======================== START TIME: Wed Jul 3 22:51:03 UTC 2024 python3 version = Python 3.10.14 ======================== The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well. Token is valid (permission: write). Your token has been saved to /admin/home/ferdinand_mom/.cache/huggingface/token Login successful Already on 'bench_cluster' M examples/config_tiny_llama.py M examples/config_tiny_llama.yaml M examples/train_tiny_llama.sh M src/nanotron/models/llama.py M src/nanotron/trainer.py Your branch is up to date with 'origin/bench_cluster'. Job status: RUNNING W0703 22:51:05.903000 140623413176128 torch/distributed/run.py:757] W0703 22:51:05.903000 140623413176128 torch/distributed/run.py:757] ***************************************** W0703 22:51:05.903000 140623413176128 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. W0703 22:51:05.903000 140623413176128 torch/distributed/run.py:757] ***************************************** [default0]:07/03/2024 22:51:22 [WARNING|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Vocab Size Padding] Padded vocab (size: 50257) with 3 dummy tokens (new size: 50260) [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Config: [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Config(general=GeneralArgs(project='bench_cluster', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: run='%date_%jobid', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: seed=42, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: step=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: consumed_train_samples=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: benchmark_csv_path=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: ignore_sanity_checks=True), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: parallelism=ParallelismArgs(dp=1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pp=2, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tp=4, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pp_engine=, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tp_mode=, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tp_linear_async_communication=False, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: expert_parallel_size=1), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: eos_token_id=2, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hidden_act='silu', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hidden_size=2048, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: initializer_range=0.02, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: intermediate_size=4096, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: is_llama_config=True, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: max_position_embeddings=4096, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_attention_heads=32, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_hidden_layers=24, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_key_value_heads=32, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pad_token_id=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pretraining_tp=1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rms_norm_eps=1e-05, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rope_scaling=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rope_theta=10000.0, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tie_word_embeddings=True, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: use_cache=True, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: vocab_size=50260), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: init_method=RandomInit(std=0.025), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: dtype=torch.bfloat16, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: make_vocab_size_divisible_by=1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: ddp_bucket_cap_mb=25), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tokenizer_revision=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tokenizer_max_length=None), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: checkpoint_interval=100000, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: save_initial_state=False, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: resume_checkpoint_path=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: checkpoints_path_is_shared_file_system=False), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: logging=LoggingArgs(log_level='info', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: log_level_replica='info', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: iteration_step_info_interval=1), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tokens=TokensArgs(sequence_length=4096, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: train_steps=20, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: micro_batch_size=32, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: batch_accumulation_per_replica=32, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: val_check_interval=-1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: limit_val_batches=0, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: limit_test_batches=0), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: adam_beta1=0.9, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: adam_beta2=0.95, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: torch_adam_is_fused=True, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: name='adamW'), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: zero_stage=1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: weight_decay=0.01, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: clip_grad=1.0, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: accumulate_grad_in_fp32=True, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_warmup_steps=1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_warmup_style='linear', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_decay_style='linear', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_decay_steps=19, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lr_decay_starting_step=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: min_decay_lr=1e-05)), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: data_stages=[DatasetStageArgs(name='Training Stage', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: start_training_step=1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hf_dataset_splits='train', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hf_dataset_config_name=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: dataset_processing_num_proc_per_process=64, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: dataset_overwrite_cache=False, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: text_column_name='text'), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: seed=42, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_loading_workers=0))], [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-1_tp-4_pp-2_mbz-32')), [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: lighteval=None) [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Model Config: [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: LlamaConfig(bos_token_id=1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: eos_token_id=2, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hidden_act='silu', [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: hidden_size=2048, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: initializer_range=0.02, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: intermediate_size=4096, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: is_llama_config=True, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: max_position_embeddings=4096, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_attention_heads=32, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_hidden_layers=24, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: num_key_value_heads=32, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pad_token_id=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: pretraining_tp=1, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rms_norm_eps=1e-05, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rope_scaling=None, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: rope_theta=10000.0, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: tie_word_embeddings=True, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: use_cache=True, [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: vocab_size=50260) [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Building model.. [default0]:07/03/2024 22:51:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Setting PP block ranks... [default1]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-178]: Local number of parameters: 173M (329.19MiB) [default1]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-178]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default1]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=1|ip-26-0-161-178]: No checkpoint path provided. [default3]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=3|ip-26-0-161-178]: Local number of parameters: 173M (329.19MiB) [default3]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=3|ip-26-0-161-178]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default3]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=3|ip-26-0-161-178]: No checkpoint path provided. [default4]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-178]: Local number of parameters: 131M (249.16MiB) [default4]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-178]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default4]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=0|ip-26-0-161-178]: No checkpoint path provided. [default7]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=3|ip-26-0-161-178]: Local number of parameters: 131M (249.16MiB) [default7]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=3|ip-26-0-161-178]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default7]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=3|ip-26-0-161-178]: No checkpoint path provided. [default2]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=2|ip-26-0-161-178]: Local number of parameters: 173M (329.19MiB) [default2]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=2|ip-26-0-161-178]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default2]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=2|ip-26-0-161-178]: No checkpoint path provided. [default0]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Total number of parameters: 1.21G (2313.42MiB) [default0]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Local number of parameters: 173M (329.19MiB) [default0]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [After model building] Memory usage: 344.13MiB. Peak allocated: 346.16MiB Peak reserved: 348.00MiB [default0]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: No checkpoint path provided. [default0]:07/03/2024 22:51:35 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Parametrizing model parameters using StandardParametrizator [default5]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-178]: Local number of parameters: 131M (249.16MiB) [default5]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-178]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default5]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=1|ip-26-0-161-178]: No checkpoint path provided. [default6]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=2|ip-26-0-161-178]: Local number of parameters: 131M (249.16MiB) [default6]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=2|ip-26-0-161-178]: [After model building] Memory usage: 260.10MiB. Peak allocated: 262.13MiB Peak reserved: 264.00MiB [default6]:07/03/2024 22:51:35 [INFO|DP=0|PP=1|TP=2|ip-26-0-161-178]: No checkpoint path provided. [default0]:07/03/2024 22:51:36 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Optimizer Building] Using LearningRateForSP as learning rate [default0]:07/03/2024 22:51:36 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [ZeRO sharding] Size of optimizer params per rank: [default0]:07/03/2024 22:51:36 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [ZeRO sharding] DP Rank 0 has 173M out of 173M (100.00%) params' optimizer states [default0]:07/03/2024 22:51:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples [default0]:07/03/2024 22:51:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Using `datasets` library [default0]:07/03/2024 22:51:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4') [default0]:07/03/2024 22:51:38 [WARNING|DP=0|PP=0|TP=0|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty. [default0]:Repo card metadata block was not found. Setting CardData to empty. [default0]:07/03/2024 22:51:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Training Plan] There are 1 training stages [default0]:07/03/2024 22:51:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Stage Training Stage] start from step 1 [default0]:07/03/2024 22:51:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [default0]:07/03/2024 22:51:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: [Start training] datetime: 2024-07-03 22:51:38.760448 | mbs: 32 | grad_accum: 32 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0 [default0]:07/03/2024 22:51:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps [default0]:07/03/2024 22:51:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-161-178]: Memory usage: 1660.89MiB. Peak allocated 1660.89MiB. Peak reserved: 1668.00MiB [default2]:Repo card metadata block was not found. Setting CardData to empty. [default3]:07/03/2024 22:51:38 [WARNING|DP=0|PP=0|TP=3|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty. [default7]:07/03/2024 22:51:38 [WARNING|DP=0|PP=1|TP=3|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty. [default1]:Repo card metadata block was not found. Setting CardData to empty. [default1]:07/03/2024 22:51:38 [WARNING|DP=0|PP=0|TP=1|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty. [default2]:07/03/2024 22:51:38 [WARNING|DP=0|PP=0|TP=2|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty. [default5]:07/03/2024 22:51:38 [WARNING|DP=0|PP=1|TP=1|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty. [default3]:Repo card metadata block was not found. Setting CardData to empty. [default7]:Repo card metadata block was not found. Setting CardData to empty. [default5]:Repo card metadata block was not found. Setting CardData to empty. [default4]:07/03/2024 22:51:39 [WARNING|DP=0|PP=1|TP=0|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty. [default4]:Repo card metadata block was not found. Setting CardData to empty. [default6]:07/03/2024 22:51:39 [WARNING|DP=0|PP=1|TP=2|ip-26-0-161-178]: Repo card metadata block was not found. Setting CardData to empty. [default6]: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 278, 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 171, in forward [default2]:[rank2]: merged_states = self.gate_up_proj(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/parallel/tensor_parallel/nn.py", line 87, in forward [default2]:[rank2]: return column_linear( [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear [default2]:[rank2]: return F.linear(input, weight, bias) [default2]:[rank2]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU  has a total capacity of 79.33 GiB of which 137.94 MiB is free. Including non-PyTorch memory, this process has 79.18 GiB memory in use. Of the allocated memory 66.63 GiB is allocated by PyTorch, and 271.33 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) [default0]:[rank0]: Traceback (most recent call last): [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in [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 278, 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 171, in forward [default0]:[rank0]: merged_states = self.gate_up_proj(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/parallel/tensor_parallel/nn.py", line 87, in forward [default0]:[rank0]: return column_linear( [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear [default0]:[rank0]: return F.linear(input, weight, bias) [default0]:[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU [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 278, 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 171, in forward [default3]:[rank3]: merged_states = self.gate_up_proj(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/parallel/tensor_parallel/nn.py", line 87, in forward [default3]:[rank3]: return column_linear( [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear [default3]:[rank3]: return F.linear(input, weight, bias) [default3]:[rank3]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU  has a total capacity of 79.33 GiB of which 377.94 MiB is free. Including non-PyTorch memory, this process has 78.95 GiB memory in use. Of the allocated memory 66.63 GiB is allocated by PyTorch, and 271.33 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) [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 278, 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 171, in forward [default1]:[rank1]: merged_states = self.gate_up_proj(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/parallel/tensor_parallel/nn.py", line 87, in forward [default1]:[rank1]: return column_linear( [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear [default1]:[rank1]: return F.linear(input, weight, bias) [default1]:[rank1]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 512.00 MiB. GPU  has a total capacity of 79.33 GiB of which 137.94 MiB is free. Including non-PyTorch memory, this process has 79.18 GiB memory in use. Of the allocated memory 66.63 GiB is allocated by PyTorch, and 271.33 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables) W0703 22:51:46.184000 140623413176128 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1034415 closing signal SIGTERM W0703 22:51:46.184000 140623413176128 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1034416 closing signal SIGTERM W0703 22:51:46.184000 140623413176128 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1034417 closing signal SIGTERM W0703 22:51:46.184000 140623413176128 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1034418 closing signal SIGTERM W0703 22:51:46.184000 140623413176128 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1034419 closing signal SIGTERM W0703 22:51:46.184000 140623413176128 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 1034420 closing signal SIGTERM E0703 22:51:47.999000 140623413176128 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 1034413) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10 Traceback (most recent call last): File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in sys.exit(main()) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper return f(*args, **kwargs) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main run(args) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run elastic_launch( File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__ return launch_agent(self._config, self._entrypoint, list(args)) File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent raise ChildFailedError( torch.distributed.elastic.multiprocessing.errors.ChildFailedError: ============================================================ /fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED ------------------------------------------------------------ Failures: [1]: time : 2024-07-03_22:51:46 host : ip-26-0-161-178.ec2.internal rank : 1 (local_rank: 1) exitcode : 1 (pid: 1034414) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html ------------------------------------------------------------ Root Cause (first observed failure): [0]: time : 2024-07-03_22:51:46 host : ip-26-0-161-178.ec2.internal rank : 0 (local_rank: 0) exitcode : 1 (pid: 1034413) error_file: traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html ============================================================ srun: error: ip-26-0-161-178: 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.