| ======================== | |
| START TIME: Wed Jul 3 23:47:12 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 | |
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| remove the file manually to continue. | |
| Job status: RUNNING | |
| W0703 23:47:14.676000 139942798907200 torch/distributed/run.py:757] | |
| W0703 23:47:14.676000 139942798907200 torch/distributed/run.py:757] ***************************************** | |
| W0703 23:47:14.676000 139942798907200 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 23:47:14.676000 139942798907200 torch/distributed/run.py:757] ***************************************** | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Config: | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Config(general=GeneralArgs(project='bench_cluster', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: run='%date_%jobid', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: seed=42, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: step=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: consumed_train_samples=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: benchmark_csv_path=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: ignore_sanity_checks=True), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: parallelism=ParallelismArgs(dp=2, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: pp=4, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: tp=1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7fb9bc670670>, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: tp_linear_async_communication=False, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: expert_parallel_size=1), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: eos_token_id=2, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: hidden_act='silu', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: hidden_size=2048, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: initializer_range=0.02, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: intermediate_size=4096, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: is_llama_config=True, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: max_position_embeddings=4096, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: num_attention_heads=32, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: num_hidden_layers=24, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: num_key_value_heads=32, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: pad_token_id=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: pretraining_tp=1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: rms_norm_eps=1e-05, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: rope_scaling=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: rope_theta=10000.0, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: tie_word_embeddings=True, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: use_cache=True, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: vocab_size=50257), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: init_method=RandomInit(std=0.025), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: dtype=torch.bfloat16, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: make_vocab_size_divisible_by=1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: ddp_bucket_cap_mb=25), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: tokenizer_revision=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: tokenizer_max_length=None), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: checkpoint_interval=100000, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: save_initial_state=False, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: resume_checkpoint_path=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: checkpoints_path_is_shared_file_system=False), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: logging=LoggingArgs(log_level='info', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: log_level_replica='info', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: iteration_step_info_interval=1), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: tokens=TokensArgs(sequence_length=4096, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: train_steps=20, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: micro_batch_size=8, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: batch_accumulation_per_replica=64, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: val_check_interval=-1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: limit_val_batches=0, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: limit_test_batches=0), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: adam_beta1=0.9, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: adam_beta2=0.95, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: torch_adam_is_fused=True, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: name='adamW'), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: zero_stage=1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: weight_decay=0.01, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: clip_grad=1.0, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: accumulate_grad_in_fp32=True, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: lr_warmup_steps=1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: lr_warmup_style='linear', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: lr_decay_style='linear', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: lr_decay_steps=19, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: lr_decay_starting_step=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: min_decay_lr=1e-05)), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: data_stages=[DatasetStageArgs(name='Training Stage', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: start_training_step=1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: hf_dataset_splits='train', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: hf_dataset_config_name=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: dataset_processing_num_proc_per_process=64, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: dataset_overwrite_cache=False, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: text_column_name='text'), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: seed=42, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: num_loading_workers=0))], | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/8_GPUS/dp-2_tp-1_pp-4_mbz-8')), | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: lighteval=None) | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Model Config: | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: LlamaConfig(bos_token_id=1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: eos_token_id=2, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: hidden_act='silu', | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: hidden_size=2048, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: initializer_range=0.02, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: intermediate_size=4096, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: is_llama_config=True, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: max_position_embeddings=4096, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: num_attention_heads=32, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: num_hidden_layers=24, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: num_key_value_heads=32, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: pad_token_id=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: pretraining_tp=1, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: rms_norm_eps=1e-05, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: rope_scaling=None, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: rope_theta=10000.0, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: tie_word_embeddings=True, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: use_cache=True, | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: vocab_size=50257) | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Building model.. | |
| [default0]:07/03/2024 23:47:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Setting PP block ranks... | |
| [default1]:07/03/2024 23:47:43 [INFO|DP=1|PP=0|TP=0|ip-26-0-169-207]: No checkpoint path provided. | |
| [default5]:07/03/2024 23:47:43 [INFO|DP=1|PP=2|TP=0|ip-26-0-169-207]: No checkpoint path provided. | |
| [default6]:07/03/2024 23:47:43 [INFO|DP=0|PP=3|TP=0|ip-26-0-169-207]: Local number of parameters: 271M (516.35MiB) | |
| [default6]:07/03/2024 23:47:43 [INFO|DP=0|PP=3|TP=0|ip-26-0-169-207]: [After model building] Memory usage: 520.36MiB. Peak allocated: 522.39MiB Peak reserved: 534.00MiB | |
| [default6]:07/03/2024 23:47:43 [INFO|DP=0|PP=3|TP=0|ip-26-0-169-207]: No checkpoint path provided. | |
| [default2]:07/03/2024 23:47:43 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-207]: Local number of parameters: 294M (560.05MiB) | |
| [default2]:07/03/2024 23:47:43 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-207]: [After model building] Memory usage: 567.07MiB. Peak allocated: 569.10MiB Peak reserved: 594.00MiB | |
| [default2]:07/03/2024 23:47:43 [INFO|DP=0|PP=1|TP=0|ip-26-0-169-207]: No checkpoint path provided. | |
| [default0]:07/03/2024 23:47:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Total number of parameters: 1.21G (2312.82MiB) | |
| [default0]:07/03/2024 23:47:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Local number of parameters: 397M (756.37MiB) | |
| [default0]:07/03/2024 23:47:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: [After model building] Memory usage: 763.38MiB. Peak allocated: 765.41MiB Peak reserved: 792.00MiB | |
| [default0]:07/03/2024 23:47:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: No checkpoint path provided. | |
| [default0]:07/03/2024 23:47:43 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Parametrizing model parameters using StandardParametrizator | |
| [default3]:07/03/2024 23:47:43 [INFO|DP=1|PP=1|TP=0|ip-26-0-169-207]: No checkpoint path provided. | |
| [default4]:07/03/2024 23:47:43 [INFO|DP=0|PP=2|TP=0|ip-26-0-169-207]: Local number of parameters: 252M (480.05MiB) | |
| [default4]:07/03/2024 23:47:43 [INFO|DP=0|PP=2|TP=0|ip-26-0-169-207]: [After model building] Memory usage: 486.06MiB. Peak allocated: 488.09MiB Peak reserved: 502.00MiB | |
| [default4]:07/03/2024 23:47:43 [INFO|DP=0|PP=2|TP=0|ip-26-0-169-207]: No checkpoint path provided. | |
| [default7]:07/03/2024 23:47:43 [INFO|DP=1|PP=3|TP=0|ip-26-0-169-207]: No checkpoint path provided. | |
| [default0]:07/03/2024 23:47:46 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: [Optimizer Building] Using LearningRateForSP as learning rate | |
| [default0]:07/03/2024 23:47:46 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: [ZeRO sharding] Size of optimizer params per rank: | |
| [default0]:07/03/2024 23:47:46 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: [ZeRO sharding] DP Rank 0 has 198M out of 397M (50.00%) params' optimizer states | |
| [default0]:07/03/2024 23:47:46 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: [ZeRO sharding] DP Rank 1 has 198M out of 397M (50.00%) params' optimizer states | |
| [default0]:07/03/2024 23:47:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples | |
| [default0]:07/03/2024 23:47:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Using `datasets` library | |
| [default0]:07/03/2024 23:47:47 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4') | |
| [default0]:07/03/2024 23:47:47 [WARNING|DP=0|PP=0|TP=0|ip-26-0-169-207]: 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 23:47:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: [Training Plan] There are 1 training stages | |
| [default0]:07/03/2024 23:47:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: [Stage Training Stage] start from step 1 | |
| [default0]:07/03/2024 23:47:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: | |
| [default0]:07/03/2024 23:47:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: [Start training] datetime: 2024-07-03 23:47:48.138496 | mbs: 8 | grad_accum: 64 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0 | |
| [default0]:07/03/2024 23:47:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps | |
| [default0]:07/03/2024 23:47:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-169-207]: Memory usage: 3032.50MiB. Peak allocated 3032.50MiB. Peak reserved: 3064.00MiB | |
| [default1]:07/03/2024 23:47:48 [WARNING|DP=1|PP=0|TP=0|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default5]:07/03/2024 23:47:48 [WARNING|DP=1|PP=2|TP=0|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default6]:07/03/2024 23:47:48 [WARNING|DP=0|PP=3|TP=0|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default2]:07/03/2024 23:47:48 [WARNING|DP=0|PP=1|TP=0|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default3]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default2]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default3]:07/03/2024 23:47:48 [WARNING|DP=1|PP=1|TP=0|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default4]:07/03/2024 23:47:48 [WARNING|DP=0|PP=2|TP=0|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default5]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default1]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default7]:07/03/2024 23:47:48 [WARNING|DP=1|PP=3|TP=0|ip-26-0-169-207]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default4]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default6]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default7]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default0]:[rank0]: Traceback (most recent call last): | |
| [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default0]:[rank0]: trainer.train(dataloader) | |
| [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default0]:[rank0]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default0]:[rank0]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 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 631, in forward | |
| [default0]:[rank0]: output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask) | |
| [default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default0]:[rank0]: return self._call_impl(*args, **kwargs) | |
| [default0]:[rank0]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default0]:[rank0]: return forward_call(*args, **kwargs) | |
| [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 565, in forward | |
| [default0]:[rank0]: key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous() | |
| [default0]:[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU | |
| [default1]:[rank1]: Traceback (most recent call last): | |
| [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default1]:[rank1]: trainer.train(dataloader) | |
| [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default1]:[rank1]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default1]:[rank1]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 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 631, in forward | |
| [default1]:[rank1]: output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask) | |
| [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default1]:[rank1]: return self._call_impl(*args, **kwargs) | |
| [default1]:[rank1]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default1]:[rank1]: return forward_call(*args, **kwargs) | |
| [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 565, in forward | |
| [default1]:[rank1]: key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous() | |
| [default1]:[rank1]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB. GPU has a total capacity of 79.33 GiB of which 111.94 MiB is free. Including non-PyTorch memory, this process has 79.21 GiB memory in use. Of the allocated memory 66.11 GiB is allocated by PyTorch, and 140.28 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) | |
| [default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) | |
| [default6]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass | |
| [default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) | |
| [default4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass | |
| [default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.) | |
| [default7]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass | |
| W0703 23:48:05.037000 139942798907200 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2691648 closing signal SIGTERM | |
| W0703 23:48:05.038000 139942798907200 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2691649 closing signal SIGTERM | |
| W0703 23:48:05.038000 139942798907200 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2691650 closing signal SIGTERM | |
| W0703 23:48:05.040000 139942798907200 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2691651 closing signal SIGTERM | |
| W0703 23:48:05.040000 139942798907200 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2691652 closing signal SIGTERM | |
| W0703 23:48:05.040000 139942798907200 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 2691653 closing signal SIGTERM | |
| E0703 23:48:07.260000 139942798907200 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 2691646) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10 | |
| Traceback (most recent call last): | |
| File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module> | |
| sys.exit(main()) | |
| File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 347, in wrapper | |
| return f(*args, **kwargs) | |
| File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 879, in main | |
| run(args) | |
| File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 870, in run | |
| elastic_launch( | |
| File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 132, in __call__ | |
| return launch_agent(self._config, self._entrypoint, list(args)) | |
| File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 263, in launch_agent | |
| raise ChildFailedError( | |
| torch.distributed.elastic.multiprocessing.errors.ChildFailedError: | |
| ============================================================ | |
| /fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED | |
| ------------------------------------------------------------ | |
| Failures: | |
| [1]: | |
| time : 2024-07-03_23:48:05 | |
| host : ip-26-0-169-207.ec2.internal | |
| rank : 1 (local_rank: 1) | |
| exitcode : 1 (pid: 2691647) | |
| error_file: <N/A> | |
| traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html | |
| ------------------------------------------------------------ | |
| Root Cause (first observed failure): | |
| [0]: | |
| time : 2024-07-03_23:48:05 | |
| host : ip-26-0-169-207.ec2.internal | |
| rank : 0 (local_rank: 0) | |
| exitcode : 1 (pid: 2691646) | |
| error_file: <N/A> | |
| traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html | |
| ============================================================ | |
| srun: error: ip-26-0-169-207: 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. | |