======================== START TIME: Tue Jul 2 19:54:39 UTC 2024 python3 version = Python 3.10.14 ======================== The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well. Token is valid (permission: write). Your token has been saved to /admin/home/ferdinand_mom/.cache/huggingface/token Login successful Already on 'bench_cluster' M examples/config_tiny_llama.py M examples/config_tiny_llama.yaml M examples/train_tiny_llama.sh M src/nanotron/models/llama.py M src/nanotron/trainer.py Your branch is up to date with 'origin/bench_cluster'. Job status: RUNNING W0702 19:54:41.839000 140483223861056 torch/distributed/run.py:757] W0702 19:54:41.839000 140483223861056 torch/distributed/run.py:757] ***************************************** W0702 19:54:41.839000 140483223861056 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. W0702 19:54:41.839000 140483223861056 torch/distributed/run.py:757] ***************************************** W0702 19:54:41.839000 139863964038976 torch/distributed/run.py:757] W0702 19:54:41.839000 139863964038976 torch/distributed/run.py:757] ***************************************** W0702 19:54:41.839000 139863964038976 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. W0702 19:54:41.839000 139863964038976 torch/distributed/run.py:757] ***************************************** [default0]:07/02/2024 19:55:00 [WARNING|DP=0|PP=0|TP=0|ip-26-0-171-62]: [Vocab Size Padding] Padded vocab (size: 50257) with 3 dummy tokens (new size: 50260) [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Config: [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Config(general=GeneralArgs(project='bench_cluster', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: run='%date_%jobid', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: seed=42, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: step=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: consumed_train_samples=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: benchmark_csv_path=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: ignore_sanity_checks=True), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: parallelism=ParallelismArgs(dp=1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: pp=4, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: tp=4, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: pp_engine=, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: tp_mode=, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: tp_linear_async_communication=False, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: expert_parallel_size=1), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: eos_token_id=2, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: hidden_act='silu', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: hidden_size=2048, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: initializer_range=0.02, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: intermediate_size=4096, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: is_llama_config=True, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: max_position_embeddings=4096, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: num_attention_heads=32, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: num_hidden_layers=24, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: num_key_value_heads=32, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: pad_token_id=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: pretraining_tp=1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: rms_norm_eps=1e-05, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: rope_scaling=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: rope_theta=10000.0, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: tie_word_embeddings=True, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: use_cache=True, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: vocab_size=50260), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: init_method=RandomInit(std=0.025), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: dtype=torch.bfloat16, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: make_vocab_size_divisible_by=1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: ddp_bucket_cap_mb=25), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: tokenizer_revision=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: tokenizer_max_length=None), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: checkpoint_interval=100000, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: save_initial_state=False, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: resume_checkpoint_path=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: checkpoints_path_is_shared_file_system=False), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: logging=LoggingArgs(log_level='info', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: log_level_replica='info', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: iteration_step_info_interval=1), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: tokens=TokensArgs(sequence_length=4096, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: train_steps=20, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: micro_batch_size=2, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: batch_accumulation_per_replica=512, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: val_check_interval=-1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: limit_val_batches=0, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: limit_test_batches=0), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: adam_beta1=0.9, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: adam_beta2=0.95, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: torch_adam_is_fused=True, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: name='adamW'), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: zero_stage=1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: weight_decay=0.01, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: clip_grad=1.0, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: accumulate_grad_in_fp32=True, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: lr_warmup_steps=1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: lr_warmup_style='linear', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: lr_decay_style='linear', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: lr_decay_steps=19, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: lr_decay_starting_step=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: min_decay_lr=1e-05)), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: data_stages=[DatasetStageArgs(name='Training Stage', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: start_training_step=1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: hf_dataset_splits='train', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: hf_dataset_config_name=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: dataset_processing_num_proc_per_process=64, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: dataset_overwrite_cache=False, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: text_column_name='text'), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: seed=42, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: num_loading_workers=32))], [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-4_pp-4_mbz-2')), [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: lighteval=None) [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Model Config: [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: LlamaConfig(bos_token_id=1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: eos_token_id=2, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: hidden_act='silu', [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: hidden_size=2048, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: initializer_range=0.02, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: intermediate_size=4096, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: is_llama_config=True, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: max_position_embeddings=4096, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: num_attention_heads=32, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: num_hidden_layers=24, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: num_key_value_heads=32, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: pad_token_id=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: pretraining_tp=1, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: rms_norm_eps=1e-05, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: rope_scaling=None, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: rope_theta=10000.0, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: tie_word_embeddings=True, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: use_cache=True, [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: vocab_size=50260) [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Building model.. [default0]:07/02/2024 19:55:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Setting PP block ranks... [default0]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=0|ip-26-0-171-88]: Local number of parameters: 62.9M (120.05MiB) [default0]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=0|ip-26-0-171-88]: [After model building] Memory usage: 126.06MiB. Peak allocated: 128.09MiB Peak reserved: 130.00MiB [default0]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=0|ip-26-0-171-88]: No checkpoint path provided. [default4]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-88]: Local number of parameters: 67.7M (129.12MiB) [default4]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-88]: [After model building] Memory usage: 134.05MiB. Peak allocated: 136.08MiB Peak reserved: 138.00MiB [default4]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-88]: No checkpoint path provided. [default6]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=2|ip-26-0-171-88]: Local number of parameters: 67.7M (129.12MiB) [default6]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=2|ip-26-0-171-88]: [After model building] Memory usage: 134.05MiB. Peak allocated: 136.08MiB Peak reserved: 138.00MiB [default6]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=2|ip-26-0-171-88]: No checkpoint path provided. [default7]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=3|ip-26-0-171-88]: Local number of parameters: 67.7M (129.12MiB) [default7]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=3|ip-26-0-171-88]: [After model building] Memory usage: 134.05MiB. Peak allocated: 136.08MiB Peak reserved: 138.00MiB [default7]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=3|ip-26-0-171-88]: No checkpoint path provided. [default3]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=3|ip-26-0-171-88]: Local number of parameters: 62.9M (120.05MiB) [default3]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=3|ip-26-0-171-88]: [After model building] Memory usage: 126.06MiB. Peak allocated: 128.09MiB Peak reserved: 130.00MiB [default3]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=3|ip-26-0-171-88]: No checkpoint path provided. [default1]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-62]: Local number of parameters: 99.2M (189.14MiB) [default1]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-62]: [After model building] Memory usage: 197.07MiB. Peak allocated: 199.10MiB Peak reserved: 200.00MiB [default1]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-62]: No checkpoint path provided. [default2]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=2|ip-26-0-171-88]: Local number of parameters: 62.9M (120.05MiB) [default2]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=2|ip-26-0-171-88]: [After model building] Memory usage: 126.06MiB. Peak allocated: 128.09MiB Peak reserved: 130.00MiB [default2]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=2|ip-26-0-171-88]: No checkpoint path provided. [default1]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=1|ip-26-0-171-88]: Local number of parameters: 62.9M (120.05MiB) [default1]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=1|ip-26-0-171-88]: [After model building] Memory usage: 126.06MiB. Peak allocated: 128.09MiB Peak reserved: 130.00MiB [default1]:07/02/2024 19:55:15 [INFO|DP=0|PP=2|TP=1|ip-26-0-171-88]: No checkpoint path provided. [default5]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=1|ip-26-0-171-88]: Local number of parameters: 67.7M (129.12MiB) [default5]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=1|ip-26-0-171-88]: [After model building] Memory usage: 134.05MiB. Peak allocated: 136.08MiB Peak reserved: 138.00MiB [default5]:07/02/2024 19:55:15 [INFO|DP=0|PP=3|TP=1|ip-26-0-171-88]: No checkpoint path provided. [default4]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=0|ip-26-0-171-62]: Local number of parameters: 73.4M (140.05MiB) [default4]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=0|ip-26-0-171-62]: [After model building] Memory usage: 147.07MiB. Peak allocated: 149.10MiB Peak reserved: 150.00MiB [default4]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=0|ip-26-0-171-62]: No checkpoint path provided. [default2]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=2|ip-26-0-171-62]: Local number of parameters: 99.2M (189.14MiB) [default2]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=2|ip-26-0-171-62]: [After model building] Memory usage: 197.07MiB. Peak allocated: 199.10MiB Peak reserved: 200.00MiB [default2]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=2|ip-26-0-171-62]: No checkpoint path provided. [default6]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=2|ip-26-0-171-62]: Local number of parameters: 73.4M (140.05MiB) [default6]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=2|ip-26-0-171-62]: [After model building] Memory usage: 147.07MiB. Peak allocated: 149.10MiB Peak reserved: 150.00MiB [default3]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=3|ip-26-0-171-62]: Local number of parameters: 99.2M (189.14MiB) [default3]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=3|ip-26-0-171-62]: [After model building] Memory usage: 197.07MiB. Peak allocated: 199.10MiB Peak reserved: 200.00MiB [default3]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=3|ip-26-0-171-62]: No checkpoint path provided. [default7]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=3|ip-26-0-171-62]: Local number of parameters: 73.4M (140.05MiB) [default7]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=3|ip-26-0-171-62]: [After model building] Memory usage: 147.07MiB. Peak allocated: 149.10MiB Peak reserved: 150.00MiB [default6]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=2|ip-26-0-171-62]: No checkpoint path provided. [default7]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=3|ip-26-0-171-62]: No checkpoint path provided. [default5]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=1|ip-26-0-171-62]: Local number of parameters: 73.4M (140.05MiB) [default5]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=1|ip-26-0-171-62]: [After model building] Memory usage: 147.07MiB. Peak allocated: 149.10MiB Peak reserved: 150.00MiB [default0]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Total number of parameters: 1.21G (2313.42MiB) [default0]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Local number of parameters: 99.2M (189.14MiB) [default0]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: [After model building] Memory usage: 197.07MiB. Peak allocated: 199.10MiB Peak reserved: 200.00MiB [default0]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: No checkpoint path provided. [default0]:07/02/2024 19:55:15 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Parametrizing model parameters using StandardParametrizator [default5]:07/02/2024 19:55:15 [INFO|DP=0|PP=1|TP=1|ip-26-0-171-62]: No checkpoint path provided. [default0]:07/02/2024 19:55:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: [Optimizer Building] Using LearningRateForSP as learning rate [default0]:07/02/2024 19:55:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: [ZeRO sharding] Size of optimizer params per rank: [default0]:07/02/2024 19:55:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: [ZeRO sharding] DP Rank 0 has 99.2M out of 99.2M (100.00%) params' optimizer states [default0]:07/02/2024 19:55:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples [default0]:07/02/2024 19:55:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Using `datasets` library [default0]:07/02/2024 19:55:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4') [default0]:07/02/2024 19:55:17 [WARNING|DP=0|PP=0|TP=0|ip-26-0-171-62]: Repo card metadata block was not found. Setting CardData to empty. [default0]:Repo card metadata block was not found. Setting CardData to empty. [default0]:07/02/2024 19:55:18 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: [Training Plan] There are 1 training stages [default0]:07/02/2024 19:55:18 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: [Stage Training Stage] start from step 1 [default0]:07/02/2024 19:55:18 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: [default0]:07/02/2024 19:55:18 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: [Start training] datetime: 2024-07-02 19:55:18.684937 | mbs: 2 | grad_accum: 512 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0 [default0]:07/02/2024 19:55:18 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps [default0]:07/02/2024 19:55:18 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 953.61MiB. Peak allocated 953.61MiB. Peak reserved: 960.00MiB [default0]:07/02/2024 19:55:18 [WARNING|DP=0|PP=2|TP=0|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty. [default4]:07/02/2024 19:55:18 [WARNING|DP=0|PP=3|TP=0|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty. [default6]:07/02/2024 19:55:18 [WARNING|DP=0|PP=3|TP=2|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty. [default3]:07/02/2024 19:55:18 [WARNING|DP=0|PP=2|TP=3|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty. [default7]:07/02/2024 19:55:18 [WARNING|DP=0|PP=3|TP=3|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty. [default5]:07/02/2024 19:55:18 [WARNING|DP=0|PP=3|TP=1|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty. [default2]:Repo card metadata block was not found. Setting CardData to empty. [default1]:07/02/2024 19:55:18 [WARNING|DP=0|PP=2|TP=1|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty. [default2]:07/02/2024 19:55:18 [WARNING|DP=0|PP=2|TP=2|ip-26-0-171-88]: Repo card metadata block was not found. Setting CardData to empty. [default1]:07/02/2024 19:55:18 [WARNING|DP=0|PP=0|TP=1|ip-26-0-171-62]: Repo card metadata block was not found. Setting CardData to empty. [default0]:Repo card metadata block was not found. Setting CardData to empty. [default3]:07/02/2024 19:55:18 [WARNING|DP=0|PP=0|TP=3|ip-26-0-171-62]: Repo card metadata block was not found. Setting CardData to empty. [default2]:07/02/2024 19:55:18 [WARNING|DP=0|PP=0|TP=2|ip-26-0-171-62]: Repo card metadata block was not found. Setting CardData to empty. [default6]:07/02/2024 19:55:18 [WARNING|DP=0|PP=1|TP=2|ip-26-0-171-62]: Repo card metadata block was not found. Setting CardData to empty. [default7]:07/02/2024 19:55:18 [WARNING|DP=0|PP=1|TP=3|ip-26-0-171-62]: Repo card metadata block was not found. Setting CardData to empty. [default7]:Repo card metadata block was not found. Setting CardData to empty. [default1]:Repo card metadata block was not found. Setting CardData to empty. [default4]:Repo card metadata block was not found. Setting CardData to empty. [default6]:Repo card metadata block was not found. Setting CardData to empty. [default7]:Repo card metadata block was not found. Setting CardData to empty. [default5]:Repo card metadata block was not found. Setting CardData to empty. [default2]:Repo card metadata block was not found. Setting CardData to empty. [default1]:Repo card metadata block was not found. Setting CardData to empty. [default3]:Repo card metadata block was not found. Setting CardData to empty. [default6]:Repo card metadata block was not found. Setting CardData to empty. [default3]:Repo card metadata block was not found. Setting CardData to empty. [default4]:07/02/2024 19:55:18 [WARNING|DP=0|PP=1|TP=0|ip-26-0-171-62]: Repo card metadata block was not found. Setting CardData to empty. [default4]:Repo card metadata block was not found. Setting CardData to empty. [default5]:07/02/2024 19:55:19 [WARNING|DP=0|PP=1|TP=1|ip-26-0-171-62]: Repo card metadata block was not found. Setting CardData to empty. [default5]:Repo card metadata block was not found. Setting CardData to empty. [default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default7]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default5]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default6]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default2]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default0]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default1]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default3]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default6]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default7]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default5]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default0]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default3]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default1]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) [default2]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass [default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default7]: warnings.warn( [default0]:07/02/2024 19:56:08 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 1021.18MiB. Peak allocated 6814.82MiB. Peak reserved: 7058.00MiB [default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default7]: warnings.warn( [default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default3]: warnings.warn( [default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default4]: warnings.warn( [default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default0]: warnings.warn( [default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default5]: warnings.warn( [default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default6]: warnings.warn( [default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default2]: warnings.warn( [default1]: warnings.warn( [default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default0]: warnings.warn( [default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default2]: warnings.warn( [default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default4]: warnings.warn( [default3]: warnings.warn( [default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default6]: warnings.warn( [default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default5]: warnings.warn( [default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions [default1]: warnings.warn( [default0]:07/02/2024 19:56:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 1777.75MiB. Peak allocated 1777.75MiB. Peak reserved: 7058.00MiB [default4]:07/02/2024 19:56:16 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-88]: iteration: 1 / 20 | consumed_tokens: 4.19M | elapsed_time_per_iteration_ms: 57K | tokens_per_sec: 73.6K | tokens_per_sec_per_gpu: 4.6K | global_batch_size: 1.02K | lm_loss: 11.2 | lr: 0.0001 | model_tflops_per_gpu: 41.7 | hardware_tflops_per_gpu: 41.7 | grad_norm: 10.9 | cuda_memory_allocated: 1.29G | cuda_max_memory_reserved: 3.1G | hd_total_memory_tb: 312G | hd_used_memory_tb: 67.8G | hd_free_memory_tb: 244G [default0]:07/02/2024 19:56:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 1777.75MiB. Peak allocated 7445.52MiB. Peak reserved: 7696.00MiB [default0]:07/02/2024 19:56:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 1777.75MiB. Peak allocated 1777.78MiB. Peak reserved: 7696.00MiB [default4]:07/02/2024 19:56:42 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-88]: iteration: 2 / 20 | consumed_tokens: 8.39M | elapsed_time_per_iteration_ms: 25.9K | tokens_per_sec: 162K | tokens_per_sec_per_gpu: 10.1K | global_batch_size: 1.02K | lm_loss: 11.2 | lr: 9.53e-05 | model_tflops_per_gpu: 91.8 | hardware_tflops_per_gpu: 91.8 | grad_norm: 11 | cuda_memory_allocated: 1.29G | cuda_max_memory_reserved: 3.1G | hd_total_memory_tb: 312G | hd_used_memory_tb: 67.8G | hd_free_memory_tb: 244G [default0]:07/02/2024 19:57:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 1777.75MiB. Peak allocated 7445.52MiB. Peak reserved: 7768.00MiB [default4]:07/02/2024 19:57:09 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-88]: iteration: 3 / 20 | consumed_tokens: 12.6M | elapsed_time_per_iteration_ms: 26.9K | tokens_per_sec: 156K | tokens_per_sec_per_gpu: 9.74K | global_batch_size: 1.02K | lm_loss: 9.83 | lr: 9.05e-05 | model_tflops_per_gpu: 88.4 | hardware_tflops_per_gpu: 88.4 | grad_norm: 44.4 | cuda_memory_allocated: 1.29G | cuda_max_memory_reserved: 3.1G | hd_total_memory_tb: 312G | hd_used_memory_tb: 67.8G | hd_free_memory_tb: 244G [default0]:STAGE:2024-07-02 19:57:09 3803264:3803264 ActivityProfilerController.cpp:314] Completed Stage: Warm Up [default0]:07/02/2024 19:57:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 1777.75MiB. Peak allocated 1777.78MiB. Peak reserved: 7768.00MiB [default0]:07/02/2024 19:57:44 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 1777.75MiB. Peak allocated 7445.52MiB. Peak reserved: 7768.00MiB [default0]:07/02/2024 19:57:44 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 1777.75MiB. Peak allocated 1777.78MiB. Peak reserved: 7768.00MiB [default4]:07/02/2024 19:57:44 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-88]: iteration: 4 / 20 | consumed_tokens: 16.8M | elapsed_time_per_iteration_ms: 35.2K | tokens_per_sec: 119K | tokens_per_sec_per_gpu: 7.45K | global_batch_size: 1.02K | lm_loss: 12.1 | lr: 8.58e-05 | model_tflops_per_gpu: 67.6 | hardware_tflops_per_gpu: 67.6 | grad_norm: 24.9 | cuda_memory_allocated: 1.29G | cuda_max_memory_reserved: 3.1G | hd_total_memory_tb: 312G | hd_used_memory_tb: 67.8G | hd_free_memory_tb: 244G [default4]:07/02/2024 19:58:19 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-88]: iteration: 5 / 20 | consumed_tokens: 21M | elapsed_time_per_iteration_ms: 34.8K | tokens_per_sec: 120K | tokens_per_sec_per_gpu: 7.52K | global_batch_size: 1.02K | lm_loss: 10.1 | lr: 8.11e-05 | model_tflops_per_gpu: 68.3 | hardware_tflops_per_gpu: 68.3 | grad_norm: 11.5 [default0]:07/02/2024 19:58:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-62]: Memory usage: 1777.75MiB. Peak allocated 7445.52MiB. Peak reserved: 7768.00MiB [default4]:07/02/2024 19:58:54 [INFO|DP=0|PP=3|TP=0|ip-26-0-171-88]: iteration: 6 / 20 | consumed_tokens: 25.2M | elapsed_time_per_iteration_ms: 34.8K | tokens_per_sec: 121K | tokens_per_sec_per_gpu: 7.53K | global_batch_size: 1.02K | lm_loss: 9.39 | lr: 7.63e-05 | model_tflops_per_gpu: 68.3 | hardware_tflops_per_gpu: 68.3 | grad_norm: 7.05 [default0]:STAGE:2024-07-02 20:00:28 3803264:3803264 ActivityProfilerController.cpp:320] Completed Stage: Collection [default0]:STAGE:2024-07-02 20:00:38 3803264:3803264 ActivityProfilerController.cpp:324] Completed Stage: Post Processing [default5]:[rank13]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600049 milliseconds before timing out. [default1]:[rank9]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600006 milliseconds before timing out. [default3]:[rank3]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178199, OpType=_REDUCE_SCATTER_BASE, NumelIn=16777216, NumelOut=4194304, Timeout(ms)=600000) ran for 600026 milliseconds before timing out. [default3]:[rank11]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600025 milliseconds before timing out. [default4]:[rank4]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600001 milliseconds before timing out. [default2]:[rank2]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178199, OpType=_REDUCE_SCATTER_BASE, NumelIn=16777216, NumelOut=4194304, Timeout(ms)=600000) ran for 600008 milliseconds before timing out. [default7]:[rank15]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600056 milliseconds before timing out. [default2]:[rank10]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600051 milliseconds before timing out. [default4]:[rank12]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600067 milliseconds before timing out. [default1]:[rank1]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178199, OpType=_REDUCE_SCATTER_BASE, NumelIn=16777216, NumelOut=4194304, Timeout(ms)=600000) ran for 600087 milliseconds before timing out. [default5]:[rank5]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600066 milliseconds before timing out. [default7]:[rank7]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600089 milliseconds before timing out. [default0]:[rank8]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600097 milliseconds before timing out. [default6]:[rank14]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600085 milliseconds before timing out. [default6]:[rank6]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600094 milliseconds before timing out. [default4]:[rank4]: Traceback (most recent call last): [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default4]:[rank4]: trainer.train(dataloader) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default4]:[rank4]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default4]:[rank4]: outputs = self.pipeline_engine.train_batch_iter( [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default4]:[rank4]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default4]:[rank4]: output = model(**micro_batch) [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default4]:[rank4]: return self._call_impl(*args, **kwargs) [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default4]:[rank4]: return forward_call(*args, **kwargs) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default4]:[rank4]: sharded_logits = self.model( [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default4]:[rank4]: return self._call_impl(*args, **kwargs) [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default4]:[rank4]: return forward_call(*args, **kwargs) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default4]:[rank4]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default4]:[rank4]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default4]:[rank4]: return self._call_impl(*args, **kwargs) [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default4]:[rank4]: return forward_call(*args, **kwargs) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default4]:[rank4]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default4]:[rank4]: pipeline_state.run_communication() [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default4]:[rank4]: recv_activation_tensor = recv_activation() [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default4]:[rank4]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default4]:[rank4]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default4]:[rank4]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default4]:[rank4]: dist.recv( [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default4]:[rank4]: return func(*args, **kwargs) [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default4]:[rank4]: pg.recv([tensor], group_src_rank, tag).wait() [default4]:[rank4]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default6]:[rank6]: Traceback (most recent call last): [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default6]:[rank6]: trainer.train(dataloader) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default6]:[rank6]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default6]:[rank6]: outputs = self.pipeline_engine.train_batch_iter( [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default6]:[rank6]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default6]:[rank6]: output = model(**micro_batch) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default6]:[rank6]: sharded_logits = self.model( [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default6]:[rank6]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default6]:[rank6]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default6]:[rank6]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default6]:[rank6]: pipeline_state.run_communication() [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default6]:[rank6]: recv_activation_tensor = recv_activation() [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default6]:[rank6]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default6]:[rank6]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default6]:[rank6]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default6]:[rank6]: dist.recv( [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default6]:[rank6]: return func(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default6]:[rank6]: pg.recv([tensor], group_src_rank, tag).wait() [default6]:[rank6]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default5]:[rank5]: Traceback (most recent call last): [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default5]:[rank5]: trainer.train(dataloader) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default5]:[rank5]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default5]:[rank5]: outputs = self.pipeline_engine.train_batch_iter( [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default5]:[rank5]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default5]:[rank5]: output = model(**micro_batch) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default5]:[rank5]: sharded_logits = self.model( [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default5]:[rank5]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default5]:[rank5]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default5]:[rank5]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default5]:[rank5]: pipeline_state.run_communication() [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default5]:[rank5]: recv_activation_tensor = recv_activation() [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default5]:[rank5]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default5]:[rank5]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default5]:[rank5]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default5]:[rank5]: dist.recv( [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default5]:[rank5]: return func(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default5]:[rank5]: pg.recv([tensor], group_src_rank, tag).wait() [default5]:[rank5]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default7]:[rank7]: Traceback (most recent call last): [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default7]:[rank7]: trainer.train(dataloader) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default7]:[rank7]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default7]:[rank7]: outputs = self.pipeline_engine.train_batch_iter( [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default7]:[rank7]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default7]:[rank7]: output = model(**micro_batch) [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default7]:[rank7]: return self._call_impl(*args, **kwargs) [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default7]:[rank7]: return forward_call(*args, **kwargs) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default7]:[rank7]: sharded_logits = self.model( [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default7]:[rank7]: return self._call_impl(*args, **kwargs) [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default7]:[rank7]: return forward_call(*args, **kwargs) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default7]:[rank7]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default7]:[rank7]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default7]:[rank7]: return self._call_impl(*args, **kwargs) [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default7]:[rank7]: return forward_call(*args, **kwargs) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default7]:[rank7]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default7]:[rank7]: pipeline_state.run_communication() [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default7]:[rank7]: recv_activation_tensor = recv_activation() [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default7]:[rank7]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default7]:[rank7]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default7]:[rank7]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default7]:[rank7]: dist.recv( [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default7]:[rank7]: return func(*args, **kwargs) [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default7]:[rank7]: pg.recv([tensor], group_src_rank, tag).wait() [default7]:[rank7]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default5]:[rank13]: Traceback (most recent call last): [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default5]:[rank13]: trainer.train(dataloader) [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default5]:[rank13]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default5]:[rank13]: outputs = self.pipeline_engine.train_batch_iter( [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter [default5]:[rank13]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default5]:[rank13]: output = model(**micro_batch) [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank13]: return self._call_impl(*args, **kwargs) [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank13]: return forward_call(*args, **kwargs) [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default5]:[rank13]: sharded_logits = self.model( [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank13]: return self._call_impl(*args, **kwargs) [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank13]: return forward_call(*args, **kwargs) [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default5]:[rank13]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default5]:[rank13]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank13]: return self._call_impl(*args, **kwargs) [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank13]: return forward_call(*args, **kwargs) [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default5]:[rank13]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default5]:[rank13]: pipeline_state.run_communication() [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default5]:[rank13]: recv_activation_tensor = recv_activation() [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default5]:[rank13]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default5]:[rank13]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default5]:[rank13]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default5]:[rank13]: dist.recv( [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default5]:[rank13]: return func(*args, **kwargs) [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default5]:[rank13]: pg.recv([tensor], group_src_rank, tag).wait() [default5]:[rank13]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default4]:[rank12]: Traceback (most recent call last): [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default4]:[rank12]: trainer.train(dataloader) [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default4]:[rank12]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default4]:[rank12]: outputs = self.pipeline_engine.train_batch_iter( [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter [default4]:[rank12]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default4]:[rank12]: output = model(**micro_batch) [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default4]:[rank12]: return self._call_impl(*args, **kwargs) [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default4]:[rank12]: return forward_call(*args, **kwargs) [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default4]:[rank12]: sharded_logits = self.model( [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default4]:[rank12]: return self._call_impl(*args, **kwargs) [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default4]:[rank12]: return forward_call(*args, **kwargs) [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default4]:[rank12]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default4]:[rank12]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default4]:[rank12]: return self._call_impl(*args, **kwargs) [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default4]:[rank12]: return forward_call(*args, **kwargs) [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default4]:[rank12]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default4]:[rank12]: pipeline_state.run_communication() [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default4]:[rank12]: recv_activation_tensor = recv_activation() [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default4]:[rank12]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default4]:[rank12]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default4]:[rank12]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default4]:[rank12]: dist.recv( [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default4]:[rank12]: return func(*args, **kwargs) [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default4]:[rank12]: pg.recv([tensor], group_src_rank, tag).wait() [default4]:[rank12]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default6]:[rank14]: Traceback (most recent call last): [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default6]:[rank14]: trainer.train(dataloader) [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default6]:[rank14]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default6]:[rank14]: outputs = self.pipeline_engine.train_batch_iter( [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter [default6]:[rank14]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default6]:[rank14]: output = model(**micro_batch) [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank14]: return self._call_impl(*args, **kwargs) [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank14]: return forward_call(*args, **kwargs) [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default6]:[rank14]: sharded_logits = self.model( [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank14]: return self._call_impl(*args, **kwargs) [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank14]: return forward_call(*args, **kwargs) [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default6]:[rank14]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default6]:[rank14]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank14]: return self._call_impl(*args, **kwargs) [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank14]: return forward_call(*args, **kwargs) [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default6]:[rank14]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default6]:[rank14]: pipeline_state.run_communication() [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default6]:[rank14]: recv_activation_tensor = recv_activation() [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default6]:[rank14]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default6]:[rank14]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default6]:[rank14]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default6]:[rank14]: dist.recv( [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default6]:[rank14]: return func(*args, **kwargs) [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default6]:[rank14]: pg.recv([tensor], group_src_rank, tag).wait() [default6]:[rank14]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default7]:[rank15]: Traceback (most recent call last): [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default7]:[rank15]: trainer.train(dataloader) [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default7]:[rank15]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default7]:[rank15]: outputs = self.pipeline_engine.train_batch_iter( [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter [default7]:[rank15]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default7]:[rank15]: output = model(**micro_batch) [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default7]:[rank15]: return self._call_impl(*args, **kwargs) [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default7]:[rank15]: return forward_call(*args, **kwargs) [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default7]:[rank15]: sharded_logits = self.model( [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default7]:[rank15]: return self._call_impl(*args, **kwargs) [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default7]:[rank15]: return forward_call(*args, **kwargs) [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default7]:[rank15]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default7]:[rank15]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default7]:[rank15]: return self._call_impl(*args, **kwargs) [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default7]:[rank15]: return forward_call(*args, **kwargs) [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default7]:[rank15]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default7]:[rank15]: pipeline_state.run_communication() [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default7]:[rank15]: recv_activation_tensor = recv_activation() [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default7]:[rank15]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default7]:[rank15]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default7]:[rank15]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default7]:[rank15]: dist.recv( [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default7]:[rank15]: return func(*args, **kwargs) [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default7]:[rank15]: pg.recv([tensor], group_src_rank, tag).wait() [default7]:[rank15]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default0]:[rank8]: Traceback (most recent call last): [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default0]:[rank8]: trainer.train(dataloader) [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default0]:[rank8]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default0]:[rank8]: outputs = self.pipeline_engine.train_batch_iter( [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default0]:[rank8]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default0]:[rank8]: output = model(**micro_batch) [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default0]:[rank8]: return self._call_impl(*args, **kwargs) [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default0]:[rank8]: return forward_call(*args, **kwargs) [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default0]:[rank8]: sharded_logits = self.model( [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default0]:[rank8]: return self._call_impl(*args, **kwargs) [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default0]:[rank8]: return forward_call(*args, **kwargs) [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default0]:[rank8]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default0]:[rank8]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default0]:[rank8]: return self._call_impl(*args, **kwargs) [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default0]:[rank8]: return forward_call(*args, **kwargs) [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default0]:[rank8]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default0]:[rank8]: pipeline_state.run_communication() [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default0]:[rank8]: recv_activation_tensor = recv_activation() [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default0]:[rank8]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default0]:[rank8]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default0]:[rank8]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default0]:[rank8]: dist.recv( [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default0]:[rank8]: return func(*args, **kwargs) [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default0]:[rank8]: pg.recv([tensor], group_src_rank, tag).wait() [default0]:[rank8]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default1]:[rank9]: Traceback (most recent call last): [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default1]:[rank9]: trainer.train(dataloader) [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default1]:[rank9]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default1]:[rank9]: outputs = self.pipeline_engine.train_batch_iter( [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default1]:[rank9]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default1]:[rank9]: output = model(**micro_batch) [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank9]: return self._call_impl(*args, **kwargs) [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank9]: return forward_call(*args, **kwargs) [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default1]:[rank9]: sharded_logits = self.model( [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank9]: return self._call_impl(*args, **kwargs) [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank9]: return forward_call(*args, **kwargs) [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default1]:[rank9]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default1]:[rank9]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank9]: return self._call_impl(*args, **kwargs) [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank9]: return forward_call(*args, **kwargs) [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default1]:[rank9]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default1]:[rank9]: pipeline_state.run_communication() [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default1]:[rank9]: recv_activation_tensor = recv_activation() [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default1]:[rank9]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default1]:[rank9]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default1]:[rank9]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default1]:[rank9]: dist.recv( [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default1]:[rank9]: return func(*args, **kwargs) [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default1]:[rank9]: pg.recv([tensor], group_src_rank, tag).wait() [default1]:[rank9]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default3]:[rank11]: Traceback (most recent call last): [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default3]:[rank11]: trainer.train(dataloader) [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default3]:[rank11]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default3]:[rank11]: outputs = self.pipeline_engine.train_batch_iter( [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default3]:[rank11]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default3]:[rank11]: output = model(**micro_batch) [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank11]: return self._call_impl(*args, **kwargs) [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank11]: return forward_call(*args, **kwargs) [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default3]:[rank11]: sharded_logits = self.model( [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank11]: return self._call_impl(*args, **kwargs) [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank11]: return forward_call(*args, **kwargs) [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default3]:[rank11]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default3]:[rank11]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank11]: return self._call_impl(*args, **kwargs) [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank11]: return forward_call(*args, **kwargs) [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default3]:[rank11]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default3]:[rank11]: pipeline_state.run_communication() [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default3]:[rank11]: recv_activation_tensor = recv_activation() [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default3]:[rank11]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default3]:[rank11]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default3]:[rank11]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default3]:[rank11]: dist.recv( [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default3]:[rank11]: return func(*args, **kwargs) [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default3]:[rank11]: pg.recv([tensor], group_src_rank, tag).wait() [default3]:[rank11]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default2]:[rank10]: Traceback (most recent call last): [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default2]:[rank10]: trainer.train(dataloader) [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default2]:[rank10]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default2]:[rank10]: outputs = self.pipeline_engine.train_batch_iter( [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default2]:[rank10]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default2]:[rank10]: output = model(**micro_batch) [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank10]: return self._call_impl(*args, **kwargs) [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank10]: return forward_call(*args, **kwargs) [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default2]:[rank10]: sharded_logits = self.model( [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank10]: return self._call_impl(*args, **kwargs) [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank10]: return forward_call(*args, **kwargs) [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default2]:[rank10]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default2]:[rank10]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank10]: return self._call_impl(*args, **kwargs) [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank10]: return forward_call(*args, **kwargs) [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default2]:[rank10]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default2]:[rank10]: pipeline_state.run_communication() [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default2]:[rank10]: recv_activation_tensor = recv_activation() [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default2]:[rank10]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default2]:[rank10]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default2]:[rank10]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta [default2]:[rank10]: dist.recv( [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default2]:[rank10]: return func(*args, **kwargs) [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default2]:[rank10]: pg.recv([tensor], group_src_rank, tag).wait() [default2]:[rank10]: torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. [default4]:[rank12]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 3] Timeout at NCCL work: 27651, last enqueued NCCL work: 27651, last completed NCCL work: 27650. [default4]:[rank12]:[E ProcessGroupNCCL.cpp:577] [Rank 3] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data. [default4]:[rank12]:[E ProcessGroupNCCL.cpp:583] [Rank 3] To avoid data inconsistency, we are taking the entire process down. [default4]:[rank12]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600067 milliseconds before timing out. [default4]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default4]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f3e8f498897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default4]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f3e90771c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f3e90776a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f3e90777dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #4: + 0xd3e95 (0x7f3edc210e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default4]:frame #5: + 0x8609 (0x7f3ee1257609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default4]:frame #6: clone + 0x43 (0x7f3ee1022353 in /lib/x86_64-linux-gnu/libc.so.6) [default4]: [default4]:terminate called after throwing an instance of 'c10::DistBackendError' [default4]: what(): [PG 4 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600067 milliseconds before timing out. [default4]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default4]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f3e8f498897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default4]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f3e90771c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f3e90776a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f3e90777dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #4: + 0xd3e95 (0x7f3edc210e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default4]:frame #5: + 0x8609 (0x7f3ee1257609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default4]:frame #6: clone + 0x43 (0x7f3ee1022353 in /lib/x86_64-linux-gnu/libc.so.6) [default4]: [default4]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first): [default4]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f3e8f498897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default4]:frame #1: + 0xe32119 (0x7f3e903fb119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #2: + 0xd3e95 (0x7f3edc210e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default4]:frame #3: + 0x8609 (0x7f3ee1257609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default4]:frame #4: clone + 0x43 (0x7f3ee1022353 in /lib/x86_64-linux-gnu/libc.so.6) [default4]: [default7]:[rank15]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 3] Timeout at NCCL work: 27651, last enqueued NCCL work: 27651, last completed NCCL work: 27650. [default7]:[rank15]:[E ProcessGroupNCCL.cpp:577] [Rank 3] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data. [default7]:[rank15]:[E ProcessGroupNCCL.cpp:583] [Rank 3] To avoid data inconsistency, we are taking the entire process down. [default7]:[rank15]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600056 milliseconds before timing out. [default7]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f8a7b5d7897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default7]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f8a7c8b0c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f8a7c8b5a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f8a7c8b6dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #4: + 0xd3e95 (0x7f8ac834fe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default7]:frame #5: + 0x8609 (0x7f8acd396609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default7]:frame #6: clone + 0x43 (0x7f8acd161353 in /lib/x86_64-linux-gnu/libc.so.6) [default7]: [default7]:terminate called after throwing an instance of 'c10::DistBackendError' [default7]: what(): [PG 4 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600056 milliseconds before timing out. [default7]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f8a7b5d7897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default7]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f8a7c8b0c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f8a7c8b5a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f8a7c8b6dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #4: + 0xd3e95 (0x7f8ac834fe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default7]:frame #5: + 0x8609 (0x7f8acd396609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default7]:frame #6: clone + 0x43 (0x7f8acd161353 in /lib/x86_64-linux-gnu/libc.so.6) [default7]: [default7]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first): [default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f8a7b5d7897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default7]:frame #1: + 0xe32119 (0x7f8a7c53a119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #2: + 0xd3e95 (0x7f8ac834fe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default7]:frame #3: + 0x8609 (0x7f8acd396609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default7]:frame #4: clone + 0x43 (0x7f8acd161353 in /lib/x86_64-linux-gnu/libc.so.6) [default7]: [default7]:[rank7]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 55299, last enqueued NCCL work: 55299, last completed NCCL work: 55298. [default7]:[rank7]:[E ProcessGroupNCCL.cpp:577] [Rank 1] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data. [default7]:[rank7]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down. [default7]:[rank7]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600089 milliseconds before timing out. [default7]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f236446e897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default7]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f2365747c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f236574ca80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f236574ddcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #4: + 0xd3e95 (0x7f23b11e6e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default7]:frame #5: + 0x8609 (0x7f23b622d609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default7]:frame #6: clone + 0x43 (0x7f23b5ff8353 in /lib/x86_64-linux-gnu/libc.so.6) [default7]: [default7]:terminate called after throwing an instance of 'c10::DistBackendError' [default7]: what(): [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600089 milliseconds before timing out. [default7]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f236446e897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default7]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f2365747c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f236574ca80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f236574ddcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #4: + 0xd3e95 (0x7f23b11e6e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default7]:frame #5: + 0x8609 (0x7f23b622d609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default7]:frame #6: clone + 0x43 (0x7f23b5ff8353 in /lib/x86_64-linux-gnu/libc.so.6) [default7]: [default7]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first): [default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f236446e897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default7]:frame #1: + 0xe32119 (0x7f23653d1119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:frame #2: + 0xd3e95 (0x7f23b11e6e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default7]:frame #3: + 0x8609 (0x7f23b622d609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default7]:frame #4: clone + 0x43 (0x7f23b5ff8353 in /lib/x86_64-linux-gnu/libc.so.6) [default7]: [default6]:[rank14]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 3] Timeout at NCCL work: 27651, last enqueued NCCL work: 27651, last completed NCCL work: 27650. [default6]:[rank14]:[E ProcessGroupNCCL.cpp:577] [Rank 3] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data. [default6]:[rank14]:[E ProcessGroupNCCL.cpp:583] [Rank 3] To avoid data inconsistency, we are taking the entire process down. [default6]:[rank14]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600085 milliseconds before timing out. [default6]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default6]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f1fc412e897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default6]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f1fc5407c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f1fc540ca80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f1fc540ddcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #4: + 0xd3e95 (0x7f2010ea6e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default6]:frame #5: + 0x8609 (0x7f2015eed609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default6]:frame #6: clone + 0x43 (0x7f2015cb8353 in /lib/x86_64-linux-gnu/libc.so.6) [default6]: [default6]:terminate called after throwing an instance of 'c10::DistBackendError' [default6]: what(): [PG 4 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600085 milliseconds before timing out. [default6]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default6]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f1fc412e897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default6]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f1fc5407c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f1fc540ca80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f1fc540ddcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #4: + 0xd3e95 (0x7f2010ea6e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default6]:frame #5: + 0x8609 (0x7f2015eed609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default6]:frame #6: clone + 0x43 (0x7f2015cb8353 in /lib/x86_64-linux-gnu/libc.so.6) [default6]: [default6]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first): [default6]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f1fc412e897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default6]:frame #1: + 0xe32119 (0x7f1fc5091119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #2: + 0xd3e95 (0x7f2010ea6e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default6]:frame #3: + 0x8609 (0x7f2015eed609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default6]:frame #4: clone + 0x43 (0x7f2015cb8353 in /lib/x86_64-linux-gnu/libc.so.6) [default6]: [default5]:[rank13]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 3] Timeout at NCCL work: 27651, last enqueued NCCL work: 27651, last completed NCCL work: 27650. [default5]:[rank13]:[E ProcessGroupNCCL.cpp:577] [Rank 3] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data. [default5]:[rank13]:[E ProcessGroupNCCL.cpp:583] [Rank 3] To avoid data inconsistency, we are taking the entire process down. [default5]:[rank13]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600049 milliseconds before timing out. [default5]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fcc332da897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default5]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7fcc345b3c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7fcc345b8a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7fcc345b9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #4: + 0xd3e95 (0x7fcc80052e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default5]:frame #5: + 0x8609 (0x7fcc85099609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default5]:frame #6: clone + 0x43 (0x7fcc84e64353 in /lib/x86_64-linux-gnu/libc.so.6) [default5]: [default5]:terminate called after throwing an instance of 'c10::DistBackendError' [default5]: what(): [PG 4 Rank 3] Process group watchdog thread terminated with exception: [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=27651, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600049 milliseconds before timing out. [default5]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fcc332da897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default5]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7fcc345b3c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7fcc345b8a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7fcc345b9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #4: + 0xd3e95 (0x7fcc80052e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default5]:frame #5: + 0x8609 (0x7fcc85099609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default5]:frame #6: clone + 0x43 (0x7fcc84e64353 in /lib/x86_64-linux-gnu/libc.so.6) [default5]: [default5]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first): [default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fcc332da897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default5]:frame #1: + 0xe32119 (0x7fcc3423d119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #2: + 0xd3e95 (0x7fcc80052e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default5]:frame #3: + 0x8609 (0x7fcc85099609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default5]:frame #4: clone + 0x43 (0x7fcc84e64353 in /lib/x86_64-linux-gnu/libc.so.6) [default5]: [default4]:[rank4]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 55299, last enqueued NCCL work: 55299, last completed NCCL work: 55298. [default4]:[rank4]:[E ProcessGroupNCCL.cpp:577] [Rank 1] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data. [default4]:[rank4]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down. [default4]:[rank4]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600001 milliseconds before timing out. [default4]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default4]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f9f68920897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default4]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f9f69bf9c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f9f69bfea80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f9f69bffdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #4: + 0xd3e95 (0x7f9fb5698e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default4]:frame #5: + 0x8609 (0x7f9fba6df609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default4]:frame #6: clone + 0x43 (0x7f9fba4aa353 in /lib/x86_64-linux-gnu/libc.so.6) [default4]: [default4]:terminate called after throwing an instance of 'c10::DistBackendError' [default4]: what(): [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600001 milliseconds before timing out. [default4]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default4]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f9f68920897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default4]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f9f69bf9c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f9f69bfea80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f9f69bffdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #4: + 0xd3e95 (0x7f9fb5698e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default4]:frame #5: + 0x8609 (0x7f9fba6df609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default4]:frame #6: clone + 0x43 (0x7f9fba4aa353 in /lib/x86_64-linux-gnu/libc.so.6) [default4]: [default4]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first): [default4]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f9f68920897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default4]:frame #1: + 0xe32119 (0x7f9f69883119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:frame #2: + 0xd3e95 (0x7f9fb5698e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default4]:frame #3: + 0x8609 (0x7f9fba6df609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default4]:frame #4: clone + 0x43 (0x7f9fba4aa353 in /lib/x86_64-linux-gnu/libc.so.6) [default4]: [default6]:[rank6]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 55299, last enqueued NCCL work: 55299, last completed NCCL work: 55298. [default6]:[rank6]:[E ProcessGroupNCCL.cpp:577] [Rank 1] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data. [default6]:[rank6]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down. [default6]:[rank6]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600094 milliseconds before timing out. [default6]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default6]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f4fefb0f897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default6]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f4ff0de8c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f4ff0deda80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f4ff0deedcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #4: + 0xd3e95 (0x7f503c887e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default6]:frame #5: + 0x8609 (0x7f50418ce609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default6]:frame #6: clone + 0x43 (0x7f5041699353 in /lib/x86_64-linux-gnu/libc.so.6) [default6]: [default6]:terminate called after throwing an instance of 'c10::DistBackendError' [default6]: what(): [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600094 milliseconds before timing out. [default6]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default6]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f4fefb0f897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default6]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f4ff0de8c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f4ff0deda80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f4ff0deedcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #4: + 0xd3e95 (0x7f503c887e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default6]:frame #5: + 0x8609 (0x7f50418ce609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default6]:frame #6: clone + 0x43 (0x7f5041699353 in /lib/x86_64-linux-gnu/libc.so.6) [default6]: [default6]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first): [default6]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f4fefb0f897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default6]:frame #1: + 0xe32119 (0x7f4ff0a72119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:frame #2: + 0xd3e95 (0x7f503c887e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default6]:frame #3: + 0x8609 (0x7f50418ce609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default6]:frame #4: clone + 0x43 (0x7f5041699353 in /lib/x86_64-linux-gnu/libc.so.6) [default6]: [default5]:[rank5]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 55299, last enqueued NCCL work: 55299, last completed NCCL work: 55298. [default5]:[rank5]:[E ProcessGroupNCCL.cpp:577] [Rank 1] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data. [default5]:[rank5]:[E ProcessGroupNCCL.cpp:583] [Rank 1] To avoid data inconsistency, we are taking the entire process down. [default5]:[rank5]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600066 milliseconds before timing out. [default5]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f858930a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default5]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f858a5e3c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f858a5e8a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f858a5e9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #4: + 0xd3e95 (0x7f85d6082e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default5]:frame #5: + 0x8609 (0x7f85db0c9609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default5]:frame #6: clone + 0x43 (0x7f85dae94353 in /lib/x86_64-linux-gnu/libc.so.6) [default5]: [default5]:terminate called after throwing an instance of 'c10::DistBackendError' [default5]: what(): [PG 4 Rank 1] Process group watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600066 milliseconds before timing out. [default5]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f858930a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default5]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f858a5e3c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f858a5e8a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f858a5e9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #4: + 0xd3e95 (0x7f85d6082e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default5]:frame #5: + 0x8609 (0x7f85db0c9609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default5]:frame #6: clone + 0x43 (0x7f85dae94353 in /lib/x86_64-linux-gnu/libc.so.6) [default5]: [default5]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first): [default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f858930a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default5]:frame #1: + 0xe32119 (0x7f858a26d119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:frame #2: + 0xd3e95 (0x7f85d6082e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default5]:frame #3: + 0x8609 (0x7f85db0c9609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default5]:frame #4: clone + 0x43 (0x7f85dae94353 in /lib/x86_64-linux-gnu/libc.so.6) [default5]: [default0]:[rank8]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 2] Timeout at NCCL work: 55299, last enqueued NCCL work: 55299, last completed NCCL work: 55298. [default0]:[rank8]:[E ProcessGroupNCCL.cpp:577] [Rank 2] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data. [default0]:[rank8]:[E ProcessGroupNCCL.cpp:583] [Rank 2] To avoid data inconsistency, we are taking the entire process down. [default0]:[rank8]:[E ProcessGroupNCCL.cpp:1414] [PG 4 Rank 2] Process group watchdog thread terminated with exception: [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600097 milliseconds before timing out. [default0]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default0]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7dfab53897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default0]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f7dfbe2cc62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default0]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f7dfbe31a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default0]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f7dfbe32dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default0]:frame #4: + 0xd3e95 (0x7f7e478cbe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default0]:frame #5: + 0x8609 (0x7f7e4c912609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default0]:frame #6: clone + 0x43 (0x7f7e4c6dd353 in /lib/x86_64-linux-gnu/libc.so.6) [default0]: [default0]:terminate called after throwing an instance of 'c10::DistBackendError' [default0]: what(): [PG 4 Rank 2] Process group watchdog thread terminated with exception: [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55299, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600097 milliseconds before timing out. [default0]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first): [default0]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7dfab53897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default0]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional > >) + 0x1d2 (0x7f7dfbe2cc62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default0]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f7dfbe31a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default0]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f7dfbe32dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default0]:frame #4: + 0xd3e95 (0x7f7e478cbe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default0]:frame #5: + 0x8609 (0x7f7e4c912609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default0]:frame #6: clone + 0x43 (0x7f7e4c6dd353 in /lib/x86_64-linux-gnu/libc.so.6) [default0]: [default0]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first): [default0]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7dfab53897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default0]:frame #1: + 0xe32119 (0x7f7dfbab6119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default0]:frame #2: + 0xd3e95 (0x7f7e478cbe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6) [default0]:frame #3: + 0x8609 (0x7f7e4c912609 in /lib/x86_64-linux-gnu/libpthread.so.0) [default0]:frame #4: clone + 0x43 (0x7f7e4c6dd353 in /lib/x86_64-linux-gnu/libc.so.6) [default0]: W0702 20:08:58.752000 140483223861056 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 791860 closing signal SIGTERM W0702 20:08:58.752000 140483223861056 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 791861 closing signal SIGTERM W0702 20:08:58.753000 140483223861056 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 791862 closing signal SIGTERM W0702 20:08:58.753000 140483223861056 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 791863 closing signal SIGTERM W0702 20:08:58.784000 139863964038976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 3803264 closing signal SIGTERM W0702 20:08:58.789000 139863964038976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 3803265 closing signal SIGTERM W0702 20:08:58.791000 139863964038976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 3803266 closing signal SIGTERM W0702 20:08:58.797000 139863964038976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 3803267 closing signal SIGTERM E0702 20:09:00.507000 140483223861056 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: -6) local_rank: 4 (pid: 791864) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10 Traceback (most recent call last): File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in sys.exit(main()) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper return f(*args, **kwargs) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main run(args) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run elastic_launch( File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__ return launch_agent(self._config, self._entrypoint, list(args)) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent raise ChildFailedError( torch.distributed.elastic.multiprocessing.errors.ChildFailedError: ============================================================ /fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED ------------------------------------------------------------ Failures: [1]: time : 2024-07-02_20:08:58 host : ip-26-0-171-88.ec2.internal rank : 13 (local_rank: 5) exitcode : -6 (pid: 791865) error_file: traceback : Signal 6 (SIGABRT) received by PID 791865 [2]: time : 2024-07-02_20:08:58 host : ip-26-0-171-88.ec2.internal rank : 14 (local_rank: 6) exitcode : -6 (pid: 791866) error_file: traceback : Signal 6 (SIGABRT) received by PID 791866 [3]: time : 2024-07-02_20:08:58 host : ip-26-0-171-88.ec2.internal rank : 15 (local_rank: 7) exitcode : -6 (pid: 791867) error_file: traceback : Signal 6 (SIGABRT) received by PID 791867 ------------------------------------------------------------ Root Cause (first observed failure): [0]: time : 2024-07-02_20:08:58 host : ip-26-0-171-88.ec2.internal rank : 12 (local_rank: 4) exitcode : -6 (pid: 791864) error_file: traceback : Signal 6 (SIGABRT) received by PID 791864 ============================================================ srun: error: ip-26-0-171-88: task 1: Exited with exit code 1 E0702 20:09:05.389000 139863964038976 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: -6) local_rank: 4 (pid: 3803268) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10 Traceback (most recent call last): File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in sys.exit(main()) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper return f(*args, **kwargs) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main run(args) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run elastic_launch( File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__ return launch_agent(self._config, self._entrypoint, list(args)) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent raise ChildFailedError( torch.distributed.elastic.multiprocessing.errors.ChildFailedError: ============================================================ /fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED ------------------------------------------------------------ Failures: [1]: time : 2024-07-02_20:08:58 host : ip-26-0-171-62.ec2.internal rank : 5 (local_rank: 5) exitcode : -6 (pid: 3803269) error_file: traceback : Signal 6 (SIGABRT) received by PID 3803269 [2]: time : 2024-07-02_20:08:58 host : ip-26-0-171-62.ec2.internal rank : 6 (local_rank: 6) exitcode : -6 (pid: 3803270) error_file: traceback : Signal 6 (SIGABRT) received by PID 3803270 [3]: time : 2024-07-02_20:08:58 host : ip-26-0-171-62.ec2.internal rank : 7 (local_rank: 7) exitcode : -6 (pid: 3803271) error_file: traceback : Signal 6 (SIGABRT) received by PID 3803271 ------------------------------------------------------------ Root Cause (first observed failure): [0]: time : 2024-07-02_20:08:58 host : ip-26-0-171-62.ec2.internal rank : 4 (local_rank: 4) exitcode : -6 (pid: 3803268) error_file: traceback : Signal 6 (SIGABRT) received by PID 3803268 ============================================================ srun: error: ip-26-0-171-62: task 0: Exited with exit code 1 Consider using `hf_transfer` for faster uploads. This solution comes with some limitations. See https://huggingface.co/docs/huggingface_hub/hf_transfer for more details.