llama-1B/64_GPUS/dp-16_tp-1_pp-4_mbz-1/log.out

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START TIME: Sat Jul  6 09:35:17 UTC 2024
python3 version = Python 3.10.14
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M	examples/config_tiny_llama.py
M	examples/config_tiny_llama.yaml
M	examples/train_tiny_llama.sh
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Job status: RUNNING
[2024-07-06 09:35:20,358] torch.distributed.run: [WARNING] 
[2024-07-06 09:35:20,358] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,358] torch.distributed.run: [WARNING] 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. 
[2024-07-06 09:35:20,358] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,365] torch.distributed.run: [WARNING] 
[2024-07-06 09:35:20,365] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,365] torch.distributed.run: [WARNING] 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. 
[2024-07-06 09:35:20,365] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,368] torch.distributed.run: [WARNING] 
[2024-07-06 09:35:20,368] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,368] torch.distributed.run: [WARNING] 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. 
[2024-07-06 09:35:20,368] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,372] torch.distributed.run: [WARNING] 
[2024-07-06 09:35:20,372] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,372] torch.distributed.run: [WARNING] 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. 
[2024-07-06 09:35:20,372] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,399] torch.distributed.run: [WARNING] 
[2024-07-06 09:35:20,399] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,399] torch.distributed.run: [WARNING] 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. 
[2024-07-06 09:35:20,399] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,420] torch.distributed.run: [WARNING] 
[2024-07-06 09:35:20,420] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,420] torch.distributed.run: [WARNING] 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. 
[2024-07-06 09:35:20,420] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,424] torch.distributed.run: [WARNING] 
[2024-07-06 09:35:20,424] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,424] torch.distributed.run: [WARNING] 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. 
[2024-07-06 09:35:20,424] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,427] torch.distributed.run: [WARNING] 
[2024-07-06 09:35:20,427] torch.distributed.run: [WARNING] *****************************************
[2024-07-06 09:35:20,427] torch.distributed.run: [WARNING] 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. 
[2024-07-06 09:35:20,427] torch.distributed.run: [WARNING] *****************************************
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Config:
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                            run='%date_%jobid',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                            seed=42,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                            step=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                            consumed_train_samples=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                            benchmark_csv_path=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                            ignore_sanity_checks=True),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        parallelism=ParallelismArgs(dp=16,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    pp=4,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    tp=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    pp_engine=<nanotron.parallel.pipeline_parallel.engine.AllForwardAllBackwardPipelineEngine object at 0x7fb44f9a0700>,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    tp_linear_async_communication=False,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    expert_parallel_size=1),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 eos_token_id=2,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 hidden_act='silu',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 hidden_size=2048,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 initializer_range=0.02,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 intermediate_size=4096,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 is_llama_config=True,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 max_position_embeddings=4096,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 num_attention_heads=32,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 num_hidden_layers=24,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 num_key_value_heads=32,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 pad_token_id=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 pretraining_tp=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 rms_norm_eps=1e-05,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 rope_scaling=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 rope_theta=10000.0,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 tie_word_embeddings=True,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 use_cache=True,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                 vocab_size=50257),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                        init_method=RandomInit(std=0.025),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                        dtype=torch.bfloat16,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                        make_vocab_size_divisible_by=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                        ddp_bucket_cap_mb=25),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                tokenizer_revision=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                tokenizer_max_length=None),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        checkpoints=CheckpointsArgs(checkpoints_path=PosixPath('/dev/null'),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    checkpoint_interval=100000,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    save_initial_state=False,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    resume_checkpoint_path=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                    checkpoints_path_is_shared_file_system=False),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        logging=LoggingArgs(log_level='info',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                            log_level_replica='info',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                            iteration_step_info_interval=1),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        tokens=TokensArgs(sequence_length=4096,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                          train_steps=20,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                          micro_batch_size=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                          batch_accumulation_per_replica=64,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                          val_check_interval=-1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                          limit_val_batches=0,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                          limit_test_batches=0),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                     adam_beta1=0.9,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                     adam_beta2=0.95,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                     torch_adam_is_fused=True,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                     name='adamW'),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                zero_stage=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                weight_decay=0.01,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                clip_grad=1.0,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                accumulate_grad_in_fp32=True,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                        lr_warmup_steps=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                        lr_warmup_style='linear',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                        lr_decay_style='linear',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                        lr_decay_steps=19,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                        lr_decay_starting_step=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                        min_decay_lr=1e-05)),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                      start_training_step=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                      data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                                 hf_dataset_splits='train',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                                 hf_dataset_config_name=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                                 dataset_processing_num_proc_per_process=64,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                                 dataset_overwrite_cache=False,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                                                 text_column_name='text'),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                    seed=42,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:                                                    num_loading_workers=0))],
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        profiler=ProfilerArgs(profiler_export_path=PosixPath('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/64_GPUS/dp-16_tp-1_pp-4_mbz-1')),
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:        lighteval=None)
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Model Config:
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: LlamaConfig(bos_token_id=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             eos_token_id=2,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             hidden_act='silu',
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             hidden_size=2048,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             initializer_range=0.02,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             intermediate_size=4096,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             is_llama_config=True,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             max_position_embeddings=4096,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             num_attention_heads=32,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             num_hidden_layers=24,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             num_key_value_heads=32,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             pad_token_id=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             pretraining_tp=1,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             rms_norm_eps=1e-05,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             rope_scaling=None,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             rope_theta=10000.0,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             tie_word_embeddings=True,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             use_cache=True,
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:             vocab_size=50257)
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Building model..
[default0]:07/06/2024 09:35:38 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Setting PP block ranks...
[default0]:07/06/2024 09:35:49 [INFO|DP=8|PP=3|TP=0|ip-26-0-173-7]: No checkpoint path provided.
[default3]:07/06/2024 09:35:49 [INFO|DP=11|PP=3|TP=0|ip-26-0-173-7]: No checkpoint path provided.
[default3]:07/06/2024 09:35:49 [INFO|DP=11|PP=2|TP=0|ip-26-0-164-75]: No checkpoint path provided.
[default3]:07/06/2024 09:35:49 [INFO|DP=11|PP=0|TP=0|ip-26-0-163-236]: No checkpoint path provided.
[default0]:07/06/2024 09:35:49 [INFO|DP=8|PP=2|TP=0|ip-26-0-164-75]: No checkpoint path provided.
[default3]:07/06/2024 09:35:49 [INFO|DP=11|PP=1|TP=0|ip-26-0-164-187]: No checkpoint path provided.
[default0]:07/06/2024 09:35:49 [INFO|DP=8|PP=1|TP=0|ip-26-0-164-187]: No checkpoint path provided.
[default0]:07/06/2024 09:35:49 [INFO|DP=8|PP=0|TP=0|ip-26-0-163-236]: No checkpoint path provided.
[default2]:07/06/2024 09:35:49 [INFO|DP=10|PP=3|TP=0|ip-26-0-173-7]: No checkpoint path provided.
[default1]:07/06/2024 09:35:49 [INFO|DP=9|PP=2|TP=0|ip-26-0-164-75]: No checkpoint path provided.
[default1]:07/06/2024 09:35:49 [INFO|DP=9|PP=3|TP=0|ip-26-0-173-7]: No checkpoint path provided.
[default2]:07/06/2024 09:35:49 [INFO|DP=10|PP=0|TP=0|ip-26-0-163-236]: No checkpoint path provided.
[default2]:07/06/2024 09:35:49 [INFO|DP=10|PP=2|TP=0|ip-26-0-164-75]: No checkpoint path provided.
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=3|TP=0|ip-26-0-172-252]: Local number of parameters: 271M (516.35MiB)
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=3|TP=0|ip-26-0-172-252]: [After model building] Memory usage: 520.36MiB. Peak allocated: 522.39MiB Peak reserved: 534.00MiB
[default1]:07/06/2024 09:35:49 [INFO|DP=9|PP=0|TP=0|ip-26-0-163-236]: No checkpoint path provided.
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Total number of parameters: 1.21G (2312.82MiB)
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Local number of parameters: 397M (756.37MiB)
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [After model building] Memory usage: 763.38MiB. Peak allocated: 765.41MiB Peak reserved: 792.00MiB
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: No checkpoint path provided.
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Parametrizing model parameters using StandardParametrizator
[default1]:07/06/2024 09:35:49 [INFO|DP=9|PP=1|TP=0|ip-26-0-164-187]: No checkpoint path provided.
[default2]:07/06/2024 09:35:49 [INFO|DP=10|PP=1|TP=0|ip-26-0-164-187]: No checkpoint path provided.
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=1|TP=0|ip-26-0-164-18]: Local number of parameters: 294M (560.05MiB)
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=1|TP=0|ip-26-0-164-18]: [After model building] Memory usage: 567.07MiB. Peak allocated: 569.10MiB Peak reserved: 594.00MiB
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=1|TP=0|ip-26-0-164-18]: No checkpoint path provided.
[default3]:07/06/2024 09:35:49 [INFO|DP=3|PP=2|TP=0|ip-26-0-164-45]: No checkpoint path provided.
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=2|TP=0|ip-26-0-164-45]: Local number of parameters: 252M (480.05MiB)
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=2|TP=0|ip-26-0-164-45]: [After model building] Memory usage: 486.06MiB. Peak allocated: 488.09MiB Peak reserved: 502.00MiB
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=2|TP=0|ip-26-0-164-45]: No checkpoint path provided.
[default6]:07/06/2024 09:35:49 [INFO|DP=14|PP=2|TP=0|ip-26-0-164-75]: No checkpoint path provided.
[default6]:07/06/2024 09:35:49 [INFO|DP=14|PP=0|TP=0|ip-26-0-163-236]: No checkpoint path provided.
[default3]:07/06/2024 09:35:49 [INFO|DP=3|PP=3|TP=0|ip-26-0-172-252]: No checkpoint path provided.
[default0]:07/06/2024 09:35:49 [INFO|DP=0|PP=3|TP=0|ip-26-0-172-252]: No checkpoint path provided.
[default3]:07/06/2024 09:35:49 [INFO|DP=3|PP=0|TP=0|ip-26-0-163-220]: No checkpoint path provided.
[default6]:07/06/2024 09:35:49 [INFO|DP=14|PP=3|TP=0|ip-26-0-173-7]: No checkpoint path provided.
[default6]:07/06/2024 09:35:49 [INFO|DP=14|PP=1|TP=0|ip-26-0-164-187]: No checkpoint path provided.
[default2]:07/06/2024 09:35:49 [INFO|DP=2|PP=1|TP=0|ip-26-0-164-18]: No checkpoint path provided.
[default3]:07/06/2024 09:35:49 [INFO|DP=3|PP=1|TP=0|ip-26-0-164-18]: No checkpoint path provided.
[default1]:07/06/2024 09:35:49 [INFO|DP=1|PP=2|TP=0|ip-26-0-164-45]: No checkpoint path provided.
[default7]:07/06/2024 09:35:49 [INFO|DP=15|PP=3|TP=0|ip-26-0-173-7]: No checkpoint path provided.
[default2]:07/06/2024 09:35:49 [INFO|DP=2|PP=2|TP=0|ip-26-0-164-45]: No checkpoint path provided.
[default5]:07/06/2024 09:35:49 [INFO|DP=13|PP=3|TP=0|ip-26-0-173-7]: No checkpoint path provided.
[default4]:07/06/2024 09:35:49 [INFO|DP=12|PP=3|TP=0|ip-26-0-173-7]: No checkpoint path provided.
[default5]:07/06/2024 09:35:49 [INFO|DP=13|PP=2|TP=0|ip-26-0-164-75]: No checkpoint path provided.
[default4]:07/06/2024 09:35:49 [INFO|DP=12|PP=0|TP=0|ip-26-0-163-236]: No checkpoint path provided.
[default5]:07/06/2024 09:35:49 [INFO|DP=13|PP=0|TP=0|ip-26-0-163-236]: No checkpoint path provided.
[default4]:07/06/2024 09:35:49 [INFO|DP=12|PP=2|TP=0|ip-26-0-164-75]: No checkpoint path provided.
[default7]:07/06/2024 09:35:49 [INFO|DP=15|PP=2|TP=0|ip-26-0-164-75]: No checkpoint path provided.
[default2]:07/06/2024 09:35:49 [INFO|DP=2|PP=0|TP=0|ip-26-0-163-220]: No checkpoint path provided.
[default1]:07/06/2024 09:35:49 [INFO|DP=1|PP=0|TP=0|ip-26-0-163-220]: No checkpoint path provided.
[default2]:07/06/2024 09:35:49 [INFO|DP=2|PP=3|TP=0|ip-26-0-172-252]: No checkpoint path provided.
[default1]:07/06/2024 09:35:49 [INFO|DP=1|PP=3|TP=0|ip-26-0-172-252]: No checkpoint path provided.
[default7]:07/06/2024 09:35:49 [INFO|DP=15|PP=1|TP=0|ip-26-0-164-187]: No checkpoint path provided.
[default7]:07/06/2024 09:35:49 [INFO|DP=15|PP=0|TP=0|ip-26-0-163-236]: No checkpoint path provided.
[default1]:07/06/2024 09:35:49 [INFO|DP=1|PP=1|TP=0|ip-26-0-164-18]: No checkpoint path provided.
[default5]:07/06/2024 09:35:49 [INFO|DP=13|PP=1|TP=0|ip-26-0-164-187]: No checkpoint path provided.
[default4]:07/06/2024 09:35:49 [INFO|DP=12|PP=1|TP=0|ip-26-0-164-187]: No checkpoint path provided.
[default5]:07/06/2024 09:35:50 [INFO|DP=5|PP=2|TP=0|ip-26-0-164-45]: No checkpoint path provided.
[default6]:07/06/2024 09:35:50 [INFO|DP=6|PP=2|TP=0|ip-26-0-164-45]: No checkpoint path provided.
[default5]:07/06/2024 09:35:50 [INFO|DP=5|PP=0|TP=0|ip-26-0-163-220]: No checkpoint path provided.
[default6]:07/06/2024 09:35:50 [INFO|DP=6|PP=0|TP=0|ip-26-0-163-220]: No checkpoint path provided.
[default5]:07/06/2024 09:35:50 [INFO|DP=5|PP=3|TP=0|ip-26-0-172-252]: No checkpoint path provided.
[default6]:07/06/2024 09:35:50 [INFO|DP=6|PP=3|TP=0|ip-26-0-172-252]: No checkpoint path provided.
[default5]:07/06/2024 09:35:50 [INFO|DP=5|PP=1|TP=0|ip-26-0-164-18]: No checkpoint path provided.
[default6]:07/06/2024 09:35:50 [INFO|DP=6|PP=1|TP=0|ip-26-0-164-18]: No checkpoint path provided.
[default4]:07/06/2024 09:35:50 [INFO|DP=4|PP=2|TP=0|ip-26-0-164-45]: No checkpoint path provided.
[default7]:07/06/2024 09:35:50 [INFO|DP=7|PP=2|TP=0|ip-26-0-164-45]: No checkpoint path provided.
[default4]:07/06/2024 09:35:50 [INFO|DP=4|PP=3|TP=0|ip-26-0-172-252]: No checkpoint path provided.
[default4]:07/06/2024 09:35:50 [INFO|DP=4|PP=0|TP=0|ip-26-0-163-220]: No checkpoint path provided.
[default7]:07/06/2024 09:35:50 [INFO|DP=7|PP=0|TP=0|ip-26-0-163-220]: No checkpoint path provided.
[default7]:07/06/2024 09:35:50 [INFO|DP=7|PP=1|TP=0|ip-26-0-164-18]: No checkpoint path provided.
[default7]:07/06/2024 09:35:50 [INFO|DP=7|PP=3|TP=0|ip-26-0-172-252]: No checkpoint path provided.
[default4]:07/06/2024 09:35:50 [INFO|DP=4|PP=1|TP=0|ip-26-0-164-18]: No checkpoint path provided.
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 0 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 1 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 2 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 3 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 4 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 5 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 6 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 7 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 8 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 9 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 10 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 11 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 12 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 13 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 14 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:58 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [ZeRO sharding] DP Rank 15 has 24.8M out of 397M (6.25%) params' optimizer states
[default0]:07/06/2024 09:35:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/06/2024 09:35:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Using `datasets` library
[default0]:07/06/2024 09:35:59 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:00 [WARNING|DP=0|PP=0|TP=0|ip-26-0-163-220]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [Training Plan] There are 1 training stages 
[default0]:07/06/2024 09:36:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [Stage Training Stage] start from step 1 
[default0]:07/06/2024 09:36:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: 
[default0]:07/06/2024 09:36:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: [Start training] datetime: 2024-07-06 09:36:01.308894 | mbs: 1 | grad_accum: 64 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
[default5]:07/06/2024 09:36:01 [WARNING|DP=5|PP=2|TP=0|ip-26-0-164-45]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:36:01 [WARNING|DP=1|PP=2|TP=0|ip-26-0-164-45]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:36:01 [WARNING|DP=4|PP=2|TP=0|ip-26-0-164-45]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:36:01 [WARNING|DP=3|PP=2|TP=0|ip-26-0-164-45]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:36:01 [WARNING|DP=9|PP=2|TP=0|ip-26-0-164-75]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:36:01 [WARNING|DP=11|PP=3|TP=0|ip-26-0-173-7]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:36:01 [WARNING|DP=14|PP=2|TP=0|ip-26-0-164-75]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:36:01 [WARNING|DP=10|PP=3|TP=0|ip-26-0-173-7]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:36:01 [WARNING|DP=7|PP=2|TP=0|ip-26-0-164-45]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:36:01 [WARNING|DP=10|PP=2|TP=0|ip-26-0-164-75]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:36:01 [WARNING|DP=9|PP=3|TP=0|ip-26-0-173-7]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:01 [WARNING|DP=0|PP=2|TP=0|ip-26-0-164-45]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:36:01 [WARNING|DP=2|PP=2|TP=0|ip-26-0-164-45]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:36:01 [WARNING|DP=13|PP=2|TP=0|ip-26-0-164-75]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:36:01 [WARNING|DP=11|PP=2|TP=0|ip-26-0-164-75]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:36:01 [WARNING|DP=6|PP=2|TP=0|ip-26-0-164-45]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:36:01 [WARNING|DP=14|PP=0|TP=0|ip-26-0-163-236]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:01 [WARNING|DP=8|PP=2|TP=0|ip-26-0-164-75]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:01 [WARNING|DP=0|PP=3|TP=0|ip-26-0-172-252]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:36:01 [WARNING|DP=10|PP=0|TP=0|ip-26-0-163-236]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:36:01 [WARNING|DP=12|PP=2|TP=0|ip-26-0-164-75]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:36:01 [WARNING|DP=5|PP=3|TP=0|ip-26-0-172-252]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:36:01 [WARNING|DP=9|PP=0|TP=0|ip-26-0-163-236]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:36:01 [WARNING|DP=6|PP=3|TP=0|ip-26-0-172-252]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:36:01 [WARNING|DP=15|PP=2|TP=0|ip-26-0-164-75]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:36:01 [WARNING|DP=3|PP=3|TP=0|ip-26-0-172-252]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:36:01 [WARNING|DP=12|PP=0|TP=0|ip-26-0-163-236]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:36:01 [WARNING|DP=14|PP=3|TP=0|ip-26-0-173-7]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:36:01 [WARNING|DP=1|PP=3|TP=0|ip-26-0-172-252]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:01 [WARNING|DP=0|PP=1|TP=0|ip-26-0-164-18]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:36:01 [WARNING|DP=3|PP=0|TP=0|ip-26-0-163-220]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:36:01 [WARNING|DP=5|PP=0|TP=0|ip-26-0-163-220]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:36:01 [WARNING|DP=2|PP=0|TP=0|ip-26-0-163-220]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:01 [WARNING|DP=8|PP=1|TP=0|ip-26-0-164-187]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:36:01 [WARNING|DP=15|PP=0|TP=0|ip-26-0-163-236]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:36:01 [WARNING|DP=2|PP=3|TP=0|ip-26-0-172-252]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:01 [WARNING|DP=8|PP=0|TP=0|ip-26-0-163-236]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:36:01 [WARNING|DP=2|PP=1|TP=0|ip-26-0-164-18]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/06/2024 09:36:01 [WARNING|DP=10|PP=1|TP=0|ip-26-0-164-187]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:36:01 [WARNING|DP=1|PP=1|TP=0|ip-26-0-164-18]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:36:01 [WARNING|DP=3|PP=1|TP=0|ip-26-0-164-18]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:36:01 [WARNING|DP=15|PP=1|TP=0|ip-26-0-164-187]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:36:01 [WARNING|DP=5|PP=1|TP=0|ip-26-0-164-18]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:36:01 [WARNING|DP=9|PP=1|TP=0|ip-26-0-164-187]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/06/2024 09:36:01 [WARNING|DP=1|PP=0|TP=0|ip-26-0-163-220]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:36:01 [WARNING|DP=4|PP=1|TP=0|ip-26-0-164-18]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:36:01 [WARNING|DP=12|PP=1|TP=0|ip-26-0-164-187]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:36:01 [WARNING|DP=7|PP=0|TP=0|ip-26-0-163-220]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:36:01 [WARNING|DP=13|PP=1|TP=0|ip-26-0-164-187]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:36:01 [WARNING|DP=14|PP=1|TP=0|ip-26-0-164-187]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:36:01 [WARNING|DP=4|PP=0|TP=0|ip-26-0-163-220]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:36:01 [WARNING|DP=11|PP=0|TP=0|ip-26-0-163-236]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:36:01 [WARNING|DP=4|PP=3|TP=0|ip-26-0-172-252]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:36:01 [WARNING|DP=6|PP=0|TP=0|ip-26-0-163-220]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:36:01 [WARNING|DP=7|PP=1|TP=0|ip-26-0-164-18]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/06/2024 09:36:01 [WARNING|DP=11|PP=1|TP=0|ip-26-0-164-187]: Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/06/2024 09:36:01 [WARNING|DP=12|PP=3|TP=0|ip-26-0-173-7]: 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.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:01 [WARNING|DP=8|PP=3|TP=0|ip-26-0-173-7]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:36:01 [WARNING|DP=13|PP=3|TP=0|ip-26-0-173-7]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/06/2024 09:36:01 [WARNING|DP=13|PP=0|TP=0|ip-26-0-163-236]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:36:01 [WARNING|DP=7|PP=3|TP=0|ip-26-0-172-252]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/06/2024 09:36:01 [WARNING|DP=6|PP=1|TP=0|ip-26-0-164-18]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/06/2024 09:36:01 [WARNING|DP=15|PP=3|TP=0|ip-26-0-173-7]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/06/2024 09:36:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/06/2024 09:36:07 [INFO|DP=0|PP=0|TP=0|ip-26-0-163-220]:  Memory usage: 2370.67MiB. Peak allocated 2370.67MiB. Peak reserved: 2402.00MiB
[default3]:Traceback (most recent call last):
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default3]:    trainer.train(dataloader)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default3]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default3]:    outputs = self.pipeline_engine.train_batch_iter(
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default3]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default3]:    output = model(**micro_batch)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default3]:    sharded_logits = self.model(
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default3]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default3]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default3]:    output = self.pp_block(**new_kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default3]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 564, in forward
[default3]:    key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous()
[default3]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 3 has a total capacity of 79.33 GiB of which 17.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 70.13 GiB is allocated by PyTorch, and 34.86 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]:Traceback (most recent call last):
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default0]:    trainer.train(dataloader)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default0]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default0]:    outputs = self.pipeline_engine.train_batch_iter(
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default0]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default0]:    output = model(**micro_batch)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default0]:    sharded_logits = self.model(
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default0]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default0]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default0]:    output = self.pp_block(**new_kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 636, in forward
[default0]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 171, in forward
[default0]:    hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default0]:    return row_linear(
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default0]:    out = F.linear(input, weight, bias)
[default0]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 16.00 MiB. GPU 0 has a total capacity of 79.33 GiB of which 9.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 70.55 GiB is allocated by PyTorch, and 35.81 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]:Traceback (most recent call last):
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default3]:    trainer.train(dataloader)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default3]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default3]:    outputs = self.pipeline_engine.train_batch_iter(
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default3]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default3]:    output = model(**micro_batch)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default3]:    sharded_logits = self.model(
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default3]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default3]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default3]:    output = self.pp_block(**new_kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return self._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default3]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default3]:    return sel[default0]:STAGE:2024-07-06 09:36:17 184411:184411 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
[default0]:STAGE:2024-07-06 09:36:17 184411:184411 ActivityProfilerController.cpp:320] Completed Stage: Collection
[default0]:STAGE:2024-07-06 09:36:17 184411:184411 ActivityProfilerController.cpp:324] Completed Stage: Post Processing
[default0]:Traceback (most recent call last):
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default0]:    trainer.train(dataloader)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default0]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default0]:    outputs = self.pipeline_engine.train_batch_iter(
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotf._call_impl(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default3]:    return forward_call(*args, **kwargs)
[default3]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 564, in forward
[default3]:    key_value_states = key_value_states.permute(1, 2, 0, 3, 4).contiguous()
[default3]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 3 has a total capacity of 79.33 GiB of which 15.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 70.13 GiB is allocated by PyTorch, and 34.86 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-varon/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default0]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default0]:    output = model(**micro_batch)
riables)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default0]:    sharded_logits = self.model(
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default0]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default0]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default0]:    output = self.pp_block(**new_kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 636, in forward
[default0]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 171, in forward
[default0]:    hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default0]:    return self._call_impl(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default0]:    return forward_call(*args, **kwargs)
[default0]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 127, in forward
[default0]:    return self.act(gate_states) * up_states
[default0]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 0 has a total capacity of 79.33 GiB of which 29.94 MiB is free. Including non-PyTorch memory, this process has 79.28 GiB memory in use. Of the allocated memory 70.52 GiB is allocated by PyTorch, and 35.81 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]:Traceback (most recent call last):
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default2]:    trainer.train(dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default2]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default2]:    outputs = self.pipeline_engine.train_batch_iter(
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default2]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default2]:    output = model(**micro_batch)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default2]:    sharded_logits = self.model(
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default2]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default2]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default2]:    output = self.pp_block(**new_kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 636, in forward
[default2]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 171, in forward
[default2]:    hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default2]:    return row_linear(
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default2]:    out = F.linear(input, weight, bias)
[default2]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 16.00 MiB. GPU 2 has a total capacity of 79.33 GiB of which 13.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 69.99 GiB is allocated by PyTorch, and 34.88 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]:Traceback (most recent call last):
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default4]:    trainer.train(dataloader)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default4]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default4]:    outputs = self.pipeline_engine.train_batch_iter(
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default4]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default4]:    output = model(**micro_batch)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default4]:    sharded_logits = self.model(
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default4]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default4]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default4]:    output = self.pp_block(**new_kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default4]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 359, in forward
[default4]:    qkv_states = self.qkv_proj(
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward
[default4]:    return column_linear(
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear
[default4]:    return F.linear(input, weight, bias)
[default4]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 48.00 MiB. GPU 4 has a total capacity of 79.33 GiB of which 47.94 MiB is free. Including non-PyTorch memory, this process has 79.27 GiB memory in use. Of the allocated memory 69.73 GiB is allocated by PyTorch, and 35.39 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]:Traceback (most recent call last):
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default7]:    trainer.train(dataloader)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default7]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default7]:    outputs = self.pipeline_engine.train_batch_iter(
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default7]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default7]:    output = model(**micro_batch)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default7]:    sharded_logits = self.model(
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default7]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default7]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:Traceback (most recent call last):
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default7]:    trainer.train(dataloader)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default7]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default7]:    outputs = self.pipeline_engine.train_batch_iter(
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default7]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default7]:    output = [default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default7]:    output = self.pp_block(**new_kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
model(**micro_batch)
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default7]:    sharded_logits = self.model(
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default7]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default7]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default7]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default7]:    ou[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 562, in forward
tput = self.pp_block(**new_kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default7]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", lin[default7]:    key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
e 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 562, in forward
[default7]:    key_value_states = torch.cat([key_states.unsqueeze(0), value_states.unsqueeze(0)], dim=0)
[default7]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 7 has a total capacity of 79.33 GiB of which 23.94 MiB is free. Including non-PyTorch memory, this process has 79.29 GiB memory in use. Of the allocated memory 69.82 GiB is allocated by PyTorch, and 35.39 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]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 7 has a total capacity of 79.33 GiB of which 23.94 MiB is free. Including non-PyTorch memory, this process has 79.29 GiB memory in use. Of the allocated memory 69.82 GiB is allocated by PyTorch, and 35.39 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]:Traceback (most recent call last):
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default5]:    trainer.train(dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default5]:    outputs = self.pipeline_engine.train_batch_iter(
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default5]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default5]:    output = model(**micro_batch)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default5]:    sharded_logits = self.model(
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default5]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default5]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default5]:    output = self.pp_block(**new_kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default5]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 359, in forward
[default5]:    qkv_states = self.qkv_proj(
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward
[default5]:    return column_linear(
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear
[default5]:    return F.linear(input, weight, bias)
[default5]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 48.00 MiB. GPU 5 has a total capacity of 79.33 GiB of which 47.94 MiB is free. Including non-PyTorch memory, this process has 79.27 GiB memory in use. Of the allocated memory 69.73 GiB is allocated by PyTorch, and 35.39 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]:Traceback (most recent call last):
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default4]:    trainer.train(dataloader)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default4]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default4]:    outputs = self.pipeline_engine.train_batch_iter(
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default4]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default4]:    output = model(**micro_batch)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default5]:Traceback (most recent call last):
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default5]:    trainer.train(dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default5]:    outputs = self.pipeline_engine.train_batch_iter(
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default4]:    sharded_logits = self.model(
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default5]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default5]:    output = model(**micro_batch)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    sharded_logits = self.model(
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default5]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default5]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default5]:    output = self.pp_block(**new_kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default4]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default4]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default5]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 359, in forward
[default5]:    qkv_states = self.qkv_proj(
[default5][default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward
[default5]:    return column_linear(
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear
[default5]:    return F.linear(input, weight, bias)
[default5]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 48.00 MiB. GPU 5 has a total capacity of 79.33 GiB of which 47.94 MiB is free. Including non-PyTorch memory, this process has 79.27 GiB memory in use. Of the allocated memory 69.73 GiB is allocated by PyTorch, and 35.39 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]:    output = self.pp_block(**new_kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default4]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 359, in forward
[default4]:    qkv_states = self.qkv_proj(
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default4]:    return self._call_impl(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default4]:    return forward_call(*args, **kwargs)
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward
[default4]:    return column_linear(
[default4]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear
[default4]:    return F.linear(input, weight, bias)
[default4]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 48.00 MiB. GPU 4 has a total capacity of 79.33 GiB of which 47.94 MiB is free. Including non-PyTorch memory, this process has 79.27 GiB memory in use. Of the allocated memory 69.73 GiB is allocated by PyTorch, and 35.39 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]:Traceback (most recent call last):
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default6]:    trainer.train(dataloader)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default6]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default6]:    outputs = self.pipeline_engine.train_batch_iter(
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default6]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default6]:    output = model(**micro_batch)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default6]:    sharded_logits = self.model(
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default6]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default6]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default6]:    output = self.pp_block(**new_kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default6]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 359, in forward
[default6]:    qkv_states = self.qkv_proj(
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward
[default6]:    return column_linear(
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear
[default6]:    return F.linear(input, weight, bias)
[default6]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 48.00 MiB. GPU 6 has a total capacity of 79.33 GiB of which 47.94 MiB is free. Including non-PyTorch memory, this process has 79.27 GiB memory in use. Of the allocated memory 69.73 GiB is allocated by PyTorch, and 35.39 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]:Traceback (most recent call last):
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default1]:    trainer.train(dataloader)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default1]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default1]:    outputs = self.pipeline_engine.train_batch_iter(
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default1]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default1]:    output = model(**micro_batch)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default1]:    sharded_logits = self.model(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default1]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default1]:Traceback (most recent call last):
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default1]:    trainer.train(dataloader)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default1]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default1]:    outputs = self.pipeline_engine.train_batch_iter(
[default1]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default1]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default1]:    output = model(**micro_batch)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default1]:    output = self.pp_block(**new_kwargs)
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default1]:    sharded_logits = self.model(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default1]:    return self.forward_with_hidden[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
_states(input_ids=input_ids, input_mask=input_mask)[0]
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default1]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default1]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:    output = self.pp_block(**new_kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 586, in forward
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:    attention_output = self.attention(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 636, in forward
[default1]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/utils.py", line 97, in wrapper
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 170, in forward
[default1]:    merged_states = self.gate_up_proj(hidden_states)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return func(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 212, in forward
[default1]:    attn_output = flash_attn_varlen_func(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 1066, in flash_attn_varlen_func
[default1]:    return FlashAttnVarlenFunc.apply(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/function.py", line 553, in apply
[default1]:    return super().apply(*args, **kwargs)  # type: ignore[misc]
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/flash_attn/flash_attn_interface.py", line 581, in forward
[default1]:    out, q, k, v, out_padded, softmax_lse, S_dmask, rng_state = _flash_attn_varlen_forward(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-pack[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
ages/flash_attn/flash_attn_interface.py", line 86, in _flash_attn_varlen_forward
[default1]:    out, q, k, v, out_padded, softmax_lse, S_dmask, rng_state = flash_attn_cuda.varlen_fwd(
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward
[default1]:    return column_linear(
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear
[default1]:    return F.linear(input, weight, bias)
[default1]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 64.00 MiB. GPU 1 has a total capacity of 79.33 GiB of which 1.94 MiB is free. Including non-PyTorch memory, this process has 79.31 GiB memory in use. Of the allocated memory 70.15 GiB is allocated by PyTorch, and 52.34 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]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 MiB. GPU 1 has a total capacity of 79.33 GiB of which 1.94 MiB is free. Including non-PyTorch memory, this process has 79.31 GiB memory in use. Of the allocated memory 70.15 GiB is allocated by PyTorch, and 50.86 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]:Traceback (most recent call last):
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default2]:    trainer.train(dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default2]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default2]:    outputs = self.pipeline_engine.train_batch_iter(
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default2]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default2]:    output = model(**micro_batch)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default2]:    sharded_logits = self.model(
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default2]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default2]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default2]:    output = self.pp_block(**new_kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 636, in forward
[default2]:    hidden_states = self.mlp(hidden_states=hidden_states)["hidden_states"]
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 171, in forward
[default2]:    hidden_states = self.down_proj(self.split_silu_mul(merged_states))
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 159, in forward
[default2]:    return row_linear(
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 474, in row_linear
[default2]:    out = F.linear(input, weight, bias)
[default2]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 16.00 MiB. GPU 2 has a total capacity of 79.33 GiB of which 13.94 MiB is free. Including non-PyTorch memory, this process has 79.30 GiB memory in use. Of the allocated memory 69.99 GiB is allocated by PyTorch, and 34.88 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]:Traceback (most recent call last):
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default6]:    trainer.train(dataloader)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default6]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default6]:    outputs = self.pipeline_engine.train_batch_iter(
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default6]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default6]:    output = model(**micro_batch)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default6]:    sharded_logits = self.model(
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default6]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default6]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 151, in forward
[default6]:    output = self.pp_block(**new_kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 630, in forward
[default6]:    output = self.attn(hidden_states=hidden_states, sequence_mask=sequence_mask)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 359, in forward
[default6]:    qkv_states = self.qkv_proj(
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/nn.py", line 87, in forward
[default6]:    return column_linear(
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/tensor_parallel/functional.py", line 359, in column_linear
[default6]:    return F.linear(input, weight, bias)
[default6]:torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 48.00 MiB. GPU 6 has a total capacity of 79.33 GiB of which 47.94 MiB is free. Including non-PyTorch memory, this process has 79.27 GiB memory in use. Of the allocated memory 69.73 GiB is allocated by PyTorch, and 35.39 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]:Traceback (most recent call last):
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default7]:    trainer.train(dataloader)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default7]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default7]:    outputs = self.pipeline_engine.train_batch_iter(
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default7]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default7]:    output = model(**micro_batch)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default7]:    sharded_logits = self.model(
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default7]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default7]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default7]:    return self._call_impl(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default7]:    return forward_call(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default7]:    new_kwargs[name] = recv_from_pipeline_state_buffer(
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default7]:    pipeline_state.run_communication()
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default7]:    recv_activation_tensor = recv_activation()
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default7]:    return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default7]:    buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default7]:    meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default7]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta
[default7]:    dist.recv(
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 72, in wrapper
[default7]:    return func(*args, **kwargs)
[default7]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1706, in recv
[default7]:    pg.recv([tensor], group_src_rank, tag).wait()
[default7]:torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. 
[default5]:Traceback (most recent call last):
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default5]:    trainer.train(dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default5]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default5]:    outputs = self.pipeline_engine.train_batch_iter(
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default5]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default5]:    output = model(**micro_batch)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default5]:    sharded_logits = self.model(
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default5]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default5]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default5]:    return self._call_impl(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default5]:    return forward_call(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default5]:    new_kwargs[name] = recv_from_pipeline_state_buffer(
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default5]:    pipeline_state.run_communication()
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default5]:    recv_activation_tensor = recv_activation()
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default5]:    return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default5]:    buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default5]:    meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default5]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta
[default5]:    dist.recv(
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 72, in wrapper
[default5]:    return func(*args, **kwargs)
[default5]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1706, in recv
[default5]:    pg.recv([tensor], group_src_rank, tag).wait()
[default5]:torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. 
[default2]:Traceback (most recent call last):
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default2]:    trainer.train(dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default2]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default2]:    outputs = self.pipeline_engine.train_batch_iter(
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default2]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default2]:    output = model(**micro_batch)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default2]:    sharded_logits = self.model(
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default2]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default2]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default2]:    return self._call_impl(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default2]:    return forward_call(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default2]:    new_kwargs[name] = recv_from_pipeline_state_buffer(
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default2]:    pipeline_state.run_communication()
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default2]:    recv_activation_tensor = recv_activation()
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default2]:    return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default2]:    buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default2]:    meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default2]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta
[default2]:    dist.recv(
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 72, in wrapper
[default2]:    return func(*args, **kwargs)
[default2]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1706, in recv
[default2]:    pg.recv([tensor], group_src_rank, tag).wait()
[default2]:torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. 
[default1]:Traceback (most recent call last):
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default1]:    trainer.train(dataloader)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default1]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default1]:    outputs = self.pipeline_engine.train_batch_iter(
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default1]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default1]:    output = model(**micro_batch)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default1]:    sharded_logits = self.model(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default1]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default1]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default1]:    return self._call_impl(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default1]:    return forward_call(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default1]:    new_kwargs[name] = recv_from_pipeline_state_buffer(
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default1]:    pipeline_state.run_communication()
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default1]:    recv_activation_tensor = recv_activation()
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default1]:    return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default1]:    buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default1]:    meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default1]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta
[default1]:    dist.recv(
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 72, in wrapper
[default1]:    return func(*args, **kwargs)
[default1]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1706, in recv
[default1]:    pg.recv([tensor], group_src_rank, tag).wait()
[default1]:torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. 
[default6]:Traceback (most recent call last):
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py", line 237, in <module>
[default6]:    trainer.train(dataloader)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 430, in train
[default6]:    outputs, loss_avg = self.training_step(dataloader=self.current_dataloader)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/trainer.py", line 459, in training_step
[default6]:    outputs = self.pipeline_engine.train_batch_iter(
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 187, in train_batch_iter
[default6]:    output = self.forward(context=context, state=state, micro_batch=micro_batch, model=model)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/engine.py", line 44, in forward
[default6]:    output = model(**micro_batch)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 890, in forward
[default6]:    sharded_logits = self.model(
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 764, in forward
[default6]:    return self.forward_with_hidden_states(input_ids=input_ids, input_mask=input_mask)[0]
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/models/llama.py", line 780, in forward_with_hidden_states
[default6]:    hidden_encoder_states = encoder_block(**hidden_encoder_states)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
[default6]:    return self._call_impl(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
[default6]:    return forward_call(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/block.py", line 126, in forward
[default6]:    new_kwargs[name] = recv_from_pipeline_state_buffer(
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/functional.py", line 117, in recv_from_pipeline_state_buffer
[default6]:    pipeline_state.run_communication()
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 150, in run_communication
[default6]:    recv_activation_tensor = recv_activation()
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/state.py", line 31, in __call__
[default6]:    return self.p2p.recv_tensors(num_tensors=1, from_rank=self.from_rank)[0]
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 353, in recv_tensors
[default6]:    buffers, futures = self.irecv_tensors(num_tensors=num_tensors, from_rank=from_rank, tag=tag)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 326, in irecv_tensors
[default6]:    meta = self._recv_meta(from_rank=from_rank, tag=tag)
[default6]:  File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/src/nanotron/parallel/pipeline_parallel/p2p.py", line 269, in _recv_meta
[default6]:    dist.recv(
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/c10d_logger.py", line 72, in wrapper
[default6]:    return func(*args, **kwargs)
[default6]:  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py", line 1706, in recv
[default6]:    pg.recv([tensor], group_src_rank, tag).wait()
[default6]:torch.distributed.DistBackendError: NCCL communicator was aborted on rank 1. 
[default7]:[rank23]:[E ProcessGroupNCCL.cpp:537] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[default7]:[rank23]:[E ProcessGroupNCCL.cpp:543] To avoid data inconsistency, we are taking the entire process down.
[default7]:[rank23]:[E ProcessGroupNCCL.cpp:1182] [Rank 1] NCCL watchdog thread terminated with exception: NCCL error: remote process exited or there was a network error, NCCL version 2.19.3
[default7]:ncclRemoteError: A call failed possibly due to a network error or a remote process exiting prematurely.
[default7]:Last error:
[default7]:socketProgress: Connection closed by remote peer ip-26-0-163-220.ec2.internal<58490>
[default7]:Exception raised from checkForNCCLErrorsInternal at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1436 (most recent call first):
[default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7c0ab2dd87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default7]:frame #1: c10d::ProcessGroupNCCL::checkForNCCLErrorsInternal(std::vector<std::shared_ptr<c10d::NCCLComm>, std::allocator<std::shared_ptr<c10d::NCCLComm> > > const&) + 0x2f3 (0x7f7c0bcd4fa3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:frame #2: c10d::ProcessGroupNCCL::WorkNCCL::checkAndSetException() + 0x7b (0x7f7c0bcd527b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:frame #3: c10d::ProcessGroupNCCL::workCleanupLoop() + 0x17d (0x7f7c0bcd8c1d in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:frame #4: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x119 (0x7f7c0bcd9839 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:frame #5: <unknown function> + 0xd3e95 (0x7f7c559dde95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default7]:frame #6: <unknown function> + 0x8609 (0x7f7c5aae5609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default7]:frame #7: clone + 0x43 (0x7f7c5a8b0353 in /lib/x86_64-linux-gnu/libc.so.6)
[default7]:
[default7]:terminate called after throwing an instance of 'c10::DistBackendError'
[default7]:  what():  [Rank 1] NCCL watchdog thread terminated with exception: NCCL error: remote process exited or there was a network error, NCCL version 2.19.3
[default7]:ncclRemoteError: A call failed possibly due to a network error or a remote process exiting prematurely.
[default7]:Last error:
[default7]:socketProgress: Connection closed by remote peer ip-26-0-163-220.ec2.internal<58490>
[default7]:Exception raised from checkForNCCLErrorsInternal at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1436 (most recent call first):
[default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7c0ab2dd87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default7]:frame #1: c10d::ProcessGroupNCCL::checkForNCCLErrorsInternal(std::vector<std::shared_ptr<c10d::NCCLComm>, std::allocator<std::shared_ptr<c10d::NCCLComm> > > const&) + 0x2f3 (0x7f7c0bcd4fa3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:frame #2: c10d::ProcessGroupNCCL::WorkNCCL::checkAndSetException() + 0x7b (0x7f7c0bcd527b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:frame #3: c10d::ProcessGroupNCCL::workCleanupLoop() + 0x17d (0x7f7c0bcd8c1d in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:frame #4: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x119 (0x7f7c0bcd9839 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:frame #5: <unknown function> + 0xd3e95 (0x7f7c559dde95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default7]:frame #6: <unknown function> + 0x8609 (0x7f7c5aae5609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default7]:frame #7: clone + 0x43 (0x7f7c5a8b0353 in /lib/x86_64-linux-gnu/libc.so.6)
[default7]:
[default7]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1186 (most recent call first):
[default7]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7c0ab2dd87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default7]:frame #1: <unknown function> + 0xdf6b11 (0x7f7c0ba2fb11 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default7]:frame #2: <unknown function> + 0xd3e95 (0x7f7c559dde95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default7]:frame #3: <unknown function> + 0x8609 (0x7f7c5aae5609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default7]:frame #4: clone + 0x43 (0x7f7c5a8b0353 in /lib/x86_64-linux-gnu/libc.so.6)
[default7]:
[default5]:[rank21]:[E ProcessGroupNCCL.cpp:537] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[default5]:[rank21]:[E ProcessGroupNCCL.cpp:543] To avoid data inconsistency, we are taking the entire process down.
[default5]:[rank21]:[E ProcessGroupNCCL.cpp:1182] [Rank 1] NCCL watchdog thread terminated with exception: NCCL error: remote process exited or there was a network error, NCCL version 2.19.3
[default5]:ncclRemoteError: A call failed possibly due to a network error or a remote process exiting prematurely.
[default5]:Last error:
[default5]:socketProgress: Connection closed by remote peer ip-26-0-163-220.ec2.internal<55744>
[default5]:Exception raised from checkForNCCLErrorsInternal at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1436 (most recent call first):
[default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7a18660d87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default5]:frame #1: c10d::ProcessGroupNCCL::checkForNCCLErrorsInternal(std::vector<std::shared_ptr<c10d::NCCLComm>, std::allocator<std::shared_ptr<c10d::NCCLComm> > > const&) + 0x2f3 (0x7f7a19807fa3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #2: c10d::ProcessGroupNCCL::WorkNCCL::checkAndSetException() + 0x7b (0x7f7a1980827b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #3: c10d::ProcessGroupNCCL::workCleanupLoop() + 0x17d (0x7f7a1980bc1d in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #4: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x119 (0x7f7a1980c839 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #5: <unknown function> + 0xd3e95 (0x7f7a63510e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default5]:frame #6: <unknown function> + 0x8609 (0x7f7a68618609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default5]:frame #7: clone + 0x43 (0x7f7a683e3353 in /lib/x86_64-linux-gnu/libc.so.6)
[default5]:
[default5]:terminate called after throwing an instance of 'c10::DistBackendError'
[default5]:  what():  [Rank 1] NCCL watchdog thread terminated with exception: NCCL error: remote process exited or there was a network error, NCCL version 2.19.3
[default5]:ncclRemoteError: A call failed possibly due to a network error or a remote process exiting prematurely.
[default5]:Last error:
[default5]:socketProgress: Connection closed by remote peer ip-26-0-163-220.ec2.internal<55744>
[default5]:Exception raised from checkForNCCLErrorsInternal at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1436 (most recent call first):
[default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7a18660d87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default5]:frame #1: c10d::ProcessGroupNCCL::checkForNCCLErrorsInternal(std::vector<std::shared_ptr<c10d::NCCLComm>, std::allocator<std::shared_ptr<c10d::NCCLComm> > > const&) + 0x2f3 (0x7f7a19807fa3 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #2: c10d::ProcessGroupNCCL::WorkNCCL::checkAndSetException() + 0x7b (0x7f7a1980827b in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #3: c10d::ProcessGroupNCCL::workCleanupLoop() + 0x17d (0x7f7a1980bc1d in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #4: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x119 (0x7f7a1980c839 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #5: <unknown function> + 0xd3e95 (0x7f7a63510e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default5]:frame #6: <unknown function> + 0x8609 (0x7f7a68618609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default5]:frame #7: clone + 0x43 (0x7f7a683e3353 in /lib/x86_64-linux-gnu/libc.so.6)
[default5]:
[default5]:Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1186 (most recent call first):
[default5]:frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7a18660d87 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libc10.so)
[default5]:frame #1: <unknown function> + 0xdf6b11 (0x7f7a19562b11 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
[default5]:frame #2: <unknown function> + 0xd3e95 (0x7f7a63510e95 in /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/../lib/libstdc++.so.6)
[default5]:frame #3: <unknown function> + 0x8609 (0x7f7a68618609 in /lib/x86_64-linux-gnu/libpthread.so.0)
[default5]:frame #4: clone + 0x43 (0x7f7a683e3353 in /lib/x86_64-linux-gnu/libc.so.6)
[default5]:
[2024-07-06 09:36:21,604] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 962330 closing signal SIGTERM
[2024-07-06 09:36:21,604] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 962331 closing signal SIGTERM
[2024-07-06 09:36:21,605] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 962332 closing signal SIGTERM
[2024-07-06 09:36:21,605] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 962333 closing signal SIGTERM
[2024-07-06 09:36:21,605] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 962334 closing signal SIGTERM
[2024-07-06 09:36:21,606] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 962335 closing signal SIGTERM
[2024-07-06 09:36:21,606] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 962336 closing signal SIGTERM
[2024-07-06 09:36:21,610] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1020917 closing signal SIGTERM
[2024-07-06 09:36:21,610] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1020918 closing signal SIGTERM
[2024-07-06 09:36:21,610] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1020921 closing signal SIGTERM
[2024-07-06 09:36:21,613] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 184412 closing signal SIGTERM
[2024-07-06 09:36:21,613] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 184413 closing signal SIGTERM
[2024-07-06 09:36:22,937] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 0 (pid: 184411) 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 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, 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 268, 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      : 2024-07-06_09:36:21
  host      : ip-26-0-163-220.ec2.internal
  rank      : 3 (local_rank: 3)
  exitcode  : 1 (pid: 184414)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[2]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-163-220.ec2.internal
  rank      : 4 (local_rank: 4)
  exitcode  : 1 (pid: 184415)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[3]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-163-220.ec2.internal
  rank      : 5 (local_rank: 5)
  exitcode  : 1 (pid: 184416)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[4]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-163-220.ec2.internal
  rank      : 6 (local_rank: 6)
  exitcode  : 1 (pid: 184417)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[5]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-163-220.ec2.internal
  rank      : 7 (local_rank: 7)
  exitcode  : 1 (pid: 184418)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-163-220.ec2.internal
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 184411)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
[2024-07-06 09:36:23,232] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 0 (pid: 1020916) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
srun: error: ip-26-0-163-220: task 0: Exited with exit code 1
[2024-07-06 09:36:23,285] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-163-236.ec2.internal_1020848_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 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, 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 268, 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      : 2024-07-06_09:36:21
  host      : ip-26-0-163-236.ec2.internal
  rank      : 11 (local_rank: 3)
  exitcode  : 1 (pid: 1020919)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[2]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-163-236.ec2.internal
  rank      : 12 (local_rank: 4)
  exitcode  : 1 (pid: 1020920)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[3]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-163-236.ec2.internal
  rank      : 14 (local_rank: 6)
  exitcode  : 1 (pid: 1020922)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
[4]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-163-236.ec2.internal
  rank      : 15 (local_rank: 7)
  exitcode  : 1 (pid: 1020923)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-163-236.ec2.internal
  rank      : 8 (local_rank: 0)
  exitcode  : 1 (pid: 1020916)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================
srun: error: ip-26-0-163-236: task 1: Exited with exit code 1
[2024-07-06 09:36:25,441] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: -6) local_rank: 7 (pid: 962337) of binary: /fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/python3.10
[2024-07-06 09:36:25,475] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-18.ec2.internal_962261_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 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, 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 268, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
============================================================
/fsx/ferdinandmom/ferdinand-hf/bench_cluster/nanotron/run_train.py FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-07-06_09:36:21
  host      : ip-26-0-164-18.ec2.internal
  rank      : 23 (local_rank: 7)
  exitcode  : -6 (pid: 962337)
  error_file: <N/A>
  traceback : Signal 6 (SIGABRT) received by PID 962337
============================================================
srun: error: ip-26-0-164-18: task 2: Exited with exit code 1
[2024-07-06 09:36:26,520] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-172-252.ec2.internal_3117869_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:26,550] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-187.ec2.internal_423836_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:26,562] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-45.ec2.internal_1411605_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:26,570] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-75.ec2.internal_968240_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:26,578] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-173-7.ec2.internal_2780372_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:26,608] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1411673 closing signal SIGTERM
[2024-07-06 09:36:26,609] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1411674 closing signal SIGTERM
[2024-07-06 09:36:26,609] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1411675 closing signal SIGTERM
[2024-07-06 09:36:26,610] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1411676 closing signal SIGTERM
[2024-07-06 09:36:26,611] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1411677 closing signal SIGTERM
[2024-07-06 09:36:26,613] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 968308 closing signal SIGTERM
[2024-07-06 09:36:26,612] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1411678 closing signal SIGTERM
[2024-07-06 09:36:26,613] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 968309 closing signal SIGTERM
[2024-07-06 09:36:26,614] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 968310 closing signal SIGTERM
[2024-07-06 09:36:26,614] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2780441 closing signal SIGTERM
[2024-07-06 09:36:26,614] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2780442 closing signal SIGTERM
[2024-07-06 09:36:26,615] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2780443 closing signal SIGTERM
[2024-07-06 09:36:26,615] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 968311 closing signal SIGTERM
[2024-07-06 09:36:26,613] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1411679 closing signal SIGTERM
[2024-07-06 09:36:26,613] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 1411680 closing signal SIGTERM
[2024-07-06 09:36:26,614] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 423906 closing signal SIGTERM
[2024-07-06 09:36:26,615] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 423907 closing signal SIGTERM
[2024-07-06 09:36:26,615] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 968312 closing signal SIGTERM
[2024-07-06 09:36:26,615] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 968313 closing signal SIGTERM
[2024-07-06 09:36:26,616] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 423908 closing signal SIGTERM
[2024-07-06 09:36:26,618] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2780445 closing signal SIGTERM
[2024-07-06 09:36:26,618] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2780446 closing signal SIGTERM
[2024-07-06 09:36:26,617] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 423909 closing signal SIGTERM
[2024-07-06 09:36:26,618] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 423910 closing signal SIGTERM
[2024-07-06 09:36:26,618] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 968314 closing signal SIGTERM
[2024-07-06 09:36:26,618] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 423911 closing signal SIGTERM
[2024-07-06 09:36:26,619] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3117939 closing signal SIGTERM
[2024-07-06 09:36:26,619] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 423912 closing signal SIGTERM
[2024-07-06 09:36:26,620] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 968315 closing signal SIGTERM
[2024-07-06 09:36:26,620] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3117940 closing signal SIGTERM
[2024-07-06 09:36:26,621] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3117941 closing signal SIGTERM
[2024-07-06 09:36:26,621] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 423913 closing signal SIGTERM
[2024-07-06 09:36:26,622] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2780447 closing signal SIGTERM
[2024-07-06 09:36:26,624] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3117942 closing signal SIGTERM
[2024-07-06 09:36:26,625] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2780448 closing signal SIGTERM
[2024-07-06 09:36:26,624] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3117943 closing signal SIGTERM
[2024-07-06 09:36:26,626] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 2780449 closing signal SIGTERM
[2024-07-06 09:36:26,627] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3117944 closing signal SIGTERM
[2024-07-06 09:36:26,629] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3117945 closing signal SIGTERM
[2024-07-06 09:36:26,631] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 3117946 closing signal SIGTERM
[2024-07-06 09:36:30,755] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-172-252.ec2.internal_3117869_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/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

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 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, 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 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
srun: error: ip-26-0-172-252: task 6: Exited with exit code 1
[2024-07-06 09:36:31,154] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-173-7.ec2.internal_2780372_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/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

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 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, 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 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
srun: error: ip-26-0-173-7: task 7: Exited with exit code 1
[2024-07-06 09:36:31,554] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-187.ec2.internal_423836_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:31,567] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-45.ec2.internal_1411605_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:31,574] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-75.ec2.internal_968240_0' has failed to send a keep-alive heartbeat to the rendezvous 'none' due to an error of type RendezvousConnectionError.
[2024-07-06 09:36:31,748] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-45.ec2.internal_1411605_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/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

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 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, 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 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
srun: error: ip-26-0-164-45: task 3: Exited with exit code 1
[2024-07-06 09:36:32,254] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-75.ec2.internal_968240_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/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

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 812, in main
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, 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 259, in launch_agent
[2024-07-06 09:36:32,257] torch.distributed.elastic.rendezvous.dynamic_rendezvous: [WARNING] The node 'ip-26-0-164-187.ec2.internal_423836_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 113, in _call_store
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    return getattr(self._store, store_op)(*args, **kwargs)
torch.distributed.DistNetworkError: Broken pipe

The above exception was the direct cause of the following exception:

    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
Traceback (most recent call last):
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/bin/torchrun", line 8, in <module>
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    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
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    return f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 812, in main
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    run(args)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/run.py", line 803, in run
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    elastic_launch(
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 135, in __call__
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
    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 259, in launch_agent
    result = agent.run()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/metrics/api.py", line 123, in wrapper
    result = f(*args, **kwargs)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 727, in run
    result = self._invoke_run(role)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/agent/server/api.py", line 900, in _invoke_run
    num_nodes_waiting = rdzv_handler.num_nodes_waiting()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 1083, in num_nodes_waiting
    self._state_holder.sync()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/dynamic_rendezvous.py", line 409, in sync
    get_response = self._backend.get_state()
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 73, in get_state
    base64_state: bytes = self._call_store("get", self._key)
  File "/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/elastic/rendezvous/c10d_rendezvous_backend.py", line 115, in _call_store
    raise RendezvousConnectionError(
torch.distributed.elastic.rendezvous.api.RendezvousConnectionError: The connection to the C10d store has failed. See inner exception for details.
srun: error: ip-26-0-164-75: task 4: Exited with exit code 1
srun: error: ip-26-0-164-187: task 5: 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.