======================== START TIME: Wed Jul 3 21:08:06 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 21:08:12.599000 140430520641344 torch/distributed/run.py:757] W0703 21:08:12.599000 140430520641344 torch/distributed/run.py:757] ***************************************** W0703 21:08:12.599000 140430520641344 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 21:08:12.599000 140430520641344 torch/distributed/run.py:757] ***************************************** [default0]:07/03/2024 21:08:33 [WARNING|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Vocab Size Padding] Padded vocab (size: 50257) with 3 dummy tokens (new size: 50260) [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Config: [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Config(general=GeneralArgs(project='bench_cluster', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: run='%date_%jobid', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: seed=42, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: step=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: consumed_train_samples=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: benchmark_csv_path=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: ignore_sanity_checks=True), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: parallelism=ParallelismArgs(dp=1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: pp=2, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: tp=4, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: pp_engine=, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: tp_mode=, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: tp_linear_async_communication=False, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: expert_parallel_size=1), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: eos_token_id=2, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: hidden_act='silu', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: hidden_size=2048, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: initializer_range=0.02, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: intermediate_size=4096, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: is_llama_config=True, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: max_position_embeddings=4096, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: num_attention_heads=32, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: num_hidden_layers=24, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: num_key_value_heads=32, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: pad_token_id=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: pretraining_tp=1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: rms_norm_eps=1e-05, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: rope_scaling=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: rope_theta=10000.0, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: tie_word_embeddings=True, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: use_cache=True, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: vocab_size=50260), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: init_method=RandomInit(std=0.025), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: dtype=torch.bfloat16, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: make_vocab_size_divisible_by=1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: ddp_bucket_cap_mb=25), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: tokenizer_revision=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: tokenizer_max_length=None), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: checkpoint_interval=100000, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: save_initial_state=False, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: resume_checkpoint_path=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: checkpoints_path_is_shared_file_system=False), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: logging=LoggingArgs(log_level='info', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: log_level_replica='info', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: iteration_step_info_interval=1), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: tokens=TokensArgs(sequence_length=4096, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: train_steps=20, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: micro_batch_size=512, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: batch_accumulation_per_replica=2, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: val_check_interval=-1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: limit_val_batches=0, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: limit_test_batches=0), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: adam_beta1=0.9, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: adam_beta2=0.95, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: torch_adam_is_fused=True, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: name='adamW'), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: zero_stage=1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: weight_decay=0.01, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: clip_grad=1.0, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: accumulate_grad_in_fp32=True, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: lr_warmup_steps=1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: lr_warmup_style='linear', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: lr_decay_style='linear', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: lr_decay_steps=19, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: lr_decay_starting_step=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: min_decay_lr=1e-05)), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: data_stages=[DatasetStageArgs(name='Training Stage', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: start_training_step=1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: hf_dataset_splits='train', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: hf_dataset_config_name=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: dataset_processing_num_proc_per_process=64, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: dataset_overwrite_cache=False, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: text_column_name='text'), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: seed=42, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: num_loading_workers=0))], [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-512')), [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: lighteval=None) [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Model Config: [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: LlamaConfig(bos_token_id=1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: eos_token_id=2, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: hidden_act='silu', [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: hidden_size=2048, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: initializer_range=0.02, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: intermediate_size=4096, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: is_llama_config=True, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: max_position_embeddings=4096, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: num_attention_heads=32, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: num_hidden_layers=24, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: num_key_value_heads=32, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: pad_token_id=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: pretraining_tp=1, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: rms_norm_eps=1e-05, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: rope_scaling=None, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: rope_theta=10000.0, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: tie_word_embeddings=True, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: use_cache=True, [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: vocab_size=50260) [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Building model.. [default0]:07/03/2024 21:08:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Setting PP block ranks... [default0]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Total number of parameters: 1.21G (2313.42MiB) [default0]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Local number of parameters: 173M (329.19MiB) [default0]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default0]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: No checkpoint path provided. [default0]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Parametrizing model parameters using StandardParametrizator [default7]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=3|ip-26-0-174-36]: Local number of parameters: 131M (249.16MiB) [default7]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=3|ip-26-0-174-36]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default7]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=3|ip-26-0-174-36]: No checkpoint path provided. [default3]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=3|ip-26-0-174-36]: Local number of parameters: 173M (329.19MiB) [default3]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=3|ip-26-0-174-36]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default3]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=3|ip-26-0-174-36]: No checkpoint path provided. [default4]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=0|ip-26-0-174-36]: Local number of parameters: 131M (249.16MiB) [default4]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=0|ip-26-0-174-36]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default4]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=0|ip-26-0-174-36]: No checkpoint path provided. [default1]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=1|ip-26-0-174-36]: Local number of parameters: 173M (329.19MiB) [default1]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=1|ip-26-0-174-36]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default1]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=1|ip-26-0-174-36]: No checkpoint path provided. [default2]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=2|ip-26-0-174-36]: Local number of parameters: 173M (329.19MiB) [default2]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=2|ip-26-0-174-36]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default2]:07/03/2024 21:08:47 [INFO|DP=0|PP=0|TP=2|ip-26-0-174-36]: No checkpoint path provided. [default5]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=1|ip-26-0-174-36]: Local number of parameters: 131M (249.16MiB) [default5]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=1|ip-26-0-174-36]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default5]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=1|ip-26-0-174-36]: No checkpoint path provided. [default6]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=2|ip-26-0-174-36]: Local number of parameters: 131M (249.16MiB) [default6]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=2|ip-26-0-174-36]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default6]:07/03/2024 21:08:47 [INFO|DP=0|PP=1|TP=2|ip-26-0-174-36]: No checkpoint path provided. [default0]:07/03/2024 21:08:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Optimizer Building] Using LearningRateForSP as learning rate [default0]:07/03/2024 21:08:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [ZeRO sharding] Size of optimizer params per rank: [default0]:07/03/2024 21:08:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [ZeRO sharding] DP Rank 0 has 173M out of 173M (100.00%) params' optimizer states [default0]:07/03/2024 21:08:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples [default0]:07/03/2024 21:08:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Using `datasets` library [default0]:07/03/2024 21:08:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4') [default0]:07/03/2024 21:08:49 [WARNING|DP=0|PP=0|TP=0|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty. [default0]:Repo card metadata block was not found. Setting CardData to empty. [default0]:07/03/2024 21:08:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Training Plan] There are 1 training stages [default0]:07/03/2024 21:08:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Stage Training Stage] start from step 1 [default0]:07/03/2024 21:08:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [default0]:07/03/2024 21:08:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: [Start training] datetime: 2024-07-03 21:08:51.525881 | mbs: 512 | grad_accum: 2 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0 [default0]:07/03/2024 21:08:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps [default0]:07/03/2024 21:08:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-174-36]: Memory usage: 1660.89MiB. Peak allocated 1660.89MiB. Peak reserved: 1668.00MiB [default7]:07/03/2024 21:08:51 [WARNING|DP=0|PP=1|TP=3|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty. [default4]:07/03/2024 21:08:51 [WARNING|DP=0|PP=1|TP=0|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty. [default1]:Repo card metadata block was not found. Setting CardData to empty. [default3]:07/03/2024 21:08:51 [WARNING|DP=0|PP=0|TP=3|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty. [default1]:07/03/2024 21:08:51 [WARNING|DP=0|PP=0|TP=1|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty. [default2]:07/03/2024 21:08:51 [WARNING|DP=0|PP=0|TP=2|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty. [default7]:Repo card metadata block was not found. Setting CardData to empty. [default5]:07/03/2024 21:08:51 [WARNING|DP=0|PP=1|TP=1|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty. [default4]:Repo card metadata block was not found. Setting CardData to empty. [default6]:07/03/2024 21:08:51 [WARNING|DP=0|PP=1|TP=2|ip-26-0-174-36]: Repo card metadata block was not found. Setting CardData to empty. [default5]:Repo card metadata block was not found. Setting CardData to empty. [default2]:Repo card metadata block was not found. Setting CardData to empty. [default6]:Repo card metadata block was not found. Setting CardData to empty. [default3]:Repo card metadata block was not found. Setting CardData to empty. [default1]:[rank1]: Traceback (most recent call last): [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default1]:[rank1]: trainer.train(dataloader) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default1]:[rank1]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default1]:[rank1]: outputs = self.pipeline_engine.train_batch_iter( [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default1]:[rank1]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default1]:[rank1]: output = model(**micro_batch) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank1]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank1]: return forward_call(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default1]:[rank1]: sharded_logits = self.model( [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank1]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank1]: return forward_call(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default1]:[rank1]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default1]:[rank1]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank1]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank1]: return forward_call(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward [default1]:[rank1]: output = self.pp_block(**new_kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank1]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank1]: return forward_call(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 631, in forward [default1]:[rank1]: output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank1]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank1]: return forward_call(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 360, in forward [default1]:[rank1]: qkv_states = self.qkv_proj( [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank1]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank1]: return forward_call(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward [default1]:[rank1]: return column_linear( [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear [default1]:[rank1]: return F.linear(input, weight, bias) [default1]:[rank1]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.00 GiB. GPU  has a total capacity of 79.33 GiB of which 185.94 MiB is free. Including non-PyTorch memory, this process has 79.14 GiB memory in use. Of the allocated memory 63.76 GiB is allocated by PyTorch, and 3.92 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) [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 360, in forward [default0]:[rank0]: qkv_states = self.qkv_proj( [default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default0]:[rank0]: return self._call_impl(*args, **kwargs) [default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default0]:[rank0]: return forward_call(*args, **kwargs) [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward [default0]:[rank0]: return column_linear( [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear [default0]:[rank0]: return F.linear(input, weight, bias) [default0]:[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.00 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 [default2]:[rank2]: trainer.train(dataloader) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default2]:[rank2]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default2]:[rank2]: outputs = self.pipeline_engine.train_batch_iter( [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default2]:[rank2]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default2]:[rank2]: output = model(**micro_batch) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default2]:[rank2]: sharded_logits = self.model( [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default2]:[rank2]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default2]:[rank2]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward [default2]:[rank2]: output = self.pp_block(**new_kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 631, in forward [default2]:[rank2]: output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 360, in forward [default2]:[rank2]: qkv_states = self.qkv_proj( [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward [default2]:[rank2]: return column_linear( [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear [default2]:[rank2]: return F.linear(input, weight, bias) [default2]:[rank2]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.00 GiB. GPU  has a total capacity of 79.33 GiB of which 185.94 MiB is free. Including non-PyTorch memory, this process has 79.14 GiB memory in use. Of the allocated memory 63.76 GiB is allocated by PyTorch, and 3.92 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) [default3]:[rank3]: Traceback (most recent call last): [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default3]:[rank3]: trainer.train(dataloader) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default3]:[rank3]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default3]:[rank3]: outputs = self.pipeline_engine.train_batch_iter( [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default3]:[rank3]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default3]:[rank3]: output = model(**micro_batch) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank3]: return forward_call(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default3]:[rank3]: sharded_logits = self.model( [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank3]: return forward_call(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default3]:[rank3]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default3]:[rank3]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank3]: return forward_call(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward [default3]:[rank3]: output = self.pp_block(**new_kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank3]: return forward_call(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 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 [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank3]: return forward_call(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 360, in forward [default3]:[rank3]: qkv_states = self.qkv_proj( [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank3]: return forward_call(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward [default3]:[rank3]: return column_linear( [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear [default3]:[rank3]: return F.linear(input, weight, bias) [default3]:[rank3]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.00 GiB. GPU  has a total capacity of 79.33 GiB of which 425.94 MiB is free. Including non-PyTorch memory, this process has 78.90 GiB memory in use. Of the allocated memory 63.76 GiB is allocated by PyTorch, and 3.92 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) [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 (0x7f71a2e47897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default7]:[rank7]: frame #1: + 0x5b3a23e (0x7f71dc96423e 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 (0x7f71dc95ec87 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 (0x7f71dc95ef82 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 (0x7f71dc95ffd1 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 (0x7f71dc914371 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 (0x7f71dc914371 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 (0x7f71dc914371 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 (0x7f71dc914371 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 (0x7f71a4121189 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 (0x7f71a4128610 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 (0x7f71a4147978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:[rank7]: frame #12: + 0x5adc309 (0x7f71dc906309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #13: + 0x5ae6f10 (0x7f71dc910f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #14: + 0x5ae6fa5 (0x7f71dc910fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #15: + 0x5124446 (0x7f71dbf4e446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #16: + 0x1acf4b8 (0x7f71d88f94b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #17: + 0x5aee004 (0x7f71dc918004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #18: + 0x5af36b5 (0x7f71dc91d6b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #19: + 0xd2631e (0x7f71ef50731e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default7]:[rank7]: frame #20: + 0x47def4 (0x7f71eec5eef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default7]:[rank7]: frame #21: + 0x1445a6 (0x55dbf78ea5a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #22: _PyObject_MakeTpCall + 0x26b (0x55dbf78e3a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #23: + 0x150866 (0x55dbf78f6866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x55dbf78df142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #25: _PyFunction_Vectorcall + 0x6c (0x55dbf78eaa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #26: PyObject_Call + 0xbc (0x55dbf78f6f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x55dbf78dd2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #28: _PyFunction_Vectorcall + 0x6c (0x55dbf78eaa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x55dbf78db8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #30: + 0x150582 (0x55dbf78f6582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x55dbf78db8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #32: + 0x150582 (0x55dbf78f6582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x55dbf78db8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #34: + 0x150582 (0x55dbf78f6582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x55dbf78db8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x55dbf78e2f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #37: _PyObject_Call_Prepend + 0x69 (0x55dbf78f4c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #38: + 0x211239 (0x55dbf79b7239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #39: _PyObject_MakeTpCall + 0x26b (0x55dbf78e3a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x55dbf78df3e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #41: _PyFunction_Vectorcall + 0x6c (0x55dbf78eaa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x55dbf78dac5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #43: _PyFunction_Vectorcall + 0x6c (0x55dbf78eaa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x55dbf78db8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #45: + 0x150582 (0x55dbf78f6582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #46: PyObject_Call + 0xbc (0x55dbf78f6f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x55dbf78dd2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #48: + 0x150582 (0x55dbf78f6582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #49: PyObject_Call + 0xbc (0x55dbf78f6f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x55dbf78dd2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #51: _PyFunction_Vectorcall + 0x6c (0x55dbf78eaa2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x55dbf78e3007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #53: _PyObject_Call_Prepend + 0x69 (0x55dbf78f4c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #54: + 0x211239 (0x55dbf79b7239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #55: PyObject_Call + 0x207 (0x55dbf78f7067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x55dbf78dd2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #57: + 0x150582 (0x55dbf78f6582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x55dbf78db8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #59: + 0x150582 (0x55dbf78f6582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #60: PyObject_Call + 0xbc (0x55dbf78f6f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x55dbf78dd2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #62: + 0x150582 (0x55dbf78f6582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #63: PyObject_Call + 0xbc (0x55dbf78f6f1c 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. [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 (0x7f7eb3c65897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default4]:[rank4]: frame #1: + 0x5b3a23e (0x7f7eed78223e 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 (0x7f7eed77cc87 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 (0x7f7eed77cf82 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 (0x7f7eed77dfd1 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 (0x7f7eed732371 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 (0x7f7eed732371 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 (0x7f7eed732371 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 (0x7f7eed732371 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 (0x7f7eb4f3f189 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 (0x7f7eb4f46610 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 (0x7f7eb4f65978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:[rank4]: frame #12: + 0x5adc309 (0x7f7eed724309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #13: + 0x5ae6f10 (0x7f7eed72ef10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #14: + 0x5ae6fa5 (0x7f7eed72efa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #15: + 0x5124446 (0x7f7eecd6c446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #16: + 0x1acf4b8 (0x7f7ee97174b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #17: + 0x5aee004 (0x7f7eed736004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #18: + 0x5af36b5 (0x7f7eed73b6b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #19: + 0xd2631e (0x7f7f0032531e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default4]:[rank4]: frame #20: + 0x47def4 (0x7f7effa7cef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default4]:[rank4]: frame #21: + 0x1445a6 (0x559e4d2bd5a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #22: _PyObject_MakeTpCall + 0x26b (0x559e4d2b6a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #23: + 0x150866 (0x559e4d2c9866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x559e4d2b2142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #25: _PyFunction_Vectorcall + 0x6c (0x559e4d2bda2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #26: PyObject_Call + 0xbc (0x559e4d2c9f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x559e4d2b02b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #28: _PyFunction_Vectorcall + 0x6c (0x559e4d2bda2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x559e4d2ae8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #30: + 0x150582 (0x559e4d2c9582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x559e4d2ae8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #32: + 0x150582 (0x559e4d2c9582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x559e4d2ae8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #34: + 0x150582 (0x559e4d2c9582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x559e4d2ae8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x559e4d2b5f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #37: _PyObject_Call_Prepend + 0x69 (0x559e4d2c7c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #38: + 0x211239 (0x559e4d38a239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #39: _PyObject_MakeTpCall + 0x26b (0x559e4d2b6a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x559e4d2b23e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #41: _PyFunction_Vectorcall + 0x6c (0x559e4d2bda2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x559e4d2adc5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #43: _PyFunction_Vectorcall + 0x6c (0x559e4d2bda2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x559e4d2ae8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #45: + 0x150582 (0x559e4d2c9582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #46: PyObject_Call + 0xbc (0x559e4d2c9f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x559e4d2b02b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #48: + 0x150582 (0x559e4d2c9582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #49: PyObject_Call + 0xbc (0x559e4d2c9f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x559e4d2b02b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #51: _PyFunction_Vectorcall + 0x6c (0x559e4d2bda2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x559e4d2b6007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #53: _PyObject_Call_Prepend + 0x69 (0x559e4d2c7c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #54: + 0x211239 (0x559e4d38a239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #55: PyObject_Call + 0x207 (0x559e4d2ca067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x559e4d2b02b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #57: + 0x150582 (0x559e4d2c9582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x559e4d2ae8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #59: + 0x150582 (0x559e4d2c9582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #60: PyObject_Call + 0xbc (0x559e4d2c9f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x559e4d2b02b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #62: + 0x150582 (0x559e4d2c9582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #63: PyObject_Call + 0xbc (0x559e4d2c9f1c 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. [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 [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 [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) [default5]:[rank5]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [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( [default6]:[rank6]: output = model(**micro_batch) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter [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 [default5]:[rank5]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [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 [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 [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 [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 [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 [default5]:[rank5]: sharded_logits = self.model( [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default5]:[rank5]: 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.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default5]:[rank5]: return self._call_impl(*args, **kwargs) [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) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default6]:[rank6]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default5]:[rank5]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default6]:[rank6]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default6]:[rank6]: pipeline_state.run_communication() [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: recv_activation_tensor = recv_activation() [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default5]:[rank5]: return forward_call(*args, **kwargs) [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) [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 [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) [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() [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 246, in _recv_meta [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): [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 [default5]:[rank5]: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fd703b3f897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [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 [default5]:[rank5]: frame #1: + 0x5b3a23e (0x7fd73d65c23e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [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 (0x7fd5d087b897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default5]:[rank5]: frame #2: c10d::TCPStore::doWait(c10::ArrayRef, std::chrono::duration >) + 0x2c7 (0x7fd73d656c87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #1: + 0x5b3a23e (0x7fd60a39823e 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 (0x7fd73d656f82 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 (0x7fd60a392c87 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 (0x7fd73d657fd1 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 (0x7fd73d60c371 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 (0x7fd60a392f82 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 (0x7fd73d60c371 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 (0x7fd60a393fd1 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 (0x7fd60a348371 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 (0x7fd60a348371 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 (0x7fd60a348371 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 (0x7fd60a348371 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 (0x7fd5d1b55189 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 (0x7fd5d1b5c610 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 (0x7fd5d1b7b978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:[rank5]: frame #7: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fd73d60c371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #12: + 0x5adc309 (0x7fd60a33a309 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 (0x7fd73d60c371 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 (0x7fd704e19189 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:[rank6]: frame #13: + 0x5ae6f10 (0x7fd60a344f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #10: c10d::ProcessGroupNCCL::getNCCLComm(std::string const&, c10::Device&, c10d::OpType, int, bool) + 0xc50 (0x7fd704e20610 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 (0x7fd704e3f978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:[rank5]: frame #12: + 0x5adc309 (0x7fd73d5fe309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #13: + 0x5ae6f10 (0x7fd73d608f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #14: + 0x5ae6fa5 (0x7fd60a344fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #15: + 0x5124446 (0x7fd609982446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #14: + 0x5ae6fa5 (0x7fd73d608fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #16: + 0x1acf4b8 (0x7fd60632d4b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #15: + 0x5124446 (0x7fd73cc46446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #17: + 0x5aee004 (0x7fd60a34c004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #18: + 0x5af36b5 (0x7fd60a3516b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #19: + 0xd2631e (0x7fd61cf3b31e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default6]:[rank6]: frame #20: + 0x47def4 (0x7fd61c692ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default5]:[rank5]: frame #16: + 0x1acf4b8 (0x7fd7395f14b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #17: + 0x5aee004 (0x7fd73d610004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #21: + 0x1445a6 (0x55a73f6fc5a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #18: + 0x5af36b5 (0x7fd73d6156b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #22: _PyObject_MakeTpCall + 0x26b (0x55a73f6f5a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #19: + 0xd2631e (0x7fd7501ff31e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default6]:[rank6]: frame #23: + 0x150866 (0x55a73f708866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #20: + 0x47def4 (0x7fd74f956ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default6]:[rank6]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x55a73f6f1142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #21: + 0x1445a6 (0x564433e715a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #25: _PyFunction_Vectorcall + 0x6c (0x55a73f6fca2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #22: _PyObject_MakeTpCall + 0x26b (0x564433e6aa6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #26: PyObject_Call + 0xbc (0x55a73f708f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #23: + 0x150866 (0x564433e7d866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x55a73f6ef2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x564433e66142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #28: _PyFunction_Vectorcall + 0x6c (0x55a73f6fca2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #25: _PyFunction_Vectorcall + 0x6c (0x564433e71a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x55a73f6ed8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #26: PyObject_Call + 0xbc (0x564433e7df1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #30: + 0x150582 (0x55a73f708582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x564433e642b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x55a73f6ed8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #28: _PyFunction_Vectorcall + 0x6c (0x564433e71a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x564433e628fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #32: + 0x150582 (0x55a73f708582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #30: + 0x150582 (0x564433e7d582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x55a73f6ed8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x564433e628fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #34: + 0x150582 (0x55a73f708582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #32: + 0x150582 (0x564433e7d582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x55a73f6ed8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x55a73f6f4f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #37: _PyObject_Call_Prepend + 0x69 (0x55a73f706c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x564433e628fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #38: + 0x211239 (0x55a73f7c9239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #39: _PyObject_MakeTpCall + 0x26b (0x55a73f6f5a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x55a73f6f13e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #41: _PyFunction_Vectorcall + 0x6c (0x55a73f6fca2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x55a73f6ecc5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #43: _PyFunction_Vectorcall + 0x6c (0x55a73f6fca2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #34: + 0x150582 (0x564433e7d582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x55a73f6ed8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x564433e628fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #45: + 0x150582 (0x55a73f708582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x564433e69f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #37: _PyObject_Call_Prepend + 0x69 (0x564433e7bc39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #38: + 0x211239 (0x564433f3e239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #39: _PyObject_MakeTpCall + 0x26b (0x564433e6aa6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x564433e663e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #41: _PyFunction_Vectorcall + 0x6c (0x564433e71a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x564433e61c5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #43: _PyFunction_Vectorcall + 0x6c (0x564433e71a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x564433e628fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #46: PyObject_Call + 0xbc (0x55a73f708f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x55a73f6ef2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #48: + 0x150582 (0x55a73f708582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #45: + 0x150582 (0x564433e7d582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #46: PyObject_Call + 0xbc (0x564433e7df1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x564433e642b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #49: PyObject_Call + 0xbc (0x55a73f708f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x55a73f6ef2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #48: + 0x150582 (0x564433e7d582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #49: PyObject_Call + 0xbc (0x564433e7df1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x564433e642b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #51: _PyFunction_Vectorcall + 0x6c (0x564433e71a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x564433e6a007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #53: _PyObject_Call_Prepend + 0x69 (0x564433e7bc39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #54: + 0x211239 (0x564433f3e239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #51: _PyFunction_Vectorcall + 0x6c (0x55a73f6fca2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #55: PyObject_Call + 0x207 (0x564433e7e067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x55a73f6f5007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #53: _PyObject_Call_Prepend + 0x69 (0x55a73f706c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x564433e642b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #54: + 0x211239 (0x55a73f7c9239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #57: + 0x150582 (0x564433e7d582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #55: PyObject_Call + 0x207 (0x55a73f709067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x564433e628fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x55a73f6ef2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #59: + 0x150582 (0x564433e7d582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #57: + 0x150582 (0x55a73f708582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #60: PyObject_Call + 0xbc (0x564433e7df1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x55a73f6ed8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x564433e642b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #59: + 0x150582 (0x55a73f708582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #62: + 0x150582 (0x564433e7d582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #60: PyObject_Call + 0xbc (0x55a73f708f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #63: PyObject_Call + 0xbc (0x564433e7df1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x55a73f6ef2b3 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]: frame #62: + 0x150582 (0x55a73f708582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #63: PyObject_Call + 0xbc (0x55a73f708f1c 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. W0703 21:09:02.767000 140430520641344 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 217791 closing signal SIGTERM W0703 21:09:02.767000 140430520641344 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 217792 closing signal SIGTERM W0703 21:09:02.767000 140430520641344 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 217793 closing signal SIGTERM W0703 21:09:02.768000 140430520641344 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 217794 closing signal SIGTERM E0703 21:09:03.992000 140430520641344 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 217787) 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_21:09:02 host : ip-26-0-174-36.ec2.internal rank : 1 (local_rank: 1) exitcode : 1 (pid: 217788) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html [2]: time : 2024-07-03_21:09:02 host : ip-26-0-174-36.ec2.internal rank : 2 (local_rank: 2) exitcode : 1 (pid: 217789) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html [3]: time : 2024-07-03_21:09:02 host : ip-26-0-174-36.ec2.internal rank : 3 (local_rank: 3) exitcode : 1 (pid: 217790) 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_21:09:02 host : ip-26-0-174-36.ec2.internal rank : 0 (local_rank: 0) exitcode : 1 (pid: 217787) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html ============================================================ srun: error: ip-26-0-174-36: task 0: Exited with exit code 1 Consider using `hf_transfer` for faster uploads. This solution comes with some limitations. See https://huggingface.co/docs/huggingface_hub/hf_transfer for more details.