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========================
START TIME: Wed Jul  3 21:09:37 UTC 2024
python3 version = Python 3.10.14
========================
The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.
Token is valid (permission: write).
Your token has been saved to /admin/home/ferdinand_mom/.cache/huggingface/token
Login successful
Already on 'bench_cluster'
M	examples/config_tiny_llama.py
M	examples/config_tiny_llama.yaml
M	examples/train_tiny_llama.sh
M	src/nanotron/models/llama.py
M	src/nanotron/trainer.py
Your branch is up to date with 'origin/bench_cluster'.
Job status: RUNNING
W0703 21:09:39.763000 140415295817536 torch/distributed/run.py:757] 
W0703 21:09:39.763000 140415295817536 torch/distributed/run.py:757] *****************************************
W0703 21:09:39.763000 140415295817536 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
W0703 21:09:39.763000 140415295817536 torch/distributed/run.py:757] *****************************************
[default0]:07/03/2024 21:09:56 [WARNING|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Vocab Size Padding] Padded vocab (size: 50257) with 3 dummy tokens (new size: 50260)
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Config:
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            run='%date_%jobid',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            seed=42,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            step=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            consumed_train_samples=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            benchmark_csv_path=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            ignore_sanity_checks=True),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        parallelism=ParallelismArgs(dp=1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    pp=2,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    tp=4,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7f92592bc940>,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    tp_linear_async_communication=False,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    expert_parallel_size=1),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 eos_token_id=2,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 hidden_act='silu',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 hidden_size=2048,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 initializer_range=0.02,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 intermediate_size=4096,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 is_llama_config=True,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 max_position_embeddings=4096,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 num_attention_heads=32,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 num_hidden_layers=24,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 num_key_value_heads=32,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 pad_token_id=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 pretraining_tp=1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 rms_norm_eps=1e-05,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 rope_scaling=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 rope_theta=10000.0,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 tie_word_embeddings=True,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 use_cache=True,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                 vocab_size=50260),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                        init_method=RandomInit(std=0.025),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                        dtype=torch.bfloat16,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                        make_vocab_size_divisible_by=1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                        ddp_bucket_cap_mb=25),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                tokenizer_revision=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                tokenizer_max_length=None),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    checkpoint_interval=100000,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    save_initial_state=False,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    resume_checkpoint_path=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                    checkpoints_path_is_shared_file_system=False),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        logging=LoggingArgs(log_level='info',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            log_level_replica='info',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                            iteration_step_info_interval=1),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        tokens=TokensArgs(sequence_length=4096,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          train_steps=20,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          micro_batch_size=128,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          batch_accumulation_per_replica=8,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          val_check_interval=-1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          limit_val_batches=0,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                          limit_test_batches=0),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                     adam_beta1=0.9,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                     adam_beta2=0.95,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                     torch_adam_is_fused=True,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                     name='adamW'),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                zero_stage=1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                weight_decay=0.01,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                clip_grad=1.0,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                accumulate_grad_in_fp32=True,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_warmup_steps=1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_warmup_style='linear',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_decay_style='linear',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_decay_steps=19,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        lr_decay_starting_step=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                        min_decay_lr=1e-05)),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                      start_training_step=1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                      data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 hf_dataset_splits='train',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 hf_dataset_config_name=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 dataset_processing_num_proc_per_process=64,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 dataset_overwrite_cache=False,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                                                 text_column_name='text'),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                    seed=42,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:                                                    num_loading_workers=0))],
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-128')),
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:        lighteval=None)
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Model Config:
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: LlamaConfig(bos_token_id=1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             eos_token_id=2,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             hidden_act='silu',
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             hidden_size=2048,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             initializer_range=0.02,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             intermediate_size=4096,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             is_llama_config=True,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             max_position_embeddings=4096,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             num_attention_heads=32,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             num_hidden_layers=24,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             num_key_value_heads=32,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             pad_token_id=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             pretraining_tp=1,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             rms_norm_eps=1e-05,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             rope_scaling=None,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             rope_theta=10000.0,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             tie_word_embeddings=True,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             use_cache=True,
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:             vocab_size=50260)
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Building model..
[default0]:07/03/2024 21:09:56 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Setting PP block ranks...
[default0]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Total number of parameters: 1.21G (2313.42MiB)
[default0]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Local number of parameters: 173M (329.19MiB)
[default0]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
[default0]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: No checkpoint path provided.
[default0]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Parametrizing model parameters using StandardParametrizator
[default7]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=3|ip-26-0-174-36]: Local number of parameters: 131M (249.16MiB)
[default7]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=3|ip-26-0-174-36]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
[default7]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=3|ip-26-0-174-36]: No checkpoint path provided.
[default5]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=1|ip-26-0-174-36]: Local number of parameters: 131M (249.16MiB)
[default5]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=1|ip-26-0-174-36]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
[default5]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=1|ip-26-0-174-36]: No checkpoint path provided.
[default2]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=2|ip-26-0-174-36]: Local number of parameters: 173M (329.19MiB)
[default2]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=2|ip-26-0-174-36]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
[default2]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=2|ip-26-0-174-36]: No checkpoint path provided.
[default1]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=1|ip-26-0-174-36]: Local number of parameters: 173M (329.19MiB)
[default1]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=1|ip-26-0-174-36]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
[default1]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=1|ip-26-0-174-36]: No checkpoint path provided.
[default3]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=3|ip-26-0-174-36]: Local number of parameters: 173M (329.19MiB)
[default3]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=3|ip-26-0-174-36]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB
[default3]:07/03/2024 21:10:09 [INFO|DP=0|PP=0|TP=3|ip-26-0-174-36]: No checkpoint path provided.
[default6]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=2|ip-26-0-174-36]: Local number of parameters: 131M (249.16MiB)
[default6]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=2|ip-26-0-174-36]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
[default6]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=2|ip-26-0-174-36]: No checkpoint path provided.
[default4]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=0|ip-26-0-174-36]: Local number of parameters: 131M (249.16MiB)
[default4]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=0|ip-26-0-174-36]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB
[default4]:07/03/2024 21:10:09 [INFO|DP=0|PP=1|TP=0|ip-26-0-174-36]: No checkpoint path provided.
[default0]:07/03/2024 21:10:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/03/2024 21:10:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/03/2024 21:10:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [ZeRO sharding] DP Rank 0 has 173M out of 173M (100.00%) params' optimizer states
[default0]:07/03/2024 21:10:11 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/03/2024 21:10:11 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Using `datasets` library
[default0]:07/03/2024 21:10:11 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
[default0]:07/03/2024 21:10:12 [WARNING|DP=0|PP=0|TP=0|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/03/2024 21:10:13 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Training Plan] There are 1 training stages 
[default0]:07/03/2024 21:10:13 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Stage Training Stage] start from step 1 
[default0]:07/03/2024 21:10:13 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: 
[default0]:07/03/2024 21:10:13 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Start training] datetime: 2024-07-03 21:10:13.140040 | mbs: 128 | grad_accum: 8 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
[default0]:07/03/2024 21:10:13 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/03/2024 21:10:13 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]:  Memory usage: 1660.89MiB. Peak allocated 1660.89MiB. Peak reserved: 1668.00MiB
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/03/2024 21:10:13 [WARNING|DP=0|PP=1|TP=3|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/03/2024 21:10:13 [WARNING|DP=0|PP=0|TP=2|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/03/2024 21:10:13 [WARNING|DP=0|PP=1|TP=1|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/03/2024 21:10:13 [WARNING|DP=0|PP=0|TP=1|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/03/2024 21:10:13 [WARNING|DP=0|PP=0|TP=3|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/03/2024 21:10:13 [WARNING|DP=0|PP=1|TP=2|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/03/2024 21:10:13 [WARNING|DP=0|PP=1|TP=0|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:[rank2]: Traceback (most recent call last):
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default2]:[rank2]:     trainer.train(dataloader)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default2]:[rank2]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default2]:[rank2]:     outputs = self.pipeline_engine.train_batch_iter(
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter
[default2]:[rank2]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default2]:[rank2]:     output = model(**micro_batch)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default2]:[rank2]:     return self._call_impl(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default2]:[rank2]:     return forward_call(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default2]:[rank2]:     sharded_logits = self.model(
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default2]:[rank2]:     return self._call_impl(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default2]:[rank2]:     return forward_call(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default2]:[rank2]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default2]:[rank2]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default2]:[rank2]:     return self._call_impl(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default2]:[rank2]:     return forward_call(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default2]:[rank2]:     output = self.pp_block(**new_kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default2]:[rank2]:     return self._call_impl(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default2]:[rank2]:     return forward_call(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
[default2]:[rank2]:     hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default2]:[rank2]:     return self._call_impl(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default2]:[rank2]:     return forward_call(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
[default2]:[rank2]:     hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default2]:[rank2]:     return self._call_impl(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default2]:[rank2]:     return forward_call(*args, **kwargs)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default2]:[rank2]:     return row_linear(
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 479, in row_linear
[default2]:[rank2]:     out = differentiable_reduce_scatter_sum(out, group=group)
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 145, in differentiable_reduce_scatter_sum
[default2]:[rank2]:     return DifferentiableReduceScatterSum.apply(tensor, group)
[default2]:[rank2]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 598, in apply
[default2]:[rank2]:     return super().apply(*args, **kwargs)  # type: ignore[misc]
[default2]:[rank2]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 111, in forward
[default2]:[rank2]:     sharded_tensor = torch.empty(
[default2]:[rank2]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU  has a total capacity of 79.33 GiB of which 209.94 MiB is free. Including non-PyTorch memory, this process has 79.11 GiB memory in use. Of the allocated memory 67.25 GiB is allocated by PyTorch, and 416.60 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default0]:[rank0]: Traceback (most recent call last):
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default0]:[rank0]:     trainer.train(dataloader)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default0]:[rank0]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default0]:[rank0]:     outputs = self.pipeline_engine.train_batch_iter(
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter
[default0]:[rank0]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default0]:[rank0]:     output = model(**micro_batch)
[default0]:[rank0]:   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]:[rank0]:     return self._call_impl(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default0]:[rank0]:     return forward_call(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default0]:[rank0]:     sharded_logits = self.model(
[default0]:[rank0]:   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]:[rank0]:     return self._call_impl(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default0]:[rank0]:     return forward_call(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default0]:[rank0]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default0]:[rank0]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default0]:[rank0]:   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]:[rank0]:     return self._call_impl(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default0]:[rank0]:     return forward_call(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default0]:[rank0]:     output = self.pp_block(**new_kwargs)
[default0]:[rank0]:   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]:[rank0]:     return self._call_impl(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default0]:[rank0]:     return forward_call(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
[default0]:[rank0]:     hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default0]:[rank0]:   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]:[rank0]:     return self._call_impl(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default0]:[rank0]:     return forward_call(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
[default0]:[rank0]:     hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default0]:[rank0]:   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]:[rank0]:     return self._call_impl(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default0]:[rank0]:     return forward_call(*args, **kwargs)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default0]:[rank0]:     return row_linear(
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 479, in row_linear
[default0]:[rank0]:     out = differentiable_reduce_scatter_sum(out, group=group)
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 145, in differentiable_reduce_scatter_sum
[default0]:[rank0]:     return DifferentiableReduceScatterSum.apply(tensor, group)
[default0]:[rank0]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 598, in apply
[default0]:[rank0]:     return super().apply(*args, **kwargs)  # type: ignore[misc]
[default0]:[rank0]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 111, in forward
[default0]:[rank0]:     sharded_tensor = torch.empty(
[default0]:[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU 
[default1]:[rank1]: Traceback (most recent call last):
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default1]:[rank1]:     trainer.train(dataloader)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default1]:[rank1]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default1]:[rank1]:     outputs = self.pipeline_engine.train_batch_iter(
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter
[default1]:[rank1]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default1]:[rank1]:     output = model(**micro_batch)
[default1]:[rank1]:   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]:[rank1]:     return self._call_impl(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default1]:[rank1]:     return forward_call(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default1]:[rank1]:     sharded_logits = self.model(
[default1]:[rank1]:   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]:[rank1]:     return self._call_impl(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default1]:[rank1]:     return forward_call(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default1]:[rank1]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default1]:[rank1]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default1]:[rank1]:   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]:[rank1]:     return self._call_impl(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default1]:[rank1]:     return forward_call(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default1]:[rank1]:     output = self.pp_block(**new_kwargs)
[default1]:[rank1]:   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]:[rank1]:     return self._call_impl(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default1]:[rank1]:     return forward_call(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
[default1]:[rank1]:     hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default1]:[rank1]:   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]:[rank1]:     return self._call_impl(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default1]:[rank1]:     return forward_call(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
[default1]:[rank1]:     hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default1]:[rank1]:   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]:[rank1]:     return self._call_impl(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default1]:[rank1]:     return forward_call(*args, **kwargs)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default1]:[rank1]:     return row_linear(
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 479, in row_linear
[default1]:[rank1]:     out = differentiable_reduce_scatter_sum(out, group=group)
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 145, in differentiable_reduce_scatter_sum
[default1]:[rank1]:     return DifferentiableReduceScatterSum.apply(tensor, group)
[default1]:[rank1]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 598, in apply
[default1]:[rank1]:     return super().apply(*args, **kwargs)  # type: ignore[misc]
[default1]:[rank1]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 111, in forward
[default1]:[rank1]:     sharded_tensor = torch.empty(
[default1]:[rank1]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU  has a total capacity of 79.33 GiB of which 209.94 MiB is free. Including non-PyTorch memory, this process has 79.11 GiB memory in use. Of the allocated memory 67.25 GiB is allocated by PyTorch, and 416.60 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default3]:[rank3]: Traceback (most recent call last):
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default3]:[rank3]:     trainer.train(dataloader)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default3]:[rank3]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default3]:[rank3]:     outputs = self.pipeline_engine.train_batch_iter(
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter
[default3]:[rank3]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default3]:[rank3]:     output = model(**micro_batch)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default3]:[rank3]:     return self._call_impl(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default3]:[rank3]:     return forward_call(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default3]:[rank3]:     sharded_logits = self.model(
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default3]:[rank3]:     return self._call_impl(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default3]:[rank3]:     return forward_call(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default3]:[rank3]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default3]:[rank3]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default3]:[rank3]:     return self._call_impl(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default3]:[rank3]:     return forward_call(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default3]:[rank3]:     output = self.pp_block(**new_kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default3]:[rank3]:     return self._call_impl(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default3]:[rank3]:     return forward_call(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward
[default3]:[rank3]:     hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default3]:[rank3]:     return self._call_impl(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default3]:[rank3]:     return forward_call(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward
[default3]:[rank3]:     hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default3]:[rank3]:     return self._call_impl(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default3]:[rank3]:     return forward_call(*args, **kwargs)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default3]:[rank3]:     return row_linear(
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 479, in row_linear
[default3]:[rank3]:     out = differentiable_reduce_scatter_sum(out, group=group)
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 145, in differentiable_reduce_scatter_sum
[default3]:[rank3]:     return DifferentiableReduceScatterSum.apply(tensor, group)
[default3]:[rank3]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 598, in apply
[default3]:[rank3]:     return super().apply(*args, **kwargs)  # type: ignore[misc]
[default3]:[rank3]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/distributed_differentiable_primitives.py", line 111, in forward
[default3]:[rank3]:     sharded_tensor = torch.empty(
[default3]:[rank3]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU  has a total capacity of 79.33 GiB of which 449.94 MiB is free. Including non-PyTorch memory, this process has 78.88 GiB memory in use. Of the allocated memory 67.25 GiB is allocated by PyTorch, and 416.60 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
[default7]:[rank7]: Traceback (most recent call last):
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default7]:[rank7]:     trainer.train(dataloader)
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default7]:[rank7]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default7]:[rank7]:     outputs = self.pipeline_engine.train_batch_iter(
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
[default7]:[rank7]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default7]:[rank7]:     output = model(**micro_batch)
[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default7]:[rank7]:     return self._call_impl(*args, **kwargs)
[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default7]:[rank7]:     return forward_call(*args, **kwargs)
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default7]:[rank7]:     sharded_logits = self.model(
[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default7]:[rank7]:     return self._call_impl(*args, **kwargs)
[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default7]:[rank7]:     return forward_call(*args, **kwargs)
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default7]:[rank7]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default7]:[rank7]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default7]:[rank7]:     return self._call_impl(*args, **kwargs)
[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default7]:[rank7]:     return forward_call(*args, **kwargs)
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default7]:[rank7]:     new_kwargs[name] = recv_from_pipeline_state_buffer(
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default7]:[rank7]:     pipeline_state.run_communication()
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default7]:[rank7]:     recv_activation_tensor = recv_activation()
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default7]:[rank7]:     return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default7]:[rank7]:     buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default7]:[rank7]:     meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default7]:[rank7]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 246, in _recv_meta
[default7]:[rank7]:     dist.recv(
[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper
[default7]:[rank7]:     return func(*args, **kwargs)
[default7]:[rank7]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv
[default7]:[rank7]:     pg.recv([tensor], group_src_rank, tag).wait()
[default7]:[rank7]: torch.distributed.DistBackendError: [1] is setting up NCCL communicator and retrieving ncclUniqueId from [0] via c10d key-value store by key '0:1', but store->get('0:1') got error: Connection reset by peer
[default7]:[rank7]: Exception raised from recvBytes at ../torch/csrc/distributed/c10d/Utils.hpp:672 (most recent call first):
[default7]:[rank7]: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7ff4dcdd9897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default7]:[rank7]: frame #1: <unknown function> + 0x5b3a23e (0x7ff5168f623e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #2: c10d::TCPStore::doWait(c10::ArrayRef<std::string>, std::chrono::duration<long, std::ratio<1l, 1000l> >) + 0x2c7 (0x7ff5168f0c87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #3: c10d::TCPStore::doGet(std::string const&) + 0x32 (0x7ff5168f0f82 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #4: c10d::TCPStore::get(std::string const&) + 0xa1 (0x7ff5168f1fd1 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #5: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7ff5168a6371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #6: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7ff5168a6371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #7: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7ff5168a6371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #8: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7ff5168a6371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #9: c10d::ProcessGroupNCCL::broadcastUniqueNCCLID(ncclUniqueId*, bool, std::string const&, int) + 0xa9 (0x7ff4de0b3189 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:[rank7]: frame #10: c10d::ProcessGroupNCCL::getNCCLComm(std::string const&, c10::Device&, c10d::OpType, int, bool) + 0xc50 (0x7ff4de0ba610 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:[rank7]: frame #11: c10d::ProcessGroupNCCL::recv(std::vector<at::Tensor, std::allocator<at::Tensor> >&, int, int) + 0x5f8 (0x7ff4de0d9978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:[rank7]: frame #12: <unknown function> + 0x5adc309 (0x7ff516898309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #13: <unknown function> + 0x5ae6f10 (0x7ff5168a2f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #14: <unknown function> + 0x5ae6fa5 (0x7ff5168a2fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #15: <unknown function> + 0x5124446 (0x7ff515ee0446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #16: <unknown function> + 0x1acf4b8 (0x7ff51288b4b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #17: <unknown function> + 0x5aee004 (0x7ff5168aa004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #18: <unknown function> + 0x5af36b5 (0x7ff5168af6b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default7]:[rank7]: frame #19: <unknown function> + 0xd2631e (0x7ff52949931e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so)
[default7]:[rank7]: frame #20: <unknown function> + 0x47def4 (0x7ff528bf0ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so)
[default7]:[rank7]: frame #21: <unknown function> + 0x1445a6 (0x558e2e9a75a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #22: _PyObject_MakeTpCall + 0x26b (0x558e2e9a0a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #23: <unknown function> + 0x150866 (0x558e2e9b3866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x558e2e99c142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #25: _PyFunction_Vectorcall + 0x6c (0x558e2e9a7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #26: PyObject_Call + 0xbc (0x558e2e9b3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x558e2e99a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #28: _PyFunction_Vectorcall + 0x6c (0x558e2e9a7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x558e2e9988fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #30: <unknown function> + 0x150582 (0x558e2e9b3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x558e2e9988fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #32: <unknown function> + 0x150582 (0x558e2e9b3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x558e2e9988fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #34: <unknown function> + 0x150582 (0x558e2e9b3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x558e2e9988fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x558e2e99ff50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #37: _PyObject_Call_Prepend + 0x69 (0x558e2e9b1c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #38: <unknown function> + 0x211239 (0x558e2ea74239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #39: _PyObject_MakeTpCall + 0x26b (0x558e2e9a0a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x558e2e99c3e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #41: _PyFunction_Vectorcall + 0x6c (0x558e2e9a7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x558e2e997c5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #43: _PyFunction_Vectorcall + 0x6c (0x558e2e9a7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x558e2e9988fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #45: <unknown function> + 0x150582 (0x558e2e9b3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #46: PyObject_Call + 0xbc (0x558e2e9b3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x558e2e99a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #48: <unknown function> + 0x150582 (0x558e2e9b3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #49: PyObject_Call + 0xbc (0x558e2e9b3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x558e2e99a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #51: _PyFunction_Vectorcall + 0x6c (0x558e2e9a7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x558e2e9a0007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #53: _PyObject_Call_Prepend + 0x69 (0x558e2e9b1c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #54: <unknown function> + 0x211239 (0x558e2ea74239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #55: PyObject_Call + 0x207 (0x558e2e9b4067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x558e2e99a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #57: <unknown function> + 0x150582 (0x558e2e9b3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x558e2e9988fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #59: <unknown function> + 0x150582 (0x558e2e9b3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #60: PyObject_Call + 0xbc (0x558e2e9b3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x558e2e99a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #62: <unknown function> + 0x150582 (0x558e2e9b3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: frame #63: PyObject_Call + 0xbc (0x558e2e9b3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default7]:[rank7]: . This may indicate a possible application crash on rank 0 or a network set up issue.
[default6]:[rank6]: Traceback (most recent call last):
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default6]:[rank6]:     trainer.train(dataloader)
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default6]:[rank6]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default6]:[rank6]:     outputs = self.pipeline_engine.train_batch_iter(
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
[default6]:[rank6]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default6]:[rank6]:     output = model(**micro_batch)
[default6]:[rank6]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default6]:[rank6]:     return self._call_impl(*args, **kwargs)
[default6]:[rank6]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default6]:[rank6]:     return forward_call(*args, **kwargs)
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default6]:[rank6]:     sharded_logits = self.model(
[default6]:[rank6]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default6]:[rank6]:     return self._call_impl(*args, **kwargs)
[default6]:[rank6]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default6]:[rank6]:     return forward_call(*args, **kwargs)
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[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
[default6]:[rank6]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default6]:[rank6]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default6]:[rank6]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default6]:[rank6]:     return self._call_impl(*args, **kwargs)
[default5]:[rank5]:     outputs = self.pipeline_engine.train_batch_iter(
[default5]:[rank5]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
[default5]:[rank5]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default6]:[rank6]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[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)
[default6]:[rank6]:     return forward_call(*args, **kwargs)
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default6]:[rank6]:     new_kwargs[name] = recv_from_pipeline_state_buffer(
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default6]:[rank6]:     pipeline_state.run_communication()
[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]
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default6]:[rank6]:     recv_activation_tensor = recv_activation()
[default5]:[rank5]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default5]:[rank5]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default6]:[rank6]:     return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[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
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default5]:[rank5]:     return self._call_impl(*args, **kwargs)
[default6]:[rank6]:     buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[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
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default5]:[rank5]:     return forward_call(*args, **kwargs)
[default6]:[rank6]:     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/block.py", line 126, in forward
[default6]:[rank6]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 246, in _recv_meta
[default5]:[rank5]:     new_kwargs[name] = recv_from_pipeline_state_buffer(
[default6]:[rank6]:     dist.recv(
[default6]:[rank6]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper
[default6]:[rank6]:     return func(*args, **kwargs)
[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
[default6]:[rank6]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv
[default6]:[rank6]:     pg.recv([tensor], group_src_rank, tag).wait()
[default5]:[rank5]:     pipeline_state.run_communication()
[default6]:[rank6]: torch.distributed.DistBackendError: [1] is setting up NCCL communicator and retrieving ncclUniqueId from [0] via c10d key-value store by key '0:1', but store->get('0:1') got error: Connection reset by peer
[default5]:[rank5]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default6]:[rank6]: Exception raised from recvBytes at ../torch/csrc/distributed/c10d/Utils.hpp:672 (most recent call first):
[default5]:[rank5]:     recv_activation_tensor = recv_activation()
[default6]:[rank6]: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fa95637d897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default5]:[rank5]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default6]:[rank6]: frame #1: <unknown function> + 0x5b3a23e (0x7fa98fe9a23e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]:     return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default6]:[rank6]: frame #2: c10d::TCPStore::doWait(c10::ArrayRef<std::string>, std::chrono::duration<long, std::ratio<1l, 1000l> >) + 0x2c7 (0x7fa98fe94c87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #3: c10d::TCPStore::doGet(std::string const&) + 0x32 (0x7fa98fe94f82 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default6]:[rank6]: frame #4: c10d::TCPStore::get(std::string const&) + 0xa1 (0x7fa98fe95fd1 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]:     buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default6]:[rank6]: frame #5: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fa98fe4a371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #6: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fa98fe4a371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default6]:[rank6]: frame #7: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fa98fe4a371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]:     meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default6]:[rank6]: frame #8: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fa98fe4a371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 246, in _recv_meta
[default6]:[rank6]: frame #9: c10d::ProcessGroupNCCL::broadcastUniqueNCCLID(ncclUniqueId*, bool, std::string const&, int) + 0xa9 (0x7fa957657189 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default6]:[rank6]: frame #10: c10d::ProcessGroupNCCL::getNCCLComm(std::string const&, c10::Device&, c10d::OpType, int, bool) + 0xc50 (0x7fa95765e610 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default6]:[rank6]: frame #11: c10d::ProcessGroupNCCL::recv(std::vector<at::Tensor, std::allocator<at::Tensor> >&, int, int) + 0x5f8 (0x7fa95767d978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default6]:[rank6]: frame #12: <unknown function> + 0x5adc309 (0x7fa98fe3c309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #13: <unknown function> + 0x5ae6f10 (0x7fa98fe46f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]:     dist.recv(
[default6]:[rank6]: frame #14: <unknown function> + 0x5ae6fa5 (0x7fa98fe46fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper
[default6]:[rank6]: frame #15: <unknown function> + 0x5124446 (0x7fa98f484446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #16: <unknown function> + 0x1acf4b8 (0x7fa98be2f4b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #17: <unknown function> + 0x5aee004 (0x7fa98fe4e004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #18: <unknown function> + 0x5af36b5 (0x7fa98fe536b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #19: <unknown function> + 0xd2631e (0x7fa9a2a3d31e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so)
[default6]:[rank6]: frame #20: <unknown function> + 0x47def4 (0x7fa9a2194ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so)
[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: [1] is setting up NCCL communicator and retrieving ncclUniqueId from [0] via c10d key-value store by key '0:1', but store->get('0:1') got error: Connection reset by peer
[default6]:[rank6]: frame #21: <unknown function> + 0x1445a6 (0x55bd94df15a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: Exception raised from recvBytes at ../torch/csrc/distributed/c10d/Utils.hpp:672 (most recent call first):
[default5]:[rank5]: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f5034b31897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default6]:[rank6]: frame #22: _PyObject_MakeTpCall + 0x26b (0x55bd94deaa6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #1: <unknown function> + 0x5b3a23e (0x7f506e64e23e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #23: <unknown function> + 0x150866 (0x55bd94dfd866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #2: c10d::TCPStore::doWait(c10::ArrayRef<std::string>, std::chrono::duration<long, std::ratio<1l, 1000l> >) + 0x2c7 (0x7f506e648c87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]: frame #3: c10d::TCPStore::doGet(std::string const&) + 0x32 (0x7f506e648f82 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x55bd94de6142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #25: _PyFunction_Vectorcall + 0x6c (0x55bd94df1a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #26: PyObject_Call + 0xbc (0x55bd94dfdf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x55bd94de42b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #28: _PyFunction_Vectorcall + 0x6c (0x55bd94df1a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #4: c10d::TCPStore::get(std::string const&) + 0xa1 (0x7f506e649fd1 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x55bd94de28fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #30: <unknown function> + 0x150582 (0x55bd94dfd582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #5: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f506e5fe371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]: frame #6: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f506e5fe371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x55bd94de28fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #7: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f506e5fe371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]: frame #8: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f506e5fe371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]: frame #9: c10d::ProcessGroupNCCL::broadcastUniqueNCCLID(ncclUniqueId*, bool, std::string const&, int) + 0xa9 (0x7f5035e0b189 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:[rank5]: frame #10: c10d::ProcessGroupNCCL::getNCCLComm(std::string const&, c10::Device&, c10d::OpType, int, bool) + 0xc50 (0x7f5035e12610 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:[rank5]: frame #11: c10d::ProcessGroupNCCL::recv(std::vector<at::Tensor, std::allocator<at::Tensor> >&, int, int) + 0x5f8 (0x7f5035e31978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:[rank5]: frame #12: <unknown function> + 0x5adc309 (0x7f506e5f0309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default5]:[rank5]: frame #13: <unknown function> + 0x5ae6f10 (0x7f506e5faf10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #32: <unknown function> + 0x150582 (0x55bd94dfd582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #14: <unknown function> + 0x5ae6fa5 (0x7f506e5fafa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x55bd94de28fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #15: <unknown function> + 0x5124446 (0x7f506dc38446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #34: <unknown function> + 0x150582 (0x55bd94dfd582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x55bd94de28fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x55bd94de9f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #37: _PyObject_Call_Prepend + 0x69 (0x55bd94dfbc39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #38: <unknown function> + 0x211239 (0x55bd94ebe239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #39: _PyObject_MakeTpCall + 0x26b (0x55bd94deaa6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #16: <unknown function> + 0x1acf4b8 (0x7f506a5e34b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x55bd94de63e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #41: _PyFunction_Vectorcall + 0x6c (0x55bd94df1a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x55bd94de1c5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #43: _PyFunction_Vectorcall + 0x6c (0x55bd94df1a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x55bd94de28fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #45: <unknown function> + 0x150582 (0x55bd94dfd582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #46: PyObject_Call + 0xbc (0x55bd94dfdf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x55bd94de42b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #48: <unknown function> + 0x150582 (0x55bd94dfd582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #49: PyObject_Call + 0xbc (0x55bd94dfdf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x55bd94de42b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #51: _PyFunction_Vectorcall + 0x6c (0x55bd94df1a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x55bd94dea007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #53: _PyObject_Call_Prepend + 0x69 (0x55bd94dfbc39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #54: <unknown function> + 0x211239 (0x55bd94ebe239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #55: PyObject_Call + 0x207 (0x55bd94dfe067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x55bd94de42b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #57: <unknown function> + 0x150582 (0x55bd94dfd582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x55bd94de28fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #17: <unknown function> + 0x5aee004 (0x7f506e602004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #59: <unknown function> + 0x150582 (0x55bd94dfd582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #18: <unknown function> + 0x5af36b5 (0x7f506e6076b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default6]:[rank6]: frame #60: PyObject_Call + 0xbc (0x55bd94dfdf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #19: <unknown function> + 0xd2631e (0x7f50811f131e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so)
[default6]:[rank6]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x55bd94de42b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #20: <unknown function> + 0x47def4 (0x7f5080948ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so)
[default6]:[rank6]: frame #62: <unknown function> + 0x150582 (0x55bd94dfd582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #21: <unknown function> + 0x1445a6 (0x55f9b078e5a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #22: _PyObject_MakeTpCall + 0x26b (0x55f9b0787a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: frame #63: PyObject_Call + 0xbc (0x55bd94dfdf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #23: <unknown function> + 0x150866 (0x55f9b079a866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default6]:[rank6]: . This may indicate a possible application crash on rank 0 or a network set up issue.
[default5]:[rank5]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x55f9b0783142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #25: _PyFunction_Vectorcall + 0x6c (0x55f9b078ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #26: PyObject_Call + 0xbc (0x55f9b079af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x55f9b07812b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #28: _PyFunction_Vectorcall + 0x6c (0x55f9b078ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x55f9b077f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #30: <unknown function> + 0x150582 (0x55f9b079a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x55f9b077f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #32: <unknown function> + 0x150582 (0x55f9b079a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x55f9b077f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #34: <unknown function> + 0x150582 (0x55f9b079a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x55f9b077f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x55f9b0786f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #37: _PyObject_Call_Prepend + 0x69 (0x55f9b0798c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #38: <unknown function> + 0x211239 (0x55f9b085b239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #39: _PyObject_MakeTpCall + 0x26b (0x55f9b0787a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x55f9b07833e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #41: _PyFunction_Vectorcall + 0x6c (0x55f9b078ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x55f9b077ec5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #43: _PyFunction_Vectorcall + 0x6c (0x55f9b078ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x55f9b077f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #45: <unknown function> + 0x150582 (0x55f9b079a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #46: PyObject_Call + 0xbc (0x55f9b079af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x55f9b07812b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #48: <unknown function> + 0x150582 (0x55f9b079a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #49: PyObject_Call + 0xbc (0x55f9b079af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x55f9b07812b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #51: _PyFunction_Vectorcall + 0x6c (0x55f9b078ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x55f9b0787007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #53: _PyObject_Call_Prepend + 0x69 (0x55f9b0798c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #54: <unknown function> + 0x211239 (0x55f9b085b239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #55: PyObject_Call + 0x207 (0x55f9b079b067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x55f9b07812b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #57: <unknown function> + 0x150582 (0x55f9b079a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x55f9b077f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #59: <unknown function> + 0x150582 (0x55f9b079a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #60: PyObject_Call + 0xbc (0x55f9b079af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x55f9b07812b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #62: <unknown function> + 0x150582 (0x55f9b079a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: frame #63: PyObject_Call + 0xbc (0x55f9b079af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default5]:[rank5]: . This may indicate a possible application crash on rank 0 or a network set up issue.
[default4]:[rank4]: Traceback (most recent call last):
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default4]:[rank4]:     trainer.train(dataloader)
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train
[default4]:[rank4]:     outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step
[default4]:[rank4]:     outputs = self.pipeline_engine.train_batch_iter(
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter
[default4]:[rank4]:     output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default4]:[rank4]:     output = model(**micro_batch)
[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default4]:[rank4]:     return self._call_impl(*args, **kwargs)
[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default4]:[rank4]:     return forward_call(*args, **kwargs)
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward
[default4]:[rank4]:     sharded_logits = self.model(
[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default4]:[rank4]:     return self._call_impl(*args, **kwargs)
[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default4]:[rank4]:     return forward_call(*args, **kwargs)
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default4]:[rank4]:     return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default4]:[rank4]:     hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
[default4]:[rank4]:     return self._call_impl(*args, **kwargs)
[default4]:[rank4]:   File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
[default4]:[rank4]:     return forward_call(*args, **kwargs)
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default4]:[rank4]:     new_kwargs[name] = recv_from_pipeline_state_buffer(
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default4]:[rank4]:     pipeline_state.run_communication()
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default4]:[rank4]:     recv_activation_tensor = recv_activation()
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default4]:[rank4]:     return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default4]:[rank4]:     buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default4]:[rank4]:     meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default4]:[rank4]:   File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 246, 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: [1] is setting up NCCL communicator and retrieving ncclUniqueId from [0] via c10d key-value store by key '0:1', but store->get('0:1') got error: Connection reset by peer
[default4]:[rank4]: Exception raised from recvBytes at ../torch/csrc/distributed/c10d/Utils.hpp:672 (most recent call first):
[default4]:[rank4]: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fd7ed516897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default4]:[rank4]: frame #1: <unknown function> + 0x5b3a23e (0x7fd82703323e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #2: c10d::TCPStore::doWait(c10::ArrayRef<std::string>, std::chrono::duration<long, std::ratio<1l, 1000l> >) + 0x2c7 (0x7fd82702dc87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #3: c10d::TCPStore::doGet(std::string const&) + 0x32 (0x7fd82702df82 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #4: c10d::TCPStore::get(std::string const&) + 0xa1 (0x7fd82702efd1 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #5: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fd826fe3371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #6: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fd826fe3371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #7: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fd826fe3371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #8: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fd826fe3371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #9: c10d::ProcessGroupNCCL::broadcastUniqueNCCLID(ncclUniqueId*, bool, std::string const&, int) + 0xa9 (0x7fd7ee7f0189 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default4]:[rank4]: frame #10: c10d::ProcessGroupNCCL::getNCCLComm(std::string const&, c10::Device&, c10d::OpType, int, bool) + 0xc50 (0x7fd7ee7f7610 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default4]:[rank4]: frame #11: c10d::ProcessGroupNCCL::recv(std::vector<at::Tensor, std::allocator<at::Tensor> >&, int, int) + 0x5f8 (0x7fd7ee816978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default4]:[rank4]: frame #12: <unknown function> + 0x5adc309 (0x7fd826fd5309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #13: <unknown function> + 0x5ae6f10 (0x7fd826fdff10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #14: <unknown function> + 0x5ae6fa5 (0x7fd826fdffa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #15: <unknown function> + 0x5124446 (0x7fd82661d446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #16: <unknown function> + 0x1acf4b8 (0x7fd822fc84b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #17: <unknown function> + 0x5aee004 (0x7fd826fe7004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #18: <unknown function> + 0x5af36b5 (0x7fd826fec6b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
[default4]:[rank4]: frame #19: <unknown function> + 0xd2631e (0x7fd839bd631e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so)
[default4]:[rank4]: frame #20: <unknown function> + 0x47def4 (0x7fd83932def4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so)
[default4]:[rank4]: frame #21: <unknown function> + 0x1445a6 (0x56122d74e5a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #22: _PyObject_MakeTpCall + 0x26b (0x56122d747a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #23: <unknown function> + 0x150866 (0x56122d75a866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x56122d743142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #25: _PyFunction_Vectorcall + 0x6c (0x56122d74ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #26: PyObject_Call + 0xbc (0x56122d75af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x56122d7412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #28: _PyFunction_Vectorcall + 0x6c (0x56122d74ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x56122d73f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #30: <unknown function> + 0x150582 (0x56122d75a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x56122d73f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #32: <unknown function> + 0x150582 (0x56122d75a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x56122d73f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #34: <unknown function> + 0x150582 (0x56122d75a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x56122d73f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x56122d746f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #37: _PyObject_Call_Prepend + 0x69 (0x56122d758c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #38: <unknown function> + 0x211239 (0x56122d81b239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #39: _PyObject_MakeTpCall + 0x26b (0x56122d747a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x56122d7433e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #41: _PyFunction_Vectorcall + 0x6c (0x56122d74ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x56122d73ec5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #43: _PyFunction_Vectorcall + 0x6c (0x56122d74ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x56122d73f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #45: <unknown function> + 0x150582 (0x56122d75a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #46: PyObject_Call + 0xbc (0x56122d75af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x56122d7412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #48: <unknown function> + 0x150582 (0x56122d75a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #49: PyObject_Call + 0xbc (0x56122d75af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x56122d7412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #51: _PyFunction_Vectorcall + 0x6c (0x56122d74ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x56122d747007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #53: _PyObject_Call_Prepend + 0x69 (0x56122d758c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #54: <unknown function> + 0x211239 (0x56122d81b239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #55: PyObject_Call + 0x207 (0x56122d75b067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x56122d7412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #57: <unknown function> + 0x150582 (0x56122d75a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x56122d73f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #59: <unknown function> + 0x150582 (0x56122d75a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #60: PyObject_Call + 0xbc (0x56122d75af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x56122d7412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #62: <unknown function> + 0x150582 (0x56122d75a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: frame #63: PyObject_Call + 0xbc (0x56122d75af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10)
[default4]:[rank4]: . This may indicate a possible application crash on rank 0 or a network set up issue.
W0703 21:10:20.045000 140415295817536 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 218723 closing signal SIGTERM
W0703 21:10:20.045000 140415295817536 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 218724 closing signal SIGTERM
W0703 21:10:20.045000 140415295817536 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 218725 closing signal SIGTERM
W0703 21:10:20.046000 140415295817536 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 218726 closing signal SIGTERM
E0703 21:10:21.164000 140415295817536 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 218719) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    sys.exit(main())
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
============================================================
/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
------------------------------------------------------------
Failures:
[1]:
  time      : 2024-07-03_21:10:20
  host      : ip-26-0-174-36.ec2.internal
  rank      : 1 (local_rank: 1)
  exitcode  : 1 (pid: 218720)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[2]:
  time      : 2024-07-03_21:10:20
  host      : ip-26-0-174-36.ec2.internal
  rank      : 2 (local_rank: 2)
  exitcode  : 1 (pid: 218721)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[3]:
  time      : 2024-07-03_21:10:20
  host      : ip-26-0-174-36.ec2.internal
  rank      : 3 (local_rank: 3)
  exitcode  : 1 (pid: 218722)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-07-03_21:10:20
  host      : ip-26-0-174-36.ec2.internal
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 218719)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
srun: error: ip-26-0-174-36: 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.