======================== START TIME: Thu Jul 4 02:31:28 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 W0704 02:31:36.822000 140065233516352 torch/distributed/run.py:757] W0704 02:31:36.822000 140065233516352 torch/distributed/run.py:757] ***************************************** W0704 02:31:36.822000 140065233516352 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. W0704 02:31:36.822000 140065233516352 torch/distributed/run.py:757] ***************************************** [default0]:07/04/2024 02:31:58 [WARNING|DP=0|PP=0|TP=0|ip-26-0-161-153]: [Vocab Size Padding] Padded vocab (size: 50257) with 1 dummy tokens (new size: 50258) [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Config: [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Config(general=GeneralArgs(project='bench_cluster', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: run='%date_%jobid', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: seed=42, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: step=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: consumed_train_samples=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: benchmark_csv_path=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: ignore_sanity_checks=True), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: parallelism=ParallelismArgs(dp=2, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: pp=2, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: tp=2, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: pp_engine=, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: tp_mode=, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: tp_linear_async_communication=False, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: expert_parallel_size=1), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: eos_token_id=2, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: hidden_act='silu', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: hidden_size=2048, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: initializer_range=0.02, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: intermediate_size=4096, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: is_llama_config=True, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: max_position_embeddings=4096, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: num_attention_heads=32, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: num_hidden_layers=24, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: num_key_value_heads=32, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: pad_token_id=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: pretraining_tp=1, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: rms_norm_eps=1e-05, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: rope_scaling=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: rope_theta=10000.0, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: tie_word_embeddings=True, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: use_cache=True, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: vocab_size=50258), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: init_method=RandomInit(std=0.025), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: dtype=torch.bfloat16, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: make_vocab_size_divisible_by=1, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: ddp_bucket_cap_mb=25), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: tokenizer_revision=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: tokenizer_max_length=None), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: checkpoint_interval=100000, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: save_initial_state=False, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: resume_checkpoint_path=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: checkpoints_path_is_shared_file_system=False), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: logging=LoggingArgs(log_level='info', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: log_level_replica='info', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: iteration_step_info_interval=1), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: tokens=TokensArgs(sequence_length=4096, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: train_steps=20, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: micro_batch_size=128, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: batch_accumulation_per_replica=4, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: val_check_interval=-1, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: limit_val_batches=0, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: limit_test_batches=0), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: adam_beta1=0.9, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: adam_beta2=0.95, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: torch_adam_is_fused=True, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: name='adamW'), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: zero_stage=1, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: weight_decay=0.01, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: clip_grad=1.0, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: accumulate_grad_in_fp32=True, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: lr_warmup_steps=1, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: lr_warmup_style='linear', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: lr_decay_style='linear', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: lr_decay_steps=19, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: lr_decay_starting_step=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: min_decay_lr=1e-05)), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: data_stages=[DatasetStageArgs(name='Training Stage', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: start_training_step=1, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: hf_dataset_splits='train', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: hf_dataset_config_name=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: dataset_processing_num_proc_per_process=64, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: dataset_overwrite_cache=False, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: text_column_name='text'), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: seed=42, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: num_loading_workers=0))], [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-2_tp-2_pp-2_mbz-128')), [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: lighteval=None) [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Model Config: [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: LlamaConfig(bos_token_id=1, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: eos_token_id=2, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: hidden_act='silu', [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: hidden_size=2048, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: initializer_range=0.02, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: intermediate_size=4096, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: is_llama_config=True, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: max_position_embeddings=4096, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: num_attention_heads=32, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: num_hidden_layers=24, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: num_key_value_heads=32, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: pad_token_id=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: pretraining_tp=1, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: rms_norm_eps=1e-05, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: rope_scaling=None, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: rope_theta=10000.0, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: tie_word_embeddings=True, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: use_cache=True, [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: vocab_size=50258) [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Building model.. [default0]:07/04/2024 02:31:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Setting PP block ranks... [default5]:07/04/2024 02:32:10 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-153]: Local number of parameters: 261M (498.24MiB) [default5]:07/04/2024 02:32:10 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-153]: [After model building] Memory usage: 508.26MiB. Peak allocated: 510.29MiB Peak reserved: 526.00MiB [default7]:07/04/2024 02:32:10 [INFO|DP=1|PP=1|TP=1|ip-26-0-161-153]: No checkpoint path provided. [default5]:07/04/2024 02:32:10 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-153]: No checkpoint path provided. [default0]:07/04/2024 02:32:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Total number of parameters: 1.21G (2313.02MiB) [default0]:07/04/2024 02:32:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Local number of parameters: 345M (658.27MiB) [default0]:07/04/2024 02:32:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [After model building] Memory usage: 672.29MiB. Peak allocated: 674.32MiB Peak reserved: 690.00MiB [default0]:07/04/2024 02:32:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: No checkpoint path provided. [default0]:07/04/2024 02:32:10 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Parametrizing model parameters using StandardParametrizator [default3]:07/04/2024 02:32:10 [INFO|DP=1|PP=0|TP=1|ip-26-0-161-153]: No checkpoint path provided. [default2]:07/04/2024 02:32:10 [INFO|DP=1|PP=0|TP=0|ip-26-0-161-153]: No checkpoint path provided. [default6]:07/04/2024 02:32:10 [INFO|DP=1|PP=1|TP=0|ip-26-0-161-153]: No checkpoint path provided. [default1]:07/04/2024 02:32:10 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-153]: Local number of parameters: 345M (658.27MiB) [default4]:07/04/2024 02:32:10 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-153]: Local number of parameters: 261M (498.24MiB) [default4]:07/04/2024 02:32:10 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-153]: [After model building] Memory usage: 508.26MiB. Peak allocated: 510.29MiB Peak reserved: 526.00MiB [default4]:07/04/2024 02:32:10 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-153]: No checkpoint path provided. [default1]:07/04/2024 02:32:10 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-153]: [After model building] Memory usage: 672.29MiB. Peak allocated: 674.32MiB Peak reserved: 690.00MiB [default1]:07/04/2024 02:32:10 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-153]: No checkpoint path provided. [default0]:07/04/2024 02:32:12 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [Optimizer Building] Using LearningRateForSP as learning rate [default0]:07/04/2024 02:32:12 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [ZeRO sharding] Size of optimizer params per rank: [default0]:07/04/2024 02:32:12 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [ZeRO sharding] DP Rank 0 has 173M out of 345M (50.00%) params' optimizer states [default0]:07/04/2024 02:32:12 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [ZeRO sharding] DP Rank 1 has 173M out of 345M (50.00%) params' optimizer states [default0]:07/04/2024 02:32:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples [default0]:07/04/2024 02:32:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Using `datasets` library [default0]:07/04/2024 02:32:14 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4') [default0]:07/04/2024 02:32:14 [WARNING|DP=0|PP=0|TP=0|ip-26-0-161-153]: Repo card metadata block was not found. Setting CardData to empty. [default0]:Repo card metadata block was not found. Setting CardData to empty. [default0]:07/04/2024 02:32:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [Training Plan] There are 1 training stages [default0]:07/04/2024 02:32:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [Stage Training Stage] start from step 1 [default0]:07/04/2024 02:32:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [default0]:07/04/2024 02:32:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: [Start training] datetime: 2024-07-04 02:32:16.759552 | mbs: 128 | grad_accum: 4 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0 [default0]:07/04/2024 02:32:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps [default0]:07/04/2024 02:32:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-153]: Memory usage: 2647.09MiB. Peak allocated 2647.09MiB. Peak reserved: 2668.00MiB [default3]:07/04/2024 02:32:16 [WARNING|DP=1|PP=0|TP=1|ip-26-0-161-153]: Repo card metadata block was not found. Setting CardData to empty. [default5]:07/04/2024 02:32:16 [WARNING|DP=0|PP=1|TP=1|ip-26-0-161-153]: Repo card metadata block was not found. Setting CardData to empty. [default7]:07/04/2024 02:32:16 [WARNING|DP=1|PP=1|TP=1|ip-26-0-161-153]: Repo card metadata block was not found. Setting CardData to empty. [default2]:07/04/2024 02:32:16 [WARNING|DP=1|PP=0|TP=0|ip-26-0-161-153]: Repo card metadata block was not found. Setting CardData to empty. [default4]:07/04/2024 02:32:16 [WARNING|DP=0|PP=1|TP=0|ip-26-0-161-153]: Repo card metadata block was not found. Setting CardData to empty. [default1]:07/04/2024 02:32:16 [WARNING|DP=0|PP=0|TP=1|ip-26-0-161-153]: Repo card metadata block was not found. Setting CardData to empty. [default1]:Repo card metadata block was not found. Setting CardData to empty. [default5]:Repo card metadata block was not found. Setting CardData to empty. [default2]:Repo card metadata block was not found. Setting CardData to empty. [default7]:Repo card metadata block was not found. Setting CardData to empty. [default4]:Repo card metadata block was not found. Setting CardData to empty. [default3]:Repo card metadata block was not found. Setting CardData to empty. [default6]:Repo card metadata block was not found. Setting CardData to empty. [default6]:07/04/2024 02:32:16 [WARNING|DP=1|PP=1|TP=0|ip-26-0-161-153]: Repo card metadata block was not found. Setting CardData to empty. [default2]:[rank2]: Traceback (most recent call last): [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default2]:[rank2]: trainer.train(dataloader) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default2]:[rank2]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default2]:[rank2]: outputs = self.pipeline_engine.train_batch_iter( [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 252, in train_batch_iter [default2]:[rank2]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default2]:[rank2]: output = model(**micro_batch) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default2]:[rank2]: sharded_logits = self.model( [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default2]:[rank2]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default2]:[rank2]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward [default2]:[rank2]: output = self.pp_block(**new_kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward [default2]:[rank2]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward [default2]:[rank2]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default2]:[rank2]: return self._call_impl(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default2]:[rank2]: return forward_call(*args, **kwargs) [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward [default2]:[rank2]: return self.act(gate_states) * up_states [default2]:[rank2]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU  has a total capacity of 79.33 GiB of which 589.94 MiB is free. Including non-PyTorch memory, this process has 78.74 GiB memory in use. Of the allocated memory 65.73 GiB is allocated by PyTorch, and 2.92 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 637, in forward [default3]:[rank3]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank3]: return forward_call(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward [default3]:[rank3]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default3]:[rank3]: return self._call_impl(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default3]:[rank3]: return forward_call(*args, **kwargs) [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward [default3]:[rank3]: return self.act(gate_states) * up_states [default3]:[rank3]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU  has a total capacity of 79.33 GiB of which 589.94 MiB is free. Including non-PyTorch memory, this process has 78.74 GiB memory in use. Of the allocated memory 65.73 GiB is allocated by PyTorch, and 2.92 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) [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 637, in forward [default1]:[rank1]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank1]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank1]: return forward_call(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward [default1]:[rank1]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default1]:[rank1]: return self._call_impl(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default1]:[rank1]: return forward_call(*args, **kwargs) [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward [default1]:[rank1]: return self.act(gate_states) * up_states [default1]:[rank1]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU  has a total capacity of 79.33 GiB of which 589.94 MiB is free. Including non-PyTorch memory, this process has 78.74 GiB memory in use. Of the allocated memory 65.73 GiB is allocated by PyTorch, and 2.92 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 637, in forward [default0]:[rank0]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] [default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default0]:[rank0]: return self._call_impl(*args, **kwargs) [default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default0]:[rank0]: return forward_call(*args, **kwargs) [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward [default0]:[rank0]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) [default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default0]:[rank0]: return self._call_impl(*args, **kwargs) [default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default0]:[rank0]: return forward_call(*args, **kwargs) [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 128, in forward [default0]:[rank0]: return self.act(gate_states) * up_states [default0]:[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB. GPU [default6]:[rank6]: Traceback (most recent call last): [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default6]:[rank6]: trainer.train(dataloader) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default6]:[rank6]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default6]:[rank6]: outputs = self.pipeline_engine.train_batch_iter( [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter [default6]:[rank6]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default6]:[rank6]: output = model(**micro_batch) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default6]:[rank6]: sharded_logits = self.model( [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default6]:[rank6]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default6]:[rank6]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default6]:[rank6]: return self._call_impl(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default6]:[rank6]: return forward_call(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default6]:[rank6]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default6]:[rank6]: pipeline_state.run_communication() [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default6]:[rank6]: recv_activation_tensor = recv_activation() [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default6]:[rank6]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default6]:[rank6]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default6]:[rank6]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 246, in _recv_meta [default6]:[rank6]: dist.recv( [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default6]:[rank6]: return func(*args, **kwargs) [default6]:[rank6]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default6]:[rank6]: pg.recv([tensor], group_src_rank, tag).wait() [default6]:[rank6]: torch.distributed.DistBackendError: [1] is setting up NCCL communicator and retrieving ncclUniqueId from [0] via c10d key-value store by key '0:1', but store->get('0:1') got error: Connection reset by peer [default6]:[rank6]: Exception raised from recvBytes at ../torch/csrc/distributed/c10d/Utils.hpp:672 (most recent call first): [default6]:[rank6]: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f41f012a897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default6]:[rank6]: frame #1: + 0x5b3a23e (0x7f4229c4723e 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 (0x7f4229c41c87 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 (0x7f4229c41f82 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 (0x7f4229c42fd1 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 (0x7f4229bf7371 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 (0x7f4229bf7371 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 (0x7f4229bf7371 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 (0x7f4229bf7371 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 (0x7f41f1404189 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 (0x7f41f140b610 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 (0x7f41f142a978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default6]:[rank6]: frame #12: + 0x5adc309 (0x7f4229be9309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #13: + 0x5ae6f10 (0x7f4229bf3f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #14: + 0x5ae6fa5 (0x7f4229bf3fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #15: + 0x5124446 (0x7f4229231446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #16: + 0x1acf4b8 (0x7f4225bdc4b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #17: + 0x5aee004 (0x7f4229bfb004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #18: + 0x5af36b5 (0x7f4229c006b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default6]:[rank6]: frame #19: + 0xd2631e (0x7f423c7ea31e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default6]:[rank6]: frame #20: + 0x47def4 (0x7f423bf41ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default6]:[rank6]: frame #21: + 0x1445a6 (0x56490a6c75a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #22: _PyObject_MakeTpCall + 0x26b (0x56490a6c0a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #23: + 0x150866 (0x56490a6d3866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x56490a6bc142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #25: _PyFunction_Vectorcall + 0x6c (0x56490a6c7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #26: PyObject_Call + 0xbc (0x56490a6d3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x56490a6ba2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #28: _PyFunction_Vectorcall + 0x6c (0x56490a6c7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x56490a6b88fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #30: + 0x150582 (0x56490a6d3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x56490a6b88fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #32: + 0x150582 (0x56490a6d3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x56490a6b88fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #34: + 0x150582 (0x56490a6d3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x56490a6b88fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x56490a6bff50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #37: _PyObject_Call_Prepend + 0x69 (0x56490a6d1c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #38: + 0x211239 (0x56490a794239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #39: _PyObject_MakeTpCall + 0x26b (0x56490a6c0a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x56490a6bc3e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #41: _PyFunction_Vectorcall + 0x6c (0x56490a6c7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x56490a6b7c5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #43: _PyFunction_Vectorcall + 0x6c (0x56490a6c7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x56490a6b88fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #45: + 0x150582 (0x56490a6d3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #46: PyObject_Call + 0xbc (0x56490a6d3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x56490a6ba2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #48: + 0x150582 (0x56490a6d3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #49: PyObject_Call + 0xbc (0x56490a6d3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x56490a6ba2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #51: _PyFunction_Vectorcall + 0x6c (0x56490a6c7a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x56490a6c0007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #53: _PyObject_Call_Prepend + 0x69 (0x56490a6d1c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #54: + 0x211239 (0x56490a794239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #55: PyObject_Call + 0x207 (0x56490a6d4067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x56490a6ba2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #57: + 0x150582 (0x56490a6d3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x56490a6b88fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #59: + 0x150582 (0x56490a6d3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #60: PyObject_Call + 0xbc (0x56490a6d3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x56490a6ba2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #62: + 0x150582 (0x56490a6d3582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: frame #63: PyObject_Call + 0xbc (0x56490a6d3f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default6]:[rank6]: . This may indicate a possible application crash on rank 0 or a network set up issue. [default5]:[rank5]: Traceback (most recent call last): [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [default5]:[rank5]: trainer.train(dataloader) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train [default5]:[rank5]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step [default5]:[rank5]: outputs = self.pipeline_engine.train_batch_iter( [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter [default5]:[rank5]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward [default5]:[rank5]: output = model(**micro_batch) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward [default5]:[rank5]: sharded_logits = self.model( [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default5]:[rank5]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default5]:[rank5]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl [default5]:[rank5]: return self._call_impl(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl [default5]:[rank5]: return forward_call(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [default5]:[rank5]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer [default5]:[rank5]: pipeline_state.run_communication() [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default5]:[rank5]: recv_activation_tensor = recv_activation() [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default5]:[rank5]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default5]:[rank5]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors [default5]:[rank5]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 246, in _recv_meta [default5]:[rank5]: dist.recv( [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 75, in wrapper [default5]:[rank5]: return func(*args, **kwargs) [default5]:[rank5]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default5]:[rank5]: pg.recv([tensor], group_src_rank, tag).wait() [default5]:[rank5]: torch.distributed.DistBackendError: [1] is setting up NCCL communicator and retrieving ncclUniqueId from [0] via c10d key-value store by key '0:1', but store->get('0:1') got error: Connection reset by peer [default5]:[rank5]: Exception raised from recvBytes at ../torch/csrc/distributed/c10d/Utils.hpp:672 (most recent call first): [default5]:[rank5]: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fd2df624897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default5]:[rank5]: frame #1: + 0x5b3a23e (0x7fd31914123e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #2: c10d::TCPStore::doWait(c10::ArrayRef, std::chrono::duration >) + 0x2c7 (0x7fd31913bc87 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 (0x7fd31913bf82 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 (0x7fd31913cfd1 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 (0x7fd3190f1371 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 (0x7fd3190f1371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #7: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7fd3190f1371 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 (0x7fd3190f1371 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 (0x7fd2e08fe189 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:[rank5]: frame #10: c10d::ProcessGroupNCCL::getNCCLComm(std::string const&, c10::Device&, c10d::OpType, int, bool) + 0xc50 (0x7fd2e0905610 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 (0x7fd2e0924978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default5]:[rank5]: frame #12: + 0x5adc309 (0x7fd3190e3309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #13: + 0x5ae6f10 (0x7fd3190edf10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #14: + 0x5ae6fa5 (0x7fd3190edfa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #15: + 0x5124446 (0x7fd31872b446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #16: + 0x1acf4b8 (0x7fd3150d64b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #17: + 0x5aee004 (0x7fd3190f5004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #18: + 0x5af36b5 (0x7fd3190fa6b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default5]:[rank5]: frame #19: + 0xd2631e (0x7fd32bce431e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default5]:[rank5]: frame #20: + 0x47def4 (0x7fd32b43bef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default5]:[rank5]: frame #21: + 0x1445a6 (0x56211d1505a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #22: _PyObject_MakeTpCall + 0x26b (0x56211d149a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #23: + 0x150866 (0x56211d15c866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x56211d145142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #25: _PyFunction_Vectorcall + 0x6c (0x56211d150a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #26: PyObject_Call + 0xbc (0x56211d15cf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x56211d1432b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #28: _PyFunction_Vectorcall + 0x6c (0x56211d150a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x56211d1418fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #30: + 0x150582 (0x56211d15c582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x56211d1418fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #32: + 0x150582 (0x56211d15c582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x56211d1418fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #34: + 0x150582 (0x56211d15c582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x56211d1418fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x56211d148f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #37: _PyObject_Call_Prepend + 0x69 (0x56211d15ac39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #38: + 0x211239 (0x56211d21d239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #39: _PyObject_MakeTpCall + 0x26b (0x56211d149a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x56211d1453e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #41: _PyFunction_Vectorcall + 0x6c (0x56211d150a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x56211d140c5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #43: _PyFunction_Vectorcall + 0x6c (0x56211d150a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x56211d1418fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #45: + 0x150582 (0x56211d15c582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #46: PyObject_Call + 0xbc (0x56211d15cf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x56211d1432b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #48: + 0x150582 (0x56211d15c582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #49: PyObject_Call + 0xbc (0x56211d15cf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x56211d1432b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #51: _PyFunction_Vectorcall + 0x6c (0x56211d150a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x56211d149007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #53: _PyObject_Call_Prepend + 0x69 (0x56211d15ac39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #54: + 0x211239 (0x56211d21d239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #55: PyObject_Call + 0x207 (0x56211d15d067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x56211d1432b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #57: + 0x150582 (0x56211d15c582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x56211d1418fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #59: + 0x150582 (0x56211d15c582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #60: PyObject_Call + 0xbc (0x56211d15cf1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x56211d1432b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #62: + 0x150582 (0x56211d15c582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default5]:[rank5]: frame #63: PyObject_Call + 0xbc (0x56211d15cf1c 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. [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) [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 [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) [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 [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 [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 [default7]:[rank7]: return forward_call(*args, **kwargs) [default4]:[rank4]: 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 [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( [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 [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) [default7]:[rank7]: pipeline_state.run_communication() [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication [default4]:[rank4]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] [default7]:[rank7]: recv_activation_tensor = recv_activation() [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default4]:[rank4]: hidden_encoder_states = encoder_block(**hidden_encoder_states) [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 [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) [default7]:[rank7]: buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag) [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) [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 [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward [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) [default4]:[rank4]: new_kwargs[name] = recv_from_pipeline_state_buffer( [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [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 [default7]:[rank7]: pg.recv([tensor], group_src_rank, tag).wait() [default4]:[rank4]: pipeline_state.run_communication() [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 (0x7f2dfe361897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [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() [default7]:[rank7]: frame #1: + 0x5b3a23e (0x7f2e37e7e23e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__ [default7]:[rank7]: frame #2: c10d::TCPStore::doWait(c10::ArrayRef, std::chrono::duration >) + 0x2c7 (0x7f2e37e78c87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0] [default7]:[rank7]: frame #3: c10d::TCPStore::doGet(std::string const&) + 0x32 (0x7f2e37e78f82 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 (0x7f2e37e79fd1 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 (0x7f2e37e2e371 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 (0x7f2e37e2e371 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 (0x7f2e37e2e371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors [default7]:[rank7]: frame #8: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f2e37e2e371 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 (0x7f2dff63b189 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 (0x7f2dff642610 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [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 [default7]:[rank7]: frame #11: c10d::ProcessGroupNCCL::recv(std::vector >&, int, int) + 0x5f8 (0x7f2dff661978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default4]:[rank4]: meta = self._recv_meta(from_rank=from_rank, tag=tag) [default7]:[rank7]: frame #12: + 0x5adc309 (0x7f2e37e20309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #13: + 0x5ae6f10 (0x7f2e37e2af10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [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) [default7]:[rank7]: frame #14: + 0x5ae6fa5 (0x7f2e37e2afa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1932, in recv [default7]:[rank7]: frame #15: + 0x5124446 (0x7f2e37468446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [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 [default7]:[rank7]: frame #16: + 0x1acf4b8 (0x7f2e33e134b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [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 (0x7f7c212be897 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so) [default7]:[rank7]: frame #17: + 0x5aee004 (0x7f2e37e32004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #1: + 0x5b3a23e (0x7f7c5addb23e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #18: + 0x5af36b5 (0x7f2e37e376b5 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 (0x7f7c5add5c87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #19: + 0xd2631e (0x7f2e4aa2131e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default4]:[rank4]: frame #3: c10d::TCPStore::doGet(std::string const&) + 0x32 (0x7f7c5add5f82 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 (0x7f7c5add6fd1 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #20: + 0x47def4 (0x7f2e4a178ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default7]:[rank7]: frame #21: + 0x1445a6 (0x555fc3d4e5a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #22: _PyObject_MakeTpCall + 0x26b (0x555fc3d47a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #23: + 0x150866 (0x555fc3d5a866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #5: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f7c5ad8b371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x555fc3d43142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #6: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f7c5ad8b371 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 (0x7f7c5ad8b371 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #25: _PyFunction_Vectorcall + 0x6c (0x555fc3d4ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #26: PyObject_Call + 0xbc (0x555fc3d5af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x555fc3d412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #8: c10d::PrefixStore::get(std::string const&) + 0x31 (0x7f7c5ad8b371 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 (0x7f7c22598189 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 (0x7f7c2259f610 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 (0x7f7c225be978 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so) [default7]:[rank7]: frame #28: _PyFunction_Vectorcall + 0x6c (0x555fc3d4ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #12: + 0x5adc309 (0x7f7c5ad7d309 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #13: + 0x5ae6f10 (0x7f7c5ad87f10 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x555fc3d3f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #30: + 0x150582 (0x555fc3d5a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x555fc3d3f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #32: + 0x150582 (0x555fc3d5a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x555fc3d3f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #34: + 0x150582 (0x555fc3d5a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #14: + 0x5ae6fa5 (0x7f7c5ad87fa5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x555fc3d3f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x555fc3d46f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #37: _PyObject_Call_Prepend + 0x69 (0x555fc3d58c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #38: + 0x211239 (0x555fc3e1b239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #39: _PyObject_MakeTpCall + 0x26b (0x555fc3d47a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x555fc3d433e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #41: _PyFunction_Vectorcall + 0x6c (0x555fc3d4ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x555fc3d3ec5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #15: + 0x5124446 (0x7f7c5a3c5446 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #43: _PyFunction_Vectorcall + 0x6c (0x555fc3d4ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #16: + 0x1acf4b8 (0x7f7c56d704b8 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #17: + 0x5aee004 (0x7f7c5ad8f004 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default7]:[rank7]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x555fc3d3f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #18: + 0x5af36b5 (0x7f7c5ad946b5 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so) [default4]:[rank4]: frame #19: + 0xd2631e (0x7f7c6d97e31e in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default4]:[rank4]: frame #20: + 0x47def4 (0x7f7c6d0d5ef4 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_python.so) [default4]:[rank4]: frame #21: + 0x1445a6 (0x55cce8bd95a6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #22: _PyObject_MakeTpCall + 0x26b (0x55cce8bd2a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #23: + 0x150866 (0x55cce8be5866 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #45: + 0x150582 (0x555fc3d5a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #24: _PyEval_EvalFrameDefault + 0x4c12 (0x55cce8bce142 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #46: PyObject_Call + 0xbc (0x555fc3d5af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #25: _PyFunction_Vectorcall + 0x6c (0x55cce8bd9a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #26: PyObject_Call + 0xbc (0x55cce8be5f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x555fc3d412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #27: _PyEval_EvalFrameDefault + 0x2d83 (0x55cce8bcc2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #28: _PyFunction_Vectorcall + 0x6c (0x55cce8bd9a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #48: + 0x150582 (0x555fc3d5a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #29: _PyEval_EvalFrameDefault + 0x13ca (0x55cce8bca8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #30: + 0x150582 (0x55cce8be5582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #49: PyObject_Call + 0xbc (0x555fc3d5af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #31: _PyEval_EvalFrameDefault + 0x13ca (0x55cce8bca8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #32: + 0x150582 (0x55cce8be5582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x555fc3d412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #51: _PyFunction_Vectorcall + 0x6c (0x555fc3d4ea2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x555fc3d47007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #53: _PyObject_Call_Prepend + 0x69 (0x555fc3d58c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #54: + 0x211239 (0x555fc3e1b239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #33: _PyEval_EvalFrameDefault + 0x13ca (0x55cce8bca8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #55: PyObject_Call + 0x207 (0x555fc3d5b067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #34: + 0x150582 (0x55cce8be5582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x555fc3d412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #35: _PyEval_EvalFrameDefault + 0x13ca (0x55cce8bca8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #57: + 0x150582 (0x555fc3d5a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #36: _PyObject_FastCallDictTstate + 0xd0 (0x55cce8bd1f50 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #37: _PyObject_Call_Prepend + 0x69 (0x55cce8be3c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #38: + 0x211239 (0x55cce8ca6239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #39: _PyObject_MakeTpCall + 0x26b (0x55cce8bd2a6b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #40: _PyEval_EvalFrameDefault + 0x4eb6 (0x55cce8bce3e6 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #41: _PyFunction_Vectorcall + 0x6c (0x55cce8bd9a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x555fc3d3f8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #42: _PyEval_EvalFrameDefault + 0x72c (0x55cce8bc9c5c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #43: _PyFunction_Vectorcall + 0x6c (0x55cce8bd9a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #44: _PyEval_EvalFrameDefault + 0x13ca (0x55cce8bca8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #59: + 0x150582 (0x555fc3d5a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #45: + 0x150582 (0x55cce8be5582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #46: PyObject_Call + 0xbc (0x55cce8be5f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #60: PyObject_Call + 0xbc (0x555fc3d5af1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x555fc3d412b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #62: + 0x150582 (0x555fc3d5a582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #47: _PyEval_EvalFrameDefault + 0x2d83 (0x55cce8bcc2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default7]:[rank7]: frame #63: PyObject_Call + 0xbc (0x555fc3d5af1c 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]: frame #48: + 0x150582 (0x55cce8be5582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #49: PyObject_Call + 0xbc (0x55cce8be5f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #50: _PyEval_EvalFrameDefault + 0x2d83 (0x55cce8bcc2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #51: _PyFunction_Vectorcall + 0x6c (0x55cce8bd9a2c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #52: _PyObject_FastCallDictTstate + 0x187 (0x55cce8bd2007 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #53: _PyObject_Call_Prepend + 0x69 (0x55cce8be3c39 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #54: + 0x211239 (0x55cce8ca6239 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #55: PyObject_Call + 0x207 (0x55cce8be6067 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #56: _PyEval_EvalFrameDefault + 0x2d83 (0x55cce8bcc2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #57: + 0x150582 (0x55cce8be5582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #58: _PyEval_EvalFrameDefault + 0x13ca (0x55cce8bca8fa in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #59: + 0x150582 (0x55cce8be5582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #60: PyObject_Call + 0xbc (0x55cce8be5f1c in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #61: _PyEval_EvalFrameDefault + 0x2d83 (0x55cce8bcc2b3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #62: + 0x150582 (0x55cce8be5582 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10) [default4]:[rank4]: frame #63: PyObject_Call + 0xbc (0x55cce8be5f1c 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. W0704 02:32:27.234000 140065233516352 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1617712 closing signal SIGTERM W0704 02:32:27.234000 140065233516352 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1617713 closing signal SIGTERM W0704 02:32:27.234000 140065233516352 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1617714 closing signal SIGTERM W0704 02:32:27.235000 140065233516352 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1617715 closing signal SIGTERM E0704 02:32:28.057000 140065233516352 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 1617708) 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 : 2024-07-04_02:32:27 host : ip-26-0-161-153.ec2.internal rank : 1 (local_rank: 1) exitcode : 1 (pid: 1617709) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html [2]: time : 2024-07-04_02:32:27 host : ip-26-0-161-153.ec2.internal rank : 2 (local_rank: 2) exitcode : 1 (pid: 1617710) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html [3]: time : 2024-07-04_02:32:27 host : ip-26-0-161-153.ec2.internal rank : 3 (local_rank: 3) exitcode : 1 (pid: 1617711) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html ------------------------------------------------------------ Root Cause (first observed failure): [0]: time : 2024-07-04_02:32:27 host : ip-26-0-161-153.ec2.internal rank : 0 (local_rank: 0) exitcode : 1 (pid: 1617708) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html ============================================================ srun: error: ip-26-0-161-153: 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.