [0m | [36mlmms_eval.loggers.evaluation_tracker[0m:[36msave_results_aggregated[0m:[36m188[0m - [1mSaving results aggregated[0m | |
| [32m2025-05-19 01:50:56.105[0m | [1mINFO [0m | [36mlmms_eval.loggers.evaluation_tracker[0m:[36msave_results_samples[0m:[36m255[0m - [1mSaving per-sample results for: mmbench_en_dev[0m | |
| [32m2025-05-19 01:50:57.564[0m | [1mINFO [0m | [36mlmms_eval.loggers.evaluation_tracker[0m:[36msave_results_samples[0m:[36m255[0m - [1mSaving per-sample results for: mmbench_en_test[0m | |
| llava (pretrained=../checkpoints/final_mmpe_finetune_vicuna-7b-1.5_clip-vit-large-patch14-336,conv_template=v1), gen_kwargs: (), limit: None, num_fewshot: None, batch_size: 1 | |
| | Tasks |Version|Filter|n-shot| Metric | | Value | |Stderr| | |
| |------------------|-------|------|-----:|--------------|---|-------|---|------| | |
| |mmbench_en | N/A| | | | | | | | | |
| | - mmbench_en_dev |Yaml |none | 0|gpt_eval_score|↑ |68.2131|± | N/A| | |
| | - mmbench_en_dev |Yaml |none | 0|submission |↑ |N/A |± | N/A| | |
| | - mmbench_en_test|Yaml |none | 0|submission |↑ |N/A |± | N/A| | |