| ======================== | |
| START TIME: Tue Jul 2 15:18:40 UTC 2024 | |
| python3 version = Python 3.10.14 | |
| ======================== | |
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| 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 | |
| W0702 15:18:43.050000 140625870714688 torch/distributed/run.py:757] | |
| W0702 15:18:43.050000 140625870714688 torch/distributed/run.py:757] ***************************************** | |
| W0702 15:18:43.050000 140625870714688 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. | |
| W0702 15:18:43.050000 140625870714688 torch/distributed/run.py:757] ***************************************** | |
| W0702 15:18:43.086000 139643089798976 torch/distributed/run.py:757] | |
| W0702 15:18:43.086000 139643089798976 torch/distributed/run.py:757] ***************************************** | |
| W0702 15:18:43.086000 139643089798976 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. | |
| W0702 15:18:43.086000 139643089798976 torch/distributed/run.py:757] ***************************************** | |
| [default0]:07/02/2024 15:19:01 [WARNING|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Vocab Size Padding] Padded vocab (size: 50257) with 7 dummy tokens (new size: 50264) | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Config: | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Config(general=GeneralArgs(project='bench_cluster', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: run='%date_%jobid', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: seed=42, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: step=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: consumed_train_samples=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: benchmark_csv_path=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: ignore_sanity_checks=True), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: parallelism=ParallelismArgs(dp=2, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pp=1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tp=8, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7f3bb57386a0>, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tp_linear_async_communication=False, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: expert_parallel_size=1), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: eos_token_id=2, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hidden_act='silu', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hidden_size=2048, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: initializer_range=0.02, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: intermediate_size=4096, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: is_llama_config=True, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: max_position_embeddings=4096, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_attention_heads=32, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_hidden_layers=24, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_key_value_heads=32, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pad_token_id=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pretraining_tp=1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rms_norm_eps=1e-05, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rope_scaling=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rope_theta=10000.0, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tie_word_embeddings=True, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: use_cache=True, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: vocab_size=50264), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: init_method=RandomInit(std=0.025), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: dtype=torch.bfloat16, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: make_vocab_size_divisible_by=1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: ddp_bucket_cap_mb=25), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tokenizer_revision=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tokenizer_max_length=None), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: checkpoint_interval=100000, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: save_initial_state=False, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: resume_checkpoint_path=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: checkpoints_path_is_shared_file_system=False), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: logging=LoggingArgs(log_level='info', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: log_level_replica='info', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: iteration_step_info_interval=1), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tokens=TokensArgs(sequence_length=4096, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: train_steps=20, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: micro_batch_size=256, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: batch_accumulation_per_replica=2, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: val_check_interval=-1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: limit_val_batches=0, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: limit_test_batches=0), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: adam_beta1=0.9, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: adam_beta2=0.95, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: torch_adam_is_fused=True, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: name='adamW'), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: zero_stage=1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: weight_decay=0.01, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: clip_grad=1.0, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: accumulate_grad_in_fp32=True, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_warmup_steps=1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_warmup_style='linear', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_decay_style='linear', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_decay_steps=19, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lr_decay_starting_step=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: min_decay_lr=1e-05)), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: data_stages=[DatasetStageArgs(name='Training Stage', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: start_training_step=1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hf_dataset_splits='train', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hf_dataset_config_name=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: dataset_processing_num_proc_per_process=64, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: dataset_overwrite_cache=False, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: text_column_name='text'), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: seed=42, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_loading_workers=32))], | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-2_tp-8_pp-1_mbz-256')), | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: lighteval=None) | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Model Config: | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: LlamaConfig(bos_token_id=1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: eos_token_id=2, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hidden_act='silu', | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: hidden_size=2048, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: initializer_range=0.02, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: intermediate_size=4096, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: is_llama_config=True, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: max_position_embeddings=4096, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_attention_heads=32, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_hidden_layers=24, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: num_key_value_heads=32, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pad_token_id=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: pretraining_tp=1, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rms_norm_eps=1e-05, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rope_scaling=None, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: rope_theta=10000.0, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: tie_word_embeddings=True, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: use_cache=True, | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: vocab_size=50264) | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Building model.. | |
| [default0]:07/02/2024 15:19:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Setting PP block ranks... | |
| [default1]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-56]: Local number of parameters: 139M (264.73MiB) | |
| [default0]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Total number of parameters: 1.11G (2117.88MiB) | |
| [default0]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Local number of parameters: 139M (264.73MiB) | |
| [default0]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB | |
| [default3]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=3|ip-26-0-171-56]: Local number of parameters: 139M (264.73MiB) | |
| [default3]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=3|ip-26-0-171-56]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB | |
| [default5]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=5|ip-26-0-171-56]: Local number of parameters: 139M (264.73MiB) | |
| [default5]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=5|ip-26-0-171-56]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB | |
| [default7]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=7|ip-26-0-171-56]: Local number of parameters: 139M (264.73MiB) | |
| [default7]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=7|ip-26-0-171-56]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB | |
| [default7]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=7|ip-26-0-171-56]: No checkpoint path provided. | |
| [default6]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=6|ip-26-0-171-56]: Local number of parameters: 139M (264.73MiB) | |
| [default6]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=6|ip-26-0-171-56]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB | |
| [default6]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=6|ip-26-0-171-56]: No checkpoint path provided. | |
| [default4]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=4|ip-26-0-171-56]: Local number of parameters: 139M (264.73MiB) | |
| [default4]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=4|ip-26-0-171-56]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB | |
| [default4]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=4|ip-26-0-171-56]: No checkpoint path provided. | |
| [default2]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=2|ip-26-0-171-56]: Local number of parameters: 139M (264.73MiB) | |
| [default2]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=2|ip-26-0-171-56]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB | |
| [default2]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=2|ip-26-0-171-56]: No checkpoint path provided. | |
| [default1]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-56]: [After model building] Memory usage: 290.76MiB. Peak allocated: 317.33MiB Peak reserved: 324.00MiB | |
| [default1]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=1|ip-26-0-171-56]: No checkpoint path provided. | |
| [default0]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: No checkpoint path provided. | |
| [default0]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Parametrizing model parameters using StandardParametrizator | |
| [default5]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=5|ip-26-0-171-56]: No checkpoint path provided. | |
| [default3]:07/02/2024 15:19:17 [INFO|DP=0|PP=0|TP=3|ip-26-0-171-56]: No checkpoint path provided. | |
| [default2]:07/02/2024 15:19:18 [INFO|DP=1|PP=0|TP=2|ip-26-0-175-132]: No checkpoint path provided. | |
| [default7]:07/02/2024 15:19:18 [INFO|DP=1|PP=0|TP=7|ip-26-0-175-132]: No checkpoint path provided. | |
| [default5]:07/02/2024 15:19:18 [INFO|DP=1|PP=0|TP=5|ip-26-0-175-132]: No checkpoint path provided. | |
| [default4]:07/02/2024 15:19:18 [INFO|DP=1|PP=0|TP=4|ip-26-0-175-132]: No checkpoint path provided. | |
| [default1]:07/02/2024 15:19:18 [INFO|DP=1|PP=0|TP=1|ip-26-0-175-132]: No checkpoint path provided. | |
| [default0]:07/02/2024 15:19:18 [INFO|DP=1|PP=0|TP=0|ip-26-0-175-132]: No checkpoint path provided. | |
| [default6]:07/02/2024 15:19:18 [INFO|DP=1|PP=0|TP=6|ip-26-0-175-132]: No checkpoint path provided. | |
| [default3]:07/02/2024 15:19:18 [INFO|DP=1|PP=0|TP=3|ip-26-0-175-132]: No checkpoint path provided. | |
| [default0]:07/02/2024 15:19:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Optimizer Building] Using LearningRateForSP as learning rate | |
| [default0]:07/02/2024 15:19:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [ZeRO sharding] Size of optimizer params per rank: | |
| [default0]:07/02/2024 15:19:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [ZeRO sharding] DP Rank 0 has 69.4M out of 139M (50.00%) params' optimizer states | |
| [default0]:07/02/2024 15:19:19 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [ZeRO sharding] DP Rank 1 has 69.4M out of 139M (50.00%) params' optimizer states | |
| [default0]:07/02/2024 15:19:21 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples | |
| [default0]:07/02/2024 15:19:21 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Using `datasets` library | |
| [default0]:07/02/2024 15:19:21 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4') | |
| [default0]:07/02/2024 15:19:21 [WARNING|DP=0|PP=0|TP=0|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default0]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default0]:07/02/2024 15:19:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Training Plan] There are 1 training stages | |
| [default0]:07/02/2024 15:19:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Stage Training Stage] start from step 1 | |
| [default0]:07/02/2024 15:19:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: | |
| [default0]:07/02/2024 15:19:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: [Start training] datetime: 2024-07-02 15:19:22.240788 | mbs: 256 | grad_accum: 2 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0 | |
| [default0]:07/02/2024 15:19:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps | |
| [default0]:07/02/2024 15:19:22 [INFO|DP=0|PP=0|TP=0|ip-26-0-171-56]: Memory usage: 1085.49MiB. Peak allocated 1085.49MiB. Peak reserved: 1120.00MiB | |
| [default4]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default4]:07/02/2024 15:19:22 [WARNING|DP=0|PP=0|TP=4|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default2]:07/02/2024 15:19:22 [WARNING|DP=0|PP=0|TP=2|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default3]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default3]:07/02/2024 15:19:22 [WARNING|DP=0|PP=0|TP=3|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default5]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default5]:07/02/2024 15:19:22 [WARNING|DP=0|PP=0|TP=5|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default2]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default2]:07/02/2024 15:19:22 [WARNING|DP=1|PP=0|TP=2|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default2]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default6]:07/02/2024 15:19:22 [WARNING|DP=1|PP=0|TP=6|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default6]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default6]:07/02/2024 15:19:22 [WARNING|DP=0|PP=0|TP=6|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default1]:07/02/2024 15:19:22 [WARNING|DP=0|PP=0|TP=1|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default1]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default6]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default7]:07/02/2024 15:19:22 [WARNING|DP=1|PP=0|TP=7|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default5]:07/02/2024 15:19:22 [WARNING|DP=1|PP=0|TP=5|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default4]:07/02/2024 15:19:22 [WARNING|DP=1|PP=0|TP=4|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default1]:07/02/2024 15:19:22 [WARNING|DP=1|PP=0|TP=1|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default4]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default5]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default0]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default0]:07/02/2024 15:19:22 [WARNING|DP=1|PP=0|TP=0|ip-26-0-175-132]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default1]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default3]:07/02/2024 15:19:22 [WARNING|DP=1|PP=0|TP=3|ip-26-0-175-132]: 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. | |
| [default7]:07/02/2024 15:19:27 [WARNING|DP=0|PP=0|TP=7|ip-26-0-171-56]: Repo card metadata block was not found. Setting CardData to empty. | |
| [default7]:Repo card metadata block was not found. Setting CardData to empty. | |
| [default6]:[rank6]: Traceback (most recent call last): | |
| [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [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 151, in forward | |
| [default6]:[rank6]: output = self.pp_block(**new_kwargs) | |
| [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 637, in forward | |
| [default6]:[rank6]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_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/models/llama.py", line 172, in forward | |
| [default6]:[rank6]: hidden_states = self.down_proj(self.split_silu_mul(merged_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/tensor_parallel/nn.py", line 159, in forward | |
| [default6]:[rank6]: return row_linear( | |
| [default6]:[rank6]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default6]:[rank6]: out = F.linear(input, weight, bias) | |
| [default6]:[rank6]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.64 GiB is free. Including non-PyTorch memory, this process has 77.67 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default3]:[rank3]: Traceback (most recent call last): | |
| [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [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 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/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default3]:[rank3]: return row_linear( | |
| [default3]:[rank3]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default3]:[rank3]: out = F.linear(input, weight, bias) | |
| [default3]:[rank3]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.77 GiB is free. Including non-PyTorch memory, this process has 77.55 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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 <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 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/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default0]:[rank0]: return row_linear( | |
| [default0]:[rank0]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default0]:[rank0]: out = F.linear(input, weight, bias) | |
| [default0]:[rank0]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. 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 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/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default1]:[rank1]: return row_linear( | |
| [default1]:[rank1]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default1]:[rank1]: out = F.linear(input, weight, bias) | |
| [default1]:[rank1]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.90 GiB is free. Including non-PyTorch memory, this process has 77.41 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default4]:[rank4]: Traceback (most recent call last): | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default4]:[rank4]: trainer.train(dataloader) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default4]:[rank4]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default4]:[rank4]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default4]:[rank4]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default4]:[rank4]: output = model(**micro_batch) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default4]:[rank4]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank4]: return forward_call(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default4]:[rank4]: sharded_logits = self.model( | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default4]:[rank4]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank4]: return forward_call(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default4]:[rank4]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default4]:[rank4]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default4]:[rank4]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank4]: return forward_call(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default4]:[rank4]: output = self.pp_block(**new_kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default4]:[rank4]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank4]: return forward_call(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default4]:[rank4]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default4]:[rank4]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank4]: return forward_call(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default4]:[rank4]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default4]:[rank4]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank4]: return forward_call(*args, **kwargs) | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default4]:[rank4]: return row_linear( | |
| [default4]:[rank4]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default4]:[rank4]: out = F.linear(input, weight, bias) | |
| [default4]:[rank4]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.64 GiB is free. Including non-PyTorch memory, this process has 77.67 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default2]:[rank2]: Traceback (most recent call last): | |
| [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [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 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/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default2]:[rank2]: return row_linear( | |
| [default2]:[rank2]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default2]:[rank2]: out = F.linear(input, weight, bias) | |
| [default2]:[rank2]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.80 GiB is free. Including non-PyTorch memory, this process has 77.52 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default7]:[rank7]: Traceback (most recent call last): | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default7]:[rank7]: trainer.train(dataloader) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default7]:[rank7]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default7]:[rank7]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default7]:[rank7]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default7]:[rank7]: output = model(**micro_batch) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default7]:[rank7]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank7]: return forward_call(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default7]:[rank7]: sharded_logits = self.model( | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default7]:[rank7]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank7]: return forward_call(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default7]:[rank7]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default7]:[rank7]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default7]:[rank7]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank7]: return forward_call(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default7]:[rank7]: output = self.pp_block(**new_kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default7]:[rank7]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank7]: return forward_call(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default7]:[rank7]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default7]:[rank7]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank7]: return forward_call(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default7]:[rank7]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl | |
| [default7]:[rank7]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank7]: return forward_call(*args, **kwargs) | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default7]:[rank7]: return row_linear( | |
| [default7]:[rank7]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default7]:[rank7]: out = F.linear(input, weight, bias) | |
| [default7]:[rank7]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.92 GiB is free. Including non-PyTorch memory, this process has 77.39 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default5]:[rank5]: Traceback (most recent call last): | |
| [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [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 151, in forward | |
| [default5]:[rank5]: output = self.pp_block(**new_kwargs) | |
| [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 637, in forward | |
| [default5]:[rank5]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_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/models/llama.py", line 172, in forward | |
| [default5]:[rank5]: hidden_states = self.down_proj(self.split_silu_mul(merged_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/tensor_parallel/nn.py", line 159, in forward | |
| [default5]:[rank5]: return row_linear( | |
| [default5]:[rank5]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default5]:[rank5]: out = F.linear(input, weight, bias) | |
| [default5]:[rank5]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.64 GiB is free. Including non-PyTorch memory, this process has 77.67 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default2]:[rank10]: Traceback (most recent call last): | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default2]:[rank10]: trainer.train(dataloader) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default2]:[rank10]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default2]:[rank10]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default2]:[rank10]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default2]:[rank10]: output = model(**micro_batch) | |
| [default2]:[rank10]: 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]:[rank10]: return self._call_impl(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default2]:[rank10]: return forward_call(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default2]:[rank10]: sharded_logits = self.model( | |
| [default2]:[rank10]: 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]:[rank10]: return self._call_impl(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default2]:[rank10]: return forward_call(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default2]:[rank10]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default2]:[rank10]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default2]:[rank10]: 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]:[rank10]: return self._call_impl(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default2]:[rank10]: return forward_call(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default2]:[rank10]: output = self.pp_block(**new_kwargs) | |
| [default2]:[rank10]: 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]:[rank10]: return self._call_impl(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default2]:[rank10]: return forward_call(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default2]:[rank10]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default2]:[rank10]: 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]:[rank10]: return self._call_impl(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default2]:[rank10]: return forward_call(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default2]:[rank10]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default2]:[rank10]: 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]:[rank10]: return self._call_impl(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default2]:[rank10]: return forward_call(*args, **kwargs) | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default2]:[rank10]: return row_linear( | |
| [default2]:[rank10]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default2]:[rank10]: out = F.linear(input, weight, bias) | |
| [default2]:[rank10]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.80 GiB is free. Including non-PyTorch memory, this process has 77.52 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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]:[rank14]: Traceback (most recent call last): | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default6]:[rank14]: trainer.train(dataloader) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default6]:[rank14]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default6]:[rank14]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default6]:[rank14]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default6]:[rank14]: output = model(**micro_batch) | |
| [default6]:[rank14]: 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]:[rank14]: return self._call_impl(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default6]:[rank14]: return forward_call(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default6]:[rank14]: sharded_logits = self.model( | |
| [default6]:[rank14]: 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]:[rank14]: return self._call_impl(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default6]:[rank14]: return forward_call(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default6]:[rank14]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default6]:[rank14]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default6]:[rank14]: 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]:[rank14]: return self._call_impl(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default6]:[rank14]: return forward_call(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default6]:[rank14]: output = self.pp_block(**new_kwargs) | |
| [default6]:[rank14]: 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]:[rank14]: return self._call_impl(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default6]:[rank14]: return forward_call(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default6]:[rank14]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default6]:[rank14]: 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]:[rank14]: return self._call_impl(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default6]:[rank14]: return forward_call(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default6]:[rank14]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default6]:[rank14]: 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]:[rank14]: return self._call_impl(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default6]:[rank14]: return forward_call(*args, **kwargs) | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default6]:[rank14]: return row_linear( | |
| [default6]:[rank14]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default6]:[rank14]: out = F.linear(input, weight, bias) | |
| [default6]:[rank14]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.64 GiB is free. Including non-PyTorch memory, this process has 77.67 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default3]:[rank11]: Traceback (most recent call last): | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default3]:[rank11]: trainer.train(dataloader) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default3]:[rank11]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default3]:[rank11]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default3]:[rank11]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default3]:[rank11]: output = model(**micro_batch) | |
| [default3]:[rank11]: 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]:[rank11]: return self._call_impl(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default3]:[rank11]: return forward_call(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default3]:[rank11]: sharded_logits = self.model( | |
| [default3]:[rank11]: 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]:[rank11]: return self._call_impl(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default3]:[rank11]: return forward_call(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default3]:[rank11]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default3]:[rank11]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default3]:[rank11]: 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]:[rank11]: return self._call_impl(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default3]:[rank11]: return forward_call(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default3]:[rank11]: output = self.pp_block(**new_kwargs) | |
| [default3]:[rank11]: 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]:[rank11]: return self._call_impl(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default3]:[rank11]: return forward_call(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default3]:[rank11]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default3]:[rank11]: 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]:[rank11]: return self._call_impl(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default3]:[rank11]: return forward_call(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default3]:[rank11]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default3]:[rank11]: 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]:[rank11]: return self._call_impl(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default3]:[rank11]: return forward_call(*args, **kwargs) | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default3]:[rank11]: return row_linear( | |
| [default3]:[rank11]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default3]:[rank11]: out = F.linear(input, weight, bias) | |
| [default3]:[rank11]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.77 GiB is free. Including non-PyTorch memory, this process has 77.55 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default4]:[rank12]: Traceback (most recent call last): | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default4]:[rank12]: trainer.train(dataloader) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default4]:[rank12]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default4]:[rank12]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default4]:[rank12]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default4]:[rank12]: output = model(**micro_batch) | |
| [default4]:[rank12]: 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]:[rank12]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank12]: return forward_call(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default4]:[rank12]: sharded_logits = self.model( | |
| [default4]:[rank12]: 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]:[rank12]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank12]: return forward_call(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default4]:[rank12]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default4]:[rank12]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default4]:[rank12]: 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]:[rank12]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank12]: return forward_call(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default4]:[rank12]: output = self.pp_block(**new_kwargs) | |
| [default4]:[rank12]: 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]:[rank12]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank12]: return forward_call(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default4]:[rank12]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default4]:[rank12]: 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]:[rank12]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank12]: return forward_call(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default4]:[rank12]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default4]:[rank12]: 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]:[rank12]: return self._call_impl(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default4]:[rank12]: return forward_call(*args, **kwargs) | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default4]:[rank12]: return row_linear( | |
| [default4]:[rank12]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default4]:[rank12]: out = F.linear(input, weight, bias) | |
| [default4]:[rank12]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.64 GiB is free. Including non-PyTorch memory, this process has 77.67 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default5]:[rank13]: Traceback (most recent call last): | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default5]:[rank13]: trainer.train(dataloader) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default5]:[rank13]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default5]:[rank13]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default5]:[rank13]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default5]:[rank13]: output = model(**micro_batch) | |
| [default5]:[rank13]: 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]:[rank13]: return self._call_impl(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default5]:[rank13]: return forward_call(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default5]:[rank13]: sharded_logits = self.model( | |
| [default5]:[rank13]: 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]:[rank13]: return self._call_impl(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default5]:[rank13]: return forward_call(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default5]:[rank13]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default5]:[rank13]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default5]:[rank13]: 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]:[rank13]: return self._call_impl(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default5]:[rank13]: return forward_call(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default5]:[rank13]: output = self.pp_block(**new_kwargs) | |
| [default5]:[rank13]: 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]:[rank13]: return self._call_impl(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default5]:[rank13]: return forward_call(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default5]:[rank13]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default5]:[rank13]: 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]:[rank13]: return self._call_impl(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default5]:[rank13]: return forward_call(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default5]:[rank13]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default5]:[rank13]: 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]:[rank13]: return self._call_impl(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default5]:[rank13]: return forward_call(*args, **kwargs) | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default5]:[rank13]: return row_linear( | |
| [default5]:[rank13]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default5]:[rank13]: out = F.linear(input, weight, bias) | |
| [default5]:[rank13]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.64 GiB is free. Including non-PyTorch memory, this process has 77.67 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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]:[rank9]: Traceback (most recent call last): | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default1]:[rank9]: trainer.train(dataloader) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default1]:[rank9]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default1]:[rank9]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default1]:[rank9]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default1]:[rank9]: output = model(**micro_batch) | |
| [default1]:[rank9]: 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]:[rank9]: return self._call_impl(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default1]:[rank9]: return forward_call(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default1]:[rank9]: sharded_logits = self.model( | |
| [default1]:[rank9]: 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]:[rank9]: return self._call_impl(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default1]:[rank9]: return forward_call(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default1]:[rank9]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default1]:[rank9]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default1]:[rank9]: 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]:[rank9]: return self._call_impl(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default1]:[rank9]: return forward_call(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default1]:[rank9]: output = self.pp_block(**new_kwargs) | |
| [default1]:[rank9]: 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]:[rank9]: return self._call_impl(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default1]:[rank9]: return forward_call(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default1]:[rank9]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default1]:[rank9]: 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]:[rank9]: return self._call_impl(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default1]:[rank9]: return forward_call(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default1]:[rank9]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default1]:[rank9]: 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]:[rank9]: return self._call_impl(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default1]:[rank9]: return forward_call(*args, **kwargs) | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default1]:[rank9]: return row_linear( | |
| [default1]:[rank9]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default1]:[rank9]: out = F.linear(input, weight, bias) | |
| [default1]:[rank9]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.90 GiB is free. Including non-PyTorch memory, this process has 77.41 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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) | |
| [default7]:[rank15]: Traceback (most recent call last): | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default7]:[rank15]: trainer.train(dataloader) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default7]:[rank15]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default7]:[rank15]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default7]:[rank15]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default7]:[rank15]: output = model(**micro_batch) | |
| [default7]:[rank15]: 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]:[rank15]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank15]: return forward_call(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default7]:[rank15]: sharded_logits = self.model( | |
| [default7]:[rank15]: 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]:[rank15]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank15]: return forward_call(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default7]:[rank15]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default7]:[rank15]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default7]:[rank15]: 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]:[rank15]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank15]: return forward_call(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default7]:[rank15]: output = self.pp_block(**new_kwargs) | |
| [default7]:[rank15]: 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]:[rank15]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank15]: return forward_call(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default7]:[rank15]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default7]:[rank15]: 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]:[rank15]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank15]: return forward_call(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default7]:[rank15]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default7]:[rank15]: 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]:[rank15]: return self._call_impl(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default7]:[rank15]: return forward_call(*args, **kwargs) | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default7]:[rank15]: return row_linear( | |
| [default7]:[rank15]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default7]:[rank15]: out = F.linear(input, weight, bias) | |
| [default7]:[rank15]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU has a total capacity of 79.33 GiB of which 1.92 GiB is free. Including non-PyTorch memory, this process has 77.39 GiB memory in use. Of the allocated memory 68.19 GiB is allocated by PyTorch, and 437.50 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]:[rank8]: Traceback (most recent call last): | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module> | |
| [default0]:[rank8]: trainer.train(dataloader) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 429, in train | |
| [default0]:[rank8]: outputs, loss_avg = self.training_step(dataloader=self.current_dataloader) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 462, in training_step | |
| [default0]:[rank8]: outputs = self.pipeline_engine.train_batch_iter( | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 278, in train_batch_iter | |
| [default0]:[rank8]: output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward | |
| [default0]:[rank8]: output = model(**micro_batch) | |
| [default0]:[rank8]: 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]:[rank8]: return self._call_impl(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default0]:[rank8]: return forward_call(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 891, in forward | |
| [default0]:[rank8]: sharded_logits = self.model( | |
| [default0]:[rank8]: 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]:[rank8]: return self._call_impl(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default0]:[rank8]: return forward_call(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward | |
| [default0]:[rank8]: return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0] | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states | |
| [default0]:[rank8]: hidden_encoder_states = encoder_block(**hidden_encoder_states) | |
| [default0]:[rank8]: 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]:[rank8]: return self._call_impl(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default0]:[rank8]: return forward_call(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward | |
| [default0]:[rank8]: output = self.pp_block(**new_kwargs) | |
| [default0]:[rank8]: 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]:[rank8]: return self._call_impl(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default0]:[rank8]: return forward_call(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 637, in forward | |
| [default0]:[rank8]: hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"] | |
| [default0]:[rank8]: 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]:[rank8]: return self._call_impl(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default0]:[rank8]: return forward_call(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 172, in forward | |
| [default0]:[rank8]: hidden_states = self.down_proj(self.split_silu_mul(merged_states)) | |
| [default0]:[rank8]: 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]:[rank8]: return self._call_impl(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl | |
| [default0]:[rank8]: return forward_call(*args, **kwargs) | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward | |
| [default0]:[rank8]: return row_linear( | |
| [default0]:[rank8]: File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear | |
| [default0]:[rank8]: out = F.linear(input, weight, bias) | |
| [default0]:[rank8]: torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB. GPU | |
| W0702 15:19:39.228000 140625870714688 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 3045195 closing signal SIGTERM | |
| W0702 15:19:39.228000 140625870714688 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 3045196 closing signal SIGTERM | |
| W0702 15:19:39.228000 140625870714688 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 3045197 closing signal SIGTERM | |
| W0702 15:19:39.232000 139643089798976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 69383 closing signal SIGTERM | |
| W0702 15:19:39.232000 139643089798976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 69384 closing signal SIGTERM | |
| W0702 15:19:39.232000 139643089798976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 69385 closing signal SIGTERM | |
| W0702 15:19:39.232000 139643089798976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 69386 closing signal SIGTERM | |
| W0702 15:19:39.233000 139643089798976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 69387 closing signal SIGTERM | |
| W0702 15:19:39.233000 139643089798976 torch/distributed/elastic/multiprocessing/api.py:851] Sending process 69389 closing signal SIGTERM | |
| E0702 15:19:40.660000 140625870714688 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 3045192) 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 : 2024-07-02_15:19:39 | |
| host : ip-26-0-171-56.ec2.internal | |
| rank : 1 (local_rank: 1) | |
| exitcode : 1 (pid: 3045193) | |
| error_file: <N/A> | |
| traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html | |
| [2]: | |
| time : 2024-07-02_15:19:39 | |
| host : ip-26-0-171-56.ec2.internal | |
| rank : 2 (local_rank: 2) | |
| exitcode : 1 (pid: 3045194) | |
| error_file: <N/A> | |
| traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html | |
| [3]: | |
| time : 2024-07-02_15:19:39 | |
| host : ip-26-0-171-56.ec2.internal | |
| rank : 6 (local_rank: 6) | |
| exitcode : 1 (pid: 3045198) | |
| error_file: <N/A> | |
| traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html | |
| [4]: | |
| time : 2024-07-02_15:19:39 | |
| host : ip-26-0-171-56.ec2.internal | |
| rank : 7 (local_rank: 7) | |
| exitcode : 1 (pid: 3045199) | |
| error_file: <N/A> | |
| traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html | |
| ------------------------------------------------------------ | |
| Root Cause (first observed failure): | |
| [0]: | |
| time : 2024-07-02_15:19:39 | |
| host : ip-26-0-171-56.ec2.internal | |
| rank : 0 (local_rank: 0) | |
| exitcode : 1 (pid: 3045192) | |
| error_file: <N/A> | |
| traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html | |
| ============================================================ | |
| srun: error: ip-26-0-171-56: task 0: Exited with exit code 1 | |
| E0702 15:19:41.361000 139643089798976 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 69382) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10 | |
| W0702 15:19:41.367000 139643089798976 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1203] The node 'ip-26-0-175-132.ec2.internal_69313_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError. | |
| W0702 15:19:41.395000 139643089798976 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1203] The node 'ip-26-0-175-132.ec2.internal_69313_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError. | |
| W0702 15:19:41.407000 139643089798976 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1203] The node 'ip-26-0-175-132.ec2.internal_69313_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError. | |
| 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 : 2024-07-02_15:19:39 | |
| host : ip-26-0-175-132.ec2.internal | |
| rank : 14 (local_rank: 6) | |
| exitcode : 1 (pid: 69388) | |
| error_file: <N/A> | |
| traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html | |
| ------------------------------------------------------------ | |
| Root Cause (first observed failure): | |
| [0]: | |
| time : 2024-07-02_15:19:39 | |
| host : ip-26-0-175-132.ec2.internal | |
| rank : 8 (local_rank: 0) | |
| exitcode : 1 (pid: 69382) | |
| error_file: <N/A> | |
| traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html | |
| ============================================================ | |
| srun: error: ip-26-0-175-132: task 1: 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. | |