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========================
START TIME: Tue Jul 2 14:58:42 UTC 2024
python3 version = Python 3.10.14
========================
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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 14:58:50.530000 140566608136000 torch/distributed/run.py:757]
W0702 14:58:50.530000 140566608136000 torch/distributed/run.py:757] *****************************************
W0702 14:58:50.530000 140566608136000 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 14:58:50.530000 140566608136000 torch/distributed/run.py:757] *****************************************
W0702 14:58:50.893000 140559373690688 torch/distributed/run.py:757]
W0702 14:58:50.893000 140559373690688 torch/distributed/run.py:757] *****************************************
W0702 14:58:50.893000 140559373690688 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 14:58:50.893000 140559373690688 torch/distributed/run.py:757] *****************************************
[default0]:07/02/2024 14:59:14 [WARNING|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Vocab Size Padding] Padded vocab (size: 50257) with 1 dummy tokens (new size: 50258)
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Config:
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: run='%date_%jobid',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: seed=42,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: step=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: consumed_train_samples=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: benchmark_csv_path=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: ignore_sanity_checks=True),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: parallelism=ParallelismArgs(dp=2,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pp=4,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tp=2,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7f7eccb24910>,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tp_linear_async_communication=False,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: expert_parallel_size=1),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: eos_token_id=2,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hidden_act='silu',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hidden_size=2048,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: initializer_range=0.02,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: intermediate_size=4096,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: is_llama_config=True,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: max_position_embeddings=4096,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_attention_heads=32,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_hidden_layers=24,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_key_value_heads=32,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pad_token_id=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pretraining_tp=1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rms_norm_eps=1e-05,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rope_scaling=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rope_theta=10000.0,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tie_word_embeddings=True,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: use_cache=True,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: vocab_size=50258),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: init_method=RandomInit(std=0.025),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: dtype=torch.bfloat16,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: make_vocab_size_divisible_by=1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: ddp_bucket_cap_mb=25),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tokenizer_revision=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tokenizer_max_length=None),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: checkpoint_interval=100000,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: save_initial_state=False,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: resume_checkpoint_path=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: checkpoints_path_is_shared_file_system=False),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: logging=LoggingArgs(log_level='info',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: log_level_replica='info',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: iteration_step_info_interval=1),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tokens=TokensArgs(sequence_length=4096,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: train_steps=20,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: micro_batch_size=1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: batch_accumulation_per_replica=512,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: val_check_interval=-1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: limit_val_batches=0,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: limit_test_batches=0),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: adam_beta1=0.9,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: adam_beta2=0.95,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: torch_adam_is_fused=True,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: name='adamW'),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: zero_stage=1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: weight_decay=0.01,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: clip_grad=1.0,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: accumulate_grad_in_fp32=True,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_warmup_steps=1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_warmup_style='linear',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_decay_style='linear',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_decay_steps=19,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_decay_starting_step=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: min_decay_lr=1e-05)),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: start_training_step=1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hf_dataset_splits='train',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hf_dataset_config_name=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: dataset_processing_num_proc_per_process=64,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: dataset_overwrite_cache=False,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: text_column_name='text'),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: seed=42,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_loading_workers=32))],
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-2_tp-2_pp-4_mbz-1')),
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lighteval=None)
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Model Config:
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: LlamaConfig(bos_token_id=1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: eos_token_id=2,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hidden_act='silu',
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hidden_size=2048,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: initializer_range=0.02,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: intermediate_size=4096,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: is_llama_config=True,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: max_position_embeddings=4096,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_attention_heads=32,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_hidden_layers=24,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_key_value_heads=32,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pad_token_id=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pretraining_tp=1,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rms_norm_eps=1e-05,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rope_scaling=None,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rope_theta=10000.0,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tie_word_embeddings=True,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: use_cache=True,
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: vocab_size=50258)
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Building model..
[default0]:07/02/2024 14:59:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Setting PP block ranks...
[default4]:07/02/2024 14:59:27 [INFO|DP=0|PP=1|TP=0|ip-26-0-171-56]: Local number of parameters: 147M (280.05MiB)
[default4]:07/02/2024 14:59:27 [INFO|DP=0|PP=1|TP=0|ip-26-0-171-56]: [After model building] Memory usage: 287.07MiB. Peak allocated: 289.10MiB Peak reserved: 302.00MiB
[default4]:07/02/2024 14:59:27 [INFO|DP=0|PP=1|TP=0|ip-26-0-171-56]: No checkpoint path provided.
[default0]:07/02/2024 14:59:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Total number of parameters: 1.21G (2313.02MiB)
[default0]:07/02/2024 14:59:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Local number of parameters: 198M (378.21MiB)
[default0]:07/02/2024 14:59:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [After model building] Memory usage: 385.23MiB. Peak allocated: 387.26MiB Peak reserved: 402.00MiB
[default0]:07/02/2024 14:59:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: No checkpoint path provided.
[default0]:07/02/2024 14:59:27 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Parametrizing model parameters using StandardParametrizator
[default2]:07/02/2024 14:59:27 [INFO|DP=1|PP=0|TP=0|ip-26-0-171-56]: No checkpoint path provided.
[default1]:07/02/2024 14:59:27 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-56]: Local number of parameters: 198M (378.21MiB)
[default3]:07/02/2024 14:59:27 [INFO|DP=1|PP=0|TP=1|ip-26-0-171-56]: No checkpoint path provided.
[default1]:07/02/2024 14:59:27 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-56]: [After model building] Memory usage: 385.23MiB. Peak allocated: 387.26MiB Peak reserved: 402.00MiB
[default1]:07/02/2024 14:59:27 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-56]: No checkpoint path provided.
[default6]:07/02/2024 14:59:27 [INFO|DP=1|PP=1|TP=0|ip-26-0-171-56]: No checkpoint path provided.
[default5]:07/02/2024 14:59:27 [INFO|DP=0|PP=1|TP=1|ip-26-0-171-56]: Local number of parameters: 147M (280.05MiB)
[default5]:07/02/2024 14:59:27 [INFO|DP=0|PP=1|TP=1|ip-26-0-171-56]: [After model building] Memory usage: 287.07MiB. Peak allocated: 289.10MiB Peak reserved: 302.00MiB
[default5]:07/02/2024 14:59:27 [INFO|DP=0|PP=1|TP=1|ip-26-0-171-56]: No checkpoint path provided.
[default0]:07/02/2024 14:59:27 [INFO|DP=0|PP=2|TP=0|ip-26-0-175-132]: Local number of parameters: 126M (240.05MiB)
[default0]:07/02/2024 14:59:27 [INFO|DP=0|PP=2|TP=0|ip-26-0-175-132]: [After model building] Memory usage: 246.06MiB. Peak allocated: 248.09MiB Peak reserved: 262.00MiB
[default0]:07/02/2024 14:59:27 [INFO|DP=0|PP=2|TP=0|ip-26-0-175-132]: No checkpoint path provided.
[default1]:07/02/2024 14:59:27 [INFO|DP=0|PP=2|TP=1|ip-26-0-175-132]: Local number of parameters: 126M (240.05MiB)
[default1]:07/02/2024 14:59:27 [INFO|DP=0|PP=2|TP=1|ip-26-0-175-132]: [After model building] Memory usage: 246.06MiB. Peak allocated: 248.09MiB Peak reserved: 262.00MiB
[default1]:07/02/2024 14:59:27 [INFO|DP=0|PP=2|TP=1|ip-26-0-175-132]: No checkpoint path provided.
[default3]:07/02/2024 14:59:27 [INFO|DP=1|PP=2|TP=1|ip-26-0-175-132]: No checkpoint path provided.
[default7]:07/02/2024 14:59:27 [INFO|DP=1|PP=1|TP=1|ip-26-0-171-56]: No checkpoint path provided.
[default6]:07/02/2024 14:59:27 [INFO|DP=1|PP=3|TP=0|ip-26-0-175-132]: No checkpoint path provided.
[default4]:07/02/2024 14:59:27 [INFO|DP=0|PP=3|TP=0|ip-26-0-175-132]: Local number of parameters: 135M (258.20MiB)
[default4]:07/02/2024 14:59:27 [INFO|DP=0|PP=3|TP=0|ip-26-0-175-132]: [After model building] Memory usage: 262.21MiB. Peak allocated: 264.24MiB Peak reserved: 280.00MiB
[default4]:07/02/2024 14:59:27 [INFO|DP=0|PP=3|TP=0|ip-26-0-175-132]: No checkpoint path provided.
[default5]:07/02/2024 14:59:27 [INFO|DP=0|PP=3|TP=1|ip-26-0-175-132]: Local number of parameters: 135M (258.20MiB)
[default5]:07/02/2024 14:59:27 [INFO|DP=0|PP=3|TP=1|ip-26-0-175-132]: [After model building] Memory usage: 262.21MiB. Peak allocated: 264.24MiB Peak reserved: 280.00MiB
[default5]:07/02/2024 14:59:27 [INFO|DP=0|PP=3|TP=1|ip-26-0-175-132]: No checkpoint path provided.
[default2]:07/02/2024 14:59:27 [INFO|DP=1|PP=2|TP=0|ip-26-0-175-132]: No checkpoint path provided.
[default7]:07/02/2024 14:59:27 [INFO|DP=1|PP=3|TP=1|ip-26-0-175-132]: No checkpoint path provided.
[default0]:07/02/2024 14:59:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/02/2024 14:59:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/02/2024 14:59:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [ZeRO sharding] DP Rank 0 has 99.1M out of 198M (50.00%) params' optimizer states
[default0]:07/02/2024 14:59:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [ZeRO sharding] DP Rank 1 has 99.1M out of 198M (50.00%) params' optimizer states
[default0]:07/02/2024 14:59:31 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/02/2024 14:59:31 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Using `datasets` library
[default0]:07/02/2024 14:59:31 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
[default0]:07/02/2024 14:59:31 [WARNING|DP=0|PP=0|TP=0|ip-26-0-171-56]: 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 14:59:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Training Plan] There are 1 training stages
[default0]:07/02/2024 14:59:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Stage Training Stage] start from step 1
[default0]:07/02/2024 14:59:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]:
[default0]:07/02/2024 14:59:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Start training] datetime: 2024-07-02 14:59:33.747803 | mbs: 1 | 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 14:59:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/02/2024 14:59:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 1519.87MiB. Peak allocated 1519.87MiB. Peak reserved: 1540.00MiB
[default4]:07/02/2024 14:59:33 [WARNING|DP=0|PP=1|TP=0|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/02/2024 14:59:33 [WARNING|DP=0|PP=0|TP=1|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/02/2024 14:59:33 [WARNING|DP=1|PP=0|TP=0|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/02/2024 14:59:33 [WARNING|DP=1|PP=0|TP=1|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/02/2024 14:59:33 [WARNING|DP=0|PP=1|TP=1|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/02/2024 14:59:33 [WARNING|DP=0|PP=2|TP=1|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/02/2024 14:59:33 [WARNING|DP=0|PP=2|TP=0|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/02/2024 14:59:33 [WARNING|DP=1|PP=2|TP=1|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/02/2024 14:59:33 [WARNING|DP=1|PP=1|TP=1|ip-26-0-171-56]: 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.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/02/2024 14:59:33 [WARNING|DP=1|PP=3|TP=0|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/02/2024 14:59:33 [WARNING|DP=0|PP=3|TP=0|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/02/2024 14:59:33 [WARNING|DP=1|PP=2|TP=0|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/02/2024 14:59:33 [WARNING|DP=1|PP=3|TP=1|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/02/2024 14:59:33 [WARNING|DP=1|PP=1|TP=0|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/02/2024 14:59:34 [WARNING|DP=0|PP=3|TP=1|ip-26-0-175-132]: 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
[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
[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
[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
[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
[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
[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
[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
[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
[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
[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(
[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(
[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(
[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(
[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(
[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
[default3]: 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(
[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(
[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(
[default0]:07/02/2024 15:01:04 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 1587.41MiB. Peak allocated 6288.74MiB. Peak reserved: 6390.00MiB
[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]:/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(
[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]:/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(
[default0]:07/02/2024 15:01:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 2343.86MiB. Peak allocated 3292.07MiB. Peak reserved: 7340.00MiB
[default4]:07/02/2024 15:01:09 [INFO|DP=0|PP=3|TP=0|ip-26-0-175-132]: iteration: 1 / 20 | consumed_tokens: 4.19M | elapsed_time_per_iteration_ms: 88.7K | tokens_per_sec: 47.3K | tokens_per_sec_per_gpu: 2.95K | global_batch_size: 1.02K | lm_loss: 11.2 | lr: 0.0001 | model_tflops_per_gpu: 26.8 | hardware_tflops_per_gpu: 26.8 | grad_norm: 14.8 | cuda_memory_allocated: 1.7G | cuda_max_memory_reserved: 3.31G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.5G | hd_free_memory_tb: 247G
[default0]:07/02/2024 15:02:04 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 2343.86MiB. Peak allocated 6879.48MiB. Peak reserved: 7340.00MiB
[default0]:07/02/2024 15:02:04 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 2343.86MiB. Peak allocated 3292.07MiB. Peak reserved: 7340.00MiB
[default4]:07/02/2024 15:02:04 [INFO|DP=0|PP=3|TP=0|ip-26-0-175-132]: iteration: 2 / 20 | consumed_tokens: 8.39M | elapsed_time_per_iteration_ms: 54.4K | tokens_per_sec: 77.1K | tokens_per_sec_per_gpu: 4.82K | global_batch_size: 1.02K | lm_loss: 11.2 | lr: 9.53e-05 | model_tflops_per_gpu: 43.7 | hardware_tflops_per_gpu: 43.7 | grad_norm: 14.9 | cuda_memory_allocated: 1.7G | cuda_max_memory_reserved: 3.32G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.5G | hd_free_memory_tb: 247G
[default0]:07/02/2024 15:03:02 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 2343.86MiB. Peak allocated 6879.48MiB. Peak reserved: 7340.00MiB
[default0]:STAGE:2024-07-02 15:03:02 2994541:2994541 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
[default4]:07/02/2024 15:03:02 [INFO|DP=0|PP=3|TP=0|ip-26-0-175-132]: iteration: 3 / 20 | consumed_tokens: 12.6M | elapsed_time_per_iteration_ms: 58.1K | tokens_per_sec: 72.1K | tokens_per_sec_per_gpu: 4.51K | global_batch_size: 1.02K | lm_loss: 9.53 | lr: 9.05e-05 | model_tflops_per_gpu: 40.9 | hardware_tflops_per_gpu: 40.9 | grad_norm: 35.8 | cuda_memory_allocated: 1.7G | cuda_max_memory_reserved: 3.32G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.5G | hd_free_memory_tb: 247G
[default0]:07/02/2024 15:03:02 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 2343.86MiB. Peak allocated 3292.07MiB. Peak reserved: 7340.00MiB
[default0]:07/02/2024 15:04:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 2343.86MiB. Peak allocated 6879.48MiB. Peak reserved: 7340.00MiB
[default0]:07/02/2024 15:04:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 2343.86MiB. Peak allocated 3292.07MiB. Peak reserved: 7340.00MiB
[default4]:07/02/2024 15:04:01 [INFO|DP=0|PP=3|TP=0|ip-26-0-175-132]: iteration: 4 / 20 | consumed_tokens: 16.8M | elapsed_time_per_iteration_ms: 59K | tokens_per_sec: 71.1K | tokens_per_sec_per_gpu: 4.45K | global_batch_size: 1.02K | lm_loss: 12.3 | lr: 8.58e-05 | model_tflops_per_gpu: 40.3 | hardware_tflops_per_gpu: 40.3 | grad_norm: 37.3 | cuda_memory_allocated: 1.7G | cuda_max_memory_reserved: 3.32G | hd_total_memory_tb: 312G | hd_used_memory_tb: 65.5G | hd_free_memory_tb: 247G
[default0]:07/02/2024 15:05:04 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 2343.86MiB. Peak allocated 6879.48MiB. Peak reserved: 7340.00MiB
[default4]:07/02/2024 15:05:04 [INFO|DP=0|PP=3|TP=0|ip-26-0-175-132]: iteration: 5 / 20 | consumed_tokens: 21M | elapsed_time_per_iteration_ms: 63.2K | tokens_per_sec: 66.4K | tokens_per_sec_per_gpu: 4.15K | global_batch_size: 1.02K | lm_loss: 9.94 | lr: 8.11e-05 | model_tflops_per_gpu: 37.6 | hardware_tflops_per_gpu: 37.6 | grad_norm: 14
[default4]:07/02/2024 15:06:06 [INFO|DP=0|PP=3|TP=0|ip-26-0-175-132]: iteration: 6 / 20 | consumed_tokens: 25.2M | elapsed_time_per_iteration_ms: 61.6K | tokens_per_sec: 68.1K | tokens_per_sec_per_gpu: 4.25K | global_batch_size: 1.02K | lm_loss: 9.44 | lr: 7.63e-05 | model_tflops_per_gpu: 38.6 | hardware_tflops_per_gpu: 38.6 | grad_norm: 8.13
[default0]:STAGE:2024-07-02 15:07:50 2994541:2994541 ActivityProfilerController.cpp:320] Completed Stage: Collection
[default0]:STAGE:2024-07-02 15:08:06 2994541:2994541 ActivityProfilerController.cpp:324] Completed Stage: Post Processing
[default1]:[rank1]:[E ProcessGroupNCCL.cpp:563] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=178199, OpType=_REDUCE_SCATTER_BASE, NumelIn=8388608, NumelOut=4194304, Timeout(ms)=600000) ran for 600028 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 600024 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 600017 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 600018 milliseconds before timing out.
[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 600016 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 600088 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 600077 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 <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 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.
[default0]:[rank8]: Traceback (most recent call last):
[default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[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.
[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 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.
[default5]:[rank13]: Traceback (most recent call last):
[default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[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 <module>
[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.
[default1]:[rank9]: Traceback (most recent call last):
[default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[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.
[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 600077 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 (0x7f681be8c897 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 (0x7f681d165c62 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 (0x7f681d16aa80 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 (0x7f681d16bdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default4]:frame #4: <unknown function> + 0xd3e95 (0x7f6868c04e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default4]:frame #5: <unknown function> + 0x8609 (0x7f686dc4b609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default4]:frame #6: clone + 0x43 (0x7f686da16353 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 600077 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 (0x7f681be8c897 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 (0x7f681d165c62 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 (0x7f681d16aa80 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 (0x7f681d16bdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default4]:frame #4: <unknown function> + 0xd3e95 (0x7f6868c04e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default4]:frame #5: <unknown function> + 0x8609 (0x7f686dc4b609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default4]:frame #6: clone + 0x43 (0x7f686da16353 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 (0x7f681be8c897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default4]:frame #1: <unknown function> + 0xe32119 (0x7f681cdef119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default4]:frame #2: <unknown function> + 0xd3e95 (0x7f6868c04e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default4]:frame #3: <unknown function> + 0x8609 (0x7f686dc4b609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default4]:frame #4: clone + 0x43 (0x7f686da16353 in /lib/x86_64-linux-gnu/libc.so.6)
[default4]:
[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 600024 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 (0x7f35d722b897 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 (0x7f35d8504c62 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 (0x7f35d8509a80 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 (0x7f35d850adcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default4]:frame #4: <unknown function> + 0xd3e95 (0x7f3623fa3e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default4]:frame #5: <unknown function> + 0x8609 (0x7f3628fea609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default4]:frame #6: clone + 0x43 (0x7f3628db5353 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 600024 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 (0x7f35d722b897 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 (0x7f35d8504c62 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 (0x7f35d8509a80 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 (0x7f35d850adcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default4]:frame #4: <unknown function> + 0xd3e95 (0x7f3623fa3e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default4]:frame #5: <unknown function> + 0x8609 (0x7f3628fea609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default4]:frame #6: clone + 0x43 (0x7f3628db5353 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 (0x7f35d722b897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default4]:frame #1: <unknown function> + 0xe32119 (0x7f35d818e119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default4]:frame #2: <unknown function> + 0xd3e95 (0x7f3623fa3e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default4]:frame #3: <unknown function> + 0x8609 (0x7f3628fea609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default4]:frame #4: clone + 0x43 (0x7f3628db5353 in /lib/x86_64-linux-gnu/libc.so.6)
[default4]:
[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 600016 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 (0x7fa486b9b897 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 (0x7fa487e74c62 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 (0x7fa487e79a80 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 (0x7fa487e7adcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #4: <unknown function> + 0xd3e95 (0x7fa4d3913e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default5]:frame #5: <unknown function> + 0x8609 (0x7fa4d895a609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default5]:frame #6: clone + 0x43 (0x7fa4d8725353 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 600016 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 (0x7fa486b9b897 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 (0x7fa487e74c62 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 (0x7fa487e79a80 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 (0x7fa487e7adcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #4: <unknown function> + 0xd3e95 (0x7fa4d3913e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default5]:frame #5: <unknown function> + 0x8609 (0x7fa4d895a609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default5]:frame #6: clone + 0x43 (0x7fa4d8725353 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 (0x7fa486b9b897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default5]:frame #1: <unknown function> + 0xe32119 (0x7fa487afe119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #2: <unknown function> + 0xd3e95 (0x7fa4d3913e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default5]:frame #3: <unknown function> + 0x8609 (0x7fa4d895a609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default5]:frame #4: clone + 0x43 (0x7fa4d8725353 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 600017 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 (0x7f419e77d897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f419fa56c62 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 (0x7f419fa5ba80 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 (0x7f419fa5cdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #4: <unknown function> + 0xd3e95 (0x7f41eb4f5e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default0]:frame #5: <unknown function> + 0x8609 (0x7f41f053c609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default0]:frame #6: clone + 0x43 (0x7f41f0307353 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 600017 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 (0x7f419e77d897 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<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f419fa56c62 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 (0x7f419fa5ba80 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 (0x7f419fa5cdcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #4: <unknown function> + 0xd3e95 (0x7f41eb4f5e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default0]:frame #5: <unknown function> + 0x8609 (0x7f41f053c609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default0]:frame #6: clone + 0x43 (0x7f41f0307353 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 (0x7f419e77d897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default0]:frame #1: <unknown function> + 0xe32119 (0x7f419f6e0119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default0]:frame #2: <unknown function> + 0xd3e95 (0x7f41eb4f5e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default0]:frame #3: <unknown function> + 0x8609 (0x7f41f053c609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default0]:frame #4: clone + 0x43 (0x7f41f0307353 in /lib/x86_64-linux-gnu/libc.so.6)
[default0]:
[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 600088 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 (0x7fabf655a897 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 (0x7fabf7833c62 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 (0x7fabf7838a80 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 (0x7fabf7839dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #4: <unknown function> + 0xd3e95 (0x7fac432d2e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default5]:frame #5: <unknown function> + 0x8609 (0x7fac48319609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default5]:frame #6: clone + 0x43 (0x7fac480e4353 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 600088 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 (0x7fabf655a897 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 (0x7fabf7833c62 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 (0x7fabf7838a80 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 (0x7fabf7839dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #4: <unknown function> + 0xd3e95 (0x7fac432d2e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default5]:frame #5: <unknown function> + 0x8609 (0x7fac48319609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default5]:frame #6: clone + 0x43 (0x7fac480e4353 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 (0x7fabf655a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default5]:frame #1: <unknown function> + 0xe32119 (0x7fabf74bd119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #2: <unknown function> + 0xd3e95 (0x7fac432d2e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default5]:frame #3: <unknown function> + 0x8609 (0x7fac48319609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default5]:frame #4: clone + 0x43 (0x7fac480e4353 in /lib/x86_64-linux-gnu/libc.so.6)
[default5]:
[default1]:[rank9]:[E ProcessGroupNCCL.cpp:1537] [PG 4 Rank 2] Timeout at NCCL work: 55299, last enqueued NCCL work: 55299, last completed NCCL work: 55298.
[default1]:[rank9]:[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.
[default1]:[rank9]:[E ProcessGroupNCCL.cpp:583] [Rank 2] To avoid data inconsistency, we are taking the entire process down.
[default1]:[rank9]:[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 600018 milliseconds before timing out.
[default1]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default1]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f38b951a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default1]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f38ba7f3c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f38ba7f8a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f38ba7f9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #4: <unknown function> + 0xd3e95 (0x7f3906292e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #5: <unknown function> + 0x8609 (0x7f390b2d9609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #6: clone + 0x43 (0x7f390b0a4353 in /lib/x86_64-linux-gnu/libc.so.6)
[default1]:
[default1]:terminate called after throwing an instance of 'c10::DistBackendError'
[default1]: 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 600018 milliseconds before timing out.
[default1]:Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:565 (most recent call first):
[default1]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f38b951a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default1]:frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1d2 (0x7f38ba7f3c62 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x1a0 (0x7f38ba7f8a80 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x10c (0x7f38ba7f9dcc in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #4: <unknown function> + 0xd3e95 (0x7f3906292e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #5: <unknown function> + 0x8609 (0x7f390b2d9609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #6: clone + 0x43 (0x7f390b0a4353 in /lib/x86_64-linux-gnu/libc.so.6)
[default1]:
[default1]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1418 (most recent call first):
[default1]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f38b951a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default1]:frame #1: <unknown function> + 0xe32119 (0x7f38ba47d119 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default1]:frame #2: <unknown function> + 0xd3e95 (0x7f3906292e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default1]:frame #3: <unknown function> + 0x8609 (0x7f390b2d9609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default1]:frame #4: clone + 0x43 (0x7f390b0a4353 in /lib/x86_64-linux-gnu/libc.so.6)
[default1]:
W0702 15:16:12.795000 140559373690688 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 9962 closing signal SIGTERM
W0702 15:16:12.795000 140559373690688 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 9963 closing signal SIGTERM
W0702 15:16:12.796000 140559373690688 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 9966 closing signal SIGTERM
W0702 15:16:12.798000 140559373690688 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 9967 closing signal SIGTERM
W0702 15:16:12.807000 140566608136000 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2994541 closing signal SIGTERM
W0702 15:16:12.812000 140566608136000 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2994542 closing signal SIGTERM
W0702 15:16:12.816000 140566608136000 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2994543 closing signal SIGTERM
W0702 15:16:12.821000 140566608136000 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2994544 closing signal SIGTERM
W0702 15:16:12.826000 140566608136000 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2994547 closing signal SIGTERM
W0702 15:16:12.827000 140566608136000 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2994548 closing signal SIGTERM
E0702 15:16:15.098000 140559373690688 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: -6) local_rank: 0 (pid: 9960) 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 : 2024-07-02_15:16:12
host : ip-26-0-175-132.ec2.internal
rank : 9 (local_rank: 1)
exitcode : -6 (pid: 9961)
error_file: <N/A>
traceback : Signal 6 (SIGABRT) received by PID 9961
[2]:
time : 2024-07-02_15:16:12
host : ip-26-0-175-132.ec2.internal
rank : 12 (local_rank: 4)
exitcode : -6 (pid: 9964)
error_file: <N/A>
traceback : Signal 6 (SIGABRT) received by PID 9964
[3]:
time : 2024-07-02_15:16:12
host : ip-26-0-175-132.ec2.internal
rank : 13 (local_rank: 5)
exitcode : -6 (pid: 9965)
error_file: <N/A>
traceback : Signal 6 (SIGABRT) received by PID 9965
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
time : 2024-07-02_15:16:12
host : ip-26-0-175-132.ec2.internal
rank : 8 (local_rank: 0)
exitcode : -6 (pid: 9960)
error_file: <N/A>
traceback : Signal 6 (SIGABRT) received by PID 9960
============================================================
srun: error: ip-26-0-175-132: task 1: Exited with exit code 1
E0702 15:16:18.681000 140566608136000 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: -6) local_rank: 4 (pid: 2994545) 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 : 2024-07-02_15:16:12
host : ip-26-0-171-56.ec2.internal
rank : 5 (local_rank: 5)
exitcode : -6 (pid: 2994546)
error_file: <N/A>
traceback : Signal 6 (SIGABRT) received by PID 2994546
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
time : 2024-07-02_15:16:12
host : ip-26-0-171-56.ec2.internal
rank : 4 (local_rank: 4)
exitcode : -6 (pid: 2994545)
error_file: <N/A>
traceback : Signal 6 (SIGABRT) received by PID 2994545
============================================================
srun: error: ip-26-0-171-56: 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.
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