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	========================
	START TIME: Wed Jul 3 22:05:59 UTC 2024
	python3 version = Python 3.10.14
	========================
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	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
	W0703 22:06:07.603000 140536135579456 torch/distributed/run.py:757]
	W0703 22:06:07.603000 140536135579456 torch/distributed/run.py:757] *****************************************
	W0703 22:06:07.603000 140536135579456 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.
	W0703 22:06:07.603000 140536135579456 torch/distributed/run.py:757] *****************************************
	[default0]:07/03/2024 22:06:29 [WARNING\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: [Vocab Size Padding] Padded vocab (size: 50257) with 3 dummy tokens (new size: 50260)
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Config:
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Config(general=GeneralArgs(project='bench_cluster',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: run='%date_%jobid',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: seed=42,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: step=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: consumed_train_samples=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: benchmark_csv_path=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: ignore_sanity_checks=True),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: parallelism=ParallelismArgs(dp=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: pp=2,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: tp=4,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7fe9b4628880>,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: tp_linear_async_communication=False,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: expert_parallel_size=1),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: eos_token_id=2,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: hidden_act='silu',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: hidden_size=2048,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: initializer_range=0.02,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: intermediate_size=4096,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: is_llama_config=True,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: max_position_embeddings=4096,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: num_attention_heads=32,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: num_hidden_layers=24,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: num_key_value_heads=32,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: pad_token_id=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: pretraining_tp=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: rms_norm_eps=1e-05,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: rope_scaling=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: rope_theta=10000.0,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: tie_word_embeddings=True,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: use_cache=True,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: vocab_size=50260),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: init_method=RandomInit(std=0.025),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: dtype=torch.bfloat16,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: make_vocab_size_divisible_by=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: ddp_bucket_cap_mb=25),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: tokenizer_revision=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: tokenizer_max_length=None),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: checkpoint_interval=100000,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: save_initial_state=False,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: resume_checkpoint_path=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: checkpoints_path_is_shared_file_system=False),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: logging=LoggingArgs(log_level='info',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: log_level_replica='info',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: iteration_step_info_interval=1),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: tokens=TokensArgs(sequence_length=4096,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: train_steps=20,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: micro_batch_size=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: batch_accumulation_per_replica=1024,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: val_check_interval=-1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: limit_val_batches=0,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: limit_test_batches=0),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: adam_beta1=0.9,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: adam_beta2=0.95,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: torch_adam_is_fused=True,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: name='adamW'),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: zero_stage=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: weight_decay=0.01,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: clip_grad=1.0,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: accumulate_grad_in_fp32=True,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: lr_warmup_steps=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: lr_warmup_style='linear',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: lr_decay_style='linear',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: lr_decay_steps=19,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: lr_decay_starting_step=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: min_decay_lr=1e-05)),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: data_stages=[DatasetStageArgs(name='Training Stage',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: start_training_step=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: hf_dataset_splits='train',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: hf_dataset_config_name=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: dataset_processing_num_proc_per_process=64,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: dataset_overwrite_cache=False,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: text_column_name='text'),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: seed=42,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: num_loading_workers=0))],
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-1')),
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: lighteval=None)
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Model Config:
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: LlamaConfig(bos_token_id=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: eos_token_id=2,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: hidden_act='silu',
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: hidden_size=2048,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: initializer_range=0.02,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: intermediate_size=4096,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: is_llama_config=True,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: max_position_embeddings=4096,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: num_attention_heads=32,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: num_hidden_layers=24,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: num_key_value_heads=32,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: pad_token_id=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: pretraining_tp=1,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: rms_norm_eps=1e-05,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: rope_scaling=None,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: rope_theta=10000.0,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: tie_word_embeddings=True,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: use_cache=True,
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: vocab_size=50260)
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Building model..
	[default0]:07/03/2024 22:06:29 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Setting PP block ranks...
	[default1]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=1\|ip-26-0-162-233]: Local number of parameters: 173M (329.19MiB)
	[default1]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=1\|ip-26-0-162-233]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
	[default1]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=1\|ip-26-0-162-233]: No checkpoint path provided.
	[default7]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=3\|ip-26-0-162-233]: Local number of parameters: 131M (249.16MiB)
	[default7]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=3\|ip-26-0-162-233]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
	[default7]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=3\|ip-26-0-162-233]: No checkpoint path provided.
	[default2]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=2\|ip-26-0-162-233]: Local number of parameters: 173M (329.19MiB)
	[default2]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=2\|ip-26-0-162-233]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
	[default2]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=2\|ip-26-0-162-233]: No checkpoint path provided.
	[default0]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Total number of parameters: 1.21G (2313.42MiB)
	[default0]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Local number of parameters: 173M (329.19MiB)
	[default6]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=2\|ip-26-0-162-233]: Local number of parameters: 131M (249.16MiB)
	[default0]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
	[default0]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: No checkpoint path provided.
	[default0]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Parametrizing model parameters using StandardParametrizator
	[default6]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=2\|ip-26-0-162-233]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
	[default6]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=2\|ip-26-0-162-233]: No checkpoint path provided.
	[default4]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: Local number of parameters: 131M (249.16MiB)
	[default4]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
	[default4]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: No checkpoint path provided.
	[default5]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=1\|ip-26-0-162-233]: Local number of parameters: 131M (249.16MiB)
	[default5]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=1\|ip-26-0-162-233]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
	[default3]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=3\|ip-26-0-162-233]: Local number of parameters: 173M (329.19MiB)
	[default5]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=1\|TP=1\|ip-26-0-162-233]: No checkpoint path provided.
	[default3]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=3\|ip-26-0-162-233]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
	[default3]:07/03/2024 22:06:44 [INFO\|DP=0\|PP=0\|TP=3\|ip-26-0-162-233]: No checkpoint path provided.
	[default0]:07/03/2024 22:06:45 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: [Optimizer Building] Using LearningRateForSP as learning rate
	[default0]:07/03/2024 22:06:45 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: [ZeRO sharding] Size of optimizer params per rank:
	[default0]:07/03/2024 22:06:45 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: [ZeRO sharding] DP Rank 0 has 173M out of 173M (100.00%) params' optimizer states
	[default0]:07/03/2024 22:06:47 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
	[default0]:07/03/2024 22:06:47 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Using `datasets` library
	[default0]:07/03/2024 22:06:47 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
	[default0]:07/03/2024 22:06:47 [WARNING\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
	[default0]:Repo card metadata block was not found. Setting CardData to empty.
	[default0]:07/03/2024 22:06:49 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: [Training Plan] There are 1 training stages
	[default0]:07/03/2024 22:06:49 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: [Stage Training Stage] start from step 1
	[default0]:07/03/2024 22:06:49 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]:
	[default0]:07/03/2024 22:06:49 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: [Start training] datetime: 2024-07-03 22:06:49.301677 \| mbs: 1 \| grad_accum: 1024 \| global_batch_size: 1024 \| sequence_length: 4096 \| train_steps: 20 \| start_iteration_step: 0 \| consumed_train_samples: 0
	[default0]:07/03/2024 22:06:49 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
	[default0]:07/03/2024 22:06:49 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 1660.89MiB. Peak allocated 1660.89MiB. Peak reserved: 1668.00MiB
	[default1]:07/03/2024 22:06:49 [WARNING\|DP=0\|PP=0\|TP=1\|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
	[default4]:Repo card metadata block was not found. Setting CardData to empty.
	[default5]:07/03/2024 22:06:49 [WARNING\|DP=0\|PP=1\|TP=1\|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
	[default4]:07/03/2024 22:06:49 [WARNING\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
	[default1]:Repo card metadata block was not found. Setting CardData to empty.
	[default5]:Repo card metadata block was not found. Setting CardData to empty.
	[default7]:07/03/2024 22:06:49 [WARNING\|DP=0\|PP=1\|TP=3\|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
	[default2]:07/03/2024 22:06:49 [WARNING\|DP=0\|PP=0\|TP=2\|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
	[default6]:07/03/2024 22:06:49 [WARNING\|DP=0\|PP=1\|TP=2\|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
	[default3]:07/03/2024 22:06:49 [WARNING\|DP=0\|PP=0\|TP=3\|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
	[default7]:Repo card metadata block was not found. Setting CardData to empty.
	[default3]:Repo card metadata block was not found. Setting CardData to empty.
	[default2]:Repo card metadata block was not found. Setting CardData to empty.
	[default6]:Repo card metadata block was not found. Setting CardData to empty.
	[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
	[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
	[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
	[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
	[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
	[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
	[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(
	[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(
	[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(
	[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
	[default0]:07/03/2024 22:08:32 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 1731.93MiB. Peak allocated 4645.52MiB. Peak reserved: 4720.00MiB
	[default2]: 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(
	[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(
	[default4]:07/03/2024 22:08:40 [INFO\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: iteration: 1 / 20 \| consumed_tokens: 4.19M \| elapsed_time_per_iteration_ms: 110K \| tokens_per_sec: 38.2K \| tokens_per_sec_per_gpu: 4.77K \| global_batch_size: 1.02K \| lm_loss: 11.1 \| lr: 0.0001 \| model_tflops_per_gpu: 43.3 \| hardware_tflops_per_gpu: 43.3 \| grad_norm: 15 \| cuda_memory_allocated: 2.44G \| cuda_max_memory_reserved: 3.18G \| hd_total_memory_tb: 312G \| hd_used_memory_tb: 66.1G \| hd_free_memory_tb: 246G
	[default0]:07/03/2024 22:08:40 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 3048.73MiB. Peak allocated 3048.73MiB. Peak reserved: 4720.00MiB
	[default4]:07/03/2024 22:10:01 [INFO\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: iteration: 2 / 20 \| consumed_tokens: 8.39M \| elapsed_time_per_iteration_ms: 81.5K \| tokens_per_sec: 51.5K \| tokens_per_sec_per_gpu: 6.43K \| global_batch_size: 1.02K \| lm_loss: 11.1 \| lr: 9.53e-05 \| model_tflops_per_gpu: 58.4 \| hardware_tflops_per_gpu: 58.4 \| grad_norm: 15.1 \| cuda_memory_allocated: 2.44G \| cuda_max_memory_reserved: 4.03G \| hd_total_memory_tb: 312G \| hd_used_memory_tb: 66.1G \| hd_free_memory_tb: 246G
	[default0]:07/03/2024 22:10:01 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 3048.73MiB. Peak allocated 5772.57MiB. Peak reserved: 5918.00MiB
	[default0]:07/03/2024 22:10:01 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 3048.73MiB. Peak allocated 3048.78MiB. Peak reserved: 5918.00MiB
	[default0]:STAGE:2024-07-03 22:11:34 1820395:1820395 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
	[default4]:07/03/2024 22:11:34 [INFO\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: iteration: 3 / 20 \| consumed_tokens: 12.6M \| elapsed_time_per_iteration_ms: 93.3K \| tokens_per_sec: 44.9K \| tokens_per_sec_per_gpu: 5.62K \| global_batch_size: 1.02K \| lm_loss: 11.4 \| lr: 9.05e-05 \| model_tflops_per_gpu: 51 \| hardware_tflops_per_gpu: 51 \| grad_norm: 106 \| cuda_memory_allocated: 2.44G \| cuda_max_memory_reserved: 4.03G \| hd_total_memory_tb: 312G \| hd_used_memory_tb: 66.1G \| hd_free_memory_tb: 246G
	[default0]:07/03/2024 22:11:34 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 3048.73MiB. Peak allocated 5772.57MiB. Peak reserved: 5918.00MiB
	[default0]:07/03/2024 22:11:34 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 3048.73MiB. Peak allocated 3048.78MiB. Peak reserved: 5918.00MiB
	[default4]:07/03/2024 22:13:40 [INFO\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: iteration: 4 / 20 \| consumed_tokens: 16.8M \| elapsed_time_per_iteration_ms: 125K \| tokens_per_sec: 33.5K \| tokens_per_sec_per_gpu: 4.18K \| global_batch_size: 1.02K \| lm_loss: 11.7 \| lr: 8.58e-05 \| model_tflops_per_gpu: 38 \| hardware_tflops_per_gpu: 38 \| grad_norm: 24.5 \| cuda_memory_allocated: 2.44G \| cuda_max_memory_reserved: 4.03G \| hd_total_memory_tb: 312G \| hd_used_memory_tb: 66.1G \| hd_free_memory_tb: 246G
	[default0]:07/03/2024 22:13:40 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 3048.73MiB. Peak allocated 5772.57MiB. Peak reserved: 5918.00MiB
	[default0]:07/03/2024 22:13:40 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 3048.73MiB. Peak allocated 3048.78MiB. Peak reserved: 5918.00MiB
	[default4]:07/03/2024 22:15:45 [INFO\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: iteration: 5 / 20 \| consumed_tokens: 21M \| elapsed_time_per_iteration_ms: 126K \| tokens_per_sec: 33.4K \| tokens_per_sec_per_gpu: 4.17K \| global_batch_size: 1.02K \| lm_loss: 10 \| lr: 8.11e-05 \| model_tflops_per_gpu: 37.8 \| hardware_tflops_per_gpu: 37.8 \| grad_norm: 11
	[default0]:07/03/2024 22:15:45 [INFO\|DP=0\|PP=0\|TP=0\|ip-26-0-162-233]: Memory usage: 3048.73MiB. Peak allocated 5772.57MiB. Peak reserved: 5918.00MiB
	[default4]:07/03/2024 22:17:54 [INFO\|DP=0\|PP=1\|TP=0\|ip-26-0-162-233]: iteration: 6 / 20 \| consumed_tokens: 25.2M \| elapsed_time_per_iteration_ms: 128K \| tokens_per_sec: 32.7K \| tokens_per_sec_per_gpu: 4.09K \| global_batch_size: 1.02K \| lm_loss: 9.46 \| lr: 7.63e-05 \| model_tflops_per_gpu: 37.1 \| hardware_tflops_per_gpu: 37.1 \| grad_norm: 7.21
	[default0]:STAGE:2024-07-03 22:24:01 1820395:1820395 ActivityProfilerController.cpp:320] Completed Stage: Collection
	[default0]:STAGE:2024-07-03 22:24:46 1820395:1820395 ActivityProfilerController.cpp:324] Completed Stage: Post Processing
	[default7]:[rank7]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600082 milliseconds before timing out.
	[default3]:[rank3]:[E ProcessGroupNCCL.cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=700453, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600033 milliseconds before timing out.
	[default6]:[rank6]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600087 milliseconds before timing out.
	[default4]:[rank4]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600088 milliseconds before timing out.
	[default1]:[rank1]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=700453, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600035 milliseconds before timing out.
	[default5]:[rank5]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600030 milliseconds before timing out.
	[default2]:[rank2]:[E ProcessGroupNCCL.cpp:563] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=700453, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=2097152, Timeout(ms)=600000) ran for 600071 milliseconds before timing out.
	[default7]:[rank7]: Traceback (most recent call last):
	[default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
	[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 278, 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.
	[default6]:[rank6]: Traceback (most recent call last):
	[default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
	[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 278, 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.
	[default4]:[rank4]: Traceback (most recent call last):
	[default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
	[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 278, 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.
	[default5]:[rank5]: Traceback (most recent call last):
	[default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
	[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 278, 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.
	[default6]:[rank6]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 55306, last enqueued NCCL work: 55306, last completed NCCL work: 55305.
	[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=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600087 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 (0x7f02fed17897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f02ffff0c62 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 (0x7f02ffff5a80 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 (0x7f02ffff6dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default6]:frame #4: <unknown function> + 0xd3e95 (0x7f034ba8fe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default6]:frame #5: <unknown function> + 0x8609 (0x7f0350ad6609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default6]:frame #6: clone + 0x43 (0x7f03508a1353 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=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600087 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 (0x7f02fed17897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f02ffff0c62 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 (0x7f02ffff5a80 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 (0x7f02ffff6dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default6]:frame #4: <unknown function> + 0xd3e95 (0x7f034ba8fe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default6]:frame #5: <unknown function> + 0x8609 (0x7f0350ad6609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default6]:frame #6: clone + 0x43 (0x7f03508a1353 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 (0x7f02fed17897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
	[default6]:frame #1: <unknown function> + 0xe32119 (0x7f02ffc7a119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default6]:frame #2: <unknown function> + 0xd3e95 (0x7f034ba8fe95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default6]:frame #3: <unknown function> + 0x8609 (0x7f0350ad6609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default6]:frame #4: clone + 0x43 (0x7f03508a1353 in /lib/x86_64-linux-gnu/libc.so.6)
	[default6]:
	[default4]:[rank4]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 55306, last enqueued NCCL work: 55306, last completed NCCL work: 55305.
	[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=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600088 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 (0x7f4b7e151897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f4b7f42ac62 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 (0x7f4b7f42fa80 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 (0x7f4b7f430dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default4]:frame #4: <unknown function> + 0xd3e95 (0x7f4bcaec9e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default4]:frame #5: <unknown function> + 0x8609 (0x7f4bcff10609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default4]:frame #6: clone + 0x43 (0x7f4bcfcdb353 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=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600088 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 (0x7f4b7e151897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f4b7f42ac62 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 (0x7f4b7f42fa80 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 (0x7f4b7f430dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default4]:frame #4: <unknown function> + 0xd3e95 (0x7f4bcaec9e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default4]:frame #5: <unknown function> + 0x8609 (0x7f4bcff10609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default4]:frame #6: clone + 0x43 (0x7f4bcfcdb353 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 (0x7f4b7e151897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
	[default4]:frame #1: <unknown function> + 0xe32119 (0x7f4b7f0b4119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default4]:frame #2: <unknown function> + 0xd3e95 (0x7f4bcaec9e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default4]:frame #3: <unknown function> + 0x8609 (0x7f4bcff10609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default4]:frame #4: clone + 0x43 (0x7f4bcfcdb353 in /lib/x86_64-linux-gnu/libc.so.6)
	[default4]:
	[default7]:[rank7]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 55306, last enqueued NCCL work: 55306, last completed NCCL work: 55305.
	[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=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600082 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 (0x7f92505da897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f92518b3c62 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 (0x7f92518b8a80 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 (0x7f92518b9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default7]:frame #4: <unknown function> + 0xd3e95 (0x7f929d352e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default7]:frame #5: <unknown function> + 0x8609 (0x7f92a2399609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default7]:frame #6: clone + 0x43 (0x7f92a2164353 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=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600082 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 (0x7f92505da897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f92518b3c62 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 (0x7f92518b8a80 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 (0x7f92518b9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default7]:frame #4: <unknown function> + 0xd3e95 (0x7f929d352e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default7]:frame #5: <unknown function> + 0x8609 (0x7f92a2399609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default7]:frame #6: clone + 0x43 (0x7f92a2164353 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 (0x7f92505da897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
	[default7]:frame #1: <unknown function> + 0xe32119 (0x7f925153d119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default7]:frame #2: <unknown function> + 0xd3e95 (0x7f929d352e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default7]:frame #3: <unknown function> + 0x8609 (0x7f92a2399609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default7]:frame #4: clone + 0x43 (0x7f92a2164353 in /lib/x86_64-linux-gnu/libc.so.6)
	[default7]:
	[default5]:[rank5]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 1] Timeout at NCCL work: 55306, last enqueued NCCL work: 55306, last completed NCCL work: 55305.
	[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=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600030 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 (0x7f1cde04f897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f1cdf328c62 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 (0x7f1cdf32da80 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 (0x7f1cdf32edcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default5]:frame #4: <unknown function> + 0xd3e95 (0x7f1d2adc7e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default5]:frame #5: <unknown function> + 0x8609 (0x7f1d2fe0e609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default5]:frame #6: clone + 0x43 (0x7f1d2fbd9353 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=55306, OpType=RECV, NumelIn=7, NumelOut=7, Timeout(ms)=600000) ran for 600030 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 (0x7f1cde04f897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f1cdf328c62 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 (0x7f1cdf32da80 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 (0x7f1cdf32edcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default5]:frame #4: <unknown function> + 0xd3e95 (0x7f1d2adc7e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default5]:frame #5: <unknown function> + 0x8609 (0x7f1d2fe0e609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default5]:frame #6: clone + 0x43 (0x7f1d2fbd9353 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 (0x7f1cde04f897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
	[default5]:frame #1: <unknown function> + 0xe32119 (0x7f1cdefb2119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
	[default5]:frame #2: <unknown function> + 0xd3e95 (0x7f1d2adc7e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
	[default5]:frame #3: <unknown function> + 0x8609 (0x7f1d2fe0e609 in /lib/x86_64-linux-gnu/libpthread.so.0)
	[default5]:frame #4: clone + 0x43 (0x7f1d2fbd9353 in /lib/x86_64-linux-gnu/libc.so.6)
	[default5]:
	W0703 22:27:58.925000 140536135579456 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1820395 closing signal SIGTERM
	W0703 22:27:58.925000 140536135579456 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1820396 closing signal SIGTERM
	W0703 22:27:58.925000 140536135579456 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1820397 closing signal SIGTERM
	W0703 22:27:58.925000 140536135579456 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1820398 closing signal SIGTERM
	E0703 22:28:08.797000 140536135579456 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: -6) local_rank: 4 (pid: 1820399) 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 <module>
	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 : 2024-07-03_22:27:58
	host : ip-26-0-162-233.ec2.internal
	rank : 5 (local_rank: 5)
	exitcode : -6 (pid: 1820400)
	error_file: <N/A>
	traceback : Signal 6 (SIGABRT) received by PID 1820400
	[2]:
	time : 2024-07-03_22:27:58
	host : ip-26-0-162-233.ec2.internal
	rank : 6 (local_rank: 6)
	exitcode : -6 (pid: 1820401)
	error_file: <N/A>
	traceback : Signal 6 (SIGABRT) received by PID 1820401
	[3]:
	time : 2024-07-03_22:27:58
	host : ip-26-0-162-233.ec2.internal
	rank : 7 (local_rank: 7)
	exitcode : -6 (pid: 1820402)
	error_file: <N/A>
	traceback : Signal 6 (SIGABRT) received by PID 1820402
	------------------------------------------------------------
	Root Cause (first observed failure):
	[0]:
	time : 2024-07-03_22:27:58
	host : ip-26-0-162-233.ec2.internal
	rank : 4 (local_rank: 4)
	exitcode : -6 (pid: 1820399)
	error_file: <N/A>
	traceback : Signal 6 (SIGABRT) received by PID 1820399
	============================================================
	srun: error: ip-26-0-162-233: 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.