======================== START TIME: Wed Jul 3 21:07:05 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 21:07:09.449000 140562804610880 torch/distributed/run.py:757] W0703 21:07:09.449000 140562804610880 torch/distributed/run.py:757] ***************************************** W0703 21:07:09.449000 140562804610880 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 21:07:09.449000 140562804610880 torch/distributed/run.py:757] ***************************************** [default0]:07/03/2024 21:07:29 [WARNING|DP=0|PP=0|TP=0|ip-26-0-162-233]: [Vocab Size Padding] Padded vocab (size: 50257) with 3 dummy tokens (new size: 50260) [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Config: [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Config(general=GeneralArgs(project='bench_cluster', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: run='%date_%jobid', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: seed=42, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: step=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: consumed_train_samples=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: benchmark_csv_path=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: ignore_sanity_checks=True), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: parallelism=ParallelismArgs(dp=1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: pp=2, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: tp=4, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: pp_engine=, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: tp_mode=, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: tp_linear_async_communication=False, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: expert_parallel_size=1), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: eos_token_id=2, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: hidden_act='silu', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: hidden_size=2048, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: initializer_range=0.02, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: intermediate_size=4096, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: is_llama_config=True, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: max_position_embeddings=4096, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: num_attention_heads=32, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: num_hidden_layers=24, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: num_key_value_heads=32, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: pad_token_id=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: pretraining_tp=1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: rms_norm_eps=1e-05, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: rope_scaling=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: rope_theta=10000.0, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: tie_word_embeddings=True, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: use_cache=True, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: vocab_size=50260), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: init_method=RandomInit(std=0.025), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: dtype=torch.bfloat16, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: make_vocab_size_divisible_by=1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: ddp_bucket_cap_mb=25), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: tokenizer_revision=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: tokenizer_max_length=None), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: checkpoint_interval=100000, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: save_initial_state=False, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: resume_checkpoint_path=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: checkpoints_path_is_shared_file_system=False), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: logging=LoggingArgs(log_level='info', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: log_level_replica='info', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: iteration_step_info_interval=1), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: tokens=TokensArgs(sequence_length=4096, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: train_steps=20, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: micro_batch_size=256, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: batch_accumulation_per_replica=4, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: val_check_interval=-1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: limit_val_batches=0, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: limit_test_batches=0), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: adam_beta1=0.9, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: adam_beta2=0.95, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: torch_adam_is_fused=True, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: name='adamW'), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: zero_stage=1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: weight_decay=0.01, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: clip_grad=1.0, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: accumulate_grad_in_fp32=True, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: lr_warmup_steps=1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: lr_warmup_style='linear', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: lr_decay_style='linear', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: lr_decay_steps=19, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: lr_decay_starting_step=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: min_decay_lr=1e-05)), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: data_stages=[DatasetStageArgs(name='Training Stage', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: start_training_step=1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: hf_dataset_splits='train', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: hf_dataset_config_name=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: dataset_processing_num_proc_per_process=64, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: dataset_overwrite_cache=False, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: text_column_name='text'), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: seed=42, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: num_loading_workers=0))], [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-256')), [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: lighteval=None) [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Model Config: [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: LlamaConfig(bos_token_id=1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: eos_token_id=2, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: hidden_act='silu', [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: hidden_size=2048, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: initializer_range=0.02, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: intermediate_size=4096, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: is_llama_config=True, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: max_position_embeddings=4096, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: num_attention_heads=32, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: num_hidden_layers=24, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: num_key_value_heads=32, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: pad_token_id=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: pretraining_tp=1, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: rms_norm_eps=1e-05, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: rope_scaling=None, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: rope_theta=10000.0, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: tie_word_embeddings=True, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: use_cache=True, [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: vocab_size=50260) [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Building model.. [default0]:07/03/2024 21:07:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Setting PP block ranks... [default5]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=1|ip-26-0-162-233]: Local number of parameters: 131M (249.16MiB) [default0]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Total number of parameters: 1.21G (2313.42MiB) [default0]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Local number of parameters: 173M (329.19MiB) [default0]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default5]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=1|ip-26-0-162-233]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default5]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=1|ip-26-0-162-233]: No checkpoint path provided. [default0]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: No checkpoint path provided. [default0]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Parametrizing model parameters using StandardParametrizator [default4]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=0|ip-26-0-162-233]: Local number of parameters: 131M (249.16MiB) [default4]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default4]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=0|ip-26-0-162-233]: No checkpoint path provided. [default2]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=2|ip-26-0-162-233]: Local number of parameters: 173M (329.19MiB) [default2]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=2|ip-26-0-162-233]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default2]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=2|ip-26-0-162-233]: No checkpoint path provided. [default3]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=3|ip-26-0-162-233]: Local number of parameters: 173M (329.19MiB) [default1]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=1|ip-26-0-162-233]: Local number of parameters: 173M (329.19MiB) [default1]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=1|ip-26-0-162-233]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default1]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=1|ip-26-0-162-233]: No checkpoint path provided. [default3]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=3|ip-26-0-162-233]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default3]:07/03/2024 21:07:43 [INFO|DP=0|PP=0|TP=3|ip-26-0-162-233]: No checkpoint path provided. [default6]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=2|ip-26-0-162-233]: Local number of parameters: 131M (249.16MiB) [default6]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=2|ip-26-0-162-233]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default6]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=2|ip-26-0-162-233]: No checkpoint path provided. [default7]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=3|ip-26-0-162-233]: Local number of parameters: 131M (249.16MiB) [default7]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=3|ip-26-0-162-233]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default7]:07/03/2024 21:07:43 [INFO|DP=0|PP=1|TP=3|ip-26-0-162-233]: No checkpoint path provided. [default0]:07/03/2024 21:07:44 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: [Optimizer Building] Using LearningRateForSP as learning rate [default0]:07/03/2024 21:07:44 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: [ZeRO sharding] Size of optimizer params per rank: [default0]:07/03/2024 21:07:44 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: [ZeRO sharding] DP Rank 0 has 173M out of 173M (100.00%) params' optimizer states [default0]:07/03/2024 21:07:46 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples [default0]:07/03/2024 21:07:46 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Using `datasets` library [default0]:07/03/2024 21:07:46 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4') [default0]:07/03/2024 21:07:46 [WARNING|DP=0|PP=0|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty. [default0]:Repo card metadata block was not found. Setting CardData to empty. [default0]:07/03/2024 21:07:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: [Training Plan] There are 1 training stages [default0]:07/03/2024 21:07:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: [Stage Training Stage] start from step 1 [default0]:07/03/2024 21:07:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: [default0]:07/03/2024 21:07:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: [Start training] datetime: 2024-07-03 21:07:47.283471 | mbs: 256 | grad_accum: 4 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0 [default0]:07/03/2024 21:07:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps [default0]:07/03/2024 21:07:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-162-233]: Memory usage: 1660.89MiB. Peak allocated 1660.89MiB. Peak reserved: 1668.00MiB [default3]:07/03/2024 21:07:47 [WARNING|DP=0|PP=0|TP=3|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty. [default6]:07/03/2024 21:07:47 [WARNING|DP=0|PP=1|TP=2|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty. [default6]:Repo card metadata block was not found. Setting CardData to empty. [default3]:Repo card metadata block was not found. Setting CardData to empty. [default4]:07/03/2024 21:07:47 [WARNING|DP=0|PP=1|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty. [default5]:07/03/2024 21:07:47 [WARNING|DP=0|PP=1|TP=1|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty. [default5]:Repo card metadata block was not found. Setting CardData to empty. [default2]:07/03/2024 21:07:47 [WARNING|DP=0|PP=0|TP=2|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty. [default1]:07/03/2024 21:07:47 [WARNING|DP=0|PP=0|TP=1|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty. [default7]:Repo card metadata block was not found. Setting CardData to empty. [default2]:Repo card metadata block was not found. Setting CardData to empty. [default1]:Repo card metadata block was not found. Setting CardData to empty. [default7]:07/03/2024 21:07:47 [WARNING|DP=0|PP=1|TP=3|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty. [default4]:Repo card metadata block was not found. Setting CardData to empty. [default0]:[rank0]: Traceback (most recent call last): [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [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 631, in forward [default0]:[rank0]: output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask) [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 565, in forward [default0]:[rank0]: key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous() [default0]:[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU [default2]:[rank2]: Traceback (most recent call last): [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default3]:[rank3]: Traceback (most recent call last): [default1]:[rank1]: Traceback (most recent call last): [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default2]:[rank2]: trainer.train(dataloader) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default3]:[rank3]: trainer.train(dataloader) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default1]:[rank1]: trainer.train(dataloader) [default2]:[rank2]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default3]:[rank3]: 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 429, in train [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default1]:[rank1]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default2]:[rank2]: outputs = self.pipeline_engine.train_batch_iter( [default1]:[rank1]: 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 [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) [default3]:[rank3]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [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) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default1]:[rank1]: 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) [default3]:[rank3]: 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 [default1]:[rank1]: 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 [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 [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: 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 [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 [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 [default1]:[rank1]: return forward_call(*args, **kwargs) [default2]:[rank2]: 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( [default3]:[rank3]: return forward_call(*args, **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) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [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 [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( [default1]:[rank1]: return forward_call(*args, **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 [default2]:[rank2]: sharded_logits = self.model( [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [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 [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 [default1]:[rank1]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default3]:[rank3]: return forward_call(*args, **kwargs) [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [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 [default3]:[rank3]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default2]:[rank2]: return forward_call(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [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] [default3]:[rank3]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default1]:[rank1]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_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 [default2]:[rank2]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default1]:[rank1]: 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 1532, in _wrapped_call_impl [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 [default3]:[rank3]: 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) [default2]:[rank2]: 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 [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 [default3]:[rank3]: 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 [default2]:[rank2]: 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 [default2]:[rank2]: 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) [default2]:[rank2]: output = self.pp_block(**new_kwargs) [default3]:[rank3]: 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 [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 [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 [default2]:[rank2]: return self._call_impl(*args, **kwargs) [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 [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 [default1]:[rank1]: return forward_call(*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) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 631, in forward [default3]:[rank3]: return forward_call(*args, **kwargs) [default1]:[rank1]: output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 631, in forward [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 [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 631, in forward [default3]:[rank3]: output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask) [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 [default1]:[rank1]: return self._call_impl(*args, **kwargs) [default3]:[rank3]: 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 [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 [default2]:[rank2]: output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask) [default3]:[rank3]: return forward_call(*args, **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 [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 565, in forward [default3]:[rank3]: key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous() [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: return forward_call(*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 [default3]:[rank3]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU  has a total capacity of 79.33 GiB of which 429.94 MiB is free. Including non-PyTorch memory, this process has 78.90 GiB memory in use. Of the allocated memory 65.74 GiB is allocated by PyTorch, and 1.93 GiB 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) [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 565, in forward [default2]:[rank2]: key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous() [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 565, in forward [default2]:[rank2]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU  has a total capacity of 79.33 GiB of which 189.94 MiB is free. Including non-PyTorch memory, this process has 79.13 GiB memory in use. Of the allocated memory 65.74 GiB is allocated by PyTorch, and 1.93 GiB 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) [default1]:[rank1]: key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous() [default1]:[rank1]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU  has a total capacity of 79.33 GiB of which 189.94 MiB is free. Including non-PyTorch memory, this process has 79.13 GiB memory in use. Of the allocated memory 65.74 GiB is allocated by PyTorch, and 1.93 GiB 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) [default5]:[rank5]: Traceback (most recent call last): [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default5]:[rank5]: trainer.train(dataloader) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default5]:[rank5]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default5]:[rank5]: outputs = self.pipeline_engine.train_batch_iter( [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter [default5]:[rank5]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default5]:[rank5]: output = model(**micro_batch) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default5]:[rank5]: sharded_logits = self.model( [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default5]:[rank5]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default5]:[rank5]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default5]:[rank5]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default5]:[rank5]: pipeline_state.run_communication() [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default5]:[rank5]: recv_activation_tensor = recv_activation() [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default5]:[rank5]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default5]:[rank5]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default5]:[rank5]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 246, in _recv_meta [default5]:[rank5]: dist.recv( [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default5]:[rank5]: return func(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default5]:[rank5]: pg.recv([tensor], group_src_rank, tag).wait() [default5]:[rank5]: torch.distributed.DistBackendError: [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]: 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 (0x7fb1cba37897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default5]:[rank5]: frame #1: + 0x5b3a23e (0x7fb20555423e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #2: c10d::TCPStore::doWait(c10::ArrayRef, std::chrono::duration >) + 0x2c7 (0x7fb20554ec87 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 (0x7fb20554ef82 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #4: c10d::TCPStore::get(std::string const&) + 0xa1 (0x7fb20554ffd1 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #5: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fb205504371 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 (0x7fb205504371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #7: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fb205504371 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 (0x7fb205504371 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 (0x7fb1ccd11189 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 (0x7fb1ccd18610 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 >&, int, int) + 0x5f8 (0x7fb1ccd37978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:[rank5]: frame #12: + 0x5adc309 (0x7fb2054f6309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #13: + 0x5ae6f10 (0x7fb205500f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #14: + 0x5ae6fa5 (0x7fb205500fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #15: + 0x5124446 (0x7fb204b3e446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #16: + 0x1acf4b8 (0x7fb2014e94b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #17: + 0x5aee004 (0x7fb205508004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #18: + 0x5af36b5 (0x7fb20550d6b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #19: + 0xd2631e (0x7fb2180f731e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default5]:[rank5]: frame #20: + 0x47def4 (0x7fb21784eef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default5]:[rank5]: frame #21: + 0x1445a6 (0x56100a42b5a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #22: _PyObject_MakeTpCall + 0x26b (0x56100a424a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #23: + 0x150866 (0x56100a437866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x56100a420142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #25: _PyFunction_Vectorcall + 0x6c (0x56100a42ba2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #26: PyObject_Call + 0xbc (0x56100a437f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x56100a41e2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #28: _PyFunction_Vectorcall + 0x6c (0x56100a42ba2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x56100a41c8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #30: + 0x150582 (0x56100a437582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x56100a41c8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #32: + 0x150582 (0x56100a437582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x56100a41c8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #34: + 0x150582 (0x56100a437582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x56100a41c8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x56100a423f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #37: _PyObject_Call_Prepend + 0x69 (0x56100a435c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #38: + 0x211239 (0x56100a4f8239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #39: _PyObject_MakeTpCall + 0x26b (0x56100a424a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x56100a4203e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #41: _PyFunction_Vectorcall + 0x6c (0x56100a42ba2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x56100a41bc5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #43: _PyFunction_Vectorcall + 0x6c (0x56100a42ba2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x56100a41c8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #45: + 0x150582 (0x56100a437582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #46: PyObject_Call + 0xbc (0x56100a437f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x56100a41e2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #48: + 0x150582 (0x56100a437582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #49: PyObject_Call + 0xbc (0x56100a437f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x56100a41e2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #51: _PyFunction_Vectorcall + 0x6c (0x56100a42ba2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x56100a424007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #53: _PyObject_Call_Prepend + 0x69 (0x56100a435c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #54: + 0x211239 (0x56100a4f8239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #55: PyObject_Call + 0x207 (0x56100a438067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x56100a41e2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #57: + 0x150582 (0x56100a437582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x56100a41c8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #59: + 0x150582 (0x56100a437582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #60: PyObject_Call + 0xbc (0x56100a437f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x56100a41e2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #62: + 0x150582 (0x56100a437582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #63: PyObject_Call + 0xbc (0x56100a437f1c 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. [default6]:[rank6]: Traceback (most recent call last): [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default6]:[rank6]: trainer.train(dataloader) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default6]:[rank6]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default6]:[rank6]: outputs = self.pipeline_engine.train_batch_iter( [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter [default6]:[rank6]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default6]:[rank6]: output = model(**micro_batch) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default6]:[rank6]: sharded_logits = self.model( [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default6]:[rank6]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default6]:[rank6]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default6]:[rank6]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default6]:[rank6]: pipeline_state.run_communication() [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default6]:[rank6]: recv_activation_tensor = recv_activation() [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default6]:[rank6]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default6]:[rank6]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default6]:[rank6]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 246, in _recv_meta [default6]:[rank6]: dist.recv( [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default6]:[rank6]: return func(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default6]:[rank6]: pg.recv([tensor], group_src_rank, tag).wait() [default6]:[rank6]: torch.distributed.DistBackendError: [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]: Exception raised from recvBytes at ../torch/csrc/distributed/c10d/Utils.hpp:672 (most recent call first): [default6]:[rank6]: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f13e8310897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default6]:[rank6]: frame #1: + 0x5b3a23e (0x7f1421e2d23e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #2: c10d::TCPStore::doWait(c10::ArrayRef, std::chrono::duration >) + 0x2c7 (0x7f1421e27c87 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 (0x7f1421e27f82 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #4: c10d::TCPStore::get(std::string const&) + 0xa1 (0x7f1421e28fd1 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #5: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f1421ddd371 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 (0x7f1421ddd371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #7: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f1421ddd371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #8: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f1421ddd371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #9: c10d::ProcessGroupNCCL::broadcastUniqueNCCLID(ncclUniqueId*, bool, std::string const&, int) + 0xa9 (0x7f13e95ea189 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 (0x7f13e95f1610 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 >&, int, int) + 0x5f8 (0x7f13e9610978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:[rank6]: frame #12: + 0x5adc309 (0x7f1421dcf309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #13: + 0x5ae6f10 (0x7f1421dd9f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #14: + 0x5ae6fa5 (0x7f1421dd9fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #15: + 0x5124446 (0x7f1421417446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #16: + 0x1acf4b8 (0x7f141ddc24b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #17: + 0x5aee004 (0x7f1421de1004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #18: + 0x5af36b5 (0x7f1421de66b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #19: + 0xd2631e (0x7f14349d031e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default6]:[rank6]: frame #20: + 0x47def4 (0x7f1434127ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default6]:[rank6]: frame #21: + 0x1445a6 (0x5567a60275a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #22: _PyObject_MakeTpCall + 0x26b (0x5567a6020a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #23: + 0x150866 (0x5567a6033866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x5567a601c142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #25: _PyFunction_Vectorcall + 0x6c (0x5567a6027a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #26: PyObject_Call + 0xbc (0x5567a6033f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x5567a601a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #28: _PyFunction_Vectorcall + 0x6c (0x5567a6027a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x5567a60188fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #30: + 0x150582 (0x5567a6033582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x5567a60188fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #32: + 0x150582 (0x5567a6033582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x5567a60188fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #34: + 0x150582 (0x5567a6033582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x5567a60188fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x5567a601ff50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #37: _PyObject_Call_Prepend + 0x69 (0x5567a6031c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #38: + 0x211239 (0x5567a60f4239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #39: _PyObject_MakeTpCall + 0x26b (0x5567a6020a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x5567a601c3e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #41: _PyFunction_Vectorcall + 0x6c (0x5567a6027a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x5567a6017c5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #43: _PyFunction_Vectorcall + 0x6c (0x5567a6027a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x5567a60188fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #45: + 0x150582 (0x5567a6033582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #46: PyObject_Call + 0xbc (0x5567a6033f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x5567a601a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #48: + 0x150582 (0x5567a6033582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #49: PyObject_Call + 0xbc (0x5567a6033f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x5567a601a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #51: _PyFunction_Vectorcall + 0x6c (0x5567a6027a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x5567a6020007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #53: _PyObject_Call_Prepend + 0x69 (0x5567a6031c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #54: + 0x211239 (0x5567a60f4239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #55: PyObject_Call + 0x207 (0x5567a6034067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x5567a601a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #57: + 0x150582 (0x5567a6033582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x5567a60188fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #59: + 0x150582 (0x5567a6033582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #60: PyObject_Call + 0xbc (0x5567a6033f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x5567a601a2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #62: + 0x150582 (0x5567a6033582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #63: PyObject_Call + 0xbc (0x5567a6033f1c 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. [default4]:[rank4]: Traceback (most recent call last): [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default4]:[rank4]: trainer.train(dataloader) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default4]:[rank4]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default4]:[rank4]: outputs = self.pipeline_engine.train_batch_iter( [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 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 (0x7fcf91ea3897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default4]:[rank4]: frame #1: + 0x5b3a23e (0x7fcfcb9c023e 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::chrono::duration >) + 0x2c7 (0x7fcfcb9bac87 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 (0x7fcfcb9baf82 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 (0x7fcfcb9bbfd1 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 (0x7fcfcb970371 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 (0x7fcfcb970371 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 (0x7fcfcb970371 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 (0x7fcfcb970371 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 (0x7fcf9317d189 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 (0x7fcf93184610 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 >&, int, int) + 0x5f8 (0x7fcf931a3978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:[rank4]: frame #12: + 0x5adc309 (0x7fcfcb962309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #13: + 0x5ae6f10 (0x7fcfcb96cf10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #14: + 0x5ae6fa5 (0x7fcfcb96cfa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #15: + 0x5124446 (0x7fcfcafaa446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #16: + 0x1acf4b8 (0x7fcfc79554b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #17: + 0x5aee004 (0x7fcfcb974004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #18: + 0x5af36b5 (0x7fcfcb9796b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #19: + 0xd2631e (0x7fcfde56331e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default4]:[rank4]: frame #20: + 0x47def4 (0x7fcfddcbaef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default4]:[rank4]: frame #21: + 0x1445a6 (0x561efd0ff5a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #22: _PyObject_MakeTpCall + 0x26b (0x561efd0f8a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #23: + 0x150866 (0x561efd10b866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x561efd0f4142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #25: _PyFunction_Vectorcall + 0x6c (0x561efd0ffa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #26: PyObject_Call + 0xbc (0x561efd10bf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x561efd0f22b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #28: _PyFunction_Vectorcall + 0x6c (0x561efd0ffa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x561efd0f08fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #30: + 0x150582 (0x561efd10b582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x561efd0f08fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #32: + 0x150582 (0x561efd10b582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x561efd0f08fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #34: + 0x150582 (0x561efd10b582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x561efd0f08fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x561efd0f7f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #37: _PyObject_Call_Prepend + 0x69 (0x561efd109c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #38: + 0x211239 (0x561efd1cc239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #39: _PyObject_MakeTpCall + 0x26b (0x561efd0f8a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x561efd0f43e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #41: _PyFunction_Vectorcall + 0x6c (0x561efd0ffa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x561efd0efc5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #43: _PyFunction_Vectorcall + 0x6c (0x561efd0ffa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x561efd0f08fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #45: + 0x150582 (0x561efd10b582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #46: PyObject_Call + 0xbc (0x561efd10bf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x561efd0f22b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #48: + 0x150582 (0x561efd10b582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #49: PyObject_Call + 0xbc (0x561efd10bf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x561efd0f22b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #51: _PyFunction_Vectorcall + 0x6c (0x561efd0ffa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x561efd0f8007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #53: _PyObject_Call_Prepend + 0x69 (0x561efd109c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #54: + 0x211239 (0x561efd1cc239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #55: PyObject_Call + 0x207 (0x561efd10c067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x561efd0f22b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #57: + 0x150582 (0x561efd10b582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x561efd0f08fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #59: + 0x150582 (0x561efd10b582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #60: PyObject_Call + 0xbc (0x561efd10bf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x561efd0f22b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #62: + 0x150582 (0x561efd10b582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #63: PyObject_Call + 0xbc (0x561efd10bf1c 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. [default7]:[rank7]: Traceback (most recent call last): [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default7]:[rank7]: trainer.train(dataloader) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default7]:[rank7]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default7]:[rank7]: outputs = self.pipeline_engine.train_batch_iter( [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 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 (0x7fd371b3e897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default7]:[rank7]: frame #1: + 0x5b3a23e (0x7fd3ab65b23e 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::chrono::duration >) + 0x2c7 (0x7fd3ab655c87 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 (0x7fd3ab655f82 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 (0x7fd3ab656fd1 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 (0x7fd3ab60b371 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 (0x7fd3ab60b371 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 (0x7fd3ab60b371 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 (0x7fd3ab60b371 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 (0x7fd372e18189 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 (0x7fd372e1f610 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 >&, int, int) + 0x5f8 (0x7fd372e3e978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:[rank7]: frame #12: + 0x5adc309 (0x7fd3ab5fd309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #13: + 0x5ae6f10 (0x7fd3ab607f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #14: + 0x5ae6fa5 (0x7fd3ab607fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #15: + 0x5124446 (0x7fd3aac45446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #16: + 0x1acf4b8 (0x7fd3a75f04b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #17: + 0x5aee004 (0x7fd3ab60f004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #18: + 0x5af36b5 (0x7fd3ab6146b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #19: + 0xd2631e (0x7fd3be1fe31e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default7]:[rank7]: frame #20: + 0x47def4 (0x7fd3bd955ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default7]:[rank7]: frame #21: + 0x1445a6 (0x563e11be35a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #22: _PyObject_MakeTpCall + 0x26b (0x563e11bdca6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #23: + 0x150866 (0x563e11bef866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x563e11bd8142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #25: _PyFunction_Vectorcall + 0x6c (0x563e11be3a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #26: PyObject_Call + 0xbc (0x563e11beff1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x563e11bd62b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #28: _PyFunction_Vectorcall + 0x6c (0x563e11be3a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x563e11bd48fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #30: + 0x150582 (0x563e11bef582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x563e11bd48fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #32: + 0x150582 (0x563e11bef582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x563e11bd48fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #34: + 0x150582 (0x563e11bef582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x563e11bd48fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x563e11bdbf50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #37: _PyObject_Call_Prepend + 0x69 (0x563e11bedc39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #38: + 0x211239 (0x563e11cb0239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #39: _PyObject_MakeTpCall + 0x26b (0x563e11bdca6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x563e11bd83e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #41: _PyFunction_Vectorcall + 0x6c (0x563e11be3a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x563e11bd3c5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #43: _PyFunction_Vectorcall + 0x6c (0x563e11be3a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x563e11bd48fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #45: + 0x150582 (0x563e11bef582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #46: PyObject_Call + 0xbc (0x563e11beff1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x563e11bd62b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #48: + 0x150582 (0x563e11bef582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #49: PyObject_Call + 0xbc (0x563e11beff1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x563e11bd62b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #51: _PyFunction_Vectorcall + 0x6c (0x563e11be3a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x563e11bdc007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #53: _PyObject_Call_Prepend + 0x69 (0x563e11bedc39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #54: + 0x211239 (0x563e11cb0239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #55: PyObject_Call + 0x207 (0x563e11bf0067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x563e11bd62b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #57: + 0x150582 (0x563e11bef582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x563e11bd48fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #59: + 0x150582 (0x563e11bef582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #60: PyObject_Call + 0xbc (0x563e11beff1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x563e11bd62b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #62: + 0x150582 (0x563e11bef582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #63: PyObject_Call + 0xbc (0x563e11beff1c 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. W0703 21:07:54.617000 140562804610880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1811570 closing signal SIGTERM W0703 21:07:54.618000 140562804610880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1811571 closing signal SIGTERM W0703 21:07:54.618000 140562804610880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1811572 closing signal SIGTERM W0703 21:07:54.618000 140562804610880 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1811573 closing signal SIGTERM E0703 21:07:55.841000 140562804610880 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 1811566) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10 Traceback (most recent call last): File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in sys.exit(main()) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper return f(*args, **kwargs) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main run(args) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run elastic_launch( File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__ return launch_agent(self._config, self._entrypoint, list(args)) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent raise ChildFailedError( torch.distributed.elastic.multiprocessing.errors.ChildFailedError: ============================================================ /fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED ------------------------------------------------------------ Failures: [1]: time : 2024-07-03_21:07:54 host : ip-26-0-162-233.ec2.internal rank : 1 (local_rank: 1) exitcode : 1 (pid: 1811567) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html [2]: time : 2024-07-03_21:07:54 host : ip-26-0-162-233.ec2.internal rank : 2 (local_rank: 2) exitcode : 1 (pid: 1811568) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html [3]: time : 2024-07-03_21:07:54 host : ip-26-0-162-233.ec2.internal rank : 3 (local_rank: 3) exitcode : 1 (pid: 1811569) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html ------------------------------------------------------------ Root Cause (first observed failure): [0]: time : 2024-07-03_21:07:54 host : ip-26-0-162-233.ec2.internal rank : 0 (local_rank: 0) exitcode : 1 (pid: 1811566) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html ============================================================ srun: error: ip-26-0-162-233: task 0: Exited with exit code 1 Consider using `hf_transfer` for faster uploads. This solution comes with some limitations. See https://huggingface.co/docs/huggingface_hub/hf_transfer for more details.